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Weather and climate patterns play an intrinsic role in societal health, yet a comprehensive synthesis of specific hazard-mortality causes does not currently exist. Country-level health burdens are thus highly uncertain, but harnessing collective expert knowledge can reduce this uncertainty, and help assess diverse mortality causes beyond what is explicitly quantified. Here, surveying 30 experts, we provide the first structured expert judgement of how weather and climate directly impact mortality, using the UK as an example. Current weather-related mortality is dominated by short-term exposure to hot and cold temperatures leading to cardiovascular and respiratory failure. We find additional underappreciated health outcomes, especially related to long-exposure hazards, including heat-related renal disease, cold-related musculoskeletal health, and infectious diseases from compound hazards. We show potential future worsening of cause-specific mortality, including mental health from flooding or heat, and changes in infectious diseases. Ultimately, this work could serve to develop an expert-based understanding of the climate-related health burden in other countries.

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We established a mixed-effects model incorporating climatic factors for the base diameter and length of the primary branches of Larix kaempferi using stepwise regression, based on climatic data from a total of 40 standard plots located in Xiaolongshan, Gansu Province, Changlinggang Forest Farm in Jianshi County, Hubei Province, and Dagujia Forest Farm in Qingyuan County, Liaoning Province, as well as the data from 120 L. kaempferi sample trees. Additionally, we created prediction charts for the fixed effects portion of the optimal mixed model to determine the relationship between climatic factors and base diameter and branch length, to explore the differential response of L. kaempferi branches to climatic variables. The results showed that the base diameter mixing model with annual mean temperature and water vapor deficit and the branch length mixing model with annual mean temperature had the best fitting effect, with R2 of 0.6152 and 0.6823, respectively. Based on the fixed effects prediction chart of the mixed model, the overall basal diameter showed an increasing trend with the increases of relative branch depth. The average basal diameter size was in an order of young-aged plantation

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Spatial variability of throughfall (i.e. the non-uniform characteristics of throughfall at different canopy positions) and its temporal persistence (i.e. time stability) are related to the quantity and efficiency of soil moisture replenishment, and affect plant competition and community succession dynamics by affecting resource availability. We carried out a meta-analysis with 554 papers (from 2000 to 2022) retrieved from Web of Science and China National Knowledge Infrastructure (CNKI) based on keyword search, quantified and compared the amount, spatial heterogeneity, and temporal stability characteristics of penetrating rain in different climate zones and plant functional types. Our results that throughfall proportion was lower in arid regions (72.0%±13.6%) than humid (75.1%±9.3%) and semi-humid areas (79.9%±10.4%). Cold climates had lower values (74.1%±14.6%) than temperate (74.2%±7.5%) and tropical climates (80.9%±14.6%). Shrubs (68.9%±14.9%) generally had lower throughfall proportion than trees (76.7%±9.1%). Broad-leaved trees (75.2%±11.1%) and conifers (75.1%±9.9%) showed similar throughfall proportions, as did evergreen (76.7%±10.0%) and deciduous species (74.7%±11.9%). Additionally, spatial variability (coefficient of variation) did not significantly differ across rainfall zones, temperature zones, or vegetation types. The spatial distribution of throughfall was relatively stable. Canopy structure was the dominant factor affecting temporal stability of throughfall. However, there was a lack of comparison between typical geographic units (i.e. spatial units with basically consistent geographical environmental conditions) at various temporal scales. Future research should expand upwards to the summary of global spatial scale rules and downwards to the analysis of process based temporal scale mechanisms, to depict the dynamic distribution of penetrating rain and unify observation standards to enhance comparability of different studies, in order to efficiently promote research on canopy penetrating rain and provide ecological and hydrological basis for protecting nature, managing artificial activities, and restoring degraded ecosystems.

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To investigate the differences on morphological growth patterns of statolith of Todarodes pacificus in the East China Sea during La Niña and normal years, we analyzed the samples of T. pacificus collected in the East China Sea by Chinese light purse seine fishery fleets from February to April in 2020 (a normal year) and 2021 (a La Niña year). The results showed that total statolith length (TSL), lateral dome length (LDL), wing length (WL), and maximum width (MW) could be used as characterization parameters to representing the morphological growth of statolith. The characterization parameters of statolith in T. pacificus differed significantly between different climate years and between different genders. The values of those characterization parameters of statolith were greater in normal year than those in La Niña year, which in both years were larger in females, except for TSL in males in La Niña year. The statolith growth of males were faster than that of females in different climate years. TSL, LDL, and WL increased faster in normal year, while MW increased faster in La Niña year. The relative size of statolith gradually slowed down with the growth of individuals.

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Climate and land use/land cover (LULC) changes have far-reaching effects on various biological processes in wildlife, particularly interspecific interactions. Unfortunately, interspecific interactions are often overlooked when assessing the impacts of environmental changes on endangered species. In this study, we examined niche similarities and habitat overlaps between wild Crested Ibis and sympatric Egret and Heron species (EHs) in Shaanxi, China, using Ecological niche models (ENMs). We aimed to forecast potential alterations in habitat overlaps due to climate and LULC changes. The results showed that although EHs possess a broader niche breadth compared to the Crested Ibis, they still share certain niche similarities, as indicated by Schoener's D and Hellinger's I values exceeding 0.5, respectively. Notably, despite varying degrees of habitat reduction, the shared habitat area of all six species expands with the changes in climate and LULC. We suggest that with the climate and LULC changes, the habitats of sympatric EHs are likely to suffer varying degrees of destruction, forcing them to seek refuge and migrate to the remaining wild Ibis habitat. This is primarily due to the effective conservation efforts in the Crested Ibis habitat in Yangxian County and neighboring areas. Consequently, due to the niche similarity, they will share and compete for limited habitat resources, including food and space. Therefore, we recommend that conservation efforts extend beyond protecting the Crested Ibis habitat. It is crucial to control human activities that contribute to LULC changes to safeguard the habitats of both Crested Ibis and other sympatric birds.

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Accurate estimation of forest aboveground biomass (AGB) is crucial for understanding and managing forest ecosystems in the context of global environmental change, and also provides a scientific basis for national and regional ecological planning and carbon emission reduction policies. In order to investigate the regional pattern of forest AGB and its influencing factors in central China, a total of 469 sample plots were measured along four sample transects and on six mountains in field survey. The results showed that: 1) Two longitudinal distribution patterns of forest AGB were found, and one was that the AGB in the Qinling Mountains and the Daba Moutains gradually decreased from east to west, and the other was that the AGB in the areas between the two mountains gradually increased from east to west. The latitudinal distribution pattern of the forest AGB showed an "increasing-decreasing-increasing-decreasing" trend from south to north. The altitudinal distribution pattern showed a "first increasing-then decreasing" pattern with increasing altitude. 2) The influence of each factor on the spatial pattern of forest AGB was manifested as temperature > precipitation > HAI > topography, indicating that the spatial pattern of forest AGB in central China was the result of the interaction of climate, human activities and natural factors.

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The Climate Suitability Index (CSI) can increase agricultural efficiency by identifying the high-potential areas for cultivation from the climate perspective. The present study develops a probabilistic framework to calculate CSI for rainfed cultivation of 12 medicinal plants from the climate perspective of precipitation and temperature. Unlike the ongoing frameworks based on expert judgments, this formulation decreases the inherent subjectivity by using two components: frequency analysis and Particle Swarm Optimization (PSO). In the first component, the precipitation and temperature layers were prepared by calculating the occurrence probability for each plant, and the obtained probabilities were spatially interpolated using geographical information system processes. In the second component, PSO quantifies CSI by classifying a study area into clusters using an unsupervised clustering technique. The formulation was implemented in the Lake Urmia basin, which was distressed by unsustainable water resources management. By identifying clusters with higher CSI values for each plant, the results provide deeper insights to optimize cultivation patterns in the basin. These insights can help managers and farmers increase yields, reduce costs, and improve profitability.

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Influence of climate change on the geospatial heterogeneity in agricultural production remains poorly understood. In this study, heterogeneity in climate's impacts on wheat production across the North China Plain (NCP) was explored by integrating APSIM model, process-based factor-control quantitative approach, and geostatistical analyses. The results indicated that increased precipitation and minimum temperature boosted yields, while elevated maximum temperature and reduced radiation exerted adverse effects. The most pronounced negative impact arose from the coupling variation between maximum temperature and radiation, contributing to yields' variations of -5.84% from 2000 to 2010 and -5.22% from 2010 to 2020. In last two decades, climate change has augmented the overall geospatial heterogeneity degree in wheat yields. The chief factor contributing to yields' heterogeneity was the maximum temperature during anthesis-maturation stage, explaining an average of 37.6% of yields' heterogeneity, followed by precipitation throughout the whole growth period and the anthesis-maturation stage, explaining 36.1% and 34.5% respectively. A reciprocal enhancement mechanism exists between factors in driving yields' heterogeneity. Wheat yields in the southwestern NCP benefited more from increased precipitation and minimum temperature. Between 2000 and 2010, yields in the central NCP (junctions of Henan, Hebei, and Shandong) experienced the most pronounced adverse impact from increased maximum temperature. However, by 2010-2020, significant adverse impact shifted to western NCP, expanding spatially. During 2010-2020, the geospatial scope of radiation's significant negative impact expanded compared to the preceding decade, particularly affecting the yields in central and eastern NCP. The identified geospatial heterogeneity pattern of climate's impacts can guide spatially-matched climate-adaptive management adjustments. For instance, intensifying the defense against high-temperature's impacts in northwestern Henan, southern Hebei, and western Shandong, while improving the adaptation to radiation reduction in the central and eastern NCP. The findings are expected to advance regional-scale climate-smart agricultural development.

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Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People's Democratic Republic (Lao PDR). This study aimed to describe spatial-temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR.

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Plant functional traits (FTs) determine growth, reproduction and survival strategies of plants adapted to their growth environment. Exploring global geographic patterns of FTs, their covariation and their relationships to climate are necessary steps towards better-founded predictions of how global environmental change will affect ecosystem composition. We compile an extensive global dataset for 16 FTs and characterise trait-trait and trait-climate relationships separately within non-woody, woody deciduous and woody evergreen plant groups, using multivariate analysis and generalised additive models (GAMs). Among the six major FTs considered, two dominant trait dimensions-representing plant size and the leaf economics spectrum (LES) respectively-are identified within all three groups. Size traits (plant height, diaspore mass) however are generally higher in warmer climates, while LES traits (leaf mass and nitrogen per area) are higher in drier climates. Larger leaves are associated principally with warmer winters in woody evergreens, but with wetter climates in non-woody plants. GAM-simulated global patterns for all 16 FTs explain up to three-quarters of global trait variation. Global maps obtained by upscaling GAMs are broadly in agreement with iNaturalist citizen-science FT data. This analysis contributes to the foundations for global trait-based ecosystem modelling by demonstrating universal relationships between FTs and climate.

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BACKGROUND: Chronic obstructive pulmonary disease (COPD) and asthma can be treated with inhaled corticosteroids (ICS) delivered by low climate impact inhalers (dry powder inhalers) or high climate impact inhalers (pressurized metered-dose inhalers containing potent greenhouse gasses). ICS delivered with greenhouse gasses is prescribed ubiquitously and frequent despite limited evidence of superior effect. Our aim was to examine the beneficial and harmful events of ICS delivered by low and high climate impact inhalers in patients with asthma and COPD. METHODS: Nationwide retrospective cohort study of Danish outpatients with asthma and COPD treated with ICS delivered by low and high climate impact inhalers. Patients were propensity score matched by the following variables; age, gender, tobacco exposure, exacerbations, dyspnoea, body mass index, pulmonary function, ICS dose and entry year. The primary outcome was a composite of hospitalisation with exacerbations and all-cause mortality analysed by Cox proportional hazards regression. RESULTS: Of the 10,947 patients with asthma and COPD who collected ICS by low or high climate impact inhalers, 2,535 + 2,535 patients were propensity score matched to form the population for the primary analysis. We found no association between high climate impact inhalers and risk of exacerbations requiring hospitalization and all-cause mortality (HR 1.02, CI 0.92-1.12, p = 0.77), nor on pneumonia, exacerbations requiring hospitalization, all-cause mortality, or all-cause admissions. Delivery with high climate impact inhalers was associated with a slightly increased risk of exacerbations not requiring hospitalization (HR 1.10, CI 1.01-1.21, p = 0.03). Even with low lung function there was no sign of a superior effect of high climate impact inhalers. CONCLUSION: Low climate impact inhalers were not inferior to high climate impact inhalers for any risk analysed in patients with asthma and COPD.

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Unraveling the phylogeographic histories of species remains a key endeavor for comprehending the evolutionary processes contributing to the rich biodiversity and high endemism found in East Asia. In this study, we explored the phylogeographic patterns and demographic histories of three endemic fishfly and dobsonfly species ( Neochauliodes formosanus, Protohermes costalis, and Neoneuromus orientalis) belonging to the holometabolan order Megaloptera. These species, which share a broad and largely overlapping distribution, were analyzed using comprehensive mitogenomic data. Our findings revealed a consistent influence of vicariance on the population isolation of Neoc. formosanus and P. costalis between Hainan, Taiwan, and the East Asian mainland during the early Pleistocene, potentially hindering subsequent colonization of the later diverged Neon. orientalis to these islands. Additionally, we unveiled the dual function of the major mountain ranges in East Asia, serving both as barriers and conduits, in shaping the population structure of all three species. Notably, we demonstrated that these co-distributed species originated from Southwest, Southern, and eastern Central China, respectively, then subsequently migrated along multi-directional routes, leading to their sympatric distribution on the East Asian mainland. Furthermore, our results highlighted the significance of Pleistocene land bridges along the eastern coast of East Asia in facilitating the dispersal of mountain-dwelling insects with low dispersal ability. Overall, this study provides novel insight into the synergistic impact of Pleistocene geological and climatic events in shaping the diversity and distribution of aquatic insects in East Asia.

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Natural populations are subject to selection caused by a range of biotic and abiotic factors in their native habitats. Identifying these agents of selection and quantifying their effects is key to understanding how populations adapt to local conditions. We performed a factorial reciprocal-transplant experiment using locally adapted ecotypes of Arabidopsis thaliana at their native sites to distinguish the contributions of adaptation to soil type and climate. Overall adaptive differentiation was strong at both sites. However, we found only very small differences in the strength of selection on local and non-local soil, and adaptation to soil type at most constituted only a few per cent of overall adaptive differentiation. These results indicate that local climatic conditions rather than soil type are the primary driver of adaptive differentiation between these ecotypes.

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BACKGROUND: Malaria remains an important public health problem, particularly in sub-Saharan Africa. In Rwanda, where malaria ranks among the leading causes of mortality and morbidity, disease transmission is influenced by climatic factors. However, there is a paucity of studies investigating the link between climate change and malaria dynamics, which hinders the development of effective national malaria response strategies. Addressing this critical gap, this study analyses how climatic factors influence malaria transmission across Rwanda, thereby informing tailored interventions and enhancing disease management frameworks. METHODS: The study analysed the potential impact of temperature and cumulative rainfall on malaria incidence in Rwanda from 2012 to 2021 using meteorological data from the Rwanda Meteorological Agency and malaria case records from the Rwanda Health Management and Information System. The analysis was performed in two stages. First, district-specific generalized linear models with a quasi-Poisson distribution were applied, which were enhanced by distributed lag non-linear models to explore non-linear and lagged effects. Second, random effects multivariate meta-analysis was employed to pool the estimates and to refine them through best linear unbiased predictions. RESULTS: A 1-month lag with specific temperature and rainfall thresholds influenced malaria incidence across Rwanda. Average temperature of 18.5 °C was associated with higher malaria risk, while temperature above 23.9 °C reduced the risk. Rainfall demonstrated a dual effect on malaria risk: conditions of low (below 73 mm per month) and high (above 223 mm per month) precipitation correlated with lower risk, while moderate rainfall (87 to 223 mm per month) correlated with higher risk. Seasonal patterns showed increased malaria risk during the major rainy season, while the short dry season presented lower risk. CONCLUSION: The study underscores the influence of temperature and rainfall on malaria transmission in Rwanda and calls for tailored interventions that are specific to location and season. The findings are crucial for informing policy that enhance preparedness and contribute to malaria elimination efforts. Future research should explore additional ecological and socioeconomic factors and their differential contribution to malaria transmission.

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BACKGROUND: Malaria mortality is influenced by several factors including climatic and environmental factors, interventions, socioeconomic status (SES) and access to health systems. Here, we investigated the joint effects of climatic and non-climatic factors on under-five malaria mortality at different spatial scales using data from a Health and Demographic Surveillance System (HDSS) in western Kenya. METHODS: We fitted Bayesian spatiotemporal (zero-inflated) negative binomial models to monthly mortality data aggregated at the village scale and over the catchment areas of the health facilities within the HDSS, between 2008 and 2019. First order autoregressive temporal and conditional autoregressive spatial processes were included as random effects to account for temporal and spatial variation. Remotely sensed climatic and environmental variables, bed net use, SES, travel time to health facilities, proximity from water bodies/streams and altitude were included in the models to assess their association with malaria mortality. RESULTS: Increase in rainfall (mortality rate ratio (MRR)=1.12, 95% Bayesian credible interval (BCI): 1.04-1.20), Normalized Difference Vegetation Index (MRR=1.16, 95% BCI: 1.06-1.28), crop cover (MRR=1.17, 95% BCI: 1.11-1.24) and travel time to the hospital (MRR=1.09, 95% BCI: 1.04-1.13) were associated with increased mortality, whereas increase in bed net use (MRR=0.84, 95% BCI: 0.70-1.00), distance to the nearest streams (MRR=0.89, 95% BCI: 0.83-0.96), SES (MRR=0.95, 95% BCI: 0.91-1.00) and altitude (MRR=0.86, 95% BCI: 0.81-0.90) were associated with lower mortality. The effects of travel time and SES were no longer significant when data was aggregated at the health facility catchment level. CONCLUSION: Despite the relatively small size of the HDSS, there was spatial variation in malaria mortality that peaked every May-June. The rapid decline in malaria mortality was associated with bed nets, and finer spatial scale analysis identified additional important variables. Time and spatially targeted control interventions may be helpful, and fine spatial scales should be considered when data are available.

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Mexico is home to 14 species of lagomorphs, 6 of which are endemic. Studies on diseases affecting native lagomorphs are scarce, and in most cases, the impact on their populations remains largely unknown. Rabbit hemorrhagic disease virus (RHDV), especially the RHDV2 variant, causes a serious and extremely contagious disease, resulting in high mortality rates and major declines in wild lagomorph populations. The objectives of this study were to identify disease hotspots and critical biodiversity regions in Mexico through the combined use of disease information and lagomorph distribution maps and to determine the areas of greatest concern. In total, 19 states of Mexico recorded RHDV2 from April 2020 to August 2021, and 12 of them reported the wild species Sylvilagus audubonii, Lepus californicus, and unidentified Leporidae species. The distribution of RHDV2 in Mexico can be closely predicted from climatic variables. RHDV2 hotspots are located in the central-southern area of the Mexican Highlands and the Trans-Mexican Volcanic Belt, where the virus affects multiple species. This knowledge is essential for proposing specific actions to manage and preserve lagomorph populations at risk and address these issues as soon as possible.

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Climatic oscillations affect fish population dynamics, ecological processes, and fishing operations in maritime habitats. This study examined how climatic oscillations affect catch rates for striped, blue, and silver marlins in the Atlantic Ocean. These oscillations are regarded as the primary factor influencing the abundance and accessibility of specific resources utilized by fishers. Logbook data were obtained from Taiwanese large-scale fishing vessels for climatic oscillations during the period 2005-2016. The results indicated that the effect of the Subtropical Indian Ocean Dipole on marlin catch rates did not have a lag, whereas those of the North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, and Indian Ocean Dipole had various lags. Pearson's correlation analysis was conducted to examine the correlations between atmospheric oscillation indices and marlin catch rates, and wavelet analysis was employed to describe the influences of the most relevant lags. The results indicated that annual atmospheric fluctuations and their lags affected the abundance and catchability of striped, blue, and silver marlins in the study region. This, in turn, may affect the presence of these species in the market and lead to fluctuations in their prices in accordance with supply and demand. Overall, understanding the effects of climatic oscillations on fish species are essential for policymakers and coastal communities seeking to manage marine resources, predict changes in marine ecosystems, and establish appropriate methods for controlling the effects of climate variability.

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Climate change affects the geographical distribution of species. Predicting the future potential areas suitable for certain species is of great significance for understanding their distribution characteristics and exerting their value. Based on the data of 276 effective distribution points of Polygonum capitatum and 20 ecological factors, the maximum entropy (MaxEnt) model and the ArcGIS software were employed to predict the areas suitable for P. capitatum growth, and the main environmental factors affecting the geographical distribution of this species were explored. Under the current climatic conditions, the areas highly suitable for P. capitatum are mainly distributed in southwestern China, with a small number of sites in coastal areas and most sites in Guizhou Province. Under different climate scenarios, the suitable areas were reduced to varying degrees. The dominant environmental variables affecting the distribution of P. capitatum were precipitation in the driest month, annual precipitation, and elevation, with a cumulative contribution rate of 84.1%. Against the background of a changing climate, the areas suitable for P. capitatum in China will be widely distributed in the southwestern region, with Guizhou Province and Yunnan Province as the main distribution areas; some sites will also be distributed throughout the southwest of Tibet Autonomous Region, the south of Sichuan Province, the north of Guangxi Autonomous Region, and the coastal area of Fujian Province. Optimal conditions for P. capitatum include a dry month precipitation range of 13.4 to 207.3 mm, elevations from 460.3 to 7214.3 m, and annual precipitation between 810 and 1575 mm. Given these insights, we recommend enhanced conservation efforts in current prime habitats and exploring potential cultivation in newly identified suitable regions to ensure the species' preservation and sustainable use.

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Lakes are indispensable to ecological balance, supporting biodiversity and human welfare. Despite their importance, lakes around the globe are diminishing at an alarming rate, presenting substantial environmental challenges exacerbated by climate variability and human-induced pressures, such as unsustainable land management and excessive water withdrawals. This study offers an extensive analysis of the desiccation phenomena affecting major lakes on the Iranian plateau, dissecting the complex interplay of contributing factors. We examine meteorological, hydrological, and agricultural drought conditions using indices like SPI, SDI, and SPEI to gain nuanced insights into drought dynamics. This study sheds light on the factors that contribute to the drying up of lakes and quantifies the impact of anthropogenic and climatic drivers on this phenomenon. The findings indicate that the area of all lakes has declined dramatically after the change point, ranging from 51% in the Urmia Lake to an impressive rate (i.e. 100%) in Southern Hamun. Despite the stable rate of meteorological droughts (increasing in temperature by about 1 °C since the 90s and stable precipitation patterns across most basins), the research highlights the ongoing struggle against severe hydrological and agricultural drought conditions. The study delineates the predominant role of anthropogenic activities in the diminishing lake inflows and the consequential drying of the lake, accounting for approximately 100 % in five of the seven lakes.

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