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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

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets Thumbnail


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

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"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."






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