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Wetlands provide vital ecological services for both humans and environment, necessitating continuous, refined and up-to-date mapping of wetlands for conservation and management. In this study, we developed an automated and refined wetland mapping framework integrating training sample migration method, supervised machine learning and knowledge-driven rules using Google Earth Engine (GEE) platform and open-source geospatial tools. We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland (DLW) during 2015–2021. First, the continuous change detection (CCD) algorithm was utilized to migrate stable training samples. Then, annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples. Ultimately, annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories, with Overall Accuracy (OA) ranging from 81.82% (2015) to 93.84% (2020) and Kappa Coefficient (KC) between 0.73 (2015) and 0.91 (2020), demonstrating satisfactory performance and substantial potential for accurate, timely and type-refined wetland mapping. Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring, conservation and sustainable development of wetland ecosystem.

The utility of semantic change detection in myriad change scenarios has garnered considerable attention in contemporary research; however, its applicability in monitoring alterations in wetland ecosystems remains incompletely elucidated. To surmount the constraints associated with binary change detection methodologies—chiefly their insufficiency in the extraction of bi-temporal attributes—we introduced the Bi-Temporal Semantic Reasoning UNet++ (Bi-SRUNet++) algorithm. This algorithm leverages the architectural strengths of UNet++ as its foundational network to precisely delineate features pertinent to multi-class change detection. As a preliminary step, the study focused on the Dongting Lake wetland in China and conducted an analysis of feature trends predicated upon the monthly Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), as derived from Landsat 8 data spanning 2021–2022. Subsequently, the optimal temporal phases for change detection were ascertained through differential analyses between NDWI and NDVI metrics. Implementing the Bi-SRUNet++ algorithm on a pair of Sentinel-2 images, captured during the optimal phases, yielded augmented change information. Comparative evaluations reveal that the Bi-SRUNet++ algorithm, conceptualized on the framework of Bi-Temporal Semantic Reasoning Network (Bi-SRNet), surpasses the performance indices of its counterpart Semantic Segmentation and Change Detection Late Fusion (SSCD-l). Furthermore, the incorporation of the UNet++ backbone network amplifies the algorithm's capacity for semantic feature extraction, thereby enhancing the efficacy of Bi-SRUNet++ in wetland change detection. The analysis divulges that the total altered area of Dongting Lake during the 2021–2022 period amounts to 1187.97 km2, comprising a water loss of 1186.16 km2, a 715.34 km2 transformation into vegetation, and a conversion of 469.96 km2 into mudflats. The codes and partial dataset in this paper are available at: https://github.com/vivianmiumiu/Bi-SRUNetplusplus-for-SCD.

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wetlands provide vital ecological services for both humans and environment, necessitating continuous, refined and up-to-date mapping of wetlands for conservation and management. In this study, we developed an automated and refined wetland mapping framework integrating training sample migration method, supervised machine learning and knowledge-driven rules using Google Earth Engine (GEE) platform and open-source geospatial tools. We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland (DLW) during 2015–2021. First, the continuous change detection (CCD) algorithm was utilized to migrate stable training samples. Then, annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples. Ultimately, annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories, with Overall Accuracy (OA) ranging from 81.82% (2015) to 93.84% (2020) and Kappa Coefficient (KC) between 0.73 (2015) and 0.91 (2020), demonstrating satisfactory performance and substantial potential for accurate, timely and type-refined wetland mapping. Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring, conservation and sustainable development of wetland ecosystem. [ABSTRACT FROM AUTHOR]

Abstract East Dongting Lake is a Ramsar site and a particularly important wintering ground for herbivorous geese along the East Asian‐Australasian Flyway. The operation of the Three Gorges Dam has changed the water regime and has a significant impact on wetland ecosystems downstream. We studied the responses of two sympatric herbivorous goose species, the Lesser white‐fronted goose Anser erythropus and Bean goose Anser fabalis, to habitat change by investigating their food conditions, habitat selection, and diet composition in the wintering periods of 2016/2017 and 2017/2018, which had early and late water recession, respectively. It was expected that the contrasting water regimes would result in different food conditions and geese responses. The results showed that the food quality and quantity differed significantly between winters. As responses to the high‐quantity/low‐quality food during 2016/2017, more geese switched to feeding on mudflat and exploited plants such as dicotyledons and moss. The tall swards of Carex spp. (dominant plants in the meadow) that developed during the first growing season decreased the food accessibility during the second growing season and hindered the exploitation of newly generated shoots by the geese, which was further confirmed by our clipping control experiment. Nearly all the geese chose to feed on meadow, and Carex spp. made up the majority of their diet in 2017/2018 when there was more low‐quantity/high‐quality food. Compared with the globally vulnerable Lesser white‐fronted geese, the larger‐sized Bean geese seemed to be less susceptible to winter food shortages and exhibited more stable responses. We concluded that the food quality–quantity condition was the external factor influencing the geese responses, while morphological and physiological traits could be the internal factors causing different responses between the two species. This study enhanced the understanding of the influence that habitat change exerts on herbivorous geese in their wintering site in the context of the Three Gorges Dam operation. We suggested that regulating hydrological regime was important in terms of wetland management and species conservation.

Understanding responses of habitat suitability of migratory birds to the water level is significant for providing countermeasures of wetland protection. East Dongting Lake serves critical wintering habitat for migratory birds along the East Asian-Australasian Flyway. However, the response relationships between the water level and the weighted usable area (WUA) for migratory birds remain largely unknown. Therefore, we established a habitat suitability model of migratory birds based on the Digital Elevation Model (DEM) and Normalized Difference Vegetation Index (NDVI) and recognized the change of WUA by comparing the transition of land-cover of similar hydrologic years before and after the operation of Three Gorge Dam (TGD). The results demonstrated that (1) the ecological water level of migratory birds in East Dongting Lake is 20.47–21.55 m. (2) Compared with the pre-TGD period, the start date of the ecological water level advanced by 25 days, the duration of the ecological water level increased by 16 days, and the fluctuation range of water level was more concentrated near the ecological water level, indicating that the TGD provides benefits for the migratory birds. (3) The most prominent transition among changes of land-cover was that the Reed beach (RB) (155.07 km2) and Marsh land (ML) (150.66 km2) changed to Tender Marsh land (TML) during dry hydrologic years, and the RB (171.90 km2) and ML (174.30 km2) changed to TML during normal hydrologic years. The findings show that water level changes habitat suitability of migratory birds by changing vegetation distribution at different elevations.

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the joint action of the Yangtze River Basin and Xiangjiang River Basin, Dongting Lake has caused irreversible heavy metal pollution to the surrounding wetland soil, and has brought about ecological, atmospheric and water natural pollution. In view of the main method to solve the heavy metal contaminated soil is the biological agriculture and forestry combined ecological restoration method, this paper takes the soil polluted by heavy metal in Dongting Lake wetland as the research object, and constructs multiple groups of comparative experiments with indoor potted plants as the object. In order to provide theoretical and technical support for improving and repairing the polluted soil in Dongting Lake wetland, ryegrass and Thiobacillus ferrooxidans were used as the objects of phytoremediation respectively to explore the method of phytoremediation combined with both of them, and to explore the effect of the method of Phytoremediation on the remediation of heavy metal pollution in soil. [ABSTRACT FROM AUTHOR]

East Dongting Lake is a Ramsar site and a particularly important wintering ground for herbivorous geese along the East Asian‐Australasian Flyway. The operation of the Three Gorges Dam has changed the water regime and has a significant impact on wetland ecosystems downstream. We studied the responses of two sympatric herbivorous goose species, the Lesser white‐fronted goose Anser erythropus and Bean goose Anser fabalis, to habitat change by investigating their food conditions, habitat selection, and diet composition in the wintering periods of 2016/2017 and 2017/2018, which had early and late water recession, respectively. It was expected that the contrasting water regimes would result in different food conditions and geese responses. The results showed that the food quality and quantity differed significantly between winters. As responses to the high‐quantity/low‐quality food during 2016/2017, more geese switched to feeding on mudflat and exploited plants such as dicotyledons and moss. The tall swards of Carex spp. (dominant plants in the meadow) that developed during the first growing season decreased the food accessibility during the second growing season and hindered the exploitation of newly generated shoots by the geese, which was further confirmed by our clipping control experiment. Nearly all the geese chose to feed on meadow, and Carex spp. made up the majority of their diet in 2017/2018 when there was more low‐quantity/high‐quality food. Compared with the globally vulnerable Lesser white‐fronted geese, the larger‐sized Bean geese seemed to be less susceptible to winter food shortages and exhibited more stable responses. We concluded that the food quality–quantity condition was the external factor influencing the geese responses, while morphological and physiological traits could be the internal factors causing different responses between the two species. This study enhanced the understanding of the influence that habitat change exerts on herbivorous geese in their wintering site in the context of the Three Gorges Dam operation. We suggested that regulating hydrological regime was important in terms of wetland management and species conservation. [ABSTRACT FROM AUTHOR]

In this report, an H12N2 influenza A virus was identified from a fecal sample in the falcated teal, Anas falcata, located in the Dongting Lake wetland. This is the first report of H12N2 IAV detected from wild birds in China. Phylogenetic analysis showed that all eight segments of this H12N2 virus clustered in the Eurasian lineage. This strain was also shown to be closely related to those from duck-origin, goose origin and wild bird origin. This suggested a transmission of infl uenza A virus along the East Asian-Australian flyway. In addition, these results implied an interaction between wild birds and domestic poultry and established the need of a long-term and systematic surveillance of wild bird populations. [ABSTRACT FROM AUTHOR]

• Dongting Lake has experienced land covers changes due to extreme hydrologic events. • We use qualitative and quantitative methods for change detection in Dongting Lake. • A new change detection method Bi-SRUNet++ is proposed for change detection. • This method has the great potential to improve the accuracy of wetland change detection. • The obtained information is important for wetland management and sustainable development. The utility of semantic change detection in myriad change scenarios has garnered considerable attention in contemporary research; however, its applicability in monitoring alterations in wetland ecosystems remains incompletely elucidated. To surmount the constraints associated with binary change detection methodologies—chiefly their insufficiency in the extraction of bi-temporal attributes—we introduced the Bi-Temporal Semantic Reasoning UNet++ (Bi-SRUNet++) algorithm. This algorithm leverages the architectural strengths of UNet++ as its foundational network to precisely delineate features pertinent to multi-class change detection. As a preliminary step, the study focused on the Dongting Lake wetland in China and conducted an analysis of feature trends predicated upon the monthly Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), as derived from Landsat 8 data spanning 2021–2022. Subsequently, the optimal temporal phases for change detection were ascertained through differential analyses between NDWI and NDVI metrics. Implementing the Bi-SRUNet++ algorithm on a pair of Sentinel-2 images, captured during the optimal phases, yielded augmented change information. Comparative evaluations reveal that the Bi-SRUNet++ algorithm, conceptualized on the framework of Bi-Temporal Semantic Reasoning Network (Bi-SRNet), surpasses the performance indices of its counterpart Semantic Segmentation and Change Detection Late Fusion (SSCD-l). Furthermore, the incorporation of the UNet++ backbone network amplifies the algorithm's capacity for semantic feature extraction, thereby enhancing the efficacy of Bi-SRUNet++ in wetland change detection. The analysis divulges that the total altered area of Dongting Lake during the 2021–2022 period amounts to 1187.97 km2, comprising a water loss of 1186.16 km2, a 715.34 km2 transformation into vegetation, and a conversion of 469.96 km2 into mudflats. The codes and partial dataset in this paper are available at: https://github.com/vivianmiumiu/Bi-SRUNetplusplus-for-SCD. [ABSTRACT FROM AUTHOR]

Understanding how migratory waterbirds respond to hydrology and climate is of great importance for providing valuable insight into conservation in wetland system. Dongting Lake Wetland is an important wintering habitat in the East Asian-Australasian Flyway. However, little is known about the effects of hydrology and climate on wintering waterbirds. Therefore, it is urgent to analyze the relationship between them. To better interpret the ecological significance, we divided the bird species into five functional groups on the basis of their typical feeding habits. Redundancy analysis (RDA) combined with forward selection procedure was applied to select the hydrological and climatic variables with significant influences. Then, response surface methodology (RSM) was carried out to identify the thresholds of the variables. The results showed that inflow and water level were probably the two critical variables accounting for 52.13% and 47.87% of the variation in the bird species, respectively. However, other variables did not reach a significant level in this study. As for the group-level, different functional bird groups had different reflections to inflow and water level. Minimal guaranteed values of the two variables were identified as 3518.82–3736.28 m 3 /s and 22.61–23.49 m respectively based on the hydrological requirements and the weights of all groups. The results highlighted that the minimal requirements of inflow and water level should be satisfied to provide appropriate habitats for waterbirds. Besides, the regulatory authorities and environmental protection agencies should develop relevant law or regulation to protect waterbird habitats from human destruction especially the activities which could change the hydrological regime. [ABSTRACT FROM AUTHOR]

Heavy metal contamination is present in wetland ecosystem worldwide, and quantitative risk assessment model is significant. In this study, an exposure model was integrated for assessing heavy metal exposure risk to migratory birds in Dongting Lake Wetland (DTW). The concentrations of Cr, Cu, Pb, Cd, Hg and As in water, plant, soil and fish were investigated from 9 migratory bird habitats. The results showed that exposure doses from drinking water pathways were very low. There was a sensitive area that Cd and As exposure doses exceeded the most conservative tolerable daily intake, which is located at the estuary of Xiang River. In general, Dunlin had a greater risk than Eurasian Spoonbill. Hg, Pb and Cr were likely to have adverse effect on carnivorous migrants in DTW, while Cu and Cd were considered to be relatively safe. Almost all heavy metals were at no risk for Lesser White-fronted Goose in DTW. [ABSTRACT FROM AUTHOR]

In recent 20 years, the area of lake grass has been drastically reduced and degraded. In order to search for reasonable recovery ways of the lake grass, the vegetational characteristics (plant height, coverage, density, biomass and biodiversity index) and soil physico-chemical characteristics (soil organic carbon, SOC; total nitrogen, TN; total phosphorus, TP; soil bulk density and moisture) were investigated in the Carex brevicuspis community from 63 sampling plots in 7 sampling belts along an elevation gradient in Dingzidi, East Dongting Lake. All biological characteristics showed an inverted "U"distribution pattern along with increasing elevation, except for diversity index, which showed a tendency of increasing at first and then decreasing. Plant growth was inhibited near water body (low elevation region) and levee (high elevation region). In contrast, the intermediate elevation region had a favorable condition for plant growth. For soil physical properties, soil water moisture decreased but soil bulk density increased along with increasing elevation. However, SOC and TN contents were higher in the intermediate elevation region and lower in both low and high elevation regions. TP content was fluctuant along with increasing elevation. The principal component analysis (PCA) showed that the key factors influencing biomass of C. brevicuspis were soil C and N contents, soil moisture and bulk density. These results indicated that increasing soil fertility and maintaining proper soil moisture might be efficient to recover the vegetation of C. brevicuspis. [ABSTRACT FROM AUTHOR]

Based on the field investigation and measurement, and by using the monetary method, this paper estimated the wetland ecosystem service value of Dongting Lake before and after the impoundment of Three Gorges Reservoir (in 1996 and 2010, respectively). After the impoundment, the total ecosystem service value increased from 156. 69×108 yuan in 1996 to 177. 11×108 yuan in 2010. The main services value in 1996 was in the order of flood storage and regulation > water storage and supply > air regulation > scientific research and education, while that in 2010 was leisure tourism > shipping transportation > air regulation > water storage and supply. In the total service value of the wetland ecosystem, the direct value associated with water decreased from 110.85×108 in 1996 to 27. 47×108 in 2010, with a decrement of 75. 2%. Though the proportion of the direct value in the production and supply of material products had somewhat increase, the indirect value in ecological environment regulation and maintenance and in culture and society still maintained at about 80% of the total value. In addition to climate factors, the impoundment of Three Gorges Reservoir and the reduction of water and sediment from Yangtze River to the Lake were the crucial reasons leading to the changes of the wetland ecosystem service value of Dongting Lake. [ABSTRACT FROM AUTHOR]

• A habitat suitability model of migratory birds based on DEM and NDVI. • Transition of land-cover of similar hydrologic years before and after 2003. • The driving factors for improving habitat suitability of migratory birds. Understanding responses of habitat suitability of migratory birds to the water level is significant for providing countermeasures of wetland protection. East Dongting Lake serves critical wintering habitat for migratory birds along the East Asian-Australasian Flyway. However, the response relationships between the water level and the weighted usable area (WUA) for migratory birds remain largely unknown. Therefore, we established a habitat suitability model of migratory birds based on the Digital Elevation Model (DEM) and Normalized Difference Vegetation Index (NDVI) and recognized the change of WUA by comparing the transition of land-cover of similar hydrologic years before and after the operation of Three Gorge Dam (TGD). The results demonstrated that (1) the ecological water level of migratory birds in East Dongting Lake is 20.47–21.55 m. (2) Compared with the pre-TGD period, the start date of the ecological water level advanced by 25 days, the duration of the ecological water level increased by 16 days, and the fluctuation range of water level was more concentrated near the ecological water level, indicating that the TGD provides benefits for the migratory birds. (3) The most prominent transition among changes of land-cover was that the Reed beach (RB) (155.07 km2) and Marsh land (ML) (150.66 km2) changed to Tender Marsh land (TML) during dry hydrologic years, and the RB (171.90 km2) and ML (174.30 km2) changed to TML during normal hydrologic years. The findings show that water level changes habitat suitability of migratory birds by changing vegetation distribution at different elevations. [ABSTRACT FROM AUTHOR]

We analyzed soil quality based on soil microbial characteristics of three different vegetation types in the wetlands of East Dongting Lake, including Carex tristachya wetland (CTW), Phragmites australis wetland (PAW), and Salix babylonica wetland (SBW). The soil microbial biomass carbon (MBC), nitrogen (MBN) and enzyme activities were measured and the key influen-cing factors were analyzed during the normal, flood, and dry periods. The results showed that: 1) The amounts of MBC, MBN, and the activities of invertase and cellulase (except cellulase of dry season) in 0-10 cm were higher than those in 10-20 cm for all wetlands, while the catalase activity showed an opposite pattern. 2) The amounts of MBC and MBN and the values of MBC/TOC and MBN/TN for the 0-20 cm soil layer of each vegetation type wetland were the lowest in flood period. 3) Soil invertase activity for each vegetation type wetland in the 0-20 cm soil layer peaked in the dry period, while soil cellulase activity peaked in the normal period. The seasonal fluctuation of soil catalase activities in all wetlands were small, with activities being slightly higher in flood period than the other two periods. 4) Among different vegetation types, soil invertase activity of PAW was significantly higher than that of other vegetation types, and cellulase activity of which was the lowest in both normal and flood periods. There was no difference in these two enzymes activities among wetlands during the dry period. The highest soil catalase activity was found in CTW during normal period and in SBW during dry period, respectively, while its lowest value was in PAW during flood period. 5) Soil MBC, MBN and invertase activity were correlated positively with soil TOC, TN and TP, and negatively correlated with soil pH. The activities of soil cellulase and catalase were significantly negatively correlated with TOC, TN, TP and positively correlated with pH. It suggested that the seasonal fluctuation of water level affected soil C, N, P contents and pH values, with consequences on soil MBC, MBN and enzyme activities.