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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.

In 2021, the International Union for Conservation of Nature (IUCN) introduced a novel method for assessing species recovery and conservation impact: the IUCN Green Status of Species. The Green Status standardizes recovery using a metric called the Green Score, which ranges from 0% to 100%. This study focuses on one crucial step in the Green Status method—the division of a species’ range into so-called “spatial units”—and evaluates whether different approaches for delineating spatial units affect the outcome of the assessment (i.e., the Green Score). We compared Green Scores generated using biologically based spatial units (the recommended method) to Green Scores generated using ecologically based or country-based spatial units for 29 species of birds and mammals in Europe. We found that while spatial units delineated using ecoregions and countries (fine-scale) produced greater average numbers of spatial units and significantly lower average Green Scores than biologically based spatial units, coarse-scale spatial units delineated using biomes and countries above a range proportion threshold did not differ significantly from biologically based results for average spatial unit number or average Green Score. However, case studies focusing on results for individual species (rather than a group average) showed that, depending on characteristics of the species’ distribution, even these coarse-scale delineations of ecological or country spatial units often over- or under-predict the Green Score compared to biologically based spatial units. We discuss cases in which the use of ecologically based or country-based spatial units is recommended or discouraged, in hopes that our results will strengthen the new Green Status framework and ensure consistency in application.

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.

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.

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】.

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.

Population viability analysis is widely used for assessing population-level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers to prioritize efforts for further data collection so that model improvements are efficient, and helps managers prioritize conservation and management actions. Usually sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then regression techniques allow measuring the importance of input parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions; effectively separating the two main questions that sensitivity analysis asks. We applied this method to Snowy Plover, assessing the effects of predicted sea-level rise. A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions. This article is protected by copyright. All rights reserved

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.

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.

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.

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.

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.

The world's governments have identified reducing the rate of biodiversity loss as a global priority. However, we lack robust measures of progress toward this target. Developing indicators that are generally representative of trends in global biodiversity has presented the scientific community with a significant challenge. Here we discuss the development and implementation of the IUCN Red List Index with a new sampled approach, permitting the assessment of the conservation status and trends of large, speciose taxonomic groups. This approach is based on the IUCN Red List and measures trends in extinction risk through time. The challenges in developing this new approach are addressed, including determining the species groups to be included in the index, identifying the minimum adequate samples size, and aggregating and weighting the index. Implementing this approach will greatly increase understanding of the status of the world's biodiversity by 2010, enabling the first assessment of a number of key groups.

Forest management shapes landscape patterns, and these patterns often differ significantly from those typical for natural disturbance regimes. This may affect wildlife habitat and other aspects of ecosystem function. Our objective was to examine the effects of different forest management decisions on landscape pattern in a fire adapted ecosystem. We used a factorial design experiment in LANDIS (a forest landscape simulation model) to test the effects of: (a) cut unit size, (b) minimum harvest age and (c) target species for management. Our study area was the Pine Barrens of northwest Wisconsin, an area where fire suppression has caused a lack of large open areas important for wildlife. Our results show that all three management choices under investigation (cut unit size, minimum harvest age and target species for management) have strong effects on forest composition and landscape patterns. Cut unit size is the most important factor influencing landscape pattern, followed by target species for management (either jack pine or red pine) and then minimum harvest age. Open areas are more abundant, and their average size is larger, when cut units are larger, target species is jack pine, and minimum harvest age is lower. Such information can assist forest managers to relate stand level management decision to landscape patterns. # 2006 Elsevier B.V. All rights reserved.

Scalar population models, commonly referred to as count-based models, are based on time-series data of population sizes and may be useful for screening-level ecological risk assessments when data for more complex models are not available. Appropriate use of such models for management purposes, however, requires understanding inherent biases that may exist in these models. Through a series of simulations, which compared predictions of risk of decline of scalar and matrix-based models, we examined whether discrepancies may arise from different dynamics displayed due to age structure and generation time. We also examined scalar and matrix-based population models of 18 real populations for potential patterns of bias in population viability estimates. In the simulation study, precautionary bias (i.e., overestimating risks of decline) of scalar models increased as a function of generation time. Models of real populations showed poor fit between scalar and matrix-based models, with scalar models predicting significantly higher risks of decline on average. The strength of this bias was not correlated with generation time, suggesting that additional sources of bias may be masking this relationship. Scalar models can be useful for screening-level assessments, which should in general be precautionary, but the potential shortfalls of these models should be considered before using them as a basis for management decisions.

The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse ( Tympanuchus phasianellus) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.

The conservation of ecosystems focuses on evaluating individual sites or landscapes based on their component species. To produce a map of conservation values, we developed a method to weight habitat-suitability maps for individual species by species-specific extinction risks. The value of a particular site reflects the importance and magnitude of the threats facing the component species of the ecological community. We applied this approach to a set of species from the California Gap Analysis Project. The resulting map of multispecies conservation values identified the areas with the best habitat for the species most vulnerable to extinction. These methods are flexible and can accommodate the quantity and quality of data available for each individual species in both the development of the habitat-suitability maps and the estimation of the extinction risks. Additionally, the multispecies conservation value can accommodate specific conservation goals, such as preservation of local endemics, making it useful for prioritizing conservation and management actions. This approach provides an estimate of the ecological worth of a site based on habitat characteristics and quantitative models in terms of all the ecological components of a site, rather than a single threatened or endangered species. Resumen: La conservacion de los ecosistemas se enfoca en la evaluacion de sitios individuales o paisajes en base a las especies que lo componen. Para producir un mapa de valores para la conservacion, desarrollamos un metodo que valora mapas de aptitud del habitat para especies a nivel individual en base a los riesgos de extincion especie-especificos. El valor de un sitio en particular refleja la importancia y la magnitud de las amenazas que enfrentan las especies que componen la comunidad ecologica. Aplicamos esta metodologia a un grupo de especies del Proyecto de Analisis de Aberturas de California. El mapa de valores de conservacion para multiples especies resultante identifico las areas con el mejor habitat para las especies mas vulnerables a la extincion. Estos metodos son flexibles y pueden abarcar la cantidad y calidad de los datos disponibles para cada especie individual tanto para el desarrollo de mapas de aptitud del habitat, como para la eliminacion de los riesgos de extincion. Ademas, los valores de conservacion multi-especie pueden abarcar metas especificas de conservacion, como lo es la preservacion de endemias locales, haciendolos utiles para priorizar las acciones de conservacion y manejo. Esta metodologia provee una estimacion del merito ecologico de un sitio en base a las caracteristicas y modelos cuantitativos en terminos de todos los componentes ecologicos de un sitio, y no en una sola especie amenazada o en peligro.

Estimating the risk of extinction or decline requires estimates of the variability in vital rates, such as survival and fecundity. This paper describes a method for estimating variance of survivals and fecundities from census data. The method involves calculating an estimate of the variance in survival and fecundity due to demographic stochasticity and subtracting this estimate from an estimate of total variance. The method is demonstrated by applying it to the data set on acorn woodpeckers by Stacey & Taper (1992), and tested in a series of simulations. The results show that the method can estimate the environmental variance with no bias. The main advantages of this method are its simplicity, its independence of the underlying distribution, and its applicability to estimating the variance of fecundity as well as of survival.

The World Conservation Union (IUCN) defined a set of categories for conservation status supported by decision rules based on thresholds of parameters such as distributional range, population size, population history, and risk of extinction. These rules have received international acceptance and have become one of the most important decision tools in conservation biology because of their wide applicability, objectivity, and simplicity of use. The input data for these rules are often estimated with considerable uncertainty due to measurement error, natural variation, and vagueness in definitions of parameters used in the rules. Currently, no specific guidelines exist for dealing with uncertainty. Interpretation of uncertain data by different assessors may lead to inconsistent classifications because attitudes toward uncertainty and risk may have an important influence on the classification of threatened species. We propose a method of dealing with uncertainty that can be applied to the current IUCN criteria without altering the rules, thresholds, or intent of these criteria. Our method propagates the uncertainty in the input parameters and assigns the evaluated species either to a single category (as the current criteria do) or to a range of plausible categories, depending on the nature and extent of uncertainties. Resumen: La Union Mundial para la Conservacion (IUCN) definio un grupo de categorias referentes a estados de conservacion sustentadas en reglas de decision basadas en umbrales de parametros como son el rango de distribucion, el tamano poblacional, la historia poblacional y el riesgo de extincion. Estas reglas han recibido aceptacion internacional y se han convertido en una de las herramientas mas importantes para la toma de decisiones en biologia de la conservacion debido a su amplia aplicabilidad, objetividad y simplicidad de uso. Los datos requeridos para estas reglas son frecuentemente estimados con una incertidumbre considerable debido a errores de medicion, variacion natural y vaguedad en la definicion de los parametros usados en las reglas. Actualmente no existen lineamientos especificos para enfrentar la incertidumbre. La interpretacion de datos inciertos por diferentes estimadores puede conducir a clasificaciones inconsistentes debido a que ciertas actitudes hacia la incertidumbre y el riesgo pueden tener una influencia importante en la clasificacion de especies amenazadas. Proponemos un metodo para enfrentar a la incertidumbre que puede ser aplicado a los criterios actuales de IUCN sin alterar las reglas, los umbrales, o la intencion de estos criterios. Nuestro metodo propaga la incertidumbre en los parametros usados y asigna a la especie evaluada a una sola categoria (a como lo hace el criterio actual) o a un rango de categorias plausibles, dependiendo de la naturaleza y la extension de las incertidumbres.

The classification of species with respect to their conservation status using the IUCN criteria is an important process in many countries, providing a guide for setting conservation priorities. Recent advances have resulted in several approaches to dealing with uncertainty in data used to classify species. These methods demand an unambiguous and transparent logical structure for the criteria. We suggest some changes to the ways in which the criteria are represented that correct an unnecessary inconsistency and which may serve to avoid important errors when uncertainty in the data is considered explicitly.

A stage-based model was developed for the population dynamics of Banksia goodii , a rare long-lived shrub in Western Australia. While few seeds are produced, death of adults due to senescence or fire has yet to be observed. A sensitivity analysis showed that population growth is close to zero as long as post-fire mortality and recruitment are within their usual low bounds. To remain viable, the size of a population remnant should exceed about 80 individuals. If fires occur at random intervals, an average of one fire in 10–15 years is optimal. Regular fires should have inter-fire periods of 15–20 years. Loss of adult plants due to human activities, such as land clearing, will increase mortality beyond its natural bounds and cannot be compensated for, due to the low fecundity of this species. Hand sowing after a fire may raise establishment by orders of magnitude and achieve a permanent population increase within the first year. Conservation authorities should target the sensitive factors through active management at the recruitment stage and by ensuring that no further loss of mature plants takes place through land clearance. ©

Summary We demonstrate the effect of uncertainty (resulting from lack of information or measurement error) on the assessment of human impact, with an analysis of the viability of the Northern Spotted Owl throughout its range in the United States. We developed a spatially-explicit, stage-structured, stochastic metapopulation model of the Northern Spotted Owl throughout its range in the United States. We evaluated the viability of the metapopulation using measures such as risk of decline and time to extinction. We incorporated uncertainty in the form of parameter ranges, and used them to estimate upper and lower bounds on the estimated viability of the species. We analyzed the effect of this type of uncertainty on the assessment of human impact by comparing the species’ viability under current conditions, and under an assumed loss of spotted owl habitat in the next 100 years. The ranges of parameters were quite large, and resulted in wide range of risks of extinction. Despite this uncertainty, the results were sensitive to parameters related to habitat loss: under all assumptions and combinations of parameters, the model predicted that habitat loss results in substantially higher risks of metapopulation decline. This result demonstrated that even with relatively large uncertainties, risk-based model results can be used to reliably assess human impact.

STUART H. M. BUTCHART,∗ H. RESIT AKCAKAYA,‡ ELIZABETH KENNEDY,§ AND CRAIG HILTON-TAYLOR∗∗ ∗BirdLife International, Wellbrook Court, Girton Road, Cambridge, CB3 0NA, United Kingdom, email stuart.butchart@birdlife.org ‡Applied Biomathematics, 100 North Country Road, Setauket, New York 11733, U.S.A. §Conservation International, 1919 M Street, NW Street 600, Washington, D.C. 20036, U.S.A. ∗∗IUCN Species Programme Office, 219c Huntingdon Road, Cambridge, CB3 0DL, United Kingdom

We present an analysis of the metapopulation dynamics of the federally threatened coastal Califor- nia Gnatcatcher ( Polioptila c. californica ) for an approximately 850 km 2 region of Orange County, California. We developed and validated a habitat suitability model for this species using data on topography, vegetation, and locations of gnatcatcher pair observations. Using this habitat model, we calculated the spatial structure of the metapopulation, including size and location of habitat patches and the distances among them. We used data based on field studies to estimate parameters such as survival, fecundity, dispersal, and catastrophes, and combined these parameters with the spatial structure to build a stage-structured, stochastic, spatially- explicit metapopulation model. The model predicted a fast decline and high risk of population extinction with most combinations of parameters. Results were most sensitive to density-dependent effects, the probability of weather-related catastrophes, adult survival, and adult fecundity. Based on data used in the model, the great- est difference in results was given when the simulation's time horizon was only a few decades, suggesting that modeling based on longer or shorter time horizons may underestimate the effects of alternative management actions.

Habitats used by most species are becoming increasingly fragmented, requiring a metapopulation modelling approach to population viability analysis (PVA). Recognising habitat patchiness from an endangered species' point of view requires utilisation of spatial information on habitat suitability. Both of these requirements may be met by linking metapopulation modelling with landscape data using GIS technology. We present a PVA model that links spatial data directly to a metapopulation model for extinction risk assessment, viability analysis, reserve design and wildlife management. The use of the model is demonstrated by an application to the spatial dynamics of the helmeted honeyeater Lichenostomus melanops cassidix, an endangered bird species endemic to Victoria, Australia. We use spatial data, organised by a GIS, on the habitat requirements of the helmeted honeyeater to define the patch structure. We then combine this patch structure with demographic data to build a metapopulation model, and use the model to analyse the effectiveness of translocations as a conservation strategy for the helmeted honeyeater.

The probability of extinction is sensitive to the presence and character of density dependence controlling the dynamics of a population. This means that our capacity to estimate a population's risks of extinction under varying environmental conditions or competing management re- gimes is linked to our ability to reconstruct from data the density-dependence relationships governing the natural dy- namics, especially when data do not reveal a trend of pop- ulation growth or decline. In an example using Gadus morhua, we show that even 10- or 20-year data sets are too short to make precise estimates of these risks. We also ob- serve, however, that under moderate or weak density depen- dence, the computed risks are lower than when density de- pendence is not included in the model. We propose, therefore, that when available data sets are insufficient for recon- structing reliable measurements of density dependence, con- servative estimates of extinction probabilities can be made from models that simply omit density dependence. Resumen: La probabilidad de extinci6n es sensible a la presencia y al cardcter de la dependencia de densidad que controla la dinamica de una poblaci6n. Esto significa que nuestra capacidad para estimar los riesgos de extinci6n de una poblacion bajo condiciones ambientales cambiantes, o diferentes regimenes de manejo, esta relacionada a nuestra capacidad de reconstruir, en base a datos, las relaciones de dependencia de densidad que gobiernan la dinamica natu- ral de poblaciones, especialmente cuando no se dispone de informaci6n que revele tendencias de crecimiento o decli- naci6n de poblaciones. En un ejemplo, utilizando Gadus morhua, demostramos que aun los datos sobre un periodo de 10 6 20 anios son insuficientes para hacer estimaciones pre- cisas sobre estos riesgos. Sin embargo, observamos que in- cluso en una situaci6n de dependencia de densidad mo- derada o debil, los riesgos calculados son mas bajos que cuando la dependencia de densidad no es incluida en el modelo. Por ello proponemos, que, cuando no se dispone de datos suficientes para reconstruir estimados confiables de dependencia de densidad, se pueden hacer estimaciones con- servadoras de probabilidades de extinci6n a partir de mo- delos que simplemente omiten los aspectos de dependencia de densidad.

This paper reports on captive and wild populations of the bald ibis Geronticus eremita in Birecik, Turkey. Captive breeding and reintroduction, aimed at increasing the wild population, are evaluated. Low breeding success in captivity, failure of reintroduced birds to join the wild population in migration, and losses during migration and in the winter appear as major factors preventing an increase in this population. Probable causes of these three factors are discussed.

*Key Centre for Tropical Wildlife Management, Northern Territory University, Darwin, Northern Territory 0909, Australia†School of Botany, University of Melbourne, Parkville, Victoria 3052, Australia‡Applied Biomathematics, 100 North Country Road, Setauket, NY 11733, U.S.A.§Key Centre for Biodiversity and Bioresources, Macquarie University, New South Wales 2109, Australia

The California least tern (Sterna antillarum browni) is federally listed as an endangered species. Its nesting habitat has been degraded, and many colony sites are vulnerable to predation and human disturbance. We examined a metapopulation model for the California least tern that can be used to predict persistence of populations along the Pacific coast and the effects of various management actions. We used the model to estimate the effect of reducing predation impact, an important source of reduced fecundity, in various populations. Apart from restricting human access to nesting sites, most management efforts have concentrated on predation. In the model, each cluster of nearby colonies is defined as a population. Within each population, the model includes age-structure, year-to-year changes in survival and fecundity, regional catastrophes (strong El Nino/Southern Oscillation [ENSO] events), and local catastrophes (reproductive failure due to predation). The model predicted a continuing population increase and a low risk of substantial decline over the next 50 years. However, this prediction was sensitive to assumptions about survival and fecundity. Under a pessimistic scenario, the model predicted a high risk of decline, although a low risk of extinction. We simulated the effect of predator management by reducing the probability of reproductive failure due to predation. The improvement in viability ranged from 1% to 4% for single populations and up to 8% when all populations were included. Results indicated that the number and location of populations selected for focused management influenced the effectiveness of management efforts.

The implications of the use of models from three fields in biology, namely, island biogeography, population genetics, and population dynamics, for the management of wildlife populations and the conservation of species are reviewed. The theory of island biogeography has little to offer to conservation practice because the formulation of the model is questionable, empirical evidence does not support it, and the predictions of the theory do not address directly the central problem of species extinctions. Unlike island biogeography, models in population genetics and population dynamics utilise population-specific information and provide answers to problems in terms of extinction probabilities and the change in population parameters in response to changes in specific environmental conditions.

Population trends play a large role in species risk assessments and conservation planning, and species are often considered threatened if their recent rate of decline meets certain thresholds, regardless how large the population is. But how reliable an indicator of extinction risk is a single estimate of population trend? Given the integral role this decline-based approach has played in setting conservation priorities, it is surprising that it has undergone little empirical scrutiny. We compile an extensive global dataset of time series of abundance data for over 1300 vertebrate populations to provide the first major test of the predictability of population growth rates in nature. We divided each time series into assessment and response periods and examined the correlation between growth rates in the two time periods. In birds, population declines tended to be followed by further declines, but mammals, salmon, and other bony fishes showed the opposite pattern: past declines were associated with subsequent population increases, and vice versa. Furthermore, in these taxa subsequent growth rates were higher when initial declines were more severe. These patterns agreed with data simulated under a null model for a dynamically stable population experiencing density dependence. However, this type of result could also occur if conservation actions positively affected the population following initial declines—a scenario that our data were too limited to rigorously evaluate. This ambiguity emphasizes the importance of understanding the underlying causes of population trajectories in drawing inferences about rates of decline in abundance.