The dominant influencing factors of changes in vegetation NPP and the relative roles of climate–human factors on the Qinghai–Tibet Plateau (QTP) differ between historical periods and are unclear. Therefore, there is an urgent need to systematically and quantitatively analyze the evolution process of the QTP’s ecosystem pattern and the driving factors of this process. Based on MOD17A3H and meteorological data, the Miami model, correlation analysis, and the residual coefficient method were used to investigate the spatiotemporal patterns of changes in vegetation NPP on the QTP from 2000 to 2020. We then quantitatively distinguished the relative roles of climate change and human activity in the process of vegetation NPP change during different historical periods. The results show the following: (1) From 2000 to 2020, zones with increasing vegetation NPP (10–30%) were the most widely distributed, and were mainly located in the Three-Rivers Headwater Region and the northern part of the Hengduan Mountains. (2) From 2000 to 2020, zones with a significant positive correlation between vegetation NPP and annual precipitation were mostly distributed in the northeastern QTP and the Three-Rivers Headwater Region, while zones with a positive correlation between vegetation NPP and annual average temperature were mostly located in southern Tibet. Zones with a significant positive correlation between NPP and annual sunshine hours were mainly distributed in the southeastern part of the QTP and the southern part of the Tanggula Mountains. In contrast, zones with a significant positive correlation between NPP and accumulated temperature (>10 °C) were mainly concentrated in the northern and eastern parts of the QTP. (3) During different historical periods, the relative roles of climate–human factors in the process of vegetation NPP change on the QTP had obvious spatiotemporal differences. These results could provide scientific support for the protection and restoration of regional ecosystems on the QTP.

Studies that consider both the differences of evaluation systems and index weights among different ecological areas in different study periods for ecological vulnerability evaluation have not been reported yet. In addition, the comparability of vulnerability assessment results among different study areas is poor. This paper proposed a novel quantitative vulnerability evaluation method for multi-type and multi-temporal ecological functional areas using a dynamic weighting method: Three-River Source region grassland–wetland ecological functional area (TRSR), Guiqiandian karst rocky desertification control ecological functional area (GQD), Hunshandake desertification control ecological functional area (HSDK), and Chuandian forest and biodiversity ecological functional area (CD), and then introduced net primary productivity (NPP) to realize the determination of multi-type ecological vulnerability thresholds, which is helpful to compare the vulnerability evaluation results of different ecological functional areas in a unified and comparable level. The proposed novel quantitative vulnerability evaluation method had higher applicability in vulnerability assessment for multi-type ecological functional areas (91.1% for TRSR, 91.9% for HSDK, 91.7% for CD, and 94.2% for GQD) based on the dynamic weight determination method. The determination of vulnerability thresholds based on NPP could provide a comparable level to investigate the spatial distribution patterns of ecological vulnerability in multi-type ecological functional areas for different periods. The average ecological vulnerability of the TRSR, GQD, and CD was classified as mild vulnerability, while that of the HSDK was classified as moderate vulnerability. The research results could provide a novel method for the support of ecological protection for multi-type ecological zones on a national scale.

The Qinghai–Tibet plateau (QTP), as the “roof of the world” and the “Asian Water Tower”, provides important ecological resources for China and other Asian countries. The changing trend of ecological assets and their dominant influencing factors in different sub-regions and periods are not yet clear. In order to reveal the differences in driving mechanisms among sub-regions under the context of global changes, this study quantitatively analyzed the ecological assets and their spatial and temporal evolution patterns during 2000–2015 by using the value equivalent method. Then, the Geodetector was introduced to reveal and clarify the dominant factors of ecological asset changes in different ecological sub-regions. The results show the following. (1) From 2000 to 2010, the total value of ecological assets in Nakchu County was the highest, followed by Kangding County, while that in 2015 was the highest in Kangding County, followed by Nakchu County. (2) During 2000–2015, the average value of ecological assets of the Qinghai–Tibet plateau gradually decreased from east to west, while the average ecological asset value in the southern Qinghai–Tibet plateau was lower. (3) The QTP showed the highest value in 2005 with an increasing trend from 2000 to 2005, followed by a subsequent decrease from 2005 to 2015. (4) Between 2000 and 2015, the area of the stable zone (slight or no change) of ecological assets was the largest, followed by that of the decreasing zone. (5) During all the study period, the spatio-temporal evolution of ecological assets in different ecological sub-regions was mainly affected by natural factors, which were the main driving variables rather than human activities. These results could provide important support for decisions regarding the protection of ecosystems and resources in the Qinghai–Tibet plateau.