Complexity of multitrophic interactions in a grassland ecosystem depends on plant species diversity

1.?We studied the theoretical prediction that a loss of plant species richness has a strong impact on community interactions among all trophic levels and tested whether decreased plant species diversity results in a less complex structure and reduced interactions in ecological networks. 2.?Using plant species-specific biomass and arthropod abundance data from experimental grassland plots (Jena Experiment), we constructed multitrophic functional group interaction webs to compare communities based on 4 and 16 plant species. 427 insect and spider species were classified into 13 functional groups. These functional groups represent the nodes of ecological networks. Direct and indirect interactions among them were assessed using partial Mantel tests. Interaction web complexity was quantified using three measures of network structure: connectance, interaction diversity and interaction strength. 3.?Compared with high plant diversity plots, interaction webs based on low plant diversity plots showed reduced complexity in terms of total connectance, interaction diversity and mean interaction strength. Plant diversity effects obviously cascade up the food web and modify interactions across all trophic levels. The strongest effects occurred in interactions between adjacent trophic levels (i.e. predominantly trophic interactions), while significant interactions among plant and carnivore functional groups, as well as horizontal interactions (i.e. interactions between functional groups of the same trophic level), showed rather inconsistent responses and were generally rarer. 4.?Reduced interaction diversity has the potential to decrease and destabilize ecosystem processes. Therefore, we conclude that the loss of basal producer species leads to more simple structured, less and more loosely connected species assemblages, which in turn are very likely to decrease ecosystem functioning, community robustness and tolerance to disturbance. Our results suggest that the functioning of the entire ecological community is critically linked to the diversity of its component plants species.     

Direct and indirect interactions co‐determine species composition in nurse plant systems

Facilitation by nurse plants plays an important role in determining community composition in severe environments. Although the unidirectional effect of nurses on beneficiary species has received considerable research interest, nurse‐mediated interactions among beneficiary species (so‐called indirect interactions) are less known. Consequently, community composition in nurse plant systems is generally considered as a simple consequence of the facilitative effect of the nurse even though beneficiary species may significantly contribute to community assembly and modulate the direct nurse effects on the community. In an observational study we assessed nurse effects and nurse‐mediated beneficiary interactions in two contrasting nurse plant systems in dry environments using a newly developed framework. We quantified plant–plant interaction intensity using the relative interaction index (RII) at the community and species level for three Retama sphaerocarpa shrub size‐classes in a semiarid shrubland and four Arenaria tetraquetra cushion plant communities differing in aspect and elevation in dry alpine gravel habitats. The observed RII was split into nurse and beneficiary effects, and related to individual mass, species frequency and abundance using generalized linear mixed models. Results showed predominantly positive nurse effects and negative beneficiary interactions. The effect size of nurse plants, however, was significantly higher than the effect size of beneficiary species in both systems. Individual plant mass and abundance of species was dependent on the combined effects of nurse and beneficiary species whereas species occurrence was related to nurse effects only. Despite evident differences, the semiarid and alpine nurse plant systems showed strong functional parallelisms. We found interdependence between the effects of nurse and beneficiary species on beneficiary plant assemblages emphasizing their combined role on community assembly in both systems. Our results highlight the need to consider indirect interactions to understand fully plant community dynamics.     

Specialization, constraints, and conflicting interests in mutualistic networks

The topology of ecological interaction webs holds important information for theories of coevolution, biodiversity, and ecosystem stability . However, most previous network analyses solely counted the number of links and ignored variation in link strength. Because of this crude resolution, results vary with scale and sampling intensity, thus hampering a comparison of network patterns at different levels . We applied a recently developed quantitative and scale-independent analysis based on information theory to 51 mutualistic plant-animal networks, with interaction frequency as measure of link strength. Most networks were highly structured, deviating significantly from random associations. The degree of specialization was independent of network size. Pollination webs were significantly more specialized than seed-dispersal webs, and obligate symbiotic ant-plant mutualisms were more specialized than nectar-mediated facultative ones. Across networks, the average specialization of animal and plants was correlated, but is constrained by the ratio of plant to animal species involved. In pollination webs, rarely visited plants were on average more specialized than frequently attended ones, whereas specialization of pollinators was positively correlated with their interaction frequency. We conclude that quantitative specialization in ecological communities mirrors evolutionary trade-offs and constraints of web architecture. This approach can be easily expanded to other types of biological interactions.     

Beyond connectedness: why pairwise metrics cannot capture community stability

The connectedness of species in a trophic web has long been a key structural characteristic for both theoreticians and empiricists in their understanding of community stability. In the past decades, there has been a shift from focussing on determining the number of interactions to taking into account their relative strengths. The question is: How do the strengths of the interactions determine the stability of a community? Recently, a metric has been proposed which compares the stability of observed communities in terms of the strength of three‐ and two‐link feedback loops (cycles of interaction strengths). However, it has also been suggested that we do not need to go beyond the pairwise structure of interactions to capture stability. Here, we directly compare the performance of the feedback and pairwise metrics. Using observed food‐web structures, we show that the pairwise metric does not work as a comparator of stability and is many orders of magnitude away from the actual stability values. We argue that metrics based on pairwise‐strength information cannot capture the complex organization of strong and weak links in a community, which is essential for system stability.     

Detection of direct versus indirect effects: were experiments long enough?

To evaluate the hypothesis that indirect effects generally take much longer to become evident in manipulative studies of community regulation than do direct effects and thus may often be missed, I studied the effect of experiment duration in a survey of marine intertidal interaction webs. Contrary to expectation, indirect effects appeared either simultaneously with direct effects or shortly after direct effects were evident. While experiment durations varied greatly, on average most direct and indirect effects became statistically significant within the first 20%-40% of the total experiment duration. Further, the duration of most experiments appeared sufficient so that most indirect effects that would be generated by the manipulation could be observed. On average, a period of "constancy" (i.e., of no further change) lasting roughly 20%-60% of the total experiment duration occurred after the last indirect effect was observed. Experiment duration did not vary with web species richness, which suggests no tendency to perform manipulations for more (or less) time in more complex webs. The number of indirect effects per species did not increase with increasing experiment duration, nor did the number of longer interaction chains (four species vs. three species), which suggests no trends for increased complexity of indirect effects with longer experiments. Ecological theory states that, in interaction webs whose dynamics are imperfectly known, indirect effects may compromise the predictability of species manipulations. However, empirical results suggest that, despite incomplete knowledge of indirect effects, community dynamics may be more predictable than expected.     

Quantifying the interaction structure and the topological importance of species in food webs: A signed digraph approach

Due to the structural complexity of nature, it is not always easy to identify topologically importance species in an ecosystem. In the past decade, several studies in ecology have developed methods for measuring species importance basing on direct and indirect inter-specific interactions. Here, by extending a previously developed methodology, we present an approach that can quantify the interaction structure of a food web and consequently the topological importance of species when the food web is viewed as a signed digraph. The basic principle behind our approach is to determine the sign and strength of direct and indirect interactions for all pathways up to a predefined number of steps. Our approach mainly differs from the previous methodology in that we are able to quantify the strength of inter-specific interaction as well as in what way species interact with each other, as it can explicitly quantify a wide range of ecological interactions such as cascading effect, indirect food supply effect, apparent and exploitive competitions in the same framework. This then allows us to quantify the topological importance of a species and examine whether it is a predominately positive or negative interactor in a food web. Furthermore, our analysis reveals that positive and negative effects from one species on others eventually cancel each other out for longer pathways resulting in stable interaction structure. Applications of our methodology include providing a more informative index for conservation biologists, and the potential use of interaction structure derived from our approach in food web robustness studies is also discussed.     

Weighting and indirect effects identify keystone species in food webs

Species extinctions are accelerating globally, yet the mechanisms that maintain local biodiversity remain poorly understood. The extinction of species that feed on or are fed on by many others (i.e. ‘hubs’) has traditionally been thought to cause the greatest threat of further biodiversity loss. Very little attention has been paid to the strength of those feeding links (i.e. link weight) and the prevalence of indirect interactions. Here, we used a dynamical model based on empirical energy budget data to assess changes in ecosystem stability after simulating the loss of species according to various extinction scenarios. Link weight and/or indirect effects had stronger effects on food‐web stability than the simple removal of ‘hubs’, demonstrating that both quantitative fluxes and species dissipating their effects across many links should be of great concern in biodiversity conservation, and the potential for ‘hubs’ to act as keystone species may have been exaggerated to date.     

Using sensitivity analysis to identify keystone species and keystone links in size‐based food webs

Human‐induced alterations in the birth and mortality rates of species and in the strength of interactions within and between species can lead to changes in the structure and resilience of ecological communities. Recent research points to the importance of considering the distribution of body sizes of species when exploring the response of communities to such perturbations. Here, we present a new size‐based approach for assessing the sensitivity and elasticity of community structure (species equilibrium abundances) and resilience (rate of return to equilibrium) to changes in the intrinsic growth rate of species and in the strengths of species interactions. We apply this approach on two natural systems, the pelagic communities of the Baltic Sea and Lake Vättern, to illustrate how it can be used to identify potential keystone species and keystone links. We find that the keystone status of a species is closely linked to its body size. The analysis also suggests that communities are structurally and dynamically more sensitive to changes in the effects of prey on their consumers than in the effects of consumers on their prey. Moreover, we discuss how community sensitivity analysis can be used to study and compare the fragility of communities with different body size distributions by measuring the mean sensitivity or elasticity over all species or all interaction links in a community. We believe that the community sensitivity analysis developed here holds some promise for identifying species and links that are critical for the structural and dynamic robustness of ecological communities.     

Species–area relationships across four trophic levels – decreasing island size truncates food chains

That larger areas will typically host more diverse ecological assemblages than small ones has been regarded as one of the few fundamental ‘laws’ in ecology. Yet, area may affect not only species diversity, but also the trophic structure of the local ecological assemblage. In this context, recent theory on trophic island biogeography offers two clear‐cut predictions: that the slope of the species–area relationship should increase with trophic rank, and that food chain length (i.e. the number of trophic levels) should increase with area. These predictions have rarely been verified in terrestrial systems. To offer a stringent test of key theory, we focused on local food chains consisting of trophic specialists: plants, lepidopteran herbivores, and their primary and secondary parasitoids. For each of these four trophic levels, we surveyed species richness across a set of 20 off‐shore continental islands spanning a hundred‐fold range in size. We then tested three specific hypotheses: that species richness is affected by island size, that the slope of the species–area curve is related to trophic rank, and that such differences in slope translate into variation in food chain length with island size. Consistent with these predictions, estimates of the species–area slope steepened from plants through herbivores and primary parasitoids to secondary parasitoids. As a result of the elevated sensitivity of top consumers to island size, food chain length decreased from large to small islands. Since island size did not detectably affect the ratio between generalists and specialists among either herbivores (polyphages vs oligophages) or parasitoids (idiobionts vs koinobionts), the patterns observed seemed more reflective of changes in the overall number of nodes and levels in local food webs than of changes in their linking structure. Overall, our results support the trophic‐level hypothesis of island biogeography. Per extension, they suggest that landscape modification may imperil food web integrity and vital biotic interactions.     

A theory for species co-occurrence in interaction networks

The study of species co-occurrences has been central in community ecology since the foundation of the discipline. Co-occurrence data are, nevertheless, a neglected source of information to model species distributions and biogeographers are still debating about the impact of biotic interactions on species distributions across geographical scales. We argue that a theory of species co-occurrence in ecological networks is needed to better inform interpretation of co-occurrence data, to formulate hypotheses for different community assembly mechanisms, and to extend the analysis of species distributions currently focused on the relationship between occurrences and abiotic factors. The main objective of this paper is to provide the first building blocks of a general theory for species co-occurrences. We formalize the problem with definitions of the different probabilities that are studied in the context of co-occurrence analyses. We analyze three species interactions modules and conduct multi-species simulations in order to document five principles influencing the associations between species within an ecological network: (i) direct interactions impact pairwise co-occurrence, (ii) indirect interactions impact pairwise co-occurrence, (iii) pairwise co-occurrence rarely are symmetric, (iv) the strength of an association decreases with the length of the shortest path between two species, and (v) the strength of an association decreases with the number of interactions a species is experiencing. Our analyses reveal the difficulty of the interpretation of species interactions from co-occurrence data. We discuss whether the inference of the structure of interaction networks is feasible from co-occurrence data. We also argue that species distributions models could benefit from incorporating conditional probabilities of interactions within the models as an attempt to take into account the contribution of biotic interactions to shaping individual distributions of species.     

Effects of partitioning allochthonous and autochthonous resources on food web stability

The flux of energetic and nutrient resources across habitat boundaries can exert major impacts on the dynamics of the recipient food web. Competition for these resources can be a key factor structuring many ecological communities. Competition theory suggests that competing species should exhibit some partitioning to minimize competitive interactions. Species should partition both in situ (autochthonous) resources and (allochthonous) resources that enter the food web from outside sources. Allochthonous resources are important sources of energy and nutrients in many low productivity systems and can significantly influence community structure. The focus of this paper is on: (i) the influence of resource partitioning on food web stability, but concurrently we examine the compound effects of; (ii) the trophic level(s) that has access to allochthonous resources; (iii) the amount of allochthonous resource input; and (iv) the strength of the consumer–resource interactions. We start with a three trophic level food chain model (resource–consumer–predator) and separate the higher two trophic levels into two trophospecies. In the model, allochthonous resources are either one type available to both consumers and predators or two distinct types, one for consumers and one for predators. The feeding preferences of the consumer and predator trophospecies were varied so that they could either be generalists or specialists on allochthonous and/or autochthonous resources. The degree of specialization influenced system persistence by altering the structure and, therefore, the indirect effects of the food web. With regard to the trophic level(s) that has access to allochthonous resources, we found that a single allochthonous resource available to both consumers and predators is more unstable than two allochthonous resources. The results demonstrate that species populating food webs that experience low to moderate allochthonous resources are more persistent. The results also support the notion that strong links destabilize food web dynamics, but that weak to moderate strength links stabilize food web dynamics. These results are consistent with the idea that the particular structure, resource availability, and relative strength of links of food webs (such as degree of specialization) can influence the stability of communities. Given that allochthonous resources are important resources in many ecosystems, we argue that the influence of such resources on species and community persistence needs to be examined more thoroughly to provide a clearer understanding of food web dynamics.     

Unravelling the complex structure of forest soil food webs: higher omnivory and more trophic levels

Food web topologies depict the community structure as distributions of feeding interactions across populations. Although the soil ecosystem provides important functions for aboveground ecosystems, data on complex soil food webs is notoriously scarce, most likely due to the difficulty of sampling and characterizing the system. To fill this gap we assembled the complex food webs of 48 forest soil communities. The food webs comprise 89 to 168 taxa and 729 to 3344 feeding interactions. The feeding links were established by combining several molecular methods (stable isotope, fatty acid and molecular gut content analyses) with feeding trials and literature data. First, we addressed whether soil food webs (n = 48) differ significantly from those of other ecosystem types (aquatic and terrestrial aboveground, n = 77) by comparing 22 food web parameters. We found that our soil food webs are characterized by many omnivorous and cannibalistic species, more trophic chains and intraguild‐predation motifs than other food webs and high average and maximum trophic levels. Despite this, we also found that soil food webs have a similar connectance as other ecosystems, but interestingly a higher link density and clustering coefficient. These differences in network structure to other ecosystem types may be a result of ecosystem specific constraints on hunting and feeding characteristics of the species that emerge as network parameters at the food‐web level. In a second analysis of land‐use effects, we found significant but only small differences of soil food web structure between different beech and coniferous forest types, which may be explained by generally strong selection effects of the soil that are independent of human land use. Overall, our study has unravelled some systematic structures of soil food‐webs, which extends our mechanistic understanding how environmental characteristics of the soil ecosystem determine patterns at the community level.     

Topological properties of food webs: from real data to community assembly models

We explore patterns of trophic connections between species in the largest and highest-quality empirical food webs to date, introducing a new topological property called the link distribution frequency (i.e. degree distribution), defined as the frequency of species S _L with L links. Non-trivial differences are shown in link distribution frequencies between species-rich and species-poor communities, which might have important consequences for the responses of ecosystems to disturbances. Coarse-grained topological properties observed, as species richness-connectance and number of links-species richness relationships, provide no support for the theory of links-species scaling law or constant connectance across empirical food webs investigated. We further explore these observations by means of simulated food webs resulting from multitrophic assembly models using different functional responses between species. Species richness-connectance and links-species richness relationships of empirical food webs are reproduced by our models, but degree distributions are not properly predicted, suggesting the need of new theoretical approximations to food web assembly. The best agreement between empirical and simulated webs occurs for low values of interaction strength between species, corroborating previous empirical and theoretical findings where weak interactions govern food web dynamics.     

Review Behaviour and indirect interactions in food webs of plant-inhabiting arthropods

With the increased use of biological control agents, artificial food webs are created in agricultural crops and the interactions between plants, herbivores and natural enemies change from simple tritrophic interactions to more complex food web interactions. Therefore, herbivore densities will not only be determined by direct predator–prey interactions and direct and indirect defence of plants against herbivores, but also by other direct and indirect interactions such as apparent competition, intraguild predation, resource competition, etc. Although these interactions have received considerable attention in theory and experiments, little is known about their impact on biological control. In this paper, we first present a review of indirect food web interactions in biological control systems. We propose to distinguish between numerical indirect interactions, which are interactions where one species affects densities of another species through an effect on the numbers of an intermediate species and functional indirect interactions, defined as changes in the way that two species interact through the presence of a third species. It is argued that functional indirect interactions are important in food webs and deserve more attention. Subsequently, we discuss experimental results on interactions in an artificial food web consisting of pests and natural enemies on greenhouse cucumber. The two pest species are the two-spotted spider mite Tetranychus urticae and the western flower thrips, Frankliniella occidentalis. Their natural enemies are the predatory mite Phytoseiulus persimilis, which is commonly used for spider mite control and the predatory mites Neoseiulus cucumeris and Iphiseius degenerans and the predatory bug Orius laevigatus, all natural enemies of thrips. First, we analyse the possible interactions between these seven species and we continue by discussing how functional indirect interactions, particularly the behaviour of arthropods, may change the significance and impact of direct interactions and numerical indirect interactions. It was found that a simple food web of only four species already gives rise to some quite complicated combinations of interactions. Spider mites and thrips interact indirectly through resource competition, but thrips larvae are intraguild predators of spider mites. Some of the natural enemies used for control of the two herbivore species are also intraguild predators. Moreover, spider mites produce a web that is subsequently used by thrips to hide from their predators. We discuss these and other results obtained so far and we conclude with a discussion of the potential impact of functional indirect and direct interactions on food webs and their significance for biological control.     

Temperature‐size responses alter food chain persistence across environmental gradients

Body‐size reduction is a ubiquitous response to global warming alongside changes in species phenology and distributions. However, ecological consequences of temperature‐size (TS) responses for community persistence under environmental change remain largely unexplored. Here, we investigated the interactive effects of warming, enrichment, community size structure and TS responses on a three‐species food chain using a temperature‐dependent model with empirical parameterisation. We found that TS responses often increase community persistence, mainly by modifying consumer‐resource size ratios and thereby altering interaction strengths and energetic efficiencies. However, the sign and magnitude of these effects vary with warming and enrichment levels, TS responses of constituent species, and community size structure. We predict that the consequences of TS responses are stronger in aquatic than in terrestrial ecosystems, especially when species show different TS responses. We conclude that considering the links between phenotypic plasticity, environmental drivers and species interactions is crucial to better predict global change impacts on ecosystem diversity and stability.     

Topological keystone species: measures of positional importance in food webs

The local extinction or large fluctuation in abundance of a species may seriously affect other species in the community. The effects spread through the community by direct and indirect interactions. The network perspective on ecology can help map the pathways of these effects, for food webs, the pathways of indirect trophic interactions. Indirect interactions typically decay in intensity as they spread. Therefore, there is a conceptual maximum range in topological space beyond which interactions have no effects, even though all species remain connected. Neither the local characteristics of species, nor the global characteristics of entire webs, suitably quantify this range. We therefore apply intermediate scale indices that reflect the limitations imposed by effect damping in networks. We present a complex analysis of the topological positional importance of species in the Chesapeake Bay web. This web is a carbon-flow network that represents trophic interactions. We present several different indices reflecting different properties and discuss which questions the different indices best answer. We look for the best indices for identifying the key players in ecosystem functioning. Our study contributes to the quantification of relative species importance and provides an exact and a priori determination of a class of candidate keystone species that can inform applied and conservation ecology as well as theoretical concerns.     

Human disease mortality kinetics are explored through a chain model embodying principles of extreme value theory and competing risks.

The distributions for human disease-specific mortality exhibit two striking characteristics: survivorship curves that intersect near the longevity limit; and, the clustering of best-fitting Weibull shape parameter values into groups centered on integers. Correspondingly, we have hypothesized that the distribution intersections result from either competitive processes or population partitioning and the integral clustering in the shape parameter results from the occurrence of a small number of rare, rate-limiting events in disease progression. In this report we initiate a theoretical examination of these questions by exploring serial chain model dynamics and parameteric competing risks theory. The links in our chain models are composed of more than one bond, where the number of bonds in a link are denoted the link size and are the number of events necessary to break the link and, hence, the chain. We explored chains with all links of the same size or with segments of the chain composed of different size links (competition). Simulations showed that chain breakage dynamics depended on the weakest-link principle and followed kinetics of extreme-values which were very similar to human mortality kinetics. In particular, failure distributions for simple chains were Weibull-type extreme-value distributions with shape parameter values that were identifiable with the integral link size in the limit of infinite chain length. Furthermore, for chains composed of several segments of differing link size, the survival distributions for the various segments converged at a point in the S(t) tails indistinguishable from human data. This was also predicted by parameteric competing risks theory using Weibull underlying distributions. In both the competitive chain simulations and the parametric competing risks theory, however, the shape values for the intersecting distributions deviated from the integer values typical of human data. We conclude that rare events can be the source of integral shapes in human mortality, that convergence is a salient feature of multiple endpoints, but that pure competition may not be the best explanation for the exact type of convergence observable in human mortality. Finally, while the chain models were not motivated by any specific biological structures, interesting biological correlates to them may be useful in gerontological research.     

Predator diversity and environmental change modify the strengths of trophic and nontrophic interactions

Understanding the dependence of species interaction strengths on environmental factors and species diversity is crucial to predict community dynamics and persistence in a rapidly changing world. Nontrophic (e.g. predator interference) and trophic components together determine species interaction strengths, but the effects of environmental factors on these two components remain largely unknown. This impedes our ability to fully understand the links between environmental drivers and species interactions. Here, we used a dynamical modelling framework based on measured predator functional responses to investigate the effects of predator diversity, prey density, and temperature on trophic and nontrophic interaction strengths within a freshwater food web. We found that (i) species interaction strengths cannot be predicted from trophic interactions alone, (ii) nontrophic interaction strengths vary strongly among predator assemblages, (iii) temperature has opposite effects on trophic and nontrophic interaction strengths, and (iv) trophic interaction strengths decrease with prey density, whereas the dependence of nontrophic interaction strengths on prey density is concave up. Interestingly, the qualitative impacts of temperature and prey density on the strengths of trophic and nontrophic interactions were independent of predator identity, suggesting a general pattern. Our results indicate that taking multiple environmental factors and the nonlinearity of density‐dependent species interactions into account is an important step towards a better understanding of the effects of environmental variations on complex ecological communities. The functional response approach used in this study opens new avenues for (i) the quantification of the relative importance of the trophic and nontrophic components in species interactions and (ii) a better understanding how environmental factors affect these interactions and the dynamics of ecological communities.     

Community assembly, stability and signatures of dynamical constraints on food web structure

To understand the dynamics of natural species communities, a major challenge is to quantify the relationship between their assembly, stability, and underlying food web structure. To this end, two complementary aspects of food web structure can be related to community stability: sign structure, which refers to the distributions of trophic links irrespective of interaction strengths, and interaction strength structure, which refers to the distributions of interaction strengths with or without consideration of sign structure. In this paper, using data from a set of relatively well documented community food webs, I show that natural communities generally exhibit a sign structure that renders their stability sensitive to interaction strengths. Using a Lotka-Volterra type population dynamical model, I then show that in such communities, individual consumer species with high values of a measure of their total biomass acquisition rate, which I term “weighted generality”, tend to undermine community stability. Thus consumer species’ trophic modules (a species and all its resource links) should be “selected” through repeated immigrations and extinctions during assembly into configurations that increase the probability of stable coexistence within the constraints of the community's trophic sign structure. The presence of such constraints can be detected by the incidence and strength of certain non-random structural characteristics. These structural signatures of dynamical constraints are readily measurable, and can be used to gauge the importance of interaction-driven dynamical constraints on communities during and after assembly in natural communities.