{"vid":"122863","uid":"0","title":"Interpretation of sea lice connectivity patterns among Scottish Farm Management Areas","log":"Created by FeedsNodeProcessor","status":"1","comment":"0","promote":"0","sticky":"0","ds_switch":"","nid":"19734","type":"data_source","language":"und","created":"1585336052","changed":"1585336052","tnid":"0","translate":"0","revision_timestamp":"1585336052","revision_uid":"0","body":{"und":[{"value":"
Scottish Marine and Freshwater Science Vol 11 No 4
\nClimatological (\u201caverage year\u201d) flow fields from the Scottish Shelf Model (SSM) have been used to estimate the degree of connectivity between Scottish finfish aquaculture Farm Management Areas (FMA) using off-line particle tracking simulations of virtual organisms (\u201cparticles\u201d) representing the infective phases of sea lice. The analysis carried out in this document is based on presence-absence of connections between FMAs as well as connection probabilities above a defined threshold. A weighting (relative to the consented biomass of farms within each FMA) was also applied to the probabilities to give a more realistic scenario.
Scottish Marine and Freshwater Science Vol 11 No 4
\nClimatological (\u201caverage year\u201d) flow fields from the Scottish Shelf Model (SSM) have been used to estimate the degree of connectivity between Scottish finfish aquaculture Farm Management Areas (FMA) using off-line particle tracking simulations of virtual organisms (\u201cparticles\u201d) representing the infective phases of sea lice. The analysis carried out in this document is based on presence-absence of connections between FMAs as well as connection probabilities above a defined threshold. A weighting (relative to the consented biomass of farms within each FMA) was also applied to the probabilities to give a more realistic scenario.