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Mortality impact of low annual crop yields in a subsistence farming population of Burkina Faso under the current and a 1.5 °C warmer climate in 2100
Abstract
In subsistence farming populations of sub-Saharan Africa reliant on rainfed agriculture, years of low crop yields result in poorer child nutrition and survival. Estimates of such impacts are critical for their reduction and prevention. We developed a model to quantify such health impacts, and the degree to which they are attributable to weather variations, for a subsistence farming population in the Nouna district of Burkina Faso (89,000 people in 2010). The method combines data from a new weather-crop yield model with empirical epidemiological risk functions. We quantify the child mortality impacts for 1984-2012 using observed weather data and estimate potential future burdens in 2050 and 2100 using daily weather data generated by global climate models parameterized to simulate global warming of 1.5°C above pre-industrial levels. For 1984-2012, crop yields below 90% of the period average were estimated to result in the total of 109.8 deaths per 10,000 children <5years, or around 7122.0years of life lost, 72% of which are attributable to unfavourable weather conditions in the crop growing season. If all non-weather factors are assumed to remain unchanged, the mortality burden related to low crop yields would increase about twofold under 1.5°C global warming by 2100. These results emphasize the importance and value of developing strategies to protect against the effects of low crop yields and specifically the adverse impact of unfavourable weather conditions in such settings under the current and future climate.
... While the 1970s and 1980s were marked by a long-lasting drought period in the Sahel region, some recovery of the rainfall including increased precipitation extremes (14,15) in combination with an increase toward more extreme temperatures were observed in the last decades (2,7,8,16). Those climatic changes can have severe negative implications on agricultural production and food availability, and thus, lead to food insecurity and undernutrition in this region (2,9,17). ...
... Diets can be assessed through dietary patterns, which reflect the complexity of a diet and provide a realistic impression of the overall diet structure (20,24,25). Children aged <5 years specifically need sufficient food and nutrients for their development and growth, wherefore a lack manifests in a higher risk for stunting, wasting, impeded cognitive development and subsequent death (17,26,27), which starts already in utero, continues into early childhood and manifests in adulthood (3,5,(28)(29)(30)(31). Both nutrition and health of children are assumed to worsen with the impacts of climate change and may even hamper efforts taken to reduce undernutrition in the coming decades (32,33). ...
... Yet, studies looking at associations between climate change and undernutrition among children aged <5 years are neither vast nor comparable due to a lack of robust data and substantial heterogeneity of research methods (17,34). In this study, we explored how rainfall variability (by location) is linked through diets to child undernutrition in rural Burkina Faso. ...
Background: Climate change and consequent increases in rainfall variability may have negative consequences for the food production of subsistence farmers in West Africa with adverse impacts on nutrition and health. We explored the pathway from rainfall through diet up to child undernutrition for rural Burkina Faso.
Methods: The study used data of a dynamic cohort with 1,439 children aged 7–60 months from the Nouna Health and Demographic Surveillance Site (HDSS) for 2017 to 2019. We assessed data on diets, height, weight, household characteristics, and daily precipitation (from 1981 to 2019). Principal component analysis was used to identify distinct child dietary patterns (Dietary Pattern Scores, DPS). These were related to 15 rainfall indicators by area to obtain a precipitation variability score (PVS) through reduced rank regression (RRR). Associations between the PVS and anthropometric measures, height-for-age (HAZ), and weight-for-height (WHZ), were examined using multi-level regression analysis.
Results: Stunting (HAZ < −2) and wasting (WHZ < −2) were seen in 24 and 6% of the children. Three main dietary patterns were identified (market-based, vegetable-based, and legume-based diets) and showed mixed evidence for associations with child undernutrition. The RRR-derived PVS explained 14% of the total variance in these DPS. The PVS was characterized by more consecutive dry days during the rainy season, higher cumulative rainfall in July and more extremely wet days. A 1-point increase in the PVS was associated with a reduction of 0.029 (95% CI: −0.06, 0.00, p < 0.05) in HAZ in the unadjusted, and an increase by 0.032 (95% CI: 0.01, 0.06, p < 0.05) in WHZ in the fully adjusted model.
Conclusion: Rainfall variability was associated with dietary patterns in young children of a rural population of Burkina Faso. Increased rainfall variability was associated with an increase in chronic undernutrition, but not in acute undernutrition among young children.
... For every surveyed household, statistics on their predicted yield per crop type can be generated. In rural subsistence farming systems, where people live from what they grow, harvest deficits translate to household food insecurity and even child undernutrition [10]. Hence, the quantitative yield estimate from Figure 3 can be translated to crucial socio-economic information, such as crop-specific calorie estimations per household. ...
... The methodological advances lie in the extremely high resolution of the household with its children's nutritional status and the food crop yields of the respective household. Such data can further be "fed" into climate impact models, e.g., with highly aggregated data [10]. ...
... This would benefit the countries as population growth poses another challenge to policymakers, who need to assure constant access and sufficient production of agricultural products to ensure self-sufficiency on a national scale and independence of international market price fluctuations. Knauer et al. [10] reported a 91% expansion of agricultural land in Burkina Faso between 2001 and 2014 and accordingly reported an agricultural area coverage of 22%. This shows the country's potential to feed its fast-growing population (3% annual population increase) and assure labor in a country where 90% work in the agricultural sector. ...
: Climate change has an increasing impact on food security and child nutrition, particularly among rural smallholder farmers in sub-Saharan Africa. Their limited resources and rainfall dependent farming practices make them sensitive to climate change-related effects. Data and research linking yield, human health, and nutrition are scarce but can provide a basis for adaptation and risk management strategies. In support of studies on child undernutrition in Burkina Faso, this study analyzed the potential of remote sensing-based yield estimates at household level. Multi-temporal Sentinel-2 data from the growing season 2018 were used to model yield of household fields (median 1.4 hectares (ha), min 0.01 ha, max 12.6 ha) for the five most prominent crops in the Nouna Health and Demographic Surveillance (HDSS) area in Burkina Faso. Based on monthly metrics of vegetation indices (VIs) and in-situ harvest measurements from an extensive field survey, yield prediction models for different crops of high dietary importance (millet, sorghum, maize, and beans) were successfully generated producing R² between 0.4 and 0.54 (adj. R² between 0.32 and 0.5). The models were spatially applied and resulted in a yield estimation map at household level, enabling predictions of up to 2 months prior to harvest. The map links yield on a 10-m spatial resolution to households and consequently can display potential food insecurity. The results highlight the potential for satellite imagery to provide yield predictions of smallholder fields and are discussed in the context of health-related studies such as child undernutrition and food security in rural Africa under climate change.
... Through satellite-based crop yield models, we want to develop a crop yield model on the ground, that ideally reduces the need for in-situ data collection while assuring accurate yield estimates at the household field level (mean field size < 2 ha). The presented work is nested in a larger research unit that focuses on aspects including food security and child undernutrition (Mank et al. 2020;Beiersmann et al. 2012), children's health (Belesova et al. 2017(Belesova et al. , 2018Belesova et al. 2019b), and heat stress (Kjellstrom et al. 2016;Sahu et al. 2013) (https: //www.cch-africa.de). ...
... With our three-year observation of the in-situ measurements, we are capable of also capturing parts of the interannual variability. As can be seen in Belesova et al. (2019b), a threeyear window captures large parts of the variability as more than two consecutive years with stable productivity were very rare between 1984 and 2012. This is also shown by the highly varying rainfall patterns from the years 2018, 2020, and 2021 (Fig. 6). ...
Increasing frequencies of climate change-induced extreme weather events like prolonged droughts pose significant challenges for small-scale subsistence farmers in sub-Saharan Africa, who rely on the yearly harvest by more than 80 % of their nutritional needs. However, we do not have a good understanding of yield estimates at the field and household level (with a mean field size of < 2 ha) to understand nutritional priorities in vulnerable communities due to their scarcity in the literature, particularly yield estimates that do not require recollection of in-situ data. Statistical models for estimating regional food crop yields based on high-resolution satellite data at the field level may provide better insights into how to address health risks such as child malnutrition. Especially in low-resource contexts, where the burden is greatest and expected to worsen in future climate projections. Our study developed crop-specific, satellite-based yield models using a novel three-year data set of in-situ yield measurements as exemplified for a rural region in Burkina Faso. The aim of the model is to reduce the need for in-situ field data collection while still assuring accurate yield estimates at the field level. The model employed LASSO regression and was based on monthly vegetation index composites from Sentinel-2 and weekly accumulated Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall data. Our yield modeling results showed that there was less overfitting when there was more training data over three years that demonstrated a wider range of yields, which also led to better model fits. R 2 values ranged from 0.62 (Maize) to 0.3 (Sorghum) for the three-year yield models, with normalized root mean square error (nRMSE) values ranging from 12 % − 16 %. An additional plausibility check confirmed the validity of our models, as we compared the magnitude of our yield estimation with national yield statistics for Burkina Faso. We demonstrated that our models based on three years of in-situ data may capture some of the inter-annual variability in yields, which could be a step toward minimizing the necessity for in-situ measurements in the future. Our advances in predicting yield estimates at the field level enable a linkage between household-level yields, socioeconomic indicators , nutritional status of children, and the health status of the household members. A further application is linking high-resolution yield data to farmers' productivity losses from increasing heat under climate change.
... Even though a decrease in suitability for malaria vectors is desirable, it is unclear whether this could yield a net-positive outcome for health in the region. There is a need for more studies to fully understand [22][23][24][25][26][27][29][30][31][32][33][34][35][36][37][38][39][40]95] food security 17 [41][42][43][44][45][46][47][48][49][96][97][98][99][100][101][102][103] nutrition 15 [50][51][52][53][54][55][56][57][58][59][60][61][62][63][64] heat stress/waves 7 [65][66][67][68][69][70][71] health perceptions 7 [72][73][74][75][76][77][78] meningitis 5 [82][83][84][85][86] diarrhoeal disease and cholera 4 [91][92][93][94] mental health and well-being 3 [79][80][81] WASH 2 [89,90] exposure to PM 2.5 2 [87,88] WASH, water, sanitation and hygiene. ...
The Sahel region is projected to be highly impacted by the more frequent hazards associated with climate change, including increased temperature, drought and flooding. This systematic review examined the evidence for climate change-related health consequences in the Sahel. The databases used were Medline (PubMed), Embase (Ovid), Web of Science (Clarivate) and CABI Global Health. Hand searches were also conducted, which included directly engaging Sahelian researchers and hand-searching in the African Journals Online database. Of the 4153 studies found, 893 were identified as duplicates and the remaining 3260 studies were screened (title and abstract only) and then assessed for eligibility. A total of 81 studies were included in the systematic review. Most studies focused on vector-borne diseases, food security, nutrition and heat-related stress. Findings suggest that mosquito distribution will shift under different climate scenarios, but this relationship will not be linear with temperature, as there are other variables to consider. Food insecurity, stunting (chronic malnutrition) and heat-related mortality are likely to increase if no action is taken owing to the projected impact of climate change on environmental factors and agriculture. Seventy-one per cent of manuscripts (n = 58) had first authors from institutions in North America or Europe, of which 39.7% (n = 23) included co-authors from African institutions.
... This raises the question of liability, which is related to climate justice. For example, in Burkina Faso, a significant proportion of child mortality is related to low crop yields in the year of birth, 72% of low crop yield is attributed to weather conditions and the burden of child mortality could increase two-fold in Sub-Saharan Africa with 1.5°of warming [11]. Further, climate-related displacement is projected to rise, with up to 32 million people in West Africa potentially compelled to move within their countries by 2050 as a consequence of slow-onset climate impacts [12]. ...
... Although HDSSs show potential for climate change and health-focused population surveillance, the current literature is sparse, necessitating further investigation. Some previous studies conducted in the Nouna HDSS in Burkina Faso, explored weather changes and child health, focusing on malnutrition (26)(27)(28)(29)(30). For example, Diboulo et al. (28) found significant associations between temperature, rainfall, and mortality rates in the Nouna HDSS. ...
Background
Climate change significantly impacts health in low-and middle-income countries (LMICs), exacerbating vulnerabilities. Comprehensive data for evidence-based research and decision-making is crucial but scarce. Health and Demographic Surveillance Sites (HDSSs) in Africa and Asia provide a robust infrastructure with longitudinal population cohort data, yet they lack climate-health specific data. Acquiring this information is essential for understanding the burden of climate-sensitive diseases on populations and guiding targeted policies and interventions in LMICs to enhance mitigation and adaptation capacities.
Objective
The objective of this research is to develop and implement the Change and Health Evaluation and Response System (CHEERS) as a methodological framework, designed to facilitate the generation and ongoing monitoring of climate change and health-related data within existing Health and Demographic Surveillance Sites (HDSSs) and comparable research infrastructures.
Methods
CHEERS uses a multi-tiered approach to assess health and environmental exposures at the individual, household, and community levels, utilizing digital tools such as wearable devices, indoor temperature and humidity measurements, remotely sensed satellite data, and 3D-printed weather stations. The CHEERS framework utilizes a graph database to efficiently manage and analyze diverse data types, leveraging graph algorithms to understand the complex interplay between health and environmental exposures.
Results
The Nouna CHEERS site, established in 2022, has yielded significant preliminary findings. By using remotely-sensed data, the site has been able to predict crop yield at a household level in Nouna and explore the relationships between yield, socioeconomic factors, and health outcomes. The feasibility and acceptability of wearable technology have been confirmed in rural Burkina Faso for obtaining individual-level data, despite the presence of technical challenges. The use of wearables to study the impact of extreme weather on health has shown significant effects of heat exposure on sleep and daily activity, highlighting the urgent need for interventions to mitigate adverse health consequences.
Conclusion
Implementing the CHEERS in research infrastructures can advance climate change and health research, as large and longitudinal datasets have been scarce for LMICs. This data can inform health priorities, guide resource allocation to address climate change and health exposures, and protect vulnerable communities in LMICs from these exposures.
... Previous studies have demonstrated that HDSSs offer considerable potential for conducting population surveillance with a focus on climate change and health. Several studies conducted in the Nouna HDSS, located in northwestern Burkina Faso, investigated the link between weather changes and the health of children, with a focus on the effects of weather exposures on child malnutrition (Belesova et al., 2019;Diboulo et al., 2012;Mank et al., 2021;Sorgho et al., 2017Sorgho et al., , 2018. The Climate and Mortality (CLIMO) study, which was launched in 2019 in the Nouna HDSS, elucidated the impact of varying climate and weather conditions on the population of the Nouna HDSS, which is one of the poorest in the world, in terms of adaptation and mitigation measures, as well as their vulnerability to climate change (Rocklöv et al., 2014). ...
BACKGROUND
Even though climate change is one of the most significant global health challenges, empirical population-based data on its impacts and adaptation measures to protect population health are still limited. The 56 long-term health cohorts in Africa and Asia, called Health and Demographic Surveillance Systems (HDSSs) are excellent for monitoring climate impact on health and adaptation measures as they: (i) follow quality controlled protocols of data collection across all sites, (ii) provide long-term continuous data, (iii) cover diverse climate hotspots, including coastal areas, rainforests, savannah and highlands, and, (iv) capture about 100-million-person years of data. However, HDSSs have not leveraged their potential for climate and health research and policy, as (i) local meteorological data or remotely sensed data is not incorporated; (ii) there are limited links to downscaled climate impact models for HDSSs; (iii) and at its core, demographic dynamics are captured, with cause of death being the major health indicator tracked over time.
OBJECTIVE
We introduced major improvements in data collection, database architecture, data transmission, as well as links to locally downsized climate models to capitalize on the strong potential of HDSSs sites for measuring health impacts of climate change, identifying particularly vulnerable groups, and testing the costs and effectiveness of adaptation interventions and policies to protect populations from these climate impacts. This bundle of methods called Climate and Health Surveillance and Response System (CHES-RS) aims to provide a consistent set of climate and health data which are routinely collected.
METHODS
The CHES-RS has already been piloted in the HDSS at the Nouna Health Research Center in Burkina Faso, and it is currently being rolled out to two other HDSS sites, one in sub-Saharan Africa, respectively in the Siaya HDSS, Kenya, and the other in the South East Asia Community Observatory (SEACO) HDSS in Malaysia. CHES-RSs are ready to conduct research in the following major health sectors: climate/weather, land use and coverage/biodiversity, agriculture/household harvest, food security, household economics, as well as research in the field of one health, including zoonotic disease surveillance. CHES-RS uses digital sensors to measure three levels of exposure: (i) Individual-level data: consumer-grade wearable devices yield objective measures in vulnerable and rural populations, and an expanded HDSS questionnaire includes a full morbidity evaluation (ii) Household-level data comprises both indoor temperature measurements and remote sensing data captured through satellites (iii) Community-level data: comes from fully automated weather stations that record temperature, precipitation, solar radiation, wind speed, and direction. To handle heterogeneous data, we leverage graph databases for data management.
RESULTS
NA
CONCLUSIONS
To address current and emerging global health challenges over the next few decades, CHES-RSs will serve as a novel architecture for existing HDSSs and similar infrastructures of population-based surveillance cohorts. They may encourage ecosystems for climate change and health research, as well as big data analysis using artificial intelligence (AI), potentially providing the foundation for calculating climate change-induced disability-adjusted life years (cDALYs) and loss and damages. Using a routine morbidity panel survey and objectively measured health data, CHES-RS generate data-rich cohorts in countries where good quality health data is scarce, allowing for early interventions and earlier detection of risk factors for illnesses.
... Heat stress resulting from heat waves is decreasing farmers' physical work capacity, limiting their ability to tend their agricultural fields, while changing rainfall patterns are decreasing the growth potential of crops, leading to poor yields and destabilized food security (Karst et al., 2020;Sorgho et al., 2020a) (Rigolot et al., 2017;Tourre et al., 2017). Direct and indirect impacts of climate change on health have been observed specifically in Burkina Faso, through increasing child undernutrition and mortality resulting from changes in rainfall and agricultural yields (Belesova et al., 2017b;Belesova et al., 2017a;Belesova et al., 2019) to increasing rates of cardiovascular, respiratory, and cerebrovascular morbidity and mortality in elderly populations due to heat waves and heat stress (Bunker, 2018;Bunker et al., 2016). The population's high exposure and vulnerability to climate change are compounded by a low individual and institutional capacity to adapt (Sorgho et al., 2020a;Williams et al., 2018). ...
West African countries, such as Burkina Faso are particularly vulnerable to an array of health impacts due to climate change. Consequently, Burkina Faso has drafted and implemented adaptation plans and programmes, with varying levels of success. This exploratory qualitative study examines the institutional barriers faced by policymakers in this process, particularly in the health system of concern. We applied in-depth interviews with policymakers, using framework analysis. We identified the barriers to implementing climate change and health programmes and categorized the barriers according to the Framework to diagnose barriers to climate change adaptation. Policymakers identified eight interconnected barriers through the framework: Four barriers in the management phase (insufficient financial resources, frequent turnover, policy-politics disconnect /weak structural support, unsustainable programming), three in the planning phase (heft of bureaucracy/lack of political will, diverging development priorities, insufficient cooperation), one in the larger context of Burkina Faso’s environment (national security). The respondents mentioned no barriers in the understanding phase. These barriers are indicative of weak institutional support systems and limited resource allocation to climate and health work in Burkina Faso.
... In recent times, a considerable amount of studies have been conducted assessing the impacts of climate change through various modeling approaches, including statistical and biophysical modeling worldwide (Aryal et al., 2020;Harvey et al., 2018;Kogo et al., 2021;Ray et al., 2019;Schleussner et al., 2018;van Oort and Zwart, 2018). A few studies based on statistical modeling report a negative impact on cereal production with increasing temperature in Burkina Faso (Belesova et al., 2019;Nana, 2019;Sossou et al., 2020), additionally causing economic loss (Henderson et al., 2018). However, there is a limitation in quantifying the impacts of climate change and adaptation measures by considering agronomic practices (biophysical modeling) and soil properties in addition to climate information spatially at the national level (at grid scale) in Burkina Faso. ...
Adaptation strategies sustaining agricultural production under climate change are urgently required in Sub-Saharan Africa. To quantify the impacts of different adaptation options in Burkina Faso, this study simulated sorghum yields under current and projected climatic conditions with and without adaptation. We used the Decision Support System for Agrotechnology Transfer (DSSAT) at 0.5° spatial resolution (around 55 km) and forced the model with two climate change scenarios. Our calibrated model showed good agreement between reported and simulated yields (Pearson’s r = 0.77; out-of-sample r = 0.68). DSSAT was configured to mimic four distinct adaptation measures: integrated soil fertility management (ISFM), irrigation, an improved variety, and agroforestry. Results show that nationally averaged sorghum yields are projected to decrease by 5.5% under high emissions by 2090 without adaptation. Major yield losses (up to 35%) would occur in the southern and western parts of the country. Our assessments identify ISFM as the most effective adaptation strategy, increasing yield up to 300%, followed by agroforestry (up to 125%), an improved variety (up to 90%), and irrigation (up to 43%) at the regional scale. ISFM is effective across all regions, while irrigation and an improved variety are most effective in the northern and western parts. Agroforestry, meanwhile, is most effective in the south and eastern part of the country. We conclude that climate change in Burkina Faso could negatively affect sorghum yields, but adequate adaptation options exist to enhance agricultural resilience.
... Yet, our results are partly comparable to two local studies. Our model skill is higher for maize and millet and lower for sorghum compared to the weather-based yield model of Belesova et al. 21 for the province Kossi and the NDVI-based yield forecast of Karst et al. 14 for the department Nouna within Kossi. The lower performance for sorghum could be related to reliability issues in the sorghum data applied here (SI Text 1). ...
Almost half of the Burkinabe population is moderately or severely affected by food insecurity. With climate change, domestic food production may become more under pressure, further jeopardizing food security. In this study, we focus on the production of maize, sorghum and millet as staple cereal crops in Burkina Faso to assess food availability as one component of food security. Based on a statistical weather-driven crop model, we provide a within-season forecast of crop production 1 month before the harvest. Hindcast results from 1984 to 2018 produce an r2 of 0.95 in case of known harvest areas and an r2 of 0.88 when harvest areas are modelled instead. We compare actually supplied calories with those usually consumed from staple crops, allowing us to provide early information on shortages in domestic cereal production on the national level. Despite the—on average—sufficient domestic cereal production from maize, sorghum and millet, a considerable level of food insecurity prevails for large parts of the population. We suggest to consider such forecasts as an early warning signal for shortages in domestic staple crop production and encourage a comprehensive assessment of all dimensions of food security to rapidly develop counteractions for looming food crises.
... Sebagai contoh, suhu yang lebih tinggi akan menggalakkan perkembangan patogen, sementara kemarau akan mempengaruhi kualiti air dan kebersihan, terutama di kawasan kering, yang dapat meningkatkan beban penyakit seperti diarea terutamanya dalam kalangan kanakkanak miskin (FAO, 2016). Tidak dapat dinafikan, kesan kekurangan zat makanan yang disebabkan oleh pemanasan global mungkin sangat teruk di kalangan golongan berisiko seperti kanak-kanak (Belesova et al., 2019) dan wanita (Bryan et al., 2018). ...
... Sebagai contoh, suhu yang lebih tinggi akan menggalakkan perkembangan patogen, sementara kemarau akan mempengaruhi kualiti air dan kebersihan, terutama di kawasan kering, yang dapat meningkatkan beban penyakit seperti diarea terutamanya dalam kalangan kanakkanak miskin (FAO, 2016). Tidak dapat dinafikan, kesan kekurangan zat makanan yang disebabkan oleh pemanasan global mungkin sangat teruk di kalangan golongan berisiko seperti kanak-kanak (Belesova et al., 2019) dan wanita (Bryan et al., 2018). ...
Pendekatan holistik ialah pendekatan yang merangkumi empat domain bagi manusia secara bersepadu yang
merangkumi aspek biologi, psikologi, sosial dan spiritual. Fenomena masyarakat di Malaysia kini sama ada di
agensi kerajaan mahupun swasta lebih banyak berada di rumah untuk bekerja akibat penularan wabak COVID-19.
Situasi ini menyebabkan kekerapan ahli keluarga yang keluar rumah untuk beraktiviti makin terhad dan dikhuatiri
meningkatkan jumlah masalah kesihatan mental dalam kalangan masyarakat. Jumlah talian bantuan sokongan sosial
di Malaysia turut dilaporkan semakin meningkat. Lebih mengejutkan apabila 85.5% panggilan ini membabitkan isu
berkaitan kesihatan mental yang memerlukan sokongan emosi dan kaunseling seperti stres akut, keresahan,
kemurungan, penderaan, dan tingkah laku bunuh diri. Dari awal Januari hingga 21 Mei 2021, dilaporkan sejumlah
101,150 panggilan yang diterima, yang mana 91.2% memerlukan sokongan emosi dan kaunseling. Panggilan ini
merangkumi pesakit COVID-19, individu yang menjalani kuarantin, petugas barisan hadapan, keluarga yang
kehilangan ahli keluarga akibat COVID-19 dan kumpulan rentan. Justeru, kajian ini akan menggumpul dan
mengusulkan beberapa cadangan pendekatan holistik yang boleh dilaksanakan menerusi perbahasan al-Quran, Hadis
dan pandangan sarjana Muslim dalam mengadakan aktiviti yang bermanfaat di rumah bersama ahli keluarga. Kajian
ini menggunakan sepenuhnya metode kualitatif dalam komponen dokumentasi melalui tafsir al-Quran, syarah Hadis
serta kajian sarjana Muslim terdahulu dan kontemporari. Hasil kajian menunjukkan perbahasan menerusi maklumat
Islami sesuai dengan masa dan keadaan semasa dalam menangai isu-isu yang berlaku terutamanya ketika pandemik
COVID-19. Penemuan ini mampu menambahkan koleksi terapi berasaskan empat domain utama manusia
berasaskan maklumat Islami serta mengurangkan bebanan perasaan masyarakat ketika terlalu lama berada di rumah.
... In 2020, over 800,000 Burkinabé were internally displaced (UN OCHA, 2020). Before the violence erupted, growing climate change pressures increased food insecurity in parts of the country (Belesova et al., 2017(Belesova et al., , 2018(Belesova et al., , 2019 potentially increasing internal mobility in a setting where seasonal migration is widespread. ...
Migration is often considered a form of climate change adaptation by which individuals, households, and communities seek to reduce the risks associated with climate change. In this study, we examine first-time seasonal migration out of a village in North-Western Burkina Faso to neighbouring countries, triggered by more irregular rainfall patterns. Through a set of 52 qualitative interviews, we analyse the perceptions of migrants themselves as well as the sending community regarding migration consequences. Men migrated in the off-season, whereas women stayed behind. Most migrant men and wives of migrants perceive migration to have negative consequences for their socio-economic situation and their health. Despite this, a lack of options and deteriorating environmental conditions might force the men to move again. We interpreted the range of narratives provided by women and men against the background of the scientific literature on migration as climate change adaptation. While migration could be beneficial, this study challenges the notion of migration as an effective adaptation strategy for people in climate-vulnerable settings, who lack other options.
... The impacts of food insecurity and malnutrition caused by production decrease due to global warming might be particularly severe among vulnerable groups such as children Sorgho et al., 2016) and women . Indeed, Belesova et al. (2019) show that low annual crop yields in the scenario of 1.5 degrees C warmer climate in 2100 would increase child mortality in a subsistence farming population of Nouna district (Kossi Province, western Burkina Faso). Moreover, evidence shows that the impacts of climate change are higher on smallholders (García de Jalón et al., 2018;Henderson et al., 2016;Waha et al., 2016;Williams et al., 2018;Wood et al., 2014). ...
The impacts of climate change (CC) are expected to be higher in developing countries (e.g. Sub-Saharan Africa). However, these impacts will depend on agriculture development and resilience. Therefore, this paper provides a comprehensive analysis of the multifaceted relationships between CC and agriculture in Burkina Faso (BF). A search performed in March 2020 on the Web of Science yielded 1,820 documents and 217 of them were included in the systematic review. The paper provides an overview on both bibliometrics (e.g. journals, authors, institutions) and topics addressed in the literature viz. agriculture subsectors, climate trends in BF, agriculture and CC mitigation (e.g. agriculture-related emissions, soil carbon sequestration), impacts of CC on agriculture (e.g. natural resources, crop suitability, yields, food security) as well as adaptation strategies. BF is experiencing CC as evidenced by warming and an increase in the occurrence of climate extremes. The literature focuses on crops, while animal husbandry and, especially, fisheries are often overlooked. Moreover, most of the documents deal with CC adaptation by the Burkinabe farmers, pastoralists and rural populations. Analysed adaptation options include conservation agriculture and climate-smart agriculture, irrigation, crop diversification, intensification, livelihoods diversification and migration. However, the focus is mainly on agricultural and individual responses, while livelihoods strategies such as diversification and migration are less frequently addressed. Further research is needed on the dual relation between agriculture and CC to contribute to the achievement of the Sustainable Development Goals. Research results are crucial to inform policies aimed at CC mitigation and/or adaptation in rural BF.
Global food security is an issue, especially in light of the scenario of a changing climate. The production, accessibility, and availability of food are anticipated to be significantly impacted by climate change, thus making the world’s population more vulnerable to food insecurity. In this situation, it is important to prioritise food security for sustainable development. Under the scenario of a changing climate, this chapter provides an overview of the need for food security while highlighting the potential and problems for food production and distribution. It examines the consequences for food security as well as how climate change affects the growth of crops, animals, fisheries, and aquaculture. The essay also outlines various institutional and policy measures that will be necessary to solve the problems. In order to guarantee that food systems are robust and sustainable in the face of climate change, the chapter emphasises the significance of a coordinated and integrated approach to food security and climate change adaptation. The effects of climate change on agriculture have been more pronounced in recent years. Global food production systems are being impacted by increasing temperatures, shifting rainfall patterns, and increasingly frequent extreme weather events like floods and droughts. For instance, increasing temperatures in certain areas are lowering the yields of important crops like wheat, maize, and rice, while shifting rainfall patterns in other areas are making it more challenging to cultivate crops.
Populations reliant on subsistence farming are particularly vulnerable to climatic effects on crop yields. However, empirical evidence on the role of the timing of exposure to crop yield deficits around early life development is limited. We examined child survival in relation to annual crop yield reductions at different stages around early life development in a subsistence farming population in Burkina Faso. Using shared frailty Cox proportional hazards models adjusted for confounders, we analysed 57,288 children <5 years of age followed by the Nouna Health and Demographic Surveillance System, 1992-2016, in relation to provincial food crop yield levels experienced in the following non-overlapping windows: 12 months before conception, in utero, birth-6 months, 6 months-2 years, 2-5 years of age; and their aggregates: birth-2 years, first 1,000 days since conception, birth-5 years. Of the non-overlapping windows, point estimates were largest for child survival related to yields for the time window of 6 months-2 years: adjusted mortality hazard ratio 1.10 (95% confidence interval 1.03 to 1.19) for a 90th to 10th centile yield reduction. These findings suggest that child survival in this setting is particularly vulnerable to cereal crop yield reductions during the period of non-exclusive breastfeeding.
This paper advances previous literature that has posited a climate-nutrition link without identifying a specific pathway via agriculture. We measure the specific effects of exposure to extreme heat on maize yields in Tanzania, and then test whether prenatal heat-induced yield losses predict subsequent child growth outcomes. In the first stage we find that substituting one full day (24 h) exposure to 39 °C for a day at 29 degrees reduces predicted yield for the entire growing season by 6–11%. In the second stage we find that in utero exposure to growing degree days greater than 29 °C predicts lower postnatal HAZ scores for Tanzanian boys 0–5 years of age, but not girls. Consistent with a maternal malnutrition mechanism, we also find a negative association between maize yields and women’s body mass. Insofar as climate change is likely to increase the incidence of heat shocks in much of sub-Saharan Africa, our results suggest a significant risk of adverse nutritional impacts.
Climate change is expected to have far-reaching impacts on food security. Such impacts are likely to be higher in developing countries. This paper analyses the state of research on the nexus between climate change and food security in Burkina Faso. In particular, it sheds light on whether and how the scholarly literature addresses the impacts of climate change on the four dimensions of food security (i.e. food availability, food access, food utilisation and stability). It also explores the synergies and trade-offs between climate change mitigation/adaptation and food security. A search performed in April 2020 on the Web of Science yielded 243 records and 62 of them, which resulted eligible, were included in the systematic review. The literature shows that climate change will affect all the four dimensions of food security. However, most of the analysed literature addresses its effects on food availability. Indeed, it focuses on impacts on crop yields and climate suitability for crops (e.g. maize, millet, sorghum). Moreover, most of the impacts on the remaining food security dimensions stem from the negative effects on food production and supply (cf. food availability). The review also shows that, on the one hand, climate change mitigation can undermine food security and, on the other hand, agriculture intensification and some adaptation strategies, which aim to enhance food security, might increase emissions from agriculture. The dual climate change-food security relationship calls for integrated policies that address trade-offs and optimise co-benefits between 'climate action' and 'zero hunger' in Burkina Faso.
In West Africa, climate change aggravates subsistence farmers' vulnerability to weather variability to sustain their agricultural and nutritional requirements. For successful adaptation policies, in-depth understanding of farmers' perceptions about climate change, agriculture, and adaptation strategies is essential. This qualitative study in rural Burkina Faso characterized farmers' perceptions and knowledge through in-depth interviews. The study enumerated the barriers, possibilities, strategies/practices, and support sources of farmers. There was awareness but limited understanding of climate change amongst farmers. Those unable to adapt, faced increased health difficulties, specifically regarding nutrition and mental health. Farmers could implement some dietary and agricultural adaptation strategies (reduce meal size, frequency and variety, preemptive purchase of cereals, multi-cropping, crop rotation, modified seeds) but were unable to implement others (soil rehabilitation, water management). Barriers to implementation comprised financial and time constraints, material and labor shortages, and inaccessible information. Farmers did not understand, trust or utilize meteorological services, but appreciated and relied on agricultural extension services. They reported that social and governmental support was sporadic and inconsistent. This study uncovers the following targets for climate change adaptation policies in rural Burkina Faso: promoting meteorological services, expanding agricultural extension services, increasing access to financial resources, and framing sustainable adaptation within national development goals.
In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a “special report in 2018 on the impacts of global warming of 1.5 ∘C above pre-industrial levels and related global greenhouse gas emission pathways”. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 ∘C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).
Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic–thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.
Background
Reduction of child undernutrition is one of the Sustainable Development Goals for 2030. Achievement of this goal may be made more difficult in some settings by climate change through adverse impact on agricultural productivity. However, there is only limited quantitative evidence on the link between household crop harvests and child nutrition. We examined this link in a largely subsistence farming population in rural Burkina Faso.
Methods
Data on the middle-upper arm circumference (MUAC) of 975 children ≤5 years of age, household crop yields, and other parameters were obtained from the Nouna Health and Demographic Surveillance System. Multilevel modelling was used to assess the relationship between MUAC and the household crop harvest in the year 2009 estimated in terms of kilocalories per adult equivalent per day (kcal/ae/d).
Results
Fourteen percent of children had a MUAC <125 mm (a value indicative of acute undernutrition). The relationship between MUAC and annual household food energy production adjusted for age, sex, month of MUAC measurement, household wealth, whether a household member had a non-agricultural occupation, garden produce, village infrastructure and market presence, suggested a decline in MUAC below around 3000 kcal/ae/d. The mean MUAC was 2.49 (95% CI 0.45, 4.52) mm less at 1000 than at 3000 kcal/ae/d.
Conclusions
Low per capita household crop production is associated with poorer nutritional status of children in a rural farming population in Burkina Faso. This and similar populations may thus be vulnerable to the adverse effects of weather on agricultural harvest, especially in the context of climate change.
Electronic supplementary material
The online version of this article (doi:10.1186/s12940-017-0258-9) contains supplementary material, which is available to authorized users.
Whether year to year variation in crop yields affects the nutrition, health, and survival of subsistence farming populations is relevant to the understanding of the potential impacts of climate change. However, the empirical evidence is limited. We examined the association of child survival with inter-annual variation in food crop yield and middle-upper arm circumference (MUAC) in a subsistence farming population of rural Burkina Faso. The study was of 44,616 children < 5 years of age included in the Nouna Health and Demographic Surveillance System, 1992-2012, whose survival was analysed in relation to the food crop yield in the year of birth (which ranged from 65% to 120% of the period average) and, for a subset of 16,698 children, to MUAC, using shared frailty Cox proportional hazards models. Survival was appreciably worse in children born in years with low yield (fully adjusted hazard ratio of 1.11 (95% confidence interval: 1.02, 1.20) for a 90th to 10th centile decrease in annual crop yield) and in children with small MUAC (hazard ratio 2.72 (95% confidence interval: 2.15, 3.44) for a 90th to 10th centile decrease in MUAC). These results suggest an adverse impact of variations in crop yields which could increase under climate change.
For agriculture in Germany and generally all around the world, yield variability due to uncertain climate conditions represents an increasing production risk. Regional assessments of future yield changes can diminish this risk. For Germany's two most important crops winter wheat (Triticum aestivum L.) and silage maize (Zea mays L.), we investigate three regression models estimating relative climate impacts on relative crop yield changes: the separate time series model (STSM), the panel data model (PDM) and the random coefficient model (RCM). These regression models use the Cobb-Douglas function to capture climatic and non-climatic impacts on yields (e.g., changing prices or inventory management). The yield influencing climatic impacts contain the potential growth and stress factors during vegetative and reproductive plant development. The models are estimated and validated at the county scale. To improve the robustness and goodness of fit, the models are aggregated at the scale of German federal states, river basins and at the national scale. The observed yield changes are satisfactorily reproduced by all models for all aggregated scales (measured by the Nash-Sutcliffe efficiency (NSE)). According to their NSE values, the methodically simple STSMs reproduce extreme yield changes better (0.85) than the RCMs (0.79) and PDMs (0.72) at the national scale. This order can be also found across all scales when considering the models' goodness of fit. Generally, spatial aggregation increases the goodness of fit by +0.16 for federal states and river basins and by +0.29 for entire Germany compared to the county scale. The mean NSE increase is lowest for STSMs (+0.11), followed by RCMs (+0.13) and PDMs (+0.25) for federal states and river basins, which is opposite to the goodness of fit order. The model parameters show clear spatial patterns, which reflect regional differences of climate and soil. Within its methodological limits, our approach can directly be combined with the output of climate models and is suitable for assessing short- and medium-term yield effects for the current agronomic practice. It requires neither bias correction of the climate variables nor explicit modeling of crop yield trends.
Significance
The World Health Organization and the Intergovernmental Panel for Climate Change propose undernutrition as the most significant impact of climate change on child health. The question then arises: Where does the empirical evidence to back this claim come from? Current evidence for the impacts of climate on childhood undernutrition draws on a limited number of heterogeneous studies with methodological limitations and is based predominantly on secondary data. Establishing and validating causal pathways among complex confounding factors remain the main challenge in quantifying the climate-attributable fraction of undernutrition. Systematically generating evidence from long-term, high-quality primary data on a range of factors (agricultural, environmental, socioeconomic, and health) at the household level is critical for designing adaptation strategies, particularly for subsistence farmers.
Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for similar to 13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (similar to 32-39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.
Climate change has the potential to significantly impact agricultural production and the stakes are large. Against this backdrop, two schools of thought find different projected impacts from climate change. On the one hand, crop models, based on plant physiology and developed and refined from field experiments over many decades, usually predict modestly negative to positive impacts from projected warming and rising carbon dioxide concentrations, both globally and in the US. The temperature distribution accounts for variation in temperatures across locations, using fine-scale weather data, and within days by assuming temperatures follow a sine curve between each day's maximum and minimum temperatures. Vapor pressure deficit (VPD) is calculated as the difference between how much water the air can hold when it is saturated and how much water it currently holds. The first two columns of the table display the marginal impact of each variable, which is assumed to be constant due to the linear functional form.
The WFDEI meteorological forcing dataset has been generated using the same methodology as the widely used WATCH Forcing Data (WFD) by making use of the ERA-Interim reanalysis data. We discuss the specifics of how changes in the reanalysis and processing have led to improvement over the WFD. We attribute improvements in precipitation and wind speed to the latest reanalysis basis data and improved downwards shortwave fluxes to the changes in the aerosol corrections. Covering 1979-2012 the WFDEI will allow more thorough comparisons of hydrological and Earth System model outputs with hydrologically- and phenologically-relevant satellite products than using the WFD.
This study estimates of the impact of climate change on yields for the four most commonly grown crops (millet, maize, sorghum and cassava) in Sub-Saharan Africa (SSA). A panel data approach is used to relate yields to standard weather variables, such as temperature and precipitation, and sophisticated weather measures, such as evapotranspiration and the standardized precipitation index (SPI). The model is estimated using data for the period 1961-2002 for 37 countries. Crop yields through 2100 are predicted by combining estimates from the panel analysis with climate change predictions from general circulation models (GCMs). Each GCM is simulated under a range of greenhouse gas emissions (GHG) assumptions. Relative to a case without climate change, yield changes in 2100 are near zero for cassava and range from –19% to +6% for maize, from –38% to –13% for millet and from –47% to –7% for sorghum under alternative climate change scenarios.
Crop-model specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on inter-model variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median projected maize and wheat yield changes were -3.6% and 6.2%, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties. This article is protected by copyright. All rights reserved.
Background:
A growing body of evidence points to the emission of greenhouse gases from human activity as a key factor in climate change. This in turn affects human health and wellbeing through consequential changes in weather extremes. At present, little is known about the effects of weather on the health of sub-Saharan African populations, as well as the related anticipated effects of climate change partly due to scarcity of good quality data. We aimed to study the association between weather patterns and daily mortality in the Nouna Health and Demographic Surveillance System (HDSS) area during 1999-2009.
Methods:
Meteorological data were obtained from a nearby weather station in the Nouna HDSS area and linked to mortality data on a daily basis. Time series Poisson regression models were established to estimate the association between the lags of weather and daily population-level mortality, adjusting for time trends. The analyses were stratified by age and sex to study differential population susceptibility.
Results:
We found profound associations between higher temperature and daily mortality in the Nouna HDSS, Burkina Faso. The short-term direct heat effect was particularly strong on the under-five child mortality rate. We also found independent coherent effects and strong associations between rainfall events and daily mortality, particularly in elderly populations.
Conclusion:
Mortality patterns in the Nouna HDSS appear to be closely related to weather conditions. Further investigation on cause-specific mortality, as well as on vulnerability and susceptibility is required. Studies on local adaptation and mitigation measures to avoid health impacts from weather and climate change is also needed to reduce negative effects from weather and climate change on population health in rural areas of the sub-Saharan Africa.
There is widespread interest in the impacts of climate change on agriculture in Sub-Saharan Africa (SSA), and on the most effective investments to assist adaptation to these changes, yet the scientific basis for estimating production risks and prioritizing investments has been quite limited. Here we show that by combining historical crop production and weather data into a panel analysis, a robust model of yield response to climate change emerges for several key African crops. By mid-century, the mean estimates of aggregate production changes in SSA under our preferred model specification are − 22, − 17, − 17, − 18, and − 8% for maize, sorghum, millet, groundnut, and cassava, respectively. In all cases except cassava, there is a 95% probability that damages exceed 7%, and a 5% probability that they exceed 27%. Moreover, countries with the highest average yields have the largest projected yield losses, suggesting that well-fertilized modern seed varieties are more susceptible to heat related losses.
The purpose of this Editorial is to set the scene for a series of profiles from INDEPTH HDSS member sites, the first examples of which are published in this edition of IJE.2–5 All these profiles will follow a set pattern, to facilitate a systematic understanding of the multiplicity of HDSS sites involved in the Network and the various ways in which they are operated by their parent institutions. This Editorial therefore, follows the same general pattern as the individual profiles, but seeks to explore the epidemiological basis on which the HDSSs operate in general, and the role of the Network, rather than dealing with site-specific issues.
Agricultural and Forest Meteorology j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / a g r f o r m e t a b s t r a c t Improved understanding of the influence of climate on agricultural production is needed to cope with expected changes in temperature and precipitation, and an increasing number of undernourished peo-ple in food insecure regions. Many studies have shown the importance of seasonal climatic means in explaining crop yields. However, climate variability is expected to increase in some regions and have significant consequences on food production beyond the impacts of changes in climatic means. Here, we examined the relationship between seasonal climate and crop yields in Tanzania, focusing on maize, sorghum and rice. The impacts of both seasonal means and variability on yields were measured at the subnational scale using various statistical methods and climate data. The results indicate that both intra-and interseasonal changes in temperature and precipitation influence cereal yields in Tanzania. Seasonal temperature increases have the most important impact on yields. This study shows that in Tanzania, by 2050, projected seasonal temperature increases by 2 • C reduce average maize, sorghum, and rice yields by 13%, 8.8%, and 7.6% respectively. Potential changes in seasonal total precipitation as well as intra-seasonal temperature and precipitation variability may also impact crop yields by 2050, albeit to a lesser extent. A 20% increase in intra-seasonal precipitation variability reduces agricultural yields by 4.2%, 7.2%, and 7.6% respectively for maize, sorghum, and rice. Using our preferred model, we show that we underestimate the climatic impacts by 2050 on crop yields in Tanzania by 3.6%, 8.9%, and 28.6% for maize, sorghum and rice respectively if we focus only on climatic means and ignore climate variability. This study highlights that, in addition to shifts in growing season means, changes in intra-seasonal variability of weather may be important for future yields in Tanzania. Additionally, we argue for a need to invest in improving the climate records in these regions to enhance our understanding of these relationships.
Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health.
We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050.
We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change).
We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia).
Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.
This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference. Keywords:˜panel data, covariance matrix estimators, generalized method of moments, R. 1.
Quantitative health impact assessments of chronic mortality, where the impacts are expected to be observed over a number of years, are complicated by the link between death rates and surviving populations. A general calculation framework for quantitative impact assessment is presented, based on standard life table calculation methods, which permits consistent future projections of impacts on mortality from changes in death rates. Implemented as a series of linked spreadsheets, the framework offers complete flexibility in the sex specific, age specific, and year specific patterns of baseline mortality death rates; in the predicted impacts upon these; in the weights or values placed on gains in life; and in the summary measures of impact. Impacts can be differential by cause of death. Some examples are given of predictions of the impacts of reductions in chronic mortality in the populations of England and Wales and of Scotland.
Background
In 2016, 23% of children (155 million) aged <5 were stunted. Global-level modeling has consistently found climate change impacts on food production are likely to impair progress on reducing undernutrition.
Objectives
We adopt a new perspective, assessing how climate change may affect child stunting via its impacts on two interacting socioeconomic drivers: incomes of the poorest 20% of populations (due to climate impacts on crop production, health, labor productivity, and disasters) and food prices.
Methods
We developed a statistical model to project moderate and severe stunting in children aged <5 at the national level in 2030 under low and high climate change scenarios combined with poverty and prosperity scenarios in 44 countries.
Results
We estimated that in the absence of climate change, 110 million children aged <5 would be stunted in 2030 under the poverty scenario in comparison with 83 million under the prosperity scenario. Estimates of climate change–attributable stunting ranged from 570,000 under the prosperity/low climate change scenario to >1 million under the poverty/high climate change scenario. The projected impact of climate change on stunting was greater in rural vs. urban areas under both socioeconomic scenarios. In countries with lower incomes and relatively high food prices, we projected that rising prices would tend to increase stunting, whereas in countries with higher incomes and relatively low food prices, rising prices would tend to decrease stunting. These findings suggest that food prices that provide decent incomes to farmers alongside high employment with living wages will reduce undernutrition and vulnerability to climate change.
Conclusions
Shifting the focus from food production to interactions between incomes and food price provides new insights. Futures that protect health should consider not just availability, accessibility, and quality of food, but also the incomes generated by those producing the food. https://doi.org/10.1289/EHP2916
Increases in cereals production risk are commonly related to increases in weather risk. We analyze weather-induced changes in wheat yield volatility as a systemic weather risk in Germany. We disentangle, however, the relative impacts of inputs and weather on regional yield volatility. For this purpose we augment a production function with phenologically aggregated weather variables. Increasing volatility can be traced back to weather changes only in some regions. On average, inputs explain 49% of the total actual wheat yield volatility, while weather explains 43%. Models with only weather variables deliver biased but reasonable approximations for climate impact research.
Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semi-empirical modeling scheme that allows for such quantification. Yield anomalies, measured as inter-annual differences, were modeled for maize, soybeans and wheat in the US and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season.
This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land
use, and emissions implications. The SSPs are part of a new scenario framework, established by the
climate change research community in order to facilitate the integrated analysis of future climate
impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a
joint community effort and describe plausible major global developments that together would lead in the
future to different challenges for mitigation and adaptation to climate change. The SSPs are based on
five
narratives describing alternative socio-economic developments, including sustainable development,
regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The longterm
demographic and economic projections of the SSPs depict a wide uncertainty range consistent with
the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and
the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy
consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a
possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than
120 GtCO2 per year by 2100. With respect to mitigation, we
find that associated costs strongly depend on
three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the
target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change
limit of 2 �C, differs in our analysis thus by about a factor of three across the SSP marker scenarios.
Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While
the SSPs were designed to represent different mitigation and adaptation challenges, the resulting
narratives and quantifications span a wide range of different futures broadly representative of the current
literature. This allows their subsequent use and development in new assessments and research projects.
Critical next steps for the community scenario process will, among others, involve regional and sectoral
extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP
scenarios with the new generation of earth system models as part of the 6th climate model
intercomparison project (CMIP6).
Barker’s fetal origins hypothesis suggests a strong association between in utero conditions, health, and overall child development after birth. Using a nationally representative population survey, this article analyzes the impact of in utero exposure to drought on early child health in rural India. We find that drought experienced in utero has detrimental effects on the nutritional status of children. The adverse effect of drought on child health is mediated through financial duress in drought years. We speculate that policies aimed at reducing vulnerability to drought may result in improved health in rain-dependent agrarian societies.
Stunting affects an individual’s educational and wage-earning potential and can even affect the next generation of children. Most research of childhood stunting focuses on the determinants and correlates that lead to stunting—through nutritional or early infant experiences, with one potential solution to stunting being an increased supply of locally produced food. This research examines the interplay of community-level cropped area as a factor relating to childhood stunting. We use the most recently collected Demographic and Health Survey (DHS) data for Mali, very high resolution remotely sensed imagery, and other remotely sensed data relating to geophysical characteristics to examine the impact of local cultivation on children’s health. We focus on evaluating the environmental, community, household, and individual characteristics of the children who report healthy anthropometrics despite the presence of specific stunting risk factors. In adopting this approach to studies of children’s health we can shed light on how small-scale agricultural production impacts childhood stunting among at-risk children.
Most studies of the influence of weather and climate on food production have examined the influence on crop yields. However, climate influences all components of crop production, includes cropping area (area planted or harvested) and cropping intensity (number of crops grown within a year). Although yield increases have predominantly contributed to increased crop production over the recent decades, increased cropping area as well as increases in cropping intensity, especially in the tropics, have played a substantial role. Therefore we need to consider these important aspects of production to get a more complete understanding of the future impacts of climate change. This article reviews available evidence on how climate might influence these under-studied components of crop production. We also discuss how farmer decision making and technology might modulate the production response to climate. We conclude by discussing important knowledge gaps that need to be addressed in future research and potential ways for moving forward.
Background:
This study aimed to investigate the relationship between household wealth and under-5 year mortality in rural and semi-urban Burkina Faso.
Methods:
The study included 15 543 children born between 2005 and 2010 in the Nouna Health and Demographic Surveillance System. Information on household wealth was collected in 2009. Two separate wealth indicators were calculated by principal components analysis for the rural and the semi-urban households, which were then divided into quintiles accordingly. Multivariable Cox proportional hazards regression was used to study the effect of the respective wealth measure on under-5 mortality.
Results:
We observed 1201 childhood deaths, corresponding to 5-year survival probability of 93.6% and 88% in the semi-urban and rural area, respectively. In the semi-urban area, household wealth was significantly related to under-5 mortality after adjustment for confounding. There was a similar but non-significant effect of household wealth on infant mortality, too. There was no effect of household wealth on under-5 mortality in rural children.
Conclusions:
Results from this study indicate that the more privileged children from the semi-urban area with access to piped water and electricity have an advantage in under-5 survival, while under-5 mortality in the rural area is rather homogeneous and still relatively high.
Projecting the impacts of climate change on agriculture requires knowing or assuming how farmers will adapt. However, empirical estimates of the effectiveness of this private adaptation are scarce and the sensitivity of impact assessments to adaptation assumptions is not well understood. Here we assess the potential effectiveness of private farmer adaptation in Europe by jointly estimating both short-run and long-run response functions using time-series and cross-sectional variation in subnational yield and profit data. The difference between the impacts of climate change projected using the short-run (limited adaptation) and long-run (substantial adaptation) response curves can be interpreted as the private adaptation potential. We find high adaptation potential for maize to future warming but large negative effects and only limited adaptation potential for wheat and barley. Overall, agricultural profits could increase slightly under climate change if farmers adapt but could decrease in many areas if there is no adaptation. Decomposing the variance in 2040 projected yields and farm profits using an ensemble of 13 climate model runs, we find that the rate at which farmers will adapt to rising temperatures is an important source of uncertainty.
Assessments of climate change impacts on agricultural markets and land-use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land-use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.
Predicting the potential effects of climate change on crop yields requires a model of how crops respond to weather. As predictions from different models often disagree, understanding the sources of this divergence is central to building a more robust picture of climate change's likely impacts. A common approach is to use statistical models trained on historical yields and some simplified measurements of weather, such as growing season average temperature and precipitation. Although the general strengths and weaknesses of statistical models are widely understood, there has been little systematic evaluation of their performance relative to other methods. Here we use a perfect model approach to examine the ability of statistical models to predict yield responses to changes in mean temperature and precipitation, as simulated by a process-based crop model. The CERES-Maize model was first used to simulate historical maize yield variability at nearly 200 sites in Sub-Saharan Africa, as well as the impacts of hypothetical future scenarios of 2°C warming and 20% precipitation reduction. Statistical models of three types (time series, panel, and cross-sectional models) were then trained on the simulated historical variability and used to predict the responses to the future climate changes. The agreement between the process-based and statistical models’ predictions was then assessed as a measure of how well statistical models can capture crop responses to warming or precipitation changes. The performance of statistical models differed by climate variable and spatial scale, with time-series statistical models ably reproducing site-specific yield response to precipitation change, but performing less well for temperature responses. In contrast, statistical models that relied on information from multiple sites, namely panel and cross-sectional models, were better at predicting responses to temperature change than precipitation change. The models based on multiple sites were also much less sensitive to the length of historical period used for training. For all three statistical approaches, the performance improved when individual sites were first aggregated to country-level averages. Results suggest that statistical models, as compared to CERES-Maize, represent a useful if imperfect tool for projecting future yield responses, with their usefulness higher at broader spatial scales. It is also at these broader scales that climate projections are most available and reliable, and therefore statistical models are likely to continue to play an important role in anticipating future impacts of climate change.
County wheat yield and wheat quality are forecast using weather information. Regression models are estimated to account for the effect of weather on county wheat yield, protein, and test weight. The explanatory variables include precipitation and temperature for growing periods that correspond to biological wheat development stages. Wheat yield, protein, and test weight are strongly influenced by weather. The forecasting power of the yield and protein models is enhanced by adding a spatial lag effect. Out of sample forecasting tests confirm the models' usefulness in predicting wheat yield and wheat quality.
For countries with recurrent droughts, the design of drought impact mitigation measures could benefit from analyses of determinants of yields and prices of local crops at regional and district level. This study applies dynamic spatial panel data regression models to yields and prices of four major food crops across regions of Burkina Faso and Niger, over sample periods between 1984 and 2006. Results lend support to mainly simultaneous spatial spillovers, particularly for millet and cowpea prices and sorghum yields in Niger, and maize yields in Burkina Faso. After accounting for these effects, most crop yields are found to be weakly price-responsive, as envisaged by a supply-side geographical diffusion hypothesis. Seasonal rainfall elasticity estimates suggest that dominant food crops have slight advantage margins in terms of relative resilience to rainfall shortages. However, this result is to be weighed against low millet yields in Niger, and marked drops in sorghum yields during officially declared droughts in Burkina Faso.
Climate change continues to have major impact on crop productivity all over the world. Many researchers have evaluated the possible impact of global warming on crop yields using mainly indirect crop simulation models. Here we use a 1979–2000 Chinese crop-specific panel dataset to investigate the climate impact on Chinese wheat yield growth. We find that a 1 °C increase in wheat growing season temperature reduces wheat yields by about 3–10%. This negative impact is less severe than those reported in other regions. Rising temperature over the past two decades accounts for a 4.5% decline in wheat yields in China while the majority of the wheat yield growth, 64%, comes from increased use of physical inputs. We emphasize the necessity of including such major influencing factors as physical inputs into the crop yield-climate function in order to have an accurate estimation of climate impact on crop yields.
The commonsense logic associating higher land security and higher incentives to invest has been recently called into question in the case of African agriculture. To be meaningful, empirical tests have to be carefully designed so as to take account of the possible endogeneity of the land rights variable. This is done in this paper by applying suitable econometric methods to the original data collected in Burkina Faso. The results obtained cast doubt on the existence of a systematic influence of land tenure security on investment. By reviewing the justifications for scepticism in the recent literature, we are able to conclude that the traditional village order, where it exists, provides the basic land rights required to stimulate small-scale investment.
A review is given of the state of knowledge in the field of assessing climate change impacts on agricultural crops and livestock. Starting from the basic processes controlling plant growth and development, the possible impacts and interactions of climatic and other biophysical variables in different agro-environments are highlighted. Qualitative and quantitative estimations of shifts in biomass production and water relations, inter-plant competition and crop species adaptability are discussed. Special attention is given to the problems encountered when scaling up physiological responses at the leaf- and plant level to yield estimates at regional to global levels by using crop simulation models in combination with geo-referenced, agro-ecological databases. Some non-linear crop responses to environmental changes and their relations to adaptability and vulnerability of agro-ecosystems are discussed.
This article investigates changes in income diversification patterns for the case of Burkina Faso between 1994 and 2003. Contrary to common beliefs, our empirical analysis shows that rural households are not increasingly diversifying their income portfolios. Beyond insuring against and coping with weather shocks, diversification behaviour reflects structural change. Higher returns to agricultural activities, in particular in the cotton and livestock sectors, appear to be the root cause for less non-agricultural diversification and some of our findings hint at better opportunities in the non-farm sector. Yet, average returns in the non-farm sector appear to remain relatively low and migration increasingly turns into a desperation-led strategy. Overall, structural change seems to be biased in favour of richer households. Regarding responses to droughts, we confirm earlier findings, especially that the poorest households are hit particularly hard, being forced to sell livestock, which is often their only asset.
This paper studies the theoretical and empirical implications of monetary policy making by committee under four different voting protocols. The protocols are a consensus model, where a supermajority is required for a policy change; an agenda-setting model, where the chairman controls the agenda; a dictator model, where the chairman has absolute power over the committee; and a simple majority model, where policy is determined by the median member. These protocols give preeminence to different aspects of the actual decision-making process and capture the observed heterogeneity in formal procedures across central banks. The models are estimated by maximum likelihood using interest rate decisions by the committees of five central banks, namely the Bank of Canada, the Bank of England, the European Central Bank, the Swedish Riksbank, and the U.S. Federal Reserve. For all central banks, results indicate that the consensus model fits actual policy decisions better than the alternative models. This suggests that despite institutional differences, committees share unwritten rules and informal procedures that deliver observationally equivalent policy decisions. (c) 2010 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology..
Child stunting in Ethiopia has persisted at alarming rates, despite enormous amounts of food aid, often procured in response
to shocks. Using nationally representative data, the study finds that while harvest failure leads to child growth faltering,
food aid affected child growth positively and offset the negative effects of shocks in communities that received food aid.
However, many communities that experienced shocks did not receive food aid. In sum, while food aid has helped reduce child
malnutrition, inflexible food aid targeting, together with endemic poverty and limited maternal education, has left the prevalence
of child stunting at alarming levels.
Summary for policymakers
- IPCC
Food Aid and Food Security in the Short- and Long Run: Country Experience from Asia and Sub-Saharan Africa. The World Bank Social Safety Nets Primer
- C Del Ninno
- P A Dorosh
- K Subbarao