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

Assessing mutualistic metacommunity capacity by integrating spatial and interaction networks

We develop a spatially realistic model of mutualistic metacommunities that exploits the joint structure of spatial and interaction networks. Assuming that all species have the same colonisation and extinction parameters, this model exhibits a sharp transition between stable non-null equilibrium states and a global extinction state. This behaviour allows defining a threshold on colonisation/extinction parameters for the long-term metacommunity persistence. This threshold, the 'metacommunity capacity', extends the metapopulation capacity concept and can be calculated from the spatial and interaction networks without needing to simulate the whole dynamics. In several applications we illustrate how the joint structure of the spatial and the interaction networks affects metacommunity capacity. It results that a weakly modular spatial network and a power-law degree distribution of the interaction network provide the most favourable configuration for the long-term persistence of a mutualistic metacommunity. Our model that encodes several explicit ecological assumptions should pave the way for a larger exploration of spatially realistic metacommunity models involving multiple interaction types.

Biodiversity modeling advances will improve predictions of nature's contributions to people

Accurate predictions of ecosystem functions and nature's contributions to people (NCP) are needed to prioritize environmental protection and restoration in the Anthropocene. However, our ability to predict NCP is undermined by approaches that rely on biophysical variables and ignore those describing biodiversity, which have strong links to NCP. To foster predictive mapping of NCP, we should harness the latest methods in biodiversity modeling. This field advances rapidly, and new techniques with promising applications for predicting NCP are still underutilized. Here, we argue that employing recent advances in biodiversity modeling can enhance the accuracy and scope of NCP maps and predictions. This enhancement will contribute significantly to the achievement of global objectives to preserve NCP, for both the present and an unpredictable future.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Integrating databases for spatial analysis of parasite-host associations and the novel Brazilian dataset

Incomplete information on parasites, their associated hosts, and their precise geographical location hampers the ability to predict disease emergence in Brazil, a continental-sized country characterised by significant regional disparities. Here, we demonstrate how the NCBI Nucleotide and GBIF databases can be used as complementary databases to study spatially georeferenced parasite-host associations. We also provide a comprehensive dataset of parasites associated with mammal species that occur in Brazil, the Brazilian Mammal Parasite Occurrence Data (BMPO). This dataset integrates wild mammal species' morphological and life-history traits, zoonotic parasite status, and zoonotic microparasite transmission modes. Through meta-networks, comprising interconnected host species linked by shared zoonotic microparasites, we elucidate patterns of zoonotic microparasite dissemination. This approach contributes to wild animal and zoonoses surveillance, identifying and targeting host species accountable for disproportionate levels of parasite sharing within distinct biomes. Moreover, our novel dataset contributes to the refinement of models concerning disease emergence and parasite distribution among host species.

The role of intra-guild indirect interactions in assembling plant-pollinator networks

Understanding the assembly of plant-pollinator communities has become critical to their conservation given the rise of species invasions, extirpations, and species' range shifts. Over the course of assembly, colonizer establishment produces core interaction patterns, called motifs, which shape the trajectory of assembling network structure. Dynamic assembly models can advance our understanding of this process by linking the transient dynamics of colonizer establishment to long-term network development. In this study, we investigate the role of intra-guild indirect interactions and adaptive foraging in shaping the structure of assembling plant-pollinator networks by developing: 1) an assembly model that includes population dynamics and adaptive foraging, and 2) a motif analysis tracking the intra-guild indirect interactions of colonizing species throughout their establishment. We find that while colonizers leverage indirect competition for shared mutualistic resources to establish, adaptive foraging maintains the persistence of inferior competitors. This produces core motifs in which specialist and generalist species coexist on shared mutualistic resources which leads to the emergence of nested networks. Further, the persistence of specialists develops richer and less connected networks which is consistent with empirical data. Our work contributes new understanding and methods to study the effects of species' intra-guild indirect interactions on community assembly.

Potential decline in the distribution and food provisioning services of the mopane worm (Gonimbrasia belina) in southern Africa

The mopane worm (Gonimbrasia belina) is an edible insect distributed across southern Africa. As a culturally important source of food, the mopane worm provides nutrition, livelihoods and improves wellbeing for rural communities across its range. However, this is strong evidence that insect populations are declining worldwide, and climate change is likely to cause many insect species to shift in their distributions. For these reasons, we aimed to model how the ecosystem service benefits of the mopane worm are likely to change in the coming decades. We modelled the distribution of the mopane worm under two contrasting climate change scenarios (RCPs 4.5 and 8.5). Moreover, given that the mopane worm shows strong interactions with other species, particularly trees, we incorporated biotic interactions in our models using a Bayesian network. Our models project significant contraction across the species' range, with up to 70% decline in habitat by the 2080s. Botswana and Zimbabwe are predicted to be the most severely impacted countries, with almost all habitat in Botswana and Zimbabwe modelled to be lost by the 2080s. Decline of mopane worm habitat would likely have negative implications for the health of people in rural communities due to loss of an important source of protein as well as household income provided by their harvest. Biogeographic shifts therefore have potential to exacerbate food insecurity, socio-economic inequalities, and gender imbalance (women are the main harvesters), with cascading effects that most negatively impact poor rural communities dependent on natural resources.

Mutualistic interactions shape global spatial congruence and climatic niche evolution in Neotropical mimetic butterflies

Understanding the mechanisms underlying species distributions and coexistence is both a priority and a challenge for biodiversity hotspots such as the Neotropics. Here, we highlight that Müllerian mimicry, where defended prey species display similar warning signals, is key to the maintenance of biodiversity in the c. 400 species of the Neotropical butterfly tribe Ithomiini (Nymphalidae: Danainae). We show that mimicry drives large-scale spatial association among phenotypically similar species, providing new empirical evidence for the validity of Müller's model at a macroecological scale. Additionally, we show that mimetic interactions drive the evolutionary convergence of species climatic niche, thereby strengthening the co-occurrence of co-mimetic species. This study provides new insights into the importance of mutualistic interactions in shaping both niche evolution and species assemblages at large spatial scales. Critically, in the context of climate change, our results highlight the vulnerability to extinction cascades of such adaptively assembled communities tied by positive interactions.

Disentangling the contributions of biotic and abiotic predictors in the niche and the species distribution model of Trypanosoma cruzi, etiological agent of Chagas disease

The potential benefits of incorporating biotic, as well as abiotic, predictors in niche and species distribution models (SDMs), as well as how to achieve this, is still debated, with their interpretability and explanatory potential being particularly questioned. It is therefore important to stress test modelling methodologies that include biotic factors against use cases where there is ample knowledge of the potential biotic component of the niche. Relatively well studied and important vector-borne diseases offer just such an opportunity, where knowledge of the agents involved in the transmission cycle -vectors and hosts- can serve to calibrate and test the niche model and corresponding SDM. Here, we study the contributions of biotic -14 vectors, 459 potential hosts- and abiotic -258 climatic categories- predictors to the explanatory and predictive features of the niche and corresponding SDM for the etiological agent of Chagas disease, Trypanosoma cruzi, in Mexico. Using an established spatial data mining technique, we generate biotic, abiotic and biotic+abiotic niche and SDM models. We test our models by comparing predictions of the most important probable hosts of Chagas disease with a previously published list of confirmed hosts. We quantify, compare, and contrast the individual and total contributions of predictors to the niche and distribution of Chagas disease in Mexico. We assess the relative predictive potential of these variables to model performance, showing that models that include relevant biotic niche variables lead to more predictive, more ecologically realistic SDMs. Our research illustrates a useful general procedure for identifying and ranking potential biotic interactions and for assessing the relative importance of biotic and abiotic predictors. We conclude that the inclusion of both abiotic and biotic predictors in SDMs not only provides more predictive and accurate models but also models that are more understandable and explainable from an ecological niche perspective.

The Resilience of Plant-Pollinator Networks

There is growing awareness of pollinator declines worldwide. Conservation efforts have mainly focused on finding the direct causes, while paying less attention to building a systemic understanding of the fragility of these communities of pollinators. To fill this gap, we need operational measures of network resilience that integrate two different approaches in theoretical ecology. First, we should consider the range of conditions compatible with the stable coexistence of all of the species in a community. Second, we should address the rate and shape of network collapse once this safe operational space is exited. In this review, we describe this integrative approach and consider several mechanisms that may enhance the resilience of pollinator communities, chiefly rewiring the network of interactions, increasing heterogeneity, allowing variance, and enhancing coevolution. The most pressing need is to develop ways to reduce the gap between these theoretical recommendations and practical applications. This perspective shifts the emphasis from traditional approaches focusing on the equilibrium states to strategies that allow pollination networks to cope with global environmental change.

Biotic Interactions and the Future of Fishes on Coral Reefs: The Importance of Trait-Based Approaches

Biotic interactions govern the structure and function of coral reef ecosystems. As environmental conditions change, reef-associated fish populations can persist by tracking their preferred niche or adapting to new conditions. Biotic interactions will affect how these responses proceed and whether they are successful. Yet, our understanding of these effects is currently limited. Ecological and evolutionary theories make explicit predictions about the effects of biotic interactions, but many remain untested. Here, we argue that large-scale functional trait datasets enable us to investigate how biotic interactions have shaped the assembly of contemporary reef fish communities and the evolution of species within them, thus improving our ability to predict future changes. Importantly, the effects of biotic interactions on these processes have occurred simultaneously within dynamic environments. Functional traits provide a means to integrate the effects of both ecological and evolutionary processes, as well as a way to overcome some of the challenges of studying biotic interactions. Moreover, functional trait data can enhance predictive modeling of future reef fish distributions and evolvability. We hope that our vision for an integrative approach, focused on quantifying functionally relevant traits and how they mediate biotic interactions in different environmental contexts, will catalyze new research on the future of reef fishes in a changing environment.

Biocrusts mediate the plant community composition of dryland restoration ecosystems

Degradation and expansion are current threats associated with drylands. During natural or artificial restoration, dryland ecosystems tend to contain a unique community, namely, biocrusts. Studies have shown that biocrusts serve multiple functions and have the potential to accelerate or inhibit degradation. However, the mechanisms by which biocrusts mediate dryland plant community structure and composition remain largely unknown. In this study, we performed a series of pot experiments under greenhouse conditions at three disturbance levels (strong, moderate and no disturbance) and at three rainfall gradients (- 50 %, normal, + 50 %) for different biocrust types. Our objective was to examine how biocrusts influence the introduction and establishment of different functional forms of plant species during the different succession stages of dryland recovery. Our results showed that biocrusts have significantly different effects on the seed germination and survival of the tested plant species. Although strong disturbances to the biocrusts and increasing rainfall alleviated the inhibitory effects of biocrusts on the perennial herb (S. glareosa) and subshrub (C. latens) species, these factors could only promote the temporary survival of these two plants in the revegetated area. These results indicate that biocrusts in revegetated systems play important sieving functions during plant species establishment. Additionally, the survival of S. viridis, a plant species with small seeds adapted to the current habitat, was promoted in the community, but two plant species that are currently unsuitable, S. glareosa and C. latens, were filtered out by the biocrusts. Our conclusions suggest that biocrusts play an ecological filtering role in plant species introduction and establishment in revegetated ecosystems and demonstrate the scientific significance of biocrusts in maintaining the health and stability of dryland ecosystems.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Microclimate and resource quality determine resource use in a range-expanding herbivore

The consequences of climate change for biogeographic range dynamics depend on the spatial scales at which climate influences focal species directly and indirectly via biotic interactions. An overlooked question concerns the extent to which microclimates modify specialist biotic interactions, with emergent properties for communities and range dynamics. Here, we use an in-field experiment to assess egg-laying behaviour of a range-expanding herbivore across a range of natural microclimatic conditions. We show that variation in microclimate, resource condition and individual fecundity can generate differences in egg-laying rates of almost two orders of magnitude in an exemplar species, the brown argus butterfly (Aricia agestis). This within-site variation in fecundity dwarfs variation resulting from differences in average ambient temperatures among populations. Although higher temperatures did not reduce female selection for host plants in good condition, the thermal sensitivities of egg-laying behaviours have the potential to accelerate climate-driven range expansion by increasing egg-laying encounters with novel hosts in increasingly suitable microclimates. Understanding the sensitivity of specialist biotic interactions to microclimatic variation is, therefore, critical to predict the outcomes of climate change across species' geographical ranges, and the resilience of ecological communities.

Learning from differences: Abiotic determinism of benthic communities in Northern Taiwan

Differences in the initial configuration of ecological communities may lead to contrasting trajectories when facing environmental changes. Here, we propose to uncover the determinism of benthic communities by carrying out a detailed investigation of their response to small-scale modification of environmental conditions, including physical, chemical, and geological factors. At ten locations (confounding site and depth) in Northern Taiwan, communities were delineated using a morpho-functional classification of the organisms. A k-means clustering was used to identify k homogenous groups among transects. Their environmental determinism was examined by combining this result with 16 environmental variables of transect conditions into a regression tree framework. Biotic and abiotic data were further analyzed with a Multivariate Regression Tree (MRT) to ascertain the hierarchical environmental determinism. The classifications produced by both approaches were compared using the Adjusted Rand index (ARI) to assess the predictive power of unsupervised clustering on its missing explanatory components (abiotic variables). k-means and MRT produced five clusters, respectively, with a similarity of 0.82 in ARI. Wave motion, followed by substrate types resolved most of the variance, while chemical factors in this study were uniform throughout the region. Comparable structures for both methods (clustering groups) demonstrated that the delineated clusters matched with contrasting environmental conditions which could be explained by the existence of various benthic communities. Further consideration of these different communities and their environmental context will be important in determining their trajectories under global changes and may help in the interpretation of community modifications with changing environmental conditions.

Effects of climate variation on bird escape distances modulate community responses to global change

Climate and land use are rapidly changing environmental conditions. Behavioral responses to such global perturbations can be used to incorporate interspecific interactions into predictive models of population responses to global change. Flight initiation distance (FID) reflects antipredator behaviour defined as the distance at which an individual takes flight when approached by a human, under standardized conditions. This behavioural trait results from a balance between disturbance, predation risk, food availability and physiological needs, and it is related to geographical range and population trends in European birds. Using 32,145 records of flight initiation distances for 229 bird species during 2006–2019 in 24 European localities, we show that FIDs decreased with increasing temperature and precipitation, as expected if foraging success decreased under warm and humid conditions. Trends were further altered by latitude, urbanisation and body mass, as expected if climate effects on FIDs were mediated by food abundance and need, differing according to position in food webs, supporting foraging models. This provides evidence for a role of behavioural responses within food webs on how bird populations and communities are affected by global change.

Temperature and Prey Species Richness Drive the Broad-Scale Distribution of a Generalist Predator

The ongoing climate change and the unprecedented rate of biodiversity loss render the need to accurately project future species distributional patterns more critical than ever. Mounting evidence suggests that not only abiotic factors, but also biotic interactions drive broad-scale distributional patterns. Here, we explored the effect of predator-prey interaction on the predator distribution, using as target species the widespread and generalist grass snake (Natrix natrix). We used ensemble Species Distribution Modeling (SDM) to build a model only with abiotic variables (abiotic model) and a biotic one including prey species richness. Then we projected the future grass snake distribution using a modest emission scenario assuming an unhindered and no dispersal scenario. The two models performed equally well, with temperature and prey species richness emerging as the top drivers of species distribution in the abiotic and biotic models, respectively. In the future, a severe range contraction is anticipated in the case of no dispersal, a likely possibility as reptiles are poor dispersers. If the species can disperse freely, an improbable scenario due to habitat loss and fragmentation, it will lose part of its contemporary distribution, but it will expand northwards.

On the Interpretations of Joint Modeling in Community Ecology

Explaining and modeling species communities is more than ever a central goal of ecology. Recently, joint species distribution models (JSDMs), which extend species distribution models (SDMs) by considering correlations among species, have been proposed to improve species community analyses and rare species predictions while potentially inferring species interactions. Here, we illustrate the mathematical links between SDMs and JSDMs and their ecological implications and demonstrate that JSDMs, just like SDMs, cannot separate environmental effects from biotic interactions. We provide a guide to the conditions under which JSDMs are (or are not) preferable to SDMs for species community modeling. More generally, we call for a better uptake and clarification of novel statistical developments in the field of biodiversity modeling.

Greater topoclimatic control of above- versus below-ground communities

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above-ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above- and below-ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above-ground species than on below-ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above-ground than for below-ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above- and below-ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems.

Multiple facets of marine biodiversity in the Pacific Arctic under future climate

Climate change is triggering a global reorganization of marine life. Biogeographical transition zones, diversity-rich regions straddling biogeographical units where many species live at, or close to, their physiological tolerance limits (i.e., range distribution edges), are redistribution hotspots that offer a unique opportunity to understand the mechanisms and consequences of climate-driven thermophilization processes in natural communities. In this context, we examined the impacts of climate change projections in the 21st century (2026-2100) on marine biodiversity in the Eastern Bering and Chukchi seas within the Pacific Arctic, a climatically exposed and sensitive boreal-to-Arctic transition zone. Overall, projected changes in species distributions, modeled using species distribution models, resulted in poleward increases in species richness and functional redundancy, along with pronounced reductions in phylogenetic distances by century's end (2076-2100). Future poleward shifts of boreal species in response to warming and sea ice changes are projected to alter the taxonomic and functional biogeography of contemporary Arctic communities as larger, longer-lived and more predatory taxa expand their leading distributional margins. Drawing from the existing evidence from other Arctic regions, these changes are anticipated to increase the susceptibility and vulnerability of the Arctic ecosystems, as trophic connectance between biological components increases, thus decreasing the modularity of Arctic food webs. Our results demonstrate how integrating multiple diversity facets can provide key insights into the relationships between climate change, species composition and ecosystem functioning across marine biogeographic regions.

Distribution and conservation of species is misestimated if biotic interactions are ignored: the case of the orchid Laelia speciosa

The geographic distribution of species depends on their relationships with climate and on the biotic interactions of the species. Ecological Niche Models (ENMs) mainly consider climatic variables only and may tend to overestimate these distributions, especially for species strongly restricted by biotic interactions. We identified the preference of Laelia speciosa for different host tree species and include this information in an ENM. The effect of habitat loss and climate change on the distribution of these species was also estimated. Although L. speciosa was recorded as epiphyte at six tree species, 96% of the individuals were registered at one single species (Quercus deserticola), which indicated a strong biotic interaction. We included the distribution of this host tree as a biotic variable in the ENM of L. speciosa. The contemporary distribution of L. speciosa is 52,892 km2, which represent 4% of Mexican territory and only 0.6% of the distribution falls within protected areas. Habitat loss rate for L. speciosa during the study period was 0.6% per year. Projections for 2050 and 2070 under optimistic and pessimistic climate change scenarios indicated a severe reduction in its distribution. Climaticaly suitable areas will also shift upwards (200-400 m higher). When estimating the distribution of a species, including its interactions can improve the performance of the ENMs, allowing for more  accurate estimates of the actual distribution of the species, which in turn allows for better conservation strategies.

Predictor species: Improving assessments of rare species occurrence by modeling environmental co-responses

Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co-occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co-responses among species. For species from a European peat bog community, our approach consistently performs better than single-species models and better than conventional multi-species approaches that include the presence of nontarget species as additional independent variables in regression models. Our approach performs particularly well with rare species and when calibration data are limited. Furthermore, we identify a group of "predictor species" that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices.

Integrating Computational Methods to Investigate the Macroecology of Microbiomes

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as “everything is everywhere, but the environment selects”) as well as applied ecological problems, such as those posed by human induced global environmental changes.

Climate shapes mammal community trophic structures and humans simplify them

Nature’s complexity is intriguing, but the circumstances determining whether or how order emerges from such complexity remains a matter of extensive research. Using the geographical distributions and food preferences of all terrestrial mammal species with masses >3 kg, we show that large mammals group into feeding guilds (species exploiting similar resources) and that these guilds form trophic structures that vary across biomes globally. We identify five trophic structures closely matching climate variability and named them boreal, temperate, semiarid, seasonal tropical and humid tropical owing to their relative overlap with the distribution of biomes. We also find that human activities simplify trophic structures, generally transitioning them to species-poorer states. Detected transitions include boreal and temperate structures becoming depauperate or seasonal- and humid-tropical becoming semiarid. Whether the observed generalities among trophic structures of large mammals are indicative of patterns across whole food webs is matter for further investigation. The results help refine projections of the effects of environmental change on the trophic structure of large mammals.

Broad scale patterns in the distribution of animal community functional properties could be determined by climate and disrupted by human activities. Here the authors show global patterns in large-mammal trophic structure related to climate variation, which human activities simplify in predictable ways.

Biodiversity patterns across taxonomic groups along a lake water-depth gradient: Effects of abiotic and biotic drivers

Understanding biodiversity patterns and the role of biotic attributes in governing these patterns remains one of the most important challenges in ecology. Here, taking water depth in Lake Lugu as a typical geographical gradient, we studied how these different taxa, that is bacteria, diatoms and chironomids, respond to the water depth and environmental gradients using molecular and morphological methods. We further evaluated the relative importance of water depth, environmental variables and biotic attributes in explaining biological characteristics, such as biomass, species richness, and community composition. The biomass of chironomids and the richness of bacteria and chironomids showed a nonlinearly decreasing pattern associated with increased water depth, while biomass and species richness of diatoms showed U-shaped and hump-shaped patterns, respectively. The three taxonomic groups all showed increasing dissimilarity with water depth changes, and there was clear cross-taxon congruence among the variations in community composition. Abiotic variables were pivotal in structuring biological characteristics; however, the biotic attributes also explained a unique portion of their variations. This suggests that biotic interactions significantly influenced the patterns of biomass, species richness, and community compositions along the water depth gradient for the three taxonomic groups studied. Our results provide new evidence that biotic attributes could help in predicting the biodiversity of aquatic communities along geographical gradients, such as water depth.

Research applications of primary biodiversity databases in the digital age

Our world is in the midst of unprecedented change-climate shifts and sustained, widespread habitat degradation have led to dramatic declines in biodiversity rivaling historical extinction events. At the same time, new approaches to publishing and integrating previously disconnected data resources promise to help provide the evidence needed for more efficient and effective conservation and management. Stakeholders have invested considerable resources to contribute to online databases of species occurrences. However, estimates suggest that only 10% of biocollections are available in digital form. The biocollections community must therefore continue to promote digitization efforts, which in part requires demonstrating compelling applications of the data. Our overarching goal is therefore to determine trends in use of mobilized species occurrence data since 2010, as online systems have grown and now provide over one billion records. To do this, we characterized 501 papers that use openly accessible biodiversity databases. Our standardized tagging protocol was based on key topics of interest, including: database(s) used, taxa addressed, general uses of data, other data types linked to species occurrence data, and data quality issues addressed. We found that the most common uses of online biodiversity databases have been to estimate species distribution and richness, to outline data compilation and publication, and to assist in developing species checklists or describing new species. Only 69% of papers in our dataset addressed one or more aspects of data quality, which is low considering common errors and biases known to exist in opportunistic datasets. Globally, we find that biodiversity databases are still in the initial stages of data compilation. Novel and integrative applications are restricted to certain taxonomic groups and regions with higher numbers of quality records. Continued data digitization, publication, enhancement, and quality control efforts are necessary to make biodiversity science more efficient and relevant in our fast-changing environment.

Research priorities for maintaining biodiversity's contributions to people in Latin America

Maintaining biodiversity is crucial for ensuring human well-being. The authors participated in a workshop held in Palenque, Mexico, in August 2018, that brought together 30 mostly early-career scientists working in different disciplines (natural, social and economic sciences) with the aim of identifying research priorities for studying the contributions of biodiversity to people and how these contributions might be impacted by environmental change. Five main groups of questions emerged: (1) Enhancing the quantity, quality, and availability of biodiversity data; (2) Integrating different knowledge systems; (3) Improved methods for integrating diverse data; (4) Fundamental questions in ecology and evolution; and (5) Multi-level governance across boundaries. We discuss the need for increased capacity building and investment in research programmes to address these challenges.

Biological and environmental drivers of trophic ecology in marine fishes - a global perspective

Dietary niche width and trophic position are key functional traits describing a consumer’s trophic ecology and the role it plays in a community. However, our understanding of the environmental and biological drivers of both traits is predominantly derived from theory or geographically restricted studies and lacks a broad empirical evaluation. We calculated the dietary niche width and trophic position of 2,938 marine fishes and examined the relationship of both traits with species’ maximum length and geographic range, in addition to species richness, productivity, seasonality and water temperature within their geographic range. We used Generalized Additive Models to assess these relationships across seven distinct marine habitat types. Fishes in reef associated habitats typically had a smaller dietary niche width and foraged at a lower trophic position than those in pelagic or demersal regions. Species richness was negatively related to dietary niche width in each habitat. Species range and maximum length both displayed positive associations with dietary niche width. Trophic position was primarily related to species maximum length but also displayed a non-linear relationship with dietary niche width, whereby species of an intermediate trophic position (3–4) had a higher dietary niche width than obligate herbivores or piscivores. Our results indicate that trophic ecology of fishes is driven by several interlinked factors. Although size is a strong predictor of trophic position and the diversity of preys a species can consume, dietary niche width of fishes is also related to prey and competitor richness suggesting that, at a local level, consumer trophic ecology is determined by a trade-off between environmental drivers and biological traits.

Micro- or macroscale? Which one best predicts the establishment of an endemic Atlantic Forest palm?

Historically, macroecology and microecology have diverged with regard to the niche concept. A better understanding of functioning ecological systems, however, depends on an integrative approach to this concept at different spatial scales. A mixed approach, merging macro- and microscale by validating ecological niche modeling (ENM) with the results of in situ experiments and environmental data collection was used to understand if areas identified by ENM as highly suitable for adult palms are also adequate for seedling establishment. Syagrus weddelliana's (Arecaceae) distribution range falls within the Atlantic Rain Forest, and more specifically Serra dos Órgãos region (Rio de Janeiro state), southeastern Brazil. The following steps were performed: (a) ENM to delimit the area of occurrence of S. weddelliana and locate experimental areas; (b) a seed sowing experiment in areas with presence or absence of the species in areas of high or low environmental suitability at 36 experimental stations; and (c) characterization of each microhabitat which was related back to the macroscale results of ENM. Evidence of biotic and abiotic limitations was found for S. weddelliana distribution. Areas of higher suitability had lower seed predation rates and, consequently, higher seed germination rates. On the other hand, areas with low environmental suitability at the macroscale were divided into two types: areas with microhabitat similar to that of areas with high environmental suitability that had some germination despite high predation and areas with different environmental conditions that had no germination and high predation rates. Seedlings and adults had different abiotic requirements. Microhabitat conditions were more important for the initial establishment of S. weddelliana than macroclimatic variables. This finding demonstrates that macro- and microecological information works in a complementary way to a better understanding of the distribution of S. weddelliana.

Mutualistic interactions reshuffle the effects of climate change on plants across the tree of life

Climatically induced local species extinctions may trigger coextinction cascades, thus driving many more species to extinction than originally predicted by species distribution models. Using seven pollination networks across Europe that include the phylogeny and life history traits of plants, we show a substantial variability across networks in climatically predicted plant extinction-and particularly the subsequent coextinction-rates, with much higher values in Mediterranean than Eurosiberian networks. While geographic location best predicts the probability of a plant species to be driven to extinction by climate change, subsequent coextinctions are best predicted by the local network of interactions. These coextinctions not only increase the total number of plant species being driven to extinction but also add a bias in the way the major taxonomic and functional groups are pruned.

Univariate Community Assembly Analysis (UniCAA): Combining hierarchical models with null models to test the influence of spatially restricted dispersal, environmental filtering, and stochasticity on community assembly

Identifying the influence of stochastic processes and of deterministic processes, such as dispersal of individuals of different species and trait-based environmental filtering, has long been a challenge in studies of community assembly. Here, we present the Univariate Community Assembly Analysis (UniCAA) and test its ability to address three hypotheses: species occurrences within communities are (a) limited by spatially restricted dispersal; (b) environmentally filtered; or (c) the outcome of stochasticity-so that as community size decreases-species that are common outside a local community have a disproportionately higher probability of occurrence than rare species. The comparison with a null model allows assessing if the influence of each of the three processes differs from what one would expect under a purely stochastic distribution of species. We tested the framework by simulating "empirical" metacommunities under 15 scenarios that differed with respect to the strengths of spatially restricted dispersal (restricted vs. not restricted); habitat isolation (low, intermediate, and high immigration rates); and environmental filtering (strong, intermediate, and no filtering). Through these tests, we found that UniCAA rarely produced false positives for the influence of the three processes, yielding a type-I error rate ≤5%. The type-II error rate, that is, production of false negatives, was also acceptable and within the typical cutoff (20%). We demonstrate that the UniCAA provides a flexible framework for retrieving the processes behind community assembly and propose avenues for future developments of the framework.

Climate and food diversity as drivers of mammal diversity in Inner Mongolia

Traditionally, geographical distribution of biodiversity is assumed to be codetermined by multiple factors, for example, temperature, precipitation, environmental heterogeneity, and biotic interactions. However, few studies have simultaneously compared the relative roles of these factors in shaping the mammal diversity patterns for different feeding groups, that is, herbivores, insectivores, and carnivores. In this study, we assessed the relations between mammal diversity and current climate (mean annual temperature and precipitation), altitudinal range as well as mammal's food diversity in Inner Mongolia. Our results showed that the species richness for the three feeding guilds of mammals consistently increased with their food diversity, that is, species richness of plants, insects, and rodents. Mammal diversity also significantly decreased with mean annual temperature and precipitation. Random Forest models indicated that climate and food diversity were always included in the combinations of variables most associated with mammal diversity. Our findings suggest that while climate is an important predictor of large scale distribution of mammal diversity, biotic interactions, that is, food diversity, could also play important roles.

Negative biotic interactions drive predictions of distributions for species from a grassland community

Understanding the factors that determine species' geographical distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritized in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships.

Towards a predictive model of species interaction beta diversity

Species interactions are fundamental to community dynamics and ecosystem processes. Despite significant progress in describing species interactions, we lack the ability to predict changes in interactions across space and time. We outline a Bayesian approach to separate the probability of species co-occurrence, interaction and detectability in influencing interaction betadiversity. We use a multi-year hummingbird-plant time series, divided into training and testing data, to show that including models of detectability and occurrence improves forecasts of mutualistic interactions. We then extend our model to explore interaction betadiversity across two distinct seasons. Despite differences in the observed interactions among seasons, there was no significant change in hummingbird occurrence or interaction frequency between hummingbirds and plants. These results highlight the challenge of inferring the causes of interaction betadiversity when interaction detectability is low. Finally, we highlight potential applications of our model for integrating observations of local interactions with biogeographic and evolutionary histories of co-occurring species. These advances will provide new insight into the mechanisms that drive variation in patterns of biodiversity.