Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management
Context: Sea lice are the most significant parasitic problem affecting wild and farmed salmon. Larval lice released from infected fish in salmon farms and their transport by water masses results in inter-farm networks of lice dispersal. Understanding this parasite connectivity is key to its control...
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ftdeakinunifig:oai:figshare.com:article/20812168 2024-06-23T07:51:25+00:00 Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management F Samsing I Johnsen Tim Dempster F Oppedal Eric Treml 2017-10-01T00:00:00Z http://hdl.handle.net/10536/DRO/DU:30107450 https://figshare.com/articles/journal_contribution/Network_analysis_reveals_strong_seasonality_in_the_dispersal_of_a_marine_parasite_and_identifies_areas_for_coordinated_management/20812168 unknown http://hdl.handle.net/10536/DRO/DU:30107450 https://figshare.com/articles/journal_contribution/Network_analysis_reveals_strong_seasonality_in_the_dispersal_of_a_marine_parasite_and_identifies_areas_for_coordinated_management/20812168 All Rights Reserved Environmental management not elsewhere classified Connectivity Spatial epidemiology Cluster analysis Sea lice Lepeophtheirus salmonis Disease management Science & Technology Life Sciences & Biomedicine Physical Sciences Ecology Geography Physical Geosciences Multidisciplinary Environmental Sciences & Ecology Physical Geography Geology LEPEOPHTHEIRUS-SALMONIS KROYER FARMED ATLANTIC SALMON POPULATION CONNECTIVITY SALAR L LANDSCAPE CONNECTIVITY EPIDEMIOLOGIC PATTERNS GRAPH-THEORY WEST-COAST WILD School of Life and Environmental Sciences 4102 Ecological applications Text Journal contribution 2017 ftdeakinunifig 2024-06-06T02:13:39Z Context: Sea lice are the most significant parasitic problem affecting wild and farmed salmon. Larval lice released from infected fish in salmon farms and their transport by water masses results in inter-farm networks of lice dispersal. Understanding this parasite connectivity is key to its control and effective management. Objectives: Quantify the spatial and seasonal patterns in sea lice (Lepeophtheirus salmonis) dispersal in an area with intensive salmon farming. Identify emergent clusters in the network, where associated salmon farms could be used for coordinated management and spatial planning of the industry. Methods: We used a biophysical model to simulate lice dispersal from 537 salmon farms along the Norwegian coastline for two seasons (spring and winter) from 2009 to 2014. We used network analysis to characterize dispersal pathways and quantify the spatial and temporal patterns in connectivity. Results: Lice dispersal patterns and network metrics varied greatly between seasons, but differences were consistent amongst years. Winter networks presented more connections, and links were on average two times longer (average winter median = 36.5 ± 7.6 km, mean ± SE; average spring median = 17.8 ± 1.7 km). We identified 12 emergent farm clusters, which were similar across seasons and with the production areas for salmon aquaculture proposed by the Norwegian government. Conclusions: Seasonal variations in lice development times, oceanographic processes and the topological arrangement of salmon farms affect lice dispersal patterns. We have identified a biologically meaningful and politically tractable alliance structure for sea lice management consisting of closely-associated clusters of farms. Article in Journal/Newspaper Atlantic salmon DRO - Deakin Research Online |
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Open Polar |
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DRO - Deakin Research Online |
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ftdeakinunifig |
language |
unknown |
topic |
Environmental management not elsewhere classified Connectivity Spatial epidemiology Cluster analysis Sea lice Lepeophtheirus salmonis Disease management Science & Technology Life Sciences & Biomedicine Physical Sciences Ecology Geography Physical Geosciences Multidisciplinary Environmental Sciences & Ecology Physical Geography Geology LEPEOPHTHEIRUS-SALMONIS KROYER FARMED ATLANTIC SALMON POPULATION CONNECTIVITY SALAR L LANDSCAPE CONNECTIVITY EPIDEMIOLOGIC PATTERNS GRAPH-THEORY WEST-COAST WILD School of Life and Environmental Sciences 4102 Ecological applications |
spellingShingle |
Environmental management not elsewhere classified Connectivity Spatial epidemiology Cluster analysis Sea lice Lepeophtheirus salmonis Disease management Science & Technology Life Sciences & Biomedicine Physical Sciences Ecology Geography Physical Geosciences Multidisciplinary Environmental Sciences & Ecology Physical Geography Geology LEPEOPHTHEIRUS-SALMONIS KROYER FARMED ATLANTIC SALMON POPULATION CONNECTIVITY SALAR L LANDSCAPE CONNECTIVITY EPIDEMIOLOGIC PATTERNS GRAPH-THEORY WEST-COAST WILD School of Life and Environmental Sciences 4102 Ecological applications F Samsing I Johnsen Tim Dempster F Oppedal Eric Treml Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
topic_facet |
Environmental management not elsewhere classified Connectivity Spatial epidemiology Cluster analysis Sea lice Lepeophtheirus salmonis Disease management Science & Technology Life Sciences & Biomedicine Physical Sciences Ecology Geography Physical Geosciences Multidisciplinary Environmental Sciences & Ecology Physical Geography Geology LEPEOPHTHEIRUS-SALMONIS KROYER FARMED ATLANTIC SALMON POPULATION CONNECTIVITY SALAR L LANDSCAPE CONNECTIVITY EPIDEMIOLOGIC PATTERNS GRAPH-THEORY WEST-COAST WILD School of Life and Environmental Sciences 4102 Ecological applications |
description |
Context: Sea lice are the most significant parasitic problem affecting wild and farmed salmon. Larval lice released from infected fish in salmon farms and their transport by water masses results in inter-farm networks of lice dispersal. Understanding this parasite connectivity is key to its control and effective management. Objectives: Quantify the spatial and seasonal patterns in sea lice (Lepeophtheirus salmonis) dispersal in an area with intensive salmon farming. Identify emergent clusters in the network, where associated salmon farms could be used for coordinated management and spatial planning of the industry. Methods: We used a biophysical model to simulate lice dispersal from 537 salmon farms along the Norwegian coastline for two seasons (spring and winter) from 2009 to 2014. We used network analysis to characterize dispersal pathways and quantify the spatial and temporal patterns in connectivity. Results: Lice dispersal patterns and network metrics varied greatly between seasons, but differences were consistent amongst years. Winter networks presented more connections, and links were on average two times longer (average winter median = 36.5 ± 7.6 km, mean ± SE; average spring median = 17.8 ± 1.7 km). We identified 12 emergent farm clusters, which were similar across seasons and with the production areas for salmon aquaculture proposed by the Norwegian government. Conclusions: Seasonal variations in lice development times, oceanographic processes and the topological arrangement of salmon farms affect lice dispersal patterns. We have identified a biologically meaningful and politically tractable alliance structure for sea lice management consisting of closely-associated clusters of farms. |
format |
Article in Journal/Newspaper |
author |
F Samsing I Johnsen Tim Dempster F Oppedal Eric Treml |
author_facet |
F Samsing I Johnsen Tim Dempster F Oppedal Eric Treml |
author_sort |
F Samsing |
title |
Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
title_short |
Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
title_full |
Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
title_fullStr |
Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
title_full_unstemmed |
Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
title_sort |
network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management |
publishDate |
2017 |
url |
http://hdl.handle.net/10536/DRO/DU:30107450 https://figshare.com/articles/journal_contribution/Network_analysis_reveals_strong_seasonality_in_the_dispersal_of_a_marine_parasite_and_identifies_areas_for_coordinated_management/20812168 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
http://hdl.handle.net/10536/DRO/DU:30107450 https://figshare.com/articles/journal_contribution/Network_analysis_reveals_strong_seasonality_in_the_dispersal_of_a_marine_parasite_and_identifies_areas_for_coordinated_management/20812168 |
op_rights |
All Rights Reserved |
_version_ |
1802642526432133120 |