Socio-ecological well-being perspectives of wetland loss scenario: A review

Effect of channel morphological changes on wetland transformation

Keeping aside the traditional approaches to investigating floodplain wetland transformation, the current study investigated various aspects of it through changes in river channel morphology and drainage pattern. The study analyzed wetland transformation using satellite image-based machine learning and intensive fieldwork. Ordinary Least Square (OLS) regression was applied to identify dominant influencing factors among 24 contributing factors under six clusters to eight dependent phenomena of transformation. The result showed that 57 % of wetland area lost since 1991, and existing wetland has also experiencing hydrological scarcity. From 1991 to 2021, the area under low water depth (<1 m.) inflated from 18.55 % to 50.54 %, the hydro-period narrowed down, and the appearance of water become inconsistent. The OLS result showed that changes in channel morphology (bottle neck channel, embankment-driven carrying capacity enhancement, etc.), interruptions in river and wetland connecting channels (source closure, breaching the continuity, conversion in to agricultural land, etc.), and changes in flood ambience (regulated by dam construction, erection of embankments, etc.) majorly contributed to wetland transformation. Very high explainability was found in the cases of rate of wetland loss, decreasing water depth under greater depth, narrowing hydro-period (R2 > 0.9). The findings of this work would be a good policy document for floodplain wetland management.

Impact of wetland health and provisioning services on the livelihood of the fishing community

The present study aimed to explore the linkage between wetland health, provisioning service value (PsV) and livelihood vulnerability of the dependent fishermen community taking examples from the Moribund deltaic wetlands of India. Wetland health including hydrological strength, habitat state, and the water quality of the wetland was assessed using a random forest (RF) and XGBoosing machine learning approach, and the Livelihood Vulnerability Index (LVI) was computed using balanced weighted approach. Ordinary least square (OLS) regression, correlation matrix, and rank correlation matrix were done to make the relationship between wetland health and LVI. Wetland health was found poor (28.38%) in the isolated, smaller, and peripheral parts of the wetland with agricultural and built-up area proximity. Hydrological strength (with r2 of 0.67) was found as the most dominant health determinant followed by habitat state (with r2 of 0.62). OLS reported that in most of the cases, the standard regression residual is low (0.5 to - 0.5) which indicates that there is a strong relation between wetland health and LVI. KDE plot and correlation matrix also figured out the same. From the field survey, it was found that the wetlands with good habitat health are promising for providing more provisioning services like fish which in turn supports the livelihood of the dependent communities. The findings of this study have a deeper insight into livelihood management through wetland management. Hence, it would inspire policymakers and stakeholders to conserve wetlands not only for the sake of ecology but also for society.

Exploring wetland change in the Gauteng Province, South Africa

This study investigated land use and land cover changes in the Gauteng Province of South Africa with emphasis on wetland ecosystems. Using Landsat images and various image manipulation software such as ArcGIS and ENVI, this study conducted a predictive analysis of the potential state of wetland ecosystems in the Gauteng Province of South Africa by year 2040, using illegal dumping trends in the last 20 years. Based on this methodological framework, it is found that continued illegal dumping trends would lead to an almost total disappearance of wetlands in the study area by 2040. It is argued that despite the pro-environmental initiatives introduced in the early 2000s to conserve wetlands in South Africa, wetland deterioration has increased rapidly due to the associated methodological flaws, which further supports the findings of this study. Ultimately, it is recommended that a collaborative approach to wetland conservation, and a robust methodological shift are required to mitigate the threats faced by wetlands in the Gauteng Province of South Africa, and the model can be deployed across developing countries.

Anthropogenic impacts on urban blue space and its reciprocal effect on human and socio-ecological health

Quantifying anthropogenic impacts on blue space (BS) and its effect on human and socio-ecological health was least explored. The present study aimed to do this in reference to the urban BS transformation scenario of Eastern India. To measure BS transformation, Landsat image-based water indices were run from 1990 to 2021. Anthropogenic impact score (AIS) and 7 components scores of 78 selected BS on 70 parameters related data driven from the field. Total 345 respondents were taken for human and socio-ecological health assessment. For this, depression (DEP), anxiety (ANX), stress (STR), physical activities (PA), social capital (SC), therapeutic landscape (TL) and environment building (EB) parameters were taken. The result exhibited that BS was reduced. About 50% of urban core BS was reported highly impacted. Human and socio-ecological health was identified as good in proximity to BS, but it was observed better in the cases of larger peripheral BS. AIS on BS was found to be positively associated with mental health (0.47-0.63) and negatively associated with PA, SC, TL and EB (-0.50 to -0.90). Standard residual in ordinary least square was reported low (-1.5 to 1.5) in 95% BS. Therefore, BS health restoration and management is crucial for sustaining the living environment.

Measuring anthropogenic impact of the ox-bow lakes in moribund Ganges deltaic India

Measuring the anthropogenic impact score (AIS) of the ox-bow lakes in order to explore the present situation and future ways of restoration is very necessary, particularly in highly populated areas. The present work targeted to do this considering 68 contributing parameters under eight AIS constituting components like pollution impact score (PIS), habitat alteration impact score (HAIS), hydrological alteration impact score (HYAIS), landscape alteration impact score (LAIS), etc. and tried to explore the major determinants behind. Machine learning (ML) algorithms were applied for computing component level and overall, AIS. A supervised correlation attribute evaluator (CAE) was applied for detecting major determinants. The result revealed out of total 44 major ox-bow lakes 40.90 % to 59.09 % (9.97 km2 to 14.69 km2) were identified as highly impacted both at the component level and overall scale as per the best predicted Random Forest (RF) model. Hydrologically connected lakes were less impacted than isolated ones. Genetically main river (Bhagirathi-Hooghly) left ox-bow lakes are less affected than those of the off-shoot channel. Larger size lakes witnessed less impact than medium and smaller lakes. Pollution, habitat, and hydrological components were found as the most dominant components of AIS. Reclamation, pollution, and eutrophication factors were identified as the dominant factors. AIS is negatively associated with fish yield and positively associated with the livelihood vulnerability of the dependent fishermen community. Since hydrological connectivity is a big issue; maintenance of it could be a good approach to its sustainability.

Economic and socioecological perspectives of urban wetland loss and processes: a study from literatures

Existing literatures across the world highlighted the causes and rate of wetland loss; however, so far, no researches tried to analyze how these are guided by the socioeconomic and ecological conditions. The current review work wished to explore how economic and socioecological perspectives could control the rate and drivers of urban wetland loss. Through meta-analysis, this study also intended to explore the changing polarity in research publication and collaborative research. Total 287 original research articles indicating the rates and drivers of wetland loss from 1990 to June 2022 for the first objective and 1500 articles focusing wetland researches from Dimensions AI database for the last objective were taken.Results clearly revealed that the rate of urban wetland loss varies from 0.03 to 3.13% annually, and three main drivers like built-up, agricultural expansions, pollution were identified all across the world. Loss rate was found maximum in the developing and least developed countries. Pollution, built-up expansion, and agriculture expansion, respectively, in developed, developing, and least developed nations were identified as the most dominant drivers of urban wetland loss. Linking loss rate and drivers with socioecological and economic perspectives revealed that human development index (HDI), ecological performance index (EPI), sustainable development goal index (SDGI), and social progress index (SPI) is negatively associated with the rate of urban wetland loss. Contrarily, a poverty rate encouraged higher rate of loss. This study articulated that improving these socioecological and economic conditions could help wetland conservation and restoration to achieve SDGs.