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Species with large local abundances tend to occupy more sites. One of the mechanisms proposed to explain this widely reported inter-specific relationship is a cross-scale hypothesis based on dynamics at the population level. Called the vital rates mechanism, it uses within-population demographic processes of population growth and density dependence to predict when inter-specific abundance-occupancy relationships can arise and when these relationships can weaken and even turn negative. Even though the vital rates mechanism is mathematically simple, its predictions has never been tested directly because of the difficulty estimating the demographic parameters involved. Here, using a recently introduced mark-recapture analysis method, we show that there is a weakly positive relationship between abundance and occupancy among 17 bird species. Our results are consistent with the predictions of the vital rate mechanism regarding the demographic processes that are expected to weaken this relationship. Specifically, we find that intrinsic growth rate and local abundance are weakly correlated; and density dependence strength shows considerable variation across species. Variability in density dependence strength is related to variability in species-level local average abundance and intrinsic growth rate; species with lower growth rate have higher abundance and are strongly regulated by density dependent processes, especially acting on survival rates. Species with higher growth rate, on average, have lower abundance and are more weakly regulated by density dependent processes especially acting on fecundity. More generally, our findings support a cross scale mechanism of macroecological abundance-occupancy relationship emerging from density-dependent dynamics at the population level.

Population reductions are often used to assess extinction risk of species in the IUCN Red List. Guidelines for Red List assessments describe specific methods for calculating the amount of reduction for species with strongly fluctuating populations. Recently, an alternative approach that involves expert opinion has been suggested for calculating population reduction in insect species. We argue that, while populations with high temporal variability do present challenges, the alternative suggestion is unnecessary, and inconsistent with the IUCN Red List Categories and Criteria. Consistent application of standardized methods for calculating population reductions allows robust and objective assessment of extinction risk faced by invertebrate species.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.Reconociendo que era imperativo evaluar la recuperación de especies y el impacto de la conservación, la Unión Internacional para la Conservación de la Naturaleza (UICN) convocó en 2012 al desarrollo de una “Lista Verde de Especies” (ahora el Estatus Verde de las Especies de la UICN). Un marco de referencia preliminar de una Lista Verde de Especies para evaluar el progreso de las especies hacia la recuperación, publicado en 2018, proponía 2 componentes separados pero interconectados: un método estandarizado (i.e., medición en relación con puntos de referencia de la viabilidad de especies, funcionalidad y distribución antes del impacto) para determinar el estatus de recuperación actual (puntuación de recuperación de la especie) y la aplicación de ese método para estimar impactos en el pasado y potenciales de conservación basados en 4 medidas (legado de conservación, dependencia de conservación, ganancia de conservación y potencial de recuperación). Probamos el marco de referencia con 181 especies representantes de diversos taxa, historias de vida, biomas, y categorías (riesgo de extinción) en la Lista Roja de la IUCN. Con base en la distribución observada de la puntuación de recuperación de las especies, proponemos las siguientes categorías de recuperación de la especie: totalmente recuperada, ligeramente mermada, moderadamente mermada, mayormente mermada, gravemente mermada, extinta en estado silvestre, e inderterminada. Cincuenta y nueve por ciento de las especies se consideraron mayormente o gravemente mermada. Aunque hubo una relación negativa entre el riesgo de extinción y la puntuación de recuperación de la especie, la variación fue considerable. Algunas especies en las categorías de riesgo bajas fueron evaluadas como más lejos de recuperarse que aquellas con alto riesgo. Esto enfatiza que la recuperación de especies es diferente conceptualmente al riesgo de extinción y refuerza la utilidad del Estado Verde de las Especies de la UICN para comprender integralmente el estatus de conservación de especies. Aunque el riesgo de extinción no predijo el legado de conservación, la dependencia de conservación o la ganancia de conservación, se correlacionó positivamente con la potencial de recuperación. Solo 1.7% de las especies probadas fue categorizado como cero en los 4 indicadores de impacto de la conservación, lo que indica que la conservación ha jugado, o jugará, un papel en la mejoría o mantenimiento del estatus de la especie la gran mayoría de ellas. Con base en nuestros resultados, diseñamos una versión actualizada del marco de referencia para la evaluación que introduce la opción de utilizar una línea de base dinámica para evaluar los impactos futuros de la conservación en el corto plazo y redefine corto plazo como 10 años.

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species includes assessment of extinction risk for 98 512 species, plus documentation of their range, habitat, elevation, and other factors. These range, habitat and elevation data can be matched with terrestrial land cover and elevation datasets to map the species’ area of habitat (AOH; also known as extent of suitable habitat; ESH). This differs from the two spatial metrics used for assessing extinction risk in the IUCN Red List criteria: extent of occurrence (EOO) and area of occupancy (AOO). AOH can guide conservation, for example, through targeting areas for field surveys, assessing proportions of species’ habitat within protected areas, and monitoring habitat loss and fragmentation. We recommend that IUCN Red List assessments document AOH wherever practical., Trends in Ecology & Evolution, 34 (11), ISSN:0169-5347, ISSN:1872-8383

Pathways to extinction start long before the death of the last individual. However, causes of early stage population declines and the susceptibility of small residual populations to extirpation are typically studied in isolation. Using validated process-explicit models, we disentangle the ecological mechanisms and threats that were integral in the initial decline and later extinction of the woolly mammoth. We show that reconciling ancient DNA data on woolly mammoth population decline with fossil evidence of location and timing of extinction requires process-explicit models with specific demographic and niche constraints, and a constrained synergy of climatic change and human impacts. Validated models needed humans to hasten climate-driven population declines by many millennia, and to allow woolly mammoths to persist in mainland Arctic refugia until the mid-Holocene. Our results show that the role of humans in the extinction dynamics of woolly mammoth began well before the Holocene, exerting lasting effects on the spatial pattern and timing of its range-wide extinction.

International audience; Accounting for taxonomic and geographic variation in historic human impacts on indigenous range will facilitate use of IUCN’s Green List of Species.

Pathways to extinction start long before the death of the last individual. However, causes of early-stage population declines and the susceptibility of small residual populations to extirpation are typically studied in isolation. Using validated process-explicit models, we disentangle the ecological mechanisms and threats that were integral in the initial decline and later extinction of the woolly mammoth. We show that reconciling ancient DNA data on woolly mammoth population decline with fossil evidence of location and timing of extinction requires process-explicit models with specific demographic and niche constraints, and a constrained synergy of climatic change and human impacts. Validated models needed humans to hasten climate-driven population declines by many millennia, and to allow woolly mammoths to persist in mainland Arctic refugia until the mid-Holocene. Our results show that the role of humans in the extinction dynamics of woolly mammoth began well before the Holocene, exerting lasting effects on the spatial pattern and timing of its range-wide extinction.

Stopping human-induced extinctions will require strong policy commitments that comprehensively address threats to species. In 2021, a new Global Biodiversity Framework will be agreed by the Convention on Biological Diversity. Here we investigate how the suggested targets could contribute to reducing threats to threatened vertebrates, invertebrates, and plants, and assess the importance of a proposed target to implement recovery actions for threatened species. We find that whilst many of the targets benefit species, extinction risk for over one third of threatened species would not be reduced sufficiently without a target on recovery actions, includingex situconservation, reintroductions and other species-specific interventions. A median of 41 threatened species per country require such actions, and they are found in most countries of the world. To prevent future extinctions, policy commitments must include recovery actions for the most threatened species in addition to broader transformative change.

Birds have been comprehensively assessed on the International Union for Conservation of Nature (IUCN) Red List more times than any other taxonomic group. However, to date, generation lengths have not been systematically estimated to scale population trends when undertaking assessments, as required by the criteria of the IUCN Red List. We compiled information from major databases of published life-history and trait data for all birds and imputed missing life-history data as a function of species traits with generalized linear mixed models. Generation lengths were derived for all species, based on our modeled values of age at first breeding, maximum longevity, and annual adult survival. The resulting generation lengths varied from 1.42 to 27.87 years (median 2.99). Most species (61%) had generation lengths3.33 years, meaning that the period of 3 generations-over which population declines are assessed under criterion A-was10 years, which is the value used for IUCN Red List assessments of species with short generation times. For these species, our trait-informed estimates of generation length suggested that 10 years is a robust precautionary value for threat assessment. In other cases, however, for whole families, genera, or individual species, generation length had a substantial impact on their estimated extinction risk, resulting in higher extinction risk in long-lived species than in short-lived species. Although our approach effectively addressed data gaps, generation lengths for some species may have been underestimated due to a paucity of life-history data. Overall, our results will strengthen future extinction-risk assessments and augment key databases of avian life-history and trait data.Duraciones Generacionales de las Aves del Mundo y sus Implicaciones para el Riesgo de Extinción Resumen Las aves han sido valoradas integralmente en la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) más veces que cualquier otro grupo taxonómico. Sin embargo, a la fecha, las duraciones generacionales no han sido estimadas sistemáticamente para escalar las tendencias poblacionales cuando se realizan las valoraciones, como lo requieren los criterios de la Lista Roja de la UICN. Compilamos información a partir de las principales bases de datos de historias de vida y datos de características publicadas para todas las aves e imputamos los datos faltantes de historias de vida como una función de las características de especies con modelos lineales mixtos generalizados. La duración por generación estuvo derivada para todas las especies con base en nuestros valores modelados de edad durante la primera reproducción, la longevidad máxima y la supervivencia anual de adultos. La duración por generación resultante varió de 1.42 a 27.87 años (mediana: 2.99). La mayoría de las especies (61%) tuvo una duración generacional3.33 años, lo que significa que el periodo de tres generaciones - durante el cual se valoran las declinaciones poblacionales bajo el Criterio A - es10 años, el cual es el valor usado por la Lista Roja de la UICN para la valoración de especies con tiempos generacionales cortos. Para estas especies, nuestras estimaciones de duración por generación informados por características sugieren que diez años es un valor preventivo sólido para la valoración de amenazas. Para otros casos, sin embargo, como familias o géneros enteros o especies individuales, la duración generacional tuvo un impacto sustancial sobre su riesgo de extinción estimado, resultando así en un riesgo de extinción más elevado para las especies con mayor longevidad que aquellas especies con una menor longevidad. Aunque nuestra estrategia lidió efectivamente con los vacíos en los datos, la duración generacional para algunas especies podría estar subestimada debido a la escasez de datos de historia de vida. En general, nuestros resultados fortalecerán las futuras valoraciones de extinción de riesgo y aumentarán las bases de datos importantes de la historia de vida de las aves y los datos de características.在《世界自然保护联盟 (IUCN) 濒危物种红色名录》中, 鸟类被全面评估的次数比其它任何类群都要多。然而, 目前的评估尚未按照《IUCN红色名单》标准的要求, 系统地估计世代时间来计算种群趋势。我们从已发表的所有鸟类生活史及特征数据的几大数据库中整理了信息, 并用广义线性混合模型构建物种特征的函数对缺失的生活史数据进行了估计。我们进而基于对初次繁殖年龄、最长寿命和成体年均存活率的模拟值, 获得了所有物种的世代时间。得到的鸟类世代时间从 1.42 年到 27.87 年不等 (中位数为 2.99 年) 。大多数物种 (61%) 的世代时间小于 3.33 年, 意味着三个时代的时长小于 10 年, 而这是《 IUCN 红色名录》评估标准 A 中对种群下降的评估周期, 用于评估世代时间短的物种。对于这些物种, 基于特征估计的世代时间表明, 10 年是评估威胁的一个稳健预警值。而在其他情况下, 世代时间对于估计整个科、属或个别物种的灭绝风险有重大影响, 结果导致寿命长的物种灭绝风险高于寿命短的物种。虽然我们的方法有效地解决了数据缺失的问题, 但由于一些物种生活史数据缺乏, 其世代时间可能会被低估。总的来说, 我们的研究结果将强化未来的灭绝风险评估, 并扩增鸟类生活史和特征数据的关键数据库。 【翻译: 胡怡思; 审校: 聂永刚】.

Forecasting changes in size and distributions of populations is at the forefront of ecological sciences in the 21st century. Such forecasts require robust estimators of fecundity, survival and density-dependence. While survival estimation is the main focus of mark-recapture modelling, fecundity and density dependence are rarely the subject of these models. Here, we demonstrate that these parameters can be simultaneously estimated in a Bayesian framework using only robust design mark-recapture data. Using simulated capture histories, we show that this framework (which we named CJS-pop) can estimate vital rates and their density dependence with little bias. When CJS-pop is applied to capture history data from Brown Creeper (Certhia americana), it provides estimates of fecundity that is expected from the breeding biology of this species. Finally, we illustrate that density dependence, even when estimated with uncertainty in the CJS-pop framework, regularizes population dynamics and reduces the frequent population extinctions and explosions observed under density-independent models. While CJS-pop as a whole is a useful addition to the current mark-recapture modelling toolbox, we argue that the independent components of this framework in estimating fecundity and density dependence can be integrated to other CJS frameworks, potentially creating models capable of population projections.

Species interactions matter to conservation. Setting an ambitious recovery target for a species requires considering the size, density, and demographic structure of its populations such that they fulfill the interactions, roles, and functions of the species in the ecosystems in which they are embedded. A recently proposed framework for an International Union for Conservation of Nature Green List of Species formalizes this requirement by defining a fully recovered species in terms of representation, viability, and functionality. Defining and quantifying ecological function from the viewpoint of species recovery is challenging in concept and application, but also an opportunity to insert ecological theory into conservation practice. We propose 2 complementary approaches to assessing a species' ecological functions: confirmation (listing interactions of the species, identifying ecological processes and other species involved in these interactions, and quantifying the extent to which the species contributes to the identified ecological process) and elimination (inferring functionality by ruling out symptoms of reduced functionality, analogous to the red-list approach that focuses on symptoms of reduced viability). Despite the challenges, incorporation of functionality into species recovery planning is possible in most cases and it is essential to a conservation vision that goes beyond preventing extinctions and aims to restore a species to levels beyond what is required for its viability. This vision focuses on conservation and recovery at the species level and sees species as embedded in ecosystems, influencing and being influenced by the processes in those ecosystems. Thus, it connects and integrates conservation at the species and ecosystem levels.Evaluación de la Función Ecológica en el Contexto de Recuperación de Especies Resumen Las interacciones entre especies son de importancia para la conservación. La definición de una meta ambiciosa de recuperación para una especie requiere considerar el tamaño, la densidad y la estructura demográfica de sus poblaciones de tal manera que lleven a cabo las interacciones, papeles y funciones de las especies en los ecosistemas donde viven. Un marco de referencia propuesto recientemente para una Lista Verde de Especies de la Unión Internacional para la Conservación de la Naturaleza (UICN)formaliza este requerimiento mediante la definición de una especie completamente recuperada en términos de su representación, viabilidad y funcionalidad. La definición y cuantificación de la función ecológica desde la perspectiva de la recuperación de especies es un reto conceptual y de aplicación, pero también es un oportunidad para insertar la teoría ecológica en la práctica de la conservación. Proponemos 2 métodos complementarios para evaluar las funciones ecológicas de una especie: confirmación (listado de interacciones de la especie, identificación de procesos ecológicos y otras especies involucradas en estas interacciones) y eliminación (inferencia de la funcionalidad descartando los síntomas de reducción en la funcionalidad, análogo al método de la lista roja que enfoca los síntomas de reducción en la viabilidad). A pesar de los retos, la incorporación de la funcionalidad en la planificación de la recuperación de especies es posible en la mayoría de los casos y es esencial para una visión de la conservación que vaya más allá de la prevención de extinciones y que tenga como objetivo restaurar a una especie a niveles más allá de lo que se requiere para su viabilidad. Su visión se centra en la conservación y recuperación a nivel de especies y ve a las especies como componentes de los ecosistemas, influyendo y siendo influenciadas por los procesos en esos ecosistemas. Así, conecta e integra la conservación a nivel de especies y ecosistemas.物种间的相互作用对保护至关重要。设定远大的物种恢复目标需要考虑其种群大小、密度和种群统计结构, 以确保物种能在其所处的生态系统中实现种间互作和物种自身的作用与功能。最近提出的《国际自然保护联盟 (IUCN) 绿色物种名录》框架正式纳入了这项需求, 提出从代表性、生存力和功能性三个方面来定义完全恢复的物种。从物种恢复的角度来定义和量化其生态功能, 在概念和应用上都具有挑战性, 但这也是在保护实践中引入生态学理论的重要机遇。我们提出了两种互补的方法来评估物种的生态功能: 一是直接确认, 即列出物种的互作、确定互作中涉及的生态学过程和其它物种, 并量化物种对该生态过程的贡献;二是消除法, 即通过排除功能性受损后的症状来推断功能, 这与红色名录中关注生存力降低后的症状的方法类似。虽然还存在上述挑战, 但在大多数情况下将功能性纳入物种恢复计划是可行的, 而且这对于不仅旨在防止灭绝、更要将物种恢复到生存所需水平的保护愿景来说至关重要。这一愿景强调物种水平的保护和恢复, 将物种视为生态系统的一部分, 影响着生态系统过程的同时也受其影响。因此, 它也连接和整合了物种及生态系统水平的保护。【翻译: 胡怡思; 审校: 聂永刚】.

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81

Robust evaluation of the impact of biodiversity conservation actions is important not only for ensuring that conservation strategies are effective and maximise return on investment, but also to identify and celebrate successful conservation strategies. This evaluation can be retrospective (comparing the current situation to a counterfactual scenario) or forward-looking (comparing future scenarios with or without conservation). However, assessment of impact using experimental or quasi-experimental designs is typically difficult in conservation, so rigorous inferential approaches are required. Inferential assessment of impact is a key part of the new IUCN Green Status of Species, which greatly amplifies the need for standardised and practical species impact evaluation methods. Here, we use the Green Status of Species method as a base to review how inferential methods can be used to evaluate conservation impact at the species level. We identify three key components of the inferential impact evaluation process—estimation of scenario outcomes, selection of baseline scenario, and frame of reference—and explain, with examples, how to reduce the subjectivity of these steps. We propose a step-by-step guide, incorporating these principles, that can be used to infer scenario outcomes in order to evaluate past and future conservation impact in a wide range of situations, not just Green Status of Species assessments. We recommend that future non-experimental conservation interventions facilitate the process of evaluating impact by identifying the variable(s) that will be used to measure impact at the design stage, and by using conceptual models to help choose conservation actions most likely to have the desired impact.

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs.

The use of long-term ecological proxies in conservation planning is currently very limited. Recent advances offer exciting prospects for enhanced use of retrospective knowledge to forecast and manage ecological outcomes under global change.

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

The temporal variability of many animal populations increases with the length of census period. This pattern is associated with the reddened spectral colour, quantified by the spectral exponent, which is typically around + 1. We used simulation models to explore the effects of various population-level processes on the spectral colour of the simulated time series of abundances. Our results showed that the observed spectral exponents could be explained as the effect of a combination of measurement error and natural variability (in the form of white environmental noise). Thus, it may not be necessary to invoke complex varieties of environmental noise to explain the observed spectral exponents.

Assessing species' vulnerability to climate change is a prerequisite for developing effective strategies to conserve them. The last three decades have seen exponential growth in the number of studies evaluating how, how much, why, when, and where species will be impacted by climate change. We provide an overview of the rapidly developing field of climate change vulnerability assessment (CCVA) and describe key concepts, terms, steps and considerations. We stress the importance of identifying the full range of pressures, impacts and their associated mechanisms that species face and using this as a basis for selecting the appropriate assessment approaches for quantifying vulnerability. We outline four CCVA assessment approaches, namely trait-based, correlative, mechanistic and combined approaches and discuss their use. Since any assessment can deliver unreliable or even misleading results when incorrect data and parameters are applied, we discuss finding, selecting, and applying input data and provide examples of open-access resources. Because rare, small-range, and declining-range species are often of particular conservation concern while also posing significant challenges for CCVA, we describe alternative ways to assess them. We also describe how CCVAs can be used to inform IUCN Red List assessments of extinction risk. Finally, we suggest future directions in this field and propose areas where research efforts may be particularly valuable.

Stopping declines in biodiversity is critically important, but it is only a first step toward achieving more ambitious conservation goals. The absence of an objective and practical definition of species recovery that is applicable across taxonomic groups leads to inconsistent targets in recovery plans and frustrates reporting and maximization of conservation impact. We devised a framework for comprehensively assessing species recovery and conservation success. We propose a definition of a fully recovered species that emphasizes viability, ecological functionality, and representation; and use counterfactual approaches to quantify degree of recovery. This allowed us to calculate a set of 4 conservation metrics that demonstrate impacts of conservation efforts to date (conservation legacy); identify dependence of a species on conservation actions (conservation dependence); quantify expected gains resulting from conservation action in the medium term (conservation gain); and specify requirements to achieve maximum plausible recovery over the long term (recovery potential). These metrics can incentivize the establishment and achievement of ambitious conservation targets. We illustrate their use by applying the framework to a vertebrate, an invertebrate, and a woody and an herbaceous plant. Our approach is a preliminary framework for an International Union for Conservation of Nature (IUCN) Green List of Species, which was mandated by a resolution of IUCN members in 2012. Although there are several challenges in applying our proposed framework to a wide range of species, we believe its further development, implementation, and integration with the IUCN Red List of Threatened Species will help catalyze a positive and ambitious vision for conservation that will drive sustained conservation action. ISSN:0888-8892 ISSN:1523-1739

[Excerpt] We thank Lehtomaki et al. (2019) for widening the discussion of the Plan-S open-access initiative (https://www.coalition-s.org) in their response to Burgman et al. (2018). They provide useful links to Plan-S documentation. They are disappointed by the focus of our position, which we took to clarify a point central to the discussion of open access that we believe has received too little attention,namely, equity of access to publication.

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.

Threats to wildlife species from extreme events, such as droughts, are predicted to increase in frequency and magnitude with climate change. Extreme events can cause mortality and community-level changes, but for some mobile species, movement away from areas affected may be a viable option. We examined the effect of extreme weather on spatial patterns of abundance for an irruptive grassland bird species, the Dickcissel (Spiza americana). We calculated route-level annual abundances and abundance anomalies from 1980 to 2012 from North American Breeding Bird Survey data, and classified the Dickcissel’s range into core and edge regions using these abundances. We then compared abundances in the core and edge regions to the standardized precipitation evapotranspiration index, a measure of drought, in linear regressions. We found that Dickcissel irruptions in the northern range edges were related to drought conditions in the range core, potentially a consequence of birds being ‘pushed’ to the range edge when weather was unsuitable. Specifically, Dickcissels moved into refuge sites containing a high proportion of cultivated crops, with higher vegetation greenness, than those areas they leave during drought years. In a changing climate where more frequent extreme weather may be more common, conservation strategies for weather-sensitive species may require consideration of habitat in the edges of species’ ranges, even though non-core areas may be unoccupied in ‘normal’ years. Our results highlight the conservation importance of range edges in providing refuge from extreme events, such as drought, and climate change.

Exploited fish populations frequently exhibit truncated age-structure. To address a basic question in fisheries science and conservation biology—how does age truncation affect population dynamics and productivity?—we explored the effect of age-structure on recruitment dynamics of ten stocks of Atlantic cod (Gadus morhua). Based on six alternative stock–recruitment relationships, we compared models that included and excluded maternal age-structure effects on recruitment. In all ten stocks, a recruitment model that included a maternal age-dependent effect was preferred over the standard Ricker model and in seven of the ten stocks, the preferred statistical model included a positive effect of either maternal age or mass on recruitment. Simulations comparing standard and maternal age dependent recruitment two decades into the future suggest that the inclusion of maternal age in recruitment models has little effect on projected biomasses. However, this similarity in biomass trajectory masked an increased sensitivity of populations with maternal age-dependent recruitment to stock age-structure. In particular, simulations with maternal age-dependent recruitment responded strongly to changes in fishing mortality on the oldest age classes, while simulations using standard recruitment models did not. Populations with maternal age-dependent recruitment can exhibit increased biomass catch even if fishing mortality on older individuals was reduced. Overall, simulations suggested that the influence of maternal age on population dynamics are more nuanced than suggested by previous research and indicate that careful consideration of the effects of age-structure on populations may lead to substantially different fisheries management reference points—particularly with respect to age-specific fishing mortality—than classical models. While these results suggest a link between maternal age and population productivity, future research requires the incorporation of biologically reasonable and empirically defensible mechanisms to clarify the effect of age on population dynamics.

The effects of climate change on biodiversity are increasingly well documented, and many methods have been developed to assess species' vulnerability to climatic changes, both ongoing and projected in the coming decades. To minimize global biodiversity losses, conservationists need to identify those species that are likely to be most vulnerable to the impacts of climate change. In this Review, we summarize different currencies used for assessing species' climate change vulnerability. We describe three main approaches used to derive these currencies (correlative, mechanistic and trait-based), and their associated data requirements, spatial and temporal scales of application and modelling methods. We identify strengths and weaknesses of the approaches and highlight the sources of uncertainty inherent in each method that limit projection reliability. Finally, we provide guidance for conservation practitioners in selecting the most appropriate approach(es) for their planning needs and highlight priority areas for further assessments.

Extinctions are important indicators of biodiversity status. When they are detected, they may trigger the redirection of conservation resources to save other species. Yet declaring extinctions is inherently uncertain. Relevant evidence for consideration includes information on threats, the time series of species records and the effort employed to search for remaining individuals. Quantitative tools have been developed to infer extinctions from data on the timing of records. In contrast, inference of extinction from threats relies on expert judgement and is susceptible to subjective influences. To use qualitative information on threats, we suggest experts should construct an argument map to identify reasons, evidence and sources in support of a claim that a species has gone extinct, as well as objections, evidence and sources as to why the claim may not be true. The reasons must explicitly address: i) whether identified threats are sufficiently severe and prolonged to cause local extinction; and ii) whether such threats are sufficiently extensive to eliminate all occurrences. Transparent mapping of reasons and objections enables experts to estimate subjective probabilities that each alternative claim is true, allowing an overall probability of extinction to be calculated. We provide examples illustrating how typical evidence may be evaluated. To deal with uncertainties, we suggest bounded estimates of subjective probabilities are obtained from multiple experts in a structured elicitation. The method requires no detailed mathematical analysis, but relies on structured reasoning. The subjective estimates of probabilities must be based on the severity and pervasiveness of threats alone, to allow comparison with estimates derived independently from other sources of information such as time series of records.

Diagnosing the processes that threaten species persistence is critical for recovery planning and risk forecasting. Dominant threats are typically inferred by experts on the basis of a patchwork of informal methods. Transparent, quantitative diagnostic tools would contribute much-needed consistency, objectivity, and rigor to the process of diagnosing anthropogenic threats. Long-term census records, available for an increasingly large and diverse set of taxa, may exhibit characteristic signatures of specific threatening processes and thereby provide information for threat diagnosis. We developed a flexible Bayesian framework for diagnosing threats on the basis of long-term census records and diverse ancillary sources of information. We tested this framework with simulated data from artificial populations subjected to varying degrees of exploitation and habitat loss and several real-world abundance time series for which threatening processes are relatively well understood: bluefin tuna (Thunnus maccoyii) and Atlantic cod (Gadus morhua) (exploitation) and Red Grouse (Lagopus lagopus scotica) and Eurasian Skylark (Alauda arvensis) (habitat loss). Our method correctly identified the process driving population decline for over 90% of time series simulated under moderate to severe threat scenarios. Successful identification of threats approached 100% for severe exploitation and habitat loss scenarios. Our method identified threats less successfully when threatening processes were weak and when populations were simultaneously affected by multiple threats. Our method selected the presumed true threat model for all real-world case studies, although results were somewhat ambiguous in the case of the Eurasian Skylark. In the latter case, incorporation of an ancillary source of information (records of land-use change) increased the weight assigned to the presumed true model from 70% to 92%, illustrating the value of the proposed framework in bringing diverse sources of information into a common rigorous framework. Ultimately, our framework may greatly assist conservation organizations in documenting threatening processes and planning species recovery. Inferencia la Naturaleza de las Amenazas Antropogenicas para los Registros de Abundancia a Largo Plazo Resumen Diagnosticar los procesos que amenazan la permanencia de las especies es critico para la planeacion de la recuperacion y la prediccion de riesgos. Las amenazas dominantes se infieren comunmente por expertos con base en un collage de metodos informales. Las herramientas de diagnostico transparentes y cuantitativas podrian contribuir con la tan necesitada consistencia, objetividad y rigor para el proceso de diagnosticar amenazas antropogenicas. Los registros de censos a largo plazo, disponibles para un creciente y diverso conjunto de taxa, pueden exhibir rasgos caracteristicos de procesos especificos de amenaza y asi proporcionar informacion para la diagnosis de amenazas. Desarrollamos un marco de trabajo Bayesiano y flexible para diagnosticar amenazas con base en los registros de censos a largo plazo y diversas fuentes subsidiarias de informacion. Probamos este marco de trabajo con datos simulados de poblaciones artificiales sujetas a diferentes grados de explotacion y perdida de habitat y varias series de tiempos de abundancia reales para los cuales estan bien entendidos los procesos de amenaza: Thunnus maccoyii y Gadus morhua para la explotacion; Lagopus lagopus scotica y Alauda arvensis para la perdida de habitat. Nuestro metodo identifico correctamente el proceso conductor de la declinacion poblacional para mas del 90% de las series de tiempo simuladas bajo escenarios moderados y severos de amenaza. Nuestro metodo identifico las amenazas con menos exito cuando los procesos de amenaza eran debiles o cuando las poblaciones estaban afectadas simultaneamente por amenazas multiples. Nuestro metodo selecciono el modelo de la presunta verdadera amenaza para todos los estudios de caso reales, aunque los resultados fueron algo ambiguos en el caso de Alauda arvensis. En el ultimo caso, la incorporacion de una fuente subsidiaria de informacion (registros de cambio en el uso de suelo) incrementaron la fuerza asignada al supuesto modelo verdadero del 70% al 92%, ilustrando el valor del marco de trabajo propuesto en la contribucion de diversas fuentes de informacion para un marco de trabajo comun y riguroso. Finalmente, nuestro marco de trabajo puede asistir enormemente a las organizaciones de la conservacion en la documentacion de procesos de amenaza y en la planeacion de la recuperacion de especies.

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long-lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire-prone ecosystems, including the biodiversity hotspots of Mediterranean-type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long-lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land-use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land-use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored.

Climate change could be a game-changer for biodiversity conservation, potentially invalidating many established methods including those employed in vulnerability assessments. Now, a simulation study finds that extinction risk due to climate change can be predicted using measurable spatial and demographic variables. Interestingly, most of those variables identified as important are already used in species conservation assessment. There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate1. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change2,3,4,5 based on the expectation that established assessments such as the IUCN Red List6 need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened7,8,9, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

Summary 1. Species interactions have been largely ignored in extinction risk assessment. However, the black-footed ferret Mustela nigripes exemplifies a class of endangered species for which strong species interactions cannot be ignored. This species is an obligate predator of prairie dogs Cynomys spp., and sylvatic plague Yersinia pestis epizootics threaten to undermine recovery efforts by functionally eliminating the prey base. Multispecies ‘metamodelling’ techniques offer new opportunities for exploring population dynamics under strong species interdependencies and disease. 2. To investigate ferret extinction risk in plague-affected landscapes, we simultaneously modelled plague epidemiological processes, prairie dog metapopulation dynamics and ferret demographic responses. Ferret population dynamics were investigated at an important release site (Conata Basin in South Dakota) and for 500 artificial prey landscapes spanning a wide range of realistic colony configurations (e.g. total area, # colonies, spatial clustering) and demographic characteristics. 3. Our simulation models indicate that ferrets are unlikely to persist through episodes of plague at Conata Basin unless they can access prey resources from a wider region or unless management actions can otherwise substantially reduce plague transmission. 4. We show that large, diffuse prairie dog metapopulations (those with colonies spread over a region >2500 km 2 ) are most likely to support ferret populations in plague-affected landscapes. Our results also highlight the potential importance of metapopulation connectivity in fuelling plague epizootics and thereby imperilling black-footed ferret conservation efforts. 5. We describe a cycle (c. 5- to 25-year period) of plague-driven population crashes that is an emergent property of our models, and which can destabilize ferret populations. 6. Synthesis and applications. On the basis of our models, we conclude that few North American prairie dog complexes cover sufficient land area to sustain black-footed ferret populations through plague-driven crashes in prey abundance. Consequently, our results underscore the importance of working with many constituents to conserve large prairie dog landscapes in addition to continued development of plague mitigation tools. In addition, the strong relationship between plague-induced oscillatory prey cycles and predator population persistence highlights the potential conservation benefits of imposing strategic barriers to connectivity in areas over which plague outbreak cycles are strongly synchronous.

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow-acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short-lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions.

Spatially explicit metapopulation models are being used with increasing frequency to forecast changes in species’ abundance in response to future climate and other environmental changes. However, to date, they have not quantified shifts in the margins of the metapopulation range – an important dynamic for understanding species responses to climate change. Here we describe a method for calculating shifts in a metapopulation's range-margin based on the geographical centroid of spatially distributed patches, where the population abundance of each patch or each landscape grid cell is used to weight its geographical (X–Y) coordinate. We evaluated our approach against a detailed virtual example and two real-world applications (threatened mountain hare in Britain and invasive European rabbits in Australia). We also investigated smoothing techniques to better portray overall trends in range changes through time. These procedures were implemented in a new user-friendly software tool, which can process the output file of the popular RAMAS Metapop software. We develop a scenario analysis to show how our weighted-centroid approach can be used to recommend species management options that are most important to long-term population viability (e.g., to choose between increasing connectivity, habitat quality or translocation) under different demographic scenarios. We show that calculating a smoothed time series of weighted centroids from a spatially explicit metapopulation model provides: (i) a useful way to identify the demographic momentum, or momentum of population shift, of the metapopulation (rather than just spatial aggregation or individual-patch behaviour) of a species through geographic space in response to climate change; and (ii) an informative metric of range movement that complements predictions of change in range area or total population size, and extirpation or founding of patches.

Scenarios are powerful tools toenvision how nature might respondto different pathways of futurehuman development and policy choices1.Most scenarios developed for globalenvironmental assessments have exploredimpacts of society on nature, such asbiodiversity loss, but have not includednature as a component of socioeconomicdevelopment2. They ignore policyobjectives related to nature protectionand neglect nature?s role in underpinningdevelopment and human well-being.This approach is becoming untenablebecause targets for human developmentare increasingly connected with targetsfor nature, such as in the United Nations?Sustainable Development Goals. The nextgeneration of scenarios should explorealternative pathways to reach theseintertwined targets, including potentialsynergies and trade-offs between natureconservation and other developmentgoals, as well as address feedbacks betweennature, nature?s contributions to people,and human well-being. The developmentof these scenarios would benefit from theuse of participatory approaches, integratingstakeholders from multiple sectors (forexample, fisheries, agriculture, forestry)and should address decision-makersfrom the local to the global scale3, therebysupporting assessments being undertakenby the Intergovernmental Platformon Biodiversity and EcosystemServices (IPBES). Fil: Rosa, Isabel M. D.. German Centre For Integrative Biodiversity Research; Alemania. Martin-universitat Halle-wittenberg; Alemania Fil: Pereira, Henrique M.. German Centre For Integrative Biodiversity Research; Alemania. Martin-universitat Halle-wittenberg; Alemania. Universidad de Porto; Portugal Fil: Ferrier, Simon. Csiro Land And Water; Australia Fil: Alkemade, Rob. Pbl Netherlands Environmental Assessment Agency; Países Bajos Fil: Acosta, Lilibeth A.. University Of The Philippines Los Banos; Filipinas Fil: Akcakaya, H. Resit. Stony Brook University; Estados Unidos Fil: Den Belder, Eefje. Pbl Netherlands Environmental Assessment Agency; Países Bajos. Wageningen University And Research Centre; Países Bajos Fil: Fazel, Asghar M.. Eco Institute Of Environmental Science And Technology; Irán. University Of Environment; Irán Fil: Fujimori, Shinichiro. International Institute For Applied Systems Analysis; Austria. National Institute For Environmental Studies Of Japan; Japón Fil: Harfoot, Mike. United Nations Environment Programme World Conservation Monitoring Centre; Reino Unido Fil: Harhash, Khaled A.. Egyptian Environmental Affairs Agency; Egipto Fil: Harrison, Paula A.. Lancaster University; Reino Unido Fil: Hauck, Jennifer. Coknow Consulting; Alemania. Helmholtz Centre for Environmental Research; Alemania Fil: Hendriks, Rob J. J.. Ministry Of Economic Affairs; Países Bajos Fil: Hernández, Gladys. Centre For World Economy Studies; Cuba Fil: Jetz, Walter. Imperial College London; Reino Unido. University of Yale; Estados Unidos Fil: Karlsson Vinkhuyzen, Sylvia I.. Wageningen University And Research Centre; Países Bajos Fil: Kim, Hyejin. National Institute Of Ecology; Corea del Sur Fil: King, Nicholas. North-west University; Sudáfrica Fil: Kok, Marcel T. J.. Pbl Netherlands Environmental Assessment Agency; Países Bajos Fil: Kolomytsev, Grygoriy O.. Schmalhausen Institute of Zoology of National Academy of Sciences of Ukrain; Ucrania Fil: Lazarova, Tanya. Pbl Netherlands Environmental Assessment Agency; Países Bajos Fil: Leadley, Paul. Université Paris Sud; Francia Fil: Lundquist, Carolyn J.. National Institute Of Water And Atmospheric Research; Nueva Zelanda. The University of Auckland; Nueva Zelanda Fil: García Márquez, Jaime. Humboldt-Universität zu Berlin; Alemania Fil: Meyer, Carsten. German Centre For Integrative Biodiversity Research; Alemania. University of Yale; Estados Unidos Fil: Navarro, Laetitia M.. German Centre For Integrative Biodiversity Research; Alemania. Martin-universitat Halle-wittenberg; Alemania Fil: Nesshöver, Carsten. Helmholtz Centre for Environmental Research; Alemania. German Centre for Integrative Biodiversity Research; Alemania Fil: Ngo, Hien T.. Ipbes Secretariat; Alemania Fil: Ninan, Karachepone N.. Centre For Economics, Environment And Society; India Fil: Palomo, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales “Bernardino Rivadavia”; Argentina Fil: Pereira, Laura M.. Stockholms Universitet; Suecia Fil: Peterson, Garry D.. Stockholms Universitet; Suecia Fil: Pichs, Ramon. Centre For World Economy Studies; Cuba Fil: Popp, Alexander. Potsdam Institute for Climate Impact Research; Alemania Fil: Purvis, Andy. Natural History Museum; Reino Unido Fil: Ravera, Federica. Consejo Superior de Investigaciones Científicas. Centre de Recerca Ecológica I Aplicacions Forestals; España. University Of Évora; Portugal. Universitat Central De Catalunya; España Fil: Rondinini, Carlo. Università degli studi di Roma "La Sapienza"; Italia Fil: Sathyapalan, Jyothis. Centre For Economic And Social Studies; India Fil: Schipper, Aafke M.. Pbl Netherlands Environmental Assessment Agency; Países Bajos Fil: Seppelt, Ralf. Coknow Consulting; Alemania. Martin Luther University Halle-Wittenberg; Alemania Fil: Settele, Josef. German Centre for Integrative Biodiversity Research; Alemania. Helmholtz Centre for Environmental Research; Alemania Fil: Sitas, Nadia. The Council For Scientific And Industrial Research; Sudáfrica Fil: Van Vuuren, Detlef. Pbl Netherlands Environmental Assessment Agency; Países Bajos

Made available in DSpace on 2018-12-11T16:45:00Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-12-01 Jaguar (Panthera onca) populations in the Upper Parana River, in the Brazilian Atlantic Forest region, live in a landscape that includes highly fragmented areas as well as relatively intact ones. We developed a model of jaguar habitat suitability in this region, and based on this habitat model, we developed a spatially structured metapopulation model of the jaguar populations in this area to analyze their viability, the potential impact of road mortality on the populations' persistence, and the interaction between road mortality and habitat fragmentation. In more highly fragmented populations, density of jaguars per unit area is lower and density of roads per jaguar is higher. The populations with the most fragmented habitat were predicted to have much lower persistence in the next 100 years when the model included no dispersal, indicating that the persistence of these populations are dependent to a large extent on dispersal from other populations. This, in turn, indicates that the interaction between road mortality and habitat fragmentation may lead to source-sink dynamics, whereby populations with highly fragmented habitat are maintained only by dispersal from populations with less fragmented habitat. This study demonstrates the utility of linking habitat and demographic models in assessing impacts on species living in fragmented landscapes. IPE-Instituto de Pesquisas Ecologicas Nazare Paulista Department of Ecology and Evolution Stony Brook University Programa de Posgraduacão em Ecologia e Biodiversidade Instituto de Biociências Universidade Estadual Paulista-UNESP Instituto para A Conservação Dos Carnivoros Neotropicais-Pro-Carnivoros Programa de Pos-graduação em Ecologia Departamento de Biologia Geral Universidade Federal de Viçosa-UFV Upper Midwest Environmental Sciences Center U.S. Geological Survey Programa de Posgraduacão em Ecologia e Biodiversidade Instituto de Biociências Universidade Estadual Paulista-UNESP

Summary 1. Linked demographic-bioclimatic models are emerging tools for forecasting climate change impacts on well-studied species, but these methods have been used in few management applications, and species interactions have not been incorporated. We combined population and bioclimatic envelope models to estimate future risks to the viability of a cockatoo population posed by climate change, increased fire frequency, beak-and-feather disease and reduced management. 2. The South Australian glossy black-cockatoo Calyptorhynchus lathami halmaturinus is restricted to Kangaroo Island, Australia, where it numbers 350 birds and is managed intensively. The cockatoo may be at particular risk from climate change because of its insular geographic constraints and specialised diet on a single plant species, Allocasuarina verticillata. The cockatoo population model was parameterised with mark-resight-derived estimates of survival and fecundity from 13 years of demographic data. Species interactions were incorporated by using a climate-change-driven bioclimatic model of Allocasuarina verticillata as a dynamic driver of habitat suitability. A novel application of Latin Hypercube sampling was used to assess the model’s sensitivity to input parameters. 3. Results suggest that unmitigated climate change is likely to be a substantial threat for the cockatoo: all high-CO2-concentration scenarios had expected minimum abundances of

Models that couple habitat suitability with demographic processes offer a potentially improved approach for estimating spatial distributional shifts and extinction risk under climate change. Applying such an approach to five species of Australian plants with contrasting demographic traits, we show that: (i) predicted climate-driven changes in range area are sensitive to the underlying habitat model, regardless of whether demographic traits and their interaction with habitat patch configuration are modeled explicitly; and (ii) caution should be exercised when using predicted changes in total habitat suitability or geographic extent to infer extinction risk, because the relationship between these metrics is often weak. Measures of extinction risk, which quantify threats to population persistence, are particularly sensitive to life-history traits, such as recruitment response to fire, which explained approximately 60% of the deviance in expected minimum abundance. Dispersal dynamics and habitat patch structure have the strongest influence on the amount of movement of the trailing and leading edge of the range margin, explaining roughly 40% of modeled structural deviance. These results underscore the need to consider direct measures of extinction risk (population declines and other measures of stochastic viability), as well as measures of change in habitat area, when assessing climate change impacts on biodiversity. Furthermore, direct estimation of extinction risk incorporates important demographic and ecosystem processes, which potentially influence species’ vulnerability to extinction due to climate change.

1.Methods used to predict shifts in species' ranges because of climate change commonly involve species distribution (niche) modelling using climatic variables, future values of which are predicted for the next several decades by general circulation models. However, species' distributions also depend on factors other than climate, such as land cover, land use and soil type. Changes in some of these factors, such as soil type, occur over geologic time and are thus imperceptible over the timescale of these types of projections. Other factors, such as land use and land cover, are expected to change over shorter timescales, but reliable projections are not available. Some important predictor variables, therefore, must be treated as unchanging, or static, whether because of the properties of the variable or out of necessity. The question of how best to combine dynamic variables predicted by climate models with static variables is not trivial and has been dealt with differently in studies to date. Alternative methods include using the static variables as masks, including them as independent explanatory variables in the model, or excluding them altogether. 2.Using a set of simulated species, we tested various methods for combining static variables with future climate scenarios. Our results showed that including static variables in the model with the dynamic variables performed better or no worse than either masking or excluding the static variables. 3.The difference in predictive ability was most pronounced when there is an interaction between the static and dynamic variables. 4.For variables such as land use, our results indicate that if such variables affect species distributions, including them in the model is better than excluding them, even though this may mean making the unrealistic assumption that the variable will not change in the future. 5.These results demonstrate the importance of including static and dynamic non-climate variables in addition to climate variables in species distribution models designed to predict future change in a species' habitat or distribution as a result of climate change. © 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society.

Sea-level rise (SLR) is a projected consequence of global climate change that will result in complex changes in coastal ecosystems. These changes will cause transitions among coastal habitat types, which will be compounded by human-made barriers to the gradual inland migration of these habitat types. The effect of these changes on the future viability of coastal species will depend on the habitat requirements and population dynamics of these species. Thus, realistic assessments of the impact of SLR require linking geomorphological models with habitat and population models. In this study, we implemented a framework that allows this linkage, and demonstrated its feasibility to assess the effect of SLR on the viability of the Snowy Plover population in Florida. The results indicate that SLR will cause a decline in suitable habitat and carrying capacity for this species, and an increase in the risk of its extinction and decline. The model projected that the population size will decline faster than the area of habitat or carrying capacity, demonstrating the necessity of incorporating population dynamics in assessing the impacts of SLR on coastal species. The results were most sensitive to uncertainties in survival rate and fecundity, and suggested that future studies on this species should focus on the average and variability of these demographic rates and their dependence on population density. The effect of SLR on this species’ viability was qualitatively similar with most alternative models that used the extreme values of each uncertain parameter, indicating that the results are robust to uncertainties in the model.

Summary 1. Where populations are confined to fragmented, human-dominated landscapes, preventing declines and extirpations will often rely on metapopulation management. Spatially-explicit population viability analyses provide tools to evaluate how well the local management efforts can be combined to conserve metapopulations across large areas. Yet, metapopulation models have rarely been combined with tools to assess the cost-effectiveness of different conservation strategies. 2. European bison Bison bonasus only occur in small, fragmented populations, making their long-term survival dependent on establishing a metapopulation across eastern Europe. We parameterized a European bison metapopulation model based on time-series of bison demography and a habitat suitability map to assess the viability of bison populations in the Carpathians and the relative cost-effectiveness of (i) reintroductions, (ii) wildlife overpasses and (iii) anti-poaching measures in establishing a viable bison metapopulation. 3. Our results suggest that the Carpathians could support a viable metapopulation of European bison provided that active efforts are taken to safeguard bison and connect isolated herds. With such steps, our model forecasts that bison numbers could increase substantially over the next 100 years as local populations increase and bison recolonize parts of the Carpathians. 4. Reintroductions appear to be the most cost-effective approach for establishing a viable bison metapopulation among our scenarios, especially when coupled with wildlife overpasses to improve connectivity among herds. The most promising region for a bison metapopulation in the Carpathians was south-eastern Poland, Ukraine and northern Romania. We identified several candidate regions for reintroductions and wildlife overpasses, especially in the border region of Romania and Ukraine. Site-specific assessments of both habitat suitability, and the costs and benefits of a large bison population, should target those regions. 5. Synthesis and applications. Our results highlight how careful conservation planning can identify solutions to preserve large mammals in human-dominated landscapes. Choosing the most effective option from a range of management strategies is a central challenge for wildlife managers. We have shown that incorporating cost-effectiveness analyses into metapopulation models can elucidate the relative value (gain per unit cost) of different conservation management options, allowing decision makers to choose cost-effective options to preserve large mammals. Our model projections also provide hope for establishing a viable free-ranging European bison population in the Carpathians, one of the last relatively wild areas in Europe.

Summary 1. The theta-logistic is a simple and flexible model for describing how the growth rate of a population slows as abundance increases. Starting at rm (taken as the maximum population growth rate), the growth response decreases in a convex or concave way (according to the shape parameter θ) to zero when the population reaches carrying capacity. 2. We demonstrate that fitting this model to census data is not robust and explain why. The parameters θ and rm are able to play-off against each other (providing a constant product), thus allowing both to adopt extreme and ecologically implausible values. 3. We use simulated data to examine: (i) a population fluctuating around a constant carrying capacity (K); (ii) recovery of a population from 10% of carrying capacity; and (iii) a population subject to variation in K. We show that estimates of extinction risk depending on this or similar models are therefore prone to imprecision. We refute the claim that concave growth responses are shown to dominate in nature. 4. As the model can also be sensitive to temporal variation in carrying capacity, we argue that the assumption of a constant carrying capacity is both problematic and presents a fruitful direction for the development of phenomenological density-feedback models.

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species was increasingly used during the 1980s to assess the conservation status of species for policy and planning purposes. This use stimulated the development of a new set of quantitative criteria for listing species in the categories of threat: critically endangered, endangered, and vulnerable. These criteria, which were intended to be applicable to all species except microorganisms, were part of a broader system for classifying threatened species and were fully implemented by IUCN in 2000. The system and the criteria have been widely used by conservation practitioners and scientists and now underpin one indicator being used to assess the Convention on Biological Diversity 2010 biodiversity target. We describe the process and the technical background to the IUCN Red List system. The criteria refer to fundamental biological processes underlying population decline and extinction. But given major differences between species, the threatening processes affecting them, and the paucity of knowledge relating to most species, the IUCN system had to be both broad and flexible to be applicable to the majority of described species. The system was designed to measure the symptoms of extinction risk, and uses 5 independent criteria relating to aspects of population loss and decline of range size. A species is assigned to a threat category if it meets the quantitative threshold for at least one criterion. The criteria and the accompanying rules and guidelines used by IUCN are intended to increase the consistency, transparency, and validity of its categorization system, but it necessitates some compromises that affect the applicability of the system and the species lists that result. In particular, choices were made over the assessment of uncertainty, poorly known species, depleted species, population decline, restricted ranges, and rarity; all of these affect the way red lists should be viewed and used. Processes related to priority setting and the development of national red lists need to take account of some assumptions in the formulation of the criteria.La Lista Roja de Especies Amenazadas de la UICN (Union Internacional para la Conservacion de la Naturaleza) fue muy utilizada durante la decada de l980 para evaluar el estatus de conservacion de especies para fines politicos y de planificacion. Este uso estimulo el desarrollo de un conjunto nuevo de criterios cuantitativos para enlistar especies en las categorias de amenaza: en peligro critico, en peligro y vulnerable. Estos criterios, que se pretendia fueran aplicables a todas las especies excepto microorganismos, eran parte de un sistema general para clasificar especies amenazadas y fueron implementadas completamente por la UICN en 2000. El sistema y los criterios han sido ampliamente utilizados por practicantes y cientificos de la conservacion y actualmente apuntalan un indicador utilizado para evaluar el objetivo al 2010 de la Convencion de Diversidad Biologica. Describimos el proceso y el respaldo tecnico del sistema de la Lista Roja de la IUCN. Los criterios se refieren a los procesos biologicos fundamentales que subyacen en la declinacion y extincion de una poblacion. Pero, debido a diferencias mayores entre especies, los procesos de amenaza que los afectan y la escasez de conocimiento sobre la mayoria de las especies, el sistema de la UICN tenia que ser amplio y flexible para ser aplicable a la mayoria de las especies descritas. El sistema fue disenado para medir los sintomas del riesgo de extincion, y utiiza cinco criterios independientes que relacionan aspectos de la perdida poblacional y la declinacion del rango de distribucion. Una especie es asignada a una categoria de amenaza si cumple el umbral cuantitativo por lo menos para un criterio. Los criterios, las reglas acompanantes y las directrices utilizadas por la UICN tienen la intencion de incrementar la consistencia, transparencia y validez de su sistema de clasificacion, pero requiere algunos compromisos que afectan la aplicabilidad del sistema y las listas de especies que resultan. En particular, se hicieron selecciones por encima de la evaluacion de incertidumbre, especies poco conocidas, especies disminuidas, declinacion poblacional, rangos restringidos y rareza; todas estas afectan la forma en que las listas rojas deberian ser vistas y usadas. Los procesos relacionados con la definicion de prioridades y el desarrollo de las listas rojas nacionales necesitan considerar algunos de los supuestos en la formulacion de los criterios.