Climate Change Scenarios Research Articles

Comprehensive Analysis of the Driving Forces Behind NDVI Variability in China Under Climate Change Conditions and Future Scenario Projections

Climate change has a significant impact on vegetation development. While existing studies provide some insights, long-term trend analysis and multifactor driver assessments for China are still lacking. At the same time, research on the future vegetation development under different climate change scenarios needs further strengthening. In response to these issues, this study analyzed China’s normalized difference vegetation index (NDVI) data from 2001 to 2023, exploring vegetation cover trends, driving factors, and predicting the impact of future climate change. Firstly, this study decomposed the time series data into seasonal, trend, and residual components using the Seasonal–Trend decomposition using Loess (STL) decomposition method, quantifying vegetation changes across different climate zones. Partial least squares (PLS) regression analysis was then used to examine the relationship between NDVI and driving factors, and the contribution of these factors to NDVI variation was determined through the variable importance in projection (VIP) score. The results show that NDVI has significantly increased over the past two decades, especially since 2010. Further analysis revealed that vegetation growth is primarily influenced by soil moisture, shortwave radiation, and total precipitation (VIP scores > 0.8). Utilizing machine learning with Coupled Model Intercomparison Project Phase 6 (CMIP6) multimodel data, this study predicts NDVI trends from 2023 to 2100 under four emission scenarios (SSP126, SSP245, SSP370, SSP585), quantifying future meteorological factors such as temperature, precipitation, and radiation to NDVI. Findings indicate that under high-emission scenarios, the vegetation greenness in some regions may experience improved vegetation conditions despite global warming challenges. Future land management strategies must consider climate change impacts on ecosystems to ensure sustainability and enhance ecosystem services.

Natural endophyte reduces disease severity in cork oak caused by Biscogniauxia mediterranea and Diplodia corticola under different watering regimes

Cork oak (Quercus suber) is an economically important species in the Mediterranean region, but its decline due to fungal pathogens such as Biscogniauxia mediterranea and Diplodia corticola poses a major threat to forest sustainability. Climate change is aggravating this problem, and few control measures are currently available. The use of naturally occurring endophytic antagonists as biocontrol agents offers a sustainable strategy to mitigate cork oak decline. In this work, cork oak seedlings subjected to normal irrigation (70% field capacity) and drought (25% field capacity) were inoculated with the endophytic fungus Simplicillium aogashimaense, followed by one of the pathogens (B. mediterranea or D. corticola). The endophyte significantly alleviated the negative impacts of both pathogens, showing a stronger protective effect under drought stress, where the combined pressures of water limitation and pathogen infection were mitigated. In addition, S. aogashimaense modulated key physiological and biochemical responses in the seedlings, including phenolic accumulation, protein expression, peroxidase activity, and oxidative stress markers. The mode of action differed between pathogens: defense responses against D. corticola involved increased hydrogen peroxide (H₂O₂) production and lipid peroxidation, while interactions with B. mediterranea were associated with reduced peroxidase activity. The consistent protective effect under both water regimes highlights the potential of S. aogashimaense in climate change scenarios characterized by increased drought frequency. This study supports the use of endophytes as environmentally sustainable tools in integrated forest management, enhancing cork oak resilience to combined stresses and contributing to a better understanding of plant responses to pathogen attack.

Combining climate models and risk assessment tools to evaluate the invasive potential of intentional plant introductions: a case study of Moringa oleifera in New Zealand

An increasing number of alien plants are escaping cultivation and becoming invasive worldwide, with devastating ecological and economic consequences. As a result, it is crucial to better assess the risks associated with intentional plant introductions before widespread cultivation, even when these plants offer potential economic benefits. In this study, we explore the use of climate suitability and weed risk assessment (WRA) tools to evaluate the invasiveness risk of Moringa oleifera (moringa) in New Zealand. Moringa is valued globally for its nutritional content and potential health benefits, making it an attractive candidate for cultivation outside its native range. Although not yet widely grown in New Zealand, the rising demand for moringa products could lead to increased cultivation and distribution. Therefore, it is essential to ensure that this crop’s expansion is both environmentally and socially responsible, preventing it from becoming invasive and threatening native species. Climate suitability analysis identified Northland and surrounding areas as potential sites for moringa growth under current climate. The Composite Match Index, which measures the climatic similarity between current global distribution sites and potential locations in New Zealand, showed an increase from 0.52 in 2030 to 0.55 in 2070 under medium climate change scenarios, suggesting that climate change will facilitate the plant’s expansion. The invasive risk assessment model classified moringa as a low-risk species for invasiveness in New Zealand, with a low uncertainty score for its impact potential (0.04) and higher uncertainty regarding its spread potential (0.21) due to a paucity of information on seed bank formation and seed storability. However, further research on the plant's growth dynamics and interactions with other species is necessary to inform responsible decision-making regarding moringa’s cultivation and management in New Zealand.

Distribution of Desmodus rotundus and Its Implications for Rabies in Mexico.

Rabies is one of the zoonoses with the most significant impact on domestic herbivores, representing a mortality of 100,000 individuals and an economic loss of US$97 million per year in Latin America. The common vampire bat (Desmodus rotundus) is the primary reservoir for livestock rabies and is naturally distributed in Latin America. The concern arises from the possibility that climate change could facilitate the species' arrival to the southern USA. In this study, we used ecological niche modeling to estimate the distribution of D. rotundus in the present time and under future climate change scenarios. We analyzed whether rabies cases in Mexico were related to D. rotundus climatic suitability, and other factors such as livestock density and an ecological impact index. Our results suggest that climate change could facilitate the colonization of new sites in northern Mexico and the southern USA, which could threaten animal and human health. Further, we found that rabies cases are explained mainly by the reservoir suitability. However, national- and state-level policies may also play a key role in explaining the rabies cases in Mexico. There is a possibility that D. rotundus may expand its range to northern and northeastern Mexico, implying a high risk for the presence of rabies virus-free areas in the southern USA.

Investigation of the usage of machine learning to explore the impacts of climate change on occupational health: a systematic review and research agenda.

Occupational accidents can be potentialized by factors related to the workplace or the environment, such as climatic conditions. Air temperature, wind speed, and humidity can be used to monitor occupational heat stress, leading to cramps, exhaustion, stroke, and even death. Under the climate change scenario, measuring these variables is fundamental to developing adaptation strategies for maintaining the workers' well-being. However, when dealing with this high data volume from distinctive factors, traditional techniques are insufficient to extract all information effectively. Therefore, computational intelligence and data analytics tools can enhance data processing and analysis. Machine learning techniques have been successfully applied to occupational health and climate contexts. This paper explores the literature regarding applying these techniques to investigate the effects of climate change on occupational health. We conducted a systematic review through five scientific databases guided by three research questions, resulting in 24 selected papers. 75% of the papers screened used primary data collected from wearable sensors to monitor the well-being of workers, where we identified a trend of using supervised machine learning techniques, especially classification and regression algorithms, such as SVM, RF, and KNN. The remaining focus is on using secondary data from national databases to investigate the risk, with a trend of using feature selection techniques and classification tasks. Considering this topic is relatively new, we developed an agenda to guide future research, with suggestions to follow the trends found in this review and highlight the potential of expanding to multiple future research paths.

Assessing the climate change impact on Epimedium brevicornu in China with the MaxEnt model.

Epimedium brevicornu is a traditional medicinal plant in China, containing rich and medically valuable extracts. In recent years, the widespread development and application of its extracts have threatened the wild population of E.brevicornu. In order to protect the population of E. brevicornu, this research employed the Maxent model to examine the influence of climate change on the geographical distribution of E. brevicornu and to forecast its potential suitable distribution in China in light of climate change scenarios. The suitable habitat for E. brevicornu is located between 25.13°-39.50°N and 102.46°-118.13°E, mainly distributed across Loess Plateau. Climate change has a significant impact on the geographic distribution of E. brevicornu, with its high suitability zone expected to increase in the future and its centroid shifts towards the southeast direction. The 2050s projections under the Shared Socioeconomic Pathways (SSP) 1-2.6 and SSP2-4.5 scenarios indicated a significant expansion of highly suitable habitats. The analysis of key environmental variables showed that the seasonal variation coefficient of temperature (bio4), the lowest temperature in the coldest month (bio6), annual precipitation (bio12), seasonal variation of precipitation (bio15), human activity (hf), and the average ultraviolet radiation (UV-B3) in the highest month were the key factors affecting E. brevicornu selection of suitable habitats. This study provided important reference for the protection of the wild population of E. brevicornu and the selection of artificial planting areas in the future.

Forest types predominantly regulate soil dissolved organic matter dynamics along an elevational gradient in the Hengduan Mountains

Abstract Soil dissolved organic matter (DOM) is vital in terrestrial ecosystem carbon (C) cycling; however, the regulatory effects of forest types and elevations on soil DOM dynamics in mountain ecosystems remain incompletely understood. Here, we investigated DOM content, spectroscopic characteristics, molecular traits and their potential drivers along an elevational gradient (2600-3500 m) in the Hengduan Mountains. Our results showed that soil dissolved organic C (DOC) content was higher in broad-leaf forest soil (at 2900 m and 3500 m) than in coniferous forest soil (at 2600 m and 3200 m) irrespective of elevation, with a greater amount in wet season than in dry season. Humification index (HIX) trends aligned with the DOC content, while the aromaticity index (AI) showed an inverse relationship. These patterns were linked to the quality of litter carbon sources. Molecular-level analysis of DOM suggested that lignins/CRAM-like structure compounds and tannins predominated in soil DOM, indicating that the molecular composition of soil DOM was typical of plant-derived sources in our study region. Additionally, the relative abundance of lignin compounds decreased gradually with increasing elevation during the dry season. We detected that soil properties (especially, NH4+-N content) predominantly mediated DOM dynamics in dry season, whereas litter traits (i.e., leaf-DOC content) were the key factors across elevations in wet season. Overall, our results revealed litter traits and soil properties predominantly regulated soil DOM mechanism along elevational gradient, indicating that soil DOM dynamics associated with tree species in alpine mountain ecosystems may differentially influence soil C sequestration under future climate change scenarios.

Assessing Chlorophyll-a Variability and Its Relationship with Decadal Climate Patterns in the Arabian Sea

The Arabian Sea has undergone significant warming since the mid-20th century, highlighting the importance of assessing how decadal climate patterns influence chlorophyll-a (Chl-a) and broader marine ecosystem dynamics. This study investigates the variability of Chl-a, sea surface temperature (SST), and sea level anomaly (SLA) over the past three decades, and their relationships with the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The mean Chl-a concentration was 1.10 mg/m3, with peak levels exceeding 2 mg/m3 between 2009 and 2013, and the lowest value (0.6 mg/m3) was recorded in 2014. Elevated Chl-a levels were consistently observed in February and March across both coastal and offshore regions. Empirical orthogonal function (EOF) analysis revealed distinct spatial patterns in Chl-a and SST, indicating dynamic regional variability. The SST increased by 0.709 °C over the past four decades, accompanied by a steady rise in the SLA of approximately 1 cm. The monthly mean Chl-a exhibited a strong inverse relationship with both the SST and SLA and a positive correlation with SST gradients (R2 > 0.5). A positive correlation (R2 > 0.5) was found between the PDO and Chl-a, whereas the PDO was negatively correlated with the SST and SLA. In contrast, the AMO was negatively correlated with Chl-a but positively associated with warming and SLA rise. These findings underline the contrasting roles of the PDO and AMO in modulating productivity and ocean dynamics in the Arabian Sea. This study emphasizes the need for continued monitoring to improve predictions of ecosystem responses under future climate change scenarios.

A Procedure to Estimate Global Natural Recharge in Karst Aquifers

Natural recharge in karst aquifers is a key component of global water resources, yet its estimation remains challenging due to the complexity of karst hydrogeological processes. The recharge assessment deserves special consideration, especially in the current global climate and sustainability challenges. This study poses a methodology to appraise natural recharge rates in karst aquifers worldwide, drawing on climatic and geological data. In this regard, this study applies a methodology previously developed by two of the authors, in which natural recharge over large areas is considered a fixed fraction of precipitation, which varies according to different lithologies of similar hydrogeological behavior (hydro-lithological units). Given that carbonate rocks are known to have the highest recharge rate relative to precipitation (34.3%), the method builds on existing karst and average precipitation maps to calculate worldwide recharge in karst aquifers. Recharge is appraised at 4,381,063.7 hm3/yr, which represents 34.5% of the global groundwater resources, a percentage that indicates the importance of karst in this regard. Based on maps of recharge values worldwide, this study highlights the importance of carbonate aquifers when compared with assessments of the world’s groundwater resources made by international institutions or other types of aquifers. The method is contrasted with other ways of assessing groundwater resources used in diverse regions of Europe. The impact of different climate change scenarios on the natural recharge of these karst aquifers has also been analyzed. Thus, under a climate change scenario in 2050, it is estimated that natural recharge will be reduced by about 10%.

Predicting Nitrous Oxide Emissions from China’s Upland Fields Under Climate Change Scenarios with Machine Learning

Upland fields are a significant source of N2O emissions. Thus, an accurate estimation of these emissions is essential. This study employed four classical modeling approaches—the Stepwise Regression Model, Decision Tree Regression, Support Vector Machine, and Random Forest (RF)—to simulate soil N2O emissions from Chinese upland fields. The upland crops considered in this study covered food crops, oil crops, cash crops, sugar crops, fruits, and vegetables, excluding flooded rice. Comparative analysis revealed that the RF algorithm performed the best, with the highest R2 at 0.66 and the lowest root mean square error at 0.008 kg N2O ha−1 day−1. The application rate of mineral nitrogen fertilizers, mean temperature during the growing season, and soil organic carbon content were the key driving factors in the N2O emission model. Utilizing the RF model, total N2O emissions from Chinese upland fields in 2020 were estimated at 183 Gg. Future projections under Representative Concentration Pathway (RCP) scenarios indicated a 2.80–5.92% increase in national N2O emissions by 2050 compared to 2020. The scenario analysis demonstrated that the proposed nitrogen reduction strategies fail to counteract climate-driven emission amplification. Under the combined scenarios of RCP8.5 and nitrogen reduction strategies, a net 4% increase in national N2O emissions was projected, highlighting the complex interplay between anthropogenic interventions and climate feedback mechanisms. This study proposes that future attention should be paid to the development of nitrogen optimization strategies under the impact of climate change.

Lobster Yield Dynamics in a Warming Ocean: A Generalized Linear Modeling Case Study in Prince Edward Island, Canada

The lobster fishery is the third largest industry in Prince Edward Island (PEI), Atlantic Canada. Rising water temperatures due to global warming are impacting the successful completion of the lobster life cycle, which is heavily dependent on water temperature. This study investigated the relationship between lobster landings and sea surface temperature (SST) in PEI. Using Generalized Linear Models (GLM), we identified a significant correlation between annual historical lobster landings and monthly sea surface temperatures (SST) in the waters around PEI from 1990 to 2021. Considering the 5–8 year maturation period of lobsters, we applied a lagged SST structure over an 8-year period and used a Generalized Linear Model (GLM) to evaluate the relationship between historical SST and lobster landings. Our findings suggest that historical increases in SST are correlated with changes in lobster landings. Given the known sensitivities of lobster life cycles (i.e., spawning, larval development) and behavior (i.e., mating) to high ambient water temperature, our study also offers important insights for future fishery management under anticipated climate change scenarios.

Measuring the effects of climate change on traditional crops in tropical highlands, Ecuador

Studying the climate of the Tropical Central Andes is challenging due to its complex topography, diverse climatic regions shaped by the Andean Mountains, and the scarcity of in-situ meteorological data. This limitation complicates assessments of climate variability and its impact on agriculture. This study evaluates the impact of 2050 climate change scenarios on blackberry, tree tomato, maize, and potato production in Tungurahua, Ecuador, by estimating water availability for rainfed crops. In-situ available meteorological data were collected and analyzed using the ClimDex methodology to assess long-term climatic trends. Additionally, the General Algebraic Modeling System (GAMS) was employed to model agricultural productivity under pessimistic and optimistic climate scenarios. Climate change projections to 2050 were based on data from Ecuador’s Third and Fourth National Communications on Climate Change. The results indicate that, to date, climate change effects in this region have not been significant; higher temperatures have reduced frost occurrence, and no substantial increases in extreme rainfall or droughts have been observed. However, future projections suggest increased precipitation, a higher likelihood of extreme rainfall, and a decline in drought frequency. These expected changes highlight the need for adaptive strategies in agricultural planning and water resource management.

Evaluating the impacts of environmental stresses on agriculture in the context of climate resilience.

Climate change presents escalating threats to agricultural productivity and global food security, primarily through increased frequency and intensity of environmental stresses. Without adaptation measures, crop yields are projected to decline by 7% to 23% under the most extreme climate change scenarios. Despite growing awareness, a critical knowledge gap persists in understanding the combined impact of abiotic and biotic stresses on crop resilience. This study examines integrated approaches including the development of drought-tolerant crop varieties and the application of integrated pest management to enhance agricultural systems against climate-induced stresses. These strategies offer the potential to improve yield stability, reduce reliance on chemical inputs, and support the transition toward more sustainable and climate-resilient food systems. The findings aim to guide policymakers and agricultural stakeholders in implementing targeted, science-based interventions to safeguard food security under changing environmental conditions.

Biological control under climate change: Distribution patterns of the South American fruit fly, Anastrepha fraterculus and two of its parasitoids in the Americas.

Climate change affects the distribution of insects, such as pests and parasitoids. Species Distribution Models (SDMs) have been developed to determine distribution patterns and risk areas for pests and biological control agents under different climate change scenarios. The South American fruit fly, Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae), is an important pest of cultivated fruits throughout the Americas that can be controlled by natural enemies, such as the native parasitoid Doryctobracon areolatus (Szépligeti) (Hymenoptera: Braconidae) and the introduced parasitoid Diachasmimorpha longicaudata (Ashmead) (Hymenoptera: Braconidae). However, the control efficacy and parasitism performance of these organisms could be affected by changing environmental conditions. SDMs were conducted using Random Forest to predict suitable areas for the establishment of A. fraterculus, D. areolatus, and D. longicaudata under different climate scenarios or Representative Concentration Pathways (SSPs) (SSP 2-4.5 and 5-8.8) in two different periods (2021-2040 and 2041-2060). Our results predicted an increase in suitable areas for A. fraterculus in the Americas, especially in some South American countries such as Colombia and Brazil. Moreover, the projected distribution of these species is intricately linked to the regional climatic patterns. Temperate and tropical areas were more suitable for the establishment of A. fraterculus; D. areolatus was better suited to temperate climates; while tropical climates were more suitable for D. longicaudata. Suitable areas for the establishment of both parasitoid species were predicted to increase in future climate scenarios, with D. longicaudata having a greater geographical expansion than D. areolatus. These parasitoids could be used as biocontrol agents in almost all areas suitable for the establishment of A. fraterculus.

European Temperature Extremes Under Different AMOC Scenarios in the Community Earth System Model

Abstract Recent simulations using the Community Earth System Model (CESM) indicate that a tipping event of the Atlantic Meridional Overturning Circulation (AMOC) would cause Europe to cool by several degrees. This AMOC tipping event was found under constant pre‐industrial greenhouse gas forcing, while global warming likely limits this AMOC‐induced cooling response. Here, we quantify the European temperature responses under different AMOC regimes and climate change scenarios. A strongly reduced AMOC state and intermediate global warming (C, Representative Concentration Pathway 4.5) has a profound cooling effect on Northwestern Europe with more intense cold extremes. The largest temperature responses are found during the winter months and these responses are strongly influenced by the North Atlantic sea‐ice extent. Enhanced North Atlantic storm track activity under an AMOC collapse results in substantially larger day‐to‐day temperature fluctuations. We conclude that the (far) future European temperatures are dependent on both the AMOC strength and the emission scenario.

Agent-based socio-spatial modelling of coupled human-flood interactions along the UK coast

Abstract This study uses agent-based modelling (ABM) to assess the socio-hydrological impacts of structural coastal flood protections (SCFPs) under different climate change scenarios considering three contrasting UK case studies: Southport, Weston-super-Mare (WSM), and Portsmouth. By integrating extreme coastal water level (ECWL) projections and population dynamics, the ABM simulations reveal five distinct phases: Design, Implementation, Latency, Flood, and Post-Flood. The results highlight that the Latency phase, whereby SCFP initially stabilises affected population (AfP), inadvertently encourages population growth in residual risk areas. This process exacerbates long-term flood exposure, leading to significant increases in AfP when ECWL exceeds the SCFP crest height, negating gains in flood protection from the initial construction/upgrade. As such, Southport and WSM saw a significant increase in coastal population within protected floodplains, with these populations potentially having limited experience with flooding, preparedness, and consequently heightened vulnerability. Conversely, Portsmouth, with limited residential development near SCFPs, demonstrated how existing land-use and high population density can reduce the unintended socio-hydrological consequences of SCFPs in densely-populated coastal settings. These findings reveal two key pathways that influence coastal population in response to SCFPs: Land-use Driven, where non-residential land-use limits population increase, and Population Driven, where high-density areas limit further growth. This study advances our understanding of the coupled human-flood dynamics by evaluating how SCFPs can increase flood impacts in the long-term by influencing socio-spatial distribution over the short- to medium-term. Moreover, it demonstrates how ABMs can provide valuable insights by simulating complex coupled human-flood dynamics; critical for supporting adaptive, resilient coastal management strategies in a changing climate.

Prospects for cereal self-sufficiency in sub-Saharan Africa

Sub-Saharan Africa (SSA) has the world's largest projected increase in demand for food. Increased dependence on imports makes SSA vulnerable to geopolitical and economic risks, while further expansion of agricultural land is environmentally harmful. Cereals, in particular, maize, millet, rice, sorghum, and wheat, take nearly 50% of the cropland and 43% of the calories and proteins consumed in the region. Demand is projected to double until 2050. Here, we assess recent developments in cereal self-sufficiency and provide outlooks until 2050 under different intensification, area expansion, and climate change scenarios. We use detailed data for ten countries. Cereal self-sufficiency increased between 2010 and 2020 from 84 to 92% despite the 29% population increase. The production increase was achieved by increased yields per hectare (44%), area expansion (34%), and a shift from millet to the higher yielding maize (22%). Outlooks for 2050 are less pessimistic than earlier assessments because of the larger 2020 baseline area, higher shares of maize and somewhat less steep projected population increase. Yet, to halt further area expansion, a drastic trend change in annual yield increase from the present 20 to 58 kg ha-1 y-1 is needed to achieve cereal self-sufficiency. While such yield increases have been achieved elsewhere and are feasible given the yield potentials in SSA, they require structural changes and substantial agronomic, socioeconomic, and political investments. We estimate that amounts of added nitrogen need to at least triple to achieve such yield improvements, but it is essential that this comes with improved context-specific agronomy.

The 2024 Floods in Valencia (Spain): Case Study of Flood Risk Education in a Primary Education Setting

The 2024 cut-off low-pressure (DANA) event had a devastating impact on the province of Valencia (Spain), resulting in 227 fatalities. This extreme weather event highlighted the urgent need to enhance education on flood risk and prevention, particularly through geography lessons in schools. This paper presents a didactic experience conducted during the 2024–2025 academic year at a primary school in Alicante (Valencian Community, Spain), within the sixth-grade subject of “Natural, Social, and Cultural Environment Studies”. The initiative aimed to increase knowledge of the causes of flooding and safety measures, with a particular focus on the DANA event of 29 October 2024. Through hands-on and collaborative activities, the project sought to raise awareness of the importance of risk prevention and management. Ultimately, this educational approach aspires to foster a more resilient society, one that is better prepared to face the challenges posed by current and future climate change scenarios.

Transboundary river water quality assessment: a case study of Kabul River Basin, Pakistan.

In developing countries, microbial contamination of freshwater resources is a significant public health concern. The concentrations of Escherichia coli (E. coli) and influencing factors in the Kabul River Basin (KRB), Pakistan, were evaluated in this research, using the Soil and Water Assessment Tool (SWAT) model under various climate change scenarios. Streamflow (R2 = 0.66-0.71, NSE = 0.62-0.68) and E. coli (R2 = 0.70, NSE = 0.69) concentrations were utilized to calibrate and validate the model. Higher values of E. coli concentrations (3.55 to 5.20 log cfu/100ml) were observed during flood events. In 2050, according to Scenario-P1, point sources (human settlements) accounted for 19.7% of E. coli concentrations, non-point sources (livestock) for 46.8%, and upstream sources for 33.5%. This data is based on a moderate growth scenario that incorporates enhanced sanitation. In Scenario-P1, the quantity of E. coli decreased by 70% in comparison to the initial value. Additional advancements in sanitation practices and manure treatment (scenarios Aa, Ab, Ac) resulted in significant decreases in E. coli concentrations, reaching as low as 96%. On the contrary, under standard operating conditions (Scenario-P2), where sanitation and effluent treatment were inadequate, the prevalence of E. coli escalated by 158% by 2050 and further escalated by 201% by 2100. E. coli concentrations were influenced by climate change in conjunction with socioeconomic factors. To reduce E. coli concentrations in the KRB, enhanced sanitation, wastewater treatment, and manure management are emphasized in this study. The findings underscore the urgent need for immediate, robust interventions in wastewater treatment and sanitation infrastructure to prevent further public health risks. Without these critical improvements, the future health of the Kabul River Basin's population will remain under significant threat from escalating waterborne diseases, exacerbated by climate change.

Global assessment of invasion risk: Ardisia elliptica, one of the most noxious tropical shrubs in the world

BackgroundGlobal risk assessment of invasive weeds is a proactive strategy for identifying high-risk species and regions, predicting invasion rates and extents, and evaluating harmful impacts on native biodiversity, agriculture, and ecosystems. In this study, species distribution modeling was used to assess the global invasion risk of Ardisia elliptica, a highly invasive tropical shrub native to South and Southeast Asia that is harmful in other parts of the world, under the current climate and future climate change scenarios [shared socioeconomic pathways (SSPs) SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5] and other environmental variables, including land use and land cover change, soil moisture, soil carbon, soil pH, and human influence index.ResultsOur study revealed that annual precipitation, human influence index, and precipitation in the wettest month contributed significantly to the MaxEnt model, with estimated contributions of 31.35%, 22.76%, and 14.77%, respectively. These findings suggest that the global distribution of A. elliptica is limited primarily by climatic variables, whereas anthropogenic factors also play an important role in its habitat expansion. The current invasion risk was highest in South America, Oceania (east), and Africa, affecting up to 24.51% of the total land surface area. A risk assessment of 165 countries revealed a risk of invasion in 41 countries with no records of species occurrence. Under future climate change scenarios, a significant global expansion of the distribution was predicted, with invasion in South America covering up to 48.97% of the land surface area by 2061–2080. Habitat suitability analysis revealed that 21 countries under the current climate and 47 countries under SSP5-8.5 had extremely suitable habitats for A. elliptica. Additionally, the species has already invaded at least 115 countries, while 15 countries, including Benin, Burundi, Japan, Uruguay, Swaziland, and South Korea, are predicted to shift categories from having unsuitable or poor invasion risk to having high invasion risk.ConclusionsThese findings are crucial for understanding the global invasion risk of A. elliptica under substantial climate change and anthropogenic activities and support the development of effective biosecurity measures and sustainable management strategies for this harmful species at the global and national levels.