|Reyes, Julian Jon|
Submitted to: Environmental Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/18/2019
Publication Date: 7/1/2019
Citation: Reyes, J.T., Elias, E.H. 2019. Spatio-temporal variation of crop loss in the United States from 2001 to 2016. Environmental Research Letters. 14:074017. https://doi.org/10.1088/1748-9326/ab1ac9.
Interpretive Summary: Agriculture is drive by complex interactions at multiple spatial and temporal scales. Crop insurance payments provides additional information on how weather and climate affect both bipohysical and socio-economic conditions of agricultural systems and vulnerabilities. Here, we performed an analysis of crop loss data from the Risk Management Agency of the United States Department of Agriculture. We analyzed these data using different normalization methods to account for changes in crop prices and program policy changes. We found that drought and excess rainfall were the top causes of loss over the nation. However, these causes of loss also varied by region and through time. Differential trends in loss cost demonstrate the importance of spatio-temporal resolution when using crop loss data. The magnitude and direction of such trends suggest possible future vulnerabilities in agricultural production systems given past crop losses.
Technical Abstract: Crop insurance loss data can illuminate variations in agricultural impacts from exposure to weather and climate-driven events, and can improve our understanding of agricultural vulnerabilities. Here we perform a retrospective analysis of weather and climate-driven reasons for crop loss (i.e. cause of loss) obtained from the Risk Management Agency of the United States Department of Agriculture. The federal crop insurance program has insured over $440 billion in liabilities representing farmers' crops from 2001 to 2016. Specifically, we examine the top ten weather and climate-driven causes of loss from 2001 to 2016 across the nation comprising at least 83% of total indemnities (i.e. insurance payouts provided to farmers after crop loss events). First, we analyzed the relative fraction of indemnities by causes of loss, over different spatial and temporal resolutions. We found that drought and excess precipitation comprised the largest sources of crop loss across the nation. However, these causes varied strongly over space and time. We applied two additional normalization techniques to indemnities using (1) insurance premia and the gross domestic product implicit price deflator, and (2) liabilities to calculate the loss cost. We conducted trend analyses using the Mann–Kendall statistical test on loss cost over time. Differential trends and patterns in loss cost demonstrated the importance of spatio-temporal resolution in assessing causes of loss. The majority of monthly significant trends (p < 0.05) showed increasing loss cost (i.e. increasing indemnities or decreasing liabilities) in response to weather events. Finally, we briefly discuss an online portal (AgRisk Viewer) to make these data accessible at multiple spatial scales and sub-annual time steps to support both research and outreach efforts promoting adaptation and resilience in agricultural systems.