Moving Matters: The Effect of Location on Crop Production

Beddow, Jason M.; Pardey, Philip G.

doi:10.1017/s002205071500008x

Cited by 36 publications

(18 citation statements)

References 39 publications

(41 reference statements)

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“…This association has a particularly vital implication given the relatively large marginal effects estimated for this region. These results are also in line with the historical movements of corn location discussed [26,27]. Average precipitation (March, April, May, June) are found to be negatively related to corn yields because preplanting time and during planting time precipitation adversely effects crop yield.…”

Section: Resultssupporting

confidence: 82%

Weather and Crop Management Impact on Crop Yield Variability

Parvez¹,

Chowdhury

2020

Agriculture and Food Sciences Research

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This research is primarily designed to examine crop yield variation due to change in weather pattern and crop management activities by exploring a comprehensive list of factors (e.g. environmental, economic etc.). Given that existing literature indicates significant effects when farmland value is regressed on weather variables, a natural question is to ask whether major agricultural crop yields responds to change in historical weather pattern. To answer this question, this study relies on a state level panel dataset including agricultural and high-resolution weather data covering the period 1997-2018. Using a Seemingly Unrelated Regression (SUR) approach, this study estimates how crop spatial distribution patterns have impacted crop yield variation in response to weather in United States Greater Midwest region. Key findings indicate that changes in crop management activities correspond closely to estimate of both crop price and weather effects. Additionally, corn yield response to weather change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Further, revenue of corn, soybeans, wheat and their respective lagged yields have positive and significant effect to respective crop yields. Finally, a major crop yield does vary across region due to variation of crop prices, precipitation and temperature. These findings have useful implications for agriculture sector on how historical weather trends have affected crop yield and distribution pattern.

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Section: Resultssupporting

confidence: 82%

Weather and Crop Management Impact on Crop Yield Variability

Parvez¹,

Chowdhury

2020

Agriculture and Food Sciences Research

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“…national or supra-national regions). General shifts of cropping areas towards higher productive areas are very likely (Beddow and Pardey, 2015) as can be investigated by land use models, which project changes in land use and production as socio-economic responses to changes in agricultural productivity. Future land use uncertainty can also be addressed by aggregating simulated changes in productivity with external land use scenarios as in Pugh et al (2015) and remain a challenge for further crop modeling studies.…”

Section: Discussionmentioning

confidence: 99%

Spatial and temporal uncertainty of crop yield aggregations

Porwollik

Müller

Elliott

et al. 2017

European Journal of Agronomy

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“…For example, CELL5M has been utilized to define and characterize study areas ( e.g ., van Wart et al , 2013); estimate market travel times ( e.g. , Damania et al , 2016); explore geography changes in crop production ( e.g ., Beddow & Pardey, 2015); calculate local agricultural commodity prices ( e.g. , Fjelde, 2015); map the threat of potential plant diseases ( e.g ., Kriticos et al , 2015); model climate change adaptations in agriculture ( e.g ., Robinson et al , 2015); and as a general data framework ( e.g.…”

Section: Cell5m Use-casesmentioning

confidence: 99%

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara

et al. 2016

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Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M—an open-access database of geospatial indicators at 5 arc-minute grid resolution—and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

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Moving Matters: The Effect of Location on Crop Production

Cited by 36 publications

References 39 publications

Weather and Crop Management Impact on Crop Yield Variability

Weather and Crop Management Impact on Crop Yield Variability

Spatial and temporal uncertainty of crop yield aggregations

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara

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