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The lake-floodplain wetlands are characterized by high biodiversity, difficult access, and significant environmental changes. Traditional remote sensing mapping methods struggle to generate consistent time-series data on wetland vegetation communities. Current research has endeavoured to address this issue through the application of deep learning methodologies. However, a significant limitation of these models is their reliance on a substantial volume of training samples, which contradicts the difficulty and high cost of obtaining samples from the lake-floodplain wetlands. Whether it is possible to construct a transferable deep learning model under small sample conditions and apply it to the mapping of lake-floodplain wetlands is an urgent issue that needs to be addressed. To solve this problem, this study first constructed a deep neural network (DNN) designed specifically for mapping complex lake-floodplain wetland vegetation under conditions of limited sample size. Subsequently, using 2021 as a reference year, a novel histogram threshold method was proposed to identify the unchanged samples for the target transfer years of 2019, 2020, 2022, and 2023. Finally, annual wetland vegetation mapping was performed in Poyang Lake using DNN and sample transfer learning (STL). The results showed that high-quality annual time-series data of wetland vegetation can be generated using the constructed DNN and STL, with all overall accuracies exceeding 80%. The histogram threshold method, which combines SAD and NDVI indicators of key phenological period, can effectively solve the problem of difficulty in determining the unchanged samples in transfer learning for heterogeneous lake wetlands. Furthermore, the performance of STL based on the constructed DNN model was significantly superior to those based on support vector machine and random forest algorithms for mapping annual wetland vegetation communities using limited training samples. This study demonstrates that the effective application of DNN and STL will be highly beneficial for long-term monitoring of vegetation in lake-floodplain wetlands, particularly where sample availability is limited. [ABSTRACT FROM AUTHOR]

Vegetation is not only directly influenced by water flow but also affected by the time-lag effects of water elements accumulated in the soil of wetland ecosystems. However, extensive studies have focused on the direct impacts of water on vegetation, with limited consideration of lag effects due to the lack of appropriate quantitative methods. This study aims to quantitatively determine the effects of two different forms of water on wetland vegetation. Using long-term Landsat data, three vegetation patches were extracted, and two types of hydrological variables (immediate and time-lag) were constructed to analyze their relationships. The results showed that: (1) Different vegetation patches exhibited distinct spatio-temporal dynamics over time. The distribution elevation of dense and high grass patches significantly decreased, and their ecological niche expanded; (2) The influence of hydrological variables on different vegetation patches varies: the sensitivity to immediate hydrological variables over time is sparse grass patch > dense grass patch > high grass patch; the influence of time-lag hydrological variables on vegetation decreases as the lag time increases. Vegetation at lower elevations is more affected by time-lag hydrological variables, with dense grass patches at moderate elevation experiencing the longest lag effects. This study provides useful insights into the effects of different forms of water on wetland vegetation, offering additional perspectives for future research on the dynamics between wetland water and vegetation. [ABSTRACT FROM AUTHOR]

Coastal wetlands play an important carbon sequestration role in China's "carbon peaking" and "carbon neutrality" goals. Monitoring aboveground biomass (AGB) is crucial for wetland management. Satellite remote sensing enables efficient retrieval of AGB. However, a variety of statistical models can be used for biomass inversion, depending on factors such as the vegetation type and inversion method. In this study, Landsat 8 Operational Land Imager (OLI) images were preprocessed in the study area through radiation calibration and atmospheric correction for modeling. In terms of model selection, 13 different models, including the univariate regression model, multiple regression model, and machine learning regression model, were compared in terms of their accuracy in estimating the biomass of various wetland vegetation types under their respective optimal parameters. The findings revealed that: (1) the regression models varied across vegetation types, with the accuracy of the biomass estimates decreasing in the order of Scirpus spp. > Spartina alterniflora > Phragmites australis; (2) overall modeling, without distinguishing vegetation types, addressed the challenges of limited samples availability and sampling difficulty. Among them, the random forest regression model outperformed the others in estimating wet and dry AGB with R2 values of 0.806 and 0.839, respectively. (3) Comparatively, individual modeling of vegetation types can better reflect the biomass of each wetland vegetation type, especially the dry AGB of Scirpus spp., whose R2 and RMSE values increased by 0.248 and 11.470 g/m2, respectively. This study evaluates the impact of coastal saltmarsh vegetation types on biomass estimation, providing insights into biomass dynamics and valuable support for wetland conservation and restoration, with potential contributions to global habitat assessment models and international policies like the 30x30 Conservation Agenda. [ABSTRACT FROM AUTHOR]

Wetland vegetation is the most crucial primary producer in wetland ecosystems and serves as an indicator of ecosystem health. After 2003, significant changes occurred in the “river-lake relationship” between Poyang Lake and the Yangtze River, with intensified dry conditions in autumn and winter leading to a shortened inundation period for sandbanks and significant changes in the community structure and spatial distribution of wetland vegetation. By coupling a Gaussian model with a population dynamics model, this study simulated the response of wetland vegetation to inundation duration under different hydrological year types, revealing the relationship between vegetation distribution and inundation duration. Key parameters, such as growth and mortality rates, were identified, and the vegetation succession and spatial distribution of Poyang Lake wetlands were simulated for five representative years: a wet year (2010), a normal year (2001), a dry year (2006), an extreme wet year (1998), and an extreme dry year (2022). The results showed that the response of wetland vegetation to inundation duration followed a Gaussian curve, with each species exhibiting an optimal range of inundation durations. Mortality rates increased when the duration fell outside this range. In 2010, the total area of wetland vegetation was similar to that in a normal year, but the proportions of different plant species varied significantly. Compared to 2001, the areas of Phalaris arundinacea and Polygonum criopolitanum increased by 50.92 % and 24.86 %, respectively, while the areas of Phragmites australis and Triarrhena lutarioriparia decreased by 71.66 % and 83.49 %. In 1998, the total vegetation area shrank considerably, with a 54.74 % reduction compared to 2001 and a 64.32 % reduction compared to 2006. In contrast, the total wetland vegetation area reached its maximum in the extreme dry year of 2022, increasing by 41.35 % compared to 2001. Among dominant species, Carex spp., Cynodon dactylon, and Phragmites australis expanded significantly in dry years, while Phalaris arundinacea and Polygonum criopolitanum were better adapted to flood conditions.

The partitioning of overall beta diversity into local contributions (LCBD; compositional uniqueness) and species contributions (SCBD) has enhanced the understanding of the organization of metacommunities. Here, we evaluated LCBD and SCBD of aquatic macrophyte metacommunities from 29 subtropical coastal wetlands, covering an extension of 640 km, in Southern Brazil. Furthermore, we assessed the environmental uniqueness, considering both the physical and chemical variables of water in wetlands, as well as climatic variables. We assessed the environmental and spatial correlates of LCBD and the environmental correlates of SCBD. We expected that (i) communities with greater compositional uniqueness would be found in environmentally more unique wetlands, (ii) the compositional uniqueness would also be related to climatic variables that determine the hydrological changes in wetlands, and (iii) the contribution of emergent species to beta diversity would be lower than of floating and submerged species. The compositional uniqueness did not present a clear spatial structure, being positively related to uniqueness in water chemistry and negatively to the mean air temperature during the driest quarter. The species contribution to beta diversity was higher for floating species than for emergent ones. Moreover, SCBD correlated to climatic variables and presented a positive relationship with site occupation, suggesting that more frequent species in terms of site occurrence contribute most to beta diversity. Our results show the importance of local environmental and broader climatic predictors in determining the compositional uniqueness of macrophyte communities and species contributions to overall beta diversity in the coastal wetlands of Southern Brazil. [ABSTRACT FROM AUTHOR]

Few studies have evaluated the invasive effects on soil properties in urban ecosystems. In this study, population density and impervious surface area were used to divide the two river wetlands of Qingdao City, China— River Zhangcun and River Wenquan—into urban and periurban types. Sediments were sampled from plots colonized by the invasive Alternanthera philoxeroides and the native Typha angustifolia in these two river wetlands. The sediment properties, including fertility, stoichiometry, microbial diversity indices (observed species, Chao1, Shannon's diversity index and Simpson's diversity index) and species composition, were evaluated and compared. We found similar fertility and stoichiometry between sediments derived from invasive and native species. A greater bacterial diversity was found in the sediment derived from A. philoxeroides in the periurban river, while a greater fungal diversity was merely shown for the Shannon's diversity index of A. philoxeroides regardless of river types. In addition, more microbes relevant to nutrient cycling processes, such as denitrification, accumulated in response to invasion, which may have decreased the habitat quality and impeded the invasion of T. angustifolia into A. philoxeroides populations. The discrepancy in urbanization status affected the impact of plant colonization on sediment properties, and the opposite results were shown for the comparisons of sediment nitrogen availability and bacterial diversity between the two species. Urbanization discriminated the impact of invasion to some degree. The invasion of A. philoxeroides altered the sediment microbiome, and the potential plant‒soil feedback needs further investigation. [ABSTRACT FROM AUTHOR]

The Poyang Lake Wetland, an internationally significant ecosystem, frequently experiences drought during the flood season. However, the total impact of extreme drought on wetland vegetation remains poorly understood. This study determined the standardised precipitation evapotranspiration index (SPEI) and analysed drought trends within the Poyang Lake Basin. Additionally, spatiotemporal variations in wetland vegetation under drought conditions were examined by analysing the mean normalised difference vegetation index (NDVI) values and categorising NDVI classifications. The key factors affecting wetland vegetation and its respective thresholds were determined. The Poyang Lake Basin has experienced increasing aridity over the past 3 years. In response to this trend, the wetland vegetation area in Poyang Lake expanded, whereas vegetation greenness declined. Notably, in the year following an extreme drought, Poyang Lake's vegetation greenness was lower than that during the same period in previous years. Regardless, the correlation analysis showed no significant relationship between the SPEI values and the wetland vegetation greenness; however, water level changes significantly impacted the wetland vegetation, with a correlation coefficient of −0.89 (p < 0.001). A critical water level of 14 m was identified as the threshold at which sudden changes in the mean NDVI were observed. This research offers valuable insights into hydrological management strategies to protect Poyang Lake Wetland's vegetation under drought conditions. Future studies should enhance the differentiation of drought tolerance among different wetland plant species, thereby achieving differentiated hydrological management. [ABSTRACT FROM AUTHOR]

Hydrology is an important environmental factor for the evolution of wetland landscape patterns. In the past 20 years, Poyang Lake, the largest freshwater lake in China, has experienced significant inundation shrinkage and water level decrease, posing a significant threat to the local vegetation community. To explore the potential relationship between aquatic vegetation and hydrological processes in the recent hydrological situation, in this study, the landscape patterns of aquatic vegetation communities in Poyang Lake were studied using time-series Landsat remote sensing images and a support vector machine classifier. The stepwise regression analysis method was adopted to analyze the relationship between the vegetation area and hydrological factors. The results indicated that the area of submerged and emergent vegetation in the entire lake decreased significantly from 2001 to 2017, whereas the area of moist vegetation showed a remarkably increasing trend. The average distribution elevation of the submerged vegetation increased by 0.06 m per year. The corresponding landscape patterns showed that the degree of fragmentation of aquatic vegetation communities in Poyang Lake increased. Several hydrological factors were selected to quantify the potential impact of water level fluctuations. The correlation analysis results indicated that hydrological conditions during the rising- and high-water periods may be the key factors affecting the area of aquatic vegetation. This study systematically investigated the evolution of vegetation communities in Poyang Lake wetlands over the past two decades, which contributes to the protection and management of this unique ecosystem. [ABSTRACT FROM AUTHOR]

Bokong Nature Reserve (BNR) forms part of the core of the first and newly established Matšeng Biosphere Reserve in Lesotho. However, lack of baseline data makes it difficult to monitor the wetland vegetation in BNR. This study characterised the vegetation of the high-altitude montane palustrine wetlands of this area. Plant species composition was assessed using the Braun-Blanquet approach, and the height and cover of the vegetation were measured. Furthermore, environmental data were collected using standard methods. The data were analysed by determining species richness and calculating Shannon-Wiener diversity and evenness, as well as employing cluster analysis, canonical correspondence analysis and redundancy analysis. The results show that a total of 175 plant species from 102 genera and 40 families were encountered. The dominant plant families were Asteraceae, Poaceae and Cyperaceae. Hierarchical cluster analysis produced 10 plant communities in the range of 1–36 species per 3 m × 3 m plot. Important environmental factors influencing the wetland vegetation were longitude, altitude, latitude, soil sodium, inundation, soil texture, soil magnesium and soil phosphorus. The results indicate that the wetlands are not only in a relatively stable condition, but also support diverse vegetation and store a substantial amount of carbon, thus contributing to biodiversity conservation and climate change mitigation. Because the wetland vegetation determines the functioning of the system, which in turn influences the supply of ecosystem services, our findings form a baseline dataset for monitoring the BNR wetland vegetation, especially in the face of climate change. Conservation implications: The BNR wetlands fall within the catchment of the Lesotho Highlands Water Project dams that are important for water resources in southern Africa. Furthermore, the wetlands are of international conservation value because they form part of the core of a UNESCO-declared man and biosphere reserve and play an important role in supporting biodiversity.

The aboveground biomass (AGB) of wetland vegetation is a crucial indicator for assessing the health of wetland ecosystems. In the context of global biodiversity threats, biodiversity has become a focal point in ecological and remote sensing research. This study focuses on the Beiliuyao area on Chongming Island, and ground-based biomass data and unmanned aerial vehicle (UAV) hyperspectral imagery are employed for the regional-scale estimation of the AGB of wetland vegetation. Considering the significant differences in AGB between Spartina alterniflora and Phragmites australis during different phenological periods, and AGB retrieval models are constructed based on vegetation classification. Multivariate stepwise regression (MSR), BP neural network (BP), and random forest regression (RFR) models are used to estimate both the dry and wet weights of AGB at the species level. The research results are as follows: (1) Compared with the other three estimation models for the same period, the RFR model yields the highest accuracy, with an R2 reaching 0.82 and an RMSE of 116.14 g/m2. (2) The accuracy of the estimations in November is lower under the same model conditions than that in other months, with the lowest R2 of 0.57 and an RMSE of 228.42 g/m2. (3) The weight of the AGB gradually decreases from August to November, and the wet AGB density ranges from 6000 to 7000 g/m2 with an account of 4.2 % of the wet ABG falling within this range in August. The results of this study demonstrate that UAV hyperspectral imagery and the RFR model can be used to effectively estimate the biomass of dominant species in wetlands. This approach provides a theoretical basis for the large-scale, efficient and dynamic monitoring of the AGB of wetland vegetation.

Wetlands perform important functions and provide essential ecological services, including flood attenuation, groundwater recharge and discharge, and water purification. Human activities such as urban and rural development, drainage, and land alteration can cause major disturbances, often resulting in the drying up of wetlands. Therefore, many restoration projects aim to restore wetland hydrology. Hydrology significantly affects wetland functions by modifying and determining the wetlands physicochemical environment that allows for the development of a specific biota. Despite the importance of hydrology, monitoring efforts are mainly focused on surveying and characterizing wetland habitats or plant composition. There are few datasets available from the monitoring of the depth to water table (DTW) in wetlands and when available they are rarely shared. Collecting hydrological data can contribute to a better understanding of the relationship between hydrology, soil and habitat and can help understand the effect of climate change. From 2021 to 2023, depth to water table, soil and habitat data were collected across a variety of wetland types in France with a focus on hydrological data. Using data loggers placed in 37 monitoring wells across 17 wetlands, 469001 hourly depth to water table and water temperature data were collected. The dataset includes two files containing a total of 22 variables that describe the location of sites, habitat (EUNIS: European Nature Information System), soil hydromorphy, depth to water table, and water temperature. The dataset can be used to better understand wetland hydrology and its relationship to soil and habitat. The data collection process may be used to help restoration project achieve their goal.

Ranunculus lingua is an Euro-Siberian vascular plant species of freshwater habitats. Distribution and vegetation preferences of this rare species, which is native to the Slovak flora, have not yet been critically revised. The present paper aimed i) to provide the first complex distribution pattern of this species in Slovakia and ii) to analyse all available vegetation plots with species occurrence in order to elucidate the variability of plant communities. The distribution data were retrieved from herbarium specimens, literature records and field surveys. Our revision suggests that R. lingua was found particularly in the lowland areas of the western, south-western and south-eastern parts of the country. It was very rare in other regions of Slovakia, and several populations have become extinct due to drainage or habitat destruction. New localities of secondary origin were additionally documented in some human-made habitats. The temporal trend showed a strong decrease in the number of localities in natural habitats, mainly in the hilly and mountainous regions of the Western Carpathians from the 1980s to the end of the twentieth century. R. lingua was recorded in both forest and treeless swamp communities. Vegetation analysis revealed numerous records mainly in eutrophic marshes (Phragmito-Magnocaricetea class), willow and alder carrs (Franguletea and Alnetea glutinosae). [ABSTRACT FROM AUTHOR]

Wetlands are one of the world's three major ecosystems. Marsh wetland vegetation, with its unique characteristics, is playing an increasingly prominent role in absorbing atmospheric carbon dioxide and mitigating climate warming. This study estimated the annual, seasonal, and monthly trends of marsh wetland vegetation net primary productivity (NPP) in China from 2005 to 2015 based on the Carnegie–Ames–Stanford approach (CASA) model. The temporal and spatial characteristics of NPP were analyzed and the driving factors were discussed. The results showed that the annual marsh wetland vegetation NPP had an increasing trend from 2005 to 2015 on national scale in China, with the lowest and highest values in 2005 (202.03 gCm−2a−1) and 2015 (222.58 gCm−2a−1), respectively. The monthly seasonal variations in marsh wetland vegetation NPP consistent with the typical growth pattern of vegetation observed in China. Monthly marsh wetland vegetation NPP showed a unimodal distribution, and May to September were the main months for NPP accumulation. The highest vegetation NPP values occurred during the summer season. Marsh wetland vegetation types did impact the NPP distribution, Gramineous marsh vegetation contributed most to the total NPP (29%). Spatially, the NPP was higher in east than in the west, and higher in the center than in the south and north. An overall positive impact of precipitation and temperature on the Chinese marsh wetland vegetation NPP was revealed. The study recommended to give greater attention the conservation of Gramineous vegetation alongside the overall protection of Chinese marsh wetlands. Our findings can offer important evaluation results and guidance for the future addressing climate change and conservation and maintenance of the carbon sink capacity of marsh wetland vegetation in China.

Wetland vegetation biomass is an essential indicator of wetland health, and its estimation has become an active area of research. Zizania latifolia (Z. latifolia) is the dominant species of emergent vegetation in Honghu Wetland, and monitoring its aboveground biomass (AGB) can provide a scientific basis for the protection and restoration of this and other wetlands along the Yangtze River. This study aimed to develop a method for the AGB estimation of Z. latifolia in Honghu Wetland using high-resolution RGB imagery acquired from an unoccupied aerial vehicle (UAV). The spatial distribution of Z. latifolia was first extracted through an object-based classification method using the field survey data and UAV RGB imagery. Linear, quadratic, exponential and back propagation neural network (BPNN) models were constructed based on 17 vegetation indices calculated from RGB images to invert the AGB. The results showed that: (1) The visible vegetation indices were significantly correlated with the AGB of Z. latifolia. The absolute value of the correlation coefficient between the AGB and CIVE was 0.87, followed by ExG (0.866) and COM2 (0.837). (2) Among the linear, quadratic, and exponential models, the quadric model based on CIVE had the highest inversion accuracy, with a validation R2 of 0.37, RMSE and MAE of 853.76 g/m2 and 671.28 g/m2, respectively. (3) The BPNN model constructed with eight factors correlated with the AGB had the best inversion effect, with a validation R2 of 0.68, RMSE and MAE of 732.88 g/m2 and 583.18 g/m2, respectively. Compared to the quadratic model constructed by CIVE, the BPNN model achieved better results, with a reduction of 120.88 g/m2 in RMSE and 88.10 g/m2 in MAE. This study indicates that using UAV-based RGB images and the BPNN model provides an effective and accurate technique for the AGB estimation of dominant wetland species, making it possible to efficiently and dynamically monitor wetland vegetation cost-effectively. [ABSTRACT FROM AUTHOR]

The study of dark carbon fixation in estuarine wetlands is of great scientific significance for the comprehensive understanding and scientific assessment of the carbon sink potential of estuarine wetlands. Taking Chongming Dongtan as a typical study area, the effects of different wetland vegetation distributions on sediment dark carbon fixation and its key environmental control factors were studied using 14C isotope labeling technology combined with molecular biology research methods. The results showed that: the annual mean values of sediment dark carbon fixation rates in mudflat, Phragmites australis, and Spartina alterniflora wetlands were (1.27±0.66), (0.88±0.40), (1.37±0.63) mmol/(m² · d) C, respectively; there were significant seasonal differences in sediment dark carbon fixation in estuarine wetlands, in which the dark carbon fixation rates increased significantly in summer, but were inhibited by extremely high temperatures; the dark carbon fixation in sediments was promoted by Spartina alterniflora, while that in the Phragmites australis area was reduced relative to the mudflat; different vegetation influenced the dark carbon fixation in the sediment by regulating the NH4+, Fe3+, S2- and the abundance of functional genes (cbbL and cbbM). The results provide a theoretical reference to accurately assess the carbon sink potential and the influence mechanisms of the estuarine wetlands. [ABSTRACT FROM AUTHOR]

Wetlands play an important role in cycling water resources, organic matter, water purification, and ecosystem conservation. Understanding flow regimes is essential for effective wetland management because it significantly influences wetland succession and circulation. This study aims to develop a methodology for quantifying flow regimes of the Jangdan Wetland (Imjin River) and the Binae Wetland (Namhan River). The study utilized water level duration curve (LDC) based on historical water level data from 2008 to 2023 for the Binae Wetland and from 2003 to 2023 for the Jangdan Wetland to analyze hydrological flow regimes. Flow regime diagrams describing the inundation characteristics over time, were then constructed using the LDC and the digital elevation models (DEM) of the wetlands. To understand the relationship between vegetation communities and hydrologic regime in the wetland, this study classified nine vegetation zones based on the tolerance of associated plant species to inundation (in weeks or months) reported for plant species in previous studies. The study revealed that the Jangdan Wetland were dry primarily on most days but experienced complete inundation during flooding events. In contrast, the Binae Wetlands were found to be frequently inundated, with approximately 40 % of the area experiencing regular flooding, while 20 % of the higher elevation areas were only inundated once every few years. • Water Level Duration Curves (LDC) quantify inundation characteristics and long-term water level changes in riparian wetlands. • LDC analyzes water level fluctuations over time by calculating exceedance probability, based on water level data. • Vegetation zones are classified by plant species' tolerance to inundation, revealing their distribution relative to flow patterns. [ABSTRACT FROM AUTHOR]

Background: Mesoamerica is one of the most important biodiversity hotspots on the planet. Despite significant efforts made over two centuries to contribute to the floristic knowledge of this region, our understanding of its flora is still scattered and uneven. Questions: What is the magnitude of the vascular plant species richness in the Usumacinta River Basin? Study site and dates: Usumacinta River Basin (Guatemala and Mexico), 1838-2018. Methods: We compiled the checklist by systematizing the floristic information acquired from various sources derived from numerous floristic and ecological studies. Results: We recorded 6,977 species, 1,892 genera and 274 families. The largest numbers of species (5,746) and records (58,859) correspond to the Mexican portion of the Usumacinta River Basin, compared to its Guatemalan counterpart (4,445 species and 19,952 records). The most species-rich families were Orchidaceae (598 species), Fabaceae (512), and Asteraceae (476). The prevalence of these and all other families with significant contributions to the flora varied among three elevation-defined sectors into which the Usumacinta River Basin was subdivided (lower, middle, and upper basin). Conclusions: The Usumacinta River Basin is a strategic region for plant biodiversity conservation as it hosts almost one third of all vascular plant species known for Mesoamerica and ca. 6 % of the entire flora in the Americas. Further botanical exploration should focus on those areas of the basin for which little or no information is available in order to gain a better appreciation of its flora.

Different perspectives use of machine learning (ML) algorithms have proven their performance depends on the quality of reference data. This is particularly true when targets are complex environments, such as wetlands, on which a vast majority of studies are site-specific and based on a single date. With this work, an extensive reference dataset of about 400,000 samples was collected, covering nine different sites and multiple seasons, to be considered representative of temperate wetland vegetation communities at continental scale. Starting from this dataset, the performance of selected ML classifiers was compared for detailed wetland vegetation type mapping, using spectral indices (SI) derived from multi-temporal composites of Sentinel-2 as input. Global and per-class accuracy metrics were computed based on four independent training and testing subsets, extracted from the overall dataset, and the impacts of input features variation in number and sites covered were assessed. Our results show a generally higher predictive power for ensemble methods, such as Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), compared to standalone ones, with the notable exception of Support Vector Machine (SVM); the latter in fact, in the algorithm that scored the highest overall accuracy (0.977 ± 0.001) and F-score for all the target classes. Decreasing the number of input features generally resulted in classification accuracy losses, less marked for RF than for SVM, while site-specific algorithms training showed more stability of SVM, thus indicating SVM stronger transferability than RF and XGBoost.

The classification of wetland plants using unmanned aerial vehicle (UAV) and satellite synergies has received increasing attention in recent years. In this study, UAV-derived training and validation data and WorldView-3 satellite imagery are integrated in the classification of five dominant wetland plants in the Old Woman Creek (OWC) estuary, USA. Several classifiers are explored: (1) pixel-based methods: maximum likelihood (ML), support vector machine (SVM), and neural network (NN), and (2) object-based methods: Naïve Bayes (NB), support vector machine (SVM), and k-nearest neighbors (k-NN). The study evaluates the performance of the classifiers for different image feature combinations such as single bands, vegetation indices, principal components (PCs), and texture information. The results showed that all classifiers reached high overall accuracy (>85%). Pixel-based SVM and object-based NB exhibited the best performance with overall accuracies of 93.76% and 93.30%, respectively. Insignificantly lower overall accuracy was achieved with ML (92.29), followed by NN (90.95) and object-oriented SVM (90.61). The k-NN method showed the lowest (but still high) accuracy of 86.74%. All classifiers except for the pixel-based SVM required additional input features. The pixel-based SVM achieved low errors of commission and omission, and unlike the other classifiers, exhibited low variability and low sensitivity to additional image features. Our study shows the efficacy of combining very high spatial resolution UAV-derived information and the super spectral observation capabilities of WorldView-3 in machine learning for mapping wetland vegetation. [ABSTRACT FROM AUTHOR]

Loss of Great Lakes wetlands due to changes in land use, hydrology, nutrient inputs, and invasive species led to the need for studies involving physical factors that influence growth of invasive cattails (Typha). Thus, in 18 Lake Ontario coastal wetlands, we sampled vegetation along stratified random transects and collected water samples for total phosphorus (TP) analyses. We used GIS to determine watershed area, percent land use as croplands, and length of lotic surface waters entering wetlands. A greenhouse growth experiment with a full factorial random block design was used to investigate the effects of variable hydroperiod and phosphorus concentrations on T. × glauca biomass changes. Correlation analyses of wetland data revealed that TP in field studies was related to percent croplands but not lotic length; mean percent Typha was not related to TP. In the growth experiment, above- and below-ground biomass increased significantly for simple main effects of hydroperiod and phosphorus concentrations. Multiple pairwise interaction comparisons between hydrology and nutrient treatments showed that effects of phosphorus concentration were present only at longer hydroperiods. Lack of correlation between Typha and phosphorus concentrations in the field was likely due to the overwhelming effect of water-level regulation on Lake Ontario. The greenhouse study demonstrated that increasing concentrations of phosphorus positively influenced cattail growth in a controlled setting. Although phosphorus positively influenced growth, hydrologic regime had the greatest influence on cattail growth, with increased biomass as hydroperiod increased. More natural hydrology and management of phosphorus inputs may help limit spread of Typha. [ABSTRACT FROM AUTHOR]

Forested vernal pools serve an integral role in the recruitment of amphibians in glaciated northeastern North America. In south-central Ontario, vernal pools exist in relatively unimpacted forest networks, but the amphibian communities face uncertain challenges from anthropogenic-induced climate change. We surveyed amphibian larvae and collected measurements of habitat characteristics from vernal pools to collect baseline information on amphibian community structure and species–habitat relationships. Amphibian communities were influenced by hydroperiod length and canopy openness, and the relative abundances of early breeding amphibians were affected by changes in the structure of vegetation communities within pools. Our study suggests that, even across moderate ranges of breeding habitat characteristics, the structure of amphibian communities is dynamic. With anthropogenic-induced climate change leading to more drought-prone summers, the conservation of intact forests that support diverse wetland assemblages will be a necessary component of future legislation.

Treatment wetlands have emerged as a potential option for the treatment of oil sands process-affected water (OSPW). The long-term viability of these treatment systems relies, in part, on the health and productivity of wetland vegetation. The aim of this study is to investigate the physiological and community-level effects on wetland vegetation at the Kearl Treatment Wetland (KTW) following exposure to different OSPW sources. Annual vegetation assessments were performed during 2016–2021 to monitor species composition, total percent cover, species richness, species morphology (plant stem density, leaf length, and leaf width), and plant vigor in the KTW. Cattail was found to dominate the deep-water zones whereas water sedge was found to dominate the shallow-water zones of the wetland. Species richness in the KTW decreased with time which is typical of constructed wetlands receiving industrial effluents. No changes in plant stem density of cattails or water sedge were observed; however, leaf length decreased from 2019 to 2021, and leaf width decreased from 2020 to 2021. Plant vigor ratings increased in the KTW each year suggesting that the vegetation does not show any major signs of phytotoxicity from OSPW exposure. These results demonstrate the complex dynamics and resiliency of the vegetative community in treatment wetlands, but continued efforts to monitor plant uptake and accumulation are needed to fully assess the phytotoxic effects of OSPW exposure. [ABSTRACT FROM AUTHOR]

Numerous wetland depressions occur across the U.S. Atlantic Coastal Plain, a region of complex physiography spanning a landward-to-seaward elevation gradient. Coastal Plain depressional wetlands are noted for supporting a diversity of plant communities that provide important faunal habitats. Because these "isolated" wetlands are vulnerable to degradation and loss on private lands, protected and managed public lands have become important refugia for their conservation. A practical system of vegetation types and vegetation-dynamics models can aid in developing management or restoration strategies for these conserved wetlands. The concept of hydrogeologic landscapes provides a useful model framework because landform, soils, and topographic position can influence not only depression form and hydropattern, but also ecological drivers of vegetation change such as drought, fire, and land-use. In the Lower Coastal Plain of South Carolina, USA, a hydrogeologic-landscapes approach was used to examine relationships between wetland vegetation and depression attributes such as size, soil type, and hydroperiod. The Lower Coastal Plain data were also combined with a similar Upper Coastal Plain study to provide a synthetic analysis of region-wide patterns. These studies identified a consistent set of wetland vegetation types that differed in landscape-associated depression attributes. Wetland types also differed in occurrence across sub-regions, owing in part to contrasting histories of land-use and wetland disturbance. The findings were used to develop conceptual state-change models that link wetland vegetation to depression hydropatterns and other ecological drivers in different landscape settings. [ABSTRACT FROM AUTHOR]

Phragmites australis (common reed) is a widely distributed emergent aquatic vegetation species in many wetland ecosystems, and its aboveground biomass (AGB) is an important parameter for evaluating the carbon–nitrogen cycle in wetlands. Satellite remote sensing (RS) is a powerful tool used to monitor the spatio-temporal distribution of AGB within reedbeds over a large area. However, when building AGB models based on satellite data, especially medium resolution satellites, it is difficult to obtain ample and properly measured AGB samples which can be matched with image pixels due to the inaccessibility of the wetlands. In this study, we proposed a solution based on the unmanned aerial vehicle (UAV) and Sentinel-2 data, which allowed us to estimate and successfully map the AGB of Phragmites australis in the Nan Da Gang Wetland Reserve (NDG) in China’s Hebei Province close to the Bohai sea. First, in an experimental area (EA) of NDG, an AGB model (R2 = 0.74, RMSE = 174 g/m2) was built based on NDVI(534, 734) and canopy height derived from UAV data, and an AGB map was obtained of the EA. Second, the AGB map was resampled to the pixel of the Sentinel-2 image, and an AGB sample set was matched with the acquired spatial resolution of the Sentinel-2 image. Finally, based on the sample set, an AGB model (R2 = 0.59, RMSE = 194 g/m2) was built using RVI derived from the Sentinel-2 image, which allowed us to map the Phragmites australis AGB in the NDG wetland reedbed. The study illustrated well that a UAV can be proficient in obtaining enough AGB samples matched with satellite pixels to build satellite-based AGB estimation models.

Wetland vegetation dynamics are of vital importance for comprehending changes in ecosystem structure and function. In the context of global climate change, it is still unclear the change in trends occurring to wetland vegetation in China. Using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index product (NDVI3g), National Oceanic and Atmospheric Association (NOAA) Vegetation Health Products (VHP), and climate data, this study explored the response of wetland vegetation NDVI to climate change in China from 1981 to 2015. The results show that: 1) NDVI of wetland vegetation in China exhibited a downward trend on the whole after the year 2004. 2) In water-limited zones, wetland vegetation NDVI was positively correlated with precipitation; while in temperature-limited zones, it was positively correlated with temperature. We also discussed the impact of climate change to wetland vegetation and the complexity of wetland vegetation response to climate change. This study has the potential to provide guidance and support decision-making for the protection, assessment, restoration and management of wetlands. [ABSTRACT FROM AUTHOR]

Biodiversity is in global decline during the Anthropocene. Declines have been caused by multiple factors, such as habitat removal, invasive species, and disease, which are often targets for conservation management. However, conservation interventions are under threat from climate change induced weather extremes. Weather extremes are becoming more frequent and devastating and an example of this was the 2019/2020 Australian drought and mega-fires. We provide a case study the impacts of these extreme weather events had on a population of the threatened frog Litoria aurea that occurs in a constructed habitat which was designed to reduce the impact of introduced fish and chytrid-induced disease. We aimed to determine what factors influenced persistence so that the design of wetlands can be further optimised to future-proof threatened amphibians. We achieved this with 4 years (2016–2020) of intensive capture–recapture surveys during austral spring and summer across nine wetlands (n = 94 repeat surveys). As hypothesized, drought caused a sharp reduction in population size, but persistence was achieved. The most parsimonious predictor of survival was an interaction between maximum air temperature and rainfall, indicating that weather extremes likely caused the decline. Survival was positively correlated with wetland vegetation coverage, positing this is an important feature to target to enhance resilience in wetland restoration programs. Additionally, the benefits obtained from measures to reduce chytrid prevalence were not compromised during drought, as there was a positive correlation between salinity and survival. We emphasize that many species may not be able to persist under worse extreme weather scenarios. Despite the potential for habitat augmentation to buffer effects of extreme weather, global action on climate change is needed to reduce extinction risk. [ABSTRACT FROM AUTHOR]

Typha shuttleworthii (Shuttleworth’s bulrush) is a rare species throughout its distribution range including Carpathians. However, a substantial increase in its finds has been noticed in the last twenty years. This study summarises the present knowledge and brings new data on vegetation with T. shuttleworthii occurrence from the western part of the Carpathians (Czech Republic, Slovakia, Poland and Ukraine) with the aims of evaluating the phytosociological affinity of this species and providing new information about the ecology of the relevant plant communities. We found that T. shuttleworthii mainly occurred in marsh vegetation (the Phragmito-Magnocaricetea class) including the Typhetum shuttleworthii association. Some plots also corresponded to transitional stands between marshes and wet meadows of the Molinio-Arrhenatheretea class (Molinietalia caeruleae order). Moisture and soil reaction were identified as principal factors responsible for variation in species composition of the vegetation. Typhetum shuttleworthii was recognised as new for the territory of Slovakia and confirmed in all other countries, Czech Republic, Poland and Ukraine. Our results could contribute to better preservation of the species and its habitats and thus be very important for practical nature conservation.

Delayed seasonal wetland drawdown is being investigated as one means of improving the scheduling of saline drainage discharge to the San Joaquin River, California, as an application of the principal of basin-scale real-time salinity management. A hybrid rapid vegetation assessment methodology was derived from the California Native Plant Society Rapid Assessment Protocol for classifying the vegetation in these seasonal wetlands. A hybrid remote sensing methodology combining pixel- and object-based components was developed to apply this classification strategy to a 160 km2 region. Twenty-six different plant communities were represented in a total of 20 land cover classes. An overall mapping accuracy ranges from 60% for identification of all 26 plant communities to 100% for identification of a single plant species. Low representation of certain associations for sensor calibration resulted in lower than anticipated mapping success as measured by errors of omission and commission. This image processing methodology provides an important tool, in concert with soil salinity mapping and wetland biology surveys, to assess the long-term impact of adaptive management strategies such as real-time salinity management on the wetland resource.

Wetlands are hotspots for various biogeochemical processes, including denitrification. Despite its ecological and economic importance, denitrification has proven difficult to measure. Plant community composition, water chemistry, and physical habitat characteristics are all known to play roles in regulating denitrification rates in wetlands. By investigating these relationships, we sought to not only better understand the factors related to denitrification within wetlands, but to build a predictive model capable of estimating the denitrification potential of those wetlands in a more accessible and efficient manner. To accomplish this, we combined a survey of 27 inland marshes throughout Michigan’s Lower Peninsula with a genetic analysis of denitrification potential within their soils. We found that denitrification, and the spatial variation therein, did not vary significantly between vegetation types at either the individual replicate or site levels. Dissolved oxygen and specific conductance were strong predictors of denitrification potential at all levels of analysis, while correlations with plant community composition varied amongst vegetation types. Spatial variation in denitrification potential, both vertically through the soil column and horizontally across the marshes, was most strongly correlated with plant community composition. Lastly, the metric-based predictive model constructed from these relationships was found to be highly predictive of denitrification potential. This model represents both a more accessible method for estimating denitrification in wetlands, and a framework for building similar models in other wetland systems.

• The Dajiuhu peatland contributed to mitigating global warming in both the short and long term. • Different regulatory pathways of environmental factors on carbon fluxes in the growing and non-growing season. • Vascular plants could play a crucial role in the regulation of carbon fluxes. Peatlands present substantial terrestrial carbon reservoirs actively engaged in land-atmosphere carbon exchanges. Ongoing variations in carbon dynamics, attributed to global climate change, underscore the necessity of elucidating the connections between carbon fluxes and meteorological parameters. Limited studies have delved into disparities in carbon fluxes and the mechanisms mediating them during growing and non-growing seasons on a long-term scale, particularly in subtropical peatlands. Consequently, this study utilized the eddy covariance technique in the Dajiuhu peatland to investigate five-year CH 4 and CO 2 fluxes, longside meteorological characteristics. The Dajiuhu peatland functioned as a CO 2 sink and CH 4 source, ultimately serving as a carbon sink. A substantial portion of the annual fluxes was measured during the non-growing season, with elevated CO 2 uptake and CH 4 emission during the growing season. Further analyses revealed that photosynthetically active radiation (PAR), soil temperature (Ts), air temperature (Ta), and soil water content (SWC) were critical environmental parameters influencing fluctuations in CO 2 and CH 4 fluxes. Two distinct controlling pathways for CO 2 fluxes were identified. In the growing season, PAR emerged as the most influential factor in CO 2 flux variations, and increasing Ts weakened CO 2 absorption by decreasing SWC. During the non-growing season, Ts emerged as the most influential factor in CO 2 exchanges, with lower Ts leading to decreased CO 2 uptake. Additionally, CH 4 flux variations were significantly regulated by PAR and Ts in both periods. The results illustrated that vascular plants played a pivotal role in the dynamics of carbon between peatlands and the atmosphere. Furthermore, it was discovered that the Dajiuhu peatland contributed to mitigating global warming in both the short and long term, with SGWP identified as a more reliable evaluation index. Our findings underscore the essential ecological function of the Dajiuhu subtropical peatland and provide a theoretical foundation for scientifically managing carbon in natural subtropical peatlands. [ABSTRACT FROM AUTHOR]

Water deficiency threatens the health and function of wetlands in semi-arid areas. Optimum re-watering is an effective method for close-to-natural restoration to mitigate wetland degradation. Although the ecological importance of optimal re-watering as a nature-based solution for promoting wetland plant growth has been widely recognized, the response mechanisms of seed germination and seedling growth to re-watering are still poorly understood despite their decisive impact on plant life history. To fill this gap, this study compared the characteristics of seed germination and seedling growth in Carex schmidtii under initial water content with three levels (30%, 50%, and 70%) and five re-watering treatments (maintained at constant water content and re-watering to 100% on 7th, 14th, 21st, and 28th day). Moreover, the degree of reserve mobilization during four germination stages (seed suckering, sprouting, 20% germination, and seedling growth) was investigated. The results showed that water deficiency and re-watering treatments significantly affected C. schmidtii seed germination, seedling growth, and reserve mobilization. Compared with the other treatments, 50% moisture content and re-watering to 100% on the 14th day (50%-RT3) treatment significantly improved germination traits (germination rate, daily germination rate, germination index, and vigor index) and seedling growth characteristics (shoot length, root length, shoot biomass, root biomass, and total biomass). Furthermore, the degree of mobilization of starch, soluble protein, fat, and soluble sugar accumulation in C. schmidtii seeds under 50%-RT3 was higher than that in the other treatments. The structural equation model showed that the characteristics of seed germination and seedling growth of C. schmidtii were directly related to water deficiency and re-watering treatments, whereas reserve mobilization indirectly affected seed germination and seedling growth. These findings demonstrated that water deficiency and re-watering treatments have a crucial regulatory effect on seed germination and seedling growth of wetland plant species through a dual mechanism. This study provides information for the formulation of an optimum re-watering strategy for wetland vegetation restoration in semi-arid areas of the world. • Re-watering solution affected seed germination and seedling growth of Carex schmidtii. • Re-watering solution regulated the process of reserve mobilization of C. schmidtii. • Re-watering solution controls the seed development through a dual mechanism. • 50% moisture content and re-watering on the 14th day as the optimum solution. [ABSTRACT FROM AUTHOR]

A phytosociological analysis of Tarsia Lake Regional Nature Reserve was carried out within a research project dealing with the vegetation of southern Italian wetlands. Twenty-four plant communities (19 associations and five communities not yet assigned to formal rank) were attributed to 17 alliances, 14 orders, and 11 classes. Most associations resulted as common in the Mediterranean area; however, as a response to the peculiarity of the local climatic and edaphic factors, some phytocoenoses were found as typical throughout central Europe but not observed in southern Italy, yet. Currently, this area is preserving a considerably interesting flora and vegetation for both naturalistic and phytogeographic reasons. Therefore, an appropriate monitoring and protection plan is needed in order to counteract the ongoing severe anthropogenic pressure.

Although palustrine wetlands cover only about 6% of the earth's surface, they are among the most productive and socio-economically valuable ecosystems globally. However, these ecosystems are facing various threats. The current study uses literature and field observations to explore the montane palustrine wetlands of Lesotho, in terms of their distribution, coverage, vegetation, ecosystem services, status, major threats and conservation. The study found that despite occurring throughout the country, the highest density of the wetlands is associated with the central and eastern parts, and generally declines towards the south and west as the rainfall decreases and the altitude becomes lower. The wetlands are rich in plant diversity and deliver various ecosystem services, including water, livestock grazing, harvestable resources, carbon storage and crop cultivation. Therefore, these wetlands play an important role at the local, national and regional scales and form an important water resource for Lesotho, South Africa and Namibia. Despite their value, some of the wetlands have been lost and the condition of those remaining is declining, mainly due to anthropogenic factors. Nevertheless, various conservation and restoration activities have been implemented in an attempt to conserve and manage these ecosystems. Despite these efforts, wetland loss and degradation continue, to the detriment of wetland biodiversity and ecosystem service delivery. Thus, this study recommends the scaling-up of the conservation efforts, as well as mainstreaming wetland conservation and management, including emphasising the wise use of these systems. Emphasis should be placed on regulating livestock grazing and trampling, harvesting of natural resources, infrastructure development and cultivation in the wetlands. [ABSTRACT FROM AUTHOR]

Biological invasion by Spartina alterniflora is widespread in coastal wetlands in China, threatening native vegetation. Obtaining the distribution of native and invasive vegetation at the small community scale is important to understand the invasion mechanism of S. alterniflora and the protection of wetland ecosystems. Remote sensing images can quickly and effectively identify vegetation at a large scale, which can have a considerable influence on the protection of biological diversity. Although Landsat-like space borne sensors have been applied in the monitoring of invasive species in wetlands, their spatial resolutions are often coarser than those of small communities of invasive species. To identify small-scale native (Phragmites australis and Scirpus mariqueter) and invasive (S. alterniflora) vegetation communities around Chongming Island in eastern China, we first investigated the performance of four classifiers based on spectral features. Then, textural features of Gaofen-1 images under an appropriate textural window size were added. Furthermore, a comprehensive classification (CC) method generated by multiple classification features was proposed to obtain a reliable classification, and CC was further improved by considering the properties of neighbouring pixels. The results demonstrated that (i) the random forest (RF) classifier reached a higher overall accuracy (OA) than all the other classifiers; (ii) adding textural features slightly increased the OA, but the production accuracy (PA) for P. australis and the user accuracy (UA) for S. alterniflora decreased; (iii) the CC method improved OA by up to 4.12 %, and accounting for the neighbouring pixels improved the OA to 93.96 %. The comprehensive method effectively improved not only OA but also PA and UA for the vegetation communities, and it can be used in other wetlands. [ABSTRACT FROM AUTHOR]

A chronosequence of wetland swales between beach ridges in the Manistique/Thompson embayments of Lake Michigan contains plant communities that differ across the strandplain. We characterized vegetation in 33 swales and compared distribution with previously reported groundwater flow systems. Older swales near a groundwater divide created by the peak Nipissing ridge receive local flows and hold sedge/leatherleaf floating mats that transition to swamp. Farther lakeward, another groundwater divide is created by discharge of calcareous waters released by termination of an underlying clay confining layer, resulting in swales dominated by northern white cedar. Cedar swamp continues lakeward in swales having flow-through calcareous groundwater, but several swales are perched above those flows. Farther lakeward, a large amalgamated beach ridge creates another groundwater divide with discharges that again support cedar swamp. Calcareous discharge from the confined aquifer, with downslope flow-through waters, then supports more cedar swamp. Flow-through waters meet yet another calcareous discharge, resulting in ponding and development of floating mats. Finally, a deep regional aquifer discharges at the Lake Michigan shore and supports marsh/shoreline species. Our results have implications for assessing potential responses to climate change, interpretation of past climate changes in paleoecological studies, and management of wetlands facing future climate changes. [ABSTRACT FROM AUTHOR]

The dynamic monitoring and analysis of wetland vegetation play important roles in revealing the change, restoration and reconstruction of the ecosystem environment. The increasing availability of high spatial-temporal resolution remote sensing data provides an unprecedented opportunity for wetland dynamic monitoring and change detection. Using the reconstructed dense monthly Landsat time series, this study focuses on the continuous monitoring of vegetation dynamics in Dongting Lake wetland, south China, in the last two decades (2000–2019) by using the Bayesian estimator of abrupt change, seasonal change, and trend (BEAST) method. Firstly, the flexible spatiotemporal data fusion (FSDAF) model is applied to blend Landsat and moderate-resolution imaging spectroradiometer (MODIS) images on the basis of the input image pair selection strategy named "cross-fusion" to generate the monthly time-series normalized difference vegetation index (NDVI) with the spatial resolution of 30 m. Then, the abrupt changes, trend, and seasonality of the vegetation in the study area as well as the uncertainties of change detection are estimated by the BEAST method. Results show that there is a close relationship between the ground true data and the estimated changepoints. A high overall accuracy (OA) of 87.37% and Kappa coefficient of 0.85 were achieved by the proposed framework. Additionally, the temporal validation got the interval intersection of 86.57% and the absolute difference of mean interval length of 6.8 days. All of the results demonstrate that the vegetation changes in the Dongting Lake wetland varied spatially and temporally in the last two decades, because of extreme weathers and anthropogenic factors. The presented approach can accurately identify the vegetation changes and time of disturbance in both the spatial and temporal domains, and also can retrieve the evolution process of wetland vegetation under the influence of climate changes and human activities. Therefore, it can be used to reveal potential causes of the degradation and recovery of wetland vegetation in subtropical areas. [ABSTRACT FROM AUTHOR]

Typha shuttleworthii (Shuttleworth's bulrush) is a rare species throughout its distribution range including Carpathians. However, a substantial increase in its finds has been noticed in the last twenty years. This study summarises the present knowledge and brings new data on vegetation with T. shuttleworthii occurrence from the western part of the Carpathians (Czech Republic, Slovakia, Poland and Ukraine) with the aims of evaluating the phytosociological affinity of this species and providing new information about the ecology of the relevant plant communities. We found that T. shuttleworthii mainly occurred in marsh vegetation (the Phragmito-Magnocaricetea class) including the Typhetum shuttleworthii association. Some plots also corresponded to transitional stands between marshes and wet meadows of the Molinio-Arrhenatheretea class (Molinietalia caeruleae order). Moisture and soil reaction were identified as principal factors responsible for variation in species composition of the vegetation. Typhetum shuttleworthii was recognised as new for the territory of Slovakia and confirmed in all other countries, Czech Republic, Poland and Ukraine. Our results could contribute to better preservation of the species and its habitats and thus be very important for practical nature conservation. [ABSTRACT FROM AUTHOR]

Aims: To create a comprehensive, consistent and unequivocal phytosociological classification of European marsh vegetation of the class Phragmito‐Magnocaricetea. Location: Europe. Methods: We applied the Cocktail method to a European data set of 249,800 vegetation plots. We identified the main purposes and attributes on which to base the classification, defined assignment rules for vegetation plots, and prepared formal definitions for all the associations, alliances and orders of the class Phragmito‐Magnocaricetea using formal logic. Each formula consists of the combination of "functional species groups", cover values of individual species, and in the case of high‐rank syntaxa also of "discriminating species groups" created using the Group Improvement (GRIMP) method. Results: The European Phragmito‐Magnocaricetea vegetation was classified into 92 associations grouped in 11 alliances and six orders. New syntaxa (previously invalidly published according to the International Code of Phytosociological Nomenclature) were introduced: Bolboschoeno maritimi‐Schoenoplection tabernaemontani, Glycerio maximae‐Sietum latifolii, Glycerio notatae‐Veronicetum beccabungae, Schoenoplectetum corymbosi and Thelypterido palustris‐Caricetum elongatae. Based on a critical revision, some other syntaxa were rejected or excluded from the class Phragmito‐Magnocaricetea. Conclusions: This work provides the first consistent classification of the class Phragmito‐Magnocaricetea at the European scale, which is an important tool for nature conservation. Our classification largely respects previously existing concepts of syntaxa, but it also proposes modifications to the recently published EuroVegChecklist. This work also provides a protocol that can be used for extending the current classification to new syntaxa and geographical regions. [ABSTRACT FROM AUTHOR]

Background: Forested wetlands support distinct vegetation and hydrology relative to upland forests and shrub-dominated or open water wetlands. Although forested wetland plant communities comprise unique habitats, these ecosystems’ community structure is not well documented in the U.S. Pacific Northwest. Here I surveyed forested wetland vegetation to identify changes in community composition and structure across an elevation gradient that corresponds to flooding stress, asking: (1) How do forested wetland plant communities change across an elevation gradient that corresponds to flood frequency and duration? (2) At what relative elevations do different plant species occur within a wetland? Methods: I measured overstory tree basal area and structure and understory vascular plant composition in three zones: wetland buffers (WB) adjacent to the wetland, an upper wetland (UW) extent, and a lower wetland (LW) extent, surveying individual trees’ root collar elevation relative to the wetland ordinary high-water mark (OHWM). I estimated understory plant species abundance in sub-plots and surveyed these plots’ height above the OHWM. I used non-metric multidimensional scaling ordination to identify patterns in vegetation communities relative to wetland elevation, and tested for compositional differences between the WB, UW and LW zones using PERMANOVA. I calculated overstory and understory indicator species for each wetland zone using indicator species analysis. Results: Forest overstory composition changed across the elevation gradient, with broad-leaved trees occupying a distinct hydrologic niche in low-lying areas close to the OHWM. Conifer species occurred higher above the OHWM on drier microsites. Pseudotsuga menziesii (mean elevation = 0.881 m) and Tsuga heterophylla (mean elevation = 1.737 m) were overstory indicator species of the WB, while Fraxinus latifolia (mean elevation = 0.005 m) was an overstory indicator for the upper and lower wetland. Understory vegetation differed between zones and lower zones’ indicator species were generally hydrophytic species with adaptations that allow them to tolerate flooding stress at lower elevations. Average elevations above the OHWM are reported for 19 overstory trees and 61 understory plant species. By quantifying forested wetland plant species’ affinities for different habitats across an inundation gradient, this study illustrates how rarely flooded, forested WB vegetation differs from frequently flooded, LW vegetation. Because common management applications, like restoring forested wetlands and managing wetland responses to forest harvest, are both predicated upon understanding how vegetation relates to hydrology, these data on where different species might establish and persist along an inundation gradient may be useful in planning for anticipated forested wetland responses to restoration and disturbance. [ABSTRACT FROM AUTHOR]

Projected future global mean sea level rise is causing wetlands resource managers to begin looking at wetlands in a new light. This project hopes to answer some of those questions and to create discussion regarding the value of wetlands in California by examining the San Elijo Lagoon in San Diego County. There is still discussion regarding what models to use when examining future potential sea level rise. Discussion continues regarding how vegetative habitats will adjust to the physical changes that may be encountered as the rate of global mean sea level increases to due to anthropogenic global warming. A difficult question that all wetlands managers are dealing with is assessing the value of the habitat that they manage. This paper examines the issues regarding global mean sea level rise models and how to interpret them. GIS tools are presented for evaluating the areas of a wetland at greatest risk from simple inundation. Finally, this paper looks at the benefits associated with averting potential impacts from global mean sea level rise.

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.

Excavating agriculturally-accrued sediment from wetland basins is an increasingly common restoration technique worldwide, but the impacts on recruiting native plant communities are unknown. Multiple agencies developed a wetland monitoring protocol to document how restoring hydrology and removing excess sediment impacted hydrology and plant assemblages both before and up to 6 years after wetland restorations in North American prairie potholes. Our results indicated that the excavated basins had marginally greater probabilities of increased total standing water, habitat interspersion, and relative plant diversity, as well as lower probabilities of having invasive plants and hybrid cattails (Typha × glauca), when compared to unexcavated basins. By year 4, the excavated basins had 50% probability of extensive cattail invasion, whereas the unexcavated basins had 85% probability of cattails. However, the benefits from excavation were typically negated by invasive species and cattail encroachment within 3–6 years of post-restoration. Therefore, the vegetation communities may benefit from sediment excavations that are also coupled with targeted management within the first few years to combat invasion. This long-term monitoring program could be continued and revised to include post-restoration management activities (e.g., seeding, invasive species control techniques, and prescribed fire) using an adaptive management framework to provide prompt feedback to managers regarding the relative efficacy of alternative post-restoration management. [ABSTRACT FROM AUTHOR]

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