Climate Change Scenarios Research Articles

Impact of extreme heat on health in Australia: a scoping review

Climate change has been recognized as a driver of increased heatwave events in the Asia Pacific region, including Australia. This review systematically retrieved and summarized published evidence on heat-related health impacts in Australia, focusing on heat-associated deaths, morbidity, and vulnerability. We searched PubMed, Scopus, Embase, and Web of Science for heat-health studies published in Australia between 2007 and 2023. A total of 64 articles met the inclusion criteria and were included in our review. Most were epidemiological studies [56 (87.5%)], which accumulatively considered 85 different cause-specific diseases linked to deaths, hospital admissions, emergency department (ED) presentations, and ambulance callouts, while eight studies focused on heat vulnerability index (HVI) assessment. We found strong evidence of increasing risks for heat-associated deaths among individuals with mental/behavioral disorders, cardiovascular diseases, diabetes, and respiratory disease. Evidence supporting an increasing risk for renal/genitourinary-related deaths was limited. The majority of studies reported an increase in heat-associated hospitalization, particularly for patients with renal disease, neurological disease, stroke, mental disorders, diabetes, and ischemic heart disease. Heat-associated ambulance callouts was prominent for patients with cardiovascular and respiratory diseases. This evidence suggests that these heat-related diseases should be used as health indicators for developing and validating HVI in Australia. Most studies did not examine the long-term changes in vulnerability and lacked evaluation with cause-specific health data. Future research must incorporate HVI across diverse climate change scenarios to more accurately inform long-term adaptation measures among vulnerable communities. In addition, research should target nationwide longitudinal heat vulnerability and examine the benefits of using HVI in heatwave action plans.

Geography and Environment Shape Spatial Genetic Variation and Predict Climate Maladaptation Across Isolated and Disjunct Populations of Pinus muricata.

Assessing the evolutionary potential of rare species with limited migration amidst ongoing climate change requires an understanding of patterns of genetic variation and local adaptation. In contrast to the large distributions and population sizes of most pines, Pinus muricata (bishop pine) occurs in a few isolated populations along coastal western North America and is listed as threatened by the IUCN. To quantify how current genetic variation is influenced by distribution and environment, we generated reduced representation DNA sequencing data for most extant populations of P. muricata (12 locations, 7828 loci). We assessed geographic variation in differentiation and diversity and used genetic-environment association (GEA) analyses to characterise the contribution of environmental variables to local adaptation and genetic structure. Based on these inferences, we quantified genomic offset as a relative estimate of potential maladaptation under mild (SSP1-2.6) and severe (SSP5-8.5) climate change scenarios across 2041-2060 and 2081-2100. Despite occurring in small, isolated populations, genetic diversity was not low in P. muricata. Population differentiation was, however, defined across a hierarchy of spatial scales, with stands generally forming genetically identifiable groups across latitude and environments. GEA analyses implicated temperature- and soil-related variables as most strongly contributing to local adaptation. Estimates of maladaptation to future climate varied non-linearly with latitude, increased with severity of projections and over time, and were predicted by increases in annual temperature. Our results suggest that isolation and local adaptation have shaped genetic variation among disjunct populations and that these factors may shape maladaptation risk under projected climate change.

A laboratory-scale physical model for freeze-thaw studies in soil columns under simulated climate change conditions.

Responses of soils to climate warming during winter can be studied by monitoring soil temperature variations in the vadose zone. Freeze-thaw cycles during winter can have a significant impact on soil biogeochemical and physical processes. Observing soil temperature at different depths offers important insights into heat availability, which influences biogeochemical activity and solute movement driven by temperature gradients. However, it is difficult to replicate the relevant processes in soil columns without maintaining freezing temperatures with an unfrozen soil layer below the freezing interface. This paper describes the development and experimental verification of a laboratory-scale physical model to assess the effect of freeze-thaw cycles on biogeochemical processes in unsaturated soil. The results show that the experimental design can (i) induce cyclical freezing of soil down to desirable depths, (ii) maintain vertical temperature gradients and (iii) ensure the rest of the column remains unfrozen below the freezing interface for pore water sampling. The rate of freezing is suitable for quick freeze-thaw cycles (0.19°C/min). This setup can be further developed to observe solute transport and attenuation in variably-saturated soil and soil moisture status for different freeze-thaw regimes under simulated climate change scenarios.

Spanish chickpea gene-bank seeds (Cicer arietinum L.) offer an enhanced nutritional quality and polyphenol profile compared with commercial cultivars.

In the global socioeconomic context and the current climate change scenario, investigating the nutritional and bioactive characteristics of landraces can provide interesting profiles with technological applications and benefits for human health. The purpose of this work was to improve our knowledge regarding the nutritional and phenolic composition of several chickpea accessions preserved in a gene bank compared with widely consumed cultivars, as a first approach to establish their potential nutritional interest. CIELab colour, mineral content, protein, and amino acids were determined, as well as a comprehensive characterization of free and bound phenolic compounds by high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry. The chickpea accessions displayed a superior macro-mineral profile and higher levels of protein, arginine, and bound phenolic compounds than commercial cultivars did. The total phenolic content ranged from 307.55 to 940.46 μg g-1 dry weight and clearly categorized the crops into desi or kabuli types. The ratio of free to bound phenolic compounds ranged between 2.8 and 50.2 in the kabuli seeds and 0.4-1.3 in the desi type. The most remarkable finding was the quantification of a total of 42 phenolic compounds, nine of them reported for the first time in chickpea seeds (methyl and dimethyl citric acids, glabranin, 3,4-dihydroxy-5-methoxybenzoic acid, myricetin 3-O-rutinoside, dihydromyricetin, phlorizin, kaempferol 7-(6″-p-succinylglucoside) and phloretin). Despite variations in genetic backgrounds and specific agronomic conditions, this research unveils a sufficiently attractive nutritional and phenolic profile to justify further investigations aimed at exploring the future expansion and applications of these chickpea accessions. © 2025 Society of Chemical Industry.

Association of ambient temperatures with suicide attempts and violence with the future projections under climate change scenarios: a nationwide time-stratified case-crossover study in South Korea

BackgroundBoth climate change and intentional injuries (suicide attempts and violence) are recognized as crucial factors that affect human health. Previous studies revealed the association between ambient temperatures and deaths due to intentional injuries but mostly about the consequences of severe events. Our study aimed to examine suicide attempts and violence incidence including mild and moderate cases with future projections, using each injury’s burden about climate change scenarios.MethodsWe collected nationally representative cases of suicide attempts (8,512 cases) and violence (9,742 cases) from the Korea National Hospital Discharge In-depth Injury Survey from 2005 to 2019. We performed a two-stage analysis with a time-stratified case-crossover design to evaluate the associations of outdoor temperatures with suicide attempts and violence using historical data (2005–2019). Based on the estimated associations in the historical period, we projected the excess suicide attempts and violence attributable to ambient temperatures in the future (2020–2099) using the three shared socioeconomic pathway (SSP) scenarios.ResultsWe found positive associations between outdoor temperatures with suicide attempts and violence individually, and the association with violence was more linear. The excess suicide attempts attributable to temperatures in the historical period were around 11%, and it was expected to increase in all SSP scenarios (up to 14.35%). For violence, the excess risk of violence attributable to temperatures in the historical period was around 3.5%, and it was also estimated to increase in the future (up to 7.92%).ConclusionsThe nationwide study about South Korea shows that there are associations between an increase in outdoor temperatures and increased risks of suicide attempts and violence, and each excess injury related to temperature is projected to grow under the SSP scenarios. Our findings might provide informative evidence for relevant action plans against climate change and intentional injuries.

World Climate Research Programme lighthouse activity: an assessment of major research gaps in solar radiation modification research

It is increasingly evident that maintaining global warming at levels below those agreed in the legally binding international treaty on climate change. i.e., the Paris Agreement, is going to be extremely challenging using conventional mitigation techniques. While future scenarios of climate change frequently include extensive use of terrestrial and marine carbon dioxide removal in the second part of the 21st century, it is unproven that these techniques can be scaled-up to reach the scale required to significantly reduce concentrations of atmospheric carbon dioxide and significant uncertainties and detrimental side-effects exist. These issues have led to increasing interest in so-called “Solar Radiation Modification” whereby the global mean temperature of the Earth is reduced by either blocking a small fraction of sunlight from reaching it or by increasing the Earth’s albedo to reflect a small proportion of incident sunlight back out to space. Here we systematically identify key research gaps associated with the two most prominent Solar Radiation Modification techniques, i.e., Stratospheric Aerosol Injection (SAI) and Marine Cloud Brightening (MCB). We provide an assessment of the research gaps associated with other less prominent SRM techniques. We assert that transparency and inclusivity in SRM research is essential in providing objective and impartial research findings to each and every stakeholder in an equitable way.

Responses of freshwater organisms to multiple stressors in a climate change scenario: a review on small-scale experiments.

This review summarizes how salinity and temperature, two key global factors driven by climate change in freshwater systems, interact with other stressors on organisms in controlled small-scale factorial experiments at the population, individual, or subindividual level (excluding mesocosm and field studies). Despite the growing interest, research following all these criteria remains limited with 156 publications of which 50% analyzed stressors + salinity, 46% stressors + temperature, and only 4% involved the triple combination. Research on the combined effect of temperature and salinity predominantly focused on metals, pesticides, and, to a lesser extent, emergent contaminants, such as microplastics and nanomaterials, encompassing various biological models and responses. In general, increased temperature amplifies the single effect of stressors, whereas salinity leads to a higher diversity of responses, with similar proportions of synergisms and antagonisms. Fish (Salmoniformes, Perciformes, and Cypriniformes) were the most studied organisms. Among Crustacea, only cladocerans of the genera Daphnia and Ceriodpahnia were considered. The present review highlights the need to include other species that play key roles in freshwater food webs and to increase triple combination studies to understand complex interactions and develop adaptation and mitigation strategies to preserve the environment and its services in this changing world.

Predicting the habitat suitability of Ilex verticillata (Aquifoliaceae) in China with field-test validations.

The cut branches of Ilex verticillata are highly ornamental and have high economic value. Since its introduction to China, it has received widespread attention. In the context of climate change today, ensuring its promotion and sustainable production in China is of great significance. In this study we evaluated the habitat suitability of the species using MaxEnt, combined with climate and soil variables, to assess the impact of climate change on its potential suitable habitat. We used 121 I. verticillata occurrence data and validated the model prediction using extensive field testing (12 test sites located in areas from 23.19° N to 42.91° N and 76.17° E to 125.14° E). The habitat suitability model (AUC = 0.854) performed well. Among them, three precipitation variables and one temperature variable were the main factors determining the distribution of I. verticillata in China. Field trial tests and model predictions of the suitability of I. verticillata were consistent, indicating that our model predictions are biologically meaningful and economically valuable. Under the Shared Socioeconomic Pathways (SSPs) climate change scenario, the high and medium suitable habitats for this species will be reduced in the future climate. This study helps to better understand the impact of climate change on I. verticillata and provides suggestions for the introduction and cultivation areas and protection of this species in China.

Impacts of climate change and reservoir operation on droughts: a case study in the Upper Part of Dong Nai River Basin, Vietnam

ABSTRACT This study aims to investigate the impacts of climate change and reservoir operation on drought in the Upper Part of Dong Nai (UPDN) River Basin. Climate change scenarios for the UPDN River Basin were portrayed according to the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on an ensemble of five general circulation models (GCMs), namely, EC-Earth3-Veg, CanESM5, EC-Earth3, HadGEM3-GC31-LL, and CNRM-CM6-1-HR for two Shared Socioeconomic Pathway scenarios, SSP2-4.5 and SSP5-8.5. The historical climate monitoring data at five weather stations and three hydrological gauges related to upstream reservoirs in the period 1990–2020 were collected. The streamflow for the period 2021–2099 was simulated by applying the Soil and Water Assessment Tool (SWAT) model. Two meteorological and hydrological drought indices of the 6-month time scale, namely, standardized precipitation index (SPI6) and streamflow drought index (SDI6), were calculated through designed modules integrated in the Drought Index Calculator (DrinC) software. The results show that climate change coupled with reservoir operation has seasonally changed the runoff, which has changed the drought situation in the entire basin. The lag time variations of hydrological drought in response to meteorological drought were significant in the main basin of the UPDN River Basin. These findings provide useful information for managers and policymakers in sustainable water resources management and development adapting to climate change.

Analysis of Suitable Cultivation Sites for Gastrodia elata Using GIS: A Comparison of Various Classification Methods

Gastrodia elata has been a valuable medicinal resource in the East for approximately 3000 years. In South Korea, G. elata is cultivated in open-fields or greenhouses near residential areas. However, due to severe continuous damage, cultivation sites need to be frequently relocated, leading to a shortage of available cultivation areas. Alternatively, farmers are focusing on mountain cultivation. This study analyzed suitable cultivation sites for G. elata in mountainous areas using a geographic information system (GIS) and applied various classification methods to identify their characteristics and similarities. The analysis showed that the Natural Breaks (Jenks) classification method maximized the differences between grades, whereas the Quantile method reclassified the area of suitable sites to a relatively high proportion. In contrast, the Equal Interval method reclassified the areas of suitable and unsuitable sites to a lower proportion, whereas the Geometric Interval method best demonstrated extreme-temperature regions as unsuitable sites. Among the classification methods, the Natural Breaks (Jenks) and Geometric Interval methods yielded the most similar results. These findings provide critical methodological outcomes for G. elata cultivation and sustainable agriculture and forestry. Future empirical research and the application of climate change scenarios are necessary to enhance the sustainability of the G. elata cultivation industry.

Integrating AI and climate change scenarios for multi-risk assessment in the coastal municipalities of the Veneto region.

Global climate is experiencing exceptional warming, leading to a rise in extreme events worldwide. Coastal regions are particularly vulnerable to climate change (CC), due to dense populations, interconnected economies, and fragile ecosystems. These areas face escalating risks as CC intensifies the severity and frequency of extreme weather phenomena, like heavy precipitation, sea-level rise (SLR), storm surges. Integrated approaches are crucial to assess the combined impacts of atmospheric and marine hazards at the land-sea interface. Machine Learning (ML) offer innovative solutions to analyse multi-risk events, leveraging large and heterogeneous datasets and modelling complex, non-linear interactions. This study introduces a two-tier ML approach to estimate risks associated with extreme weather events for the Veneto coastal municipalities under current and future scenarios. The model, tested and validated with present-day data, showed satisfactory performance (error margin ∼20%). The model was applied to mid-term (until 2045) and long-term (until 2100) periods under different CC scenarios, represented by various Representative Concentration Pathways (RCP). Mid-term analysis reveals an increasing risk trend, driven by SLR under RCP8.5, underscoring the significance of considering non-linear interactions between multiple marine and atmospheric hazards. Long-term analysis highlights how future risks depend mainly on precipitation and SLR across the analysed CC scenarios (RCP2.6/4.5/8.5). Results indicate a gradual increase in the expected annual risk trend, with RCP8.5 scenario showing the most severe outcomes. By 2100, the risks under RCP8.5 are projected to be ten times higher than those observed during the historical period, highlighting the importance of developing effective strategies to address these challenges.

Projections of future heat-related emergency hospitalizations for asthma under climate and demographic change scenarios: a Japanese nationwide time-series analysis

There is growing concern about climate impacts on human health. However, empirical evidence is lacking regarding future projections of heat-related asthma hospitalizations. This study aimed to project excess emergency hospitalizations for heat-related asthma exacerbation in Japan. Using Japanese nationwide administrative data from 2011 to 2019, we conducted an ecological time-series quasi-Poisson regression analysis to estimate the heat-related relative risk of emergency hospitalization for asthma over a lag of 0-3 days during the warm season (June to September). Heat exposure was defined as the region-specific daily mean temperature exceeding the locally defined minimum morbidity temperature percentile (MMP). Heat-related excess hospitalizations for asthma were projected under future climate and demographic change scenarios based on Shared Socioeconomic Pathways (SSPs). We identified 75,829 emergency hospitalizations for asthma. The heat-related relative risk of hospitalization was 1.22 (95% confidence interval (CI): 1.12-1.33) at the 99th percentile temperature relative to the MMP, with the highest estimates for cases aged 0-14 years. Heat-related excess hospitalizations were projected to increase by 6.78 (95%CI: 5.84-7.67) times in 2091-2099 versus 2011-2019 along SSP5-8.5 when constant population structure was assumed. The increasing trend persisted even when the future population decline was considered (4.19 (95%CI: 3.53-4.85) times in 2091-2099 versus 2011-2019 under SSP5-8.5). Future heat-related impacts on asthma exacerbation are expected to increase in Japan toward the end of this century, even when the future demographic change is considered. Our projections will contribute to resilient health systems adapting to ongoing climate change.

Predicting climate-change impacts on the global glacier-fed stream microbiome.

The shrinkage of glaciers and the vanishing of glacier-fed streams (GFSs) are emblematic of climate change. However, forecasts of how GFS microbiome structure and function will change under projected climate change scenarios are lacking. Combining 2,333 prokaryotic metagenome-assembled genomes with climatic, glaciological, and environmental data collected by the Vanishing Glaciers project from 164 GFSs draining Earth's major mountain ranges, we here predict the future of the GFS microbiome until the end of the century under various climate change scenarios. Our model framework is rooted in a space-for-time substitution design and leverages statistical learning approaches. We predict that declining environmental selection promotes primary production in GFSs, stimulating both bacterial biomass and biodiversity. Concomitantly, predictions suggest that the phylogenetic structure of the GFS microbiome will change and entire bacterial clades are at risk. Furthermore, genomic projections reveal that microbiome functions will shift, with intensified solar energy acquisition pathways, heterotrophy and algal-bacterial interactions. Altogether, we project a 'greener' future of the world's GFSs accompanied by a loss of clades that have adapted to environmental harshness, with consequences for ecosystem functioning.

Climate-adaptive optimal water resources management: A multi-sectoral approach for the Munneru river basin, India.

Climate change profoundly affects water resource allocation by disrupting the availability, distribution, and quality of water across various regions. Optimal allocation of water resources represents a comprehensive strategy for water resource management by addressing the intricate connections between water allocation systems and their repercussions on the environment, society, and economy. In this study, an Optimal Water Resources Management (OWRM) framework was developed, focusing on the optimal allocation of water resources and crop planting structures across various sectors. The Munneru river basin, located in the lower Krishna River region of India, was selected as the study area to validate the proposed framework. Five distinct water-demanding sectors-irrigation, domestic, livestock, industrial, and irrigation water requirements for major agricultural seasons-were identified in the study area, and their sectoral water demands were calculated at the basin level. The crop water and irrigation water requirements for various crops were estimated using the CROPWAT tool, while the framework also optimized crop planting structures to maximize returns and resource efficiency. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was applied, with two objectives focused on equity and economic value. Superior solutions were then identified using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The OWRM framework was applied after identifying critical cases of water availability in future periods under climate change scenarios. Through this integrated approach, an average annual increase of 52.6% in agricultural sector returns was achieved for the simulation period (2016-17 to 2022-23). For a condition of providing at least 90% water supply to each sector, the optimal crop patterns led to revenue increases of 136.4%, 59.2%, and 74.7% compared to actual revenues for the water years 2020-21, 2021-22 and 2022-23 respectively. The developed OWRM methodology can be applied to other basins across the world that are impacted by climate change.

Assessing consistency in drought risks in India with multiple multivariate meteorological drought indices (MMDI) under climate change.

This study investigates the spatio-temporal consistency of different MMDI formulations and their role in meteorological drought characterization uncertainty under historic and future climates using ERA5 reanalysis, and outputs from eight Coupled Model Intercomparison Project Phase 6 models, respectively, across different climate zones and shared socioeconomic pathways (SSP) in the Indian subcontinent. Six MMDI formulations namely the Standardized Precipitation Evaporation Index (SPEI), Reconnaissance Drought Index (RDI), and self-calibrated Palmer Drought Severity Index (scPDSI), Standardized Palmer Drought Index (SPDI), Standardized Moisture Anomaly Index (SZI) and Supply Demand Drought Index (SDDI) are used. A suite of analysis including agreement mapping, category difference analysis and uncertainty contribution analysis using global sensitivity analysis (GSA) are employed to quantify the consistency of MMDIs and uncertainty in drought characterization due to the MMDI formulation. The variation in MMDI consistency due to different reference evapotranspiration (ETo) methods is also studied. Results demonstrate strong agreement among the MMDIs under historic climate. Under climate change scenarios our findings demonstrate broad agreement among majority of the MMDIs across the study domain, but in substantial areas where MMDI not agree, especially for higher emission scenarios and arid zones. Increased uncertainty under climate change is due to SDDI and SPEI projecting dryer conditions while scPDSI projecting wetter conditions in the far future period owing to varying degrees of sensitivity of MMDIs to its constituent variables (Precipitation and ETo). Results also show that the uncertainty due to MMDIs varied considerably based on ETo methods as well. Finally, based on GSA analysis, the most significant sources of uncertainty in drought projections under climate change are attributed to MMDI-GCM interactions and MMDIs for the Penman-Monteith method. Discrepancies in drought estimates caused by the MMDI selection highlight the need for careful evaluation of drought indices before adopting for climate change impact assessment.

Future climate change facilitates the herb drought-tolerant species distribution than woody species.

Drought-tolerant species play a crucial role in maintaining ecosystem services in arid and semi-arid regions wherein subject to rapid climate change. However, how future climate change affect the distribution of drought-tolerant plants with different growth forms (e.g., herb and woody) remains largely unknown. Here, we used the MaxEnt model to simulate the potential species distribution under current conditions, and predicted the future species distribution of 82 common drought-tolerant plants in China under two time periods (2041-2060 and 2081-2100) and three climate change scenarios (SSP126, SSP245 and SSP585) in the future. We found that the western and northern regions of China are hotspots for drought-tolerant plant distribution. Compared with other predictors, aridity index (AI) explained the largest portion of variation (45%) in the distribution patterns of drought-tolerant plant plants. Climate change would change the distribution of drought-tolerant plants, with more than 50% of the species showing a trend of shrinking ranges in China. For both herb and woody plants, the highest turnover values were observed under SSP585 for the period 2081-2100, reaching 37.67% and 29.08%, respectively. Our results highlighted that herb and woody plants respond differently to climate change stresses, with herb plants projected to greatly expand their ranges in the future. These insights are vital for evaluating the impacts of climate change on biodiversity and informing the development of effective adaptation strategies.

HSP mRNA sequences and theirexpression under different thermal oscillation patterns and heat stress in two populations of Nodipecten subnodosus.

Understanding the molecular mechanisms underlying thermal acclimation and heat shock responsesin marine ectotherms is critical for assessing their adaptive capacity in the context of climate change and climate extremes. This study examines the expression dynamics of heat shock proteins (HSPs) in the scallop Nodipecten subnodosus, shedding light on their role in thermal adaptation. Our analysis revealed the presence of several conserved functional signatures in N. subnodosus HSPs deduced amino acid sequences. Comparative gene expression profiling between two populations of N. subnodosus, maintained for 15 days under constant and oscillatory thermal regimes and then exposed to acute heat stress, revealed conserved adaptive traits. The heat-inducible nature of N. subnodosus HSP70 (HSPA8) gene expression highlights its potential as a stress marker, in contrast to its human homolog, which is constitutively expressed. Furthermore, the identification of HSP90 (HSPC3) and its overexpression during acute heat stress underscores its critical role in initiating a protective stress response. Population-specific responses in the magnitude of gene expression were observed; however, both populations exhibited similar overall patterns of HSP induction, suggesting a shared adaptive response mechanism. This study also elucidated the diversity and expansion of members of the HSP70 family members, specifically the HSPA12 subfamily, in N. subnodosus. This characteristic, previously observed in other bivalves, underscores the role of HSPA12 in environmental adaptation, providing molecular plasticity to withstand varying environmental pressures. These findings offer valuable insights into the molecular basis of thermal adaptation in N. subnodosus, highlighting the importance of HSPs in coping with environmental stochasticity under climate change scenarios.

Modelling Sustainable Adaptation Strategies toward Climate-smart Agriculture in the Coastal Region of Sundarban Biosphere Reserve of India under Climate Change Scenarios

Modelling Sustainable Adaptation Strategies toward Climate-smart Agriculture in the Coastal Region of Sundarban Biosphere Reserve of India under Climate Change Scenarios

Depositional environment of shallow-marine arenites in the Northern Apennines (Italy) affects aquifer performance: an interpretive key to groundwater management in a climate change scenario

Depositional environment of shallow-marine arenites in the Northern Apennines (Italy) affects aquifer performance: an interpretive key to groundwater management in a climate change scenario

Predicting suitable habitats for Asian elephant (Elephas maximus) in Tropical Asia under changing climatic scenarios

Predicting suitable habitats for Asian elephant (Elephas maximus) in Tropical Asia under changing climatic scenarios