Bioremediation potential of nutrient-rich effluent using aquatic vegetation in suburban watersheds

Kathryn Samarro; P. Zion Klos; Kathryn Samarro; P. Zion Klos

doi:10.3934/urs.2025005

Urban Resilience and Sustainability

2025, Volume 3, Issue 1: 102-118. doi: 10.3934/urs.2025005

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Research article

Bioremediation potential of nutrient-rich effluent using aquatic vegetation in suburban watersheds

Kathryn Samarro ,
P. Zion Klos ^,

Department of Environmental Science and Policy, Marist University, Poughkeepsie, NY, USA

Received: 03 May 2025 Revised: 19 June 2025 Accepted: 27 June 2025 Published: 15 July 2025

Nutrient loading in watersheds from anthropogenic sources has led to eutrophication and decreased biodiversity within water bodies globally. Denitrification via aquatic vegetation can assist with bioremediation; however, its effectiveness at fine spatial scales (i.e., < 1 km) in stream systems is less understood. In this study, we used 50-m-scale longitudinal observations of changes in aquatic macrophyte abundance and frequency across more than 50 species. We related species abundance to changes in nitrate concentration and other water quality metrics along a low-order stream across an urban-suburban gradient in the Hudson River Valley, New York. Observations from a 2 km section of the Fall Kill stream corridor were conducted in a summer period of lower flows (0.14 m³/sec) and a fall period of higher flows (0.24 m³/sec). For statistical and predictive analyses, we aimed to establish potential relationships between biotic and abiotic variables to identify candidate species for future applied bioremediation studies and potential instream applications. Our findings indicated that low flow nitrate concentrations most strongly relate to the abundance of Persicaria hydropiperoides (r = 0.35, p = 0.03) and Ludwiga palustris (r = −0.29, p = 0.07). The strongest relationship analyzed with high flow nitrate concentrations was floating growth forms (r = −0.33, p = 0.04), such as Lemna sp. Machine learning (neural network modeling), also demonstrated the importance of Viburnum species in predicting in-stream nitrate concentrations, suggesting another potential candidate. The compounded effects of other correlated abiotic and biotic variables were also measured and considered, such as relations between macrophyte abundance and hydrologic conditions like depth and overhead light. Determining the specific relationships between nitrate concentrations and species-level aquatic macrophyte abundance and presence at these unique fine scales provides detailed suggestions for bioremediation in similarly eutrophicated low-order, urban-suburban watersheds regionally to globally.
- ecosystem biology,
- urban ecosystem,
- bioremediation,
- fine-scale,
- biometric observation,
- Hudson River watershed,
- aquatic macrophyte
Citation: Kathryn Samarro, P. Zion Klos. Bioremediation potential of nutrient-rich effluent using aquatic vegetation in suburban watersheds[J]. Urban Resilience and Sustainability, 2025, 3(1): 102-118. doi: 10.3934/urs.2025005

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Abstract

Nutrient loading in watersheds from anthropogenic sources has led to eutrophication and decreased biodiversity within water bodies globally. Denitrification via aquatic vegetation can assist with bioremediation; however, its effectiveness at fine spatial scales (i.e., < 1 km) in stream systems is less understood. In this study, we used 50-m-scale longitudinal observations of changes in aquatic macrophyte abundance and frequency across more than 50 species. We related species abundance to changes in nitrate concentration and other water quality metrics along a low-order stream across an urban-suburban gradient in the Hudson River Valley, New York. Observations from a 2 km section of the Fall Kill stream corridor were conducted in a summer period of lower flows (0.14 m³/sec) and a fall period of higher flows (0.24 m³/sec). For statistical and predictive analyses, we aimed to establish potential relationships between biotic and abiotic variables to identify candidate species for future applied bioremediation studies and potential instream applications. Our findings indicated that low flow nitrate concentrations most strongly relate to the abundance of Persicaria hydropiperoides (r = 0.35, p = 0.03) and Ludwiga palustris (r = −0.29, p = 0.07). The strongest relationship analyzed with high flow nitrate concentrations was floating growth forms (r = −0.33, p = 0.04), such as Lemna sp. Machine learning (neural network modeling), also demonstrated the importance of Viburnum species in predicting in-stream nitrate concentrations, suggesting another potential candidate. The compounded effects of other correlated abiotic and biotic variables were also measured and considered, such as relations between macrophyte abundance and hydrologic conditions like depth and overhead light. Determining the specific relationships between nitrate concentrations and species-level aquatic macrophyte abundance and presence at these unique fine scales provides detailed suggestions for bioremediation in similarly eutrophicated low-order, urban-suburban watersheds regionally to globally.

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