A framework to quantitatively assess the influence of land use and land cover on coastal wetland hydrological connectivity from a landscape resistance perspective.

Land use and land cover (LULC) change is one of the dominant factors contributing to coastal wetland degradation and loss. Most studies focused on LULC changes or whether they influenced on ecosystems. However, few studies quantitatively assessed the impact of different LULCs on hydrological connectivity. This study aimed to understand how LULC affected hydrological connectivity in the coastal wetlands in the Yellow River Delta (YRD), China, from 1985 to 2020. A framework from a landscape resistance perspective was used to evaluate the LULC's influence. LULCs were converted into a series of resistance surfaces whose values represent the degree to which LULC facilitated or restricted hydrological connectivity. The LULC's influence was evaluated by parameterizing the resistance surfaces using observed hydrological connectivity. The results showed that human-related LULC had more influence on hydrological connectivity. The critical time of LULC's influence on hydrological connectivity was 1985-1990 and 2010-2015. The critical areas were Zone II, Zone I, and Zone VI. The LULCs of agriculture, industry, town/city, and river had the most significant impact on the hydrological connectivity of the YRD coastal wetland. The result could direct LULC planning to mitigate the negative effect on coastal wetlands and provide support for the environmental impact assessment of coastal development practices. This paper advances the study by assessing LULCs' impact on hydrological connectivity and providing a quantitative method. The framework of this study enriches the coastal wetland conservation theory and policy-making of coastal management.

Rare earth elements in the upland soils of northern China: Spatial variation, relationships, and risk assessment.

While global demand for rare earth elements (REEs) is rapidly growing, recent studies have suggested that REEs are pollutants of emerging concern. In this study, the spatial distribution and risk assessments of REEs in the upland soils of northern China were comprehensively investigated. The total REE concentrations ranged from 81 to 180 mg/kg, with average concentrations of 123, 128, and 98.3 mg/kg in the northwestern, northern, and northeastern zones, respectively. The decreasing trend of REE contents from northwest to northeast might be influenced by variation in the REE metallogenic belt distribution, mining activities, and precipitation intensity in these regions. The ratio of light rare elements (LREEs) to heavy rare elements (HREEs) ranged from 5.04 to 9.06, revealing obvious fractionation between them in upland soils and indicating that LREEs enrichment was common in northern China. The significantly positive correlations between the REEs indicated that REEs might frequently coexist and share similar sources in the upland soils of northern China. Based on a modified ecological risk index (eRI), REEs were estimated to pose relatively low ecological risks to current environmental residues, with eRI values ranging from 0.564 to 0.984. Fortunately, the estimated daily intakes of REEs from soils for children (1.08-2.41 µg/kg/day) and adults (0.119-0.312 µg/kg/day) were well below the safety thresholds. However, the health risks posed by REEs in upland soils were estimated to be higher for children. Thus, the continuous monitoring of REE abundance in soils is essential to avoid potential health risks.

Diffuse phthalate acid esters losses induced from large amount of agricultural plastic film residues caused low risks for water quality in China during 1991-2017.

Extensive application of agricultural plastic films has resulted in abundant film residues in farmlands. Phthalate acid esters (PAEs) are vital additives of the agricultural plastic film and are easily emitted into soils. However, spatio-temporal variations of diffuse PAEs loss to water bodies have not been explored in China. This study used an integrated estimation framework and high-resolution activity data to conduct a comprehensive inventory of diffuse PAEs loss associated with plastic films of six main crop types in China for 1991-2017. We found that the diffuse PAEs loss induced from agricultural plastic films increased 10.57-46.30 kg over the same time. Di-butyl phthalate (DBP) and bis(2-ethylhexyl) phthalate (DEHP) accounted for ~75% of the national total loss. High PAEs loss regions are mainly located in Eastern China, the Middle-Lower Yangtze Plain, and eastern Yunnan and Sichuan provinces. We proved that PAEs emission, agricultural film residues, surface runoff, precipitation, and soil organic carbon explained 19.64%, 17.50%, 15.45%, 12.88%, and 9.83% of the total variation, respectively. The potential ecological risks to the various aquatic species were assessed to be low. Overall, our results are valuable for addressing severe agricultural plastic film residues and associated pollutant emissions and losses in China.

Presence, sources, and risk assessment of heavy metals in the upland soils of northern China using Monte Carlo simulation.

The spatial dynamics of heavy metal contamination in the upland soils of northern China are relatively unknown, despite the region's high contribution to the national grain output. In this study, the concentrations of As, Cd, Co, Cr, Cu, Mn, Pb, Sb, Sc, Ti, and Zn and subsequent ecological and human health risks were investigated in three major grain producing areas (Hexi Corridor, L1; Hetao irrigation area, L2; and eastern Inner Mongolia, L3) of northern China. Among the heavy metals, Ti had the highest average concentration of 3.02 g/kg, followed by Mn (470 mg/kg), Cr (56.6 mg/kg), Zn (34.3 mg/kg), Pb (19.4 mg/kg), Cu (17.8 mg/kg), Co (9.66 mg/kg), Sc (7.26 mg/kg), As (5.35 mg/kg), Sb (0.73 mg/kg), and Cd (0.17 mg/kg). Generally, the heavy metal concentrations decreased from west to east (L1 > L2 > L3) across northern China. Moreover, three potential sources of the heavy metal were distinguished, including natural process, anthropogenic activities (industrial development and agricultural cultivation), and atmospheric deposition. Although the contamination of the single metal (including Cd, Cr, Cu, and Pb) was moderate in L1 and L2, the combined contamination was low in the upland soils. It was noted that Cd posed a moderate to considerable ecological risk on the upland soils in northern China. This metal was the most sensitive factor in assessing the combined ecological risk, with a contribution rate of 91.56-94.84%. Considering the ingestion exposure, the current concentrations of the metals posed minimal risks to human health. Furthermore, children experienced higher health risks than adults. Present study analyzed the probabilistic distribution of contamination, ecological, and health risk of heavy metals in upland soils of northern China, providing fundamental information for better agricultural heavy metal pollution assessment in China.

Investment in science can mitigate the negative impacts of land use on declining primate populations.

Changes in land use and the conversion of natural forests to agricultural fields and cattle pastures are threatening the survival of many species of wild animals, including nonhuman primates. Given its almost 1.4 billion people, China faces a difficult challenge in balancing economic development, human well-being, environmental protection, and animal conservation. We examined the effects of poverty, anthropogenic land use (cropland and pasture/grazing), human population growth, government investment in science and public attention to primates during the period from the 1980s to 2015 on primate population persistence in China. We analyzed these data using generalized mixed-effects models, structural equation models (SEM) and random forests (a machine learning technique). We found that 16 of 21 (76%) primate species in China, for which data are available, have experienced a population decline over the past 35 years. Factors contributing most to primate population decline included human poverty and the conversion of natural habitat to cropland. In contrast, the five species of primates that were characterized by recent population increases were the subjects of substantial government research funding and their remaining distribution occurs principally in protected areas (PAs). We argue that increased funding for research, the establishment and expansion of PAs, a national policy focused on reducing poverty, and educational programs designed to inform and encourage local people to participate in scientific investigation and wildlife protection, can mitigate the negative impacts of historical patterns of land conversion on primate population survival in China.

Ammonia volatilization modeling optimization for rice watersheds under climatic differences.

The ammonia (NH3) volatilization mechanism is complicated with pronounced watershed differences of climate conditions, soil properties, and tillage practices. The watershed NH3 emission dynamics model was developed with the combination of field measurements, Soil Water Assessment Tool and NH3 volatilization algorithms. The temporal NH3 emissions patterns and the watershed NH3 volatilization dynamics were simulated with the improved NH3 volatilization modeling. Five monitoring sites and three case watersheds across China were selected to highlight the impacts of climatic conditions and validated the modeling. The average NH3 emissions of the three watersheds ranged from 14.94 to 120.33 kg N ha-1, which were mainly positively correlated with temperatures (r = 0.56, p < 0.01) and negatively correlated with soil organic carbon content (r = -0.33, p < 0.01). Analysis of similarities indicated that significant differences existed between the watersheds in terms of NH3 volatilization (RANOSIM = 0.758 and 0.834, p < 0.01). These analysis imply that environmental variabilities were more important than N input amounts.

Considering atmospheric N2O dynamic in SWAT model avoids the overestimation of N2O emissions in river networks.

Modeling studies have focused on N2O emissions in temperate rivers under static atmospheric N2O (N2Oairc), with cold temperate river networks under dynamic N2Oairc receiving less attention. To address this knowledge and methodological gap, the dissolved N2O concentration (N2Odisc) and N2Oairc algorithms were integrated with an air-water gas exchange model (FN2O) into the SWAT (Soil and Water Assessment Tool). This new model (SWAT-FN2O) allows users to simulate daily riverine N2O emissions under dynamic atmospheric N2O. The spatiotemporal fluctuations in the riverine N2O emissions was simulated and its response to the static and dynamic atmospheric N2O were analyzed in a middle-high latitude agricultural watershed in northeastern China. The results show that the SWAT-FN2O model is a useful method for capturing the hotspots in riverine N2O emissions. The model showed strong riverine N2O absorption and weak N2O emissions from September to February, which acted as a sink for atmospheric N2O in this cold temperate area. High N2O emissions occurred from April to July, which accounted for 83.34% of the yearly emissions. Spatial analysis indicated that the main stream and its tributary could contribute 302.3-1043.7 and 41.5-163.4 µg N2O/(m2·d) to the total riverine N2O emissions (15.02 t/a), respectively. The riverine N2O emissions rates in the subbasins dominated by forests and paddy fields were lower than those in the subbasins dominated by arable and residential land. Riverine N2O emissions can be overestimated under the static atmospheric N2O rather than under the increasing atmospheric N2O. This overestimation has increased from 1.52% to 23.97% from 1990 to 2016 under the static atmospheric N2O. The results of this study are valuable for water quality and future climate change assessments that aim to protect aquatic and atmospheric environments.