Effectiveness of China's National Forest Protection Program and nature reserves

There is profound interest in knowing the degree to which China's institutions are capable of protecting its natural forests and biodiversity in the face of economic and political change. China's 2 most important forest-protection policies are its National Forest Protection Program (NFPP) and its national-level nature reserves (NNRs). The NFPP was implemented in 2000 in response to deforestation-caused flooding. We undertook the first national, quantitative assessment of the NFPP and NNRs to examine whether the NFPP achieved its deforestation-reduction target and whether the NNRs deter deforestation altogether. We used MODIS data to estimate forest cover and loss across mainland China (2000-2010). We also assembled the first-ever polygon dataset for China's forested NNRs (n = 237, 74,030 km(2) in 2000) and used both conventional and covariate-matching approaches to compare deforestation rates inside and outside NNRs (2000-2010). In 2000, 1.765 million km(2) or 18.7% of mainland China was forested (12.3% with canopy cover of ≥70%)) or woodland (6.4% with canopy cover <70% and tree plus shrub cover ≥40%). By 2010, 480,203 km(2) of forest and woodland had been lost, an annual deforestation rate of 2.7%. Forest-only loss was 127,473 km(2) (1.05% annually). In the NFPP provinces, the forest-only loss rate was 0.62%, which was 3.3 times lower than in the non-NFPP provinces. Moreover, the Landsat data suggest that these loss rates are overestimates due to large MODIS pixel size. Thus, China appears to have achieved, and even exceeded, its target of reducing deforestation to 1.1% annually in the NFPP provinces. About two-thirds of China's NNRs were effective in protecting forest cover (prevented loss 4073 km(2) unmatched approach; 3148 km(2) matched approach), and within-NNR deforestation rates were higher in provinces with higher overall deforestation. Our results indicate that China's existing institutions can protect domestic forest cover.