Integrated water security and coupling of social-ecological system to improve river basin sustainability.

The river basin sustainability depends on both the coordinated development of socio-ecological systems and resilience to water resources. However, the lack of integrating them on spatial and temporal scales compromises our capacity to develop precise interventions towards sustainable river basins. We developed an approach by integrating water security and social-ecological coupling to assess the river basin sustainability. We divided it into four categories including highly sustainable (secure and coordinated), insecure, uncoordinated, and low sustainable (insecure and uncoordinated). The middle reach of Heihe River (MHR) was taken as the study area with the sub-basin as the spatial analysis unit from 2000 to 2020. The results showed that there was heterogeneity and agglomeration in spatial distribution. 23.8 %, 38.8 %, and 11% of the sub-basins mainly clustered in the north and central areas were found in the state of water insecure and SES uncoordinated, or both respectively. The unsustainable areas (five sub-basins) and lose-lose areas (two sub-basins) should be the priority areas for management interventions. Our approach can provide an important reference for assessing and improving the river basin sustainability.

Assessing progress towards sustainable development goals for Chinese urban land use: A new cloud model approach.

Rapid urbanization poses great challenges to China's urban land use sustainability (ULUS). Land is the essential space to achieve the Sustainable Development Goals (SDGs) of the United Nations, so SDGs provide a new guide to evaluate land use sustainability. However, there is still a lack of SDGs-oriented assessment of urban land use at national level. Moreover, there is still a need to address the problems about the randomness and fuzziness within evaluation, which tends to cause more uncertainties. Here we developed a SDGs-oriented evaluation framework based on the cloud model and derived the spatial and temporal patterns of urban land use sustainability for China at the prefecture-level from 2004 to 2019. Then, we used the McKinsey matrix to classify the types of urban land use sustainability, and examined their main drivers using the Geodetector method. The results showed that the development level of ULUS in China was high in the east and low in the west. High-value hotspots were mainly distributed in primary and secondary urban agglomerations in China. From 2004 to 2019, the development level of ULUS in China gradually increased, but the growth rate slowed down. In 2009 the value of central China exceeded that of the northeast. In contrast, the coordination level of ULUS had declined in more than 50% of Chinese cities during the study period. The high values were in southern China, northeast China, and Chengdu-Chongqing urban agglomeration, while the low values were in central and southern Liaoning and the urban agglomeration in the Central Plains. The development level was mainly controlled by anthropogenic activities and urban development, while natural conditions constrained the improvement of the coordination level. Combining the development and coordination, we found that cities with higher development level often had a wide range of coordination level, and suggestions were put forward for different regions to achieve sustainable land use. Our research provides scientific guidance for China's territory planning and sustainable urban development.

Circuit theory-based ecological security pattern could promote ecological protection in the Heihe River Basin of China.

Building ecological security patterns is essential to maintain regional ecological security and achieve sustainable development in the inland river basins with ecologically vulnerable environment. Numerous methods have been developed to build the ecological security pattern. However, to our knowledge, rare studies have quantified to what extent the derived pattern can improve ecological protection in the future. Taking Heihe River Basin (HRB), the second largest inland river basin in China, as the study area, we applied the circuit theory to build the ecological security pattern of HRB, and simulated how our built pattern contributed to ecological protection using the CLUMondo model. The results showed that the ecological security pattern of HRB contained 17 ecological sources, 35 key ecological corridors, and some ecological strategic points. The ecological sources were distributed in areas with better ecological conditions such as the Qilian Mountain Nature Reserve and Heihe National Wetland Park. The ecological corridors showed a pattern of "two horizontal and three vertical belts." Pinch points were mostly close to ecological sources or distributed on the corridors that played a key role in landscape connectivity, while barriers were mainly distributed on the corridors with large ecological resistance in the middle and lower reaches. The optimal ecological security pattern presented a "one screen, one belt, four districts and multiple centers" shape in HRB and could more effectively promote ecological protection compared to current development and protection scenarios. Our study provides a reliable decision-making guide for ecological protection and restoration of HRB, and can be extended to build ecological security patterns for broad-scale arid areas.

Fuzzy evaluation of the ecological security of land resources in mainland China based on the Pressure-State-Response framework.

The extensive exploitation and use of land resources has caused a variety of land degradation problems including soil erosion, desertification and salinization in China, which gradually raises our concerns of ecological security. However, there still lacks an understanding of ecological security of land resources at the national scale. Moreover, few studies conduct the validation and uncertainty analysis of models for ecological security evaluation, which tends to undermine the reliability of evaluation results. Here we followed the Pressure-State-Response (PSR) framework to systematically construct the evaluation index system for ecological security, and developed fuzzy evaluation models to convert the original index data into individual index scores. After that, we used the multiplicative model to aggregate the individual index scores into a comprehensive evaluation score for the ecological security level of land resources across the Chinese mainland. To enhance the reliability of evaluation results, we validated our results by comparing with the proxies of ecological effects including landscape pattern index, land use change rate and net primary productivity, and made uncertainty analysis using the Monte Carlo method. Finally, we applied an obstacle model to quantify the negative contribution of pressure, state and response which would deter the security from achieving the optimal condition. The results showed that our model could effectively reflect the ecological security level of land resources. The pressure was higher in the east and lower in the west of China, and that of urban areas was much higher than the rural areas, reflecting the disturbance of socio-economic activities. The state condition was strongly related to natural conditions. The response level, determined mainly by socio-economic conditions, was higher in the southeast and northwest of China but lower in the northeast and southwest of China. The ecological security level was structured by natural and socio-economic conditions and demonstrated a high level of security in the southeast while a low level in the northwest. Developed urban areas often had low security due to strong socio-economic pressure. Areas with unfavorable natural and environmental conditions had poor state level, which tended to cause lower response capability, and consequently led to a low security level. Our research improves the understanding of national ecological security and its obstacle factors, which supports the management and sustainable use of land resources at the national scale.

Spatial-temporal pattern of land use conflict in China and its multilevel driving mechanisms.

Land use conflict describes the incoordination of land use structure when meeting the diverse human demands under the deterioration of natural environment, which is a sensitive indicator of human-environmental interaction. The increased demand for different land use types due to rapid population growth and urbanization in China places tremendous pressure on limited land resources, which raises great concerns about land use conflict. To solve them, nation-scale assessment is essential, but such kind of research is still lacking due to the high data requirements. Here we drew on the conceptual framework of ecological risk assessment and the theories in landscape ecology, and developed a methodology to derive the spatio-temporal patterns of land use conflict in China from 2001 to 2017. We then used multilevel regression model to identify the driving factors of land use conflict at different levels. The results showed that the areas with strong land use conflict had a higher frequency of land use change, indicating that our model based on the framework of ecological risk assessment could effectively measure land use conflict. Land use conflict showed significant differences between two sides of the Hu Huanyong line, an important division line of population density and socio-economic background. The Main types of land use conflict in China included the strong competition between the use of cultivated land and grassland, the rapid expansion of construction land and the high risk of desertification. Among the driving forces, population density had a positive impact on land use conflict at the upper level, and altitude had a negative impact at the bottom level. Our research provides essential information to solve land use conflict through scientific land use planning and management and further to achieve the sustainable use of land resources.

Spatio-temporal Analysis of Anthropogenic Disturbances on Landscape Pattern of Tourist Destinations: a case study in the Li River Basin, China.

The impact of human-related activities on the eco-environment of tourist destinations is an important part of recreation ecology research. However, traditional studies have mainly concentrated on the static influences upon the simple factors of soil or vegetation in tourist destinations, and the relationship between anthropogenic disturbances and landscape patterns is little understood. In this study, we constructed a disturbance model on a landscape scale to identify and quantify the main anthropogenic disturbances. The overall variation coefficient (OVC) index is defined as the intensity of different disturbance sources, and landscape structure analysis methods are used for temporal and spatial differentiation, which is applied in the Li River Basin, China. Three typical types of human-related activities are identified as possible anthropogenic disturbance sources in the region, and their notable influential spheres are determined. Then, the dynamic changes in tourism disturbance in two periods and the spatial distribution characteristics related to three factors are explored. The results suggest that settlement and tourism disturbances have exerted considerable impacts on landscape patterns, and the differentiation characteristics are closely related to local tourism development policies and patterns. The disturbance model could be applied in other tourism destinations and provide countermeasures for regional tourism management.

Predicting the patterns of change in spring onset and false springs in China during the twenty-first century.

Spring onset has generally shifted earlier in China over the past several decades in response to the warming climate. However, future changes in spring onset and false springs, which will have profound effects on ecosystems, are still not well understood. Here, we used the extended form of the Spring Indices model (SI-x) to project changes in the first leaf and first bloom dates, and predicted false springs for the historical (1950-2005) and future (2006-2100) periods based on the downscaled daily maximum/minimum temperatures under two emission scenarios from 21 General Circulation Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5). On average, first leaf and first bloom in China were projected to occur 21 and 23 days earlier, respectively, by the end of the twenty-first century in the Representative Concentration Pathway (RCP) 8.5 scenario. Areas with greater earlier shifts in spring onset were in the warm temperate zone, as well as the north and middle subtropical zones of China. Early false spring risk increased rapidly in the warm temperate and north subtropical zones, while that declined in the cold temperate zone. Relative to early false spring risk, late false spring risk showed a common increase with smaller magnitude in the RCP 8.5 scenario but might cause greater damage to ecosystems because plants tend to become more vulnerable to the later occurrence of a freeze event. We conclude that future climate warming will continue to cause earlier occurrence of spring onset in general, but might counterintuitively increase plant damage risk in natural and agricultural systems of the warm temperate and subtropical China.

Comparison of the driving forces of spring phenology among savanna landscapes by including combined spatial and temporal heterogeneity.

Understanding spatial and temporal dynamics of land surface phenology (LSP) and its driving forces are critical for providing information relevant to short- and long-term decision making, particularly as it relates to climate response planning. With the third generation Global Inventory Monitoring and Modeling System (GIMMS3g) Normalized Difference Vegetation Index (NDVI) data and environmental data from multiple sources, we investigated the spatio-temporal changes in the start of the growing season (SOS) in southern African savannas from 1982 through 2010 and determined its linkage to environmental factors using spatial panel data models. Overall, the SOS occurs earlier in the north compared to the south. This relates in part to the differences in ecosystems, with northern areas representing high rainfall and dense tree cover (mainly tree savannas), whereas the south has lower rainfall and sparse tree cover (mainly bush and grass savannas). From 1982 to 2010, an advanced trend was observed predominantly in the tree savanna areas of the north, whereas a delayed trend was chiefly found in the floodplain of the north and bush/grass savannas of the south. Different environmental drivers were detected within tree- and grass-dominated savannas, with a critical division being represented by the 800 mm isohyet. Our results supported the importance of water as a driver in this water-limited system, specifically preseason soil moisture, in determining the SOS in these water-limited, grass-dominated savannas. In addition, the research pointed to other, often overlooked, effects of preseason maximum and minimum temperatures on the SOS across the entire region. Higher preseason maximum temperatures led to an advance of the SOS, whereas the opposite effects of preseason minimum temperature were observed. With the rapid increase in global change research, this work will prove helpful for managing savanna landscapes and key to predicting how projected climate changes will affect regional vegetation phenology and productivity.

Determining the relative importance of climatic drivers on spring phenology in grassland ecosystems of semi-arid areas.

Understanding climate controls on spring phenology in grassland ecosystems is critically important in predicting the impacts of future climate change on grassland productivity and carbon storage. The third-generation Global Inventory Monitoring and Modeling System (GIMMS3g) normalized difference vegetation index (NDVI) data were applied to derive the start of the growing season (SOS) from 1982-2010 in grassland ecosystems of Ordos, a typical semi-arid area in China. Then, the conditional Granger causality method was utilized to quantify the directed functional connectivity between key climatic drivers and the SOS. The results show that the asymmetric Gaussian (AG) function is better in reducing noise of NDVI time series than the double logistic (DL) function within our study area. The southeastern Ordos has earlier occurrence and lower variability of the SOS, whereas the northwestern Ordos has later occurrence and higher variability of the SOS. The research also reveals that spring precipitation has stronger causal connectivity with the SOS than other climatic factors over different grassland ecosystem types. There is no statistically significant trend across the study area, while the similar pattern is observed for spring precipitation. Our study highlights the link of spring phenology with different grassland types, and the use of coupling remote sensing and econometric tools. With the dramatic increase in global change research, Granger causality method augurs well for further development and application of time-series modeling of complex social-ecological systems at the intersection of remote sensing and landscape changes.

[Research progress on index system of regional ecological risk assessment].

Regional ecological risk assessment (RERA) covers the assessments of multiple risk sources, receptors, and endpoints, while the selection of assessment indices is quite complicated, being a hotspot in regional environment management research. Domestic and international researches on RERA revealed that three processes in RERA are of vital, i.e., risk probability assessment measured by risk probability index, status and value assessment of ecosystem at regional scale indicated by ecological index, and vulnerability assessment of each ecosystem in a region under risk measured by vulnerability index. The main problems in the establishment of RERA index system are the strong subjectivity and poor comparability, and thus, the index system should be set up in the three key processes under the principles of objectivity, integration, hierarchy, and comparability. Due to the fact that the status and value assessment of ecosystem is most complicated, the index system should be formulated by compulsory and optional components to increase the comparability of RERA results between regions.