Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas

Assessing habitats and organism-habitat relationships by airborne laser scanning

Three-dimensional structure is a fundamental physical element of habitat. Because of the well-recognised link between vegetation structure and organism-habitat associations, many published studies that make use of airborne LiDAR for forest applications have results of potential relevance for habitat assessment. This chapter reviews those published studies that have made direct use of airborne LiDAR data for habitat assessment of individual species or groups of species in a woodland or forest context. This is followed by a case study of the authors’ own work at a study site in eastern England, Monks Wood National Nature Reserve. We conclude that airborne LiDAR has the capability for supplying a range of forest structural measures that are key elements of an organism’s habitat at the meso-scale. Examined in combination with detailed field ecology data on species distributions, abundances or biological activity, airborne LiDAR data can be used as an exploratory tool to advance ecological understanding by quantifying how forest structure impacts habitat use and thereby influences habitat quality