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Water use efficiency (WUE) is an important indicator in linking the carbon and water cycles of ecosystems. Previous studies performed in alpine and cold regions have contributed greatly to understanding the WUE response of single ecosystem or specific species in small-scale regions to climatic factors; however, studies focusing on differences in the WUE response among ecosystems or species are insufficient, which has limited the understanding of the climatic adaptation of WUE in alpine and cold regions. Here, based on the 134 leaf δ13C records measured for the 46 dominant species in two main ecosystems on the Qinghai-Tibetan Plateau, variation in the response of WUE among biomes was analyzed by grouped linear regression, redundancy analysis (RDA), and structural equation models (SEMs). The results showed that (1) photosynthetically active radiation (PAR0), moisture index (MI) and vapor pressure deficit (VPD) were significantly correlated with the variation in WUE; (2) compared with the WUE of alpine grasslands, alpine desert grasslands was more sensitive to climatic factors, which presenting a steeper slope that varied with modified growing degree days (MGDD0), PAR0, MI, VPD and CO2; (3) composition of genera distributions explained 32.22% of the variation in WUE, while the WUE of Stipa was more sensitive compared to other species to most climatic factors; (4) climate (composition of genera) and their joint effects explained 58.98% (63.53%) of the variation in WUE of alpine desert grasslands (alpine grasslands), while altitude indirectly controlled the WUE variation in alpine grasslands and MI directly controlled the WUE variation in alpine desert grasslands. This study quantified the driving effects of climates and biomes on the variation in WUE and contributed to the understanding of vegetation adaptation in alpine and cold regions.

Biodiversity and ecosystem services are seriously threatened by human activities, and there have been calls for the expansion of protected areas (PAs) to mitigate this situation. Currently, there is an urgent need to establish new PA cost-effectively from concentrating on biodiversity to including the provision of ecosystem services. Hence, a prefectural evaluation was conducted across the Qinghai-Tibet Plateau (QTP) to quantify endangered species habitat provision and three key ecosystem services to identify conservation priority zones (CPZs), which were then combined with low human footprint zones to determine cost–effective zones (CEZs). A scenario simulation, which contains conservative, moderate, and ambitious targets, was further proposed to conserve more CEZs for PA design. We found that biodiversity, ecosystem services, and human footprints varied significantly among the different taxonomic groups. CPZs and CEZs cover 33 and 28 % of the QTP, respectively, including almost all forest areas, and near medium and high elevations (approximately 3000 ∼ 4700 m). In comparison with existing PAs systems, the new PAs system is considering cost-effective in terms of biodiversity and ecosystem services, increasing 42–60 %, 32–46 %, and 62–69 %, and 47–62 % of the important habitats that serve mammals, birds, amphibians, and plants, respectively, and promoting 48–66 % carbon service, 37–54 % soil retention, and 22–37 % water yield. More importantly, it reduces conflict with the human footprint by up to 22 %. Moreover, the conservative, moderate, and ambitious targets conserved 44, 48, and 53 % of the QTP, respectively. These three targets were set for each prefecture and prefectural–level city with spatially specific CEZs recognized, providing some implications on prefectural PAs priorities for policymakers.

Although biodiversity has been shown to profoundly affect ecosystem function in forests, the processes which it impacts are limited understood. Various plant species with diverse sizes interact to form complex networks to complete resource use processes, but little is known about the role of species-size networks in influencing ecosystem function and biodiversity-ecosystem function relationships. Using a dataset encompassing 423 species and 32,067 individuals, we constructed species–tree diameter and species–tree height networks for two sampling areas (0.04 and 0.09 ha), and then calculated the network modularity for species and size interlinked specialization and nestedness, species or sizes with relatively few links are a subset of those with more network links. We analyzed the relationships between modularity, nestedness, and the aboveground biomass. The direct and indirect effects of species abundance and richness on the aboveground biomass through network structures were explored using structural equation modelling. Regardless of the species–tree diameter or height network, modularity was positively associated with the aboveground biomass, independent of the sampling area, while nestedness was negatively associated. Species abundance negatively affected the modularity, but positively affected nestedness, whereas species richness had the opposite effect. Species abundance and richness affected the aboveground biomass indirectly through modularity and nestedness, but the effect of modularity was greater than that of nestedness. Our study confirms that the importance of species–size networks in the context of the aboveground biomass has similar effects on species–diameter and height networks across sampling areas. It clarifies that modularity from interactions between species and individuals is a useful indicator to reveal the mechanism by which plant diversity acquires resources for biomass production. These results provide new insights into biodiversity–ecosystem function relationships from a network perspective.

Dynamic monitoring of forest ecosystem quality is necessary for restoration program evaluation but remains challenging for very large-scale programs. Current evaluation methods employ regional forest quality indicators that compare the quality status of targeted forests with benchmarks from remnant old-growth forest communities, however data availability usually limits the application of available methods to small scales. We constructed an improved framework, integrating forest site classification selection and local remnant old-growth forest community delimitation, to quantify and map forest quality using environmental data and remote sensing (RS) based approaches. A classification strength model was introduced to improve the accuracy of forest site classification. The remote-sensing-based method integrates species composition and forest biological productivity characteristics recognition to develop a practical tool for large-scale remnant old-growth forest community delimitation. The new assessment framework was tested across the entire spatially heterogeneous Yangtze River Basin, the largest watershed in China and showed high accuracy in forest quality assessment based on observed field data validation. The forest site classification was selected by considering spatial heterogeneities in climate, topography and soil type, with 37 forest sites classified. The native forest community groups with less human disturbance in each forest site used for forest quality baseline estimation were also selected as forests with top 10% of biomass in protected areas. The case study demonstrated that forest areas of low and poor quality accounted for 34.46% of the total forest area in 2015. Between 2000 and 2015, 55.72% of forest areas experienced increases in quality level, and 7.07% experienced decreases. The improved forest quality assessment framework enhances the scope and accuracy of forest restoration information and can be applied as an evaluation tool for forest restoration management.