scholarly journals Assessment of climate change impacts on agriculture in Mali

2021 ◽  
Vol 9 (1) ◽  
pp. 313-329
Author(s):  
Tiémoko SOUMAORO
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Agricultural Research ◽  
Climate Change Impacts ◽  
Maize Yield ◽  
Spillover Effects ◽  
Temperature And Precipitation ◽  
Negative Impacts ◽  
Surrounding Areas ◽  
Millet Yield

This study examined the total, direct and indirect effects of climatic variables (temperature and precipitation) on crop yields (maize and millet) between regions located in close proximity to each other a spatial panel analysis of five administrative regions of Mali over a period of 30 years (1988-2017). Our results show that temperature and rainfall have direct, indirect and total effects on maize yield, while the direct effect on millet yield is not statistically significant. In other words, the effect on regions closely linked to region i where the change in temperature or rainfall occurred will be greater than the effect on more remote regions. In addition, the coefficient of variation of precipitation and the interaction between temperature and precipitation as well as area planted all have negative impacts on maize yield. However, millet yield is negatively correlated with drought in the study area. Based on these findings, decision-makers need to take into account that conditions in surrounding areas can influence cereal crop yields and that spillover effects differ between crop types. Investments in agricultural research and development must be encouraged to counter the effects of climate change.

scholarly journals Assessment of Climate Change Impacts on Maize Production in Mali

2021 ◽  
Author(s):  
Tiémoko SOUMAORO
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Agricultural Research ◽  
Climate Change Impacts ◽  
Spillover Effects ◽  
Local Area ◽  
Extreme Weather Events ◽  
Maize Production ◽  
Temperature And Precipitation ◽  
Maize Yields

Abstract This study examined the total, direct and indirect effects of climatic variables (temperature and rainfall) on crop yields maize in a given region and in neighbouring regions, through a spatial panel analysis of five administrative regions of Mali over a 30-year period (1988 - 2017). Our results show that temperature and rainfall have direct, indirect and total effects on maize yields. In other words, the effect on regions closely linked to the region where the change in temperature or rainfall occurred will be greater than the effect on more remote regions. In addition, the coefficient of variation of precipitation and the interaction between temperature and precipitation as well as the area sown all have negative impacts on maize yields. However, maize yields are negatively correlated with drought. This means that maize production in the local area is declining as a result of increased extreme weather events. Based on these findings, policy makers need to take into account that conditions in the surrounding areas can influence maize yields and that spillover effects differ between crop types. Investments in agricultural research and development should be encouraged to counteract the effects of climate change.

scholarly journals Challenges in simulating economic effects of climate change on global agricultural markets

2021 ◽  
Vol 166 (3-4) ◽  
Author(s):  
Angelo C. Gurgel ◽  
John Reilly ◽  
Elodie Blanc
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Agricultural Sector ◽  
Crop Yields ◽  
Agricultural Research ◽  
Climate Change Impacts ◽  
Well Being ◽  
Climate Impacts ◽  
Agricultural Markets ◽  
Crop Models

AbstractMany approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets.

scholarly journals The fingerprint of climate trends on European crop yields

2015 ◽  
Vol 112 (9) ◽  
pp. 2670-2675 ◽  
Author(s):  
Frances C. Moore ◽  
David B. Lobell
Keyword(s):  
Climate Change ◽  
Statistical Power ◽  
Crop Yields ◽  
Statistical Tests ◽  
Climate Change Impacts ◽  
Climate Trends ◽  
Temperature And Precipitation ◽  
Yield Trends ◽  
Parameter Values

Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ∼10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies.

Reassessing Climate Change Impacts on Agriculture in China

2015 ◽  
Vol 03 (02) ◽  
pp. 1550011
Author(s):  
Jie LIU ◽  
Changyi LIU ◽  
Yan WEN
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Empirical Studies ◽  
Climate Change Impacts ◽  
Adaptation Effect ◽  
Future Climate ◽  
Future Climate Change ◽  
Bias Estimation ◽  
Rcp Scenarios ◽  
Negative Impacts

Nonlinearity and adaptation effect are rarely taken into consideration in the existing literature of empirical studies on climate change impacts, which may lead to bias estimation of the impacts on agricultural production. This paper aims to reassess the impacts on crop yields (rice, wheat, and maize) by incorporating the terms of nonlinearity and adaptation into a provincial panel data model and further study the impacts of future climate change under the represented concentration pathways (RCP) scenarios. Results reveal that the historical warming temperature benefits rice but harm wheat and maize productions, and decreasing precipitation benefits rice and maize but harm wheat production. Adaptation can significantly mitigate the negative impacts. Under RCP4.5 and RCP8.0, after adaptation, the yield changes attributed to future climate change vary from 0.66% to 0.98% for rice, -0.65% to -0.84% for wheat, and -0.24 to 0.08% for maize. The shifts of means of climatic variables impose no challenge on national food security of China.

Climate change impacts on crop yields in Ethiopia

2019 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Climate Change Impacts

Climate Change Impacts on Agriculture in Latin America and the Caribbean: An Application of the Integrated Economic-Environmental Modeling (IEEM) Platform

2021 ◽  
Author(s):  
Onil Banerjee ◽  
Martin Cicowiez ◽  
Ana Rios ◽  
Cicero De Lima
Keyword(s):  
Climate Change ◽  
Labor Productivity ◽  
Latin American ◽  
Climate Change Impacts ◽  
Crop Productivity ◽  
Environmental Modeling ◽  
Sectoral Output ◽  
The Caribbean ◽  
Negative Impacts ◽  
Agricultural Yields

In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affected according to key indicators including Gross Domestic Product (GDP), international commerce, sectoral output, poverty, and emissions. Most countries experience negative impacts on GDP, with the exception of the major soybean producing countries, namely, Brazil, Argentina and Uruguay. We find that CC-induced crop productivity and labor productivity changes affect countries differently. The combined impact, however, indicates that Belize, Nicaragua, Guatemala and Paraguay would fare the worst. Early identification of these hardest hit countries can enable policy makers pre-empting these effects and beginning the design of adaptation strategies early on. In terms of greenhouse gas emissions, only Argentina, Chile and Uruguay would experience small increases in emissions.

Modeling climate change impacts on blue, green, and grey water footprints and crop yields in the Texas High Plains, USA

2021 ◽  
Vol 310 ◽  
pp. 108649
Author(s):  
Yong Chen ◽  
Gary W. Marek ◽  
Thomas H. Marek ◽  
Dana O. Porter ◽  
David K. Brauer ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Climate Change Impacts ◽  
High Plains ◽  
Grey Water ◽  
Texas High Plains

Adapting to climate change for food security in the Rift Valley dry lands of Ethiopia: supplemental irrigation, plant density and sowing date

2016 ◽  
Vol 155 (5) ◽  
pp. 703-724 ◽  
Author(s):  
A. MULUNEH ◽  
L. STROOSNIJDER ◽  
S. KEESSTRA ◽  
B. BIAZIN
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Plant Density ◽  
Maize Yield ◽  
Sowing Date ◽  
Supplemental Irrigation ◽  
Dry Spells ◽  
Negative Impacts ◽  
Improve Food Security ◽  
Impacts Of Climate Change

SUMMARYStudies on climate impacts and related adaptation strategies are becoming increasingly important to counteract the negative impacts of climate change. In Ethiopia, climate change is likely to affect crop yields negatively and therefore food security. However, quantitative evidence is lacking about the ability of farm-level adaptation options to offset the negative impacts of climate change and to improve food security. The MarkSim Global Climate Model weather generator was used to generate projected daily rainfall and temperature data originally taken from the ECHAM5 general circulation model and ensemble mean of six models under high (A2) and low (B1) emission scenarios. The FAO AquaCrop model was validated and subsequently used to predict maize yields and explore three adaptation options: supplemental irrigation (SI), increasing plant density and changing sowing date. The maximum level of maize yield was obtained when the second level of supplemental irrigation (SI2), which is the application of irrigation water when the soil water depletion reached 75% of the total available water in the root zone, is combined with 30 000 plants/ha plant density. It was also found that SI has a marginal effect in good rainfall years but using 94–111 mm of SI can avoid total crop failure in drought years. Hence, SI is a promising option to bridge dry spells and improve food security in the Rift Valley dry lands of Ethiopia. Expected longer dry spells during the shorter rainy season (Belg) in the future are likely to further reduce maize yield. This predicted lower maize production is only partly compensated by the expected increase in CO2 concentration. However, shifting the sowing period of maize from the current Belg season (mostly April or May) to the first month of the longer rainy season (Kiremt) (June) can offset the predicted yield reduction. In general, the present study showed that climate change will occur and, without adaptation, will have negative effects. Use of SI and shifting sowing dates are viable options for adapting to the changes, stabilizing or increasing yield and therefore improving food security for the future.

scholarly journals Satellites, Self-reports, and Submersion: Exposure to Floods in Bangladesh

2015 ◽  
Vol 105 (5) ◽  
pp. 232-236 ◽  
Author(s):  
Raymond Guiteras ◽  
Amir Jina ◽  
A. Mushfiq Mobarak
Keyword(s):  
Climate Change ◽  
Economic Activity ◽  
Climate Change Impacts ◽  
Objective Data ◽  
Short Term ◽  
Temperature And Precipitation ◽  
Flood Exposure ◽  
Self Reports ◽  
Term Variation

A burgeoning “Climate-Economy” literature has uncovered many effects of changes in temperature and precipitation on economic activity, but has made considerably less progress in modeling the effects of other associated phenomena, like natural disasters. We develop new, objective data on floods, focusing on Bangladesh. We show that rainfall and self-reported exposure are weak proxies for true flood exposure. These data allow us to study adaptation, giving accurate measures of both long-term averages and short term variation in exposure. This is important in studying climate change impacts, as people will not only experience new exposures, but also experience them differently.

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

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