Identifying the Risk Regions of Wild Boar (Sus scrofa) Incidents in China

Abstract

The objectives of this study were to identify the risk regions of wild boar incidents in China and to draw a risk map. Risk maps can be used to plan the prioritization of preventive measures, increasing management effectiveness from both a short- and a long-term perspective. We used a web crawler (web information access technology) to obtain reports of wild boar incidents from China’s largest search engine (Baidu) and obtained 196 valid geographic locations of wild boar incidents from the reports. Subsequently, a system of environmental variables—with climate, topography, landscape, and human disturbance as the main variable types—was constructed, based on human–land-system thinking. Finally, the Maxent model was applied to predict the risk space of wild boar incidents in China by integrating the geographic location information for wild boar incidents with the environmental variables. We observed that the types of environmental variables that contributed to wild boar incidents were in the descending order of climate (40.5%) > human disturbance (25.2%) > landscape (24.4%) > topography (9.8%). Among the 14 environmental variables, annual precipitation, the GDP index, and the mean annual temperature were the main environmental variables. The distance from woodland, distance from cultivated land, and elevation were the secondary environmental variables. The response curves of the environmental variables demonstrated that the highest probability of wild boar incidents occurred when the annual average temperature was 16 °C, the annual precipitation was 800 mm, and the altitudes were 150 m and 1800 m. The probability of wild boar incidents decreased with an increase in the distance from cultivated and forested land, and increased sharply and then levelled off with an increase in the GDP index. Approximately 12.18% of China was identified as being at a high risk of wild boar incidents, mainly on the eastern side of the Huhuanyong Line.

Human–Wildlife Conflict Mitigation Based on Damage, Distribution, and Activity: A Case Study of Wild Boar in Zhejiang, Eastern China

“…In order to mitigate human–wildlife conflicts, it is important to understand the spatial and temporal distribution and loss caused by human–wildlife conflicts [ 43 ] and predict the potential distribution areas of human–wildlife conflicts [ 22 , 44 ]. In the current study, we collaborated with the local forestry management department to conduct a wild boar damage survey across all districts and counties (n = 90) of Zhejiang Province.…”

“…In comparison to compensatory management, which often focuses on addressing emergency conflicts, precautionary management allows decision-makers to better understand wildlife itself, such as where the damage is distributed, how the species are distributed and when the species conduct their activity [ 17 ]. Many studies on human–wildlife conflict have focused on the regional conflict status [ 18 , 19 ], mitigation measure development [ 20 , 21 ], the identification and prediction of risk areas [ 7 , 22 ], the cognition and tolerance of residents [ 23 , 24 ] and other areas, including both single aspects and multiple aspects. Moreover, adding a social perspective (identification tolerability and other key factors), public participation and shared governance could provide other perspectives in mitigation management [ 25 ].…”