The wetland loss rate in Iran is faster than the global average. Comprehending the shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is essential for safeguarding their ecosystems' health and services. This study proposes a novel gray‐box modeling framework to quantify the effects of climate change and anthropogenic activities on the wetlands, by combining process‐based and machine learning models. The developed model is utilized to project the Anzali coastal wetland shrinkage by simulating the complex interaction between the meteorological, hydrological, anthropogenic and sea water level characteristics, and the changes in wetland water surface area. Our framework aggregates Soil and Water Assessment Tool model, the 12 General Circulation Models of the Coupled Model Intercomparison Project Phase 6, Landsat imagery, and the Long Short‐Term Memory model to project the shrinkage of the wetland till 2100. A comprehensive range of climate and Land Use/Cover change scenarios are analyzed. The results show that wetland will seasonally desiccate in 2058, mainly due to increasing air temperature, reduction in precipitation and inflow, excessive sediment loading to the wetland, and decline in the Caspian Sea level. For optimistic scenarios, where no changes in the Caspian Sea level is considered, the wetland will gradually diminish and become a seasonal waterbody by 2100. The outcomes of this study highlight that the Anzali wetland desiccation has profound implications for the regional‐scale ecological balance, ecosystem health and function, public health, and local economy. Robust environmental interventions and sustainable development strategies are urgently needed to mitigate the detrimental impacts of climate and anthropogenic drivers on the wetland.

Anzali Wetland Crisis: Unraveling the Decline of Iran's Ecological Gem

Distinctive zones of inundation water during floods were shown to originate from different sources in some major floodplains around the world. Recent research showed that the zonation of water in rivers and floodplains is related to vegetation patterns. In spite of this, water source zones were not used for vegetation modeling due to difficulties in their delineation. In this study, we used simulation results of a fully-coupled groundwater-surface water integrated hydrological model (IHM) HydroGeoSphere and the Hydraulic Mixing-Cell method to provide standard hydrological predictors (e.g. water depth, inundation length, groundwater depth, exchange flux) and the extent of inundation zones having a certain water source (discharged groundwater, river, rainfall, and snowmelt). These variables were used to train a vegetation model for the lower Biebrza floodplain (about 290 km2) using vegetation maps from 1960, 1980, and 2000. We used a one-at-a-time (OAT) approach, where each map was validated based on a model trained on the remaining two maps to obtain realistic error estimates. We also used a fractional approach in which a fraction of each map was used for training and validation. The single model from the fractional approach was used to assess the importance of predictors and to predict vegetation for the 20th century and for the 21st century using IHM simulation forced by the Twentieth Century Reanalysis data and EURO-CORDEX RCP 2.6, 4.5, and 8.5 model ensembles. The model which used both water sources extent and standard predictors performed the best overall and was sensitive to the future trends. The extent of river water within the inundation area was by far the most important vegetation predictor. The models that neither used the water sources extent predictors nor the exchange flux were not able to predict the trends of areas covered by certain vegetation types under future climate. The advantage of the water sources extent predictors was their ability to represent the spatial effect of local hydrological phenomena. This was not possible with the standard predictors, because they show only the source of the phenomena (e.g. groundwater discharge zone), but do not indicate the actual area affected by its physical and chemical properties, which is more relevant for vegetation development. Our results highlight the relevance of using water extent predictors due to their ability to explain spatiotemporal ecological processes, such as vegetation development. We suggest to use water extent predictors in modelling for developing more accurate decision support for wetland floodplains. 

Using water sources extent during inundation as a reliable predictor for vegetation zonation in a natural wetland floodplain

Abstract Wetlands of the Laurentian Great Lakes of North America (i.e., lakes Superior, Michigan, Huron, Erie, and Ontario) provide critical habitat for marsh birds. We used 11 years (2011–2021) of data collected by the Great Lakes Coastal Wetland Monitoring Program at 1,962 point-count locations in 792 wetlands to quantify the first-ever annual abundance indices and trends of 18 marsh-breeding bird species in coastal wetlands throughout the entire Great Lakes. Nine species (50%) increased by 8–37% per year across all of the Great Lakes combined, whereas none decreased. Twelve species (67%) increased by 5–50% per year in at least 1 of the 5 Great Lakes, whereas only 3 species (17%) decreased by 2–10% per year in at least 1 of the lakes. There were more positive trends among lakes and species (n = 34, 48%) than negative trends (n = 5, 7%). These large increases are welcomed because most of the species are of conservation concern in the Great Lakes. Trends were likely caused by long-term, cyclical fluctuations in Great Lakes water levels. Lake levels increased over most of the study, which inundated vegetation and increased open water-vegetation interspersion and open water extent, all of which are known to positively influence abundance of most of the increasing species and negatively influence abundance of all of the decreasing species. Coastal wetlands may be more important for marsh birds than once thought if they provide high-lake-level-induced population pulses for species of conservation concern. Coastal wetland protection and restoration are of utmost importance to safeguard this process. Future climate projections show increases in lake levels over the coming decades, which will cause “coastal squeeze” of many wetlands if they are unable to migrate landward fast enough to keep pace. If this happens, less habitat will be available to support periodic pulses in marsh bird abundance, which appear to be important for regional population dynamics. Actions that allow landward migration of coastal wetlands during increasing lake levels by removing or preventing barriers to movement, such as shoreline hardening, will be useful for maintaining marsh bird breeding habitat in the Great Lakes. 

Increasing marsh bird abundance in coastal wetlands of the Great Lakes, 2011–2021, likely caused by increasing water levels

Improving water level monitoring in small to medium-sized rivers: An enhanced footprint filter-based conditional threshold retracker approach

ABSTRACT Lakeshores are ecotones encompassing diverse habitats that support high biodiversity, interact with pelagic ecosystems, and provide desirable ecosystem services. Hydrological regimes altered by climate change significantly impact lakeshore ecosystems. In this opinion paper, we highlight ecological consequences of distinct multiannual hydrological regimes (superimposed on natural seasonal ones) that affect the lakeshore environment of stratified lakes. Under natural hydrological conditions (Regime A), lakes maintain a stable annual mean water level, supporting diverse biota adapted to the seasonal fluctuations of water level. By contrast, under multiannual drought, the annual mean water level continuously declines (Regime B), and the resulting exposed shores become covered with dense vegetation, dominated by a few species. As the waterline recedes, structural complexity in the shallow water is reduced, limiting populations of native invertebrates and fish and facilitating establishment of invasive species. Storm-induced rapid rises in annual mean water levels during extremely rainy years (Regime C) are the least studied. While lake refilling is intuitively beneficial, undesirable short-term effects are common, including organic matter accumulation and decomposition, temporary hypoxia, pungent odors, loss of fish habitat, and formation of mosquito-infested shore pools. Littoral zone recovery and alleviation of nuisances occur only after the extreme conditions subside. Under climate change, the frequency and intensity of Regimes B and C are likely to increase. From a management perspective, maintaining water levels close to natural amplitudes can minimize the adverse conditions and damage caused by Regimes B and C.

Opinion: multiannual water level regimes altered by climate change modify lakeshore structure and function

The influence of extreme water levels on coastal wetland extent across the Laurentian Great Lakes

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The influence of extreme water levels on coastal wetland extent across the Laurentian Great Lakes