Wetlands最新文献

Anthropogenic climate change significantly impacts ecosystem health, biodiversity, and the life cycle and distribution of aquatic macrophytes. Mexican aquatic habitats for macrophytes are particularly vulnerable, with their degradation posing severe ecological risks for freshwater, wetland, and terrestrial ecosystems. This study analyzed the current and future distributions of Sagittaria latifolia and S. macrophylla, two crucial aquatic plant species in Mexico. Species distribution models (SDM) were used, incorporating bioclimatic and topographic variables, with projections for 2041–2060 and 2061–2080 using three Global Circulation Models. Niche overlap was also assessed. The Trans-Mexican Volcanic Belt emerged as a significant region for both species. We observed substantial variability among climate models. For S. latifolia, gains ranged from 1.708% (CNRM-CM6-1 model) to 74.806% (HadGEM3-GC31-LL model) for 2041–2060, while the highest loss was 44.11% (MPI-ESM1-2-HR model). Similarly, S. macrophylla showed gains up to 73.591% (MPI-ESM1-2-HR) and losses up to 19.734% (CNRM-CM6-1). These results highlight species-specific responses to future climate scenarios. Niche overlap analyses revealed that both species currently share up to 41% of their niches, with this overlap likely to continue in the future. This study provides insights into the potential impacts of climate change on species distributions, informing conservation and management strategies. Given S. latifolia’s native status and S. macrophylla’s endemic and threatened nature, understanding their distribution dynamics is crucial for conservation efforts. This research underscores the need to address climatic threats to ensure the survival of these key species and maintain the health of Mexican aquatic ecosystems.

The Prairie Pothole Region (PPR) has an extremely variable climate and has pronounced impacts on wetlands as they are highly responsive to the variability in air temperature and precipitation. In recent years, the PPR has been in a novel wet climate continuum since 1993, facilitating severe flooding in the Devils Lake Basin (DLB), North Dakota– costing the US ~$1B USD. Many studies using remotely sensed imagery reported a substantial increase in the number of surface water bodies and expansion of the existing water bodies during 1988–2013 period. In addition to surface water area, the water storage of the potholes also substantially increased. However, very few studies quantify the surface water storage and its dynamics to the recent increase in precipitation using remotely sensed data in the PPR. In this study, we utilize high resolution LiDAR DEM and monthly global surface water data (GSWD) to estimate filled storage of each pothole in the Starkweather Coulee Basin (SCB, 700 km²)– a headwater basin draining to a terminal lake (Devils Lake). Our findings suggest that the SCB storage gradually filling up during two wet periods: 1990–1998 and 2009–2013, resulting in massive streamflow and subsequent flooding. The SBC fractional storage also exhibits a strong positive and exponential relationship with peak streamflow and annual streamflow volume indicating strong influence of wetland storage and fill-spill hydrology on the streamflow generation. The exponential relationships also point toward a threshold SCB fractional storage for generating extreme streamflow generation.

Wetlands are important ecosystems due to their high biodiversity and provisioning of ecosystem services. Historically, however, wetlands were often considered hostile or strange by mainstream societies. These views percolated to stories about wetlands. Wetland stories highlighted their danger, physical encumbrance, or antithesis to civilized society. One of the most prominent ways wetlands are portrayed in modern storytelling is in film. Many films have prominently featured wetlands, and mass media has been shown to influence attitudes and behaviors in the audience. However, there has never been a systematic overview of wetland portrayal. In this study, we apply a thematic template analysis to synthesize wetland portrayal in modern (1980-present) films. Using two plot summary corpus databases, we first identified films that prominently featured wetlands. We then recorded qualitative data on wetlands portrayal by watching each film and coding featured attributes. Our broad objective was to determine how wetlands are used as storytelling devices, specifically by understanding basic portrayal information, narrative elements, themes, imagery, and portrayed biodiversity. We also characterized the attitude of the portrayal to the wetland environment, expecting portrayals to be predominantly negative. We identified and analyzed 163 films that featured wetlands. Swamps were the most frequently featured wetland type and screentime of the wetlands was generally a small part of the narrative. Wetlands were most commonly used as trials and tribulations for the protagonist—most notably as physical obstacles, sites of conflicts with the antagonists, or chase scenes. Prominent themes of wetland portrayal included death, refuge, and ostracism. Attitudes of portrayal leaned negative, and half of films had a statically negative portrayal. Despite this relative negativity, wetlands were directly or implicitly portrayed as productive and biodiverse ecosystems. We suggest wetlands are portrayed in films because their quintessential attributes (e.g., saturation, remoteness, biodiversity) are useful to embellish the stories’ dramatic effects. We also show that some historical attitudes and ideas surrounding wetlands may persist into the fundamental components of modern film storytelling. Wetlands may often be negatively portrayed as environmental caricatures, which could subconsciously harm public attitudes toward wetland conservation and biodiversity.

Peatland ponds are abundant in the boreal permafrost landscapes, which is a hotspot for greenhouse gas emissions. In this study, we observed annual CH₄ and CO₂ fluxes, as well as CH₄ and CO₂ concentrations of water and ice-trapped bubbles in a peatland pond in the permafrost region of Northeast China. The results show that water CH₄ and CO₂ concentrations increased by 1–4 orders of magnitude during the ice cover period compared to the open water period. (CH₄: 300.37 µM vs. 0.014 µM, CO₂: 2915.73 µM vs. 300.34 µM). During the spring thaw period, water CH₄ and CO₂ concentrations decrease dramatically, with CH₄ and CO₂ fluxes reaching the highest values (CH₄ flux: 30.01 mg m^− 2 h^− 1, CO₂ flux: 401.88 mg m^− 2 h^− 1). High fluxes of CH₄ and CO₂ during the spring thaw period came not only from the release of CH₄ and CO₂ in water under the ice, but also from bubbles trapped in the ice. This study showed the importance of considering CH₄ and CO₂ storage during the ice cover period and spring thaw fluxes in boreal peatland ponds. Given that dynamics of CH₄ and CO₂ fluxes during the spring thaw period in peatland ponds remain understudied, we encourage an increased focus on observations of CH₄ and CO₂ fluxes dynamics during the spring thaw period. The lack of observation during the spring thaw period may underestimate the annual budget for CH₄ and CO₂ in peatland ponds.

Wetlands are disappearing globally at alarming rates; since 1900, 71% of wetlands have changed into other forms of land cover. The CA-Markov model is one of the most effective methods for forecasting LULC change. In order to predict LULC changes of Shadegan wetland in 2050, images for the years 1980, 1990, 2000, 2010, and 2020 were classified based on segmentation and artificial neural networks (ANNs), and three classes were considered, including vegetation, bare land, and water. To assess accuracy of classification and prediction, the Kappa coefficient was calculated. Results indicate that CA-Markov has moderate predictive capability for future changes. Results of the image classification show that most of the changes occurred in vegetation from 2000 to 2020. So, about 170,000 hectares of this class have been converted to bar land. By comparing the LULC map in 2020 and 2050, if the current trend in the region is continued, in the 2050 year, 79.6% of the total area will be covered by the bare land. Increasing the amount of dry land in the area can create dust sources. During the last years, with the intensification and continuation of drought, dried parts of wetlands such as Shadegan became the most active dust sources in the southwest of Iran. The aerosol optical depth time series data were used to verify the model’s prediction findings. The result of the Mann-Kendall (MK) test shows the positive trend in the AOD time series, indicating an increasing trend in dust concentration.

This paper presents the first analysis of impacts of COVID-19 on willingness-to-pay for wetland restoration. Two potential effects were identified that may affect willingness-to-pay for wetland restoration and empirically tested using a referendum-style contingent valuation survey that was administered in the midst of the pandemic to measure willingness-to-pay for restoring mangroves and saltmarshes in Tampa Bay, Florida. Results indicate that willingness-to-pay was $2,791 per household during COVID, but it would have been $3,262 if there had not been COVID. These results imply a loss of $3.8 billion in the total value of restoring wetlands in the state of Florida.

Climate change and its variability impact water availability in wetlands, jeopardizing their ecosystems. This study focuses on the Sudd Wetland, Africa’s most extensive and one of the world’s largest tropical wetland systems. We analyzed historical climate data (temperature, rainfall) in the Sudd and its upstream regions to assess climate impacts on the wetland’s health (NDVI) and water conditions (surface water extent, lake height) using spatial and temporal trends. The study unveils distinct seasonal and long-term variations in vegetation and temporal fluctuations in surface water dynamics within the Sudd Wetland. While central areas experienced declining NDVI (vegetation cover), peripheries showed an increase. The wetland gained open water surface area, with a slight rise in permanent water (3%) and a significant increase in seasonal inundations (19%). All monitored water bodies in the Sudd displayed a gradual increase in surface water height. Climate shifts are observed as rising temperatures and increased rainfall trends. Annual and seasonal temperatures rose across the basin, with the January-Feburary season experiencing the most significant increase (~ 1.3 °C). Rainfall trends were mostly flat, except for the south-central and southeastern regions, where a statistically significant increase ranging from 5 mm to 17 mm per year was observed. Conclusive evidence from this paper could be used to assess water policy and management in the region while protecting key parts of the hydrologic cycle.

Wetlands are important ecosystems for mitigating climate change impacts on the environment and society. Most studies focus on how single environmental factors affect those ecosystems, although several environmental factors may change simultaneously. This study focused on nutrient – water level interaction effects on two different but associated wet grassland species Carex acuta and Glyceria maxima. Biomass allocation and root exudates were measured in a full-factorial mesocosm experiment. Species identity and water level mostly determined total alive biomass and the biomass allocation pattern. Root weight ratio generally increased in C. acuta whereas increased rhizome biomass was associated with G. maxima. Furthermore, increased water levels increased relative aboveground biomass allocation with C. acuta having more leaf and G. maxima having more stem biomass. Surprisingly, fertilisation had little impact on total biomass, but decreased relative biomass allocation to the roots and also strongly suppressed root exudation. There is an apparent nutrient dependent shift in the realised hydrological niche of both plants towards drier conditions. C. acuta behaves similar under all water levels without fertilisation, but thrives best under dry conditions when fertilised. Without fertilisation, G. maxima thrives best under flooded conditions (water level ~ 15 cm above soil surface), but does equally well in saturated water conditions (water level ~ soil surface) when fertilised.

In freshwater forested wetlands, bald cypress knees (Taxodium distichum (L.) Rich.) have the potential to emit large amounts of methane (CH₄), but only a few studies have examined their greenhouse gas contribution. In this study, we measured CH₄ fluxes associated with cypress knees across various climate and flooding gradients of the Mississippi River Alluvial Valley in southcentral United States. Greenhouse gases were measured using a portable gas analyzer with a custom-made chamber placed over the knees. We also conducted 3D lidar scans of knees using a smartphone to estimate the surface area and volume of knees. We investigated the following: (1) What parameters influence CH₄ fluxes (i.e., knee height, distance to stream, temperature, relative humidity, water level, precipitation)? and (2) Which type of knee shape measurement (i.e., cone, frustrum, or lidar scan) provides the best fit to model data while maximizing measurement efficiency? We found that knee CH₄ flux rates ranged from − 0.005 to 182 mmol m^− 2 d^− 1. There were positive correlations between CH₄ fluxes, water levels, and temperature, and a negative correlation with knee height. Sites that had been dry for longer periods of time emitted less CH₄ than sites where the soil remained saturated. The frustrum shape produced a knee volume estimate that was within 12% of lidar scans, whereas cone shapes underestimate knee dimensions (-100%). Further research of emissions and fluxes in cypress knees could fill knowledge gaps within the carbon cycle and could represent a major component of wetland CH₄ budgets.

Along with wetland loss, wetland habitat quality degradation is a growing concern that requires immediate attention. The current study aimed to assess the Wetland Habitat Quality State (WHQS) of Rarh region, Murshidabad, West Bengal. WHQS used a total of seventeen metrics, including water quality, hydrology, and landscape composition. Machine learning techniques such as ANN, SVM, RF, BAGGING, and REP-TREE were used to model WHQS. The effectiveness of the models was evaluated using statistical techniques such as the Receiver operating characteristics (ROC) curve. According to machine learning models, 6% of the area fall under very weak habitat quality zones in 1990 which increased by 15%, 26%, 41% in 2000, 2010 and 2020, respectively. Very strong portions of wetland area have been decreased from 32.74% in 1990 to 20.72% in 2020. The current study's findings could provide comprehensive research on the monitoring of habitat quality in wetlands, which will serve as the foundation for developing water resource management plans for the conservation, management, and restoration of wetlands.