Spatial differentiation of the NPP and NDVI and its influencing factors vary with grassland type on the Qinghai-Tibet Plateau.

Grasslands are the dominant ecosystem of the Qinghai-Tibet Plateau (QTP), and they play an important role in climate regulation and represent an important ecological barrier in China. However, the spatial differentiation characteristics of net primary productivity (NPP) and normalized differential vegetation index (NDVI) and the main influencing factors that vary with grassland type on the QTP are not clear. In this study, standardized precipitation evapotranspiration index (SPEI), digital elevation model (DEM), precipitation, temperature, slope, photosynthetically active radiation (PAR) and grazing intensity were considered the driving factors. First, a grey relational degree analysis was performed to test for the quantitative relationships between NPP, NDVI and factors. Then, the geographical detector method was applied to analyze the interaction relationships of the factors. Finally, based on the geographically weighted regression (GWR) model, the influence of factors varied with grassland type on the NPP and NDVI was revealed from the perspective of spatial differentiation. The results were as follows: (1) The NPP and NDVI had roughly the same degrees of correlation with each impact factor by the grey relational degree analysis, each factor was closely related to the NPP and NDVI, and the relational degree between grazing intensity and NPP was greater than that between grazing intensity and NDVI. (2) The interaction relationships between influencing factors and NPP and NDVI varied with the grassland type and presented bivariate enhancement and nonlinear enhancement, and the interaction effects between grazing intensity and any factor on each grassland type had a greater impact on NPP. (3) The main influencing factors of the spatial heterogeneity of NPP were grazing intensity and PAR, which were "high from northeast to southwest, low from northwest to southeast" and "low in the middle and high around". The main influencing factors on the NDVI were precipitation and PAR, which were "low in the middle and high around" and "high in the north, low in the south".

Climatic factors and human disturbance influence ungulate species distribution on the Qinghai-Tibet Plateau.

Due to human activities and climate change, the habitats of ungulate species on the Qinghai-Tibet Plateau have been greatly affected in recent decades. In this study, the distribution patterns of 19 ungulate species on the Qinghai-Tibet Plateau were identified based on MaxEnt model in the past (1960-1990) and current periods (2000-2015). Then the changes of their habitat distribution and the species richness in different periods were compared. Finally, the Zonation model was used to identify the key protected areas of ungulate species. The results show that the MaxEnt model can well predict the distribution of ungulate species. Most ungulate species are mainly distributed in the southeast of the Qinghai-Tibet Plateau. The distance to lakes and precipitation are the main factors affecting the distribution of most ungulate species. The habitats originally located in the southeast of the Qinghai-Tibet Plateau have mainly extended northeastwards, while the habitats originally located in the northwest has been largely lost. The changes in the habitats of ungulate species in the southeast and northwest are diametrically opposite. The key protected areas identified by Zonation model are mainly located in the southeast of the Qinghai-Tibet Plateau. The existing nature reserves can effectively protect the suitable habitats of the Tibetan antelope, Tibetan wild ass and wild yak. This research can provide scientific basis for coordinating the contradiction between development and protection and promoting the biodiversity conservation on the Qinghai-Tibet Plateau.

Composition and Diversity of Soil Microbial Community Associated With Land Use Types in the Agro-Pastoral Area in the Upper Yellow River Basin.

The microorganisms of soil are sensitive to their living microenvironment, and their community structure and function will change with the environmental conditions. In the agro-pastoral area on the Qinghai-Tibet Plateau, revealing the diversity of the soil microbial communities and its response to different soil physicochemical properties and environmental factors are important for ecosystem management. The microbial (bacteria and archaea) community composition and diversity under different land use types (cultivated land, grazing grassland and planted forest) were analyzed by 16S rRNA (V4 region) method in a typical agro-pastoral region in the upper Yellow River basin. Also, the soil nutrients were studied and correlated with the microbial community. The results showed that the soil nutrient contents in grassland were low, but the available nutrients were relatively high. There was a great spatial variability under different distances to the river. The microbial community diversity was lower in the grassland than the cultivated land and forest land closer to the river. For all land uses, the dominant phyla of soil microorganisms included Proteobacteria, Actinobacteria, and Bacteroidetes, while the abundance of Clostridia was significantly higher than that of the other groups, indicating that Clostridia dominated the Firmicutes and affected soil microbial community composition. The linear discriminant analysis (LDA) effect size (LefSe) analysis showed different biomarkers were more abundant in grassland than other land use types, suggesting that the structure and diversity of soil microorganisms in grassland were significantly different compared with cultivated land and forest land. The distance-based redundancy analysis (db-RDA) results showed that the total phosphorus (TP) and calcium (Ca) were the key environmental factors affecting the diversity and abundance of the soil microbial community in cultivated land and forestland, respectively. However, the microbial diversity in grassland was more related to spatial distance of the river. These results provided a theoretical basis for the changes in the composition, structure, and function of soil microbial communities in agro-pastoral areas.

Effects of the interaction among climate, terrain and human activities on biodiversity on the Qinghai-Tibet Plateau.

Disentangling the driving factors of biodiversity is critical for understanding biogeographical patterns of vegetation and ecosystem function. However, the biotic and abiotic attributes that shape biodiversity on the Qinghai-Tibet Plateau (QTP) are still not been quantified. Previous studies have not distinguished the direct and indirect effects of climate, terrain, and human disturbance on biodiversity. In this study, we applied a structural equation model (SEM) to assess the interactions among 4 attributes and biodiversity. A conceptual framework with 8 explanatory variables was built to identify the driving forces of biodiversity. A geographically weighted regression (GWR) model was applied to explore the response sensitivity of biodiversity to climate, terrain, and human attributes. We found that the SEM passed the tests of validity, reliability and fit, indicating that the hypothetical model was reasonable and credible. Among terrain conditions, elevation had the greatest, most-negative effect on biodiversity. Among the human factors, distance to town showed the strongest and most negative influence on biodiversity. Among the climate factors, precipitation had the greatest influence on biodiversity. Moreover, the direct effects of terrain and human activity were 0.348 and 0.135, respectively, and their indirect effects were 0.769 and 0.213, respectively, revealing that they had stronger indirect effects on biodiversity than direct effects. Climate exhibited only direct effects on biodiversity and had no indirect effects. The total effects of climate, terrain and human activity on biodiversity were 1.39, 0.35 and 0.13, respectively, indicating that climate was the main driving force of biodiversity on the QTP. The response sensitivity of biodiversity to climate, terrain and human factors showed obvious spatial variations. This study contributes to exploring the interactive effects and driving mechanisms of human-natural attributes on biodiversity and provides further effective guidance and support for biodiversity conservation and restoration.

Spatio-temporal evolution scenarios and the coupling analysis of ecosystem services with land use change in China.

Ecosystem service (ES) supply and demand are affected by changes in land use and the supply of specific ecosystem services for human consumption, respectively. Future spatio-temporal dynamics and their coupling relations with land use in China have not been well analysed. In this study, based on future land use scenarios of Li's database, ES supply, demand and balance (supply minus demand) were revealed utilizing land use and land cover (LULC) matrix model in China in 2010, 2050 and 2100. The results showed that ES supply, demand and balance had great spatial and temporal variations under different scenarios at national and provincial scales. Higher population and higher urban expansion scenarios will lead to a significant decreasing in the balance values of different categories and total ESs in most provinces. The ecological sensitivity index was calculated to indicate the impact of land use intensity on ecosystem services. The results showed that the sensitivity levels in approximately 90% of provinces were low for all the scenarios, as only Anhui, Zhejiang, Jiangxi and Liaoning in 2050 and Gansu in 2100 were extremely sensitive to changes in supply, while only provinces in the central-eastern regions were sensitive with obvious differences from the demand. The coupling coordination analysis between land use intensity and ES balance was applied to identify the provinces with low-level coordination in land use and ES management. The results showed that the coordination change in most provinces remained stable under four scenarios. However, some provinces displayed an improving trend from low to moderate coordination or from moderate to high coordination and a degrading trend from moderate to low coordination or from high to moderate coordination from 2010 to 2100. This study contributes to exploring the effect of land use on ecosystem service evolution, thereby providing credible guidance for future land and ES management.