Effects of Bio-physical, Economic and Ecological Policy Drivers on
China’s Forest Quality transition: Evidence from Panel Analysis
Abstract
Similar to the effects of changes in land use and cover, forest
transitions have implications for biodiversity and ecosystem
functioning. However, forest transition theory ignores ecologically
important characteristics, such as forest age, species composition,
vertical structure, and all but the most severe levels of degradation.
In this study, based on National Forestry Inventories (NFIs) data and
socioeconomic panel data covering more than 40 years (1977–2018), we
investigate the spatial-temporal dynamics and the spatial determinants
of forest quality transition at the province level in China using
spatial econometric regression models. Based on our results, we reached
the conclusions that follow. (1) Forest area, forest volume, and forest
coverage have greatly improved as of 2018, especially for plantations,
but uneven forest distribution is an important feature of forest
adaptation to the environment. (2) The global Moran’s I value is greater
than 0.3, and the forest quality of the provinces has a positive spatial
correlation and exhibits obvious spatial clustering characteristics. In
particular, the spatial expansion of forest quality has shown an
accelerated concentration from 1977 to 2018. (3) The most suitable model
for empirical analysis and interpretation was the Spatial Durbin Model
(SDM) with fixed effects. The average annual precipitation and the area
ratio of the collective forest are positively correlated with forested
quality (significance level 1%). Ultimately, this framework can guide
future research, describe actual and potential changes in forest quality
associated with forest transitions, and promote management plans that
incorporate forest area changes.