Forecasting water-associated vegetation dynamics of a Ramsar wetland using multivariate and remote sensing approaches

The Ramsar Convention on Wetlands is an international framework through which countries identify and protect important wetlands. Yet Ramsar wetlands are under substantial anthropogenic pressure worldwide, and tracking ecological change relies on multitemporal data sets. Here, we evaluated the spatial extent, temporal change, and anthropogenic threat to Ramsar wetlands at a national scale across China to determine whether their management is currently sustainable. We analyzed Landsat data to examine wetland dynamics and anthropogenic threats at the 57 Ramsar wetlands in China between 1980 and 2018. Results reveal that Ramsar sites play important roles in preventing wetland loss compared to the dramatic decline of wetlands in the surrounding areas. However, there are declines in wetland area at 18 Ramsar sites. Among those, six lost a wetland area greater than 100 km 2 , primarily caused by agricultural activities. Consistent expansion of anthropogenic land covers occurred within 43 (75%) Ramsar sites, and anthropogenic threats from land cover change were particularly notable in eastern China. Aquaculture pond expansion and Spartina alterniflora invasion were prominent threats to coastal Ramsar wetlands. The observations within China’s Ramsar sites, which in management regulations have higher levels of protection than other wetlands, can help track progress towards achieving United Nations Sustainable Development Goals (SDGs). The study findings suggest that further and timely actions are required to control the loss and degradation of wetland ecosystems.

Nonlinear interactions between physical, chemical and biological factors determine the spatiotemporal extent of flooding, the level of salinisation and the vegetation dynamics in wetlands subjected to a certain climate signal.These interactions were studied using an ecohydrological model of a wetland in a semi-arid climate designed to account for the tolerance of vegetation functional groups to salinity and water availability.In particular, the model represents Melaleuca strobophylla and Casuarina obesa, as well as terrestrial short-rooted grasses, to represent those typically found in Lake Toolibin, a Ramsar appointed wetland of south-west Western Australian (SWWA).In a previous study, the model showed a good agreement when compared against available field data from Lake Toolibin.In this study, we explored specifically how variability in rainfall delivery can affect salt mobilization and subsequent vegetation abundance and assemblage.In order to test this, the model was tested under a range of rainfall intra-annual distribution with the same annual depth.Being particularly interested in semi-arid regions, the rainfall realisations were synthetically generated by a model previously calibrated to represent the precipitation typical of SWWA.The model demonstrated the co-evolution between hydrology and vegetation, as well as the non-linear responses of vegetation dynamics to climate forcing, both being strongly influenced by salinisation.A higher rainfall intensity enhanced runoff, raised the water table level and decreased salt leaching, intensifying accumulation of salt in the root zone.This altered salt mobilization affected vegetation abundance, water uptake and significantly changed to the vegetation assemblage.The short-rooted, terrestrial-adapted C. obesa benefited from a rainfall signal that was more evenly distributed over the year, while M. strobophylla benefited from more intense rainfall events that cause water to pond for prolonged periods.This exercise highlighted the fact that salinity amplifies the impact of climate variability, significantly affecting both the overall vegetation density and assemblage.This fact reinforces the need to include salinisation processes within ecohydrological models used to study vegetation dynamics in semi-arid regions.

Understanding the impact of anthropogenic climate variability on the surface inundation dynamics in the wetlands of drylands:  A case study of Ile-Balkhash Delta, Kazakhstan.Kanchan Mishra1*, Philip Weber1, Kathryn E. Fitzsimmons21Department of Geosciences, University of Tübingen, Schnarrenbergstrasse 94-96, 72076 Tübingen, Germany.2School of Earth Atmosphere and Environment, Monash University, Clayton VIC, Australia(*Email: kanchan.mishra@uni-tuebingen.de)The Ile-Balkhash Delta, a Ramsar wetland of international importance in southeastern Kazakhstan, is one of the largest deltas in arid Central Asia (ACA). Like other waterbodies in dryland regions, the Ile-Balkhash delta faces degradation and desertification driven by anthropogenic climate change and human-induced alterations. These changes disrupt the structure, function, and distribution of wetlands, resulting in ecological and socio-economic impacts, including habitat loss, declining water quality and quantity, and reduced carbon sequestration. Despite their sensitivity to environmental changes, the surface water dynamics of these wetlands remain poorly understood in arid settings.This study aims to assess the seasonal surface inundation patterns (SIP) and their spatio-temporal dynamics in the Ile-Balkhash Delta from 1992 to 2024 using remote sensing, GIS, and logistic regression analysis. Climatic and anthropogenic drivers of wetland dynamics are identified, while a new classification algorithm quantifies degradation patterns and transitions under the current regulated hydrological regime, offering insights into physical processes and conservation strategies.The study reveals a strong seasonal variability, with persistent water coverage peaking in spring (15.4%) and declining in summer (10.4%), reflecting substantial reductions during drier months. Interannual variability shows peaks in wetland areas during years such as 2000, 2004, 2010, 2016, and 2018, likely linked to upstream discharge and snowmelt. However, a marked decline in coverage post-2018 suggests potential shifts in the hydrological conditions of the wetlands. The analysis further highlights that upstream inflows and hydrological connectivity exert a stronger influence on wetland dynamics than localized rainfall and temperature, which primarily regulate evaporation rates. Across the entire delta (27,791 km²), total lost (231.95 km²) and gained (246.04 km²) areas are nearly balanced. However, persistent water remains limited (617.28 km², 10.6%), while seasonal and temporary water has expanded, emphasizing the dominance of temporary water areas. Regionally, the coastal region (SR-1, 2,750 km²) shows a net increase in inundation, with gains (117.84 km²) far exceeding losses (7.99 km²), resulting in dynamic seasonal water coverage. In contrast, the main Central Ile River Delta (SR-2, 5,357 km²) shows a net areal decline, with losses (127.35 km²) surpassing gains (40.70 km²), despite heightened seasonal fluctuations. Similarly, the southern arid inland regions (SR-3, 1,039 km²) exhibit modest gains (11.64 km²) dominated by larger losses (37.46 km²), indicating a shift toward ephemeral water occurrences. The findings highlight the complex and dynamic nature of water variability in the Ile-Balkhash Delta, emphasizing the need for integrated water management strategies to address ongoing hydrological changes and support wetland conservation under evolving climate and human pressures. 

The Macquarie Marshes is a freshwater wetland system located in semiarid Australia. The ecological importance of this site has been recognized under the Ramsar convention. Plant associations in the marshes has shown a complex dynamic where some wetland vegetation patches have transitioned to terrestrial vegetation during severe drought, but also quickly responded to increased inflows due to record and near record rainfall accompanied by water releases from an upstream reservoir. Management decisions regarding the environmental flows require the use of predictive tools in order to assess the response of the vegetation. We have developed a vegetation response model that couples hydrodynamic modelling of the northern Macquarie Marshes with watering requirements of different plant associations and vegetation succession rules. The model simulates floods in the wetland during a series of years, after which patches of vegetation are analysed according to water depth, percent exceedance time and frequencies of inundation. During the simulated period, the patch can have adequate watering conditions, or it can have critical conditions that would lead to a succession to another type of vegetation. The predicted vegetation is reintroduced in the model, providing feedbacks for the next simulation period. In this contribution, we implemented the model to simulate changes of wetland understory during the period 1991 to 2014.

In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China’s second largest freshwater lake in the middle reaches of the Yangtze River—the Dongting Lake—and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA’s Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake’s wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km2, indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km2. Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km2, which is consistent with the Global WaterPack, deviating by only 4%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.

Water depth and flow effects on growth and nutrient content of three marsh plants (Cladium jamaicense Crantz, Eleocharis cellulosa Torr., and Nymphaea odorata Aiton) and on soil-building were estimated in the Loxahatchee Impoundment Landscape Assessment where macrocosms contain habitats distinguished by relative water depth (deep slough, shallow slough, and mid-ridge) but that differ in flow. We hypothesized that optimal growth would vary with water depth and species, paralleling distributions in the natural environment, and that growth and tissue nutrients would be positively affected by flow. In addition, we hypothesized that plant morphology would influence sediment deposition with the dense growth of C. jamaicense supporting greatest accretion. Our hypotheses were partly supported. Cladium jamaicense unexpectedly grew best in deep sloughs at depths greater than previously reported. Eleocharis cellulosa had a wide depth tolerance and grew best in flowing conditions. Nymphaea odorata grew best in slough habitats. Nutrient contents differed among species and plant parts but were not affected by flow. Soil accretion did not vary with biomass but partially varied with depth and flow, both key factors in conceptual models of vegetation and soil dynamics in wetlands, especially in the Everglades ridge-and-slough topography.

Reference wetlands play an important role in efforts to protect wetlands and assess wetland condition. Because wetland vegetation integrates the influence of many ecological factors, a useful reference system would identify natural vegetation types and include models relating vegetation to important regional geomorphic, hydrologic, and geochemical properties. Across the U.S. Atlantic Coastal Plain, depression wetlands are a major hydrogeomorphic class with diverse characteristics. For 57 functional depression wetlands in the Upper Coastal Plain of South Carolina, we characterized the principal vegetation types and used a landscape framework to assess how local (wetland-level) factors and regional landscape settings potentially influence vegetation composition and dynamics. Wetland sites were stratified across three Upper Coastal Plain landscape settings that differ in soils, surface geology, topography, and land use. We sampled plant composition, measured relevant local variables, and analyzed historical transitions in vegetative cover types. Cluster analysis identified six vegetation types, ranging from open-water ponds and emergent marshes to closed forests. Significant vegetation-environment relationships suggested environmental “templates” for plant community development. Of all local factors examined, wetland hydrologic regime was most strongly correlated with vegetation type, but depression size, soil textural type, and disturbance history were also significant. Because hydrogeologic settings influence wetland features, local factors important to vegetation were partly predictable from landscape setting, and thus wetland types were distributed non-randomly across landscape settings. Analysis of long-term vegetation change indicated relative stability in some wetlands and succession in others. We developed a landscape-contingent model for vegetation dynamics, with hydroperiod and fire as major driving variables. The wetland classification, environmental templates, and dynamics model provide a reference framework to guide conservation priorities and suggest possible outcomes of restoration or management.

Using cloud computing techniques to monitor long-term variations in ecohydrological dynamics of small seasonally-flooded wetlands in semi-arid South Africa

Wetlands are acknowledged as important resources for carbon storage, yet their capacity to facilitate longterm carbon storage is extremely susceptible to human influence. Here, we evaluate the impacts of various management regimes on carbon retention at the Burgas lake RAMSAR site, Bulgaria - a wetland of international importance that also supports rich biodiversity. We conducted field soil analyses and satellite observations to assess unmanaged, occasionally mown, regularly managed and polluted wetland areas. Soil samples collected in July 2025, revealed clear contrasts: the unmanaged site contained the highest carbon and nitrogen levels, while mown and polluted sites showed reduced carbon retention and altered nutrient balances. Electrical conductivity was significantly elevated in the polluted zone, reflecting anthropogenic pressure. Remote sensing indicators, derived from Sentinel-2 (NDVI, NDRE, MSAI2, NBR, NDWI), showed vegetation productivity, chlorophyll content, soil background effects, moisture and structural disturbance. High positive correlations were noted as a result for the soil carbon, as an index with the vegetation indices and negative correlations with pH and moisture proxies. These results reveal how management and disturbance determine the carbon dynamics in wetlands, and show the benefit of combination of soil and remote sensing methods. The findings are the basis to guide research and implement evidence-based solutions for restoring and managing wetlands, and promoting the carbon sequestration ability of wetlands, without jeopardizing ecological soundness.

Climate change is projected to induce drought, resulting in the deterioration of avian food vegetation in large floodplain wetlands. The construction of water conservancy project may potentially alleviate this deterioration; however, the combined impact of climate change and water conservancy project regulation on avian food vegetation requires further investigation. In this study, a vegetation community model was developed by integrating a 2D hydrodynamic model and Cellular Automata to simulate the vegetation dynamics in floodplain wetlands. The developed model was applied in Poyang Lake, an important floodplain wetland conservation area in China under the Ramsar Convention, and the potential impact of the proposed Poyang Lake sluice on the deterioration of avian food vegetation caused by climate change was projected. We found that the avian food vegetation would continue to degrade under the influence of climate change, due to the enhanced drought conditions in the future. The extent of hygrophilous avian food vegetation experienced a significant reduction after the sluice operation, whereas the area of submerged avian food vegetation saw a notable increase. In the short term, the operation of the Poyang Lake sluice had a detrimental impact on avian food vegetation, which is primarily attributed to elevated water levels caused by sluice operation leading to submersion of hygrophilous avian food vegetation. Over time, however, the decrease in avian food vegetation caused by climate change will be mitigated by sluice operation, because the stabilized water levels and increased flooding time provide favorable conditions for the growth of submerged avian food vegetation.

Carbon sequestration and climate change in crops, natural vegetation, and wetland dynamics in the high Andes The Andes, one of the world's most extensive mountain ranges, stretches across a vast latitudinal range from tropical to subpolar regions along the western side of South America (Clapperton, 1993) . This extensive distribution gives rise to diverse ecosystems, including natural forests, shrublands, grasslands, and wetlands. Notably, at elevations beyond the upper limit of tree growth (i.e., treeline), high-altitude wetlands emerge as the most productive ecosystems in the Andes. They provide relevant natural contributions as freshwater for human settlements or livestock and constitute habitats for particular biodiversity in contrast with other regional Andean landscapes. In addition, high-Andean wetlands are important in climate and biogeochemical cycles regulation (Mitsch and Gosselink, 2015) . Climate change is already impacting ecosystems worldwide, and it is expected to continue or accelerate its impact in the future, representing a major threat to high mountain ecosystems worldwide (Pauli and Halloy, 2019; Cuesta et al., 2023) . Andean wetland ecosystem dynamics are mainly regulated by temperature and precipitation, a factor that places them among the most sensitive and vulnerable ecosystems facing global climate change (Dangles et al., 2017; Cuesta et al., 2019) . Moreover, they store considerable amounts of carbon, acting as important global sinks (Hribljan et al., 2016; Alavi-Murillo et al., 2022) . Carbon storage in soil and plants growing in these environments play a fundamental role to mitigate global warming, reducing emissions of CO 2 into the atmosphere (Mitsch et al., 2013; Hribljan et al., 2017) .

Abstract. Simulations of the spatiotemporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate. Hydrologic inundation models, such as the TOPography-based hydrological model (TOPMODEL), are based on a fundamental parameter known as the compound topographic index (CTI) and offer a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains a large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl (Lund–Potsdam–Jena Wald Schnee und Landschaft version) Dynamic Global Vegetation Model (DGVM) and quantifies uncertainties by comparing three digital elevation model (DEM) products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland data set can help to successfully delineate the seasonal and interannual variation of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows the best accuracy for capturing the spatiotemporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of ∼ 5.17 Mkm2 for 1980–2010. When integrated with wetland methane emission submodule, the uncertainty of global annual CH4 emissions from topography inputs is estimated to be 29.0 Tg yr−1. This study demonstrates the feasibility of TOPMODEL to capture spatial heterogeneity of inundation at a large scale and highlights the significance of correcting maximum wetland extent to improve modeling of interannual variations in wetland area. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.

The interaction between plant growth and nutrient availability is an important aspect of vegetation dynamics in wetlands. In this study, seedlings of Typha domingensis were used to assay the nutrient availability of fire-disturbed Florida Everglades soils. Seedlings were planted in soils that had been naturally muck- (MB), surface- (SB), or non-burned (NB) and that showed significant differences in concentrations of inorganic: total phosphorus according to fire severity. After two months of growth, plant height, number of leaves, culm diameter, number of rhizomes, length of rhizomes, live leaf biomass, and above-and below-ground biomass were greatest in MB seedlings. In addition, root architecture and biomass allocation were influenced by soil type. Seedlings from NB and SB soils developed thinner roots with numerous root hairs and had higher percentages of below-ground biomass. In contrast, seedlings grown in muck-burned soils developed large rhizomes in addition to thicker, hairless roots while allocating proportionally more biomass to aboveground parts. Tissue nutrient analyses showed that both experimental and field-harvested plants grown in MB soils contained significantly more phosphorus than plants from SB or NB soils. Typha domingensis has displaced plant communities in areas of the Everglades that receive nutrient-enriched agricultural runoff. However, this study suggests that establishment and expansion of this species also may occur in overdrained regions of the Everglades where muck fires are a frequent occurrence. In addition to creating an opening in the landscape, muck fires increase the bioavailability of soil phosphorus, thus providing a competitive advantage for T. domingensis.

Grass Vegetation Dynamics in Wetlands with Different Utilization

Grass Vegetation Dynamics in Wetlands with Different Utilization