Abstract

Surveillance of pathogen richness in wildlife is needed to identify host species with a high risk of zoonotic disease spillover. While several predictors of pathogen richness in wildlife hosts have been proposed, their relative importance has not been formally examined. This hampers our ability to identify potential disease reservoirs, particularly in remote areas with limited surveillance efforts. Here we analyzed 14 proposed predictors of pathogen richness using ensemble modeling and a dataset of 1040 host species to identify the most important predictors of pathogen richness in wild mammal species. After controlling for research effort, larger species geographic range area was identified to be associated with higher pathogen richness. We found evidence of duality in the relationship between the fast–slow continuum of life-history traits and pathogen richness, where pathogen richness increases near the extremities. Taxonomic orders Carnivora, Proboscidea, Artiodactyla, and Perissodactyla were predicted to host high pathogen richness. The top three species with the highest pathogen richness predicted by our ensemble model were Canis lupus, Sus scrofa, and Alces alces. Our results can help support evidence-informed pathogen surveillance and disease reservoir management to prevent the emergence of future zoonotic diseases.

Details

Title
Range area and the fast–slow continuum of life history traits predict pathogen richness in wild mammals
Author
Choo, Jacqueline 1 ; Nghiem, Le T. P. 2 ; Benítez-López, Ana 3 ; Carrasco, Luis R. 1 

 National University of Singapore, Department of Biological Sciences, Singapore, Singapore (GRID:grid.4280.e) (ISNI:0000 0001 2180 6431) 
 University of British Columbia, Vancouver, Canada (GRID:grid.17091.3e) (ISNI:0000 0001 2288 9830) 
 Museo Nacional de Ciencias Naturales (MNCN-CSIC), Department of Biogeography and Global Change, Madrid, Spain (GRID:grid.420025.1) (ISNI:0000 0004 1768 463X) 
Pages
20191
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2892063935
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.