Salmon lice dispersion in a northern Norwegian fjord system and the impact of vertical movements

Abstract

The abundance and distribution of salmon lice Lepeophtheirus salmons originating from fish farms in a northern Norwegian fjord during the summer of 2010 was investigated by means of a numerical model, underpinned by field observations. In order to evaluate the robust-ness of the simulated distribution of the lice, we reran the simulation several times, changing the vertical responses of the lice to environmental cues such as light and turbulence, in addition to altering their vertical swimming velocity. The model was able to realistically reproduce the observed currents and stratification in the region. The simulated distribution of lice was not sensitive to different implementations of surface light nor to the light sensitivity level of the lice. However , the vertical swimming velocity and a mixing parameter influenced both their vertical distribution and horizontal dispersion. The aggregation of lice along land was influenced by their response to turbulent water. The simulated infectious stages of the lice were transported on average 20 to 45 km from their release site. The simulated concentrations of infectious lice varied in synchronisation with lice infestations observed on wild fish in the area. Less than 1% of the simulated lice reached a farm site. The ratio between internal and external exposure ranged from 7 to 57%. Farms in the north of the fjord system were more exposed to lice released in the south than vice versa. KEY WORDS: Salmon lice · Lepeophtheirus salmonis · Dispersion · Fjord · Aquaculture management · IBM · Model

Toward a model-based prediction system for salmon lice infestation pressure

“…In our study, we assumed that the infestation levels (abundance) found on the smolt are linked to the modeled salmon lice densities through a linear relationship. Our results indicate that this is a reasonable assumption and is also in accordance with results of Johnsen et al (2016). Although it has been shown that factors like the age of the lice, the water temperature, the current speed, the light conditions, turbulence, the water salinity, etc., influence the infestation process (Bricknell et al 2006, Samsing et al 2014), a complete understanding is still not established.…”

“…However, using a newer neighboring verification method (Ebert 2008), it was possible to demonstrate the potential of the model in the sense that the observed infestation levels are a possible projection from the model within a slight shift in space. The results are in accordance with the findings of Johnsen et al (2016), who tested the model system in a northern Norwegian fjord system (the Folda fjord system). The main finding in their paper was that the simulated densities of infective salmon lice varied in synchronization with lice infestations observed on wild sea trout.…”

“…A number of studies have shown that 'particles' transported in the ocean rarely constitute smooth continuous fields but rather establish patchy patterns with strong gradients, increasing the difficulty of comparison (Mackas et al 1985), and this is also the case in our study (e.g. Johnsen et al 2016). Therefore, we have taken ad vantage of the comprehensive experience of newer model verification methods established in atmospheric science, where e.g.…”

Nearby farms are a source of lice for wild salmonids: a reply to Jansen et al. (2016)

“…Helland et al (2015) and Thorstad et al (2015) strongly suggest the transmission of lice from farm salmon to wild salmonids in systems where the fish occur in close vicinity. Future similar analyses should use available hydrodynamic-biological dispersal models , Johnsen et al 2016 to get a better estimate of the lice infestation pressure imposed by fish farms in different parts of the fjord systems along the Norwegian coast. …”

Effect of exposure on salmon lice Lepeophtheirus salmonis population dynamics in Faroese salmon farms

“…The growth of a sea lice population has an exponential nature (Frazer et al 2012) and is generally modelled as such (Costello 2006, Krkošek et al 2010, Frazer et al 2012. Several dispersion models have been developed which assume that the planktonic stages of the sea lice drift freely with prevailing currents close to the surface (Amundrud & Murray 2009, Adams et al 2012, Salama et al 2013, with recent works including vertical positioning as a response to environmental cues (Johnsen et al , 2016. Sea temperature is widely accepted as a basic factor influencing the growth rate of sea lice populations, as the generation time decreases with increasing temperature (Tully 1992, Heuch et al 2000.…”