ABSTRACT
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.
Subject(s)
Ecosystem , Wetlands , Carbon Dioxide , Carbon Cycle , ChinaABSTRACT
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.
ABSTRACT
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.
Subject(s)
Environmental Monitoring , Eutrophication , Animals , Climate Change , Environmental Monitoring/methods , Lakes , WindABSTRACT
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.
Subject(s)
Ecosystem , Wetlands , Sustainable Development , China , Poaceae , Introduced SpeciesABSTRACT
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.
Subject(s)
Conservation of Natural Resources , Wetlands , Angiotensin Receptor Antagonists , Angiotensin-Converting Enzyme Inhibitors , Asian People , Environmental Monitoring , Humans , Rivers , RussiaABSTRACT
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.
Subject(s)
Ecosystem , Mining , China , Conservation of Natural Resources , Economic Development , Humans , PolicyABSTRACT
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.
Subject(s)
Ecosystem , Poaceae , China , Introduced Species , WetlandsABSTRACT
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.
ABSTRACT
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.
Subject(s)
Ecosystem , Wetlands , Agriculture , China , Conservation of Natural ResourcesABSTRACT
Given the extensive spread and ecological consequences of exotic Spartina alterniflora (S. alterniflora) over the coast of mainland China, monitoring its spatiotemporal invasion patterns is important for the sake of coastal ecosystem management and ecological security. In this study, Landsat series images from 1990 to 2015 were used to establish multi-temporal datasets for documenting the temporal dynamics of S. alterniflora invasion. Our observations revealed that S. alterniflora had a continuous expansion with the area increasing by 50,204 ha during the considered 25 years. The largest expansion was identified in Jiangsu Province during the period of 1990-2000, and in Zhejiang Province during the periods 2000-2010 and 2010-2015. Three noticeable hotspots for S. alterniflora invasion were Yancheng of Jiangsu, Chongming of Shanghai, and Ningbo of Zhejiang, and each had a net area increase larger than 5000 ha. Moreover, an obvious shrinkage of S. alterniflora was identified in three coastal cities including the city of Cangzhou of Hebei, Dongguan, and Jiangmen of Guangdong. S. alterniflora invaded mostly into mudflats (>93%) and shrank primarily due to aquaculture (55.5%). This study sheds light on the historical spatial patterns in S. alterniflora distribution and thus is helpful for understanding its invasion mechanism and invasive species management.
Subject(s)
Biosensing Techniques/methods , Ecosystem , Environmental Monitoring/methods , Poaceae/physiology , China , Humans , Introduced SpeciesABSTRACT
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.
ABSTRACT
In order to explore the spatiotemporal variation characteristics and driving mechanism of water quality in the Xiangjiang River Basin, the data of 16 water quality parameters at 113 stations over 26 years from 1990 to 2016 in the Xiangjiang River Basin were collected for synthetically assessing the water quality and identifying its main pollutants through the water quality index and other methods. The causal mechanism of water quality, especially the driving effect of water level and land use pattern, was analyzed. The results showed thatï¼ â The overall water quality grade of the Xiangjiang River Basin during the study period was "good." However, the water quality deteriorated first ï¼from 1990 to 2003ï¼ and then improved ï¼from 2004 to 2016ï¼. The season variation in water quality was not obvious, but the water quality fluctuation of the wet season was larger. The water pollution load of the main stream decreased successively from the middle reaches, downstream reaches, and upstream reaches. The upstream tributaries had the best water quality, whereas areas with poor water quality were mainly distributed at the mouth of the middle and downstream tributaries, especially in areas where multiple tributaries converged. â¡ Toxic heavy metals had the characteristics of toxicity, persistence, and bioaccumulation. If they exceeded a certain concentration in water, they were difficult to purify, posing great harm to the natural environment and human health. The toxic metal index ï¼CI1ï¼ was the leading factor affecting water quality, in which Hg and Cd were the main parameters affecting the overall water quality of the Xiangjiang River Basin. ⢠The water level had a positive impact on the water quality of the Xiangjiang River by diluting environmental parameters. Land type had little effect on heavy metal concentration, whereas forest land could improve water quality. Grassland had a negative correlation with permanganate index over a large scale range ï¼≥ 5 kmï¼. The increase in water bodies, arable land, and impermeable surface areas within the watershed increased the probability of high fecal coliform concentration in the water body. ⣠With the increase in buffer distance, the water quality explained by the land use pattern increased. On the scale of 10 km buffer zone in the riparian zone, the explanation degree by land use pattern on water quality was the highest, which was an effective scale for water quality control of the Xiangjiang River. This research showed that the driving factors of heavy metal pollution and other pollution were different, but their regional differences were all obvious in the Xiangjiang River Basin. Therefore, pollution control should be classified and taken according to local conditions.
ABSTRACT
This study explores the conservation of historic flyway corridors for egret in the Greater Bay Area (GBA), with a focus on habitat connectivity and dynamic corridors. To address the gaps in previous research, we used field observations, bio-climatic data and landcover information spanning three decades. Our approach involves MaxENT modeling and the Linkage Mapper method. The results showed that the MaxENT model effectively simulated the egret habitats at different levels, with coastlines and riverbanks emerging as primary habitat zones. Moreover, bio-climatic factors, particularly Bio 19 and Bio 8, played a dominant role, accounting for 90 % of the habitat suitability in 2020. Other factors contributed rather minimally. Through the utilization of resistance surface and corridor extraction methods, noteworthy alterations in the flyway networks emerged post-2000, followed by a gradual return to normal. Connectivity analyses highlighted a critical 30 km threshold for the egret preservation. Corridor widths should be determined based on cost-effective considerations. We conclude that combining MaxENT with the Linkage Mapper method, even with limited egret observations and integrating multi-source data, such as land cover, might simulate potential suitable habitats and flyway dynamics for waterbirds such as egrets. This study provides valuable insights for the egret conservation and the preservation of their habitats in the GBA, contributing to a global waterbird diversity and habitat quality.
Subject(s)
Birds , Conservation of Natural Resources , Ecosystem , Urbanization , Animals , China , Bays , Environmental MonitoringABSTRACT
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. Results exhibit that total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) in water are mostly concerned and highly responsive to landscape changes. Expansion of urban lands fundamentally degraded worldwide water quality over the past 20 years, of which the arid areas tended to suffer more harsh deterioration. Increasing forest cover, particularly low-latitude forests, significantly decreased the risk of water pollution, especially biological and heavy metal contamination, suggesting the importance of forest restoration in global urbanization. The effect size of agricultural land changes on water quality was spatially scale-dependent, decreasing and then increasing with the buffer radius expanding. Wetland coverage positively correlated with organic matter in water typified by COD, and the correlation coefficient peaked in the boreal areas (r=0.82, p<0.01). Overall, the global impacts of landscape changes on water quality have been intensifying since the 1990s. Nevertheless, knowledge gaps still exist in developing areas, especially in Africa and South America, where the water quality is sensitive to landscape changes and is expected to experience dramatic shifts in foreseeable future development. Our study revealed the worldwide consistency and heterogeneity between regions, thus serving as a research roadmap to address the quality-induced global water scarcity under landscape changes and to direct the management of land and water.
Subject(s)
Water Quality , Phosphorus/analysis , Nitrogen/analysis , Wetlands , Environmental Monitoring , Climate ChangeABSTRACT
Nutrient proportion, light intensity, and temperature affect the succession of dominant phytoplankton species. Despite these insights, this transformation mechanism in highly turbid lakes remains a research gap, especially in response to climate change. To fill this gap, we investigated the mechanism by which multi-environmental factors influence the succession of dominant phytoplankton species in Lake Chagan. This investigation deployed the structural equation model (SEM) and the hydrodynamic-water quality-water ecology mechanism model. Results demonstrated that the dominant phytoplankton species in Lake Chagan transformed from diatom to cyanobacteria during 2012 and 2022. Notably, Microcystis was detected in 2022. SEM revealed the primary environment variables for this succession, including water temperature (Tw), nutrients (total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (NH4N)), and total suspended solids (TSS). Moreover, this event was not the consequence of zooplankton grazing. An integrated hydrodynamic-water quality-bloom mechanism model was built to explore the mechanism driving phytoplankton succession and its response to climate change. Nutrients determined the phytoplankton biomass and dominant species succession based on various proportions. High NH4N:NO3N ratios favored cyanobacteria and inhibited diatom under high TSS. Additionally, the biomass proportions of diatom (30.77 % vs. 22.28 %) and green (30.56 % vs. 23.30 %) decreased dramatically. In contrast, cyanobacteria abundance remarkably increased (35.78 % to 51.71 %) with the increasing NH4-N:NO3-N ratios. In addition, the proportion of non-nitrogen-fixing cyanobacteria was higher than that of the nitrogen-fixing cyanobacteria counterparts when TN:TP≥20 and NH4N:NO3N ≥ 10. Light-limitation phenotypes also experienced an increase with the rising NH4N:NO3N ratios. Notably, the cyanobacterial biomass reached 3-6 times that in the baseline scenario when the air temperature escalated by 3.0 °C until 2061 under the SSP585 scenario. We highlighted the effect of nitrogen forms on the succession of dominant phytoplankton species. Climate warming will increase nitrogen proportion, providing an insightful reference for controlling cyanobacterial blooms.
ABSTRACT
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.
Subject(s)
Fresh Water , Ponds , Eutrophication , PhosphorusABSTRACT
Spartina alterniflora has rapidly and extensively encroached on China's coastline over the past decades. Among the coastal areas invaded by S. alterniflora, at most 93% are mudflats. However, the effect of S. alterniflora invasion on soil organic carbon (SOC) stocks of coastal mudflats has not been systematically studied on a national scale. Here, we quantified the nationwide changes in SOC stocks in coastal mudflats associated with S. alterniflora invasion between 1990 and 2020. We found that S. alterniflora invasion significantly enhanced SOC stocks in coastal China. Nonetheless, the benefit of S. alterniflora invasion of coastal SOC stock may be weakened by continuing human intervention. We found that S. alterniflora invading mudflats added 2.3 Tg SOC stocks to China's coastal blue carbon, while 1.78 Tg SOC stocks were lost mainly due to human activities, resulted in a net SOC stock gain of 0.52 Tg C. These findings overturned the traditionally thought that S. alterniflora invasion would reduce ecosystem services by highlighting that the historical invasion of S. alterniflora has broadly and consistently enhanced blue carbon stock in coastal China.
Subject(s)
Carbon Sequestration , Carbon , Ecosystem , Introduced Species , Poaceae , Soil , China , Soil/chemistry , Carbon/analysis , HumansABSTRACT
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.
Subject(s)
Conservation of Natural Resources , Ecosystem , Water , Agriculture , ChinaABSTRACT
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.