A geospatially resolved wetland vulnerability index: Synthesis of physical drivers

Cultural adaptation and validation of the mental illness associated stigma scale for Arabic-speaking population in Saudi Arabia

Objective

This research aimed to culturally adapt and validate the MIAS scale for Arabic-speaking individuals within the Saudi Arabian general population, with an emphasis on cultural, societal, and individual nuances.

Methods

An initial pilot testing with a small group ensured the scale's clarity. Subsequently, two cross-sectional studies involving 189 participants to assess structural validity of the Arabic MIAS scale, and 38 participants to assess the test-retest reliability. Descriptive statistics, Cronbach's α, Intraclass Correlation Coefficient (ICC), and Confirmatory Factor Analysis (CFA) were employed for data analysis.

Results

The Arabic MIAS scale demonstrated good internal consistency and acceptable test-retest reliability (ICC α = 0.631). A three-factor model emerged (CFI = 0.890, TLI = 0.845, RMSEA = 0.094), including "Outcomes," "Negative Stereotypes," and "Recovery," closely mirroring the original study's structure. one item was excluded from the model since it didn't align with any of the three factors.

Conclusion

The study contributes a culturally adapted, validated, non-condition-specific tool to gauge public attitudes toward mental health stigma in an Arabic context. It highlights the need for culturally sensitive stigma research and interventions and underscores the importance of improving such tools for cross-cultural applicability and comparability.

Spatio-temporal variability of seawater mixing in the coastal aquifers based on hydrogeochemical fingerprinting and statistical modeling

This study discusses monitoring and characterization of spatial and temporal variability to comprehend groundwater salinization based on hydrogeochemical fingerprinting and statistical modeling in the coastal belt of Digha-Shankarpur-Tajpur-Mandarmani, West Bengal, India. An integrated study of hydrogeochemical, bulk magnetic susceptibility, multivariate statistical, and geochemical modeling methods is implemented. The major cationic and anionic concentrations in groundwater are in the order Na+ > Ca2+ > Mg2+ > K+ and Cl- > HCO3- > SO4- > NO3- > F- respectively. The major water types are dominated by (Ca2+ - HCO3-) followed (Ca2+ - Mg2+ - Cl-), (Ca2+ - Na+ - HCO3-), (Na+ - HCO3-), and (Na+ - Cl). The results showed that the groundwater quality continuously declined steadily from pre-monsoon 2020 to pre-monsoon 2022. The deterioration of groundwater is due to an interplay of multiple factors, i.e., water-rock interaction, including ion-exchange, seawater mixing, and anthropogenic actions. Furthermore, it is also found that the regions showing higher seawater mixing index and oversaturated with carbonate minerals are also areas where groundwater is unsuitable for irrigation. The findings are beneficial in assisting local communities and legislators in designing appropriate management and mitigation techniques to arrest seawater intrusion in coastal regions.

Marsh migration and beyond: A scalable framework to assess tidal wetland resilience and support strategic management

Tidal wetlands are critical but highly threatened ecosystems that provide vital services. Efficient stewardship of tidal wetlands requires robust comparative assessments of different marshes to understand their resilience to stressors, particularly in the face of relative sea level rise. Existing assessment frameworks aim to address tidal marsh resilience, but many are either too localized or too general, and few directly translate resilience evaluations to recommendations for management strategies. In response to the deficiencies in existing frameworks, we identified a set of metrics that influence overall marsh resilience that can be assessed at any spatial scale. We then developed a new comprehensive assessment framework to rank relative marsh resilience using these metrics, which are nested within three categories. We represent resilience as the sum of results across the three metric categories: current condition, adaptive capacity, and vulnerability. Users of this framework can add scores from each category to generate a total resilience score to compare across marshes or take the score from each category and refer to recommended management actions we developed based on expert elicitation for each combination of category results. We then applied the framework across the contiguous United States using publicly available data, and summarized results at multiple spatial scales, from regions to coastal states to National Estuarine Research Reserves to finer scale marsh units, to demonstrate the framework's value across these scales. Our national analysis allowed for comparison of tidal marsh resilience across geographies, which is valuable for determining where to prioritize management actions for desired future marsh conditions. In combination, the assessment framework and recommended management actions function as a broadly applicable decision-support tool that will enable resource managers to evaluate tidal marshes and select appropriate strategies for conservation, restoration, and other stewardship goals.

Multiscale spatial analysis of headwater vulnerability in South-Central Chile reveals a high threat due to deforestation and climate change

Headwaters represent an essential component of hydrological, ecological, and socioeconomical systems, by providing constant water streams to the complete basin. However, despite the high importance of headwaters, there is a lack of vulnerability assessments worldwide. Identifying headwaters and their vulnerability in a spatially explicit manner can enable restauration and conservation programs. In this study, we assess the vulnerability of headwaters in South-Central Chile (38.4 to 43.2°S) considering multiple degradation factors related to climate change and land cover change. We analyzed 2292 headwaters, characterizing multiple factors at five spatial scales by using remote sensing data related to Land Use and Cover Change (LUCC), human disturbances, vegetation cover, climate change, potential water demand, and physiography. We then generated an index of vulnerability by integrating all the analyzed variables, which allowed us to map the spatial distribution of headwater vulnerability. Finally, to estimate the main drivers of degradation, we performed a Principal Components Analysis with an Agglomerative Hierarchical Clustering, that allowed us to group headwaters according to the analyzed factors. The largest proportion of most vulnerable headwaters are located in the north of our study area with 48.1 %, 62.1 %, and 28.1 % of headwaters classified as highly vulnerable at 0, 10, and 30 m scale, respectively. The largest proportion of headwaters are affected by Climate Change (63.66 %) and LUCC (23.02 %) on average across all scales. However, we identified three clusters, in which the northern cluster is mainly affected by LUCC, while the Andean and Coastal clusters are mainly affected by climate change. Our results and methods present an informative picture of the current state of headwater vulnerability, identifying spatial patterns and drivers at multiple scales. We believe that the approach developed in this study could be useful for new studies in other zones of the world and can also promote Chilean headwater conservation.

Combining stakeholder perception and ecological approaches for assessing vulnerability of floodplain wetlands in changing climate: a regional study

Wetland fisheries are most vulnerable to climate and anthropogenic change, and therefore, vulnerability assessment is essential for the formulation of prudent management strategies. In the present study, vulnerability assessment was carried out in nine floodplain wetlands from three districts of West Bengal using stakeholder perception and ecological conditions. In absence of long-term time series data on ecology and fisheries of wetlands, stakeholder perception study was carried out to assess the vulnerability status to climate change. Phased interviews were conducted using structured questionnaires to study the stakeholder perception on climatic variability and changes in ecology and fisheries of wetlands over the past 15 years. Climate data used for climate trend analysis was procured from Indian Meteorological Department. Ecological parameters were studied from the wetlands seasonally from January 2018 to December 2018. Analysis of climatic variables for last three decades revealed a warming trend and decreasing rainfall in the study area. The temperature anomaly ranged from + 0.07 to + 0.31 °C while rainfall anomaly ranged from - 61.41 to - 372.62 mm. Respondents showed high level of consensus (75.3%) on climate change awareness. The respondents were aware of the fact that climate anomaly affects ecology and fisheries of wetlands in most of the cases with consensus ranging from 67.8 to 94.7%. The studied wetlands showed 2 to 81.28% reduction in depth, 21.52-61.29% reduction in species diversity, and 30-95% macrophyte infestation. The stakeholder perception-based vulnerability scores ranged from 18 to 31 and indicated 6 out of 9 wetlands (66.6%) as highly vulnerable and the rest as moderately vulnerable. The ecological vulnerability scores ranged from 17 to 21 and indicated 5 out of 9 wetlands (55.6%) as highly vulnerable and 4 wetlands in the moderately vulnerable range. Although both the approaches used in the present study categorized the studied wetlands as moderately to highly vulnerable, the category of some of the wetlands varied in both the approaches. This suggests that utilizing a single approach may not give precise vulnerability status of an ecosystem. Use of combined approaches for construction of a composite vulnerability index covering different aspects impacted by climate change might present a better picture of the vulnerability status and aid in formulation of effective mitigation/management plan.

A Conterminous USA-Scale Map of Relative Tidal Marsh Elevation

Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation (Z*_MHW), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z*_MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85-98, 2019). Supporting a third hypothesis, propagated uncertainty in Z*_MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z*_MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z*_MHW and Z*_MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z*_MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z*_MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12237-021-01027-9.

Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh

Wetland risk assessment is a global concern especially in developing countries like Bangladesh. The present study explored the spatiotemporal dynamics of wetlands, prediction of wetland risk assessment. The wetland risk assessment was predicted based on ten selected parameters, such as fragmentation probability, distance to road, and settlement. We used M5P, random forest (RF), reduced error pruning tree (REPTree), and support vector machine (SVM) machine learning techniques for wetland risk assessment. The results showed that wetland areas at present are declining less than one-third of those in 1988 due to the construction of the dam at Farakka, which is situated at the upstream of the Padma River. The distance to the river and built-up area are the two most contributing drivers influencing the wetland risk assessment based on information gain ratio (InGR). The prediction results of machine learning models showed 64.48% of area by M5P, 61.75% of area by RF, 62.18% of area by REPTree, and 55.74% of area by SVM have been predicted as the high and very high-risk zones. The results of accuracy assessment showed that the RF outperformed than other models (area under curve: 0.83), followed by the SVM, M5P, and REPTree. Degradation of wetlands explored in this study demonstrated the negative effects on biodiversity. Therefore, to conserve and protect the wetlands, continuous monitoring of wetlands using high resolution satellite images, feeding with the ecological flow, confining built up area and agricultural expansion towards wetlands, and new wetland creation is essential for wetland management.

Assessment of Ecological Vulnerability on Northern Sand Prevention Belt of China Based on the Ecological Pressure–Sensibility–Resilience Model

Quantitative assessment of ecological vulnerability is of great significance for ecological protection and restoration in ecologically vulnerable regions. Here, the ecological vulnerability of the northern sand prevention belt (NSPB) of China was assessed using an ecological pressure–sensibility–resilience model from 2000 to 2015. Results showed that the ecological vulnerability index (EVI) displayed low values in the eastern part and high values in the western part of the study region. The EVI ranged from 0.29 to 1.32 in 2000, with the mean value of 0.88, whereas it averaged 0.78 in 2015, ranging from 0.21 to 1.26. Decreasing EVI from 2000 to 2015 indicated that the ecological status has been improved. Moreover, the area proportion of moderately, heavily, and extremely ecological vulnerability levels occupied approximately 87% in both 2000 and 2015, indicating a high ecological vulnerability level. Furthermore, the change in area proportion of different ecological vulnerability levels were associated with the change in the spatial distribution of vegetation coverage, indicating that eco-environmental protection projects were indeed effective. These findings indicated that differential strategies in different restoration zones should be adopted, especially in the western parts of the study region, and eco-environmental protection projects should be reinforced to improve the ecological restoration.