Combining food web and species distribution models for improved community projections

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant–herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks.     

Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model

Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non‐random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant–pollinator and plant–frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.     

Diversity indices for ecological networks: a unifying framework using Hill numbers

Describing how ecological interactions change over space and time and how they are shaped by environmental conditions is crucial to understand and predict ecosystem trajectories. However, it requires having an appropriate framework to measure network diversity locally, regionally and between samples (α‐, γ‐ and β‐diversity). Here, we propose a unifying framework that builds on Hill numbers and accounts both for the probabilistic nature of biotic interactions and the abundances of species or groups. We emphasise the importance of analysing network diversity across different species aggregation levels (e.g. from species to trophic groups) to get a better understanding of network structure. We illustrate our framework with a simulation experiment and an empirical analysis using a global food‐web database. We discuss further usages of the framework and show how it responds to recent calls on comparing ecological networks and analysing their variation across environmental gradients and time.     

Predicting network topology of mistletoe–host interactions: do mistletoes really mimic their hosts?

Network analysis provides a unified framework for investigating different types of species interactions at the community level. Network analysis is typically based on null models that test for specific patterns in network topology. Here we use a novel predictive approach to investigate the topology of a mistletoe–host network. It has been hypothesised that Australian mistletoes mimic the phenotype of their preferred hosts to avoid herbivory. We developed a deterministic model based on phenotypic similarity to predict the topology of a quantitative network between Lauranthaceaous mistletoes and their hosts. We quantified mistletoe–host interactions in a semi‐arid woodland central Australia, along with the size, shape and colour of leaves produced by both players in the interaction. Traditional null model analyses showed support for negative co‐occurrence patterns, web specialisation and strong links between species pairs. However, our deterministic model showed that the observed network topology could not be predicted by phenotypic similarity, suggesting that Australian mistletoes do not mimic their hosts.     

The macroecology of reef fish agonistic behaviour

Understanding the interplay between processes operating at large and small spatiotemporal scales in shaping biotic interactions remains challenging. Recent studies illustrate how phenotypic specialization, species life-history traits and/or resource partitioning recurrently underlie the structure of mutualistic interactions in terrestrial ecosystems along large latitudinal gradients of biodiversity. However, we know considerably less about how local processes interact with large-scale patterns of biodiversity in modulating biotic interactions in the marine realm. Considering agonistic behaviour as a proxy for contest competition, we empirically investigate whether the structure of reef fish agonistic interactions is conserved across a 34 000-km longitudinal gradient of biodiversity. By sampling coral reefs using standardized remote underwater video, we found recurrent patterns of fish agonistic behaviour in disparate communities distributed across five biogeographic provinces of the Pacific and Atlantic oceans. While the sheer number of species increases with regional richness, the number of aggressive disputes at the habitat scale is similar across communities. We then combined generalized linear models and network theory to reveal that, the emergent structure of local agonistic networks is not modular but instead recurrently display a nested structure, with a core of highly interactive site-attached herbivores of the Pomacentridae family. Therefore, despite the increase in the number of species involved in agonistic interactions toward speciose communities, the network structure is conserved along the longitudinal richness gradient because local disputes are mostly driven by closely-related, functionally-similar species. These findings suggest that evolutionary and local processes interact in modulating reef fish agonistic behaviour and that fine-scale niche-partitioning can structure the ecological networks in marine ecosystems.     

Characterizing topology of ecological networks along gradients: The limits of metrics’ standardization

Species interact in nature to form complex ecological networks. There has been a rising interest in recent years to characterize the topology of such networks along various gradients (e.g. successional, climatic, elevational) to better understand how they assemble in space and time. However, to compare structure of networks that vary in size, shape and connectance, topological metrics need to be standardized (as most metrics covary with such network attributes). Traditionally, this has been done by transforming network metrics into z-scores prior comparisons. Here, I show that such standardized metrics are not independent of basic network properties such as connectance. Instead, I found that there was a consistent tendency for z-scores to approach 0 when connectance progressively decreased and approached its minimal value. This is probably due to the reduced null space available for null models to randomize interactions at such low connectance. I discuss ways to circumvent the problem in future studies.     

Interspecific networks in ground beetle (Coleoptera: Carabidae) assemblages

Although changes to interspecific relationships can significantly alter the composition of insect assemblages, they are often ignored when assessing impacts of environmental change. Long-term ground beetle data were used in this study to analyse ecological networks from three habitats at two sites in Scotland. A Bayesian Network inference algorithm was used to reveal interspecific relationships. The significance and strength of relationships between species (nodes) were estimated along with other network properties. Links were identified as positive relationships if co-occurrences of beetles correlated positively, and as negatives relationships if there was a negative correlation between the occurrences of the species. Most of the species had few links and only 10% of the nodes were connected with several links. Calathus fuscipes, a common carabid in the samples, was the most connected, with nine links to other species. More interspecific relationships were found to be positive than negative, with 48 and 23 links, respectively. The modular structure of the network was assessed and eight separate sub-networks were found. Habitat preferences of the species were clearly represented in the structure of the sets of those five sub-networks containing more than one species and were in line with the findings of the indicator species analysis. In our study, we showed that generated Bayesian networks can model interspecific relationships between carabid species. Due to the relative ease of the collection of field data and the high information content of the results, this method could be incorporated into everyday ecological analysis.     

Motifs in the assembly of food web networks

The assembly of local communities from regional pools is a multifaceted process that involves the confluence of interactions and environmental conditions at the local scale and biogeographic and evolutionary history at the regional scale. Understanding the relative influence of these factors on community structure has remained a challenge and mechanisms driving community assembly are often inferred from patterns of taxonomic, functional, and phylogenetic diversity. Moreover, community assembly is often viewed through the lens of competition and rarely includes trophic interactions or entire food webs. Here, we use motifs – subgraphs of nodes (e.g. species) and links (e.g. predation) whose abundance within a network deviates significantly as compared to a random network topology – to explore the assembly of food web networks found in the leaves of the northern pitcher plant Sarracenia purpurea. We compared counts of three‐node motifs across a hierarchy of scales to a suite of null models to determine if motifs are over‐, under‐, or randomly represented. We then assessed if the pattern of representation of a motif in a given network matched that of the network it was assembled from. We found that motif representation in over 70% of site networks matched the continental network they were assembled from and over 75% of local networks matched the site networks they were assembled from for the majority of null models. This suggests that the same processes are shaping networks across scales. To generalize our results and effectively use a motif perspective to study community assembly, a theoretical framework detailing potential mechanisms for all possible combinations of motif representation is necessary.     

Can plant-pollinator network metrics indicate environmental quality?

Plant-pollinator interaction networks may be more informative than the diversity of species in the evaluation of the effects of environmental change. Considering that networks vary with the integrity of ecosystems, their changes may help to predict the consequences of anthropogenic impacts on biodiversity and ecological processes. This characteristic highlights its use as environmental quality indicator. However, to employ interaction networks as ecological indicators it is necessary to identify the most sensitive metrics and understand how and why they vary with environmental changes. This review aimed to identify, in empirical studies, which network metrics have been evidenced as being more sensitive to changes in environmental quality. We analyzed published empirical studies, that applied the network approach on environmental quality gradients. In addition to the network metric behavior, we studied the interactions between them and possible causes of their variation. The available empirical data indicated that degree, nestedness and connectance did not have a simple, linear or unidirectional response to habitat degradation. Conversely, the metrics interaction asymmetry, d' (reciprocal specialization index of the species) showed the most consistent responses to environmental change. The role of the species changed, ranging between generalists and specialists under different conditions. In addition, specialist species with morphological and behavioral constraints were lost in worse environmental quality situations. The identity of interacting species and their role in the network, with a further specification of groups and interactions most affected, are the properties with greater potential to indicate changes in environmental quality. Most of the available studies focused on metrics at the network level, but several studies and this review indicate that the patterns at the network level can be better understood in the light of metrics analyzed at the species level. Our results provide information that enrich the network analysis, highlighting the need to consider important features that are often neglected. Discussions and information compiled here are important for deciding how to look at empirical data and what to look for, as well as to indicate some caveats when interpreting data on plant-pollinator interactions with a complex network approach. Network metrics can be good indicators of environmental quality if the underlying ecological causes of the numerical changes are carefully analyzed.     

Fine-scale spatial genetic structure across a strong environmental gradient in the saltmarsh plant <Emphasis Type="Italic">Puccinellia maritima</Emphasis>

Saltmarsh forms the transition between maritime and terrestrial environments where biotic and abiotic conditions vary substantially along a gradient in elevation. Theoretical and empirical population genetics studies have focused on the influence of environmental gradients on intra-specific genetic variation. Contrastingly, only a few studies have focused on genetic variation in saltmarsh plants, despite the potentially strong influence of environmental gradients shaping diversity in these species. In the present paper, we assess the genetic structure of the saltmarsh plant Puccinellia maritima collected across an elevation gradient in restored and natural saltmarsh. Both spatial autocorrelograms of genetic variation and spatial analysis of principal components detected genetic structure in the natural saltmarsh organized along the gradient in elevation, yet no such pattern was identified considering distance between individuals without taking elevation into account. In combination with previous phenotypic analyses, our results imply that ecological divergence likely plays a key role in shaping genetic structure within saltmarsh species. Comparison of restored and natural saltmarsh indicated that interspecific competition plays an important role in shaping the genetic structure observed on the natural saltmarsh. The results of this study demonstrate that saltmarshes are valuable models in which to test effects of ecological differentiation and, by extension, provide a better understanding of the functioning of this threatened environment.     

Rewiring and indirect effects underpin modularity reshuffling in a marine food web under environmental shifts

Species are characterized by physiological and behavioral plasticity, which is part of their response to environmental shifts. Nonetheless, the collective response of ecological communities to environmental shifts cannot be predicted from the simple sum of individual species responses, since co‐existing species are deeply entangled in interaction networks, such as food webs. For these reasons, the relation between environmental forcing and the structure of food webs is an open problem in ecology. To this respect, one of the main problems in community ecology is defining the role each species plays in shaping community structure, such as by promoting the subdivision of food webs in modules—that is, aggregates composed of species that more frequently interact—which are reported as community stabilizers. In this study, we investigated the relationship between species roles and network modularity under environmental shifts in a highly resolved food web, that is, a “weighted” ecological network reproducing carbon flows among marine planktonic species. Measuring network properties and estimating weighted modularity, we show that species have distinct roles, which differentially affect modularity and mediate structural modifications, such as modules reconfiguration, induced by environmental shifts. Specifically, short‐term environmental changes impact the abundance of planktonic primary producers; this affects their consumers’ behavior and cascades into the overall rearrangement of trophic links. Food web re‐adjustments are both direct, through the rewiring of trophic‐interaction networks, and indirect, with the reconfiguration of trophic cascades. Through such “systemic behavior,” that is, the way the food web acts as a whole, defined by the interactions among its parts, the planktonic food web undergoes a substantial rewiring while keeping almost the same global flow to upper trophic levels, and energetic hierarchy is maintained despite environmental shifts. This behavior suggests the potentially high resilience of plankton networks, such as food webs, to dramatic environmental changes, such as those provoked by global change.     

Invariant antagonistic network structure despite high spatial and temporal turnover of interactions

Recent work has suggested that emergent ecological network structure exhibits very little spatial or temporal variance despite changes in community composition. However, the changes in network interactions associated with turnover in community composition have seldom been assessed. Here we examine whether changes in ecological networks are best detected by standard emergent network metrics or by assessing internal network changes (i.e. interaction and composition turnover). To eliminate possible spatial or phylogenetic effects, that in large‐scale studies may obscure mechanisms structuring networks and interactions, we sampled multiple antagonistic (plant–herbivore) networks for a single diverse plant family (the Restionaceae) in the hyperdiverse Cape Floristic Region. These are the first plant–herbivore networks constructed for this global biodiversity hotspot. We found invariant emergent network structure despite considerable changes in insect and plant composition across communities over time and space. In contrast, there was high interaction turnover between networks. Seasonally, this was driven by turnover in insect species and insect host switching. Spatially, this was driven by simultaneous turnover in plant and insect species, suggesting that many insects are host specific or that both groups exhibit parallel responses to environmental gradients. Spatial interaction turnover was also driven by turnover in plants, showing that many insects can utilise multiple (possibly closely related) hosts and this may create divergent selection gradients that promote insect speciation. Thus we show highly variable interaction fidelity, despite invariant emergent network structure. We suggest that evaluating internal network changes may be more effective at elucidating the processes structuring networks, and many fine‐scale changes may be obscured when only calculating emergent network metrics.     

Testing for local adaptation and evolutionary potential along altitudinal gradients in rainforest Drosophila: beyond laboratory estimates

Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species’ abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species’ range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species’ distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high‐altitude sites, and declined towards warmer, low‐altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower‐altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species’ range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high‐altitude than low‐altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade‐offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species’ responses to environmental change.     

Strong, long-term temporal dynamics of an ecological network

Nature is organized into complex, dynamical networks of species and their interactions, which may influence diversity and stability. However, network research is, generally, short-term and depict ecological networks as static structures only, devoid of any dynamics. This hampers our understanding of how nature responds to larger disturbances such as changes in climate. In order to remedy this we studied the long-term (12-yrs) dynamics of a flower-visitation network, consisting of flower-visiting butterflies and their nectar plants. Global network properties, i.e. numbers of species and links, as well as connectance, were temporally stable, whereas most species and links showed a strong temporal dynamics. However, species of butterflies and plants varied bimodally in their temporal persistance: Sporadic species, being present only 1-2(-5) years, and stable species, being present (9-)11-12 years, dominated the networks. Temporal persistence and linkage level of species, i.e. number of links to other species, made up two groups of species: Specialists with a highly variable temporal persistence, and temporally stable species with a highly variable linkage level. Turnover of links of specialists was driven by species turnover, whereas turnover of links among generalists took place through rewiring, i.e. by reshuffling existing interactions. However, in spite of this strong internal dynamics of species and links the network appeared overall stable. If this global stability-local instability phenomenon is general, it is a most astonishing feature of ecological networks.     

Flower‐visitor networks only partially predict the function of pollen transport by bees

Mutualistic networks display distinct structural and organizational features such as nestedness, power‐law degree distribution and asymmetric dependencies. Attention is now focused on how these structural properties influence network function. Most plant‐pollinator networks are constructed using records of animals contacting flowers, which is based on the assumption that all visitors to flowers are pollinators; however, animals may visit flowers as nectar robbers, florivores, or to prey upon other visitors. To differentiate potential pollinator interactions from other interaction types, we examined individual bees that had visited flowers to detect if they carried pollen. Using these data, we constructed visitation and pollen‐transport networks for a spinifex‐dominated arid zone grassland. To determine how the structure of the visitation network reflects pollen transport, we compared the two networks using a null model approach to account for differences in network size. Differences in number of species, nestedness and connectance observed between the visitation and pollen‐transport networks were within expected ranges generated under the null model. The pollen‐transport network was more specialized, had lower interaction evenness, and fewer links compared to the visitation network. Almost half the number of species of the visitation network participated in the pollen‐transport network, and one‐third of unique visitation interactions resulted in pollen transport, highlighting that visitation does not always result in pollination. Floral visitor data indicate potential pollen transporters, but inferring pollination function from visitation networks needs to be performed cautiously as pollen transport resulted from both common and rare interactions, and depended on visitor identity. Although visitation and pollen‐transport networks are structurally similar, the function of all species cannot be predicted from the visitation network alone. Considering pollen transport in visitation networks is a simple first step towards determining pollinators from non‐pollinators. This is fundamental for understanding how network structure relates to network function.     

Antagonistic interaction networks are structured independently of latitude and host guild

An increase in species richness with decreasing latitude is a prominent pattern in nature. However, it remains unclear whether there are corresponding latitudinal gradients in the properties of ecological interaction networks. We investigated the structure of 216 quantitative antagonistic networks comprising insect hosts and their parasitoids, drawn from 28 studies from the High Arctic to the tropics. Key metrics of network structure were strongly affected by the size of the interaction matrix (i.e. the total number of interactions documented between individuals) and by the taxonomic diversity of the host taxa involved. After controlling for these sampling effects, quantitative networks showed no consistent structural patterns across latitude and host guilds, suggesting that there may be basic rules for how sets of antagonists interact with resource species. Furthermore, the strong association between network size and structure implies that many apparent spatial and temporal variations in network structure may prove to be artefacts.     

Partitioning the variation in African vertebrate distributions into environmental and spatial components – exploring the link between ecology and biogeography

There has been a proliferation of studies aimed at predicting the distributions of species from environmental variables despite evidence that spatial interpolation or spatially‐constrained mechanistic models have comparable explanatory power. Moreover, the processes behind environmental and spatial correlations – and their interactions – remain elusive. Here, we examined geographic patterns in the amount of variation explained by environmental correlation and exogenous or endogenous spatial autocorrelation for 4423 terrestrial vertebrate species in Africa using variation partitioning analysis. We also tested the effects of range size and taxonomic class on the relative importance of environmental and spatial correlations, and contrasted empirical patterns to two environmentally‐neutral models to identify potential underlying environmental and spatial mechanisms. Results showed that geographic range size was associated with environmental and spatial variation components in ways that where qualitatively indistinguishable from environmentally‐neutral species with constrained dispersal, suggesting that proportions of variation are due to range cohesiveness rather than other ecological processes. As a consequence, large‐scale patterns of biodiversity should be studied cautiously due to the difficulty of obtaining evidence of causal mechanistic links between species distributions and spatio‐environmental gradients. However, we also uncovered ecologically‐meaningful patterns in the residuals of the relationship between range size and the respective variation components, which differed among vertebrate classes. Moreover, these patterns coincided with contemporary biogeographical regions. This study, therefore, demonstrates that it is possible to extract meaningful environmental and spatial associations that potentially link ecological and biogeographical processes.     

Environmental Stress, Bottom-up Effects, and Community Dynamics: Integrating Molecular-Physiological and Ecological Approaches

Environmental stress and nutrient/productivity models predict the responses of community structure along gradients of physical conditions and bottom-up effects. Although both models have succeeded in helping to understand variation in ecological communities, most tests have been qualitative. Until recently, two roadblocks to more quantitative tests in marine environments have been a lack of (1) inexpensive, field-deployable technology for quantifying (e.g.) temperature, light, salinity, chlorophyll, and productivity, and (2) methods of quantifying the sub-organismal mechanisms linking environmental conditions to their ecological expression. The advent of inexpensive remote-sensing technology, adoption of molecular techniques such as quantification of heat-shock proteins and RNA:DNA ratios, and the formation of interdisciplinary alliances between ecologists and physiologists has begun to overcome these roadblocks. An integrated eco-physiological approach focuses on the determinants of: distributional limits among microhabitat patches and along (local-scale) environmental gradients (e.g., zonation); among-site (mesoscale) differences in community pattern; and geographic (macroscale) differences in ecosystem structure. These approaches promise new insights into the physiological mechanisms underlying variation in processes such as species interactions, physical disturbance, survival and growth. Here, we review two classes of models for community dynamics, and present examples of ecological studies of these models in consumer-prey systems. We illustrate the power of new molecular tools to characterize the sub-organismal responses of some of the same consumers and prey to thermal stress and food concentration. Ecological and physiological evidence tends to be consistent with model predictions, supporting our argument that we are poised to make major advances in the mechanistic understanding of community dynamics along key environmental gradients.     

Including species interactions in risk assessments for global change

Most ecological risk assessments for global change are restricted to the effects of trends in climate or atmospheric carbon dioxide. In order to move beyond investigation of the effects of climate alone, the climex ^™ model was extended to investigate the effects of species interactions, in the same or different trophic levels, along environmental gradients on a geographical scale. Specific needs that were revealed during the investigations include: better treatment of the effects of temporal and spatial climatic variation; elucidation of the nature of boundaries of species ranges; data to quantify the role of species traits in interspecies interactions; integrated observational, experimental, and modelling studies on mechanisms of species interactions along environmental gradients; and high‐resolution global environmental datasets. Greater acknowledgement of the shared limitations of simplified models and experimental studies is also needed. Above all, use of the scientific method to understand representative species ranges is essential. This requires the use of mechanistic approaches capable of progressive enhancement.     

Resource availability determines the importance of niche‐based versus stochastic community assembly in grasslands

Niche‐based selection and stochastic processes can operate simultaneously to generate spatial and temporal variation in species composition. Yet, the conditions under which ecological dynamics are dominated by niche‐based versus stochastic processes are poorly understood. Using a field experiment in early‐successional temperate grassland and null models of beta diversity, this study investigates the effects of soil nutrient supply on the relative importance of niche‐based selection versus stochastic dynamics for variation in species composition among sites. Nutrient availability was manipulated experimentally, individual seed mixtures with 25 species were sown in each experimental plot, and then stochastic and deterministic niche‐based assembly processes were allowed to happen. We found that compositional variation among grassland plots with low nutrient supply was driven by stochastic immigration and extinctions. In contrast, nutrient enrichment reduced the importance of stochasticity and imposed a deterministic environmental filter that homogenized communities through the selection of few species with greater competitive ability for light. This demonstrates that soil nutrient availability is a critical environmental feature that dictates the degree to which terrestrial plant communities are controlled by niche‐based selection versus stochastic assembly processes. Our study shows further that alternative states of eutrophic grasslands emerge from initial stochastic variation in the composition of a particular functional group of species that can become dominant at high nutrient supply. We discuss potential mechanisms underlying the shift from stochastic to niche‐driven dynamics along soil nutrient gradients.