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This ethnographic study examines the disaster subculture of impoverished urban poor communities regarding extreme weather disasters, through the case of jjokbang‐chon, one of the most marginalized communities in Seoul, South Korea. The findings shed light on how jjokbang‐chon residents make meaning of disasters, where a sense of normalcy surrounds extreme weather, developed in response to recurring exposure to everyday hazards. This study offers insights into their lived experiences, revealing that the residents' perception of vulnerability often diverges from objective reality, primarily due to the pervasive "everyday disasters" that continually disrupt their lives. This "every day is a disaster" perspective, born from the chronic distress they endure, challenges their ability to recognize extreme weather events as disasters. This research carries implications for the field of social work by emphasizing the necessity of broadening the concept of vulnerability to encompass "everyday disasters," and highlights the pivotal role of social work in addressing the multifaceted challenges presented by everyday disasters. [ABSTRACT FROM AUTHOR]

The present study conducts a comparative analysis of India's eight Tier-1 cities, Mumbai, Delhi, Chennai, Kolkata, Bengaluru, Hyderabad, Ahmedabad, and Pune, for their climate vulnerability assessment. The secondary data was collected from the India Meteorological Department and published climate vulnerability atlas to draw the relative importance index (RII) score for each exposure indicator of climate vulnerability for each city on the ten climate parameters, including earthquake, rainfall, wind, thunderstorm, cyclone, drought, floods, heatwave, cold wave vulnerabilities. The cities based on inland and coastal boundaries were also considered in scoring calculations. The study's findings indicate that Chennai and Mumbai are the most vulnerable cities, primarily due to extreme weather events and sea-level rise, necessitating targeted adaptation strategies. Bengaluru shows lower vulnerability, reflecting its resilient infrastructure and proactive measures. Mid-range vulnerabilities are observed for Delhi, Kolkata, Ahmedabad, and Pune, highlighting diverse challenges from heat waves to flooding. Hyderabad's relatively lower score suggests moderate risk yet underscores the importance of continuous infrastructure improvement. The comparative analysis offers critical insights for urban planners and policymakers to develop tailored climate resilience strategies, emphasising sustainable infrastructure, community preparedness, and proactive urban design to mitigate climate risks and foster sustainable development across these urban conglomerates. The study serves as a foundational step towards enhancing the climate resilience of India's major cities. [ABSTRACT FROM AUTHOR]

Rural areas are disproportionately affected by climate change due to their relative social and economic vulnerability. Particularly in a coastal region like Shanghai where sea level rise and natural hazards are worsened by climate change, it is crucial to address these problems. Despite this, there exists a knowledge gap on climate change vulnerability in Shanghai rural areas. This study assesses the climate change vulnerability of rural areas in Shanghai by constructing a climate change vulnerability index based on the IPCC framework for vulnerability. Statistical, geospatial, and biophysical data was collected on all rural areas in Shanghai, and factor analysis was performed on the dataset to extract 6 factors from a total of 21 indicators, with these factors making up 67.39% of total variance in data. These factors included: socio-ecological-built characteristics (21.8%), demographic pressure (13.32%), weather variability and climate hazards (11.41%), sponge city characteristics (8.42%), demographic sensitivity (6.86%), and landscape characteristics (6.09%). It was found that 542,377 (7%) of the total rural population in Shanghai was living in subdistricts with high CVI, including 62,891 children (8%) and 58,441 elders (8%). Based on the results of this study it is suggested that planners prioritize robust transportation networks during times of emergency, robust weather and storm monitoring systems, policies that aim to preserve agricultural land and promote ecological agriculture practices and provide additional resources for more vulnerable populations such as the elderly, children, and women to mitigate climate change vulnerability. This research study provides a scientific basis for local planners and policy makers to formulate risk management policies to mitigate the negative impacts of climate change and provides crucial implications for rural planning. [ABSTRACT FROM AUTHOR]

While socioeconomic gradients in regional health inequalities are firmly established, the synergistic interactions between socioeconomic deprivation and climate vulnerability within convenient proximity and neighbourhood locations with health disparities remain poorly explored and thus require deep understanding within a regional context. Furthermore, disregarding the importance of spatial spillover effects and nonlinear effects of covariates on childhood stunting are inevitable in dealing with an enduring issue of regional health inequalities. The present study aims to investigate the spatial inequalities in childhood stunting at the district level in Pakistan and validate the importance of spatial lag in predicting childhood stunting. Furthermore, it examines the presence of any nonlinear relationships among the selected independent features with childhood stunting. The study utilized data related to socioeconomic features from MICS 2017–2018 and climatic data from Integrated Contextual Analysis. A multi-model approach was employed to address the research questions, which included Ordinary Least Squares Regression (OLS), various Spatial Models, Machine Learning Algorithms and Explainable Artificial Intelligence methods. Firstly, OLS was used to analyse and test the linear relationships among selected variables. Secondly, Spatial Durbin Error Model (SDEM) was used to detect and capture the impact of spatial spillover on childhood stunting. Third, XGBoost and Random Forest machine learning algorithms were employed to examine and validate the importance of the spatial lag component. Finally, EXAI methods such as SHapley were utilized to identify potential nonlinear relationships. The study found a clear pattern of spatial clustering and geographical disparities in childhood stunting, with multidimensional poverty, high climate vulnerability and early marriage worsening childhood stunting. In contrast, low climate vulnerability, high exposure to mass media and high women's literacy were found to reduce childhood stunting. The use of machine learning algorithms, specifically XGBoost and Random Forest, highlighted the significant role played by the average value in the neighbourhood in predicting childhood stunting in nearby districts, confirming that the spatial spillover effect is not bounded by geographical boundaries. Furthermore, EXAI methods such as partial dependency plot reveal the existence of a nonlinear relationship between multidimensional poverty and childhood stunting. The study's findings provide valuable insights into the spatial distribution of childhood stunting in Pakistan, emphasizing the importance of considering spatial effects in predicting childhood stunting. Individual and household-level factors such as exposure to mass media and women's literacy have shown positive implications for childhood stunting. It further provides a justification for the usage of EXAI methods to draw better insights and propose customised intervention policies accordingly. [ABSTRACT FROM AUTHOR]

The aim of the paper is to examine the influence of climate vulnerability (CV) on the formation of new firms. Employing a large sample of 140 countries spanning the time frame 2006–2020, it has been found that climate vulnerability harms new firm formation. The empirical results show that the negative impact of CV on the average new business formation rate has been 3.40. The results prove to be robust for alternative subsamples and methodology. Furthermore, the results of the quantile regression highlight a parameter heterogeneity in the effect of CV on entrepreneurial activity. Overall, the empirical findings highlight the key role of climate vulnerabilities in developing public policies aimed to spur entrepreneurial activity. [ABSTRACT FROM AUTHOR]

The Indian west coast is under constant threat from climate change-induced hazards. Various social, economic, and infrastructural disparities along the coast cause significant variations in climate vulnerability. Current literature assesses vulnerability either over (1) a large area with poor spatial resolution or (2) a local area with better spatial resolution. The former assessments provide more comprehensive and broad insights into large spatial trends of vulnerability, while the latter provide more accurate and specific inputs needed by the local governments for effective intervention. However, there is a lack of studies that assess vulnerability simultaneously at a high-resolution and over a large geographic area, due to inadequacies in existing methodologies and difficulty in data management and analysis. This is a key gap that we address in our paper. We assess climate vulnerability of the entire Indian west coast at the village level, and propose a novel machine-learning based methodology tailored for high-resolution assessment over large geographic areas. This helped us produce the first high-resolution (i.e. village-level) climate vulnerability map of the entire Indian west coast. We found that the state of Maharashtra has the highest number of vulnerable villages and the state of Kerala has the least number of vulnerable villages. We collate and utilize a large dataset of 112 indicators describing socioeconomic characteristics, infrastructure and availability of financial services, among other aspects, to obtain a comprehensive picture of vulnerability. We analyze geospatial trends and attribute high vulnerability to specific indicators, which will help in effective decision-making at the village level. [ABSTRACT FROM AUTHOR]

Reducing vulnerability of smallholder farmers to climate change is a global issue. One approach viewed as important in reducing farmers' vulnerability to climate change is Climate-Smart Agriculture (CSA). CSA is often seen as an approach to redefine, reposition and sustainably manage agriculture. Given the importance of CSA practices in sustaining the food needs of many farm households in sub-Saharan Africa and Ghana, this study investigates CSA practices that were introduced to farmers by Center for Indigenous Knowledge and Development (CIKOD), interrogates the contributions of CSA to reducing farmers vulnerability to climate change and established the relationship between CSA and climate change adaptation. The study employed a mixed method approach, using 146 smallholder millet and sorghum farmers. Questionnaire and interviews were used to generate primary data for analysis. Descriptive statistics, involving Chisquare test and relative importance index were used to analyze the questionnaire while thematic analytical approach was used to analyze the interviews. The results of the study revealed that CSA practices such as crop rotation, weed control, contour farming, and land rotation are deployed by smallholder farmers to respond to drought, dry spell and flood in the Municipality. Asset holding capacity, credit, access to climate information, and extension services were found to be key determinants of farmers' adoption of CSA practices. The study recommends the need for the Ministry of Food and Agriculture to provide some technical support to smallholder farmers to successfully adopt these practices for sustainable farming. Again, the study recommends the need for nongovernmental organizations and development partners, which over the years have shown interest in promoting CSA practices among farmers, to continuous to support and promote the adoption of CSA by farmers. [ABSTRACT FROM AUTHOR]

Changing rainfall patterns make farmers increasingly vulnerable to crop failure, income loss and food insecurity. Agroecology is proposed to reduce climate vulnerabilities of farmers, as such practices and social movement aim to create more resilient farm and food systems. It is however fairly unknown if, and to what extent, agroecological farmers are better able to cope with climate induced exposures as compared to conventional smallholders. We conducted 194 surveys with agroecological and conventional smallholders to explore the three components of climate vulnerability: exposure, sensitivity and adaptive capacity. We combined this with field observations and interviews, and an analysis of longterm rainfall data. We also followed up the initial survey analysis with additional focus group discussions. Just as climate change occurs incrementally over time, we highlight modest, yet important differences between conventional and agroecological farmers. We find that agroecological farmers are less vulnerable to short-term dry spells, due to a combination of farming practices that improve soil water retention, like mulching and the use of cover crops. However, the use of botanicals might induce new vulnerabilities, as their processing requires additional labor, and sometimes expenditures, and may not protect the crops from pests and diseases. We also find limitations to agroecology in terms of scale, as most farmers are unable to use botanicals on all their farmland. Yet, agroecological farmers process and apply botanicals for health benefits both in production and consumption of foods, and they can occasionally sell their organic farm products for a higher price than conventional famers. With this study, we emphasize that farmers' reasons to practice agroecology is not just to boost productivity and become more climate resilient, but rather for improving the long-term health of producers, consumers, soils and the environment. [ABSTRACT FROM AUTHOR]

Climate change is anticipated to cause species to shift their ranges upward and poleward, yet space for tracking suitable habitat conditions may be limited for range‐restricted species at the highest elevations and latitudes of the globe. Consequently, range‐restricted species inhabiting Arctic freshwater ecosystems, where global warming is most pronounced, face the challenge of coping with changing abiotic and biotic conditions or risk extinction. Here, we use an extensive fish community and environmental dataset for 1762 lakes sampled across Scandinavia (mid‐1990s) to evaluate the climate vulnerability of Arctic char (Salvelinus alpinus), the world's most cold‐adapted and northernly distributed freshwater fish. Machine learning models show that abiotic and biotic factors strongly predict the occurrence of Arctic char across the region with an overall accuracy of 89 percent. Arctic char is less likely to occur in lakes with warm summer temperatures, high dissolved organic carbon levels (i.e., browning), and presence of northern pike (Esox lucius). Importantly, climate warming impacts are moderated by habitat (i.e., lake area) and amplified by the presence of competitors and/or predators (i.e., northern pike). Climate warming projections under the RCP8.5 emission scenario indicate that 81% of extant populations are at high risk of extirpation by 2080. Highly vulnerable populations occur across their range, particularly near the southern range limit and at lower elevations, with potential refugia found in some mountainous and coastal regions. Our findings highlight that range shifts may give way to range contractions for this cold‐water specialist, indicating the need for pro‐active conservation and mitigation efforts to avoid the loss of Arctic freshwater biodiversity. [ABSTRACT FROM AUTHOR]

Food security and livelihood vulnerability are important issues for the economic sustainability of developing countries like Bangladesh. This study examines the influence of total factor productivity (TFP) on the livelihood vulnerability and food security of rice farming households in Bangladesh. Data from 1,841 rice farming households were extracted from the Bangladesh Integrated Household Survey (2015 and 2018) conducted by the International Food Policy Research Institute. Various statistical methods, such as the stochastic frontier model, principal component analysis, path analysis using structural equation modeling, and multivariate regression, were employed to analyze the data. The study utilizes a multivariate modeling approach that combines the stochastic frontier model to determine TFP and sophisticated methodologies to estimate the livelihood vulnerability index (LVI) and women's empowerment in agriculture index (WEAI). The LVI, household dietary diversity Score (HDDS), TFP, and WEAI scores were 0.454, 10.72, 0.703, and 0.717, respectively. The results indicate a significant relationship between TFP and both LVI and HDDS. Higher TFP is associated with lower LVI and higher HDDS among rice farming households, suggesting that improving TFP can enhance food security and reduce vulnerability. The multivariate regression analysis reveals that TFP, household wealth index, women's empowerment in agriculture index, per capita food expenditure, household level welfare, and household size have a positive significant impact on HDDS, while TFP is negatively associated with LVI, per capita food expenditure and household size. The findings underscore the importance of increasing TFP to improve food security, reduce livelihood vulnerability, and achieve sustainable development goals in countries like Bangladesh. Higher TFP yields positive outcomes regarding household dietary diversity and livelihood vulnerability, highlighting the need for agricultural policies that prioritize TFP enhancement. Policymakers and professionals can use these findings as a roadmap to implement advanced agricultural policies to achieve food security and reduce livelihood vulnerability. Improving household dietary diversity and reducing livelihood vulnerability can be achieved by focusing on increasing TFP, enhancing household wealth, women's empowerment, per capita food expenditure, household welfare, and household size. Therefore, increasing TFP should be considered in the design of policies aiming to achieve SDGs Goal 2. [ABSTRACT FROM AUTHOR]

Ecuador, a country with distinct coastal (CO), highland (HL), and Amazon (AM) regions that are characterized by unique climatic, ecological, and socio-economic features is highly vulnerable to climate change. This study focuses on these three regions, highlighting their individual importance in the broader context of Ecuador's climate vulnerability. Utilizing dynamically downscaled data from the Regional Climate Model (RCM), we generated precipitation and air temperature projections for the period 2070-2099 under three different climate change scenarios. We indicate projected temperature increases across all three regions: mean temperature increases for the CO, HL and AM regions are of 1.35, 1.55, and 1.21°C, respectively. Each year, the largest temperature increases are predicted for the third quarter (June-August), with the smallest increases predicted for the last quarter (December-February). Precipitation patterns show varied changes, with CO exhibiting a positive mean daily change, in contrast to a mean negative change in the AM region. These region-specific projections underscore the differential impacts of climate change within Ecuador and highlight the necessity for tailored adaptation measures. The study's novel approach, focusing on distinct regional impacts within a single nation, offers valuable insights for policymakers, aiding in the development of effective, region-specific climate change mitigation and adaptation strategies. This targeted approach is crucial to address unique challenges faced by different regions, thereby supporting national resilience strategies. [ABSTRACT FROM AUTHOR]

Addressing climate vulnerability remains a priority for economies globally. This study used the panel-corrected standard error (PCSE) methodology to investigate the impact of adaptation financing on climate vulnerability. This analysis examined 52 African countries from 2012 to 2021 while considering their climate adaptation readiness. The impact was also assessed based on the Human Development Index (HDI) categories to reflect different levels of development. The findings showed that adaptation finance considerably influenced climate vulnerability reduction in Africa, particularly in nations with a moderate HDI. However, most countries still need higher levels of adaptation financing, resulting in a small impact on vulnerability reduction. Furthermore, the impact of readiness measures differed by HDI category. Economic and social climate readiness strongly impacted climate vulnerability in high-HDI nations, but governance preparedness was more critical in low-HDI countries. Based on the empirical facts, two policy proposals emerge. First, it is critical to reconsider the distribution of adaptation financing to reduce disparities and effectively alleviate climate vulnerability. Moreover, African economies should consider implementing innovative localized financing mechanisms to mobilize extra adaptation finance. Second, African governments should customize climate readiness interventions based on their HDI levels to improve the achievement of a positive impact on climate vulnerability. [ABSTRACT FROM AUTHOR]

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Among the issues most related to climate change, the built environment is also subjected to short- and long-term risks. Referring to tangible cultural heritage, materials and buildings are subjected to different types of damage that require adaptive risk prevention and containment strategies, currently missing from conventional risk assessments. Thus, there is an increasingly urgent need for scientific and technical knowledge, tools, and solutions aimed at solving critical issues in cultural heritage due to climate change. In this context, the aim of this study is to study the mechanisms of impacts brought about by climate change and the formulation of a possible set of indices as benchmarks to measure climate change's effect on cultural heritage buildings. The study is structured on a methodology that identifies three sections: the first and second parts systematize and critically interpret data on impact mechanisms and indices for climate vulnerability and risk assessment; the third part, data processing, reports the perspective findings. The main intermediate indices, contributing to a comprehensive damage index, were identified, and a procedural protocol was developed. Finally, through the correlation of indices, a potential case study could be analyzed, and benchmarks made effective. The study reports partial results of one of the "Ecosystems of Innovation" pilot projects funded by the National Recovery and Resilience Plan. The study is still a work in progress and needs advancement and deepening to verify case study indices. [ABSTRACT FROM AUTHOR]

Reducing vulnerability of smallholder farmers to climate change is a global issue. One approach viewed as important in reducing farmers’ vulnerability to climate change is Climate-Smart Agriculture (CSA). CSA is often seen as an approach to redefine, reposition and sustainably manage agriculture. Given the importance of CSA practices in sustaining the food needs of many farm households in sub-Saharan Africa and Ghana, this study investigates CSA practices that were introduced to farmers by Center for Indigenous Knowledge and Development (CIKOD), interrogates the contributions of CSA to reducing farmers vulnerability to climate change and established the relationship between CSA and climate change adaptation. The study employed a mixed method approach, using 146 smallholder millet and sorghum farmers. Questionnaire and interviews were used to generate primary data for analysis. Descriptive statistics, involving Chi-square test and relative importance index were used to analyze the questionnaire while thematic analytical approach was used to analyze the interviews. The results of the study revealed that CSA practices such as crop rotation, weed control, contour farming, and land rotation are deployed by smallholder farmers to respond to drought, dry spell and flood in the Municipality. Asset holding capacity, credit, access to climate information, and extension services were found to be key determinants of farmers’ adoption of CSA practices. The study recommends the need for the Ministry of Food and Agriculture to provide some technical support to smallholder farmers to successfully adopt these practices for sustainable farming. Again, the study recommends the need for non-governmental organizations and development partners, which over the years have shown interest in promoting CSA practices among farmers, to continuous to support and promote the adoption of CSA by farmers.

Changing rainfall patterns make farmers increasingly vulnerable to crop failure, income loss and food insecurity. Agroecology is proposed to reduce climate vulnerabilities of farmers, as such practices and social movement aim to create more resilient farm and food systems. It is however fairly unknown if, and to what extent, agroecological farmers are better able to cope with climate induced exposures as compared to conventional smallholders. We conducted 194 surveys with agroecological and conventional smallholders to explore the three components of climate vulnerability: exposure, sensitivity and adaptive capacity. We combined this with field observations and interviews, and an analysis of long-term rainfall data. We also followed up the initial survey analysis with additional focus group discussions. Just as climate change occurs incrementally over time, we highlight modest, yet important differences between conventional and agroecological farmers. We find that agroecological farmers are less vulnerable to short-term dry spells, due to a combination of farming practices that improve soil water retention, like mulching and the use of cover crops. However, the use of botanicals might induce new vulnerabilities, as their processing requires additional labor, and sometimes expenditures, and may not protect the crops from pests and diseases. We also find limitations to agroecology in terms of scale, as most farmers are unable to use botanicals on all their farmland. Yet, agroecological farmers process and apply botanicals for health benefits both in production and consumption of foods, and they can occasionally sell their organic farm products for a higher price than conventional famers. With this study, we emphasize that farmers’ reasons to practice agroecology is not just to boost productivity and become more climate resilient, but rather for improving the long-term health of producers, consumers, soils and the environment.

Over the past decade, the increase in extreme weather events requires each sector to reflect on vulnerabilities to develop strategies for ramping up climate action. Owing to the shortage of climate data, significant knowledge gaps exist in some sectors of society and the economy, particularly in developing countries such as Africa. This has caused challenges for adaptation and resilience building as governments and other stakeholders cannot leverage knowledge for policy and practice and to seek funding for climate change action. This study responds to this knowledge by examining sea level challenges and their implications on coastal national parks in South Africa. The key question for this study is the most at-risk areas regarding sea level in coastal national parks and the implications of sea level on coastal national parks. The study utilises primary, secondary and archival data to arrive at conclusions. The study also uses climate change modelling data from SSP2-4.5 and SSP3-7.0. The study found that the most vulnerable coastal park in South Africa is the Garden Route National Park , which has the highest sea level rise, which will result in the Knysna section followed by the Cape Point section of Table Mountain, which will see the areas witnessing a 1m rise in sea level around 2100. Sea level rise is a threat to infrastructure, heritag e, beaches, tourism employees and tourist safety, to mention but a few. The study recommends scaling up climate change action to assist the parks in adapting and building climate change resilience.

Access to safe sanitation is a basic requirement for human well-being and is critical for protecting public health and preventing environmental contamination at the community level. The increasing global risk of climate-related disasters exacerbates the likelihood of traditional sanitation solutions failing and exposing communities to harmful pathogens. This risk is ubiquitous in Cambodia's flood-prone Tonle Sap Lake region, which has some of the lowest rates of sanitation coverage in the country. This study sought to design and test a targeted mechanism in the region to deliver sanitation subsidies to households in a vulnerable position due to climate and socioeconomic characteristics. Subsidy eligibility was evaluated using the poverty probability index for Cambodia, with thresholds set according to households' individual and community-level climate vulnerability. In a randomized controlled trial, offering subsidies increased the likelihood of successful sales conversions for climate-resilient latrine products among targeted households by 32 percentage points, indicating effectiveness for increasing market-based sanitation uptake. The research did not find evidence of widespread or sustained market distortion due to the subsidy program. HIGHLIGHTS Being offered a subsidy increased the likelihood that a given household would purchase a latrine by 31% (over ineligible comparison households).; The sales closing rate among eligible households in treatment areas was 38% compared to 6% among ineligible treatment households.; When offered a subsidy, households who were climate vulnerable were most likely to purchase a latrine.; No evidence of significant market distortion due to the subsidy was identified.;

While socioeconomic gradients in regional health inequalities are firmly established, the synergistic interactions between socioeconomic deprivation and climate vulnerability within convenient proximity and neighbourhood locations with health disparities remain poorly explored and thus require deep understanding within a regional context. Furthermore, disregarding the importance of spatial spillover effects and nonlinear effects of covariates on childhood stunting are inevitable in dealing with an enduring issue of regional health inequalities. The present study aims to investigate the spatial inequalities in childhood stunting at the district level in Pakistan and validate the importance of spatial lag in predicting childhood stunting. Furthermore, it examines the presence of any nonlinear relationships among the selected independent features with childhood stunting. The study utilized data related to socioeconomic features from MICS 2017–2018 and climatic data from Integrated Contextual Analysis. A multi-model approach was employed to address the research questions, which included Ordinary Least Squares Regression (OLS), various Spatial Models, Machine Learning Algorithms and Explainable Artificial Intelligence methods. Firstly, OLS was used to analyse and test the linear relationships among selected variables. Secondly, Spatial Durbin Error Model (SDEM) was used to detect and capture the impact of spatial spillover on childhood stunting. Third, XGBoost and Random Forest machine learning algorithms were employed to examine and validate the importance of the spatial lag component. Finally, EXAI methods such as SHapley were utilized to identify potential nonlinear relationships. The study found a clear pattern of spatial clustering and geographical disparities in childhood stunting, with multidimensional poverty, high climate vulnerability and early marriage worsening childhood stunting. In contrast, low climate vulnerability, high exposure to mass media and high women’s literacy were found to reduce childhood stunting. The use of machine learning algorithms, specifically XGBoost and Random Forest, highlighted the significant role played by the average value in the neighbourhood in predicting childhood stunting in nearby districts, confirming that the spatial spillover effect is not bounded by geographical boundaries. Furthermore, EXAI methods such as partial dependency plot reveal the existence of a nonlinear relationship between multidimensional poverty and childhood stunting. The study’s findings provide valuable insights into the spatial distribution of childhood stunting in Pakistan, emphasizing the importance of considering spatial effects in predicting childhood stunting. Individual and household-level factors such as exposure to mass media and women’s literacy have shown positive implications for childhood stunting. It further provides a justification for the usage of EXAI methods to draw better insights and propose customised intervention policies accordingly.

Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non‐migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype‐environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change. [ABSTRACT FROM AUTHOR]

Vulnerability to climate change is a complex, multi-dimensional construct influenced by multiple interacting factors. Several methods and approaches have been developed over the past three decades, yet there are no standard methods for assessing vulnerability (Connelly et al. in State of the art report (4) vulnerability assessment: definitions, indicators and existing assessment methods (issue 4), 2015). The vulnerability assessment studies differ in conceptualization, methodology, sectors affected, exposure to specific hazards, regional factors, and the scale of impact. Assessment of climate vulnerability and identification of indicators to measure it are significant problems. This paper provides a comprehensive and systematic review of indicator-based vulnerability assessment studies from 1990 to 2020. We analyse 84 studies to understand various aspects of vulnerability assessment—concept and approach, dimensions and indicators, and assessment methods. Though multi-dimensional assessments represent the overall vulnerability of an area, only 29.8% of the studies assessed more than one dimension. Analysis shows that 68.8% (75 of 109) of the identified indicators belong to the socioeconomic dimension. Socioeconomic vulnerability is the most assessed, and environmental vulnerability is the least assessed dimension, possibly attributed to ease of data availability. Due to the lack of methodological differences, there has been confusion associated with index-based and indicator-based studies in the literature (Ramieri et al. in Methods for assessing coastal vulnerability to climate change. ETC CCA Tech Paper 1/2011 (issue January), 2011. 10.13140/RG.2.1.1906.9840). Therefore, we develop a taxonomy of the existing vulnerability assessment methods based on their methodological approach. To avoid ambiguity, we denote all methods that employ indicators as indicator-based vulnerability assessment methods and classify them into index-based, clustering-based, and GIS-based methods. Finally, we discuss the advantages and disadvantages of each vulnerability assessment method and the open challenges in this research area. [ABSTRACT FROM AUTHOR]

Accumulation by adaptation names the phenomenon by which political and economic elites profit from climate adaptation efforts. As with the notion of 'accumulation by dispossession' from which it derives, the term speaks to the injustice of capital accumulation—in this case, accumulation associated with configuring some groups' vulnerability to climate change as business opportunities. However, unlike accumulation by dispossession, the mechanisms by which accumulation by adaptation proceeds have not been adequately conceptualized. This review synthesizes critiques of Marx's formulation of primitive accumulation, recent scholarship on colonial racial capitalism, and critical adaptation studies to locate how capital circulates through and reproduces the violence of climate change. [ABSTRACT FROM AUTHOR]

Seagrass is an important natural attribute of 28 World Heritage (WH) properties. These WH seagrass habitats provide a wide range of services to adjacent ecosystems and human communities, and are one of the largest natural carbon sinks on the planet. Climate change is considered the greatest and fastest‐growing threat to natural WH properties and evidence of climate‐related impacts on seagrass habitats has been growing. The main objective of this study was to assess the vulnerability of WH seagrass habitats to location‐specific key climate stressors. Quantitative surveys of seagrass experts and site managers were used to assess exposure, sensitivity and adaptive capacity of WH seagrass habitats to climate stressors, following the Climate Vulnerability Index approach. Over half of WH seagrass habitats have high vulnerability to climate change, mainly from the long‐term increase in sea‐surface temperature and short‐term marine heatwaves. Potential impacts from climate change and certainty scores associated with them were higher than reported by a similar survey‐based study from 10 years prior, indicating a shift in stakeholder perspectives during the past decade. Additionally, seagrass experts' opinions on the cumulative impacts of climate and direct‐anthropogenic stressors revealed that high temperature in combination with high suspended sediments, eutrophication and hypoxia is likely to provoke a synergistic cumulative (negative) impact (p <.05). A key component contributing to the high vulnerability assessments was the low adaptive capacity; however, discrepancies between adaptive capacity scores and qualitative responses suggest that managers of WH seagrass habitats might not be adequately equipped to respond to climate change impacts. This thematic assessment provides valuable information to help prioritize conservation actions, monitoring activities and research in WH seagrass habitats. It also demonstrates the utility of a systematic framework to evaluate the vulnerability of thematic groups of protected areas that share a specific attribute. [ABSTRACT FROM AUTHOR]

Climate warming, land use change, and altered fire regimes are driving ecological transformations that can have critical effects on Earth's biota. Fire refugia—locations that are burned less frequently or severely than their surroundings—may act as sites of relative stability during this period of rapid change by being resistant to fire and supporting post‐fire recovery in adjacent areas. Because of their value to forest ecosystem persistence, there is an urgent need to anticipate where refugia are most likely to be found and where they align with environmental conditions that support post‐fire tree recruitment. Using biophysical predictors and patterns of burn severity from 1180 recent fire events, we mapped the locations of potential fire refugia across upland conifer forests in the southwestern United States (US) (99,428 km2 of forest area), a region that is highly vulnerable to fire‐driven transformation. We found that low pre‐fire forest cover, flat slopes or topographic concavities, moderate weather conditions, spring‐season burning, and areas affected by low‐ to moderate‐severity fire within the previous 15 years were most commonly associated with refugia. Based on current (i.e., 2021) conditions, we predicted that 67.6% and 18.1% of conifer forests in our study area would contain refugia under moderate and extreme fire weather, respectively. However, potential refugia were 36.4% (moderate weather) and 31.2% (extreme weather) more common across forests that experienced recent fires, supporting the increased use of prescribed and resource objective fires during moderate weather conditions to promote fire‐resistant landscapes. When overlaid with models of tree recruitment, 23.2% (moderate weather) and 6.4% (extreme weather) of forests were classified as refugia with a high potential to support post‐fire recruitment in the surrounding landscape. These locations may be disproportionately valuable for ecosystem sustainability, providing habitat for fire‐sensitive species and maintaining forest persistence in an increasingly fire‐prone world. [ABSTRACT FROM AUTHOR]

This study dissects the patterns and trends of communal violence in Nigeria with the need to watch out for emerging predictors. Using variables like ethno-religious polarization, lootable resources, and climate vulnerability, the article dissects their impacts on the trends of communal violence in Nigeria. Based on data from the Nigerian Security Tracker, Nigeria Watch, and the Federal Ministry of Environment (2014 to 2021), this study uses cluster analyses of the conflicts using maps and tables to analyze the patterns and new dimensions of conflicts. The study found evidence that ethno-religious polarization is a predictor of trends of communal violence in Nigeria. The weakest predictor of communal violence, according to the model, is climate vulnerability in Nigeria. [ABSTRACT FROM AUTHOR]

Ecuador, a country with distinct coastal (CO), highland (HL), and Amazon (AM) regions that are characterized by unique climatic, ecological, and socio-economic features is highly vulnerable to climate change. This study focuses on these three regions, highlighting their individual importance in the broader context of Ecuador's climate vulnerability. Utilizing dynamically downscaled data from the Regional Climate Model (RCM), we generated precipitation and air temperature projections for the period 2070–2099 under three different climate change scenarios. We indicate projected temperature increases across all three regions: mean temperature increases for the CO, HL and AM regions are of 1.35, 1.55, and 1.21°C, respectively. Each year, the largest temperature increases are predicted for the third quarter (June–August), with the smallest increases predicted for the last quarter (December–February). Precipitation patterns show varied changes, with CO exhibiting a positive mean daily change, in contrast to a mean negative change in the AM region. These region-specific projections underscore the differential impacts of climate change within Ecuador and highlight the necessity for tailored adaptation measures. The study's novel approach, focusing on distinct regional impacts within a single nation, offers valuable insights for policymakers, aiding in the development of effective, region-specific climate change mitigation and adaptation strategies. This targeted approach is crucial to address unique challenges faced by different regions, thereby supporting national resilience strategies.

Food security and livelihood vulnerability are important issues for the economic sustainability of developing countries like Bangladesh. This study examines the influence of total factor productivity (TFP) on the livelihood vulnerability and food security of rice farming households in Bangladesh. Data from 1,841 rice farming households were extracted from the Bangladesh Integrated Household Survey (2015 and 2018) conducted by the International Food Policy Research Institute. Various statistical methods, such as the stochastic frontier model, principal component analysis, path analysis using structural equation modeling, and multivariate regression, were employed to analyze the data. The study utilizes a multivariate modeling approach that combines the stochastic frontier model to determine TFP and sophisticated methodologies to estimate the livelihood vulnerability index (LVI) and women’s empowerment in agriculture index (WEAI). The LVI, household dietary diversity Score (HDDS), TFP, and WEAI scores were 0.454, 10.72, 0.703, and 0.717, respectively. The results indicate a significant relationship between TFP and both LVI and HDDS. Higher TFP is associated with lower LVI and higher HDDS among rice farming households, suggesting that improving TFP can enhance food security and reduce vulnerability. The multivariate regression analysis reveals that TFP, household wealth index, women’s empowerment in agriculture index, per capita food expenditure, household level welfare, and household size have a positive significant impact on HDDS, while TFP is negatively associated with LVI, per capita food expenditure and household size. The findings underscore the importance of increasing TFP to improve food security, reduce livelihood vulnerability, and achieve sustainable development goals in countries like Bangladesh. Higher TFP yields positive outcomes regarding household dietary diversity and livelihood vulnerability, highlighting the need for agricultural policies that prioritize TFP enhancement. Policymakers and professionals can use these findings as a roadmap to implement advanced agricultural policies to achieve food security and reduce livelihood vulnerability. Improving household dietary diversity and reducing livelihood vulnerability can be achieved by focusing on increasing TFP, enhancing household wealth, women’s empowerment, per capita food expenditure, household welfare, and household size. Therefore, increasing TFP should be considered in the design of policies aiming to achieve SDGs Goal 2.

Zinc is a green mineral that is increasingly required for manufacturing low-carbon technology. This demand has been promoted mainly by the Global North-led green policies to mitigate the impacts of climate change. However, simultaneously expanding zinc mining risks further entrenching climate threats in fragile socio-ecological environments such as the Peruvian highlands. This article analyses the linkages between the accelerated green extractivism of zinc and its associated climate-related vulnerabilities in the Cunas watershed in the Central highlands of Peru. The study draws on ethnographic-oriented fieldwork in the area in 2019, and 2022 and a review of policy documents on climate mitigation and zinc mining in Peru. The analysis particularly focuses on the recently reopened Azulcocha zinc mine and its intertwined socio-ecological effects on the local waterscapes amid climate change. The analysis draws the theoretical approaches of the political ecology of green extractivism and vulnerability to disentangle the multi-scalar power dynamics embedded in the global low-carbon transition and green extractivism and how these shape climate-related vulnerabilities. The study shows that with the impacts of climate change, accelerated extractivism risks (re)producing multiple vulnerabilities in the Andean highland communities. The findings highlight the urgent need to rethink the global climate proposals in such a way that they do not deepen climate damage in the already marginalized waterscapes in the Andes and elsewhere in the Global South.

Abstract Background Malaria is still a disease of massive burden in Africa, also influenced by climate change. The fluctuations and trends of the temperature and precipitation are well-known determinant factors influencing the disease’s vectors and incidence rates. This study provides a concise account of malaria trends. It describes the association between average temperature and malaria incidence rates (IR) in nine sub-Saharan African countries: Nigeria, Ethiopia, South Africa, Kenya, Uganda, Ghana, Mozambique, Zambia and Zimbabwe. The incidence of malaria can vary both in areas where the disease is already present, and in regions where it is present in low numbers or absent. The increased vulnerability to the disease under increasing average temperatures and humidity is due to the new optimal level for vector breeding in areas where vector populations and transmission are low, and populations are sensitive due to low acquired immunity. Methods A second source trend analysis was carried out of malaria cases and incidence rates (the number of new malaria cases per 1000 population at risk per year) with data from the World Health Organization (WHO) and average annual mean temperature from 2000 to 2018 from the World Bank’s Climate Change Knowledge Portal (CCKP). Additionally, descriptive epidemiological methods were used to describe the development and trends in the selected countries. Furthermore, MS Excel was chosen for data analysis and visualization. Results Findings obtained from this article align with the recent literature, highlighting a declining trend (20–80%) of malaria IR (incidence rate) from 2000 to 2018. However, malaria IR varies considerably, with high values in Uganda, Mozambique, Nigeria and Zambia, moderate values in Ghana, Zimbabwe, and Kenya, and low values in South Africa and Ethiopia in 2018. Evidence suggests varying IRs after average temperature fluctuations in several countries (e.g., Zimbabwe, Ethiopia). Also, an inverse temperature-IR relationship occurs, the sharp decrease of IR during 2012–2014 and 2000–2003, respectively, occurred with increasing average temperatures in Ghana and Nigeria. The decreasing trends and fluctuations, partly accompanying the temperature, should result from the intervention programmes and rainfall variability. The vulnerability and changing climate could arrest the recent trends of falling IR. Conclusion Thus, malaria is still a crucial public health issue in sub-Saharan Africa, although a robust decreasing IR occurred in most studied countries.

Abstract Background Global climate change poses a significant challenge in contemporary society, particularly affecting vulnerable populations like small farmers residing in arid and semiarid regions. This study aims to investigate the perception of health risks and adaptive responses in the semiarid region of Northeast Brazil (NEB). Four questions were formulated: (1) How do socioeconomic factors influence the perception of health risks during extreme climate events? (2) How do socioeconomic factors impact the adoption of adaptive responses to mitigate health risks during extreme weather events? (3) How does the perceived risk level affect the utilization of adaptive responses? (4) What is the influence of extreme climate events on the perceived risks and the adoption of adaptive responses? Method The research was conducted in the rural community of Carão, situated in the Agreste region of the State of Pernambuco, NEB. Semi-structured interviews were conducted with 49 volunteers aged 18 and above. The interviews aimed to gather socioeconomic information, including sex, age, income, access to healthcare services, family size, and education level. Additionally, the interviews explored the perceived risks and responses employed during different extreme climate events such as droughts or heavy rainfall. The perceived risks and adaptive responses data were quantified to address the research questions. Generalized linear models were employed to analyze the data for the first three questions, while the nonparametric Mann–Whitney test was used for the fourth question. Results The study found no significant differences in the level of perceived risk and adaptive responses between the two climate extremes. However, the quantity of adaptive responses was found to be directly influenced by the perceived risks, regardless of the type of extreme climate event. Conclusion The study concludes that risk perception is influenced by various complex factors, including socioeconomic variables, and plays a critical role in the adoption of adaptive responses during extreme climate events. The findings suggest that specific socioeconomic variables have a more pronounced influence on how individuals perceive and adapt to risks. Furthermore, the results indicate a cause-and-effect relationship between perceived risks and the generation of adaptive responses. These findings contribute to a better understanding of the factors shaping risk perception and provide valuable insights for future studies in regions prone to extreme climate events.

Abstract Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non‐migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype‐environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change.

Within the past decade, the attribution of extreme weather events and their impacts has enabled scientists, the public, and policymakers alike to connect real-world experiences of extreme weather events with scientific understanding of anthropogenic climate change. Attribution studies of recent extreme weather events have formed a new and important line of evidence in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report understanding present-day impacts of climate change. IPCC studies using different methods of event attribution have been assessed together, highlighting that these differences are smaller than the academic discourse on the methods suggests. This development raised two important research questions the science needs to answer: First, how do we formally combine attribution statements using highly conditional methods with probabilistic assessments of how climate change alters the likelihood and intensity of extreme weather events? Second, under what circumstances are individual attribution studies still necessary and to what extent do existing attribution studies provide enough information to answer societal questions? Furthermore, the scientific development still leaves important gaps, particularly in countries of the Global South, leading to ethical questions around the need and requirement of attribution of extreme events in policy contexts, informing adaptation and loss and damage and the role of vulnerability. [ABSTRACT FROM AUTHOR]

According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply of forage crops, a decrease in the productivity of forage crops is expected to cause increased damage to the domestic livestock industry. In this paper, to solve the issue of climate vulnerability for forage crops, we performed a study to predict the productivity of forage crops in relation to climate change. We surveyed and compiled not only forage crop production data from various regions, but also experimental cultivation production data over several years from reports of the Korea Institute of Animal Science and Technology. Then, we crawled related climate data from the Korea Meteorological Administration. Therefore, we were able to construct a basic database for forage crop production data and related climate data. Using the database, a production prediction model was implemented, applying a multivariate regression analysis and deep learning regression. The key factors were determined as a result of analyzing the changes in forage crop production due to climate change. Using the prediction model, it could be possible to forecast the shifting locations of suitable cultivation areas. As a result of our study, we were able to construct electromagnetic climate maps for forage crops in Republic of Korea. It can be used to present region-specific agricultural insights and guidelines for cultivation technology for forage crops against climate change. [ABSTRACT FROM AUTHOR]

Rural areas of the United States play a vital role in coping with, adapting to and mitigating climate change, yet they often lag urban areas in climate planning and action. Rural leaders—e.g., policymakers, state/federal agency professionals, non-profit organization leadership, and scholars – are pivotal for driving the programs and policies that support resilient practices, but our understanding of their perspectives on climate resilience writ large is limited. We conducted semi-structured interviews with 23 rural leaders in Missouri to elucidate their conceptualizations of climate resilience and identify catalysts and constraints for climate adaptation planning and action across rural landscapes. We investigated participants' perceptions of the major vulnerabilities of rural communities and landscapes, threats to rural areas, and potential steps for making rural Missouri more resilient in the face of climate change. We found that most rural leaders conceptualized climate resilience as responding to hazardous events rather than anticipating or planning for hazardous trends. The predominant threats identified were flooding and drought, which aligns with climate projections for the Midwest. Participants proposed a wide variety of specific steps to enhance resilience but had the highest agreement about the utility of expanding existing programs. The most comprehensive suite of solutions was offered by participants who conceptualized resilience as involving social, ecological, and economic systems, underscoring the importance of broad thinking for developing more holistic solutions to climate-associated threats and the potential impact of greater collaboration across domains. We highlight and discuss a Missouri-based levee setback project that was identified by participants as a showcase of collaborative resilience-building. [ABSTRACT FROM AUTHOR]

Over the past decade, the increase in extreme weather events requires each sector to reflect on vulnerabilities to develop strategies for ramping up climate action. Owing to the shortage of climate data, significant knowledge gaps exist in some sectors of society and the economy, particularly in developing countries such as Africa. This has caused challenges for adaptation and resilience building as governments and other stakeholders cannot leverage knowledge for policy and practice and to seek funding for climate change action. This study responds to this knowledge by examining sea level challenges and their implications on coastal national parks in South Africa. The key question for this study is the most at-risk areas regarding sea level in coastal national parks and the implications of sea level on coastal national parks. The study utilises primary, secondary and archival data to arrive at conclusions. The study also uses climate change modelling data from SSP2-4.5 and SSP3-7.0. The study found that the most vulnerable coastal park in South Africa is the Garden Route National Park, which has the highest sea level rise, which will result in the Knysna section followed by the Cape Point section of Table Mountain, which will see the areas witnessing a 1m rise in sea level around 2100. Sea level rise is a threat to infrastructure, heritag e, beaches, tourism employees and tourist safety, to mention but a few. The study recommends scaling up climate change action to assist the parks in adapting and building climate change resilience. [ABSTRACT FROM AUTHOR]

Species' thermal tolerances are used to estimate climate vulnerability, but few studies consider the role of the hydric environment in shaping thermal tolerances. As environments become hotter and drier, organisms often respond by limiting water loss to lower the risk of desiccation; however, reducing water loss may produce trade‐offs that lower thermal tolerances if respiration becomes inhibited. Here, we measured the sensitivity of water loss rate and critical thermal maximum (CTmax) to precipitation in nature and laboratory experiments that exposed click beetles (Coleoptera: Elateridae) to acute‐ and long‐term humidity treatments. We also took advantage of their unique clicking behavior to characterize subcritical thermal tolerances. We found higher water loss rates in the dry acclimation treatment compared to the humid, and water loss rates were 3.2‐fold higher for individuals that had experienced a recent precipitation event compared to individuals that had not. Acute humidity treatments did not affect CTmax, but precipitation indirectly affected CTmax through its effect on water loss rates. Contrary to our prediction, we found that CTmax was negatively associated with water loss rate, such that individuals with high water loss rate exhibited a lower CTmax. We then incorporated the observed variation of CTmax into a mechanistic niche model that coupled leaf and click beetle temperatures to predict climate vulnerability. The simulations indicated that indices of climate vulnerability can be sensitive to the effects of water loss physiology on thermal tolerances; moreover, exposure to temperatures above subcritical thermal thresholds is expected to increase by as much as 3.3‐fold under future warming scenarios. The correlation between water loss rate and CTmax identifies the need to study thermal tolerances from a "whole‐organism" perspective that considers relationships between physiological traits, and the population‐level variation in CTmax driven by water loss rate complicates using this metric as a straightforward proxy of climate vulnerability. [ABSTRACT FROM AUTHOR]

Forecasting long‐term consequences of global warming requires knowledge on thermal mortality and how heat stress interacts with other environmental stressors on different timescales. Here, we describe a flexible analytical framework to forecast mortality risks by combining laboratory measurements on tolerance and field temperature records. Our framework incorporates physiological acclimation effects, temporal scale differences and the ecological reality of fluctuations in temperature, and other factors such as oxygen. As a proof of concept, we investigated the heat tolerance of amphipods Dikerogammarus villosus and Echinogammarus trichiatus in the river Waal, the Netherlands. These organisms were acclimated to different temperatures and oxygen levels. By integrating experimental data with high‐resolution field data, we derived the daily heat mortality probabilities for each species under different oxygen levels, considering current temperatures as well as 1 and 2°C warming scenarios. By expressing heat stress as a mortality probability rather than a upper critical temperature, these can be used to calculate cumulative annual mortality, allowing the scaling up from individuals to populations. Our findings indicate a substantial increase in annual mortality over the coming decades, driven by projected increases in summer temperatures. Thermal acclimation and adequate oxygenation improved heat tolerance and their effects were magnified on longer timescales. Consequently, acclimation effects appear to be more effective than previously recognized and crucial for persistence under current temperatures. However, even in the best‐case scenario, mortality of D. villosus is expected to approach 100% by 2100, while E. trichiatus appears to be less vulnerable with mortality increasing to 60%. Similarly, mortality risks vary spatially: In southern, warmer rivers, riverine animals will need to shift from the main channel toward the cooler head waters to avoid thermal mortality. Overall, this framework generates high‐resolution forecasts on how rising temperatures, in combination with other environmental stressors such as hypoxia, impact ecological communities. [ABSTRACT FROM AUTHOR]

For policies and programs aiming at reducing climate risk, it is important to obtain vulnerability information at the sub-national level to identify hotspots. For the case of Costa Rica, no sub-national climate vulnerability index exists to date. To fill this gap, we constructed a climate vulnerability index at the canton level. We ground our work in the conceptual framework that vulnerability is a function of exposure, sensitivity, and adaptive capacity. Making extensive use of geographic information systems and publicly available data, we constructed 13 spatial layers to reflect the multi-dimensionality of vulnerability. Layers reflect for example, changes in climatic extremes, flood risk, vegetation cover, access to infrastructure (road density) and health services (distance to hospitals), as well as various socioeconomic (wealth level, employment rates, remittances, literacy rate) and demographic (infant mortality) characteristics. Following normalization, we constructed an inverse variance weighted index of canton-level climate vulnerability. We confirmed the validity of our climate vulnerability index through correlation with disaster damage data. We find the strongest climate vulnerability not only in the rural, agricultural producing border cantons (Los Chiles, Matina, Talamanca, Buenos Aires), but also for a few central urban cantons (Tibas, San Jose). Projects and interventions in these hot spot cantons may reduce sensitivity through strengthening hydrological infrastructure and economic development, while adaptive capacity may be improved through addressing barriers of remittance transfer, and via public health programs. [ABSTRACT FROM AUTHOR]

African countries contribute less than 4% of global carbon emissions and are susceptible to the repercussions of climate change due to pre-existing challenges such as poverty, unemployment, and food insecurity. The Paris Agreement underscores the need for climate finance to support resilience and low-carbon investments. However, African nations struggle to access adequate funds, hindering effective adaptation and mitigation. Against this background, a bibliometric analysis was conducted on climate finance literature for the period 2007–2023 in order to explore the publication trends, emerging themes, and future research directions. Merging 91 documents from Web of Science and 94 from Scopus yielded a dataset of 139 records. Web of Science experienced a 10.58% publication growth rate, while Scopus had a higher publication growth rate of 13.18%. The merged dataset's publication growth rate was 13.88%, reflecting consistent contributions. The surge in publications from 2019 to 2023 points to intensified discussions on climate change and associated policies. International collaboration between authors is evident, with Web of Science at 37.76%, Scopus at 28.7%, and the merged dataset at 26.62%. Temporally, 2007–2023 saw escalating interest, especially post-2012, reflecting the evolution of climate change and renewable energy policies. Authors were ranked based on article count and fractionalized ranks, with Chirambo D being the lead author in the field of climate finance in Africa. Key articles advocated for supplementary fund integration into government budgets. The UK, USA, and Germany topped in citations, reflecting the availability of research funding, expertise, and collaborations. Leading sources included Climate Policy and Climate and Development. Keyword co-occurrence identified five emerging thematic trends, contributing to an in-depth understanding of climate finance literature's dynamics and future directions. [ABSTRACT FROM AUTHOR]

As climate change unfolds, changes in population dynamics and species distribution ranges are expected to fundamentally reshuffle communities worldwide. Yet, a comprehensive understanding of the mechanisms and extent of community reorganization remains elusive. This is particularly true in riverine systems, which are simultaneously exposed to changing temperature and streamflow, and where land-use change continues to be a major driver of biodiversity loss. Here, we use the most comprehensive compilation of fish abundance time series to date to provide a global synthesis of climate- and LU-induced effects on riverine biota with respect to changes in species thermal and streamflow affinities. We demonstrate that fish communities are increasingly dominated by thermophilic (warm-water) and limnophilic (slow-water) species. Despite being consistent with trends in water temperature and streamflow observed over recent decades, these community changes appear largely decoupled from each other and show wide spatial variation. We further reveal a synergy among climate- and land use-related drivers, such that community thermophilization is heightened in more human-modified systems. Importantly, communities in which species experience thermal and flow regimes that approach or exceed their tolerance thresholds (high community sensitivity), as well as species-poor communities (low community resilience), also display faster rates of compositional change. This research illustrates that quantifying vulnerability of riverine systems to climate change requires a broadening from a narrower thermal focus to more integrative approaches that account for the spatially varying and multifaceted sensitivity of riverine organisms to the interactive effects of water temperature, hydrology, and other anthropogenic changes.

Background: Malaria is still a disease of massive burden in Africa, also influenced by climate change. The fluctuations and trends of the temperature and precipitation are well-known determinant factors influencing the disease's vectors and incidence rates. This study provides a concise account of malaria trends. It describes the association between average temperature and malaria incidence rates (IR) in nine sub-Saharan African countries: Nigeria, Ethiopia, South Africa, Kenya, Uganda, Ghana, Mozambique, Zambia and Zimbabwe. The incidence of malaria can vary both in areas where the disease is already present, and in regions where it is present in low numbers or absent. The increased vulnerability to the disease under increasing average temperatures and humidity is due to the new optimal level for vector breeding in areas where vector populations and transmission are low, and populations are sensitive due to low acquired immunity. Methods: A second source trend analysis was carried out of malaria cases and incidence rates (the number of new malaria cases per 1000 population at risk per year) with data from the World Health Organization (WHO) and average annual mean temperature from 2000 to 2018 from the World Bank's Climate Change Knowledge Portal (CCKP). Additionally, descriptive epidemiological methods were used to describe the development and trends in the selected countries. Furthermore, MS Excel was chosen for data analysis and visualization. Results: Findings obtained from this article align with the recent literature, highlighting a declining trend (20–80%) of malaria IR (incidence rate) from 2000 to 2018. However, malaria IR varies considerably, with high values in Uganda, Mozambique, Nigeria and Zambia, moderate values in Ghana, Zimbabwe, and Kenya, and low values in South Africa and Ethiopia in 2018. Evidence suggests varying IRs after average temperature fluctuations in several countries (e.g., Zimbabwe, Ethiopia). Also, an inverse temperature-IR relationship occurs, the sharp decrease of IR during 2012–2014 and 2000–2003, respectively, occurred with increasing average temperatures in Ghana and Nigeria. The decreasing trends and fluctuations, partly accompanying the temperature, should result from the intervention programmes and rainfall variability. The vulnerability and changing climate could arrest the recent trends of falling IR. Conclusion: Thus, malaria is still a crucial public health issue in sub-Saharan Africa, although a robust decreasing IR occurred in most studied countries. [ABSTRACT FROM AUTHOR]

In the billion-dollar global illegal wildlife trade, rosewoods have been the world's most trafficked wild product since 2005. Dalbergia cochinchinensis and Dalbergia oliveri are the most sought-after rosewoods in the Greater Mekong Subregion. They are exposed to significant genetic risks and the lack of knowledge on their adaptability limits the effectiveness of conservation efforts. Here, we present genome assemblies and range-wide genomic scans of adaptive variation, together with predictions of genomic offset to climate change. Adaptive genomic variation was differentially associated with temperature and precipitation-related variables between the species, although their natural ranges overlap. The findings are consistent with differences in pioneering ability and in drought tolerance. We predict their genomic offsets will increase over time and with increasing carbon emission pathway but at a faster pace in D. cochinchinensis than in D. oliveri. These results and the distinct gene--environment association in the eastern coastal edge of Vietnam suggest species-specific conservation actions: germplasm representation across the range in D. cochinchinensis and focused on hotspots of genomic offset in D. oliveri. We translated our genomic models into a seed source matching application, seedeR, to rapidly inform restoration efforts. Our ecological genomic research uncovering contrasting selection forces acting in sympatric rosewoods is of relevance to conserving tropical trees globally and combating risks from climate change. [ABSTRACT FROM AUTHOR]

Undertaking climate vulnerability assessments (CVAs) on marine fisheries is instrumental to the identification of regions, species, and stakeholders at risk of impacts from climate change, and the development of effective and targeted responses for fisheries adaptation. In this global literature review, we addressed three important questions to characterize fisheries CVAs: (i) what are the available approaches to develop CVAs in various social–ecological contexts, (ii) are different geographic scales and regions adequately represented, and (iii) how do diverse knowledge systems contribute to current understanding of vulnerability? As part of these general research efforts, we identified and characterized an inventory of frameworks and indicators that encompass a wide range of foci on ecological and socioeconomic dimensions of climate vulnerability on fisheries. Our analysis highlighted a large gap between countries with top research inputs and the most urgent adaptation needs. More research and resources are needed in low‐income tropical countries to ensure existing inequities are not exacerbated. We also identified an uneven research focus across spatial scales and cautioned a possible scale mismatch between assessment and management needs. Drawing on this information, we catalog (1) a suite of research directions that could improve the utility and applicability of CVAs, particularly the examination of barriers and enabling conditions that influence the uptake of CVA results into management responses at multiple levels, (2) the lessons that have been learned from applications in data‐limited regions, particularly the use of proxy indicators and knowledge co‐production to overcome the problem of data deficiency, and (3) opportunities for wider applications, for example diversifying the use of vulnerability indicators in broader monitoring and management schemes. This information is used to provide a set of recommendations that could advance meaningful CVA practices for fisheries management and promote effective translation of climate vulnerability into adaptation actions. [ABSTRACT FROM AUTHOR]