Analysis of game damage estimation methods in winter wheat (Triticum aestivum) thruogh GIS simulations

Absztrakt

Wildlife damage to agriculture causes significant economic loss worldwide annually. Game managers or hunters are responsible for the financial compensation of the crop damage caused by game species in several countries, including Hungary. Accredited experts estimate the level of the damage; however, currently, there are no standardised methods that would be obligatory to apply. In order to obtain information on the accuracy and bias of the different sampling methods, we designed GIS simulations in winter wheat (Triticum aestivum), which covers a significant proportion of the arable land not only in Hungary, but also globally.

We tested two sampling methods with three sampling plot arrangements in a GIS environment. Our questions were the following: (1) How accurate and biased are the examined samplings? (2) Does the rate or the spatial distribution of the damage (or the interaction of these factors) affect the results of the investigated methods?

We created 15 wheat field models with 1:2 side ratio, 12 cm row width and the area of 3 ha. We simulated 5 damage rates (10%, 30%, 50%, 70%, 90%) and 3 spatial damage patterns [random, aggregated in 1 and 2 field edges], of which the latter two follow the actual pattern of crop damage caused by big game species. V, W and X sampling tracks were allocated on each field model, and then they were sampled with square shaped, 1 m² quadrats and 1 m long row sections (with 5 repetitions). The sample size was 20 and 25 plots, respectively (determined by the original description of the methods). At the sample plots, the total number of plants and the number of damaged plants were counted.

According to our results, the statistical parameters of the different samplings were similar; the difference between the best and the poorest values was low. The rate and spatial distribution of the damage, as well as their interaction,  had a significant effect on the estimation of each quadrat sampling, while the row sections were significantly affected only by the damage distribution (V and W tracks) or the damage rate (X track).

According to our findings however, the difference between the labour-intensity of the two approaches can be decisive. With the sample sizes in our study, remarkably lower number of plants had to be examined along the row sections, than in the quadrats. This suggests that the experts can obtain similar quality results with less effort, if they choose the row section sampling over the quadrats.