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Faced with huge environmental problems of ecosystem degradation, “Ecological Redline Policy (ERP)” in China is a new key national-level policy to manage different land use functions in accordance with development and environmental limits. As the water–land complex ecosystem with the largest freshwater lake, wetland natural reserves and ecological importance in China, Poyang Lake Region (PLR) is selected to quantify and map multiple ecosystem services, investigate the ecological function zoning as part of research on ecological zoning control and major ecological source areas to illustrate and address the implementation of this strategy based on the importance and vulnerability analysis of ecosystem services. According to ecological function zoning results, extremely important, highly important, medium important and important zones respectively account for 26.1%, 28.1%, 17.4% and 28.4% of the total area. With an area of 5422.2 km2, the extremely important zone is 1010.6 km2 larger than the ERP. Moreover, 81.6% of the ERP is located in the extremely important zone. By discussing the implications and applications of ecological management, this study contributes to the ecological protection of Poyang Lake and provides a foundation for research on ecological function zoning at the regional scale.

Water level fluctuations (WLF) are natural patterns that are necessary for the survival of various plants, and WLF guarantee both the productivity and the biodiversity of wetlands. However, the underlying mechanisms of how changes in vegetation are linked to seasonal WLF remain unclear. Using vegetation and hydrological data from 1989 to 2009, we identified the key seasonal fluctuations and their impacts on vegetation in the Poyang Lake wetland by utilizing a tree-based hierarchical model. According to our results: 1) WLF in summer had significant impacts on both sedges and reeds. The severe summer floods promoted the expansion of sedges, while they inhibited the expansion of reeds; 2) WLF in autumn also greatly impacted sedges, while reeds were severely affected in spring. Specifically, we found that low water levels in autumn led to the expansion of sedges, and low water levels in spring led to the expansion of reeds. The results were well corroborated through comparisons of the vegetation distribution patterns over the last two decades (i.e., the 1990s and 2000s), which may shed light on corresponding water resource and wetland management.

Floodplain lakes are valuable to humans because of their various functions and are characterized by dramatic hydrological condition variations. In this study, a two-dimensional coupled hydrodynamic and water quality model was applied in a large floodplain lake (i.e., Poyang Lake), to investigate spatial and temporal water quality variations. The model was established based on detailed data such as lake terrain, hydrological, and water quality. Observed lake water level and discharge and water quality parameters (TN, TP, CODMn, and NH4-N) were used to assess model performance. The hydrodynamic model results showed satisfactory results with R2 and MRE values ranging between 0.96 and 0.99 and between 2.45 and 6.14%, respectively, for lake water level simulations. The water quality model basically captured the temporal variations in water quality parameters with R2 of TN, TP, CODMn, and NH4-N simulation ranges of 0.56–0.91, 0.44–0.66, 0.64–0.67, and 0.44–0.57, respectively, with TP of Xingzi Station and CODMn of Duchang Station excluded, which may be further optimized with supplementation of sewage and industrial discharge data. The modeled average TN, TP, CODMn, and NH4-N concentrations across the lake were 1.36, 0.05, 1.99, and 0.48 mg/L, respectively. The modeled spatial variations of the lake showed that the main channel of the lake acted as a main pollutant passageway, and the east part of the lake suffered high level of pollution. In addition, consistent with previous water quality evaluations based on field investigations, water quality was the highest (average TN = 1.35 mg/L) during high water level periods and the poorest (average TN = 1.96 mg/L) during low water level periods. Scenario analysis showed that by decreasing discharge of upstream flow by 20% could result in the increase of TN and TP concentrations by 25.6% and 23.2% respectively. In summary, the model successfully reproduced the complex water and pollutant exchange processes in the systems involving upstream rivers, the Poyang Lake, and the Yangtze River. The model is beneficial for future modeling of the impact of different load reduction and other hydrological regime changes on water quality variation and provides a relevant example for floodplain lake management.

Flooding is an important factor influencing the biomass production of vegetation in natural wetland ecosystems. However, how biomass production is linked to flooding patterns in wetland areas remains unclear. We utilized gauging station data, a digital elevation model, vegetation survey data, and a Landsat 8 image to study the effects of average inundation depth (AID) and inundation duration (IDU) of flooding on end-of-season biomass of vegetation in Poyang Lake wetland, in particular, after operation of Three Gorges Dam. The end-of-season biomass of wetland vegetation showed Gaussian distributions along both the AID and IDU gradients. The most favorable flooding conditions for biomass production of vegetation in the wetland had an AID ranging from 3.9 to 4.0 m and an IDU ranging from 39% to 41%. For sites with a lower AID ( 41%), the end-of-season biomass values were negatively related. After the operation of the Three Gorges Dam, flooding patterns characterized by AID and IDU of the Poyang Lake wetland were significantly alleviated, resulting in a mixed changing trend of vegetation biomass across the wetland. Compared with 1980–2002, the increase of end-of-season biomass in lower surfaces caused by the alleviated flooding pattern far exceeded the decrease of end-of-season biomass in higher surfaces, resulting in an end-of-season biomass increase of 1.0%–6.7% since 2003. These results improved our understanding of the production trends of vegetation in the wetland and provided additional scientific guidance for vegetation restoration and wetland management in similar wetlands.

The carbon sequestration capacity of wetland vegetation determines carbon stocks and changes in wetlands. However, modeling vegetation carbon sequestration of herbaceous wetlands is still problematic due to complex hydroecological processes and rapidly changing biomass carbon stocks. Theoretically, a vegetation index (VI) time series can retrieve the dynamic of biomass carbon stocks and could be used to calculate the cumulative composite of biomass carbon stocks during a given interval, i.e., vegetation carbon sequestration. Hence, we explored the potential for mapping vegetation carbon sequestration in herbaceous wetlands in this study by using a combination of remotely sensed VI time series and field observation data. This method was exemplarily applied for Poyang Lake wetland in 2016 by using a 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) time series. Results show that the vegetation carbon sequestration in this area was in the range of 193–1221 g C m−2 year−1 with a mean of 401 g C m−2 year−1 and a standard deviation of 172 g C m−2 year−1 in 2016. The approach has wider spatial applicability in wetlands than the currently used global map of vegetation production (MOD17A3) because our carbon estimation in areas depicted by ‘no data’ in the MOD17A3 product is considerable, which accounts for 91.2–91.5% of the total vegetation carbon sequestration of the wetland. Thus, we determined that VI time series data shows great potential for estimating vegetation carbon sequestration in herbaceous wetlands, especially with the continuously improving quality and frequency of satellite VI images.

Total phosphorus (TP) standards for lakes differ from those for rivers in GB3838-2002. This disjunction may lead to the failure of lake-water quality improvement plans that control nutrient inputs from inflow rivers. With monthly monitoring data for the period 2009–2015, Northwest Lake Taihu was regarded as a case study and the BATHTUB model was utilised to simulate the correspondence between concentrations of TP in the lake and in its inflow rivers. A control plan for TP in Northwest Lake Taihu's inflow rivers is proposed. To guarantee the fulfillment of the control goals of TP in the lake, concentration of TP in the inflow rivers of North Zone, Zhushan Bay, Meiliang Bay and Gonghu Bay should be reduced by 50%, 58%, 18% and 11%, respectively, and TP flux loads should be maintained under 227.35, 173.39, 113.69 and 90.62 ta−1, respectively. Meanwhile, total TP influxes from Northwest Lake Taihu should be maintained under 604.63 ta−1. A control plan that is more restrictive than GB3838-2002 should be proposed to address the TP pollution of the lake. This research provides the foundation for quantifying reduction of the nutrient loading from the catchment and for maintaining Lake Taihu and other typical eutrophic lakes.

The blocking or reversing effect of the downstream trunk river on its tributary lakes is an essential aspect of river-lake hydraulics. To measure how and the extent to which a trunk river can influence its tributary lakes, we made a case study in Changjiang River and one of its tributary lakes, Lake East Dongting (Lake ED) during a 35-year study period (1980–2014). Specifically, we investigated Lake ED’s discharge ability into Changjiang River using stage-discharge relationship curves, and hence the changes of the lake discharge ability under different hydrologic conditions of the Changjiang River. The results show that (1) the Changjiang River does exert a huge impact on the water regimes of Lake ED. And this impact varies seasonally. A variation of 3000 m3/s in Changjiang River’s runoff would change the lake water level by about 1.1 m in dry seasons, by 0.4 m in wet seasons, and by 0.6 m during severe summer floods. (2) Changes in the Changjiang River runoff triggered by the Three Gorges Dam since 2003 have led to dramatic water regime variations in Lake ED. Other factors, including reduction of lake inflow and the lake bed erosion, also exacerbated the water regime variations in Lake ED.

Wetland biomass is an important indicator of wetland ecosystem health. In this study, four dominant vegetation communities (Carex cinerascens, Phalaris arundinacea, Artemisia selengensis, and Miscanthus sacchariflorus) in the Poyang Lake wetland from 2010 to 2016 were classified from Landsat images using spectral information divergence (SID). We combined aboveground biomass (AGB) field measurements and remote sensing data to establish a suitable model for estimating wetland AGB in Poyang Lake, which is on the Ramsar Convention’s list of Wetlands of International Importance. The results showed that (1) overall, the classification accuracy for vegetation pixels across 5 years ranged from 59.1% to 73.7% and (2) the inter-annual and spatial variations in the AGB of the four vegetation types were clear. C. cinerascens had an average AGB density value of 1.28 kg m−2 in Poyang Lake from 2010 to 2016; M. sacchariflorus had the highest AGB density with an average value of 1.39 kg m−2; A. selengensis had almost the same level at 1.26 kg m−2; and P. arundinacea had the lowest AGB density at 0.64 kg m−2. This study provides useful experience for estimating carbon sequestration of vegetation in freshwater wetlands.

Floodplain lakes are valuable to humans because of their various functions. An emerging public concern on lake eutrophication has heightened the need to assess and predict the trophic status in floodplain lakes, particularly for those with high spatial heterogeneity. In this study, combined multivariate statistical techniques and random forests model were used to characterize the water quality and trophic status of Poyang Lake. By classifying and characterizing seasonal water samples comprising 11 water quality parameters collected from 13 sampling sites in Poyang Lake between 2008 and 2014, the dataset was divided into the central and northern lake groups, which corresponded to lentic and lotic regions in Poyang Lake, respectively. The spatial water quality variations and underlying patterns were investigated by performing discriminant analysis and principal component analysis (PCA). Lastly, random forests (RF) were used to predict the chlorophyll a (Chl-a) variations of the central and northern lakes. The PCA results indicated that the water quality of the central and northern areas of the lake was controlled by different environmental variables and underlying pollutant sources. The RF model outperformed the artificial neural network and linear regression and was robust with strong predictive capabilities. It was determined that the most important predictors of the Chl-a variations in the northern lake were water temperature (T) and water level, whereas transparency, T, and water level were the most efficient predictors in the central lake. The RF model can also be applied to trophic prediction in other large lakes with considerable spatial variations. This study will have implications on water quality management and eutrophication prevention in floodplain lakes with high spatial heterogeneity.

Water and mass exchange between rivers and lakes are key processes that maintain the health of the ecology of river–lake systems. Alteration to river–lake interactions have great impacts on water and mass balances. Naturally connected to the middle Yangtze River are the Poyang Lake and Dongting Lake, which are the largest and the second largest freshwater lakes in China. The operation of the Three Gorges Dam (TGD) in the upper Yangtze River was found to have substantial impacts on the middle Yangtze river–lake system. In the past decade, unusual seasonal dryness was evident in the two lakes. Considerable deviations in lake water quality and wetland ecosystem were also detected. In order to explore and distinguish the causal factors influencing the river–lake system, the Ministry of Sciences and Technology (China) launched a research project in 2012, the National Basic Research Program of China (973 Program) (2012CB417000). This article provides an overview of advances in this research, including the evolution of the river–lake interactions, the impacts of the TGD, and the influences on lake hydrology, water quality, and ecosystem. The 20 papers in this issue deliver part of the research outcomes of this project.

Poyang Lake is an important wetland with international significance in biodiversity conservation and local carbon cycle. A study was conducted to investigate the effects of vegetation communities on seasonal and spatial variations of soil organic carbon (SOC) and dissolved organic carbon (DOC) in two dominant wetlands (dish-shaped pit wetland and delta wetland) of Poyang Lake, China. Results revealed significant variations of SOC and DOC along the vegetation gradient. Maximum accumulation of SOC and DOC was produced in Phragmites community, and the minimum ones in Phalaris community both in spring and in autumn. In comparison with delta wetland, dish-shaped pit wetland obtained higher SOC within the same vegetation type, which indicated that soils of dish-shaped pit wetland had greater capacity to store carbon. Compared with SOC, DOC represented stronger seasonal variations with great increase in autumn, which suggested that DOC was more sensitive to hydrology processing. Furthermore, significant variations of SOC and DOC were closely related to vegetation biomass both in spring and in autumn. Moreover, elevation and gradient also affected the distributing pattern of organic carbon suggesting significant influence of topography characteristics on the carbon pool.

The effect of water-level fluctuations (WLF) on vegetation distribution and the makeup of the wetland environment is of growing interest as hydrological regimes become even more profoundly modified by human actions and climate change. It is necessary to develop a scientifically defensible and empirically testable relationship between changes in WLF and the corresponding ecological responses on a regional scale. We utilized correlation analyses, curve-fitting methods, and the classification and regression tree model to quantify both the linear continuum responses and the discontinuous threshold responses of the distribution of spring sedges in the Poyang Lake wetland in relation to different indicators of WLF. Our results suggest that: (1) the sedges exposed to a rapidly fluctuating water regime adjust their distribution pattern approximately every 30 days in an attempt to adapt to the new and ever changing environment; (2) the continual presence of high water levels lasting up to 20 days during the spring or extremely low water levels during the previous retreating season could trigger substantial changes in the distribution of spring sedges. Results of this study will help water resource managers to make informed decisions about how to regulate water conservation projects and protect the degrading wetland ecosystems.

Poyang Lake, a wetland area of critical ecological importance, is characterized by dish-shaped patterns of vegetation along the lakeshore. In this study, we intensively investigated seasonal and spatial variations of soil microbial biomass (SMB) within three representational vegetation communities in the two dominant types of wetlands within Poyang Lake. The results showed high levels of SMB carbon (SMBC) and SMB nitrogen (SMBN) among the vegetation communities within both types of wetlands. The highest concentrations of SMBC and SMBN were found in spring and autumn in the Phragmites community, the lowest in the Phalaris community. Compared to the delta wetland, the dish-shaped pit wetland was found to have higher levels of SMBC and SMBN within the same vegetation type. Interestingly, variations of SMB were also significantly and positively correlated with vegetation biomass both in spring and autumn. Moreover, we found variations of SMB to be consistently correlated with soil bulk density, soil nutrient conditions and elevation. However, contrary to seasonal tendency, we detected relationships between SMB and community biodiversity, indicating a hidden interaction between these aspects in Poyang Lake.

Poyang Lake, the largest freshwater lake of China, provides critical ecological functions for water circulation and biodiversity conservation as a dynamic wetland system. However, recent climate change and human activities exerted strong pressures on this ecosystem. In this paper, we applied object-based image analysis (OBIA) and Radom Forests (RF) classifier to ten Landsat images to examine the land cover composition and its change during 1987–2017 low water season at Poyang Lake. NDVI time series (2000–2017) derived from MODIS imagery was used to document the changes of vegetation growth status. To investigate the potential driving mechanism of the inundation patterns, we differentiated the spatial-temporal changes of vegetation coverage and NDVI accumulation on eight elevation bands. Major result indicates that the vegetation area increased by 15.5% of the lake area during 1987–2017. A much faster-increasing rate (58.0 km2 year−1) can be observed during 2001–2009 as compared to that of the overall study period (18.4 km2 year−1). Analysis of NDVI accumulation showed that 42.1% of the lake's area displayed a significant increasing trend during 2000–2017. Spatially, the increase of vegetation area and NDVI accumulation mainly took place in the 11–12 m elevation band in the lower lake center. Early dry season and prolonged exposure period after the operation of Three Gorges Dam (TGD) was the major reason for the spatio-temporal evolution of the wetland vegetation in Poyang Lake. The Lake's water level started to fall below 12 m before 9th November might cause a boost of vegetation growth in the low lake center, and in turn, triggering xerophilization for the vegetation in the highlands and a shift in foraging patterns of waterbirds due to phenology variations. The findings of this study provide a clear reference for sustaining the inter-annual stability of the ecosystem by controlling the depth of water in the lake.

Quantitative estimation of wetland aboveground biomass (AGB) is an essential aspect in evaluating the health and conservation of this valuable ecosystem. We combine AGB field measurements and remote sensing data to establish a suitable model for estimating wetland AGB in the Poyang Lake National Nature Reserve (PLNNR), which is included in the Ramsar Convention’s List of Wetlands of International Importance. All field sampling points cover four dominant vegetation communities (Carex cinerascen, Phalaris arundinacea, Artemisia selengensis, and Miscanthus sacchariflorus) in the PLNNR. Wetland AGB is retrieved from the Landsat-8 OLI image. To improve the accuracy of wetland AGB estimation, we compare the performances of three machine learning algorithms, namely, random forest (RF), back-propagation neural network (BPNN), and support vector regression (SVR), with linear regression (LR) in estimating the AGB in the PLNNR. Results are as follows: (1) the RF model with a root-mean-square error of 0.25 kg m − 2 performs better than BPNN (0.29 kg m − 2), SVR (0.27 kg m − 2), and LR (0.31 kg m − 2) in our testing dataset, and AGB density in the PLNNR is between 0 and 1.973 kg m − 2. (2) The four most important features for AGB modeling are near-infrared, short-wave infrared 1 band, enhanced vegetation index, and red band. Our study presents an effective and operational RF model that estimates wetland AGB from Landsat data, providing a scientific basis for floodplain wetland carbon accounting and possible future studies, such as the linkage between wetland AGB and the great water level fluctuations.

Nine cross sections of three typical rivers in the river-network plain to the east of Tai Lake were selected to measure water quality and water flow parameters monthly from September 2007 to August 2008. The spatial and temporal features of water quality were analyzed and the water pollution loads at river sections were estimated using statistic analysis. Combining land use in the riparian buffer zone interpreted form Remote Sensing images, the relationship between river water pollution load and land use were analyzed. It was clear that river water in the study area was polluted so seriously that water quality was ranked Grade V or worse. Pollutant input process in most river sections prevailed river self-purifying process. River qualities varied seasonally as that pollutant were denser in spring and winter than that in summer and autumn. Residential land in the 100 m buffer zone and industrial land in the 500 m buffer zone had the greatest influence on water quality. Forested and grassed riparian land appeared important in mitigating water quality degradation.

Determining the spatiotemporal water quality patterns and their corresponding driving factors is crucial for lake water quality managements. This study analyzed hydrological data and concentrations of 11 water quality parameters, including total nitrogen, total phosphorus, ammonia nitrogen and chlorophyll–a (Chl–a), for water samples collected from 15 sampling sites between 2009 and 2014. The water quality of sites in the northern Poyang Lake–Yangtze River waterway was influenced by different environmental parameters compared to sites in central lake, especially for Chl–a concentration. All pollutant parameters were significantly higher in the river phase (water level 14 m) (p < 0.05). These results were confirmed via principal component analysis, which identified three principal components that explained over 79% of the dataset variance. Among all the parameters related to climatic factors, eutrophication and organic pollution were the most important contributors in water quality. Dilution was the controlling factor that drove the seasonal variability in the water quality of the Poyang Lake, China. This work further indicated that regulating pollutant effluents in tributaries and water level within the lake could improve the water quality in Poyang Lake, which may give some impetus for water quality management.