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. 2020 Oct 28;10(1):18467.
doi: 10.1038/s41598-020-74948-3.

Increasing temperatures accentuate negative fitness consequences of a marine parasite

Affiliations

Increasing temperatures accentuate negative fitness consequences of a marine parasite

Sean C Godwin et al. Sci Rep. .

Abstract

Infectious diseases are key drivers of wildlife populations and agriculture production, but whether and how climate change will influence disease impacts remains controversial. One of the critical knowledge gaps that prevents resolution of this controversy is a lack of high-quality experimental data, especially in marine systems of significant ecological and economic consequence. Here, we performed a manipulative experiment in which we tested the temperature-dependent effects on Atlantic salmon (Salmo salar) of sea lice (Lepeophtheirus salmonis)-a parasite that can depress the productivity of wild-salmon populations and the profits of the salmon-farming industry. We explored sea-louse impacts on their hosts across a range of temperatures (10, 13, 16, 19, and 22 °C) and infestation levels (zero, 'low' (mean abundance ± SE = 1.6 ± 0.1 lice per fish), and 'high' infestation (6.8 ± 0.4 lice per fish)). We found that the effects of sea lice on the growth rate, condition, and survival of juvenile Atlantic salmon all worsen with increasing temperature. Our results provide a rare empirical example of how climate change may influence the impacts of marine disease in a key social-ecological system. These findings underscore the importance of considering climate-driven changes to disease impacts in wildlife conservation and agriculture.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Growth rates of Atlantic salmon post-smolts as a function of infestation level and temperature. The points depict observed growth rates (jittered by infestation level for visualization purposes) and the lines describe the mean predictions from the top linear mixed-effects model (with 95% bootstrapped confidence intervals).
Figure 2
Figure 2
Condition of Atlantic salmon post-smolts at the end of the experiment relative to the start. The points represent observed change-in-condition values (jittered by infestation level for visualization purposes) and the lines give the mean predictions from the top change-in-condition model (with bootstrapped 95% confidence intervals) across the range of experimental temperatures for each of the three infestation levels.
Figure 3
Figure 3
Survival curves for Atlantic salmon post-smolts across three infestation levels and five temperatures. In total, there were 82 mortalities during the experiment. The curves are constrained to the duration of the experiment, which differed among temperature treatments because sea-louse development rate increases with temperature. Since the statistical framework for generating survival curves from mixed-effects Cox models has yet to be developed, we show the survival curves from a basic Cox model with the same fixed effects as our top model.

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