Download Species loss and the structure and functioning of multitrophic

OIKOS 104: 467 /478, 2004
Species loss and the structure and functioning of multitrophic aquatic
systems
Owen L. Petchey, Amy L. Downing, Gary G. Mittelbach, Lennart Persson, Christopher F. Steiner,
Philip H. Warren and Guy Woodward
Petchey, O. L., Downing, A. L., Mittelbach, G. G., Persson, L., Steiner, C. F., Warren,
P. H. and Woodward, G. 2004. Species loss and the structure and functioning of
multitrophic aquatic systems. / Oikos 104: 467 /478.
Experiments and theory in single trophic level systems dominate biodiversity and
ecosystem functioning research and recent debates. All natural ecosystems contain
communities with multiple trophic levels, however, and this can have important effects
on ecosystem structure and functioning. Furthermore, many experiments compare
assembled communities, rather than examining loss of species directly. We identify
three questions around which to organise an investigation of how species loss affects
the structure and functioning of multitrophic systems. 1) What is the distribution of
species richness among trophic levels; 2) from which trophic levels are species most
often lost; and 3) does loss of species from different trophic levels influence ecosystem
functioning differently? Our analyses show that: 1) Relatively few high-quality data are
available concerning the distribution of species richness among trophic levels. A new
data-set provides evidence of a decrease in species richness as trophic height increases.
2) Multiple lines of evidence indicate that species are lost from higher trophic levels
more frequently than lower trophic levels. 3) A theoretical model suggests that both the
structure of food webs (occurrence of omnivory and the distribution of species richness
among trophic levels) and the trophic level from which species are lost determines the
impact of species loss on ecosystem functioning, which can even vary in the sign of the
effect. These results indicate that, at least for aquatic systems, models of single trophic
level ecosystems are insufficient for understanding the functional consequences of
extinctions. Knowledge is required of food web structure, which species are likely to be
lost, and also whether cascading extinctions will occur.
O. L. Petchey and P. H. Warren, Dept of Animal and Plant Sciences, Univ. of Sheffield,
Alfred Denny Building, Western Bank, UK, S10 2TN ([email protected]). / A. L
Downing, Dept of Zoology Ohio Wesleyan Univ., Delaware, OH 43015, USA. / G. G
Mittelbach, W. K. Kellogg Biological Station, Michigan State Univ., Hickory Corners,
MI 49060, USA. / L. Persson, Dept of Ecology and Environmental Science, Umeå Univ.,
SE-901-87 Umeå, Sweden. / C. F. Steiner, Dept of Ecology, Evolution and Natural
Resources, 14 College Farm Road, Cook College, Rutgers Univ., New Brunswick, NJ
08901-8511, USA. / G. Woodward, Dept of Zoology, Ecology and Plant Science, Univ.
College Cork, Cork, Ireland.
Most experiments and virtually all theory about the
effects of biodiversity on ecosystem functioning have
focused on a single trophic level-primary producers. Yet
interactions between trophic levels are integral to the
dynamics of most natural ecosystems, especially aquatic
ones (Hairston and Hairston 1993, Polis and Strong
1996). Trophic cascades in aquatic systems can affect the
biomass of organisms, water clarity and temperature,
nutrient dynamics, community structure, and more
(Oksanen et al. 1981, Carpenter and Kitchell 1993,
Hairston and Hairston 1993). The strength of a trophic
cascade depends on the species or functional group
Accepted 16 September 2003
Copyright # OIKOS 2004
ISSN 0030-1299
OIKOS 104:3 (2004)
467
composition within a trophic level (Leibold et al. 1997,
Persson 1999). Keystone species provide striking examples of how the presence or absence of a species can
change biomass flow and storage in ecosystems as well as
altering community composition (Paine 1966). The
presence or absence of omnivores can have important
consequences for ecosystems through their direct and
indirect interactions with other species (Diehl 1993). It is
clear from a long history of theory, experiments, and
observations that trophic interactions affect ecosystems.
However, our understanding of how biodiversity per se
influences ecosystem functioning in systems where
trophic interactions play such a dominant role is only
beginning to develop (Raffaelli et al. 2002).
Studies investigating how biodiversity influences ecosystem functioning in multitrophic systems have been
conducted in terrestrial grasslands (Wardle et al. 1999),
soils (Mikola 1998), laboratory microbial communities
(McGrady-Steed et al. 1997), freshwater mesocosms
(Norberg 2000), and rocky intertidal communities (Paine
2002). These studies have shown that species diversity
and especially species composition can have large
impacts on ecosystem functioning via direct and indirect
pathways (Downing and Leibold 2002). In situations
where species diversity changes across more than one
trophic level, diversity at adjacent trophic levels can act
synergistically to affect ecosystem functioning (Naeem et
al. 2000), and the diversity and composition of a
community can influence ecosystems through indirect
interactions that alter trophic structure (Petchey et al.
1999, Downing and Leibold 2002).
Predicting the effects of species extinction is more
difficult in multiple trophic level systems compared to
single trophic levels for several reasons. First, the more
complex community structure makes models involving
multiple trophic levels harder to formulate and analyse.
Indirect effects in these communities make predicting
effects of perturbations difficult (Yodzis 1988). Second,
the order in which species are lost will be even more
important in multitrophic-level systems than within a
single trophic level. For example, unbalanced extinctions
among trophic levels can increase or decrease the
proportion of species that reside within a particular
trophic level depending on the original distribution of
species among trophic levels. Such changes in trophic
structure may alter the flow of energy through the food
web or change food-web stability or both (King and
Pimm 1983). For example, it is likely that the loss of a
predator will have very different ecosystem consequences
than the loss of a herbivore.
We focus here upon potential ecosystem-level effects
of species loss, rather than the more general question of
how biodiversity may influence ecosystem functioning.
Species loss is the process by which an extant community
becomes a more depauperate community. This impoverishment contrasts with situations in typical biodiversity
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experiments in which assembled communities with
different numbers of species are compared in order to
simulate effects of species loss (Symstad et al. 1998).
Such purely synthetic experiments cannot show any
short-term transient effects of the loss of a species, or,
indeed, any long-term historical effects of now extinct
species. Species loss is better simulated in removal
experiments, though these too have limitations (Dı́az
and Chapin 2000).
Here we explore aspects of species loss in multitrophic-level systems from an empirical and theoretical
perspective. First, we investigate how species richness
and extinctions are distributed amongst trophic levels.
For example, are there more producer species than
consumer species and which will go extinct first? Second,
we use a simple food-web model to examine how the loss
of species at different trophic levels will affect ecosystem
structure and functioning. Most of our examples come
from multi-trophic aquatic systems, although many of
the issues we cover appear to be common to aquatic and
terrestrial systems alike.
Patterns of diversity and species loss in natural
aquatic ecosystems
The distribution of species richness among trophic levels
will influence post-extinction trophic structure, for
example, if there are few species at a particular trophic
level there is an increased likelihood that extinctions will
cause loss of this entire group. In addition, the outcome
of a species deletion is also influenced by whether the
species that goes extinct is high up or low down in the
food web (Pimm 1980). Both observations make documenting the patterns of diversity and extinctions across
trophic levels important if we are to predict effects of
extinctions on ecosystem structure and functioning.
The distribution of species among trophic levels
Patterns of species richness across trophic levels are
generally less well documented than either total abundance or biomass in each trophic level. Studies have
mainly drawn on data from detailed species surveys of
specific systems (Evans and Murdoch 1968, Moran and
Southwood 1982), food web data (Cohen 1977, Briand
and Cohen 1984, Sugihara et al. 1989, Martinez 1991,
Schoenly et al. 1991a, Havens 1992), or species lists from
many different studies (Warren and Gaston 1992). All
yield information on the shape of food webs, but
interpreting their results is not straightforward for a
number of reasons. First, not all types of data have
information across all trophic levels (for example, studies
of trophic guild structure only examine the faunal
component of the community). Second, assignment to
trophic position may be based on the recorded feeding
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links in a particular web, but this may not reflect the
typical trophic role of the species (for example, a
herbivore might appear as a top consumer simply
because it is not consumed in a particular web). Thirdly,
the food web data in particular have considerable
variation in resolution, both of links and taxa, which is
not independent of trophic position (for example, top
predators are likely to be much better resolved taxonomically than species near the base of the food web). As a
result of these problems, early generalizations about
trophic richness ratios are unreliable (Polis 1991). Some
of the later studies, however, whilst still imperfect, may
nonetheless provide useful guidance as to the relative
richness of different trophic levels.
Systematic cross-community comparisons of food web
shape have most extensively been carried out using food
web data, classifying species as ‘basal’ (i.e. feed on
nothing else in the web), ‘top’ (are fed on by nothing else
in the web) and ‘intermediate’ (both feed on, and are fed
upon by, others in the web). Studies using this approach
suggest that there is a tendency for intermediate species
to account for a smaller fraction of the community as
diversity is reduced, at least at lower diversity, with the
proportions of basal and top species becoming correspondingly larger (Briand and Cohen 1984, Sugihara et
al. 1989, Havens 1992, Martinez 1993), though the
strength of this effect is subject to debate (Havens
1992, Martinez 1993). Analysis of such data from
aquatic food webs produces rather mixed results (Fig.
1). While there is some indication of triangularity in the
shape of the web for top and intermediate species, basal
species constitute a very variable fraction of the web
(Fig. 1). This may genuinely be the case, though there are
also two possible artefactual explanations. First, the base
Fig. 1. Proportions of basal (B), intermediate (I) and top (T)
species from different studies as follows: a) Schoenly et al.
(1991b), means from nine insect dominated aquatic food webs;
b) Martinez (1991, 1991a) single large lake food web; c) Hall
and Raffaelli (1991, 1991a) single large estuarine food web; d)
Havens (1992), pelagic food webs from fifty lakes; e) Closs and
Lake (1994) stream food webs for different seasons; f) and g)
Deb (1995), two pond food webs; h) and i) Thompson and
Townsend (2000) means, over season, for two streams.
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of many aquatic food webs, especially in benthic systems,
is largely dead organic matter (detritus), and the
associated heterotrophic microbes. Taxonomic resolution of these elements of most food webs is notoriously
coarse, and so provides little guidance as to taxonomic
diversity. Second, even where food webs have a substantial component of basal species, these may be
aggregated into broad groups (e.g. ‘periphyton’ or
‘phytoplankton’) rather than resolved to species. These
problems make it difficult to judge whether difference in
species richness among trophic levels are an artefact, or
reflect real differences between types of aquatic systems.
In the relatively few food webs where effort has been put
explicitly into obtaining good taxonomic resolution in
both basal and other levels, the basal level can be as, or
more, diverse than the levels above (Havens 1992)
though this is not inevitably the case (Martinez 1991).
Assignment of species to the other categories is ambiguous. Intermediate species can be second, third or fourth
level consumers, provided there is at least one species
that (perhaps occasionally) feeds on them. This results in
there being almost no true ‘top’ species as food webs
become large (Martinez and Lawton 1995), at which
point the classification seems of little value. Clearly,
estimating the distribution of species richness amongst
trophic levels requires both good taxonomic resolution
across all trophic levels, and a clear definition of trophic
position.
Here we present a new compilation of data from a
number of studies in benthic freshwater systems, that
may suffer less from the problems discussed above.
Species richness data were collated from a total of 141
freshwater sites, 91 from running waters, 50 from
standing waters. The sites spanned a wide range of
systems across a large acidity gradient (pH 4 /8.5)
created mostly by variation in geology and land-use.
One hundred and twenty-three of the sites were located
within the U.K. Eighteen New Zealand streams (Townsend et al. 1998) were also included, to compare the
shape of food webs from two regions with very different
evolutionary histories. We standardised taxonomic resolution by identifying taxa to the lowest common
denominator across studies: i.e. to species where possible, or to the next highest taxonomic level if species
could not be distinguished with certainty. This meant
that our estimates of species richness are conservative
and certain large taxonomic groups whose members are
difficult to identify, such as meiofauna and bacteria,
were excluded all together. We then sub-divided our
communities into trophic levels: because we ignored
trophic interactions within the microbial part of the food
web (microbial loop), we defined ‘consumer 1’ species as
those that eat only at the ‘basal’ level (primary producers, detritus, and associated microbes), ‘consumer 2’
species as invertebrates that eat other metazoans, and
‘consumer 3’ species as vertebrates (fish here) that eat
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other metazoans (Jeffries and Lawton 1985). Although a
large proportion of the consumer 2 species in benthic
aquatic systems are traditionally described as ‘detritivores’ (e.g. many stoneflies and caddisflies), many of
these are, in fact, facultative grazers (Ledger and
Hildrew 2000) as, indeed, are many of the consumer 3
species (Woodward and Hildrew 2002). We further
limited our analysis to communities and restricted basal
species to include only diatoms because of a lack of
sufficiently detailed taxonomic data for cyanobacteria
and other algae. Aquatic macrophytes were excluded
since they contribute to the food web primarily via the
detrital pathway (Hildrew 1992, Jones et al. 1998).
Benthic grazers (e.g. some snails and mayflies) feed
predominantly on biofilms, which are typically rich in
diatoms and coat both mineral and organic surfaces
(Hildrew 1992, Jones et al. 2002).
Species richness decreased from the lower to the
higher trophic levels in both running and standing
waters (Fig. 2). In fact, our analysis of empirical data
shows that food webs were probably even more triangular than suggested by our results because our basal
species category included only diatoms. The New
Zealand data exhibited broadly similar patterns to those
from the U.K., despite the very different evolutionary
histories and environmental conditions of these two
regions, suggesting that the trophic structuring of
benthic freshwater systems might follow similar ‘rules’
across a wide range of environments.
Fig. 2. Variation in numbers of species in each of four trophic
levels for the data-set described in the text. See the text also for a
description of how species were assigned to the trophic levels.
Open circles are UK lakes and ponds; open squares are UK
streams and rivers; open triangles are New Zealand (NZ)
streams. Bars represent 9/95% CL. Sample sizes are: diatoms:
11 Lakes, 11 UK streams, 18 NZ streams; primary consumers:
40 Lakes, 91 UK streams, 18 NZ streams; invertebrate
predators: 40 Lakes, 91 UK streams, 18 NZ streams; fish: 43
Lakes, 59 UK streams, 18 NZ streams. Raw data were provided
by the contributors listed below, with the relevant literature
cited where appropriate: S. J. Ormerod (Bradley and Ormerod
2001, Bradley and Ormerod 2002); F. Edwards (unpubl.); C.
Gjerløv (Gjerløv et al. in press); S. S. C. Harrison (Pretty et al.
2003); J. I. Jones and C. D. Sayer (Jones and Sayer 2003); A. M.
J. Lane (Lane 1999); N. Towers (unpubl.); R. Thompson
(Townsend et al. 1998); W. Beaumont (UKAWMN 2000); G.
Woodward (unpubl.).
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The distribution of extinctions among trophic levels
Multiple factors may predispose for extinction of species
at higher trophic levels compared to those at lower ones.
The relatively small population sizes of species at higher
trophic levels increase their risk of extinction via
demographic stochasticity and environmental fluctuations (Lande 1993). Longer generation times and relative
rarity of resting stages mean that evolutionary and
ecological change will lag further behind altering environments, putting species at higher trophic levels at
special risk again. Furthermore, species occupying
higher trophic levels depend on the presence of species
at lower trophic levels, causing higher extinction risk for
species occupying higher trophic levels in simple foodwebs (Fowler and MacMahon 1982, Holt et al. 1999)
and perhaps also in more complex webs (Holt et al.
1999). However, effects of trophic dependencies on
extinction risk in complex food webs are harder to
predict (Pimm 1980, Holt et al. 1999), because species
occupying higher trophic levels can promote co-existence
of competing species at lower trophic levels (Paine 1966).
Nevertheless, disproportionate extinction probabilities
among trophic groups, with generally higher extinction
rates for species at higher trophic levels seems to be an
emerging general pattern (Dickerson and Robinson
1986, Mikkelson 1993, Wright and Coleman 1993,
Kruess and Tscharntke 1994, Lawton 1995, Gilbert et
al. 1998, Holt et al. 1999). Indeed, it can be difficult to
find any combination of species in microbial aquatic
communities in microcosms that both include a species
at a high trophic level and are persistent (Weatherby et
al. 1998).
The data we compiled on species richness distributions
amongst trophic levels (Fig. 2) were collected from
systems spanning a gradient in acidity; they suggest
that the species at some trophic levels were more
vulnerable to acidification than others. Despite the fact
that species richness always increased with pH, the
strength of the relationship and the rate of increase
varied among trophic levels (Fig. 3). However, there was
no evidence that the effect of pH on richness increased
with increasing trophic level (p /0.37 for Spearman’s
rank correlation between the slopes of the relationships
in Fig. 3 and trophic level (1, 2, 3 or 4 corresponding to
basal, consumer 1, consumer 2, and consumer 3 levels)
for either streams and rivers or ponds and lakes). Our
data supported the view that populations of species at
high trophic levels (here fish) are often severely reduced,
or even extirpated, at low pH (Brown and Sadler 1989,
Muniz 1990). This suppression of the consumer 3 species
can often lead to release of the large invertebrate
consumers at the adjacent trophic level, which can
become very abundant (Hildrew et al. 1984). Despite
these variations among trophic groups and given that
our data were collated from different communities, the
positive relationships between pH and species richness
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particular, are sensitive to heavy metal pollution, which
typically accompanies acidification in mine tailings
(Brown and Sadler 1989). Fishes and amphibians, which
occupy the highest trophic levels in many freshwaters,
are also susceptible to the effects of climate change; even
slight rises in temperature can lead to population crashes
and extinctions (Carpenter et al. 1992). Species at higher
trophic levels also tend to be most heavily exploited
(Pauly and Christensen 1995). Consequently, their
extinction resulting from over-harvesting is a very real
concern, as is evidenced by the precarious position of the
much of the world’s cetacean fauna and the collapse of
many marine fisheries (Griffith 2000).
Despite the often strong influences of a single
environmental stressor, many natural systems are simultaneously affected by multiple stressors (Breitburg et al.
1999, Folt et al. 1999, Vinebrooke et al. 2003), which can
induce more complex ecosystem responses. For instance,
some of the pH-species richness relationships were
altered in the sites with greater nutrient availability
(denoted by crosses in Fig. 3): invertebrate species
richness in standing waters was unusually low, but
phytoplankton were far more speciose under elevated
nutrient loadings. In contrast, fish species richness was
largely unaffected by nutrient enrichment, as were
invertebrates in running waters. These deviations suggest
that very different food web configurations can occur
when multiple stressors are operating, and that responses
can vary among trophic levels and are also systemspecific. Indeed, alternative stable states, transiently
maintained by trophic cascades, are well documented
in eutrophic shallow lakes (Van de Bund and Van Donk
2002, Jones and Sayer 2003), but are far less prevalent in
running waters.
Fig. 3. Numbers of species in each of four trophic groups, and
chlorophyll a concentration for phytoplankton along a pH
gradient in (a) streams and rivers and (b) ponds and lakes. See
the text for a description of how species were assigned to the
trophic levels. Regression statistics were from log10(x/1)
transformed data. Circles denote ‘normal’ water bodies; crosses
denote sites that are subject to significant artificial eutrophication resulting from either sewage or agricultural fertiliser input.
Open triangles represent freshwater bodies that recently experienced altered productivity or acidity and were excluded from
regression analyses.
were strong and consistent within most trophic levels
and remarkably similar across running and standing
waters.
Although our analysis of data from running and
standing waters focussed on acidification, examples of
stressors that lead to disproportionate species loss at
high trophic levels are legion. For instance, biomagnification of organochlorine pesticides has been implicated
in the impaired reproduction or loss of top predators
from many freshwater food webs (Mason 1991) and
similar effects have been reported in marine systems
(Jarman et al. 1996). Fish in general, and salmonids in
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Modelling multitrophic extinctions and effects on
ecosystem properties
The discussions above are limited forays into what is
clearly a complex problem. Attempting to predict the
possible effects of species loss on functional aspects of
aquatic systems by piecing together inferences from our
current understanding of how such systems work is an
important endeavour, but has limitations. In particular, it
is difficult to relate insights from specific results in one
system to more general principles across different types
of system, and it is difficult, from field observations and
experiments, to separate the effects of species loss from
other confounding factors (Huston 1997). One approach
to tackling these problems is to explore the problem in
model systems, trading off the advantages of clear
comparison of the effects of interest, with the inevitable
danger of oversimplification (Morin 1998). Here we take
this approach and explored how standard Lotka /
Volterra consumer /resource equations respond to loss
471
of species from different trophic levels. For simplicity,
the model we present includes three trophic levels and
species within a trophic level differ in growth rate and
interaction strength. Because of our restriction to three
trophic levels, consumer 2 biomass is relatively high
because of release from consumption (Oksanen et al.
1981). We focus upon total biomass, a state variable, of
each trophic level as the ecosystem-level property of
interest. Focusing on total biomass enables direct
comparison with the results of experiments that also
focused on total autotroph biomass (Tilman 1997,
Hector et al. 1999), though we stress that standing
biomass may (Leibold et al. 1997) or may not inform
about the rate of biomass production, especially in
aquatic systems where much of the biomass is quickly
consumed. Regardless, the total biomass of a trophic
level, especially of primary producers, is a valid and
important ecosystem property in its own right.
Modelling methods
Four different food web structures were simulated; all
were composed of three trophic levels: a basal level of
autotrophic primary producers (hereafter called basal), a
primary consumer level (hereafter called consumer 1),
and a secondary consumer level (hereafter called consumer 2). Web structure differed in the level of omnivory
(present or absent) and shape (rectangular or triangular)
in a 2 /2 design. Omnivory was manipulated by creating
webs in which consumers fed only on the trophic level
below them (no omnivory) and webs in which consumer
2 species fed on both consumer 1 and basal species. Web
shape was either ‘‘rectangular’’, in which each trophic
level was composed of an equal number of species (3
species per level for a total of 9) or ‘‘triangular’’, in
which fewer species were found at successively higher
trophic levels (4 basal species, 3 species at the consumer
1 level, and 2 species at the consumer 2 level, for a total
of 9). We modelled rectangular webs in addition to the
more realistic triangular webs to explore whether web
structure may be a determinant of responses to extinction, but we only show graphs of results from triangular
webs, given that in reality food webs are rarely if ever
rectangular.
All interactions were modelled using Lotka /Volterra
consumer /resource equations of the general form:
dBi =dtBi f i (B)
(1)
where
f i (B)Bi Sj aij Bj
Bi is the biomass of species i, fi is its per biomass rate of
increase, and aij is the effect of species j on species i. The
state variables of this class of model are often assumed to
be the number of individuals in some area or volume
472
(e.g. density of individuals). The models are, strictly
speaking, based on biomass conversion equations, however, so that the state variables are the biomasses of
species (Berryman 1999). Basal species were self-limited
populations exhibiting logistic growth with an intrinsic
rate of increase (bi) chosen randomly from a uniform
distribution between 0.00001 and 1 and a self-limitation
term, aii /bi/K, where K was the carrying capacity set at
10 for all basal species. For simplicity, we did not model
interspecific competition among basal species. Consumers were modelled without self-limitation (aii /0). An
effect of consumer j on resource i (parameter aij) was
chosen randomly from a uniform distribution between 0
and 1. The consumers gain from their resource (aji) was
calculated as /aij /cji, where cji was a conversion
efficiency (the fraction of consumed prey that is
converted into predator biomass) chosen randomly
from a uniform distribution between 0.01 and 0.9.
Consumer mortality rates (bi) were chosen randomly
from a uniform distribution between /0.00001 and
/1.
We randomly generated 1000 feasible food webs for
each of the four web structures. Unlike previous studies
that have relied upon asymptotic population stability as
a criterion for determining the feasibility of randomly
generated communities (Pimm 1982, Moore et al. 1993,
Borrvall et al. 2000), we use permanence as our
determinant of food-web feasibility following methods
in Law and Morton (1996). Permanence is a global
property of a model community requiring only that
biomasses of all component species are positive and
finite (Hofbauer and Sigmund 1988, Law and Morton
1996). Consequently, permanence allows for asymptotically stable communities (local and global) as well as
classically unstable systems such as cyclic fluctuations in
populations biomass or chaotic states (Law and Morton
1996). Hence, the permanence criterion includes a wider
range of dynamics, some of which may occur in natural
systems and yet be excluded by less inclusive feasibility
criteria.
To explore effects of species losses, we subjected each
permanent community to a series of species deletions.
For the sake of simplicity and tractability, we only
consider deletions within single trophic levels. For each
trophic level in the rectangular food webs, every possible
one-species deletion was performed, followed by every
possible two-species combination. Deletions of all three
species were performed for the consumer 1 and consumer 2 trophic levels, though not for basal species since
this would result in a ‘community with no species’. In the
triangular food webs, every possible one-species and
two-species deletion was executed for the consumer 2
level and every possible combination of one, two, and
three-species deletion was performed for the consumer 1
and basal levels.
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Following each deletion, the resultant community was
assessed for permanence. If not permanent, an attracting
(permanent and non-invasible) species sub-set was
obtained by checking every possible combination of
species left following deletion for the properties of
permanence and non-invasibility by species not included
in the sub-set of interest. For example, consider a web
with four species initially (1,2,3,4) from which species 4
is subsequently deleted. The resultant community (1,2,3)
is checked for permanence. If not permanent, then every
possible sub-set (1), (2), (3), (1,2), (1,3), and (2,3) is
checked for permanence and non-invasibility by species
from the post-deletion species pool not included in the
focal sub-set. Invasibility was determined by calculating
the invaders growth rate (fi(x) from Eq. 1) when its
biomass was equal to zero and the biomasses of the
resident species were set at equilibrium values (Law and
Morton 1996). In rare instances (4% of total deletion
attempts), a single attracting sub-set could not be
obtained or permanence could not be determined. In
such cases we relied on numerical integration to determine community composition following species deletions using a 4th/5th order Runge /Kutta solver. The
post-deletion community was given initial biomasses
equal to their pre-deletion equilibrium values, and
dynamics were then allowed to run for 6000 time steps.
Visual inspection of haphazardly selected cases showed
that transient dynamics generally disappeared within the
first 500 time steps. Any species with biomass greater
than an arbitrary lower limit (1/10 6) at the end of the
simulation were retained and equilibrium population
biomasses were calculated as the average over the final
1000 time steps.
Once a permanent attracting subsystem was found,
the community composition was saved and response
variables were calculated. We recorded the total biomass
of basal species and the incidence of cascading extinctions (losses of species other than those deleted). To
calculate biomasses, we relied upon equilibrium values
(i.e. we set Eq. 1 to zero and solved for Bi). Though nonequilibrium dynamics were possible, equilibrium population biomasses derived from linear Lotka /Volterra
equations are equivalent to biomasses averaged through
time (Hofbauer and Sigmund 1988, Law and Morton
1996).
number of species deleted on basal biomass, we used
repeated-measures analysis of variance (rm-ANOVA)
with the number of species deleted modelled as a
within-subjects effect. Statistical significance should
not be over-interpreted since it is a partly a function of
the number of replicates chosen. We ran separate
repeated-measures analyses for deletions within the
basal, consumer 1, and consumer 2 trophic levels.
Because some trophic levels experienced different levels
of species deletion in rectangular versus triangular webs,
we focused only on 0, 1 and 2 species deletion combinations in our statistical analyses to ease comparisons. We
log10(100/B/1) transformed all values for both statistical analyses and graphical depiction. We multiplied
biomass by 100 before adding the constant to reduce the
influence of the constant. All statistical analyses were
performed using Systat Version 8.0.
Modelling results
Focusing first on basal species deletions, biomass at all
trophic levels decreased as a function of increasing losses
of basal species (Fig. 4A, 4B). Declines in basal biomass
Analyses of modelling results
For analyses of simulation results, we considered each
randomly generated food web to be an experimental
unit. Because multiple combinations of a level of species
deletion were performed within a trophic level, biomass
responses to these multiple combinations were averaged
to obtain a single response for a given community. To
explore effects of omnivory, food web shape, and the
OIKOS 104:3 (2004)
Fig. 4. Effects of deletions of basal species (A, B), consumer 1
species (C, D) and consumer 2 species (E, F) on total biomass of
basal species (triangles), consumers 1 (squares) and consumers 2
(diamonds). Food webs either excluded (A, C, E) or included (B,
D, F) omnivory. Shown are means and standard deviations.
Symbols are slightly displaced along the x-axis to increase
clarity.
473
were generally steeper in webs without omnivory (p B/
0.0001, omnivory /number deleted within-subjects effect). Loss of biomass with increasing numbers of basal
species deletions was greatest in rectangular webs without omnivory, as indicated by a significant three-way
interaction between number of species deleted, food web
shape, and omnivory (p B/0.0001, within-subjects effect).
Cascading extinctions of basal species were infrequent
(Fig. 5A, 5B). However, cascading extinctions of consumer 1 and consumer 2 species occurred in the majority
of food webs, regardless of food web shape or omnivory
(Fig. 5A). The exception was consumer 2 in triangular
webs without omnivory.
Basal biomass increased as more consumer 1 species
were deleted (Fig. 4C, pB/0.0001, within-subjects effect).
However, this effect was weaker in food webs with
omnivory (p B/0.0001, omnivory/number deleted effect). Consumer 1 biomass decreased with increasing
numbers of extinctions (Fig. 4C), while the effect on
consumer 2 biomass depended on the presence of
omnivory (Fig. 4C, 4D). Compared to deletions of basal
species, consumer 1 deletions tended to increase the
frequency of cascading extinctions of basal species (Fig.
5C, 5D). These basal species extinctions were more
frequent in webs with omnivory and were most common
in triangular webs with omnivory, occurring in greater
than 50% of the communities. Cascading extinctions
were relatively rare in the consumer 1 trophic level (Fig.
5C). However, cascading extinctions of consumer 2
species were very frequent in webs without omnivory,
but less so in food webs with omnivory (Fig. 5C, 5D).
Species deletions within the consumer 2 trophic level
caused basal biomass to decrease (Fig. 4E, pB/0.0001,
within subjects effect of number deleted). This effect was
more pronounced in food webs without omnivory and
was especially strong in triangular webs without omnivory as indicated by a significant within-subjects interaction between web shape, omnivory and number of
consumer 2 species deleted (pB/0.0001). The deletions
increased consumer 1 biomass and decreased consumer
2 biomass (Fig. 4E). Increasing losses of consumer 2
species also resulted in large increases in the frequency of
cascading extinctions within the basal trophic level (Fig.
5E). Triangular webs were particularly prone to cascading extinctions.
Model conclusions
Fig. 5. Effects of deletions of basal species (A, B), consumer 1
species (C, D) and consumer 2 species (E, F) on the frequency of
cascading extinctions of basal species (triangles), consumers 1
(squares) and consumers 2 (diamonds). Food webs either
excluded (A, C, E) or included (B, D, F) omnivory. Shown
are means and standard deviations. Symbols are slightly
displaced along the x-axis to increase clarity.
474
Simplistic community models suggest that basal (e.g.
primary producer) species extinctions can only reduce
total biomass at the basal level (Tilman et al. 1997,
Loreau 1998). In contrast, extinctions from our multitrophic model can either increase or decrease the total
biomass within a trophic level. In general, our simple
model exploration shows that effects of species loss from
multitrophic systems depend on how many species are
lost, from which trophic level species are lost, and also
on food web shape (triangular or rectangular). The
effects of extinctions were, however, suggestive of a
simple consumer /resource dynamic. As more species
are removed from a trophic level, the more their
resources are freed from top-down control. This can
then cascade to lower trophic levels as those intermediate species exert stronger control of their resources, the
basal species (as seen in the consumer 2 deletions). It is
not unexpected that losses of consumer species may
influence basal species either directly or indirectly
through consumptive effects, assuming that feeding links
are not donor-controlled. These relatively intuitive
changes in total biomass within a trophic level (an
aggregate ecosystem property) contrast with the indeterminate effects of species loss on abundances of
individual species (Yodzis 1988). This mirrors the
qualitatively different responses of population-level and
community-level stability to change in biodiversity
(McNaughton 1977).
However, this simplistic interpretation disregards the
impacts of species extinctions that may cascade through
a food web as the result of species deletions. Our results
OIKOS 104:3 (2004)
indicate that loss of a focal species or group of species
commonly results in further species extinctions in
adjacent and non-adjacent trophic levels. Though previous studies have examined such phenomena in model
food webs, revealing important effects of species richness
and food web structure (Pimm 1980, Borrvall et al. 2000,
Lundberg et al. 2000, Dunne et al. 2002), these studies
did not expose the precise distribution of extinctions
within the food web or their consequences for ecosystem
properties. Some cascading extinctions are expected
based on first principles. For instance, in rectangular
food webs without omnivory, loss of a single consumer 1
species will result in three consumer 2 species feeding on
only two consumer 1 species, a case in which stable
coexistence is unlikely under constant environmental
conditions. Omnivory can buffer consumer 2 populations from this effect, as can triangular food web
configurations (compare Fig. 5C, D). Potentially more
complex are extinctions that cascade down trophic levels.
If consumers mediate coexistence of their resources (e.g.
by feeding on competitive dominants, curtailing competitive exclusion), then deletions of those consumers can
cause extinctions among the resource species. This is a
plausible explanation for consumer 1 extinctions following consumer 2 removals (Fig. 5E, F). However, this
cannot explain extinctions of basal species following
consumer 1 deletions (Fig. 5C, D), as competitive
interactions were not modelled for basal species. If we
had modelled interspecific competition among basal
species, it is likely that extinctions at the basal level
would have been even more frequent in this case. Finally,
consumer 2 deletions vividly illustrate how extinctions
may cascade to non-adjacent trophic levels (Fig. 5E, F).
The high frequency of cascading extinctions among
basal species was likely to be due to apparent competition following the release of consumer 1 species from
consumer 2 control. If true, this illustrates how coexistence of species within trophic levels may be indirectly
mediated by consumers in higher, non-adjacent trophic
levels, a balance that may be easily disrupted.
As with any model, our study required a number of
simplifying assumptions and abstractions to maintain
tractability. Consequently, there are several caveats that
deserve mentioning. First, strong consumer effects were
due to our use of Lotka /Volterra equations with
recipient control. Incorporation of donor-control or
ratio-dependent functional responses should weaken
consumer effects (direct and indirect) on basal species.
Secondly, we modelled basal species without interspecific
competition. This implicitly assumes no overlap in
resource requirements of basal species (i.e. in the absence
of consumers, basal biomass is a linear, increasing
function of basal species richness). Hence, losses of
basal species will have a greater impact on basal biomass
compared to situations in which species display some
degree of niche overlap and can exhibit density compenOIKOS 104:3 (2004)
sation following competitive release (note, however, that
there may be a greater tendency for competitive exclusion and cascading extinctions in this scenario).
Our models have focussed on food webs where
primary producer species form the basal food resource.
However, in some freshwater ecosystems, allochthonous,
rather than autochthonous, inputs can dominate the
basal resources (Wallace et al. 1997). In these systems,
dependence on terrestrial subsidies results in a predominance of donor-controlled interactions between basal
species and consumers. Donor-control (e.g. semi-chemostat dynamics in basal resource) can produce qualitatively different effects from Lotka /Volterra dynamics
with logistic growth, and may serve to stabilise food web
structure (Polis and Strong 1996). It seems possible,
though clear answers would require further investigation, that the models above are appropriate if we
consider the detritivores as the basal trophic level;
organisms that feed on detritivores would then occupy
the consumer 1 level, and organisms that consume these
would occupy the consumer 2 level.
Extinctions within our model were random within
trophic levels. Future models could simulate extinctions
that correspond to generalism (e.g. connectedness, as in
Dunne et al. 2002), interaction strength, vulnerability to
predation, and competitive ability (though note that any
cascading extinctions must have resulted from these
kinds of difference among species). Because we modelled
all consumers as generalists (every species within a
consumer trophic level fed on every species in their
resource trophic level) extinctions were not ordered by
generalism. However, simulated extinctions from food
webs differ in effect depending on whether more or less
connected species go extinct (Dunne et al. 2002). For
simplicity also, our simulated extinctions occurred without regard to aij or aji (Borrvall et al. 2000). Loss of
species that are more vulnerable to predation might have
qualitatively different effects than the loss of species that
resist predation. If invulnerable species are lost, more
nutrients will be passed to consumers via vulnerable
species.
Another complexity that we chose not to include in
the model was that of ontogenic shifts in the trophic level
occupied by a species. Often species in aquatic systems
occupy one trophic level while young and another
trophic level in the adult stage (Wu and Culver 1992),
and large ontogenetic shifts in trophic position can occur
even among insect larvae (Woodward and Hildrew
2002). The occurrence of ontogenetic niche shifts could
have several implications for the effect of extinctions on
ecosystem properties. Extinction of a single species
might remove a component of two trophic levels
simultaneously and consequently have greater effects
than otherwise. Finally, we chose not to allow the
replacement of the extinct species with a different
species. This contrasts with observations of some aquatic
475
systems, where species replacements along an environmental gradient are common and also important in
regulating trophic structure (Leibold et al. 1997).
Further modeling that includes ontogenic shifts and a
regional pool of species that could replace extinct species
could inform about how species replacements might
temper the functional consequences of extinctions.
Future directions
Our multi-trophic level model shows how effects of
species deletions may depend critically on food web
shape and omnivorous links (independent of species
richness). This is perhaps not surprising when considering species losses amongst consumers. Yet, even losses of
basal species affect species at other trophic levels, with
ultimate impacts on total production being linked to
consumers, food-web shape, and degree of omnivory. We
argue that there is little un-biased and or reliable
information about the shape of food webs, though they
are generally though to be triangular; a proposition that
is supported by the new compilation of data that we
present. New high-resolution studies of food webs
provide a method for assessing the consequences of
extinction in very complex food webs with realistic
structure (Dunne et al. 2002). Linking this work to
ecosystem functioning would scale up from the study of
small modules of interacting species (used here) to much
more complex and realistic food web structures.
The model also shows that where in the food web
species loss is focused can be crucial for eventual impacts
on ecosystem functioning. We argue that multiple
mechanisms will increase the extinction risk of species
at higher trophic levels. Assessing the relative importance of these mechanisms (e.g. is trophic position per se
important, Lawton 1995) would be an interesting academic exercise. Nevertheless, future research could focus
more closely on the consequences of extinctions at high
trophic levels. For example, loss of consumer 2 are the
most context-dependent (Fig. 4); is this model prediction
borne out in empirical data?
Ultimately, predicting a system’s capacity to maintain
fundamental properties will at least require knowledge of
the prevalence of omnivory, the manner in which species
richness is partitioned among trophic levels within the
community, and from where in the food web species are
lost. Total biodiversity loss and changes in ecosystem
functioning are not simply a product of a focal group of
species that are especially prone to extinction (whatever
the cause). Effects of losing such species may cascade
through food webs, leading to more extinctions. It
follows that impacts of species losses on ecosystem
processes such as primary production will ultimately be
the product of both trophic interactions (a release or
intensification of consumer effects) and extinctions that
476
cascade through the food web. The challenge for future
research will be to link all of these potential consequences of species loss to produce a general and
predictive framework for the consequences of species
loss in multitrophic system.
Acknowledgements / This manuscript is a product of the
Biodiversity in Multitrophic Systems Working Group at the
Aquatic Biodiversity and Ecosystem Functioning Workshop,
4 /7 April 2002, Ascona, Switzerland, funded by LINKECOL
(European Science Foundation; ESF), the US National Science
Foundation (NSF), DIVERSITAS, the Swiss National Science
Foundation (SNF), and the Swiss Federal Institute of
Environmental Science and Technology (EAWAG). Order of
authorship does not necessarily represent individuals’ relative
contributions. CFS performed the modelling and thanks
Richard Law for his expert advice on determining
permanence. GW compiled the data presented in Fig. 2 and 3
and thanks especially W. Beaumont and M. Lane for assistance.
GGM acknowledges support during manuscript preparation
from the National Center for Ecological Analysis and Synthesis,
a Center funded by the US NSF (Grant #DEB-0072909), the
University of California, and the Santa Barbara campus. OLP
was funded by a NERC Fellowship. Mark Gessner and Pablo
Inchausti commented on previous drafts of this article and
made significant improvements possible.
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