Spatio-temporal variations and coupling of human activity intensity and ecosystem services based on the four-quadrant model on the Qinghai-Tibet Plateau

et al. 2022

Front. Environ. Sci.

Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

Section: Quantitative Attribution Of the Driving Factors Of Ecosystem...supporting

confidence: 88%

Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

et al. 2022

Front. Environ. Sci.

“…In this study, we used the InVEST model to estimate the habitat quality on the QTP, and found that the habitat quality was generally good, and the areas with poor habitat quality were mainly distributed in the central part of Tibet, the northern part, and the northwestern part of the QTP. These conclusions were similar to the research of Sun et al (2020), in 2015, the habitat quality in the northern and central parts of the QTP was poor (Sun et al, 2020b). The research of Li et al (2018a,b) found that the eastern basin of the QTP and the central region of Tibet were more vulnerable to human disturbances (Li et al, 2018a,b).…”

Section: Response Of Habitat Quality To Grazing Activitiessupporting

confidence: 83%

Responses of Habitat Quality and Animal Biodiversity to Grazing Activities on the Qinghai-Tibet Plateau

Liu

et al. 2021

Front. Ecol. Evol.

Grazing activities perhaps lead to habitat quality degradation and animal biodiversity loss while the effects on the Qinghai-Tibet Plateau (QTP) is still relatively poorly studied. Based on the Integrated Valuation of Ecosystem Services and Tradeoffs model, geographical detector model and generalized linear mixed model, the responses of habitat quality and animal biodiversity to grazing activities at 5 km grid scale were analyzed. Results showed that the overall habitat quality on the QTP was high with 76.43% of the total area, and poor level accounted for 19.56%. High level habitat was mainly distributed in the southern part, while the poor level in the northern part. The mean grazing activity explanatory ability to habitat quality, bird species richness and mammal richness were 0.346, 0.430, and 0.354. The interaction effects between slope and grazing activities on habitat quality, bird species richness and mammal richness were the most important interaction effects, and the area affected by the interaction was 73.82, 46.00, and 46.17% of habitat quality, bird species richness and mammal richness, respectively. The interaction effects on habitat quality, bird species richness and mammal richness all showed “low in the northwest and high in the southeast”. Grazing activities and habitat quality had a positive correlation while bird species richness, and mammal richness negative correlations. The spatial relationship of grazing activities of habitat quality was “higher in the middle and lower around the periphery”, while the spatial distribution of grazing activities of bird species richness and mammal richness was “higher in the east and lower in the west”. This study explicitly revealed the responses of habitat quality and animal biodiversity to grazing activities, thus providing references for biodiversity conservation on the QTP.

“…At the beginning of ERP implementation, the area of forest land and FVC increased rapidly, although with the decrease in ERP implementation intensity, the increase in forest land slowed, and the increase in FVC slowed after reaching the mature stages (Figures 5 and 6). Overgrazing and human activities led to a decrease in grassland area and an increase in bare land area (Li et al, 2018; Sun et al, 2020). However, these changes did not lead to a decrease in ESs, possibly because ERPs and warmer and wetter climates drove an increase in FVC, thereby offsetting the negative effects of overgrazing and human activities (Duan et al, 2021; Ma, Li, & Liu, 2021).…”

Section: Discussionmentioning

confidence: 99%

Multiple ecological effects and their drivers of ecological restoration programmes in the Qinghai‐Tibet Plateau, China

et al. 2023

Land Degrad Dev

A series of ecological restoration programmes (ERPs) have been implemented in the Qinghai‐Tibet Plateau to reverse ecological deterioration. However, the multiple ecological benefits of these ERPs and their driving factors remain unclear. This study analyzed the dynamic changes in fractional vegetation cover (FVC), ecosystem services [water yield (WY), net primary productivity (NPP), and soil conservation (SC)], and sustainable development goals (SDGs) in the Forest Protection and Construction Programme (FPCP), Grassland Protection and Construction Programme (GPCP), Sandy Land Control Programme (SLCP), and Soil Erosion Control Programme (SECP) in the Qinghai‐Tibet Plateau from 2000 to 2015. The geographically weighted regression model was used to reveal the spatial differences of drivers of various ecological benefits. The results showed that ecological benefits increased synergistically in the GPCP and SLCP, while trade‐offs between NPP and WY were observed for the FPCP and SECP. ERPs resulted in a significant increase (p < 0.05) in FVC, SDG 15.1.1, and SDG 15.3.1 and a significant decrease (p < 0.01) in SDG 15.4.2, except for the SLCP. ERPs improved the FVC, WY, and SC, but did not reverse grassland degradation. The ecological benefits of the FPCP and SLCP were poor after 2010, while the ecological benefits of the SLCP have been better since 2012. FVC and WY were dominated by precipitation, and NPP was dominated by FVC. Slope dominated SC in the GPCP, SECP, and SLCP, while precipitation dominated SC in the FPCP. This study can provide scientific support for sustainable vegetation management.