Impact of alternative metrics on estimates of extent of occurrence for extinction risk assessment.

In International Union for Conservation of Nature (IUCN) Red List assessments, extent of occurrence (EOO) is a key measure of extinction risk. However, the way assessors estimate EOO from maps of species' distributions is inconsistent among assessments of different species and among major taxonomic groups. Assessors often estimate EOO from the area of mapped distribution, but these maps often exclude areas that are not habitat in idiosyncratic ways and are not created at the same spatial resolutions. We assessed the impact on extinction risk categories of applying different methods (minimum convex polygon, alpha hull) for estimating EOO for 21,763 species of mammals, birds, and amphibians. Overall, the percentage of threatened species requiring down listing to a lower category of threat (taking into account other Red List criteria under which they qualified) spanned 11-13% for all species combined (14-15% for mammals, 7-8% for birds, and 12-15% for amphibians). These down listings resulted from larger estimates of EOO and depended on the EOO calculation method. Using birds as an example, we found that 14% of threatened and near threatened species could require down listing based on the minimum convex polygon (MCP) approach, an approach that is now recommended by IUCN. Other metrics (such as alpha hull) had marginally smaller impacts. Our results suggest that uniformly applying the MCP approach may lead to a one-time down listing of hundreds of species but ultimately ensure consistency across assessments and realign the calculation of EOO with the theoretical basis on which the metric was founded.

Quantifying the relative irreplaceability of important bird and biodiversity areas.

World governments have committed to increase the global protected areas coverage by 2020, but the effectiveness of this commitment for protecting biodiversity depends on where new protected areas are located. Threshold- and complementarity-based approaches have been independently used to identify important sites for biodiversity. We brought together these approaches by performing a complementarity-based analysis of irreplaceability in important bird and biodiversity areas (IBAs), which are sites identified using a threshold-based approach. We determined whether irreplaceability values are higher inside than outside IBAs and whether any observed difference depends on known characteristics of the IBAs. We focused on 3 regions with comprehensive IBA inventories and bird distribution atlases: Australia, southern Africa, and Europe. Irreplaceability values were significantly higher inside than outside IBAs, although differences were much smaller in Europe than elsewhere. Higher irreplaceability values in IBAs were associated with the presence and number of restricted-range species; number of criteria under which the site was identified; and mean geographic range size of the species for which the site was identified (trigger species). In addition, IBAs were characterized by higher irreplaceability values when using proportional species representation targets, rather than fixed targets. There were broadly comparable results when measuring irreplaceability for trigger species and when considering all bird species, which indicates a good surrogacy effect of the former. Recently, the International Union for Conservation of Nature has convened a consultation to consolidate global standards for the identification of key biodiversity areas (KBAs), building from existing approaches such as IBAs. Our results informed this consultation, and in particular a proposed irreplaceability criterion that will allow the new KBA standard to draw on the strengths of both threshold- and complementarity-based approaches.

Global patterns of terrestrial vertebrate diversity and conservation.

Identifying priority areas for biodiversity is essential for directing conservation resources. Fundamentally, we must know where individual species live, which ones are vulnerable, where human actions threaten them, and their levels of protection. As conservation knowledge and threats change, we must reevaluate priorities. We mapped priority areas for vertebrates using newly updated data on >21,000 species of mammals, amphibians, and birds. For each taxon, we identified centers of richness for all species, small-ranged species, and threatened species listed with the International Union for the Conservation of Nature. Importantly, all analyses were at a spatial grain of 10 × 10 km, 100 times finer than previous assessments. This fine scale is a significant methodological improvement, because it brings mapping to scales comparable with regional decisions on where to place protected areas. We also mapped recent species discoveries, because they suggest where as-yet-unknown species might be living. To assess the protection of the priority areas, we calculated the percentage of priority areas within protected areas using the latest data from the World Database of Protected Areas, providing a snapshot of how well the planet's protected area system encompasses vertebrate biodiversity. Although the priority areas do have more protection than the global average, the level of protection still is insufficient given the importance of these areas for preventing vertebrate extinctions. We also found substantial differences between our identified vertebrate priorities and the leading map of global conservation priorities, the biodiversity hotspots. Our findings suggest a need to reassess the global allocation of conservation resources to reflect today's improved knowledge of biodiversity and conservation.

Network structure beyond food webs: mapping non-trophic and trophic interactions on Chilean rocky shores.

How multiple types of non-trophic interactions map onto trophic networks in real communities remains largely unknown. We present the first effort, to our knowledge, describing a comprehensive ecological network that includes all known trophic and diverse non-trophic links among >100 coexisting species for the marine rocky intertidal community of the central Chilean coast. Our results suggest that non-trophic interactions exhibit highly nonrandom structures both alone and with respect to food web structure. The occurrence of different types of interactions, relative to all possible links, was well predicted by trophic structure and simple traits of the source and target species. In this community, competition for space and positive interactions related to habitat/refuge provisioning by sessile and/or basal species were by far the most abundant non-trophic interactions. If these patterns are orroborated in other ecosystems, they may suggest potentially important dynamic constraints on the combined architecture of trophic and non-trophic interactions. The nonrandom patterning of non-trophic interactions suggests a path forward for developing a more comprehensive ecological network theory to predict the functioning and resilience of ecological communities.

Building robust conservation plans.

Systematic conservation planning optimizes trade-offs between biodiversity conservation and human activities by accounting for socioeconomic costs while aiming to achieve prescribed conservation objectives. However, the most cost-efficient conservation plan can be very dissimilar to any other plan achieving the set of conservation objectives. This is problematic under conditions of implementation uncertainty (e.g., if all or part of the plan becomes unattainable). We determined through simulations of parallel implementation of conservation plans and habitat loss the conditions under which optimal plans have limited chances of implementation and where implementation attempts would fail to meet objectives. We then devised a new, flexible method for identifying conservation priorities and scheduling conservation actions. This method entails generating a number of alternative plans, calculating the similarity in site composition among all plans, and selecting the plan with the highest density of neighboring plans in similarity space. We compared our method with the classic method that maximizes cost efficiency with synthetic and real data sets. When implementation was uncertain--a common reality--our method provided higher likelihood of achieving conservation targets. We found that χ, a measure of the shortfall in objectives achieved by a conservation plan if the plan could not be implemented entirely, was the main factor determining the relative performance of a flexibility enhanced approach to conservation prioritization. Our findings should help planning authorities prioritize conservation efforts in the face of uncertainty about future condition and availability of sites.

Estimating the normal background rate of species extinction.

A key measure of humanity's global impact is by how much it has increased species extinction rates. Familiar statements are that these are 100-1000 times pre-human or background extinction levels. Estimating recent rates is straightforward, but establishing a background rate for comparison is not. Previous researchers chose an approximate benchmark of 1 extinction per million species per year (E/MSY). We explored disparate lines of evidence that suggest a substantially lower estimate. Fossil data yield direct estimates of extinction rates, but they are temporally coarse, mostly limited to marine hard-bodied taxa, and generally involve genera not species. Based on these data, typical background loss is 0.01 genera per million genera per year. Molecular phylogenies are available for more taxa and ecosystems, but it is debated whether they can be used to estimate separately speciation and extinction rates. We selected data to address known concerns and used them to determine median extinction estimates from statistical distributions of probable values for terrestrial plants and animals. We then created simulations to explore effects of violating model assumptions. Finally, we compiled estimates of diversification-the difference between speciation and extinction rates for different taxa. Median estimates of extinction rates ranged from 0.023 to 0.135 E/MSY. Simulation results suggested over- and under-estimation of extinction from individual phylogenies partially canceled each other out when large sets of phylogenies were analyzed. There was no evidence for recent and widespread pre-human overall declines in diversity. This implies that average extinction rates are less than average diversification rates. Median diversification rates were 0.05-0.2 new species per million species per year. On the basis of these results, we concluded that typical rates of background extinction may be closer to 0.1 E/MSY. Thus, current extinction rates are 1,000 times higher than natural background rates of extinction and future rates are likely to be 10,000 times higher.

Mapping change in human pressure globally on land and within protected areas.

It is widely accepted that the main driver of the observed decline in biological diversity is increasing human pressure on Earth's ecosystems. However, the spatial patterns of change in human pressure and their relation to conservation efforts are less well known. We developed a spatially and temporally explicit map of global change in human pressure over 2 decades between 1990 and 2010 at a resolution of 10 km(2) . We evaluated 22 spatial data sets representing different components of human pressure and used them to compile a temporal human pressure index (THPI) based on 3 data sets: human population density, land transformation, and electrical power infrastructure. We investigated how the THPI within protected areas was correlated to International Union for Conservation of Nature (IUCN) management categories and the human development index (HDI) and how the THPI was correlated to cumulative pressure on the basis of the original human footprint index. Since the early 1990s, human pressure increased 64% of the terrestrial areas; the largest increases were in Southeast Asia. Protected areas also exhibited overall increases in human pressure, the degree of which varied with location and IUCN management category. Only wilderness areas and natural monuments (management categories Ib and III) exhibited decreases in pressure. Protected areas not assigned any category exhibited the greatest increases. High HDI values correlated with greater reductions in pressure across protected areas, while increasing age of the protected area correlated with increases in pressure. Our analysis is an initial step toward mapping changes in human pressure on the natural world over time. That only 3 data sets could be included in our spatio-temporal global pressure map highlights the challenge to measuring pressure changes over time.

Biodiversity hotspots house most undiscovered plant species.

For most organisms, the number of described species considerably underestimates how many exist. This is itself a problem and causes secondary complications given present high rates of species extinction. Known numbers of flowering plants form the basis of biodiversity "hotspots"--places where high levels of endemism and habitat loss coincide to produce high extinction rates. How different would conservation priorities be if the catalog were complete? Approximately 15% more species of flowering plant are likely still undiscovered. They are almost certainly rare, and depending on where they live, suffer high risks of extinction from habitat loss and global climate disruption. By using a model that incorporates taxonomic effort over time, regions predicted to contain large numbers of undiscovered species are already conservation priorities. Our results leave global conservation priorities more or less intact, but suggest considerably higher levels of species imperilment than previously acknowledged.

More than a meal integrating non-feeding interactions into food webs.

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Global protected area impacts.

Protected areas (PAs) dominate conservation efforts. They will probably play a role in future climate policies too, as global payments may reward local reductions of loss of natural land cover. We estimate the impact of PAs on natural land cover within each of 147 countries by comparing outcomes inside PAs with outcomes outside. We use 'matching' (or 'apples to apples') for land characteristics to control for the fact that PAs very often are non-randomly distributed across their national landscapes. Protection tends towards land that, if unprotected, is less likely than average to be cleared. For 75 per cent of countries, we find protection does reduce conversion of natural land cover. However, for approximately 80 per cent of countries, our global results also confirm (following smaller-scale studies) that controlling for land characteristics reduces estimated impact by half or more. This shows the importance of controlling for at least a few key land characteristics. Further, we show that impacts vary considerably within a country (i.e. across a landscape): protection achieves less on lands far from roads, far from cities and on steeper slopes. Thus, while planners are, of course, constrained by other conservation priorities and costs, they could target higher impacts to earn more global payments for reduced deforestation.

How many species of flowering plants are there?

We estimate the probable number of flowering plants. First, we apply a model that explicitly incorporates taxonomic effort over time to estimate the number of as-yet-unknown species. Second, we ask taxonomic experts their opinions on how many species are likely to be missing, on a family-by-family basis. The results are broadly comparable. We show that the current number of species should grow by between 10 and 20 per cent. There are, however, interesting discrepancies between expert and model estimates for some families, suggesting that our model does not always completely capture patterns of taxonomic activity. The as-yet-unknown species are probably similar to those taxonomists have described recently-overwhelmingly rare and local, and disproportionately in biodiversity hotspots, where there are high levels of habitat destruction.

Constraints to species' elevational range shifts as climate changes.

Predicting whether the ranges of tropical species will shift to higher elevations in response to climate change requires models that incorporate data on topography and land use. We incorporated temperature gradients and land-cover data from the current ranges of species in a model of range shifts in response to climate change. We tested four possible scenarios of amphibian movement on a tropical mountain: movement upslope through and to land cover suitable for the species; movement upslope to land-cover types that will not sustain survival and reproduction; movement upslope to areas that previously were outside the species' range; and movement upslope to cooler areas within the current range. Areas in the final scenario will become isolated as climate continues to change. In our scenarios more than 30% of the range of 21 of 46 amphibian species in the tropical Sierra Nevada de Santa Marta is likely to become isolated as climate changes. More than 30% of the range of 13 amphibian species would shift to areas that currently are unlikely to sustain survival and reproduction. Combined, over 70% of the current range of seven species would become thermally isolated or shift to areas that currently are unlikely to support survival and reproduction. The constraints on species' movements to higher elevations in response to climate change can increase considerably the number of species threatened by climate change in tropical mountains.

On the protection of "protected areas".

Tropical moist forests contain the majority of terrestrial species. Human actions destroy between 1 and 2 million km(2) of such forests per decade, with concomitant carbon release into the atmosphere. Within these forests, protected areas are the principle defense against forest loss and species extinctions. Four regions-the Amazon, Congo, South American Atlantic Coast, and West Africa-once constituted about half the world's tropical moist forest. We measure forest cover at progressively larger distances inside and outside of protected areas within these four regions, using datasets on protected areas and land-cover. We find important geographical differences. In the Amazon and Congo, protected areas are generally large and retain high levels of forest cover, as do their surroundings. These areas are protected de facto by being inaccessible and will likely remain protected if they continue to be so. Deciding whether they are also protected de jure-that is, whether effective laws also protect them-is statistically difficult, for there are few controls. In contrast, protected areas in the Atlantic Coast forest and West Africa show sharp boundaries in forest cover at their edges. This effective protection of forest cover is partially offset by their very small size: little area is deep inside protected area boundaries. Lands outside protected areas in the Atlantic Coast forest are unusually fragmented. Finally, we ask whether global databases on protected areas are biased toward highly protected areas and ignore "paper parks." Analysis of a Brazilian database does not support this presumption.

Sentiment Analysis of Conservation Studies Captures Successes of Species Reintroductions.

Learning from the rapidly growing body of scientific articles is constrained by human bandwidth. Existing methods in machine learning have been developed to extract knowledge from human language and may automate this process. Here, we apply sentiment analysis, a type of natural language processing, to facilitate a literature review in reintroduction biology. We analyzed 1,030,558 words from 4,313 scientific abstracts published over four decades using four previously trained lexicon-based models and one recursive neural tensor network model. We find frequently used terms share both a general and a domain-specific value, with either positive (success, protect, growth) or negative (threaten, loss, risk) sentiment. Sentiment trends suggest that reintroduction studies have become less variable and increasingly successful over time and seem to capture known successes and challenges for conservation biology. This approach offers promise for rapidly extracting explicit and latent information from a large corpus of scientific texts.

Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations.

Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented and artificial inteligence (AI) and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. We argue that collaborative efforts in data curation and storage, scientific computing, and training are of paramount importance to empower researchers within environmental sciences and the broader public health community to apply AI approaches and fully realize their potential. Leaders in the field were asked to prioritize challenges in incorporating big data in environmental public health research: inconsistent implementation of FAIR principles in data collection and sharing, a lack of skilled data scientists and appropriate cyber-infrastructures, and limited understanding of possibilities and communication of benefits were among those identified. These issues are discussed, and actionable recommendations are provided.

The IPBES Global Assessment: Pathways to Action.

The first Global Assessment of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) found widespread, accelerating declines in Earth's biodiversity and associated benefits to people from nature. Addressing these trends will require science-based policy responses to reduce impacts, especially at national to local scales. Effective scaling of science-policy efforts, driven by global and national assessments, is a major challenge for turning assessment into action and will require unprecedented commitment by scientists to engage with communities of policy and practice. Fulfillment of science's social contract with society, and with nature, will require strong institutional support for scientists' participation in activities that transcend conventional research and publication.