Climate and land-use interactions shape the future of an endangered butterfly in a warming world

Combined effects of environmentally relevant glyphosate concentration and elevated temperature on zebrafish embryotoxicity.

Identifying functional climate refugia of marine megafauna through analysis of functional diversity.

Increased groundwater recharge under climate change will enhance nitrogen fixation in groundwater-dependent ecosystems.

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Rhipicephalus microplus, a one-host tick species, serves as a principal vector of tick-borne diseases in agricultural ecosystems worldwide by harboring and transmitting various pathogens through blood-feeding. In China, the climatically suitable range of R. microplus has been gradually expanding. However, the climatic suitability of R. microplus under future climate change scenarios remains unclear. This study evaluates both current and projected climatic suitability of R. microplus by integrating climatic variables, thereby providing insight into shifts in climatic suitability under present and future climate conditions. The MaxEnt model was applied using 78 occurrence records of R. microplus collected from 1970 to 2023, along with 19 environmental variables obtained from WorldClim. By identifying the most influential environmental factors affecting the climatic suitability of R. microplus, we predicted future changes under three Shared Socioeconomic Pathways (SSP126, SSP245, SSP585) for three future periods (2021-2040, 2041-2060, and 2061-2080). This study indicates that the current climatically suitable areas for R. microplus are mainly located in southern China, covering approximately 1,051,406 km2, which accounts for about 10.91% of China's total land area. The minimum temperature of the coldest month (Bio06, 69.6%) and precipitation of the warmest quarter (Bio18, 20.1%) were identified as the most influential climatic variables. Under future climate scenarios, the suitable habitat for R. microplus is projected to expand and shift northward. By 2061-2080 under the SSP585, the suitable area could reach up to 2,994,700 km2, representing a 2.85-fold increase relative to its current extent. This study projects a significant northward expansion of climatic suitability for R. microplus in mainland China under future climate scenarios, driven primarily by rising minimum winter temperatures. These findings highlight an urgent need for proactive, climate-integrated surveillance and adaptive control strategies to mitigate the growing threat of this tick vector and its associated diseases in newly vulnerable regions.

Iris kuschakewiczii B.Fedtsch. is a rare ornamental plant endemic to the Northern Tien Shan mountains. The analysis of the species' distribution range is important given the declining habitat area. This study employed MaxEnt to project the distribution of I. kuschakewiczii under current and three future climate change scenarios (SSP126, SSP245, SSP585) for two time periods (the 2050s and the 2090s). Prediction models showed high validity (AUC = 0.997), strong accuracy, and reliability. Moreover, key environmental variables affecting the distribution of I. kuschakewiczii were identified. It included Weight and Percentage of Sand (70%), Temperature Seasonality (~ 2300), and Elevation (700-1300m above the sea level). Highly suitable distribution areas were mainly found in the Chu-Ili Mountains (Southeastern Kazakhstan). The analysis showed that only 26.7% of the total highly suitable area is protected by reserves and nature parks, underlying the need for conservation. The recently founded Kurty Valley Important Plant Area in Kazakhstan provides a strong foundation for the scientific conservation of I. kuschakewiczii and other rare and endangered plants. This research provides insights into the potential dynamics of habitat distribution for the endangered I. kuschakewiczii and offers a basis for strengthening cooperative international conservation and sustainable management strategies in the face of climate change.

Climate change is altering mosquito distributions and may reshape the risk of mosquito-borne diseases in the Republic of Korea (ROK). However, nationwide, multi-species projections for medically important mosquitoes remain limited. We compiled 1,969 spatially filtered occurrence records for 18 mosquito species and developed species distribution models using MaxEnt. Environmental predictors included bioclimatic, topographic, and land cover variables. Future distributions were projected for the 2030s, 2050s, and 2070s under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios using MIROC6 climate data. A Climate Change Vulnerability Index (CCVI) was calculated to compare species-specific range expansion and contraction. Current habitat suitability patterns grouped the 18 species into nationwide, northern-preferring, southwestern-preferring, and southern-preferring distribution types. Topographic Wetness Index (36.6%), elevation (18.6%), and land cover type (18.4%) contributed more strongly to model performance than climatic variables alone. Under SSP5-8.5 in the 2070s, Aedes albopictus and Culex tritaeniorhynchus were projected to expand suitable habitat by 183.4% and 236.5%, respectively, whereas northern-preferring Anopheles species showed marked habitat contraction. Anopheles pullus and Anopheles belenrae were projected to lose 100.0% of their suitable habitat under the highest-emission scenario. The CCVI classified five species, mainly Anopheles, as highly vulnerable, one species as moderately affected, and 12 species as range-expanding. These findings indicate that climate change may substantially reorganize mosquito communities in the ROK, reducing habitat suitability for several malaria vectors while expanding suitable areas for important arbovirus and Japanese encephalitis vectors. Adaptive surveillance and vector management should therefore integrate climate projections with local landscape and hydrological risk factors.

Peering into the twilight: a systematic review on visual-based investigation of worldwide mesophotic ecosystems.

Introduction Aconitum pendulum is a rare medicinal plant endemic to the Qinghai-Tibet Plateau and a key indicator species for alpine ecosystems. It possesses both medicinal and ecological value. However, its wild populations are on the verge of decline due to overharvesting and low reproductive capacity, and the species is highly sensitive to climate change. Methods In this research, the kuenm package was employed to optimize the maximum entropy model, so as to predict the distribution of A. pendulum in China under both current and future climate scenarios. From a total of 103 environmental variables, 11 key factors influencing the distribution of A. pendulum were selected through correlation analysis and variable contribution rate evaluation. Based on 188 valid distribution sites of A. pendulum , an analysis was conducted on its potential habitat distribution in China under current and future climatic conditions. Results The results demonstrate that under the current climate, the total area of suitable habitats for A. pendulum is 2.08×10 6 km 2 , accounting for 21.56% of China’s land area, and these habitats are mainly distributed in the southwest, northwest, and central regions of the country. Altitude, september solar radiation, and temperature seasonality were identified as the main factors affecting the distribution of A. pendulum . Under future climate change scenarios, the overall area of suitable habitats for A. pendulum exhibits a decreasing trend. Under the low-emission scenario, the area of unsuitable areas shows slight fluctuations, while the low-, medium-, and high-suitable distribution areas within the suitable zones remain balanced. Under the high-emission scenario, the edge areas of unsuitable areas shrink rapidly, whereas the high-suitable areas expand slightly. The centroid migration of the suitable habitats did not deviate from the core region located on the eastern edge of the Qinghai-Tibet Plateau, indicating that A. pendulum still has adaptive potential under climate change. Discussion This study highlights the significant impacts of altitude, September solar radiation, and temperature seasonality on the distribution of A. pendulum , and provides a scientific basis for the protection, planting planning, and sustainable development of A. pendulum .

Echinococcosis, a neglected zoonosis caused by Echinococcus parasites, imposes a dual burden on public health and socioeconomic development across China, with disproportionate impacts on impoverished pastoral communities. A critical barrier to targeted and effective control lies in the lack of high-resolution national risk maps and limited understanding of how climate change modulates transmission dynamics. Here, we address these gaps by integrating multi-source epidemiological and environmental data to model and map high-resolution echinococcosis transmission risk across China. We further project its spatiotemporal evolution under four climate change scenarios (SSP126, SSP245, SSP370, SSP585) from 2040 to 2100, employing a One Health framework to assess echinococcosis transmission risk. Our model exhibits robust predictive performance, identifying elevation, annual precipitation, precipitation seasonality, isothermality, and average monthly precipitation in January as key driving factors. Results reveal concentrated high-risk regions in western and northern China, including Sichuan, Qinghai, Tibet, Xinjiang, and Gansu provinces, which are characterized by pastoral economies, socioeconomic underdevelopment, and constrained healthcare access. Future projections show a concerning expansion of high and very high transmission risk regions across all scenarios, with the most significant increase under the high-emission SSP585 pathway by the late twenty-first century. These findings clarify the current echinococcosis risk landscape and its environmental determinants while providing forward-looking, spatially explicit evidence. This work establishes a science-based foundation for optimizing resource allocation, designing adaptive prevention strategies, and enhancing health equity within a One Health framework, particularly for climate-vulnerable and resource-limited settings.

ABSTRACTPlant distribution correlates with climate change, especially in mountain flora. Using an optimized MaxEnt model and the latest WorldClim 2.1 bioclimatic data, this study identified the key environmental determinants of habitat suitability and projected the current and future distribution patterns of seven Meconopsis spp. in China under various climate change scenarios. Results reveal that the primary environmental variables shaping the distribution are isothermal (bio3), seasonal variation coefficient of temperature (bio4), and elevation. Seven taxa were concentrated in southwestern China, with suitable habitats encompassing 1.3% to 10.1% of the land area in China. Under future climate scenarios, M. lyrata is expected to experience a decline in habitat suitability, and other species showed mixed responses. Given the limited extent of suitable habitats for most Meconopsis species in China, ex‐situ conservation—particularly through initiatives spearheaded by national botanical research institutions—should prioritize domestication and conservation efforts to safeguard genetic diversity.

The physiological and metabolic responses of juvenile Chinese softshell turtles, Pelodiscus sinensis, exposed to single or double heatwaves (33 °C for 4 days) were investigated based on liver antioxidant assay and transcriptomic and metabolomic analyses. Heatwave exposure increased superoxide dismutase and catalase activities, but did not significantly alter malondialdehyde and reactive oxygen species levels, indicating enhanced antioxidant defense. Transcriptomic analysis revealed the differential expression of genes involved in carbohydrate metabolism, immune function, cardiovascular regulation, and signal transduction, with more pronounced alterations in single-heatwave-exposed turtles. Additionally, metabolic dysregulation in amino acids was revealed by significantly altered levels of some key amino acids and their derivatives. Compared with single-heatwave-exposed turtles, fewer differentially expressed genes and less metabolic disruptions in double-heatwave-exposed turtles probably indicated less physiological disorders under recurrent heat stress. Although P. sinensis can adopt physiological and metabolic adjustments to mitigate the adverse effects of short-term heatwaves, repeated heatwave exposure might still cause severe physiological consequences in aquatic turtles. These findings may have important implications for the conservation of freshwater turtle species under future climate change scenarios.

This study examined historical trends and variability, as well as future projections of rainfall and temperature under different emission scenarios in Bale Mountains National Park (BMNP), southeastern Ethiopia. For the historical analysis, thirty years (1994-2023) of daily rainfall and temperature data from eight meteorological stations within and surrounding the park were obtained from the National Meteorology Institute of Ethiopia. Future climate conditions were projected using an ensemble of eight Global Climate Models (ACCESS-CM2, CMCC-ESM2, CNRM-CM6-1, INM-CM4-8, MIROC-ES2L, MPI-ESM1-2-LR, NorESM2-MM, and MRI-ESM2-0) from CMIP6 under three emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5), covering the near future (2021-2040), mid-century (2041-2070), and end of the century (2071-2099). Statistical methods, including descriptive statistics, spatial interpolation, the Mann-Kendall trend test, and Sen's slope estimator, were used to evaluate spatiotemporal patterns of historical climate variables. In addition, decadal deviations from long-term means were analyzed using the Inverse Distance Weighting (IDW) technique in ArcGIS 10.8 to identify climate shifts. The Delta method was applied to downscale Global Climate Model outputs for improved regional relevance. Results revealed strong spatial variability in rainfall influenced by elevation and orographic effects, with higher precipitation observed in elevated areas. Despite noticeable year-to-year fluctuations, most stations showed declining rainfall trends, particularly after 2000, indicating a shift toward drier conditions. Over the last three decades (1994-2023), the annual mean rainfall decreased by about 100mm, while the maximum and minimum temperatures increased by approximately 1.6°C and 1.7°C, respectively, between the first decade (1994-2003) and the last decade (2014-2023). Future projections indicate increases in both rainfall and temperature relative to the 1985-2014 baseline period. The most pronounced changes are expected under the high-emission scenario (SSP5-8.5) by 2071-2099, with rainfall increasing by about 265mm and temperatures rising by up to 3.9°C. These findings highlight the urgency of sustained climate monitoring and adaptive conservation strategies.

Projected Increases in Heat-Related Emergency Department Imaging Utilization Under Climate Change Scenarios.

ABSTRACTThe Qinghai–Tibet Plateau hosts the rare alpine Tibetan medicinal herb Corydalis hendersonii Hemsl. The wild resources of C. hendersonii are being increasingly threatened by climate warming and intensified human activity. We employed a biomod2 ensemble species distribution model, integrating climatic variables, light/radiation variables, soil‐property layers, topographic variables, and the Human Footprint Index with 75 spatially rarefied occurrence records, to predict the potential geographic distribution and shifts in habitat suitability under SSP126 and SSP585 (2050s, 2070s, and 2090s), climate dependence, human‐footprint effects, and ecological niche dynamics. 10 algorithms were calibrated with pseudo‐absences and repeated resampling, and the high‐performing models (ROC > 0.9; TSS > 0.8) were combined into a weighted ensemble; XGBoost yielded the highest single‐model accuracy. Ultraviolet radiation (UV‐B) was the dominant predictor of suitability, followed by elevation and key thermal‐contrast variables (BIO1, BIO4, and BIO7), indicating strong adaptation to high‐altitude extreme environments characterized by intense radiation, low mean temperature, and large temperature amplitudes. The current high‐suitability habitats are concentrated in Tibet, with limited patches in southern Xinjiang, southern Qinghai, western Sichuan, and northern Yunnan, reflecting a narrow alpine niche. Future projections diverge strongly between pathways: under SSP126, moderate–high suitability is maintained and slightly expanded, whereas under SSP585, high‐suitability areas contract, leading to an overall shift toward higher‐elevation refugia and a northwestward migration of the centroid. When the Human Footprint Index layer was included, high‐suitability areas consistently decreased and peripheral contraction became more pronounced, indicating that climate‐only projections overestimate realized habitat area. Climatic niche overlap remained high overall but declined and fluctuated more under SSP585, suggesting niche displacement under intense climate warming. The results provide a basis for conserving C. hendersonii by prioritizing core habitats and implementing targeted management under future climate change scenarios.

Climate change profoundly affects plant habitats and ecological niches, particularly among Tertiary relict flora—remnants of warm and humid climatic conditions that prevailed during the Tertiary period—which are recognized as highly climate-sensitive lineages. The genus Lindera (Lauraceae), a representative group of deciduous broad-leaved trees in East Asian temperate forests, provides an ideal model for examining shifts in habitat suitability and changes in predicted suitable environments under future climate change scenarios. In this study, we developed ensemble species distribution models (SDMs) using six algorithms to predict the distributions of four Lindera species—L. obtusiloba, L. glauca, L. erythrocarpa, and L. sericea—under three Shared Socioeconomic Pathway (SSP) scenarios (SSP1–2.6, SSP3–7.0, SSP5–8.5). Among the three categories of environmental variables, climatic factors exerted the greatest influence on habitat suitability, with temperature seasonality (bio4) and growing-season precipitation (gsp) identified as the primary determinants. With intensifying climate change, suitable habitats shifted northward and upward, accompanied by pronounced habitat losses across southern and central Korea. Despite its broad geographic range, L. obtusiloba exhibited an 81% reduction in suitable habitat, whereas L. sericea, due to its localized distribution, showed a 91% decrease and was identified as the most climate-vulnerable species. Ecological niche overlap (Schoener’s D) declined across all scenarios, indicating increasing ecological differentiation among species. Although the four Lindera species exhibited distinct spatial responses, all consistently experienced range contractions and reduced overlap in predicted suitable environments, indicating high vulnerability to climate change. These results suggest that intrinsic ecological traits, climatic sensitivity, and niche stability—rather than current geographic range extent—are key determinants of species persistence. Accordingly, Lindera species in southern Korea should be considered climate-vulnerable taxa, and conservation strategies should integrate the protection of climatically stable refugia with complementary conservation measures beyond natural habitats to ensure long-term persistence under future climate change.

The physical structure of lakes, particularly vertical temperature stratification, governs the dissolved oxygen distribution and underpins freshwater ecosystem health. Accurately predicting temperature profiles is therefore essential for understanding key ecological processes. Traditional mechanistic models provide physically consistent simulations but can be computationally intensive and sensitive to input assumptions, whereas purely data-driven models may offer high predictive accuracy, yet lack physical interpretability. In this work, we present a mixture-of-experts framework that integrates a physics-motivated neural network with an unconstrained deep neural network model to predict lake water temperatures across depths. The physics-motivated component enforces physically consistent vertical profiles via a learnable logistic formulation, while the data-driven expert captures empirical patterns from observations. A gating mechanism dynamically combines the two experts, balancing statistical flexibility and physical fidelity. Applied across lakes with diverse morphologies, the framework accurately reproduces the timing, magnitude, and vertical structure of thermal stratification. The model is further used to project future lake temperatures under climate change scenarios, which point to a warming trend in near-surface temperatures, providing a tool to assess potential shifts in stratification and their ecological consequences for freshwater systems.

Co-occurrence bloom of lipophilic toxic-producers in a hotspot Chilean fjord: Fine-scale distribution, toxins and fate in shellfish.

Rising temperatures and humidity threaten global livestock production and food security. This study assesses the future impacts of heat stress in regions with high livestock production in Brazil by analyzing high-resolution (5 km) climate projections from the Eta Regional Climate Model under the RCP4.5 and RCP8.5 scenarios. Using the Temperature-Humidity Index (THI), we evaluated future heat stress conditions for dairy and beef cattle, goats, sheep, pigs, broilers, and layers. The results indicate a substantial increase in both the frequency and intensity of heat stress events across Brazil during the 21st century, especially under the RCP8.5 scenario. The number of days reaching extreme heat-stress levels ( ndaysTHI ) is projected to increase significantly, particularly in the western and central regions of the study area, and for more vulnerable species such as pigs and poultry. For instance, the number of extreme THI days for dairy cattle and goats is projected to increase by up to 244 days by the end of the century (long-term period compared to historical) under RCP8.5. This research provides essential data for developing effective and sustainable adaptation strategies to mitigate the effects of climate change on Brazil's livestock sector, offering insights applicable to other countries facing similar challenges. It addresses a significant knowledge gap by providing high-resolution, localized projections of future heat stress across Brazil's major production regions. • Extreme heat stress days (ndaysTHI) will substantially increase in Brazil. • High-resolution Eta RCM used for novel, localized impact projections. • Pigs and poultry are the most vulnerable species to future heat stress. • Dairy cattle/goats ndaysTHI projected to increase up to 244 days (RCP8.5). • Results inform sustainable adaptation strategies for Brazil's livestock sector.