4.7 Article

Estimation of wildlife damage from federal crop insurance data

期刊

PEST MANAGEMENT SCIENCE
卷 77, 期 1, 页码 406-416

出版社

JOHN WILEY & SONS LTD
DOI: 10.1002/ps.6031

关键词

crop damage; federal crop insurance; wildlife damage; fractional regression

资金

  1. U.S. Department of Agriculture, Animal Plant and Health Inspection Services

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A new method utilizing federal crop insurance data was used to estimate wildlife damage to major crops in the USA from 2015 to 2019. The study identified eastern and southern regions as most susceptible to wildlife damage, with soybeans and corn incurring the highest losses.
BACKGROUND Wildlife damage to crops is a persistent and costly problem for many farmers in the USA. Most existing estimates of crop damage have relied on direct assessment methods such as field studies conducted by trained biologists or surveys distributed to farmers. In this paper, we describe a new method of estimating wildlife damage that exploits federal crop insurance data. We focused our study on four crops: corn, soybean, wheat, and cotton, chosen because of their economic importance and their vulnerability to wildlife damage. RESULTS We determined crop-raiding hot spots across the USA over the 2015-2019 period and identified the eastern and southern regions of the USA as being the most susceptible to wildlife damage. We estimated lower bounds for dollar and percent losses attributable to wildlife to these four crops. The combined loss across four crops was estimated at $592.6 million. The highest total estimated losses to wildlife were incurred by soybeans ($323.9 million) and corn ($194.0 million) and the highest percentage losses were estimated for soybeans (0.87%) and cotton (0.72%). CONCLUSION We believe the proposed method is a reliable way to evaluate geographic and temporal heterogeneity in damages for the coming years. Accurate information on damages benefits various management agencies by allowing them to allocate management resources to crops and regions where the problem is relatively severe. A better understanding of damage heterogeneity can also help guide research and development of new management techniques.

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