Crop yield response to climate change varies with cropping intensity

Challinor, Andrew J.; Parkes, Ben; Ramírez-Villegas, Julián

doi:10.1111/gcb.12808

Cited by 68 publications

(48 citation statements)

References 54 publications

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“…A second meta-analysis by Challinor et al (2014) presents results by temperature change; our results at 1.5 K are within the range of results found in their analysis. The multi-model ensemble yield results contain two sources of uncertainty, the IAV and the variability across the meteorological input datasets.…”

Section: Crop Model Resultssupporting

confidence: 84%

“…The largest increase is found for the linear models and is 4.2 % for millet. This range of results is within the range found for tropical maize in Challinor et al (2014). ORCHIDEE-CROP replicates the observed IAV, in contrast with the other process-based models, GLAM and SARRA-H.…”

Section: Discussionsupporting

confidence: 85%

“…The yield changes are not consistent across national borders and some nations are expected to lose more than others. The yield gains predicted herein need to be considered as part of longer-term trends that show severe yield reductions as the 21st century progresses (Challinor et al, 2014;Knox et al, 2012). As global temperatures approach 1.5 K above the pre-industrial levels, the knowledge of the most effective adaptation methods becomes critical and therefore it is of high importance to develop models capable of simulating them.…”

Section: Discussionmentioning

confidence: 99%

“…The temperature changes were locally analysed and grouped independent of carbon dioxide fertilization of global climate conditions. Tropical maize was found to experience a decline in yields as temperatures increase for both studies with and without adaptation (Challinor et al, 2014). There are multiple potential adaptation methods to ameliorate the impacts of climate change, a non-exhaustive list contains intercropping, changing the variety or species grown, and use of fertilizers and crop rotation to replenish nutrients in the soil.…”

Section: Introductionmentioning

confidence: 99%

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Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

et al. 2018

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Abstract. The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes?An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) and a near-term future when global temperatures are 1.5 K above preindustrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates.Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively.The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

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Section: Crop Model Resultssupporting

confidence: 84%

Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

et al. 2018

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“…These land use changes are the result of a complex set of drivers, including, inter alia, climate policy [123] and food demand [124]. Land use changes can also have implications for the skill of crop models [125].…”

Section: Future Trends and Challengesmentioning

confidence: 99%

Contribution of Remote Sensing on Crop Models: A Review

et al. 2018

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Abstract:Crop growth models simulate the relationship between plants and the environment to predict the expected yield for applications such as crop management and agronomic decision making, as well as to study the potential impacts of climate change on food security. A major limitation of crop growth models is the lack of spatial information on the actual conditions of each field or region. Remote sensing can provide the missing spatial information required by crop models for improved yield prediction. This paper reviews the most recent information about remote sensing data and their contribution to crop growth models. It reviews the main types, applications, limitations and advantages of remote sensing data and crop models. It examines the main methods by which remote sensing data and crop growth models can be combined. As the spatial resolution of most remote sensing data varies from sub-meter to 1 km, the issue of selecting the appropriate scale is examined in conjunction with their temporal resolution. The expected future trends are discussed, considering the new and planned remote sensing platforms, emergent applications of crop models and their expected improvement to incorporate automatically the increasingly available remotely sensed products.

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Exploration of the cropping pattern based on the irrigation water–energy–food and carbon emission nexus

Chand,

Bimali

2023

Irrigation and Drainage

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This study examined the existing cropping patterns, yield, irrigation water and energy use and carbon emission responses to explore the best cropping pattern based on the optimum water–energy–food and carbon emission nexus. The study consisted of field visits, questionnaire surveys among 510 farmers, 10 key informant interviews, one focused group discussion and subsequent analysis of collected data. The result of the research indicated that the best existing cropping pattern was rice–wheat–no crops with a net benefit of USD 491 ha⁻¹, benefit–cost ratio: 1.33, water use: 8830 m3 ha⁻¹, energy use: 43 GJ ha⁻¹ and carbon emission: 2420 kg CO2‐eq ha⁻¹. This study found spring rice to be the most appropriate agricultural commodity in the third season of the crop calendar and rice–wheat–spring rice, as the recommended cropping pattern in the selected area based on maximum production: 13.3 t ha⁻¹, the largest net income: USD 668 ha⁻¹, the highest benefit‐cost ratio: 1.27 and the least use of energy 802 GJ ha⁻¹ with release of3840 kg CO2‐eq ha⁻¹ of carbon. After applying the recommended cropping pattern of this study, there will be significant growth in the benefit per unit use of water and energy and a substantial reduction in carbon emission per tonne of food production.

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Crop yield response to climate change varies with cropping intensity

Abstract: Abstract

Cited by 68 publications

References 54 publications

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

Contribution of Remote Sensing on Crop Models: A Review

Exploration of the cropping pattern based on the irrigation water–energy–food and carbon emission nexus

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