Understanding how habitat, landscape context, and human disturbance influence local species-specific deer density provides evidence informing strategic management of increasing deer populations. Across an extensive (187 km 2) heterogeneous forest-mosaic landscape in eastern England, spatially explicit density surface models of roe deer Capreolus capreolus and introduced muntjac Muntiacus reevesi were calibrated by thermal imaging distance sampling (recording 1590 and 400 muntjac and roe deer groups, respectively, on 567 km of driven transects). Models related deer density to local habitat composition, recreational intensity, and deer density (roe deer models controlled for muntjac density and vice versa) at a local grain across 1162 composite transect segments, incorporating geographical coordinates accounting for spatial autocorrelation. Abundance of both species was lower in localities with more grasslands (inter-quartile, IQ, effect size: roe −2.9 deer/km 2; muntjac −2.9 deer/km 2). Roe abundance (mean = 7 deer/km 2, SD = 6) was greater in localities with more young stands (IQ effect size, + 1.3 deer/km 2) and lower at localities with more recreationists (−1.1 deer/km 2). Muntjac density (mean = 21 deer/km 2, SD = 10) was greater in localities with more recreationists (+ 2.4 deer/km 2), with more mature (≥ 46 years) stands (+ 1.5 deer/km 2), or calcareous soil (+ 7.1 deer/km 2). Comparison of models incorporating candidate variables and models comprising geographical coordinates only shows candidate variables to be weak predictors of deer densities. Adapting forest management to manipulate habitat and recreational access may influence local deer densities, but only subtly: effect sizes are not sufficient to mitigate deer impacts through planting vulnerable tree crops in areas avoided by deer. Effective culling remains the most viable management option.
- Forest management
- Introduction biology
- Landscape-scale deer management
- Species-habitat model
- Sustainable hunting