ENETwild modelling of wild boar distribution and abundance: initial model output based on hunting data and update of occurrence‐based models

Lingua Undefined

Published on: Fri, 03 May 2019

After presenting preliminary models to estimate the habitat suitability for wild boar in MSs and neighbouring countries as a proxy for its relative abundance (i.e. the relative representation of a species in a particular ecosystem, a kind of proxy of the density) the ENETWILD consortium has developed further models for the estimation of wild boar abundance across this extent based on hunting yields (HY). This report therefore presents: i) updated maps of habitat suitability at 10x10 km resolution based on newly available data of wild boar occurrence together with new analysis to test the feasibility of performing such analysis at higher resolution (2x2 km); and, ii) a new model for predicting wild boar relative abundance, also at 10x10 km resolution, using hunting yields. The results of the occurrence model show that more occurrence data are required for specific locations in Eastern Europe in order to ensure robust model prediction of habitat suitability and consequently wild boar distribution. We used the hunting yields model to identify the environmental drivers of species abundance at European scale and fitted separate models for three regions (Southern, Western and Eastern Europe) to predict the distribution of wild boar at 10x10 km resolution. Our initial results highlighted some methodological issues relating to the statistical downscaling that should be taken into account to improve the reliability of the predictions. Whilst the spatial pattern in some areas was similar when comparing the predictions from both the occurrence and abundance models, in other regions there were marked discrepancies. To improve the models it is recommended to i) collect more occurrence data in the North‐Eastern region of Europe, in particular on survey effort; ii) combine regional and local hunting records to validate hunting yield predictions to higher spatial resolutions; and, iii) incorporate new environmental variables, especially those closely associated with wild boar abundance and distribution.