What constrains food webs? A maximum entropy framework for predicting their structure with minimal biases.

Food webs are complex ecological networks whose structure is both ecologically and statistically constrained, with many network properties being correlated with each other. Despite the recognition of these invariable relationships in food webs, the use of the principle of maximum entropy (MaxEnt) in network ecology is still rare. This is surprising considering that MaxEnt is a statistical tool precisely designed for understanding and predicting many types of constrained systems. This principle asserts that the least-biased probability distribution of a system's property, constrained by prior knowledge about that system, is the one with maximum information entropy. MaxEnt has been proven useful in many ecological modeling problems, but its application in food webs and other ecological networks is limited. Here we show how MaxEnt can be used to derive many food-web properties both analytically and heuristically. First, we show how the joint degree distribution (the joint probability distribution of the numbers of prey and predators for each species in the network) can be derived analytically using the number of species and the number of interactions in food webs. Second, we present a heuristic and flexible approach of finding a network's adjacency matrix (the network's representation in matrix format) based on simulated annealing and SVD entropy. We built two heuristic models using the connectance and the joint degree sequence as statistical constraints, respectively. We compared both models' predictions against corresponding null and neutral models commonly used in network ecology using open access data of terrestrial and aquatic food webs sampled globally (N = 257). We found that the heuristic model constrained by the joint degree sequence was a good predictor of many measures of food-web structure, especially the nestedness and motifs distribution. Specifically, our results suggest that the structure of terrestrial and aquatic food webs is mainly driven by their joint degree distribution.

Will a large complex system be productive?

While the relationship between food web complexity and stability has been well documented, how complexity affects productivity remains elusive. In this study, we combine food web theory and a data set of 149 aquatic food webs to investigate the effect of complexity (i.e. species richness, connectance, and average interaction strength) on ecosystem productivity. We find that more complex ecosystems tend to be more productive, although different facets of complexity have contrasting effects. A higher species richness and/or average interaction strength increases productivity, whereas a higher connectance often decreases it. These patterns hold not only between realized complexity and productivity, but also characterize responses of productivity to simulated declines of complexity. Our model also predicts a negative association between productivity and stability along gradients of complexity. Empirical analyses support our predictions on positive complexity-productivity relationships and negative productivity-stability relationships. Our study provides a step forward towards reconciling ecosystem complexity, productivity and stability.

Predator-mediated interactions through changes in predator home range size can lead to local prey exclusion.

The strength of indirect biotic interactions is difficult to quantify in the wild and can alter community composition. To investigate whether the presence of a prey species affects the population growth rate of another prey species, we quantified predator-mediated interaction strength using a multi-prey mechanistic model of predation and a population matrix model. Models were parametrized using behavioural, demographic and experimental data from a vertebrate community that includes the arctic fox (Vulpes lagopus), a predator feeding on lemmings and eggs of various species such as sandpipers and geese. We show that the positive effects of the goose colony on sandpiper nesting success (due to reduction of search time for sandpiper nests) were outweighed by the negative effect of an increase in fox density. The fox numerical response was driven by changes in home range size. As a result, the net interaction from the presence of geese was negative and could lead to local exclusion of sandpipers. Our study provides a rare empirically based model that integrates mechanistic multi-species functional responses and behavioural processes underlying the predator numerical response. This is an important step forward in our ability to quantify the consequences of predation for community structure and dynamics.

No complementarity no gain-Net diversity effects on tree productivity occur once complementarity emerges during early stand development.

Although there is compelling evidence that tree diversity has an overall positive effect on forest productivity, there are important divergences among studies on the nature and strength of these diversity effects and their timing during forest stand development. To clarify conflicting results related to stand developmental stage, we explored how diversity effects on productivity change through time in a diversity experiment spanning 11 years. We show that the strength of diversity effects on productivity progressively increases through time, becoming significantly positive after 9 years. Moreover, we demonstrate that the strengthening of diversity effects is driven primarily by gradual increases in complementarity. We also show that mixing species with contrasting resource-acquisition strategies, and the dominance of deciduous, fast-developing species, promote positive diversity effects on productivity. Our results suggest that the canopy closure and subsequent stem exclusion phase are key for promoting niche complementarity in diverse tree communities.

On the sensitivity of food webs to multiple stressors.

Evaluating the effects of multiple stressors on ecosystems is becoming increasingly vital with global changes. The role of species interactions in propagating the effects of stressors, although widely acknowledged, has yet to be formally explored. Here, we conceptualise how stressors propagate through food webs and explore how they affect simulated three-species motifs and food webs of the Canadian St. Lawrence System. We find that overlooking species interactions invariably underestimate the effects of stressors, and that synergistic and antagonistic effects through food webs are prevalent. We also find that interaction type influences a species' susceptibility to stressors; species in omnivory and tri-trophic food chain interactions in particular are sensitive and prone to synergistic and antagonistic effects. Finally, we find that apex predators were negatively affected and mesopredators benefited from the effects of stressors due to their trophic position in the St. Lawrence System, but that species sensitivity is dependent on food web structure. In conceptualising the effects of multiple stressors on food webs, we bring theory closer to practice and show that considering the intricacies of ecological communities is key to assess the net effects of stressors on species.

Thermal mismatches in biological rates determine trophic control and biomass distribution under warming.

Temperature has numerous effects on the structure and dynamics of ecological communities. Yet, there is no general trend or consensus on the magnitude and directions of these effects. To fill this gap, we propose a mechanistic framework based on key biological rates that predicts how temperature influences biomass distribution and trophic control in food webs. We show that these predictions arise from thermal mismatches between biological rates and across trophic levels. We couple our theory with experimental data for a wide range of species and find that warming should lead to top-heavier terrestrial food chains and stronger top-down control in aquatic environments. We then derive predictions for the effects of temperature on herbivory and validate them with data on stream grazers. Our study provides a mechanistic explanation of thermal effects on consumer-resource systems which is crucial to better understand the biogeography and the consequences of global warming on trophic dynamics.

Asymmetric foraging lowers the trophic level and omnivory in natural food webs.

Food webs capture the trophic relationships and energy fluxes between species, which has fundamental impacts on ecosystem functioning and stability. Within a food web, the energy flux distribution between a predator and its prey species is shaped by food quantity-quality trade-offs and the contiguity of foraging. But the distribution of energy fluxes among prey species as well as its drivers and implications remain unclear. Here we used 157 aquatic food webs, which contain explicit energy flux information, to examine whether a predator's foraging is asymmetric and biased towards lower or higher trophic levels, and how these patterns may change with trophic level. We also evaluate how traditional topology-based approaches may over- or under-estimate a predator's trophic level and omnivory by ignoring the asymmetric foraging patterns. Our results demonstrated the prevalence of asymmetric foraging in natural aquatic food webs. Although predators prefer prey at higher trophic levels with potentially higher food quality, they obtain their energy mostly from lower trophic levels with a higher food quantity. Both tendencies, that is, stronger feeding preference for prey at higher trophic levels and stronger energetic reliance on prey at lower trophic levels are alleviated for predators at higher trophic levels. The asymmetric foraging lowers trophic levels and omnivory at both species and food web levels, compared to estimates from traditional topology-based approaches. Such overestimations by topology-based approaches are most pronounced for predators at lower trophic levels and communities with higher number of trophic species. Our study highlights the importance of energy flux information in understanding the foraging behaviour of predators as well as the structural complexity of natural food webs. The increasing availability of flux-based food web data will thus provide new opportunities to reconcile food web structure, functioning and stability.

Co-occurrence is not evidence of ecological interactions.

There is a rich amount of information in co-occurrence (presence-absence) data that could be used to understand community assembly. This proposition first envisioned by Forbes (1907) and then Diamond (1975) prompted the development of numerous modelling approaches (e.g. null model analysis, co-occurrence networks and, more recently, joint species distribution models). Both theory and experimental evidence support the idea that ecological interactions may affect co-occurrence, but it remains unclear to what extent the signal of interaction can be captured in observational data. It is now time to step back from the statistical developments and critically assess whether co-occurrence data are really a proxy for ecological interactions. In this paper, we present a series of arguments based on probability, sampling, food web and coexistence theories supporting that significant spatial associations between species (or lack thereof) is a poor proxy for ecological interactions. We discuss appropriate interpretations of co-occurrence, along with potential avenues to extract as much information as possible from such data.

Scaling-up biodiversity-ecosystem functioning research.

A rich body of knowledge links biodiversity to ecosystem functioning (BEF), but it is primarily focused on small scales. We review the current theory and identify six expectations for scale dependence in the BEF relationship: (1) a nonlinear change in the slope of the BEF relationship with spatial scale; (2) a scale-dependent relationship between ecosystem stability and spatial extent; (3) coexistence within and among sites will result in a positive BEF relationship at larger scales; (4) temporal autocorrelation in environmental variability affects species turnover and thus the change in BEF slope with scale; (5) connectivity in metacommunities generates nonlinear BEF and stability relationships by affecting population  synchrony at local and regional scales; (6) spatial scaling in food web structure and diversity will generate scale dependence in ecosystem functioning. We suggest directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross-scale feedbacks. Tests of this theory may combine remote sensing with a generation of networked experiments that assess effects at multiple scales. We also show how anthropogenic land cover change may alter the scaling of the BEF relationship. New research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.

Moderate disturbances accelerate forest transition dynamics under climate change in the temperate-boreal ecotone of eastern North America.

Several temperate tree species are expected to migrate northward and colonize boreal forests in response to climate change. Tree migrations could lead to transitions in forest types, but these could be influenced by several non-climatic factors, such as disturbances and soil conditions. We analysed over 10,000 forest inventory plots, sampled from 1970 to 2018 in meridional Québec, Canada, to identify what environmental conditions promote or prevent regional-scale forest transitions. We used a continuous-time multi-state Markov model to quantify the probabilities of transitions between forest states (temperate, boreal, mixed, pioneer) as a function of climate (mean temperature and climate moisture index during the growing season), soil conditions (pH and drainage) and disturbances (severity levels of natural disturbances and logging). We further investigate how different disturbance types and severities impact forests' short-term transient dynamics and long-term equilibrium using properties of Markov transition matrices. The most common transitions observed during the study period were from mixed to temperate states, as well as from pioneer to boreal forests. In our study, transitions were mainly driven by natural and anthropogenic disturbances and secondarily by climate, whereas soil characteristics exerted relatively minor constraints. While major disturbances only promoted transitions to the pioneer state, moderate disturbances increased the probability of transition from mixed to temperate states. Long-term projections of our model under the current environmental conditions indicate that moderate disturbances would promote a northward shift of the temperate forest. Moreover, disturbances reduced turnover and convergence time for all transitions, thereby accelerating forest dynamics. Contrary to our expectation, mixed to temperate transitions were not driven by temperate tree recruitment but by mortality and growth. Overall, our results suggest that moderate disturbances could catalyse rapid forest transitions and accelerate broad-scale biome shifts.

Seasonal food webs with migrations: multi-season models reveal indirect species interactions in the Canadian Arctic tundra.

Models incorporating seasonality are necessary to fully assess the impact of global warming on Arctic communities. Seasonal migrations are a key component of Arctic food webs that still elude current theories predicting a single community equilibrium. We develop a multi-season model of predator-prey dynamics using a hybrid dynamical systems framework applied to a simplified tundra food web (lemming-fox-goose-owl). Hybrid systems models can accommodate multiple equilibria, which is a basic requirement for modelling food webs whose topology changes with season. We demonstrate that our model can generate multi-annual cycling in lemming dynamics, solely from a combined effect of seasonality and state-dependent behaviour. We compare our multi-season model to a static model of the predator-prey community dynamics and study the interactions between species. Interestingly, including seasonality reveals indirect interactions between migrants and residents not captured by the static model. Further, we find that the direction and magnitude of interactions between two species are not necessarily accurate using only summer time-series. Our study demonstrates the need for the development of multi-season models and provides the tools to analyse them. Integrating seasonality in food web modelling is a vital step to improve predictions about the impacts of climate change on ecosystem functioning. This article is part of the theme issue 'The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

Towards a multi-trophic extension of metacommunity ecology.

Metacommunity theory provides an understanding of how spatial processes determine the structure and function of communities at local and regional scales. Although metacommunity theory has considered trophic dynamics in the past, it has been performed idiosyncratically with a wide selection of possible dynamics. Trophic metacommunity theory needs a synthesis of a few influential axis to simplify future predictions and tests. We propose an extension of metacommunity ecology that addresses these shortcomings by incorporating variability among trophic levels in 'spatial use properties'. We define 'spatial use properties' as a set of traits (dispersal, migration, foraging and spatial information processing) that set the spatial and temporal scales of organismal movement, and thus scales of interspecific interactions. Progress towards a synthetic predictive framework can be made by (1) documenting patterns of spatial use properties in natural food webs and (2) using theory and experiments to test how trophic structure in spatial use properties affects metacommunity dynamics.

Assessing changes in arthropod predator-prey interactions through DNA-based gut content analysis-variable environment, stable diet.

Analysing the structure and dynamics of biotic interaction networks and the processes shaping them is currently one of the key fields in ecology. In this paper, we develop a novel approach to gut content analysis, thereby deriving a new perspective on community interactions and their responses to environment. For this, we use an elevational gradient in the High Arctic, asking how the environment and species traits interact in shaping predator-prey interactions involving the wolf spider Pardosa glacialis. To characterize the community of potential prey available to this predator, we used pitfall trapping and vacuum sampling. To characterize the prey actually consumed, we applied molecular gut content analysis. Using joint species distribution models, we found elevation and vegetation mass to explain the most variance in the composition of the prey community locally available. However, such environmental variables had only a small effect on the prey community found in the spider's gut. These observations indicate that Pardosa exerts selective feeding on particular taxa irrespective of environmental constraints. By directly modelling the probability of predation based on gut content data, we found that neither trait matching in terms of predator and prey body size nor phylogenetic or environmental constraints modified interaction probability. Our results indicate that taxonomic identity may be more important for predator-prey interactions than environmental constraints or prey traits. The impact of environmental change on predator-prey interactions thus appears to be indirect and mediated by its imprint on the community of available prey.

Intraguild predation enhances biodiversity and functioning in complex food webs.

Intraguild predation (IGP), that is, feeding interaction between two consumers that share the same resource species, is commonly observed in natural food webs. IGP expands vertical niche space and slows down energy flows from lower to higher trophic levels, which potentially affects the diversity and dynamics of food webs. Here, we use food-web models to investigate the effects of IGP on species diversity and ecosystem functioning. We first simulate a five-species food-web module with different strengths of IGP at the herbivore and/or carnivore level. Results show that as the strength of IGP within a trophic level increases, the biomass of its resource level increases because of predation release; this increased biomass in turn alters the energy fluxes and biomass of other trophic levels. These results are then extended by subsequent simulations of more diverse food webs. As the strength of IGP increases, simulated food webs maintain (1) higher species diversity at different trophic levels, (2) higher total biomasses at different trophic levels, and (3) larger energy fluxes across trophic levels. Our results challenge the intuitive hypothesis that food-web structure should maximize the efficiency of energy transfer across trophic levels; instead, they suggest that the assembly of food webs should be governed by a balance between efficiency (of energy transfer) and persistence (i.e., the maintenance of species and biomasses). Our simulations also show that the relationship between biodiversity and ecosystem functioning (e.g., total biomass or primary production) is much stronger in the presence of IGP, reconciling the contrast from recent studies based on food-chain and food-web models. Our findings shed new light on the functional role of IGP and contribute to resolving the debate on structure, diversity and functioning in complex food webs.

Springtail community structure is influenced by functional traits but not biogeographic origin of leaf litter in soils of novel forest ecosystems.

With ongoing global change, shifts in the ranges of non-native species and resulting novel communities can modify biotic interactions and ecosystem processes. We hypothesized that traits and not biogeographic origin of novel plant communities will determine community structure of organisms that depend on plants for habitat or as a food resource. We tested the functional redundancy of novel tree communities by verifying if six pairs of congeneric European and North American tree species bearing similar leaf litter traits resulted in similar ecological filters influencing the assembly of springtail (Collembola) communities at two sites. Litter biogeographic origin (native versus non-native) did not influence springtail community structure, but litter genus, which generally reflected trait differences, did. Our empirical evidence suggests that a functional trait approach may be indeed as relevant as, and complementary to, studying biogeographic origin to understand the ecological consequences of non-native tree species in soils of novel forest ecosystems.

On the development of a predictive functional trait approach for studying terrestrial arthropods.

The characterization of ecological communities with functional traits allows to consider simultaneously the ability of a species to survive and reproduce in an environment, its interactions with other species and its effects on the ecosystem. Functional traits have been studied mainly by plant ecologists, but are increasingly common in the study of other taxa including arthropods. Arthropods represent a group for which a functional trait approach could be highly profitable because of their high diversity, abundance, ubiquity and role in many important ecological processes. This review synthesizes two decades of functional trait research on terrestrial arthropods. We show that while the approach has gained popularity, particularly in the last decade, the absence of clearly postulated hypotheses is a recurrent problem limiting generalization. Furthermore, studied traits are often poorly related to studied functions. To address these problems, we propose a step-by-step protocol to postulate clear hypotheses prior to trait selection and emphasize the need for a common set of more generalizable traits in future studies. Extending the functional trait approach to arthropods opens the door to improving our understanding of interspecific interactions and potential links between response and effect traits. We present the concept of trait-matching with several examples of arthropod traits known to be effective predictors of consumer-resource interactions. The development of a successful functional trait approach for terrestrial arthropods will necessitate an understanding of relevant traits, standardized measurement protocols and open access databases to share this information. Such progress will provide ecologists with a new set of tools to answer broad questions in several fields including the study of community assembly, ecological networks and multitrophic functionality.

Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation.

The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species-area relationship. We compare model predictions to the body-size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large-sized species than large and connected reefs. We also find that knowledge of species body-size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation.

Food-web structure of willow-galling sawflies and their natural enemies across Europe.

Communities consist of species and their interactions. They can thus be described as networks, with species as nodes and interactions as links. Within such networks, the diversity of nodes and the distribution of links may affect patterns of energy transfer between trophic levels, the dynamics of the system, and the outcome in terms of ecosystem functioning. To date, most descriptions of networks have focused on single or relatively few sites, and have oftentimes been built on poorly resolved nodes and links. Yet, comparisons of local interaction networks reveal variation in space and in time, thus spurring interest in methods and theory for understanding patterns, drivers, and consequences of this variation. Progress in this field relies on access to replicate samples of comparable food webs across large spatiotemporal scales, resolved to species rather than to compound nodes. Due to the massive efforts required, high-quality data sets are still scarce. We created a data set on a single community type sampled across Europe: willow species (Salix), willow-galling sawflies (Hymenoptera: Tenthredinidae: Nematinae: Euurina), and their natural enemies (hymenopteran parasitoids and coleopteran, lepidopteran, dipteran, and hymenopteran inquilines). Each sample was referenced in space and time, and each node resolved with the highest possible resolution, including taxonomic affinity, gall type (for herbivores), and mode of parasitism (for natural enemies). Galler survival and link structure were resolved by dissection and rearing of gall inhabitants. In total, the data set is based on 641 site visits over 29 years, and on 165,424 galls representing 96 herbivore nodes and 52 plant nodes. The dissections and rearings yielded 42,129 natural enemies belonging to 126 species, and revealed 1,173 different links. The spatiotemporal and taxonomic resolution of these data make them amenable to analyses of both ecological and evolutionary processes of network assembly. Thus, this data set will facilitate testing of important hypotheses in recent community theory, concerning, e.g., the sampling effort needed to adequately describe interaction structure within ecological communities, the impact of environmental conditions and biotic filters on the distribution of species and their interactions, and the relationship between the global "metaweb" and its local realizations.

Experimental niche evolution alters the strength of the diversity­productivity relationship.

The relationship between biodiversity and ecosystem functioning (BEF) has become a cornerstone of community and ecosystem ecology and an essential criterion for making decisions in conservation biology and policy planning. It has recently been proposed that evolutionary history should influence the BEF relationship because it determines species traits and, thus, species' ability to exploit resources. Here we test this hypothesis by combining experimental evolution with a BEF experiment. We isolated 20 bacterial strains from a marine environment and evolved each to be generalists or specialists. We then tested the effect of evolutionary history on the strength of the BEF relationship with assemblages of 1 to 20 species constructed from the specialists, generalists and ancestors. Assemblages of generalists were more productive on average because of their superior ability to exploit the environmental heterogeneity. The slope of the BEF relationship was, however, stronger for the specialist assemblages because of enhanced niche complementarity. These results show how the BEF relationship depends critically on the legacy of past evolutionary events.

Functional identity is the main driver of diversity effects in young tree communities.

Two main effects are proposed to explain biodiversity-ecosystem functioning relationships: niche complementarity and selection effects. Both can be functionally defined using the functional diversity (FD) and functional identity (FI) of the community respectively. Herein, we present results from the first tree diversity experiment that separated the effect of selection from that of complementarity by varying community composition in high-density plots along a gradient of FD, independent of species richness and testing for the effects of FD and community weighted means of traits (a proxy for FI) on stem biomass increment (a proxy for productivity). After 4 years of growth, most mixtures did not differ in productivity from the averages of their respective monocultures, but some did overyield significantly. Those positive diversity effects resulted mostly from selection effects, primarily driven by fast-growing deciduous species and associated traits. Net diversity effect did not increase with time over 4 years.