Bayesian Modeling Can Facilitate Adaptive Management in Restoration

Cara Applestein, T. Trevor Caughlin, Matthew J. Germino

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

There is an urgent need for near-term predictions of ecological restoration outcomes despite imperfect knowledge of ecosystems. Restoration outcomes are always uncertain but integrating Bayesian modeling into the process of adaptive management allows researchers and practitioners to explicitly incorporate prior knowledge of ecosystems into future predictions. Although barriers exist, employing qualitative expert knowledge and previous case studies can help narrow the range of uncertainty in forecasts. Software and processes that allow for repeatable methodologies can help bridge the existing gap between theory and application of Bayesian methods in adaptive management.
Original languageAmerican English
Article numbere13596
JournalRestoration Ecology
Volume30
Issue number4
DOIs
StatePublished - May 2022

Keywords

  • expert knowledge
  • iterative modeling
  • predictions
  • priors

EGS Disciplines

  • Other Ecology and Evolutionary Biology

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