Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R-and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples.

The extent to which behavioural choices reflect fine-tuned evolutionary adaptation remains an open debate. For herbivorous insects, the preference-performance hypothesis (PPH) states that female insects will evolve to oviposit on hosts on which their offspring fare best. In this study, we use meta-analysis to assess the balance of evidence for and against the PPH, and to evaluate the role of individual factors proposed to influence host selection by female insects. We do so in an explicitly bitrophic context (herbivores versus plants). Overall, our analyses offer clear support for the PPH: Offspring survive better on preferred plant types, and females lay more eggs on plant types conducive to offspring performance. We also found evidence for an effect of diet breadth on host choice: female preference for Ôgood quality plantsÕ was stronger in oligophagous insects than in polyphagous insects. Nonetheless, despite the large numbers of preference-performance studies conducted to date, sample sizes in our meta-analysis are low due to the inconsistent format used by authors to present their results. To improve the situation, we invite authors to contribute to the data base emerging from this work, with the aim of reaching a strengthened synthesis of the subject field.

Biotic interactions underlie ecosystem structure and function, but predicting interaction outcomes is difficult. We tested the hypothesis that biotic interaction strength increases toward the equator, using a global experiment with model caterpillars to measure predation risk. Across an 11,660-kilometer latitudinal gradient spanning six continents, we found increasing predation toward the equator, with a parallel pattern of increasing predation toward lower elevations. Patterns across both latitude and elevation were driven by arthropod predators, with no systematic trend in attack rates by birds or mammals. These matching gradients at global and regional scales suggest consistent drivers of biotic interaction strength, a finding that needs to be integrated into general theories of herbivory, community organization, and life-history evolution.

Most eukaryotic organisms are arthropods. Yet, their diversity in rich terrestrial ecosystems is still unknown. Here we produce tangible estimates of the total species richness of arthropods in a tropical rainforest. Using a comprehensive range of structured protocols, we sampled the phylogenetic breadth of arthropod taxa from the soil to the forest canopy in the San Lorenzo forest, Panama. We collected 6144 arthropod species from 0.48 hectare and extrapolated total species richness to larger areas on the basis of competing models. The whole 6000-hectare forest reserve most likely sustains 25,000 arthropod species. Notably, just 1 hectare of rainforest yields >60% of the arthropod biodiversity held in the wider landscape. Models based on plant diversity fitted the accumulated species richness of both herbivore and nonherbivore taxa exceptionally well. This lends credence to global estimates of arthropod biodiversity developed from plant models.M ost eukaryote species are terrestrial arthropods (1), and most terrestrial arthropods occur in tropical rainforests (2). However, considerably greater sampling effort is required in tropical arthropod surveys to yield realistic estimates of global species richness (3-7). A basic hindrance to estimating global biodiversity lies in a lack of empirical data that establish local biodiversity, which can be scaled up to achieve a global estimate.Although many studies reported species richness for selected groups of well-studied insect taxa, no satisfactory estimate of total arthropod species richness exists for a single tropical rainforest location to date.The unstructured collection and small-scale survey of tropical arthropods cannot yield convincing estimates of total species richness at a specific forest (7-9). Most studies either target few arthropod orders or trophic guilds, or use a limited array of sampling methods, or ignore the diverse upper canopy regions of tropical forests (10-15). Moreover, sampling protocols have rarely been structured in such a way that, with increased sampling, incomplete data on local diversity (7) can be extrapolated to estimate total species richness across multiple spatial scales (16). Where such structured estimates are made, it is invariably for insect herbivores on their host plants (5). However, species accumulation rates may differ markedly for nonherbivore guilds, which include more than half of all described arthropod species (1, 17). As the degree of host specificity (effective specialization) of other guilds can be much lower than that of insect herbivores, or may be driven by different factors (18,19), global estimates based on herbivores alone are questionable. Consequently, extensive cross-taxon surveys with structured protocols at reference sites may be the only effective approach toward estimating total arthropod species richness in tropical forests (3).To provide a comprehensive estimate of total arthropod species richness in a tropical rainforest, we established a collaboration involving 102 researchers with expertise encom...

A large array of species distribution model (SDM) approaches has been developed for explaining and predicting the occurrences of individual species or species assemblages. Given the wealth of existing models, it is unclear which models perform best for interpolation or extrapolation of existing data sets, particularly when one is concerned with species assemblages. We compared the predictive performance of 33 variants of 15 widely applied and recently emerged SDMs in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDMs that model each species individually combining the predictions afterward. We offer a comprehensive evaluation of these SDM approaches by examining their performance in predicting withheld empirical validation data of different sizes representing five different taxonomic groups, and for prediction tasks related to both interpolation and extrapolation. We measure predictive performance by 12 measures of accuracy, discrimination power, calibration, and precision of predictions, for the biological levels of species occurrence, species richness, and community composition. Our results show large variation among the models in their predictive performance, especially for communities comprising many species that are rare. The results do not reveal any major trade‐offs among measures of model performance; the same models performed generally well in terms of accuracy, discrimination, and calibration, and for the biological levels of individual species, species richness, and community composition. In contrast, the models that gave the most precise predictions were not well calibrated, suggesting that poorly performing models can make overconfident predictions. However, none of the models performed well for all prediction tasks. As a general strategy, we therefore propose that researchers fit a small set of models showing complementary performance, and then apply a cross‐validation procedure involving separate data to establish which of these models performs best for the goal of the study.

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.

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.

Oaks have been one of the classic model systems in elucidating the role of polyphenols in plant-herbivore interactions. This study provides a comprehensive description of seasonal variation in the phenolic content of the English oak (Quercus robur). Seven different trees were followed over the full course of the growing season, and their foliage repeatedly sampled for gallic acid, 9 individual hydrolyzable tannins, and 14 flavonoid glycosides, as well as for total phenolics, total proanthocyanidins, carbon, and nitrogen. A rare dimeric ellagitannin, cocciferin D2, was detected for the first time in leaves of Q. robur, and relationships between the chemical structures of individual tannins were used to propose a biosynthetic pathway for its formation. Overall, hydrolyzable tannins were the dominant phenolic group in leaves of all ages. Nevertheless, young oak leaves were much richer in hydrolyzable tannins and flavonoid glycosides than old leaves, whereas the opposite pattern was observed for proanthocyanidins. However, when quantified as individual compounds, hydrolyzable tannins and flavonoid glycosides showed highly variable seasonal patterns. This large variation in temporal trends among compounds, and a generally weak correlation between the concentration of any individual compound and the total concentration of phenolics, as quantified by the Folin-Ciocalteau method, leads us to caution against the uncritical use of summary quantifications of composite phenolic fractions in ecological studies.