Remote assessment of locally important ecological features across landscapes: how representative of reality?. Issue 5 (1st July 2015)

• Record Type: Journal Article
• Authors: Willis, Katherine J.; Seddon, Alistair W. R.; Long, Peter R.; Jeffers, Elizabeth S.; Caithness, Neil; Thurston, Milo; Smit, Mathijs G. D.; Hagemann, Randi; Macias-Fauria, Marc
• Is Part Of: Ecological applications. Volume 25:Issue 5(2015)
• Page Start: 1290
• Page End: 1302
• Publication Date: 2015-07-01
• Subjects: beta-diversity -- biodiversity evaluation -- ecological footprint -- ecological risk -- field forecast verification -- local ecological footprinting tool -- local field data -- threatened species -- vulnerability -- web-based landscape planning tool; Ecology -- Periodicals; Environmental protection -- Periodicals; Biology, Economic -- Periodicals; 577.05
• DOI: 10.1890/14-1431.1
• Languages: English
• ISSNs: 1051-0761

Abstract

Abstract : The local ecological footprinting tool (LEFT) uses globally available databases, modeling, and algorithms to remotely assess locally important ecological features across landscapes based on five criteria: biodiversity (beta‐diversity), vulnerability (threatened species), fragmentation, connectivity, and resilience. This approach can be applied to terrestrial landscapes at a 300‐m resolution within a given target area. Input is minimal (latitude and longitude) and output is a computer‐generated report and series of maps that both individually and synthetically depict the relative value of each ecological criteria. A key question for any such tool, however, is how representative is the remotely obtained output compared to what is on the ground. Here, we present the results from comparing remotely‐ vs. field‐generated outputs from the LEFT tool on two distinct study areas for beta‐diversity and distribution of threatened species (vulnerability), the two fields computed by LEFT for which such an approach is feasible. The comparison method consists of a multivariate measure of similarity between two fields based on discrete wavelet transforms, and reveals consistent agreement across a wide range of spatial scales. These results suggest that remote assessment tools such as LEFT hold great potential for determining key ecological features across landscapes and for being utilized in preplanning biodiversity assessment tools.