ForestSim Model of Impacts of Smallholder Dynamics: Forested Landscapes of the Upper Peninsula of Michigan

Abstract

Many forested landscapes in the United States contain a large number of small private landowners (smallholders). The individual decisions of these smallholders can collectively have a large impact on the structure, composition, and connectivity of forests. While models have been developed to try to understand this large-scale collective impact, few models have incorporated extensive information from individual decision-making. Here we introduce an agent-based model, infused with sociological data from smallholders, overlaid on a GIS layer to represent individual smallholders, and used to simulate the impact of thousands of harvesting decisions. Our preliminary results suggest that certain smallholder characteristics (such as relative smallholder age and education level as well as whether a smallholder is resident or absentee) and information flow among owners can radically impact forests at the landscape scale. While still in its preliminary stages, this modeling approach is likely to demonstrate in detail the consequences of decision-making due to changing smallholder demographics or new policies and programs. This approach can help estimate the effectiveness of programs based on landscape-scale programmatic goals and the impact of new policy initiatives.

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

“…The number of foresters, number of peer leaders, and opinion type were statistically different regarding percentage of the landscape harvested and percentage of landowners that trust foresters. Similar ABMs include FLAME [ 15 ], ForestSim [ 13 ], and a model of spatial interaction and information flow [ 12 ]. Our model configuration and outputs are consistent with these models.…”

“…Satake et al [ 12 ] studied interaction between neighboring parcels on patterns of harvesting and found that the harvest rate was higher in a weakly-connected society. Mayer and Rouleau [ 13 ] found that information flow between landowners changes landscape-level forest structure, given certain sociological parameters. There is also a growing literature that explores wood markets using ABMs [ 14 ].…”

Use of a participatory approach to develop a regional assessment tool for bioenergy production

“…Following the rapid downsizing of these industries by the 1960s, the subsequent outmigration had a tremendous impact on the regional economy. In the intervening decades the forests have regenerated, and currently more than 80% of the WUP land is forested [21]. The forest industry remains as an important part of the local economy and culture in the WUP.…”

A New Agent-Based Model Provides Insight Into Assumptions in Modeling Forest Management Under Deep Uncertainty

“…Exploratory modeling is frequently applied in forestry to study forest management questions, with approaches to modeling forest management varying widely. For example, some models do not include dynamic forest management (Albert et al, 2015(Albert et al, , 2018Handler et al, 2014;Keeley et al, 2009;Maxwell et al, 2020;Seidl & Lexer, 2013), some include dynamic but probabilistic forest management (e.g., Mayer & Rouleau, 2013;Wear et al, 2013;, and others include dynamic feedback-based forest management (e.g., Barros et al, 2017;Rammer & Seidl, 2015) and at multiple scales (e.g., Bolte et al, 2007). Such differences, which implicitly re ect assumptions about the degree of deep uncertainty future forest management will face, substantially contribute to simulation outcomes (Rinaldi & Jonsson, 2020) but are rarely discussed in this context (but see Yousefpour et al [2012], who review the differences in non-exploratory approaches to modeling forest management under uncertainty).…”