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Highlights • Our RS-based method integrates 11 dimensional features to map urban land use. • We develop multi-dimensional DPSIR-based indicators to analyze urban land expansion. • Increasing sprawl while decreasing density reduces economic-socio-ecological benefits. • Quantifying the interactions between multiple indicators can aid urban planning. • Optimizing multi-dimensional trade-offs and synergies is the key to sustainability. Abstract Rapid urban land expansion not only stimulates socioeconomic development, but can lead to negative impacts that threaten regional food security, ecological construction, and sustainable urban development, including losses of cropland and habitats, the creation of housing bubbles, and reductions in biodiversity. Because these economic-socio-ecological problems are generally more serious in ecologically fragile areas, this study focuses on trends seen in Ganzhou District, a typical oasis city within the Heihe River Basin (HRB) in an arid-to-semi-arid area of China. We apply a remote-sensing (RS)-based method that incorporates 11 dimensional features of Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images to map changes in urban land, and also develop a series of multi-dimensional indicators within a drivers, pressures, states, impacts, and responses (DPSIR) framework to quantify urban land expansion. The results of this study show that the urban land area of Ganzhou District in 2016 had expanded by 394.43% from 1987 levels, from 1979.64 ha to 9787.86 ha. These increasing pressures, jointly driven by gross domestic product (GDP), urban population, cropland area, and the industrial structure indicator (ISI), have led to the worsening economic-socio-ecological states and impacts of urban land expansion. Specifically, between 1987 and 2016, expansion intensity (EIPI) and expansion rate pressure indicators (ERPI) increased from 60.27 ha/a to 520.88 ha/a, and from 3.04%/a to 10.21%/a, respectively. Thus, the state indicators of economic development (EDSI), population carrying capacity (FDSI), food security (FSSI), and ecological construction (ECSI) decreased by 2.21 × 103 USD/ha, 17.62 population/ha, 34.20, and 10.80, respectively. Moreover, the impact indicators of economic development (EDII), population carrying capacity (FDII), and food security (FSII) decreased by 150.68 × 103 USD/ha, 62.12 population/ha, and 27.31, respectively, while the ecological construction impact indicator (ECII) increased by 29.39 between 1997 and 2007 and decreased by 13.31 between 2007 and 2016. Data also show that the area and proportion of cropland and ecological land occupied by urban land expansion increased over time. We therefore propose a series of economic-socio-ecological responses to help limit urban sprawl and foster compact green cities. Measures include planning urban growth boundaries, revitalizing urban centers and brownfields, using and re-using urban land more efficiently, strengthening land regulations, curbing excessive cropland expansion, cultivating more urban green spaces, and optimizing the trade-offs and synergies between multiple conflicting dimensions. [ABSTRACT FROM AUTHOR]

Human-induced land use changes over short time scales have significant impacts on water yield, especially in China because of the rapid social economic development. As the biggest developing country of the world, China's economy is expected to continuously grow with a high speed in the next few decades. Therefore, what kind of land use changes will occur in the future in China? How these changes will influence the water yields? To address this issue, we assessed the water yields in the karst mountain area of China during the periods of 1990–2010 and 2010–2030 by coupling an Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and a Conversion of Land Use and its Effects (CLUE) model. Three different land use scenarios i.e. natural growth, economic development, and ecological protection, were developed in 2030 using the CLUE model. It was concluded that, given land use changes between 1990 and 2010, total water yields in the karst mountain area are characterized by a trend towards fluctuating reduction. However, total water yields of 2030 in the economic development scenario revealed an increase of 1.25% compared to the actual water yields in 2010. The economy development in karst mountain areas of China in the future has a slight positive influence on water yields. [ABSTRACT FROM AUTHOR]

With rapid economic development in China, crops have undergone remarkable changes in both their type and spatial pattern. Timely and accurate information of crop type distribution will help government and agricultural producers quickly understand regional agricultural production conditions to better facilitate appropriate adjustments in planting patterns and policies. Another benefit of acquiring such knowledge of crops is that it should enhance regional agricultural competitiveness, optimize resource allocations, and further guarantee national food security. Towards this end, and using the Zhangye City in the Heihe River Basin as a study area, the present research elaborated upon a methodology to classify crop type distribution based on multi-temporal Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images. Using this methodology we achieved the spatial distributions of crop types in Zhangye City in 2007 and 2012, and analyzed changes in their distributions over this period. In addition, some landscape indices were calculated to clarify the landscape pattern of crops. The crop conversion potentials in 2017 were modeled using four conversion sub-models of the Multi-Layer Perceptron (MLP) neural network. Generally, the overall accuracy of crop classification in Zhangye was high, at 89.38%. From 2007 to 2012, the cultivated land area in Zhangye increased from 463.81 × 10 3 ha to 493.89 × 10 3 ha. The sowing area of corn and oilseed rape increased by 39.21 × 10 3 ha and 5.99 × 10 3 ha, respectively, while for wheat and barley the sowing area decreased by 3.61 × 10 3 ha and 9.14 × 10 3 ha, respectively. Considering other crop types as a group, their sowing area decreased by only 2.37 × 10 3 ha. The increase in corn sowing area mainly came from the conversion of other crops to corn, which accounted for 43.09% of its total sowing area in 2012. Furthermore, corn and oilseed rape showed a tendency of intensive sowing, whereas for wheat and barley the tendency was towards scattered sowing. For the future, corn has high conversion potential in Linze and Gaotai counties of Zhangye, while wheat, barley and oilseed rape have high conversion potentials in Minle and Shandan counties. [ABSTRACT FROM AUTHOR]

Maximizing resource use efficiency is generally recognized as a key strategy for developing an environment-friendly agricultural system. Although there have been many studies on single topic of resource use efficiency or environmental impacts, little is known about the spatially-explicit comprehensive estimation of the potentials in resource use efficiency improvement and environmental impacts mitigation. Here, this study proposed a comprehensive assessment framework to estimate the resource use efficiency and its environmental impacts in rice-production system at a county level, and also analyzed their improving potentials compared with both the domestically excellent province level (DEPL) and globally excellent country level (GECL). Results show that the resource use efficiency in Fujian Province was lower than 0.89 and 0.84 fold for nitrogen use efficiency (NUE), and 0.83 and 0.63 fold for irrigation water productivity (IWP) of those at the DEPL (Hunan Province, China) and GECL (Japan), respectively, while the environmental impacts were more than those in the DEPL and GECL (2.66 and 5.78 fold for grey water footprint (GYWF), 1.10 and 1.20 fold for greenhouse gases (GHG) emissions). The decrease of 26.74% blue water footprint (BWF) in Fujian Province can be achieved by that IWPs in the bottom 50% counties of Fujian Province reached at the GECL. Moreover, improving the NUEs in the bottom 40% counties of Fujian Province to the GECL can not only decrease nitrogen (N) application in Fujian Province by 17.52%, but also decrease GYWF and N 2 O emissions in Fujian Province by 8.49% and 14.71%, respectively. The assessment framework we proposed based on spatially-explicit analysis at a county level can be used broadly for comprehensive assessment of agricultural production inputs and its environmental impacts in other rice production regions. • We proposed an evaluation framework for counties' rice production sustainability. • The use efficiency of N and water have large spatial variations at county level. • The Southeast Fujian have greater environmental mitigation potential than others. • It can be reduced by 18% N and 27% blue water when efficiency reaches Japan level. [ABSTRACT FROM AUTHOR]

Accurate estimates of soil organic carbon (SOC) stocks are important in understanding terrestrial carbon cycling. Based on the fundamental theorem of surfaces, an alternative method, high accuracy surface modelling (HASM) combined with soil depth information was applied to predict the spatial pattern of SOC stocks in Hebei Province, China. In this study, we collected 434 soil samples and key environmental covariates related to soil-forming factors (soil, climate, organisms, topography, and soil depth information) in the study area, and compared the accuracy of 16 spatial prediction models (including single models, hybrid models, and HASM combined with single or hybrid models) on the spatial distribution of SOC stocks. The results confirmed that the method of HASM combined with the generalized additive model (GAM) with soil depth covariate (HASM_GAMD) achieved a better performance than other methods at soil depths of 0–30, 0–100 and 0–200 cm. The root-mean-square error and coefficient of determination values of predicting the spatial pattern of SOC stocks by the HASM_GAMD model demonstrated a 43% and 49% improvement, respectively, compared with models without depth information. The prediction uncertainty of the HASM_GAMD model based on 90% prediction interval was lower than that of other models. The HASM_GAMD model excels in addressing not only the nonlinear relationship between covariates and SOC stocks, but also in incorporating point observation data that varies with soil depth. Furthermore, the model conducts modelling by integrating surface and optimal control theories. Results obtained from the HASM_GAMD demonstrated that the SOC stocks in Hebei Province amounted to 1449.08 Tg C. Our study introduces an alternative model for modelling of SOC stocks and our findings are a valuable reference for assessing carbon stocks in Hebei Province to support sustainable land management and climate change mitigation. • We applied a surface modeling method to predict soil organic carbon stocks. • Combining surface modeling methods with soil depth can improve the performance. • Soil organic carbon stocks are 1449.08 Tg C (60% in >30 cm soil layer) in study area. [ABSTRACT FROM AUTHOR]

The human-environment relationship has always been a research topic of sustainable development. In the past century, many theories about the human-environment relationship, such as environmental determinism, possibilism (probability theory), adaptation theory, cultural landscape theory, and human-environment harmony theory, have been put forward. These theories have reflected the dynamic change of the relationship between human and the natural environment, and advanced human understanding on nature. In the past 30 years, few breakthroughs have occurred in the studies on the human-environment relationship until the 'Two Mountains' theory ('Clear waters and green mountains are as valuable as mountains of gold and silver', or 'lucid waters and lush mountains are invaluable assets') was put forward by President Xi Jinping. The 'Two Mountains' theory is a new theory of the human-environment relationship based on the general trend of world development and the difficult practice in the past 70 years since the founding of the People's Republic of China. It is a qualitative leap in the development of the human-environment relationship theory, and has resonated with the requirements of the times from human-environment separation, human-environment mutual respect to human-environment integration. Furthermore, it has provided Chinese wisdom for the development and innovation of the human-environment relationship theories in the world. From a scientific perspective, the 'Two Mountains' theory contains a rich philosophy about the evolution of the human-environment system, and has interpreted the methods and paths of achieving the intrinsic unity, mutual promotion and coordinated symbiosis between the human development and environment protection. It has inherited and carried forward the traditional Chinese thought of the 'unity of man and nature', and expanded and deepened the Marxist dialectical relationship between man and nature. Enriching and innovating the Xi Jinping Thought on Ecological Civilization in the new era, it has profoundly revealed the basic laws of economic and social development, and laid the theoretical foundation for the construction of a 'modernization characterized by harmonious coexistence between man and nature'. From the perspective of the value of the times, the theory meets the requirements of the national 'five in one' overall layout, and demonstrates the implications of the human-environment relationship from philosophical, economic, social, ecological, and cultural dimensions. It is an important guide for the construction of a beautiful China in the new era. Additionally, the 'Two Mountains' theory enriches and develops the theories of the human-environment relationship in geography and is worthy of in-depth exploration and promotion by scholars from multiple fields. [ABSTRACT FROM AUTHOR]

Highlights: [•] We measured impacts of land use and insecticides on ladybeetles in cotton. [•] First empirical evidence on landscape effects in a developing country context. [•] Insecticide sprays significantly affected ladybeetle density in cotton. [•] Ladybeetle density was higher in landscapes with more maize. [•] Land use diversity was negatively associated with ladybeetle density. [Copyright &y& Elsevier]

Water and land (W-L) resources become even more important in the context of urban-rural integration in China's arid northwest region in order to achieve sustainable development goals (SDGs). Our study used Gini coefficients to examine the relationship between natural resources and economic development in China's Xinjiang Uygur Autonomous Region. Cobb-Douglas (C-D) production functions were used to determine the economic impacts of W-L resources on rural-urban economic development. We also examined the spatiotemporal interaction characteristics of the growth drag effect of W-L resources. As a result of the decline in Gini coefficients between 2000 and 2020, Xinjiang experienced a decrease in water resources, land resources, and urban-rural GDP (gross domestic product). The output elasticities of urban-rural land and water resources were 0.3544 and 0.4790, respectively, whereas the output elasticities of urban-rural land resources were 0.1501 and 0.2185, respectively. As a result, water resources contribute to the growth of urban-rural GDP more than land resources, and W-L resources contribute to the economic development of rural areas more than it does to that of urban areas. Land resources were found to have a drag effect on urban and rural economies, respectively, in 7 and 56 counties, respectively, and water resources were found to have a drag effect on urban and rural economies, respectively, in 67 and 58 counties. In Xinjiang, water resources contributed more to economic growth than land resources. Even though W-L resources still have a drag effect on urban-rural economic growth, we can gain greater driving force by optimizing and improving resource use. However, this requires an optimal allocation and efficient use of water resources. • The drag model can analyze the drag effects of natural resource use on the urban-rural economy. • Water resources are more compatible with the urban-rural economy than land resources. • Water constraints affect Xinjiang's economic growth more than land constraints. • Water scarcity reduced Xinjiang's urban economic growth by 0.68%–1.57% from 2000 to 2020. [ABSTRACT FROM AUTHOR]

Summary: This paper examines the conflict that may exist between conservation and food security. In China, policymakers and scholars are debating whether or not conservation set-aside programs threaten food security. To address the debate, we describe China’s conservation set-aside program known as Grain for Green and compare it with similar programs outside of China. We then use data that we collected to measure the production and price impacts of the program on China’s grain economy since 1999. Our simulations find that Grain for Green has only a small effect on China’s grain production and almost no effect on prices or food imports. [Copyright &y& Elsevier]

Tracking China's national and regional CO2 emission trends is becoming ever more crucial. The country recently pledged to achieve ambitious emissions reduction targets, however, high-resolution datasets for provincial level CO2 emissions in China are still lacking. This study provides daily CO2 emission datasets for China's 31 provinces, including for the first time, the province of Tibet. The inventory covers the emissions from three industrial sectors (power, industry and ground transport) during 2019 to 2020, with its temporal resolution at a daily level. In addition, the variations in CO2 emissions for seasonal, weekly and holiday periods have been uncovered at a provincial level for the first time. This new data was added to further analyze the impact that weekends and holidays have on China's CO2 emissions. Over weekend periods, carbon emissions are shown to reduce by around 3%. Spring Festival meanwhile, has the greatest impact on the reduction of China's CO2 emissions. This detailed and time-related inventory will facilitate a more local and adaptive management of China’s CO2 emissions during both the COVID-19 pandemic’s recovery and the ongoing energy transition. The data are archived at https://doi.org/10.5281/zenodo.4730175 (Cui et al., 2021). [ABSTRACT FROM AUTHOR]

Urban–rural industry convergence is a critical factor in addressing the dual urban–rural structure, as it has the potential to increase agricultural productivity and update the industry structure. This study aims to assess the mechanisms through which urban–rural industry convergence affects farmers’ incomes in the Xinjiang Uyghur Autonomous Region of China. First, we developed an evaluation framework to measure urban–rural industry convergence and conducted an exploratory spatiotemporal data analysis to assess the trends in convergence across 99 districts and counties in Xinjiang between 2001 and 2020. Thereafter, using an econometric model, we then analyzed the mediating effects of industrial structure upgrading on the relationship between urban–rural industry convergence and farmers’ income, and the implementation path. The results indicated that urban–rural industrial convergence in Xinjiang has fluctuated and declined over time, with a spatial distribution skewed from north to south. Moreover, it was found that urban–rural industry convergence and industrial structure upgrading significantly contribute to the growth of farmers’ income. Additionally, the impact pathway analysis revealed that urban–rural industry convergence promotes industrial structure upgrading, thereby stimulating growth in farmers’ incomes. This positive effect had long-term implications and became more noticeable over time due to cumulative effects. Furthermore, the effects of urban–rural industry convergence on farmers’ income varied depending on income levels. It had a significant positive effect on the income of low-income farmers but a negative effect on high-income farmers. Moreover, the impact of the digital economy on farmers’ incomes varied based on regional and group differences, particularly affecting low, medium, and medium–high-income groups in northern Xinjiang. These findings provided empirical evidence for promoting urban–rural industry convergence and increasing farmers’ incomes, contributing to both theoretical and practical understanding of the subject matter. [ABSTRACT FROM AUTHOR]

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China. [ABSTRACT FROM AUTHOR]

Clarifying the interactive relationship between urban land-use efficiency (ULUE), industrial transformation, and carbon emissions is of great realistic significance for promoting the coordination of 'resources-economy-environment' and achieving green development. This study used the stochastic frontier analysis (SFA), index method (IM), and remote sensing inversion to calculate the ULUE, the industrial transformation degree (ITD), and the carbon emission intensity (CEI) for 108 cities in the Yangtze River Economic Belt (YREB) from 2005 to 2017, and analyzed their spatiotemporal evolution characteristics. The generalized method of moments (GMM) and impulse response function (IRF) in the panel vector autoregressive (PVAR) model are used to empirically test the dynamic interactive effects of ULUE, ITD, and CEI. The empirical results show that: (i) During the study period, the ULUE and ITD of the YREB increased year-by-year, showing the pattern characteristics of high in the east and low in the west. The CEI decreased by 50.20% cumulatively, and the low-value areas spread from the center of the urban agglomeration towards the periphery. (ⅱ) The GMM shows that there is a significant dynamic dependence between the ULUE, ITD, and CEI. The ULUE has a positive driving effect on the industrial transformation and a negative effects on the CEI in the short term. (ⅲ) The IRF shows that the ULUE and industrial transformation show a synergistic effect of interactive growth. The improvement of the ULUE and industrial restructuring will force the reduction of CEI. The article proposes that the city should take the new urbanization path of resource-conserving, cost-effective, and environment-friendly. • The paper depicted the spatiotemporal patterns for ULUE, ITD, and CEI in the YREB. • The dynamic interactive effects of the ULUE, ITD, and CEI are revealed. • The ULUE has negative influence on CEI. • The ULUE and ITD show a synergistic effect of interactive growth. • The improvement of the ULUE and ITD jointly form a carbon reduction mechanism. [ABSTRACT FROM AUTHOR]

While the biocontrol potential of natural enemies is well established, it is largely unknown how landscape‐mediated effects on pest and natural enemy communities impact the cascade of biocontrol potential, crop injury, yield and profit, taking into account crop management and surrounding landscape composition.We compared natural biocontrol with chemical control according to local farmers' practice, across the 'full cascade' from natural enemy and pest abundance to crop injury, yield loss, yield and economic performance. This 2‐year study was conducted in 20 rice fields embedded in a gradient of landscapes from crop‐dominated to semi‐natural habitat‐dominated, in subtropical China, the world's largest rice‐producing region.Natural enemies suppressed brown planthopper population growth in unsprayed plots, irrespective of landscape composition. However, crop injury was lower in pesticide treated plots than in unsprayed plots, and yields in sprayed plots were 20% higher than in unsprayed plots. Nevertheless, pesticide applications were only profitable in less than half of the cases when only costs for pesticides were considered, and in less than one third of the cases when costs for pesticides and labour were considered.Synthesis and applications. Our findings question the cost‐effectiveness of current chemical‐based pest management in farming, and highlight opportunities for more ecologically based pest management strategies based on the widespread activity of natural enemies. Pest damage and biocontrol, however, are largely independent from the landscape context, which might be due to the small‐scale character of Chinese rice landscapes. To maintain high levels of biocontrol, conserving this small‐scale character appears more important than increasing the proportion of semi‐natural habitat. [ABSTRACT FROM AUTHOR]

In light of the problem of environmental pollution caused by fossil fuel combustion, and its association with rapid urbanization, China is grappling with the question of how to reduce carbon emissions through more efficient energy consumption while simultaneously advancing its economic development. We applied a directional distance function to estimate the carbon emission performance of 30 provinces in China during the period 2000–2016. We selected an index system to assess urbanization processes in these provinces and conducted a spatial analysis to investigate the relationship between urbanization and carbon emission performance. We obtained the following results. First, the carbon emission performance of the eastern region, valued at 0.853, was relatively higher than the corresponding values of 0.810, 0.804, and 0.843 in the central, western, and northeastern regions, respectively. However, during this period, disparities among provinces increased. Second, the average urbanization value for each province showed an upward trend during the study period, and urbanization assumed a “striped” spatial agglomeration pattern. A third finding was that carbon emission performance and urbanization demonstrated a relationship of positive spatial dependence. The average value of their coordinated coupling indicated an upward trend, with an annual increase of 0.85%. Last, we found that efforts to reduce carbon emissions that are solely based on carbon emission performance do not yield reliable results. Accordingly, measurements of urbanization values can enable more detailed differentiation. In conclusion, reasonable measures should be implemented to improve carbon emission performance and urbanization that are in alignment with the actual situation within a given region. [ABSTRACT FROM AUTHOR]

Physical water consumption (PW) in economic sectors are linked with virtual water consumption (VW) embodied in the supply chain of commodities. It is important to quantitatively assess PW and VW in economic sectors and understand interconnections between them for supporting water resources management. Here, we applied an IO framework to analyse how the PW is linked to the VW from both production and consumption perspectives. A water scarce region consisting of Ganzhou, Linze, and Gaotai counties (GLG) in the Heihe river basin in China is used as a case study. The agricultural sector is broken down into seven sub-sectors represented by individual major crops. From production perspective, the results show that the agricultural sector accounted for 98.1% of total PW, which can be divided into 79.0% of final demand driven water consumption and 21% of intermediate demand driven water consumption. From consumption perspective, the VW of all the sub-sectors in the agricultural sector was largely attributed to the direct VW. The sector "Food and tobacco processing" (the downstream of the agricultural sector) has the largest indirect VW among all the sectors. Most PW in GLG was used to produce the low value added primary agricultural products to fulfil the final demand (VW) outside GLG. The results suggest that the water resources management in arid regions should guide the restructuring of economy from increasing agricultural production to increasing the economic value of the embodied virtual water, and reducing the export of the virtual water from the low economic value products. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate datagaps are a major challenge for understanding the impacts of climate change on ecosystems, particularly in highly climate vulnerable countries such as Nigeria. The generation of gridded climate data sets in the form of interpolated surfaces may help to fill climate datagaps and in turns enable climate change impact assessments. This article generates climate surfaces of monthly total precipitation and minimum and maximum temperatures for Nigeria at 0.001° spatial resolution by comparing two spatial interpolation techniques, i.e. kriging with external drifts and thin plate splines. Climate data from 43 meteorological stations covering the period of 1960-2012 were used to generate climate surfaces fitting the longitude, latitude, elevation and distance to coastline of the stations as independent variables. Three model error statistics, i.e. root mean square error ( RMSE), Nash-Sutcliffe efficiency ( NSE) and index of agreement ( d), were used to evaluate and compare the performances of interpolation techniques. The second-order and third-order partial thin plate splines were identified as the optimal models for generating precipitation, and minimum and maximum temperatures surfaces, respectively. The best-fit surfaces yielded an average RMSE, NSE and d of 14.98, 0.87 and 0.97 for precipitation, 0.42, 0.91 and 0.98 for minimum temperature and 0.52, 0.89 and 0.97 for maximum temperature. Our high-resolution climate surfaces are freely available from an online repository and widely applicable for climate change analysis as well as for biological, forestry and agricultural studies in Nigeria. [ABSTRACT FROM AUTHOR]

Pollination by insects is key for the productivity of many fruit and non-graminous seed crops, but little is known about the response of pollinators to landscapes dominated by small-holder agriculture. Here we assess the relationships between landscape context, pollinator communities (density and diversity) and pollination of oilseed rape in 18 landscapes with proportions of small-holder farming ranging from 10% to 70% in southern China. To quantify the contribution of pollinators to oilseed rape yield, we manipulated pollinator access in a focal oilseed rape field in each landscape using open and closed cages. The pollinator communities in the focal fields were sampled using pan traps. The abundance of wild pollinators increased significantly with the proportion of cultivated land, but the diversity of the wild pollinator communities declined. The responses of pollinator abundance and diversity to cultivated land were best explained at scales of around 1000 m. The abundance of the unmanaged honey bee Apis cerana was positively associated with the proportion of cultivated land, whereas the abundance of the managed A. mellifera was not. A pollination services index (PSI) was calculated by comparing the reproductive investment in seeds between plants with or without pollinator access. PSI was positively correlated with wild pollinator abundance, but not with the abundance of honeybee species. PSI was also not significantly correlated with the area proportion of cultivated land. Our results indicate that crop dominated landscapes with numerous small fields supported an abundant, but relatively species poor bee community that delivered pollination services to oilseed rape. Conservation of (semi-)natural habitats, however, is important for maintaining the diversity of wild pollinators. [ABSTRACT FROM AUTHOR]

In an effort to contribute to climate change mitigation, China has committed to achieving its peak carbon by 2030 and carbon neutrality by 2060. However, reaching these goals will require a massive reduction in carbon emissions. The humans have to consume food to meet their survival needs. Furthermore, the society's demand for food is consistent with the development level of agricultural structures. At present, reducing environmental costs associated with food to adjust the agricultural structure has not received sufficient scientific attention. Because of this, the present study combines food consumption, climate change, and agricultural structure to design future scenarios based on the widely used SSP storyline. Moreover, in order for China to reach its carbon peak in 2030, this study applies a life-cycle approach to uncover the potential carbon reduction of Chinese residents under different dietary structures. From a demand perspective, this study puts forward recommendations for dietary restructuring and guides the direction of future agricultural restructuring in China. It also shows that a diet structure that replaces red meat with plant foods such as vegetables and fruits will have a more significant carbon reduction potential. The traditional agricultural structure consumes a large amount of food and produces a significant amount of greenhouse gases. Reducing meat and high-fat foods consumption may help reduce GHG emissions produced by food consumption. In addition, reducing the proportion of food used for feeding in the agricultural structure will also help achieve peak carbon targets. The shift in diet structure will advance China's agricultural structure and promote green agriculture development. • Food consumption and related carbon emissions within the 2030 scenario will continue to increase, with the highest share of rice consumption. • The carbon emissions of food consumption in the environmentally sustainable scenario will decrease. • Readjusting toward a more balanced diet could significantly contribute to the carbon peak goal. • A shift in dietary structure will promote agricultural restructuring. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO 2) has affected global surface and atmospheric energy balance since the Industrial Revolution. The spatial distribution of CO 2 concentrations derived from satellite observation are introduced into the coupled Beijing Normal University Earth System Model (BNU-ESM) to study the responses of temperature and surface energy balance to non-uniform CO 2 distribution under the Representative Concentration Pathway 8.5 scenario to 2100. Global annual mean atmospheric CO 2 concentrations are set to equal those specified in the standard uniform CO 2 simulations with differences in spatial pattern and seasonal cycles amounting to tens of ppm. Relative to the uniform CO 2 simulation, global annual mean surface air temperature increases by 0.44 ± 0.03 °C over 2071–2100 when forced with non-uniformly distributed CO 2 , in the Arctic by 1.63 ± 0.28 °C and by 0.67 ± 0.08 °C in northern midlatitudes. The non-uniform CO 2 simulation increases global surface energy by 0.68 ± 0.06 W m−2, principally due to a 0.73 ± 0.08 W m−2 increase in net downward surface longwave flux. Surface energy balance increases by 0.33 ± 0.11 W m−2 (7.4%) averaged over oceans indicting a significant increase in ocean heat uptake. Surface energy budget averaged over the Arctic summer increases by 0.91 ± 0.68 W m−2 in the non-uniform CO 2 simulation, which would have impact on sea ice extent and land ice melt rates with associated feedbacks. The increased surface energy fluxes and temperatures imply reduced time and emission space for greenhouse gases before running into scientific and politically flagged temperature limits. • The distributions of CO 2 concentrations are introduced into Earth System Model. • There are some changes in surface energy fluxes due to non-uniform CO 2. • Changes in surface energy fluxes have impact on sea ice extent with its feedbacks. [ABSTRACT FROM AUTHOR]

• Provided a framework to explore the dynamic relevance (DR) between landscape pattern and NST. • DR was different in 2000–2010 and 2010–2020, and it was seasonal various. • DR of landscape composition was more significantly correlated than non-area related spatial configuration metrics. • The proportion of green space was positively correlated with NST in summer in BTH from 2000 to 2020. Landscape management and planning is an important way to mitigate climate change. Previous studies have proved landscape pattern (composition and configuration) was correlated to thermal environment based on a single image data in time, but the static results were inconclusive and contradictory. In this study, a framework to investigate the dynamic relevance between landscape pattern change and near surface air temperature (NST) difference was constructed through the Weather Research and Forecasting Model (WRF) and geospatial methods including landscape metrics. The landscape pattern change of Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2000 to 2020 were examined and their impacts on NST were simulated. Results showed it was dominant that cropland, water and grass land urbanized in the landscape evolution process, which led BTH average NST rise by 0.05℃ and 0.177℃ in January and July, respectively. The dynamic relevance (DR) between landscape composition and configuration and NST of all land classifications over the two decades were investigated quantitatively. Results indicated the DR between the change of landscape pattern and NST in different periods was different and it was seasonal various. DR of composition metric was more significantly correlated than non-area related spatial configuration metrics. In this twenty years, the DR of urban land (UBL) was positive, and it was negative for cropland (CPL). The landscape pattern of water (WTR) was positively correlated with NST in winter and negatively in summer. The DR of green space was an opposite correlation with DR of WTR in winter and summer, due to the newly added green space was mainly transformed from WTR. The dynamic perspective of relevance based on WRF and landscape indicators can enhance the understanding the effects of landscape pattern on thermal environment and provide a methodological framework for evaluating the dynamic relationship of landscape indicators and thermal effects. [ABSTRACT FROM AUTHOR]

• Track interannual variations of surface water area (SWA) in NCP in 1987–2020. • SWA in NCP expanded by 68%, with the most rapid increase in Shandong Province. • Increasing reservoirs/lakes and aquaculture ponds contributed to SWA expansion. • SWA expansion accelerated regional water loss through increasing water evaporation. Water shortage has severely threatened the North China Plain (NCP), a typical grain bowl and highly populated and urbanized area in China. As surface water body area (SWA) is a critical variable for measuring regional water resources, understanding its changes and driving mechanisms is important for sustainable water management. Here, we examine the interannual variations and trends of SWA in the NCP during 1987–2020 by using all the available Landsat imagery, the water indices- and threshold-based water mapping algorithm, and cloud computing platform Google Earth Engine (GEE). The results show that SWA of the NCP significantly (p < 0.05) expanded by 68.0% (from 4740.0 km2 in 1987 to 7963.7 km2 in 2020) at a rate of 101.9 km2/yr. The most remarkable expansion of SWA happened in Shandong Province (75.0 km2/yr), which is an increasingly important aquaculture production region. We find that the increasing artificial reservoirs/lakes due to the implementation of water projects, together with aquaculture development, are the main drivers for the expansion of SWA in the NCP. The expansion of SWA caused a significant increase in water evaporation (0.09 km3/yr) in the NCP as the shallow nature of these artificial reservoirs/lakes and aquaculture ponds could lead to excess evaporation because of the frequent heating and cooling cycles due to their limited abilities to store energy. Similarly, Shandong Province experienced the most rapid increase in water evaporation (0.03 km3/yr), which could accelerate the loss of water storage at a rate of 8.4–14.4 mm/yr in the regions covered by surface water bodies. Continuous temperature rise (0.02–0.06 °C/yr) in the future, as predicted by the climate models (CMIP5) under the two Representative Concentration Pathway (RCP) scenarios of medium (RCP 4.5) and high (RCP 8.5) greenhouse gas emission, could further increase water evaporation, which may add more pressure to regional water shortage. This study warns that, despite an observed significant SWA expansion, water shortage remains a major concern in the NCP. [ABSTRACT FROM AUTHOR]

• Distribution effect of carbon-food nexus for Chinese cities were explored. • Several methods built using the spatial decoupling index were proposed. • Chinese cities exhibited varying degrees of the distribution effect over the period. • Driver pattern of carbon-food nexus has changed over the years. Climate change mitigation and food security are sustainable development goals (SDGs) of the United Nations. Despite extensive studies focused on the nexus of different SDGs and corresponding mechanisms, the distribution effect of carbon-food nexus and its driver has received limited attention, hindering policy making for balancing pathways of regional emission reduction and food production improvement. The present study explored the distribution effect (i.e., spatial performance) of carbon-food nexus from multiple perspectives (namely, status quo, drivers, and trend) based on a unique city-level dataset from 2005 to 2017. To this end, we proposed the spatial decoupling index, the corresponding decomposition and nonparametric models for capturing the multi-perspective distribution effects. The results indicated that Chinese cities, categorized by population scale and economic structure, exhibited varying degrees of distributions of carbon-food nexus over the period. Moreover, the driver pattern of carbon-food nexus was noted to have changed, wherein investment efficiency and scale were positive drivers. Furthermore, we showed that a more developed city's economy was statistically significantly associated with higher carbon emission and lower food production. Therefore, related stakeholders should take more actions such as strengthening capital accumulation and joint management of carbon intensity, for improving the distribution effect of the overall city-level carbon-food nexus. [ABSTRACT FROM AUTHOR]

Abstract: There are large discrepancies among estimates of the cropland area in China due to the lack of reliable data. In this study, we used Landsat TM/ETM data at a spatial resolution of 30 m to reconstruct spatial and temporal patterns of cropland across China for the time period of 1990–2000. Our estimate has indicated that total cropland area in China in 2000 was 141.1 million hectares (ha), including 35.6 million ha paddy land and 105.5 million ha dry farming land. The distribution of cropland is uneven across the regions of China. The North-East region of China shows more cropland area per capita than the South-East and North regions of China. During 1990–2000, cropland increased by 2.79 million ha, including 0.25 million ha of paddy land and 2.53 million ha of dry farming land. The North-East and North-West regions of China gained cropland area, while the North and South-East regions showed a loss of cropland area. Urbanization accounted for more than half of the transformation from cropland to other land uses, and the increase in cropland was primarily due to reclamation of grassland and deforestation. Most of the lost cropland had good quality with high productivity, but most gained cropland was poor quality land with less suitability for crop production. The globalization as well as changing environment in China is affecting land-use change. Coordinating the conflict between environmental conservation and land demands for food will continue to be a primary challenge for China in the future. [Copyright &y& Elsevier]