We develop an agent-based model for forest harvesting to study how interactions between neighboring land parcels and the degree of information flow among landowners influence harvesting patterns. We assume a forest is composed of a number of land parcels that are individually managed. Each parcel is either mature forested, just-harvested, or immature forested. The state transition of each parcel is described by a Markov chain that incorporates the successional dynamics of the forest ecosystem and landowners' decisions about harvesting. Landowners decide to cut trees based on the expected discounted utility of forested vs. harvested land. One landowner's decision to cut trees is assumed to cause the degradation of ecosystem services on the downstream forested parcels. We investigated two different scenarios: in a strongly-connected society, landowners are familiar with each other and have full information regarding the behavior of other landowners. In a weakly-connected society, landowners do not communicate and therefore need to make subjective predictions about the behavior of others without adequate information. Regardless of the type of society, we observed that the spatial interaction between management units caused a chain reaction of tree harvesting in the neighborhood even when healthy forested land provided greater utility than harvested land. The harvest rate was higher in a weakly-connected society than that in a strongly-connected society. If landowners employed a long-term perspective, the harvest rate declined, and a more robust forested landscape emerged. Our results highlight the importance of institutional arrangements that encourage a long-term perspective and increased information flow among landowners in order to achieve successful forest management.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modelling and Simulation
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics