Detection and Projection of Forest Changes by Using the Markov Chain Model and Cellular Automata

A central challenge for sustainability is how to preserve forest ecosystems and the services that they provide us while enhancing food production. This challenge for developing countries confronts the force of economic globalization, which seeks cropland that is shrinking in availability and triggers deforestation. Four mechanisms-the displacement, rebound, cascade, and remittance effects-that are amplified by economic globalization accelerate land conversion. A few developing countries have managed a land use transition over the recent decades that simultaneously increased their forest cover and agricultural production. These countries have relied on various mixes of agricultural intensification, land use zoning, forest protection, increased reliance on imported food and wood products, the creation of off-farm jobs, foreign capital investments, and remittances. Sound policies and innovations can therefore reconcile forest preservation with food production. Globalization can be harnessed to increase land use efficiency rather than leading to uncontrolled land use expansion. To do so, land systems should be understood and modeled as open systems with large flows of goods, people, and capital that connect local land use with global-scale factors.

In recent decades, many climate manipulation experiments have investigated biosphere responses to global change. These experiments typically examined effects of elevated atmospheric CO(2), warming or drought (driver variables) on ecosystem processes such as the carbon and water cycle (response variables). Because experiments are inevitably constrained in the number of driver variables tested simultaneously, as well as in time and space, a key question is how results are scaled up to predict net ecosystem responses. In this review, we argue that there might be a general trend for the magnitude of the responses to decline with higher-order interactions, longer time periods and larger spatial scales. This means that on average, both positive and negative global change impacts on the biosphere might be dampened more than previously assumed. Copyright © 2011 Elsevier Ltd. All rights reserved.