Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species,Lasiocampidae) using different representations of modelled host tree distributions

Biotic interactions influence species niches and may thus shape distributions. Nevertheless, species distribution modelling has traditionally relied exclusively on environmental factors to predict species distributions, while biotic interactions have only seldom been incorporated into models. This study tested the ability of incorporating biotic interactions, in the form of host plant distributions, to increase model performance for two host‐dependent lepidopterans of economic interest, namely the African silk moth species, Gonometa postica and Gonometa rufobrunnea (Lasiocampidae). Both species are dependent on a small number of host tree species for the completion of their life cycle. We thus expected the host plant distribution to be an important predictor of Gonometa distributions. Model performance of a species distribution model trained only on abiotic predictors was compared to four species distribution models that additionally incorporated biotic interactions in the form of four different representations of host plant distributions as predictors. We found that incorporating the moth–host plant interactions improved G. rufobrunnea model performance for all representations of host plant distribution, while for G. postica model performance only improved for one representation of host plant distribution. The best performing representation of host plant distribution differed for the two Gonometa species. While these results suggest that incorporating biotic interactions into species distribution models can improve model performance, there is inconsistency in which representation of the host tree distribution best improves predictions. Therefore, the ability of biotic interactions to improve species distribution models may be context‐specific, even for species which have obligatory interactions with other organisms.     

Host plant availability potentially limits butterfly distributions under cold environmental conditions

Species ranges are shaped by both climatic factors and interactions with other species. The stress gradient hypothesis predicts that under physiologically stressful environmental conditions abiotic factors shape range edges while in less stressful environments negative biotic interactions are more important. Butterflies provide a suitable system to test this hypothesis since larvae of most species depend on biotic interactions with a specific set of host plants, which in turn can shape patterns of occurrence and distribution. Here we modelled the distribution of 92 butterfly and 136 host plant species with three different modelling algorithms, using distribution data from the Swiss biodiversity monitoring scheme at a 1 × 1 km spatial resolution. By comparing the ensemble prediction for each butterfly species and the corresponding host plant(s), we assessed potential constraints imposed by host plant availability on distribution of butterflies at their distributional limits along the main environmental gradient, which closely parallels an elevational gradient. Our results indicate that host limitation does not play a role at the lower limit. At the upper limit 50% of butterfly species have a higher elevational limit than their primary host plant, and 33% have upper elevational limits that exceed the limits of both primary and secondary hosts. We conclude that host plant limitation was not relevant to butterfly distributional limits in less stressful environments and that distributions are more likely limited by climate, land use or antagonistic biotic interactions. Obligatory dependency of butterflies on their host plants, however, seems to represent an important limiting factor for the distribution of some species towards the cold, upper end of the environmental gradient, suggesting that biotic factors can shape ranges in stressful environments. Thus, predictions by the stress gradient hypothesis were not always applicable.     

Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions

Predicting changes in potential habitat for endangered species as a result of global warming requires considering more than future climate conditions; it is also necessary to evaluate biotic associations. Most distribution models predicting species responses to climate change include climate variables and occasionally topographic and edaphic parameters, rarely are biotic interactions included. Here, we incorporate biotic interactions into niche models to predict suitable habitat for species under altered climates. We constructed and evaluated niche models for an endangered butterfly and a threatened bird species, both are habitat specialists restricted to semiarid shrublands of southern California. To incorporate their dependency on shrubs, we first developed climate‐based niche models for shrubland vegetation and individual shrub species. We also developed models for the butterfly's larval host plants. Outputs from these models were included in the environmental variable dataset used to create butterfly and bird niche models. For both animal species, abiotic–biotic models outperformed the climate‐only model, with climate‐only models over‐predicting suitable habitat under current climate conditions. We used the climate‐only and abiotic–biotic models to calculate amounts of suitable habitat under altered climates and to evaluate species' sensitivities to climate change. We varied temperature (+0.6, +1.7, and +2.8 °C) and precipitation (50%, 90%, 100%, 110%, and 150%) relative to current climate averages and within ranges predicted by global climate change models. Suitable habitat for each species was reduced at all levels of temperature increase. Both species were sensitive to precipitation changes, particularly increases. Under altered climates, including biotic variables reduced habitat by 68–100% relative to the climate‐only model. To design reserve systems conserving sensitive species under global warming, it is important to consider biotic interactions, particularly for habitat specialists and species with strong dependencies on other species.     

Towards a mechanistic understanding of temperature and enrichment effects on species interaction strength,omnivory and food‐web structure

Revealing the links between species functional traits, interaction strength and food‐web structure is of paramount importance for understanding and predicting the relationships between food‐web diversity and stability in a rapidly changing world. However, little is known about the interactive effects of environmental perturbations on individual species, trophic interactions and ecosystem functioning. Here, we combined modelling and laboratory experiments to investigate the effects of warming and enrichment on a terrestrial tritrophic system. We found that the food‐web structure is highly variable and switches between exploitative competition and omnivory depending on the effects of temperature and enrichment on foraging behaviour and species interaction strength. Our model contributes to identifying the mechanisms that explain how environmental effects cascade through the food web and influence its topology. We conclude that considering environmental factors and flexible food‐web structure is crucial to improve our ability to predict the impacts of global changes on ecosystem diversity and stability.     

No species is an island: testing the effects of biotic interactions on models of avian niche occupation

Traditionally, the niche of a species is described as a hypothetical 3D space, constituted by well‐known biotic interactions (e.g. predation, competition, trophic relationships, resource–consumer interactions, etc.) and various abiotic environmental factors. Species distribution models (SDMs), also called “niche models” and often used to predict wildlife distribution at landscape scale, are typically constructed using abiotic factors with biotic interactions generally been ignored. Here, we compared the goodness of fit of SDMs for red‐backed shrike Lanius collurio in farmlands of Western Poland, using both the classical approach (modeled only on environmental variables) and the approach which included also other potentially associated bird species. The potential associations among species were derived from the relevant ecological literature and by a correlation matrix of occurrences. Our findings highlight the importance of including heterospecific interactions in improving our understanding of niche occupation for bird species. We suggest that suite of measures currently used to quantify realized species niches could be improved by also considering the occurrence of certain associated species. Then, an hypothetical “species 1” can use the occurrence of a successfully established individual of “species 2” as indicator or “trace” of the location of available suitable habitat to breed. We hypothesize this kind of biotic interaction as the “heterospecific trace effect” (HTE): an interaction based on the availability and use of “public information” provided by individuals from different species. Finally, we discuss about the incomes of biotic interactions for enhancing the predictive capacities on species distribution models.     

Biotic Interactions in the Face of Climate Change: A Comparison of Three Modelling Approaches

Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap (‘overlap approach’). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate (‘explanatory variable approach’). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species (‘reference area approach’). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of the ‘reference area approach’ as this method allows a separation of the effect of climate and occurrence of host plant.     

Simulated shifts in trophic niche breadth modulate range loss of alpine butterflies under climate change

Species currently track suitable abiotic and biotic conditions under ongoing climate change. Adjustments of trophic interactions may provide a mechanism for population persistence, an option that is rarely included in model projections. Here, we model the future distribution, of butterflies in the western Alps of Switzerland under climate change, simulating potential diet expansion resulting from adaptive behavior or new host opportunities. We projected the distribution of 60 butterfly and 298 plant species with species distribution models (SDMs) under three climate change scenarios. From known host plants, we allowed a potential diet expansion based on phylogenetic constraints. We assessed whether diet expansion could reduce the rate of expected regional species extinction under climate change. We found that the risk of species extinctions decreased with a concave upward decreasing shape when expanding the host plant range. A diet expansion to even a few phylogenetically closely related host plants would significantly decrease extinction rates. Yet, even when considering expansion toward all plant species available in the study area, the overall regional extinction risk would remain high. Ecological or evolutionary shifts to new host plants may attenuate extinction risk, but the severe decline of suitable abiotic conditions is still expected to drive many species to local extinction.     

Host plant distributions and climate interact to affect the predicted geographic distribution of a Neotropical termite

Species distribution models (SDMs) have been widely used in the scientific literature. The majority of SDMs use climate data or other abiotic variables to forecast the potential distribution of a species in geographic space. Biotic interactions can affect the predicted spatial distribution of a species in many ways across multiple spatial scales, and incorporating these predictors in an SDM is a current topic in the scientific literature. Constrictotermes cyphergaster is a widely distributed termite in the Neotropics. This termite species nests in plants and more frequently nests in some arboreal species. Thus, this species is an excellent model to evaluate the influence of biotic interactions in SDMs. We evaluate the influences of climate and the geographic distribution of host plants on the potential distribution of C. cyphergaster. Three correlative models (MaxEnt) were built to predict the geographic distribution of the termite: (1) climate data, (2) biotic data (i.e., the geographic distribution of host plants), and (3) climate and biotic data. The models that were generated indicate that the potential geographic distribution of C. cyphergaster is concentrated in the Cerrado and Caatinga regions. In addition, path analysis and multiple regression revealed the importance of the direct effects of biological interactions in the geographic distribution of the termite, while climate affected the distribution of the termite mainly through indirect effects by influencing the geographic distributions of host plants. The current study endorses the importance of including biological interactions in SDMs. We recommend using biotic predictors in SDM studies of insect species, mainly because insects have important environmental services and biotic interaction data can improve the macroecological studies of this group.     

Biotic predictors with phenological information improve range estimates for migrating monarch butterflies in Mexico

Although long-standing theory suggests that biotic variables are only relevant at local scales for explaining the patterns of species' distributions, recent studies have demonstrated improvements to species distribution models (SDMs) by incorporating predictor variables informed by biotic interactions. However, some key methodological questions remain, such as which kinds of interactions are permitted to include in these models, how to incorporate the effects of multiple interacting species, and how to account for interactions that may have a temporal dependence. We addressed these questions in an effort to model the distribution of the monarch butterfly Danaus plexippus during its fall migration (September–November) through Mexico, a region with new monitoring data and uncertain range limits even for this well-studied insect. We estimated species richness of selected nectar plants (Asclepias spp.) and roosting trees (various highland species) for use as biotic variables in our models. To account for flowering phenology, we additionally estimated nectar plant richness of flowering species per month. We evaluated three types of models: climatic variables only (abiotic), plant richness estimates only (biotic) and combined (abiotic and biotic). We selected models with AICc and additionally determined if they performed better than random on spatially withheld data. We found that the combined models accounting for phenology performed best for all three months, and better than random for discriminatory ability but not omission rate. These combined models also produced the most ecologically realistic spatial patterns, but the modeled response for nectar plant richness matched ecological predictions for November only. These results represent the first model-based monarch distributional estimates for the Mexican migration route and should provide foundations for future conservation work. More generally, the study demonstrates the potential benefits of using SDM-derived richness estimates and phenological information for biotic factors affecting species distributions.     

Novel feeding interactions amplify the impact of species redistribution on an Arctic food web

Species are redistributing globally in response to climate warming, impacting ecosystem functions and services. In the Barents Sea, poleward expansion of boreal species and a decreased abundance of Arctic species are causing a rapid borealization of the Arctic communities. This borealization might have profound consequences on the Arctic food web by creating novel feeding interactions between previously non co‐occurring species. An early identification of new feeding links is crucial to predict their ecological impact. However, detection by traditional approaches, including stomach content and isotope analyses, although fundamental, cannot cope with the speed of change observed in the region, nor with the urgency of understanding the consequences of species redistribution for the marine ecosystem. In this study, we used an extensive food web (metaweb) with nearly 2,500 documented feeding links between 239 taxa coupled with a trait data set to predict novel feeding interactions and to quantify their potential impact on Arctic food web structure. We found that feeding interactions are largely determined by the body size of interacting species, although species foraging habitat and metabolic type are also important predictors. Further, we found that all boreal species will have at least one potential resource in the Arctic region should they redistribute therein. During 2014–2017, 11 boreal species were observed in the Arctic region of the Barents Sea. These incoming species, which are all generalists, change the structural properties of the Arctic food web by increasing connectance and decreasing modularity. In addition, these boreal species are predicted to initiate novel feeding interactions with the Arctic residents, which might amplify their impact on Arctic food web structure affecting ecosystem functioning and vulnerability. Under the ongoing species redistribution caused by environmental change, we propose merging a trait‐based approach with ecological network analysis to efficiently predict the impacts of range‐shifting species on food webs.     

Rewiring of interactions in a changing environment: nettle-feeding butterflies and their parasitoids

Climate and land use change can alter the incidence and strength of biotic interactions, with important effects on the distribution, abundance and function of species. To assess the importance of these effects and their dynamics, studies quantifying how biotic interactions change in space and time are needed. We studied interactions between nettle-feeding butterflies and their shared natural enemies (parasitoids) locally and across 500 km latitudinal gradient in Sweden. We also examined the potential impact of the range-expansion of the butterfly Araschnia levana on resident butterflies via shared parasitoids, by studying how parasitism in resident butterflies covaries with the presence or absence of the newly-established species. We collected 6777 larvae of four nettle-feeding butterfly species (Aglais urticae, Aglais io, Ar. levana and Vanessa atalanta), over two years, at 19 sites distributed along the gradient. We documented the parasitoid complex for each butterfly species and measured their overlap, and analysed how parasitism rates were affected by butterfly species assemblage, variations in abundance, time, and the arrival of Ar. levana. Parasitoids caused high mortality, with substantial overlap in the complex of parasitoids associated with the four host butterflies. Levels of parasitism differed significantly among butterflies and were influenced by the local butterfly species assemblage. Our results also suggest that parasitism in resident butterflies is elevated at sites where Ar. levana has been established for a longer period. In our study system, variations in butterfly species assemblages were associated in a predictable way with substantial variations in rates of parasitism. This relationship is likely to affect the dynamics of the butterfly host species, and potentially cascade to the larger number of species with which they interact. These results highlight the importance of indirect interactions and their potential to reorganise ecological communities, especially in the context of shifts in species distributions in a warmer world.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

Endoparasitism in cereal aphids: molecular analysis of a whole parasitoid community

Insect parasitoids play a major role in terrestrial food webs as they are highly diverse, exploit a wide range of niches and are capable of affecting host population dynamics. Formidable difficulties are encountered when attempting to quantify host–parasitoid and parasitoid–parasitoid trophic links in diverse parasitoid communities. Here we present a DNA-based approach to effectively track trophic interactions within an aphid–parasitoid food web, targeting, for the first time, the whole community of parasitoids and hyperparasitods associated with a single host. Using highly specific and sensitive multiplex and singleplex polymerase chain reaction, endoparasitism in the grain aphid Sitobion avenae (F) by 11 parasitoid species was quantified. Out of 1061 aphids collected during 12 weeks in a wheat field, 18.9% were found to be parasitized. Parasitoids responded to the supply of aphids, with the proportion of aphids parasitized increasing monotonically with date, until the aphid population crashed. In addition to eight species of primary parasitoids, DNA from two hyperparasitoid species was detected within 4.1% of the screened aphids, with significant hyperparasitoid pressure on some parasitoid species. In 68.2% of the hyperparasitized aphids, identification of the primary parasitoid host was also possible, allowing us to track species-specific parasitoid-hyperparasitoid links. Nine combinations of primary parasitoids within a single host were found, but only 1.6% of all screened aphids were multiparasitized. The potential of this approach to parasitoid food web research is discussed.     

Loss of adaptive variation during evolutionary responses to climate change

The changes in species' geographical distribution demanded by climate change are often critically limited by the availability of key interacting species. In such cases, species' persistence will depend on the rapid evolution of biotic interactions. Understanding evolutionary limits to such adaptation is therefore crucial for predicting biological responses to environmental change. The recent poleward range expansion of the UK brown argus butterfly has been associated with a shift in female preference from its main host plant, rockrose (Cistaceae), onto Geraniaceae host plants throughout its new distribution. Using reciprocal transplants onto natural host plants across the UK range, we demonstrate reduced fitness of females from recently colonised Geraniaceae‐dominated habitat when moved to ancestral rockrose habitats. By contrast, individuals from ancestral rockrose habitats show no reduction in fitness on Geraniaceae. Climate‐driven range expansion in this species is therefore associated with the rapid evolution of biotic interactions and a significant loss of adaptive variation.     

Constraints and variation in food web link-species space

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. The most fundamental aspect of food web structure—the relationship between the number of links and species—is still poorly understood. Some species interactions may be physically or physiologically ‘forbidden''—like consumption by non-consumer species—with possible consequences for food web structure. We show that accounting for these ‘forbidden interactions'' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.     

Lags in the response of mountain plant communities to climate change

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: “dispersal lags” affecting plant species’ spread along elevational gradients, “establishment lags” following their arrival in recipient communities, and “extinction lags” of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species’ range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide.     

Factors shaping community assemblages and species co‐occurrence of different trophic levels

Species assemblages are the results of various processes, including dispersion and habitat filtering. Disentangling the effects of these different processes is challenging for statistical analysis, especially when biotic interactions should be considered. In this study, we used plants (producers) and leafhoppers (phytophagous) as model organisms, and we investigated the relative importance of abiotic versus biotic factors that shape community assemblages, and we infer on their biotic interactions by applying three‐step statistical analysis. We applied a novel statistical analysis, that is, multiblock Redundancy Analysis (mbRA, step 1) and showed that 51.8% and 54.1% of the overall variation in plant and leafhopper assemblages are, respectively, explained by the two multiblock models. The most important blocks of variables to explain the variations in plant and leafhopper assemblages were local topography and biotic factors. Variation partitioning analysis (step 2) showed that pure abiotic filtering and pure biotic processes were relatively less important than their combinations, suggesting that biotic relationships are strongly structured by abiotic conditions. Pairwise co‐occurrence analysis (step 3) on generalist leafhoppers and the most common plants identified 40 segregated species pairs (mainly between plant species) and 16 aggregated pairs (mainly between leafhopper species). Pairwise analysis on specialist leafhoppers and potential host plants clearly revealed aggregated patterns. Plant segregation suggests heterogeneous resource availability and competitive interactions, while leafhopper aggregation suggests host feeding differentiation at the local level, different feeding microhabitats on host plants, and similar environmental requirements of the species. Using the novel mbRA, we disentangle for the first time the relative importance of more than five distinct groups of variables shaping local species communities. We highlighted the important role of abiotic processes mediated by bottom‐up effects of plants on leafhopper communities. Our results revealed that in‐field structure diversification and trophic interactions are the main factors causing the co‐occurrence patterns observed.     

Wood‐inhabiting fungi with tight associations with other species have declined as a response to forest management

Research on mutualistic and antagonistic networks, such as plant–pollinator and host–parasite networks, has shown that species interactions can influence and be influenced by the responses of species to environmental perturbations. Here we examine whether results obtained for directly observable networks generalize to more complex networks in which species interactions cannot be observed directly. As a case study, we consider data on the occurrences of 98 wood‐inhabiting fungal species in managed and natural forests. We specifically ask if and how much the positions of wood‐inhabiting fungal species within the interaction networks influence their responses to forest management. For this, we utilize a joint species distribution model that partitions variation in species occurrences among environmental (i.e. resource availability) and biotic (i.e. species‐to‐species associations) predictors. Our results indicate that in addition to the direct loss of resource‐specialised species, forest management has indirect effects mediated through interactive associations. In particular, species with strong associative links to other species are especially sensitive to forest management.     

Tree Species Richness Strengthens Relationships between Ants and the Functional Composition of Spider Assemblages in a Highly Diverse Forest

In species‐rich ecosystems, such as subtropical and tropical forests, higher trophic level interactions are key mediators of ecosystem functioning. Plant species loss may alter these interactions, but the effects of plant diversity might be modified by intraguild interactions, particularly among predators. We analyzed the relationships between spiders and ants, two dominant predatory arthropod taxa, on tree saplings across a gradient from medium to high woody plant species richness in a subtropical forest in Southeast China. Neither ant nor spider total biomass was significantly related to plant species richness. By contrast, the biomass distribution of web‐building and hunting spiders changed and spider family richness increased in the presence of ants, resulting in more web builder‐dominated assemblages. However, these relationships depended on the plant communities, and were stronger in plots with higher plant species richness. Our results indicate that in addition to potential effects of ants on hunting spiders in particular, ants could indirectly influence intraguild interactions within spider assemblages. The observed shifts in the spider assemblages with increasing ant presence and plant species richness may have functional consequences, as web‐building and hunting spiders have distinct prey spectra. The relationships among ants, spiders, and plant species richness might contribute to explaining the non‐significant relationship between the overall effects of predators and plant diversity previously observed in the same forest plots. Our findings thus give insight into the complexity of biotic interactions in such species‐rich ecosystems.     

Defining and measuring trophic role similarity in food webs using regular equivalence

We present a graph theoretic model of analysing food web structure called regular equivalence. Regular equivalence is a method for partitioning the species in a food web into "isotrophic classes" that play the same structural roles, even if they are not directly consuming the same prey or if they do not share the same predators. We contrast regular equivalence models, in which two species are members of the same trophic group if they have trophic links to the same set of other trophic groups, with structural equivalence models, in which species are equivalent if they are connected to the exact same other species. Here, the regular equivalence approach is applied to two published food webs: (1) a topological web (Malaysian pitcher plant insect food web) and (2) a carbon-flow web (St. Marks, Florida seagrass ecosystem food web). Regular equivalence produced a more satisfactory set of classes than did the structural approach, grouping basal taxa with other basal taxa and not with top predators. Regular equivalence models provide a way to mathematically formalize trophic position, trophic group and trophic niche. These models are part of a family of models that includes structural models used extensively by ecologists now. Regular equivalence models uncover similarities in trophic roles at a higher level of organization than do the structural models. The approach outlined is useful for measuring the trophic roles of species in food web models, measuring similarity in trophic relations of two or more species, comparing food webs over time and across geographic regions, and aggregating taxa into trophic groups that reduce the complexity of ecosystem feeding relations without obscuring network relationships. In addition, we hope the approach will prove useful in predicting the outcome of predator-prey interactions in experimental studies.