The assessment of wildlife damage estimation methods in maize with simulation in GIS environment

Abstract

Wildlife damage to agriculture causes significant economic losses worldwide. The amount of compensation payment is often determined by field damage evaluation, but there is little statistically sound information on the applied sampling and calculation methods of such losses. In this study, we tested the accuracy and bias of V-Track Method (VTM), W-Track Method (WTM), Double Diagonal Method (DDM), and Grid Arrangement Method (GAM) in GIS environment. Besides the accuracies and biases, the effects of the rate and spatial distribution of the damage (and the interaction of these factors) on the sampling results were examined. Simulations were conducted with four different spatial damage patterns [random, aggregated in patches (DAinP), furthermore aggregated in one and two field edges (DAinE-1, DAinE-2) to simulate the effect of an adjacent forest on the damage caused by big game species] and three levels of damage (10%, 20%, 30%). According to our results, the GAM provided the majority (58.3%) of best results for each statistical parameter (28/48), while gave the worst result three times. The WTM resulted in the highest number (17/48) of worst values and 8/48 best results. The DDM gave 14/48 poorest values, while provided 7/48 best results. The VTM resulted in 14/48 worst values, while provided the best result five times. The rate and spatial distribution of the damage, as well as the interaction of these factors, had a significant effect on the Percentage Relative Bias of the VTM, WTM and DDM estimations, while the GAM sampling was significantly affected only by the damage distribution.