Microplastics (MPs) are widely found in coastal areas and oceans worldwide. The MPs are environmentally concerning due to their bioavailability and potential impacts on a wide range of marine biota, so assessing their impact on the biota has become an urgent research priority. In the present study, we exposed Crassostrea gigas oysters to irregular MPs of two polymer types (polyethylene (PE) and polyethylene terephthalate (PET)) at concentrations of 10 and 1000 μg L-1 for 21 days. Accumulation of MPs, changes in metabolic enzyme activity, and histological damage were evaluated, and metabolomics analysis was conducted. Results demonstrated that PE and PET MPs were detected in the gills and digestive gland following exposure to both tested concentrations, confirming ingestion of MPs by the organisms. Moreover, both PE and PET MPs inhibited lipid metabolism, while energy metabolism enzyme activities were activated in the oysters. Histopathological damage of exposed oysters was also observed in this study. Integrated biomarker response (IBR) results showed that MPs toxicity increased with increasing MPs concentration, and the toxic effects of PET MPs on oysters was greater than PE MPs. In addition, metabolomics analysis suggested that MPs exposure induced alterations in metabolic profiles in oysters, with changes in energy metabolism and inflammatory responses. This study reports new insights into the consequences of MPs exposure in marine bivalves at environmentally relevant concentrations, providing valuable information for ecological risk assessment of MPs in a realistic conditions.Dynamic Global Vegetation Models (DGVMs) are commonly used to describe the land biogeochemical processes and regulate carbon and water pools. However, the simulation efficiency and validation of DGVMs are limited to varying temporal and spatial resolutions. Additionally, the uncertainties caused by different interpolation methods used in DGVMs are still not clear. In this study, we employ Socio-Economic and natural Vegetation ExpeRimental (SEVER) DGVM to simulate Net Ecosystem Exchange (NEE) flux with large scale National Centers for Environmental Prediction (NCEP) daily climate data as inputs for the years 1997-2000 at 14 Euroflux sites. It is shown that daily local NEE flux on chosen sites can be reasonably simulated, and daily temperature and shortwave radiation are the most essential inputs for daily NEE simulation compared with precipitation and the ratio of sunshine hours. Different running means (1 to 30 days) methods are analysed for each Euroflux site, and the best results of both averaged regression coefficient and averaged slope of regression are discovered by using 5 days running mean method. SEVER DGVM, driven by linearly interpolated daily climate data is compared at the monthly time step with Lund-Potsdam-Jena (LPJ) DGVM, which combines the linear interpolation of daily temperature with stochastic generation of daily precipitation. The comparison demonstrates that the stochastic generation of daily precipitation provides an acceptable fit to local observed NEE, but with a slight decrease in accuracy. Simulation experiments with SEVER DGVM demonstrate that daily local NEE flux inside a grid cell for a region as large as Europe can be modelled by DGVMs, using only large scale climate data as inputs.The study area is situated in Shouguang City, Shandong Province, as the largest greenhouse vegetable production base in Northern China. Samples of facility agricultural soil, open-field agricultural soil, and agricultural plastic mulch film were collected to investigate the distribution characteristics, influencing factors, and discharging sources of microplastics (MPs). Microplastic abundance of three soil layers at all sampling sites ranged from 310 to 5698 items/kg, with an average value of 1444 ± 986 items/kg. The main size category of MPs was less than 0.5 mm, and the contribution of MPs with sizes less then 0.5 mm in the 10-25 cm layer of facility agricultural soils was significantly higher (p less then 0.05) than that in the 0-5 cm soil layer, which indicated that small MPs tended to migrate to deeper soil layers. The prevailing shapes of MPs were fragment and film, while polypropylene, ethylene-propylene copolymer, and polyethylene dominated among chemical compositions. The fractions of silty and sandy particles were correlated with the abundance of MPs, and the microplastic abundance in sandy loam was significantly higher (p less then 0.05) than that in silty loam or loam based on the international classification standard. Thus, the soil texture may affect the distribution of MPs in local agricultural soils. In addition, the planting age of facility agricultural soil was related to microplastic abundance, while there was no significant difference in the microplastic abundances of facility agricultural soils under different irrigation methods. CAPSULE The microplastic abundance in sandy loam surpassed that in silty loam or loam, small size ( less then 0.5 mm) MPs tended to migrate to deeper soil layers, and planting age affected microplastic abundance in facility agricultural soils.The limited runoff in cold and arid regions is sensitive to environmental changes, and it is thus urgent to explore the change and controlling factors of runoff under the background of global warming and intensified human activities. However, previous studies have rarely considered the combined effects of multiple controlling factors at varying scales over time. buy TAPI-1 With the headwater region of the Manas River in northwest China as the study area, we investigated the change in runoff for the period of 1954-2016 and its relationship with regional environmental factors (e.g. precipitation PCP, temperature TMP, potential evapotranspiration ET0, snow cover extent SCE, land use, and normalized difference vegetation index NDVI) and/or global atmospheric circulation (e.g. North Atlantic Oscillation NAO, Arctic Oscillation AO, Pacific Interdecadal Oscillation PDO, and El Nino Southern Oscillation ENSO). In particular, the combined effects of multiple environmental factors were determined at different scales by the multiple wavelet coherence.