Freshwater ecosystems are highly biodiverse1 and important for livelihoods and economic development2, but are under substantial stress3. To date, comprehensive global assessments of extinction risk have not included any speciose groups primarily living in freshwaters. Consequently, data from predominantly terrestrial tetrapods4,5 are used to guide environmental policy6 and conservation prioritization7, whereas recent proposals for target setting in freshwaters use abiotic factors8, 9, 10, 11, 12-13. However, there is evidence14, 15, 16-17 that such data are insufficient to represent the needs of freshwater species and achieve biodiversity goals18,19. Here we present the results of a multi-taxon global freshwater fauna assessment for The IUCN Red List of Threatened Species covering 23,496 decapod crustaceans, fishes and odonates, finding that one-quarter are threatened with extinction. Prevalent threats include pollution, dams and water extraction, agriculture and invasive species, with overharvesting also driving extinctions. We also examined the degree of surrogacy of both threatened tetrapods and freshwater abiotic factors (water stress and nitrogen) for threatened freshwater species. Threatened tetrapods are good surrogates when prioritizing sites to maximize rarity-weighted richness, but poorer when prioritizing based on the most range-restricted species. However, they are much better surrogates than abiotic factors, which perform worse than random. Thus, although global priority regions identified for tetrapod conservation are broadly reflective of those for freshwater faunas, given differences in key threats and habitats, meeting the needs of tetrapods cannot be assumed sufficient to conserve freshwater species at local scales.

State Wildlife Action Plans (SWAPs), including lists of Species of Greatest Conservation Need (SGCN), outline state strategies for protecting species and habitats in the United States. In developing the current, second revision SWAPs, states are increasingly pursuing coordinated landscape conservation approaches. Analyzing SGCN lists in the first revision SWAPs, we found evidence that they already support multistate conservation. Most states address a common set of vertebrate and invertebrate groups, include most of the imperiled species from these groups, do not prioritize endemics over non-endemics, and often include most imperiled species that are shared with neighboring states. Also, a regional SGCN coordination effort was successful. Although 65% of animals on each SGCN list were assessed as at elevated risk of extirpation by state authorities, only 43% of the combined national list were at elevated risk of global extinction. Over 40% of the combined animal SGCNs are considered globally apparently secure. Plants, snails, freshwater shrimps, and freshwater insects were poorly represented in SGCN lists. For the current SWAP revisions, we recommend improving foundational data on taxonomy, range-wide distribution, and conservation status; expanded taxonomic coverage in SGCN lists; supporting existing and establishing new interstate initiatives; and diversifying funding mechanisms that target regional cooperation.

Comprehensive assessments of species' extinction risks have documented the extinction crisis(1) and underpinned strategies for reducing those risks(2). Global assessments reveal that, among tetrapods, 40.7% of amphibians, 25.4% of mammals and 13.6% of birds are threatened with extinction(3). Because global assessments have been lacking, reptiles have been omitted from conservation-prioritization analyses that encompass other tetrapods(4-7). Reptiles are unusually diverse in arid regions, suggesting that they may have different conservation needs(6). Here we provide a comprehensive extinction-risk assessment of reptiles and showthat at least 1,829 out of 10,196 species (21.1%) are threatened-confirming a previous extrapolation(8) and representing 15.6 billion years of phylogenetic diversity. Reptiles are threatened by the same major factorsthat threaten othertetrapods-agriculture, logging, urban development and invasive species-although the threat posed by climate change remains uncertain. Reptiles inhabiting forests, where these threats are strongest, are more threatened than those in arid habitats, contrary to our prediction. Birds, mammals and amphibians are unexpectedly good surrogates for the conservation of reptiles, although threatened reptiles with the smallest rangestend to be isolated from other threatened tetrapods. Although some reptiles-including most species of crocodiles and turtles-require urgent, targeted action to prevent extinctions, efforts to protect other tetrapods, such as habitat preservation and control of trade and invasive species, will probably also benefit many reptiles.

Opportunistic and unstructured observations of biodiversity crowdsourced from volunteers, community, and citizen scientists make up an increasingly large proportion of our global biodiversity knowledge. This incredible wealth of information exists in real time at both high resolutions and large extents of space, time, and taxonomy, thus holding huge potential to fill gaps in global biodiversity monitoring coverage in a cost‐effective way. Yet, the full potential of these data to provide essential indicators of biodiversity change for both research and management remains mostly unrealized, in large part due to the prevailing perception that the lack of standardization presents an unsurmountable barrier. In this paper, we provide an overview of the main challenges of working with unstructured community‐contributed data and synthesize the four fundamental approaches to overcome these challenges and extract useful inferences of biodiversity change, namely: 1) reverse‐engineering survey structure; 2) borrowing strength across taxa; 3) modeling the observation process, and; 4) integrating standardized data sources. To illustrate each of these approaches, we provide examples comparing community‐contributed observations crowdsourced via iNaturalist with long‐term standardized monitoring surveys for a subset of rocky intertidal organisms on the California coast from 2010 to 2019. We conclude by highlighting ways forward for the successful integration of unstructured community‐contributed observations within the global ecosystem of biodiversity change monitoring tools. Our ultimate goal is to update the prevailing perception among researchers and practitioners that unstructured community‐contributed observations of biodiversity are too noisy to use, and help establish this data stream as a key tool for research and management.

Human activities are altering the structure of ecosystems, compromising the benefits they provide to nature and people. Effective conservation actions and management under ongoing global change rely on a better understanding of socio-ecological patterns and processes across broad spatiotemporal scales. Both macroecology and conservation science contribute to this improved understanding and, while they have different scopes, these disciplines have become increasingly interconnected over time. Here we describe examples of how macroecology has contributed to conservation science, and how conservation science can motivate further macroecological developments and applications. We identify challenges and untapped potential to further strengthen the links between these two disciplines. Major macroecological contributions include developing ecological theory, providing methodologies useful for biodiversity assessments and projections, making data more accessible and addressing knowledge gaps. These contributions have played a major role in the development of conservation science, and have supported outreach to policy makers, media, and the public. Nonetheless, a pure macroecological lens is limited to inform conservation decisions, particularly in local contexts, which frequently leads to the misuse of macroecological analyses for conservation applications, misunderstandings of research outputs, and skepticism among conservation practitioners and scientists. We propose possible solutions to overcome these challenges and strengthen links between macroecology and conservation science, including a stronger focus on ecological mechanisms and predictive approaches, and the creation of hybrid journals and meetings. Finally, we suggest new avenues for macroecological research that would further benefit conservation science.

Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready-to-use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservation and management, and for quantifying impacts from global change. However, models must be fit for purpose, with all important aspects of their development and applications properly considered. Despite the widespread use of SDMs, standardisation and documentation of modelling protocols remain limited, which makes it hard to assess whether development steps are appropriate for end use. To address these issues, we propose a standard protocol for reporting SDMs, with an emphasis on describing how a study's objective is achieved through a series of modeling decisions. We call this the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol, as its components reflect the main steps involved in building SDMs and other empirically-based biodiversity models. The ODMAP protocol serves two main purposes. First, it provides a checklist for authors, detailing key steps for model building and analyses, and thus represents a quick guide and generic workflow for modern SDMs. Second, it introduces a structured format for documenting and communicating the models, ensuring transparency and reproducibility, facilitating peer review and expert evaluation of model quality, as well as meta-analyses. We detail all elements of ODMAP, and explain how it can be used for different model objectives and applications, and how it complements efforts to store associated metadata and define modelling standards. We illustrate its utility by revisiting nine previously published case studies, and provide an interactive web-based application to facilitate its use. We plan to advance ODMAP by encouraging its further refinement and adoption by the scientific community.

The difficulty of integrating multiple theories, data and methods has slowed progress towards making unified inferences of ecological change generalizable across large spatial, temporal and taxonomic scales. However, recent progress towards a theoretical synthesis now provides a guiding framework for organizing and integrating all primary data and methods for spatiotemporal assemblage‐level inference in ecology. In this paper, we describe how recent theoretical developments can provide an organizing paradigm for linking advances in data collection and methodological frameworks across disparate ecological sub‐disciplines and across large spatial and temporal scales. First, we summarize the set of fundamental processes that determine change in multispecies assemblages across spatial and temporal scales by reviewing recent theoretical syntheses of community ecology. Second, we review recent advances in data and methods across the main sub‐disciplines concerned with ecological inference across large spatial, temporal and taxonomic scales, and organize them based on the primary fundamental processes they include, rather than the spatiotemporal scale of their inferences. Finally, we highlight how iteratively focusing on only one fundamental process at a time, but combining all relevant spatiotemporal data and methods, may reduce the conceptual challenges to integration among ecological sub‐disciplines. Moreover, we discuss a number of avenues for decreasing the practical barriers to integration among data and methods. We aim to reconcile the recent convergence of decades of thinking in community ecology and macroecology theory with the rapid progress in spatiotemporal approaches for assemblage‐level inference, at a time where a robust understanding of spatiotemporal change in ecological assemblages is more crucial than ever to conserve biodiversity.

Issue Owing to their large-scale scope and emphasis on prediction, macroecological models have the potential to provide key contributions to evidence-based conservation practice. However, examples of macroecological modelling outputs directly influencing conservation practice and decision-making remain rare. The general barriers to implementation of ecological research into conservation practice have been discussed at length, whereas much less attention has been given to the specific barriers faced by macroecological modelling research. Evidence Here, I start to address this gap by discussing how two important barriers could be overcome in a practical manner, because their burden falls primarily on the researcher. The first barrier is the potential perception of macroecological models as "black boxes" by potential end-users, who may have little time and/or quantitative training to inspect the underlying methods fully. The second barrier is the difficulty in effective translation of the uncertainty inherent to most macroecological models, given the high threshold for weight of evidence required to support most decisions. To overcome these barriers, I put forward a number of solutions, most of which rely on researchers agreeing to and adopting model documentation and communication standards already in existence. Conclusion I conclude by introducing the bigger challenges ahead for the macroecology-conservation practice interface: transformation of publication incentives and establishment of a two-way flow of knowledge between macroecologists and conservation practitioners. Macroecologists can contribute much-needed evidence to support conservation decisions. However, fundamental changes to their research communication standards, their publication incentives and their understanding of regulatory settings will be needed to ensure that macroecological contributions are considered in practice.

Documenting ecological patterns across spatially, temporally and taxonomically diverse ecological communities is necessary for a general understanding of the processes shaping biodiversity. A major gap in our understanding remains the comparison of diversity patterns across a broad spectrum of evolutionarily and functionally diverse organisms, particularly in the marine realm. Here, we aim to narrow this gap by comparing the diversity patterns of free-living microbes and macro-invertebrates across a natural experiment provided by the marine lakes of Palau: geographically discrete and environmentally heterogeneous bodies of seawater with comparable geological and climatic history, and a similar regional species pool. We find contrasting patterns of α-diversity but remarkably similar patterns of β-diversity between microbial and macro-invertebrate communities among lakes. Pairwise dissimilarities in community composition among lakes are positively correlated between microbes and macro-invertebrates, and influenced to a similar degree by marked gradients in oxygen concentration and salinity. Our findings indicate that a shared spatio-temporal and environmental context may result in parallel patterns of β-diversity in microbes and macro-invertebrates, in spite of key trait differences between these organisms. This raises the possibility that parallel processes also influence transitions among regional biota across the tree of life, at least in the marine realm.

EDITORIAL article Front. Ecol. Evol., 08 November 2019 | https://doi.org/10.3389/fevo.2019.00428

Model transferability is an emerging and important branch of predictive science that has grown primarily from a need to produce ecological forecasts in the face of widespread data deficiency and escalating environmental novelty. In our recent article in Trends in Ecology and Evolution, we outlined some of the major roadblocks that currently undermine the practice of model transfers in ecology. The response of Radchuk et al. to our work stresses the value of considering ‘first principles’ in projections of ecosystem change and offers insights into outstanding challenges specific to mechanistic (synonym: process-based) models.

Remotely sensed data can help to identify both suitable habitat for individual species, and environmental conditions that foster species richness, which is important when predicting how biodiversity will respond to global change. The question is how to summarize remotely sensed data so that they are most relevant for biodiversity analyses, and the Dynamic Habitat Indices are three metrics designed for this. Our goals here were to a) derive, for the first time, the Dynamic Habitat Indices (DHIs) globally, and b) use these to evaluate three hypotheses (available energy, environmental stress, and environmental stability) that attempt to explain global variation in species richness of amphibians, birds, and mammals. The three DHIs summarize three key measures of vegetative productivity: a) annual cumulative productivity, which we used to evaluate the available energy hypothesis that more energy is associate with higher species richness; b) minimum productivity throughout the year, which we used to evaluate the environmental stress hypothesis that higher minima cause higher species richness, and c) seasonality, expressed as the annual coefficient of variation in productivity, which we used to evaluate the environmental stability hypothesis that less intra-annual variability causes higher species richness. We calculated the DHIs globally at 1-km resolution from MODIS vegetation products (NDVI, EVI, LAI, fPAR, and GPP), based on the median of the good observations of all years from the entire MODIS record for each of the 23 or 46 possible dates (8- vs. 16-day composites) during the year, and calculated species richness for three taxa (amphibians, birds, and mammals) at 110-km resolution from species range maps from the IUCN Red List. We found marked global patterns of the DHIs, and strong support for all three hypotheses. The three DHIs for a given vegetation product were well correlated (Spearman rank correlations ranging from −0.6 (cumulative vs. variation DHIs) to −0.93 (variation vs. minimum DHI)). Similarly, DHI components derived from different MODIS vegetation products were well correlated (0.8–0.9), and correlations of the DHIs with temperature and precipitation were moderate and strong respectively. All three DHIs were well correlated with species richness, showing in ranked order positive correlations for cumulative DHI based on GPP (Spearman rank correlations of 0.75, 0.63, and 0.67 for amphibians, resident birds, and mammals respectively) and minimum DHI (0.73, 0.83, and 0.62), and negative for variation DHI (−0.69, −0.83, and −0.59). Multiple linear models of all three DHIs explained 67%, 65%, and 61% of the variability in species richness of amphibians, resident birds, and mammals, respectively. The DHIs, which are closely related to well-established ecological hypotheses of biodiversity, can predict species richness well, and are promising for application in biodiversity science and conservation.

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.

Preserving the evolutionary history and ecological functions that different species embody, in addition to species themselves, is a growing concern for conservation. Recent studies warn that conservation priority regions identified using species diversity differ from those based on phylogenetic or functional diversity. However, spatial mismatches in conservation priority regions need not indicate low surrogacy among these dimensions in conservation planning. Here, we use data for 10,213 terrestrial vertebrate species across the Americas to evaluate surrogacy; that is, the proportion of phylogenetic or functional diversity represented in conservation plans targeting species. We find that most conservation plans targeting species diversity also represent phylogenetic and functional diversity well, despite spatial mismatches in the priority regions identified by each plan. However, not all phylogenetic and functional diversity is represented within species-based plans, with the highest-surrogacy conservation strategy depending on the proportion of land area included in plans. Our results indicate that targeting species diversity could be sufficient to preserve much of the phylogenetic and functional dimensions of biodiversity in terrestrial vertebrates of the Americas. Incorporating phylogenetic and functional data in broad-scale conservation planning may not always be necessary, especially when the cost of doing so is high.

Global variation in species richness is widely recognized, but the explanation for what drives it continues to be debated. Previous efforts have focused on a subset of potential drivers, including evolutionary rate, evolutionary time (maximum clade age of species restricted to a region), dispersal (migration from one region to another), ecological factors and climatic stability. However, no study has evaluated these competing hypotheses simultaneously at a broad spatial scale. Here, we examine their relative contribution in determining the richness of the most comprehensive dataset of tetrapods to our knowledge (84% of the described species), distinguishing between the direct influences of evolutionary rate, evolutionary time and dispersal, and the indirect influences of ecological factors and climatic stability through their effect on direct factors. We found that evolutionary time exerted a primary influence on species richness, with evolutionary rate being of secondary importance. By contrast, dispersal did not significantly affect richness patterns. Ecological and climatic stability factors influenced species richness indirectly by modifying evolutionary time (i.e. persistence time) and rate. Overall, our findings suggest that global heterogeneity in tetrapod richness is explained primarily by the length of time species have had to diversify.

The emergence rate of new plant diseases is increasing due to novel introductions, climate change, and changes in vector populations, posing risks to agricultural sustainability. Assessing and managing future disease risks depends on understanding the causes of contemporary and historical emergence events. Since the mid-1990s, potato growers in the western United States, Mexico, and Central America have experienced severe yield loss from Zebra Chip disease and have responded by increasing insecticide use to suppress populations of the insect vector, the potato psyllid, Bactericera cockerelli (Hemiptera: Triozidae). Despite the severe nature of Zebra Chip outbreaks, the causes of emergence remain unknown. We tested the hypotheses that (1) B. cockerelli occupancy has increased over the last century in California and (2) such increases are related to climate change, specifically warmer winters. We compiled a data set of 87,000 museum specimen occurrence records across the order Hemiptera collected between 1900 and 2014. We then analyzed changes in B. cockerelli distribution using a hierarchical occupancy model using changes in background species lists to correct for collecting effort. We found evidence that B. cockerelli occupancy has increased over the last century. However, these changes appear to be unrelated to climate changes, at least at the scale of our analysis. To the extent that species occupancy is related to abundance, our analysis provides the first quantitative support for the hypothesis that B. cockerelli population abundance has increased, but further work is needed to link B. cockerelli population dynamics to Zebra Chip epidemics. Finally, we demonstrate how this historical macro-ecological approach provides a general framework for comparative risk assessment of future pest and insect vector outbreaks.

Aim: Examining the biogeography of body size is crucial for understanding how animal communities are assembled and maintained. In tetrapods, body size varies predictably with temperature, moisture, productivity seasonality and topographical complexity. Although millennial-scale human pressures are known to have led to the extinction of primarily large-bodied tetrapods, human pressure history is often ignored in studies of body size that focus on extant species. Here, we analyse 11,377 tetrapod species of the Western Hemisphere to test whether millennial-scale human pressures have left an imprint on contemporary body mass distributions throughout the tetrapod clade.Location: Western Hemisphere.Time period: Contemporary.Major taxa studied: Tetrapods (birds, mammals, amphibians and reptiles).Methods: We mapped the distribution of assemblage-level median tetrapod body mass at a resolution of 110 km across the Western Hemisphere. We then generated multivariate models of median body mass as a function of temperature, moisture, productivity seasonality and topographical complexity, as well as two variables capturing the history of human population density and human-induced land conversion over the past 12,000 years. We controlled for both spatial and phylogenetic autocorrelation effects on body mass-environment relationships.Results: Human pressures explain a small but significant portion of geographical variation in median body mass that cannot be explained by ecological constraints alone. Overall, the median body mass of tetrapod assemblages is lower than expected in areas with a longer history of high human population density and land conversion, but there are important differences among tetrapod classes.Main conclusions: At this broad scale, the effect of human pressure history on tetrapod body mass is low relative to that of ecology. However, ignoring spatial variation in the history of human pressure is likely to lead to bias in studies of the present-day functional composition of tetrapod assemblages, at least in areas that have long been influenced by humans.