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Rapid monitoring for ecological persistence

View ORCID ProfileChuliang Song, View ORCID ProfileBenno I. Simmons, Marie-Josée Fortin, Andrew Gonzalez, Christopher N. Kaiser-Bunbury, Serguei Saavedra
doi: https://doi.org/10.1101/2022.07.02.498308
Chuliang Song
1Department of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, Quebec H3A 1B1, Canada
2Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street, Toronto, Ontario M5S 3B2, Canada
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  • For correspondence: clsong.ecology@gmail.com
Benno I. Simmons
3Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, Penryn TR10 9FE, UK
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Marie-Josée Fortin
2Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street, Toronto, Ontario M5S 3B2, Canada
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Andrew Gonzalez
1Department of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, Quebec H3A 1B1, Canada
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Christopher N. Kaiser-Bunbury
3Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, Penryn TR10 9FE, UK
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Serguei Saavedra
4Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Av., Cambridge, MA 02139, USA
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Abstract

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of ecological communities is largely supported by its structured architecture of species interactions, known as an ecological network. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, we can only monitor small subsets of these networks due to logistical sampling constraints. There is therefore an urgent need to establish links between the small snapshots of data conservationists are able to collect, and the ‘big picture’ conclusions about ecosystem health demanded by policy makers, scientists and societies. Here we show that the persistence of small subnetworks in isolation — that is, their persistence when considered separately from the larger network of which they are a part — is a reliable probabilistic indicator of the persistence of the network as a whole. Our results are general across both antagonistic and mutualistic interaction networks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies. This could significantly improve our ability to monitor progress towards achieving policy targets, such as those enshrined in the UN Convention on Biological Diversity.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted July 05, 2022.
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Rapid monitoring for ecological persistence
Chuliang Song, Benno I. Simmons, Marie-Josée Fortin, Andrew Gonzalez, Christopher N. Kaiser-Bunbury, Serguei Saavedra
bioRxiv 2022.07.02.498308; doi: https://doi.org/10.1101/2022.07.02.498308
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Rapid monitoring for ecological persistence
Chuliang Song, Benno I. Simmons, Marie-Josée Fortin, Andrew Gonzalez, Christopher N. Kaiser-Bunbury, Serguei Saavedra
bioRxiv 2022.07.02.498308; doi: https://doi.org/10.1101/2022.07.02.498308

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