The Effects of Selective Logging Behaviors on Forest Fragmentation and Recovery

Xanic J Rondon,Jane Southworth,Graeme S Cumming,Rosa E Cossío

doi:10.1155/2012/170974

Abstract

To study the impacts of selective logging behaviors on a forest landscape, we developed an intermediate-scale spatial model to link cross-scale interactions of timber harvesting, a fine-scale human activity, with coarse-scale landscape impacts. We used the Lotka-Volterra predator-prey model with Holling’s functional response II to simulate selective logging, coupled with a cellular automaton model to simulate logger mobility and forest fragmentation. Three logging scenarios were simulated, each varying in timber harvesting preference and logger mobility. We quantified forest resilience by evaluating (1) the spatial patterns of forest fragmentation, (2) the time until the system crossed a threshold into a deforested state, and (3) recovery time. Our simulations showed that logging behaviors involving decisions made about harvesting timber and mobility can lead to different spatial patterns of forest fragmentation. They can, together with forest management practices, significantly delay or accelerate the transition of a forest landscape to a deforested state and its return to a recovered state. Intermediate-scale models emerge as useful tools for understanding cross-scale interactions between human activities and the spatial patterns that are created by anthropogenic land use.

Highlights

Humans both create and respond to spatial patterns across a range of spatial and temporal scales [1,2,3]
Our simulations showed that logging behaviors involving decisions made about harvesting timber and mobility can lead to different spatial patterns of forest fragmentation
Intermediate-scale models emerge as useful tools for understanding cross-scale interactions between human activities and the spatial patterns that are created by anthropogenic land use

Summary

Introduction

Humans both create and respond to spatial patterns across a range of spatial and temporal scales [1,2,3]. Broad-scale models, often lack important elements of complex processes that can be modeled using a multi-scale approach [9,10,11] Land use is both a response to socioeconomic driving factors (e.g., the price of beef) and a cause of changes in socioeconomic systems (e.g., forest clearing for increased cattle production leads to an increased supply of beef, reducing prices) [12, 13]. Cross-scale interactions can have important influences on fine-scale processes, or vice versa [17, 18] In this context, intermediates or mesoscale models, which focus on connecting fine- and broad-scale patternprocess relationships [19], have an important role to play because they are well suited to capturing human agency, an important element that many models of land-use ignore [8, 10, 20, 21]

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