Mismatch between IUCN range maps and species interactions data illustrated using the Serengeti food web

Higino, Gracielle T., Banville, Francis, Dansereau, Gabriel, Forero Muñoz, Norma R., Windsor, Fredric ORCID: https://orcid.org/0000-0001-5030-3470 and Poisot, Timothée 2023. Mismatch between IUCN range maps and species interactions data illustrated using the Serengeti food web. PeerJ – the Journal of Life & Environmental Sciences 11 , e14620. 10.7717/peerj.14620

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Abstract

Background Range maps are a useful tool to describe the spatial distribution of species. However, they need to be used with caution, as they essentially represent a rough approximation of a species’ suitable habitats. When stacked together, the resulting communities in each grid cell may not always be realistic, especially when species interactions are taken into account. Here we show the extent of the mismatch between range maps, provided by the International Union for Conservation of Nature (IUCN), and species interactions data. More precisely, we show that local networks built from those stacked range maps often yield unrealistic communities, where species of higher trophic levels are completely disconnected from primary producers. Methodology We used the well-described Serengeti food web of mammals and plants as our case study, and identify areas of data mismatch within predators’ range maps by taking into account food web structure. We then used occurrence data from the Global Biodiversity Information Facility (GBIF) to investigate where data is most lacking. Results We found that most predator ranges comprised large areas without any overlapping distribution of their prey. However, many of these areas contained GBIF occurrences of the predator. Conclusions Our results suggest that the mismatch between both data sources could be due either to the lack of information about ecological interactions or the geographical occurrence of prey. We finally discuss general guidelines to help identify defective data among distributions and interactions data, and we recommend this method as a valuable way to assess whether the occurrence data that are being used, even if incomplete, are ecologically accurate.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Biosciences
Subjects:	Q Science > QL Zoology
Publisher:	PeerJ
ISSN:	2167-8359
Date of First Compliant Deposit:	10 February 2023
Date of Acceptance:	1 December 2022
Last Modified:	07 Nov 2023 00:30
URI:	https://orca.cardiff.ac.uk/id/eprint/156872

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