Prof Joseph Jackson J.A.Jackson@salford.ac.uk
Professor
Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets
Jackson, Joseph A.; Bajer, Anna; Behnke-Borowczyk, Jolanta; Gilbert, Francis; Grzybek, Maciej; Alsarraf, Mohammed; Behnke, Jerzy
Authors
Anna Bajer
Jolanta Behnke-Borowczyk
Francis Gilbert
Maciej Grzybek
Mohammed Alsarraf
Jerzy Behnke
Abstract
The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the importance of the environment in determining infectious disease dynamics. However, there has been little evaluation of the temporal predictiveness of remotely sensed environmental data for infection reservoirs in vertebrate hosts due to a deficit of corresponding high‐quality long‐term infection datasets. Here we employ two unique decade‐spanning datasets for assemblages of infectious agents, including zoonotic agents, in rodents in stable habitats. Such stable habitats are important, as they provide the baseline sets of pathogens for the interactions within degrading habitats that have been identified as hotspots for zoonotic emergence. We focus on the enhanced vegetation index (EVI), a measure of vegetation greening that equates to primary productivity, reasoning that this would modulate infectious agent populations via trophic cascades determining host population density or immunocompetence. We found that EVI, in analyses with data standardised by site, inversely predicted more than one‐third of the variation in an index of infectious agent total abundance. Moreover, in bipartite host occupancy networks, weighted network statistics (connectance and modularity) were linked to total abundance and were also predicted by EVI. Infectious agent abundance and, perhaps, community structure are likely to influence infection risk and, in turn, the probability of transboundary emergence. Thus, the present results, which were consistent in disparate forest and desert systems, provide proof‐of‐principle that within‐site fluctuations in satellite‐derived greenness indices can furnish useful forecasting that could focus primary surveillance. In relation to the well‐documented global greening trend of recent decades, the present results predict declining infection burden in wild vertebrates in stable habitats; but if greening trends were to be reversed, this might magnify the already upwards trend in zoonotic emergence.
Citation
Jackson, J. A., Bajer, A., Behnke-Borowczyk, J., Gilbert, F., Grzybek, M., Alsarraf, M., & Behnke, J. (in press). Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets. Global Change Biology, https://doi.org/10.1111/gcb.16898
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 6, 2023 |
Online Publication Date | Aug 7, 2023 |
Deposit Date | Jul 27, 2023 |
Publicly Available Date | Aug 8, 2024 |
Journal | Global Change Biology |
Print ISSN | 1354-1013 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.1111/gcb.16898 |
Keywords | connectance, greening, parasites, community networks, EVI, time series, modularity, wild rodent, zoonotic reservoir, infectious agents |
Files
Published Version
(1.4 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Accepted Version
(389 Kb)
PDF
Copyright Statement
"This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited."
You might also like
Some observations on meaningful and objective inference in radioecological field studies
(2022)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search