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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. 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The nutritional value of dietary of n-3 and n-6 fatty acids for the Chinese prawn (Penaeus chinesis). Aquaculture 118: 277-285. 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. 140