Complex decisions made simple: a primer on stochastic dynamic programming. Issue 9 (8th August 2013)

• Record Type: Journal Article
• Authors: Marescot, Lucile; Chapron, Guillaume; Chadès, Iadine; Fackler, Paul L.; Duchamp, Christophe; Marboutin, Eric; Gimenez, Olivier; Freckleton, Robert
• Is Part Of: Methods in ecology and evolution. Volume 4:Issue 9(2013:Sep.)
• Page Start: 872
• Page End: 884
• Publication Date: 2013-08-08
• Subjects: Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12082
• Languages: English
• ISSNs: 2041-210X

Abstract

<abstract abstract-type="main" id="mee312082-abs-0001"> <title>Summary</title> <p> <list id="mee312082-list-0001" list-type="order"> <list-item> <p>Under increasing environmental and financial constraints, ecologists are faced with making decisions about dynamic and uncertain biological systems. To do so, stochastic dynamic programming (SDP) is the most relevant tool for determining an optimal sequence of decisions over time.</p> </list-item> <list-item> <p>Despite an increasing number of applications in ecology, SDP still suffers from a lack of widespread understanding. The required mathematical and programming knowledge as well as the absence of introductory material provide plausible explanations for this.</p> </list-item> <list-item> <p>Here, we fill this gap by explaining the main concepts of SDP and providing useful guidelines to implement this technique, including R code.</p> </list-item> <list-item> <p>We illustrate each step of SDP required to derive an optimal strategy using a wildlife management problem of the French wolf population.</p> </list-item> <list-item> <p>Stochastic dynamic programming is a powerful technique to make decisions in presence of uncertainty about biological stochastic systems changing through time. We hope this review will provide an entry point into the technical literature about SDP and will improve its application in ecology.</p> </list-item> </list> </p> </abstract>