Suitable Habitat Research Articles

Reaching new lands: Updating the distribution of Angiostrongylus cantonensis in South America with the first record in Argentina.

Angiostrongylus cantonensis, commonly known as the rat lungworm, is a metastrongyloid nematode found primarily not only in tropical and subtropical regions but also in temperate areas and considered the leading cause of eosinophilic meningitis in humans. Synanthropic rodents such as Rattus norvegicus and Rattus rattus are the most frequent definitive hosts of this parasite. The presence of this parasite was detected in the pulmonary arteries of three specimens of R. norvegicus in the city of Buenos Aires representing the species' southernmost known record in natural hosts. Species confirmation was achieved through partial sequences of 18S and COI genes. By comparing the COI gene sequences with those available in GenBank through the construction of a haplotype network, we obtained that the analysed specimen presents high similarity with those reported in Japan and Southeast Asia. All infected rats were captured in an area surrounding a port with significant import and export activity, suggesting that A. cantonensis may have been introduced through commercial ships. Specifically, the parasite was detected in a neighbourhood with vulnerable socio-economic conditions and in a nature reserve, which exhibit biotic and abiotic characteristics conducive to sustaining high-density rat populations, scattered waste, areas of spontaneous vegetation, debris accumulation and flooded areas or lagoons offering suitable habitats for intermediate hosts such as snails. Thus, the close proximity of the port to these sites creates a favourable ecological context for the establishment of A. cantonensis. This study shows the need to conduct research to detect A. cantonensis in non-endemic areas but with the characteristics that promote its arrival and development of its life cycle in order to implement control measures to prevent expansion of this parasite and its transmission to humans and other animals.

Floodplains as a Suitable Habitat for Freshwater Fish: The Length–Weight Relationships and Condition Factors of Fish Inhabiting a Danube Floodplain in Croatia

When studying the well-being and fitness of ichthyofauna in a specific area, vital information comes from length–weight relationships (LWRs) and condition factor analyses and calculations. Data were collected from 2015 to 2019 in an area important for fish shelter, feeding, and spawning. Twenty four species belonging to 10 different families were identified from the total 16,895 of caught individuals, with the most abundant species being Blicca bjoerkna. The calculation of LWRs was possible for 19 species, (R2 = 0.7049–0.9998 (p < 0.05)), with the values of the mean coefficient b ranging from 2.6831 to 3.5747, indicating an overall positive allometric growth in the fish population. The results of Fulton’s and the relative condition factors showed that a total of eight species were in a relatively good condition, although the species in question varied between the two condition factors. Fulton’s condition factor showed the highest average value for Lepomis gibbosus (1.4956), while Cobitis elongatoides had the lowest (0.4739). Contrarily, the relative condition factor showed the highest average value for Silurus glanis (1.0524), and the lowest for Gymnocephalus cernua (1.0023). The lower values of calculated condition factors in some species could be attributed to sampling being conducted during the colder months of autumn and winter. Future studies should include seasonal sampling in order to achieve a better understanding how various abiotic factors impact the condition factors of these fish species. Nevertheless, this research provided valuable data on the status of the fish population in the floodplain and could be used as a guideline for designing future ichthyofauna studies in this area.

Modeling the distribution of pine wilt disease in China using the ensemble models MaxEnt and CLIMEX.

Pine wilt disease (PWD) is a devastating plant disease caused by the pinewood nematode (PWN, Bursaphelenchus xylophilus) that is transmitted by several beetle species in the genus, Monochamus. Once present, the disease is difficult to control. Prevention rather than control is regarded as an effective strategy for PWD management. Central to this prevention strategy is the ability to predict the potential distribution of the disease. Here, we employed an integrated MaxEnt and CLIMEX approach to model the potential distribution of PWD under various climate-change scenarios. Our results indicate that rising temperatures and lower humidity under climate change will render some of the northern regions of China more suitable for the nematode and these beetles, causing the gradual northward movement of PWD. Furthermore, suitable habitats for three pine species, Pinus massoniana, P. taiwanensis and P. shurbergia, overlap with PWN and Monochamus, suggesting that these three species are potentially at high risk of PWD. Thus, PWD management should target the northern regions of China and the three pine species that are most susceptible to PWD.

Bridging climate refuges for climate change adaptation: A spatio-temporal connectivity network approach

Enhancing the spatio-temporal connectivity of dynamic landscapes is crucial for species to adapt to climate change. However, a spatio-temporal connectivity network approach considering climate change and species movement is often overlooked. Taking Tibetan wild ass on the Qinghai-Xizang Plateau as an example, we simulated species distribution under current (2019) and future scenarios (2100), constructed spatio-temporal connectivity networks, and assessed the spatio-temporal connectivity. The results show that under the current, SSP2-4.5 and SSP3-7.0 scenarios, the suitable habitats for Tibetan wild ass account for 21.11%, 21.34%, and 20.95% of the total area, respectively, which show more fragmentation in 2100. 78.35% of habitats which are predicted to be suitable under current conditions will remain suitable in the future, which can be regarded as stable climate refuges. With the increase in future emission intensity, the number percentage of auxiliary connectivity corridors increases from 27.65% to 33.57%. This indicates that more patches will function as temporary refuges and the auxiliary connectivity corridors will gradually weaken the dominance of direct connectivity corridors. Under different SSP-RCP scenarios, the internal spatio-temporal connectivity is the highest, accounting for 42%–43%. Compared with the spatio-temporal perspective, the purely spatial perspective overestimates network connectivity by about 28% considering all current and future patches, and underestimates network connectivity by 16%–21% when only considering all current or future patches. In this study, a new approach of spatio-temporal connectivity network is proposed to bridge climate refuges, which contributes to the long-term effectiveness of conservation networks for species’ adaptation to climate change.

Identification of biodiversity hotspots for threatened mammal species under future climate

Climate change has led to changes in distribution, movement, and extinction risk for various wildlife species, raising concern among conservation biologists. Therefore, this study aimed to predict suitable habitats that help wildlife managers protect wildlife more effectively. To achieve our aim, we first evaluated the vulnerability of 183 terrestrial mammal species identified in Iran under climate change based on habitat, phenology and physiology, biotic interactions, and national protection status. Then, MaxEnt was used to predict the potential changes in the distribution of vulnerable species due to climate change in the next 70 years under two scenarios: SSP126 and SSP585. In the third step, a framework was employed to identify existing and future hotspots of mammal biodiversity, and the potential changes in these areas for the species were predicted in the next 70 years. The results showed that 69 terrestrial mammals were vulnerable to climate change. Subsequently, 15 species wereselected for modeling based on presence records and vulnerability to climate change. The species modeling results showed that 42 % of Iran’s habitats are currently suitable for the studied mammal species. In the future, under both climate scenarios, biodiversity hotspots for these species will be reduced, and approximately 37 % of Iran’s habitats will be suitable for the species. As a result, the current conservation network will have diminished capacity to protect the species from climate change.

Evaluating a process‐guided deep learning approach for predicting dissolved oxygen in streams

AbstractDissolved oxygen (DO) is a critical water quality constituent that governs habitat suitability for aquatic biota, biogeochemical reactions and solubility of metals in streams. Recently introduced high‐frequency sensors have increased our ability to measure DO, but we still lack the capacity to understand and predict DO concentrations at high spatial resolutions or in unmonitored locations. Machine learning (ML) has been a commonly used approach for modelling DO, however, conventional ML models have no representation of the limnological processes governing DO dynamics. Here we implement and evaluate two process‐guided deep learning (PGDL) approaches for predicting daily minimum, mean and maximum DO concentrations in rivers from the Delaware River Basin, USA. In both cases, a multi‐task approach was taken in which the PGDL models predicted stream metabolism and gas exchange rates in addition to the DO concentrations themselves. Our results showed that for these sites, the PGDL approaches did not improve upon baseline predictions in temporal and spatially similar holdout experiments. One of the approaches did, however, improve predictions when applied to spatially dissimilar sites. Although this particular PGDL approach did not improve predictive accuracy in most cases, our results suggest that process guidance, perhaps a more constrained approach, could benefit a data‐driven DO model.

Will cinereous vulture (Aegypius monachus L.) become extinct in the forests of Türkiye in the future?

Changing climate conditions and different climate scenarios on a global scale are associated with the shrinkage, fragmentation and even extinction of habitats of important bird species. Based on this, the aim is to conduct habitat suitability modelling and mapping of the cinereous vulture (Aegypius monachus), which has the largest body among the four different vulture species in the world, under the circumstances of climate change in Türkiye. MaxEnt method was performed to reveal the current habitat suitability model of the cinereous vulture, which is an indicator of old and high-quality black pine forests in terms of biological diversity in Türkiye. It was determined that the variables contributing to the current habitat suitability model of the cinereous vulture were bedrock, isothermality, landform classification and seasonal precipitation. Chelsa climate scenarios (SSP126-SSP370-SSP585) for the year 2100 were used to reveal the effects of changing climate conditions on the cinereous vulture. Mapping results according to different scenarios were classified as 0.5 – unsuitable, 0.51-0.8 – suitable and 0.81-1.0 – the most suitable habitat. According to the mapping results based on different year and scenarios, cinereous vulture has suitable habitat in a minimum of 16.13% of the study area in the present state, 13.95% in the year 2100 in the SPP126 climate scenario, 10.11% in the SPP370 climate scenario and 7.36% in the SPP585climate scenario. As a result, when the 2100 SSP585 climate scenario mapping was compared to the current habitat suitability mapping, it was determined that habitat suitability for the cinereous vulture decreased by approximately 55%. Therefore, these results will be a source of information to prevent the extinction of the cinereous vulture, in order to protect its current and potential distributions in advance, and to reduce the impact of changing climate conditions.

The Characteristics and Variation of the Golden Eagle Aquila chrysaetos Home Range

Satellite tracking allows for novel investigations into golden eagle home range characteristics. Understanding home range characteristics is important for conservation and for assessing the potential impact of landscape changes from forest planting, wind farms, etc. Small sample sizes, inconsistent definitions and methods restricted several previous studies. Our study involved 69 resident tagged eagles with over one year of data across five Scottish regions. Home range size was estimated from 95% isopleth contours extracted from Utilisation Distributions. Above a small threshold, estimated range size was not affected by the number of records but at least one year of data is required, largely because of the breeding and non-breeding seasonal differences. There were no significant range size differences between birds tagged as range holders and those previously tagged as nestlings. Across four regions, with considerable intra-regional variation, planar 95% isopleths did not differ (medians, km2): Argyll 58.9, Northwest Highlands 61.7, Northeast Highlands 89.3, South of Scotland 91.9. Ranges in the isolated Outer Hebrides region were exceptionally small, at 24.0 km2. Estimated range area was usually reduced to 70–80% of the planar area when restricted to usable habitat, as estimated by the Golden Eagle Topography (GET) model. Applying measures of known unsuitable habitat (closed-canopy commercial forest and wind turbines) further reduced usable open land. Loss of otherwise suitable habitat was substantially due to commercial forest. Larger ranges had larger extents of suitable habitat (according to GET), with no apparent optimum of preferred GET habitat. Range size was not different across a year between the sexes. Breeding ranges were smaller, and females’ breeding ranges were much smaller than those of males, but larger than males’ ranges in the non-breeding season. Breeding attempt duration was probably also influential. Our study provides novel insights into golden eagle home range characteristics and can guide further research and practical applications.

The estimation of suitable habitat for coastal plants and the risk of blown sand in coastal sand dune area

The estimation of suitable habitat for coastal plants and the risk of blown sand in coastal sand dune area

A simple method to map pollination ecosystem services potential in urban lawns

Urban areas have detrimental impacts on the ecosystems. Nevertheless, they still supply many ecosystem services (ES), such as Pollination, in different urban green spaces (UGS). Lawns are among the most degraded UGS due to very high human impact. Still, flowers such as Dandelions (Taraxacum officinalis) live in these spaces. These flowers are considered a suitable habitat for pollinators. In this work, we develop a methodology to map Pollination ES potential in urban lawns using an Unmanned Aerial Vehicle. A detailed protocol was developed using high-resolution images, consisting of orthomosaic creation, flower vectorisation, field validation, and finally, Pollination ES potential mapping using Kernel and Point Density. This method can be applied to urban lawns and grasslands in Spring and Summer.•A novel method was developed to map pollination potential in lawns.•Dandelions (Taraxacum officinale) were mapped using UAV high-resolution images.•The method is helpful to identify areas with pollination potential in urban lawns.

Python-Based Urban Land Suitability Evaluation for Effective Urban Planning

Abstract: One of the global environmental problems is that the population is growing rapidly around the world. unfortunately, land is a limited resource. Land suitability analysis merges as the most efficient and commonly used method that represents an effective informative tool to support policymakers and planners in developing optimal master plans, maintaining sustainability, and ensuring social equity among residents. Python's free and open-source ecosystem of geospatial libraries like Geo Pandas makes it a cost-effective alternative to proprietary GIS software for this purpose. Furthermore, Python excels at automation, allowing you to write scripts that save time and ensure consistency for repetitive tasks in land suitability analysis. At first, users can choose the project type based on the classification of land use and input raster and vector data. After that, each layer is reclassified, and a weighted overlay is applied at the end. A raster would be the final land suitability output file. Urban planning benefits greatly from Python's capabilities. Land suitability models can assess the viability of development projects by considering factors like flood risk, slope stability, and proximity to infrastructure. The applications extend far beyond these initial examples. Python's land suitability models are instrumental in environmental management as well. Habitat suitability modeling, for instance, considers factors like vegetation cover, water availability, and connectivity to existing habitats to identify areas suitable for specific wildlife species. This information is crucial for conservation planning and restoration efforts. This paper is designed to explain the beneficial aspects of a Python-based approach to land suitability modelling and how it operates.

Habitat suitability and protected area coverage for an expanding cougar Puma concolor population in Canada.

Successful conservation of expanding large carnivore populations and management of human-wildlife conflict to promote coexistence requires sufficient spatiotemporal knowledge to inform appropriate action. In Canada, cougars (Puma concolor) are expanding their range eastwards and little research is available for use in decision making by land managers and conservation planners. To inform proactive management regarding expanding populations of cougars in Canada, we utilized open-source cougar presence and land-cover data in a maximum entropy habitat suitability model to determine potentially suitable habitat for cougars across the country. We then used a gap analysis to determine the effectiveness of existing formal protected areas to protect potential cougar habitat. Suitable habitat exists for range-expanding cougars dispersing eastwards through the central and eastern provinces to the Atlantic coast. While the habitat is highly fragmented, the highest suitability occurs in areas of medium road density, indicating that the potential for new human-cougar conflict will likely involve residents of exurban and rural areas. Protected areas offered 16% coverage of suitable habitat, although most protected areas that overlap predicted cougar habitat are not large enough to effectively conserve the large home range requirements of cougars. Synthesis and Applications: High fragmentation of suitable habitat and the potential for human-wildlife conflict requires proactive management to ensure appropriately sized and connected areas are maintained for the establishment of expanding cougar populations. Many of the management actions intended to aid in the conservation of cougars and their habitat can also serve to mitigate potential human-cougar conflict arising as a consequence of an expanding population, such as highway wildlife crossing structures and formal habitat protection.

Predicting the Potential Global Distribution of the Plum Fruit Moth Grapholita funebrana Treitscheke Using Ensemble Models.

The plum fruit moth, Grapholita funebrana Treitschke, is one of the most significant borer pests, often causing huge economic losses in fruit production. However, the potential distribution range of this economically important pest is still poorly understood. For this study, we simulated an ensemble species distribution model to predict the spatiotemporal distribution pattern of G. funebrana at a global scale. The results show that the suitable habitats for this moth, under current environmental conditions, are mainly distributed in Europe; East Asia, including China and Japan; Central Asia; and some parts of America. In future projections, the suitable habitats are predicted to generally expand northward, while the suitable area will remain unchanged overall. However, the area of highly suitable habitat will decrease to only 17.49% of that found under current conditions. None of the nine factors used were revealed to be predominant predictors in terms of contributing to the model, suggesting that the integrated effects of these variables shape G. funebrana's distribution. In this study, the distribution range that has been predicted, especially for the regions with a highly suitable habitat, poses a high risk of G. funebrana outbreaks, highlighting the urgency of pest management. Moreover, in the United States of America (USA) and Japan (for which G. funebrana distributions were not previously recorded), especially in areas highly suitable for this moth, monitoring and quarantine measures should be strengthened to prevent the colonization and further dispersal of this pest, as seen with its close relative G. molesta, which has become a cosmopolitan pest species, migrating from its native region (East Asia) to other continents, including the Americas.

Genetic structure and climate niche differentiation among populations of Leopardus geoffroyi.

Geoffroy's cat (Leopardus geoffroyi) is a small-sized felid native to South America. Given the species' distribution covering a wide variety of habitats, and the presence of high levels of anthropization in part of its range, it is possible that genetically differentiated groups exist and that they occupy different climatic niches. We assessed patterns of contemporary genetic diversity and structure in the species across most of its range, characterizing each inferred genetic group based on ecological niche models. We genotyped 11 microsatellites for 142 samples covering most of Geoffroy's cat distribution, and investigated patterns of genetic structure and diversity, applying spatial and nonspatial Bayesian clustering methods and a spatial principal component analysis. We created ecological niche models for each genetic cluster, evaluating whether these clusters occupy different climatic spaces and display differences in the suitability of different values of the climatic variables analyzed. We identified two genetic clusters, one in the north-northeast and the other in the south-southwest of the species' distribution. These clusters showed moderate FST values between them and differences in dispersal/genetic diversity. We found isolation-by-distance patterns globally and within each cluster. We observed lower expected heterozygosity compared with other studies and a north-south gradient in allelic richness. The southern cluster showed lower genetic variability and a more restricted climatic niche suggesting that this group is more vulnerable to the effects of the current context of climate change. Individuals from the southern genetic cluster are under different pressures, likely a product of the particularly dry habitat they occupy. Climatic variables associated with habitat suitability suggest the southern cluster has affinity for the arid and semiarid conditions present in its distribution. Conservation measures should consider the genetic structure observed and differences in climatic spaces to maintain the evolutionary potential of the species.

Assessing abundance-suitability models to prioritize conservation areas for the dwarf caimans in South America.

Species-environment relationships have been extensively explored through species distribution models (SDM) and species abundance models (SAM), which have become key components to understand the spatial ecology and population dynamics directed at biodiversity conservation. Nonetheless, within the internal structure of species' ranges, habitat suitability and species abundance do not always show similar patterns, and using information derived from either SDM or SAM could be incomplete and mislead conservation efforts. We gauged support for the abundance-suitability relationship and used the combined information to prioritize the conservation of South American dwarf caimans (Paleosuchus palpebrosus and P. trigonatus). We used 7 environmental predictor sets (surface water, human impact, topography, precipitation, temperature, dynamic habitat indices, soil temperature), 2 regressions methods (Generalized Linear Models-GLM, Generalized Additive Models-GAM), and 4 parametric distributions (Binomial, Poisson, Negative binomial, Gamma) to develop distribution and abundance models. We used the best predictive models to define four categories (low, medium, high, very high) to plan species conservation. The best distribution and abundance models for both Paleosuchus species included a combination of all predictor sets, except for the best abundance model for P. trigonatus which incorporated only temperature, precipitation, surface water, human impact, and topography. We found non-consistent and low explanatory power of environmental suitability to predict abundance which aligns with previous studies relating SDM-SAM. We extracted the most relevant information from each optimal SDM and SAM and created a consensus model (2,790,583 km2) that we categorized as low (39.6%), medium (42.7%), high (14.9%), and very high (2.8%) conservation priorities. We identified 279,338 km2 where conservation must be critically prioritized and only 29% of these areas are under protection. We concluded that optimal models from correlative methods can be used to provide a systematic prioritization scheme to promote conservation and as surrogates to generate insights for quantifying ecological patterns.

Variations in risk‐taking behaviour mediate matrix mortality's impact on biodiversity under fragmentation

The impact of fragmentation on biodiversity is driven by more than the spatial configuration of suitable habitat patches. Habitat is embedded in the surrounding anthropogenic land cover, known as the matrix, which plays a key role in species movement and connects the fragmented habitat. Whether the matrix is a barrier or a conduit to movement depends on the mortality of the moving individuals. However, individuals differ in their behavioural response to the risk posed by the matrix, with the willingness to enter the matrix depending on an individual's risk‐taking behaviour. This individual‐level behavioural variability is rarely considered but represents an additional mechanism shaping inter‐ and intraspecific competition as well as evolutionary behavioural responses. We used an individual‐based model to scale up from individual foraging movements to the resulting community structure of a competitive small mammal community in differently fragmented landscapes. The model interactively considers extrinsic matrix conditions, given as a certain mortality rate, and individual differences in intrinsic movement decisions when moving into the matrix. The model was used to investigate consequences of fragmentation and matrix mortality for species and behavioural diversity. Low matrix mortality resulted in a positive effect of fragmentation on species diversity. At the same time, it led to a high average risk‐taking behaviour. While this was an important adaptive response to fragmentation, it also led to a loss of intraspecific diversity. High matrix mortality reversed the effect of fragmentation, leading to a drastic loss of species with increasing fragmentation. High mortality risk reduced average risk‐taking, especially at high fragmentation. Study findings suggest that the feasibility of movement in the matrix can influence species diversity and evolutionary responses of movement‐related behavioural traits in fragmented landscapes. The matrix may thus play a key role in reconciling contrasting empirical results and provides a promising tool for future biodiversity conservation.

Multi-Scenario Ecological Network Conservation Planning Based on Climate and Land Changes: A Multi-Species Study in the Southeast Qinghai–Tibet Plateau

The Qinghai–Tibet Plateau ecosystem is fragile, experiencing rapid changes in land cover driven by both climate change and human activities, leading to habitat fragmentation and loss and resulting in biodiversity decline. Habitat ecological networks (HA-ENs) are considered effective solutions for habitat connectivity and biodiversity conservation in response to these dual drivers. However, HA-EN studies typically rely on current or historical landscape data, which hinders the formulation of future conservation strategies. This study proposes three future scenarios—improvement, deterioration, and baseline scenarios—focused on the southeastern Qinghai–Tibet Plateau (SE-QPT). The habitats of 10 species across three classes are extracted, integrating land use and climate change data into habitat ecological network modeling to assess the long-term dynamics of HA-ENs in the SE-QPT. Finally, conservation management strategies are proposed based on regional heterogeneity. The results show the following: Climate change and human activities are expected to reduce the suitable habitat area for species, intensifying resource competition among multiple species. By 2030, under all scenarios, the forest structure will become more fragmented, and grassland degradation will be primarily concentrated in the southeastern and western parts of the study area. Compared to 1985 (71,891.3 km2), the habitat area by 2030 is projected to decrease by 12.9% (62,629.3 km2). The overlap rate of species habitats increases from 25.4% in 1985 to 30.9% by 2030. Compared to the HA-EN control in 1985, all scenarios show a decrease in connectivity and complexity, with only the improvement scenario showing some signs of recovery towards the control network, albeit limited. Finally, based on regional heterogeneity, a conservation management strategy of “two points, two cores, two corridors, and two regions” is proposed. This strategy aims to provide a framework for future conservation efforts in response to climate change and human activities.

Using cumulative human impact assessment to support adaptive management of the threatened species’ habitats in the Yangtze River Estuary

The conflict between multiple functions of human use and habitat conservation represents an intractable challenge for environmental management. While numerous studies on marine conservation prioritize cumulative impact assessments (CIA) to tackle this issue, estuaries — despite their immense conservation significance amidst intense human activities — remain overlooked. Taking the Yangtze River Estuary (YRE) as the case study area, it is one of the most intensely human-utilized estuaries globally, yet it serves as a critical habitat and migratory corridor for the endangered Chinese sturgeon (Acipenser sinensis).We employed ecological indicators and quantitative modeling to assess habitat suitability and cumulative anthropogenic impacts on this endangered species in the YRE. The results demonstrated that suitable habitat distribution and human impact varied for juvenile Chinese sturgeon in the YRE. The suitable habitat distribution for juvenile Chinese sturgeon was concentrated in Chongming Dongtan and the North Channel. Ship density, submarine optical cables, and smooth cord grass invasion were the main anthropogenic factors impacting the Chinese sturgeon's migrating habitat in the YRE. Moreover, existing Chinese sturgeon habitats remain at risk, with 36.24 % of potential habitats and 56.60 % of high human impact areas requiring enhanced protection. Adaptive management strategies were proposed, tailored to the spatial and environmental protection needs across the dynamic habitat demands of aquatic species. Our spatially explicit and indicator-based findings provide key scientific support for enlarging protected areas and implementing adaptive management of human activities to balance conservation and sustainable use in this highly utilized ecosystem.

Habitat Loss in the IUCN Extent: Climate Change-Induced Threat on the Red Goral (Naemorhedus baileyi) in the Temperate Mountains of South Asia.

Climate change has severely impacted many species, causing rapid declines or extinctions within their essential ecological niches. This deterioration is expected to worsen, particularly in remote high-altitude regions like the Himalayas, which are home to diverse flora and fauna, including many mountainous ungulates. Unfortunately, many of these species lack adaptive strategies to cope with novel climatic conditions. The Red Goral (Naemorhedus baileyi) is a cliff-dwelling species classified as "Vulnerable" by the IUCN due to its small population and restricted range extent. This species has the most restricted range of all goral species, residing in the temperate mountains of northeastern India, northern Myanmar, and China. Given its restricted range and small population, this species is highly threatened by climate change and habitat disruptions, making habitat mapping and modeling crucial for effective conservation. This study employs an ensemble approach (BRT, GLM, MARS, and MaxEnt) in species distribution modeling to assess the distribution, habitat suitability, and connectivity of this species, addressing critical gaps in its understanding. The findings reveal deeply concerning trends, as the model identified only 21,363 km2 (13.01%) of the total IUCN extent as suitable habitat under current conditions. This limited extent is alarming, as it leaves the species with very little refuge to thrive. Furthermore, this situation is compounded by the fact that only around 22.29% of this identified suitable habitat falls within protected areas (PAs), further constraining the species' ability to survive in a protected landscape. The future projections paint even degraded scenarios, with a predicted decline of over 34% and excessive fragmentation in suitable habitat extent. In addition, the present study identifies precipitation seasonality and elevation as the primary contributing predictors to the distribution of this species. Furthermore, the study identifies nine designated transboundary PAs within the IUCN extent of the Red Goral and the connectivity among them to highlight the crucial role in supporting the species' survival over time. Moreover, the Dibang Wildlife Sanctuary (DWLS) and Hkakaborazi National Park are revealed as the PAs with the largest extent of suitable habitat in the present scenario. Furthermore, the highest mean connectivity was found between DWLS and Mehao Wildlife Sanctuary (0.0583), while the lowest connectivity was observed between Kamlang Wildlife Sanctuary and Namdapha National Park (0.0172). The study also suggests strategic management planning that is a vital foundation for future research and conservation initiatives, aiming to ensure the long-term survival of the species in its natural habitat.

Assessing climate change threats to biodiversity and protected areas of Iran

Our research endeavors to evaluate the precise ramifications of climate change on Iran’s protected regions, utilizing species distribution modeling to anticipate the effects of climate change on 394 bird species, 157 plant species, 72 reptiles, and 20 mammals across two climate change scenarios: SSP245 and SSP585 in 2070. Subsequently, we employed binary species distribution maps to determine the extent of overlap between 125 protected areas, 27 wildlife refuges, and 15 national parks and species distribution, quantifying the proportion of these areas encompassed by their distribution. We found that under the SSP585 scenario, 174 bird species could experience a 319% expansion in suitable habitats, while 220 species could decline by 57.1%. Among plants, 16 species are projected to grow by 40.3%, whereas 141 species may decrease by 68.8%. Reptiles could experience an increase of 279.1% in 24 species, with a 66.6% decrease in 48 species, while mammals may witness a significant increase of 147.3% in 5 species, but a 71.8% decrease in 15 species. Also, under the SSP585 scenario, in national parks, bird coverage declines from 32.2% (current) to 19.9%, plants from 24.2 to 13.2%, reptiles from 18.4 to 6.8%, and mammals from 17.7 to 10%. In wildlife refuges, birds decrease from 9.7 to 5.7%, plants from 10.9 to 4.6%, reptiles from 12.9 to 2.5%, and mammals from 7.4 to 4.3%. In protected areas, birds drop from 29.3 to 20.4%, plants from 27.7 to 12.5%, reptiles from 18.7 to 9.7%, and mammals from 24 to 12.1%. The low overlap of species with national parks, wildlife refuges, and protected areas underscores the importance of re-evaluating and potentially expanding protected areas to ensure they encompass a broader range of habitats, particularly those that are underrepresented, to enhance the conservation of Iran’s biodiversity amidst the challenges posed by climate change.