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On December 24, 2021, the 32nd meeting of the Standing Committee of the 13th National People's Congress of China passed the Wetland Conservation Law of the People's Republic of China, which came into force on June 1, 2022. This is the first time that China has legislated specifically on wetland ecosystems in order to strengthen wetland conservation and restoration. China's Wetland Conservation Law clarifies the concept and management system of wetlands within a framework of legal protection. Fully considering ecosystem integrity, the law explicitly stipulates prohibitive and restrictive acts and further establishes systems of wetland protected areas, protected wetland directories, overall size maintenance, acquiring and occupying wetlands, ecological compensation, wetland restoration, community engagement and wise use of wetlands, and basic management of wetland resources, which are based on legal systems of wetland conservation, restoration and management that have effectively achieved conservation goals worldwide. Furthermore, China's Wetland Conservation Law emphasizes the importance of scientific and technological support for rational wetland conservation. The formulation and implementation of China’s Wetland Conservation Law constitute an important action for China to conserve wetland ecosystems, which will not only play a vital role in reversing the current trend of continuing wetland loss in China but also have a far-reaching impact on the development of human civilization through nature conservation. [ABSTRACT FROM AUTHOR]

Background/objectives: The results linking body iron stores to the risk of gestational diabetes mellitus (GDM) are conflicting. We aimed to measure the serum ferritin level of women in early pregnancy and evaluate the risk of GDM in a Chinese urban population.Subjects/methods: In total, 851 pregnant women between 10 and 20 weeks of gestation took part in the prospective, observational study conducted. The women were divided into four groups by quartiles of serum ferritin levels (Q1-4). Their blood samples were collected and assayed for several biochemical variables at the beginning of the study, and the women were followed up with a 75-g oral glucose tolerance test at 24-28 weeks of gestation.Results: The participants had an average serum ferritin concentration of 65.67 μg/L. GDM prevalence within each serum ferritin quartile was 9.4%, 14.6%, 18.8% and 19.3%, respectively, (P = 0.016). The odds ratio for GDM in the ferritin Q2-4 was 1.64 (CI: 0.90-2.99), 2.23 (CI: 1.26-3.96) and 2.31 (CI: 1.30-4.10), compared with Q1, respectively. This association persisted after adjusting for potential confounders factors. In addition, in Q4, pregnant women with a pre-pregnancy body mass index ≥24 kg/m2, maternal age ≤35 years old or haemoglobin≥ 110 g/L did have an increased risk of developing GDM.Conclusions: Elevated serum ferritin concentrations in early gestation are associated with an increased risk of GDM, especially in pregnant women who have a high baseline iron storage status with no anaemia or who are overweight/obese. Individual iron supplementation should be considered to minimize the risk of GDM. [ABSTRACT FROM AUTHOR]

A reasonable predicting model for spatial variation of soil carbon would be a useful tool in monitoring and restoration of salt marshes. In this study, radial basis function neural networks model (RBFNN) and back propagation neural networks model (BPNN) were built to predict total carbon (TC), total organic carbon (TOC) and dissolved organic carbon (DOC) contents in salt marsh of the Yellow River Delta. Both models contained thirteen input parameters, i.e., nine topographic factors selected from ASTER GDEM Version2 and Geographical Information System (GIS), one vegetation index – MODIS 16-day composite Enhanced Vegetation Index (EVI), and three soil physicochemical properties. For prediction of TC, the MAE, MSE and RMSE values of RBFNN were smaller than those of BPNN by 61.87%, 81.36% and 56.82%; for TOC, the MAE, MSE and RMSE values of RBFNN were smaller than those of BPNN by 37.13%, 58.06% and 35.23%; both models had no significant difference in accuracy for DOC prediction, but the MAE, MSE and RMSE values of RBFNN were smaller. All ME values of RBFNN rather than BPNN were closer to zero. RBFNN integrating environmental factors had a higher accuracy than BPNN in predicting soil carbon content at a relatively small regional scale. [ABSTRACT FROM AUTHOR]

Metal distributions were monitored along soil profiles and their sources as well as ecological risks were assessed in tidal zone (T), petroleum exploitation zone (P) and restoration zone (R) under different vegetation covers- Phragmites australis (p), Suaeda salsa (s) and bare land (b) in Yellow River estuary (YRE). In the three zones, mean concentrations of metals and mean values of potential ecological risk index ( RI) kept the order of P > T > R. For different vegetation covers, the order of mean concentrations and ecological risk factor of all metals was b > s > p in zone P, while it shifted to p > b > s in zone T and p > s > b in zone R, respectively. Principal component analysis inferred that As, Cu, Ni and Zn were derived from natural alluviation and sedimentation, while Cd and Pb were derived from allochthonous inputs and air emissions of oil extraction. Correlation analysis indicated that soil organic matter, moisture, large aggregates as well as electric conductivity were key factors influencing metal distributions in these zones. Although YRE was not heavily polluted by heavy metals, it should be vigilant for metal accumulation in 20-30 cm layer of oil spilled soils, and zones P and T with high RI greatly contributed by Cd. [ABSTRACT FROM AUTHOR]

Purpose: Heavy metal distribution in soils is affected by soil aggregate fractionation. This study aimed to demons trate the aggregate-associated heavy metal concentrations and fractionations in 'sandy,' 'normal,' and 'mud' soils from the restored brackish tidal marsh, oil exploitation zone, and tidal mudflat of the Yellow River Delta (YRD), China. Materials and methods: Soil samples were sieved into the aggregates of >2, 0.25-2, 0.053-0.25, and <0.053 mm to determine the concentrations of exchangeable (F1), carbonate-bound (F2), reducible (F3), organic-bound (F4), and residual fraction (F5) of Cd, Cr, Cu, Ni, Pb, and Zn. Results and discussion: The 0.25-2 mm aggregates presented the highest concentrations but the lowest mass loadings (4.23-12.18 %) for most metal fractions due to low percentages of 0.25-2 mm aggregates (1.85-3.12 %) in soils. Aggregates <0.053 mm took majority mass loadings of metals in sandy and normal soils (62.04-86.95 %). Most soil aggregates had residual Cr, Cu, Ni, Zn, and reducible Cd, Pb dominated in the total Cd, Cr, Cu, Ni, Pb, and Zn concentrations. Sandy soil contained relatively high F4, especially of Cu (F4) in 0.25-2 mm aggregates (10.22 mg kg), which may relate to significantly high organic carbon contents (23.92 g kg, P < 0.05). Normal soil had the highest total concentrations of metals, especially of Cu, Ni, and Pb, which was attributed to the high F3 and F5 in the <0.053 mm aggregates. Although mud soil showed low total concentrations of heavy metals, the relatively high concentrations of bioavailable Cd and Cu resulted from the relatively high Cd (F2) and Cu (F2) in the >2 mm aggregates indicated contribution of carbonates to soil aggregation and metal adsorption in tidal mud flat. Conclusions: Soil type and aggregate distribution were important factors controlling heavy metal concentration and fractionation in YRD wetland soil. Compared with mud soil, normal soil contained increased concentrations of F5 and F3 of metals in the 0.053-0.25 mm aggregate, and sandy soil contained increased concentrations of bioavailable and total Cr, Ni, and Zn with great contribution of mass loadings in the <0.053 mm aggregate. The results of this study suggested that oil exploitation and wetland restoration activities may influence the retention characteristics of heavy metals in tidal soils through variation of soil type and aggregate fractions. [ABSTRACT FROM AUTHOR]