###### Abstract
The most commonly used quantitative methods can be classified into three categories: the regression model method, the biophysical model method, and the residual trend method [9; 14]. The regression model method is the simplest, but it is hard to distinguish the complex interactions between forest and internal and external influence factors such as climate factors and human activities [14]. The biophysical model method can study the driving mechanism of vegetation change [13]. Its idea is to simulate the potential and actual NPP, then by their difference for the separation of the relative role of human activities and climate change to forest dynamics. But the model needs a lot of forest physiological and ecological parameters, which may cause the uncertainty of the model to increase [15]. The residual trend method is to construct an NDVI-climate model, then to predict NDVI which is considered undisturbed by human activities [12; 16]. However, this method is primarily applicable to these regions that precipitation is the main restrictive factor for vegetation growth such as arid and semi-arid climate zones [17]. Both the residual method and the biophysical mode regard the difference between the predicted value and the simulated value as the impact of human activities on vegetation. However, for forests, far away from residential areas and poor accessibility (such as primary forests), they are less directly disturbed by human activities and hold long stand periods [1]. Under these conditions, this residual should be regarded as the influence of other climatic factors (such as forest fire, natural disasters). But a large number of regarding the impacts of climate and human activities on forest changes, they all are considered residuals as the impact of human activities on them, and they do not classify the forest [12; 16]. This could overestimate the impact of human activities on vegetation. But with the protection and management of primary forests strengthened in China, human activities, such as the implementation of the natural forest conservation program and prohibition of commercial logging in natural forests, have a positive effect on forests. There exists a knowledge gap to deal with residuals when we study the causes of forest changes. Against this background, in this study, the quantitative method based on the partial derivative was applied to evaluate the relative contribution of climatic factors, other climate factors, and human activities to forest net primary productivity in the Yangtze River Basin (YRB). To better clarify whether the residuals should refer to human activities or other climatic factors, forests are divided into two categories: old forests (Fold) and new forests (Fnew). Old forests refer to those that have existed before our research, while new forests are those that only appeared during our research period (such as the conversion of grassland into forestland). We assume that old forests (Fold)were dominated by climate and the residual of old forests referred to other climatic factors. The objectives were as follows:(1) to investigate two types of forest variations; (2) to quantify the contribution of climatic and human drivers to forest restoration or degradation; (3) to explore whether climate factors or human activities dominate the restoration and degradation of old forests and new forests.