Blue Green Algae DOI
Scott A. Fritz, Savannah R. Charnas,

Steve Ensley

et al.

Veterinary Clinics of North America Equine Practice, Journal Year: 2023, Volume and Issue: 40(1), P. 121 - 132

Published: Nov. 23, 2023

Language: Английский

Enhanced activity of enzymes encapsulated in spheres metal azolate framework-7 with defects DOI

Cai Cheng,

Xiaoliang Guo,

Yu‐Qi Feng

et al.

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 283, P. 137689 - 137689

Published: Nov. 17, 2024

Language: Английский

Citations

2
A Two-Stage Interpretable Machine Learning Framework for Accurate Prediction of Trace Pollutants: With an Application to Microcystin DOI

Sifeng Wu,

Zhongyao Liang,

Qianlinglin Qiu

et al.

ACS ES&T Water, Journal Year: 2023, Volume and Issue: 4(3), P. 1155 - 1165

Published: Sept. 26, 2023

Trace pollutants are widely observed in aquatic ecosystems and can significantly impact human health the environment. Accurate prediction of trace understanding their response to environmental drivers key management, yet these tasks remain challenging. An important reason for this challenge is that monitoring data often left-censored, leading biased estimation inaccurate response-driver relationships. Here we propose a novel two-stage interpretable machine learning framework applicable left-censored pollutant data. The two stages include (1) classifier predict presence (2) regressor concentration if present. were followed by model interpretation understand contribution accordingly. We take microcystin (MICX) lakes across United States as case study. Applying MICX consistently improved accuracy, including its occurrence regardless algorithms performance metrics used. best-performing algorithm using framework, compared with baseline model, improves classification 48% 290% regression 11% 33%, depending on metric used evaluate performance. also successfully revealed impacts most concentration. Our results showed advantages interpretability driver-response relationship, ability handle nonlinearity, better performance, differentiation between underlying processes, potential be generalized other pollutants. As such, anticipate will starting point state-of-the-art models predicting

Language: Английский

Citations

2
Microcystin Concentrations, Partitioning, and Structural Composition during Active Growth and Decline: A Laboratory Study DOI Creative Commons
Emily Pierce, Astrid Schnetzer

Toxins, Journal Year: 2023, Volume and Issue: 15(12), P. 684 - 684

Published: Dec. 6, 2023

Microcystin can be present in variable concentrations, phases (dissolved and particulate), structural forms (congeners), all which impact the toxicity persistence of algal metabolite. Conducting incubation experiments with six bloom assemblages collected from Chowan River, North Carolina, we assessed microcystin dynamics during active growth biomass degradation. Upon collection, average particulate dissolved ranged between 0.2 993 µg L−1 0.5 3.6 L−1, respectively. The presence congeners MC-LA, -LR, -RR, -YR was confirmed MC-RR MC-LR being most prevalent. Congener composition shifted over time varied phases. Particulate exponentially declined five incubations an half-life 10.2 ± 3.7 days, while remained detectable until end trials (up to 100 days). Our findings suggest that concerns about food-web transfer via intracellular toxins seem warranted within first few weeks peak, linger for several months aftermath event. Also, it indicated there were differences congener profiles linked sampling method. We believe this study inform monitoring strategies aid microcystin-exposure risk assessments cyanobacterial blooms.

Language: Английский

Citations

2
An evaluation of statistical models of microcystin detection in lakes applied forward under varying climate conditions DOI
Grace M. Wilkinson, Jonathan A. Walter, Ellen Albright

et al.

Harmful Algae, Journal Year: 2024, Volume and Issue: 137, P. 102679 - 102679

Published: June 17, 2024

Language: Английский

Citations

0
Unprecedented toxic blooms of Microcystis spp. in 2019 in the Chowan River, North Carolina DOI
Emily Pierce,

Marco Valera,

Mark Vander Borgh

et al.

Harmful Algae, Journal Year: 2024, Volume and Issue: 140, P. 102747 - 102747

Published: Nov. 9, 2024

Language: Английский

Citations

0
Effects of Cyanobacterial Decomposition on Sediment Microbial Communities and Greenhouse Gases Production Under Allelopathic Algaecide Intervention DOI
Cunhao Du,

Wenlu Sang,

Yushen Ma

et al.

Published: Jan. 1, 2023

Cyanobacterial natural decomposition can alter the physicochemical characteristics and microbial communities, thereby contributing to greenhouse gases (GHGs) emissions from lakes. However, effects of cyanobacterial under algaecides on communities GHG remain poorly understood. This study selected artemisinin sustained-release microspheres (ASMs) for algae inhibition experiment, denoted as IDG, established NDG, explore sediment GHGs production. The results showed that dissolved oxygen (DO) oxidation-reduction potential (ORP) in both NDG IDG decreased significantly, creating an anaerobic reduction environment. also resulted release a large amount nutrients organic matter, which provided favorable conditions fermentation microorganisms. were altered treatment groups, with significant increase abundance Proteobacteria Bacteroidetes associated fermentation. Compared enhanced production carbon dioxide (CO2) methane (CH4), while reducing nitrous oxide (N2O), without further increasing global warming potential. could provide new insights into application allelochemicals control blooms.

Language: Английский

Citations

0
Blue Green Algae DOI
Scott A. Fritz, Savannah R. Charnas,

Steve Ensley

et al.

Veterinary Clinics of North America Equine Practice, Journal Year: 2023, Volume and Issue: 40(1), P. 121 - 132

Published: Nov. 23, 2023

Language: Английский

Citations

0