Abstract
The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health.
Highlights
The wild boar (Sus scrofa, L. 1758) is a generalist and opportunistic species found from western Europe and the Mediterranean Basin to eastern Russian Federation and Japan, throughout
We present a geostatistical method based on regression modelling and area-to-point residual kriging to disaggregate wild boar statistics, map and predict its abundance from spatially heterogeneous administrative units to high resolution raster maps at 5 km using climatic and environmental covariates
The wild boar population density was estimated from western Europe to central-northern Asia (Fig 1)
Summary
Due to a combination of biological (i.e., species ecological plasticity, high reproduction rate), environmental (i.e., climate change, mild winters), and anthropogenic factors (i.e., depopulation of rural areas, reintroduction, lack of large natural predators, change in agricultural practices, reduced hunting pressure, supplementary feeding and other husbandry practices), the abundance of the wild boar has continuously increased over the last decades and its distribution expanded across the whole geographic range [3,4,5,6]. The involvement of the species in the recent expansion and persistence of African swine fever in eastern Europe and the Caucasus, despite control efforts, has attracted considerable international attention, stressing the difficulties of managing animal diseases in wild populations [10]
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