A novel, post-Soviet fire disturbance regime drives bird diversity and abundance on the Eurasian steppe.

Many grassland ecosystems and their associated biodiversity depend on the interactions between fire and land-use, both of which are shaped by socioeconomic conditions. The Eurasian steppe biome, much of it situated in Kazakhstan, contains 10% of the world's remaining grasslands. The break-up of the Soviet Union in 1991, widespread land abandonment and massive declines in wild and domestic ungulates led to biomass accumulation over millions of hectares. This rapid fuel increase made the steppes a global fire hotspot, with major changes in vegetation structure. Yet, the response of steppe biodiversity to these changes remains unexplored. We utilized a unique bird abundance dataset covering the entire Kazakh steppe and semi-desert regions together with the MODIS burned area product. We modeled the response of bird species richness and abundance as a function of fire disturbance variables-fire extent, cumulative burned area, fire frequency-at varying grazing intensity. Bird species richness was impacted negatively by large fire extent, cumulative burned area, and high fire frequency in moderately grazed and ungrazed steppe. Similarly, overall bird abundance was impacted negatively by large fire extent, cumulative burned area and higher fire frequency in the moderately grazed steppe, ungrazed steppe, and ungrazed semi-deserts. At the species level, the effect of high fire disturbance was negative for more species than positive. There were considerable fire legacy effects, detectable for at least 8 years. We conclude that the increase in fire disturbance across the post-Soviet Eurasian steppe has led to strong declines in bird abundance and pronounced changes in community assembly. To gain back control over wildfires and prevent further biodiversity loss, restoration of wild herbivore populations and traditional domestic ungulate grazing systems seems much needed.

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.

Area of Habitat maps for the world's terrestrial birds and mammals.

Area of Habitat (AOH) is "the habitat available to a species, that is, habitat within its range". It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species' associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66 ± 28% of the range maps for mammals and 64 ± 27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modelling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals and globally threatened birds.

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.

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.

Climatic change and extinction risk of two globally threatened Ethiopian endemic bird species.

Climate change is having profound effects on the distributions of species globally. Trait-based assessments predict that specialist and range-restricted species are among those most likely to be at risk of extinction from such changes. Understanding individual species' responses to climate change is therefore critical for informing conservation planning. We use an established Species Distribution Modelling (SDM) protocol to describe the curious range-restriction of the globally threatened White-tailed Swallow (Hirundo megaensis) to a small area in southern Ethiopia. We find that, across a range of modelling approaches, the distribution of this species is well described by two climatic variables, maximum temperature and dry season precipitation. These same two variables have been previously found to limit the distribution of the unrelated but closely sympatric Ethiopian Bush-crow (Zavattariornis stresemanni). We project the future climatic suitability for both species under a range of climate scenarios and modelling approaches. Both species are at severe risk of extinction within the next half century, as the climate in 68-84% (for the swallow) and 90-100% (for the bush-crow) of their current ranges is predicted to become unsuitable. Intensive conservation measures, such as assisted migration and captive-breeding, may be the only options available to safeguard these two species. Their projected disappearance in the wild offers an opportunity to test the reliability of SDMs for predicting the fate of wild species. Monitoring future changes in the distribution and abundance of the bush-crow is particularly tractable because its nests are conspicuous and visible over large distances.

Multiple species delimitation approaches applied to the avian lark genus Alaudala.

Species delimitation has advanced from a purely phenotypic exercise to a branch of science that integrates multiple sources of data to identify independently evolving lineages that can be treated as species. We here test species limits in the avian Lesser Short-toed Lark Alaudala rufesens-Sand Lark A. raytal complex, which has an intricate taxonomic history, ranging from a single to three recognised species, with different inclusiveness in different treatments. Our integrative taxonomic approach is based on a combination of DNA sequences, plumage, biometrics, songs, song-flights, geographical distributions, habitat, and bioclimatic data, and using various methods including a species delimitation program (STACEY) based on the multispecies coalescent model. We propose that four species should be recognised: Lesser Short-toed Lark A. rufescens (sensu stricto), Heine's Short-toed Lark A. heinei, Asian Short-toed Lark A. cheleensis and Sand Lark A. raytal. There is also some evidence suggesting lineage separation within A. cheleensis and A. raytal, but additional data are required to evaluate this. The species delimitation based on STACEY agrees well with the non-genetic data. Although computer-based species delimitation programs can be useful in identifying independently evolving lineages, we stress that whenever possible, species hypotheses proposed by these programs should be tested by independent, non-genetic data. Our results highlight the difficulty and subjectivity of delimiting lineages and species, especially at early stages in the speciation process.

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.

A global map of terrestrial habitat types.

We provide a global, spatially explicit characterization of 47 terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for quantifying species' Area of Habitat. We produced this novel habitat map for the year 2015 by creating a global decision tree that intersects the best currently available global data on land cover, climate and land use. We independently validated the map using occurrence data for 828 species of vertebrates (35152 point plus 8181 polygonal occurrences) and 6026 sampling sites. Across datasets and mapped classes we found on average a balanced accuracy of 0.77 ([Formula: see text]0.14 SD) at Level 1 and 0.71 ([Formula: see text]0.15 SD) at Level 2, while noting potential issues of using occurrence records for validation. The maps broaden our understanding of habitats globally, assist in constructing area of habitat refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments. Periodic updates are planned as better or more recent data becomes available.

Roads as a contributor to landscape-scale variation in bird communities.

Roads and their traffic can affect wildlife over large areas and, in regions with dense road networks, may influence a high proportion of the ecological landscape. We assess the abundance of 75 bird species in relation to roads across Great Britain. Of these, 77% vary significantly in abundance with increasing road exposure, just over half negatively so. The effect distances of these negative associations average 700 m from a road, covering over 70% of Great Britain and over 40% of the total area of terrestrial protected sites. Species with smaller national populations generally have lower relative abundance with increasing road exposure, whereas the opposite is true for more common species. Smaller-bodied and migratory species are also more negatively associated with road exposure. By creating environmental conditions that benefit generally common species at the expense of others, road networks may echo other anthropogenic disturbances in bringing about large-scale simplification of avian communities.

The genetic sex-determination system predicts adult sex ratios in tetrapods.

The adult sex ratio (ASR) has critical effects on behaviour, ecology and population dynamics, but the causes of variation in ASRs are unclear. Here we assess whether the type of genetic sex determination influences the ASR using data from 344 species in 117 families of tetrapods. We show that taxa with female heterogamety have a significantly more male-biased ASR (proportion of males: 0.55 ± 0.01 (mean ± s.e.m.)) than taxa with male heterogamety (0.43 ± 0.01). The genetic sex-determination system explains 24% of interspecific variation in ASRs in amphibians and 36% in reptiles. We consider several genetic factors that could contribute to this pattern, including meiotic drive and sex-linked deleterious mutations, but further work is needed to quantify their effects. Regardless of the mechanism, the effects of the genetic sex-determination system on the adult sex ratio are likely to have profound effects on the demography and social behaviour of tetrapods.

Protection reduces loss of natural land-cover at sites of conservation importance across Africa.

There is an emerging consensus that protected areas are key in reducing adverse land-cover change, but their efficacy remains difficult to quantify. Many previous assessments of protected area effectiveness have compared changes between sets of protected and unprotected sites that differ systematically in other potentially confounding respects (e.g. altitude, accessibility), have considered only forest loss or changes at single sites, or have analysed changes derived from land-cover data of low spatial resolution. We assessed the effectiveness of protection in reducing land-cover change in Important Bird Areas (IBAs) across Africa using a dedicated visual interpretation of higher resolution satellite imagery. We compared rates of change in natural land-cover over a c. 20-year period from around 1990 at a large number of points across 45 protected IBAs to those from 48 unprotected IBAs. A matching algorithm was used to select sample points to control for potentially confounding differences between protected and unprotected IBAs. The rate of loss of natural land-cover at sample points within protected IBAs was just 42% of that at matched points in unprotected IBAs. Conversion was especially marked in forests, but protection reduced rates of forest loss by a similar relative amount. Rates of conversion increased from the centre to the edges of both protected and unprotected IBAs, but rates of loss in 20-km buffer zones surrounding protected IBAs and unprotected IBAs were similar, with no evidence of displacement of conversion from within protected areas to their immediate surrounds (leakage).

Crop expansion and conservation priorities in tropical countries.

Expansion of cropland in tropical countries is one of the principal causes of biodiversity loss, and threatens to undermine progress towards meeting the Aichi Biodiversity Targets. To understand this threat better, we analysed data on crop distribution and expansion in 128 tropical countries, assessed changes in area of the main crops and mapped overlaps between conservation priorities and cultivation potential. Rice was the single crop grown over the largest area, especially in tropical forest biomes. Cropland in tropical countries expanded by c. 48,000 km(2) per year from 1999-2008. The countries which added the greatest area of new cropland were Nigeria, Indonesia, Ethiopia, Sudan and Brazil. Soybeans and maize are the crops which expanded most in absolute area. Other crops with large increases included rice, sorghum, oil palm, beans, sugar cane, cow peas, wheat and cassava. Areas of high cultivation potential-while bearing in mind that political and socio-economic conditions can be as influential as biophysical ones-may be vulnerable to conversion in the future. These include some priority areas for biodiversity conservation in tropical countries (e.g., Frontier Forests and High Biodiversity Wilderness Areas), which have previously been identified as having 'low vulnerability', in particular in central Africa and northern Australia. There are also many other smaller areas which are important for biodiversity and which have high cultivation potential (e.g., in the fringes of the Amazon basin, in the Paraguayan Chaco, and in the savanna woodlands of the Sahel and East Africa). We highlight the urgent need for more effective sustainability standards and policies addressing both production and consumption of tropical commodities, including robust land-use planning in agricultural frontiers, establishment of new protected areas or REDD+ projects in places agriculture has not yet reached, and reduction or elimination of incentives for land-demanding bioenergy feedstocks.

Financial costs of meeting global biodiversity conservation targets: current spending and unmet needs.

World governments have committed to halting human-induced extinctions and safeguarding important sites for biodiversity by 2020, but the financial costs of meeting these targets are largely unknown. We estimate the cost of reducing the extinction risk of all globally threatened bird species (by ≥1 International Union for Conservation of Nature Red List category) to be U.S. $0.875 to $1.23 billion annually over the next decade, of which 12% is currently funded. Incorporating threatened nonavian species increases this total to U.S. $3.41 to $4.76 billion annually. We estimate that protecting and effectively managing all terrestrial sites of global avian conservation significance (11,731 Important Bird Areas) would cost U.S. $65.1 billion annually. Adding sites for other taxa increases this to U.S. $76.1 billion annually. Meeting these targets will require conservation funding to increase by at least an order of magnitude.

Identifying priority areas for conservation: a global assessment for forest-dependent birds.

Limited resources are available to address the world's growing environmental problems, requiring conservationists to identify priority sites for action. Using new distribution maps for all of the world's forest-dependent birds (60.6% of all bird species), we quantify the contribution of remaining forest to conserving global avian biodiversity. For each of the world's partly or wholly forested 5-km cells, we estimated an impact score of its contribution to the distribution of all the forest bird species estimated to occur within it, and so is proportional to the impact on the conservation status of the world's forest-dependent birds were the forest it contains lost. The distribution of scores was highly skewed, a very small proportion of cells having scores several orders of magnitude above the global mean. Ecoregions containing the highest values of this score included relatively species-poor islands such as Hawaii and Palau, the relatively species-rich islands of Indonesia and the Philippines, and the megadiverse Atlantic Forests and northern Andes of South America. Ecoregions with high impact scores and high deforestation rates (2000-2005) included montane forests in Cameroon and the Eastern Arc of Tanzania, although deforestation data were not available for all ecoregions. Ecoregions with high impact scores, high rates of recent deforestation and low coverage by the protected area network included Indonesia's Seram rain forests and the moist forests of Trinidad and Tobago. Key sites in these ecoregions represent some of the most urgent priorities for expansion of the global protected areas network to meet Convention on Biological Diversity targets to increase the proportion of land formally protected to 17% by 2020. Areas with high impact scores, rapid deforestation, low protection and high carbon storage values may represent significant opportunities for both biodiversity conservation and climate change mitigation, for example through Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives.