Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology

Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians

Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.

Saving the Last West African Giraffe Population: A Review of Its Conservation Status and Management

The West African giraffe (Giraffa camelopardalis peralta) was historically spread across much of the Sudano-Sahelian zone but is now restricted to Niger. Several factors resulted in their dramatic decline during the late 20th century. In 1996, only 49 individuals remained, concentrated in the 'Giraffe Zone'. Conservation activities implemented by the Government of Niger, supported by local communities and NGOs, facilitated their population numbers to increase. This review summarizes past and present conservation activities and evaluates their impact to advise and prioritize future conservation actions for the West African giraffe. The long-term conservation of the West African giraffe is highly dependent on the local communities who live alongside them, as well as supplementary support from local and international partners. Recent conservation initiatives range from community-based monitoring to the fitting of GPS satellite tags to better understand their habitat use, spatial movements to expansion areas, and environmental education to the establishment of the first satellite population of West African giraffe in Gadabedji Biosphere Reserve, the latter serving as a flagship for the future restoration of large mammal populations in West Africa. The integration of modern technologies and methods will hopefully provide better-quality data, improved spatial analyses, and greater understanding of giraffe ecology to inform the long-term management of West African giraffe.

One elephant may sustain 2 million dung beetles in East African savannason any given day

In East African savannas, in the rainy season, an elephant dung bolus is usually transformed into a flat mat of dung residue within a few hours. We extracted the coprophilous beetles of a dung mat from a 1 kg bolus after a one-night exposure and counted 13,699 specimens, most of them aphodiine dung beetles. This is the largest number of dung beetles per kilogram of mammal dung ever counted. Given that an elephant produces an average of 160 kg of feces per day, we extrapolate that one adult elephant provides food for 2.12 million dung beetles on any given day. The elephant population in the Laikipia-Samburu ecosystem in central Kenya, an elephant-rich environment, can sustain, by sheer extrapolation, 14.3 billion dung beetles in an area of 55,000 km2, which translates to ca. 260,000 dung beetles/km2. The decline or extinction of elephants, at least in East African grasslands, may have a massive cascade effect on the populations of coprophagous beetles and the biota dependent on or gaining an advantage from them.

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.

Human-modified landscapes driving the global primate extinction crisis

The world's primates have been severely impacted in diverse and profound ways by anthropogenic pressures. Here, we evaluate the impact of various infrastructures and human-modified landscapes on spatial patterns of primate species richness, at both global and regional scales. We overlaid the International Union for the Conservation of Nature (IUCN) range maps of 520 primate species and applied a global 100 km2 grid. We used structural equation modeling and simultaneous autoregressive models to evaluate direct and indirect effects of six human-altered landscapes variables (i.e., human footprint [HFP], croplands [CROP], road density [ROAD], pasture lands [PAST], protected areas [PAs], and Indigenous Peoples' lands [IPLs]) on global primate species richness, threatened and non-threatened species, as well as on species with decreasing and non-decreasing populations. Two-thirds of all primate species are classified as threatened (i.e., Critically Endangered, Endangered, and Vulnerable), with ~86% experiencing population declines, and ~84% impacted by domestic or international trade. We found that the expansion of PAST, HFP, CROP, and road infrastructure had the most direct negative effects on primate richness. In contrast, forested habitat within IPLs and PAs was positively associated in safeguarding primate species diversity globally, with an even stronger effect at the regional level. Our results show that IPLs and PAs play a critical role in primate species conservation, helping to prevent their extinction; in contrast, HFP growth and expansion has a dramatically negative effect on primate species worldwide. Our findings support predictions that the continued negative impact of anthropogenic pressures on natural habitats may lead to a significant decline in global primate species richness, and likely, species extirpations. We advocate for stronger national and international policy frameworks promoting alternative/sustainable livelihoods and reducing persistent anthropogenic pressures to help mitigate the extinction risk of the world's primate species.

Hunter-Gatherers in context: Mammal community composition in a northern Tanzania landscape used by Hadza foragers and Datoga pastoralists

In many regions of sub Saharan Africa large mammals occur in human-dominated areas, yet their community composition and abundance have rarely been described in areas occupied by traditional hunter-gatherers and pastoralists. Surveys of mammal populations in such areas provide important measures of biodiversity and provide ecological context for understanding hunting practices. Using a sampling grid centered on a Hadza hunter-gatherer camp and covering 36 km² of semi-arid savannah in northern Tanzania, we assessed mammals using camera traps (n = 19 stations) for c. 5 months (2,182 trap nights). In the study area (Tli’ika in the Hadza language), we recorded 36 wild mammal species. Rarefaction curves suggest that sampling effort was sufficient to capture mammal species richness, yet some species known to occur at low densities in the wider area (e.g. African lions, wildebeest) were not detected. Relative abundance indices of wildlife species varied by c. three orders of magnitude, from a mean of 0.04 (African wild dog) to 20.34 capture events per 100 trap-nights (Kirk’s dik dik). To contextualize the relative abundance of wildlife in the study area, we compared our study’s data to comparable camera trap data collected in a fully protected area of northern Tanzania with similar rainfall (Lake Manyara National Park). Raw data and negative binomial regression analyses show that wild herbivores and wild carnivores were generally detected in the national park at higher rates than in the Hadza-occupied region. Livestock were notably absent from the national park, but were detected at high levels in Tli’ika, and cattle was the second most frequently detected species in the Hadza-used area. We discuss how these data inform current conservation efforts, studies of Hadza hunting, and models of hunter-gatherer foraging ecology and diet.

Targeting Conservation Actions at Species Threat Response Thresholds

Given the failure of the world's governments to improve the status of biodiversity by 2020, a new strategic plan for 2030 is being developed. In order to be successful, a step-change is needed to not just simply halt biodiversity loss, but to bend the curve of biodiversity loss to stable or increasing species' populations. Here, we propose a framework that quantifies species' responses across gradients of threat intensity to implement more efficient and better targeted conservation actions. Our framework acknowledges the variation in threat intensities as well as the differences among species in their capacity to respond, and is implemented at a relevant scale for national and international policy-making.

Land-use conflicts between biodiversity conservation and extractive industries in the Peruvian Andes

The exceptional endemic species richness found in the Tropical Andes is being subjected to high rates of environmental degradation and natural resources exploitation. While many forms of land-cover change and other impacts on species are difficult to control through environmental regulations, governments usually determine how and where extractive industries can take place. This study examines potential conflict between the location of extractive industry activities and biodiversity conservation in the Peruvian Andes. Using geographic information systems, we carry out overlay analyses to determine the spatial congruence between mineral mining, hydrocarbon and logging concessions, on the one hand, and the distribution of protected areas and endemic vertebrate species on the other. The results show that regional protected areas extensively overlap with resource concessions. Furthermore, 16% of endemic species hotspots concur with current concessions, while the geographical distribution of 21 endemic vertebrate species overlap by more than 90% with concession areas. To reconcile conservation and economic development objectives in the future, the geographical distribution of biodiversity, and in particular of endemic species, needs to be considered in natural resources planning and land-use/management activities.

Conserving wildlife in a changing world: Understanding capture myopathy-a malignant outcome of stress during capture and translocation

The number of species that merit conservation interventions is increasing daily with ongoing habitat destruction, increased fragmentation and loss of population connectivity. Desertification and climate change reduce suitable conservation areas. Physiological stress is an inevitable part of the capture and translocation process of wild animals. Globally, capture myopathy-a malignant outcome of stress during capture operations-accounts for the highest number of deaths associated with wildlife translocation. These deaths may not only have considerable impacts on conservation efforts but also have direct and indirect financial implications. Such deaths usually are indicative of how well animal welfare was considered and addressed during a translocation exercise. Importantly, devastating consequences on the continued existence of threatened and endangered species succumbing to this known risk during capture and movement may result. Since first recorded in 1964 in Kenya, many cases of capture myopathy have been described, but the exact causes, pathophysiological mechanisms and treatment for this condition remain to be adequately studied and fully elucidated. Capture myopathy is a condition with marked morbidity and mortality that occur predominantly in wild animals around the globe. It arises from inflicted stress and physical exertion that would typically occur with prolonged or short intense pursuit, capture, restraint or transportation of wild animals. The condition carries a grave prognosis, and despite intensive extended and largely non-specific supportive treatment, the success rate is poor. Although not as common as in wildlife, domestic animals and humans are also affected by conditions with similar pathophysiology. This review aims to highlight the current state of knowledge related to the clinical and pathophysiological presentation, potential treatments, preventative measures and, importantly, the hypothetical causes and proposed pathomechanisms by comparing conditions found in domestic animals and humans. Future comparative strategies and research directions are proposed to help better understand the pathophysiology of capture myopathy.

Changes in human footprint drive changes in species extinction risk

Predicting how species respond to human pressure is essential to anticipate their decline and identify appropriate conservation strategies. Both human pressure and extinction risk change over time, but their inter-relationship is rarely considered in extinction risk modelling. Here we measure the relationship between the change in terrestrial human footprint (HFP)—representing cumulative human pressure on the environment—and the change in extinction risk of the world’s terrestrial mammals. We find the values of HFP across space, and its change over time, are significantly correlated to trends in species extinction risk, with higher predictive importance than environmental or life-history variables. The anthropogenic conversion of areas with low pressure values (HFP < 3 out of 50) is the most significant predictor of change in extinction risk, but there are biogeographical variations. Our framework, calibrated on past extinction risk trends, can be used to predict the impact of increasing human pressure on biodiversity.

Species extinction risk is difficult to measure and often lags behind the pace of increasing threats. Here, the authors demonstrate how monitoring changes in cumulative human pressures could be used to rapidly assess potential change in species’ conservation status.

Transcending data gaps: a framework to reduce inferential errors in ecological analyses

The analysis of functional diversity (FD) has gained increasing importance due to its generality and utility in ecology. In particular, patterns in the spatial distribution and temporal change of FD are being used to predict locations and functional groups that are immediately vulnerable to global changes. A major impediment to the accurate measurement of FD is the pervasiveness of missing data in trait datasets. While such prevalent data gaps can engender misleading inferences in FD analyses, we currently lack any practical guide to handle missing data in trait datasets. Here, we identify significant mismatches between true FD and values derived from datasets that contain missing data. We demonstrate that imputing missing data with a phylogeny-informed approach reduces the risk of misinterpretation of FD patterns, and provides baseline information against which central questions in ecology can be evaluated.

Geography of current and future global mammal extinction risk

Identifying which species are at greatest risk, what makes them vulnerable, and where they are distributed are central goals for conservation science. While knowledge of which factors influence extinction risk is increasingly available for some taxonomic groups, a deeper understanding of extinction correlates and the geography of risk remains lacking. Here, we develop a predictive random forest model using both geospatial and mammalian species' trait data to uncover the statistical and geographic distributions of extinction correlates. We also explore how this geography of risk may change under a rapidly warming climate. We found distinctive macroecological relationships between species-level risk and extinction correlates, including the intrinsic biological traits of geographic range size, body size and taxonomy, and extrinsic geographic settings such as seasonality, habitat type, land use and human population density. Each extinction correlate exhibited ranges of values that were especially associated with risk, and the importance of different risk factors was not geographically uniform across the globe. We also found that about 10% of mammals not currently recognized as at-risk have biological traits and occur in environments that predispose them towards extinction. Southeast Asia had the most actually and potentially threatened species, underscoring the urgent need for conservation in this region. Additionally, nearly 40% of currently threatened species were predicted to experience rapid climate change at 0.5 km/year or more. Biological and environmental correlates of mammalian extinction risk exhibit distinct statistical and geographic distributions. These results provide insight into species-level patterns and processes underlying geographic variation in extinction risk. They also offer guidance for future conservation research focused on specific geographic regions, or evaluating the degree to which species-level patterns mirror spatial variation in the pressures faced by populations within the ranges of individual species. The added impacts from climate change may increase the susceptibility of at-risk species to extinction and expand the regions where mammals are most vulnerable globally.

Quantification of habitat fragmentation reveals extinction risk in terrestrial mammals

Although habitat fragmentation is often assumed to be a primary driver of extinction, global patterns of fragmentation and its relationship to extinction risk have not been consistently quantified for any major animal taxon. We developed high-resolution habitat fragmentation models and used phylogenetic comparative methods to quantify the effects of habitat fragmentation on the world's terrestrial mammals, including 4,018 species across 26 taxonomic Orders. Results demonstrate that species with more fragmentation are at greater risk of extinction, even after accounting for the effects of key macroecological predictors, such as body size and geographic range size. Species with higher fragmentation had smaller ranges and a lower proportion of high-suitability habitat within their range, and most high-suitability habitat occurred outside of protected areas, further elevating extinction risk. Our models provide a quantitative evaluation of extinction risk assessments for species, allow for identification of emerging threats in species not classified as threatened, and provide maps of global hotspots of fragmentation for the world's terrestrial mammals. Quantification of habitat fragmentation will help guide threat assessment and strategic priorities for global mammal conservation.

Historical drivers of extinction risk: using past evidence to direct future monitoring

Global commitments to halt biodiversity decline mean that it is essential to monitor species' extinction risk. However, the work required to assess extinction risk is intensive. We demonstrate an alternative approach to monitoring extinction risk, based on the response of species to external conditions. Using retrospective International Union for Conservation of Nature Red List assessments, we classify transitions in the extinction risk of 497 mammalian carnivores and ungulates between 1975 and 2013. Species that moved to lower Red List categories, or remained Least Concern, were classified as 'lower risk'; species that stayed in a threatened category, or moved to a higher category of risk, were classified as 'higher risk'. Twenty-four predictor variables were used to predict transitions, including intrinsic traits (species biology) and external conditions (human pressure, distribution state and conservation interventions). The model correctly classified up to 90% of all transitions and revealed complex interactions between variables, such as protected areas (PAs) versus human impact. The most important predictors were: past extinction risk, PA extent, geographical range size, body size, taxonomic family and human impact. Our results suggest that monitoring a targeted set of metrics would efficiently identify species facing a higher risk, and could guide the allocation of resources between monitoring species' extinction risk and monitoring external conditions.

Scenarios of large mammal loss in Europe for the 21st century

Distributions and populations of large mammals are declining globally, leading to an increase in their extinction risk. We forecasted the distribution of extant European large mammals (17 carnivores and 10 ungulates) based on 2 Rio+20 scenarios of socioeconomic development: business as usual and reduced impact through changes in human consumption of natural resources. These scenarios are linked to scenarios of land-use change and climate change through the spatial allocation of land conversion up to 2050. We used a hierarchical framework to forecast the extent and distribution of mammal habitat based on species' habitat preferences (as described in the International Union for Conservation of Nature Red List database) within a suitable climatic space fitted to the species' current geographic range. We analyzed the geographic and taxonomic variation of habitat loss for large mammals and the potential effect of the reduced impact policy on loss mitigation. Averaging across scenarios, European large mammals were predicted to lose 10% of their habitat by 2050 (25% in the worst-case scenario). Predicted loss was much higher for species in northwestern Europe, where habitat is expected to be lost due to climate and land-use change. Change in human consumption patterns was predicted to substantially improve the conservation of habitat for European large mammals, but not enough to reduce extinction risk if species cannot adapt locally to climate change or disperse.

Human pressures predict species' geographic range size better than biological traits

Geographic range size is the manifestation of complex interactions between intrinsic species traits and extrinsic environmental conditions. It is also a fundamental ecological attribute of species and a key extinction risk correlate. Past research has primarily focused on the role of biological and environmental predictors of range size, but macroecological patterns can also be distorted by human activities. Here, we analyse the role of extrinsic (biogeography, habitat state, climate, human pressure) and intrinsic (biology) variables in predicting range size of the world's terrestrial mammals. In particular, our aim is to compare the predictive ability of human pressure vs. species biology. We evaluated the ability of 19 intrinsic and extrinsic variables in predicting range size for 4867 terrestrial mammals. We repeated the analyses after excluding restricted-range species and performed separate analyses for species in different biogeographic realms and taxonomic groups. Our model had high predictive ability and showed that climatic variables and human pressures are the most influential predictors of range size. Interestingly, human pressures predict current geographic range size better than biological traits. These findings were confirmed when repeating the analyses on large-ranged species, individual biogeographic regions and individual taxonomic groups. Climatic and human impacts have determined the extinction of mammal species in the past and are the main factors shaping the present distribution of mammals. These factors also affect other vertebrate groups globally, and their influence on range size may be similar as well. Measuring climatic and human variables can allow to obtain approximate range size estimations for data-deficient and newly discovered species (e.g. hundreds of mammal species worldwide). Our results support the need for a more careful consideration of the role of climate change and human impact - as opposed to species biological characteristics - in shaping species distribution ranges.

Association of extinction risk of saproxylic beetles with ecological degradation of forests in Europe

To reduce future loss of biodiversity and to allocate conservation funds effectively, the major drivers behind large-scale extinction processes must be identified. A promising approach is to link the red-list status of species and specific traits that connect species of functionally important taxa or guilds to resources they rely on. Such traits can be used to detect the influence of anthropogenic ecosystem changes and conservation efforts on species, which allows for practical recommendations for conservation. We modeled the German Red List categories as an ordinal index of extinction risk of 1025 saproxylic beetles with a proportional-odds linear mixed-effects model for ordered categorical responses. In this model, we estimated fixed effects for intrinsic traits characterizing species biology, required resources, and distribution with phylogenetically correlated random intercepts. The model also allowed predictions of extinction risk for species with no red-list category. Our model revealed a higher extinction risk for lowland and large species as well as for species that rely on wood of large diameter, broad-leaved trees, or open canopy. These results mirror well the ecological degradation of European forests over the last centuries caused by modern forestry, that is the conversion of natural broad-leaved forests to dense conifer-dominated forests and the loss of old growth and dead wood. Therefore, conservation activities aimed at saproxylic beetles in all types of forests in Central and Western Europe should focus on lowlands, and habitat management of forest stands should aim at increasing the amount of dead wood of large diameter, dead wood of broad-leaved trees, and dead wood in sunny areas.

Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

Protected areas in tropical Africa: assessing threats and conservation activities

Numerous protected areas (PAs) have been created in Africa to safeguard wildlife and other natural resources. However, significant threats from anthropogenic activities and decline of wildlife populations persist, while conservation efforts in most PAs are still minimal. We assessed the impact level of the most common threats to wildlife within PAs in tropical Africa and the relationship of conservation activities with threat impact level. We collated data on 98 PAs with tropical forest cover from 15 countries across West, Central and East Africa. For this, we assembled information about local threats as well as conservation activities from published and unpublished literature, and questionnaires sent to long-term field workers. We constructed general linear models to test the significance of specific conservation activities in relation to the threat impact level. Subsistence and commercial hunting were identified as the most common direct threats to wildlife and found to be most prevalent in West and Central Africa. Agriculture and logging represented the most common indirect threats, and were most prevalent in West Africa. We found that the long-term presence of conservation activities (such as law enforcement, research and tourism) was associated with lower threat impact levels. Our results highlight deficiencies in the management effectiveness of several PAs across tropical Africa, and conclude that PA management should invest more into conservation activities with long-term duration.

Migratory herbivorous waterfowl track satellite-derived green wave index

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

Local scale comparisons of biodiversity as a test for global protected area ecological performance: a meta-analysis

Terrestrial protected areas (PAs) are cornerstones of global biodiversity conservation. Their efficacy in terms of maintaining biodiversity is, however, much debated. Studies to date have been unable to provide a general answer as to PA conservation efficacy because of their typically restricted geographic and/or taxonomic focus, or qualitative approaches focusing on proxies for biodiversity, such as deforestation. Given the rarity of historical data to enable comparisons of biodiversity before/after PA establishment, many smaller scale studies over the past 30 years have directly compared biodiversity inside PAs to that of surrounding areas, which provides one measure of PA ecological performance. Here we use a meta-analysis of such studies (N = 86) to test if PAs contain higher biodiversity values than surrounding areas, and so assess their contribution to determining PA efficacy. We find that PAs generally have higher abundances of individual species, higher assemblage abundances, and higher species richness values compared with alternative land uses. Local scale studies in combination thus show that PAs retain more biodiversity than alternative land use areas. Nonetheless, much variation is present in the effect sizes, which underscores the context-specificity of PA efficacy.

Satellite remote sensing, biodiversity research and conservation of the future

Assessing and predicting ecosystem responses to global environmental change and its impacts on human well-being are high priority targets for the scientific community. The potential for synergies between remote sensing science and ecology, especially satellite remote sensing and conservation biology, has been highlighted by many in the past. Yet, the two research communities have only recently begun to coordinate their agendas. Such synchronization is the key to improving the potential for satellite data effectively to support future environmental management decision-making processes. With this themed issue, we aim to illustrate how integrating remote sensing into ecological research promotes a better understanding of the mechanisms shaping current changes in biodiversity patterns and improves conservation efforts. Added benefits include fostering innovation, generating new research directions in both disciplines and the development of new satellite remote sensing products.

Role of African protected areas in maintaining connectivity for large mammals

The African protected area (PA) network has the potential to act as a set of functionally interconnected patches that conserve meta-populations of mammal species, but individual PAs are vulnerable to habitat change which may disrupt connectivity and increase extinction risk. Individual PAs have different roles in maintaining connectivity, depending on their size and location. We measured their contribution to network connectivity (irreplaceability) for carnivores and ungulates and combined it with a measure of vulnerability based on a 30-year trend in remotely sensed vegetation cover (Normalized Difference Vegetation Index). Highly irreplaceable PAs occurred mainly in southern and eastern Africa. Vegetation cover change was generally faster outside than inside PAs and particularly so in southern Africa. The extent of change increased with the distance from PAs. About 5% of highly irreplaceable PAs experienced a faster vegetation cover loss than their surroundings, thus requiring particular conservation attention. Our analysis identified PAs at risk whose isolation would disrupt the connectivity of the PA network for large mammals. This is an example of how ecological spatial modelling can be combined with large-scale remote sensing data to investigate how land cover change may affect ecological processes and species conservation.