Carbon fluxes of China's coastal wetlands and impacts of reclamation and restoration.

Coastal wetlands play an important role in regulating atmospheric carbon dioxide (CO2) concentrations and contribute significantly to climate change mitigation. However, climate change, reclamation, and restoration have been causing substantial changes in coastal wetland areas and carbon exchange in China during recent decades. Here we compiled a carbon flux database consisting of 15 coastal wetland sites to assess the magnitude, patterns, and drivers of carbon fluxes and to compare fluxes among contrasting natural, disturbed, and restored wetlands. The natural coastal wetlands have the average net ecosystem exchange of CO2 (NEE) of -577 g C m-2 year-1, with -821 g C m-2 year-1 for mangrove forests and -430 g C m-2 year-1 for salt marshes. There are pronounced latitudinal patterns for carbon dioxide exchange of natural coastal wetlands: NEE increased whereas gross primary production (GPP) and respiration of ecosystem decreased with increasing latitude. Distinct environmental factors drive annual variations of GPP between mangroves and salt marshes; temperature was the dominant controlling factor in salt marshes, while temperature, precipitation, and solar radiation were co-dominant in mangroves. Meanwhile, both anthropogenic reclamation and restoration had substantial effects on coastal wetland carbon fluxes, and the effect of the anthropogenic perturbation in mangroves was more extensive than that in salt marshes. Furthermore, from 1980 to 2020, anthropogenic reclamation of China's coastal wetlands caused a carbon loss of ~3720 Gg C, while the mangrove restoration project during the period of 2021-2025 may switch restored coastal wetlands from a carbon source to carbon sink with a net carbon gain of 73 Gg C. The comparison of carbon fluxes among these coastal wetlands can improve our understanding of how anthropogenic perturbation can affect the potentials of coastal blue carbon in China, which has implications for informing conservation and restoration strategies and efforts of coastal wetlands.

Assessment and analysis of the balance between economic development and ecological environment protection and its implementation strategy derived from spatial planning-Take three heterogeneous and representative provinces in China as an example.

Balancing ecological environment protection (EEP) and economic development (ED) (balance for short) is a difficult problem that must be solved in the development of modern society, particularly important for realizing UN Sustainable Development Goals. How to assess the regional balance situation and reveal the spatial and temporal heterogeneous characteristics of the balance (especially for the vast China) and its influencing factors are the primary scientific problems and realistic needs. Taking Zhejiang, Hunan and Gansu Provinces in the eastern, central and western region of China as a regional representative, an index system characterizing EEP and ED were established, which were processed by extreme difference method and entropy weight method. The coupling characteristics, stress factors and coordination type from 2010 to 2019 in the 3 provinces were assessed and analyzed by means of the coupling coordination model and the grey correlation degree model. Balance is the mission and responsibility of the spatial planning system for spatial planning is of the source, whole-region and comprehensiveness of public strategy, therefore, the balance strategies and its integration approaches are constructed in the 3 provincial spatial planning based on the assessment and analysis of balance characteristics. Research results show that: (1) the 3 provinces' coupling coordination degree is rising year by year, coordination type is more and more better indicating that the balance of EEP and ED is getting better and better, but coordination type differentiates at one level between 3 provinces at the east, central, western region of China, Zhejiang province is from nearby imbalance to primary coordination, Hunan Province is from nearby imbalance to narrow coordination, and Gansu Province is from medium imbalance to nearby imbalance. (2) The ED have same strong stress on EEP in the 3 provinces, and the constraints of EEP on ED are different, the current balance characteristics of Zhejiang, Hunan and Gansu province are the types of ecological environment pressure constraints primary coordination, ecological environment pressure constraints narrow coordination, and ecological environment condition constraints nearby imbalance. (3) The coordination types are the co-environmental pressure constraints primary coordination (Zhejiang Province), eco-environmental pressure constraints narrow coordination (Hunan Province) and eco-environmental condition constraints nearby imbalance (Gansu Province), and corresponding balanced planning strategy system are to promote ecological modernization, implement ecological industrialization and adhere to the ecological fundamentalization.

Extraction of eutrophic and green ponds from segmentation of high-resolution imagery based on the EAF-Unet algorithm.

Inland ponds exhibit remarkable ubiquity across the globe, playing a vital role in the sustainability of global continental freshwater resources and contributing significantly to their biodiversity. Numerous ponds are eutrophic and experience recurrent seasonal or year-round algal blooms or persistent duckweed cover, conferring a characteristic green hue. Here, we denote these eutrophic and green ponds as EGPs. The excessive proliferation of algal blooms and duckweed within these EGPs poses a significant threat to the ecological functioning of these aquatic systems, which can lead to hypoxia or the release of microcystins. To identify these EGPs automatically, we constructed an Efficient Attention Fusion Unet (EAF-Unet) algorithm using Gaofen-2 (GF2) panchromatic and multispectral imagery. The attention mechanism was incorporated in Unet to help better detect EGPs. Using the first EGP labeled dataset, we determined the best input feature combination (RGB, NIR, NDVI, and Bright) and the most effective encoding (Rasnet50) for EAF-Unet for distinguishing EGPs from other ground cover types. The evaluation indices - Precision (0.81), Recall (0.79), F1-Score (0.80), and Intersection over Union (IoU, 0.67) - indicate that EAF-Unet can accurately and robustly extract EGPs from GF2 images without relying on pond water masks. Remote-sensing EGP products can assist in identifying ponds with severe eutrophication. Moreover, these products can serve as references for identifying high-risk areas prone to improper sewage discharge or inadequate sewer construction.

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 (p < 0.01) at the rate of 0.023 per decade from 1982 to 2020, and the NDVI on the Russian side (0.03 per decade) increased faster than that on the Chinese side (0.02 per decade). The NDVI of wetland was significantly positively correlated with daily mean temperature (p < 0.05, r = 0.701) and negatively correlated with precipitation, although the correlation was not significant (p > 0.05, r = -0.12). However, the asymmetric effects of diurnal warming on wetland vegetation were weak in the ARB. Correlations between the NDVI of wetland and climatic factors were zonal in latitudinal and longitudinal directions, and 49°N and 130°E were the points for a shift between increasing and decreasing correlation coefficients, closely related to the climatic zone. Under climate warming scenarios, the NDVI of wetland is predicted to continue to increase until 2080. The findings of this study are expected to deepen the understanding on response of wetland ecosystem to global change and promote regional wetland ecological protection.

China's wetland soil organic carbon pool: New estimation on pool size, change, and trajectory.

Robust estimates of wetland soil organic carbon (SOC) pools are critical to understanding wetland carbon dynamics in the global carbon cycle. However, previous estimates were highly variable and uncertain, due likely to the data sources and method used. Here we used machine learning method to estimate SOC storage and their changes over time in China's wetlands based on wetland SOC density database, associated geospatial environmental data, and recently published wetland maps. We built a database of wetland SOC density in China that contains 809 samples from 181 published studies collected over the last 20 years as presented in the published literature. All samples were extended and standardized to a 1-m depth, on the basis of the relationship between SOC density data from soil profiles of different depths. We used three different machine learning methods to evaluate their robustness in estimating wetland SOC storage and changes in China. The results indicated that random forest model achieved accurate wetland SOC estimation with R2 being .65. The results showed that average SOC density of top 1 m in China's wetlands was 25.03 ± 3.11 kg C m-2 in 2000 and 26.57 ± 3.73 kg C m-2 in 2020, an increase of 6.15%. SOC storage change from 4.73 ± 0.58 Pg in 2000 to 4.35 ± 0.61 Pg in 2020, a decrease of 8.03%, due to 13.6% decreased in wetland area from 189.12 × 103 to 162.8 × 103 km2 in 2020, despite the increase in SOC density during the same time period. The carbon accumulation rate was 107.5 ± 12.4 g C m-2 year-1 since 2000 in wetlands with no area changes. Climate change caused variations in wetland SOC density, and a future warming and drying climate would lead to decreases in wetland SOC storage. Estimates under Shared Socioeconomic Pathway 1-2.6 (low-carbon emissions) suggested that wetland SOC storage in China would not change significantly by 2100, but under Shared Socioeconomic Pathway 5-8.5 (high-carbon emissions), it would decrease significantly by approximately 5.77%. In this study, estimates of wetland SOC storage were optimized from three aspects, including sample database, wetland extent, and estimation method. Our study indicates the importance of using consistent SOC density and extent data in estimating and projecting wetland SOC storage.

Mapping global distribution of mangrove forests at 10-m resolution.

Mangrove forests deliver incredible ecosystem goods and services and are enormously relevant to sustainable living. An accurate assessment of the global status of mangrove forests warrants the necessity of datasets with sufficient information on spatial distributions and patch patterns. However, existing datasets were mostly derived from âˆ¼30 m resolution satellite imagery and used pixel-based image classification methods, which lacked spatial details and reasonable geo-information. Here, based on Sentinel-2 imagery, we created a global mangrove forest dataset at 10-m resolution, namely, High-resolution Global Mangrove Forests (HGMF_2020), using object-based image analysis and random forest classification. We then analyzed the status of global mangrove forests from the perspectives of conservation, threats, and resistance to ocean disasters. We concluded the following: (1) globally, there were 145,068 km2 mangrove forests in 2020, among which Asia contained the largest coverage (39.2%); at the country level, Indonesia had the largest amount of mangrove forests, followed by Brazil and Australia. (2) Mangrove forests in South Asia were estimated to be in the better status due to the higher proportion of conservation and larger individual patch size; in contrast, mangrove forests in East and Southeast Asia were facing intensive threats. (3) Nearly, 99% of mangrove forest areas had a patch width greater than 100 m, suggesting that nearly all mangrove forests were efficient in reducing coastal wave energy and impacts. This study reports an innovative and up-to-date dataset and comprehensive information on mangrove forests status to contribute to related research and policy implementation, especially for supporting sustainable development.

Quantitative assessment of agricultural horizontal ecological compensation in China, from the perspective of virtual land and virtual water.

A stable and complete agricultural horizontal ecological compensation (AHEC) is an essential means of reconciling agricultural ecosystem protection and regional development and is also the key to the sustainable use of agricultural water and land resources. Unlike previous methods of studying agricultural ecological compensation (AEC), this study analysed the direction and amount of net transfer of agricultural land and water use along with inter-provincial trade. In conjunction with the value of ecosystem services embedded in agricultural land and water resources, this study calculated AHEC standards and estimated payments/reimbursements from each province. We found that agricultural land and water resources continued to flow from the underdeveloped inland provinces to the developed coastal provinces in 2017. In addition, the value of agricultural ecosystem in the central and coastal areas can be further enhanced by reducing the negative value of their cropland. Even though the ecological compensation standards for virtual agricultural water use (AWU) was much lower than the ecological compensation standards for virtual agricultural land use (ALU), the integrated AHEC in 31 provinces was more reasonable than considering only virtual ALU and virtual AWU. These findings are of great theoretical and application significance for the government to establish a systematic and feasible framework for inter-provincial AHEC and serve as a reference for other countries to conduct related research.

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. This study aims to assess the effectiveness of S. alterniflora management during China's SDGs implementation from 2015 to 2020. Landsat images acquired in 2015 (the beginning year of SDGs), 2018, and 2020 (the end year of SDGs' targets 6.6, 14.2, 14.5, and 15.8 related to alien invasion) were applied to quantify the spatiotemporal dynamics of S. alterniflora extent. The results revealed a consistent shrinkage of S. alterniflora, with a net areal reduction of 2610 ha from 2015 to 2020, implying the effectiveness of control measures on S. alterniflora invasion. Provinces including Zhejiang, Jiangsu, and Shanghai have succeeded in controlling S. alterniflora, evidenced by the sharp reduction in S. alterniflora area by 4908 ha, 2176 ha, and 1034 ha, respectively, from 2015 to 2020. However, better management of S. alterniflora is needed in regions with more severe S. alterniflora invasion, e.g., Shandong, Fujian, and Guangdong provinces. Our results suggest that relevant policies, regulations, and ecological restoration projects implemented by national or local governments in China received satisfactory results in S. alterniflora control. Nevertheless, S. alterniflora potential utilities and its governance effectiveness should be objectively evaluated and weighed to obtain the greatest ecological benefits and promote sustainable coastal ecosystems. The results of this study are expected to provide important baseline information benefitting the formulation of coastal protection and restoration strategies in China.

An evaluating system for wetland ecological risk: Case study in coastal mainland China.

Coastal wetland degradation and fragmentation contribute to habitat and biodiversity loss. We construct wetland ecological risk assessment framework to evaluate the risk posed to 35 coastal wetland national nature reserves (NNRs) in China for the years 2000 and 2020. Our wetland ecological risk index (WRI) is based on an external hazard sub-index (EHI) and an internal vulnerability sub-index. Most NNRs have low EHI values in both 2000 and 2020. Ratios of change in EHI range from -22.76% to 52.15% (a negative value indicates a decrease, a positive value an increase), and the EHI for 20 of 35 NNRs (57.1%) decreases over time. Variation in the internal vulnerability index ranges -44.78% to 88.97%, and increases at 18 NNRs (51.4%) over time. WRI variation ranges between -48.13% and 82.91%, and increases at 19 NNRs (54.3%). Most NNRs are ranked as being at low, medium risk in both 2000 and 2020. Notably, the number of high-risk NNRs increases from 3 to 10 (for which WRI values also increase). Expansion of built-up land, cropland occupation (in 2020), road disturbance, and water quality are all significantly associated WRI. Intensified management of the 10 NNRs ranked at high risk is necessary to prevent further deterioration.

Global divergent trends of algal blooms detected by satellite during 1982-2018.

Algal blooms (ABs) in inland lakes have caused adverse ecological effects, and health impairment of animals and humans. We used archived Landsat images to examine ABs in lakes (>1 km2 ) around the globe over a 37-year time span (1982-2018). Out of the 176032 lakes with area >1 km2 detected globally, 863 were impacted by ABs, 708 had sufficiently long records to define a trend, and 66% exhibited increasing trends in frequency ratio (FRQR, ratio of the number of ABs events observed in a year in a given lake to the number of available Landsat images for that lake) or area ratio (AR, ratio of annual maximum area covered by ABs observed in a lake to the surface area of that lake), while 34% showed a decreasing trend. Across North America, an intensification of ABs severity was observed for FRQR (p < .01) and AR (p < .01) before 1999, followed by a decrease in ABs FRQR (p < .01) and AR (p < .05) after the 2000s. The strongest intensification of ABs was observed in Asia, followed by South America, Africa, and Europe. No clear trend was detected for the Oceania. Across climatic zones, the contributions of anthropogenic factors to ABs intensification (16.5% for fertilizer, 19.4% for gross domestic product, and 18.7% for population) were slightly stronger than climatic drivers (10.1% for temperature, 11.7% for wind speed, 16.8% for pressure, and for 11.6% for rainfall). Collectively, these divergent trends indicate that consideration of anthropogenic factors as well as climate change should be at the forefront of management policies aimed at reducing the severity and frequency of ABs in inland waters.

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. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.

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 km2 in 2015 and that Inner Mongolia had the largest surface mining area (28%). Surface mining expanded remarkably from 1990 to 2015, with an increase by 2.7 times after 2000. In particular, Inner Mongolia, Shanxi, and Qinghai had the greatest increases in surface mining area. Rapid expansion of surface mining led to obvious declines in natural habitat area, water retention, net primary productivity, and grain production, and these ES losses showed apparent spatiotemporal variations. China has taken many measures to reclaim the abandoned surface mining sites. Given the rapid expansion of surface mining and related ES loss, China should continue to perform ecological restoration for its sustainability.

Dual threat of tidal flat loss and invasive Spartina alterniflora endanger important shorebird habitat in coastal mainland China.

China's coastal wetlands are critically important to shorebirds. Substantial loss of tidal flats, shorebirds' primary foraging grounds, has occurred from land claim and other processes, and is driving population declines in multiple species. Smooth cordgrass Spartina alterniflora was intentionally introduced to the coast of China in 1979 to promote conversion of tidal flats into dry land and has since spread rapidly. The occurrence of S. alterniflora reduces the availability of foraging and roosting habitat for shorebirds, and may be particularly detrimental in places that have experienced other tidal flat loss. However, the extent to which S. alterniflora is encroaching upon important shorebird habitat throughout coastal mainland China, and its intersection with tidal flat loss, has not been quantified. Here, we i) estimate change in the spatial extent of tidal flats between 2000 and 2015 in coastal mainland China where internationally important numbers of shorebirds have been recorded; ii) map the extent of S. alterniflora coverage in 2015 at the same set of sites; and, iii) investigate where these two threats to important shorebird habitat intersect. Our analysis of remote sensing data indicated a 15% net loss in tidal flat area between 2000 and 2015 across all sites, including a net loss in tidal flat area in 39 of 53 individual sites (74%). Spartina alterniflora occurred at 28 of 53 sites (53%) in 2015, of which 22 sites (79%) also had a net loss in tidal flat area between 2000 and 2015. Combined pressures from tidal flat loss and S. alterniflora invasion were most severe in eastern coastal China. Species highly dependent on migrating through this region, which include the Critically Endangered Spoon-billed Sandpiper and Endangered Nordmann's Greenshank and Far Eastern Curlew, may be particularly impacted. Our results underscore the urgent need to arrest tidal flat declines and develop a comprehensive control program for S. alterniflora in coastal areas of mainland China that are important for shorebirds.

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 km2. Our objectives were to address the information deficiencies of spatially explicit wetland distributions and their changes and to quantify the proximate causes of these changes in various periods in the ARB. A hybrid approach combining object-based and hierarchical decision-trees classification (HOHC) was applied to Landsat series images to obtain multitemporal land cover datasets from 1980 to 2016. Further quantitative analysis revealed that the ARB held 184,561 km2 of wetlands in 2016, accounting for 9% of the whole basin area. Among these, 59% of the wetlands were identified on the Russian side, while 40% were on the Chinese side, and 1% were on the Mongolian side. The ARB lost 22% of its wetland (52,246 km2) from 1980 to 2016, with a consistent net loss from 1980 to 2010 but an area gain from 2010 to 2016. Human activities dominated the consistent wetland losses on the Chinese side of the ARB, of which cropland expansion was the primary proximate cause of wetland loss (69%). Conversely, the wetlands on the Russian side had consistent losses from 1980 to 2010 followed by a gain from 2010 to 2016, which could be attributed to climate change. These quantified data will inform decision-making on wetland conservation and benefit scientific studies depending on spatially explicit wetland information.

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 soil organic carbon concentration in the Liao River Basin has apparent spatial and vertical heterogeneities with values decreasing from southeast to northwest and concentrates present mainly in the topsoil (0-30 cm). Mean wetland soil organic carbon concentration values at the three soil depths were 10.43 ± 0.38, 7.93 ± 0.25, and 7.61 ± 0.22 g/kg, respectively, which are smaller than those over other wetland regions in Northeast China. Terrain aspect contributed the most in predicting wetland soil organic carbon concentration at each of the three soil depths, followed by normalized difference vegetation index at 0-30 cm and mean annual precipitation at 30-60 and 60-100 cm. This study provides a framework method and baseline to quantify the soil organic carbon concentration dynamics in response to climatic and anthropogenic drivers.

Rising vegetation activity dominates growing water use efficiency in the Asian permafrost region from 1900 to 2100.

Permafrost play an important role in regulating global climate system. We analyzed the gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) derived from MODIS and three earth system models participated in the Coupled Model Inter-comparison Project Phase 6 (CMIP6) in the Asian permafrost region. The water use efficiency (WUE) was further computed. The simulated GPP, NPP, and ET show slightly increasing trends during historical period (1900-2014) and strong increasing trends in projection period (2015-2100), and projected impacts of climate change on all variables are greater under high-emission scenarios than low-emission scenarios. Further analysis revealed higher increases in GPP and NPP than that of ET, indicating that vegetation carbon sequestration governs the growing WUE under historical and projected periods in this region. The GPP, NPP and ET showed higher changing rates in western, central and southeast areas of this region, and WUE (WUEGPP, and WUENPP) shows the similar spatial pattern. Compared to MODIS-derived GPP, NPP, and ET during 2000-2014, Earth system models yield the best estimates for NPP, while slight underestimations for GPP and ET, and thus slight overestimations for WUEGPP and WUENPP. This study highlights the predominant role of vegetation activity in regulating regional WUE in Asian permafrost region under future climate change. Vegetation domination of the growing water use efficiency implies that the permafrost region may continue acting efficiently in sequestrating atmospheric carbon in terms of water consumption throughout the 21st century.

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. Results reveal that the NWCP played critical roles in reducing wetland loss and improving regional ESs. The shrinkage rate of wetlands in the Sanjiang Plain has been decreased remarkably, with a declined rate of wetland loss from 750 km2 yr-1 to 189 km2 yr-1. The reduction rate of habitat area in good suitable grade and ecosystem carbon stock declined notably during the period 2000-2015 compared to the period 1990-2000. The amount of water retention increased by 5.4%, while the grain production capacity was enhanced by nine times from 1990 to 2015. Specifically, since 2000, the reduction rate of wetland area in NNRWs (33 km2 yr-1) was obviously lower than that in the entire Sanjiang Plain, whilst various ESs in NNRWs were better than that in the whole Sanjiang Plain. This study is expected to provide an example for evaluating the effectiveness of the NWCP at other regions and support regional wetland conservation management.

A Large Cohort of Neurocysticercosis in Shandong Province, Eastern China, 1997-2015.

Neurocysticercosis (NCC) has a wide spectrum of neurologic and psychiatric manifestations, including epileptic seizures, high intracranial pressure, cognitive dysfunction, and meningoencephalitis. This study presents the clinical diagnosis of 2539 NCC patients in Shandong Province, Eastern China, from 1997 to 2015. The diagnosis was based primarily on clinical features, neuroimaging, immunology, and electroencephalogramy studies. In all age groups, seizures were found to be the most common manifestation, followed by headaches, memory loss, and limb numbness, and disability. After antiparasitic treatment, computed tomography and magnetic resonance imaging showed that most of the lesions had been completely absorbed in 2106 (82.95%) patients, most of the lesions had been absorbed and a small proportion was converted into calcifications in 433 (17.05%) cases. Indirect hemagglutination (IHA), enzyme-linked immunosorbent assay (ELISA), and circulating antigen (CAg) serum tests initially gave 76.45%, 86.37%, and 80.66% positive results, respectively. After antiparasitic therapy, the positive rates of the IHA, ELISA, and CAg tests were 74.77%, 84.70%, and 3.75%, respectively, showing no significant difference in antibody levels (p > 0.05), but a significant difference in CAg levels (p < 0.01). The clinical antiparasitic treatment of NCC with three to four courses of a combination of albendazole and praziquantel achieved satisfactory therapeutic efficacy.