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Historical Framework to Explain Long-Term Coupled Human and Natural System Feedbacks: Application to a Multiple Ownership Forest Landscape in the Northern Great Lakes Region, USA

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Type: Journal Article
Author: Steen-Adams, Michelle M.; Langston, Nancy; Adams, Mark D. O.; Mladenoff, David J.
Journal: Ecology and Society
Volume: 20
Date: 2015
URI: https://hdl.handle.net/10535/9739
Sector: Forestry
Region: North America
Subject(s): Great Lakes region
Abstract: "Current and future human and forest landscape conditions are influenced by the cumulative, unfolding history of social-ecological interactions. Examining past system responses, especially unintended consequences, can reveal valuable insights that promote learning and adaptation in forest policy and management. Temporal couplings are complex, however; they can be difficult to trace, characterize, and explain. We develop a framework that integrates environmental history into analysis of coupled human and natural systems (CHANS). Our study demonstrates how historical data and methods can help to explain temporal complexity of long-term CHANS feedbacks. We focus on two sources of temporal complexity: legacy effects and lagged interactions. We apply our framework to a multiple-ownership forest landscape comprising tribal and nonindustrial private forest ownerships in Wisconsin. Our framework features four elements that help investigators better understand complex systems through time: (1) a temporal axis parsed into historical periods (periodization), (2) representation of links between historical periods and system feedbacks, (3) representation of land ownership history, and (4) nested geographical scales of historical analysis. The framework can help to reveal legacy effects and lagged interactions, illuminate turning points and periods in system dynamics, and distil insights from unintended consequences that inform institutional and policy adaptation. We also assess the validity of using land ownership to represent the social component of CHANS models. When treated as a categorical variable and interpreted in historical context, land ownership can validly represent decision-making structure, culture, and knowledge system in spatially explicit social-ecological models."

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