Search Results (152)

Raptors, being at top of the food chain, serve as important models to study the impact of changing climate, as they are more vulnerable due to their unique ecology. They are vulnerable to extinction, with 52% species declining population and 18% are threatened globally. The effect of climate change on raptors is poorly studied in the Eastern Himalayan region. The present study offers a complete investigation of climate change effects on the raptors in the northeast region of the Eastern Himalayas, employing ensemble species distribution modeling. The future predictions were employed to model the climate change across two socioeconomic pathways (SSP) i.e. SSP245 and SSP585 for the periods 2041–2060 and 2061–2080. Specifically, five algorithms were employed for the ensemble model, viz. boosted regression tree (BRT), generalized linear model (GLM), multivariate adaptive regression splines (MARS), maximum entropy (MaxEnt) and random forest (RF). The study highlights worrying results, as only 10.5% area of the NE region is presently suitable for Falco severus, 11.4% for the critically endangered Gyps tenuirostris, and a mere 6.9% area is presently suitable for the endangered Haliaeetus leucoryphus. The most influential covariates were precipitation of the driest quarter, precipitation of the wettest month, and temperature seasonality. Future projection revealed reduction of 33–41% in suitable habitats for F. severus, G. tenuirostris is expected to lose 53–96% of its suitable habitats, and H. leucoryphus has lost nearly 94–99% of its suitable habitats. Such decline indicates apparent habitat fragmentation, with shrinking habitat patches. Full article

Species distribution models (SDMs) have become an important tool to inform conservation and pest surveillance programs about the potential biological invasion of insect pests. Nonetheless, to be operational, SDMs need to incorporate multiple environmental covariates and a representative number of occurrence points depicting the species’ ecological niche. The algorithm of choice, model of choice, and comparison can also have a great effect on the final prediction output. We created a dataset based on previously published records, plus 36 new occurrences and 37 environmental predictors, to generate the first global ensemble distribution model for Aulacaspis yasumatsui. We employed a strategy that aggregates SDMs with the best performance (i.e., greater accuracy) from six different algorithms, resulting in an averaged and weighted model, i.e., the ensemble model. We then selected models from algorithms whose true skill statistic (TSS) was above 0.5 in order to map the potential global distribution of A. yasumatsui. Our results suggest that covariate selection and the individual model algorithms used in the ensemble may be more important for achieving an accurate SDM than the number of occurrence points. Full article

Global climate change poses a significant management challenge for vital transboundary resources like the Pacific saury (Cololabis saira). To address this, we developed an innovative framework that uses high-resolution Automatic Identification System (AIS) data and deep learning to define species distribution, which then informs a robust Ensemble Species Distribution Model (ESDM). The model (TSS > 0.89, AUC > 0.97) identifies sea surface temperature (SST) and chlorophyll-a (CHL) as key habitat drivers. Projections under future climate scenarios reveal two critical threats: (1) a continuous northeastward migration of the habitat’s centroid, exceeding 400 km by 2100 under a high-emission SSP5-8.5 scenario, and (2) a drastic contraction of highly suitable habitat (suitability > 0.8), shrinking by up to 94% under the high-emission SSP3-7.0 scenario. By directly linking key oceanographic features to these climate-driven risks, this study delivers an essential scientific decision-support tool for management bodies like the North Pacific Fisheries Commission (NPFC) to develop climate-adaptive strategies. Full article

Climate change poses a serious threat to biodiversity, particularly for woody species with limited dispersal capacity such as Prunus avium L. (wild cherry). In this study, we assessed potential shifts in its suitable distribution range (SDR) across Türkiye by applying an ensemble modeling framework that combined Generalized Additive Models (GAM), Maximum Entropy (MaxEnt), and Random Forest (RF). We used updated occurrence data (including GBIF and EUFORGEN records) and 11 ecologically relevant bioclimatic variables under SSP2-4.5 and SSP5-8.5 scenarios. Model performance was validated using AUC (Area Under the ROC Curve) and TSS (True Skill Statistic) metrics. Results suggest that while 60–70% of current SDRs remain stable by 2100, approximately 10% may be lost, with 20–23% new expansions. Temperature seasonality (Bio4) and seasonal precipitation (Bio15) were consistently identified as dominant predictors across models. Notably, newly suitable habitats are expected to be spatially isolated, limiting natural colonization. Our findings highlight the necessity of proactive conservation planning, including assisted migration and drought-resistant genotype selection, to ensure long-term persistence of wild cherry under changing climates. These results offer actionable insights for adaptive forest management and biodiversity conservation in Mediterranean-type ecosystems. Full article

Understanding the distribution pattern and its drivers of species is crucial for developing effective and sustainable management strategies. Amphioctopus fangsiao is the octopus of significant commercial and ecological value along the coast of China, with multiple distinct populations. However, research on their ecological dynamics remains limited and requires further investigation. Here, ensemble models were constructed to examine the spatio-temporal distribution and inter-populational differentiation in environmental adaptability of A. fangsiao in the East China Sea (ECS) and the South Yellow Sea (SYS). Specifically, we generated the ensemble models by integrating Gradient Boosting Machine (GBM), Generalized Linear Models (GLMs), and Maximum Entropy Models (MaxEnt) for the different populations across four seasons, using fishery-independent data collected from 2015 to 2021. The results revealed two hotspots of A. fangsiao in the ECS and SYS: one is the area of SYS along the coastal waters, with latitudes 33° N–34° N and longitudes 120° E–122° E (northern population, NP); the other one is near the Kuroshio-adjacent area with latitudes 28.5° N–29° N and longitudes 123° E–124.5° E (southern population, SP). Both NP and SP exhibited distinct seasonal habitat preferences, with key environmental drivers showing seasonal variations. The NP tended to inhabit coastal waters with lower sea surface heights (SSHs), shallower water depth, and a narrower sea bottom salinity range (SBS). In contrast, SP preferred marine environments with a thicker mixed layer thickness (MLT) and higher concentrations of bottom chlorophyll-a (Chl_b). The environmental characterization of suitable habitats revealed distinct patterns in resource utilization and environmental adaptation strategies between the two populations. This study provides fundamental data for understanding A. fangsiao population dynamics and underscores the importance of considering population-specific habitat preferences within dynamic marine environments. Full article

Gentiana pneumonanthe L., a wetland specialist and exclusive host of the Alcon Blue (Phengaris alcon), is highly vulnerable to climate change. This study assessed the future climate suitability of the Iberian Peninsula (IP) for G. pneumonanthe. From 14 bioclimatic variables (ISIMIP3b, processed by CHELSA method at 1 km²) and two topographic variables, four bio-ecological indicators were selected using Pearson correlation and Variance Inflation Factors: Thermicity Index, Ombrothermic Index, Accumulated summer precipitation from June to August, and Maximum of the daily maximum temperature of August. A species distribution model platform (Biomod2) was applied for historical (1995–2014) and future periods (2041–2060, 2081–2100) under two anthropogenic radiative forcing scenarios (SSP3-7.0, SSP5-8.5). The ensemble model created shows a strong predictive performance (BOYCE: 0.98). Historically, 13.4% of the IP was climatically suitable, mainly in mountain areas. Under SSP3-7.0, suitable areas are projected to decline by 74.2% (2041–2060) and 99.3% (2081–2100); under SSP5-8.5, by 75.5% and 99.9%, respectively. While small gains may occur in the Pyrenees, most conservation protected areas (Natura 2000, RAMSAR) may lose suitability for species persistence. Such losses could disrupt ecological ecosystems and directly threaten the survival of P. alcon. These findings highlight the urgent need for climate-informed land-use planning and effective habitat conservation. Full article

Solanum rostratum Dunal is a highly invasive species with strong environmental adaptability and reproductive capacity, posing serious threats to agroforestry ecosystems and human health. In this study, we compiled occurrence records of S. rostratum in China from online databases and sources in the literature. We employed the Biomod2 ensemble modeling framework to predict the potential distribution of the species under current climatic conditions and four future climate scenarios (SSP126, SSP245, SSP370, and SSP585), and to identify the key environmental variables influencing its distribution. The ensemble model based on the committee averaging (EMca) approach achieved the highest predictive accuracy, with a true skill statistic (TSS) of 0.932 and an area under the curve (AUC) of 0.990. Under present climatic conditions, S. rostratum is predominantly distributed across northern China, particularly in Xinjiang, Inner Mongolia, and the northeastern provinces, covering a total suitable area of 1,191,586.55 km², with highly suitable habitats accounting for 50.37% of this range. Under future climate scenarios, the species’ suitable range is projected to expand significantly, particularly under the high-emissions SSP585 scenario, with the distribution centroid expected to shift significantly toward high-altitude regions in Gansu Province. Precipitation and temperature emerged as the most influential environmental factors affecting habitat suitability. These findings indicate that ongoing global warming may facilitate the survival, reproduction, and rapid spread of S. rostratum across China in the coming decades. Full article

The potential distribution of the pulse blue butterfly, Lampides boeticus (Lepidoptera: Lycaenidae), was determined using MaxEnt, random forest, and ensemble models. The results indicate that most tropical, subtropical, and some temperate regions are suitable habitats. Climate change is projected to expand the species’ habitat northward in the Northern Hemisphere. Predicted distributions aligned well with the known occurrence records for the species. The minimum temperature of the coldest month was the climatic variable that most strongly influenced the distribution of L. boeticus. As a tropical and subtropical species, it is assumed that cold temperatures are the main factor limiting its habitat range. Because the potential distribution of this pest covers major pulse cultivation areas under both current and future climate scenarios, these findings highlight the urgent need for developing a sustainable pest management strategy. Full article

Understanding the impacts of climate change on species’ geographic distributions is fundamental for biodiversity conservation and resource management. As a key plant group for ecological restoration and windbreak and sand fixation in arid and semi-arid ares in China’s Three Northern Regions (Northeast, North, and Northwest China), Caragana spp. exhibit distribution patterns whose regulatory mechanisms by environmental factors remain unclear, with a long-term lack of climatic explanations influencing their spatial distribution. This study integrated 2373 occurrence records of 44 Caragana species in China’s Three Northern Regions with four major environmental variable categories. Using the Biomod2 ensemble model, current and future climate scenario-based suitable habitats for Caragana spp. were predicted. This study innovatively combined quantitative analyses with Kira’s thermal indexes (warmth index, coldness index) and Wenduo Xu’s humidity index (HI) to elucidate species-specific relationships between distribution patterns and hydrothermal climatic constraints. The main results showed that (1) compared to other environmental factors, climate is the key factor affecting the distribution of Caragana spp. (2) The current distribution centroid of Caragana spp. is located in Alxa Left Banner, Inner Mongolia. In future scenarios, the majority of centroids will shift toward lower latitudes. (3) The suitable habitats for Caragana spp. will expand overall under future climate scenarios. High-stress scenarios exhibit greater spatial changes than low-stress scenarios. (4) Hydrothermal requirements varied significantly among species in China’s Three Northern Regions, and 44 Caragana species can be classified into five distinct types based on warmth index (WI) and humidity index (HI). The research findings will provide critical practical guidance for ecological initiatives such as the Three-North Shelterbelt Program and the restoration and management of degraded ecosystems in arid and semi-arid regions under global climate change. Full article

Abies nephrolepis and Picea jezoensis are native Pinaceae trees distributed in high mountainous regions of Northeast Asia (typically above ~1000 m a.s.l. on the Korean peninsula, northeastern China, Sakhalin, and the Russian Far East) and southern boreal forests, vulnerable to climate change and human disturbances, necessitating accurate habitat identification for effective conservation. While protected areas (PAs) are essential, merely expanding existing ones often fail to protect populations under human pressure and climate change. Using species distribution models with current and projected climate data, we mapped potential habitats across Northeast Asia. Spatial clustering analyses integrated with PA and land cover data helped identify optimal sites and priorities for new conservation areas. Ensemble species distribution models indicated extensive suitable habitats, especially in southern Sikhote-Alin, influenced by maritime-continental climates. Specific climate variables strongly affected habitat suitability for both species. The Kamchatka peninsula consistently emerged as an optimal habitat under future climate scenarios. Our study highlights essential environmental characteristics shaping the habitats of these species, reinforcing the importance of strategically enhancing existing PAs, and establishing new ones. These insights inform proactive conservation strategies for current and future challenges, by focusing on climate refugia and future habitat stability. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

South and Southeast Asia are considered biodiversity hotspots, yet they face escalating threats from deforestation and climate change. This study evaluates the suitable habitat extent of two sympatric flying squirrels, Petaurista elegans and Hylopetes phayrei, using ensemble distribution models based on the climate-only model (COM) and habitat–climate model (HCM) approaches. The results indicated severe habitat loss, with suitable areas comprising only 1.56–1.66% (P. elegans) and 0.22–2.47% (H. phayrei) of their estimated extent of occurrence. Within IUCN-defined ranges, the suitability for P. elegans was 28.25% and 30.04%, while H. phayrei showed 2.86% and 32.39% in terms of the HCM and COM, respectively. The analysis further revealed habitat fragmentation, reduced patch size, and edge complexity, with future scenarios predicting increased isolation. These results highlight the urgent necessity for region-specific conservation strategies focusing on habitat recovery, connectivity, and transboundary cooperation. The recommended actions include genetic studies, corridor analysis, and field validation. This research provides critical baseline data to inform integrated, multi-stakeholder conservation planning across South and Southeast Asia for the long-term persistence of these vulnerable flying squirrel species. Full article

Climate change poses a significant threat to the persistence of rear-edge populations, which are located at the margins of a species’ distribution range and are particularly vulnerable to environmental shifts. This study focuses on Yew (Taxus baccata L.) in the Iberian Peninsula, representing the southernmost extent of its range, where warming temperatures and decreasing moisture may compromise its survival. Our research aims to assess the climate sensitivity and habitat variability of Yew, addressing the hypothesis that future climate scenarios will significantly reduce the species’ climatic suitability, particularly in southern and low-altitude regions, and that this reduction will negatively impact individual growth performance. We used species distribution models (SDMs) based on ecological niche modeling (ENM) to project the current and future distribution of suitable habitats for Yew under two climate scenarios (SSP126 and SSP585). The models were calibrated using bioclimatic variables, and the resulting suitability maps were integrated with field data on individual growth performance, measured as basal area increment over the last five years (BAI5). The ensemble model showed high predictive performance, highlighting precipitation seasonality and annual mean temperature as the most influential variables explaining the climatic suitability distribution in the Iberian Peninsula. Our results indicate a substantial reduction in suitable habitats for Yew, especially under the high-emission scenario (SSP585), with southern populations experiencing the greatest losses. Furthermore, individual growth was positively correlated with climatic suitability, confirming that populations in favorable habitats exhibit better performance. These findings highlight the vulnerability of rear-edge populations of Yew to climate change and underscore the need for targeted conservation strategies, including the identification of climatic refugia and the potential use of assisted migration. Full article

Sterculia foetida L., commonly known as the Java olive, is a tropical tree species native to regions of East Africa, tropical Asia, and northern Australia. This study employs species distribution modeling (SDM) to predict the potential geographic distribution of S. foetida under current and future climate scenarios. Using 1425 occurrence data and 19 environmental variables, we applied an ensemble modelling approach of three algorithms: Boosting Regression Trees (BRT), Generalized Linear Model (GLM), and Random Forests (RF), to generate distribution maps. Our models showed high accuracy (mean AUC = 0.98) to indicate that S. foetida has a broad ecological niche, with high suitability in tropical and subtropical regions of north Australia (New Guinea and Papua), Southeast Asia (India, Thailand, Myanmar, Taiwan, Philippines, Malaysia, Sri Lanka), Oman and Yemen in the southwest of Asia, Central Africa (Guinea, Ghana, Nigeria, Congo, Kenya and Tanzania), the Greater and Lesser Antilles, Mesoamerica, and the north of South America (Colombia, Panama, Venezuela, Ecuador and Brazil). Indeed, the probability of occurrence of S. foetida positively correlates with the Maximum temperature of warmest month (bio5), Mean temperature of wettest quarter (bio8) and Precipitation of wettest month (bio13). The model results showed a suitability area of 4,744,653 km², representing 37.86% of the total study area, classified into Low (14.12%), Moderate (8.71%), and High suitability (15.02%). Furthermore, the study found that habitat suitability for S. foetida showed similar trends under both near future climate scenarios (SSP1-2.6 and SSP5-8.5 for 2041–2060), with a slight loss in potential distribution (0.24% and 0.25%, respectively) and moderate gains (1.98% and 2.12%). In the far future (2061–2080), the low scenario (SSP1-2.6) indicated a 0.29% loss and a 2.52% gain, while the high scenario (SSP5-8.5) showed a more dramatic increase in both loss (0.6%) and gain areas (3.79%). These findings are crucial for conservation planning and management, particularly in regions where S. foetida is considered invasive and could become problematic. The study underscores the importance of incorporating climate change projections in SDM to better understand species invasiveness dynamics and inform biodiversity conservation strategies. Full article

Climate change is reshaping the distribution of forest species globally, yet its effects on the temperate tree genus Carpinus in China remain understudied. This study used an ensemble species distribution modeling framework to predict current and future suitable habitats for 32 Carpinus taxa under three shared socioeconomic pathway (SSP) climate scenarios for the 2090s. Five algorithms were integrated, and models with high predictive performance (AUC > 0.9) were used to generate ensemble forecasts. The ensemble models achieved AUC values no lower than 0.987 and TSS values no lower than 0.904. The results showed a clear trend of northwestward and upslope range shifts, with substantial habitat contractions under high-emission scenarios. Temperature seasonality and annual precipitation were identified as key environmental drivers. Two narrowly distributed species, C. omeiensis and C. londoniana var. lanceolata, are projected to lose all suitable habitats under SSP585, indicating a high extinction risk. These findings emphasize the importance of integrating climate-based risk assessments into conservation strategies and highlight the need to prioritize vulnerable species and high-elevation refugia to safeguard the long-term persistence of Carpinus diversity in China. Full article