Harnessing online digital data in biodiversity monitoring.

Online digital data from media platforms have the potential to complement biodiversity monitoring efforts. We propose a strategy for integrating these data into current biodiversity datasets in light of the Kunming-Montreal Global Biodiversity Framework.

Global conservation of species' niches.

Environmental change is rapidly accelerating, and many species will need to adapt to survive1. Ensuring that protected areas cover populations across a broad range of environmental conditions could safeguard the processes that lead to such adaptations1-3. However, international conservation policies have largely neglected these considerations when setting targets for the expansion of protected areas4. Here we show that-of 19,937 vertebrate species globally5-8-the representation of environmental conditions across their habitats in protected areas (hereafter, niche representation) is inadequate for 4,836 (93.1%) amphibian, 8,653 (89.5%) bird and 4,608 (90.9%) terrestrial mammal species. Expanding existing protected areas to cover these gaps would encompass 33.8% of the total land surface-exceeding the current target of 17% that has been adopted by governments. Priority locations for expanding the system of protected areas to improve niche representation occur in global biodiversity hotspots9, including Colombia, Papua New Guinea, South Africa and southwest China, as well as across most of the major land masses of the Earth. Conversely, we also show that planning for the expansion of protected areas without explicitly considering environmental conditions would marginally reduce the land area required to 30.7%, but that this would lead to inadequate niche representation for 7,798 (39.1%) species. As the governments of the world prepare to renegotiate global conservation targets, policymakers have the opportunity to help to maintain the adaptive potential of species by considering niche representation within protected areas1,2.

Global priority areas for ecosystem restoration.

Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity1 and stabilizing the climate of the Earth2. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2-30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.

Bending the curve of terrestrial biodiversity needs an integrated strategy.

Increased efforts are required to prevent further losses to terrestrial biodiversity and the ecosystem services that it  provides1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity3; however, just feeding the growing human population will make this a challenge4. Here we use an ensemble of land-use and biodiversity models to assess whether-and how-humanity can reverse the declines in terrestrial biodiversity caused by habitat conversion, which is a major threat to biodiversity5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, could enable the provision of food for the growing human population while reversing the global terrestrial biodiversity trends caused by habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land and generalize landscape-level conservation planning, biodiversity trends from habitat conversion could become positive by the mid-twenty-first century on average across models (confidence interval, 2042-2061), but this was not the case for all models. Food prices could increase and, on average across models, almost half (confidence interval, 34-50%) of the future biodiversity losses could not be avoided. However, additionally tackling the drivers of land-use change could avoid conflict with affordable food provision and reduces the environmental effects of the food-provision system. Through further sustainable intensification and trade, reduced food waste and more plant-based human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all of the models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats-such as climate change-must be addressed to truly reverse the declines in biodiversity, our results show that ambitious conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy.

Modelling the probability of meeting IUCN Red List criteria to support reassessments.

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

Global inequities and political borders challenge nature conservation under climate change.

Underlying sociopolitical factors have emerged as important determinants of wildlife population trends and the effectiveness of conservation action. Despite mounting research into the impacts of climate change on nature, there has been little consideration of the human context in which these impacts occur, particularly at the global scale. We investigate this in two ways. First, by modeling the climatic niches of terrestrial mammals and birds globally, we show that projected species loss under climate change is greatest in countries with weaker governance and lower Gross Domestic Product, with loss of mammal species projected to be greater in countries with lower CO2 emissions. Therefore, climate change impacts on species may be disproportionately significant in countries with lower capacity for effective conservation and lower greenhouse gas emissions, raising important questions of international justice. Second, we consider the redistribution of species in the context of political boundaries since the global importance of transboundary conservation under climate change is poorly understood. Under a high-emissions scenario, we find that 35% of mammals and 29% of birds are projected to have over half of their 2070 climatic niche in countries in which they are not currently found. We map these transboundary range shifts globally, identifying borders across which international coordination might most benefit conservation and where physical border barriers, such as walls and fences, may be an overlooked obstacle to climate adaptation. Our work highlights the importance of sociopolitical context and the utility of a supranational perspective for 21st century nature conservation.

Connectivity between countries established by landbirds and raptors migrating along the African-Eurasian flyway.

The conservation of long-distance migratory birds requires coordination between the multiple countries connected by the movements of these species. The recent expansion of tracking studies is shedding new light on these movements, but much of this information is fragmented and inaccessible to conservation practitioners and policy makers. We synthesized current knowledge on the connectivity established between countries by landbirds and raptors migrating along the African-Eurasian flyway. We reviewed tracking studies to compile migration records for 1229 individual birds, from which we derived 544 migratory links, each link corresponding to a species' connection between a breeding country in Europe and a nonbreeding country in sub-Saharan Africa. We used these migratory links to analyze trends in knowledge over time and spatial patterns of connectivity per country (across species), per species (across countries), and at the flyway scale (across all countries and all species). The number of tracking studies available increased steadily since 2010 (particularly for landbirds), but the coverage of existing tracking data was highly incomplete. An average of 7.5% of migratory landbird species and 14.6% of raptor species were tracked per country. More data existed from central and western European countries, and it was biased toward larger bodied species. We provide species- and country-level syntheses of the migratory links we identified from the reviewed studies, involving 123 populations of 43 species, migrating between 28 European and 43 African countries. Several countries (e.g., Spain, Poland, Ethiopia, Democratic Republic of Congo) are strategic priorities for future tracking studies to complement existing data, particularly on landbirds. Despite the limitations in existing tracking data, our data and results can inform discussions under 2 key policy instruments at the flyway scale: the African-Eurasian Migratory Landbirds Action Plan and the Memorandum of Understanding on the Conservation of Migratory Birds of Prey in Africa and Eurasia.

Conectividad entre países establecida por aves terrestres y rapaces que migran a través del corredor aéreo africano-euroasiático Resumen La conservación de las aves que migran grandes distancias requiere de una coordinación entre los varios países conectados por los movimientos de estas especies. La expansión reciente de los estudios de rastreo está descubriendo novedades en estos movimientos, aunque gran parte de esta información está fragmentada y es inaccesible para quienes practican y elaboran las políticas de conservación. Sintetizamos el conocimiento actual sobre la conectividad establecida entre países por las aves terrestres y rapaces que migran a través del corredor aéreo africano-euroasiático. Revisamos los estudios de rastreo para compilar los registros migratorios de 1229 aves, de los cuales derivamos 544 conexiones migratorias, con cada conexión correspondiendo a la conexión que tiene una especie entre un país europeo en donde se reproduce con un país de la África subsahariana en donde no se reproduce. Usamos estas conexiones migratorias para analizar las tendencias informativas en patrones espaciales y temporales de conectividad por país (en todas las especies), por especie (en todos los países) y a escala del corredor aéreo (en todas las especies y en todos los países). El número de estudios de rastreo disponibles incrementó gradualmente a partir de 2010 (particularmente para las aves terrestres), pero la cobertura de los datos de rastreo existentes estaba incompleta. Se rastreó en promedio 7.5% de especies de aves terrestres migratorias y 14.6% de aves rapaces por país. Existían más datos de los países del centro y oeste de Europa, los cuales estaban sesgados hacia las especies de mayor tamaño. Proporcionamos varias síntesis a nivel de especie y país de las conexiones migratorias que identificamos a partir de la revisión de estudios, las cuales involucran a 123 poblaciones de 43 especies que migran entre 28 países europeos y 43 países africanos. Varios países, como España, Polonia, Etiopía y la República Democrática del Congo son prioridades estratégicas para complementar los datos existentes en los siguientes estudios de rastreo, en especial para las aves terrestres. A pesar de las limitaciones que tienen los datos de rastreo existentes, nuestros datos y resultados pueden orientar las discusiones con dos instrumentos claves para las políticas: el Plan de Acción de las Aves Terrestres Migratorias Africanas-Euroasiáticas y el Memorando de Entendimiento sobre la Conservación de las Aves Rapaces Migratorias de África y Eurasia.

Rates of tree cover loss in Key Biodiversity Areas on Indigenous Peoples' lands.

Indigenous Peoples' lands (IPL) cover at least 38 million km2 (28.1%) of Earth's terrestrial surface. These lands can be important for biodiversity conservation. Around 20.7% of IPL intersect areas protected by government (PAs). Many sites of importance for biodiversity within IPL could make a substantial but hitherto unquantified contribution to global site-based conservation targets. Key Biodiversity Areas (KBAs) represent the largest global network of systematically identified sites of high importance for biodiversity. We assessed the effectiveness of IPL in slowing biodiversity loss inside and outside PAs by quantifying tree cover loss from 2000 to 2019 in KBAs at international and national levels and comparing it with losses at equivalent sites outside mapped IPL. Based on a matched sample of 1-km2 cells in KBAs inside and outside mapped IPL, tree cover loss in KBAs outside PAs was lower inside IPL than outside IPL. By contrast, tree cover loss in KBAs inside PAs was lower outside IPL than inside IPL (although the difference was far smaller). National rates of tree cover loss in KBAs varied greatly in relation to their IPL and PA status. In one half of the 44 countries we examined individually, there was no significant difference in the rate of tree cover loss in KBAs inside and outside mapped IPL. The reasons for this intercountry variation could illuminate the importance of IPL in meeting the Convention on Biological Diversity's ambition of conserving 30% of land by 2030. Critical to this will be coordinated action by governments to strengthen and enforce Indigenous Peoples' rights, secure their collective systems of tenure and governance, and recognize their aspirations for their lands and futures.

Tasas de pérdida de la cobertura arbórea en áreas clave de biodiversidad en suelo indígena Resumen Las tierras de los pueblos indígenas (TPI) cubren al menos 38 millones de km2 (28.1%) de la superficie del planeta. Estas tierras pueden ser importantes para la conservación de la biodiversidad. Un 20.7% de las TPI se intersecan con áreas protegidas (AP) por el gobierno. Muchos sitos con importancia para la biodiversidad dentro de las TPI podrían contribuir de forma sustancial, pero todavía sin cuantificar, a los objetivos globales de conservación in situ. Las áreas clave para la biodiversidad (ACB) representan la mayor red mundial de sitios con identificación sistemática de gran valor para la biodiversidad. Evaluamos la efectividad de las TPI en la reducción de la pérdida de la biodiversidad dentro y fuera de las AP mediante la cuantificación de la pérdida de la cobertura arbórea entre el 2000 y 2019 en las ACB a niveles nacional e internacional. También comparamos esta efectividad con las pérdidas en sitios equivalentes fuera de las TPI mapeadas. Con base en una muestra emparejada de celdas de 1-km2 en ACB dentro y fuera de las TPI mapeadas, la pérdida de la cobertura arbórea en las ACB ubicadas fuera de las AP fue menor dentro de las TPI que fuera de ellas. Al contrario, la pérdida en las ACB ubicadas dentro de las AP fue menor afuera de las TPI que adentro de ellas (aunque la diferencia fue por mucho menor). Las tasas nacionales de pérdida de la cobertura arbórea en las ACB variaron sobremanera en relación con su estado en las TPI y en las AP. En la mitad de los 44 países que analizamos individualmente no hubo una diferencia significativa en la tasa de pérdida de la cobertura arbórea en las ACB dentro y fuera de las TPI mapeadas. Las razones detrás de esta variación entre los países podrían aclarar la importancia que tienen las TPI para cumplir con la meta del Convenio sobre Diversidad Biológica de conservar el 30% del suelo para el 2030. La acción coordenada de los gobiernos será crítica para fortalecer y hacer cumplir los derechos de los pueblos indígenas, asegurar su sistema colectivo de tenencia y gobierno, y reconocer sus objetivos para sus tierras y el futuro.

Introducing a common taxonomy to support learning from failure in conservation.

Although some sectors have made significant progress in learning from failure, there is currently limited consensus on how a similar transition could best be achieved in conservation and what is required to facilitate this. One of the key enabling conditions for other sectors is a widely accepted and standardized classification system for identifying and analyzing root causes of failure. We devised a comprehensive taxonomy of root causes of failure affecting conservation projects. To develop this, we solicited examples of real-life conservation efforts that were deemed to have failed in some way, identified their underlying root causes of failure, and used these to develop a generic, 3-tier taxonomy of the ways in which projects fail, at the top of which are 6 overarching cause categories that are further divided into midlevel cause categories and specific root causes. We tested the taxonomy by asking conservation practitioners to use it to classify the causes of failure for conservation efforts they had been involved in. No significant gaps or redundancies were identified during this testing phase. We then analyzed the frequency that particular root causes were encountered by projects within this test sample, which suggested that some root causes were more likely to be encountered than others and that a small number of root causes were more likely to be encountered by projects implementing particular types of conservation action. Our taxonomy could be used to improve identification, analysis, and subsequent learning from failed conservation efforts, address some of the barriers that currently limit the ability of conservation practitioners to learn from failure, and contribute to establishing an effective culture of learning from failure within conservation.

Introducción de una taxonomía común como apoyo al aprendizaje a partir del fracaso en la conservación Resumen Mientras que algunos sectores han progresado significativamente en el aprendizaje a partir del fracaso, actualmente hay un consenso limitado sobre cómo podría lograrse una transición similar en la conservación y qué se requiere para facilitarla. Una de las condiciones habilitantes más importantes en otros sectores es un sistema de clasificación estandarizado y aceptado por la mayoría para la identificación y análisis de las causas fundamentales del fracaso. Diseñamos una taxonomía completa de las causas fundamentales del fracaso que afecta a los proyectos de conservación. Para desarrollarla, solicitamos ejemplos de esfuerzos de conservación reales que de alguna manera se consideraron como fracasos, identificamos las causas fundamentales no aparentes de su fracaso y luego las usamos para desarrollar una taxonomía genérica de tres niveles de las maneras en las que fracasan los proyectos, en cuyo nivel superior están seis categorías de causas generales que después se dividen en categorías de nivel medio de categorías de causas y causas fundamentales específicas. Pusimos a prueba la taxonomía al pedirle a los practicantes de la conservación que la usaran para clasificar las causas del fracaso de los esfuerzos de conservación en los que han participado. No identificamos vacíos o redundancias importantes durante esta fase de prueba. Después, analizamos la frecuencia con la que los proyectos de esta muestra se enfrentaron a causas fundamentales particulares, lo que sugirió que algunas causas fundamentales tienen mayor probabilidad de ocurrir y que un número reducido de causas fundamentales tiene mayor probabilidad de ocurrir en proyectos que implementan ciertos tipos de acciones de conservación. Nuestra taxonomía podría usarse para mejorar el análisis, identificación y aprendizaje subsecuente a partir del fracaso de los esfuerzos de conservación; tratar algunas de las barreras que en la actualidad limitan a los practicantes de la conservación a aprender del fracaso; y contribuir al establecimiento de una cultura efectiva del aprendizaje a partir del fracaso dentro de la conservación.

Prioritizing the reassessment of data-deficient species on the IUCN Red List.

Despite being central to the implementation of conservation policies, the usefulness of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species is hampered by the 14% of species classified as data-deficient (DD) because information to evaluate these species' extinction risk was lacking when they were last assessed or because assessors did not appropriately account for uncertainty. Robust methods are needed to identify which DD species are more likely to be reclassified in one of the data-sufficient IUCN Red List categories. We devised a reproducible method to help red-list assessors prioritize reassessment of DD species and tested it with 6887 DD species of mammals, reptiles, amphibians, fishes, and Odonata (dragonflies and damselflies). For each DD species in these groups, we calculated its probability of being classified in a data-sufficient category if reassessed today from covariates measuring available knowledge (e.g., number of occurrence records or published articles available), knowledge proxies (e.g., remoteness of the range), and species characteristics (e.g., nocturnality); calculated change in such probability since last assessment from the increase in available knowledge (e.g., new occurrence records); and determined whether the species might qualify as threatened based on recent rate of habitat loss determined from global land-cover maps. We identified 1907 species with a probability of being reassessed in a data-sufficient category of >0.5; 624 species for which this probability increased by >0.25 since last assessment; and 77 species that could be reassessed as near threatened or threatened based on habitat loss. Combining these 3 elements, our results provided a list of species likely to be data-sufficient such that the comprehensiveness and representativeness of the IUCN Red List can be improved.

Priorización de la reevaluación de las especies con datos deficientes en la Lista Roja de la UICN Resumen No obstante que es fundamental para la implementación de políticas de conservación, la utilidad de la Lista Roja de Especies Amenazadas de la Unión Internacional para la Conservación de la Naturaleza (UICN) está limitada por el 14% de especies clasificadas con datos deficientes (DD) debido a que la información para evaluar el riesgo de extinción de estas especies no existía cuando fueron evaluadas la última vez o porque los evaluadores no consideraron la incertidumbre apropiadamente. Se requieren métodos robustos para identificar las especies DD con mayor probabilidad de ser reclasificadas en alguna de las categorías en la Lista Roja UICN con datos suficientes. Diseñamos un método reproducible para ayudar a que los evaluadores de la lista roja prioricen la reevaluación de especies DD y lo probamos con 6,887 especies DD de mamíferos, reptiles, anfibios, peces y Odonata (libélulas y caballitos del diablo). Para cada una de las especies DD en estos grupos, calculamos la probabilidad de ser clasificadas en una categoría con datos suficientes si fuera reevaluada hoy a partir de covariables que miden el conocimiento disponible (e.g., número de registros de ocurrencia o artículos publicados disponibles), sustitutos de conocimiento (e.g., extensión del rango de distribución) y características de la especie ((e.g., nocturnidad); calculamos el cambio en tal probabilidad desde la última reevaluación a partir del incremento en el conocimiento disponible (e.g., registros de ocurrencia nuevos); y determinamos si las especies podrían calificar como amenazadas con base en pérdidas de hábitat recientes a partir de mapas globales de cobertura de suelo recientes. Identificamos 1,907 especies con una probabilidad >0.5 de ser reclasificados en una categoría con datos suficientes; 624 especies cuya probabilidad aumentó en >0.25 desde la última evaluación, y 77 especies que podrían ser reclasificadas como casi en peligro con base en la pérdida de hábitat. Combinando estos 3 elementos, nuestros resultados proporcionaron una lista de especies probablemente con datos suficientes de tal modo que la exhaustividad y la representatividad de la Lista Roja de la UICN pueden ser mejoradas.

Global forest loss disproportionately erodes biodiversity in intact landscapes.

Global biodiversity loss is a critical environmental crisis, yet the lack of spatial data on biodiversity threats has hindered conservation strategies. Theory predicts that abrupt biodiversity declines are most likely to occur when habitat availability is reduced to very low levels in the landscape (10-30%). Alternatively, recent evidence indicates that biodiversity is best conserved by minimizing human intrusion into intact and relatively unfragmented landscapes. Here we use recently available forest loss data to test deforestation effects on International Union for Conservation of Nature Red List categories of extinction risk for 19,432 vertebrate species worldwide. As expected, deforestation substantially increased the odds of a species being listed as threatened, undergoing recent upgrading to a higher threat category and exhibiting declining populations. More importantly, we show that these risks were disproportionately high in relatively intact landscapes; even minimal deforestation has had severe consequences for vertebrate biodiversity. We found little support for the alternative hypothesis that forest loss is most detrimental in already fragmented landscapes. Spatial analysis revealed high-risk hot spots in Borneo, the central Amazon and the Congo Basin. In these regions, our model predicts that 121-219 species will become threatened under current rates of forest loss over the next 30 years. Given that only 17.9% of these high-risk areas are formally protected and only 8.9% have strict protection, new large-scale conservation efforts to protect intact forests are necessary to slow deforestation rates and to avert a new wave of global extinctions.

Setting priorities for climate change adaptation of Critical Sites in the Africa-Eurasian waterbird flyways.

Despite their importance for biodiversity and ecosystem services, wetlands are among the most threatened ecosystems globally. The conservation of many migratory waterbirds depends on the conservation of a network of key sites along their flyways. However, the suitability of these sites is changing under climate change, and it is important that management of individual sites in the network adapts to these changes. Using bioclimatic models that also account for changes in inundation, we found that projected climate change will reduce habitat suitability for waterbirds at 57.5% of existing Critical Sites within Africa-Eurasia, varying from 20.1% in Eastern Europe to 87.0% in Africa. African and Middle East sites are particularly threatened, comprising 71 of the 100 most vulnerable sites. By highlighting priority sites for conservation and classifying Critical Sites into Climate Change Adaptation Strategy (CCAS) classes, our results can be used to support the climate change adaptation of both individual sites and the entire site network.

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates.

Area of habitat (AOH) is defined as the "habitat available to a species, that is, habitat within its range" and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.

Conversión de la Categoría de Hábitat a Cobertura de Terreno para Mapear el Área de Hábitat de los Vertebrados Terrestres Resumen El área del hábitat (AOH) está definida como "el hábitat disponible para una especie, es decir, el hábitat dentro del área de distribución de la especie" y se calcula mediante la sustracción de las áreas de terreno inadecuado y la elevación del área de distribución. El Esquema de Clasificación de Hábitats de la Unión Internacional para la Conservación de la Naturaleza proporciona información sobre las asociaciones entre los hábitats de las especies y con frecuencia se utilizan las opiniones no validadas de expertos para cotejar el hábitat con los tipos de cobertura de terreno, lo que genera una fuente de incertidumbre en los mapas de AOH. Desarrollamos un método orientado por datos para convertir las categorías de hábitat que maneja la UICN en cobertura de terreno basado en los datos de localidad puntual de 6,986 especies de mamíferos terrestres, aves, anfibios y reptiles. Extrajimos la categoría de cobertura de terreno en cada localidad puntual y la cotejamos con la categoría o categorías de hábitat de UICN asignada a cada especie incidente en la localidad. Después modelamos cada categoría de cobertura de terreno como función del hábitat según la UICN usando modelos de regresión logística. Las proporciones de probabilidad resultantes fueron usadas para evaluar la solidez de la asociación entre cada categoría de hábitat y de cobertura de terreno. Después comparamos el desempeño de nuestro modelo orientado por datos con el desempeño de una tabla de conversión publicada basada en el conocimiento de expertos. Calculamos la asociación entre las categorías de hábitat y las de cobertura de terreno como una variable continua, pero para mapear el AOH como una presencia o ausencia binaria, fue necesario aplicar un umbral de asociación. Este umbral puede ser elegido por el usuario de acuerdo con el balance requerido entre los errores de omisión y comisión. Algunos hábitats (p. ej.: bosques y desiertos) fueron asignados a las categorías de cobertura de terreno con más confianza que otros (p. ej.: humedales y artificiales). El modelo de conversión orientado por los datos y el conocimiento de los expertos tuvieron un desempeño igual de eficiente, pero el modelo proporcionó una mayor estandarización, objetividad y repetitividad. Además, nuestra estrategia permitió una mayor flexibilidad en el uso de los resultados y de la incertidumbre para ser cuantificados. Nuestro modelo puede modificarse para análisis regionales y para diferentes grupos taxonómicos.

A quantitative global review of species population monitoring.

Species monitoring, defined here as the repeated, systematic collection of data to detect long-term changes in the populations of wild species, is a vital component of conservation practice and policy. We created a database of nearly 1200 schemes, ranging in start date from 1800 to 2018, to review spatial, temporal, taxonomic, and methodological patterns in global species monitoring. We identified monitoring schemes through standardized web searches, an online survey of stakeholders, in-depth national searches in a sample of countries, and a review of global biodiversity databases. We estimated the total global number of monitoring schemes operating at 3300-15,000. Since 2000, there has been a sharp increase in the number of new schemes being initiated in lower- and middle-income countries and in megadiverse countries, but a decrease in high-income countries. The total number of monitoring schemes in a country and its per capita gross domestic product were strongly, positively correlated. Schemes that were active in 2018 had been running for an average of 21 years in high-income countries, compared with 13 years in middle-income countries and 10 years in low-income countries. In high-income countries, over one-half of monitoring schemes received government funding, but this was less than one-quarter in low-income countries. Data collection was undertaken partly or wholly by volunteers in 37% of schemes, and such schemes covered significantly more sites and species than those undertaken by professionals alone. Birds were by far the most widely monitored taxonomic group, accounting for around half of all schemes, but this bias declined over time. Monitoring in most taxonomic groups remains sparse and uncoordinated, and most of the data generated are elusive and unlikely to feed into wider biodiversity conservation processes. These shortcomings could be addressed by, for example, creating an open global meta-database of biodiversity monitoring schemes and enhancing capacity for species monitoring in countries with high biodiversity. Article impact statement: Species population monitoring for conservation purposes remains strongly biased toward a few vertebrate taxa in wealthier countries.

Una Revisión Global Cuantitativa del Monitoreo Poblacional de Especies Resumen El monitoreo de especies, definido aquí como la recolección sistemática y repetida de datos para detectar cambios a largo plazo en las poblaciones de las especies silvestres, es un componente vital de la práctica y las políticas de la conservación. Generamos una base de datos de casi 1,200 esquemas, con un rango de fecha de inicio desde 1800 hasta 2018, para revisar los patrones espaciales, temporales, taxonómicos y metodológicos en el monitoreo global de especies. Identificamos los esquemas de monitoreo por medio de búsquedas estandarizadas en línea, una encuesta digital realizada a los actores, búsquedas a profundidad en una muestra de países y en una revisión global de las bases de datos sobre la biodiversidad. Estimamos el número total mundial de esquemas funcionales de monitoreo entre 3,300 y 15,000. Desde el 2000, ha habido un fuerte aumento en el número de esquemas nuevos que han iniciado en países de bajo o mediano ingreso y en países megadiversos, pero una disminución en los países de alto ingreso. El número total de esquemas de monitoreo en un país y su producto interno bruto per cápita tuvieron una correlación sólida y positiva. Los esquemas que estaban activos en 2018 lo habían estado en un promedio de 21 años en los países de alto ingreso, comparado con un promedio de 13 años en los países de mediano ingreso y de 10 años en los países de bajo ingreso. En los países de alto ingreso, más de la mitad de los esquemas de monitoreo recibieron financiamiento del gobierno, comparado con menos de un cuarto de los esquemas en los países de bajo ingreso. La recolección de datos se realizó parcial o totalmente por voluntarios en 37% de los esquemas, y dichos esquemas cubrieron significativamente más sitios y especies que aquellos realizados sólo por profesionales. Las aves fueron por mucho el grupo taxonómico más monitoreado, comprendiendo casi la mitad de todos los esquemas, pero este sesgo declinó con el tiempo. El monitoreo en la mayoría de los grupos taxonómicos todavía es disperso y descoordinado, y la mayoría de los datos generados son vagos y tienen poca probabilidad de alimentar procesos más amplios de conservación de biodiversidad. Estas deficiencias podrían abordarse, por ejemplo, creando una meta-base de datos globales abiertos de los esquemas de monitoreo de la biodiversidad y mejorando la capacidad para el monitoreo de especies en los países con alta biodiversidad.

Antarctica and the strategic plan for biodiversity.

The Strategic Plan for Biodiversity, adopted under the auspices of the Convention on Biological Diversity, provides the basis for taking effective action to curb biodiversity loss across the planet by 2020-an urgent imperative. Yet, Antarctica and the Southern Ocean, which encompass 10% of the planet's surface, are excluded from assessments of progress against the Strategic Plan. The situation is a lost opportunity for biodiversity conservation globally. We provide such an assessment. Our evidence suggests, surprisingly, that for a region so remote and apparently pristine as the Antarctic, the biodiversity outlook is similar to that for the rest of the planet. Promisingly, however, much scope for remedial action exists.

Generation lengths of the world's birds and their implications for extinction risk.

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 lengths <3.33 years, meaning that the period of 3 generations-over which population declines are assessed under criterion A-was <10 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 generacional <3.33 años, lo que significa que el periodo de tres generaciones - durante el cual se valoran las declinaciones poblacionales bajo el Criterio A - es <10 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.