Despite considerable advances in understanding the causes and consequences of tropical deforestation, less is known about how it manifests itself spatially across landscapes in the Amazon. Recently the study of landscape ecology has provided much insight into the ecological consequences of forest fragmentation and loss. The project seeks to complement this ecological knowledge by illuminating the human dimensions of deforestation, examining the social and behavioral processes that generate forest fragmentation. It will do so by addressing fragmentation in Amazônia associated with roads built by loggers. Specifically, the project will develop theory about forest fragmentation by examining the network formation processes of logging roads. To accomplish this, it will develop, implement, and test spatial models that generate road networks. The project seeks to base modeling efforts on empirical information about the human drivers involved, and will therefore obtain survey data to specify model assumptions, parameters values, and constraints. Project fieldwork is needed because much remains unknown about the spatial decision-making of loggers. Of interest to the project is the manner in which multiple loggers territorialize their "exploitation" domains, as a function of local power relations. Prior research suggests that this could be a key spatial factor in explaining and potentially predicting patterns of forest fragmentation.

The project possesses significant societal value beyond its contribution to basic science. Given ongoing destruction of Amazonian and other tropical forests, calls for their conservation will increase in the future. Land use policy for tropical regions will necessarily address the role of logging there, so understanding the behavior of loggers is crucial. Clearly, hardwoods represent a valuable Amazonian resource, which is all the more reason that they be logged sustainably, and that associated environmental impacts be kept to a minimum. To do this, policy must be based on a better understanding of how loggers impact the forest. The project will provide new and basic information in this regard, essential to the formulation of effective environmental policy, and to maintaining the long-term integrity of tropical forests.

Project Report

Many have expressed concern about tropical deforestation given its impact on natural resources and ecosystems. One of the prime mechanisms of impact is the spatial manner in which deforestation occurs, which is referred to as forest fragmentation. The pattern of forest fragmentation affects the function of ecosystems, with some patterns visiting extreme impact, and other patterns, lesser impact. The project reported on here investigated the way in which forest fragmentation occurs in the Amazon basin, with a special focus on loggers. Although a great deal of research has been conducted on the Amazonian forests, relatively little of it has investigated the way in which human actions actually give rise to patterns of forest fragmentation. This is especially important in the present era of climate change, when plant and animal species might be forced to migrate across landscapes that have been impacted by human settlement. The research involved field work in the Amazon basin undertaken in active logging frontiers in both Pará and Amazonas States. It also involved the development of mathematical models, and their implementation in new computer codes. During the field work, individuals knowledgeable about logging were interviewed in three campaigns addressing the spatial decision-making of loggers, the prime focus of the research. In other words, the project gathered empirical information about the patterns of road networks that loggers build in exploiting Amazonian timber resources. The project then used this information in the formulation of mathematical models that were used to develop spatial software for simulating spatial decision-making. Road networks were simulated in this manner, then compared to actual networks observable on maps generated using new methods in remote sensing analysis. On the basis of simulation, the research found that loggers possess good spatial information in their road-building activities, but also discount the future such that the networks that result fragment the forest more than necessary. Thus, a significant project finding is that current fragmentation of the Amazon forest is excessive; the same volume of wood may have been harvested with more efficient spatial networks.

Agency
National Science Foundation (NSF)
Institute
Division of Behavioral and Cognitive Sciences (BCS)
Application #
0822597
Program Officer
Thomas J. Baerwald
Project Start
Project End
Budget Start
2008-08-15
Budget End
2012-01-31
Support Year
Fiscal Year
2008
Total Cost
$151,077
Indirect Cost
Name
Michigan State University
Department
Type
DUNS #
City
East Lansing
State
MI
Country
United States
Zip Code
48824