The EDGE2 protocol: Advancing the prioritisation of Evolutionarily Distinct and Globally Endangered species for practical conservation action.

The conservation of evolutionary history has been linked to increased benefits for humanity and can be captured by phylogenetic diversity (PD). The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to prioritise threatened species for practical conservation that embody large amounts of evolutionary history. While there have been important research advances since 2007, they have not been adopted in practice because of a lack of consensus in the conservation community. Here, building from an interdisciplinary workshop to update the existing EDGE approach, we present an "EDGE2" protocol that draws on a decade of research and innovation to develop an improved, consistent methodology for prioritising species conservation efforts. Key advances include methods for dealing with uncertainty and accounting for the extinction risk of closely related species. We describe EDGE2 in terms of distinct components to facilitate future revisions to its constituent parts without needing to reconsider the whole. We illustrate EDGE2 by applying it to the world's mammals. As we approach a crossroads for global biodiversity policy, this Consensus View shows how collaboration between academic and applied conservation biologists can guide effective and practical priority-setting to conserve biodiversity.

Invertebrate biodiversity continues to decline in cropland.

Modern agriculture has drastically changed global landscapes and introduced pressures on wildlife populations. Policy and management of agricultural systems has changed over the last 30 years, a period characterized not only by intensive agricultural practices but also by an increasing push towards sustainability. It is crucial that we understand the long-term consequences of agriculture on beneficial invertebrates and assess if policy and management approaches recently introduced are supporting their recovery. In this study, we use large citizen science datasets to derive trends in invertebrate occupancy in Great Britain between 1990 and 2019. We compare these trends between regions of no- (0%), low- (greater than 0-50%) and high-cropland (greater than 50%) cover, which includes arable and horticultural crops. Although we detect general declines, invertebrate groups are declining most strongly in high-cropland cover regions. This suggests that even in the light of improved policy and management over the last 30 years, the way we are managing cropland is failing to conserve and restore invertebrate communities. New policy-based drivers and incentives are required to support the resilience and sustainability of agricultural ecosystems. Post-Brexit changes in UK agricultural policy and reforms under the Environment Act offer opportunities to improve agricultural landscapes for the benefit of biodiversity and society.

Rapid Anthropocene realignment of allometric scaling rules.

The negative relationship between body size and population density in mammals is often interpreted as resulting from energetic constraints. In a global change scenario, however, this relationship might be expected to change, given the size-dependent nature of anthropogenic pressures and vulnerability to extinction. Here we test whether the size-density relationship (SDR) in mammals has changed over the last 50 years. We show that the relationship has shifted down and became shallower, corresponding to a decline in population density of 31-73%, for the largest and smallest mammals, respectively. However, the SDRs became steeper in some groups (e.g. carnivores) and shallower in others (e.g. herbivores). The Anthropocene reorganisation of biotic systems is apparent in macroecological relationships, reinforcing the notion that biodiversity pattens are contingent upon conditions at the time of investigation. We call for an increased attention to the role of global change on macroecological inferences.

Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets.

We combined participatory science data and museum records to understand long-term changes in occupancy for 29 ant species in Denmark over 119 years. Bayesian occupancy modelling indicated change in occupancy for 15 species: five increased, four declined and six showed fluctuating trends. We consider how trends may have been influenced by life-history and habitat changes. Our results build on an emerging picture that biodiversity change in insects is more complex than implied by the simple insect decline narrative.

Comparing Life Histories across Taxonomic Groups in Multiple Dimensions: How Mammal-Like Are Insects?

Explaining variation in life histories remains a major challenge because they are multidimensional and there are many competing explanatory theories and paradigms. An influential concept in life-history theory is the fast-slow continuum, exemplified by mammals. Determining the utility of such concepts across taxonomic groups requires comparison of the groups' life histories in multidimensional space. Insects display enormous species richness and phenotypic diversity, but testing hypotheses like the fast-slow continuum has been inhibited by incomplete trait data. We use phylogenetic imputation to generate complete data sets of seven life-history traits in orthopterans (grasshoppers and crickets) and examine the robustness of these imputations for our findings. Three phylogenetic principal components explain 83%-96% of variation in these data. We find consistent evidence of an axis mostly following expectations of a fast-slow continuum, except that "slow" species produce larger, not smaller, clutches of eggs. We show that the principal axes of variation in orthopterans and reptiles are mutually explanatory, as are those of mammals and birds. Essentially, trait covariation in Orthoptera, with "slow" species producing larger clutches, is more reptilelike than mammal-like or birdlike. We conclude that the fast-slow continuum is less pronounced in Orthoptera than it is in birds and mammals, reducing the universal relevance of this pattern and the theories that predict it.

Landscape simplification weakens the association between terrestrial producer and consumer diversity in Europe.

Land-use change is one of the primary drivers of species loss, yet little is known about its effect on other components of biodiversity that may be at risk. Here, we ask whether, and to what extent, landscape simplification, measured as the percentage of arable land in the landscape, disrupts the functional and phylogenetic association between primary producers and consumers. Across seven European regions, we inferred the potential associations (functional and phylogenetic) between host plants and butterflies in 561 seminatural grasslands. Local plant diversity showed a strong bottom-up effect on butterfly diversity in the most complex landscapes, but this effect disappeared in simple landscapes. The functional associations between plant and butterflies are, therefore, the results of processes that act not only locally but are also dependent on the surrounding landscape context. Similarly, landscape simplification reduced the phylogenetic congruence among host plants and butterflies indicating that closely related butterflies become more generalist in the resources used. These processes occurred without any detectable change in species richness of plants or butterflies along the gradient of arable land. The structural properties of ecosystems are experiencing substantial erosion, with potentially pervasive effects on ecosystem functions and future evolutionary trajectories. Loss of interacting species might trigger cascading extinction events and reduce the stability of trophic interactions, as well as influence the longer term resilience of ecosystem functions. This underscores a growing realization that species richness is a crude and insensitive metric and that both functional and phylogenetic associations, measured across multiple trophic levels, are likely to provide additional and deeper insights into the resilience of ecosystems and the functions they provide.

Measuring ß-diversity with species abundance data.

In 2003, 24 presence-absence ß-diversity metrics were reviewed and a number of trade-offs and redundancies identified. We present a parallel investigation into the performance of abundance-based metrics of ß-diversity. ß-diversity is a multi-faceted concept, central to spatial ecology. There are multiple metrics available to quantify it: the choice of metric is an important decision. We test 16 conceptual properties and two sampling properties of a ß-diversity metric: metrics should be 1) independent of α-diversity and 2) cumulative along a gradient of species turnover. Similarity should be 3) probabilistic when assemblages are independently and identically distributed. Metrics should have 4) a minimum of zero and increase monotonically with the degree of 5) species turnover, 6) decoupling of species ranks and 7) evenness differences. However, complete species turnover should always generate greater values of ß than extreme 8) rank shifts or 9) evenness differences. Metrics should 10) have a fixed upper limit, 11) symmetry (ßA,B  = ßB,A ), 12) double-zero asymmetry for double absences and double presences and 13) not decrease in a series of nested assemblages. Additionally, metrics should be independent of 14) species replication 15) the units of abundance and 16) differences in total abundance between sampling units. When samples are used to infer ß-diversity, metrics should be 1) independent of sample sizes and 2) independent of unequal sample sizes. We test 29 metrics for these properties and five 'personality' properties. Thirteen metrics were outperformed or equalled across all conceptual and sampling properties. Differences in sensitivity to species' abundance lead to a performance trade-off between sample size bias and the ability to detect turnover among rare species. In general, abundance-based metrics are substantially less biased in the face of undersampling, although the presence-absence metric, ßsim , performed well overall. Only ßBaselga R turn , ßBaselga B-C turn and ßsim measured purely species turnover and were independent of nestedness. Among the other metrics, sensitivity to nestedness varied >4-fold. Our results indicate large amounts of redundancy among existing ß-diversity metrics, whilst the estimation of unseen shared and unshared species is lacking and should be addressed in the design of new abundance-based metrics.

Quantifying the relative importance of agricultural land use as a predictor of catchment nitrogen and phosphorus concentrations.

Agriculture is a major source of nitrogen (N) and phosphorus (P) in freshwater ecosystems, and different management strategies exist to reduce farmland nutrient losses and thus mitigate freshwater eutrophication. The importance of agricultural sources of N and P as drivers of water quality is known to vary spatially, but quantification of the relative importance of the nutrient sources shaping this variability remains challenging, especially with reference to inputs from waste water treatment works. Addressing this knowledge gap is key for targeting management strategies to where they are likely to have the greatest effect. To advance our understanding in this area, this study assesses the impact of population density as a driver of the relative importance of agricultural land use for predicting mean Total Oxidised Nitrogen (TON) and Reactive Phosphorus (RP) concentrations in rivers in England, using two different data-driven, statistical approaches: a generalised linear model and random forest. Our results show that agricultural N and P sources dominate in catchments with low population density, where stream water concentrations are lower and waste water treatment works are numerous, but smaller in terms of the population equivalent served. Agricultural N and P sources are not important predictors of N and P in catchments with high population density, where contributions from waste water treatment works dominate. These results require cautious interpretation, as model validation outcomes show that high TON and RP concentrations are consistently underpredicted. Altogether, our results suggest that the relative contribution of agricultural sources may be overestimated in densely populated catchments, relative to point sources from waste water treatment works, and that management strategies to reduce the contribution of agriculture to N and P in rivers may be better targeted towards catchments with lower population density, as this is where agricultural land use is the primary source of N and P.

Treating gaps and biases in biodiversity data as a missing data problem.

Big biodiversity data sets have great potential for monitoring and research because of their large taxonomic, geographic and temporal scope. Such data sets have become especially important for assessing temporal changes in species' populations and distributions. Gaps in the available data, especially spatial and temporal gaps, often mean that the data are not representative of the target population. This hinders drawing large-scale inferences, such as about species' trends, and may lead to misplaced conservation action. Here, we conceptualise gaps in biodiversity monitoring data as a missing data problem, which provides a unifying framework for the challenges and potential solutions across different types of biodiversity data sets. We characterise the typical types of data gaps as different classes of missing data and then use missing data theory to explore the implications for questions about species' trends and factors affecting occurrences/abundances. By using this framework, we show that bias due to data gaps can arise when the factors affecting sampling and/or data availability overlap with those affecting species. But a data set per se is not biased. The outcome depends on the ecological question and statistical approach, which determine choices around which sources of variation are taken into account. We argue that typical approaches to long-term species trend modelling using monitoring data are especially susceptible to data gaps since such models do not tend to account for the factors driving missingness. To identify general solutions to this problem, we review empirical studies and use simulation studies to compare some of the most frequently employed approaches to deal with data gaps, including subsampling, weighting and imputation. All these methods have the potential to reduce bias but may come at the cost of increased uncertainty of parameter estimates. Weighting techniques are arguably the least used so far in ecology and have the potential to reduce both the bias and variance of parameter estimates. Regardless of the method, the ability to reduce bias critically depends on knowledge of, and the availability of data on, the factors creating data gaps. We use this review to outline the necessary considerations when dealing with data gaps at different stages of the data collection and analysis workflow.

Space-use scaling and home range overlap in primates.

Space use is an important aspect of animal ecology, yet our understanding is limited by a lack of synthesis between interspecific and intraspecific studies. We present analyses of a dataset of 286 estimates of home range overlap from 100 primate species, with comparable samples for other space-use traits. To the best of our knowledge, this represents the first multispecies study using overlap data estimated directly from field observations. We find that space-use traits in primates are only weakly related to body mass, reflecting their largely arboreal habits. Our results confirm a theory that home range overlap explains the differences in allometric scaling between population density and home range size. We then test a suite of hypotheses to explain home range overlap, both among and within species. We find that overlap is highest for larger-bodied species living in large home ranges at high population densities, where annual rainfall is low, and is higher for arboreal than terrestrial species. Most of these results are consistent with the economics of resource defence, although the predictions of one specific theory of home range overlap are not supported. We conclude that home range overlap is somewhat predictable, but the theoretical basis of animal space use remains patchy.

The relationship between body mass and field metabolic rate among individual birds and mammals.

1. The power-law dependence of metabolic rate on body mass has major implications at every level of ecological organization. However, the overwhelming majority of studies examining this relationship have used basal or resting metabolic rates, and/or have used data consisting of species-averaged masses and metabolic rates. Field metabolic rates are more ecologically relevant and are probably more directly subject to natural selection than basal rates. Individual rates might be more important than species-average rates in determining the outcome of ecological interactions, and hence selection. 2. We here provide the first comprehensive database of published field metabolic rates and body masses of individual birds and mammals, containing measurements of 1498 animals of 133 species in 28 orders. We used linear mixed-effects models to answer questions about the body mass scaling of metabolic rate and its taxonomic universality/heterogeneity that have become classic areas of controversy. Our statistical approach allows mean scaling exponents and taxonomic heterogeneity in scaling to be analysed in a unified way while simultaneously accounting for nonindependence in the data due to shared evolutionary history of related species. 3. The mean power-law scaling exponents of metabolic rate vs. body mass relationships were 0.71 [95% confidence intervals (CI) 0.625-0.795] for birds and 0.64 (95% CI 0.564-0.716) for mammals. However, these central tendencies obscured meaningful taxonomic heterogeneity in scaling exponents. The primary taxonomic level at which heterogeneity occurred was the order level. Substantial heterogeneity also occurred at the species level, a fact that cannot be revealed by species-averaged data sets used in prior work. Variability in scaling exponents at both order and species levels was comparable to or exceeded the differences 3/4-2/3 = 1/12 and 0.71-0.64. 4. Results are interpreted in the light of a variety of existing theories. In particular, results are consistent with the heat dissipation theory of Speakman & Król (2010) and provided some support for the metabolic levels boundary hypothesis of Glazier (2010). 5. Our analysis provides the first comprehensive empirical analysis of the scaling relationship between field metabolic rate and body mass in individual birds and mammals. Our data set is a valuable contribution to those interested in theories of the allometry of metabolic rates.

Socioeconomic factors predict population changes of large carnivores better than climate change or habitat loss.

Land-use and climate change have been linked to changes in wildlife populations, but the role of socioeconomic factors in driving declines, and promoting population recoveries, remains relatively unexplored. Here, we evaluate potential drivers of population changes observed in 50 species of some of the world's most charismatic and functionally important fauna-large mammalian carnivores. Our results reveal that human socioeconomic development is more associated with carnivore population declines than habitat loss or climate change. Rapid increases in socioeconomic development are linked to sharp population declines, but, importantly, once development slows, carnivore populations have the potential to recover. The context- and threshold-dependent links between human development and wildlife population health are challenges to the achievement of the UN Sustainable development goals.

An operational workflow for producing periodic estimates of species occupancy at national scales.

Policy makers require high-level summaries of biodiversity change. However, deriving such summaries from raw biodiversity data is a complex process involving several intermediary stages. In this paper, we describe an operational workflow for generating annual estimates of species occupancy at national scales from raw species occurrence data, which can be used to construct a range of policy-relevant biodiversity indicators. We describe the workflow in detail: from data acquisition, data assessment and data manipulation, through modelling, model evaluation, application and dissemination. At each stage, we draw on our experience developing and applying the workflow for almost a decade to outline the challenges that analysts might face. These challenges span many areas of ecology, taxonomy, data science, computing and statistics. In our case, the principal output of the workflow is annual estimates of occupancy, with measures of uncertainty, for over 5000 species in each of several defined 'regions' (e.g. countries, protected areas, etc.) of the UK from 1970 to 2019. This data product corresponds closely to the notion of a species distribution Essential Biodiversity Variable (EBV). Throughout the paper, we highlight methodologies that might not be applicable outside of the UK and suggest alternatives. We also highlight areas where the workflow can be improved; in particular, methods are needed to mitigate and communicate the risk of bias arising from the lack of representativeness that is typical of biodiversity data. Finally, we revisit the 'ideal' and 'minimal' criteria for species distribution EBVs laid out in previous contributions and pose some outstanding questions that should be addressed as a matter of priority. Going forward, we hope that this paper acts as a template for research groups around the world seeking to develop similar data products.

Linking climate warming and land conversion to species' range changes across Great Britain.

Although increased temperatures are known to reinforce the effects of habitat destruction at local to landscape scales, evidence of their additive or interactive effects is limited, particularly over larger spatial extents and longer timescales. To address these deficiencies, we created a dataset of land-use changes over 75 years, documenting the loss of over half (>3000 km2) the semi-natural grassland of Great Britain. Pairing this dataset with climate change data, we tested for relationships to distribution changes in birds, butterflies, macromoths, and plants (n = 1192 species total). We show that individual or additive effects of climate warming and land conversion unambiguously increased persistence probability for 40% of species, and decreased it for 12%, and these effects were reflected in both range contractions and expansions. Interactive effects were relatively rare, being detected in less than 1 in 5 species, and their overall effect on extinction risk was often weak. Such individualistic responses emphasise the importance of including species-level information in policies targeting biodiversity and climate adaptation.

What is macroecology?

The symposium 'What is Macroecology?' was held in London on 20 June 2012. The event was the inaugural meeting of the Macroecology Special Interest Group of the British Ecological Society and was attended by nearly 100 scientists from 11 countries. The meeting reviewed the recent development of the macroecological agenda. The key themes that emerged were a shift towards more explicit modelling of ecological processes, a growing synthesis across systems and scales, and new opportunities to apply macroecological concepts in other research fields.

Taxonomic variation in size-density relationships challenges the notion of energy equivalence.

The relationship between body mass and abundance is a major focus for research in macroecology. The form of this relationship has been suggested to reflect the partitioning of energy among species. We revisit classical datasets to show that size-density relationships vary systematically among taxonomic groups, with most variation occurring at the order level. We use this knowledge to make a novel test of the 'energy equivalence rule', at the taxonomic scale appropriate for the data. We find no obvious relationship between order-specific exponents for abundance and metabolic rate, although most orders show substantially shallower (less negative) scaling than predicted by energy equivalence. This finding implies greater energy flux among larger-bodied animals, with the largest species using two orders of magnitude more energy than the smallest. Our results reject the traditional interpretation of energy equivalence as a predictive rule. However, some variation in size-density exponents is consistent with a model of geometric constraints on foraging.

Patterns of invertebrate functional diversity highlight the vulnerability of ecosystem services over a 45-year period.

Declines in invertebrate biodiversity1,2 pose a significant threat to key ecosystem services.3-5 Current analyses of biodiversity often focus on taxonomic diversity (e.g., species richness),6,7 which does not account for the functional role of a species. Functional diversity of species' morphological or behavioral traits is likely more relevant to ecosystem service delivery than taxonomic diversity, as functional diversity has been found to be a key driver of a number of ecosystem services including decomposition and pollination.8-12 At present, we lack a good understanding of long-term and large-scale changes in functional diversity, which limits our capacity to determine the vulnerability of key ecosystem services with ongoing biodiversity change. Here we derive trends in functional diversity and taxonomic diversity over a 45-year period across Great Britain for species supporting freshwater aquatic functions, pollination, natural pest control, and agricultural pests (a disservice). Species supporting aquatic functions showed a synchronous collapse and recovery in functional and taxonomic diversity. In contrast, pollinators showed an increase in taxonomic diversity, but a decline and recovery in functional diversity. Pest control agents and pests showed greater stability in functional diversity over the assessment period. We also found that functional diversity could appear stable or show patterns of recovery, despite ongoing changes in the composition of traits among species. Our results suggest that invertebrate assemblages can show considerable variability in their functional structure over time at a national scale, which provides an important step in determining the long-term vulnerability of key ecosystem services with ongoing biodiversity change.

Using the IUCN Red List to map threats to terrestrial vertebrates at global scale.

The Anthropocene is characterized by unparalleled human impact on other species, potentially ushering in the sixth mass extinction. Yet mitigation efforts remain hampered by limited information on the spatial patterns and intensity of the threats driving global biodiversity loss. Here we use expert-derived information from the International Union for Conservation of Nature Red List on threats to 23,271 species, representing all terrestrial amphibians, birds and mammals, to generate global maps of the six major threats to these groups: agriculture, hunting and trapping, logging, pollution, invasive species, and climate change. Our results show that agriculture and logging are pervasive in the tropics and that hunting and trapping is the most geographically widespread threat to mammals and birds. Additionally, current representations of human pressure underestimate the overall pressure on biodiversity, due to the exclusion of threats such as hunting and climate change. Alarmingly, this is particularly the case in areas of the highest biodiversity importance.

Why are metabolic scaling exponents so controversial? Quantifying variance and testing hypotheses.

The metabolic theory of ecology links physiology with ecology, and successfully predicts many allometric scaling relationships. In recent years, proponents and critics of metabolic theory have debated vigorously about the scaling of metabolic rate. We show that the controversy arose, in part, because researchers examined the mean exponent separately from the variance. We estimate both quantities simultaneously using linear mixed-effects models and data from 1242 animal species. Metabolic rate scaling converges on the predicted value of 3/4 but is highly heterogeneous: 50% of orders lie outside the range 0.68-0.82. These findings are robust to several forms of statistical uncertainty. We then test competing hypotheses about the variation. Metabolic theory is currently unable to explain differences in scaling among orders, but the patterns are not consistent with competing explanations either. We conclude that current theories are inadequate to explain the full range of metabolic scaling patterns observed in nature.