Evaluation of buffer-radius modelling approaches used in forest conservation and planning

Spatial modelling approaches are increasingly being used to direct forest management and conservation planning at the landscape scale. A popular approach is the use of buffer-radius methods, which create buffers around distinct forest habitat patches to assess habitat connectivity within anthropogenic landscapes. However, the effectiveness and sensitivity of such methods have rarely been evaluated. In this study, Euclidean and least-cost buffer-radius approaches were used to predict functional ecological networks within the wooded landscape of the Isle of Wight (UK). To parameterize the models, a combination of empirical evidence and expert knowledge was used relating to the dispersal ability of a model species, the wood cricket (Nemobius sylvestris Bosc.). Three scenarios were developed to assess the influence of increasing the amount of spatial and species-specific input data on the model outcomes. This revealed that the level of habitat fragmentation for the model species is likely to be underestimated when few empirical data are available. Furthermore, the least-cost buffer approach outperformed simple Euclidean buffer in predicting presence and absence for the model species. Sensitivity analyses on model performance revealed high sensitivity of the models to variation in buffer distance (i.e. maximum dispersal distance) and permeability of common landscape features such as roads, watercourses, grassland and semi-natural habitat. This indicates that when data are lacking with which to parameterize buffer-radius models, the model outcomes need to be interpreted with caution. This study also showed that if sufficient empirical data are available, least-cost buffer approaches have the potential to be a valuable tool to assist forest managers in making informed decisions. However, least-cost approaches should always be used as an indicative rather than prescriptive management tool to support forest landscape conservation and planning.