High correlation between species‐level environmental data estimates extracted from IUCN expert range maps and from GBIF occurrence data

Abstract

Aim The International Union for Conservation of Nature (IUCN) expert range maps and the Global Biodiversity Information Facility (GBIF) species occurrence data are commonly used to estimate species’ geographic range. Macroecological studies often cross‐reference geographic range data with a climate dataset, to extract the mean environmental conditions encountered by a species within its geographic range. We aimed to assess the consistency of the environmental data estimates derived from IUCN versus GBIF geographic range data, and to test whether such differences may affect estimates of ecogeographical relationships, such as Bergmann's rule. Location Worldwide. Time period Around 2000. Taxa Rodents (Rodentia). Methods We first assessed the correlation between environmental data estimates (19 bioclimatic variables and elevation) derived from IUCN versus GBIF geographic range data of 1,315 rodent species, comparing how range size, conservation status, habitat, zoogeographic realm or elevation changed these correlations. Then, we compared the association between body mass and climate (mean temperature and precipitation) when the latter are derived from IUCN or GBIF data. Results There was high correlation between environmental data estimates derived from IUCN versus GBIF data, especially when excluding GBIF occurrences outside of IUCN polygons. Species’ characteristics, or using the mean or median, did not change the consistency between estimates. Overall, GBIF occurrence data and IUCN range maps produced similar patterns of body mass—climate correlations. Main conclusions At the large spatial and taxonomic scale employed in this study, there does not seem to be any considerable differences in the average environmental data estimates derived from IUCN versus GBIF geographic range data. This result indicates that both sources of geographic range data could be used independently or in concert for macroecological inferences that involve summarizing species’ niches by a single estimate of the average of their used environments.

Connecting species’ geographical distributions to environmental variables: range maps versus observed points of occurrence

“…For the most part values of environmental variables derived from the two different sources in our analyses were highly correlated across species, which we might expect given the overlap in points and ranges due to the constraints we placed on including points for analysis (no further than 500 km from published range boundaries). These results mirror those of Alhajeri and Fourcade () in a similar analysis based on data for 1191 species of rodents, who observed high correlations across all 19 WorldClim variables plus elevation in a comparison of GBIF points to IUCN range maps. Using all of a species’ GBIF points regardless of range boundaries, Alhajeri and Fourcade () observed a median distance between centroids of GBIF and IUCN data of 224 km, remarkably close to our observed 234 km.…”

“…Areas of introduction were derived from information presented in HBW (del Hoyo et al ). In a similar analysis for mammals, Alhajeri and Fourcade () created two data sets from GBIF, one containing all points after cleaning regardless of proximity to the range edge or status as introductions, the other retaining only those species’ points that fell within range polygons.…”

“…Because species distributed across small spatial extents likely experience a smaller range of environmental conditions, it is possible that their correlations between range‐based and point‐based medians might be higher (Alhajeri and Fourcade ); thus we repeated these correlations within each of three groups of species based on the number of 10′ × 10′ cells included within their range maps. As there were no obvious breaks in the frequency distribution of range sizes, particularly at sizes < 10 000 cells, we simply classified them as small (1–1000 cells, n = 132 species), medium (1000–10 000 cells, n = 117 species) and large (> 10 000 cells, n = 40 species).…”

“…Regardless, to the extent that environmental associations do differ between the two, we can expect to see differences in conclusions we might draw about life history patterns, or for that matter in any other macroecological analysis that relies on these associations (e.g. species distribution modeling; Beck et al , Fourcade , Alhajeri and Fourcade ).…”

“…What remains less investigated is the extent to which range maps and point‐based data actually differ in their representation of a species’ environmental associations (Alhajeri and Fourcade ). For example, if a range map polygon contains a considerable proportion of otherwise unsuitable environmental conditions for a species, then we expect to see a discrepancy between mean or median values of the relevant variables calculated over the entire range versus those calculated just from known occupied points within the range.…”