Ecosystem services (ES) delivery in quantity and quality are essential to improve human wellbeing. Nevertheless, often a considerable part of ES provisioning depends on the use of private land (e.g., flood retention, carbon sequestration, water purification). In this context, the operationalization and implementation of ES concept may collide with legal property rights. Therefore, it is essential to find constructive mechanisms to engage and encourage private owners to implement sustainable land uses to reduce the onsite and offsite impacts of their activities. This paper aims to identify if ES delivery can be constrained by legal private land and how it can be tackled. It is undeniable that land-use changes (e.g., urbanization, agriculture intensification, and land abandonment) affect the territory's capacity to deliver ES in quality and quantity. These changes, especially land abandonment, are increasing the tradeoffs among ES (e.g., between carbon sequestration and water yield). Land-use planning should consider these aspects. Therefore, incorporating ES into spatial plans is crucial for stakeholders to understand the impacts of land-use change in the loss of ES value. This information can be transmitted through maps that communicate the message in a simplified way. Private owners can easily perceive the ES relevance that their land can provide if an understandable message is delivered. Although this can be a good solution, conflicts can appear even with the implementation of schemes such as Payment for ES (PES). PES is not always effective and can impose losses to farmers, disregard their cultural traditions, or not prevent poverty alleviation. In this context, it is crucial to consider local specificities to safeguard PES's success, create a “win-win” and transform a problem into a solution. Private owners' active participation in implementing sustainable practices or a determined land-use in their properties is vital to achieving global targets such as sustainable development goals.

Grassland ecosystems support well-being with food, shelter, income, and culture of herdsmen. While the association between ecosystem services and human well-being has been widely studied, such association is understudied in grassland ecosystems. This study aims to fill this gap through a case study of Xilinhot City, Inner Mongolia Autonomous Region, China. We examined the association between grassland provisioning services and herdsmen's well-being between 1985 and 2015 through participatory observations, interviews, surveys, and Bayesian belief network modeling. Considering the uncertainties of weather and sheep prices, we developed four scenarios to examine the future well-being of herdsmen. Our results show that the most important factor for herdsmen's well-being was income, which is highly sensitive to the market price of sheep and precipitation. Considering the uncertainties of sheep prices and precipitation, scenario analysis revealed a divergence between income and well-being. While herdsmen's income is most likely to increase with low precipitation and increased sheep prices, their well-being is most likely to improve with abundant precipitation and increased sheep prices. Based on our findings, we argue that developing alternative income sources (e.g., tourism), reducing dependence on government subsidies through commercial insurance, and branding lamb with grassland ecosystem to alleviate the impact of price fluctuations would help improve herdsmen's well-being in all scenarios.

Agriculture consumes huge amounts of water in China and is profoundly affected by climate change. This study projects the agricultural water use towards 2030 under the climate change mitigation target at the provincial level in China by linking a computable general equilibrium (CGE) model and a regression model. By solving the endogeneities amongst agricultural water use, output and climate factors, we explore how these variables affect water use and further predict future trends through soft-link with the IMED|CGE model. It is found that sunshine duration has a slightly positive impact on water use. Furthermore, agricultural output will significantly drive agricultural water use based on historical data of the past 16 years. Results also show that carbon reduction would have a trade-off or co-benefit effect on water use due to regional disparity. Provinces with increasing agricultural exports, such as Xinjiang and Ningxia, would anticipate considerable growth in agricultural water use induced by carbon reduction. The soft-link method proposed by this study could be applied for future studies that aim to incorporate natural and geographical factors into human activities, and vice versa, for assessing sustainable development policies in an integrated way.

Climate, land use and land cover (LULC) changes are among the primary driving forces of soil loss. Decoupling their effects can help in understanding the magnitude and trend of soil loss in response to human activities and ecosystem management. Here, the RUSLE model was applied to estimate the spatial-temporal variations of soil loss rate in the Three Gorges Reservoir (TGR) area during 2001-2015, followed by a scenario design to decouple the effects of climate and LULC changes. The results showed that increasing rainfall generated as much as 2.90 × 10⁷ t soil loss in the TGR area. However, such effect was offset by changes in LULC particularly afforestation, which retained about 1.10 × 10⁷ t soil annually. Other human activities such as dam development and urbanization aggravated soil loss by as much as 1.40 × 10⁶ t annually. Because of land use policies that favor economic development, distinct spatial variances of soil loss were observed in TGR area. Soil loss in some counties located downstream of the TGR area (i.e., close to the dam) was more influenced by dam development, but soil loss in the other counties was more influenced by urbanization. As climate change (i.e., increasing rainfall) did not affect plant performance in TGR area, our findings suggested that ecological restoration was more beneficial to curb the amount of soil loss caused by urbanization and dam construction.

Climate change requires joint actions between government and local actors. Understanding the perception of people and communities is critical for designing climate change adaptation strategies. Those most affected by climate change are populations in coastal regions that face extreme weather events and sea-level increases. In this article, geospatial perception of climate change is identified, and the research parameters are quantified. In addition to investigating the correlations of hotspots on the topic of climate change perception with a focus on coastal communities, Natural Language Processing (NLP) was used to examine the research interactions. A total of 27,138 articles sources from Google Scholar and Scopus were analyzed. A systematic method was used for data processing combining bibliometric analysis and machine learning. Publication trends were analyzed in English, Spanish and Portuguese. Publications in English (87%) were selected for network and data mining analysis. Most of the research was conducted in the USA, followed by India and China. The main research methods were identified through correlation networks. In many cases, social studies of perception are related to climatic methods and vegetation analysis supported by GIS. The analysis of keywords identified ten research topics: adaptation, risk, community, local, impact, livelihood, farmer, household, strategy, and variability. “Adaptation” is in the core of the correlation network of all keywords. The interdisciplinary analysis between social and environmental factors, suggest improvements are needed for research in this field. A single method cannot address understanding of a phenomenon as complicated as the socio-environmental. This study provides valuable information for future research by clarifying the current context of perception work carried out in the coastal regions; and identifying the tools best suited for carrying out this type of research.

Global warming and rapid economic development have led to increased levels of disaster risk in China. Previous attempts at assessing drought risk were highly subjective in terms of assessment methods and selection of the assessment indicators and which resulted in appreciable uncertainty in the results of these risk assessments. Based on the assumption that areas with historically high drought losses are more likely to suffer future high drought losses, we develop a new drought risk assessment model that includes historical drought loss data. With this model, we map the regional differentiation of Chinese drought risk. Regions with high (extreme high) drought risk account for 4.3% of China's area. Five significant high-risk areas have been identified: Northeast China, North China, the east part of Northwest China, the east part of Southwest China and a small part in the west of Northwest China. Areas with high and extreme high drought risk are dominant in the Heilongjiang Province, accounting for 32% of the total area, followed by the Ningxia Hui Autonomous Region, with 26% of total area. The contribution of each influencing factor has been quantified, which indicates that high-exposure and high-vulnerability account for the high-risk of drought. We recommend that measures like strengthening the protection of cultivated land and reducing dependence on the primary industry should be taken to mitigate to drought-induced losses.

Tillage is the most common agricultural practice dating back to the origin of agriculture. In recent decades, no-tillage (NT) has been introduced to improve soil and water quality. However, changes in soil properties resulting from long-term NT can increase losses of dissolved phosphorus, nitrate and some classes of pesticides, and NT effect on nitrous oxide (N₂O) emission remains controversial. Complementary management that enhances the overall environmental benefits of NT is therefore crucial. By incorporating cover crops, nutrient cycling and nutrient use efficiency in NT fields could be improved given the nutrient supplying capacity of some cover crops. Cover crops could also offset the need for occasional tillage of NT cropland, an operation whose effect is only temporary in reducing, for example, soil compaction associated with NT management. When used in combination with NT, cover crop termination methods, using agrochemicals, should be carefully considered to prevent further jeopardy to water quality. Compared to herbicides, the use of roller crimping could potentially result in production cost saving while minimizing soil disturbance and export of agrochemicals. Future research should focus on various combinations of cover crop traits (e.g., decomposition rate) and management (e.g., timing of cover crop termination) that account for siteand cash crop-specific requirements.

The Tibetan Plateau (TP) is undergoing rapid urbanization. To improve urban sustainability and construct ecological security barriers, it is essential to quantify the spatial patterns of urbanization level on the TP, but the existing studies on the topic have been limited by the lack of socioeconomic data. This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01 (LJ1-01) high-resolution nighttime light (NTL) data. Specifically, the compounded night light index is used to quantify spatial patterns of urbanization level at multiple scales. The results showed that the TP had a low overall urbanization level with a large internal difference. The urbanization level in the northeast, southeast and south of the TP was relatively high, forming three hotspots centered in Xining City, Lhasa City and Shangri-La City, while the urbanization level in the central and western regions was relatively low. The analysis of influencing factors, based on the random forest model, showed that transportation and topography were the main factors affecting the TP's spatial patterns of urbanization level. The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas. These advantages are attributed to the high spatial resolution of the data, appropriate imaging time and unaffected by saturation phenomena. Thus, the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world, especially in less-developed regions lacking statistical data. Using this method, we refined the measurement of the TP's urbanization level in 2018 for multiple scales including the region, basin, prefecture and county levels, which provides basic information for the further urban sustainability research on the TP.

In 2018, a total of US$166 billion global economic losses and a new high of 55.3 Gt of CO₂ equivalent emission were generated by 831 climate-related extreme events. As the world's largest CO₂ emitter, we reported China's recent progresses and pitfalls in climate actions to achieve climate mitigation targets (i.e., limit warming to 1.5-2°C above the pre-industrial level). We first summarized China's integrated actions (2015 onwards) that benefit both climate change mitigation and Sustainable Development Goals (SDGs). These projects include re-structuring organizations, establishing working goals and actions, amending laws and regulations at national level, as well as increasing social awareness at community level. We then pointed out the shortcomings in different regions and sectors. Based on these analyses, we proposed five recommendations to help China improving its climate policy strategies, which include: 1) restructuring the economy to balance short-term and long-term conflicts; 2) developing circular economy with recycling mechanism and infrastructure; 3) building up unified national standards and more accurate indicators; 4) completing market mechanism for green economy and encouraging green consumption; and 5) enhancing technology innovations and local incentives via bottom-up actions.