## 1 Introduction  
Vegetation is the core of material circulation and energy flow on Earth, and plays a crucial role in the ecosystem [1]. Vegetation is not only an important environmental factor, but also a sensitive indicator of the land's ecosystem [2]. With the increase in large-scale productivity studies and the progress in understanding plant eco-physiological processes, gross primary production (GPP) and net primary productivity (NPP) have been proposed to represent the productivity of vegetation [3]. Defined as the amount of organic matter produced by green plants per unit of time and area [4],NPP indicates the balance between the carbon gained by GPP and the carbon released by plant respiration [5]. And the normalized difference vegetation index (NDVI) as displayed in temporal variation of a spectral vegetation index has been used to reflect the state of vegetation cover, which is calculated as the difference between the near-infrared and visible reflectances divided by the sum of the two [6].  
The Sanjiangyuan region lies in the hinterland of the Qinghai-Tibet Plateau, Qinghai Province, China and is generally considered to be one of the most sensitive zones to climate change in the world [7; 8]. In recent decades, understanding the spatial and temporal patterns of vegetation and its interactions with environmental factors (i.e., climate factors and anthropogenic factors) has been the focus of studies on global climate change [9; 10; 11; 12]. As an important aspect of the studies on global climate change and the response of vegetation to the changes [13], a series of studies have been carried out in the Sanjiangyuan region. Many scholars have studied the spatial and temporal distribution of vegetation status (i.e., NDVI, NPP) and the effects of climate change and human activities on the vegetation status. The methods used to estimate NPP in the Sanjiangyuan region can be broadly divided into two categories: Field measurements and model simulations [14]. Among these techniques, the Carnegie-Ames-Stanford Approach (CASA) model has been successfully applied as a remote-sensing-based approach to mapping NPP patterns worldwide, including in mainland China [15]. These approaches are relatively simple and are efficient for the exploration of dynamic changes in NPP and their spatiotemporal variations at larger scales.  
Since the year 2000, the Chinese government has adopted a variety of measures to protect and restore the ecological environment, including the creation of the Sanjiangyuan National Nature Reserve (SNNR) in 2000 and the implementation of a project of ecological protection and construction for the SNNR. The overall trends of the degradation of the ecosystem were initially contained and partially improved [16]. The effectiveness of ecological conservation has been assessed quantitatively, and the contributions of climate change and human activity to vegetation growth were calculated to be 79.32% and 20.68%, respectively [17].  
In particular, the establishment of the Sanjiangyuan National Park in 2016 has further strengthened the efforts to protect the authenticity and integrity of ecosystem. Thus, human disturbances to vegetation cover in the Sanjiangyuan National Park have been strictly limited. Climatic conditions can be considered to be the dominant factor determining vegetation dynamics and ecological quality status. Therefore, the examination of the spatiotemporal patterns of the status of vegetation and environmental controls is necessary and is of great importance to the decision-making regarding vegetation protection and restoration by the management of Sanjiangyuan National Park. The aims of this study are (i) to examine the spatial pattern of NDVI and NPP in Sanjiangyuan National Park, (ii) to explore the response of different vegetation types to climate change in Sanjiangyuan National Park, and (iii) to investigate the relationships between NDVI, NPP, and climate factors at a spatiotemporal scale in Sanjiangyuan National Park.