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An empirical analysis of the driving forces of forest cover change in northeast China

Shi, Miaoying, Yin, Runsheng, Lv, Hongdi
Forest policy and economics 2017 v.78 pp. 78-87
agricultural land, cropping systems, data collection, deforestation, economic development, equations, forests, irrigation, issues and policy, land use and land cover maps, land use change, models, remote sensing, statistics, wetlands, China
In this paper, we investigate the interactions and feedbacks between the drivers of forest cover and other land uses by building a novel longitudinal dataset and adopting alternative modeling strategies. Our longitudinal dataset integrates land-use and land-cover change (LULCC) information, derived by interpreting satellite imagery, with social-economic statistics across eight counties in Heilongjiang over a period of 37years. Employing both instrument variable and system of equations methods, our models capture the inherent endogeneity embedded in the land-use changes and the effects of such factors as demographic change, economic development, and management transition on the forest condition. To validate the robustness of our models, a series of identification, endogeneity, and other tests are conducted. Our results demonstrate the dominant role of agricultural expansion in forestland loss as well as the importance of considering the substitution between forestland and wetland in analyzing the drivers of LULCC in general and deforestation in particular. The significant coefficient of the Natural Forest Protection Program implies that it has played a positive role in protecting local forests. The positive coefficient of built-up area in the farmland equation suggests a strong link between farming and residential/commercial construction; likewise, the negative coefficient of irrigation indicates that wetland loss is adversely affected by the change in local cropping pattern. It is hoped that these and other findings will improve our knowledge of the forest dynamics and their socioecological drivers, leading to more effective policy making and implementation and, ultimately, better resource conditions.