Barriers and corridors: Assessment of gene flow and movement among red panda populations in eastern Himalayas

Landscape features can impede dispersal, gene flow, and population demography, resulting in the formation of several meta-populations within a continuous landscape. Understanding a species' ability to overcome these barriers is critical for predicting genetic connectivity and population persistence, and implementing effective conservation strategies. In the present study, we conducted a fine-scale spatial genetic analysis to understand the contemporary gene flow within red panda populations in the Eastern Himalayas. Employing geometric aspects of reserve design, we delineated the critical core habitats for red pandas, which comprise 14.5 % of the landscape (12,189.75 Km2), with only a mere 443 Km2 falling within the protected areas. We identified corridors among the core habitats, which may be vital for the species' long-term genetic viability. Furthermore, we identified substantial landscape barriers, including Sela Pass in the western region, Siang river in the central region, and the Dibang river, Lohit river, along with Dihang, Dipher, and Kumjawng passes in the eastern region, which hinder gene flow. We suggest managing red panda populations through the creation of Community Conservation Reserves in the identified core habitats, following landscape-level management planning based on the core principles of geometric reserve design. This includes a specific emphasis on identified core habitats of red panda (CH-RP 5 and CH-RP 8) to facilitate corridors and implement meta-population dynamics. We propose the development of a comprehensive, long-term conservation and management plan for red pandas in the transboundary landscape, covering China, Nepal, and Bhutan.

Assessment of habitat suitability and connectivity across the potential distribution landscape of the sambar (Rusa unicolor) in Southwest China

Habitat suitability assessment is the basis for wildlife conservation management and habitat restoration. It is a useful tool to understand the quality of wildlife habitat and its potential spatial distribution. In order to reveal the habitat suitability and connectivity of sambar (Rusa unicolor) to promote species and biodiversity conservation, this study collected records of sambar (Rusa unicolor) from over 2,000 camera traps in the forests of Southwest China in the past 5 years to assess the overall situation of their habitat. The results of the species distribution model revealed that the suitable habitat area for sambar in the five major mountain ranges (Minshan, Qionglai, Daxiangling, Xiaoxiangling, and Liangshan) in Southwest China is 18,231 km2, accounting for 17.02% of the total area. The most suitable habitat of sambar is primarily distributed in Qionglai, as well as the intersection areas of Daxiangling, Xiaoxiangling, and Minshan. The temperature annual range, temperature seasonality, elevation, and distance to road were important factors affecting the distribution of suitable habitat for sambar. Analysis of landscape pattern shows that there were 273 habitat patches, with a maximum patch area of 9,983 km2, accounting for 54.8% of the total suitable habitat area. However, the segmentation index and separation index of each habitat patch were 0.99 and 106.58, respectively, indicating a relatively high habitat fragmentation in the study area. The results of habitat connectivity analysis showed that the Qionglai mountains have the largest suitable habitat area and the highest connectivity among habitat patches. However, habitat connectivity between the five mountains is very low, suggesting that gene flow among these mountain ranges is probably limited. We therefore recommend strengthening protection of sambar and their habitat, with special attention to the establishment of corridors between the different mountain populations.

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.

Identifying connectivity for two sympatric carnivores in human-dominated landscapes in central Iran

Central Iran supports a diversity of carnivores, most of which are threatened by habitat loss and fragmentation. Carnivore conservation requires the identification and preservation of core habitats and ensuring connectivity between them. In the present study, we used species distribution modeling to predict habitat suitability and connectivity modeling to predict linkage (resistant kernel and factorial least-cost path analyses) for grey wolf and golden jackal in central Iran. For grey wolf, elevation, topographic ruggedness, and distance to Conservation Areas (CAs) were the strongest predictors; for golden jackal, distance to human settlements, dump sites and topographic ruggedness were the most influential variables in predicting the occurrence of this species. Our results also indicated a high potential for large parts of the landscape to support the occurrence of these two canid species. The largest and the most crucial core habitats and corridor paths for the conservation of both species are located in the southern part of the study landscape. We found a small overlap between golden jackal corridor paths and core habitats with CAs, which has important implications for conservation and future viability of the golden jackal populations. Some sections of core areas are bisected by roads, where most vehicle collisions with grey wolf and golden jackal occurred. To minimize mortality risk, we propose that successful conservation of both species will necessitate integrated landscape-level management, as well as conservation of core areas and corridors and development of mitigation strategies to reduce vehicle collisions.

Combining multiscale niche modeling, landscape connectivity, and gap analysis to prioritize habitats for conservation of striped hyaena (Hyaena hyaena)

Identifying spatial gaps in conservation networks requires information on species-environment relationships, and prioritization of habitats and corridors. We combined multi-extent niche modeling, landscape connectivity, and gap analysis to investigate scale-dependent environmental relationships, and identify core habitats and corridors for a little-known carnivore in Iran, the striped hyaena (Hyaena hyaena). This species is threatened in Iran by road vehicle collisions and direct killing. Therefore, understanding the factors that affect its habitat suitability, spatial pattern of distribution, and connectivity among them are prerequisite steps to delineate strategies aiming at human-striped hyaena co-existence. The results showed that the highest predictive power and extent of habitats was obtained at the extent sizes of 4 and 2 km, respectively. Also, connectivity analysis revealed that the extent and number of core habitats and corridors changed with increasing dispersal distance, and approximately 21% of the landscape was found to support corridors. The results of gap analysis showed that 15–17% of the core habitats overlapped with conservation areas. Given the body size of the species, its mobility, and lack of significant habitat specialization we conclude that this species would be more strongly influenced by changes in habitat amount rather than landscape configuration. Our approach showed that the scale of variables and dispersal ability must be accounted for in conservation efforts to prioritize habitats and corridors, and designing conservation areas. Our results could facilitate the conservation of striped hyaena through the identification and prioritization of habitats, establishment of conservation areas, and mitigating conflicts in corridors.

Genetic structure and ecological niche segregation of Indian gray mongoose (Urva edwardsii) in Iran

Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose (Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between-clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain-building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat-specific and climate change-integrated management strategies.

Multispecies landscape functional connectivity enhances local bird species' diversity in a highly fragmented landscape

Local species assemblages are likely the result of habitat and landscape filtering. However, there is still limited knowledge on how landscape functional connectivity complements habitat attributes in mediating local species assemblages in real-world fragmented landscapes. In this study, we set up a non-manipulative experimental design in a standard production forest to demonstrate how functional connectivity determines the spatial distribution of a bird community. We test single- and multispecies spatially explicit, landscape functional connectivity models framed within the circuit theory, considering also patch attributes describing habitat size and quality, to weight their effects on species occurrence and community assemblage. We found that single-species functional connectivity effects contributed positively for occurrence of each species. However, they rarely provided competing alternatives in predicting community parameters when compared to multispecies connectivity models. Incorporating multispecies connectivity showed more consistent effects for all community parameters, than single-species models, since the overlap between species' dispersal abilities in the landscape shows poor agreement. Habitat size and quality, though less important, were also determinant in explaining community parameters while possibly relating to the provision of suitable nesting and foraging conditions. Both habitat and landscape filters concur to govern community assembly, though likely influencing different processes: while landscape connectivity determines which species can reach a patch, habitat quality determines which species settle in the patch. Our results also suggest that surrogating multispecies connectivity from single species has potential to source bias by assuming species perceive landscape and its barriers similarly. Inference on this issue must be gathered from as much species as possible.

Accessing habitat suitability and connectivity for the westernmost population of Asian black bear (Ursus thibetanus gedrosianus, Blanford, 1877) based on climate changes scenarios in Iran

Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and even risk of extinction of various wildlife species and this has raised concerns among conservation biologists. Different species have two options in the face of climate change, either to adopt or follow their climatic niche to new places through the connectivity of habitats. The modeling of interpatch landscape communications can serve as an effective decision support tool for wildlife managers. This study was conducted to assess the effects of climate change on the distribution and habitat connectivity of the endangered subspecies of Asian black bear (Ursus thibetanus gedrosianus) in the southern and southeastern Iran. The presence points of the species were collected in Provinces of Kerman, Hormozgan, and Sistan-Baluchestan. Habitat modeling was done by the Generalized Linear Model, and 3 machine learning models including Maximum Entropy, Back Propagation based artificial Neural Network, and Support Vector Machine. In order to achieve the ensemble model, the results of the mentioned models were merged based on the method of "accuracy rate as weight" derived from their validation. To construct pseudo-absence points for the use in the mentioned models, the Ensemble model of presence-only models was used. The modeling was performed using 15 habitat variables related to climatic, vegetation, topographic, and anthropogenic parameters. The three general circulation models of BCC-CSM1, CCSM4, and MRI-CGCM3 were selected under the two scenarios of RCP2.6 and RCP8.5 by 2070. To investigate the effect of climate change on the habitat connections, the protected areas of 3 provinces were considered as focal nodes and the connections between them were established based on electrical circuit theory and Pairwise method. The true skill statistic was employed to convert the continuous suitability layers to binary suitable/unsuitable range maps to assess the effectiveness of the protected areas in the coverage of suitable habitats for the species. Due to the high power of the stochastic forest model in determining the importance of variables, this method was used. The results showed that presence/absence models were successful in the implementation and well distinguished the points of presence and pseudo-absence from each other. Based on the random forests model, the variables of Precipitation of Driest Quarter, Precipitation of Coldest Quarter, and Temperature Annual Range have the greatest impact on the habitat suitability. Comparing the modeling findings to the realities of the species distribution range indicated that the suitable habitats are located in areas with high humidity and rainfall, which are mostly in the northern areas of Bandar Abbas, south of Kerman, and west and south of Sistan-Baluchestan. The area of suitable habitats, in the MRI-CGCM3 (189731 Km2) and CCSM4 (179007 Km2) models under the RCP2.6 scenario, is larger than the current distribution (174001 Km2). However, in terms of the performance of protected areas, the optimal coverage of the species by the boundary of the protected areas, under each of the RCP2.6 and RCP8.5 scenarios, is less than the present time. According to the electric circuit theory, connecting the populations in the protected areas of Sistan-Baluchestan province to those in the northern Hormozgan and the southern Kerman would be based on the crossing through the heights of Sistan-Baluchestan and Hormozgan provinces and the plains between these heights would be the movement pinch points under the current and future scenarios. Populations in the protected areas of Kerman have higher quality patch connections than that of the other two provinces. The areas such as Sang-e_Mes, Kouh_Shir, Zaryab, and Bahr_Aseman in Kerman Province and Kouhbaz and Geno in Hormozgan Province can provide suitable habitats for the species in the distribution models. The findings revealed that the conservation of the heights along with the caves inside them could be a protective priority to counteract the effects of climate change on the species.

Roads threaten Asiatic cheetahs in Iran

Wildlife-vehicle collisions are an important cause of mortality for many animal species. They also prove extremely detrimental to the critically endangered Asiatic cheetah (Acinonyx jubatus venaticus) [1,2]. One to two Asiatic cheetahs are killed by vehicles on Iran's roads annually [3,4]. As such, the Asiatic cheetah could be the next charismatic felid subspecies to go extinct in the near future [5]. We identified one statistically-significant cluster of cheetah-vehicle collisions on the Shahroud-Sabzevar Highway (SSH), in Semnan Province. Because of the extremely small population of cheetahs and the corresponding difficulty of finding statistically-significant clusters, we propose that every single cheetah-vehicle collision should be considered important. We further recommend that wildlife underpasses and associated fencing be constructed in areas of previous cheetah-vehicle collisions.

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Climate Modelling Shows Increased Risk to Eucalyptus sideroxylon on the Eastern Coast of Australia Compared to Eucalyptus albens

Aim: To identify the extent and direction of range shift of Eucalyptus sideroxylon and E. albens in Australia by 2050 through an ensemble forecast of four species distribution models (SDMs). Each was generated using four global climate models (GCMs), under two representative concentration pathways (RCPs). Location: Australia. Methods: We used four SDMs of (i) generalized linear model, (ii) MaxEnt, (iii) random forest, and (iv) boosted regression tree to construct SDMs for species E. sideroxylon and E. albens under four GCMs including (a) MRI-CGCM3, (b) MIROC5, (c) HadGEM2-AO and (d) CCSM4, under two RCPs of 4.5 and 6.0. Here, the true skill statistic (TSS) index was used to assess the accuracy of each SDM. Results: Results showed that E. albens and E. sideroxylon will lose large areas of their current suitable range by 2050 and E. sideroxylon is projected to gain in eastern and southeastern Australia. Some areas were also projected to remain suitable for each species between now and 2050. Our modelling showed that E. sideroxylon will lose suitable habitat on the western side and will not gain any on the eastern side because this region is one the most heavily populated areas in the country, and the populated areas are moving westward. The predicted decrease in E. sideroxylon's distribution suggests that land managers should monitor its population closely, and evaluate whether it meets criteria for a protected legal status. Main conclusions: Both Eucalyptus sideroxylon and E. albens will be negatively affected by climate change and it is projected that E. sideroxylon will be at greater risk of losing habitat than E. albens.