Benefit To Soybean Farmers
Deer are the leading cause of crop damage by wildlife in Maryland, with most recent government estimates showing approximately $10 million in losses annually, with 77% of those losses attributable to deer (USDA NASS 2011). Maryland in particular faces greater challenges than many other soybean growing areas in the country due to smaller field sizes that are more often interspersed with and bordered by forested areas that provide refuge for deer, which emerge to graze highly palatable and nutritious soybeans. Farmers have regularly identified deer and wildlife damage as one of their top concerns, and frustrations by farmers are well documented in news media articles. Soybean yields in 2020 in certain fields at the Wye Research & Education Center in Queenstown, MD, were reduced by 20-30 bushels per acre in a field bordering a forested area. While hunting and crop damage permits allow some farmers to reduce deer population densities, some locations are not amenable to this due to factors such as landowners or neighbors that do not allow hunting, nocturnal grazing activity, and time required to harvest sufficient numbers of deer.
In 2021 and 2022, we engaged in research to better understand deer preferences and plant response in heavily damaged agricultural fields. In 2021, the study found a surprising performance of a less expensive Group 4.7 forage soybean, GT1 Brier Ridge from Lacrosse Seed as one of the higher performing varieties just after a Group 5.3 conventional soybean. These yields were considered by the farm manager as one of the best yields he’s observed out of these fields in many years. In 2022, we continued this work with an enhanced study design and greater numbers of wildlife trail cameras to monitor deer activity. We augmented this with a simulated grazing experiment for each of the varieties and monthly forage analysis. The results of 2022 study are forthcoming. We have begun to analyze deer grazing activity patterns against weather variables to try to predict the spikes in deer grazing we observed in the fields. Initial analysis suggests that rainfall in the prior 1-2 days is a significant predictor of deer grazing activity, and we plan to augment the analysis to incorporate wind and other factors.