The Three Gorges Reservoir area is one of the most ecologically sensitive areas in China, and the forest landscape pattern in this region shows dramatic change due to the influence of the Three Gorges reservoir project. In this study, the locally parameterized Biome-BGC model, generated with long-term meteorological monitoring data, was used to simulate net primary productivity (NPP) and carbon density of the vegetation layer, the litter layer, and the soil layer for various forest types from 1992 to 2012 in this area. The total and unitary forest NPP presented obvious annual fluctuation under the combined influences of land use change and extreme weather events. Apart from the year 2006, from 1992 to 2012, the NPP values of each forest type showed an increasing trend, although the growth rates decreased. In 2006, due to abnormally high air temperatures and less precipitation, total and unit area forest NPP values decreased by 46.3% and 53.9%, respectively, compared to 2002. From 1992 to 2012, the carbon stocks of the forest vegetation layer, the litter layer, the soil layer, and the entire area gradually increased with decreasing growth rates. Additionally, forest carbon stocks were high in the east and the south and low in the west and the north. Generally, the forest productivity is greatly affected by the physiological and ecological characteristics of the plants themselves as well as the environmental factors, whereas total forest productivity is largely influenced by human activities. The increase in forest area and the optimization of the forest landscape pattern could improve the forest productivity and carbon sequestration.

Ecological or environmental compensation policies are usually designed with multiple policy objectives such as protecting the ecological environment and promoting farmers’ livelihoods, but in the enforcement process, there are often inconsistencies between realistic choices and policy objectives. Based on pooled cross-section data from the 2017–2019 public announcement of the selection of ecological forest rangers (EFRs, who mainly refers to manage and protect forests, grasslands, deserts and rivers, and report or prevent the situation or behavior of the forest area disasters, animal and plant resources, and infrastructure damage in time) among the poor in Sichuan Province in China, we used the Probit model to analyze the influencing factors of the re-employment behavior of EFRs among the poor, with the aim of assessing the differences between central government goal positioning and local government enforcement options. We find that (1) EFRs from poor households who have not yet escaped poverty and have a high per capita income level are given priority to be re-employed. This finding shows that the policy of ecological forest rangers for the poor (PEFRP, it mainly refers to an environmental protection policy that only hires the poor) pays close attention to poverty reduction goals, but it does not consider the poorest people because the EFRs with a higher income obtain higher re-employment opportunities. (2) Age, health, and education, which represent the human capital level, have no significant impact on renewal. This finding shows that the local government has not jointly achieved the goal of “poverty reduction and environmental protection” in the enforcement of the PEFRP and has deviated from the initial goal positioning of the central government. Therefore, in order to achieve the multiple policy objectives such as poverty reduction and environmental protection together, future policy enforcement needs to be adjusted in terms of local administrative assessment and the selection and recruitment of EFRs.