Comparing methods for mapping global parasite diversity. Issue 1 (24th October 2019)

• Record Type: Journal Article
• Authors: Pappalardo, Paula; Morales‐Castilla, Ignacio; Park, Andrew W.; Huang, Shan; Schmidt, John P.; Stephens, Patrick R.
• Editors: Jordan, Greg
• Is Part Of: Global ecology & biogeography. Volume 29:Issue 1(2020)
• Page Start: 182
• Page End: 193
• Publication Date: 2019-10-24
• Subjects: biodiversity -- cartography -- geographic range -- infectious disease -- mammalian host -- mapping -- parasite -- pathogen -- species richness; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.13008
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe. Innovation: To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity. Main conclusions: The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.