Contribution of warm habitat to cold-water fisheries

A central tenet of landscape ecology is that mobile species depend on complementary habitats, which are insufficient in isolation, but combine to support animals through the full annual cycle. However, incorporating the dynamic needs of mobile species into conservation strategies remains a challenge, particularly in the context of climate adaptation planning. For cold-water fishes, it is widely assumed that maximum temperatures are limiting and that summer data alone can predict refugia and population persistence. We tested these assumptions in populations of redband rainbow trout (Oncorhynchus mykiss newberrii) in an arid basin, where the dominance of hot, hyperproductive water in summer emulates threats of climate change predicted for cold-water fish in other basins. We used telemetry to reveal seasonal patterns of movement and habitat use. Then, we compared contributions of hot and cool water to growth with empirical indicators of diet and condition (gut contents, weight–length ratios, electric phase angle, and stable isotope signatures) and a bioenergetics model. During summer, trout occurred only in cool tributaries or springs (<20 °C) and avoided Upper Klamath Lake (>25 °C). During spring and fall, ≥65% of trout migrated to the lake (5–50 km) to forage. Spring and fall growth (mean [SD] 0.58% per day [0.80%] and 0.34 per day [0.55%], respectively) compensated for a net loss of energy in cool summer refuges (–0.56% per day [0.55%]). In winter, ≥90% of trout returned to tributaries (25–150 km) to spawn. Thus, although perennially cool tributaries supported thermal refuge and spawning, foraging opportunities in the seasonally hot lake ultimately fueled these behaviors. Current approaches to climate adaptation would prioritize the tributaries for conservation but would devalue critical foraging habitat because the lake is unsuitable and unoccupied during summer. Our results empirically demonstrate that warm water can fuel cold-water fisheries and challenge the common practice of identifying refugia based only on summer conditions.     

Difference in the net value of ecological services between natural and artificial forests in China

Land degradation is a global problem that seriously threatens human society. However, in China and elsewhere, ecological restoration still largely relies on a traditional approach that focuses only on ecological factors and ignores socioeconomic factors. To improve the effectiveness of ecological restoration and maximize its economic and ecological benefits, a more efficient approach is needed that provides support for policy development and land management and thereby promotes environmental conservation. We devised a framework for assessing the value of ecosystem services that remain after subtracting costs, such as the opportunity costs, costs of forest protection, and costs for the people who are affected by the program; that is, the net value of ecosystem services (NVES). To understand the difference between the value of a resource and the net value of the ecosystem service it provides, we used data on VES, timber sales, and afforestation costs from China's massive national afforestation programs to calculate the net value of forest ecosystem services in China. Accounting for the abovementioned costs revealed an NVES of ¥6.1 × 10¹² for forests in 2014, which was 35.9% less than the value calculated without accounting for costs. As a result, the NVES associated with afforestation was 55.9% less than the NVES of natural forests. In some regions, NVES was negative because of the huge costs of human-made plantations, high evapotranspiration rates (thus, high water opportunity costs), and low forest survival rates. To maximize the ecological benefits of conservation, it is necessary to account for as many costs as possible so that management decisions can be based on NVES, thereby helping managers choose projects that maximize both economic and ecological benefits.     

An economic evaluation framework for land-use-based conservation policy instruments in a changing climate

Climate change is a key threat to biodiversity. To conserve species under climate change, ecologists and conservation scientists suggest 2 main conservation strategies regarding land use: supporting species’ range shifts to enable it to follow its climatic requirements by creating migration pathways, such as corridors and stepping stones, and conserving climate refugia (i.e., existing habitat areas that are somewhat buffered from climate change). The policy instruments that could be used to implement these conservation strategies have yet to be evaluated comprehensively from an economic perspective. The economic analyses of environmental policy instruments are often based on ecological effectiveness and cost-effectiveness criteria. We adapted these general criteria to evaluate policy instruments for species’ conservation under climate change and applied them to a conceptual analysis of land purchases, offsets, and conservation payments. Depending on whether the strategy supporting species’ range shifts or conserving climate refugia is selected, the evaluation of the policy instruments differed substantially. For example, to ensure ecological effectiveness, habitat persistence over time was especially important for climate refugia and was best achieved by a land-purchase policy instrument. In contrast, for the strategy supporting range shifts to be ecologically effective, a high degree of flexibility in the location of conserved sites was required to ensure that new habitat sites can be created in the species’ new range. Offset programs were best suited for that because the location of conservation sites can be chosen comparatively freely and may also be adapted over time.     

Exploring metapopulation-scale suppression alternatives for a global invader in a river network experiencing climate change

Invasive species can dramatically alter ecosystems, but eradication is difficult, and suppression is expensive once they are established. Uncertainties in the potential for expansion and impacts by an invader can lead to delayed and inadequate suppression, allowing for establishment. Metapopulation viability models can aid in planning strategies to improve responses to invaders and lessen invasive species’ impacts, which may be particularly important under climate change. We used a spatially explicit metapopulation viability model to explore suppression strategies for ecologically damaging invasive brown trout (Salmo trutta), established in the Colorado River and a tributary in Grand Canyon National Park. Our goals were to estimate the effectiveness of strategies targeting different life stages and subpopulations within a metapopulation; quantify the effectiveness of a rapid response to a new invasion relative to delaying action until establishment; and estimate whether future hydrology and temperature regimes related to climate change and reservoir management affect metapopulation viability and alter the optimal management response. Our models included scenarios targeting different life stages with spatially varying intensities of electrofishing, redd destruction, incentivized angler harvest, piscicides, and a weir. Quasi-extinction (QE) was obtainable only with metapopulation-wide suppression targeting multiple life stages. Brown trout population growth rates were most sensitive to changes in age 0 and large adult mortality. The duration of suppression needed to reach QE for a large established subpopulation was 12 years compared with 4 with a rapid response to a new invasion. Isolated subpopulations were vulnerable to suppression; however, connected tributary subpopulations enhanced metapopulation persistence by serving as climate refuges. Water shortages driving changes in reservoir storage and subsequent warming would cause brown trout declines, but metapopulation QE was achieved only through refocusing and increasing suppression. Our modeling approach improves understanding of invasive brown trout metapopulation dynamics, which could lead to more focused and effective invasive species suppression strategies and, ultimately, maintenance of populations of endemic fishes.     

城市生态气象监测评估初步研究与实践——以北京为例

气象条件作为影响生态系统最活跃、最直接的驱动因子,影响着生态系统的质量和人类生存的环境,关系着生态保护和建设的成果,而城市生态系统具有与其他系统不一样的气候特征,目前还未形成一套有关城市的生态气象监测评估方法。基于生态气象学理论,分别从城市气候环境、与气候相关的陆表环境、大气环境、人居环境以及城市高影响天气气候事件等5个方面选择不同的要素和指标开展了城市生态气象监测评估初步研究,并以北京为例,利用2018年国家和区域自动气象站资料、大气成分观测资料、2002—2018年MODIS卫星资料、Landsat及环境一号卫星资料,开展了2018年北京城市生态气象监测评估。监测评估显示,(1)2018年北京城市“热岛”和“干岛”气候特征明显,并在北京二环与五环之间存在一个“冂”形风速低值区。(2)2018年北京陆表生态环境、大气环境、人居环境进一步好转:其中植被覆盖度达61.6%,创2002年以来新高,气象条件贡献率达50%,生态涵养区植被生态质量处于正常偏好的面积比例达93.2%;中心城区陆表温度为2011年以来最低值;重要水源地密云水库、官厅水库水体面积均为2000年以来最大值;气溶胶光学厚度、霾日数、大气静稳指数分别较过去4年平均值下降14%、31%和8%,大气扩散条件偏好,对霾日减少贡献率达21%,外地污染传输对PM2.5贡献达到53%;城市生态冷源较2013年明显增加,城市“热岛”得到缓解。(3)历史罕见的夏季高温闷热、冬季阶段低温、极端强降水以及持续无降水等高影响天气气候事件给城市安全运行和生态环境带来不利影响。综合评估表明2018年北京气象条件总体利于陆表生态环境改善,有利的气候条件提高了生态环境的质量,但城市生态质量仍面临着极端天气气候事件、城市热岛、低风速以及外来大气污染输送等风险。     

Measuring impacts on species with models and metrics of varying ecological and computational complexity

Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data-rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

Site-selection bias and apparent population declines in long-term studies

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.     

Forecast-based action for conservation

Extreme weather events pose an immediate threat to biodiversity, but existing conservation strategies have limitations. Advances in meteorological forecasting and innovation in the humanitarian sector provide a possible solution—forecast-based action (FbA). The growth of ecological forecasting demonstrates the huge potential to anticipate conservation outcomes, but a lack of operational examples suggests a new approach is needed to translate forecasts into action. FbA provides such a framework, formalizing the use of meteorological forecasts to anticipate and mitigate the impacts of extreme weather. Based on experience from the humanitarian sector, I suggest how FbA could work in conservation, demonstrating key concepts using the theoretical example of heatwave impacts on sea turtle embryo mortality, and address likely challenges in realizing FbA for conservation, including establishing a financing mechanism, allocating funds to actions, and decision-making under uncertainty. FbA will demand changes in conservation research, practice, and governance. Researchers must increase efforts to understand the impacts of extreme weather at more immediate and actionable timescales and should coproduce forecasts of such impacts with practitioners. International conservation funders should establish systems to fund anticipatory actions based on uncertain forecasts.     

A new method for broad-scale modeling and projection of plant assemblages under climatic,biotic, and environmental cofiltering

There is increasing interestin broad-scale analysis, modeling, and prediction of the distribution and composition of plant species assemblages under climatic, environmental, and biotic change, particularly for conservation purposes. We devised a method to reliably predict the impact of climate change on large assemblages of plant communities, while also considering competing biotic and environmental factors. To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. We applied our model to a large set of plant communities in the Swiss Alps. Our model explained presences and absences of 175 plant species in 608 plots with >87% cross-validated accuracy, predicted decreases in α, β, and γ diversity by 2040 under both moderate and extreme climate scenarios, and identified likely advantaged and disadvantaged plant species under climate change. Multilabel variable selection revealed the overriding importance of topography, soils, and temperature extremes (rather than averages) in determining the distribution of plant species in the study area and their response to climate change. Our method addressed a number of challenging research problems, such as scaling to large numbers of species, considering species relationships and rarity, and addressing an overwhelming proportion of absences in presence–absence matrices. By handling hundreds to thousands of plants and plots simultaneously over large areas, our method can inform broad-scale conservation of plant species under climate change because it allows species that require urgent conservation action (assisted migration, seed conservation, and ex situ conservation) to be detected and prioritized. Our method also increases the practicality of assisted colonization of plant species by helping to prevent ill-advised introduction of plant species with limited future survival probability.     

Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.     

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial–environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial–environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.     

Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.     

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate

Scientists, resource managers, and decision makers increasingly use knowledge coproduction to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley (USA) to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We coproduced scenario narratives, spatially explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We documented our coproduction process, and using the coproduced models, we determined when and where management actions make a difference and when climate overrides these actions. The outcomes of this process provide lessons learned on how to cocreate usable information and how to increase climate adaptive capacity in a highly managed landscape. Actions to restore wetlands and prioritize their water supply created habitat outcomes resilient to climate change impacts particularly in March, when habitat was most limited; land protection combined with management can increase the ecosystem's resilience to climate change; and uptake and use of this information was influenced by the roles of different stakeholders, rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. Although a broad stakeholder group contributed knowledge to scenario narratives and model development, to coproduce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped build legitimacy. Yet, broadscale use of climate adaptation knowledge depends on state and local policies, engagement with decision makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.     

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968–1993 and 1994–2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.     

Protected area planning to conserve biodiversity in an uncertain future

Protected areas are a key instrument for conservation. Despite this, they are vulnerable to risks associated with weak governance, land-use intensification, and climate change. We used a novel hierarchical optimization approach to identify priority areas for expanding the global protected area system that explicitly accounted for such risks while maximizing protection of all known terrestrial vertebrate species. To incorporate risk categories, we built on the minimum set problem, where the objective is to reach species distribution protection targets while accounting for 1 constraint, such as land cost or area. We expanded this approach to include multiple objectives accounting for risk in the problem formulation by treating each risk layer as a separate objective in the problem formulation. Reducing exposure to these risks required expanding the area of the global protected area system by 1.6% while still meeting conservation targets. Incorporating risks from weak governance drove the greatest changes in spatial priorities for protection, and incorporating risks from climate change required the largest increase (2.52%) in global protected area. Conserving wide-ranging species required countries with relatively strong governance to protect more land when they bordered nations with comparatively weak governance. Our results underscore the need for cross-jurisdictional coordination and demonstrate how risk can be efficiently incorporated into conservation planning. Planeación de las áreas protegidas para conservar la biodiversidad en un futuro incierto     

Long-term drivers of persistence and colonization dynamics in spatially structured amphibian populations

Many organisms live in networks of local populations connected by dispersing individuals, called spatially structured populations (SSPs), where the long-term persistence of the entire network is determined by the balance between 2 processes acting at the scale of local populations: extinction and colonization. When multiple threats act on an SSP, a comparison of the different factors determining local extinctions and colonizations is essential to plan sound conservation actions. We assessed the drivers of long-term population dynamics of multiple amphibian species at the regional scale. We used dynamic occupancy models within a Bayesian framework to identify the factors determining persistence and colonization of local populations. Because connectivity among patches is fundamental to SSPs dynamics, we considered 2 measures of connectivity acting on each focal patch: incidence of the focal species and incidence of invasive crayfish. We used meta-analysis to summarize the effect of different drivers at the community level. Persistence and colonization of local populations were jointly determined by factors acting at different scales. Persistence probability was positively related to the area and the permanence of wetlands, whereas it was negatively related to occurrence of fish. Colonization probability was highest in semipermanent wetlands and in sites with a high incidence of the focal species in nearby sites, whereas it showed a negative relationship with the incidence of invasive crayfish in the landscape. By analyzing long-term data on amphibian population dynamics, we found a strong effect of some classic features commonly used in SSP studies, such as patch area and focal species incidence. The presence of an invasive non-native species at the landscape scale emerged as one of the strongest drivers of colonization dynamics, suggesting that studies on SSPs should consider different connectivity measures more frequently, such as the incidence of predators, especially when dealing with biological invasions.     

A global ecological signal of extinction risk in terrestrial vertebrates

To determine the distribution and causes of extinction threat across functional groups of terrestrial vertebrates, we assembled an ecological trait data set for 18,016 species of terrestrial vertebrates and utilized phylogenetic comparative methods to test which categories of habitat association, mode of locomotion, and feeding mode best predicted extinction risk. We also examined the individual categories of the International Union for Conservation of Nature Red List extinction drivers (e.g., agriculture and logging) threatening each species and determined the greatest threats for each of the four terrestrial vertebrate groups. We then quantified the sum of extinction drivers threatening each species to provide a multistressor perspective on threat. Cave dwelling amphibians (p < 0.01), arboreal quadrupedal mammals (all of which are primates) (p < 0.01), aerial and scavenging birds (p < 0.01), and pedal (i.e., walking) squamates (p < 0.01) were all disproportionately threatened with extinction in comparison with the other assessed ecological traits. Across all threatened vertebrate species in the study, the most common risk factors were agriculture, threatening 4491 species, followed by logging, threatening 3187 species, and then invasive species and disease, threatening 2053 species. Species at higher risk of extinction were simultaneously at risk from a greater number of threat types. If left unabated, the disproportionate loss of species with certain functional traits and increasing anthropogenic pressures are likely to disrupt ecosystem functions globally. A shift in focus from species- to trait-centric conservation practices will allow for protection of at-risk functional diversity from regional to global scales.