In conservation biology, umbrella species are often used as agents for a broader set of species, or as representatives of an ecosystem, and their conservation is expected to benefit a large number of naturally co-occurring species. Southwest China is home to not only global biodiversity hotspots, but also rapid economic and population growth and extensive changes in land use. However, because of the large regional span, the diverse species distributions, and the difficulty of field investigations, traditional methods used to assess umbrella species are not suitable for implementation in Southwest China. In the current study, we assessed 810 key protected species from seven taxa by indicator value analysis, correlation analysis, and factor analysis. We selected 32 species as umbrella species, whose habitats overlapped the habitats of 97% of the total species. Furthermore, the selected species were significantly correlated with 70% of all species in the study area. A total of 16 out of 19 selected animal species have been previously mentioned as umbrella species, compared with only 3 out of 13 plants species; this is despite plants accounting for a large proportion of the total species in Southwest China. We discuss the roles of indicator species and co-occurring species, and provide suggestions for species protection in Southwest China based on the current results. Our research provides valuable scientific information for research on umbrella conservation species over large geographical scales, and related fields of biodiversity conservation.

A bibliometric analysis of current research, hotspots, and development trends was used to develop an overall framework of mechanisms of alpine grassland degradation on the Qinghai-Tibet Plateau. This investigation includes data from 1,330 articles on alpine grassland degradation on the Qinghai-Tibet Plateau, acquired from the Chinese Science Citation Database (CSCD) and Web of Science Core Collection (WOS). Research was divided into three themes: spatial scope and management of typical grassland degradation problems, dynamic mechanisms of grassland degradation and effects of ecological engineering, and grassland degradation risk based on remote sensing technology. The results of the analysis showed that the research can be summarized into three aspects: typical grassland degradation identification, dynamic mechanism analysis of grassland degradation, and grassland ecosystem stability strategy. The main findings can summarized, as follows: (1) Ecological analyses using the river source as a typical region defined the formation of “black soil beach” type degraded grasslands in the region, and promoted the ecological environment management and protection of the alpine grassland by discussing the causes of regional ecological environment changes; (2) Dynamic mechanism analyses of climate change and characteristics analyses of grassland vegetation-soil degradation revealed that alpine grassland degradation is the result of multiple main factors; and (3) Risk prediction methods for grassland degradation, methods of grassland management and sustainable countermeasures for agriculture and animal husbandry development, and the development of a comprehensive index of influencing factors on grassland degradation all indicate that selecting the right grassland restoration measures is the key to grassland restoration. Remote sensing monitoring and high-throughput sequencing technology should be used in future research on grassland ecosystems. In addition, multiscale, multidimensional, and multidisciplinary systematic research methods and long-term series data mining could help identify the characteristics and causes of alpine grassland system degradation. These findings can help identify a more effective coordination of landscape, water, lake, field, forest, grass, and sand management for the prevention of alpine grassland degradation.

By 2050, 70% of the human population is likely to be living in cities, making urbanization an increasing global trend. Detecting changes in ecosystem services (ES) and their bundles in response to urbanization is critical for evaluating land-use policies. We examined changes in the provision of grains, vegetables, fruits, carbon sequestration, soil retention, sandstorm prevention, and water retention from 2000 to 2010 in the Beijing–Tianjin–Hebei metropolitan area, China; then, using a k-means cluster analysis, we classified 202 counties of this area into groups (bundles) based on their similar sets of ES. We found that (1) urban area, forestland, and grassland increased by 22%, 3.6%, and 1.7%, respectively, while cropland decreased by 4.6%; (2) the provision of grains, vegetables, and fruits increased by 24–90%, despite an overall loss in cropland; carbon storage and sand retention increased by 40% and 7%, respectively, while soil and water retention increased slightly by approx. 1% each; (3) 72 counties changed their ES bundles; and the “agriculture bundle” dominated the landscape in 2000 while it decreased by 50% in 2010 and was mainly transformed to “sub-developed urban bundle”, indicating loss of cropland during that decade. The transformation of ES bundles can be used to understand the effects of urbanization. The study indicated that improved technologies and ecological restoration in rural areas can help sustain multiple ES in our rapidly urbanizing world.

Biodiversity, regulating ecosystem services (RES), and vegetation productivity are key indicators to instruct natural conservation planning. Decision makers often hope that ecosystems can be protected by focusing on certain key indicators, which requires an understanding of the relationships between the indicators. Using individual case studies, many have argued that these indicators commonly have significant relationships. However, these relationships at different spatial scales are unclear. Therefore, in this study, biodiversity and ecosystem services are modelled by the ecological niche model, the universal soil loss equation, and the equation of water balance in two study areas at different scales. The influence of vegetation productivity on the spatial pattern of other ecological indicators in the two areas is examined by a spatial lag model. The contributions of the driving factors on biodiversity distribution at both scales are identified by a boosted regression tree (BRT) model. The results showed that at the fine scale, the spatial correlations were strongest for species richness, especially mammalian species richness, and water retention. However, biodiversity had no significant relationship with vegetation productivity. In contrast, at a coarser scale, the correlation was stronger between plant diversity and regulating ecosystem services. In addition, plant diversity was significantly correlated with vegetation productivity. These differences between scales were controlled by various explanatory variables. At the fine scale, biophysical and climatic factors had the strongest effects on biodiversity distribution, while Net Primary Productivity (NPP) and ecoregion also had relatively high influences on biodiversity at the coarse scale. This demonstrates the critical importance of spatial scale in selecting conservation indicators. We suggest that rare mammalian species richness or flagship mammal species are suitable as conservation surrogates in fine-scale conservation planning. However, at a coarser scale, selecting vegetation patches with more rare plant species and high productivity for each ecoregion is a workable alternative method for conservation planning.

The real emission mitigation by the ecological restoration projects depends upon the integrated effect of all greenhouse gas (GHG) budgets rather than the carbon sequestration alone. However, a comprehensive and robust methodology for estimating the relevant GHG budgets and net mitigation of China's ecological restoration projects is still urgently to await development. Based on the methods from IPCC and statistical data of the management practices under the projects, we constructed a methodology for carbon accounting and determining net mitigation for ecological restoration projects in China (CANM-EP). GHG emissions generated from different processes and practices of the projects were included in the CANM-EP, and by this methodology, carbon sequestration, GHG balance changes induced by ecological response, on-site and off-site GHG emissions could be estimated. Therefore, the CANM-EP provides comprehensive methods to estimate the whole GHG budgets as well as the net mitigation of China's ecological restoration projects. •The CANM-EP provides accounting methods for comprehensive processes and management practices under respective ecological restoration projects in China.•The CANM-EP could simultaneously estimate carbon sequestration and GHG emissions of the projects.•The CANM-EP indicates net carbon sequestration and net contribution of China's ecological restoration projects to climate change mitigation.

National parks (NPs) are the flagship protected areas in China’s conservation network and play a key role in the ecological protection of core objects and important natural landscapes. However, the shortage of spatial optimization methods based on quantitative indicators has limited the spatially explicit identification of national parks. Therefore, in this study, we selected the main area of the Tarim River (MTR) in Xinjiang as an example to optimize the spatial boundary of a national park. We constructed an evaluation system based on representativeness, ecological importance, and the foundation of the existing protected area. Subsequently, we comprehensively employed a species distribution model to simulate the habitat of the primary conservation targets. Additionally, we spatially optimized the region using an integer linear model, considering multiple scenarios. The results of this study show that fewer than 30% of the existing protected areas in the MTR protect conservation objects. Using different protection objects and quantitative goals, the spatial optimization results for the eight protection scenarios show that the most effective national park establishment scenario covers a total area of 15,009.3 km², which is 8157.5 km² more than the protected area already in place and would include the Tarim Populus National Nature Reserve and Luntai Tarim Populus Forest Park. The opportunity cost to be paid for protection according to this boundary is approximately USD 115.14 million. The protection ratios of each protection object for the expanded park are more than 50%, which is 27.7% higher than the protection effect produced by the existing protected area, so we recommend that Tarim National Park be set up on the basis of this boundary.