Abstract
Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes–recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity–yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making.
Highlights
Due to the difficulty in sampling ecological data at sufficient spatial and temporal resolutions, many ecological studies rely on the use of surrogates to understand species distribution and ecological processes
Without necessarily contributing to this debate, the current study confirmed that results gained from the artificial fractal surfaces in Lecours et al [4] hold when using a DTM representation of a real terrain (i.e. German Bank) at another spatial scale. It confirmed the appropriateness of the proposed framework for selecting terrain attributes and its application to any terrestrial and marine ecological application, regardless of the scale of the environmental data
Selecting the most appropriate environmental variables to use in a specific study can be very challenging
Summary
Due to the difficulty in sampling ecological data at sufficient spatial and temporal resolutions, many ecological studies rely on the use of surrogates to understand species distribution and ecological processes. Terrain attributes (e.g. slope, rugosity, aspect) derived from digital elevation (DEM) or bathymetric (DBM) models have proven their value in a broad range of terrestrial and marine ecological studies [1]. Such attributes can be derived using tools available in most Geographic Information Systems (GIS). Software developers and authors of published work are often not explicit on the methods they use to derive terrain attributes (e.g. algorithm or tool) This lack of information can possibly influence the analysis and interpretation of the resulting terrain attribute surfaces, and the ecological application for which they are being used
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