Very high‐resolution digital elevation models: are multi‐scale derived variables ecologically relevant?

Abstract

Summary1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevance must be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0Á5 m, we generated DEM-derived variables at 1, 2 and 4 m spatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived from species composition, were assessed with multivariate generalized linear models (GLM) and mixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelled measured ambient humidity and soil moisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimum with a 2 m resolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

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“…From such high‐resolution DEMs, microsite conditions may also be derived (Leempoel et al . in press). Furthermore, a wealth of other environmental data can possibly be considered, including geological factors, vegetation types, land cover, land use or species distributions, which might also serve as proxies for trophic interactions, prey availability or pathogen pressure (Gugerli et al .…”

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“…Alternatively or additionally, environmental variables can be computed from DEMs, and used as proxies to relevant ecological features (Kozak et al, 2008;Manel et al, 2010;Leempoel et al, 2015). DEMs are available on Earth Explorer (Earth Explorer, 2016) and come in formats such as geotiff or SAGA Grids BOX 1 | Sampling design and scale.…”

“…On the other hand, when the spatial resolution of the variable is too coarse, nearby samples will retrieve their environmental values from the same pixels (i.e., pseudo-replicates), thus inflating autocorrelation. One solution to this problem is to compute variables at multiple resolutions (Pradervand et al, 2014;Leempoel et al, 2015).…”

“…The most common use of DEMs in ecology consists in retrieving altitude or computing primary terrain attributes (i.e., slope, orientation and curvature; Guisan and Zimmermann, 2000;Wilson and Gallant, 2000;Kozak et al, 2008;Manel et al, 2010). However, we recommend going beyond the traditional use of DEMs as a diversity of variables can be computed, like e.g., solar radiation, morphometric indices or hydrological variables (Leempoel et al, 2015). The treatment of DEMs and the production of topographic variables can be processed in software like SAGA GIS (SAGA GIS, 2004;Conrad et al, 2015) or GRASS GIS, now included in QGIS.…”

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“…With the success of Earth and environment systems with these scale-diversified processes, persistent demands exist for extending their utility to new and expanding scopes (Ringler et al, 2008;Tarolli, 2014;Wilson, 2012), as exemplified by lapse-rate-controlled functional plant distributions (Ke et al, 2012), orographic forcing imposed on oceanic and atmospheric dynamics (Nunalee et al, 2015;Brioude et al, 2012;Hughes et al, 2015), topographic dominated flood inundations (Bilskie et al, 2015;Hunter et al, 2007), and many other geomorphological (Wilson, 2012), soil (Florinsky and Pankratov, 2015), and ecological (Leempoel et al, 2015) examples from Earth systems. However, as numerical simulation systems evolved to incorporate broader scales and finer processes to produce more exact predictions (Ringler et al, 2011;Weller et al, 2016;Wilson, 2012;Zarzycki et al, 2014), how to accurately assimilate or transform the finePublished by Copernicus Publications on behalf of the European Geosciences Union.…”