Human judgment vs quantitative models for the management of ecological resources

Holden, Matthew H. and Ellner, Stephen P. (2016) Human judgment vs quantitative models for the management of ecological resources. Ecological Applications, 26 5: 1553-1565. doi:10.1890/15-1295

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
UQ398930_OA.pdf Full text (open access) application/pdf 287.09KB 0

Author Holden, Matthew H.
Ellner, Stephen P.
Title Human judgment vs quantitative models for the management of ecological resources
Journal name Ecological Applications   Check publisher's open access policy
ISSN 1051-0761
1939-5582
Publication date 2016-07
Year available 2016
Sub-type Article (original research)
DOI 10.1890/15-1295
Open Access Status File (Publisher version)
Volume 26
Issue 5
Start page 1553
End page 1565
Total pages 13
Place of publication Hoboken, United States
Publisher John Wiley & Sons
Collection year 2017
Language eng
Formatted abstract
Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1–3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time.
Keyword Adaptive management
Bioeconomics
Conservation
Ecological modeling
Expertjudgment
Fisheries management
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: CEED Publications
HERDC Pre-Audit
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Sun, 07 Aug 2016, 00:17:36 EST by System User on behalf of Learning and Research Services (UQ Library)