Theodore Roosevelt

Global warming significantly impacts amphibian populations globally, and modeling helps understand these effects. Here, we used MaxEnt and MigClim models to predict the impact of climate change on habitat suitability for Hoplobatrachus chinensis. Our results indicate that temperature is a key factor affecting H. chinensis distribution. Increasing temperatures positively correlated with habitat suitability, with suitable habitat expanding northward by 2060 while maintaining suitability in the southern parts of the range. We found a 25.18% overlap between the current potential suitable habitat of H. chinensis and agricultural wetlands. Our model indicated that H. chinensis might be able to track shifts in suitable habitats under climate change given a 15 km dispersal ability per generation. Climate change will likely expand suitable habitat for H. chinensis. Our predictions offer important guidance for the conservation of the species, especially for the integrated role of natural and agricultural wetlands such as rice paddies.

Since the confirmation of African swine fever (ASF) in South Korea in 2019, its spread, predominantly in wild boars, has been a significant concern. A key factor in this situation is the lack of identification of risk factors by surveillance bias. The unique orography, characterized by high mountains, complicates search efforts, leading to overlooked or delayed case detection and posing risks to the swine industry. Additionally, shared rivers with neighboring country present a continual threat of virus entry. This study employs geospatial analysis and statistical methods to 1) identify areas at high risk of ASF occurrence but possibly under-surveilled, and 2) indicate strategic surveillance points for monitoring the risk of ASF virus entry through water bodies and basin influences. Pearson’s rho test indicated that elevation (rho = -0.908, p-value < 0.001) and distance from roads (rho = -0.979, p-value < 0.001) may have a significant impact on limiting surveillance activities. A map of potential under-surveilled areas was created considering these results and was validated by a chi-square goodness-of-fit test (X-square = 208.03, df = 1, p-value < 0.001). The strong negative correlation (rho = -0.997, p-value <0.001) between ASF-positive wild boars and distance from water sources emphasizes that areas surrounding rivers are one of the priority areas for monitoring. The subsequent hydrological analyses provided important points for monitoring the risk of virus entry via water from the neighboring country. This research aims to facilitate early detection and prevent further spread of ASF.

Context Shifts in climate and land use have dramatically reshaped ecosystems, impacting the distribution and status of wildlife populations. For many species, data gaps limit inference regarding population trends and links to environmental change. This deficiency hinders our ability to enact meaningful conservation measures to protect at risk species. Objectives We investigated historical drivers of environmental niche change for three North American weasel species (American ermine, least weasel, and long-tailed weasel) to understand their response to environmental change. Methods Using species occurrence records and corresponding environmental data, we developed species-specific environmental niche models for the contiguous United States (1938–2021). We generated annual hindcasted predictions of the species’ environmental niche, assessing changes in distribution, area, and fragmentation in response to environmental change. Results We identified a 54% decline in suitable habitat alongside high levels of fragmentation for least weasels and region-specific trends for American ermine and long-tailed weasels; declines in the West and increased suitability in the East. Climate and land use were important predictors of the environmental niche for all species. Changes in habitat amount and distribution reflected widespread land use changes over the past century while declines in southern and low-elevation areas are consistent with impacts from climatic change. Conclusions Our models uncovered land use and climatic change as potential historic drivers of population change for North American weasels and provide a basis for management recommendations and targeted survey efforts. We identified potentially at-risk populations and a need for landscape-level planning to support weasel populations amid ongoing environmental changes.

Assessing niche evolution remains an open question and an actively developing area of study. The family Ursidae consists of eight extant species for which, despite being the most studied family of carnivores, little is known about the influence of climate on their evolutionary history and diversification. We evaluated their evolutionary patterns based on a combined phylogeography and niche modeling approach. We used complete mitogenomes, estimated divergence times, generated ecological niche models and applied a phyloclimatic model to determine the species evolutionary and diversification patterns associated with their respective environmental niches. We inferred the family evolutionary path along the environmental conditions of maximum temperature and minimum precipitation, from around 20 million years ago to the present. Our findings show that the phyloclimatic niches of the bear species occupy most of the environmental space available on the planet, except for the most extreme warm conditions, in accordance with the wide geographic distribution of Ursidae. Moreover, some species exhibit broader environmental niches than others, and in some cases, they explore precipitation axes more extensively than temperature axes or vice versa, suggesting that not all species are equally adaptable to these variables. We were able to elucidate potential patterns of niche conservatism and evolution, as well as niche overlapping, suggesting interspecific competitive exclusion between some of the bear species. We present valuable insights into the ecological and evolutionary processes driving the diversification and distribution of the Ursidae. Our approach also provides essential information for guiding effective conservation strategies, particularly in terms of distribution limits in the face of climate change.

Climate change is a potential human-induced threat to rhino populations and their habitat. Information on the effects of climate change on rhinoceros species can help manage and develop conservation plans to adapt to these changes. In this study, two climate change scenarios were used to predict temperature and precipitation changes in national parks in southern Africa and the effect those changes would have on black (Diceros bicornis) and white (Ceratotherium simum) rhinoceros populations. The study used the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) 4.5 and 8.5, atmospheric CO2 concentrations of 650 and 1370 ppm, for the years 2055 and 2085 to explore the temperature and precipitation changes. All spatial information was processed using Geographic Information Systems and statistical analysis. Results show the changing climate will have significant negative impacts on the probability of occurrence of both species. Temperature changes will affect these probabilities more than precipitation changes. All study parks will have zero probability of occurrence for the species throughout their ranges should conditions reach those represented by the RCP 8.5 scenario late in the century. Conservation activities for the rhinoceros should take into consideration the potential for temperature and precipitation changes modelled in this study.

Climate change is one of the main threats to biodiversity in the 21st century. However, the effects that it may have on different mammal species are unknown, making it difficult to implement conservation strategies. In this paper, we used species distribution models (SDM) to assess the effect of global climate change on the potential distribution of the 8 of the 9 marsupial species in Mexico, and analyzed their distribution in the current system of natural protected areas (NPAs). We used presence records for each species and bioclimatic variables from the present and the future (2050 and 2080) with 2 contrasting possible scenarios (representative concentration pathways RCP 4.5 and 8.5). We found that Tlacuatzin canescens would have the most stable potential range under any climate change scenario, while the remaining species (Caluromys derbianus, Chironectes minimus, Didelphis marsupialis, D. virginiana, Philander opossum, Marmosa mexicana, and Metachirus nudicaudatus) would undergo notable range losses in the future, though there would not only be losses—according to our SDMs, for all species there would be some range gain under the different climate scenarios, assuming the vegetation cover remained. The current system of NPAs in Mexico currently protects and under the 2 future scenarios would protect less than 20% of the potential range of marsupials, so a reevaluation of their areas beyond the NPAs is highly recommended for the long-term conservation of this group. Our results provide relevant information on the estimated effects of global climate change on marsupials, allowing us to design more effective methodologies for the protection of this portion of the mammalian fauna in Mexico.

Background Carnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future? Methods We evaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios. Results The SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness.

Background Range maps are a useful tool to describe the spatial distribution of species. However, they need to be used with caution, as they essentially represent a rough approximation of a species’ suitable habitats. When stacked together, the resulting communities in each grid cell may not always be realistic, especially when species interactions are taken into account. Here we show the extent of the mismatch between range maps, provided by the International Union for Conservation of Nature (IUCN), and species interactions data. More precisely, we show that local networks built from those stacked range maps often yield unrealistic communities, where species of higher trophic levels are completely disconnected from primary producers. Methodology We used the well-described Serengeti food web of mammals and plants as our case study, and identify areas of data mismatch within predators’ range maps by taking into account food web structure. We then used occurrence data from the Global Biodiversity Information Facility (GBIF) to investigate where data is most lacking. Results We found that most predator ranges comprised large areas without any overlapping distribution of their prey. However, many of these areas contained GBIF occurrences of the predator. Conclusions Our results suggest that the mismatch between both data sources could be due either to the lack of information about ecological interactions or the geographical occurrence of prey. We finally discuss general guidelines to help identify defective data among distributions and interactions data, and we recommend this method as a valuable way to assess whether the occurrence data that are being used, even if incomplete, are ecologically accurate.

Sloths and anteaters form the monophyletic order Pilosa, which is currently represented by only 16 extant species distributed exclusively in the Neotropics. This present‐day low species richness is an inheritance of the Pleistocene megafaunal extinctions, where over 65 Pilosa species known from the fossil record went extinct. The large number of species lost in the recent past suggests that this group is greatly vulnerable to extinction. Here, we propose long‐term priority conservation areas for the order Pilosa, considering different future climate change scenarios, biotic stability, and the multiple dimensions of the group's biodiversity, such as species richness, species endemism, and phylogenetic diversity. Projections of species distribution for future scenarios show increased fragmentation and clear habitat loss as the Amazon Forest is replaced by savanna‐like habitats. Conservation solutions were highly congruent for the different dimensions of biodiversity, with priority areas emerging mainly in the Atlantic Forest, Amazonian wetlands, highlands of Ecuador, and the Central American isthmus. Expanding the currently protected areas network by 6% with the proposed priority areas, independently of which future climatic scenario is considered, can increase sloths and anteaters' coverage in the future by 12%. As a group of high phylogenetic and ecological importance, future conservation planning should deliberately aim to protect areas favorable to Pilosa, especially given the current scenario of environmental dismantling and neglect of critical Neotropical biomes.

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.