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Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment
Myriophyllum spicatum is a sediment‐rooted, aquatic macrophyte growing submerged, with a wide geographical distribution and high ecological relevance in freshwater ecosystems. It is used in testing and risk assessment for pesticides in water and sediment. Population models enable effects measured un...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545951/ https://www.ncbi.nlm.nih.gov/pubmed/34755447 http://dx.doi.org/10.1002/ieam.4553 |
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author | Arts, Gertie H. P. van Smeden, Jasper Wolters, Marieke F. Belgers, J. Dick M. Matser, Arrienne M. Hommen, Udo Bruns, Eric Heine, Simon Solga, Andreas Taylor, Seamus |
author_facet | Arts, Gertie H. P. van Smeden, Jasper Wolters, Marieke F. Belgers, J. Dick M. Matser, Arrienne M. Hommen, Udo Bruns, Eric Heine, Simon Solga, Andreas Taylor, Seamus |
author_sort | Arts, Gertie H. P. |
collection | PubMed |
description | Myriophyllum spicatum is a sediment‐rooted, aquatic macrophyte growing submerged, with a wide geographical distribution and high ecological relevance in freshwater ecosystems. It is used in testing and risk assessment for pesticides in water and sediment. Population models enable effects measured under laboratory conditions to be extrapolated to effects expected in the field with time‐variable environmental factors including exposure. These models are a promising tool in higher‐tier risk assessments. However, there is a lack of data on the seasonal dynamics of M. spicatum, which is needed to test model predictions of typical population dynamics in the field. To generate such data, a two‐year study was set up in outdoor experimental systems from May 2017 to May 2019. The growth of M. spicatum was monitored in 0.2025 m(2) plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh weight [FW] and dry weight [DW]), shoot length, seasonal short‐term growth rates of shoots, relevant environmental parameters, and weather data. The results showed a clear seasonal pattern of biomass and shoot length and their variability. M. spicatum reached a maximum total shoot length (TSL) of 279 m m(−2) and a maximum standing crop above‐ground DW of 262 g m(−2). Periodical growth rates reached up to 0.072, 0.095, and 0.085 day(−1) for total length, FW, and DW, respectively. Multivariate regression revealed that pH (as a surrogate for the availability of carbon species) and water temperature could explain a significant proportion of the variability in M. spicatum growth rates (p < 0.05). This study has provided an ecologically relevant data set on seasonal population dynamics representative of shallow freshwater ecosystems, which can be used to test and refine population models for use in chemical risk assessment and ecosystem management. Integr Environ Assess Manag 2022;18:1375–1386. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). |
format | Online Article Text |
id | pubmed-9545951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95459512022-10-14 Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment Arts, Gertie H. P. van Smeden, Jasper Wolters, Marieke F. Belgers, J. Dick M. Matser, Arrienne M. Hommen, Udo Bruns, Eric Heine, Simon Solga, Andreas Taylor, Seamus Integr Environ Assess Manag Health & Ecological Risk Assessment Myriophyllum spicatum is a sediment‐rooted, aquatic macrophyte growing submerged, with a wide geographical distribution and high ecological relevance in freshwater ecosystems. It is used in testing and risk assessment for pesticides in water and sediment. Population models enable effects measured under laboratory conditions to be extrapolated to effects expected in the field with time‐variable environmental factors including exposure. These models are a promising tool in higher‐tier risk assessments. However, there is a lack of data on the seasonal dynamics of M. spicatum, which is needed to test model predictions of typical population dynamics in the field. To generate such data, a two‐year study was set up in outdoor experimental systems from May 2017 to May 2019. The growth of M. spicatum was monitored in 0.2025 m(2) plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh weight [FW] and dry weight [DW]), shoot length, seasonal short‐term growth rates of shoots, relevant environmental parameters, and weather data. The results showed a clear seasonal pattern of biomass and shoot length and their variability. M. spicatum reached a maximum total shoot length (TSL) of 279 m m(−2) and a maximum standing crop above‐ground DW of 262 g m(−2). Periodical growth rates reached up to 0.072, 0.095, and 0.085 day(−1) for total length, FW, and DW, respectively. Multivariate regression revealed that pH (as a surrogate for the availability of carbon species) and water temperature could explain a significant proportion of the variability in M. spicatum growth rates (p < 0.05). This study has provided an ecologically relevant data set on seasonal population dynamics representative of shallow freshwater ecosystems, which can be used to test and refine population models for use in chemical risk assessment and ecosystem management. Integr Environ Assess Manag 2022;18:1375–1386. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). John Wiley and Sons Inc. 2021-12-03 2022-09 /pmc/articles/PMC9545951/ /pubmed/34755447 http://dx.doi.org/10.1002/ieam.4553 Text en © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Health & Ecological Risk Assessment Arts, Gertie H. P. van Smeden, Jasper Wolters, Marieke F. Belgers, J. Dick M. Matser, Arrienne M. Hommen, Udo Bruns, Eric Heine, Simon Solga, Andreas Taylor, Seamus Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title | Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title_full | Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title_fullStr | Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title_full_unstemmed | Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title_short | Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
title_sort | seasonal dynamics of the macrophyte test species myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment |
topic | Health & Ecological Risk Assessment |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545951/ https://www.ncbi.nlm.nih.gov/pubmed/34755447 http://dx.doi.org/10.1002/ieam.4553 |
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