Adaptive Capacity Index Research Articles

Recurrent Flooding and Household Food Access in Central Java, Indonesia.

It is unknown how recurring flooding impacts household diet in Central Java. We aimed to assess how recurrent flooding influenced household food access over 22 years in Central Java by linking the Global Surface Water dataset (GSW) to the Indonesian Family Life Survey. We examined linear and nonlinear relationships and joint effects with indicators of adaptive capacity. We measured recurrent flooding as the fraction of district raster cells with episodic flooding from 1984-2015 using GSW. Food access outcomes were household food expenditure share (FES) and dietary diversity score (DDS). We fit generalized linear mixed models and random forest regression models. We detected joint effects with flooding and adaptive capacity. Wealth and access to credit were associated with improved FES and DDS. The effect of wealth on FES was stronger in households in more flood-affected districts, while access to credit was associated with reduced odds of DDS in more flood-affected districts. Flooding had more predictive importance for FES than for DDS. Access to credit, a factor that ordinarily improves food access, may not be effective in flood-prone areas. Wealthier households may be better able to adapt in terms of food access. Future research should incorporate land use data to understand how different locales are affected and further understand the complexity of these relationships.

Vulnerability of barley yields in Québec.

Climate projections across Québec indicate increased water stress and recurrent vulnerability of cropping systems. In recent years, reports of droughts and water stress have been recorded across the province. Many parts of Québec have experienced droughts in the past few years, which have had uninvestigated impacts on crops. These droughts have been described as some of the most significant in the last 80 years. On the positive side, climate change is likely to trigger shorter winters and therefore longer growing seasons for several crops. However, for crops like maple syrup, the regions suitable for their cultivation will shift northwards. Despite these projections, studies monitoring the susceptibility of barley to environmental changes, climate variability, and adaptive capacity across Québec are still limited. This study aims to provide a provincial-scale portrait of vulnerability of barley in Québec based on historical growing season precipitation, barley yield, and socioeconomic data (literacy and poverty rates) using a composite statistical model. Growing season precipitation data were downloaded from Ouranos. Barley yield data were collected from the Institut de la Statistique du Québec, and the socio-demographic data were collected from the Advisory Council of Poverty and the Institut de la Statistique du Québec. A vulnerability index with sub-indices (sensitivity, exposure, and adaptive capacity) is deployed. It is hypothesised that (1) vulnerability is inversely associated with adaptive capacity, and (2) the peripheral regions of Québec are more vulnerable and less adaptive to climate stressors. Initial results show that when the vulnerability index for barley is more prominent, the associated index of adaptive capacity is relatively lower. A significant gradient between the peripheral and southern regions of Québec is observed, with vulnerability lowest around Montreal/Laval and gradually increasing towards the peripheral regions. A better understanding of vulnerability warrants a change in approach from focusing solely on climate-related variables to integrating socioeconomic proxies. The challenge, however, has been how to introduce these socioeconomic proxies into empirical and process-based crop models.

Climate Change Adaptation and Economic Vulnerability of Small Scale Fishermen in the Spermonde Islands, Indonesia

The general objectives of the research are: 1) To investigates the economic hardships faced by fishermen households in the Spermonde Islands due to climate change., and 2) To examine the adoption of diversified livelihoods as a tactic for confronting and adjusting to climate change among fishermen in the Spermonde Islands. Meanwhile, the specific objectives of the research are: 1) Calculating the economic vulnerability of fishermen to climate change, 2) Determining the adaptive capacity index (ACI), 3) Determining possible scenarios taken by fishermen in making decisions related to the impact of climate change on fishermen's income and 4) Determine co-development scenarios for adaptation to climate change. The research method uses in-depth interviews with small-scale fishermen on four islands in Makassar City (Barrang Lompo Island and Kodingareng Lompo) and Pangkep Regency (Ballang Lompo and Badi Islands) and data analysis to understand the impact of climate change on fishermen's livelihoods and the factors that influence vulnerability. their economy. The research results show that fishermen in the Spermonde Islands face various challenges due to climate change, including increased frequency and intensity of extreme weather, changes in seasonal patterns, and rising sea levels. This impact negatively impacts their production and income, and threatens the sustainability of their livelihoods. A factor that most influenced the economic vulnerability of fishing households in the Spermonde Archipelago was the existence an alternative income for a fishermen.

Beyond coastal hazards: A comprehensive methodology for the assessment of climate-related hazards in European coastal cities

As climate change intensifies, European coastal cities face escalating risks from multiple climate-related hazards. Addressing these challenges requires capturing the multifaceted nature of climate risks adequately. This paper presents a novel multi-hazard risk assessment methodology for European coastal cities, which integrates indicators of hazard, exposure, sensitivity, and adaptive capacity. It advances beyond existing models by incorporating a wide array of climate-related hazards and significant indicators. Applied to six diverse coastal cities across different climatic zones and urbanization levels, the methodology proves robust and versatile, offering a comprehensive approach to understanding climate risks. Findings reveal that Varna has the lowest hazard score compared to other cities. Cork and Viana do Castelo are significantly affected by coastal hazards, while La Spezia exhibits very low coastal hazard scores but high land hazard scores. The exposure component ranges between medium and low values, with a maximum in Klaipeda and a minimum in Viana do Castelo. In terms of vulnerability, Viana do Castelo and Bergen stand out, while Cork exhibits the lowest score. Finally, risk presents a balanced landscape, where cities with the highest scores in hazard and exposure also exhibit the lowest levels of vulnerability and vice versa. The discussion on policy implications advocates for participatory resilience-building, leveraging new technologies and non-traditional indicators to enhance urban adaptive capacity. The granularity and specificity inherent to the proposed methodology offer a tool to compare and identify high-risk cities systematically, allowing for a more informed and targeted approach to resilience building and strategic allocation of often limited resources.

The role of agroforestry systems for addressing climate change livelihood vulnerability of farmers of Northwestern Ethiopia

Farmers in Ethiopia have been vulnerable to climate change in recent decades. In the face of this change, farmers have managed agroforestry systems to maintain their livelihoods. However, studies exploring the role of agroforestry in reducing household vulnerability are lacking in Northwestern Ethiopia. The objectives of the study were to (i) investigate households’ livelihoods vulnerability to climate change in Northwestern Ethiopia; (iii) assess the role of agroforestry in mitigating the negative impacts of climate change on farmers livelihoods. Key informant interviews, in-depth interviews, household surveys (387), and focus group discussions were used to collect the data. Descriptive statistics, principal component analysis, the X2-test, and the t-test were run to analyze the data. The findings revealed that households are vulnerable to rising temperatures, rainfall variability, frost, disease and pests, erosion, hailstorms, price hikes, wildlife damage to crops, and health stress. Agroforestry non-practitioners had a higher livelihood vulnerability index (LVI) (0.42 ± 0.081) than practitioners (0.46 ± 0.079). The Livelihood Vulnerability-Intergovernmental Panel for Climate Change Index (LVI-IPCC) showed that AF non-practitioners had a higher exposure (0.58), sensitivity (0.54) index, and a lower adaptive capacity index (0.44) than the exposure (0.34), sensitivity (0.38), and adaptive capacity index (0.51) of practitioners. Plant diversity, income level and diversity, livelihood activities, social network, and food security status of farmers were improved by agroforestry. Farmers were therefore less susceptible to adverse climate shocks. Thus, the AF system could be part of future adaptation and resilience programs that provide dependable tools to minimize households’ vulnerability to climate shocks. However, management guidelines, such as understanding local ecosystems, setting clear objectives, choosing suitable species, planning for diversity, considering the market, and regular maintenance and monitoring, are needed for agroforestry to improve its contribution.

Assessment of heat stress contributing factors in the indoor environment among vulnerable populations in Klang Valley using principal component analysis (PCA)

Rising global temperatures can lead to heat waves, which in turn can pose health risks to the community. However, a notable gap remains in highlighting the primary contributing factors that amplify heat-health risk among vulnerable populations. This study aims to evaluate the precedence of heat stress contributing factors in urban and rural vulnerable populations living in hot and humid tropical regions. A comparative cross-sectional study was conducted, involving 108 respondents from urban and rural areas in Klang Valley, Malaysia, using a face-to-face interview and a validated questionnaire. Data was analyzed using the principal component analysis, categorizing factors into exposure, sensitivity, and adaptive capacity indicators. In urban areas, five principal components (PCs) explained 64.3% of variability, with primary factors being sensitivity (health morbidity, medicine intake, increased age), adaptive capacity (outdoor occupation type, lack of ceiling, longer residency duration), and exposure (lower ceiling height, increased building age). In rural, five PCs explained 71.5% of variability, with primary factors being exposure (lack of ceiling, high thermal conductivity roof material, increased building age, shorter residency duration), sensitivity (health morbidity, medicine intake, increased age), and adaptive capacity (female, non-smoking, higher BMI). The order of heat-health vulnerability indicators was sensitivity > adaptive capacity > exposure for urban areas, and exposure > sensitivity > adaptive capacity for rural areas. This study demonstrated a different pattern of leading contributors to heat stress between urban and rural vulnerable populations.

Taking Stock of Recent Progress in Livelihood Vulnerability Assessments to Climate Change in the Developing World

Over the past few decades, the use of vulnerability assessments has grown substantially to support rural communities in developing countries. These studies aim to help these communities achieve their livelihood goals, such as sustainable resource use and adaptation to global changes, by evaluating their susceptibility to climate change impacts. This systematic review critically examines the extensive body of literature on Livelihood Vulnerability Index (LVI) assessments related to climate change impacts in developing countries. By synthesizing findings from various studies, this review highlights patterns and methodologies used to understand the effects of climate change on vulnerable populations. Key focus areas include geographical distribution, methodological approaches, and the frameworks utilized in vulnerability assessments. The review identifies prominent frameworks, such as the LVI and LVI-IPCC, which integrate indicators of sensitivity, exposure, and adaptive capacity to evaluate climate risks. Findings reveal a concentration of studies in Asia and Africa, with a strong emphasis on agricultural and coastal ecosystems. Methodologically, there is a notable reliance on stratified random sampling to accurately capture community and household-level vulnerabilities. A detailed comparative analysis of the LVI, LVI-IPCC, and Sustainable Livelihood Framework (SLF) is also presented, highlighting their characteristics, benefits, and limitations. The review underscores the need for methodological refinements to better address temporal and regional variations in vulnerability. It concludes with recommendations for future research, integrating broader climate scenarios, exploring sectoral interdependencies, and adopting dynamic approaches to enhance the accuracy and applicability of vulnerability assessments.

Evaluating Adaptive Capacity and Welfare of Farmers in Uganda's Climate-Vulnerable Regions Using an Index-Based Method

The escalating impacts of climate change on agricultural regions in Africa underscore the urgent need for effective adaptation strategies. This study aims to quantify factors influencing the well-being and adaptation capacity of farmers in climate-vulnerable areas. Conducted from December 2023 to March 2024 in Kigezi and Acholi regions, the study sampled 320 farmers using random sampling. The Adaptive Capacity and Welfare Index (ACWI) was used to describe the well-being and adaptive capacity of farmers in climate-vulnerable areas. ACWI comprises five components (Access to Welfare Programs, Social Relationship Conditions, Family Welfare Conditions, Adaptation Capacity, Experience with Innovation/Technology, and Climate Change Extension). Linear regression results identify several significant factors influencing ACWI, such as village location, planting activities during the dry season, number of family dependents, cultivated land area, education level, income from rice farming, alternative employment, and fishing activities. Kigezi region showed a higher ACWI compared to Acholi, indicating better business diversification and climate change awareness. This study underscores the importance of considering local conditions and socio-economic factors in enhancing farmers' adaptive capacity and welfare. Policy recommendations should focus on improving access to resources, adaptation programs, training, and promoting farmer education and business diversification to ensure sustainability and productivity in agriculture amidst climate change challenges

Assessment of the vulnerability of coastal agriculture to seawater intrusion using remote sensing, GIS, and Multi-Criteria Decision Analysis

ABSTRACT The Philippines heavily relies on crop production, with a significant portion cultivated in coastal agricultural areas. However, these farmlands are impacted by salinity intrusion, which adversely affects agricultural productivity. This study assessed the coastal agricultural barangays in Kalibo (Aklan, Philippines) using the exposure, sensitivity, and adaptive capacity indicators, and following the Intergovernmental Panel on Climate Change (IPCC) framework. It aimed to enhance local and national stakeholders’ understanding of vulnerability to seawater intrusion. Physical, agroecological, and socioeconomic parameters were used as indicators, with weights determined through the Analytic Hierarchy Process (AHP). Various aggregation methods were used, and datasets from participatory methods and remote sensing technologies, including LiDAR, were integrated to evaluate vulnerability on a 500 × 500-meter grid. The assessment focused on coastal barangays selected by local officials and agricultural experts. Caano was the most vulnerable, while Bachaw Norte was the least. The exposure map highlighted Nalook, Estancia, and Caano as areas with the highest levels of exposure. The results were compared with the knowledge of city agricultural experts. A sensitivity analysis was conducted to assess the model for exposure indicators. This research contributes to planning and management approaches in Kalibo and advances knowledge of critical indicators in addressing the current challenges.

Community Vulnerability to Lake Drought in Muara Enggelam Village

Drought vulnerability epitomizes a community's capacity to cope with drought-related calamities. In Muara Enggelam Village, the susceptibility to lake drought stems from diminished rainfall and lake water levels plummeting below 4.5 meters, as documented by the Mahakam River observation station in Kota Bangun. Consequently, the study focuses on the manifestation of lake drought vulnerability within Muara Enggelam Village. The research methodology encompasses a multifaceted approach involving observation, documentation, interviews, and questionnaires to gauge vulnerability levels. These assessments were based on key indicators of exposure, sensitivity, and adaptive capacity. Employing a cluster random sampling technique, 75 respondents were selected to represent the village population. Data analysis entailed the application of scoring and weighting methodologies. The outcomes of the study reveal that Muara Enggelam Village falls within Zone D, denoting high sensitivity as the primary component of vulnerability. Specifically, the indicators yield values of 0.41 for exposure intensity (EI), 0.81 for sensitivity intensity (SI), and 0.49 for adaptive capacity intensity (CI). The highest sensitivity observed in the village can be attributed to factors such as low-income levels and a significant proportion of the population engaged in fishing activities. In conclusion, this research sheds light on the intricate dynamics of drought vulnerability in Muara Enggelam Village, emphasizing the urgent need for targeted interventions to bolster the community's resilience against future drought events.

Indigenous Adaptive Capacity Index to climate change: a Brazilian case study

Indigenous Adaptive Capacity Index to climate change: a Brazilian case study

Assessing the climate change adaptation of Sam Son city to guide tourism development using AHP model

The tourism industry in Vietnam is developing rapidly and making significant contributions to the country's economy. However, tourism is also facing challenges related to climate change, especially coastal tourism. The article presents the adaptive capacity of Sam Son city in the development of the tourism industry in respond to the impact of climate change. The adaptive capacity of the Thanh Hoa city is constrained by three groups of factors, including infrastructure, socio-economic, and policy mechanisms. This article employs a GIS (Geographic Information System) technology approach and an Analytic Hierarchy Process (AHP) model to spatialize and quantify the adaptive capacity factors. Among the adaptive factors, the group of policy mechanism factors has the highest weight contributing to the adaptive capacity of Sam Son, with weights ranging from 0.25÷0.29. Meanwhile, the factor of the percentage of households with solid houses contributes insignificantly to adaptive capacity with a weight of 0.04. The study results in Sam Son city show that: The Adaptive Capacity (AC) index of the Sam Son city in guiding the development of the tourism industry is affected by the impact of climate change ranging from 0.28÷0.72, belonging to three levels: low (AC = 0.0÷0.30) was found in 6/11 communes and wards, medium (AC = 0.31÷0.63) was found in 7/11 communes and wards, and high (AC = 0.64÷1.0) was found in 3/11 communes and wards. Overall assessment, the AC of Sam Son city, Thanh Hoa province is at an average level in condition of climate change.

Vulnerability of maize, barley, and wheat yields to growing season temperature and socioeconomic indicators in Morocco

Abstract In Morocco, the historical record depicts a situation characterized by increasing temperatures and diminishing precipitation, which often ends up in severe drought episodes. This research examines the vulnerability of wheat, barley, and maize to growing season temperature changes as well as socio-economic adaptive capacity proxies. This work uses a composite index of vulnerability that posits that the vulnerability index is a function of the exposure, sensitivity, and the adaptive capacity indexes. FAOSTAT and Yield Gap Atlas data were used for the period 1991-2016 to calculate the sensitivity index. The World Bank Climate Portal provided the mean annual growing season temperature data used to compute the exposure index. The World Bank, figshare, and MPR archives were used to capture the proxies of adaptive capacity such as literacy and poverty rates. These findings indicate that wheat has the lowest vulnerability index and the greatest adaptive capacity index, while barley has the strongest vulnerability and lowest adaptive capacity indexes. Sub-nationally, the indices of vulnerability and the standardized growing season's temperature decreased northwards. Northwards, wheat records the lowest vulnerability and highest adaptive capacity, and the second highest standard growing season temperature. In perspective, enhance adaptive capacity for climate resilience in policies, reduce vulnerability.

Identifying vulnerable populations in urban society: a case study in a flood-prone district of Wuhan, China

Abstract. In the context of unprecedented extreme weather and climatic events, the internal structural factors of society play a decisive role in determining the extent to which human beings are affected by disasters and their ability to respond to them. In the past few decades, rapid urbanization in developing countries, such as China, has greatly increased social vulnerability. This process has generated uneven living conditions and created many vulnerable groups, including urban poverty, migrants, and socially and geographically marginalized groups. These groups face difficulties in living conditions, education, livelihood stability, and more. This study sets up indicators from a micro-perspective: three indicators of exposure, four indicators of sensitivity, and eight indicators of adaptive capacity. Based on this evaluation index system, this study conducted a social vulnerability assessment of the population in Hongshan District, Wuhan, China, through individual questionnaire surveys. K-means cluster analysis was used to determine high, medium, and low levels of social vulnerability, which were used to compare different community types and identify vulnerable groups. The results showed close interrelationships between different types of communities in terms of physical and built environments as well as varying levels of social vulnerability to disasters. The high-vulnerability group accounted for 12.9 % of the 599 samples, the medium-vulnerability group accounted for 48.4 %, and the low-vulnerability group accounted for 38.7 %. The higher-vulnerability groups exhibited characteristics such as low education, poor health, low annual income, unstable work, and insufficient social security. Quantitative understanding of the degree of dissimilarity in social vulnerability among different communities and populations is significant in reducing social vulnerability and disaster risk specifically and effectively.

Vulnerability assessment of forest ecosystem based on exposure, sensitivity and adaptive capacity in the Valmiki Tiger Reserve, India: A geospatial analysis

Forests are becoming increasingly vulnerable to a range of climatic and non-climatic stressors. Thus, the forest vulnerability assessment is crucial for identifying potential risks and enhancing forest resilience. The present study attempts to explore the forest vulnerability in the protected area of Valmiki Tiger Reserve (VTR), India. A forest ecosystem vulnerability index (FEVI) was constructed using its three components (exposure, sensitivity and adaptive capacity) and site-specific indicators. Exposure, sensitivity and adaptive capacity indices were integrated to prepare the forest vulnerability map. The map was validated through the receiver operating characteristic curve (ROC) and confusion metrics and found reliable. The results revealed that of the total area of the Reserve, the largest area was found under moderate vulnerability (48.36%), followed by high vulnerability (32.28%) and low vulnerability (19.36%). Madanpur, Raghia, and the lower part of Harnatanr and Chiutaha were identified as the most vulnerable ranges in the VTR. High exposure, high sensitivity and low adaptive capacity were attributed to high forest vulnerability in the VTR. Thus, continuous monitoring and devising effective forest management strategies are essential for reducing vulnerability and enhancing the resilience of the VTR. Urgent policy interventions are also required for promoting ecotourism and minimizing the dependency of communities on forest. The systematic framework employed in the present study may be applied to diverse geographical regions for identifying vulnerable sites and suggesting effective conservation and restoration strategies.

Development of Inherent Vulnerability Index within Jammu Municipal Limits, India

Evaluating inherent vulnerability, an intrinsic characteristic becomes imperative for the formulation of adaptation strategies, particularly in highly complex and vulnerable regions of Himalayas. Jammu City, situated in the north-western Himalayas within a transitional zone between the Himalayan range and the plains, is not only susceptible to intense seismic activities but also faces multiple hazards, including floods, earthquakes, avalanches, and landslides. In recent years, the region has experienced growth in population with rapid progress in infrastructure development, encompassing the construction of highways, dams, and tunnels as integral components of urban development initiatives. Therefore, this study has been conducted to assess the inherent vulnerability index (VI) in Jammu City at ward level as a function of sensitivity, adaptive capacity, and exposure, using ecological and social indicators in GIS environment. The primary objective was to identify the most vulnerable area and ascertain the corresponding municipal ward, aiming to formulate a comprehensive ranking. The 22 indicators analysed were from four major components, namely social, infrastructure, technological, and ecological. The ecological indicators like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Land use/Land cover were derived from Landsat 8 OLI satellite data. The results show that the majority of the area of the city falls into the moderate (20%), high (25.49%), and very high (25.17%) vulnerability categories, respectively, clustered in north-western and south-western transects with densely populated residential areas. The results can assist policymakers in identification of components of inherent vulnerability for focused resource management and formulating adaptation strategies to address the current stressors in the region.

Analysing food farming vulnerability in Kalimantan, Indonesia: Determinant factors and adaptation measures.

As a result of plans to relocate the Indonesian capital city to East Kalimantan province, Kalimantan is expected to develop rapidly and the surrounding regencies and provinces will become food support areas for the new capital. However, the vulnerability of food farming in Kalimantan is a concern that must be addressed to ensure food security. This study aims to assess the vulnerability of food farming at the regency level of the island of Kalimantan, to assess the determinant factors of the food farming vulnerability and to compose adaptation measures that can reduce vulnerability. Socio economic, climate, water and land data are sorted and analyzed to represent the level of sensitivity and exposure index (SEI) and adaptive capacity index (ACI). Locations with 'High' and 'Very High' levels of farming vulnerability become interview sites with a total of 150 respondents. The results of the interviews strengthen the results of the vulnerability analysis which helps to determine the condition of farmers and food farming in vulnerable locations. The results indicated 'Very High' and 'High' level of vulnerability in 14 regencies/cities. Floods are climate-related disasters that most often affect farmers surveyed (46%), followed by droughts (30%) and pest attacks (24%) with significant impacts (49%). The identification of the determinant factors becomes the basis for adaptive measures to support decision-makers, local practitioners, and farmers by highlighting local challenges and proposing local-specific adaptation strategies.

LIVELIHOOD VULNERABILITY AND CONSTRAINTS FACED BY THE GUAVA GROWERS

The present study investigated the livelihood vulnerability index and constraints encountered by guava growers in the Prayagraj district of Uttar Pradesh. The livelihood vulnerability index (LVI) comprises (the exposure index, sensitivity index, and adaptive capacity index) by using the IPCC- vulnerability approach, to evaluate the livelihood vulnerability of 120 guava growers selected by simple random sampling, and the data was collected with the help of a pre-tested interview schedule. The study revealed that the guava growers are greatly exposed (0.81) to climate change, and sensitivity indices underscore the high sensitivity (0.55), in contrast, the adaptive capacity indices (0.34) indicate a comparatively lower adaptive capacity among the surveyed respondents when juxtaposed with the exposure and sensitivity indices. For the constraints, a list of 19 constraints was prepared and grouped into 5 major dimensions. Addressing these challenges has the potential to improve the overall welfare and livelihood vulnerability of guava growers in the study area.

Gender-based vulnerability and adaptive capacity in the disaster-prone coastal areas from an intersectionality perspective

Households in the coastal areas are more vulnerable to various environmental, social, and economic disruptions in terms of an intersectionality point of view. As a first step in mitigating potential effects on families, knowing how susceptible they are and, ideally, fortifying themselves against existing and potential disruptions is essential. Vulnerability and adaptive capacity could not be uniformly distributed between households owing to gender-based socio-economic disparities and inequities. This research, thereby, examined the vulnerability and adaptive capacity variation between households headed by males and females in the two coastal areas of an emerging economy like Bangladesh. This study utilized the Evaluation-based on the Distance from Average Solution(EDAS)method and Boosted Regression Trees (BRT) technique to conduct the analysis. The EDAS method has been used to analyze the adaptive capacity index. Using BRT, an innovative approach in the area, we showed that male and female-headed households are different in terms of their capability to adapt. The findings from this study suggest that the households led by females are more vulnerable than those headed by males in the study region across a variety of dimensions (social, health, economic, housing, and land ownership) from an intersectionality perspective. The study findings can provide a new outlook for the decision-makers in the coastal region on the vulnerability and adaptive capacity differences among the residents and thus lead to more efficient disaster management practices.

A regional stocktake of maize yield vulnerability to droughts in the Horn of Africa.

Climate projections in sub-Saharan Africa predict increased frequency of droughts with parallel impacts on crop yield. The Horn of Africa is among the most vulnerable regions in Africa to these changes because agriculture in general andmaize productionin particularly is highly climate driven, and rain-fed. Current research approaches have mostly focused on the climatic and biophysical drivers of crop yield without including the socio-economic drivers of crop yield. This study fills this gap by investigating the vulnerability of maize yield in the Horn of Africa to climate and socio-economic indicators. The hypothesis is that there is an inverse relationship between vulnerability and adaptive capacity. The vulnerability index is a composite index that integrates sensitivity, exposure, and adaptive capacity sub-indices. Maize yield data to compute the sensitivity index were collected from FAOSTAT, precipitation data to compute the exposure index were collected from the Climate Research Unit (CRU), and the data for the proxies of adaptive capacity were collected from the readiness index database on figshare. From the results, Somalia records the highest vulnerability index of 1.15, followed by Ethiopia with a vulnerability index of 0.61. Kenya records the lowest vulnerability index of 0.33. Also, there is a positive relationship between the vulnerability, sensitivity, and the exposure indices and an inverse relationship between the vulnerability index and the adaptive capacity index. The high vulnerability index recorded in Somalia is accentuated by a low adaptive capacity index of 0.44 that is anchored on low literacy and high poverty rates. As Somalia records the lowest adaptive capacity index of 0.44, Ethiopia and Kenya record 0.91 and 0.99 respectively. This study has shown that to better understand vulnerability, a shift from the old paradigm that focuses on the climatic variables to integrating socio-economic variables or proxies of adaptive capacity whichenhances ourunderstanding ofvulnerability. Though leveraging the benefits of climatic and non-climatic variables is important, the challenge so far has been on how to integrate these in the same model; a challenge this work has succinctly overcome by integrating adaptive capacity in the vulnerability equation.