Species richness, hotspots, and the scale dependence of range maps in ecology and conservation

Abstract

Most studies examining continental-to-global patterns of species richness rely on the overlaying of extent-of-occurrence range maps. Because a species does not occur at all locations within its geographic range, range-map-derived data represent actual distributional patterns only at some relatively coarse and undefined resolution. With the increasing availability of high-resolution climate and land-cover data, broad-scale studies are increasingly likely to estimate richness at high resolutions. Because of the scale dependence of most ecological phenomena, a significant mismatch between the presumed and actual scale of ecological data may arise. This may affect conclusions regarding basic drivers of diversity and may lead to errors in the identification of diversity hotspots. Here, we examine avian range maps of 834 bird species in conjunction with geographically extensive survey data sets on two continents to determine the spatial resolutions at which range-map data actually characterize species occurrences and patterns of species richness. At resolutions less than 2 degrees ( approximately 200 km), range maps overestimate the area of occupancy of individual species and mis-characterize spatial patterns of species richness, resulting in up to two-thirds of biodiversity hotspots being misidentified. The scale dependence of range-map accuracy poses clear limitations on broad-scale ecological analyses and conservation assessments. We suggest that range-map data contain less information than is generally assumed and provide guidance about the appropriate scale of their use.

Fig. 1.

The range map of E. gregalis (gray) in southern Africa, atlas cells in which the species was observed (red), and well surveyed atlas cells in which it was not observed (blue) at 0.25° (A), 0.5° (B), 1° (C), and 2° (D). Values reflect the range occupancy of the species (atlas cell occurrences/total number of well surveyed atlas cells falling within the species' geographic range) at each scale.

Fig. 2.

Boxplots illustrating the distribution of range occupancy values (Upper) and the cumulative proportion of species with range occupancy values ≥0.95 (Lower) in southern Africa (n = 435 species) and Australia (n = 399 species).

Fig. 3.

Spatial patterns of species richness in southern Africa (left two columns) and Australia (right two columns) across six levels of spatial resolution, from ≈0.25° grid cells to 8° grid cells. For each region, the column on the left reflects species richness based on atlas data, whereas the column on the right reflects richness based on the overlaying of range maps. Only grid cells with sufficient sampling effort are shown.

Fig. 4.

Boxplots reflecting the ratio between atlas- and range-map-based richness in southern Africa and Australia over six levels of spatial resolution. Asterisks denote where the distribution of atlas richness values differed significantly from the corresponding range-map richness values based on Wilcoxon signed-rank tests. **, P < 0.0001; *, P < 0.001; +, P > 0.1.

Fig. 5.

The relationship between species richness based on range maps and species richness based on atlas data at 0.25° (Upper) and 2° (Lower) resolution. The solid line indicates y = x; the red shaded area indicates values ≥95th percentile for range-map richness (range-map hotspots); blue shaded areas indicate values in the ≥95th percentile for atlas richness (atlas hotspots). Green indicates where the identification of hotspots coincides. Southern Africa, n = 1,384 0.25° grid cells (A) and n = 45 2° grid cells (C). Australia, n = 2,021 0.25° grid cells (B) and n = 57 2° grid cells (D). The outlier in D represents a grid cell on Tasmania that also includes two pixels on the mainland.

Fig. 6.

Lack of congruence between atlas (blue) and range-map (red) hotspots (the 5% most species-rich grid cells) in southern Africa using 0.25° grid cells. Gray areas indicate IUCN-designated protected areas, and green grid cells represent hotspots identified by both types of data. At this resolution, only 31% of the range-map-based hotspots are also identified as hotspots by atlas data. No data were available for countries in white.