DOI: 10.5061/dryad.tmpg4f4v6
title: Noise pollution: acute noise exposure increases susceptibility to disease and chronic exposure reduces host survival

description: Anthropogenic noise is a pervasive global pollutant that has been detected
 in every major habitat on the planet. Detrimental impacts of noise
 pollution on physiology, immunology and behaviour have been shown in
 terrestrial vertebrates and invertebrates. Equivalent research on aquatic
 organisms has until recently been stunted by the misnomer of a silent
 underwater world. In fish, however, noise pollution can lead to stress,
 hearing loss, behavioural changes and impacted immmunity. But, the
 functional effects of impacted immunity on disease resistance due to noise
 exposure have remained neglected. Parasites that cause transmissible
 disease are key drivers of ecosystem biodiversity and a significant factor
 limiting the sustainable expansion of the animal trade. Therefore,
 understanding how a pervasive stressor is impacting host-parasite
 interactions will have far reaching implications for global animal
 health.   Here, we investigated the impact of acute and
 chronic noise on vertebrate susceptibility to parasitic infections, using
 a model host-parasite system (guppy-Gyrodactylus turnbulli). Hosts
 experiencing acute noise suffered significantly increased parasite burden
 compared to those in no noise treatments. In contrast, fish experiencing
 chronic noise had the lowest parasite burden. However, these hosts died
 significantly earlier compared to those exposed to acute and no noise
 treatments, demonstrating a potential functional trade-off between
 improved parasite-resistance and shorter life span. By revealing the
 detrimental impacts of acute and chronic noise on host-parasite
 interactions, we add to the growing body of evidence demonstrating a link
 between noise pollution and reduced animal health. 
description: All statistical analyses were conducted using RStudio v2.1. Peak
 parasite burden is the maximum number of parasites at a given time point,
 defined here as peak day. To quantify total infection trajectory over the
 17 days, we calculated Area Under the Curve (AUC) using the trapezoid
 rule. To analyse peak parasite burden, peak day and AUC we used a
 Generalised Linear Model (GLM) with a negative binomial error family and a
 log link function in the R MASS package. A GLM with poisson error family
 and log link function was utilized for analyzing death day. All GLM error
 families were chosen based on the lowest dispersion parameter, theta. A
 Generalised Linear Mixed Model (GLMM) with a negative binomial error
 family and log link function was used to analyze intrinsic rate of
 parasite increase. Fish ID was treated as a random factor to prevent
 pseudoreplication in our GLMM as parasite intensity was recorded for each
 fish at different time points. Standard length, day and noise treatment
 (chronic and acute) were treated as fixed factors. As experimental fish
 were placed in n=6 (acute treatment) and n=7 (chronic treatment) tanks,
 tank number was also treated as a fixed factor to rule out batch
 effect. For all models used in analysis, no batch effect was found for
 either noise exposure treatments (P&gt; 0.05 for all models). All
 models stated above were chosen based on the lowest Akaike’s information
 criterion (AIC) value. A Chi-squared test was used to analyse host
 mortality for all treatments.