Download Feeding of detritivores in freshwater sediments

CHAPTER 1
GENERAL INTRODUCTION
9
Chapter 1
In all natural waters particles of non-living organic matter are present, which are
derived from autotrophic plants or dying animals. These non-living particles, or detritus,
support distinct assemblages of animals which use the particles as a food source. When
this food source is suspended it requires filter feeding to be consumed, but when the
detritus particles are sedimented in aquatic systems, the bottom material serves as both
habitat and food for detritivores. Detritivory is defined as the intake of nonliving particulate organic matter together with the microorganisms that are associated with it
(Cummins 1973). Although the general view of food webs supposes a dominance of
grazers cropping plant material, these herbivores being eaten by carnivores, in fact as
much as 90% of primary plant production in aquatic systems enters the detritus food
web (Pomeroy 1980). Detritivores form a major link in the foodweb processing
nutritionally low quality dead organic matter. Through their activity they stimulate
degradation of organic matter by microorganisms (Ten Winkel et al. 1982, Harris 1983,
Shepard & Minshall 1984, van de Bund & Davids 1993, van den Bund et al. 1994,
Goedkoop 1994). In aquatic systems detritivores in soft sediments are one of the main
food sources for predators, like fish and birds, or carnivorous invertebrates such as
mites and damselfly larvae (Healey 1984, Walde & Davies 1984, Hershey 1985a & b,
Hershey & Dodson 1987, Ten Winkel et al. 1989, review Wallace & Webster 1996).
Benthic detritivores can be partioned into functional feeding groups based on
food-acquiring mechanisms. Deposit feeders, also termed collector gatherers are bulkfeeders, processing large volumes of sediment at high rate. Deposit feeders typically
process at least one body weight of sediment daily. A way to attain a high rate of
sediment processing is to sort the sediment but reject most before ingestion as pseudofaeces. Collector gatherers feed on fine particle detritus (Fine Particular Organic Matter,
FPOM, < 1 mm) deposited on the substrate surface. Filtering gatherers feed on particles
in suspension and therefore are also called suspension feeders. Shredders are
detritivorous species that use plant debris with somewhat bigger particle size (Coarse
Particular Organic Matter, CPOM, > 1 mm) compared to the gatherers. Shredders only
process 0.01 to 0.4 times their body weights daily. Quite often taxa can not be assigned
to one particular functional feeding group only. For instance, some species of polychaetes have the ability to switch between suspension feeding and deposit feeding,
depending on the availability of suspended particles, while certain species of bivalves
10
General Introduction
simultaneously display both suspension and deposit feeding. Shredders often ingest
FPOM while feeding on leaf litter (Cummins 1973, Cummins & Klug 1979, review
Lopez & Levinton 1987).
The principal food sources for detritivores are materials that are derived from
algae and macrophytes, but detritus may also include fragments of dead animals and
terrestrial run-off introducing soil particles and leaf litter. The nutritional value of the
food sources of detritivores varies spatially and temporally. Spatial differences depend
on the contribution of the different sources to detritus. Detritus of large lakes will
contain more algal material formed in the water column, whereas detritus of small
streams is likely to contain more material from macrophytes, eroded soil particles, and
leaf litter.
Detritivores are confronted with different quantities of organic matter admixed
with mineral particles with different nutritional qualities throughout the year, depending
on a number of factors such as seasonal input of leaf litter, algal blooms, and macrophytes growth, on the depth of the watersystem, and the degradation rate of phytodetritus (Johannson & Beaver 1983, Johnson 1987, Lopez & Levinton 1987, Moore
1987, Marsh & Tenore 1990, Hill et al. 1992, Cheng et al. 1993, Ahlgren et al. 1997).
Seasonality of algal input to the benthic ecosystem is illustrated by a study of Ahlgren et
al. (1997). Plankton net samples and sedimenting matter in traps from mesotrophic Lake
Erken were analysed for carbon, nitrogen, phosphorus, total lipids and fatty acid content
to follow seasonal changes in food availibility. Organic matter abundance in the pelagic
and the benthic zone depended on respectively the presence and sedimentation of
phytoplankton. Biochemical analyses of plankton and sedimenting matter showed that
the benthic fauna have access to high-quality food only during spring and autumn due
the dominance of diatoms during these periods. Studies on benthic-pelagic coupling in
the field reported a rapid response of the macrofauna community to an increase of the
input from the pelagic zone, suggesting food limitation during much of the year (Graf et
al. 1982, Graf 1989, Lopez & Levinton 1987, Goedkoop & Johnson 1996). Field studies
also showed that algal blooms composed of different algal species caused different
responses of local macrofauna communities (Marsh et al. 1989, Marsh & Tenore 1990,
Cheng et al. 1993) indicating regulation of macroinvertebrates by organic matter
composition. Noting that food is a primary need for heterotrophic animals, the supply
11
Chapter 1
rate and quality of detritus particles reaching the benthos is a key limiting factor. It is
hypothesized that temporal and spatial differences in the availibility of food sources for
detritivores are main regulating factors for communities of benthic invertebrates. This
regulation is the main subject of this thesis.
Composition of organic matter in sediments
Composition of organic matter is dependent of its source and of the degree of
degradation. During the complex process of decomposition the most labile components
are degraded first. Conversely, the refractory matter is slowly broken down and tends to
accumulate in the sediment (Fry 1987, Kemp & Johnston 1979). Therefore, depositfeeders mostly depend on low-quality organic matter as food bulk compared to organisms that consume selectively other food items (Bowen 1987, Ahlgren et al. 1997).
Decay of the organic matter encompasses fragmentation, cell leaching, bacterial
decomposition, and chemical oxidation. In the pelagic column zooplankters strip the
seston of useful biochemical compounds (Cavaletto & Gardner 1999). After sedimentation, oxidation and fragmentation of organic matter continues on the lake bottom.
Bioturbation of surface sediments may prolong the exposure of the sedimented matter to
oxidation-reduction cycles.
Microorganisms are mostly the first to take advantage of the most labile
components that are released from decaying organic matter. Benthic microbial activity
and biomass are observed to increase within hours after sedimentation of algae (Graf
1992). In aerobic environments, aquatic hyphomycetes are dominant during the early
stages of decomposition of plant matter. The fungal hyphae invade the structure of the
plant and fungal exoenzymes break down the structural cellulose. This weakens the
plant tissue. Bacteria typically colonize the remaining fragments.
Microbial conditioning enhances the palatibility of leaf material to detritivores
(Bärlocher & Kendrick 1975, McGrath & Matthews 2000). Being part of detrital aggregates microorganisms contribute to the potential food sources of detritivores. However,
bacteria are often estimated to contribute less than 1% to the weight of fine detrital
particles. A number of studies showed that microorganisms’ biomass consumed by
detritivores accounts for less than 10% of the detritivore's growth (Bowen et al. 1984,
Findlay et al. 1984). Other studies, however, stress that microbes are efficiently digested
12
General Introduction
and provide a nutrient rich diet (Martin et al. 1980, review Bowen 1987, review Graf
1992). Even though the microorganisms' biomass constitutes a low share of the ingested
food, small quantities of microorganisms may supply significant quantities of nutrients
such as vitamins and amino acids (review Phillips 1984a, Wolf et al. 1997). Thus,
colonization by microorganisms may increase overall nutritional value of originally
refractive organic matter significantly, which is called microbial enrichment. The term
enrichment is also used because the microorganisms convert soluble components that
otherwise would be lost for further consumption by benthic invertebrates into biomass.
In summary, degradation of organic matter by microorganisms is based on at least two
mechanisms. 1) Microorganisms convert refractory material and soluble components
into microbial biomass which is more easy to digest and more nutritious compared to
the degradating organic matter. 2) Microbial degradation breaks organic matter into
subunits digestible for detritus-feeders.
During the complex process of degradation the originally nutritious organic
material (e.g. from recently died algae) is deprived of the most nutritious components
and only part of the lost biomass is replaced by microbial biomass. Therefore, detritivores probably have to deal with food sources of low nutritional value which will vary
with states of degradation and microbial conditioning. The present study aims to investigate the variety in composition of food exploited by detritivores and thereby to relate
the nutritional value of the food source for detritivores to its degradation state.
Nutritional requirements of invertebrates
Assimilation may follow basically similar patterns among different animals. The
needs of heterotrophic organisms in regard to nutrition can roughly be divided into two
classes. Firstly, the organism needs energy for activity and internal maintenance. The
need for energy can be satisfied by a variety of compounds that are oxidized and
therefore is called a non-specific need. Secondly, heterotrophic organisms need a supply
of specific substances for synthesis of new tissue. Such specific needs can only be satisfied by a limited suite of organic compounds: the essential nutrients.
Influence of food abundance, and hence of available energy, has been examined
in several studies on a number of invertebrate species. Manipulation of food availability
in laboratory experiments show that life history responses to food limitation range from
13
Chapter 1
retarded growth and an increase in longevity to lowered fertility and reproduction rate
and as an extreme consequence, death. Changes in life history parameters due to food
limitation lower the intrinsic rate of population growth.
Requirements for some essential nutrients (e.g., polyunsaturated fatty acids and
vitamins) are fairly consistent among vertebrates and invertebrates, whereas the
requirements for others vary, depending on the particular taxonomic or physiological
group or developmental stage of the animal (Downer 1981, Phillips 1984a). Polyunsaturated fatty acids (PUFA) are a relatively well studied group of essential components. PUFA are responsible for regulation of animal cell membrane physiology and
serve as precursors to eicosanoids. Eicosanoids are critical in a wide range of
physiological processes in invertebrates. Deficiencies in PUFA can impair functioning
of membranes and membrane-bound enzyme systems and are needed for optimal eggproduction, egg-laying, spawning, and hatching (Brett & Müller-Navarra 1995).
Animals can convert one form of PUFA to another through elongation and
desaturation, but very few species can synthesize PUFA de novo (review Blomquist et
al. 1991). Polyunsaturated fatty acids are almost exlusively synthesized by plants.
Consequently, most freshwater organisms exhibit a strong dietary demand for PUFA.
The vast body of literature on aquaculture shows that diets rich in PUFA are essential
for fishes, molluscs, crustaceans, and zooplankton. This literature is reviewed by Brett
& Müller-Navarra (1995). Prawns are most thoroughly studied because of their
economic importance as highly valued food for humans. Studies show that PUFA
content of artificial and natural diets impacts survival, growth, fecundity, egg
hatchability, molting and osmotic stress tolerance of shrimps (D'Abramo & Sheen 1993,
Xu et al. 1993, Rees et al. 1994). Prawns are primarily carnivores, but literature on
pelagic herbivores also documents a strong dietary demand for PUFA-rich phytoplankton. All herbivorous insects require PUFA of plant origin (Blomquist et al. 1991).
Adding emulsions of PUFA to algae cultures can markedly increase the growth rates of
herbivorous zooplankton (Brett & Müller-Navarra 1995).
Literature on PUFA-demands of benthic detritivores is scarce. Although overall
nutritional demands of organisms may be similar among taxa it should be noted that
adaptations in specific species may have taken place due to existence of special environmental conditions or specific modes of behavior. In regard to modes of feeding physio-
14
General Introduction
logical adaptations may have occurred to be able to digest certain food sources. Hanson
et al. (1985) presented a study on the fatty acid composition of aquatic insects from
different orders and with different modes of feeding. Fatty acid composition differed
predictably among orders and functional feeding groups, most noticeably for the
polyunsaturated fatty acids. Collector gatherers of the order Diptera contained relatively
lower levels of PUFA than filterers, predators, scrapers, and shredders from the same
order, implying that the collector gatherers use diets poor in PUFA compared to the
food sources of the Diptera taxa with other modes of feeding. Collector gatherers from
the order Trichoptera, however, contained levels of PUFA comparable to PUFA levels
measured in Trichoptera specimen with other feeding modes. Thus, the effect of food
sources on detritivores cannot be predicted with precision by means of data on other
orders of insects with similar modes of feeding or data on insects of the same order but
with different feeding modes.
Studies on detritivores
Nutritional demands
Literature on the influence of food composition on detritivores is limited and
concentrates on the effect of microbial enrichment (Martin et al. 1980, Bowen 1987),
food particle size selection, and ingestion rate as a function of food value (Taghon
1982), but mostly does not take biochemical composition into consideration. Food
particle size selection often is the result of the limitation of most detritivores in their
ability to handle or ingest certain particle sizes (Jumars et al. 1982, Taghon 1982). Some
studies on detritivores indicate that particle size selection originates from the aim to
maximize net rate of energy gain. Two schools of thought have arisen on the effects of
food quality on ingestion rate. One group reports that ingestion rate vary inversely with
food quality as mechanism to maintain constant intake rate of some food component,
such as energy (Calow 1975, Cammen 1980, Phillips 1984b). Conversely, others find
ingestion rate to be positively related to food quality (refs. in Taghon 1981).
Digestion of refractory food sources
Detritivores seem to have adapted their digestion system to the low palatibility
of their food. Bjarnov (1972) compared the digestion of saccharides by Chironomus
15
Chapter 1
plumosus and C. antracinus, Gammarus pulex, and various Trichoptera which have
different feeding modes and different food sources. Significant differences between
species was only found for the degradation of polysaccharides. All "– and ß –glucosides
and galactosides were degraded by all tested species. Marked species differences existed
in the degradation of pectin, xylan and chitin. Digestion of pectine and xylan was
clearly observed for 5 species of Trichoptera, which were all shredders or suspension
feeders. The carnivores were better adapted to digest chitin. The results suggest that
most invertebrates are not able to digest the long chain cellulose and other structural
polysaccharides on their own, but also show that aquatic invertebrates have adapted
their digestion to their particular food source.
A number of studies focussed on the digestive systems in stream detritivores,
e.g. several Gammarus species, Hydropsyche betteni, Tipula caloptera, T. abdominalis,
Pteronarcys proteus, and Pycnopsyche luculenta (Martin et al. 1980, Sinsabaugh et al.
1985, Bärlocher & Porter 1986, Chamier & Willoughby 1986, Chamier 1991, McGrath
& Matthews 2000). The ability to digest major plant polysaccharides was restricted to
the Gammarus species, Pteronarcys proteus, and Pycnopsyche luculenta, but enzymes
capable of breaking glycosidic linkages, similar to enzymes that are released during
microbial breakdown of leaf polysaccharides, were present in the gut fluid of all
animals. Ingested fungi are partly responsible for the cellulase activity in the gut of
Gammarus species, but production of an endogenous cellulase system by the insects has
also been noted (Sinsabaugh et al. 1985, Chamier & Willoughby 1986, Chamier 1991,
Harris 1993).
For grazers percentages of 10 to 50 % of the plant material that is actually
consumed are mentioned not to be digested but excreted as faeces or pseudofaeces
(Pomeroy 1980). Since detritivores cope with more refractory food than grazers the
percentage of ingested food that is not digested probably will be higher. Furthermore, a
rapid rate of passage through the gut probably allows little time for most detritivores to
exercise extensive digestion and therefore will not be able to thoroughly digest cellulose
or other polysaccharides (Bjarnov 1972).
16
General Introduction
Sediment as habitat
Sediment constitutes both the food source and the physical environment of
benthic detritivores. The physical characteristics of sediments are mainly determined by
particle size distribution and organic matter. The impact of organic matter content and
grain size distribution on detritivores in the field is difficult to distinguish, because they
often covary in natural sediments (e.g., Rabeni & Minshall 1977, Pinder 1986, 1995,
Suedel & Rodgers 1994, Maxon et al. 1997, Reinhold-Dudok van Heel & den Besten
1999).
Several ways have been proposed in which particle size could affect preference
and performance of a sediment inhabitant. Particle size distribution of a substrate may
influence the suitability of a substratum to borrow in as reflected by penetration rate by
the organisms (Wiley 1981a, Winnell & Jude 1984). Particle size distribution determines if the organism is able to construct a living tube, because many insects are limited
in their ability to handle particles of certain sizes (Brennan & McLachlan 1979).
Inhabiting a tube diminishes the risk of predation by damselflies, stoneflies, mites and
fish as is found in several laboratory and field studies (Hershey 1985 & 1987, Ten
Winkel 1987, Macchiusi & Baker 1991, Baker & Ball 1995). Particle size distribution
and organic matter also influence oxygen concentrations within the substrate, consequently selecting the species that are able to sustain themselves in the substrate
(Verdonschot 1990, Heinis 1993).
Detritivores may show preference for a distinct type of habitat. Such preference
for a habitat is often related to the options for the organisms to develop (Wiley 1981b).
Suitability of a sediment type can be tested through the migration of an organism from a
reference substrate, although migration towards a suitable substrate has hardly been
observed over larger distances (Wiley 1981a, Butman 1987, Rosillon 1987). During a
laboratory study by Sibley et al. (1998) on preferences of Chironomus tentans larvae the
interaction of physical characteristics with organic matter content was obviated by using
mineral particle substrates with different particle size ranges and by imposing uniform
oxygen conditions. C. tentans larvae consistently selected the smaller particle size range
of two substrates when they only needed to travel short distances (cms).
Not all detritivores will be able to handle the broad range of particle sizes as
chironomid larvae do. In addition, chironomid larvae are probably more tolerant to low
17
Chapter 1
oxygen levels in substrates than other detritivores. One other possible mode of action of
particle size distribution on detritivores has still been unexplored. Deposit-feeders ingest
inorganic particles together with the organic detritus (Rasmussen 1984, Lopez &
Levinton 1987). I expected that ingestion of inorganic material obstructs food uptake
and therefore may hamper growth of detritivores.
Biology and ecology of the test organism Chironomus riparius
To study the impact of nutritional value of sediments we choose C. riparius as
model species being a well-known deposit-feeder (Rasmussen 1984). C. riparius
belongs to the dipteran family of Chironomidae which encompasses at least 15,000
different species. The family is the most widely distributed group of insects, having
adapted to nearly every type of aquatic or semiaquatic environment, ranging from large
lakes to small streams (Armitage et al. 1995, Lindegaard & Brodersen 1995, Batzer &
Wissinger 1996, Silver Botts 1997). The midges account for most of the macroinvertebrate numbers in freshwater environments. In many aquatic habitats this group
constitutes more than half of the total number of macroinvertebrate species present.
Chironomids are often the earliest colonizers to arrive in newly formed or disturbed
habitats (Sheldon 1984, Layton & Voshell 1991, Batzer & Wissinger 1996).
Abundances of certain species or species groups of Chironomidae are often used to
characterize types of watersystems (Saether 1975, Resh & Rosenberg 1984, Johnson
1995) and as biological indicators of water quality.
Deposit-feeding is the most common feeding mode exhibited by chironomids.
Most detritivorous and tube-dwelling chironomids feed by extending the head and
anterior part of the body outside the tube while using the posterior prolegs to maintain
contact with the inner surface of the tube. Therefore, foraging areas are restricted to a
region immediately surrounding the tube. Detritivores cope with special feeding conditions. Firstly, the organisms mostly deal with organic matter of low nutritious value as
was argued above. The second special condition is the high mineral particle content of
most sediments. Mineral particles may be ingested along with organic matter, thereby
potentially reducing the nutritional value of the food intake.
The larvae of C. riparius are found in both lentic and lotic environments. The
species favours eutrophic conditions or conditions with organic loading (Armitage et al.
18
General Introduction
1995), where it can reach densities upto 50,000 individuals per square meter (Köhn &
Frank 1980, Rasmussen 1984). Larvae of C. riparius are known as "bloodworms"
especially to fishermen due to their red colour. The red colour is caused by haemoglobine which aids the chironomids to tolerate reduced levels of dissolved oxygen. Low
oxygen levels are rarely a problem for invertebrates living on stones or submerged
macrophytes but may cause problems for species such as chironomid larvae that live in
soft sediments with a high content of organic matter. Oxygen consumption within mud
can create sharp gradients of reducing oxygen concentration in the few millimetres or
centimetres above the sediment (Watling 1991, Heinis 1993, Armitage et al. 1995).
The ability of chironomids to construct tubes decreases the risk of predation by
vertebrates and invertebrates and may minimize dislodgement by currents. C. riparius is
known to build protective tubes from detritus, algae and other sediment particles. Particles are joined together with the larvae's saliva (Edgar & Meadows 1969). Larvae are
capable of handling only a certain range of particle size for tube construction. Similarly,
penetration of a substrate by chironomid larvae is dependent of particle size distribution
(Armitage et al. 1995, Wiley 1981a). Thus, the suitability of a substrate for chironomids
to settle in depends on the particle size distribution.
The life-cycle of chironomids comprises an egg stage, four larval stages, and a
pupal stage, which all live in the aquatic environment. In principal the first instar larvae
are planktonic, while older individuals inhabit the upper layer of the sediment.
Wintering of C. riparius occurs in the 3rd or 4th larval stage. The pupal stage lasts a few
Fourth instar larvae of Chironomus riparius.
19
Chapter 1
days and takes place in the mud. These stages of aquatic life are followed by a terrestrial
adult stage which does not feed. Adults often emerge simultaneously and form vast
mating clouds. After swarming and mating of male and female adults, the females
deposit egg masses at the water surface and attach them to some kind of substrate. Egg
masses may contain upto 600 eggs. At 20 °C hatching occurs within three days after egg
deposition. In temperate regions C. riparius displays multivoltine life cycles (Groenendijk et al. 1996) although the number of consecutive generations per year is strongly
related to the water temperature (Mackey 1977).
1 mm
Life cycle of Chironomidae displaying the egg stage, the four larval instars, the pupal
stage and the terrestrial imago (adopted from Timmermans 1991).
20
General Introduction
Objectives of this study
Although food is recognized as potentially important factor for macrofauna
communities, the influence of sedimentary organic matter and its biochemical composition on benthic detritivores has been neglected so far. Therefore, this study aims to
clarify the influence of the nutritional value of sediments on benthic detritivores. Focal
points are the influence of sedimentary organic matter and its biochemical composition
on the survival and growth of benthic detritivores and the interaction between particle
size distribution and nutritional value of sediments.
During the present study efforts were made to answer the following questions:
1) Which biochemical components of potential food influence growth and survival of
Chironomus riparius under controlled conditions and which components
influence growth of this species in natural sediments?
2) Do physical characteristics of sediments, which serve simultaneously as food and
habitat, alter behaviour, growth, and survival of C. riparius?
3) How do differences in nutritional value of sediments lead to differences in multispecies communities of detritus feeders in the field?
21
Chapter 1
Outline of this thesis
The present study aims to clarify the influence of nutritional value of sediments
on detritivores. Firstly, the effects of organic matter abundance and composition on
detritivorous invertebrates were assessed. For this purpose a set of artificial food items
were analyzed biochemically and offered in concentration series to first instar larvae of
the model species Chironomus riparius in standardized mineral substrate (Chapter 2).
Growth after one week at limiting food levels and at excess of food was correlated to
biochemical composition of the food and
key parameters for food limitation and
saturation of growth were derived. The
results of this study were verified for the
field situation in Chapter 3. In this
chapter sediments were sampled in the
field and growth of chironomid larvae on
these substrates was determined in the laboratory. The sediments were analyzed for a set
of biochemical variables, water content, and particle size distribution. Correlations were
sought between the biochemical variables and larval growth. The generally sub-optimal
growth of chironomid larvae measured in natural sediments was shown not to be caused
by physical characteristics of the substrates tested. Yet, results suggested that
indigestible sediment particles which were ingested indiscriminately with food reduced
the growth potential. Therefore, Chapter 4 focused on the effect of particle size distribution on chironomid larval growth using artificial mineral substrates. Simultaneously,
preference of the chironomid larvae for the particle size distribution was examined.
Because suitability of substrates may be expressed in preference of organisms, the
active search strategies of the larvae for sediment substrates with different food
concentrations was also explored in Chapter 4. In Chapter 5 the observations on the
effect of nutritional value of sediments on the model species C. riparius is extrapolated
to the field. Biochemical composition of a number of sediments is correlated to the
densities of taxa, with reference to modes of feeding of the benthic invertebrates. In
Chapter 6 the main findings of this thesis are summarized and reviewed.
22
CHAPTER 2
INTERACTION BETWEEN FOOD AVAILABILITY AND FOOD QUALITY
DURING GROWTH OF EARLY INSTAR CHIRONOMID LARVAE
J. H. Vos1, M. A. G. Ooijevaar, J. F. Postma2 and W. Admiraal. 2000.
Journal of the North American Benthological Society 19: 158-168.
Department of Aquatic Ecology and Ecotoxicology, University of Amsterdam, Kruislaan
320, 1098 SM Amsterdam, The Netherlands, 1E-mail: [email protected], 2present
address: AquaSense, P.O. Box 95125, 1090 HC Amsterdam, The Netherlands
23
Chapter 2
Abstract
The nutritional requirements of sediment-feeding invertebrates are poorly
understood. Therefore, growth experiments with larvae of the midge Chironomus
riparius (Meigen) were performed using food items of differing composition. Firstinstar larvae were reared in the presence of different concentrations of each food item,
and larval length and instar were recorded after 1 wk. Saturation growth curves were
fitted, and for each food item the slope and the maximum length attained by larvae were
estimated. Food items were analyzed for organic matter, C, N, P, carbohydrates,
proteins, and total fat content. Maximum length attained by larvae reared on fish foods
and on food items of animal origin was higher than maximum length reached on food
items of plant origin. In general, slopes of the growth curves for larvae reared on foods
of plant origin were higher than slopes of the growth curves for larvae reared on fish
food and food of animal origin. Foods of plant origin had lower N, P, and lipid content
and higher carbohydrate content than fish food and food of animal origin. Ordination of
food composition and the saturation growth-curve parameters indicated that the optimal
food composition depended on the amount of food available. For instance, high N, P,
and lipid contents stimulated growth at high food levels, whereas the amount of
carbohydrate appeared to be important in defining growth at low food levels. We
suggest that this interaction is caused by limiting energy availability at low food levels
versus limiting food quality at high food levels.
24
Quality of organic matter as food for chironomids
Introduction
The role of food as a factor regulating population dynamics of sediment-feeding
freshwater invertebrates is widely recognized (e.g., Rasmussen 1985, Pinder 1995).
Both quantity (Ristola 1995) and quality of food are principal factors influencing the life
histories of benthic invertebrates (Beenakkers et al. 1981). Food quality often is
investigated in the framework of microbial production or enrichment (e.g., Cummins &
Klug 1979, Ward & Cummins 1979, Findlay et al. 1984, Phillips 1984, Bowen 1987,
Couch et al. 1996). Studies in which life-history parameters of benthic invertebrates are
related to the biochemical composition of food are scarce, probably because of problems
with chemical analyses. These benthic invertebrate studies are performed mostly with
artificial diets and focus on only 1 component or 1 category of components (Cowey &
Forster 1971, Roman 1983, Cargill et al. 1985, D'Abramo & Sheen 1993).
In contrast to benthic invertebrates, the role of food composition for zooplankton, especially cladocerans,
has been studied more extensively. Most of this
research has focussed on elemental C, N, P, and on fatty acids (e.g., Brett & MüllerNavarra 1997, DeMott & Müller-Navarra 1997, Gulati & DeMott 1997), although
additional components (carbohydrates and protein) also have been studied (Sterner
1993, Cowie & Hedges 1996, Kilham et al. 1997, Lürling & van Donk 1997). Both P
and polyunsaturated fatty acids (PUFAs) are positively correlated with food quality for
pelagic grazers, in terms of the chemical composition of living phytoplankton. These
same parameters may not be suitable as indicators of food quality in sediments because
processes such as zooplankton grazing, chemical oxidation, and bacterial decomposition
have taken place before phytoplankton settles on the sediment as detritus (Bowen 1987,
Ahlgren et al. 1997). The organic matter in sediments is of lower nutritional value
compared to living phytoplankton, as shown by the large differences in the PUFA
content of the 2 food resources (Ahlgren et al. 1997). Thus, food composition may be a
limiting factor in the life history of detritus-feeding invertebrates.
The objective of our study was to determine the relative importance of both food
quantity and composition for benthic invertebrates. We focussed on artificial food
sources, reasoning that the parameters with the strongest interaction with invertebrate
growth would be promising factors for future characterization of food quantity and
25
Chapter 2
quality in freshwater sediments. Early instar larvae of the midge Chironomus riparius
were used as test organisms because chironomids represent an abundant group of
benthic insects in freshwater ecosystems.
Methods
Food items
Ten different food items were tested: 2 fish foods that often are used in
laboratory experiments (Trouvit® and TetraMin®), 2 food items of animal origin
(Gammarus and Chaoborus), 4 items of plant origin (Ceratophyllum, Potamogeton,
Utricularia, and Populus), 1 algal species (Scenedesmus acuminatus), and 1 yeast
(Saccharomyces cerevisiae). Trouvit® and TetraMin® Flaked Staple Food are commercially available fishfoods. Gammarus pulex originated from Tetra Gammarus® and
Chaoborus partim from Ruto Frozen Fishfood®. Living leaves of Ceratophyllum
demersum, Potamogeton lucens, and Utricularia vulgaris were harvested in June 1996
at Lake Maarsseveen, an oligo-mesotrophic lake situated in the center of the Netherlands. Leaves of Populus tremula were gathered as fresh litter from the ground at
Pampus, Almere, in August 1996. The leaves were gently washed with destilled water
and major veins were removed before further treatment. Scenedesmus acuminatus was
grown in batch culture using Wood’s Hole medium (Guillard 1975) without Na2SiO2.
The algae were grown at 20°C and 200-220 µE·m-2·s-1. After 3-4 d the algae were
harvested by filtration over a Whatman 0.45 µm GFC filter and rinsed with distilled
water. Yeast was bought at a bakery.
All food items were freeze-dried, ground, sieved through a 106-µm mesh, and
stored at -18°C before conducting chemical analyses and growth experiments.
Growth experiments with series of food concentrations
Growth experiments were conducted in polyethylene containers (10 x 10 x 6.5
cm) containing 50 g of prewashed and combusted Litofix® sand (<500 µm, heated at
550°C for 6 h). Two hundred ml of artificial freshwater (Dutch Standard Water, pH 8.2,
210 mg CaCO3, not sterile) were added per container, and the water was aerated
26
Quality of organic matter as food for chironomids
constantly. The food items were tested in concentration series, and each series was
replicated 4 times.
Each concentration series consisted of 9 containers in which freeze-dried food
was added to the overlying water and allowed to settle on the sand. The food amounts
ranged from 0 to 128 mg (± 1% m/m of sediment per container). For most food items, 0,
2, 4, 8, 16, 32, 64, 96, and 128 mg of food were used, resulting in 36 containers per food
item. Different concentrations were used for Scenedesmus, Populus, and yeast to cover
the complete saturation growth curve, i.e. 25 and 50 mg for Scenedesmus and yeast, and
10, 25, 160, 200, and 400 mg for Populus. Replicates of each concentration series were
started on different days to ensure complete statistical independence. Growth experiments on a concentration series were considered successful if larval survival exceeded
80% in the 96-mg containers. Preliminary growth experiments showed that survival at
saturating food levels was optimal and generally exceeded 80% after 7 d of incubation.
All growth periods were restricted to 7 d to avoid possible bacterial or fungal growth or
development of anaerobic conditions in high-food concentrations. Experiments were
conducted at 20°C ± 1°C with a light/dark regimen of 16:8 h under incandescent light.
For each concentration series, larvae (< 24 h old) hatched from at least 10 egg
masses of laboratory cultured Chironomus riparius (Meigen) were combined, and 20
randomly selected individuals were added to each container. An additional group of 20
larvae was randomly collected to determine the length of the larvae at the start of the
experiment. The length of all surviving larvae was measured after 7 d, and survival in
each experimental unit was reported. Larval length was measured rather than biomass
because the biomass of individuals was below the accurate detection limit of the
analytical balance. The duration of the experiment was restricted to 1 wk to ensure that
larvae did not reach the 4th instar. Under favourable food conditions the larvae enter the
3rd instar within 1 wk. The 4th instar was avoided because during that stage both growth
and development towards the pupal and adult stage occur, and the larvae become
sexually dimorphic (Gilbert 1967, Beenakkers et al. 1981). Moreover, last-instar larvae
of several Diptera species have a different chemical composition than earlier instars,
particularly a pronounced increase of lipid content (Gilbert 1967, Beenakkers et al.
1981), which may imply a difference in growth response to food composition compared
to earlier-instar larvae.
27
Chapter 2
5
4
3
2
1
®
®
Trouvit
TetraMin
Gammarus
Chaoborus
Ceratophyllum
Potamogeton
Utricularia
Scenedesmus
Populus
Yeast
0
4
3
2
1
0
4
3
2
1
0
4
3
2
1
0
4
3
2
1
0
0
10
20
30
40
50
60
0
10
20
30
40
50
60
70
-1
food (mg organic matter container )
Fig. 1. Length (± SE) of Chironomus riparius larvae after 1 wk of growth on 10 food items as a
function of food concentration and the saturation growth curves.
28
Quality of organic matter as food for chironomids
Chemical analyses
The organic matter content (ash-free dry mass, AFDM) of food samples was
determined, according to the loss-on-ignition technique, by combusting samples at
550°C for 6 h (Luczak et al. 1997). Total C and N were measured with a Carbo-Erba
Element Analyser. Total P was determined according to Murphy and Riley (1962) and
proteins were determined following Lowry et al. (1951). Carbohydrate analysis was
conducted using the phenol-sulphuric acid-method of Dubois et al. (1956). Total lipid
content was measured gravimetrically after 6 h of soxhlet-extraction using n-hexane (de
Boer 1988). Energy content was calculated by assuming that 1 g of fat releases 38.9 kJ,
1 g of protein releases 17.3 kJ, and 1 g of carbohydrate yields 16.9 kJ.
Statistical analyses
A saturation growth curve was fitted using the least squares method to estimate
the slope (k) and the maximum value (lmax) of the saturation growth curves for larvae
reared on the individual food items. This model provided easily interpretable parameters
and a good fit was obtained. The model follows the equation:
l = l max − (l max − l min ) ∗ e
where
l
− ( k∗
food
100
)
= larval length (mm) for a certain food level, achieved after 7 d of growth,
lmax = maximum larval length (mm), achieved on an individual food item after
7 d of growth,
lmin = minimum larval length (mm), achieved after 7 d of growth with no food
present,
k
= slope of the growth curve (mm mg-1 organic matter), and
food = food level (mg organic matter added to the experimental unit).
Both maximum larval length and slope of the saturation growth curve for each
concentration series were estimated using averages of larval lengths for each container.
Food was expressed as the amount of food added per container in terms of mass of
organic matter (AFDM). Lmax was used as an indicator of optimal growth on the specific
food item. k was used as an indicator of the effect of additional food on growth when
food level was non-saturating.
29
Chapter 2
Multivariate ANOVA (MANOVA) was used to analyze differences in lmax and k
between food items, using the saturation-curve parameters that were estimated for each
concentration series. The chi-square test of heterogeneity of independence (Lozán 1992)
was used to analyze differences in food composition, using the averages of food
component contents per food item, expressed as %s of total freeze-dried matter and of
organic matter. This rather unusual test was used because it can accommodate a large set
of dependent variables such as the chemical parameters of the food items.
Multivariate analyses (redundancy analysis [RDA] and detrended correspondence
analysis [DCA]) were performed using the canonical community ordination program
CANOCO© 3.11 (ter Braak 1988). Chemical parameters of food, expressed as %s of
organic matter, were chosen as "species", food items as "samples", and lmax and k,
resulting from fitting the saturation growth curve, as "explanatory variables". The chemical parameters were ln(x+1) transformed, centered, and standardized to correct for differences in the range of measurements between the different parameters. First, the length
of gradient was calculated by DCA to determine the model that was followed by the
relationship between the chemical parameters of food items and lmax and k. Because the
length of gradient was < 2.0 (0.7), the linear response model (RDA) was chosen for final
ordination (ter Braak 1986). This ordination technique constrained the ordination axes to
Table 1. Food composition expressed in %s of organic matter content (± SE). Coefficients of
variation (CV, %) for each of the food composition variables are given in the last row.
% organic
Biochemical analyses (%)
Energy content
-1
matter
carbohydrates
lipids
protein
(kJ g )
86.8 (0.14)
20.1 (0.64)
17.9 (0.05)
38.2 (2.54)
17.3 (0.54)
87.6 (0.05)
30.1 (0.99)
6.3 (0.07)
37.6 (2.63)
14.4 (0.50)
Gammarus
74.5 (0.09)
12.7 (0.59)
11.6 (0.13)
41.8 (0.28)
14.2 (0.08)
Chaoborus
93.3 (0.09)
8.7 (0.40)
14.2 (0.56)
42.1 (0.66)
14.6 (0.25)
Ceratophyllum
91.1 (0.34)
53.5 (0.86)
3.9 (0.20)
40.1 (0.60)
17.9 (0.21)
Potamogeton
80.5 (0.05)
45.8 (0.91)
2.4 (0.09)
47.8 (0.60)
17.4 (0.21)
Utricularia
85.9 (0.28)
45.7 (0.59)
4.6
37.0 (0.47)
16.3 (0.13)
Scenedesmus
95.8 (0.17)
42.6 (1.39)
9.6 (0.63)
36.8 (0.26)
17.7 (0.33)
Populus
90.2 (0.31)
38.8 (0.91)
3.5 (0.10)
50.8 (1.58)
17.2 (0.32)
Yeast
93.7 (0.13)
41.1 (1.01)
2.2 (0.04)
42.3 (0.68)
15.5 (0.21)
7.4
45.1
11.3
9.2
Trouvit
®
TetraMin
CV
30
®
71.5
-
Quality of organic matter as food for chironomids
be linear combinations of lmax and k. A direct gradient analysis was used because the
experimental setup aimed to analyze the influence of food composition on growth. The
variance inflation factors (VIFs) of lmax and k were used to determine the correlation
between parameters. The VIFs of lmax and k were both below 2, implying low collinearity, and consequently none of the variables was deleted from the dataset. In the
resulting ordination diagram, positively correlated chemical parameters, food items, and
growth-curve parameters were placed near each other, and negatively correlated objects
were placed far apart.
Results
Food composition
The food items had comparable organic matter contents, ranging between 75 and
96% (Table 1). Between 65% (Chaoborus) and 98% (Ceratophyllum) of the organic
matter in food items consisted of carbohydrates, lipids and proteins. Consequently,
between 35 and 2% of the organic matter was not analyzed by the biochemical analyses.
Organic matter, C, protein, and energy content were similar among foods with coefficients of variation (CV) of ≤ 11 %, calculated across all food items. The other chemical
Table 1. Extended
Elemental analyses (%)
Elemental ratios
C
N
P
C/N
C/P
N/P
55.8 (0.36)
9.6 (0.05)
1.2 (0.04)
5.8 (0.03)
47.9 (1.57)
8.2 (0.28)
53.5 (0.08)
9.1 (0.01)
1.2 (0.10)
5.9 (0.00)
46.0 (5.08)
7.8 (0.87)
55.5 (0.19)
10.3 (0.04)
1.3 (0.06)
5.4 (0.01)
41.7 (1.86)
7.7 (0.34)
51.6 (0.08)
11.1 (0.03)
1.2 (0.04)
4.7 (0.01)
40.9 (0.83)
8.8 (0.16)
46.4 (0.46)
4.1 (0.03)
0.3 (0.01)
11.4 (0.07)
177.5 (9.71)
15.6 (0.81)
48.7 (0.18)
4.3 (0.03)
0.3 (0.01)
11.2 (0.09)
134.1 (3.97)
12.0 (0.39)
47.3 (0.40)
4.2 (0.03)
0.3 (0.02)
11.2 (0.09)
152.0 (7.82)
13.6 (0.79)
52.9 (0.08)
5.3 (0.05)
0.6 (0.02)
10.0 (0.08)
80.0 (1.08)
8.0 (0.12)
51.7 (0.72)
4.1 (0.06)
0.2 (0.02)
12.6 (0.07)
231.8 (30.3)
18.4 (2.37)
50.4 (0.42)
9.2 (0.07)
1.5 (0.04)
5.5 (0.03)
33.1 (0.92)
6.1 (0.16)
6.2
41.3
61.8
37.7
71.5
38.3
31
Chapter 2
parameters (%N, %P, %carbohydrates, %lipids, C/N, C/P, and N/P) had CVs of ≥ 35%.
For example, N content of the food items varied between 4 and 11%. The lowest N
contents were found in plant items, whereas the highest %s were found in animal foods.
P content also was lowest in the plant materials (< 0.64%). In contrast, the carbohydrate
content, which varied between 9 and 53%, was lowest in the animal foods and highest in
the plant (macrophyte and algae) foods. Last, lipid content was lowest for yeast,
followed by the plant items, whereas the highest lipid contents were observed in
Trouvit® and the animal foods. Significant differences in composition between food
items are shown in Table 2. In general, food composition was similar among items of
plant origin, and among items of animal origin and fish foods.
Growth and survival
Larval survival generally exceeded 80%, except in the experimental units with
the lowest food levels (2 mg organic matter container-1), where survival ranged between
25 and 100%. Maximum larval length was reached at 70 mg food container-1 for all food
items (Fig. 1). The x-axis of Fig. 1 is truncated at 70 mg food container-1 to present
differences in slope clearly.
Average length of 1st instar larvae at the start of the growth experiments was 0.95 (±
0.02) mm. After 7 d larval length had reached 1.37 (± 0.02) mm in the experimental
units in which no food was added (lmin). Larval length after 7 d of growth increased with
increasing food concentrations, but the food concentrations at which lmax was reached
Table 2. Chi-square test of heterogeneity of independence values (20 df). Significant differences
(P < 0.05) between chemical composition of food items are indicated with an *.
Trouvit
TetraMin
®
®
TetraMin
®
Gammarus
Chaoborus
Ceratophyllum
0.440
Gammarus
0.802
0.036*
Chaoborus
0.269
0.001*
0.956
Ceratophyllum
0.000*
0.000*
0.000*
0.000*
Potamogeton
0.000*
0.000*
0.000*
0.000*
0.692
Utricularia
0.000*
0.000*
0.000*
0.000*
0.999
Scenedesmus
0.007*
0.290
0.000*
0.000*
0.000*
Populus
0.000*
0.000*
0.000*
0.000*
0.251
Yeast
0.006*
0.794
0.000*
0.000*
0.000*
32
Quality of organic matter as food for chironomids
differed between food items. For example, larvae grown with Ceratophyllum,
Potamogeton, Utricularia, and Populus reached their lmax at food levels of 10 to 20 mg
organic matter container-1. In contrast, larvae grown with Scenedesmus reached their lmax
at food concentrations of 70 mg organic matter container-1. Midge larvae fed plant items
reached lower lmax values (2.5 to 3.9 mm) than midge larvae fed artificial fish foods and
animal matter (3.7 to 4.8 mm) (Table 3). The slopes of the saturation growth curves for
larvae fed plant items and Trouvit® were greater than for the other foods. Significant
differences between saturation growth-curve parameters of the individual food items
occured between almost all food items (Table 4).
Ordination triplot
The ordination explained 55% of the variance in the chemical parameters of the food
items, unevenly divided over 2 axes (Fig. 2). Most of the variance of the data set was
expressed on the 1st axis (48%), whereas the 2nd axis explained only 7%. The food items
were ordinated roughly into 2 groups, consisting of either plant and algal material or
commercial fish food and animal items. Maximum length was most strongly associated
with the commercial fish foods and animal items group. In general, these foods were
high in C, N, P, and lipids, and lmax was positively and significantly correlated with %C,
%N, %P, and %lipids (Table 5). Slope was most strongly associated with the plant and
algal group (Fig. 2). In general, these foods were high in C/N, C/P, N/P, and carbohydrates and k was positively and significantly correlated with the ratios C/N, C/P, and
Table 2. Extended.
Potamogeton
Utricularia
Scenedesmus Populus
0.945
0.006*
0.005*
0.106
0.297
0.000*
0.000*
0.000*
0.007*
0.000*
33
Chapter 2
Table 3. Saturation growth-curve parameters (± SE). Maximum length (lmax , mm) and slope (k,
-1
mm mg
2
organic matter). R was calculated for the whole saturation curve as an estimate for
the goodness of fit.
lmax
Trouvit
®
R
k
2
3.7 (0.07)
19.9 (4.22)
0.82
4.0 (0.20)
9.9 (3.28)
0.63
Gammarus
4.8 (0.18)
8.2 (1.71)
0.82
Chaoborus
4.1 (0.18)
7.4 (2.06)
0.72
Ceratophyllum
2.9 (0.10)
16.7 (5.17)
0.60
Potamogeton
2.5 (0.11)
18.2 (8.42)
0.43
Utricularia
2.5 (0.08)
17.5 (5.82)
0.59
Scenedesmus
3.9 (0.22)
4.6 (1.64)
0.64
Populus
2.7 (0.06)
28.3 (7.40)
0.69
Yeast
3.5 (0.11)
8.0 (1.93)
0.75
TetraMin
®
Table 4. F-values of MANOVA (18 df) used to compare maximum larval length and slope of the
growth curves of the individual food items. Significant differences (P < 0.05) between growth
curve parameters of food items are indicated with an *.
Trouvit
TetraMin
®
®
TetraMin
®
Gammarus
Chaoborus
Ceratophyllum
17 *
Gammarus
114 *
40 *
Chaoborus
51 *
2
29 *
Ceratophyllum
68 *
108 *
415 *
307 *
Potamogeton
100 *
109 *
664 *
405 *
165 *
Utricularia
97 *
485 *
353 *
342 *
46 *
Scenedesmus
12
2
23 *
30 *
238 *
Populus
65 *
98 *
539 *
55 *
17 *
18
396 *
11
139 *
Yeast
34
2
Quality of organic matter as food for chironomids
N/P (Table 5). Proteins, organic matter, and energy content were situated near the center
of the plot because of their low variance in the dataset, indicating little influence on
larval growth under the experimental conditions in this study.
Discussion
The high level of variance explained by the ordination suggests that the set of
chemical parameters measured in this study was appropriate for explaining the growth of
early instar chironomid larvae and consequently also for determining food quality. A
part of the remaining unexplained variance is most probably attributable to larval growth
resulting from feeding of the 1st instar larvae on the remains of the egg masses before the
start of the growth experiment, or from microbial growth during the experiment. Another
part is probably attributable to variability of growth among individual larvae. However,
these factors were of minor importance when compared to the effect of composition and
quantity of the food items on larval growth reflected in the high level of variance
explained by the ordination.
Both quantity and biochemical composition of food influenced larval growth of
the midge as indicated by differences in k and in lmax values of the saturation growth
curves. In addition, our results demonstrated an interaction between food quantity and
food quality on larval growth; i.e., different food components were the limiting factors
for growth at different food levels. High N, P, and lipid contents stimulated growth at
Table 4. Extended
Potamogeton
Utricularia
Scenedesmus
Populus
0.1
316 *
282 *
10 *
20 *
126 *
779 *
195 *
28 *
143 *
35
Chapter 2
high food levels (lmax), whereas the amount of carbohydrates appeared to be important in
defining growth at low food levels (k). The interaction of food quality and quantity
might be the consequence of 2 coexisting functions of food. Food can be used as an
energy source (e.g., for maintenance), but it also is used as a source of nutrients essential
for the production of new tissue. Compounds that are easily respired, or have a high
energy content (e.g., carbohydrates) are mainly used as an energy source. Other food
components such as proteins and lipids can be used as energy source, but often are used
preferentially to deliver the components necessary for growth. Proteins supply essential
amino acids (Prosser & Brown 1965, Kimball 1968), and lipids contain fatty acids,
some of which cannot be synthesized by animals and are needed as building blocks of
animal tissue (e.g., polyunsaturated fatty acids, Turunen 1979, Cook 1996).
We found correlations between lmax and certain food components. Because a
surplus of energy is present at high food levels, the qualitative composition of food is
the limiting factor for growth. Lmax was correlated with lipids, N, and P, indicating that
these factors represent growth restricting assimilative compounds at high food levels.
During low food availability, it is more probable that energy is the limiting factor for
growth. The addition of high energy compounds under low food availability may lead to
Table 5. Spearman coefficients of the correlations of maximum larval length (lmax) and slope (k)
with chemical parameters of the food items. Significant correlations (P < 0.05) are indicated with
an *. Chemical parameters and saturation growth-curve parameters were not transformed.
lmax
k
% organic matter
+ 0.152
- 0.261
%C
+ 0.661*
- 0.188
%N
+ 0.770*
- 0.552
%P
+ 0.697*
- 0.661*
% carbohydrates
- 0.782*
+ 0.285
% lipids
+ 0.697*
- 0.273
% protein
- 0.261
+ 0.358
Energy content
+ 0.139
+ 0.406
C/N
- 0.782*
+ 0.648*
C/P
- 0.658*
+ 0.648*
N/P
- 0.638*
+ 0.685*
36
Quality of organic matter as food for chironomids
the effective use of scarce building blocks for growth. This reasoning is confirmed by
the RDA plot where the high energy and easily dissimilable carbohydrates and growth at
low food levels (k) were ordinated on the same side of axis 1. Therefore, it would be
expected that lipids also are correlated with k, because lipids also contain higher levels
of energy than the other food components. Nevertheless, lipid content was not correlated
with k, implying that lipids were not as easily available and respired as carbohydrates
(Prosser & Brown 1965, Kimball 1968). A similar example of the effective use of scarce
building blocks for growth is the “protein sparing” effect that has been observed in
invertebrates and other organisms (Roman 1983). The protein sparing effect is the result
of high-energy compounds being used for maintenance, allowing more proteins to be
used for growth. Interaction of food quality and food quantity also has been found in
daphnids (Sterner et al. 1993, Sterner & Robinson 1994). In these studies, the effect of
food quantity depended on algal food composition, although only C, N, and P were used
to define food quality.
Our study illustrates the importance of food quantity and food quality in
regulating the growth of early instar chironomid larvae for one week under laboratory
conditions. It can be expected that both factors also influence later life stages of
chironomids. Processes such as wing development during the last larval instar, pupation,
succesful emergence, and egg development are crucial to complete the life cycle, but
also are processes with their own special nutrient demands (Beenakkers et al. 1981,
Stanley-Samuelson 1994). Specific fatty acids in the diet are important for normal
growth, successful emergence, egg production, and survival of a number of
invertebrates species (Gilbert 1967, Beenakkers et al. 1981, D’Abramo & Sheen 1993,
Stanley-Samuelson 1994). Other food components such as P and N influence growth,
survival, and fecundity of zooplankton (Brett & Müller-Navarra 1997, Gulati & DeMott
1997). Nutritional growth demands of early instar larvae probably are similar to the
growth demands during the larval stages that follow. However, during the prepupal
stage in which the first changes towards the adult imago take place, different nutritional
needs may be expected, reflected in dependencies on food quality and quantity that
differ from those of young larvae.
Both food quality and quantity are potential factors in the regulation of
invertebrate life history and field distribution because of their variation in place and
37
Chapter 2
Fig. 2. Redundancy analysis plot showing the direct ordination of saturation growth-curve
parameters and food composition, with 48% of variance on ais 1 and 7% on axis 2. Open
triangles indicate chemical parameters, black squares food items, and arrows the saturation
growth-curve parameters. Lmax is an indicator of optimal growth on the specific food item, k is an
indicator of the effect of additional food on growth when the food level is non-saturating.
+1.0
POPULUS
k
TROUVIT®
C
Axis 2, eigenvalue 0.07
N/P
TETRAMIN®
proteins
C/P
lipids
CERATOPHYLLUM
E-content
GAMMARUS
N
C/N
P
organic matter
CHAOBORUS
carbohydrates
UTRICULARIA
POTAMOGETON
YEAST
Lmax
SCENEDESMUS
-1.0
-1.0
Axis 1, eigenvalue 0.48
+1.0
time. For example, algal inputs are characterized by strong seasonal fluctuations and are
subjected to a certain degree of microbial degradation and chemical oxidation (Bowen
1987, Canuel & Martens 1993, Goedkoop & Johnson 1996, Ahlgren et al. 1997,
Kreeger et al. 1997). Moreover, organic matter composition is dependent on the source
of detritus (Cowie and Hedges 1992, Canuel & Martens 1993, Hecky et al. 1993,
Kreeger et al. 1997). It can be expected that both food quantity and quality are lower in
the field compared to the present study (e.g., see N/P, C/P, and C/N ratios in Ahlgren et
al. 1997), which makes it even more probable that these factors are important in
regulating growth of sediment-feeding chironomids. Therefore, more attention should be
38
Quality of organic matter as food for chironomids
paid to biochemical composition and quantity of natural food sources to understand
growth of sediment-feeding chironomids under natural conditions.
Acknowledgements
The study was supported by the Institute for Inland Water Management and
Waste Water Treatment (RIZA), Lelystad. We thank Ronald Gylstra and Paul J. van den
Brink for their help with the canonical and statistical analyses, and Heather A. Leslie for
her comments on the English grammar. We thank Pamela Silver and the 2 anonymous
referees for improving the manuscript with their valuable suggestions.
39
CHAPTER 3
GROWTH RESPONSE OF A BENTHIC DETRITIVORE TO ORGANIC
MATTER COMPOSITION OF SEDIMENTS
J.H. Vos1, P.J. van den Brink2, F.P. van den Ende, M.A.G. Ooijevaar, A.J.P. Oosthoek,
J.F. Postma3, and W. Admiraal
Department of Aquatic Ecology and Ecotoxicology, Institute for Biodiversity and
Ecosystem Dynamics, University of Amsterdam, Kruislaan 320, 1098 SM Amsterdam,
The Netherlands,
1
[email protected],
2
ALTERRA Green World Research,
Department of Water and the Environment, P.O. Box 47, 6700 AA, Wageningen, The
Netherlands, [email protected], 3present address: AquaSense Consultants, P.O. Box
95125, 1090 HC Amsterdam, The Netherlands, [email protected]
Submitted for publication
41
Chapter 3
Abstract
The biochemical composition of lake and stream sediments were analyzed and
compared to detritivore growth and survival to determine which biochemical parameters
correlated most strongly with sediment food quality. Sediments were collected from soft
bottoms of 41 sites and fed to the midge larvae of Chironomus riparius. These
sediments were analyzed for organic matter (OM) content, C, N, P, carbohydrates,
protein, fatty acids, pigments, and grain size distribution. A microbial assay was used as
indicator of the fraction easily biodegradable OM. Data were analyzed by means of
univariate and multivariate analyses. Positive correlations of growth or survival with
polyunsaturated fatty acids (PUFAs), pigments, and labile OM were found when
standardized on dry weight. When variables were standardized based on mass of OM,
additional significant positive correlations with P, carbohydrates, proteins, and fatty
acids of bacterial origin were detected. Similarly, multivariate analyses revealed
stronger correlations between larval growth and survival and biochemical variables
standardized on OM compared to those standardized on dry weight. It was postulated
that dilution of OM by mineral particles caused the difference between the
standardization methods. Organic matter composition constituted an important factor
influencing detritivore growth. Labile OM was found to support the highest larval
growth.
42
Chironomid larvae growth on sediments
Introduction
Detritivorous animals feed on particles that vary through time in abundance and
in state of decomposition. Consequently, food resources available to detritivores differ
in nutritional quality during the course of the year (e.g. Hill et al. 1992, Canuel and
Martens 1993, Ahlgren et al. 1997, Cavaletto and Gardner 1999). The strong positive
response of deposit feeders to seasonal inputs of newly produced organic matter (OM)
suggests that food abundance is a limiting factor much of the year (Lopez and Levinton
1987, Goedkoop and Johnson 1996). Indeed the species composition of algal blooms
has also been recognized as a factor regulating the population dynamics of benthic
fauna (Marsh and Tenore 1990, Cheng et al. 1993). Such factors may be entirely
explained through the varying quality of OM in sediments. Food quality of the pelagic
input to the benthic pool of detritus is dependent on the species that comprise the algae
blooms. For instance, diatoms and flagellates form a high quality food due to their high
polyunsaturated fatty acid (PUFA) content, whereas the low PUFA content of cyanobacteria make their quality as food for detritivores poor (Ahlgren et al. 1997, Brett and
Müller-Navarra 1997, review Napolitano 1999). During sedimentation, the biochemical
content of algae changes due to chemical oxidation, bacterial decomposition, cell
leaching, and stripping by zooplankters prior to settling on to the substrate. The more
labile components degrade first, leaving less easily digested compounds. This process
continues after sedimentation and is promoted by bioturbation. As a consequence, sediments typically contain less digestible OM compared to other food sources consumed
by aquatic animals (Bowen 1987, Fry 1987, Meyers and Ishiwatari 1995). Ahlgren et al.
(1997) found distinct differences in chemical composition between plankton samples
taken in the photic zone and sedimentation samples collected in the aphotic zone of a
large mesotrophic lake. C/N ratios of sedimentation samples were mostly higher than
those of plankton, but the greatest differences between plankton and sedimentation
samples were found for PUFAs. Thus, ongoing degradation leads to a lower food quality to which benthic invertebrates have access compared to that accessible to pelagic
zooplankters.
Planktonic algae are not the sole sources of OM in sediments. Macrophytes, OM
of animal origin, and litter from terrestrial vegetation also add to sediment organic
43
Chapter 3
material. The diverse sources of OM and degradation histories are expected to result in
highly different food sources for the detritivorous component of benthos inhabiting
substrates of water systems that differ in primary and secondary production, current
regime, and terrestrial vegetation type. This study explored differences in food
composition and nutritional state between individual sediments from various sites as
regulating factors of detritivore growth. Field samples of unpolluted sediments of
streams and lakes in the Netherlands and the Pripyat basin (Republic of Belorussia)
were taken to the laboratory where growth of the detritivorous Chironomus riparius
Meigen larvae on the individual substrates was determined. In conjunction, the sediments were characterized with respect to a large number of chemical and physical parameters to identify the main factors regulating growth of the invertebrates. Growth and
survival of the larvae were correlated to these sediment parameters by means of univariate and multivariate analyses.
Methods
Sediment sampling
A total of 41 freshwater sediment samples taken from habitats ranging from
small streams to large lakes were obtained using an Eckman-Birdge grab which was
adjusted to sample the upper 4 cm surface layer. All sediments were analyzed by the
analytical laboratory AlControl, Hoogvliet, the Netherlands, for metals, PAHs, PCBs,
and pesticides. The sediments contained the sum of PCBs (PCB-28, -52, -101, -118, 138, -153, and -180) 7 < µg kg-1, sum of pesticides (aldrin, dieldrin, endrin, DDT, endosulfan, HCHs, heptachlor, and heptachlorepoxide) < 13 µg kg-1, sum of chloride benzenes (di-, tri-, tetra-, penta-, and hexachloride benzenes) < 1 µg kg-1, sum of PAKs
(naftalene, benzo(a)antracene, benzo(ghi)perylene, benzo(a)pyrene, fenanthene, indeno(1, 2, 3-cd)pyrene, anthacene, benzo(k)fluoranthene, chrysene, fluoranthene) < 0.55 mg
kg-1, EOX < 0.31 mg kg-1, mineral oil 47 < mg kg-1, and Cd < 0.4 mg kg-1, Hg < 0.05
mg kg-1, Cu < 5 mg kg-1, Ni < 8 mg kg-1, Pd < 13 mg kg-1, Zn < 16 mg kg-1, Cr < 15 mg
kg-1, and As < 4 mg kg-1 dry mass. According to the Dutch regulations (Evaluatienota
Water 1994) all 41 sediments were clean.
The sediment samples were collected between March 1997 and October 1998
44
Chironomid larvae growth on sediments
from 38 sites throughout the Netherlands and from 3 sites in the Republic of Belorussia
(Pripyat basin). Of the 41 samples, 20 were taken from large and shallow lakes, 6 from
small lakes, 6 from large rivers (width > 5m), and 9 from small streams. Riparian vegetation ranging from woods to meadows. All sediments were frozen at -20°C within 6 h
after sampling. After thawing the sediments were sieved through a 1000 µm mesh to
remove larger particles such as pebbles, leaves, and twigs. The sediments were frozen a
second time to ensure the removal of all indigenous animals.
Growth experiments with chironomid larvae
Growth experiments were conducted at 20°C ± 1°C and a 16:8 hour light:dark
regime. Experiments were carried out in polyethylene containers (10 x 10 x 6.5 cm).
100 ml of homogenized sediment and 200 ml of artificial freshwater (Dutch Standard
Water, pH 8.2, 210 mg CaCO3 l-1) were added to each container and the water was
continuously gently aerated. The sediments were allowed to settle and stabilize for 24 h,
and pH and oxygen saturation of the overlying water were measured at the beginning of
the experiment.
At the start of each experiment, larvae originating from at least 10 egg masses of
Chironomus riparius (Meigen), a detritivorous (Rasmussen 1984, 1985) laboratory
cultured midge, were used. Experiments were started by randomly adding 20 1st instar
larvae less than 24 h old to each container. An additional group of 20 larvae was
randomly collected to determine initial larval length by means of a binocular microscope. During the experiment, oxygen levels and pH were checked every 2-3 d. In
addition, ammonium, nitrite, and nitrate concentrations in the overlying water were
measured at the start of the experiment using Quantofix test sticks (SE = 5 mg N l-1 for
NH4+) and TetraTest Nitrite test kit (SE = 0.05 mg N l-1 for NO2- and NO3-). After 14
d, the lengths of surviving larvae were measured with a binocular microscope. Since
larvae decrease in length during the prepupal stage it was decided to give these larvae
the greatest length found in the reference containers of growth experiments that were
started at the same day. Growth experiments on each sediment sampled in 1997 were
replicated 4 times while the growth experiments sampled on sediments sampled in 1998
were replicated 3 times. To test for food limitation, larval growth on the 1997 sediments
was also tested 4 times with additions of 100 mg of the fishfood mixture each week.
45
Chapter 3
The condition of 1st instar larvae used in the growth experiments was monitored by
taking along 3 control units each day growth experiments were started. Controls consisted of containers with 50 g of combusted Litofix© sand (<500 µm, heated at 550°C for 6
h), 200 ml of Dutch Standard Water and 100 mg of a mixture of the commercial
available fishfoods Trouvit and Tetraphyll (95:5 m:m) each week. Replicates of each
sediment were started at different days to ensure complete statistical independence.
Chemical analyses
Sediment samples for chemical analyses were collected in containers similar to
those used for growth experiments, and were treated identically as sediment used for the
growth experiments. These sediments were frozen directly after starting the growth
experiments. The resulting 3 or 4 subsamples per sediment were mixed quantitatively,
than freeze-dried and stored at -20°C. Grain size distribution was determined by sieving
and the pipet method descibed in ISO 11277 (1998). Water content was determined by
freeze drying a preweighted sediment sample in triplicate.
The OM content was determined as loss-on-ignition by combusting the material
at 550°C for 6 h (Luczak et al. 1997) in triplicate. Total C was measured in duplicate
with a Carbo-Erba Element Analyser. N was measured according to Kjeldahl (ISO
11261 1995).
Total P was determined according to Murphy and Riley (1962) and protein
according to Rice (1982), with both analyses conducted in duplicate. For analyzing
carbohydrates, a modified method based on the phenol-sulphuric acid-method of Dubois
et al. (1956) was used. It was noted that the baseline of the photometric spectra between
400 and 600 nm of the phenol-sulphuric acid solution of the individual sediments
differed in intercept. It was decided to correct absorption at 485 nm with additional
spectrophotometric measurements at 440 and 550 nm according to the following
calculation for both sediment samples and calibration curve: Abs
485 nm’=
Abs
485 nm
((Abs 550 nm + ((Abs 440 nm - Abs 550nm)*65/110)), in which Abs = absorption and Abs
nm’=
-
485
Abs at 485 nm corrected for intercept of the baseline.
Chlorophyll-a and pheaophytin were measured according to Nusch and Palme
(1975) in duplicate sediment samples. The ethanol solution was centrifuged in closed
test-tubes to avoid optical disturbance by suspended sediment. Chlorophyll-a and
46
Chironomid larvae growth on sediments
pheaophytin contents were summed because during the analytical procedure chlorophyll-a was found to partly degrade into pheaophytin indicated by a large standard error
of chlorophyll:pheaophytin ratio among replicates.
Lipids were extracted with a 1:1:0.9 v/v/v chloroform:methanol:water mixture
following the Bligh and Dyer (1959) procedure. Prior to the extraction, preweighed
sediment samples of 5 - 10 g together with 8 ml double destilled water were sonificated
for at least 5 minutes in a -4°C water bath. The resulting collected chloroform was
evaporated with nitrogen gas. For analyses of fatty acid composition the lipid samples
were diluted again in an appropriate volume of hexane containing heneicosaenoic acid
(21:0, 838.75 mg ml-1) as an internal standard and BHT (2,6-di-tert-butyl-p-cresol, 50
mg ml-1) as an antioxidant with nitrogen as the overstanding gas and were stored at
-20°C until transesterification. Fatty acid methyl esters (FAME) were obtained by mild
alcanolic methanolic transesterification as described in Guckert et al. (1985). The
FAME samples were stored at -20°C with overstanding nitrogen gas for no longer than
2 months before Gas Chromatographic analysis took place. GC separation of the FAME
was performed by injecting a 1 µl aliquot in a very polar 50 m CP-Sil 88 column (ID
0.25 mm, film thickness 0.20 mm) with a splitflow of 1:40. Optimal separation of
FAME peaks was obtained with a temperature program that began at injection with an
initial column temperature of 180°C for 10 minutes followed by a rise of 3°C min-1 to a
final temperature of 225°C, where it was held for 10 minutes. Fatty acid nomenclature
used in this study conforms to the A:BωC model where A designates the number of
carbon atoms in the fatty acid methyl ether, B the number of double bonds, and C the
distance of the closest double bond from the aliphatic (ω) end of the molecule. The fatty
acids (FAs) mentioned in this study and used for further calculation and statistical
analyses were all cis-isomers.
Tentative identification of FAME peaks was based on co-elution with the 21:0
standard and by comparison of relative retention times, calculated as the retention time
(RT) of the peak minus the time at which the solvent peak appeared divided by the
retention time of 16:0 or 21:0 minus the RT of the solvent peak. Final identification was
based on Mass Spectrometry analyses of 4 sediment FA samples performed by dr. Eric
Boschker, NIOO, Yerseke, The Netherlands. A PUFA variable was obtained by
summing up the peak areas of 16:2ω4, 16:3ω4, 18:2ω6, 18:3ω3, and 18:3ω6. Peak
47
Chapter 3
areas of FAMEs of bacterial origin (i.e. i14:0, i15:0, a15:0, 15:1, i16:0, i16:1, i17:0, and
a17:0; Parkes 1987; Napolitano 1999) were added to obtain a bacterial FA variable. A
measure for total FA was calculated by adding all fatty acid peaks from 12:0 up to the
last peak appearing in the chromatogram before the 21:0 internal standard peak
(18:3ω3). Only FAME peaks which appeared before the internal standard in the
chromatogram were used for further calculations because the peaks appearing later in
the chromatogram showed irregular retention times.
Energy content (E-content) was calculated by assuming that 1 g of fat releases
38.9 kJ, 1 g of protein releases 17.3 kJ, and 1 g of carbohydrate yields 16.9 kJ.
Assessment of the most labile fraction of the organic matter
A microbial assay was used to obtain a measure of the labile, i.e. easily
degradable, fraction of the sediment organic matter. Microbial mineralization was
measured as CO2 production. Wet sediments were used that had been kept frozen until
analysis. A bacteria inoculum was prepared from the surface layer of a sediment
containing a decaying cyanobacterial mat (Oscillatoria sp.). Bacteria were detached by
ultrasonic treatment and particles were removed by centrifugation (5 min 50 g). In a 77
ml gas-tight bottle 4 ml of sediment was suspended in 11 ml of a 55 mM phosphate
buffer (pH 7.1) and 1 ml of the bacteria inoculum was added. After 30 min of aeration
pH was measured and the bottles were capped gas-tight. The bottles were placed on a
rotary shaker at 20°C in the dark and after allowing one hour equilibration the CO2
concentration in the headspace was measured gaschromatographically. After 48 hours
incubation the CO2 concentration was measured again and the pH was measured. The
headspace contained sufficient oxygen to maintain oxic conditions throughout the
experiments. Gas in the headspace was assumed to remain at atmospheric pressure and
the CO2 concentration in equilibrium with the aqueous phase. Total CO2 in carbonic
acid, bicarbonate and carbonate in the aqueous phase was calculated according to
Stumm and Morgan (1981). Due to the large size of the headspace (61 ml) around half
the total CO2 was in the gas-phase thus ensuring accuracy of the measurement. CO2
production was calculated by subtracting the total concentration in water and headspace
at the start from the total concentration after 48 h. Blancs showed that CO2 produced
from organic matter in the inoculum was negligible. Controls with yeast extract (2 mg
48
Chironomid larvae growth on sediments
per bottle) in stead of sediment were used to check for reproducibility during the
measurements and to allow comparison with future experiments. None of the sediments
was rich in inorganic carbonates so no attempt was made to remove these. During the
incubation the pH declined less that 0.25 units, thus limiting possible interference of
carbonates.
Univariate statistical analyses
Correlations between larval growth, survival and chemical variables were
determined with Pearson correlation using the average larval survival and growth per
sediment and the mean of repeated analyses for the different sediment variables.
Correlations were performed with variables standardized on both dry weight (DW) and
OM. Growth and survival on sediments collected in 1997, with and without surplus of
food were compared with a two-way ANOVA.
Multivariate analyses
Multivariate analyses were performed using Principal Component Analysis to
obtain a graphical summary of the data set and an overview of mutual relationships
between sediment variables on the one hand and larval growth and survival as
determined in the laboratory tests on the other hand (ter Braak 1995). PCA was chosen
for final ordination because the length of gradient was < 2.0 as was determined with
Detrended Corresponce Analysis (DCA). PCA is an ordination method which uses a
Table 1. Summary of variables found in the 41 substrates. Averages are calculated from the
average values of each indiviual sediment. CV = coefficient of variance. Min = minimum and
max = maximum value as found in the dataset. SWC = sediment water content (% of wet
weight), OM = organic matter (% of dry weight), %<63 µm = percentage of volume particles <
63 µm, and %<210 µm = percentage of volume particles 0-210 µm.
average
min
max
CV
SWC
32.9
14.1
90.6
24
OM
2.3
0.2
8.8
121
C/N
24.2
3.0
107
91
%<63 µm
20.8
0.7
79
126
%<210 µm
60.9
5.1
96
50
49
Chapter 3
Table 2. Overview of variables expressed as portion of dry weight or of organic matter
measured in the 41 sediments. Averages are calculated from the average values of the
individual sediments. CV = coefficient of variance. Minimum (min) and maximum (min) value as
107
2,276
0
613
81
20.9
0
7.0
-1
mmol g
CO2 production
104
4,148
17.2
972
122
77
0.3
12.6
µg g
pigments
-1
96
34
0.9
8
135
0.9
0
0.1
-1
kCal g
E-content
110
1,263
0
271
116
20.3
0
-1
µg g
bacterial FAs
4.1
145
779
0
148
127
7.4
0
-1
µg g
PUFAs
1.7
161
214,622
184
21,355
124
1,616
2.8
-1
µg g
ΣFA
212
135
731
5.3
104
179
18.1
0
1.7
-1
mg g
protein
133
224
0
27
161
5.5
0
1
-1
mg g
carbohydrates
79
56
2.8
15
116
3.2
0.01
0.3
-1
65
169
6
43
145
6.6
0.1
1
-1
mg g
mg g
P
C
N
64
1,000
126
755
114
59
0.5
17
-1
CV
max
min
average
unit
mg g
max
min
organic matter
dry weight
average
variables standardized on
variables standardized on
CV
found in the dataset.
linear model for dimension reduction. In PCA, imaginary, latent explanatory variables
(principal components) are calculated from the data set which best explain the variation
in sediment parameter composition between sites. The first principle component is
constructed in such a way that it explains the largest part of the total variance possible,
50
Chironomid larvae growth on sediments
the second one the largest part of the remaining variance, etc. The first two principle
components were used as axes to construct an ordination diagram and the weights of the
parameters and sites with these variables are plotted in the diagram represented by
points. After the construction of the diagram, the larval performance parameters (growth
and survival) were superposed on the diagram, i.e. they were regressed on the axes
using the site points. Within PCA, all sediment characteristics were standardized and
centered to make them mathematically equally important. This is necessary because all
characteristics were measured or expressed in different units. Two analyses were performed, 1 on the sediment data with biochemical variables standardized on DW, and 1
on data with biochemical variables standardized on OM. Permutation tests were performed on whether larval growth and survival have a significant relation with the variation
in sediment characteristics among sites, using the constrained version of PCA, Redundancy Analysis (ter Braak and Smilauer 1998). All multivariate analyses were performed with the CANOCO for Windows software package (ter Braak and Smilauer 1998).
Results
Composition of the sediments
Grain size distribution of sediments samples ranged from silty to sandy (Table
1). Sediment water content ranged from 14.1 to 90.6 % of wet weight, but the coefficient of variation among samples was relatively low (CV = 24%). The variation in
organic matter (OM) content was well spread over the samples (CV = 121%). All
biochemical variables showed a high CV when standardized on dry weight (DW) (Table
2). Standardization on OM content resulted in lower variation for most of the biochemical variables. Only ΣFA, PUFAs, and labile OM had slightly higher CVs when standardized on OM.
If the variables were standardized on DW many significant correlations were
found among the biochemical variables (Table 3). Most biochemical variables standardized on DW were also found to be significantly correlated with OM content. This may
be expected, since the biochemical variables are all considered to represent part of the
OM fraction. Levels of biochemical variables expressed as proportion of DW may
therefore be expected to follow the level of OM. Only ΣFA and PUFAs were found to
51
Chapter 3
Table 3. Correlations of sediment parameters with the biochemical variables standardized on
total fatty acids, PUFAs = polyunsaturated fatty acids, bac. FAs = fatty acids of bacterial origin,
%<63 µm = percentage of volume particles smaller than 63 µm, %<210 µm = percentage of
C
N
P
carbohydrates protein ΣFA
PUFAs bac. FAs
N
+0.81**
P
+0.70** +0.52**
carbohydrates
+0.77** +0.83** +0.37**
protein
+0.51** +0.57** +0.67**
+0.45**
ΣFA
+0.17
+0.12
+0.26
+0.10
+0.18
PUFAs
+0.26
+0.06
+0.55**
+0.05
+0.26
bacterial FAs
+0.70** +0.44** +0.86**
+0.37**
+0.54** +0.20
+ 0.71**
pigments
+0.51** +0.35*
+0.44**
+0.33**
+0.34*
+ 0.29*
E-content
+0.64** +0.70** +0.68**
+0.64**
+0.96** +0.33* + 0.26
+0.33*
+0.52** +0.10
CO2 production +0.51** +0.38** +0.64**
+0.21
+0.06
+ 0.50**
+ 0.57**
+ 0.43** + 0.68**
have a low number of significant correlations with the other chemical variables if
expressed as portion of DW. Standardization on OM content decreased the number of
correlations between biochemical variables, thus indicating a diverse composition of
OM (Table 4). OM was strongly correlated to particle sizes < 63 µm (R2 = 0.92, P <
0.01) and less strong to particle sizes < 210 µm (R2 = 0.31, P < 0.05).
Table 4. Correlations of sediment parameters with the biochemical variables standardized on
total fatty acids, PUFAs = polyunsaturated fatty acids, bac. FAs = fatty acids of bacterial origin,
%<63µm = percentage of volume particles smaller than 63 µm, %<210 µm = percentage of
C
N
P
carbohydrates protein ΣFA
PUFAs bac. FAs
N
+0.23
P
+0.67** +0.09
carbohydrates
- 0.00
+0.10
+0.08
protein
+0.11
+0.07
+0.33*
+0.08
ΣFA
+0.21
- 0.02
+0.29*
+0.05
+0.05
PUFAs
+0.54** +0. 20
+0.78**
+0.19
+0.34*
+0.20
bacterial FAs
+0.36*
+0.06
+0.58**
+0.12
+0.28*
+0.09
+0.83**
pigments
+0.11
+0.18
+0.21
+0.31*
+0.04
+0.05
+0.55** +0.49**
E-content
+0.18
+0.07
+0.42**
+0.29*
+0.87** +0.49** +0.41** +0.29*
CO2 production +0.03
+0.07
+0.16
+0.17
+0.24
52
+0.16
+0.47** +0.58**
Chironomid larvae growth on sediments
dry weight. Pearson coefficient R and significance level. * = P < 0.05, ** = P < 0.01. ΣFA =
2
E-content = energy content, SWC = sediment water content, OM = organic matter,
volume particles smaller than 210 µm.
pigments
E-content SWC
+0.35*
+0.64**
+0.52**
OM
C/N
%<63 µm %<210 µm
+ 0.89**
+ 0.83**
-0.20
+ 0.77**
+0.26*
+ 0.63**
+ 0.74**
+0.09
+ 0.81**
+0.41**
+ 0.84**
+ 0.79**
+0.07
+ 0.63**
+0.29*
+ 0.54**
+ 0.57**
-0.12
+ 0.56**
+0.34*
+ 0.14
+ 0.12
+0.04
+ 0.20
+0.07
+ 0.25
+ 0.16
+0.11
+ 0.25
+0.49**
+ 0.63**
+ 0.69**
+0.09
+ 0.73**
+0.49**
+ 0.44**
+ 0.52**
+0.08
+ 0.40**
+0.37**
+ 0.68**
+ 0.69**
-0.07
+ 0.65**
+0.36**
+ 0.50**
+ 0.53**
-0.08
+ 0.52**
+0.56**
Growth and survival of midge larvae
Length of the larvae at the start of the experiments averaged 0.89 mm (SE =
0.02). After 14 d larvae in the controls averaged 12.5 mm (SE = 0.28) in length and
>70% were in their 4th instar. After 14 days larval survival exceeded 80% in all controls.
Survival per experimental unit with sampled sediment ranged between 0 and 100% and
organic matter. Pearson coefficient R and significance level. * = P < 0.05, ** = P < 0.01. ΣFA =
2
E-content = energy content, SWC = sediment water content, OM = organic matter,
volume particles smaller than 210 µm.
pigments
E-content SWC
+0.12
+0.54**
+0.31*
OM
C/N
%<63 µm %<210 µm
+0.06
-0.08
-0.45**
-0.04
+0.01
-0.11
-0.22
+0.11
-0.14
+0.29*
+0.10
+0.02
-0.08
-0.04
+0.31*
-0.09
-0.17
-0.16
-0.16
+0.34*
-0.25
-0.30*
+0.02
-0.25
-0.19
-0.14
-0.30*
+0.00
-0.26
+0.23
-0.14
-0.26
-0.07
-0.22
+0.15
-0.25
-0.35*
-0.17
-0.37**
+0.15
-0.17
-0.27*
-0.14
-0.25
+0.27*
-0.32*
-0.43**
-0.24
-0.43**
+0.05
53
Chapter 3
Fig. 1. Larval growth (mm) and survival (%) after 14 days on sediments provided with and
without surplus of food. White bars represent sediments supplemented with 100 mg of fish food
per week, black bars represent sediments without additional food. Errors bars = SE.
12
growth (mm)
10
8
6
4
2
0
control
Roode
Hierdense
Klif Drontermeer
Heijnen
Beek
Krammerse
Blauwe
shoar
Slikken
Oude
Kamer
Waal
Mirns
Drentsche
Oostvaarders
Drontermeer
Aa Plassen
channel
100
survival (%)
80
60
40
Drontermeer channel
Drontermeer channel
Oostvaarders Plassen
Oostvaarders Plassen
Drentsche Aa
Drentsche Aa
Mirns
Mirns
Oude
Waal
Oude Waal
Blauwe
Kamer
Blauwe Kamer
Krammerse
Slikken
Krammerse
Slikken
Drontermeer
shoar
Drontermeer
shoar
Heijnen
Heijnen
Hierdense
Beek
Hierdense
Beek
Roode
Klif
Roode
Klif
0
control
control
20
growth between 0.8 and 11.0 mm. Growth was highly significantly correlated with
survival in sediments not augmented with fish food (R2 = 0.69; P < 0.01).
Larval growth and survival on sediments that were provided with fish food
(those collected in 1997) were similar to growth in the controls (Fig. 1). Survival was
>80% in all experimental units provided with fish food. Growth and survival were significantly lower (P < 0.05) on the sediments not provided with fish food compared to
the sediments provided with excess of food.
54
Chironomid larvae growth on sediments
Table 5. Correlations of growth and survival of C. riparius larvae after 14 days with sediment
2
parameters. Pearson coefficient R and significance level. * = P < 0.05, ** = P < 0.01. SWC =
sediment water content, OM = organic matter, %<63 µm = percentage of volume particles
smaller than 63 µm, %<210 µm = percentage of volume particles between 0 and 210 µm.
growth
survival
survival
+0.69**
SWC
-0.01
-0.15
OM
-0.14
-0.25
C/N
-0.24
-0.33*
%<63 µm
-0.15
-0.19
%<210 µm
+0.51**
+0.34
During the growth experiments, the oxygen saturation level did not fall below
60% in any of the experimental units of the 41 sediments. All NO2- concentrations were
<1 mg l-1, the NH4+ concentrations <10 mg l-1, and the pH in the overlying water varied
between 7.1 and 8.5 during the experimental period.
Correlations of larval growth and survival with sediment parameters
Larval growth and survival in non-augmented sediments were significantly correlated (P < 0.01, Table 5). Growth was positivily correlated with the particle size fraction < 210 µm.
When biochemical variables were expressed on the basis of DW, correlations of
growth and survival were found with PUFAs, pigments, and labile OM (P < 0.05, Table
6). When sediment variables were standardized on OM content, the strength and number
of correlations increased, with additional significant correlations (P < 0.05) found with
P, carbohydrates, protein, FAs of bacterial origin, and energy-content.
Multivariate analyses
The first 2 axes of the PCA plot based on biochemical variables expressed on a
DW basis display 62% of the total variance among sediment variable (Fig. 2, Table 7).
All of the sediment characteristics are displayed on the right side of the diagram, indicating that they are all, to some extent, positively correlated with each other (see also
Table 3). Larval growth and survival correlated most strongly with sediment PUFA
content. The results of the Monte Carlo permutation tests also show a significant corre-
55
Chapter 3
Table 6. Correlations of growth and survival of C. riparius larvae after 14 days with the
biochemical variables expressed per unit of dry weight or organic matter weight. Pearson
coefficient R and significance level. * = P < 0.05, ** = P < 0.01. ΣFA = total fatty acids, PUFAs
2
= polyunsaturated fatty acids, E-content = energy content.
variables standardized on
dry weight
organic matter
growth
survival
growth
survival
C
-0.10
-0.27*
+0.24
+0.02
N
-0.06
-0.20
+0.21
+0.12
P
+0.12
+0.06
+0.45**
+0.31*
carbohydrates
-0.01
-0.22
+0.41**
+0.20
protein
+0.21
+0.13
+0.32*
+0.29*
ΣFA
-0.05
-0.01
-0.03
+0.08
PUFAs
+0.51**
+0.39**
+0.58**
+0.49**
bacterial FAs
+0.25
+0.21
+0.49**
+0.50**
pigments
+0.39**
+0.11
+0.70**
+0.51**
E-content
+0.15
+0.04
+0.33*
+0.32*
CO2 production
+0.56**
+0.41**
+0.54**
+0.59**
lation between the larval performance parameters and the sediment characteristics
(Table 7).
The biplot of the sediment characteristics with biochemical variables expressed
on an OM basis explained 43% of the total variance, while larval performance explained
20% of the total variance (Fig. 3, Table 7). Again all sediment characteristics are
displayed on the right in the diagram, with the exception of water content. The setting of
the biplot indicates a positive correlation with most of the sediment characteristics, and
especially with CO2 production, pigments, fatty acids of bacterial origin, energycontent, protein, carbohydrates, and N. A very strong correlation between the larval
performance parameters and the sediment characteristics is indicated by the Monte
Carlo permutation tests (Table 7).
Stronger correlation of larval performance and sediment characteristics (lower
P-values) are found if the biochemical variables are standardized on OM content
compared to standardization of the biochemical variables on DW (Table 7). Moreover, a
higher % of variance used to explain larval growth and survival is displayed in the
biplot with the standardization on OM whereas the total variance expressed of the sedi-
56
Chironomid larvae growth on sediments
ment characteristics is lower. This means that a lower % of variance is used to explain a
higher % of variance of larval growth and survival in the data set with the biochemical
variables standardized on OM content compared to the data set with the biochemical
variables standardized on DW.
Discussion
During this study, sediments were sampled in several different water systems
ranging from large lakes to small streams and from silty to sandy sediments. The origin
of the organic matter (OM) presumably varied between predominantly algal in some
systems to being largely land-derived in others. In spite of the broad variation in the
substrates used in this study, growth and survival of Chironomus riparius larvae were
well correlated to chemical characteristics of these sediments. Evidently, the nutritional
value of ingested matter is highly limiting for larval growth and survival in many
sediments, since supplementation with high quality fish food stimulated larval growth in
sediments from all 41 sites, simultaneously showing that physical characteristics of the
sediments did not influence larval growth of C. riparius. This finding supports the
hypothesis posed by a few field studies that OM limits and regulates population dynamics of benthic macrofauna (Lopez and Levinton 1987; Goedkoop and Johnson 1996).
The degree of food limitation that we demonstrate may partly be affected by the use of
C. riparius as a test species. C. riparius is known to abound in organically enriched
waters. The very low survival and growth rates in the poorest sediments may have been
caused by relatively high food demands of this species.
Besides growth limitation caused by food supply, specific biochemical components were found to correlate with larval growth and survival. Standardization of these
variables on the basis of sediment OM content resulted in more and stronger
correlations with growth and survival of midge larvae than did standardization on basis
of dry weight (DW). The PCA analyses also showed more variance of larval performance was explained when sediment characteristics were expressed on the basis of OM
content. OM content of the sediments was strongly correlated with the small particulate
fraction (< 63 µm). C. riparius larvae are mainly deposit feeders that eat whole sediments with a particle size limit determined by the mentum width (for instance, between
57
Chapter 3
Fig. 2. PCA biplot showing characteristics of 41 unpolluted sediments with the (bio)chemical
variables standardized on dry weight. Open circles represent sediments, black dots sediments
parameters, and arrows larval performance parameters. For percentages of total variance and
results of additional Monte Carlo permutation tests see Table 7.
+1.0
Axis 2, eigenvalue 0.13
carbohydrates N
organic matter
C
E-content
proteins
C/N
survival
total FA
pigments
P
CO2 production
%>210 µm
bacterial FA
growth
PUFA
-1.0
-1.0
Axis 1, eigenvalue 0.49
+1.0
42 and 65 µm for 2nd instar larvae, Chapter 4). The strong correlation of OM content
with the small particle fraction of the sediments secures that standardization of variables
on an OM basis includes the part of the sediments that potentially can be used as food
source by the chironomid larvae. The small particle fraction probably not only contained OM, but also mineral particles. The midge larvae used in our experiments inevitably ingested different quantities of small mineral particles along with the OM during
feeding trials. Consequently, growth may have been limited to varying extents by dilution effects, associated with the portion of small mineral particles ingested (Chapter 4).
Differences in mineral constituents and thus in the quantity of ingested OM among the
58
Chironomid larvae growth on sediments
Fig. 3. PCA biplot showing characteristics of 41 sediments with the biochemical variables
standardized on organic matter content. Open circles represent sediments, black dots
sediments parameters, and arrows larval performance parameters. For displayed percentages
of total variance and results of additional Monte Carlo permutation tests is referred to Table 7.
+1.0
%>210 µm
carbohydrates CO2 production
N
proteins growth
Axis 2, eigenvalue 0.13
SWC
E-content
survival
pigments
bacterial FA
PUFA
P
total FA
C
C/N
-1.0
-1.0
Axis 1, eigenvalue 0.30
+1.0
individual sediments may have disguished the influence of a set of biochemical constituents of OM present in the sediments on the life history parameters of C. riparius when
these biochemical constituents were expressed on a DW basis. However, correlating
larval growth to biochemical variables standardized based on OM content revealed the
influence of organic matter composition directly. The effect of organic matter composition is independent of organic matter abundance and consequently is not influenced by
overall food ingestion rate of the chironomid larvae.
In most studies, chemical parameters of sediments are expressed as portion of
DW. If sedimentation traps are used to examine food sources of detritivorous inver-
59
Chapter 3
tebrates, the two different standardization procedures will likely not lead to the differences found during the present study because organic content of the sedimented matter
is expected to be high. However, as in the present study, sampled sediments often contain a broad range of mineral contents, potentially obfuscating a number of relationships
if biochemical variables are standardized based on DW alone.
Growth and survival of Chironomus riparius larvae did correlate with a few
variables standardized based on DW, e.g. CO2 production as indicator of labile OM,
PUFAs, and pigments. The strong correlation between larval growth and PUFAs may
have arisen from the inability of animals to synthesize essential fatty acids (especially
ω3 and ω6 fatty acids; Brett and Müller-Navarra 1997, Napolitano 1999). Therefore,
PUFAs have to be obtained from the diet, for instance from algae with high PUFA
contents. Fatty acids in the sediments sampled during this study represented only a
small portion of the total amount of OM and, as such, PUFAs were a minor portion of
the total fatty acids in the substrates. Consequently, it is probable that PUFAs were a
limiting factor for larval growth in most of the sediments tested during this study. Labile
OM was assessed with a microbial degradation assay. Microorganisms were chosen in
order to obtain a measure of overall digestibility of OM. Enzymatic assays are used to
Table 7. Summary of the PCA analyses. Percentage of total variance displayed on the first and
second axis and percentage of the total variance explained by larval performance (growth and
survival). P-values of permutation tests.
biochemical variables
standardized on
dry weight
organic matter
of sediment characteristics displayed on axis 1
49
30
of sediment characteristics displayed on axis 2
13
13
of sediment characteristics explaining larval performance
11
20
explaining larval performance displayed on axis 1
28
76
explaining larval performance displayed on axis 2
41
8
P -value growth
0.035
P -value survival
0.050
≤0.005
≤0.005
% of total variance
Permutation test
60
Chironomid larvae growth on sediments
establish the digestable fraction of specific components such as proteins (Dauwe et al.
1999a,b), but comparable assays that cover all food components are not available.
Judged from the good correlation between larval performance and labile OM the microbial assay was adequate to determine the digestible fraction of OM. Similar to shortchain PUFAs, pigments may be considered as indicators of fresh algal material (Napolitano 1999), while CO2 production is an overall assessment of digestibility of OM.
Together, correlations of PUFAs, pigments, and labile OM with chironomid larvae
growth suggest that the nutritious and relatively easy digestible OM of algal origin was
an important factor regulating growth of chironomid larvae in the field.
Organic matter composition of sediments appeared to constitute a major factor
influencing the growth and survival of Chironomus riparius larvae, in spite of the
complex nature of this material. We base this conclusion on the high number of correlations between the food quality parameters standardized on OM with larval growth and
survival, and the high percentage of variance explained by ordination. For instance, P
was found to be positively correlated with growth and survival. In an extensive number
of studies on daphnid crustaceans, both P and PUFAs have been identified as good
predictors of food quality of living phytoplankton (e.g., Brett and Müller-Navarra 1997,
Gulati and DeMott 1997). Carbohydrates were also found to be positively correlated
with larval growth in spite of the diversity of polymeric sugars. The presently used
carbohydrate analysis not only measures simple sugars, but also complex sugars such as
cellulose which are hardly digestible. At low food levels, carbohydrates are preferentially used for maintenance of the body structures, leaving essential nutrients for
building of new tissue (Roman 1983, Vos et al. 2000). A similar mechanism may have
aided the chironomid larvae to survive in the low nutritional conditions of some of the
sediments sampled during this study. Proteins are also a heterogeneous group, consisting of a range of amino acids, some of which are essential and others non-essential
nutrients. The chironomid larvae may have used proteins as source of essential amino
acids (Cowey and Forster 1971, Cowie and Hedges 1996), of nitrogen, or of amino N
(Kreeger et al. 1996).
In conclusion, the composition of OM in sediments strongly influences growth
and survival of chironomid larvae. The presence of newly produced and labile OM,
indicated by pigments, PUFAs, and microbial mineralization rate, was strongly
61
Chapter 3
correlated with larval growth. That population dynamics of benthic invertebrates in lake
sediments follow seasonal inputs from the pelagic zone, and that the response to algal
inputs varies with the species composition of algal blooms, has been previously
established (Marsh and Tenore 1990, Goedkoop and Johnson 1996, Goedkoop et al.
1998). Here, we stress the importance of the variable organic matter composition as a
key factor regulating the growth of detritivorous invertebrates. This study gives solid
evidence that spatial and temporal differences in detritus quality are a major factor
regulating the growth dynamics of detritivores in soft bottoms.
Acknowledgements
Part of the project was financed by the Institute for Inland Water Management
and Waste Water Treatment (RIZA), Lelystad, The Netherlands. We thank Ronald
Gylstra and Edwin Peeters (Wageningen University) for their valuable comments on
this paper. Steven Arisz (UvA, Amsterdam, The Netherlands) greatly helped with the
fatty acid analyses, by improving the GC analysis and with theoretical support. We are
endebted to Eric Boschker (NIOO, Yerseke, The Netherlands) who identified fatty acid
peaks with the MS. Joke Westerveld (UvA, Amsterdam, The Netherlands) supported the
CO2 analysis.
62
CHAPTER 4
PARTICLE SIZE EFFECT ON PREFERENTIAL SETTLEMENT AND
GROWTH RATE OF DETRITIVOROUS CHIRONOMID LARVAE AS
INFLUENCED BY FOOD LEVEL
J.H. Vos1, M. Teunissen, J.F. Postma2, F.P. van den Ende
Department of Aquatic Ecology and Ecotoxicology, University of Amsterdam,
Kruislaan 320, 1098 SM Amsterdam, the Netherlands. Phone (0031)-20-5257718, fax
(0031)-20-5257716, [email protected], 2present address: AquaSense Consultants,
P.O. Box 95125, 1090 HC Amsterdam, The Netherlands
Submitted for publication
63
Chapter 4
Abstract
Sediment particle size distribution and organic matter content are reported to
determine the field distribution of chironomid larvae. Therefore, combinations of
mineral particles of different size ranges and food level were tested for the influence on
the preference and growth of detritivorus chironomid larvae. Mineral particle size had
no effect on larval growth at saturating food supply. However, at limiting food levels
growth of third instar larvae was hampered by ingestion of small mineral grains (8-63
µm). Second, third and fourth instar larvae were able to construct tubes of silty and
sandy substrates, but tubes that were found in the larger particle size range (550-1200
µm) were less stable compared to those constructed from small particles.
Larvae showed a clear preference for the compartment supplied with food when
offered a choice between two different particle size substrates with only one particle
size substrate supplied with surplus of food, independent of the particle size ranges.
During preference experiments in which larvae were offered two food levels, a threshold concentration between 0.075 and 0.10 mg ml-1 was found below which larvae
continued crawling and did not settle to construct tubes as they did at higher food levels.
When allowed to choose between two food levels both above the threshold concentration, larvae preferred the higher food concentration if the difference between food
levels exceeded 0.75 mg ml-1.
Food level and substrate particle size determined larval motility and preference.
The influence of both factors was governed by food threshold and saturation
concentrations. It is postulated that organic matter content and particle size distribution
in the natural environment are interacting factors determining the abundance of detritivorus chironomid larvae.
64
Particle size and food level effect on C. riparius
Introduction
Chironomid larvae are often a quantitatively important component of macrofauna communities inhabiting freshwater sediments. Hence, their distribution has been
well studied and related to sediment composition and other environmental factors (see
Pinder 1986, 1995 for reviews). In general, detritus feeding chironomids are more
numerous in silty sediments than in sandy sediments (e.g., Thienemann 1954, Maitland
1979, Pinder 1986, 1995), although chironomid-substratum associations may vary with
morphological characteristics of the taxa (Winnell & Jude 1984). The impact of organic
matter content and grain size distribution on the distribution of chironomids in the field
is difficult to distinguish, because they often covary in natural sediments (e.g., Rabeni &
Minshall 1977, Pinder 1986, 1995, Suedel & Rodgers 1994, Maxon et al. 1997,
Reinhold-Dudok van Heel & den Besten 1999). For Chironomus riparius Meigen, a
detritivorous species of eutrophic waters (Rasmussen 1984, 1985), a negative correlation of density with particle size, and a positive correlation with organic matter
content have been found (Learner & Edwards 1966, Leppänen et al. 1998). In the River
Dommel (The Netherlands), a lowland river with high organic input from partially
treated sewage, C. riparius is the most abundant midge species (Groenendijk et al.
1998). The sediment consists mainly of sand, with detritus and silt accumulating locally
along the banks. It is in this patchy environment that the highest density of larvae is
found (Leppänen et al. 1998).
Chironomus riparius larvae are highly sedentary for most of their lifespan. Egg
masses are laid on substrata just below the water surface and, after emergence, the first
instar larvae drift away to find a suitable place to settle. Within a few days the larvae
start to build a living-tube. The larvae keep in physical contact with their tube and
therefore the foraging area is restricted to the immediate surroundings of the tube
entrance (personal observations in laboratory cultures). Consequently, the choice of
settlement site is of critical importance. If larvae leave their burrow they will have to
find a new site that meets their demands. Site choice is not restricted to the early instar
larvae, but also takes place during later life stages. Larval drift in the River Dommel
was studied by Groenendijk et al. (1998), who found that the majority of the drifting
larvae consisted of 3rd instars.
65
Chapter 4
Several ways have been proposed in which particle size could affect larval
preference and performance, including suitability of the substratum for burrowing
(Wiley 1981a, Winnell & Jude 1984) and for tube construction (Brennan & McLachlan
1979) and the risk of physical damage by large particles (Winnell & Jude 1984). Apart
from these factors we hypothesize that particle size determines the feeding mode,
thereby influencing growth opportunities. C. riparius is a deposit feeder ingesting
inorganic particles together with the organic detritus that constitutes the principal food
(Rasmussen 1984b). However, if the inorganic particles are too large to be swallowed
the larvae can only feed on organic aggregates or scrape the organic film from solid
surfaces.
In this study we used an experimental approach to examine if site choice of C.
riparius larvae results from active selection for food level, particle size or both, and if
preferences arise from suitability of the substrate as a food source or habitat. Two types
of experiments were performed: (1) to test the effect of combinations of particle size
and food supply on larval growth. Growth was studied at saturated and non-saturated
food levels with mineral particles of different sizes as substrate. During these growth
experiments larval intestines were checked for the presence of mineral particles. (2) to
determine the capacity of larvae to differentiate between food levels and particle size
ranges. Results of growth and preference experiments are discussed in relation to
substrate suitability and foraging behavior of chironomid larvae.
Methods
Overview of the experiments and general experimental setup
Two growth experiments and two preference experiments were performed. The
first growth experiment was carried out with a set of different particle size ranges and
with a surplus of food to examine the effect of particle size as sole factor influencing
growth and survival of chironomid larvae. The second growth experiment was
performed with two particle size ranges and a set of food concentrations to examine the
influence of mineral particles present in the larval intestines. The small particle size
substrate of 8-63 µm and the large particle size substrate of 550-1200 µm were chosen,
because it was expected that the former could be ingested and the latter could not be
66
Particle size and food level effect on C. riparius
ingested by 3rd instar larvae based on mentum width of 3rd instar larvae (mentum widths
are presented below). Third instars (7 days old) were used, because the intestines of
these larvae are easily dissectable. A growth period of 1 week was chosen, because at
the age of 14 days the first prepupal stages can already be observed. Growth was
measured per individual larva as increase of length.
During the first preference experiment (experiment 3) both 1st and 3rd instars
were allowed to choose between the 2 halves of the experimental unit containing
particles of different size ranges. This experiment was performed first, with excess of
food on both halves of the container and second, with an excess of food on just 1 half of
the container. The aim was to evaluate the relative importance of particle size and food
as determinants of substrate selection by the chironomid larvae. During the second
preference experiment (experiment 4) the ability of 3rd instar larvae to distinguish
between different food levels was tested. During experiments 1 (Larval growth at
saturating food level in a range of different particle sizes) and 3 (Larval preference for
particle sizes in the presence and absence of food), excess food was added at the surface
of the substrate to ensure easily available food. The excess food level chosen was 0.4
mg cm-2 to allow comparison with Sibley et al. (1998). Different food concentrations
during the experiments 2 (Larval growth response to limiting food levels in two
different particle size ranges) and 4 (Preference for food level) were obtained by mixing
preweighed amounts of food through a certain volume of mineral substrate.
For all experiments polyethylene containers (10 x 10 x 6.5 cm) were used as
experimental units; Dutch Standard Water (DSW, NEN 6503, pH 8.2, 210 mg CaCO3)
as artificial freshwater, and a 95%/5% (m/m) mixture of the commercially available
fishfoods Trouvit© (95%) (Trouw, France) and Tetraphyll© (5%) (TetraWerke, Germany) as food source were used. For each experimental series at least 10 egg masses
from a laboratory culture of C. riparius Meigen were used. Newly hatched 1st instar
larvae (<24 h old) were obtained directly from egg ropes. Early 3rd instar larvae were
obtained by culturing newly hatched larvae for 7 days in an aerated aquarium containing
DSW, a layer of sand and a surplus of food. Larval instar was determined for all
individuals based on head capsule width, measured using a binocular microscope. Head
capsule width of 1st, 2nd, 3rd, and 4th instars ranged between 94 and 140, 195 and 246,
335 and 428, and between 484 and 605 µm respectively. Mentum width was measured
67
Chapter 4
for 20 individuals per instar and ranged between 28 and 42, 42 and 65, 84 and 112 and
between 158 and 167 µm respectively for 1st, 2nd, 3rd, and 4th instars. This resulted in a
mentum/head capsule ratio ranging between 0.25 and 0.31 for all instars.
The quartz particle size ranges used in the experiments are presented in Table 1.
Before use in the experiments the substrates were washed and organic matter was
removed by combustion at 550°C for 6 hours. All particle sizes were checked by laser
diffraction (Master Sizer X Ver. 1.2a, Malvern).
All experiments were conducted at 20°C ± 1°C. Growth experiments were
performed under a light/dark regime of 16/8 hours. The preference experiments were
performed in the dark, since Baker & Ball (1995) have found negative phototactic
behavior for C. tentans larvae which had not constructed a tube and similar behavior
was observed for C. riparius during preliminary studies (unpubl. data). The containers
of both the growth and the preference experiments were not aerated in order to avoid
resuspension of food and fine grained material (1.5-20 µm).
Experiment 1: Larval growth at saturating food level in a range of different
particle sizes
The effect of particle size on larval growth was determined after 7 and 14 days
using the 6 different particle size ranges. Growth on each particle size range was tested
5 times for both growth periods. Replicates were started on different days with larvae
originating from different egg masses. In each of the containers 400 ml of artificial
freshwater was added to 200 ml of substrate with a defined grain size range, resulting
Table 1. Mineral particle size ranges ranked after the 5 and 95% percentiles of volume (5-95
vol%), median particle size and origin of the substrate
grain size range (µm, 5-95 vol%)
1.5-20
median particle size (µm)
3.5
origin
®
Sibelco quartz powder M500
®
8-63
26
Sibelco quartz powder M10
50-175
95
Sibelco quartz sand
105-300
173
Sibelco quartz sand
275-600
392
Praxis
550-1200
68
757
®
®
®
®
playing sand
Praxis playing sand
Particle size and food level effect on C. riparius
in a substrate layer of 2 cm. One hundred mg of food was added and allowed to settle on
the substrate after which 20 1st instar larvae were released in the water. The length of a
group of 20 randomly chosen larvae was measured to determine initial length. After 7
days half of the culture vessels were randomly chosen and analyzed. The remaining
vessels were provided an additional 100 mg of food and this part of the growth experiment was terminated after 14 days. At the end of the experiments larval body length
was measured and instar stage was identified of each surviving larva, after which gut
contents were studied through a binocular microscope. During the experiments behavior
of the larvae and the presence and position of the living tubes were noted. One-way
ANOVA was used to compare growth and survival in the different particle size ranges
(P < 0.05).
Experiment 2: Larval growth response to limiting food levels in two different
particle size ranges
To 200 ml of silty (8-63 µm) or coarse (550-1200 µm) substrate 5, 10, 25, 50,
100, 150, 200, 400 or 800 mg of food was added and substrate and food were
thoroughly mixed. This resulted in food concentrations of 0.025, 0.05, 0.125, 0.25, 0.5,
0.75, 1.0, 2.0 and 4.0 mg food ml-1 mineral substrate respectively. Four hundred ml of
artificial freshwater was added carefully. At the start of each experiment 20 3rd instar
larvae were added to the water and the initial length was measured on a group of 20
randomly chosen larvae. After 7 days the length of the surviving larvae was measured.
Each experimental unit was replicated twice. The effect of particle size combined with
food level was analyzed using a two-way ANOVA (P < 0.05).
Experiment 3: Larval preference for particle sizes in the presence and absence
of food
The containers were filled with 400 ml artificial freshwater and divided
diagonally in half by a polyethylene barrier. On both sides of the barrier 100 ml
substrate of a specific particle size range was released and allowed to settle, after which
10 or 20 mg food was added to the water at both sides of the strip, resulting in 0.2 or 0.4
mg food cm-2. The barrier was removed after settling of the food. The containers with
0.2 mg food cm-2 were used to test preference of 1st instar larvae and the 0.4 mg cm-2
69
Chapter 4
containers for preference tests with 3rd instar larvae. Each possible combination of the
particle size ranges 1.5-20, 8-63, 105-300 and 550-1200 µm was replicated 4 times,
including pairings with the same particle size substrate serving as controls. Replicates
were started at different days. The experiments were started by randomly adding 20 1st
or 20 3rd instar larvae above the interface between the particle sizes. The experiments
were ended by replacing the barrier after 72 h after which the larvae were counted at
each side of the separating barrier.
Additional experiments were performed, similar in setup, except that food was
added to only one side of the container (10 mg for 1st instars, 20 mg for 3rd instars), and
the other side was left without food. All possible combinations of particle size ranges
were tested once with food on the first half and once with food on the second half of the
container. Pairings of the same particle size served as controls.
A chi-square test was used to compare the number of larvae on each side of the
container (P < 0.05), with 50% of the total larvae as the expected number of larvae for
each half of the container.
Experiment 4: Preference for food level
Containers were divided in halves by a polyethylene barrier and on each side
100 ml of 8-63 µm substrate was added together with a specific amount of food (0, 1.0,
2.5, 5.0, 7.5, 10, 17.5, 25, 37.5, 50, 100 or 200 mg). Substrate and food were thoroughly
mixed, resulting in food concentrations of 0, 0.01, 0.025, 0.05, 0.075, 0.10, 0.175, 0.25,
0.375, 0.50, 1.0 and 2.0 mg ml-1 respectively. Four hundred ml of artificial freshwater
was added gently. The barrier was removed and 20 3rd instar larvae were released in the
water above the interface. After 72 h the number of larvae on each side of the containers
was counted. Each combination of food levels was tested once, including combinations
of the same food level that represented the controls.
A chi-square test was used to compare the number of larvae on each side of the
container (P < 0.05), with 50% of the total larvae as expected number of larvae per half
container.
70
Particle size and food level effect on C. riparius
Results
Experiment 1: Larval growth at saturating food level in a range of different
particle sizes
Average length of the 1st instar larvae at the start of the experiments was 0.95
(SE = 0.02) mm. No significant differences in larval growth and survival after 7 days or
after 14 days, were found between any of the particle size ranges tested (F = 0.98, df =
12
length (mm)
10
8
6
4
2
0
survival (%)
80
60
40
20
0
1.5-20
8-63
50-175
105-300
275-600 550-1200
particle size ranges (µm)
Fig. 1. Survival (%) and growth (final – initial length, mm) of larvae after 7 days (grey bars) and
after 14 days (black bars) on substrates with different particle size ranges and with saturating
-2
st
food levels of 0.4 mg cm . Error bars represent standard errors. Initial length of the 1 instar
larvae was 0.95 (± 0.02) mm.
71
Chapter 4
5, MS = 0.18) (Fig. 1). After one week an average length of 5.2 mm (± 0.1) was
reached. Most of the larvae were in the 3rd instar, although a few 2nd instar larvae were
found (<1%). After two weeks of growth the larvae were mainly 4th instars with an
average length of 10.2 mm (± 0.1). Survival in both tests and in all experimental units
exceeded 80%. The 2nd, 3rd, and 4th instars were able to build tubes in all particle size
ranges, using both mineral and food particles. The tubes were mainly situated horizontally, on the surface of the substrates. Up to approximately 30% of the tubes in each
particle size range was built into the substrate, with the exception of the 1.5-20 µm and
8-63 µm substrates, where all tubes were situated vertically in the substrate. During the
1 and 2 week growth periods it was noted that the tubes that were constructed in the
largest particle size range (550-1200 µm) were less stable than tubes constructed using
smaller particles when they were gently crumbled between the fingers. In all particle
size ranges most of the tubes were 1.5 to 2 times the length of the inhabiting larvae, but
occasionally tubes were found with lengths up to 3-4 times the length of the inhabiting
larvae.
Dissection of the larval gut contents showed that 2nd instar larvae (n = 4) were
able to ingest grains with diameters up to approximately 30 µm, 3rd instar larvae (n =
20) up to approximately 60 µm while the guts of 4th instar larvae (n = 20) contained
particles up to 100 µm. Thus, grain size diameters found in the guts of the individual
instars were smaller than the measured minimum mentum width of the corresponding
instar.
Initial length of the 3rd instar larvae used in the experiment was 4.0 mm (± 0.05).
Survival at the end of the experiment exceeded 80% in all experimental units.
Experiment 2: Larval growth response to limiting food levels in two different
particle size ranges
Larval growth on the 8-63 µm substrate was significantly lower than growth on
the 550-1200 µm substrate (F = 0.77, df = 7, P ≤ 0.05 ) (Fig. 2) at limiting food levels.
Maximum increase in length was similar for both particle size ranges, but was reached
at 2 mg ml-1 on 8-63 µm and at 1 mg ml-1 on 550-1200 µm. The larvae that were grown
at the highest food concentrations were still in the growing phase, since the 4th instar
larvae of C. riparius can reach lengths up to 18 mm.
72
Particle size and food level effect on C. riparius
rd
Fig. 2. Length (mm) of 3 instar larvae after one week of growth on two particle size ranges and
different amounts of food. Black circles: 8-63 µm substrate, grey squares: 550-1200 µm
rd
substrate. Error bars represent standard errors. Initial length of the 3 instar larvae was 4.0 mm
3
(± 0.05) (0.26 mm )
12
length (mm)
10
8
6
4
2
0
0
0.5
1
-1
mg food ml
1.5
2
On average higher larval motility was observed in the 550-1200 µm containers
compared to the 8-63 µm containers, although at the highest food levels (1-2 mg ml-1) in
both particle size ranges hardly any larval activity was observed. This activity encompassed mainly crawling over the surface of the substrate, efforts to penetrate the
substrate and occasionally swimming. In containers with the highest food levels of both
particle size ranges the longest tubes were found with lengths up to 3-4 times of the
larval length. Observations with a binocular microscope indicated that guts of larvae
grown in the 8-63 µm substrates were filled with proportions of mineral particles to
food volume similar to the proportions observed in the substrates.
Experiment 3: Larval preference for particle sizes in the presence and absence
of food
Both 1st and 3rd instar larvae were observed to swim freely after being released
in the water and readily moved between particle sizes. If an excess of food was provided
on both sides of the container no significant preference for a particle size range was
73
Chapter 4
st
Table 2. Preference of 1 instar larvae for combinations of particle sizes (µm) and presence of
-2
food. Percentage of the initial 20 larvae found on the section provided with food (0.2 mg cm )
(± SE) after 72 hours
section without food
section with food
1.5-20
8-63
105-300
550-1200
1.5-20
90 (5)
92
81
92
8-63
85
95 (7)
85
93
105-300
89
93
92 (2)
85
550-1200
85
100
97
100 (0)
found for either 1st or 3rd instars (data not shown). Average of the highest number of
larvae found at one side was 10.6 (± 0.35) in the experimental units containing different
particle size substrates on both sides (n = 24).
During the experiments in which only one side of the container was
supplemented with food, 1st and 3rd instar larvae showed a significant preference for the
food side, independent of the particle size (Table 2 and 3). On average 91% (± 1.4) of
the 1st instar larvae and 94% (± 1.5) of the 3rd instar larvae were found on the food side
after 72 h of incubation. Observations of the 3rd instar larvae indicated that the larvae
either started swimming after release or immediately penetrated the substrate they had
landed on. If the larvae had penetrated the substrate on the side without food they
mostly were found to crawl on the surface or to swim again after a few hours. If the half
containing food was penetrated the larvae were observed to build tubes within a few
hours (1.5-2 h) after release.
rd
Table 3. Preference of 3 instar larvae for combinations of particle sizes (µm) and presence of
-2
food. Percentage of the initial 20 larvae found on the section provided with food (20 mg cm ) (±
SE) after 72 hours
section without food
section with food
1.5-20
8-63
105-300
550-1200
1.5-20
89 (11)
95
85
90
8-63
90
100 (0)
95
100
105-300
89
100
92 (6)
85
550-1200
100
95
85
91 (9)
74
Particle size and food level effect on C. riparius
Experiment 4: Preference for food level
Food concentrations were split into 2 groups: low food concentrations of 00.075 mg ml-1 and high food concentrations of 0.1-2 mg ml-1 to illustrate differences in
reaction of larvae to the food concentration in Figures 3 and 4. This resulted in three
combinations of food concentration in the experimental containers: low with low food
concentrations, low with high and high with high food concentrations. If food levels on
both sides of the container were low no preference of the 3rd instars for a food level was
observed. If food concentration differences between both halves were > 0.75 mg ml-1 or
low/high food concentration < 0.3 almost all larvae were found on the side with the
higher food level. Interestingly, the percentage of larvae that were found in the highest
food concentration hardly ever reached 100% if both sides contained a high food
% of larvae at higher food concentration
concentration. If there was a high food concentration on one side and on the other side a
100
80
60
40
20
0
0
0.5
1
1.5
2
-1
difference in food concentration (mg ml )
Fig. 3. Preference of third instar larvae for different food levels. The X-axis represents
-1
differences in food concentration (mg ml ) between the two halves of the container. The Y-axis
represents the percentage of larvae at the highest food level. The area between the two
horizontal lines in the graph marks the field where preference was not significant.
Black squares: food concentrations on both sides ≥ 0.1 mg ml .
-1
Crosses:
lower food concentration < 0.1 mg ml , higher food concentration ≥ 0.1 mg ml .
Grey circles:
food concentrations at both sides < 0.1 mg ml .
-1
-1
-1
75
Chapter 4
low food concentration and food concentration differences were > 0.75 mg ml-1 100%
of the larvae were found on the side with the higher food concentration. No consistent
preference was observed when concentration differences were < 0.75 mg ml-1. In fig. 4
food concentration differences are expressed as lower food concentration:higher food
concentration ratio. The curve shown in the graph follows the equation the curve y =
100/(x+1) in which y = % of larvae at the higher food side and x = lower/higher food
concentration. The equation expresses the larval distribution over the 2 halves of the
experimental unit if this distribution is proportional to the distribution of the food.
Larval distribution roughly followed this equation but fit was low (R = 0.38).
% larvae at higher food concentration
120
100
80
60
40
20
0
0.01
0.1
1
lower:higher food concentration
Fig. 4. Preference of third instar larvae for different food levels. The X-axis represents the ratio
lower food concentration : higher food concentration. The Y-axis represents the percentage of
larvae at the highest food level side. The curve represents the distribution of the larvae following
-1
the curve y = 100 x (x+1) ,in which y = % of larvae at the higher food side and x = lower/ higher
food concentration.
Black squares: food concentrations at both sides ≥ 0.1 mg ml .
-1
Crosses:
lower food concentration < 0.1 mg ml , higher food concentration ≥ 0.1 mg ml .
Open circles:
food concentrations at both sides < 0.1 mg ml .
76
-1
-1
-1
Particle size and food level effect on C. riparius
Similar to the experiment on larval preference for combinations of particle size
and food level, it was observed that the 3rd instar larvae started to swim if the food level
of the half of the container that they had landed on was low, or first penetrated the
substrate and started swimming or crawling again after a few hours. Consequently, in
containers which had a low food concentration (0-0.075 mg ml-1) on both sides the
larvae were relatively active and ± 50% of the larvae were found not to inhabit a tube
after 72 h of incubation. This resulted in no observed preference for either of the food
concentrations. In the containers with both sides having substrates with ≥ 0.10 mg ml-1,
all larvae inhabited a tube.
Discussion
The data gathered during this study give new insights into the possible role that
mineral particle sizes in combination with different food levels play in the habitat of
detritivores. Firstly, differences in tube construction and feeding mode of Chironomus
riparius larvae were found when grown on different particle size ranges. The 2nd, 3rd,
and 4th instar larvae were observed to be able to construct tubes of all particle size
ranges, but the tubes that were found in the large particle size ranges seemed to be less
stable than tubes constructed from smaller particles. A few studies reported that
chironomid larvae do not discriminate among particles for tube building, but in the few
studies done only small particles and small ranges of particle sizes were examined
(Edgar & Meadows 1969, Brennan & McLachlan 1979, Dudgeon 1990). In our study,
food and faecal pellets may also have been used as tube building material, and thus
might have compensated for a possible lack of smaller particle size substrate for tube
construction in the large particle size containers. Nevertheless, at lower, non-saturating
food levels, a clear effect of particle size was noted. Larval growth was negatively
affected by the small and ingestible particle substrate. This lower growth can be
explained by differences in food availability resulting in different modes of feeding. In
the small particle substrate the larvae had unselectively ingested the food together with
the substrate. In the large particle substrate the larvae did not ingest mineral particles
and were able to feed solely on the added fishfood by specifically picking food items
between sand grains, or scraping adhered food from particle surfaces. Consequently, in
77
Chapter 4
larvae feeding on small particle substrates the amount of non-food particles in the gut at
non-saturating food levels may have limited food uptake. In contrast, food uptake in
large particle substrates is not hampered by mineral particles occupying gut space. Food
uptake diluted with inedible particles is likely to be a common phenomenon in nature.
In the field small mineral particles are often associated with fine organic material and
then bulkfeeding detritivores will be bound to ingest mineral particles together with
organic matter in order to feed.
The C. riparius larvae showed different particle size preference than C. tentans
at high food levels (Sibley et al. 1998). The C. riparius larvae did not show any preference for particle size in contrast with C. tentans. A strong selection preference of C.
tentans was found for the smaller particle size range of 2 substrates at surplus food
levels in both halves of the container. In agreement with our findings, both 1st and 3rd
instar C. tentans larvae showed a strong response to food availability independent of the
mean particle size of the substrate (Sibley et al. 1998). When offered a choice in our
experiments between substrates with and without food, the larvae immediately selected
the side with food and showed no preference for particle size. In an additional
experiment that is not described in the preceding paragraphs larvae were observed to
quickly find a small spot with surplus of food in a sediment otherwise devoid of food.
This indicates that similar to C. tentans (Baker and Ball 1995) olfactory sense is used by
C. riparius to find food.
The threshold food concentration for 3rd instar larvae of C. riparius to reside in
during the food preference experiment was found between 0.075 and 0.10 mg fishfood
ml-1. The larvae may not have been able to sense food below this threshold concentration and therefore may not have been motivated to settle. Moreover, food
concentrations below the threshold offer only low growth potential, which also might
stimulate larvae to find better growth conditions elsewhere. If in one compartment a
food concentration was below, and in the other compartment above, the threshold
concentration all larvae were found in the higher food concentration. The larvae
probably ended up at the higher food concentration because below the threshold the
larvae did not settle, leaving only the higher food concentration for residence. At higher
food concentrations (0.1-2 mg ml-1) the C. riparius larvae were observed to penetrate
the substrate and to build tubes. The higher food concentrations were only distinguished
78
Particle size and food level effect on C. riparius
if food concentration differences were large (≥ 0.75 mg ml-1). A possible motivation to
leave a substrate above the threshold after settling was observed if another high food
concentration was present in the vicinity, e.g. the ability to find food through olfaction.
The ability to sense differences in food concentration would facilitate choosing a site of
settlement or might motivate larvae to leave the place of residence. However, it is not
yet known whether the larvae also can sense quantitative differences in available food.
Another possible trigger for chironomid larvae to leave the substrate might be depletion
of food at the place of residence until a threshold concentration is reached. At low food
concentrations food will locally be depleted faster than in high food concentrations and
consequently larvae will leave low food level substrates faster to find other places to
feed. Within our experimental setup each time a larva leaves the substrate it has a
chance to end up at the higher food concentration. Thus, higher food concentrations will
hold the larvae for a longer time compared to lower food concentrations resulting in
higher chironomid densities at higher food concentrations.
However, it remains unclear why a small proportion of larvae was still found in
the lower of the two food concentrations above the threshold even if food concentration
differences exceeded 1.5 mg ml-1. Wiley (1981b) examined the influence of chironomid
density and habitat suitability on emigration rates of chironomid larvae in artificial
stream chambers. Emigration rates were positively correlated with population density,
but if a suitable substrate type was offered emigration rates decreased and higher
population densities were sustained. Similar interaction of population density and
preference may have occurred during our food level preference experiments. The length
of the 3rd instar larvae during the 72 hours preference experiments ranged between 4.0
and 8.0 mm. Assuming that a larvae keeps physical contact with the tube entrance and
extends up to 60% of larva’s total body length (Wiley 1981b) one larvae is able to cover
22-90 mm2. If the larvae would evenly and ideally disperse over the triangular area of
50 cm2 one half of an experimental container would be able to sustain 40-200 larvae. A
number of field studies reported densities of C. riparius up to 19 times the density that
is reached when all larvae were found at one side of the experimental unit (4,000 ind
m-2). Under favorable conditions, C. riparius can reach densities between 30,000 and
50,000 individuals m-2 (Learner & Edwards 1966, Köhn & Frank 1980, Davies &
Hawkes 1981). Groenendijk et al. (1998) even recorded peak densities of 42,797
79
Chapter 4
individuals m-2 at a clean site and 75,000 m-2 at a highly polluted site, although generally larval densities did not exceed 40,000 m-2. Taking these densities into consideration it seems unlikely that overcrowding has occurred during our experiments.
Nevertheless, no data are available on emigration rates and differences in population
densities between substrates with different organic matter contents. Therefore, overcrowding as a stimulant to emigrate during our experiments can not be ruled out.
Rasmussen (1985) found significant negative effects of chironomid larvae density on
growth rates of C. riparius. Consequently, the lower food concentration could still be
rewarding to settle in for a low number of larvae, having a bigger area at their disposal
and less stress coming from competing neighbouring larvae.
Results of this study suggest that the higher density of chironomids in silty
sediments compared to sandy sediments can partly be explained by the preference of the
larvae for substrates with high food concentrations even though silty sediments contain
small and ingestible mineral grains that may limit food uptake and therefore also larval
growth. Besides preference for high organic matter contents, higher chironomid
densities in silty sediments may have resulted from lower risk of predation compared to
sandy sediments. Lower risk of predation in silty sediments is expected because in
general silty sediments contain higher organic matter contents compared to sandy
sediments. Higher organic matter contents hold the larvae for a longer time at one place
simultaneously reducing the risk of predation by fish that is associated with migration
(Hershey 1987, Ten Winkel 1987, Macchiusi & Baker 1991). Risk of predation may
also be influenced by the suitability of sediments for building larval tubes. Silty
sediments contain small mineral particles that were observed to be constructed into
stronger tubes compared to tubes constructed from big particles. The high organic
matter contents of silty sediments also will facilitate tube construction. Inhabiting a tube
diminishes the risk of predation in damselflies, stoneflies, mites and fish as is found in
several laboratory and field studies (Hershey 1985 & 1987, Ten Winkel 1987,
Macchiusi & Baker 1991, Baker & Ball 1995). Overall chironomid densities are
diminished by predation, but relative decrease in densities of tube dwelling chironomids
are typically lower than those of free-living species (Walde & Davies 1984, Hershey
1987, Ten Winkel 1987).
80
Particle size and food level effect on C. riparius
This study did not point out one single factor regulating chironomid densities in
the field. Results show that organic matter content and particle size distribution may not
only be correlated in the field, but are interacting master factors determining the
abundance of C. riparius in situ. Coping with these environmental factors has been
shown to be ruled by specific threshold values, food saturation values, and migration or
settling behaviour. Therefore, we propose quantitative studies on other detritivorous
benthic species that might provide insight in the distribution of the large diversity of coexisting detrivorus species in the natural environment.
81
CHAPTER 5
NUTRITIONAL VALUE OF SEDIMENTS AS A FACTOR
STRUCTURING MACROFAUNA COMMUNITIES IN SHALLOW
EUTROPHIC WATERS
J.H. Vos1,3, E.T.H.M. Peeters2,4, R. Gylstra2,5, M.H.S. Kraak1,6, and W. Admiraal1,7
1
Department of Aquatic Ecology and Ecotoxicology, Institute for Biodiversity and
Ecosystem Dynamics, University of Amsterdam, Kruislaan 320, 1098 SM Amsterdam,
The Netherlands, 2Aquatic Ecology and Water Quality Management Group, Department
of Environmental Sciences, Wageningen University & Research Center, PO Box 8080,
6700 DD Wageningen, The Netherlands, [email protected], 4edwin.peeters@aqec.
wkao.wau.nl, 5ronald.gylstra@aqec. wkao.wau.nl, [email protected], 7admiraal@
bio. uva.nl
Submitted for publication
83
Chapter 5
Abstract
The role of the nutritional quality of organic matter of soft-bottom sediments as
a factor structuring natural macrofauna communities was studied in shallow eutrophic
waters. Growth experiments with Chironomus riparius were conducted to obtain a
direct measure of nutritional value of a range of sediments sampled in The Netherlands.
Sediments were also analyzed for water content, organic matter content, C, N, P,
carbohydrates, protein, fatty acids, pigments, CO2 production, and grain size distribution. Macrofauna species were enumerated and their occurrence in the sediment
samples was correlated to the results of the bioassays and to biochemical sediment
composition by means of univariate and multivariate analyses. Newly produced organic
matter, represented by the variables polyunsaturated fatty acids (PUFA), bacterial fatty
acids, pigments, and mineralization rate, was associated with abundances of a number
of detritivorous taxa and therefore is most likely a key factor for the nutritional value of
sediments. Chironomid larval growth correlated well with the abundance of Chironomidae taxa but not with taxa that have other modes of feeding. Therefore, growth of C.
riparius was found to effectively indicate the nutritional value of sediment bulk feeders.
The use of bioassays with midge larvae excludes indirect effects caused by covariation
of organic matter content with other factors determining the habitat for macrofauna
species, e.g. oxygen regime or stability of the substrate. It is postulated that such nonfood parameters select the species that dominate sites. Yet, nutritional value determines
the overall density of detritivores and therefore is concluded to be a major structuring
factor for faunal composition.
84
Organic matter structuring macrofauna
Introduction
Knowledge on the role of organic matter in sediments is crucial to fully
understand the mechanisms influencing population dynamics of macroinvertebrates in
the field, because the abundance of organic matter and organic matter composition
determines the nutritional value of a sediment (Prosser and Brown 1965). If a sediment
does not suffice nutritional demands of macroinvertebrates these organisms tend to
migrate or development and reproduction are inhibited (Johnson 1984, Gresens and
Lowe 1994, Wolf et al. 1997). Thus, the nutritional value is likely to be fundamental for
the capacity of sediments to sustain a certain number of invertebrate individuals.
Patterns in community structure in relation to temporal changes in organic
matter input can be derived from a few studies in large waterbodies monitoring
macrofauna structure and input of phytodetritus. In general, macrofauna densities
increase, but diversities of faunal assemblages tend to decrease with a rise in food
supply (Marsh and Tenore 1990, Goedkoop and Johnson 1996, Dauwe et al. 1998).
Organic matter composition has also been shown to influence the life history of benthic
invertebrates in laboratory experiments testing artificial diets (Marsh et al. 1989,
D’Abramo and Sheen 1993, Vos et al. 2000). Likewise, in the field, algal blooms
composed of different algal species caused different responses of macrofauna communities indicating a significant influence of organic matter composition on seasonal
variation in macrofauna community composition (Marsh et al. 1989, Marsh and Tenore
1990, Cheng et al. 1993).
In spite of the obvious importance of organic matter abundance and
composition, most studies on macrofauna communities do not explicitly take into
account the nutritional quality of organic matter in terms of biochemical composition.
This ignores the fact that systems with similar organic matter contents may contain
organic matter of different nutritional quality, because organic input may originate from
different sources or differs in degradation state. Differences in nutritional value between
substrates have been examined in Chapter 3 by determining growth of the detritivorous
larvae of Chironomus riparius. Distinct differences in larval growth were found, which
could be attributed to a number of biochemical variables representing freshly produced
organic matter. The physical characteristics of the sediments did not influence larval
85
Chapter 5
growth of C. riparius. However, the response to food supply may be taxon-specific,
some taxa being able to take more advantage of organic matter input than others
(Mackey 1977, Montagna et al. 1983, Goedkoop and Johnson 1996). Therefore, it is
hypothesized that the nutritional quality of organic matter may be a differentiating
factor for macrofauna community composition.
The present study focusses on soft sediments of eutrophic and shallow
freshwater systems and their benthic macroinvertebrate fauna. Benthic detritivores
constitute a substantial part of the benthic community in the majority of eutrophic
watersystems in The Netherlands (Moller Pillot & Buskens 1990, Armitage et al. 1995).
Our aim was to examine the nutritional value of sediments as a factor spatially
structuring natural macrofauna communities. The nutritional value of sediments
depends on several (bio)chemical variables which may interact with each other, with
environmental factors (temperature, light, current), and with biological factors
(predation, competition). Therefore, the nutritional value of sediments was assessed by
chemical analyses (water content, organic matter content, C, N, P, carbohydrates,
protein, fatty acids, pigments, labile organic matter). The overall nutritional value of
unpolluted sediments can be assessed by laboratory tests with benthic detritivores
(Cheng et al. 1993). To this purpose data were incorporated from a previous study on
growth of detritivorous Chironomus riparius larvae on the same sediment samples as
used during the present study (Chapter 3). To identify the main components responsible
for changes in macrofauna composition taxa densities were correlated to larval growth
of C. riparius and to biochemical composition of sediments by means of univariate and
multivariate analyses.
Materials and Methods
Study sites and sampling
Sediments were sampled from May until October 1998 throughout the
Netherlands (Fig. 1). Peeters et al. (subm.) showed that the duration of the sampling
period had no significant effect on the macrofauna communities. For sediment sampling
an Ekman-Birdge grab was used that was adjusted to sample the upper 4 cm surface
layer (400 cm2). The dataset comprised only unpolluted substrates according to Dutch
86
Organic matter structuring macrofauna
standards (Evaluatienota Water, 1994). The sediments originated from large, shallow
lakes (width > 5 m, #17), rivers (width > 5 m, #3), and small lakes (#4), all classified as
being eutrophic. Samples were taken in unvegetated or scarcely vegetated zones at < 1.5
m of depth. Sediments were frozen at –20°C within 6 h after sampling. After thawing,
the sediments were sieved over a mesh of 1000 µm in order to remove the larger
particles such as pebbles, leaves, and twigs. The sediments were frozen a second time to
ensure the death of indigenous animals.
Besides sediment samples for biochemical analyses and growth experiments,
macrofauna was sampled in triplicate per sampling point. The identification level is
shown in Table 1 (Appendix I). Information on feeding behavior was extracted from
Verdonschot (1990) and Merrit and Cummins (1996) (Table 1, Appendix I). Shannon-
Fig. 1. Distribution of the 24 sampling sites in the Netherlands. Several sites are located at short
distances and therefore are indicated by a single symbol.
87
Chapter 5
Weaver index of diversity (H' log base 10) was calculated according to Shannon and
Weaver (1949) and Lambshead et al. (1983).
Bioassays
A detailed description of the growth experiments can be found in Chapter 3.
Shortly, the growth experiments were carried out in polyethylene containers (surface
area of 100 cm2). 100 ml of homogenized sediment and 200 ml of artificial freshwater
(Dutch Standard Water; pH 8.2, 210 mg CaCO3 l-1) was added to each container. The
sediments were allowed to settle for 24 h after which the water was gently added.
Oxygen concentration and pH were measured at the beginning of the experiment.
Controls consisted of containers with 50 g of combusted Litofix© sand (<500 µm,
heated at 550°C for 6 h), 200 ml of Dutch Standard Water and 100 mg of a mixture of
the commercial available fishfoods Trouvit
®
and Tetraphyll
®
(95:5 m/m) each week.
st
Growth experiments were started by randomly adding 20 1 instar larvae less than 24 h
old to each container. An additional group of 20 larvae was collected to determine the
length of the larvae at the start of the experiment. During the growth experiment the
experimental units were constantly and gently aerated. After 14 d, the length of all
surviving larvae was measured with a binocular and growth was calculated by
subtracting the average starting length from larval length after 14 d. Growth
experiments were replicated 3 times, starting on different days.
Sediment characterization
Chemical analyses were performed on freeze-dried substrates described in
Chapter 3. In short, organic matter content was determined in triplicate according to the
loss-on-ignition technique by combusting the material at 550°C for 6 h (Luczak et al.
1997). Total C was measured in duplicate with a Carbo-Erba Element Analyser. N was
measured according to Kjeldahl (ISO 11261 1995). Total P was determined according
to Murphy and Riley (1962) in duplicate. The protein analysis was performed according
to Rice (1982) in duplicate. For analysis of carbohydrates, a modified method based on
the phenol-sulphuric acid-method of Dubois et al. (1956) was used (Chapter 3).
Chlorophyll-a and phaeophytin were measured according to Nusch en Palme (1975) in
88
Organic matter structuring macrofauna
duplicate. Chlorophyll-a and phaeophytin contents were added up to obtain a measure
of pigment content.
Lipids were extracted with a 1:1:0.9 v/v/v chloroform:methanol:water mixture
following the Bligh and Dyer procedure (1959). Fatty acid methyl esters (FAME) were
obtained by mild alcanolic methanolic transesterification as described in Guckert et al.
(1985). Gas chromatographic separation of the FAME was performed by injecting a 1
µl aliquot in the very polar 50 m CP-Sil 88 column (ID 0.25 mm, film thickness 0.20
mm) with a splitflow of 1:40. Optimal separation of FAME peaks was obtained with a
temperature program that began at injection with an initial column temperature of
180°C for 10 minutes followed by a rise of 3°C min-1 to a final temperature of 225°C,
where it was held for 10 minutes. A PUFA variable was obtained by summing up the
peak areas of 16:2ω4, 16:3ω4, 18:2ω6, 18:3ω3, and 18:3ω6. Peak areas of FAME of
bacterial origin (i.e. i14:0, i15:0, a15:0, 15:1, i16:0, i16:1, i17:0, and a17:0; Napolitano
1999) were added to obtain a bacterial FA variable. A measure for total FA was
calculated by adding all fatty acid peaks from 12:0 upto the last peak appearing in the
chromatogram before the 21:0 internal standard peak (18:3ω3). Only FAME peaks
which appeared before the internal standard in the chromatogram were used for further
calculations because the peaks appearing later in the chromatogram showed irregular
retention times.
Grain size distribution was determined by sieving and the pipet method descibed
in ISO 11277 (1998). Water content was determined by freeze drying a preweighted
sediment sample in triplicate.
Assessment of the most labile fraction of the organic matter
A microbial assay was used to obtain a measure of the most labile, i.e. easily
degradable, fraction of the sediment organic matter. The procedure is described in
Chapter 3. In short, wet sediments were used that had been kept frozen until analysis. A
bacteria inoculum was prepared from a decaying cyanobacterial mat (Oscillatoria sp.).
Bacteria were detached by ultrasonic treatment and particles were removed by
centrifugation (5 min 50 g). In a 77 ml gas-tight bottle 4 ml of sediment was suspended
in 11 ml of a 55 mM phosphate buffer (pH 7.1) and 1 ml of the bacteria inoculum was
added. After 30 min of aeration the pH was measured and the bottles were capped gas-
89
Chapter 5
tight. The bottles were placed on a rotary shaker at 20°C in the dark and after allowing
one hour equilibration the CO2 concentration in the headspace was measured gaschromatographically. After 48 hours incubation the CO2 concentration was measured again
and the pH was measured.
Multivariate analyses
Multivariate analyses were performed with sediment variables and distribution
of all taxa. Multivariate analyses (redundancy analysis [RDA] and detrended
correspondence analysis [DCA]) were performed using CANOCO for Windows
software package (Ter Braak and Smilauer 1998). In all analyses species densities were
log (x+1) transformed and the species were centered. Species densities were not
standardized in order to give the species the weight during the ordination directly
dependent of their presence. Environmental variables included results of bioassays and
sediment variables. Two analyses were performed, one with the biochemical variables
standardized on dry weight and one with the biochemical variables standardized on
10,000
-2
density (ind m )
1,000
100
1
Oligochaeta
Oligochaeta
Hirudinae
Hirudinae
Mollusca
Mollusca
Hydracarina
Hydracarina
Malacostraca
Malacostraca
Ephemeroptera
Ephemeroptera
Odonata
Odonata
Hemiptera
Hemiptera
Megaloptera
Megaloptera
Coleoptera
Coleoptera
Trichoptera
Trichoptera
Lepidoptera
Lepidoptera
Tabandiae
Tabanidae
Ceratopogonidae
Ceratopogonidae
Limnophila
Limnophila
Simuliidae
Simuliidae
Chironomini
Chironomini
Orthocladiinae
Orthocladiinae
Tanypodinae
Tanypodinae
Tanytarsini
Tanytarsini
total
#
individuals
total # individuals
10
-2
Fig. 2. Average densities of taxa (ind m ) for all stations. Error bars represent standard errors.
90
Organic matter structuring macrofauna
organic matter content. First, the length of gradient was calculated by DCA to determine
the model that fitted the relationship between the species densities and sediment
variables best. The linear response model (RDA) was chosen for final ordination,
because the length of gradient was < 2.0 for both datasets (Ter Braak 1995). The Monte
Carlo Permutation test was used to calculate the significance of the influence of the
sediment variables on the macrofauna species distribution.
During the ordination of the dataset containing biochemical variables
standardized on dry weight the variance inflation factors (VIFs) showed high collinearity of organic matter, N-, P-, and the particle size fraction < 63 µm-content (VIFs >
20). In the dataset with biochemical variables standardized on organic matter content
the particle size fraction < 63 µm and C showed high VIFs. The variables with VIFs >
20 were deleted from the datasets for further ordination. In the dataset with the
biochemical variables standardized on dry weight axis 1 had an eigenvalue of 0.28 and
axis 2 of 0.11. The 2 axes represent 58% of the species-environment correlation. In the
multivariate analysis of the dataset containing the biochemical variables standardized on
organic matter content the eigenvalue of axis 1 was 0.33 and of axis 2 was 0.12. In this
analysis axes 1 and 2 represent 63% of the species-environment correlation.
Univariate statistical analyses
Correlations were determined according to the Pearson method using the
averages of chemical and physical analyses, averages of larval growth, and of species
densities per substrate. Numbers of individuals were log(x+1) transformed. Densities of
taxa were only correlated with results of growth data or biochemical analyses if the taxa
occurred in 8 or more substrates to avoid correlations based on a low number of
observations.
Results
Macrofauna
The densities of total number of individuals varied between 40 and 36,100 ind
-2
m with an average density of 8,800 ind m-2 (Fig. 2). Average density of oligochaetes
found in the field was ca. 4,000 ind m-2, but the maximum density was 15,300 ind m-2.
91
Chapter 5
Oligochaetes made up 0 to 98% of the total macrofauna individuals with an average of
ca. 54%. The chironomids comprised 1 to 88% of the individuals and were found in
densities of 8 to 30,160 ind m-2 with an average of 4,200 ind m-2. One of the most
abundant groups of chironomid taxa were the Tanytarsini, reaching a maximum density
of 25,730 ind m-2 and comprising 0 to 71% of the macrofauna specimens. Average
density of Tanytarsini was the highest among the subfamilies of Chironomidae (2,450
ind m-2) followed by the Chironomini (1,600 ind m-2). Malacostraca, Ephemeroptera,
Coleoptera, and Ceratopogonidae occasionally made out a high percentage of macrofauna individuals, but all had on average a presence of < 20% of the total individuals.
The number of sites where a species occurred is shown in Table 1. Oligochaetes,
Sphaeridae spec., Hydracarina spp., Gammarus tigrinus, Ceratopogonidae spp., Stichtochironomus spp., Cryptochironomus spec., Chironomus spp., Glyptotendipes spp.,
Cladotanytarsus spec., Procladius s.l., Polypedilum gr. nubeculosum, and Polypedilum
gr. bicrenatum, were present in >50% of the sediments. However, most taxa were
present in less than 20% of the sediments.
Table 2. Overview of variables standardized on dry weight measured in the 24 sediments.
Averages are calculated from the average values of the individual sediments. Growth and
survival of Chironomus riparius. CV = coefficient of variance. Minimum (min) and maximum
(min) value observed in the dataset.
C
N
P
carbohydrates
unit
average
min
max
CV
-1
15
2.0
51
110
-1
0.8
0.1
3.5
123
-1
0.3
0.02
1.4
113
-1
0.5
0.03
2.0
120
-1
mg g
mg g
mg g
mg g
protein
mg g
2.2
0.02
18.1
168
total FA
µg g
-1
181
2.8
535
85
PUFA
µg g
-1
1.8
0
7.4
126
bacterial FA
µg g
-1
4.4
0
20.3
115
pigments
µg g
-1
11.0
0.3
49.0
108
mmol g
-1
7.3
0
18.2
76
mm
4.4
0.7
11.0
60
%
76
0
100
108
CO2 production
growth
survival
92
Organic matter structuring macrofauna
If densities of taxa with the same feeding mode were added up, detriti(herbi)vores were found in 23, herbivores in 22, and carnivores in 23 of the 24 sampled
substrates. Shannon-Weaver index of diversity (H' log base 10) ranged from 0.047 to
0.892 with a coefficient of variance of 49 % among all 24 sites. The sites with the
lowest diversities (n = 2, S < 0.1) only comprised oligochaetes, and a number of Chironomidae species (mostly inhabited by Mollusca, Malacostraca, Ephemeroptera, Ceratopogonidae, and members of subfamilies of Chironomidae other than Chironomini.
Bioassays with Chironomus riparius
Length of the 1st instar larvae (< 24 h) at the start of the growth experiments was
0.89 mm (± 0.02). Larvae in the controls reached lengths of 12.5 mm (± 0.28) in 14 d
Table 3. P-values of correlations between sediment variables and macrofauna community
composition calculated with the Monte Carlo permutation test. Biochemical variables
standardized on dry weight or on organic matter content. SWC = sediment water content, %<63
µm = particle size < 63 µm.
biochemical variable standardized on
dry weight
organic matter
C
0.095
0.026
N
0.082
0.275
P
0.102
0.001
carbohydrates
0.286
0.566
proteins
0.304
0.625
total FA
0.691
0.977
PUFA
0.003
0.002
bacterial FA
0.127
0.000
pigments
0.775
0.016
CO2 production
0.126
0.004
SWC
0.034
organic matter
0.070
%<63 µm
0.004
%>210 µm
0.212
C/N
0.185
growth
0.004
survival
0.021
93
Chapter 5
and were mostly (70%) in the 4th larval stage. Survival in the controls exceeded 80% in
each experimental unit. Growth in the individual substrates ranged between 0.7 and 11.0
mm with an average of 4.4 mm and a coefficient of variance (CV) of 60% (Table 2).
Survival in the individual substrates ranged between 0 and 100% per experimental unit
with an average of 76% and a CV of 108%. Growth and survival were significantly
correlated (R2 = 0.71; P < 0.01).
Sediment composition
A range from silty to sandy sediments was sampled. Particles < 63 µm constituted 0.8 – 79.0% DW with an average of 21%. Particles > 210 µm ranged between 0.3
and 81% DW with an average of 24%. Sediment water content ranged from low to high
(20.6-59.1% of wet weight), with an average of 32.3%. Organic matter content ranged
between 0.3-8.4% of DW among the substrates with an average of 2.0%. C/N-ratio had
an average of 20.5 and ranged between 5.9 and 55.0.
Biochemical variables were expressed in 2 ways: standardized on dry weight
and standardized on organic matter content. The high CVs of the biochemical variables
standardized on DW indicate a broad variety of organic matter types present in the
individual substrates (Table 2). Standardization on dry weight resulted in a high number
of correlations among biochemical variables in contrast to standardization on organic
matter content, which showed low correlation coefficients in most cases (data not
shown).
Multi- and univariate analyses
Multivariate analyses were used to survey correlations between biochemical
sediment composition, bioassay determined nutritional value and macrofauna community composition. Univariate analyses were performed to determine the correlations
between individual taxa and sediment variables.
Multivariate analyses
Multivariate analyses of the dataset was carried out in two modifications; one
using biochemical variables expressed per unit dry weight and one with the variables
normalized on organic matter. The two standardization methods affected the interactions of macrofauna community and individual biochemical variables, as calculated
94
Organic matter structuring macrofauna
with the Monte Carlo permutation test (Table 3). Only PUFA-content was significantly
correlated to macrofauna community composition when variables were standardized on
dry weight. A distinct higher number of significant interactions of biochemical variables
with macrofauna community was found (P < 0.05) when biochemical variables were
standardized on organic matter content. In that case C, P, PUFA, bacterial FA,
pigments, and labile organic fraction measured as bacterial CO2 production were significantly correlated to species densities in the field. Larval growth and survival, sediment
water content (SWC), and particle size fraction < 63 µm were also signicantly correlated to species densities. A high collinearity among biochemical variables standardized
on dry weight and the high number of significant correlations for biochemical variables
standardized on organic matter prompted us to further analyse the dataset with the latter
type of standardization.
Fig. 3 shows the biplot resulting from the direct ordination (RDA) of the dataset.
The parameters for sediment characteristics were plotted as arrows and the ordination of
fauna composition as individual species or groups of species. The arrows of the food
related parameters 'larval growth' and 'survival' of Chironomus riparius, pigments,
PUFA, P, bacterial FA, and CO2 production all point to the right. Densities of the
detriti(herbi)vorous Tanytarsini, Chironomini, Polypedilum gr. nubeculosum, Cladotanytarsus spec., Cryptochironomus spec., Stichtochironomus spp., and Einfeldia/Fleuria,
and the total numbers of individuals (group 6 in Fig. 3) were positioned near these
sediment variables, away from the origin of the biplot. Thus, this faunal group shows a
positive correlation with growth and survival of C. riparius in bioassays and with the
(bio)chemical parameters PUFA, P, pigments, bacterial FA, and CO2 production.
The non-food parameters SWC and the particle size fraction > 210 µm together
with organic matter content were ordinated in the opposite direction of the food
parameters, in the left panel of Fig. 3. The carnivorous taxa Tanypus punctipennis cf.,
and Micronectra spec., and the detritivorous Chaetocladius piger agg. were associated
with high organic matter contents. The position of group 3, that consists mostly of
carnivorous and herbivorous taxa, suggests a positive association of these taxa with
sediments particle sizes > 210 µm. The setting of the biplot indicates a strong negative
correlation of organic matter content with Shannon index.
95
Chapter 5
Fig. 3. Redundancy analysis plot (RDA) showing the direct ordination of species densities,
sediment variables and results of bioassays with Chironomus riparius, with 33% of variance on
axis 1 and 12% on axis 2. Arrows represent the sediment variables and growth and survival of
C. riparius. EINFFLEU = Einfeldia/Fleuria, CRICSYLV = Cricotopus sylvestris agg., POPENUBE
= Polypedilum gr. nubeculosum, TANYPUNC = Tanypus punctipennis cf., PARACONC = Paracorixa concinna, MINECTSP = Micronecta spp. larvae, CHAEPIGE = Chaetocladius piger agg.,
PROACOXA = Proasellus coxalis, LIMNOPHI = Limnophila spec., TABANIAE = Tabanidae
spec., CLTANERV = Clinotanypus nervosus. Group 1 consists of Neomysis integer, Chironomus spp., Cricotopus intersectus agg., and Micropsectra spec. Group 2: Erpobdella octoculata,
Bithynia tentaculata, Gyraulus albus, Gammarus pulex, Sigara falleni/longipalis, Sialis lutaria,
Laccophilus spec. larvae, Psychodidae spec., Endochironomus albipennis, Tanypodinae,
Procladius s.l. Group 3: Valvata piscinalis, Zygotera spec. juveniles, Haliplus spec. larvae,
Oxyethira, spec., Ecnomus tenellus, Mystacides spec., Ceratopogonidae spec., Pseudochirono-
+1.0
P
EINFFLEU
C/N
SWC
PUFA
CRICSYLV
TANYPUNC
Oligochaetes
1
organic matter
Axis 2, eigenvalue 0.12
bacterial FA
PARACONC
MINECTSP
PROACOXA
CHAEPIGE
LIMNOPHI
total FA
proteins
growth
N
6
survival Chironomini
carbohydrates pigments
TABANIAE
POPENUBE
CLTANERV
2
%>210 µm
5
Tanytarsini
CO2 production
3
4
Shannon
n
Group with overlapping
species names
-1.0
-1.0
96
Axis 1, eigenvalue 0.33
+1.0
Organic matter structuring macrofauna
mus spec., Tribelos intextus. Group 4: Helobdella stagnalis, Mollusca, Potamopyrgus antipodarum, Lymnaea spec. juveniles, Planorbis spec. juveniles, Sphaeridae spec., Hydracarina
spp., Malacostraca, Gammarus tigrinus, Corophium curvispinum, Caenis horaria, Agraylea
multipunctata, Oecetis ochracea, Cyrnus spec., Lepidoptera spec. larvae, Dicrotendipes gr.
nervosus, Mircotendipes chloris agg., Corynoneura scutellata agg., Ablabesmyia spec.,
Tanytarsus spec., Paratanytarsus Neureclipsis bimaculata, Athripsodes spec. juveniles, Simulium spec., Polypedilum gr. bicrenatum, Glyptotendipes spp., Demicryptochironomus vulneratus,
Harnischia spec., Cryptotendipes spec., spec. Group 5: Valvata cristata, Dreissena polymorpha,
Asellus aquaticus, Baetis spec., Hydrophilidae spec. larvae, Oulimnius spec. larvae, Paroecetis
struckii, Hydroptila spec., Parachironomus gr. arcuatus, Psectrocladius gr. sordidellus/
limbatellus, Orthocladiinae, Cricotopus bicinctus, Prodiamesa olivacea, Orthocladius orthocladius, Conchapelopia spec., Macropelopia spec., Rheotanytarsus spec., Stempellina spec.
Group 6: Stichtochironomus spp., Cryptochironomus spec., Cladotanytarsus spec., total number
of individuals.
A high number of taxa is positioned near the centre of the biplot (group 1 and 2
in Fig. 3). Most of these taxa were found in a low number of sites (#<6) or have feeding
modes other than of detriti(herbi)vores. The position near the centre of the first axis
implicates that the densities of the taxa did not correlate well with the sediment variables analyzed during this study. Protein, carbohydrates, N, and total FA were also
ordinated near the centre of the biplot meaning that these variables hardly contributed to
the variance explained by the sediment variables.
Univariate analyses
The univariate analyses were also done with the two methods of standardizing
biochemical variables. Densities of macrofauna species and higher taxonomic units
were correlated with these biochemical variables and results of bioassays. Table 4
presents the significant correlations using biochemical variables standardized on organic
matter. Densities of the detritivore groups Chironomini, Tanytarsini, Chironomus spp.,
and Stichtochironomus spp. as well as total number of individuals correlated positively
with growth and survival of Chironomus riparius larvae in the bioassays (P < 0.05) and
with the variables representing fresh organic matter (PUFA, bacterial FA, pigments, and
CO2 production). Densities of individual species that correlated positively with growth
and survival were Gammarus tigrinus, Cryptochironomus spec., Polypedilum gr. nubeculosum, Polypedilum gr. bicrenatum, and Cladotanytarsus spec., which are also detriti-
97
Chapter 5
(herbi)vores. Fig. 4 shows that the sediments were highly different in their capacity to
support growth of C. riparius. These differences are due to different nutritional value,
since amendment with artificial food stimulated uniform rapid growth (Chapter 3).
Faunal diversity was not correlated to larval growth and survival of C. riparius, but a
positive correlation was found with water content and negative correlations with the
fractions of organic matter and silt. Carnivores such as Ceratopogonidae spp., Hydracarina spp., and Procladius s.l. do not occur in Table 4, because these animals show no
Table 4. Significant correlations of sediment variables with species densities. Biochemical variables are standardized on organic matter content. Growth and survival of Chironomus riparius.
SWC = sediment water content, %<16 µm = particle size < 16 µm. Positive correlations with P <
0.05 = +, with P < 0.01 = ++, and negative correlations with P < 0.05 = -, and with P < 0.01 = --.
Tanytarsini
++
++
+
+
++
++
+
+
-
+
-
--
+
Polypedilum gr. bicrenatum
++
++
++
+
+
+
+
+
+
++
+
++
Cryptochironomus spec.
+
+
+
98
++
-
+
++
-
-
+
+
-
-
++
++
+
++
++
++
++
++
+
Glyptotendipes spp.
Shannon
++
-
Chironomus spp.
# of individuals
++
++
Polypedilum gr. nubeculosum
Cladotanytarsus spec.
C/N
--
-
Gammarus tigrinus
Stictochironomus spp.
++
+
Tanypodinae
Sphaeridae spec.
survival
++
-
growth
Orthocladiinae
%<63 µm
++
+
-
+
Malacostraca
Chironomini
organic matter
+
Oligochaeta
SWC
CO2 production
pigments
PUFA
bacterial FA
carbohydrates
P
N
C
Taxa densities are log (x+1) transformed.
++
+
++
+
+
++
++
+
+
+
++
-
++
--
--
++
++
++
+
Organic matter structuring macrofauna
significant correlation with the food related parameters, but carnivore abundance is
significantly correlated (P < 0.05) to the total number of herbivores (R2 = 0.61) and
detriti(herbi)vores (R2 = 0.42). The same univariate analysis described above has been
performed with biochemical variables standardized on dry weight of sediment. Many
correlations between biochemical variables and taxa abundances were found to be
weaker or absent (data not shown), which is consistent with the multivariate analyses. In
case abundances of taxa were significantly correlated to biochemical variables standardized on dry weight, similar correlations of these taxa with organic matter content were
found.
Discussion
The present study identified the influence of organic matter composition and the
nutritional value of sediments on the distribution of macroinvertebrate species in the
field. Searching for correlations between the occurrence of macrofauna species and
experimentally determined growth and survival of midge larvae circumvented some
problems of covariation of factors in field observations, i.e. biochemical composition,
organic matter content, grain size, etc. During the bioassays in the laboratory larval
growth and survival were determined by the nutritional value of the sediments (cf.
Chapter 3) and not by other conditions such as suitability for larval settling, oxygen
regimes, and predation. Although larval growth can be influenced by ingestion of a
variable fraction of mineral particles, the bioassays gave a good measure of nutritional
value of sediments as experienced by the sediment swallowing invertebrates. The
densities of a number of invertebrate taxa correlated well with tested larval growth
indicating that the nutritional value of sediments determines the capacity to sustain a
certain density of individuals. Such positive correlations between larval growth and
densities of detritivorous animals were conspicuous for detritivores among the closely
related group of the chironomids, while such correlations were non-significant for the
sediment swallowing oligochaetes. The latter group, however, also included species
with other feeding types, such as herbivores that feed on the sediment surface. The
causal relationship of detritivore abundance with measured food quality of detritus in
the present study is underlined by the opposing observations on carnivores. The
99
Chapter 5
occurrence of these animals was not correlated to any quality of the detritus, but to the
total number of invertebrates, i.e. the density of prey. Using chironomid larval growth
as indicator of nutritional value of substrates seems to be effective for sediment bulk
feeders, but is not appropriate for organisms with different feeding modes or other food
sources. Not withstanding these restrictions it is concluded that the bioassays using
growth of Chironomus riparius larvae are a better alternative to quantify the nutritional
value of substrates for macroinvertebrates than determination of organic matter content
of sediments.
The abundance of detritivorous macrofaunal species also correlated strongly
with biochemical parameters, especially when these were standardized on organic
matter. This standardization highlights food composition, whereas the less effective
standardization on dry weight puts emphasis on food quantity. When standardized on
dry weight biochemical variables were strongly correlated among each other and with
organic matter content showing that standardization on dry weight resulted in variables
which in fact represented alternative measures for organic matter content. The positive
correlations of abundances of detritivorous macrofauna species and organic matter
quality in the present study confirms the earlier analysis of such correlations between
measured growth and survival of C. riparius and biochemical quality of sediments
(Chapter 3). Abundance of freshly produced organic matter represented by the variables
polyunsaturated fatty acids (PUFA), bacterial fatty acids, pigments, and labile organic
matter was associated with the abundance of invertebrate species in the field. Insects
need to obtain PUFA from their diet, because they are not able to synthesize these
essential fatty acids themselves. For benthic invertebrates algae are an important source
of PUFA (Napolitano 1999). A few field studies mentioned algal input as stimulating
factor of macrofauna densities (Marsh and Tenore 1990, Goedkoop and Johnson 1996).
However, these studies did not determine organic matter composition of the algal input
and therefore were not able to separate the influence organic matter abundance from
organic matter composition. PUFA, bacterial fatty acids, pigments, and the most labile
fraction of organic matter were also found to be the most important factors stimulating
larval growth and survival of C. riparius (Chapter 3). Thus, freshly produced organic
matter is likely to promote the nutritional value of sediments thereby increasing the
capacity of sediments to sustain numbers of detritus feeders. It is concluded that the
100
Organic matter structuring macrofauna
Fig. 4. Scatterplots of measured larval growth of Chironomus riparius with observed densities of
2
2
Oligochaeta (black diamonds, R = 0.377, P > 0.05), Chironomini (crosses, R = 0.584, P <
2
0.01), and Cryptochironomus spec. (open circles, R = 0.608, P < 0.01).
100,000
-2
density (ind m )
10,000
1,000
100
10
1
0
2
4
6
growth (mm)
8
10
12
specific biochemical parameters measured in the present study, like PUFA, bacterial
fatty acids, and CO2 production are accurate descriptors of the nutritional value of
sediment for macrofauna species.
As previously observed by Vos et al. (subm.) standardization of biochemical
components on organic matter content renders quality parameters independent of organic matter abundance. This circumvents covariation of organic matter with factors other
than food. These factors include oxygen levels, grain size and the twoway dependance
between organic matter abundance and densities of macrofauna, e.g. top-down control
by invertebrates and bottom-up control by organic matter content. Organic matter
content may influence densities of macroinvertebrates, but grazing by macroinvertebrates may decrease organic matter contents and thereby the nutritional value of
sediments. Organic matter is known to influence oxygen levels in sediments through
oxygen consumption and by increasing the packing of the sediment, generally resulting
in lowered oxygen concentrations in substrates with high organic matter contents
101
Chapter 5
(Watling 1991). In sediments with elevated organic matter levels species diversity was
reduced and mainly oligochaetes and chironomid species (Cryptochironomus spec.,
Chironomus spp., Tanypus punctipennis) were found, indeed species which are resistant
to low oxygen levels (Verdonschot 1990, Heinis 1993). This makes it probable that
organic matter abundance constituted a factor indirectly structuring the macrofauna
communities by influencing oxygen concentrations in the substrate. Certainly, the
present series of macrofauna communities are representative for organically rich
sediments that are prone to oxygen depletion (Heinis 1993). Organic matter composition
did not correlate to species diversity suggesting that habitat factors selected the number
of species that were able to inhabit the particular substrates. This contrasts with the role
of organic matter composition proposed here as a factor determining the capacity of a
sediment to sustain a certain density of detritivores. The separate mode of actions of
organic matter composition and physical characteristics to structure macrofauna
communities is visualized by the separation of biochemical variables and physical
variables in the ordination biplot. The diversity of physical characteristics of the
sediments within the present dataset was high (e.g. silty to sandy substrates). Therefore,
it is expected that physical characteristics contributed to the selection of species which
could inhabit the substrate. For instance, particle size distribution is known to influence
the suitability of the substrate for tube construction and penetration which are both
indispensable for settlement of several invertebrate species (Brennan and McLachlan
1979, Wiley 1981).
The present study showed that the overall nutritional value of sediments
measured in the tests with C. riparius determines the number of detritivorous specimens
that can maintain themselves in the substrate, indicating a strong bottom-up control of
this group of animals. The role of organic matter abundance in terms of food supply can
not be quantified separately from the multiple other influences of oxygen, grain size,
etc., on so many macroinvertebrate species. The high number of non-food parameters
(e.g. organic matter abundance) may have selected the species that occupy the niche of
the benthic detritivores. Yet, it can be concluded that the quality of fresh organic matter
is likely to determine the abundance of detritivores and therefore is a main structuring
factor in soft-bottom communities.
102
Organic matter structuring macrofauna
Acknowledgments
We thank E. Bleeker for his comments on the manuscript. M. Ooijevaar, A.J.P.
Oosthoek, and S. Lücker helped with field sampling and chemical analyses. S. Arisz
(Department of Plant Fysiology, University of Amsterdam) greatly helped with the fatty
acid analyses. The study was partly supported by the Institute for Inland Water
Management and Waste Water Treatment (RIZA), Lelystad.
103
Chapter 5
Appendix I.
Table 1. Feeding mode and number of occurences of macrofauna species taxa. # substrates =
number out of the total of 24 sampled sites where species or taxa were found.
mode of feeding
# substrates
Oligochaeta
Oligochaeta spp.
detritiherbivore
Hirudinea
Helobdella stagnalis
carnivore
2
Erpobdella octoculata
carnivore
1
Valvata piscinalis
herbivore
9
Valvata cristata
herbivore
1
Bithynia tentaculata
herbivore
2
Potamopyrgus antipodarum
herbivore
6
Lymnaea spec. juveniles
herbivore
2
Gyraulus albus
herbivore
1
Planorbis spec. juveniles
herbivore
1
Sphaeridae spec.
herbivore
14
Dreissena polymorpha
herbivore
4
Hydracarina
Hydracarina spp.
carnivore
12
Amphipoda
Gammarus pulex
detritiherbivore
1
Gammarus tigrinus
detritiherbivore
12
Corophium curvispinum
detritiherbivore
1
Asellus aquaticus
detritivore
1
Proasellus coxalis
detritivore
1
Mysidae
Neomysis integer
detritivore
2
Ephemeroptera
Caenis horaria
detritivore
8
Baetis spec.
detritiherbivore
1
Odonata
Zygoptera spec. juveniles
carnivore
2
Hemiptera
Sigara falleni/longipalis
herbivore
1
Micronecta spp. larvae
omnivore
4
Paracorixa concinna
carnivore
1
Megaloptera
Sialis lutaria
carnivore
1
Coleoptera
Haliplus spec. larvae
herbivore
5
Laccophilus spec. larvae
carnivore
1
Hydrophilidae spec. larvae
carnivore
1
Oulimnius spec. larvae
herbivore
1
Agraylea multipunctata
herbivore
2
Oxyethira spec.
herbivore
1
Ecnomus tenellus
carnivore
1
Gastropoda
Bivalvia
Isopoda
Trichoptera
104
24
Organic matter structuring macrofauna
Lepidoptera
Mystacides spec.
detritiherbivore
4
Paroecetis struckii
detritiherbivore
1
Oecetis ochracea
omnivore
6
Hydroptila spec.
herbivore
1
Neureclipsis bimaculata
herbivore
1
Athripsodes spec. juveniles
detritiherbivore
1
Cyrnus spec.
carnivore
1
Lepidoptera spec. larvae
herbivore
3
carnivore
14
Diptera
Ceratopogonidae Ceratopogonidae spp.
Tipulidae
Limnophila spec.
detritiherbivore
1
Psychodidae
Psychodidae spec.
detritivore
1
Tabanidae
Tabanidae spec.
carnivore
1
Simuliidae
Simulium spec.
detritiherbivore
1
Chironomidae
Chironomini:
Stictochironomus spp.
detritiherbivore
13
Pseudochironomus spp.
detritiherbivore
1
Endochironomus albipennis
detritiherbivore
2
Tribelos intextus
detritivore
1
Dicrotendipes gr. nervosus
detritiherbivore
3
Polypedilum gr. nubeculosum
detritiherbivore
15
Polypedilum gr. bicrenatum
detritiherbivore
13
Cryptochironomus spec.
detritiherbivore
21
Chironomus spp.
detritivore
16
Microtendipes chloris agg.
detritivore
7
Glyptotendipes spp.
detritiherbivore
Demicryptochironomus vulneratus
detritivore
1
Harnischia spec.
carnivore
1
Cryptotendipes spec.
detritiherbivore
1
Parachironomus gr. arcuatus
detritiherbivore
1
Einfeldia/Fleuria
detritiherbivore
5
12
Psectrocladius gr. sordidellus/ limbatellus herbivore
10
Orthocladiinae:
Cricotopus sylvestris agg.
detritiherbivore
2
Cricotopus intersectus agg.
detritiherbivore
1
Cricotops bicinctus
detritiherbivore
1
Chaetocladius piger agg.
detritivore
1
Prodiamesa olivacea
detritiherbivore
1
105
Chapter 5
Orthocladius orthocladius
detritiherbivore
1
Corynoneura scutellata agg.
detritiherbivore
2
Clinotanypus nervosus
carnivore
2
Procladius s.l.
carnivore
16
Ablabesmyia spec.
carnivore
3
Conchapelopia spec.
carnivore
1
Macropelopia spec.
carnivore
1
Tanypus punctipennis cf.
carnivore
4
Cladotanytarsus spec.
detritiherbivore
12
Tanytarsus spec.
detritiherbivore
5
Rheotanytarsus spec.
herbivore
1
Stempellinella spec.
detritiherbivore
1
Paratanytarsus spec.
detritiherbivore
6
Micropsectra spec.
detritiherbivore
2
Tanypodinae:
Tanytarsini:
106
CHAPTER 6
CONCLUDING REMARKS
107
Chapter 6
Parameters characterizing nutritional value of sediments
This thesis showed that the nutritional value of sediments for detritivores
depends on the presence of different fractions, e.g. algal material. In this paragraph it is
attempted to define the ideal parameters for measuring nutritional value of sediments,
allowing regulation of communities of detritivores to be analyzed properly.
The effect of food quantity and quality was separated here by standardization of
food components on either organic matter content or total dry weight. Strict separation
of organic matter abundance and composition may seem artificial, because in studies on
benthic-pelagic coupling food quantity and composition are mostly related. For detritivores sedimenting algal blooms represent both an increase in food availability and food
quality. However, after sedimentation of phytodetritus is mixed with inorganic or
refractive organic material. This mixing poses several practical problems for measuring
nutritional value, because the admixture of mineral particles and refractive organic
matter in the ingestible size ranges is lowering the apparent quality of food, since these
fractions load the guts of detritivores with indigestible material. Standardization of
biochemical parameters on organic matter content of the sediment separates the effect of
food quality from the effect of food dilution by mineral particles and from the multiple
role of organic matter abundance (Chapters 3 and 5). So, a simplified conclusion is that
sedimentary organic matter needs to be chemically characterized to assess nutritional
value of sediments. However, mineral particle size distribution should also be measured
in relation to the ingestion capacity of the detritivore concerned. Parameterization of
food quality is still bound to rely on such complexity.
The biochemical nature of food suitable for detritivores was proven to be
diverse. PUFA-content (polyunsaturated fatty acids) was one of the factors strongly
associated with food quality in Chapters 3 and 5. Short-chained PUFA as well as
pigments are biomarkers for the presence of algae (Napolitano 1999). This labile
organic matter of algal origin is likely to stimulate growth of chironomid larvae. Nutritional value of sediments was also found to be related to bacterial biomass, indicating
that detritivores are versatile and opportunistic feeders. The finding that biomarkers of
both algal and bacterial material are related to nutritional value of sediments can be
explained by the sequence of degradation and microbial enrichment of organic matter.
After cell-death algae will be broken down fast, through chemical and microbial
108
Concluding Remarks
processes. Degradation of algal material will proceed fastest when algal material has
just sedimented and still contains the most labile components such as PUFA and
chlorophyll (Napolitano 1999), leading to the correlation between mineralization rate
and nutritional value of sediments. Microbial degradation advances conversion of organic matter into refractive material. Simultaneously, microbial biomass supplements the
food sources of detritivores (Martin et al. 1980, review Phillips 1984a, review Bowen
1987, review Graf 1992, Wolf et al. 1997). Microorganisms do not contain PUFA such
as algae and macrophytes do (Napolitano 1999), but a number of studies suggests that
microorganisms enrich organic matter with other essential compounds, such as vitamins
and amino acids (Phillips 1984a, Wolf et al. 1997). Fungi are thought to supplement
invertebrates with enzymes capable of breaking down cellulose (Martin et al. 1980,
Sinsabaugh et al. 1985, Bärlocher & Porter 1986, Chamier & Willoughby 1986,
Chamier 1991, McGrath & Matthews 2000). This microbial activity was represented by
specific fatty acids which are biomarkers for bacteria (Napolitano 1999).
Although it is most likely that heterotrophic microorganisms constitute a part of
the nutrition for detritivores as is supported by numerous studies (see references above),
the correlations found between detritivores and bacterial abundance may also have
resulted from the interaction between macrofauna abundance and microbial activity.
Bioturbation by benthic fauna stimulates microbial activity through mechanical
disturbance and subsequent physical and chemical alteration of organic matter in sediments (Johnson et al. 1989, Van de Bund et al. 1994). However, changes in numbers of
bacteria have been reported to be faunal species specific. In laboratory studies with
sediments from eutrophic lakes Tubifex tubifex and Chironomus plumosus affected
bacterial abundance negativily between densities of 0 and 20,000 ind m-2, but Monoporeia affinis and C. riparius did not affect bacterial abundance (densities between 0 and
10,000 ind m-2) (Johnson et al. 1989, Van de Bund et al. 1994). Mechanical stirring and
ingestion of sediment bacteria were mentioned to reduce bacterial numbers. Evidently,
there is no simple one-way relationship between bacteria and detritivores. Since many
studies confirm the nutritional role of microorganisms in food for detritivores it is
assumed that microorganisms enriched the food sources of detritivores also during the
present study similarly as in the microbial-enrichment studies (see references above).
109
Chapter 6
In the present study the nutrition of invertebrates in field sediments was
approached statically, assuming no feed back between food and consumer. Naturally,
the nutritional value in natural sediments is not static but rather is in dynamic equilibrium with detritivores. Grazing of macroinvertebrates may decrease organic matter
contents (Hillebrand et al. 2000) and bioturbation enhances bacterial productivity
stimulating degradation of organic matter (Johnson et al. 1989, Van de Bund et al.
1994). Therefore, it is expected that the nutritional state of sediment at a certain point in
time is strongly related to the period prior to sampling.
The present thesis shows that the nutritional value of sediments regulates
detritivore communities and that in turn the nutritional value of sediments depends on
labile biomass, e.g. algal material and bacteria. This implies that future studies focusing
on food quality (effect of food composition) should include biomarkers for these
organisms, such as PUFA for algae and branched fatty acids for bacteria. These
biomarkers have to be properly normalized. Yet, it is not possible to ignore the role
played by co-ingestion of mineral particles with organic matter and the feedback of
detritivores on microbial regrowth in sediments.
Feeding strategies of Chironomus riparius and other detritivores
This section reviews the response of Chironomus riparius and other detritivores
to organic matter as a food source in sediments. Furthermore, the use of C. riparius as
model organism for detritivore assemblages in eutrophic watersystems is discussed.
The model organism in the present study, C. riparius, is a detritivore of the
collector-gatherer type. Collector-gatherers maximize ingestion rate in order to maximize food uptake (Cummins & Klug 1979, review Lopez & Levinton 1987). A consequence of the short passing time of sediment in the gut is that the organism is not able to
perform intensive digestion processes (Bjarnov 1972). Less than 10% of the organic
matter ingested can be assimilated by detritivores (Cummins 1973). Therefore, it is
likely that detritivores only use the most easily absorbed components present in the
ingested sediment. Assimilation efficiencies of > 70% have been reported in invertebrates using algae as food (Johannsson & Beaver 1983, Fitzgerald & Garner 1993,
Cowie & Hedges 1996). Also bacteria have shown to be efficiently digested by
detritivores (Harper et al. 1981, review Phillips 1984a, Lopez & Levinton 1987).
110
Concluding Remarks
Especially extracellular polysaccharides of bacteria can be assimilated with high
efficiency (Couch et al. 1996). Absence of an intensive digestion system in most
detritivores may have led to the correlations of labile organic matter with resident
species of detritivores in the field and larval growth of C. riparius (Chapter 5), because
of a relative uniform exploitation of only labile components. However, extrapolation of
nutritional demands of C. riparius to other taxa found in the shallow and eutrophic
ecosystems sampled in Chapter 5 should be performed with care. The macrofauna
community did not only consist of chironomid larvae, but also of taxa which may have
different nutritional demands. Differences in nutritional demands may be based on
differences in body size, body composition, and physiological adaptations. Chironomini
are indicators of eutrophic watersystems (Saether 1975, Resh & Rosenberg 1984,
Johnson 1995) and, therefore, could demand a high organic matter abundance compared
to some other oligotrophic detritivores. Since invertebrates mostly have similar
demands for certain sets of food components in order to be able to produce new animal
tissue (Downer 1981, Phillips 1984a, Blomquist et al. 1991), demands for food
components are expected to be similar. Even though C. riparius larvae may have
nutritional demands higher than some other taxa, the use of C. riparius larvae as test
organisms in bioassays has been shown to discriminate nutritional values of a wide
range of sediments (Chapter 3).
Organisms such as collector-gatherers that live in an environment with organic
matter of overall low nutritional value would greatly profit of an ability to detect and
select habitats based on nutritional value. Detection and selection of sites based on
nutritional value would increase chances to develop and can increase population growth
(Hart & Robinson 1990, Fonseca & Hart 1996). However, a high number of taxa is
limited in their ability to migrate and therefore, the distribution of sediment infauna is
assumed to result mainly from larval settling and less so through migration (Butman
1987). For tube-inhabiting chironomid larvae changing site is not attractive, because
building a tube takes time and energy (Armitage et al. 1995). Moreover, spending time
on the surface of the sediment instead of in the tube increases predation risk (Hershey
1985 & 1987, Ten Winkel 1987, Macchiusi & Baker 1991, Baker & Ball 1995). So,
many detritivores will limit active migration. Yet, under unfavourable conditions they
may move from their habitat to increase chances to survive. For instance, if individuals
111
Chapter 6
stay at an overcrowded site chances to mature are low due to competition for food
sources (Rasmussen 1985).
Migration is not restricted to 1st instar chironomid larvae, but also takes place
during later life stages of C. riparius (Groenendijk et al. 1998). In Chapter 4 3rd instar C.
riparius larvae were also found to be able to migrate from sites with unfavourable food
concentrations. Similar results were found for 3rd instars of Chironomus tentans (Sibley
et al. 1998). If food concentrations were lowered under a threshold concentration C.
riparius larvae did not settle (Chapter 4). At higher, but still limiting food conditions,
larvae settled after physical contact with the substrate and build tubes, but emigration
occurred after a number of hours. Observations of C. riparius larvae at food levels
below the threshold concentration suggests the presence of olfaction in C. riparius
similar as was observed in C. tentans (Baker & Ball 1995). Delayed emigration after
settlement in food levels above the threshold concentration may have been stimulated
by depletion of food at the site of settlement.
Since nutritional value of sediments is affected by ingestion of mineral particle
sizes a negative preference for substrates with small mineral particles would be
expected (Chapter 4). For C. riparius preference for a certain particle size distribution
was not observed, but particle size preference tests were performed at food levels in
which the chironomid larvae reached maximum growth rate. In contrast with expectations, Sibley et al. (1998) found consistent selection preference of 1st instar of
Chironomus tentans for the smaller particle size range of two substrates at surplus food
levels, but food level preference was stronger than and independent of preference for
particle size distribution. Preference of C. tentans found for both small mineral particle
size substrates and high organic matter abundance (Sibley et al. 1998) is in accordance
with the situation in the field. In natural systems fine grained substrates are typically
associated with higher concentrations of organic matter and chironomids are often
strongly correlated with patches of accumulated organic matter (Armitage et al. 1995).
The study of Sibley et al. (1998) and Chapter 4 of this thesis suggest that chironomid
larvae prefer a substrate primarily for its food content. Inhibition of food intake by
ingestion of small mineral particles along with organic matter is not likely to be a main
factor determining preference of detritivorous chironomid larvae.
112
Concluding Remarks
In conclusion, the main characteristics of the model species C. riparius feeding
on detritus have been captured in the present thesis. It has been proven that key
parameters like half-saturation values for food-limited growth and threshold food
concentrations for settlement or migration can be quantified. Expanding this knowledge
from the model species to co-existing detritivore species is likely to clarify observations
on complex invertebrate assemblages exploiting sediment detritus.
Regulation of invertebrate communities dominated by detritivores
In this thesis the nutritional value and physical characteristics of sediments have
been discussed and reviewed as factors regulating communities of detritivores.
However, communities of detritivores are also regulated by biological factors such as
predation (top-down control) and interspecific competition. This section will discuss
these ecological factors for detritivores in relation to the bottom-up control by limiting
nutritional value of sediments.
Top-down control
Top-down control of detritivores in sediments is to be expected, since predators
such as fish and water mites are known to have a strong impact e.g. on chironomid
communities (Ten Winkel 1987) and invertebrate predators have been noted in the
sediments sampled in the present study (Chapter 5). In spite of the potential control of
detritivores by predators in the sampled sediments a number of correlations between
nutritional value and densities of detritivores were observed. Positive correlations
between carnivores and detritivores, and between detritivores and detritus are compatible when predation and detrital feeding are more or less in equilibrium. Equilibrium
predatory-prey theories emphasize the role of predators in maintaining prey populations
at or near an equilibrium (Resh & Rosenberg 1984). These theories define predation as
positively dependent on prey density. As the density of prey decreases, the predator
captures and eats proportionally fewer individuals (Ten Winkel 1987). In some cases
the predators feed opportunistically and captures prey species according to numerical
representation, e.g. the predators switch the majority of the attacks to an abundant
species. Although densities of prey may very well be suppressed by predation at peak
densities of prey (Gee 1989) an equilibrium between densities of predators and prey
explains the correlations between prey and predator numbers noted in Chapter 5.
113
Chapter 6
Another explanation for the correlation between predators and herbivorous or
detritivorous invertebrates in sediment is that predation may not be able to reduce
densities of detritivores to low densities. In a soil food-web bacterial- and fungalfeeding nematodes have been shown not to be top-down controlled by predatory
nematodes and hence, the secondary production of the bacterial- and fungal-feeding
nematodes is high compared to the production rate of the predatory nematodes (Wardle
& Yeates 1993). Similarly, predation was not able to restrain microbivore biomass
responding to enhanced resources (Mikola & Setälä 1998). The benthic macrofauna
assemblages in soft sediments (Chapter 5) consisted for the greatest portion of
chironomids and oligochaetes which may indeed be taxa with high secondary
production rates (Bonacina et al. 1996, Benke 1998, Specziar & P. Biro 1998). Still
their biomass is dispersed in large volumes of sediments and therefore may be hard to
retrieve for carnivores compared to for instance pelagic fauna. Thus, the top-down
control of detritivores in both soils and sediments is likely to be much less stringent than
in free-living consumers.
Chironomids and oligochaetes spend most time in the sediment while other taxa
are mostly active at the surface of the sediment. Behavioural differences between taxa
lead to preferential predation on specific species. For instance, specific mobility and
vertical distribution of meiofauna in the sediments lead to preferential predation on
benthic copepods by several fish species, shrimps, and mysids (review Coull 1990). For
chironomids it is known that inhabiting a tube decreases risk of predation by a number
of predators (Healey 1984, Hershey 1985a & b, Macchiusi & Baker 1991, Ten Winkel
1987). The same may apply for oligochaetes, which react to the presence of predators
by migrating deeper in the sediment. Harpacticoid copepods is the meiofaunal group
that is most preyed upon by epibenthic predators, even when they are greatly
outnumbered by nematodes (review Gee 1989, review Coull 1990, Nilsson 1992).
Preference for harpacticoid copepods were mentioned to possibly be an active choice by
predators, because harpacticoids are a food source of superior nutritional quality.
However, more strongly it was suggested that high activity of the copepods on the
sediments surface versus the deep burrowing of nematodes during presence of predators
has lead to preferential preying on copepods. Thus, chironomids and oligochaetes may
show clear correlations with the nutritional value of the sediment because other taxa are
114
Concluding Remarks
preferred to prey upon. If specific taxa are strongly selected by the predator obviously
correlations between predator and prey disappear. For example, extreme predation
pressure of the snail Urosalpinx cinera was able to drive the hard surface inhabiting
barnacle Balanus balanoides to extinction (Katz 1985).
If the prey is in equilibrium with its predator correlations between predator and
prey densities are likely to be observed. Yet, this does not imply that top-down control
of detritivores by carnivores is very strong, because of the embedding of both predator
and prey in an amorphic mass of sediment.
Interspecific competition
Interspecific competition may also hinder a clear response of species to resource
availability. Competition for resources may result in exclusion of species, some species
taking faster or more efficient advantage of food than others (such as discussed before).
Examples of competitive exclusion is evident from studies on all kinds of ecosystems.
A classical case is the mutual exclusion of two barnacle species in competing for space
in the intertidal zone (Connell 1961). Also, competitive exclusion at microscale was
demonstrated with microcosm experiments during which one species of protozoa in soil
was shown to be able to use food more rapidly and efficiently than the other species, the
latter eventually being excluded from the microcosm (Hanson 1964).
Coexistence of species with similar food sources is made possible by resource
partitioning and character displacement. A textbook example of resource partitioning is
found among the seed eating ant species living in the desert (Davidson 1977). When ant
species were separated from other species grain sizes that were used as food source
overlapped among ant species. However, the different species of ants were able to coexist because of their adapted selection for sizes of seeds when sharing the same
habitats. Coexistence of two competitors can also be realized by partitioning of the food
sources through character displacement. Character displacement is found in deposit
feeding mud snails coexisting in brackish waters (Fenchel 1975). Two species of snails
are able to co-exist by differentiating food sources and adapting the ingestion apparatus
to these different particle sizes.
In the present study several detritivorous taxa co-exist and showed similar
correlations to the nutritional value of sediments. There is no proof of the mechanisms
115
Chapter 6
of competition here, but it is plausible that resource partitioning between detritivores
occurs. Later instar chironomid larvae indeed are known to be able to ingest larger
particles than oligochaetes because of bigger menta of later instar chironomid larvae.
Using different particle sizes reduces competition for food sources thereby potentially
enabling coexistence of chironomids and oligochaetes. An even more clear distinction
between food sources of detritivores found in the sampled sediments is provided for
shredders (e.g. Gammarus) and collector gatherers (Chironomus spp.). Both feeding
modes belong to detritivores but shredders consume Coarse Particulate Organic Matter
(CPOM) and collector-gatherers Fine Particulate Organic Matter (FPOM) (Cummins &
Klug 1979). In some cases the presence of one detritivorous taxa benefits another by
conditioning of the environment. For instance, chydorids take advantage of the presence
of chironomid larvae by feeding on chironomid larvae faeces, although early instar
chironomid growth was inhibited by presence of chydorids (Van de Bund 1994). Thus,
competition and commensalisms is likely to almost concur in detritivores. Another
example of commensalism are shredders which produce FPOM thereby stimulating
growth rates of the FPOM-feeding collectors (Cummins et al. 1973).
Resource partitioning makes it probable that more than just one species of
detritivores is able to take advantage of detritus. In the sediments used in this thesis
shredders and collector-gatherers probably do not compete for food because the taxa
aim at different forms of detritus. Also, other taxa of detritivores are expected to coexist
in sediments without competing with other detritivorous taxa as was already postulated
for oligochaetes and chironomid larvae based on differences in mentum widths. The
evidence for resource partitioning is sufficient to explain correlations of densities of
several coexisting detritivorous taxa with parameters of nutritional value of sediments.
In conclusion, positive correlations found in this study between detritivores and
predators on the one hand and correlations between densities of detritivores and
sediment food quality on the other hand can be explained by an equilibrium between
predators, detritivores, and food quality. This equilibrium may be stimulated by the
physical distribution of all components in large volumes of sediment. Resource
partitioning or commensalism is indicated to modify competition for food among
detritivorous animals in sediment. The diverse options to use detritus as food enhance
species diversity of the detritivorous community.
116
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117
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129
Summary
Particulate organic matter in natural waters originates from algae and macrophytes, but can also include fragments of dead animals and terrestrial run-off. This
material tends to accumulate at the bottom and there supports distinct assemblages of
detritivores that use the organic matter as both habitat and food source. Detritivores
form a major link in the food web, processing the nutritionally low quality dead organic
matter, and constituting one of the main food sources for predators, like carnivorous
invertebrates, fish, and birds.
Field studies on the response of benthic macrofauna to sedimentation of algal
blooms suggest that food limitation controls benthic macrofauna during most of the
year. Although these field studies clearly recognize the role of food as factor regulating
population dynamics of sediment-feeding freshwater invertebrates, literature on the
influence of food composition on detritivores is limited. Also the physical characteristics of sediments are likely to affect the suitability of sediment for invertebrates. Detritivores ingest mineral particles along with organic detritus and it was expected that inorganic material obstructs food uptake and consequently hampers growth of detritivores.
The present study aimed to clarify the influence of the nutritional value of sediments on benthic detritivores. Focal points were the influence of sedimentary organic
matter and its biochemical composition on the survival and growth of benthic detritivores and the interaction between particle size distribution and nutritional value of sediments.
In Chapter 2 the quantitative effects of organic matter abundance and composition on the detritivorous Chironomus riparius was assessed. For this purpose a set of
artificial food items were biochemically analyzed for C, N, P, carbohydrates, proteins,
and total fat content, and offered in concentration series to first instar larvae of the
model species in standardized mineral substrate. Larval length and survival were recorded after one week of growth. Saturation growth curves were fitted, and for each food
item the slope and the maximum length were estimated. In general, maximum length
attained by larvae reared on fish foods and on food items of animal origin was higher
than the maximum length reached on food items of plant origin, whereas slopes at
limiting food concentrations of the growth curves for larvae reared on foods of plant
origin were steeper than slopes of curves for larvae reared on fish food or on food of
animal origin. Results indicated that the optimal food composition depended on the
131
Summary
amount of food available. For instance, high N, P, and lipid contents stimulated growth
at high food levels, whereas the amount of carbohydrates appeared to be important in
defining growth at low food levels. This interaction of food quantity and quality was
suggested to be the result of limiting energy availability at low food levels versus
limiting food quality at high food levels.
The results of Chapter 2 were verified for the field by sampling sediment and
measuring growth and survival of the midge C. riparius on these sediments in the
labora-tory (Chapter 3). The sediments were also analyzed for a set of biochemical
varia-bles. Correlations were sought between the biochemical variables and larval
growth and survival. Positive correlations of larval growth and survival with
polyunsaturated fatty acids (PUFA), pigments, and microbial mineralization rate were
found when biochemical variables were standardized on dry weight. When the variables
were standardized on organic matter weight additional significant positive correlations
with P, carbohydrates, proteins, and fatty acids of bacterial origin appeared. Clearly,
organic matter composition constituted an important factor influencing detritivore
growth, with newly produced organic material supporting highest larval growth.
The generally sub-optimal growth of chironomid larvae measured in natural
sediments was not caused by the widely diverging physical characteristics of the
substrates tested, because amendment with food permitted undisturbed larval development (Chapter 3). Biochemical variables needed to be standardized on organic matter
content in order to reveal a number of correlations between biochemical variables and
larval growth. The close correlation of organic matter content and small particle sizes
secured that standardization on organic matter basis focussed on the size fraction available as food source to the chironomid larvae. The necessity to standardize suggested
that mineral sediment particles, indiscriminately ingested with food, may have reduced
growth potential of sediments. Therefore, Chapter 4 focused on the effect of particle
size distribution on chironomid larvae growth using artificial mineral substrates.
Mineral particle size had no effect on larval growth at saturating food supply. However,
at limiting food levels growth of third instar larvae was hampered by ingestion of small
mineral grains, thereby confirming the hypothesis posed in Chapter 3 that mineral
sediment particles ingested along with food can reduce growth potential of sediments.
In Chapter 4 preference of C. riparius larvae for particle size distributions of
132
Summary
substrates and for food levels were also explored. When offered a choice between two
different particle size substrates larvae clearly preferred the substrate supplied with
food, independent of the particle size ranges. During preference experiments in which
larvae were offered two food levels, a threshold concentration was found below which
larvae continued crawling and did not settle to construct tubes. When allowed to choose
between two food levels both above the threshold concentration, the food concentrations
were only distinguished if food concentration differences were large enough. In food
concentrations higher than the threshold concentration larvae were observed to settle
within a few hours and to construct tubes. Depletion of food at the place of residence
and the ability of larvae to find food through olfaction were mentioned as possible
triggers for chironomid larvae to leave the substrate above the threshold concentration.
Growth and preference experiments in Chapter 4 showed that organic matter content
and particle size distribution are interacting factors determining larval growth of C.
riparius and abundance in situ.
Chapter 5 examined if the nutritional value of sediments is a factor structuring
natural macrofauna communities and which food components are responsible for the
regulation of macrofauna communities. Macrofauna species in a range of soft-bottom
sediments sampled in The Netherlands were enumerated and their occurrence in the
sediment samples was correlated to the results of bioassays performed with C. riparius
and to biochemical sediment composition. Growth of Chironomus riparius was used as
a direct measure of nutritional value. Newly produced organic matter, represented by
variables similar to the variables found to support growth of C. riparius in Chapter 3
(PUFA, bacterial fatty acids, pigments, and labile organic matter fraction), was
associated with abundances of a number of detritivorous taxa and therefore is most
likely a key factor for the nutritional
value of sediments. Growth of C.
riparius larvae correlated well with
abundances of detritivorous taxa but
not with taxa that have other modes
of feeding. Therefore, growth of C.
riparius was found to effectively
indicate the nutritional value of
133
Summary
sediment for bulk feeders. The use of bioassays with midge larvae excluded indirect
effects caused by covariation of organic matter content with other factors determining
the habitat for macrofauna species, e.g. oxygen regime or stability of the substrate. It
was postulated that non-food cq. habitat parameters selected the species inhabiting sites.
Yet, nutritional value determined the overall density of detritivores. Therefore, it was
concluded that sediment food quality in soft-bottom sediments is a major structuring
factor for faunal composition.
In the concluding remarks (Chapter 6) it was attempted to define the ideal parameters for measuring nutritional value, in order to analyze regulation of communities of
detritivores properly. The present thesis showed that the nutritional value of sediments
depends on labile biomass, e.g. algal material and bacteria. This implies that future
studies focusing on food quality (effect of food composition) should include biomarkers
for these organisms, such as PUFA as biomarker for algae and branched fatty acids for
bacteria. Biomarkers have to be properly normalized, e.g. on organic matter content.
Standardization of biochemical variables on organic matter content is useful to
circumvent covariation of organic matter with factors other than food.
In the second part of Chapter 6 it was concluded that the main characteristics of
feeding of the model species C. riparius on detritus have been captured in the present
thesis. Key parameters determining nutritional value of organic matter in sediments,
half-saturation values for food-limited growth of chironomid larvae, and threshold food
concentrations for settlement or migration can be quantified. Expansion of knowledge
on the model species to co-existing detritivore species was recommended in order to
clarify the observations on complex invertebrate assemblages exploiting sediment
detritus.
Finally, Chapter 6 discussed the biological factors predation and interspecific
competition in relation to bottom-up control of detritivore populations. Positive
correlations that were found in this study between detritivores and predators on the one
hand and correlations between densities of detritivores and sediment food quality on the
other hand can be explained by an equilibrium between predators, detritivores, and food
quality. It was suggested that this equilibrium is stimulated by the distribution of all
components in large volumes of sediment.
134
Samenvatting
Particulair organisch materiaal in natuurlijke wateren is afkomstig van fytoplankton en hogere waterplanten, maar bestaat ook uit dood dierlijk en terrestrisch
materiaal. Dit organische materiaal accumuleert op waterbodems en vormt daar het
habitat en voedsel voor levensgemeenschappen van detritivoren. Detritivoren vormen
een belangrijke schakel in het voedselweb, omdat ze één van de omvangrijkste voedselbronnen zijn voor predatoren als vissen en vogels. Bovendien verwerken detritivoren
het weinig voedzame organische materiaal in sedimenten.
Veldstudies suggereren dat benthische macrofauna gemeenschappen gedurende
het grootste deel van het jaar gelimiteerd wordt door voedsel. Alhoewel de rol van
voedsel als regulerende factor van detritivoren alom erkend wordt, is weinig literatuur
over de invloed van voedselsamenstelling op detritivoren beschikbaar. Detritivoren
worden naast voedsel ook door de fysische samenstelling van sedimenten beïnvloed.
Detritivoren nemen minerale delen op samen met organisch materiaal. Tijdens de
huidige studie werd verwacht dat het anorganische materiaal de voedselopname limiteert en zo de groei van detritivoren belemmert. Deze studie concentreerde zich op de
invloed van voedselwaarde van sedimenten. Punten van aandacht waren het effect van
voedselsamenstelling op de groei en overleving van detritivoren en de interactie tussen
korrelgrootte-verdeling en de voedselwaarde van sedimenten.
In hoofdstuk 2 werden de effecten van voedselhoeveelheid en -samenstelling op
de detritivore larven van Chironomus riparius bekeken. Een set artificiële voedsels
werd biochemisch geanalyseerd op C-, N-, P-, carbohydraten-, proteïne-, en vet-inhoud.
Het voedsel werd in concentratie-series aangeboden aan eerste stadium larven op
gestandaardiseerd substraat. Na 1 week werden lengte en overleving van de larven
geregistreerd. Voor elk voedseltype werd een groei-verzadigingscurve gefit en werden
maximale groei en helling van de curve geschat. Op visvoer en voedsel van dierlijke
oorsprong was de maximale groei hoger dan op plantaardig voedsel. Groei-verzadigingscurves van plantaardig voedsel hadden daarentegen stijlere hellingen vergeleken
met curves van dierlijk voer. De resultaten indiceerden dat optimale voedselsamenstelling afhankelijk is van de beschikbare voedselhoeveelheid. Hoge N-, P- en
vetgehaltes stimuleerden bijvoorbeeld hoge groei bij hoge voedselhoeveelheden, maar
carbohydraten stimuleerden juist groei bij lage voedselhoeveelheden. De interactie
tussen voedselkwaliteit en -kwantiteit zou het resultaat kunnen zijn van limiterende
135
Samenvatting
voedselkwaliteit bij hoge voedselhoeveelheden versus limiterend energie-nivo bij lage
voedselhoeveelheden.
In hoofdstuk 3 werden de resultaten van hoofdstuk 2 getoetst op de veldsituatie.
Groei en overleving van C. riparius larven op natuurlijke sedimenten werd gemeten en
gecorreleerd aan de biochemische samenstelling. Groei en overleving correleerde
positief met meervoudig onverzadigde vetzuren (PUFA), pigmenten, en microbiële
afbraak, als deze variabelen werden uitgedrukt als een percentage van het sediment
drooggewicht (DW). Als de biochemische variabelen werden gestandaardiseerd op
organisch materiaal gehalte werden daar significante correlaties met P, carbohydraten,
proteïnes en bacteriële vetzuren aan toegevoegd. Samenstelling van organisch materiaal
bleek van grote invloed op de groei van detritivoren, waarbij vers, labiel organisch
materiaal de hoogste larvale groei tot stand bracht.
De suboptimale groei van chironomide larven in natuurlijke sedimenten werd
niet veroorzaakt door de fysische samenstelling van de substraten, want verrijking van
de sedimenten met artificiëel voer leidde tot ongestoorde groei. Biochemische variabelen moesten op organische stof hoeveelheid gestandaardiseerd worden om een aantal
correlaties tussen chemische variabelen en larvale groei te onthullen. Dit suggereert dat
minerale delen, die samen met voedsel worden opgenomen, het ontwikkelingspotentiëel
van sedimenten voor muggenlarven verlagen. In hoofdstuk 4 werd daarom bekeken of
minerale korrelgrootte-verdeling van substraten de groei van muggenlarven beïnvloedt.
Bij verzadigende voedselconcentraties had de korrelgrootte-verdeling geen effect op de
larvale groei. Bij limiterende voedselhoeveelheden werd de groei van derde stadium
larven belemmerd door inname van kleine minerale delen. Dit bevestigde de hypothese
in hoofdstuk 2, dat opname van minerale delen samen met voedsel de voedzaamheid
van sedimenten verlaagt.
In hoofdstuk 4 werd ook de voorkeur van C. riparius larven voor korrelgrootteverdeling en voedselconcentraties onderzocht. Als de larven konden kiezen tussen 2
verschillende korrelgrootte substraten dan lieten de larven duidelijk voorkeur zien voor
het substraat waaraan voedsel was toegevoegd, onafhankelijk van de korrelgrootte van
de 2 substraten. Er werd een grenswaarde voor de voedselconcentratie gevonden waaronder de larven zich niet vestigden, maar op het oppervlakte van het substraat bleven
kruipen. Als de larven de keuze kregen tussen 2 voedselconcentraties boven de grens-
136
Samenvatting
waarde, dan werden de concentraties alleen onderscheiden als het verschil tussen de
voedselconcentraties groot genoeg was. Mogelijke stimulansen om een substraat te
verlaten zouden uitputting van het voedsel en aanwezigheid van reukzin bij de muggenlarven kunnen zijn. De groei- en preferentie-experimenten uit hoofdstuk 4 lieten zien
dat voedselhoeveelheid en korrelgrootte-verdeling interacterende factoren zijn die
larvale groei en abundantie in situ van C. riparius beïnvloeden.
In hoofdstuk 5 werd onderzocht of de voedzaamheid van sedimenten macrofauna gemeenschappen beïnvloedt en welke voedselcomponten voor regulatie van de
gemeenschappen verantwoordelijk zijn. Hiervoor werd macrofauna van een aantal
zachte waterbodems bemonsterd en gedetermineerd. Macrofauna abundanties werden
gecorreleerd aan de biochemische samenstelling van de sedimenten en aan resultaten
van bioassays die waren uitgevoerd met C. riparius. Groei van muggenlarven werd
gebruikt als maat voor voedingswaarde van sedimenten. Bioassays met muggenlarven
sluiten indirecte effecten door covariatie van organisch materiaal met andere factoren,
gerelateerd aan het habitat van macrofauna (bv. zuurstof), uit. Vers en labiel organisch
materiaal, gerepresenteerd door dezelfde variabelen die de groei van muggenlarven
bevorderen (hoofdstuk 3), was gerelateerd aan abundanties van een aantal soorten
detritivoren en was daarom waarschijnlijk een sleutelfactor voor de voedingswaarde van
sedimenten. Groei van C. riparius larven correleerde goed met dichtheden van een
aantal soorten detritivoren, maar niet met soorten met andere voedingswijzen. De resultaten van de veldstudie suggereerden dat habitat-factoren de soorten selecteerden die in
staat waren bepaalde sedimenten te bewonen en dat voedselkwaliteit de macrofauna
dichtheden bepaalde.
In het afsluitende hoofstuk 6 werd gepoogd om de ideale parameters voor
voedselwaarde van sedimenten te definiëren, zodat regulatie van detritivoor gemeenschappen accuraat kan worden geanalyseerd. Het huidige proefschrift toont aan dat de
voedingswaarde van sedimenten afhankelijk is van labiel biomassa, namelijk algenmateriaal en bacteriën. Dit impliceert dat in studies omtrent voedsel biomarkers van algen
(PUFA) en microorganismen (bacteriële vetzuren) moeten worden gebruikt. Inname van
minerale delen samen met voedsel door detritivoren maakt standaardisatie van de
biomarkers op organisch materiaal noodzakelijk. Bovendien omzeilt standaardisatie op
organisch materiaal covariatie van organisch materiaal met habitat factoren.
137
Samenvatting
In het tweede deel van hoofdstuk 6 werd geconcludeerd dat parameters die
voedselwaarde beschrijven (biochemische componenten, half-verzadigingsconcentraties en grenswaarden) kunnen worden gekwantificeerd. Kennis omtrent voedsel in
relatie met het modelsoort zou moeten worden uitgebreid om verspreiding van
detritivoren in het veld beter te kunnen verklaren.
In het derde deel van hoofdstuk 6 werden biologische factoren als predatie en
competitie tussen soorten besproken, in relatie met bottom-up control van detritivoren
gemeenschappen. Positieve correlaties tussen detritivoren en predatoren tegenover
correlaties tussen detritivoren en voedselkwaliteit, zoals die werden gevonden in de
huidige studie, kunnen verklaard worden door evenwicht tussen voedselkwaliteit en
dichtheden van predatoren en detritivoren. Er werd gesuggereerd dat het evenwicht
tussen voedselkwaliteit, detritivoren en predatoren verstevigd wordt door de
verspreiding van deze componenten in grote hoeveelheden sediment.
138
Dankwoord
Mijn promotie-tijd in Amsterdam was een leerzame periode, zowel op sociaal
als op wetenschappelijk vlak. Zoals iedere promovendus had ik mijn pieken en dalen,
heb ik kleine successen geboekt, maar ook fouten gemaakt.
Jaap Postma en Marco hebben de eerste opvang in groot boos Amsterdam
verzorgd. Hun energie heeft mij de eerste 2 jaar doorgeholpen. Jaap had de trein al
rijdende toen ik aankwam op de vakgroep. 's Ochtends maakten Marco's trouwe kopjes
koffie mij wakker, en de rest van de dag hield Marco's geluidswal van grappen en
grollen mij verdoofd aan het werk. Na Marco kwam Sieppie me helpen als analiste, die
ook van gezelligheid houdt, maar minder van soxhlet en modder. Mijn eerste studente
Maaike heeft samen met Marco emmers modder en zand gezeefd. Ondanks de
toenemende stank in het nat-lab hebben ze de enorme klus geklaard. Annelies was de
derde analist die aan mij werd toegewezen. Zij is een toegewijde en secure werker.
Annelies was altijd in voor een rondje wandelen, tijdens welke we vaak maatschappelijke problemen, maar ook de natuur bespraken. Helen wees tijdens deze rondjes
trouw elk konijn aan dat op onze weg kwam. Helen heeft ook getracht me UvA-politiek
bij te brengen en stond me altijd met
raad en daad bij. Helen, je kan zeggen
wat je wilt, maar de vakgroep bouwt op
je. Wim heeft me vooral de laatste fase
van de promotie doorgetrokken. Net als
elke promovendus van onze vakgroep
werd ik onder perenbomen gezet en
moest ik aan manuscripten ruiken,
maar gelukkig vond hij sommige
bevindingen ook "lollig". Jaap Dorgelo wil ik bedanken voor zijn advies en luisterend
oor als promovendus decaan. Michiel heeft zich in de laatste fase spontaan opgeworpen
als begeleider en strategisch adviseur, wat ik erg gewaardeerd heb.
Hulp kwam af en toe uit onverwachte hoek. Jos Brouwer (UU) en Eric Boschker
(NIOO, Yerseke) hebben mij belangeloos geholpen bij het identificeren van vetzuurpieken. Steven Arisz heeft mij geweldig geholpen door me wegwijs te maken op zijn
GC en deze dagenlang, zo niet wekenlang, aan mij uit te lenen. Op het GC-lab is ook
een fijne vriendschap ontstaan. Frans Kerkum (RIZA, Lelystad) heeft mij geholpen met
139
Dankwoord
het bemonsteren van sedimenten. Deze reisjes waren altijd gezellige uitjes.
Promovendi moeten regelmatig stoom afblazen, bij voorkeur bij andere
promovendi. Gelukkig leende menigeen op de vakgroep zich daar dankbaar voor. Met
Saskia kon ik lekker raaskallen, want haar kan het niet gek of luidruchtig genoeg. Dat
doet me meteen herinneren dat ik me bij mijn (voormalige) kamergenotes moet verontschuldigen voor elk overlast dat ik hun heb
bezorgd. Vrouwenkamer 4.09 was altijd een gezellig kippenhok. Vraagbaak Eric, het stukje is af.
Helpdesk Harm, het was fijn de laatste periode van
de promotie de smart te kunnen delen. De vakgroep
heeft me enorm geholpen alert te blijven onder alle
omstandigheden, aangezien het op AEE elke dag
kermis is. Ik wil specifiek alle studenten bedanken
voor alle gezelligheid die ze met zich mee brengen.
Het thuisfront bestaat uit mijn familie en
vrienden. Ik heb hele lieve vrienden, die geduldig
mijn verhalen aanhoren. Twee van hen, Anna en
Hilde, ronden hun promotie bijna gelijktijdig met
mij af. Ik zie uit naar hun proefschriften, die
ongetwijfeld onbegrijpelijke taal bevatten voor eenvoudige aquatisch ecologen. Ik wens
ze succes met de laatste loodjes en het verkrijgen van voldoende gram. Mijn zus Thera
heeft mij het goede voorbeeld gegeven, alhoewel ik nu pas snap welke boontjes zij heeft
moeten doppen tijdens haar promotie-tijd. Dankjewel voor de belangstelling die je altijd
hebt getoond voor de voortgang van mijn promotie. Mijn ouders bieden mij een veilige
basis, waar ik altijd terecht kan. Zij zijn mijn trouwste supporters, mijn hele leven al.
Over mijn liefje Ronald zou ik wereldkundig willen maken dat hij mij thuis in
de watten heeft gelegd, maar dat hij ook op werkvlak klaar stond om mij te helpen. Ik
hou van jou.
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