Climate change impacts on altitudinal movements of society large mammals in the Alborz

This study examines the impact of climate change on the altitudinal movement patterns and number of individuals of four large mammal species within the Central Alborz Protected Area (CAPA) region of the Alborz Mountains, a biodiversity hotspot, over a 23-year period (1999 to 2022). During the warm season (May 25-September 29), temperatures were reported to have increased by 2-2.5 °C, while relative humidity was observed to have decreased by 4-4.5%. Compared to the past two decades (2000-2022), Caspian red deer were observed to initiate their annual high-altitude migrations 15-20 days earlier, with the number of individuals in the summer range increasing more than threefold. Wild goats also migrated earlier, with peak arrivals increasing from 20-36 (1999-2003) to 36-57 (2018-2022) between May 25 and May 31, highlighting temperature as the primary driver of herbivore movement. In contrast, brown bears exhibited more subtle altitudinal movement, likely influenced by both temperature and humidity. Wild boars, with an approximate 40% increase in the number of individuals, tended to return to lower elevations earlier than in previous years (1999-2003). These patterns highlight the role of climate as a significant regulator of movement ecology, influencing high-altitude habitat use. However, human-induced barriers, such as roads and settlements, present additional threats to these seasonal migrations. This underscores the urgent need for adaptive management strategies, including the protection of movement corridors, the expansion of core zones, and enhanced community engagement, to support the resilience of these species under changing climatic conditions.

Understanding Multi-Scale and Multi-Species Habitat Selection by Mammals in the Eastern Himalayan Biodiversity Hotspot

Human-induced habitat loss and fragmentation threaten biodiversity in the Eastern Himalayas, a crucial part of the Indo-Myanmar biodiversity hotspot. This study examines the distribution of 10 mammal species in Arunachal Pradesh using a multi-scale ensemble modeling approach, integrating Generalized Linear Models (GLM), Generalized Additive Models (GAM), and MaxEnt to assess habitat suitability. By analyzing 57 environmental predictor variables across multiple spatial scales, we found that elevation is a key determinant for carnivores such as the dhole and the Asiatic golden cat, while herbivores like the northern red muntjac and the mainland serow prefer broadleaf forests. Species distributions showed distinct patterns, with most carnivores concentrated in the south, except for the widely distributed yellow-throated marten. Dhole and leopard cat preferred elevated broadleaf forests, while the Asiatic golden cat favored mixed forests. Herbivores like the northern red muntjac and mainland serow were found at higher elevations, whereas the Indian wild pig preferred grasslands and degraded habitats near human settlements. While protected areas (PAs) exhibited higher species richness, significant suitable habitats also exist outside these regions, underscoring the need for landscape-level conservation strategies. Precipitation seasonality and human population density emerged as significant predictors, highlighting the influence of climatic and anthropogenic factors on habitat suitability. Our findings emphasize the necessity of conserving large, connected landscapes to mitigate human-induced pressures and climate change impacts on these species. By combining spatial modeling with ecological insights, this study provides a framework for prioritizing conservation efforts. Future research should expand data collection across broader temporal and geographic scales and incorporate climate change projections to anticipate species distribution shifts. These findings are critical for guiding effective conservation planning and habitat management in this ecologically rich yet vulnerable region.

Impacts of Climate-Land Dynamics on Global Population and Sub-Populations of a Desert Equid

Climate change and escalating land-use transformations pose a significant threat to global biodiversity by disrupting natural habitats. The Asiatic wild ass (Equus hemionus), a near-threatened species, faces various pressures across its Asian range. This study employs a niche modeling approach to assess suitable habitats for the Asiatic wild ass at both the global population and sub-population levels. The analysis integrates the impacts of climate scenarios and land use change across three temporal periods: past, present, and future. To investigate the uncertainty of climate models for the Asiatic wild ass habitat, we used two climate models, CMIP5 and CMIP6, at both global and sub-population levels. Niche overlap models were developed to examine patterns of niche similarity among sub-populations. The results demonstrate a severe decline in both suitable habitat area and the number of viable patches for all sub-populations. Projections reveal that the Mongolian wild ass and Indian wild ass endure the highest levels of isolation and habitat loss, alongside the extinct Syrian wild ass. Sub-population models often predict larger distributions compared to global population models using the same inputs. The outputs of the models indicate a severe decline in suitable habitat, underscoring the necessity of accounting for both ecological and conservation perspectives to understand species distribution dynamics. Our study highlights the need to consider both global population and sub-population levels in climate change assessments. These models provide essential guidance for conservation strategies by identifying suitable habitats and sites for reintroduction. Identifying habitat patches as refuges for large herbivores amidst land-use changes and climate fluctuations is crucial. Incorporating these patches into conservation planning is imperative for preserving biodiversity.

N-mixture models with camera trap imagery produce accurate abundance estimates of ungulates

Abundance estimates inform ungulate management and recovery efforts. Yet effective and affordable estimation techniques remain absent for most ungulates lacking identifiable marks and inhabiting rugged or highly vegetated terrain. Methods using N-mixture models with camera trap imagery form an appealing solution but remain unvalidated. We assess this method using populations of desert bighorn sheep (DBS; Ovis canadensis) in New Mexico, USA, plus bison (Bison bison bison) and Texas longhorn cattle (Bos taurus taurus) in Oklahoma, USA, by calculating and comparing abundance estimates to censused values. We parsed data by 3 and 7-day intervals, using images filtered or unfiltered, and collected with motion detection or timed camera settings. We employed priors informed by subject matter experts (SME) and calculated using detection-nondetection methods. Abundance estimates from filtered images captured by motion detection in 3-day intervals included the censused value across all seasons for adult DBS, rams and ewes, indicating "best practices". This "best practices" method also captured censused values for population estimates of bison (detection-nondetection) and cattle with both priors. Our assessment validates the use of N-mixture with camera trap imagery, while presenting sampling approaches, data handling procedures and model calibration to estimate wildlife population sizes more appropriately and accurately.

Climate change extinctions

Climate change is expected to cause irreversible changes to biodiversity, but predicting those risks remains uncertain. I synthesized 485 studies and more than 5 million projections to produce a quantitative global assessment of climate change extinctions. With increased certainty, this meta-analysis suggests that extinctions will accelerate rapidly if global temperatures exceed 1.5°C. The highest-emission scenario would threaten approximately one-third of species, globally. Amphibians; species from mountain, island, and freshwater ecosystems; and species inhabiting South America, Australia, and New Zealand face the greatest threats. In line with predictions, climate change has contributed to an increasing proportion of observed global extinctions since 1970. Besides limiting greenhouse gases, pinpointing which species to protect first will be critical for preserving biodiversity until anthropogenic climate change is halted and reversed.

Should I stay or move? Quantifying landscape of fear to enhance environmental management of road networks in a highly transformed landscape

The development and expansion of road networks pose considerable threats to natural habitats and wildlife, fostering a landscape of fear. In addition to direct mortality caused by road collisions, road construction and maintenance often result in habitat fragmentation and loss, impeding animal movement and gene flow between populations. Mountain ungulates are already confined to fragmented habitat patches and roads can cause substantial disturbances to their critical ecological processes, such as dispersal and migration. In this study, we employed two key mountain ungulates, the wild goat (Capra aegagrus) and mouflon (Ovis gmelini), as functional models to examine how road networks impact the quantity and connectivity of natural habitats in southwestern Iran, where extensive road construction has led to significant landscape changes. We used the MaxEnt method to predict species distribution, the circuit theory to evaluate habitat connectivity, and the Spatial Road Disturbance Index (SPROADI) to assess road impacts. During the modeling process, we selected eleven important variables and employed a model parametrization strategy to identify the optimal configuration for the MaxEnt model. For SPROADI index we used three sub-indices, including traffic intensity, vicinity impact, and fragmentation grade. We then integrated the results of these analyses to identify areas with the most significant environmental impacts of roads on the coherency of the natural habitats. The findings indicate that suitable habitats for wild goats are widely distributed across the study area, while suitable habitats for mouflon are primarily concentrated in the northeastern region. Conservation gap analysis revealed that only 8% of wild goat habitats and 7% of mouflon habitats are covered by protected areas (PAs). The SPROADI map highlighted that 23% of the study area is negatively influenced by road networks. Moreover, 30.4% of highest-probability corridors for mouflon, and 25.7% for wild goat, were highly vulnerable to the impacts of roads. Our combined approach enabled us to quantitatively assess species-specific vulnerability to the impacts of heavy road networks. This study emphasizes the urgent need to address the negative effects of road networks on wildlife habitats and connectivity corridors. Our approach effectively identifies sensitive areas, which can help inform mitigation strategies and support more effective conservation planning in significantly transformed landscapes.

Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China

The South China tiger (Panthera tigris amoyensis) is a tiger subspecies unique to China and one of the top ten endangered species in the world. It used to play an important role in the overall function of the ecosystem. This study rationally screened out key prey species of the South China tiger-the Chinese serow, Chinese goral, tufted deer, water deer, Chinese muntjac, red muntjac, sambar deer, and wild boar. Candidate sites for the rewilding and reintroduction of the South China tiger were derived by exploring changes in suitable habitats for the prey using the MaxEnt model. The results show that: (1) by 2070, except for the high-suitability areas of water deer and Chinese muntjac, the areas of suitable habitats for the other six prey species would all have decreased significantly; (2) the location of the high-suitability area of the South China tiger obtained by superimposing the suitable areas of the eight prey species would be almost stable in 2050 and 2070, but the habitat index of some high- and medium-suitability areas would decrease and turn into low-suitability areas; (3) the core candidate sites were 83,415 km2 in total, of which 25,630 km2 overlapped with existing protected areas, accounting for 30.7% of the core candidate sites, and the remaining 69.3% of the core candidate sites were mostly distributed around the protected areas; (4) the maximum core candidate site area was projected to be 10,000 km2 by 2070, which could support a small population of 23 male tigers and 66 female tigers to survive and reproduce in the wild. This study revealed the core candidate sites for the rewilding of South China tigers and estimated the number of tigers that could be reintroduced to these areas, providing a preliminary research basis for promoting the rewilding of South China tigers in China.

Mapping climate adaptation corridors for biodiversity-A regional-scale case study in Central America

Climate adaptation corridors are widely recognized as important for promoting biodiversity resilience under climate change. Central America is part of the Mesoamerican biodiversity hotspot, but there have been no regional-scale analyses of potential climate adaptation corridors in Central America. We identified 2375 potential corridors throughout Central America that link lowland protected areas (≤ 500 m) with intact, high-elevation forests (≥ 1500 m) that represent potential climate change refugia. Whereas we found potential corridors in all Central American countries, potential corridors in Panama, Belize, and Honduras were most protected (medians = 64%, 49%, and 47%, respectively) and potential corridors in El Salvador were least protected (median = 10%). We also developed a corridor priority index based on the ecological characteristics and protected status of potential corridors and their associated start and end points. Compared to low- and medium-priority corridors, high-priority corridors (n = 160; top 7% of all corridors) were generally more protected, forested, and distributed across wider elevational gradients and more Key Biodiversity Areas, but also generally linked larger lowland protected areas to target areas that were larger, more protected, and spanned wider elevational gradients. For example, based on median values, high-priority corridors were 9% more protected and overlapped with 2-3 more Key Biodiversity Areas than low- and medium-priority corridors. Although high-elevation targets spanned considerably wider elevational gradients than lowland protected areas (medians = 695 vs. 142 m, respectively) and thus may be more likely to support refugia, they were considerably smaller than lowland protected areas (medians = 11 vs. 50 km2 respectively) and mostly unprotected (median = 4% protection). This initial, regional assessment can help prioritize locations for finer-scale research, conservation, and restoration activities in support of climate adaptation corridors throughout Central America and highlights the need for greater conservation of potential high-elevation refugia.

Variable intraspecific response to climate change in a medicinally important African tree species, Vachellia sieberiana (DC.) (paperbark thorn)

Climate change is predicted to disproportionately impact sub-Saharan Africa, with potential devastating consequences on plant populations. Climate change may, however, impact intraspecific taxa differently. The aim of the study was to determine the current distribution and impact of climate change on three varieties of Vachellia sieberiana, that is, var. sieberiana, var. villosa and var. woodii. Ensemble species distribution models (SDMs) were built in "biomod2" using 66, 45, and 137 occurrence records for var. sieberiana, var. villosa, and var. woodii, respectively. The ensemble SDMs were projected to 2041-2060 and 2081-2100 under three general circulation models (GCMs) and two shared socioeconomic pathways (SSPs). The three GCMs were the Canadian Earth System Model version 5, the Institut Pierre-Simon Laplace Climate Model version 6A Low Resolution, and the Model for Interdisciplinary Research on Climate version 6. The suitable habitat of var. sieberiana predominantly occurs in the Sudanian and Zambezian phytochoria while that of var. villosa largely occurs in the Sudanian phytochorion. The suitable habitat of var. woodii mainly occurs in the Zambezian phyotochorion. There is coexistence of var. villosa and var. sieberiana in the Sudanian phytochorion while var. sieberiana and var. woodii coexist in the Zambezian phytochorion. Under SSP2-4.5 in 2041-2060 and averaged across the three GCMs, the suitable habitat expanded by 33.8% and 119.7% for var. sieberiana and var. villosa, respectively. In contrast, the suitable habitat of var. woodii contracted by -8.4%. Similar trends were observed in 2041-2060 under SSP5-8.5 [var. sieberiana (38.6%), var. villosa (139.0%), and var. woodii (-10.4%)], in 2081-2100 under SSP2-4.5 [var. sieberiana (4.6%), var. villosa (153.4%), and var. woodii (-14.4%)], and in 2081-2100 under SSP5-8.5 [var. sieberiana (49.3%), var. villosa (233.4%), and var. woodii (-30.7%)]. Different responses to climate change call for unique management and conservation decisions for the varieties.

Predicting current and future habitat of Indian pangolin (Manis crassicaudata) under climate change

Climate change is among the greatest drivers of biodiversity loss, threatening up to 15-30% of described species by the end of the twenty-first century. We estimated the current suitable habitat and forecasted future distribution ranges of Indian pangolin (Manis crassicaudata) under climate change scenarios. We collected occurrence records of Indian pangolin using burrow counts, remote camera records and previously published literature in Pakistan during 2021-2023. We downloaded bioclimatic data for current (1970-2000) and future (2041-2060, 2061-2080, 2081-2100) climate scenarios from the WorldClim database using the Hadley Global Environment Model (HadGEM3-GC31-LL). We used MaxEnt software to predict current and future distributions of Indian pangolin, then computed the amount of habitat lost, gained, and unchanged across periods. We obtained 560 Indian pangolin occurrences overall, 175 during the study, and 385 from our literature search. Model accuracy was very good (AUC = 0.885, TSS = 0.695), and jackknife tests of variable importance showed that the contribution of annual mean temperature (bio1) was greatest (33.4%), followed by the mean temperature of the coldest quarter (bio-12, 29.3%), temperature seasonality (bio 4, 25.9%), and precipitation seasonality (bio 15, 11.5%). The maxent model predicted that during the current time period (1970-2000) highly suitable habitat for Indian pangolin was (7270 km2, 2.2%), followed by moderately suitable (12,418 km2, 3.7%), less suitable (49,846 km2, 14.8%), and unsuitable habitat (268,355 km2, 79.4%). Highly suitable habitat decreased in the western part of the study area under most SSPs and in the central parts it declined under all SSPs and in future time periods. The predicted loss in the suitable habitat of the Indian pangolin was greatest (26.97%) under SSP 585 followed by SSP 126 (23.67%) during the time 2061-2080. The gain in suitable habitat of Indian pangolin was less than that of losses on average which ranged between 1.91 and 13.11% under all SSPs during all time periods. While the stable habitat of the Indian pangolin ranged between 64.60 and 83.85% under all SSPs during all time periods. Our study provides the current and future habitat ranges of Indian pangolin in the face of a changing climate. The findings of our study could be helpful for policymakers to set up conservation strategies for Indian pangolin in Pakistan.

Modeling climate change impacts on the distribution of an endangered brown bear population in its critical habitat in Iran

Climate change is one of the major challenges to the current conservation of biodiversity. Here, by using the brown bear, Ursus arctos, in the southernmost limit of its global distribution as a model species, we assessed the impact of climate change on the species distribution in western Iran. The mountainous forests of Iran are inhabited by small and isolated populations of brown bears that are prone to extinction in the near future. We modeled the potential impact of climate change on brown bear distribution and habitat connectivity by the years 2050 and 2070 under four representative concentration pathways (RCPs) of two general circulation models (GCMs): BCC-CSM1-1 and MRI-CGCM3. Our projections revealed that the current species' range, which encompasses 6749.8 km² (40.8%) of the landscape, will decline by 10% (2050: RCP2.6, MRI-CGCM3) to 45% (2070: RCP8.5, BCC-CSM1-1). About 1850 km² (27.4%) of the current range is covered by a network of conservation (CAs) and no-hunting (NHAs) areas which are predicted to decline by 0.64% (2050: RCP2.6, MRI-CGCM3) to 15.56% (2070: RCP8.5, BCC-CSM1-1) due to climate change. The loss of suitable habitats falling within the network of CAs and NHAs is a conservation challenge for brown bears because it may lead to bears moving outside the CAs and NHAs and result in subsequent increases in the levels of bear-human conflict. Thus, re-evaluation of the network of CAs and NHAs, establishing more protected areas in suitable landscapes, and conserving vital linkages between habitat patches under future climate change scenarios are crucial strategies to conserve and manage endangered populations of the brown bear.

Assessing Asiatic cheetah’s individual diet using metabarcoding and its implication for conservation

Knowledge on diet composition allows defining well-targeted conservation measures of large carnivores. Little is known about ecology of critically endangered Asiatic cheetah, especially the overall diet and its possible regional differences. We used cheetah scats, metabarcoding technique and microsatellite markers to assess the individual and overall diet composition of the species across its entire range in Asia. Cheetahs were primarily predating on mouflon; following by ibex, cape hare and goitered gazelle. Despite their high availability, small-sized livestock was never detected. Goitered gazelles were only detected in an area where the habitat is mainly flatlands. In hilly areas, mouflon was the most frequent prey item taken. Ibex was typically taken in rugged terrain, but mouflon was still the most frequently consumed item in these habitats. High consumption of mouflon in comparison to goitered gazelle suggests that human pressure on lowland habitats has possibly forced Asiatic cheetahs to occupy suboptimal habitats where gazelles are less abundant. The protection of flatlands and the removal of livestock from them are needed to ensure the long-term survival of Asiatic cheetah. The laboratory and bioinformatics pipelines used in this study are replicable and can be used to address similar questions in other threatened carnivores.

Embryo production by in vitro fertilization in wild ungulates: progress and perspectives

Wild ungulates are of fundamental importance for balancing ecosystems, as well as being the species of economic interest. Increasing concern over the accelerated population reduction of these species has resulted in the development of assisted reproduction techniques, such as in vitro fertilization (IVF), as a tool for conservation and multiplication. In the present scenario, IVF protocols were developed based on the methodologies used for domestic ungulates. Nevertheless, owing to the physiological and reproductive differences among the species, several factors associated with IVF and its relationship with the characteristics of the species of interest require clarification. In vitro conditions for the collection and selection of female and male gametes, oocyte maturation, sperm capacitation, co-incubation of gametes, and embryonic development can influence IVF results. Therefore, the present review considers the main advances in the methodologies already used for wild ungulates, emphasizing the strategies for improving the protocols to obtain better efficiency rates. Additionally, we discuss the conditions of each IVF stage, with emphasis on aspects related to in vitro manipulation and comparability with the protocols for domestic ungulates.

Habitat Connectivity for the Conservation of Small Ungulates in A Human-Dominated Landscape

Conserving landscape connections among favorable habitats is a widely used strategy to maintain populations in an increasingly fragmented world. A species can then exist as a metapopulation consisting of several subpopulations connected by dispersal. Our study focuses on the importance of human–wildlife coexistence areas in maintaining connectivity among primary habitats of small ungulates within and outside protected areas in a large landscape in central India. We used geospatial information and species presence data to model the suitable habitats, core habitats, and connectivity corridors for four antelope species in an ~89,000 km2 landscape. We found that about 63% of the core habitats, integrated across the four species, lie outside the protected areas. We then measured connectivity in two scenarios: the present setting, and a hypothetical future setting—where habitats outside protected areas are lost. We also modelled the areas with a high risk of human-influenced antelope mortality using eco-geographical variables and wildlife mortality records. Overall, we found that the habitats in multiple-use forests play a central role in maintaining the connectivity network for antelopes. Sizable expanses of privately held farmlands and plantations also contribute to the essential movement corridors. Some perilous patches with greater mortality risk for species require mitigation measures such as underpasses, overpasses, and fences. Greater conservation efforts are needed in the spaces of human–wildlife coexistence to conserve the habitat network of small ungulates.

Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment

The conservation field is experiencing a rapid increase in the amount, variety, and quality of spatial data that can help us understand species movement and landscape connectivity patterns. As interest grows in more dynamic representations of movement potential, modelers are often limited by the capacity of their analytic tools to handle these datasets. Technology developments in software and high-performance computing are rapidly emerging in many fields, but uptake within conservation may lag, as our tools or our choice of computing language can constrain our ability to keep pace. We recently updated Circuitscape, a widely used connectivity analysis tool developed by Brad McRae and Viral Shah, by implementing it in Julia, a high-performance computing language. In this initial re-code (Circuitscape 5.0) and later updates, we improved computational efficiency and parallelism, achieving major speed improvements, and enabling assessments across larger extents or with higher resolution data. Here, we reflect on the benefits to conservation of strengthening collaborations with computer scientists, and extract examples from a collection of 572 Circuitscape applications to illustrate how through a decade of repeated investment in the software, applications have been many, varied, and increasingly dynamic. Beyond empowering continued innovations in dynamic connectivity, we expect that faster run times will play an important role in facilitating co-production of connectivity assessments with stakeholders, increasing the likelihood that connectivity science will be incorporated in land use decisions.

Application of InVEST habitat quality module in spatially vulnerability assessment of natural habitats (case study: Chaharmahal and Bakhtiari province, Iran)

There has been a growing pressure of human activities, especially road network, on natural habitats of the world, which has led to habitat degradation and loss of ecosystem services. To mitigate the impacts of human activities, appropriate studies quantifying ecosystem services and assessing ecological impacts of road network are essential. The main goal of this study was modeling habitat quality and habitat degradation of Chaharmahal and Bakhtiari province in the southwestern part of Iran, which is among the most important habitats for wild sheep (Ovis orientalis) classified as vulnerable on the IUCN Red List. In this study, we used the habitat quality module of the InVEST software (Integrated Valuation of Environmental Services and Tradeoffs), which was driven from land use/cover data, information on anthropogenic threats, and expert knowledge. We tested the reliability of the habitat quality values by comparing them with the distribution map of wild sheep obtained from the Department of the Environment. Then, to have a more comprehensive assessment of the roads' effects on the natural habitats of this province, considering ecosystem services model, the Spatial Road Disturbance Index (SPROADI) was applied as a landscape index. The results of this study revealed that the east and north eastern parts of the study area which were among the most suitable habitats for wild sheep were highly affected by road network. Overall, findings of our study provided useful information on the spatially explicit distribution of habitat quality and degradation which were a valuable input for conservation planning and enhancing ecosystem services.