scholarly journals Effects of Land Use and Pollution Loadings on Ecotoxicological Assays and Bacterial Taxonomical Diversity in Constructed Wetlands

Diversity ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 149
Author(s):  
Subhomita Ghosh Roy ◽  
Charles F. Wimpee ◽  
Stephen A. McGuire ◽  
Timothy J. Ehlinger

Freshwater ecosystems are affected by anthropogenic alterations. Different studies have extensively studied the concentrations of metals, nutrients, and water quality as measurements of pollution in freshwater ecosystems. However, few studies have been able to link these pollutants to bioindicators as a risk assessment tool. This study aimed to examine the potential of two bioindicators, plant ecotoxicological assays and sediment bacterial taxonomic diversity, in ecological risk assessment for six freshwater constructed wetlands in a rapidly urbanizing watershed with diverse land uses. Sediment samples were collected summer, 2015 and 2017, and late summer and early fall in 2016 to conduct plant ecotoxicological assays based on plant (Lepidium, Sinapis and Sorghum) growth inhibition and identify bacterial taxonomical diversity by the 16S rRNA gene sequences. Concentrations of metals such as lead (Pb) and mercury (Hg) (using XRF), and nutrients such as nitrate and phosphate (using HACH DR 2800TM spectrophotometer) were measured in sediment and water samples respectively. Analyses of response patterns revealed that plant and bacterial bioindicators were highly responsive to variation in the concentrations of these pollutants. Hence, this opens up the scope of using these bioindicators for ecological risk assessment in constructed freshwater wetland ecosystems within urbanizing watersheds.

2021 ◽  
Author(s):  
Richard E Grewelle ◽  
Elizabeth Mansfield ◽  
Fiorenza Micheli ◽  
Giulio A De Leo

Ecological Risk Assessment is a formal process widely applied to terrestrial, marine, and freshwater ecosystems to evaluate the likelihood of adverse ecological effects occurring as a result of exposure to natural or anthropogenic stressors. For many species, data is sparse and semi-quantitative methodologies provide valuable insight for ecosystem management. Recent statistical developments have improved the quality of these analyses yet a rigorous theoretical framework to assess the cumulative impact of multiple stressors is lacking. We present EcoRAMS, a web application and open-source software module that provides easy-to-use, statistically-robust ecological risk assessments of multiple stressors in data-poor contexts. The software receives attribute scores for two variables (e.g. exposure-sensitivity, productivity-susceptibility, severity-likelihood) via CSV templates and outputs results according to a probabilistic metric of risk. We demonstrate comparative results across a range of assumptions, using simulated and empirical datasets including up to five stressors. Accounting for multiple stressors even when data is limited provides a more detailed analysis of risk that may otherwise be understated in single stressor analyses. This application will allow quantification of risk across data-poor contexts for which statistical results have been previously unavailable. The web app format of EcoRAMS.net lowers the barrier of use for practitioners and scientists at any level of statistical training.


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