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Physical and biological feedbacks of deforestation
Author(s) -
Runyan Christiane W.,
D'Odorico Paolo,
Lawrence Deborah
Publication year - 2012
Publication title -
reviews of geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.087
H-Index - 156
eISSN - 1944-9208
pISSN - 8755-1209
DOI - 10.1029/2012rg000394
Subject(s) - deforestation (computer science) , vegetation (pathology) , environmental science , scale (ratio) , ecology , agroforestry , geography , computer science , biology , cartography , medicine , pathology , programming language
Forest vegetation can interact with its surrounding environment in ways that enhance conditions favorable for its own existence. Removal of forest vegetation has been shown to alter these conditions in a number of ways, thereby inhibiting the reestablishment of the same community of woody plants. The effect of vegetation on an environmental variable along with vegetation susceptibility to the associated environmental conditions may imply a positive feedback: Changes in the internal conditions controlling this variable such as deforestation could inhibit the reestablishment of woody vegetation cover that in turn would act to further degrade the conditions necessary for forest regeneration. Understanding these feedbacks is important because in some cases where these feedbacks are present, deforestation can lead to irreversible state shifts where the forest vegetation cannot recover. In this review, we examine the different cases in which deforestation can lead to a loss of conditions necessary to sustain forest vegetation. We examine the spatial scale and extent of each feedback in addition to considering the temporal scale over which a feedback may be considered irreversible. Juxtaposing the spatial extent of these feedbacks with a map of deforestation enables the identification and discussion of at‐risk areas to state changes following deforestation. Last, we discuss the economic implications of these feedbacks and how socioeconomic factors can affect the convergence of a system to a given stable state.

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