An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

PLoS One. 2015 Nov 12;10(11):e0142453. doi: 10.1371/journal.pone.0142453. eCollection 2015.

Abstract

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner's management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of 'harvest readiness' and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Conservation of Natural Resources / methods*
  • Decision Making*
  • Forestry / methods
  • Forests*
  • Information Dissemination
  • Interpersonal Relations
  • Models, Theoretical
  • Ownership*
  • Trees / physiology
  • Trust

Grants and funding

This research was made possible by the National Science Foundation (NSF) Sustainable Energy Pathways (SEP) award #1230908 and as part of the Sustainability Solutions Initiative, supported by NSF award #EPS-0904155 to Maine EPSCoR at the University of Maine to JEL and ESH. This project was also supported by the Maine Agricultural and Forest Experiment Station and the Northeastern States Research Cooperative through funding made available by the USDA Forest Service to JEL and ESH. The conclusions and opinions in this paper are those of the authors and not the NSRC, the Forest Service, or the USDA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.