A First Attempt at Modelling Roe Deer ( Capreolus capreolus ) Distributions Over Europe

(2) Methods Steps Binary presence and absence Five independent sets of distribution data were combined to produce a single presence absence mask. The data sets used were as follows: • The EMMA Database [2]: Mapping Europe’s mammals using data from the Atlas of European Mammals • The Global Biodiversity Information Facility (GBIF) [3] • IUCN Red List Dataset [4] • The National Biodiversity Network [5] UK 10k Data • Spanish Ministry of Agriculture National Inventory of Biodiversity [6]

Five independent sets of distribution data were combined to produce a single presence absence mask.The data sets used were as follows: • The EMMA Database [2]: Mapping Europe's mammals using data from the Atlas of European Mammals • The Global Biodiversity Information Facility (GBIF) [3] • IUCN Red List Dataset [4] • The National Biodiversity Network [5] UK 10k Data • Spanish Ministry of Agriculture National Inventory of Biodiversity [6] Habitat definition For much of the indicated range the distributions detailed above were, by their nature, simple presence limits.Within these designated boundaries there was no indication of absence.In order to introduce absences within these limits, suitability masks were defined using species-specific habitat preferences derived from land cover classes, using GLOBCOVER [7] at 1 km resolution.The habitats were defined as more than 10% Woodland, and neither urban nor peri-urban, according to Tapper(1999) [8], and is thus somewhat UK centric To allow for behaviours where deer utilise pasture/heathland/grassland close to woodland shelter we also defined as suitable habitat areas where grassland/heathland occurred within 1km of a cell with sufficient woodland (Searle, personal communication).The 300m GLOBCOVER dataset was reclassified three times for woodland = 1 and other = 0; for urban areas = 0

DATA PAPER
A First Attempt at Modelling Roe Deer (Capreolus capreolus) Distributions Over Europe by the VMERGE Steering Committee as VMERGE001 (http://www.vmerge.eu).The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.
The presence of roe deer can be an important component within ecological and epidemiological systems contributing to the risk and spread of a range of vector-borne diseases.Deer are important hosts for many vectors, and may therefore serve as a focal point or attractant for vectors or may themselves act as a reservoir for vector-borne disease.Three spatial modelling techniques were used to generate an ensemble model describing the proportion of suitable roe deer habitat within recorded distributions for Europe as identified from diverse sources.The resulting model is therefore an index of presence, which may be useful in supporting the modelling of vector-borne disease across Europe.other = 1 and for grassland & pasture = 1 other = 0 as per Table 1.The three layers were each aggregated to 1km, and then Suitable habitat was defined as a) those cells containing more than 10% woodland but no urban area; or b) grassland cells next to otherwise suitable habitat.All data processing was undertaken in ESRI ArcGIS 10.0.
The 1km resolution habitat suitability masked data was then combined with the presence data and converted to a percentage of suitable habitat at a 20km resolution.

Model predictor suite
The spatial modelling requires a comprehensive predictor variable suite that included a wide range of remotely sensed variables as follows: • Human population density derived from the Global Rural Urban Mapping project at CEISIN [14] • A distance weighted human population index layer [15] representing the likelihood of human visits based on the population within 30km.
systems-based approach to modelling deer abundance at a country scale.