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.

Savviness of prey to introduced predators.

The prey naivety hypothesis posits that prey are vulnerable to introduced predators because many generations in slow gradual coevolution are needed for appropriate avoidance responses to develop. It predicts that prey will be more responsive to native than introduced predators and less responsive to introduced predators that differ substantially from native predators and from those newly established. To test these predictions, we conducted a global meta-analysis of studies that measured the wariness responses of small mammals to the scent of sympatric mammalian mesopredators. We identified 26 studies that met our selection criteria. These studies comprised 134 experiments reporting on the responses of 36 small mammal species to the scent of six introduced mesopredators and 12 native mesopredators. For each introduced mesopredator, we measured their phylogenetic and functional distance to local native mesopredators and the number of years sympatric with their prey. We used predator and prey body mass as a measure of predation risk. Globally, small mammals were similarly wary of the scent of native and introduced mesopredators; phylogenetic and functional distance between introduced mesopredators and closest native mesopredators had no effect on wariness; and wariness was unrelated to the number of prey generations, or years, since first contact with introduced mesopredators. Small mammal wariness was associated with predator-prey body mass ratio, regardless of the nativity. The one thing animals do not seem to recognize is whether their predators are native.

La hipótesis de la ingenuidad de la presa plantea que ésta es vulnerable a los depredadores introducidos porque se requiere que muchas generaciones atraviesen una coevolución lenta y gradual para que se desarrollen las respuestas de evasión adecuadas. La hipótesis supone que la presa será más sensible a los depredadores introducidos que difieren notoriamente de los nativos y de aquellos recién establecidos. Realizamos un metaanálisis global de estudios que midieron las respuestas cautelosas de mamíferos pequeños ante el rastro de meso depredadores simpátricos para probar estas suposiciones. Identificamos 26 estudios que cumplieron con nuestro criterio de selección. Estos estudios estuvieron conformados por 134 experimentos que reportaban las respuestas de 36 especies de mamíferos pequeños ante el rastro de seis meso depredadores introducidos y 12 nativos. Medimos la distancia funcional y filogenética entre cada meso depredador introducido y los meso depredadores locales nativos y el número de años simpátricos con su presa. Usamos la masa corporal del depredador y la presa como medida del riesgo de depredación. A nivel mundial, los mamíferos pequeños compartieron la cautela ante el rastro de los meso depredadores nativos e introducidos; la distancia funcional y la filogenética entre los meso depredadores introducidos y el meso depredador nativo más cercano no tuvieron efecto sobre la cautela; y la cautela no estuvo relacionada con el número de generaciones de la presa, o años, desde el primer contacto con los meso depredadores introducidos. La cautela de los mamíferos pequeños estuvo asociada con las proporciones de masa corporal entre el depredador y la presa, sin importar el origen. Lo único que los animales parecen no reconocer es si el depredador es nativo o no.

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.

The impacts of linear infrastructure on terrestrial vertebrate populations: A trait-based approach.

While linear infrastructures, such as roads and power lines, are vital to human development, they may also have negative impacts on wildlife populations up to several kilometres into the surrounding environment (infrastructure-effect zones, IEZs). However, species-specific IEZs are not available for the vast majority of species, hampering global assessments of infrastructure impacts on wildlife. Here, we synthesized 253 studies worldwide to quantify the magnitude and spatial extent of infrastructure impacts on the abundance of 792 vertebrate species. We also identified the extent to which species traits, infrastructure type and habitat modulate IEZs for vertebrate species. Our results reveal contrasting responses across taxa based on the local context and species traits. Carnivorous mammals were generally more abundant in the proximity of infrastructure. In turn, medium- to large-sized non-carnivorous mammals (>1 kg) were less abundant near infrastructure across habitats, while their smaller counterparts were more abundant close to infrastructure in open habitats. Bird abundance was reduced near infrastructure with larger IEZs for non-carnivorous than for carnivorous species. Furthermore, birds experienced larger IEZs in closed (carnivores: ≈130 m, non-carnivores: >1 km) compared to open habitats (carnivores: ≈70 m, non-carnivores: ≈470 m). Reptiles were more abundant near infrastructure in closed habitats but not in open habitats where abundances were reduced within an IEZ of ≈90 m. Finally, IEZs were relatively small in amphibians (<30 m). These results indicate that infrastructure impact assessments should differentiate IEZs across species and local contexts in order to capture the variety of responses to infrastructure. Our trait-based synthetic approach can be applied in large-scale assessments of the impacts of current and future infrastructure developments across multiple species, including those for which infrastructure responses are not known from empirical data.

Intact but empty forests? Patterns of hunting-induced mammal defaunation in the tropics.

Tropical forests are increasingly degraded by industrial logging, urbanization, agriculture, and infrastructure, with only 20% of the remaining area considered intact. However, this figure does not include other, more cryptic but pervasive forms of degradation, such as overhunting. Here, we quantified and mapped the spatial patterns of mammal defaunation in the tropics using a database of 3,281 mammal abundance declines from local hunting studies. We simultaneously accounted for population abundance declines and the probability of local extirpation of a population as a function of several predictors related to human accessibility to remote areas and species' vulnerability to hunting. We estimated an average abundance decline of 13% across all tropical mammal species, with medium-sized species being reduced by >27% and large mammals by >40%. Mammal populations are predicted to be partially defaunated (i.e., declines of 10%-100%) in ca. 50% of the pantropical forest area (14 million km2), with large declines (>70%) in West Africa. According to our projections, 52% of the intact forests (IFs) and 62% of the wilderness areas (WAs) are partially devoid of large mammals, and hunting may affect mammal populations in 20% of protected areas (PAs) in the tropics, particularly in West and Central Africa and Southeast Asia. The pervasive effects of overhunting on tropical mammal populations may have profound ramifications for ecosystem functioning and the livelihoods of wild-meat-dependent communities, and underscore that forest coverage alone is not necessarily indicative of ecosystem intactness. We call for a systematic consideration of hunting effects in (large-scale) biodiversity assessments for more representative estimates of human-induced biodiversity loss.

Time-lagged effects of habitat fragmentation on terrestrial mammals in Madagascar.

Biodiversity is severely threatened by habitat destruction. As a consequence of habitat destruction, the remaining habitat becomes more fragmented. This results in time-lagged population extirpations in remaining fragments when these are too small to support populations in the long term. If these time-lagged effects are ignored, the long-term impacts of habitat loss and fragmentation will be underestimated. We quantified the magnitude of time-lagged effects of habitat fragmentation for 157 nonvolant terrestrial mammal species in Madagascar, one of the biodiversity hotspots with the highest rates of habitat loss and fragmentation. We refined species' geographic ranges based on habitat preferences and elevation limits and then estimated which habitat fragments were too small to support a population for at least 100 years given stochastic population fluctuations. We also evaluated whether time-lagged effects would change the threat status of species according to the International Union for the Conservation of Nature (IUCN) Red List assessment framework. We used allometric relationships to obtain the population parameters required to simulate the population dynamics of each species, and we quantified the consequences of uncertainty in these parameter estimates by repeating the analyses with a range of plausible parameter values. Based on the median outcomes, we found that for 34 species (22% of the 157 species) at least 10% of their current habitat contained unviable populations. Eight species (5%) had a higher threat status when accounting for time-lagged effects. Based on 0.95-quantile values, following a precautionary principle, for 108 species (69%) at least 10% of their habitat contained unviable populations, and 51 species (32%) had a higher threat status. Our results highlight the need to preserve continuous habitat and improve connectivity between habitat fragments. Moreover, our findings may help to identify species for which time-lagged effects are most severe and which may thus benefit the most from conservation actions.

La biodiversidad se encuentra seriamente amenazada por la destrucción del hábitat. Como consecuencia de esta destrucción, el hábitat remanente se vuelve más fragmentado. Esto resulta en extirpaciones poblacionales retardadas dentro de los fragmentos restantes cuando éstos son muy pequeños para mantener a las poblaciones a largo plazo. Si se ignoran estos efectos retardados, se subestimarán los impactos a largo plazo de la pérdida del hábitat y la fragmentación. Cuantificamos la magnitud de los efectos retardados de la fragmentación del hábitat para 157 especies de mamíferos terrestres no voladores en Madagascar, uno de los puntos calientes de biodiversidad con las tasas más elevadas de pérdida del hábitat y fragmentación. Depuramos las extensiones geográficas de las especies con base en las preferencias de hábitat y los límites de elevación y después estimamos cuáles fragmentos de hábitat eran muy pequeños para mantener una población durante al menos cien años dadas las fluctuaciones estocásticas de las poblaciones. También analizamos si los efectos retardados cambiarían el estado de amenaza de la especie de acuerdo con el programa de evaluación de la Lista Roja de la UICN. Usamos relaciones alométricas para obtener los parámetros poblacionales requeridos para simular las dinámicas poblacionales de cada especie y cuantificamos las consecuencias de la incertidumbre en estos parámetros estimados mediante análisis repetidos con una gama de valores plausibles de los parámetros. Con base en los resultados promedio, descubrimos que para 34 especies (22% de las 157 especies) al menos el 10% de su hábitat actual tiene poblaciones inviables. Ocho especies (5%) cambiaron a un estado más elevado de amenaza cuando se consideraron los efectos retardados. Con base en los valores del centil 0.95, adherido a un principio precautorio, para 108 especies (32%) al menos el 10% de su hábitat tiene poblaciones inviables y 51 especies (32%) cambiaron negativamente su estado de amenaza. Nuestros resultados resaltan la necesidad de conservar la continuidad de los hábitats y mejorar la conectividad entre los fragmentos. Además, nuestros hallazgos pueden ayudar a identificar especies para las cuales los efectos retardados son más serios y que podrían beneficiarse más con las acciones de conservación.

Habitat destruction and overexploitation drive widespread declines in all facets of mammalian diversity in the Gran Chaco.

Global biodiversity is under high and rising anthropogenic pressure. Yet, how the taxonomic, phylogenetic, and functional facets of biodiversity are affected by different threats over time is unclear. This is particularly true for the two main drivers of the current biodiversity crisis: habitat destruction and overexploitation. We provide the first long-term assessment of multifaceted biodiversity changes caused by these threats for any tropical region. Focussing on larger mammals in South America's 1.1 million km2 Gran Chaco region, we assessed changes in multiple biodiversity facets between 1985 and 2015, determined which threats drive those changes, and identified remaining key areas for all biodiversity facets. Using habitat and threat maps, we found, first, that between 1985 and 2015 taxonomic (TD), phylogenetic (PD) and functional (FD) diversity all declined drastically across over half of the area assessed. FD declined about 50% faster than TD and PD, and these declines were mainly driven by species loss, rather than species turnover. Second, habitat destruction, hunting, and both threats together contributed ~57%, ~37%, and ~6% to overall facet declines, respectively. However, hunting pressure increased where TD and PD declined most strongly, whereas habitat destruction disproportionally contributed to FD declines. Third, just 23% of the Chaco would have to be protected to safeguard the top 17% of all three facets. Our findings uncover a widespread impoverishment of mammal species richness, evolutionary history, and ecological functions across broad areas of the Chaco due to increasing habitat destruction and hunting. Moreover, our results pinpoint key areas that should be preserved and managed to maintain all facets of mammalian diversity across the Chaco. More generally, our work highlights how long-term changes in biodiversity facets can be assessed and attributed to specific threats, to better understand human impacts on biodiversity and to guide conservation planning to mitigate them.

Conditional love? Co-occurrence patterns of drought-sensitive species in European grasslands are consistent with the stress-gradient hypothesis.

AIM: The stress-gradient hypothesis (SGH) postulates that species interactions shift from negative to positive with increasing abiotic stress. Interactions between species are increasingly being recognized as important drivers of species distributions, but it is still unclear whether stress-induced changes in interactions affect continental-to-global scale species distributions. Here, we tested whether associations of vascular plant species in dry grasslands in Europe follow the SGH along a climatic water deficit (CWD) gradient across the continent. LOCATION: Dry grasslands in Europe. TIME PERIOD: Present. MAJOR TAXA STUDIED: Vascular plants. METHODS: We built a context-dependent joint species distribution model (JSDM) to estimate the residual associations (i.e., associations that are not explained by the abiotic environment) of 161 plant species as a function of the CWD based on community data from 8,660 vegetation plots. We evaluated changes in residual associations between species for pairs and on the community level, and we compared responses for groups of species with different drought tolerances. RESULTS: We found contrasting shifts in associations for drought-sensitive and drought-tolerant species. For drought-sensitive species, 21% of the pairwise associations became more positive with increasing CWD, whereas 17% became more negative. In contrast, only 17% of the pairwise associations involving drought-tolerant species became more positive, whereas 27% became more negative in areas with a high CWD. Additionally, the incidence of positive associations increased with drought for drought-sensitive species and decreased for drought-tolerant species. MAIN CONCLUSIONS: We found that associations of drought-sensitive plant species became more positive with drought, in line with the SGH. In contrast, associations of drought-tolerant species became more negative. Additionally, changes in associations of single species pairs were highly variable. Our results indicate that stress-modulated species associations might influence the distribution of species over large geographical extents, thus leading to unexpected responses under climate change through shifts in species associations.

Projecting terrestrial biodiversity intactness with GLOBIO 4.

Scenario-based biodiversity modelling is a powerful approach to evaluate how possible future socio-economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio-economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc-seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area-weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (-0.02) than the regional rivalry and fossil-fuelled development scenarios (-0.06 and -0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub-Saharan Africa. In some scenario-region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but also focus on reducing or mitigating the impacts of other pressures.

Assessing the reliability of predicted plant trait distributions at the global scale.

AIM: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a systematic evaluation of their reliability in terms of the accuracy of the models, ecological realism and various sources of uncertainty. LOCATION: Global. TIME PERIOD: Present. MAJOR TAXA STUDIED: Vascular plants. METHODS: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble modelling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the uncertainty across geographical space attributed to spatial extrapolation and diverging model predictions. RESULTS: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait-environment relationships and trait-trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in predictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model performance by 28%. MAIN CONCLUSIONS: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high-quality data for traits that mostly respond to large-scale environmental factors. We recommend applying ensemble forecasting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions.

Combined effects of land use and hunting on distributions of tropical mammals.

Land use and hunting are 2 major pressures on biodiversity in the tropics. Yet, their combined impacts have not been systematically quantified at a large scale. We estimated the effects of both pressures on the distributions of 1884 tropical mammal species by integrating species' range maps, detailed land-use maps (1992 and 2015), species-specific habitat preference data, and a hunting pressure model. We further identified areas where the combined impacts were greatest (hotspots) and least (coolspots) to determine priority areas for mitigation or prevention of the pressures. Land use was the main driver of reduced distribution of all mammal species considered. Yet, hunting pressure caused additional reductions in large-bodied species' distributions. Together, land use and hunting reduced distributions of species by 41% (SD 30) on average (year 2015). Overlap between impacts was only 2% on average. Land use contributed more to the loss of distribution (39% on average) than hunting (4% on average). However, hunting reduced the distribution of large mammals by 29% on average; hence, large mammals lost a disproportional amount of area due to the combination of both pressures. Gran Chaco, the Atlantic Forest, and Thailand had high levels of impact across the species (hotspots of area loss). In contrast, the Amazon and Congo Basins, the Guianas, and Borneo had relatively low levels of impact (coolspots of area loss). Overall, hunting pressure and human land use increased from 1992 to 2015 and corresponding losses in distribution increased from 38% to 41% on average across the species. To effectively protect tropical mammals, conservation policies should address both pressures simultaneously because their effects are highly complementary. Our spatially detailed and species-specific results may support future national and global conservation agendas, including the design of post-2020 protected area targets and strategies.

Efectos Combinados del Uso de Suelo y la Caza en la Distribución de los Mamíferos Tropicales Resumen El uso de suelo y la caza son dos de las principales presiones ejercidas sobre la biodiversidad de los trópicos. Aun así, los impactos combinados que generan no han sido cuantificados sistemáticamente a gran escala. Estimamos los efectos de ambas presiones sobre la distribución de 1,884 especies de mamíferos tropicales al integrar mapas de distribución de las especies, mapas detallados del uso de suelo (de 1992 y 2015), datos de preferencia de hábitat específicos por especie y un modelo de presión de caza. Identificamos además las áreas en donde los impactos combinados eran mayores (puntos calientes) y menores (puntos fríos) para determinar las áreas prioritarias para la mitigación o prevención de dichas presiones. El uso de suelo fue el principal conductor de la reducción de la distribución para todas las especies de mamíferos que consideramos. Sin embargo, la presión por caza causó reducciones adicionales en la distribución de especies de gran tamaño. Juntas, el uso de suelo y la caza redujeron la distribución de las especies en un 41% (DS 30) en promedio (año 2015). El solapamiento entre los impactos fue, en promedio, sólo del 2%. El uso de suelo contribuyó más a la pérdida de la distribución (39%, en promedio) que la caza (4%, en promedio). A pesar de esto, en promedio la caza redujo la distribución de los mamíferos de gran tamaño en un 29%; por lo tanto, los grandes mamíferos perdieron una cantidad desproporcionada de área debido a la combinación de ambas presiones. El Gran Chaco, el Bosque Atlántico y Tailandia tuvieron niveles altos de impacto en todas las especies (puntos calientes de pérdida de área). Como contraste, las cuencas del Amazonas y el Congo, las Guayanas y Borneo tuvieron niveles relativamente bajos de impacto (puntos fríos de pérdida de área). En general, las presiones por caza y uso de suelo incrementaron desde 1992 a 2015 y las correspondientes pérdidas de distribución incrementaron de un 38% a un 41% en promedio para todas las especies. Para proteger de forma efectiva a los mamíferos tropicales, las políticas de conservación deberían considerar a ambas presiones de manera simultánea, pues sus efectos son altamente complementarios. Nuestros resultados espacialmente detallados y específicos para cada especie pueden respaldar las futuras agendas de conservación nacionales e internacionales, incluyendo el diseño de las estrategias y los objetivos de las áreas protegidas para después de 2020.

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments.

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species' distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5-2.3% and 6.4-14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.

Aplicación de Modelos de Hábitat y de Densidad Poblacional a Series de Tiempo de la Cobertura del Suelo para Informar las Valoraciones de la Lista Roja de la UICN Resumen Las categorías y los criterios de la Lista Roja de la UICN (Unión Internacional para la Conservación de la Naturaleza) son el marco de referencia utilizado con mayor frecuencia para valorar el riesgo de extinción relativo de las especies. Los criterios se basan en umbrales cuantitativos relacionados con el tamaño, las tendencias y la estructura de la distribución y las poblaciones de las especies. Sin embargo, los datos sobre estos parámetros son escasos e inciertos para muchas especies y para otras no se encuentran disponibles, lo puede resultar en una clasificación errónea o en que se las clasifique como una especie con deficiencia de datos. Hemos diseñado una estrategia que combina datos sobre el cambio en la cobertura del suelo, las preferencias de hábitat específicas por especie, la abundancia poblacional, y la distancia de dispersión para estimar los parámetros más importantes (extensión de la presencia, área máxima de ocupación, tamaño poblacional, y grado y tendencia de la fragmentación) y así predecir las categorías de la Lista Roja de la UICN para cada especie. Hemos aplicado nuestra estrategia a las aves no pelágicas y a los mamíferos terrestres de todo el mundo (∼15,000 especies). Las categorías pronosticadas fueron bastante consecuentes con las valoraciones publicadas por la Lista Roja de la UICN, aunque en general fueron más optimistas. Pronosticamos que el 4.2% de las especies (467 aves y 143 mamíferos) se encuentran más amenazadas que su valoración actual y el 20.2% de las especies con deficiencia de datos (10 aves y 114 mamíferos) se encuentran en riesgo de extinción. La incorporación del sub-criterio de fragmentación del hábitat redujo estas predicciones en un 1.5 - 2.3% y 6.4 - 14.9% (dependiendo de la definición cuantitativa de la fragmentación) para las especies amenazadas y las que tienen deficiencia de datos, respectivamente, lo que resalta la necesidad de mejorar la aplicación de este sub-criterio por parte de los asesores de la Lista Roja de la UICN. Nuestra estrategia complementa los métodos tradicionales de estimación de parámetros para las valoraciones de la Lista Roja. Además, proporciona un sistema inmediato de alerta temprana basado en actualizaciones periódicas de la información sobre la cobertura del suelo que permite identificar a las especies que, potencialmente, merezcan un cambio en su categoría de riesgo de extinción. Nuestro método está basado en suposiciones optimistas sobre la distribución y la abundancia de las especies, por lo tanto todas las especies que predecimos que tienen una mayor categoría de riesgo que la que reconoce la evaluación actual deberían ser priorizadas para su revaloración.

Variability of Greenhouse Gas Footprints of Field Tomatoes Grown for Processing: Interyear and Intercountry Assessment.

Our study provides an integrated analysis of the variability of greenhouse gas (GHG) footprints of field-grown tomatoes for processing. The global farm-specific data set of 890 observations across 14 countries over a three-year period (2013-2015) was obtained from farms grown under Unilever's sustainable agricultural code. It represents on average 3% of the annual global production of processing tomatoes: insights can be used to help inform corporate sourcing strategies and certification schemes. The median GHG footprint ranged from 18 in Chile to 61 kg CO2-equiv per tonne of tomatoes in India, lower than results reported in other studies. We found that footprints are more consistent within countries than between them. Using linear mixed effect models, we quantified the relative influence of environmental conditions and farm management factors. Key variables were area of production and the method of fertilizer application. GHG footprints decreased with increasing area of production to a threshold of 17.4 ha. Farms using single fertilizer application methods in general had a larger GHG footprint than those using a combination of methods. We conclude that farm management factors should be prioritized for future data collection, and more stringent guidance on acceptable practices is required if greater comparability of outcomes is needed either within a scheme, such as the Unilever's sustainable agriculture code, or between schemes.

Changes in behaviour and faecal glucocorticoid levels in response to increased human activities during weekends in the pin-tailed sandgrouse.

Human recreational activities are becoming increasingly widespread and frequent, a fact that may potentially exacerbate their effects on wildlife. These human-related disturbances on animals may induce behavioural and physiological changes that can ultimately affect their fitness, showing a similar anti-predator response that against natural predator or other threats. Here, we combine the use of behavioural and physiological approaches to assess the potential effect of winter human activities on a threatened farmland bird in Europe, the pin-tailed sandgrouse (Pterocles alchata). We compared before, during and after weekend variations in human activity rates, pin-tailed sandgrouse behaviour (flocking and flying behaviour, interspecific association in mixed flocks and habitat use) and faecal glucocorticoid metabolite concentrations. Human disturbances, in particular those associated with hunting activities, peaked during weekends. Sandgrouse showed significant behavioural changes (increased sandgrouse-only flock sizes, increased proportion of birds flying and changes in habitat use) during weekends and higher faecal glucocorticoid metabolite concentrations after the weekends compared with during or before weekends. Therefore, physiological stress levels could be modulated by behavioural adjustments such as increased flock sizes and changes in habitat use that may allow sandgrouse to cope with increased human disturbance rates during weekends. Nevertheless, temporal and spatial organization of hunting days among groups of estates might be good strategies to buffer these potential adverse effects on wintering pin-tailed sandgrouse and other steppe species of conservation concern, while preserving a socio-economically important activity such as hunting.

Niche-habitat mechanisms and biotic interactions explain the coexistence and abundance of congeneric sandgrouse species.

Ascertaining which niche processes allow coexistence between closely related species is of special interest in ecology. We quantified variations in the environmental niches and densities of two congeneric species, the pin-tailed and the black-bellied sandgrouse (Pterocles alchata and Pterocles orientalis) in allopatry and sympatry under similar abiotic, habitat and dispersal contexts to understand their coexistence. Using principal component analysis, we defined environmental gradients (niche dimensions) including abiotic, habitat and anthropogenic variables, and calculated niche breadth, position and overlap of both species in sympatry and allopatry. Additionally, sandgrouse density was modelled as a function of the niche dimensions and the density of the other species. We found evidence that each species occupies distinct environmental niches in sympatry and in allopatry. The black-bellied sandgrouse exploits a broader range of environmental conditions (wider niche breadth) while the pin-tailed sandgrouse reaches high densities where conditions seem to match its optimum. In sympatry, both species shift their niches to intermediate positions, indicating the importance of abiotic factors in setting coexistence areas. Environmental conditions determine regional densities of pin-tailed sandgrouse whereas biotic interactions explain the density of the black-bellied sandgrouse in areas with abiotic conditions similarly conducive for both species. Highly suitable areas for the pin-tailed sandgrouse fall beyond the upper thermal limit of the black-bellied sandgrouse, leading to niche segregation and low densities for the latter. Finally, local niche shift and expansion plus possible heterospecific aggregation allow the pin-tailed sandgrouse to thrive in a priori less favourable environments. This work provides insight into how different mechanisms allow species coexistence and how species densities vary in sympatry compared to allopatry as a result of environmental filtering and biotic interactions.

Range area and the fast-slow continuum of life history traits predict pathogen richness in wild mammals.

Surveillance of pathogen richness in wildlife is needed to identify host species with a high risk of zoonotic disease spillover. While several predictors of pathogen richness in wildlife hosts have been proposed, their relative importance has not been formally examined. This hampers our ability to identify potential disease reservoirs, particularly in remote areas with limited surveillance efforts. Here we analyzed 14 proposed predictors of pathogen richness using ensemble modeling and a dataset of 1040 host species to identify the most important predictors of pathogen richness in wild mammal species. After controlling for research effort, larger species geographic range area was identified to be associated with higher pathogen richness. We found evidence of duality in the relationship between the fast-slow continuum of life-history traits and pathogen richness, where pathogen richness increases near the extremities. Taxonomic orders Carnivora, Proboscidea, Artiodactyla, and Perissodactyla were predicted to host high pathogen richness. The top three species with the highest pathogen richness predicted by our ensemble model were Canis lupus, Sus scrofa, and Alces alces. Our results can help support evidence-informed pathogen surveillance and disease reservoir management to prevent the emergence of future zoonotic diseases.

Bat responses to climate change: a systematic review.

Understanding how species respond to climate change is key to informing vulnerability assessments and designing effective conservation strategies, yet research efforts on wildlife responses to climate change fail to deliver a representative overview due to inherent biases. Bats are a species-rich, globally distributed group of organisms that are thought to be particularly sensitive to the effects of climate change because of their high surface-to-volume ratios and low reproductive rates. We systematically reviewed the literature on bat responses to climate change to provide an overview of the current state of knowledge, identify research gaps and biases and highlight future research needs. We found that studies are geographically biased towards Europe, North America and Australia, and temperate and Mediterranean biomes, thus missing a substantial proportion of bat diversity and thermal responses. Less than half of the published studies provide concrete evidence for bat responses to climate change. For over a third of studied bat species, response evidence is only based on predictive species distribution models. Consequently, the most frequently reported responses involve range shifts (57% of species) and changes in patterns of species diversity (26%). Bats showed a variety of responses, including both positive (e.g. range expansion and population increase) and negative responses (range contraction and population decrease), although responses to extreme events were always negative or neutral. Spatial responses varied in their outcome and across families, with almost all taxonomic groups featuring both range expansions and contractions, while demographic responses were strongly biased towards negative outcomes, particularly among Pteropodidae and Molossidae. The commonly used correlative modelling approaches can be applied to many species, but do not provide mechanistic insight into behavioural, physiological, phenological or genetic responses. There was a paucity of experimental studies (26%), and only a small proportion of the 396 bat species covered in the examined studies were studied using long-term and/or experimental approaches (11%), even though they are more informative about the effects of climate change. We emphasise the need for more empirical studies to unravel the multifaceted nature of bats' responses to climate change and the need for standardised study designs that will enable synthesis and meta-analysis of the literature. Finally, we stress the importance of overcoming geographic and taxonomic disparities through strengthening research capacity in the Global South to provide a more comprehensive view of terrestrial biodiversity responses to climate change.

Dwarfism and gigantism drive human-mediated extinctions on islands.

Islands have long been recognized as distinctive evolutionary arenas leading to morphologically divergent species, such as dwarfs and giants. We assessed how body size evolution in island mammals may have exacerbated their vulnerability, as well as how human arrival has contributed to their past and ongoing extinctions, by integrating data on 1231 extant and 350 extinct species from islands and paleo islands worldwide spanning the past 23 million years. We found that the likelihood of extinction and of endangerment are highest in the most extreme island dwarfs and giants. Extinction risk of insular mammals was compounded by the arrival of modern humans, which accelerated extinction rates more than 10-fold, resulting in an almost complete demise of these iconic marvels of island evolution.

Reproducibility in ecology and evolution: Minimum standards for data and code.

We call for journals to commit to requiring open data be archived in a format that will be simple and clear for readers to understand and use. If applied consistently, these requirements will allow contributors to be acknowledged for their work through citation of open data, and facilitate scientific progress.