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Land system intensification has substantially enhanced crop production; however, it has also created soil antibiotic pollution, undermining crop production. Here, we projected soil antibiotic pollution risks to crop production at multiple geographical scales in China and linked them to land system intensification (including arable land expansion and input increase). Our projections suggest that crop production will substantially decrease when the soil antibiotic pollution risk quotient exceeds 8.30–9.98. Land systems explain most of the variability in antibiotic pollution risks (21–66%) across spatial scales. The convex nonlinearities in tradeoffs between antibiotic pollution risk and crop production indicate that vegetable and wheat production have higher thresholds of land system intensification at which the risk–yield tradeoffs will peak than do maize and rice production. Our study suggests that land system intensification below the minimum thresholds at multiple scales is required for acceptable antibiotic pollution risks related to crop yield reduction. Crop intensification has increased agricultural production albeit with an increase in field antibiotic pollution. Here, Chen et al. project how antibiotic pollution undermines production and how intensification needs to be kept below a threshold.

Soil conservation service (SC) is defined as the ability of terrestrial ecosystems to control soil erosion and protect soil function. A long-term and high-resolution estimation of SC is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution Chinese soil conservation dataset (CSCD) from 1992 to 2019, for the first time, is established based on the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE modelling was conducted based on five key parameters, including the rainfall erosivity (interpolation of daily rainfall), land cover management (provincial data), conservation practices (weighted by terrain and crop types), topography (30 m), and soil properties (250 m). The dataset agrees with previous measurements in all basins (R 2  > 0.5) and other regional simulations. Compared with current studies, the dataset has long-term, large-scale, and relatively high-resolution characteristics. This dataset will serve as a base to open out the mechanism of SC variations in China and could help assess the ecological effects of land management policies.

Mega-urban agglomerations are strategic core areas for national economic development and the main regions of new urbanization. They also have important roles in shifting the global economic center of gravity to China. However, the development of mega-urban agglomerations has triggered the interactive coercion between resources and the eco-envi- ronment. The interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations represent frontier and high-priority research topics in the field of Earth system science over the next decade. In this paper, we carried out systematic theo- retical analysis of the interactive coupling mechanisms and coercing effects between ur- banization and the eco-environment in mega-urban agglomerations. In detail, we analyzed the nonlinear-coupled relationships and the coupling characteristics between natural and human elements in mega-urban agglomerations. We also investigated the interactive coercion intensities between internal and external elements, and the mechanisms and patterns of local couplings and telecouplings in mega-urban agglomeration systems, which are affected by key internal and external control elements. In addition, we proposed the interactive coupling theory on urbanization and the eco-environment in mega-urban agglomerations. Furthermore we established a spatiotemporal dynamic coupling model with multi-element, multi-scale, multi-scenario, multi-module and multi-agent integrations, which can be used to develop an intelligent decision support system for sustainable development of mega-urban agglomera- tions. In general, our research may provide theoretical guidance and method support to solve problems related to mega-urban agglomerations and maintain their sustainable development.

Aims Non-native trees are widely used to prevent soil erosion in the Loess Plateau. We aim to investigate the effects of non-native tree plantations on the communities of understory plants and soil macroinvertebrates. Methods The soil, understory plants and soil macroinvertebrates were sampled in non-native Robinia pseudoacacia (RP) and Populus ×canadensis (PC) stands, and native Armeniaca sibirica (AS) stands. Results Abundance and richness of understory plants were significantly greatest in the RP stands. The macroinvertebrates collected belonged to 13 orders across all stands. At the community level, richness did not differ among the stand types, but the abundance was significantly greatest in the PC stands. At the functional group level, phytophages and detritivores preferred the PC stands, whereas predators preferred the RP stands. The generalist macroinvertebrate abundance was significantly greatest in the PC stands. Moreover, the community composition of understory plants clearly differed among the stand types; that of soil macroinvertebrates in the PC stands was separated from the other stand types, which was mediated by environmental variables, especially the soil temperature and soil organic carbon. Conclusions Non-native tree plantations had positive effects on the overall abundance of understory plants and soil macroinvertebrates, but their effects on functional groups were inconsistent, associated with tree identity. The selection of non-native tree should be considered in term of multiple trophic levels, if afforestation has biodiversity objectives.

The rapid and relentless development of urban areas highlights the importance of landscape multifunctionality. However, there is limited research on the temporal dynamics and climatic effects of urban landscape multifunctionality. This study aimed to address this gap by analyzing the features of multiple landscape functions triggered by seasonal climate change in different urban park types. In this study, we investigated five typical urban landscape functions (alleviating urban heat islands, vegetation growth, biodiversity promotion, alleviation of waterlogging, and provision of recreational activities) by establishing a set of indices: ecological supply capability ( S P ), proportion of ecological supply ( SP P ), capability of human benefits ( B P ), and human benefits efficiency ( BE P ) of urban parks. The average S P of the landscape functions was 58% in summer and 46% in winter. During the transition from summer to winter, urban parks witnessed a significant decrease in SP P for alleviating the urban heat island, dropping from 34% to 5%. The primary landscape functions shifted from alleviating the urban heat island (34%) and providing recreation (29%) to providing recreation (38%) and biodiversity promotion (29%). Concerning park types, nature parks provided the highest S P , whereas community parks provided the highest BE P . This study has useful implications for landscape management in urban parks, particularly regarding timely adjustments across seasonal climates. It is possible to promote sustainable and effective human well-being by maximizing landscape functions.

The credible urban heat island (UHI) trend is crucial for assessing the effects of urbanization on climate. Land surface temperature (LST) and near surface air temperature (SAT) have been extensively used to obtain UHI intensities. However, the consistency of UHI trend between LST and SAT has rarely been discussed. This paper quantified the temporal stability and trend consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) LST and in situ SAT. Linear regressions, temporal trends and coefficients of variations (CV) were analyzed based on the yearly mean, maximum and minimum temperatures. The findings in this study were: (1) Good statistical consistency (R2 = 0.794) and the same trends were found only in mean temperature between LST-UHI and SAT-UHI. There are 54% of cities that showed opposite temporal trends between LST-UHI and SAT-UHI for minimum temperature while the percentage was 38% for maximum temperature. (2) The high discrepancies in temporal trends were observed for all cities, which indicated the inadequacy of LST for obtaining reliable UHI trends especially when using the maximum and minimum temperatures. (3) The larger uncertainties of LST-UHI were probably due to high inter-annual fluctuations of LST. The topography was the predominant factor that affected the UHI variations for both LST and SAT. Therefore, we suggested that SAT should be combined with LST to ensure the dependable temporal series of UHI. This paper provided references for understanding the UHI effects on various surfaces.

The topsoil around Beijing metropolis, China, is experiencing impacts of rapid urbanization, intensive farming, and extensive industrial emissions. We analyzed the concentrations of Cu, Ni, Pb, Zn, Cd, and Cr from 87 topsoil samples in the pre-rainy season and 115 samples in the post-rainy season. These samples were attributed to nine land use types: forest, grass, shrub, orchard, wheat, cotton, spring maize, summer maize, and mixed farmland. The pollution index (PI) of heavy metals was calculated from the measured and background concentrations. The ecological risk index (RI) was assessed based on the PI values and toxic-response parameters. The results showed that the mean PI values of Pb, Cr, and Cd were > 1 while those of Cu, Ni, and Zn were < 1. All the samples had low ecological risk for Cu, Ni, Pb, Zn, and Cr while only 15.35% of samples had low ecological risk for Cd. Atmospheric transport rather than land use factors best explained the seasonal variations in heavy metal concentrations and the impact of atmospheric transport on heavy metal concentrations varied according to the heavy metal types. The concentrations of Cu, Cd, and Cr decreased from the pre- to post-rainy season, while those of Ni, Pb, and Zn increased during this period. Future research should be focused on the underlying atmospheric processes that lead to these spatial and seasonal variations in heavy metals. The policymaking on environmental management should pay close attention to potential ecological risks of Cd as well as identifying the transport pathways of different heavy metals.

Cities worldwide are expanding greenspaces, including parks, urban forests, and grasslands. However, population exposure to tree and nontree vegetation is less well understood. Here, we use multiple satellite-derived datasets on vegetation, climate, and socioeconomic factors to examine the variations of urban tree and nontree vegetation cover, drivers of changes, and the impacts on global urban population exposure between 2000 to 2020. We find that approximately 90% of cities experienced an ascending trend in tree cover, and 49% of cities showed growth in nontree vegetation ( p < 0.05). The increase in urban tree cover is most evident in high-latitude areas, such as Eastern Russia and Northern Europe. Human exposure to urban tree vegetation considerably declined in the Global South, widening the disparity between the North and South. Our study underscores persistent inequalities in human exposure to green space in cities and calls for evidence-based strategies that reduce increasing disparities.

The present study investigated the impacts of urban geometry on incident solar radiation on building envelopes. A three-dimensional model was developed and applied to examine these relationships, with implications for building landscapes as a potential heat source for urban heat islands. In the model, we classified building envelopes into three types, including ground, roofs, and building façades. Satisfactory model performance was confirmed by comparing measured and predicted incident solar radiation results. Furthermore, we developed the Incident Solar Radiation Prediction Index (ISRPI) to address relationships between urban geometry and incident solar radiation. Our overall results showed the solar irradiance incident on building envelopes was significantly affected by urban geometry. Building façades consistently shared a large amount of the building landscape’s total surface area and therefore determined more influence on variation in incident solar radiation. Weather conditions showed strong influence on incident solar radiation, primarily due to variation in atmospheric transmittance. Diffuse radiation demonstrated a larger share of incident solar radiation on the cloudy sampling day. ISRPI, which cumulatively combined the strengths of several traditional urban morphological metrics, exhibited a strong linear relationship with incident solar radiation under sunny and cloudy weather conditions. This index provided a more convenient approach to estimate the spatial-temporal variations of solar radiations at urban scale.

Tracking seasonally changing resources is regarded as a widespread proximate mechanism underpinning animal migration. Migrating herbivores, for example, are hypothesized to track seasonal foliage dynamics over large spatial scales. Previous investigations of this green wave hypothesis involved few species and limited geographical extent, and used conventional correlation that cannot disentangle alternative correlated effects. Here, we introduce stochastic simulations to test this hypothesis using 222 individual spring migration episodes of 14 populations of ten species of geese, swans and dabbling ducks throughout Europe, East Asia, and North America. We find that the green wave cannot be considered a ubiquitous driver of herbivorous waterfowl spring migration, as it explains observed migration patterns of only a few grazing populations in specific regions. We suggest that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds. The green wave hypothesis is often considered a key driver of spring migration in avian herbivores. Here the authors employ a multispecies comparison and find that migration did not track the green wave better than simulated stochastic migrations.