Forecasting adoption with epidemiological models can enable adaptively scaling out conservation
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Achieving global climate and biodiversity goals will require the rapid adoption of conservation initiatives across communities, regions, and, in some cases, the planet. However, the non-linearity and variability of adoption processes limit efforts to assess whether initiatives are on track to meet scaling targets. This uncertainty hampers practitioners’ and policymakers’ ability to adaptively allocate resources to accelerate scaling. Here, we adapt epidemiological models to forecast adoption patterns of 19 conservation initiatives, isolating the effects of independently and socially learned adoption. Our models forecast cumulative adoption with an average error of 15.9% and net adoption with a 19.6% error, indicating they reliably forecast future scaling trajectories based on early trends and capture key underlying processes. Moreover, these models offer inference regarding the mechanisms driving adoption, providing a comprehensive strategy for iteratively and adaptively identifying management actions to shape the scale of conservation initiatives.
Date Issued
2024-10-18
Date Acceptance
2024-08-29
Citation
One Earth, 2024, 7 (10), pp.1820-1832
ISSN
2590-3322
Publisher
Elsevier BV
Start Page
1820
End Page
1832
Journal / Book Title
One Earth
Volume
7
Issue
10
Copyright Statement
© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
License URL
Publication Status
Published
Date Publish Online
2024-09-23