Global warming threatens agricultural productivity in Africa and South Asia

Production of cereals in northern marginal areas: An integrated assessment of climate change impacts at the farm level

The impacts of climate change on the food system are a key concern for societies and policy makers globally. Assessments of the biophysical impacts of crop productivity show modest but uncertain impacts. But crop growth is not the only factor that matters for the food production. Climate impacts on the labour force through increased heat stress also need to be considered. Here, we provide projections for the integrated climate-induced impacts on crop yields and worker productivity on the agro-economy in a global multi-sector economic model. Biophysical impacts are derived from a multi-model ensemble, which is based on a combination of climate and crop models, and the economic analysis is conducted for different socio-economic pathways. This framework allows for a comprehensive assessment of biophysical and socio-economic risks, and outlines rapid risk increases for high-warming scenarios. Considering heat effects on labour productivity, regional production costs could increase by up to 10 percentage points or more in vulnerable tropical regions such as South and South-East Asia, and Africa. Heat stress effects on labour might offset potential benefits through productivity gains due to the carbon dioxide fertilisation effect. Agricultural adaptation through increased mechanisation might allow to alleviate some of the negative heat stress effects under optimistic scenarios of socio-economic development. Our results highlight the vulnerability of the food system to climate change impacts through multiple impact channels. Overall, we find a consistently negative impact of future climate change on crop production when accounting for worker productivity next to crop yields.

Food Security Under The Era Of Climate Change Threat

Multi-model ensembles for assessing the impact of future climate change on rainfed wheat productivity under various cultivars and nitrogen levels

<p>Evapotranspiration (ET) or the water vapour flux is an important component in the water cycle and is widely studied due to its implications in disciplines ranging from hydrology to agricultural and climate sciences. In the recent past, growing attention has been given to estimating ET fluxes at regional and global scales. However, estimation of ET at large scales has been a difficult task due to direct measurement of ET being possible only at point locations, for example using flux towers. For the African continent, only a limited number of flux tower data are openly available for use, which makes verification of regional and global ET products very difficult. Recent advances in satellite based products provide promising data to fill these observational gaps.</p><p>In this study we propose to investigate the Climate Change (CC) impact on crop water productivity across Africa using ET and crop yield predictions of different crop models for future climate scenarios. Different model outputs are evaluated including models from both the ISI-MIP 2a and 2b protocols. Considering the problem of direct observations of ET being difficult to obtain, especially over Africa, we use ET estimates from several remotely sensed derived products as a references to evaluate the crop models (maize) in terms of magnitude, spatial patterns and variations between models. The crop model results for crop yield are compared to FAO reported crop yields at country scale. The results show a very strong disagreement between the different crop models of the baseline scenario and when compared with ET and crop yield data.  Also, a very large uncertainty is obtained for the climate change predictions. It is hence recommended to improve the crop models for application in Africa.</p>

Climate changes and trends in phenology and yields of field crops in China, 1981–2000

The present study investigated the impact of climate variability and change on maize yields in the Semi-Arid Lands of lower Eastern Kenya. A major factor in rain-fed agriculture is the climate. The primary determinant of crop production in Kenya and other regions of the world has been climate variability and change. There hasn't been much study, though, on how climate variability affects maize yields in the Arid and Semi-Arid Lands (ASALs) in lower eastern Kenya counties. For the purpose of establishing a foundation for maize crop monitoring and modelling, the impact of three meteorological parameters on maize yields at various temporal and spatial scales was assessed. This paper argues that maize yields were declining at high levels in Machakos County followed by Kitui, Mwingi, and Makueni Counties. The maize yields Z-values and thus the effect of climate was predominately negative in the period 1994–2008 in all the counties. Rainfall trend analysis revealed that four of the six weather stations were declining up to 3 mm pa. Evidently there was upward warming of annual and seasonal temperatures at rate of 0.03°C pa. The study has confirmed that the arid and semi arid counties suffer from significant climate variability which has huge implications on maize yields and food security of lower eastern Kenya. Relationship between maize and rainfall was positive and negative, respectively, and was statistically significant. Maize yield has a pro- nounced declining negative trend in all the four coun- ties of lower eastern Kenya. Thus, to counter the adverse effects of climate change, it is necessary to climate-proof agricultural crops through adaptation strategies such as developing maize varieties that tolerate water stress and mature early, practice early planting, increase the awareness of climate change and its impacts on agriculture, and develop appropriate mitigation measures. These findings are crucial in planning appropriate adaptation mechanisms in support of enhancing resilience of maize production and food security.

Climate change has emerged as the most prominent of the global environment issues and there is a need to evaluate its impact on agriculture. Crop simulation models help greatly in this regard. Crop models such as WTGROWS, INFOCROP, ORYZA and DSSAT have been widely used for land use planning, agri-production estimates, impact of climate change and environmental impact analysis. Vulnerable regions under future scenarios of climate change and adaptation strategies (agronomic and input management) have been evolved for many important crops by using simulation techniques. One of the simple empirical techniques for evaluating the impact of future climate change is through historic analysis of the response of crops to inter-seasonal climatic variability. The impact of temperature rise is different for crops grown under variable production environments. Interactions exist for changes in temperature, carbon dioxide concentration, solar radiation and rainfall on growth and yield of crops. Adaptation strategies through the adoption of agronomic management options (such as altered date of sowing, scheduling of water and nutrients) can sustain agricultural productivity under climate change. The rapid changes in land use and land cover have to be included for impact analysis. Linking of the socioeconomic aspects needs to be strengthened.

Climate change is one of the most pressing global issues of the twenty-first century. This phenomenon has an increasingly severe impact on water resources and crop production. The main purpose of this study is to evaluate the impact of climate change on water resources, crop production, and agricultural sustainability in an arid environment in Iran. To this end, the study constructs a new integrated climate-hydrological-economic model to assess the impact of future climate change on water resources and crop production. Furthermore, the agricultural sustainability is evaluated using the multicriteria decision making (MCDM) technique in the context of climate change. The findings regarding the prediction of climate variables show that the minimum and maximum temperatures are expected to increase by about 5.88% and 6.05%, respectively, while precipitation would decrease by approximately 30.68%. The results of the research reveal that water availability will decrease by about 13.79–15.45% under different climate scenarios. Additionally, the findings show that in the majority of cases crop production will reduce in response to climate scenarios so that rainfed wheat will experience the greatest decline (approximately 59.95%). The results of the MCDM model show that climate change can have adverse effects on economic and environmental aspects and, consequently, on the sustainability of the agricultural system of the study area. Our findings can inform policymakers on effective strategies for mitigating the consequences of climate change on water resources and agricultural production in dry regions.

Uniting the Global Gastroenterology Community to Meet the Challenge of Climate Change and Non-Recyclable Waste

Quantitatively projecting the impact of future climate change on the socio-economy and exploring its internal mechanism are of great practical significance to adapt to climate change and prevent climate risks. Based on the economy-climate (C-D-C) model, this paper introduces a yield impact of climate change (YICC) model that can quantitatively project the climate change impact. The model is based on the YICC as its core concept and uses the impact ratio of climate change (IRCC) indicator to assess the response of the economic system to climate change over a long period of time. The YICC is defined as the difference between the economic output under changing climate condition and that under assumed invariant climate condition. The IRCC not only reflects the sensitivity of economic output to climate change but also reveals the mechanism of the nonlinear interaction between climate change and non-climatic factors on the socio-economic system. Using the main grain-producing areas in China as a case study, we use the data of the ensemble average of 5 GCMs in CMIP6 to project the possible impact of climate change on grain production in the next 15–30 years under three future scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results indicate that the long-term climate change in the future will have a restraining effect on production in North region and enhance production in South region. From 2021 to 2035, climate change will reduce production by 0.60–2.09% in North region, and increase production by 1.80–9.01% in South region under three future scenarios. From 2021 to 2050, compared with the climate change impact in 2021–2035, the negative impact of climate change on production in North region will weaken, and the positive impact on production in South region will enhance with the increase in emission concentration. Among them, climate change will reduce grain output in North region by 0.52–1.99%, and increase output in South region by 1.35–9.56% under the three future scenarios. The combination of economic results and climate change research is expected to provide scientific support for further revealing the economic mechanism of climate change impacts.

ABSTRACTClimate change and political instability have implications for food and agricultural production. Africa is often described as one of the most vulnerable continents to the impacts of climate change, political instability, and conflicts. However, empirical evidence on the impacts of climate change, political instability, and violent conflicts on food and agricultural production is scanty and mixed. A better understanding of the impacts of climate change and political instability on food and agricultural production on the continent is needed to achieve some of the sustainable development goals. This paper investigates the impacts of climate change and political instability on food and agricultural production in Africa. The study relied on panel data from 43 countries spanning a period of 20 years (2000–2019). The data were obtained from the World Bank Climate Change Knowledge Portal, World Development Indicators, and FAOSTAT databases. Using the panel autoregressive distributed lag model, we find that the annual maximum number of consecutive dry days, temperature, and rainfall data significantly decreased the food production index, livestock production index, cereal production, and crop production index in the long run. Also, we find that total greenhouse gas emissions significantly increased the food production index, livestock production index, cereal production, total fisheries production, and crop production index in the long run. Political stability significantly increased the livestock production index, cereal production, and total fisheries production in the long run, while employment in agriculture significantly increased the food production index, crop production index, and total fisheries production in the long run. We conclude that climate change and political stability impact agricultural production in Africa.

The climate is changing due to higher concentrations of greenhouse gases. If concentrations continue to increase, climate models project climate change in this century, with significant impacts on many human sectors, and particularly agriculture. Agriculture is a fundamental production sector for society, especially for large population countries such as China. Wheat is the second most important crop in China. Therefore, using climate change projections and crop models in order to understand the impacts of climate change on Chinese agriculture, especially on winter wheat, is extremely helpful to policy makers and international agencies. CERES-Wheat, a dynamic process crop growth model, will be calibrated and validated for current production at ten sites in the major winter wheat-growing region of China-Yellow Huai-Hai plain. Using two Global Climate Models, it will then be used to simulate production changes under IPCC SRES A2 and B2 climate change scenarios. Simulations will consider impacts for rainfed and irrigated winter wheat, with and without CO2 fertilization. Simulation results indicated the possibility of significant impacts of climate change on winter wheat production in this region, with marked differences between rainfed and irrigated production. In conclusion, this exercise successfully tested the applicability of standard climate change impact assessment methodology to an important production region of China.

Africa is thought to be the region most vulnerable to the impacts of climate variability and change. Agriculture plays a dominant role in supporting rural livelihoods and economic growth over most of Africa. Three aspects of the vulnerability of food crop systems to climate change in Africa are discussed: the assessment of the sensitivity of crops to variability in climate, the adaptive capacity of farmers, and the role of institutions in adapting to climate change. The magnitude of projected impacts of climate change on food crops in Africa varies widely among different studies. These differences arise from the variety of climate and crop models used, and the different techniques used to match the scale of climate model output to that needed by crop models. Most studies show a negative impact of climate change on crop productivity in Africa. Farmers have proved highly adaptable in the past to short- and long-term variations in climate and in their environment. Key to the ability of farmers to adapt to climate variability and change will be access to relevant knowledge and information. It is important that governments put in place institutional and macro-economic conditions that support and facilitate adaptation and resilience to climate change at local, national and transnational level.

Review of literature related to the impact of climate change on maize (Zea mays L.) yield using Global Climate Models (GCMs), statistical downscaling, and crop simulation (APSIM-maize-and-CERES-maize models) models are discussed. GCMs can simulate the current and future climatic scenarios. Crop yield projections using crop models require climate inputs at higher spatial resolution than that provided by GCMs. The computationally inexpensive statistical downscaling technique is widely used for this translation. Studies on regional climate modeling have mostly focused on Southern Africa and West Africa, with very few studies in Zambia. Additionally, the integrated use of climate and crop models have received relatively less attention in Africa compared to other parts of the world. Conversely, the AgMIP protocols have been implemented in Sub-Saharan Africa (SSA) (Ethiopia, Kenya, Tanzania, Uganda and South Africa) and South Asia (SA) (Sri Lanka). In Zambia, however, the protocols have not been applied at either regional or local scale. Applying crop and statistical downscaling models requires calibration and validation, and these are crucial for correct climate and crop simulation. The review shows that although uncertainties exist in the design of models, and parameters, soil, climate and management options, the climate would adversely affect maize yield production in SSA. The potential effect of climate change on maize production can be studied using crop models such as agricultural production simulator (APSIM) and decision support system for agrotechnology (DSSAT) models. There is need to use integrated assessment modeling to study future climate impact on maize yield. The assessment is essential for long-term planning in food security and in developing adaptation and mitigation strategies in the face of climate variability and change. Key words: Review, AgMIP, climate scenario, climate change, variability, crop simulation model, bias correction, dynamical downscaling, Global Climate Model (GCM), statistical downscaling.