A Lagrangian particle-tracking approach to modelling larval drift in rivers
The migration of larval fish from spawning to rearing habitat in rivers is not well understood. This paper describes a methodology to predict larval drift using a Lagrangian particle-tracking (LPT) model with passive and active behavioural components loosely coupled to a quasi-three-dimensional hydr...
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ftdatacite:10.6084/m9.figshare.12286694 2023-05-15T15:47:15+02:00 A Lagrangian particle-tracking approach to modelling larval drift in rivers McDonald, Richard R. Nelson, Jonathan M. 2020 https://dx.doi.org/10.6084/m9.figshare.12286694 https://tandf.figshare.com/articles/journal_contribution/A_Lagrangian_particle-tracking_approach_to_modelling_larval_drift_in_rivers/12286694 unknown Taylor & Francis https://dx.doi.org/10.1080/24705357.2019.1709102 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Neuroscience Physiology FOS Biological sciences 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences Text article-journal Journal contribution ScholarlyArticle 2020 ftdatacite https://doi.org/10.6084/m9.figshare.12286694 https://doi.org/10.1080/24705357.2019.1709102 2021-11-05T12:55:41Z The migration of larval fish from spawning to rearing habitat in rivers is not well understood. This paper describes a methodology to predict larval drift using a Lagrangian particle-tracking (LPT) model with passive and active behavioural components loosely coupled to a quasi-three-dimensional hydraulic model. In the absence of measured larval drift, a heuristic approach is presented for the larval drift of two species of interest, white sturgeon ( Acipenser transmontanus ) and burbot ( Lota lota ), in the Kootenai River, Idaho. Previous studies found that many fish species prefer certain vertical zones within the water column; sturgeon tend to be found near the bottom and burbot close to the water surface. Limiting the vertical movement of larvae is incorporated into the active component of the LPT model. The results illustrate a pattern of drift where secondary flow in meander bends and other zones of flow curvature redistributes particles toward the outside of the bend for surface drifters and toward the inside of the bend for bottom drifters. This pattern periodically reinforces the intersection of drifting larvae with channel margins in meander bends. In the absence of measured larval drift data, the model provides a tool for hypothesis testing and a guide to both field and laboratory experiments to further define the role of active behaviour in drifting larvae. Text Burbot Lota lota lota DataCite Metadata Store (German National Library of Science and Technology) |
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Neuroscience Physiology FOS Biological sciences 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences |
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Neuroscience Physiology FOS Biological sciences 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences McDonald, Richard R. Nelson, Jonathan M. A Lagrangian particle-tracking approach to modelling larval drift in rivers |
topic_facet |
Neuroscience Physiology FOS Biological sciences 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences |
description |
The migration of larval fish from spawning to rearing habitat in rivers is not well understood. This paper describes a methodology to predict larval drift using a Lagrangian particle-tracking (LPT) model with passive and active behavioural components loosely coupled to a quasi-three-dimensional hydraulic model. In the absence of measured larval drift, a heuristic approach is presented for the larval drift of two species of interest, white sturgeon ( Acipenser transmontanus ) and burbot ( Lota lota ), in the Kootenai River, Idaho. Previous studies found that many fish species prefer certain vertical zones within the water column; sturgeon tend to be found near the bottom and burbot close to the water surface. Limiting the vertical movement of larvae is incorporated into the active component of the LPT model. The results illustrate a pattern of drift where secondary flow in meander bends and other zones of flow curvature redistributes particles toward the outside of the bend for surface drifters and toward the inside of the bend for bottom drifters. This pattern periodically reinforces the intersection of drifting larvae with channel margins in meander bends. In the absence of measured larval drift data, the model provides a tool for hypothesis testing and a guide to both field and laboratory experiments to further define the role of active behaviour in drifting larvae. |
format |
Text |
author |
McDonald, Richard R. Nelson, Jonathan M. |
author_facet |
McDonald, Richard R. Nelson, Jonathan M. |
author_sort |
McDonald, Richard R. |
title |
A Lagrangian particle-tracking approach to modelling larval drift in rivers |
title_short |
A Lagrangian particle-tracking approach to modelling larval drift in rivers |
title_full |
A Lagrangian particle-tracking approach to modelling larval drift in rivers |
title_fullStr |
A Lagrangian particle-tracking approach to modelling larval drift in rivers |
title_full_unstemmed |
A Lagrangian particle-tracking approach to modelling larval drift in rivers |
title_sort |
lagrangian particle-tracking approach to modelling larval drift in rivers |
publisher |
Taylor & Francis |
publishDate |
2020 |
url |
https://dx.doi.org/10.6084/m9.figshare.12286694 https://tandf.figshare.com/articles/journal_contribution/A_Lagrangian_particle-tracking_approach_to_modelling_larval_drift_in_rivers/12286694 |
genre |
Burbot Lota lota lota |
genre_facet |
Burbot Lota lota lota |
op_relation |
https://dx.doi.org/10.1080/24705357.2019.1709102 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.12286694 https://doi.org/10.1080/24705357.2019.1709102 |
_version_ |
1766382049083523072 |