Editor’s Choice: Assessing biodiversity by remote sensing in mountainous terrain

Abstract

Müller, J. & Brandl, R. (2009) Assessing biodiversity by remote sensing in mountainous terrain: the potential of LiDAR to predict forest beetle assemblages. Journal of Applied Ecology, 46, 897–905. The development of effective conservation management requires accurate information on the spatial distribution of biodiversity. This information underpins almost all aspects of systematic conservation planning and priority-setting exercises, from reserve design to ecological-economic zoning (Margules & Pressey 2000). However, biodiversity data can be expensive to collect and is often limited by the availability of appropriate taxonomic expertise (Gardner et al. 2008). Furthermore, biodiversity surveys often take place on relatively small spatial scales, while decisions about land-use and conservation often involve areas many orders of magnitude larger, which would be impossible to cover in biodiversity assessments. As a result, it has been increasingly common to use remote sensing to help fill the gap between biodiversity surveys and decision-making. While a number of remote-sensing methods are available, most attention has been directed towards satellite-derived information that operates at fairly coarse spatial scales, assessing land cover change or ecosystem degradation (e.g. Asner et al. 2005). More recently, airborne imagery has received increased attention, mostly focusing on the vegetation as the most visible portion of terrestrial biodiversity (e.g. Carlson et al. 2007) or simple metrics of avian species richness (Goetz et al. 2007). Müller & Brandl (this issue) take a novel approach using Light Detection And Ranging (LiDAR)-derived variables to model both the species richness and composition of forest-dwelling beetles in a mountainous region of south-eastern Germany. LiDAR is based on the use of laser light that is emitted from a source (normally an aircraft) and reflected back to a sensor, providing proxy variables of the structural diversity of the forest, including the density of the canopy layer, forest gaps and elevation (Lefsky et al. 2002). The study by Müller & Brandl is one of the first to attempt to link this remotely sensed data with arthropod communities, and all aspects of this study were impressive in their extent and rigour. The ground surveys alone recorded 50 910 beetles (composed of 782 species) at the 171 sampling stations, while the LiDAR measurements were complemented by a detailed suite of habitat measurements recorded from the ground at each of the sampling points. Moreover, the study took place in difficult mountainous terrain – exactly the kind of region where remotely sensed biodiversity surrogates are likely to be most useful. The results demonstrate the high predictive power of LiDAR-derived variables, which captured most of the predictive power of the environmental variables that were measured during the ground surveys. The relationships observed between the LiDAR data and beetle community patterns are striking, and show a surprisingly high degree of correspondence, suggesting that airborne laser scanning can be used to map faunal biodiversity in some forested regions. Furthermore, the LiDAR survey appears to be a cost-effective solution to the scarcity of biodiversity data: in total, the LiDAR mapping cost just 5% of the cost of sampling beetles in the field, when area was taken into consideration. In summary, this study provides real hope that LiDAR can become an integral part of the toolkit used by conservation scientists, allowing conservation managers to predict the species richness and composition of assemblages at scales relevant for planning and management. However, the authors are careful not to lose sight of the importance of robust ground-truthing. Remote sensing is not an alternative to field surveys, which form the basis for any extrapolation exercise, and are absolutely essential whenever these techniques are used in different regions or for different faunal taxa.