Potential Changes in Suitable Habitats of Prunus laurocerasus in Türkiye under the Impacts of Global Climate Change

Climate change has already impacted ecosystems and species and substantial impacts of climate change in the future are expected. Species distribution modeling is widely used to map the current potential distribution of species as well as to model the impact of future climate change on distribution of species. Mapping current distribution is useful for conservation planning and understanding the change in distribution impacted by climate change is important for mitigation of future biodiversity losses. However, the current distribution of Chinese caterpillar fungus, a flagship species of the Himalaya with very high economic value, is unknown. Nor do we know the potential changes in suitable habitat of Chinese caterpillar fungus caused by future climate change. We used MaxEnt modeling to predict current distribution and changes in the future distributions of Chinese caterpillar fungus in three future climate change trajectories based on representative concentration pathways (RCPs: RCP 2.6, RCP 4.5, and RCP 6.0) in three different time periods (2030, 2050, and 2070) using species occurrence points, bioclimatic variables, and altitude. About 6.02% (8,989 km2) area of the Nepal Himalaya is suitable for Chinese caterpillar fungus habitat. Our model showed that across all future climate change trajectories over three different time periods, the area of predicted suitable habitat of Chinese caterpillar fungus would expand, with 0.11–4.87% expansion over current suitable habitat. Depending upon the representative concentration pathways, we observed both increase and decrease in average elevation of the suitable habitat range of the species.

We predict current distribution and abundance for tree species present in eastern North America, and subsequently estimate potential suitable habitat for those species under a changed climate with 2×CO2. We used a series of statistical models (i. e., Regression Tree Analysis (RTA), Multivariate Adaptive Regression Splines (MARS), Bagging Trees (BT) and Random Forests (RF)) via our model, DISTRIB, for this purpose. These techniques were evaluated on several tree species, and advantages and disadvantages of each method were noted. RF provides the best prediction maps of potential suitable habitat. Overall, a combination of RTA, BT, and RF may yield the best information and most interpretable maps of suitable habitat. Using these tools, we provide statistics on potential changes in suitable habitat for 135 tree species of eastern North America.A suitable habitat does not guarantee the presence of a species, as many barriers for the species still exist before it will be able to colonize that new suitable habitat. Dispersal ability, abundance of the colonizing species, and the nature of fragmented landscapes also influence migration and are modeled with our cellular automata model, SHIFT. For each cell outside a species' current boundary, SHIFT creates an estimate of the probability that each unoccupied cell will become colonized over 100 years. By evaluating the probability of colonization within the potential “new” suitable habitat, we can estimate the proportion of new habitat that might be colonized within a century. This proportion is low (<15%) for five example species, suggesting that there is a serious lag between the potential movement of suitable habitat and the potential for the species to migrate into the new habitat. However, humans could accidentally or purposefully alter the migration rates of species by physically moving the propagules.

Differential impact of climate and land use change on habitat suitability of migrant passerines according to habitat preferences

Vultures provide invaluable ecosystem services and play an important role in ecosystem balancing. The number of native vultures in India has declined in the past. Acquiring present knowledge of their habitat spread is essential to manage and prevent such a decline. It is envisaged that ongoing climate crisis may further cause change in habitat suitability and impact the existing population. Therefore, this study in Central India—a vulture stronghold, is aimed at predicting habitat changes in the short and long term and present the data statistically and graphically by using Species Distribution Model. MaxEnt software was chosen for its advantages over other models, like using presence-only data and performing well with incomplete data, small sample sizes and gaps, etc. Global Climate Model ensemble (CCSM4, HadGEM2AO and MIROC5), was used to get better prediction. Fourteen robust models (AUC 0.864–0.892) were developed using data from over 1000 locations of seven vulture species over two seasons together. Selected climatic and other environmental variables were used to predict the current habitat. Future prediction was based on climatic variables only. The most important variables influencing the distribution were precipitation (bio 15, bio 18, bio 19) and temperature (bio 3, bio 5). Forest and water bodies were the major influencers within land use-landcover in the current prediction. At finer scale, while extremely suitable habitat area decreased and highly suitable area increased over time, the total suitable area marginally increased in 2050 but decreased in 2070. For broader consideration, net loss in suitable area was 5% in 2050 and 7.17% in 2070 (RCP4.5). Similarly, in the RCP8.5 this was 6% in 2050 and 7.3% in 2070. The data generated can be used in conservation planning and management and thus protecting the vultures from any future threat.

BackgroundUnderstanding the abiotic and biotic drivers of species distribution is critical for climate-informed ecosystem management. We aimed to understand habitat selection of northern fur seals in the eastern Bering Sea, a declining population that is also a key predator of walleye pollock, the target species for the largest U.S. commercial fishery.MethodsWe developed species distribution models using random forest models by combining satellite telemetry data from lactating female fur seals tagged at different rookery complexes on the Pribilof Islands in the eastern Bering Sea with regional ocean model simulations. We explored how data aggregation at two spatial scales (Pribilof-wide and complex-specific) impacted model performance and predicted distributions. Spatial predictions under hindcasted (1992–2018) and projected (2050–2059) physical and biological conditions were used to identify areas of core habitat, overlap with commercial fishery catches, and potential changes in future habitat suitability.ResultsThe most important environmental predictor variables across all models were bathymetry, bottom temperature, and surface temperature. The Pribilof-wide model both under- and overrepresented the importance of specific areas, while complex-specific models exhibited considerable variability in transferability performance. The majority of core habitat occurred on the continental shelf in areas that overlapped with commercial catches of walleye pollock during the “B” season (June – October), with an average of 76% of the total percentage of the catch occurring in core fur seal habitat within the foraging range of lactating females. Projections revealed that considerable changes in fur seal habitat suitability may occur in the coming decades, with complex-specific variation in the magnitude and direction of changes.ConclusionsOur results illustrate the need to sample multiple sites whenever possible and consider spatial scale when extrapolating species distribution model output for central-place foragers, even when terrestrial sites are < 10 km apart. The high overlap between suitable fur seal habitat and commercial fishery catches of pollock, coupled with projected changes in habitat suitability, underscore the need for targeted studies investigating fisheries impacts on this declining population.

Predicting the potential habitat suitability of Saussurea species in China under future climate scenarios using the optimized Maximum Entropy (MaxEnt) model

Background: Habitat suitability of Anopheles mosquitoes depends on appropriate climate and land-use conditions. Anopheles are the main vectors for malaria transmissions in the Euro-Mediterranean region. There is major concern that there will be a spread or shift of Anopheles species due to the expected climate and land-use change. This study aims to identify the main climate and land-use drivers for changes in the habitat suitability for six different Anophelesspecies between 2000 and 2020 within the Euro-Mediterranean region. Methods: Boosted Regression Trees were applied to establish the link between climate and land-use predictors and habitat suitability. An ensemble of 16 models, based on different methods of selecting background points and statistical predictors, was applied to each species. The ensemble was evaluated by means of model skill and transferability to identify the best model. Under consideration of contribution, interactions and response range, the most important predictors and those responsible for changes were identified. Results: The model ensembles agree on the direction of change for four species within the study area, with two showing an overall increase (An. atroparvus, An. sacharovi) of areas with suitable conditions and two showing a decrease (An. messeae, An. sergentii). Climate change is mainly responsible for shifts in the habitat suitability. Only a few models attribute changes mainly to land-use. The limited influence of land-use changes may be due to the too coarse spatial resolution. For most species, temperature-related bioclimatic variables (BIO4, BIO5, BIO8) are the most important predictors for changes in habitat suitability. A superior method for either the specific background points or predictor selection did not emerge, because they depend on the species analyzed. Conclusions: Between 2000 and 2020, rising temperatures were the main driver of changes in the habitat suitability of the Anopheles species in the Euro-Mediterranean region, with land-use changes having a relatively minor impact. Especially regions to the north of the distribution area are characterized by a greater habitat suitability, while regions to the south show decreasing trends. This may also impact the risk of local malaria transmission in these regions.

BackgroundHabitat suitability of Anopheles mosquitoes depends on appropriate climate and land-use conditions. Anopheles mosquitoes are the main vectors for malaria transmission in the Euro-Mediterranean region, and there are major concerns that these species will expand and/or shift their range due to the expected changes in climate and land-use. This study aims to identify the main climate and land-use drivers of changes in the habitat suitability for six different Anopheles species between 2000 and 2020 within the Euro-Mediterranean region.MethodsBoosted regression trees were applied to establish the link between climate and land-use predictors and habitat suitability. An ensemble of 16 models, based on different methods of selecting background points and statistical predictors, was applied to each species. The ensemble was evaluated by means of model skill and transferability to identify the best model. Taking contribution, interactions and response range into account, the most important predictors and those responsible for changes were identified.ResultsThe model ensembles agreed on the direction of change for four Anopheles species within the study area, with two of these showing an overall increase (An. atroparvus, An. sacharovi) of areas with suitable conditions and two showing a decrease (An. messeae, An. sergentii). Climate change was found to be the main driver of shifts in habitat suitability, with only a few models attributing changes mainly to land-use. The limited influence of land-use changes may be due to the spatial resolution being too coarse. For most species, temperature-related bioclimatic variables (BIO4, BIO5, BIO8) were the most important predictors of changes in habitat suitability. A superior method for either the specific background points or predictor selection did not emerge because the relative ranking of the corresponding models is dependent on the species analyzed.ConclusionsBetween 2000 and 2020, rising temperatures were the main driver of changes in the habitat suitability of Anopheles mosquitoes in the Euro-Mediterranean region, with land-use changes having a relatively minor impact. In particular, regions to the north of the respective distribution area were found to be characterized by an increasing habitat suitability, while regions to the south showed decreasing trends. These trends may also impact the risk of local malaria transmission in these regions.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s13071-025-07115-0.

Organisms are projected to shift their distribution ranges under climate change. The typical way to assess range shifts is by species distribution models (SDMs), which predict species’ responses to climate based solely on projected climatic suitability. However, life history traits can impact species’ responses to shifting habitat suitability. Additionally, it remains unclear if differences in vital rates across populations within a species can offset or exacerbate the effects of predicted changes in climatic suitability on population viability. In order to obtain a fuller understanding of the response of one species to projected climatic changes, we coupled demographic processes with predicted changes in suitable habitat for the monocarpic thistle Carlina vulgaris across northern Europe. We first developed a life history model with species‐specific average fecundity and survival rates and linked it to a SDM that predicted changes in habitat suitability through time with changes in climatic variables. We then varied the demographic parameters based upon observed vital rates of local populations from a translocation experiment. Despite the fact that the SDM alone predicted C. vulgaris to be a climate ‘winner’ overall, coupling the model with changes in demography and small‐scale habitat suitability resulted in a matrix of stable, declining, and increasing patches. For populations predicted to experience declines or increases in abundance due to changes in habitat suitability, altered fecundity and survival rates can reverse projected population trends.

AimTo assess how climate change may decouple the ecosystems used by a migratory fish, and how decoupling influences priorities for stream restoration.LocationAustralia.MethodsWe modelled changes in habitat suitability under climate change in both riverine and marine habitats for a threatened diadromous species, the Australian Grayling Prototroctes maraena, using niche models. The loss of riverine habitats for Grayling was compared with or without considering the impact of climate change on adjacent marine habitats. We also asked whether considering marine climate change changed the locations where removing dams had the greatest benefit for Grayling conservation.ResultsClimate change is expected to cause local extinction in both marine and river habitats regardless of whether dams are retained or removed at the trailing edge of the Grayling's range (north‐eastern). Decoupling of habitats was most apparent in the eastern and south‐eastern portion of the Grayling's range, where ocean warming may cause a decline in the suitability of marine habitats for larvae, while many freshwater habitats retained suitable habitat for adults. Removing dams to restore connectivity between ocean and freshwater habitats was predicted to have the greatest benefit for Grayling in southern portions of their range. Under climate change, the priorities for barrier removal gradually shift towards dams at higher elevation because of increasing suitability of freshwater habitats at higher elevations.Main conclusionsOur study highlights the importance of assessing climate range shifts in multiple ecosystems for migratory species and can help inform priorities for stream restoration under a changing climate.

Introduction: Climate change alters environmental and climatic conditions, leading to expansion or contraction and possible shifts in the geographical distribution of vectors that transmit diseases. Bulinus globosus and Biomphalaria pfeifferi are the intermediate host snails for human schistosomiasis in KwaZulu-Natal (KZN) province, South Africa.Methods: Using the Maximum entropy (MaxEnt) model, we modelled the current and future distribution of human schistosomiasis intermediate host snails in KZN using two representation concentration pathways (RCP4.5 and RCP8.5) for the year 2085. Thirteen and ten bioclimatic variables from AFRICLIM were used to model the habitat suitability for B. globosus and B. pfeifferi, respectively. The Jack-knife test was used to evaluate the importance of each bioclimatic variable.Results: Mean temperature warmest quarter (BIO10, 37.6%), the number of dry months (dm, 32.6%), mean diurnal range in temperature (BIO2, 10.8%), isothermality (BIO3, 6.7%) were identified as the top four bioclimatic variables with significant contribution to the model for predicting the habitat suitability for B. globosus. Annual moisture index (mi, 34%), mean temperature warmest quarter (BIO10, 21.5%), isothermality (BIO3, 20.5%), and number of dry months (dm, 7%) were identified as the four important variables for the habitat suitability of B. pfeifferi. Area under the curve for the receiving operating characteristics was used to evaluate the performance of the model. The MaxEnt model obtained high AUC values of 0.791 and 0.896 for B. globosus and B. pfeifferi, respectively. Possible changes in the habitat suitability for B. globosus and B. pfeifferi were observed in the maps developed, indicating shrinkage and shifts in the habitat suitability of B. pfeifferi as 65.1% and 59.7% of the current suitable habitats may become unsuitable in the future under RCP4.5 and RCP8.5 climate scenarios. Conversely, an expansion in suitable habitats for B. globosus was predicted to be 32.4% and 69.3% under RCP4.5 and RCP8.5 climate scenarios, with some currently unsuitable habitats becoming suitable in the future.Discussion: These habitat suitability predictions for human schistosomiasis intermediate host snails in KZN can be used as a reference for implementing long-term effective preventive and control strategies for schistosomiasis.

Predicting the current habitat suitability and future habitat changes of Antarctic jonasfish Notolepis coatsorum in the Southern Ocean

Coffea arabica (Arabica coffee) is an important cash crop in Yunnan, China. Ongoing climate change has made coffee production more difficult to sustain, posing challenges for the region's coffee industry. Predictions of the distribution of potentially suitable habitats for Arabica coffee in Yunnan could provide a theoretical basis for the cultivation and rational management of this species. In this study, the MaxEnt model was used to predict the potential distribution of suitable habitat for Arabica coffee in Yunnan under current and future (2021-2100) climate scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) using 56 distributional records and 17 environmental variables and to analyze the important environmental factors. Marxan model was used to plan the priority planting areas for this species at last. The predicted suitable and sub-suitable areas were about 4.21×104 km2 and 13.87×104 km2, respectively, accounting for 47.15% of the total area of the province. The suitable areas were mainly concentrated in western and southern Yunnan. The minimum temperature of the coldest month, altitude, mean temperature of the wettest quarter, slope, and aluminum saturation were the main environmental variables affecting the distribution of Arabica coffee in Yunnan Province. Changes in habitat suitability for Arabica coffee were most significant and contracted under the SSP3-7.0 climate scenario, while expansion was highest under the SSP5-8.5 climate scenario. Priority areas for Arabica coffee cultivation in Yunnan Province under the 30% and 50% targets were Pu'er, Xishuangbanna, Honghe, Dehong, and Kunming. Climate, soil, and topography combine to influence the potential geographic distribution of Arabica coffee. Future changes in suitable habitat areas under different climate scenarios should lead to the delineation of coffee-growing areas based on appropriate environmental conditions and active policy measures to address climate change.

The smoke tree (Cotinus coggygria Scop.) is a woody species mainly distributed in the Mediterranean region and East Asia, known for its high ecological and ornamental value. Investigation of changes in suitable habitats under different conditions can provide valuable insights with implications for predicting the distribution of C. coggygria. In this study, we employed a MaxEnt model to simulate the current, historical, and future suitable habitat of C. coggygria using distribution records and environmental variables. The results indicated that climatic variables had a much stronger impact on the suitable habitat of this species compared with soil and topographic variables, and bio11 (mean temperature of the coldest quarter) and bio12 (annual precipitation) played particularly important roles in determining the suitable habitat. The core distribution of C. coggygria exhibited an East Asian-Tethyan disjunction. During the glacial period (Last Glacial Maximum), C. coggygria in Europe was concentrated in the glacial refugia in southern Europe; its range was substantially smaller during the glacial period than during interglacial periods (mid-Holocene). In contrast, C. coggygria in East Asia survived in regions similar to those of the interglacial period. Future climate change led to a gradual northward expansion of suitable habitats for C. coggygria, and the area of suitable habitat was substantially larger in Europe than in East Asia. There were significant differences among the four climate scenarios in Europe, with minimal variation in East Asia. Our findings provide valuable insights into the contrasting effects of climate change on European and East Asian populations of C. coggygria, which enhances our understanding of Eurasian species with discontinuous distributions.

Chimonobambusautilis is a unique edible bamboo species valued for its economic and nutritional benefits. However, its existence in natural habitats is at risk due to environmental shifts and human interventions. This research utilised the maximum entropy model (MaxEnt) to predict potential habitats for Ch.utilis in China, identifying key environmental factors influencing its distribution and analysing changes in suitable habitats under future climate conditions. The results show that the results of the MaxEnt model have high prediction accuracy, with an AUC (Area Under the receiver operating characteristic Curve) value of 0.997. Precipitation in the driest month (Bio14), altitude (Alt) and isothermality (Bio03) emerged as the primary environmental factors influencing the Ch.utilis distribution. Currently, the suitable habitats area for Ch.utilis is 10.55 × 104 km2. Projections for the 2050s and 2090s indicate potential changes in suitable habitats ranging from -3.79% to 10.52%. In general, the most suitable habitat area will decrease and shrink towards higher latitude areas in the future. This study provides a scientific basis for the introduction, cultivation and conservation of Ch.utilis.