Abstract
AbstractAimTo explore the scale dependence of relationships between novel measures of geodiversity and species richness of both native and alien vascular plants.LocationGreat Britain.Time periodData collected 1995â2015.Major taxaVascular plants.MethodsWe calculated the species richness of terrestrial native and alien vascular plants (6,932 species in total) across the island of Great Britain at grain sizes of 1 km2 (n = 219,964) and 100 km2 (n = 2,121) and regional extents of 25â250 km diameter, centred around each 100âkm2 cell. We compiled geodiversity data on landforms, soils, hydrological and geological features using existing national datasets, and used a newly developed geomorphometric method to extract landform coverage data (e.g., hollows, ridges, valleys, peaks). We used these as predictors of species richness alongside climate, commonly used topographic metrics, landâcover variety and human population. We analysed species richness across scales using boosted regression tree (BRT) modelling and compared models with and without geodiversity data.ResultsGeodiversity significantly improved models over and above the widely used topographic metrics, particularly at smaller extents and the finer grain size, and slightly more so for native species richness. For each increase in extent, the contribution of climatic variables increased and that of geodiversity decreased. Of the geodiversity variables, automatically extracted landform data added the most explanatory power, but hydrology (rivers, lakes) and materials (soil, superficial deposits, geology) were also important.Main conclusionsGeodiversity improves our understanding of, and our ability to model, the relationship between species richness and abiotic heterogeneity at multiple spatial scales by allowing us to get closer to the realâworld physical processes that affect patterns of life. The greatest benefit comes from measuring the constituent parts of geodiversity separately rather than one combined variable (as in most of the few studies to date). Automatically extracted landform data, the use of which is novel in ecology and biogeography, proved particularly valuable in our study.
Highlights
Understanding the spatial patterns of biodiversity is important for scientific theory, conservation and management of ecosystem services (Hanski et al, 2012; Lomolino, Riddle, Whittaker, & Brown, 2010)
The contribution of âtopographyâ showed similar patterns to geodiversity, but was less important at smaller scales and declined less sharply as scales increased
Mapping the results (Figure 2) shows the widespread dominance of the geodiversity predictor set at the smaller geographical extents, its importance generally declining relative to climate with increasing extent, except in FIG URE 2 The dominant predictor set for native and alien species richness at the 1-km2 grain size for three spatial extents
Summary
Understanding the spatial patterns of biodiversity is important for scientific theory, conservation and management of ecosystem services (Hanski et al, 2012; Lomolino, Riddle, Whittaker, & Brown, 2010). We introduce the term âgeodiversity componentâ (GDC; Figure 1b), to refer to the quantified geofeature, whether this be areal coverage (e.g., of a particular landform), richness (e.g., the number of geological types) or length (e.g., of a river) These GDCs together measure âgeodiversityâ at the scale being studied. The GDCs we use here are intended to capture aspects of the abiotic heterogeneity with which living organisms interact â and better and more explicitly measure environmental heterogeneity for the purposes of explaining species richness patterns than crude topographic measures such as mean slope, elevational range or mean aspect (Figure 1) Such topographic measures have been widely used as correlates or predictors of species richness (Stein & Kreft, 2014), and to create a conceptual distinction we omit these from our definition of geodiversity
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