Effects of landscape changes on water quality: A global meta-analysis.

Landscape changes resulting from anthropogenic activities and climate changes severely impact surface water quality. A global perspective on understanding their relationship is a prerequisite for pursuing equity in water security and sustainable development. A sequent meta-analysis synthesizing 625 regional studies from 63 countries worldwide was conducted to analyze the impacts on water quality from changing landscape compositions in the catchment and explore the moderating factors and temporal evolution.

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau.

Climate change and human activities have intensified variations of water table depth (WTD) in wetlands around the world, which may strongly affect greenhouse gas emissions. Here, we analyzed how emissions of CO, CH, and NO from the Zoige wetland on the Qinghai-Tibetan Plateau (QTP) vary with the WTD. Our data indicate that the wetland shows net positive global warming potential (11.

Heterogeneous responses of wetland vegetation to climate change in the Amur River basin characterized by normalized difference vegetation index from 1982 to 2020.

Climate change affects wetland vegetation dramatically in mid- and high- latitudes, especially in the Amur River basin (ARB), straddling three countries and distributing abundance wetlands. In this study, spatiotemporal changes in average normalized difference vegetation index (NDVI) of wetland during the annual growing season were examined in the ARB from 1982 to 2020, and the responses of wetland vegetation to climatic change (temperature and precipitation) in different countries, geographic gradients, and time periods were analyzed by correlation analysis. The NDVI of wetland in the ARB increased significantly ( < 0.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests.

Introduction: Conductance-photosynthesis (G-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (G) and transpiration (T) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (g and g) and maximum LUE (ϵ and ϵ) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in T estimation errors, as it contradicts field observations.

Invasion of Spartina alterniflora in the coastal zone of mainland China: Control achievements from 2015 to 2020 towards the Sustainable Development Goals.

The Sustainable Development Goals (SDGs) and the Convention on Biological Diversity's 15th Conference of the Parties (CBD COP15) both emphasized the urgency of protecting biological diversity. Spartina alterniflora (S. alterniflora), as an invasive species in China, has posed severe biodiversity challenges, demanding nationwide control and management.

Quantifying the influences of climate change and human activities on the grassland in the Southwest Transboundary Basin, China.

The Southwest Transboundary Basin (STB), which contains a part of the Tibetan Plateau and Southwest China, covers a large area of grassland that has been experiencing significant climate change (Cc) and human activities (Ha). However, variabilities of the grasslands and respective contributions of the drivers have not been fully understood. In this study, we quantitatively investigated the influences of Cc and Ha on the grasslands from 1982 to 2015 across the STB, using residual analysis, trend analysis, and partial correlation analysis.

Current status and influential factors for family health management during quarantine: A latent category analysis.

Objective: We aimed to explore factors affecting family health management during home quarantine as well as the effects of variations in family health management (FHM) on individuals' health status.

Methods: Using stratified random sampling, 618 families in Wuhan as well as cities within its surrounding provinces were recruited and surveyed online. Latent class variables were extracted from four modules: disinfection, space layout, physical exercise, and food reserves.

Development of remote sensing algorithm for total phosphorus concentration in eutrophic lakes: Conventional or machine learning?

Phosphorus is a limiting nutrient in freshwater ecosystems. Therefore, the estimation of total phosphorus (TP) concentration in eutrophic water using remote sensing technology is of great significance for lake environmental management. However, there is no TP remote sensing model for lake groups, and thus far, specific models have been used for specific lakes.

The effects of climate on soil microbial diversity shift after intensive agriculture in arid and semiarid regions.

In arid and semiarid desert areas, climate factors distinctly impact soil microbial community, which can also be greatly altered after agricultural practices at multiple spatial scales. However, it is still poorly unknown whether the effects of climate on soil microbial diversity change after intensive agriculture at a large spatial scale. To uncover this concern, we used time-interval archived soils, taken from paired desert and agricultural experiments at five field stations of the Chinese Ecosystem Research Network across northern China, and performed high-throughput sequencing.

Linking soil bacterial diversity to satellite-derived vegetation productivity: a case study in arid and semi-arid desert areas.

Increasing studies have begun to focus on biodiversity-productivity relationships for soil microorganisms through molecular ecology methods. However, most of these studies involve controlled experiments, and whether the relationship remains at large spatial scales is still largely unknown. To unravel this issue, archived desert soils from long-term experiments were analysed using high-throughput sequencing, and satellite-derived vegetation datasets were acquired to quantify productivity.

Eddy covariance measurements of ozone flux above and below a southern subtropical forest canopy.

While extensive eddy covariance (EC) measurements of ozone (O) flux have been reported in American and European forests, such measurements in Asian forests are scarce. Here, we presented the first EC measurements of O flux at two levels (above and below the canopy) in a Chinese forest. Above the canopy, O always moved downward, with a maximum O flux intensity of -15 ~ -10 nmol m s occurring at 9:00-14:00 LT and a maximum O deposition velocity of 1.

Surface mining caused multiple ecosystem service losses in China.

China's surface mining greatly supported the rapid socio-economic development; however, there was a scarcity in the systematic understanding of national changes in surface mining changes and associated ecosystem services (ESs) losses, which inevitably affected human well-being and limited sustainable ecosystem management and policy optimization. In this study, we quantified the areal changes in surface mining based on the ChinaCover database and performed further analysis of ES loss from expanded surface mining using multidimensional geospatial data from 1990 to 2015, including MODIS products, meteorological records, and statistical datasets. Our observations reveal that China's surface mining was estimated to be 4746 km in 2015 and that Inner Mongolia had the largest surface mining area (28%).

Vegetation Dynamic Assessment by NDVI and Field Observations for Sustainability of China's Wulagai River Basin.

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018.

Optimized remote sensing estimation of the lake algal biomass by considering the vertically heterogeneous chlorophyll distribution: Study case in Lake Chaohu of China.

Due to the difference of vertical distribution of algae in lakes, it is necessary to carry out remote sensing estimation of algal biomass based on the vertically heterogeneous distribution of chlorophyll in order to improve the accuracy of biomass inversion. A new algorithm is proposed and validated to measure algal biomass in Lake Chaohu based on the Moderate Resolution Imaging Spectrometer (MODIS) images. The algal biomass index (ABI) is defined as the difference in remote-sensing reflectance (R, sr) at 555 nm normalized against two baselines with one formed linearly between R(859) and R(469) and another formed linearly between R(645) and R(469).

Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China's Liao River Basin.

Accurate prediction of wetland soil organic carbon concentration and an understanding of its controlling factors are important for studying regional climate change and wetland carbon cycles; with that knowledge mechanisms can be put in place that are conducive to sustainable ecosystem management for environmental health. In this study, a hybrid approach combining an artificial neural network and ordinary kriging and 103 soil samples at three soil depth ranges (0-30, 30-60, and 60-100 cm) were used to predict wetland soil organic carbon concentration in China's Liao River Basin. The model evaluation indicated that a combination of artificial neural network and ordinary kriging and limited soil samples achieved good performance in predicting wetland soil organic carbon concentration.

Wetland changes in the Amur River Basin: Differing trends and proximate causes on the Chinese and Russian sides.

According to the United Nations Sustainable Development Goals (SDGs), understanding the extent of wetlands, their change trends and the proximate causes is important for the conservation of wetlands and endangered waterfowls. Here we studied the world's ninth largest river basin, the Amur River Basin (ARB), with a land area of 2.08 million km.

Global response of terrestrial gross primary productivity to climate extremes.

Extreme climate events undoubtedly have essential impacts on ecosystem gross primary productivity (GPP), but the global spatio-temporal patterns of GPP responses to climate extremes are unclear. In this study, we analyzed the responses of GPP to temperature and precipitation extremes during historical (1901-2016) and future (2006-2100) periods using climate extreme indices (CEIs) developed by the Expert Team on Climate Change Detection and Indices. Eight temperature-related CEIs and eight precipitation-related CEIs were used for this analysis, along with three future greenhouse gas concentration trajectory scenarios generated by the IPCC: RCP 2.

Long-term variation in CO emissions with implications for the interannual trend in PM over the last decade in Beijing, China.

Long-term CO and PM measurements in urban areas have important impacts on understanding the roles of urbanization in climate change and air pollution. From 2009 to 2017, CO fluxes were measured by the eddy covariance (EC) system at a height of 140 m on the Beijing Meteorological Tower. The CO fluxes followed a typical two-peak diurnal pattern all year round.

What did China's National Wetland Conservation Program Achieve？Observations of changes in land cover and ecosystem services in the Sanjiang Plain.

China implemented the National Wetland Conservation Program (NWCP) from 2002 to protect and rehabilitate wetlands. Under the background of sustainable development, assessment on the effectiveness of the NWCP is important to ecosystem management, especially in the Sanjiang Plain, the largest marsh distribution area and hotspot area with wetland loss. To achieve this aim, this study examined the changes in land cover and ecosystem services (ESs) from 1990 to 2000 and from 2000 to 2015 in the Sanjiang Plain as well as the nine national nature reserves for wetlands (NNRWs) by means of Landsat series images and the InVEST model.

Concurrent and lagged effects of spring greening on seasonal carbon gain and water loss across the Northern Hemisphere.

Spring greening has been widely observed across the Northern Hemisphere (NH) using a remotely sensed vegetation index (e.g., the normalized difference vegetation index, NDVI).