Noise pollution: acute noise exposure increases susceptibility to disease and chronic exposure reduces host survival
Cite this dataset
Masud, Numair; Hayes, Laura; Crivelli, Davide; Cable, Jo (2020). Noise pollution: acute noise exposure increases susceptibility to disease and chronic exposure reduces host survival [Dataset]. Dryad. https://doi.org/10.5061/dryad.tmpg4f4v6
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.
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> 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.