Intermediate predator impact on consumers weakens with increasing predator diversity in the presence of a top-predator

acta oecologica 31 (2007) 79–85

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Original article

Intermediate predator impact on consumers weakens with increasing predator diversity in the presence of a top-predator Micael Jonssona,b,*, Frank Johanssonb, Cecilia Karlssonb, Tomas Brodinb a

Department of Forest Vegetation Ecology, SLU, SE-90183 Umea˚, Sweden Department of Ecology and Environmental Science, Umea˚ University, SE-90187 Umea˚, Sweden

b

article info

abstract

Article history:

Adding or removing a top-predator is known to affect lower trophic levels with potentially

Received 14 February 2006

large, indirect effects on primary production. However, little is known about how predator

Accepted 3 October 2006

diversity may affect lower trophic levels, or how adding or removing a top-predator influ-

Published online 12 January 2007

ences the effects of predator diversity. Using aquatic mesocosms containing three and four trophic levels, we tested whether intermediate predator diversity affected predation

Keywords:

on consumers and if top-predator presence influenced such effects. We found that the

Aquatic

presence of intermediate predators suppressed the consumer population and that this

Dragonfly

suppression tended to increase with increased intermediate predator diversity when the

Non-lethal

top-predator was absent. However, with the top-predator present, increased intermediate

Trait-mediated indirect interactions

predator diversity showed the opposite effect on the consumers compared to without a

Predator–prey interactions

top-predator, i.e. decreased suppression of consumers with increased diversity. Hence, in

Zooplankton

our study, the loss of intermediate predator species weakened or strengthened predator– prey interactions depending on if the top-predator was present or not, while loss of the top-predator only strengthened the predator–prey interactions. Therefore, the loss of a predator species may render different, but perhaps predictable effects on the functioning of a system depending on from which trophic level it is lost and on the initial number of species in that trophic level. ª 2006 Elsevier Masson SAS. All rights reserved.

1.

Introduction

Trophic cascades, where predators indirectly affect primary production via direct effects on consumers, are well known phenomena that occur in a wide variety of systems (Shurin et al., 2002). Food web complexity is thought to affect the

amplitude and direction of the trophic cascades (Shurin et al., 2002). Since food web complexity is formed by the species and their interactions, it is likely that both diversity and composition, and the effect of these on species interactions, are important factors for trophic cascades. In a simple, 3-level linear system, food web theory predicts that the predator

* Corresponding author. Department of Forest Vegetation Ecology, SLU, SE-90183 Umea˚, Sweden. Tel.: þ46 90 786 8601; fax: þ46 90 786 8166. E-mail address: [email protected] (M. Jonsson). 1146-609X/$ – see front matter ª 2006 Elsevier Masson SAS. All rights reserved. doi:10.1016/j.actao.2006.10.007

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acta oecologica 31 (2007) 79–85

suppresses the consumers, thus indirectly benefiting primary production (Carpenter et al., 1985). However, the addition of a top-predator, a fourth trophic level, might weaken the intermediate predator’s effect on the consumers leading to increased suppression of primary production (Abrams, 1995). In addition to adding or removing top-trophic levels, also adding or removing species within trophic levels may affect lower trophic levels. However, effects of such experimental manipulations have been equivocal, hence more debated (Hector et al., 2000; Huston et al., 2000), and little is known about how important such changes are for the nature of trophic cascades (however, see Finke and Denno, 2004, 2005; Duffy et al., 2005; Byrnes et al., 2006). Considering the rapid, global extinction of species that we currently are experiencing, it is essential to investigate how diversity and composition, both intra- and inter-trophically, and especially in combination, affect trophic cascades, thus ecosystem functioning. Food web theory proposes two mechanistic explanations for how predator–prey interactions indirectly affect primary production. One mechanism referred to as density mediated indirect interactions (DMIIs) states that the direct numerical reduction of consumer populations by predation is the principal cause of indirect effects on primary producers (Abrams, 1995; Werner and Peacor, 2003). A second mechanism states that trait-mediated indirect interactions (TMIIs) are important for the strengths of predator–prey interactions and subsequent effects on primary production (Kerfoot and Sih, 1987; Abrams, 1995; Werner and Peacor, 2003). TMII strategies may involve decreased foraging activity of the consumers resulting in lower impact on primary producers. One way of studying the importance of TMIIs is to prevent direct predation (Schmitz et al., 2004), for example by using non-lethal predators. Both DMIIs and TMIIs are widespread and well documented in freshwater pond/lake systems (e.g. Hrba´cek et al., 1961; Huang and Sih, 1990; Carpenter and Kitchell, 1993; Peacor and Werner, 2000). A common, generalised, aquatic, trophic system can be viewed as a 4-level system with fish as top-predators, large invertebrates as intermediate predators, small invertebrates as consumers and phytoplankton as primary producers. At each of these levels there exists a wide variety of species that interact both within and between trophic levels. The numbers of species and the interactions they participate in, such as facilitation, niche complementarity or competition, have been shown to affect ecosystem functioning (see Loreau et al., 2001, for a review). However, few studies have considered how the diversity within trophic levels affects lower trophic levels in aquatic systems. Those few studies that have done so have focused only on a 2-level trophic system and with very few species within each trophic level (e.g. Sih et al., 1998; Eklo¨v and Werner, 2000; Eklo¨v and VanKooten, 2001; Duffy et al., 2003, 2005; Gamfeldt et al., 2005). Dragonfly larvae are common inhabitants in freshwater systems and they are important food for fish while also having impact on abundance and diversity of prey communities (Butler, 1989; Rask, 1986; Larson, 1990; Burks et al., 2000). Within the dragonfly larvae guild, predation, cannibalism, interference and exploitation competition have been shown to occur and the outcome of these interactions are species specific ( Van Buskirk, 1989; Johnson, 1991; Johansson, 1993a). For

example, some species are more efficient intra-guild predators than others (Wissinger, 1988), and some species are more efficient predators on zooplankton than others (Stoks et al., 2003). Similarly, though predation by fish on dragonfly larvae is ubiquitous, dragonfly larvae species differ in their vulnerability to fish predation and in their anti-predator behaviour response to fish predators (Pierce, 1988; Stoks et al., 2003). Since dragonfly larvae exhibit this variety in behaviour and interactions, and since they have an intermediate position in aquatic food webs, they are suitable organisms to use in studies on how the effect of predator diversity at one trophic level affects trophic cascades and if those effects are altered when a higher trophic level is introduced. In this study we manipulated the number of species of intermediate predators in the presence and absence of a non-lethal top-predator, and examined how these manipulations affected the growth and mortality of the intermediate predators, and the density of the consumers. Our purpose was not to distinguish between DMIIs and TMIIs by the top-predator, so we used only a non-lethal predator to exclude possible density mediated effects from the top-predator level while possible trait-mediated effects remained. Even though intermediate predator species may vary in response to the presence of a non-lethal top-predator (Richardson, 2001; Stoks et al., 2003), we assumed that the average response would be similar in low- and high-diversity treatments (Fig. 1). This assumption can be made since, in our experimental setup, all intermediate predator species were included in both the one- and four-species treatments (but not in the two-species treatment), the total density of intermediate predators was constant across treatments, and the top-predator was nonlethal disallowing for any direct effects on intermediate predator species densities. In addition, our focus was not on the mechanisms behind effects of diversity at the intermediate predator level. Instead, we focused on how diversity per se at the intermediate trophic level affects predator–prey interactions. Compared to a species-poor predator system, a speciesrich system should represent a wider spectrum of predator strategies that is more efficient at suppressing the consumer population (e.g. Naeem and Li, 1997; Duffy et al., 2003; Gamfeldt et al., 2005), and the addition of a non-lethal top-predator

Non-lethal top-predator Intermediate predator Consumer A

B

C

D

Fig. 1 – Illustrations of the four different systems in our study: (A) low intermediate predator diversity, (B) high intermediate predator diversity (C) low intermediate predator diversity with non-lethal predator present, and (D) high intermediate predator diversity with non-lethal predator present. The arrows represent predicted impact of predators on consumersdthe arrow thickness showing the strength of the impact. Dashed arrows represent non-lethal impacts (trait-mediated indirect interaction).

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acta oecologica 31 (2007) 79–85

is expected to lower the level of impact of the intermediate predators on the consumer (e.g. Schmitz, 2003). Therefore we predicted that the intermediate predator would suppress the consumer population (‘A’, Fig. 1), and the addition of intermediate predator species would increase predation, leading to a stronger suppression of the consumer population (‘B’, Fig. 1). Adding a non-lethal top-predator would lead to weakened predator–prey interactions (‘C’ and ‘D’, Fig. 1). According to the above expectations combined, we therefore predict that ‘B’ would show the strongest predator–prey interactions, followed by ‘D’, ‘A’ and, with the weakest interactions, ‘C’ (Fig. 1). Hence, in freshwater pond systems loss of a top-predator species should increase the strength of the predator–prey interactions while loss of intermediate species will weaken the predator–prey interactions. Our experimental setup enabled us test our predictions.

2.

Materials and methods

2.1.

Study methods

The experiment was run for 66 days in 36 aerated containers (65 L, 53 cm diameter) covered with fine fabric to prevent immigration of insects. Before the start of the experiment, the containers were filled with non-chlorinated tap water. As a basal resource and substrate, grass (29.0  1 g) was put into each container along with 2 L of filtered (0.5 mm mesh) pond water providing a natural assemblage of zooplankton species. One week before introducing the predators an additional 100 Daphnia magna Straus were introduced into each container, to ensure sufficient consumer population levels. Five species of dragonflies (Odonata) were used in the experiment, viz. Coenagrion hastulatum Charpentier, Erythromma najas Hansemann, Enallagma cyathigerum Charpentier, Libellula quadrimaculata L., and Leucorrhinia dubia Van der Linden. These species were used since they are common and coexist regularly in the waters in the area (Johansson, 1993b; Johansson and Brodin, 2003). The dragonflies were collected as eggs in June and July. Dragonflies were caught when mating pairs were flying in tandem. Females of species ovipositing in vegetation were placed in glass jars with moist filter paper in which the eggs were deposited within a couple of days. Ovipositing by females of species that deposit eggs directly into the water was stimulated by dipping the abdomen in water-filled glass jars. The filter papers containing eggs and the eggs suspended in water were placed in water-filled, aerated containers. After approximately 3 weeks, the larvae hatched. Since collection of egg-laying females took more than a month, the water temperature in the hatching chambers was manipulated so that the hatching of the larvae was synchronised. The larvae were fed laboratory cultured Brine shrimp (Artemia) before the start of the experiment. When all larvae were hatched, they were combined in diversity treatments (using different species compositions except for one four-species composition that was replicated twice) with a total of 20 individuals in each treatment (Table 1). Each diversity treatment (1, 2 and 4) was replicated five times each in the fish and fishless treatment leading to a total of 30

Table 1 – Species compositions used in the diversity treatments. The setup was used in both the fish and the fishless treatments Diversity 1 2 4

Species combinations a a, d a, b, c, d

b b, d a, b, c, d

c a, b a, b, c, e

d a, c a, b, d, e

e b, c a, b, d, e

Small letters stand for: a ¼ C. hastulatum, b ¼ E. cyathigerum, c ¼ E. najas, d ¼ L. dubia and e ¼ L. quadrimaculata.

containers. In addition, six water-filled containers with only the basal resource and zooplankton were used as controls. Average initial dry mass of each larval species was estimated from five individuals before the start of the experiment. This initial biomass estimate was subtracted from final biomass to obtain growth of each individual during the experiment. The experiment was initiated outdoors in an experimental field arena August 12. The non-lethal top-predator was held in a plastic cylinder (20 cm long, 11.2 cm diameter) submerged into each container. A nylon string was tied around each cylinder to make them easy to pick up and a small rock was placed into each cylinder to submerge them. In 15 of the 36 containers a second-year perch (Perca fluviatilis L.) was placed. The fishless containers had an empty cylinder. The open sides of the cylinders were covered with fine mesh (0.25 mm), attached with rubber bands, to prevent the fish from escaping from the cylinder while providing for water exchange and oxygenation in the cylinders. To neutralise fertilisation effects caused by fish presence, 0.11 g of chicken food was ˚ bjo¨rnsson introduced into the fishless containers (e.g. A et al., 2002). Lastly, the dragonfly larvae were introduced into the containers. The perch were fed 4–6 damselfly larvae twice a week both as food and to stimulate anti-predator response among the free-living dragonfly larvae in the containers. Every week, samples of zooplankton were taken by extracting 2 L of water. The water was filtered through a mesh (0.5 mm) to collect the zooplankton that later were preserved in 70% ethanol and counted under a microscope. Due to subzero temperatures the experiment was moved indoors September 16 to a room with controlled temperature (20  C) and light (10 h daylight). Shortly after moving the containers indoors, some of the perch died. Unsuccessful attempts to collect new perch were made. Instead, the remaining perch were alternated between the fish containers every fifth day. Also, live damselfly larvae were ground and put into the fish containers to simulate chemicals produced from perch feeding on dragonflies. The experiment was terminated October 15. The containers were emptied so that the dragonflies could be collected, and subsequently preserved in 70% alcohol before being dried at 60  C for 48 h and weighed.

2.2.

Statistical methods

To account for the variance in zooplankton densities caused by moving the experiment from outdoors to indoors, average values from the outdoor and indoor measurements were

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acta oecologica 31 (2007) 79–85

500 450

(a)

Fish Fishless

400

Control

350 300 250

Zooplankton density (individuals * subsample-1)

used in the analysis (‘location’ as a factor). For all analyses a mixed model, nested design was used with fish, diversity, and composition nested within diversity as fixed factors. This statistical design enables separation of diversity and composition effects (e.g. Jonsson and Malmqvist, 2000). To isolate the effects of dragonfly diversity and composition, and fish presence/absence, and to take possible effects of resource depletion into account, zooplankton density (resource level) was used as covariate for the analysis on per capita growth of the dragonfly larvae. Since biomass differences between individuals may increase intra-guild predation, and to isolate the effects of dragonfly diversity and composition, and fish presence/absence, we used per capita final biomass of the dragonfly larvae as covariate for the analysis of dragonfly survival. The results are presented after removing non-significant interactions (P > 0.2) in the analyses (Winer, 1971). To compare mean zooplankton densities in the different diversity treatments, LSD post hoc comparisons were performed. To compare mean zooplankton densities in controls and treatments with or without fish, two-tailed t-tests were performed. For all analyses SPSS 11.0 for Mac OS X was used.

200 150 100 50 0

250

(b)

200

150

3.

Results

In the mixed model analysis, neither dragonfly diversity nor composition had a significant effect on zooplankton densities, while fish, location and the interaction between dragonfly diversity and fish did (Table 2a). There was no difference due to fish presence in the single-species treatments suggesting that the effect of fish presence was weak when the dragonfly species were single (Fig. 2), though this lack of difference between

100

50

0 1

2

4

C

Species richness

Table 2 – Mixed model analyses on effects of dragonfly diversity, dragonfly composition, fish presence and location on (a) zooplankton density, (b) dragonfly growth and (c) dragonfly survival. Sp. ID stands for species composition (nested within diversity) and Location for indoor/outdoors measurements Source

Numerator Denominator df df

F

P

a Diversity Sp. ID (Diversity) Fish Location Diversity  Fish

2 10 1 1 2

43 43 43 43 43

2.02 0.145 1.75 0.101 10.72 <0.005 52.65 <0.001 3.61 <0.05

b Diversity Sp. ID (Diversity) Fish Zooplankton density

2 10 1 1

15 15 15 15

4.74 <0.05 9.58 <0.001 5.06 <0.05 1.77 0.203

c Diversity Sp. ID (Diversity) Fish Biomass

2 10 1 1

16 16 15 16

0.85 0.447 3.28 <0.05 0.49 0.495 2.05 0.942

Fig. 2 – Average zooplankton density in relation to dragonfly diversity for both the fish and fishless treatments, and for controls, (a) outdoors and (b) indoors. Error bars represent average ± 1 S.E.

treatments could also result from the addition of fertilisers in the fishless treatment over-compensating for the fertilising effects of fish presence on zooplankton growth in the fish treatment. Hence, it is possible that the indirect effects of fish on zooplankton densities are underestimated throughout the study, since zooplankton densities may have been fertilised to levels somewhat higher than to compensate for the fertilising effect of fish. The significant interaction between fish and dragonfly diversity is noticeable in trends of increased zooplankton density with increased dragonfly diversity in the presence of fish, and decreased zooplankton density with increased diversity without fish (Fig. 2). However, despite these trends, there were only significant differences towards the end of the study between the one- and four-species treatments in the presence of fish (P < 0.05, Fig. 2b), and between the one- and two-species treatments in the absence fish (P < 0.01, Fig. 2b). Moving the experiment indoors resulted in a significant decrease in zooplankton densities, most likely due to lower light levels (Fig. 2). The lower light levels most

acta oecologica 31 (2007) 79–85

likely affected phytoplankton growth negatively, which in turn had a negative effect on the zooplankton population. If we had chosen to leave the experiment outdoors it probably would have resulted in a similar crash in zooplankton densities due to decreasing water temperatures (e.g. Loiterton et al., 2004). Nevertheless, the significant effects of fish and the interaction between fish and dragonfly diversity remained significant after moving the experiment indoors despite the drop in zooplankton densities (all interactions with ‘location’, P > 0.2). Diversity, composition and fish showed significant effects on per capita dragonfly growth (Table 2b). However, although the fishless treatment always showed higher growth than in the fish treatment, the relationship between growth and diversity was U-shaped rather than linear (Fig. 3). The survival percentages of the dragonfly larvae in the fish treatment were 40.0  8.5, 36.0  6.4 and 37.3  1.9 for the one-, twoand four-species treatments, respectively. Without fish, the corresponding numbers were 42.7  6.9, 42.0  4.9 and 36.0  2.9. Species composition showed a significant effect on dragonfly survival, while diversity and biomass was nonsignificant (Table 2c). In the beginning of the study, zooplankton densities were highly variable between the containers and both within and across treatments, and the control treatments did not always contain the highest density of zooplankton (Fig. 2). On the last two sample dates, when the zooplankton densities were stabilised across all treatments, the zooplankton densities in the fish treatments did not differ significantly from the densities in the controls (121.2  9.0 and 133.7  26.2 respectively; P > 0.05, in two-tailed t-test assuming unequal variances), which indicate low predation by the intermediate predator due to fish presence. In contrast, the zooplankton densities were lower in the fishless treatment than in the control (60.2  6.1 and 133.7  21.6, respectively; P < 0.05, in two-

3.0 Fish Fishless

Growth (mg * individual-1)

2.5

2.0

1.5

1.0

0.5

0 1

2

4

Species richness Fig. 3 – The relationship between dragonfly diversity and dragonfly growth during the experiment for both the fish and fishless treatment. Error bars represent average ± 1 S.E.

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tailed t-test assuming unequal variances) indicating higher predation on the zooplankton than in the fish treatments.

4.

Discussion

The dragonfly larvae had a significant, negative effect on the zooplankton densities in the absence of fish, compared to the zooplankton densities in the controls. With fish present, the zooplankton densities were not different from those in the controls, supporting our predictions that fish presence would weaken the effect of the intermediate predators on the consumers. In the fishless treatment, the zooplankton density was lower in the two-species treatment compared to the one-species treatment towards the end of the study, giving some support to our prediction that increased dragonfly diversity would strengthen their impact on the consumers (Fig. 2b). However, with fish present there was, in contrast to our predictions, a significant weakening of the predator impact (i.e. increased zooplankton densities) with increased predator diversity (Fig. 2b). Hence, the fish presence seems to have changed the way in which the dragonfly species interacted with each other leading to lowered predation with higher predator diversity and, thus, weakened predator effects on consumers compared to when fish was absent. Possibly, there was an increased inter-specific interference with diversity (e.g. Jonsson and Malmqvist, 2003) among the dragonflies in the presence of fish caused by crowding in refugia. Dragonfly larvae show a decrease in foraging rate under crowded conditions, because the sight of other larvae inhibits feeding (Crowley et al., 1988; Van Buskirk, 1993). Inter-specific interference has been found to be stronger than intra-specific interference among predators due to larger individual size differences between than within species leading to an increased risk of intra-guild predation (e.g. Wissinger, 1988; Johansson, 1993a; Wissinger and McGrady, 1993). Therefore, if interspecific size differences exist, individuals in multi-species assemblages should experience stronger levels of interference leading to more inhibited feeding than among individuals in single-species assemblages where individuals are similar in size. Increased intra-guild predation and cannibalism among the dragonflies may cause reductions in inter-guild predation (e.g. Robinson and Wellborn, 1987), but in this study any interspecific interference with effects on predation on zooplankton seems to have been non-lethal since there were no significant differences in dragonfly mortality between the fish and fishless treatments. Our results show, besides effects of density and composition of species (e.g. Peacor and Werner, 2004), that diversity may affect the indirect impact of top-predator presence on consumer populations. The obtained results suggest that the loss of a non-lethal predator from a system with several intermediate predator species causes a strengthening of predator impact on the consumers, since the consumer densities go from high to low, similar to the effect of removing a lethal predator (e.g. Abrams, 1995). In the presence of a non-lethal top-predator, the loss of intermediate predator species led to increased predator impact on the consumers, which is in contrast to what we predicted. The fact that the significant effects of fish and the interaction between fish and dragonfly

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diversity on zooplankton density remained significant despite a drop in zooplankton densities after moving the study indoors, suggests that the top-predator had a stronger influence on the intermediate predators’ predation rate than the consumer (resource) densities had. Accordingly, dragonfly growth was not significantly affected by zooplankton densities (Table 2b). Our results can be compared with results obtained by Finke and Denno (2004). They found that increased predator diversity weakened the predator–prey interactions in a system of zero, one or multiple lethal predators. Their conclusion is in conflict with our results from the fishless treatment where we found somewhat strengthened predator–prey interactions with increased diversity of the intermediate predator, but as we added one top-predator to the system we found similar results to theirs. However, in their treatment containing multiple predator species they included one species that could be argued to be a top-predator since it fed on all the other predator species and on the consumers, and they had no treatment controlling for top-predator effects as we did. Hence, their results showing a weakening of predator–prey interactions with increased predator diversity could have been an effect of adding a top-trophic level to the system when increasing predator diversity (e.g. Abrams, 1995). Consequently, in a more recent study the suppression of consumers by predators weakened with increasing predator diversity when intra-guild predators were included (Finke and Denno, 2005). In a study by Duffy et al. (2005) on diversity effects in an estuarine system, it was found that grazer diversity enhanced consumption of algae, but only in the presence of a top-predator. Thus, their results are the opposite of what we found. However, their study system differs from ours in at least two important ways. First, they used a lethal top-predator that, besides suppressing overall grazing rates via TMII, more successfully reduced the grazer density in the low-diversity treatment than in the high diversity treatment. This density reduction resulted in lower grazing in the low-diversity treatment compared to in the high-diversity treatment where poor predation success led to grazing being similar to that of the treatment without a top-predator. Second, grazers probably interact quite differently both intra- and inter-specifically compared to the predator species we used. In our system, we suggest that top-predator presence led to increased inter-specific interference with increased diversity. Since grazers lack intra-guild predation, the presence of a top-predator is likely to have other effects on grazing than the ones we found on predation. As expected from the zooplankton results, the dragonfly growth was significantly higher in the absence of fish since higher consumption, shown by lower zooplankton densities, in general led to higher growth among the dragonflies. However, dragonfly growth in each diversity treatment deviated somewhat from what might be expected from the zooplankton densities. Although diversity significantly affected growth, the trends between diversity and growth were not like those found between diversity and zooplankton density. Instead, the pattern was rather U-shaped, and there were noticeable deviations from expected growth in the single-species treatment without fish and in the four-species treatment with fish - both showing growth higher than expected. This U-shaped pattern may be an effect of species composition

since L. quadrimaculata, which was larger in size that the other species, was used only in the one- and four-species treatments. Hence, since composition was of significant importance for both growth and survival, but not for zooplankton densities, the different effect of diversity on growth from that on zooplankton density may be due to the presence/absence of this species. However, we do not have any mechanistic explanations for the results on dragonfly biomass.

5.

Conclusion

Our results suggest that a non-lethal top-predator via TMIIs not only may induce significant effects on predator–prey interactions at lower trophic levels, but also change interspecific interactions among intermediate predators. In combination, both these effects of top-predator presence may result in a strong weakening of the predator–prey interactions. Hence, not only presence or absence of certain species may be important for the effect of higher trophic levels on lower trophic levels, also diversity and the interaction between diversity and trophic levels might matter. Losing a top-predator species may strengthen predator–prey interactions, while losing intermediate predator species may result in strengthened or weakened predator–prey interactions, depending on whether a top-predator is present or not. Therefore, although effects of species loss on ecosystem functioning may differ depending on which species is lost, the effects may be somewhat predictable due to the trophic position of the lost species and on the structure of the food web from which the species loss occurs.

Acknowledgements We thank Maano Aunapuu and Jon Moen for helpful comments on the manuscript. Financial support was provided by the Swedish Research Council (F.J.) and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (M.J.).

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