Abstract

Effective forestation policies are urgently required across the globe under the initiative of the UN Decade on Ecosystem Restoration. Rather than simply planting trees, such initiatives involve complex components of societal and biophysical systems. However, the underlying pathways by which forestation influences ecological outcomes are not well understood, especially given the lack of a unified quantification framework. In this study, such a framework was developed to reveal the pathways by which reforestation programs influenced ecological outcomes by identifying the linkages among reforestation efforts, societal changes, land system changes and ecological outcomes. The framework was applied to the reforestation program of the Grain for Green Program (GFGP), to explore how the GFGP influenced vegetation dynamics and ecosystem functioning in Guizhou Province, China, through direct and indirect pathways. Two remote sensing based indicators, namely the enhanced vegetation index, derived from the Moderate Resolution Imaging Spectroradiometer, and gross primary production (GPP), obtained from the Orbiting Carbon Observatory-2 solar-induced chlorophyll fluorescence (SIF) fine-resolution dataset GOSIF, were combined with inventory data and land-use maps to detect changes in social and ecological outcomes. Using the structural equation model to apply the framework, the results showed that the GFGP positively contributed to the increasing greenness and GPP of the study area through the direct conservation pathway. Although implementation of the GFGP encouraged the rural outmigration and led to a decrease in the area of farmland, the GFGP showed negative indirect effects on greenness and GPP because of the difficulty of reforestation during land-use conversion from farmland to forest land. This study revealed divergent impacts of the reforestation program through multiple pathways, which could provide valuable information for other parts of the globe for more precise design of ecological restoration policies.

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