Avian influenza antibody prevalence increases with mercury contamination in wild waterfowl

Abstract

Environmental contamination is widespread and can negatively impact wildlife health. Some contaminants, including heavy metals, have immunosuppressive effects, but prior studies have rarely measured contamination and disease simultaneously, which limits our understanding of how contaminants and pathogens interact to influence wildlife health. Here, we measured mercury concentrations, influenza infection, influenza antibodies and body condition in 749 individuals from 11 species of wild ducks overwintering in California. We found that the odds of prior influenza infection increased more than fivefold across the observed range of blood mercury concentrations, while accounting for species, age, sex and date. Influenza infection prevalence was also higher in species with higher average mercury concentrations. We detected no relationship between influenza infection and body fat content. This positive relationship between influenza prevalence and mercury concentrations in migratory waterfowl suggests that immunotoxic effects of mercury contamination could promote the spread of avian influenza along migratory flyways, especially if influenza has minimal effects on bird health and mobility. More generally, these results show that the effects of environmental contamination could extend beyond the geographical area of contamination itself by altering the prevalence of infectious diseases in highly mobile hosts.

Keywords: avian influenza; body condition; duck; environmental contaminant; mercury; wildlife health.

Figure 1.

Hypothesized and predicted relationships among mercury concentrations, body condition, active infection and antibody detection. Dashed blue arrows represent negative relationships between variables and solid orange arrows represent positive relationships. Grey ovals are variables that are important mechanistically but were not measured directly in this study. In pathway A, MeHg immunotoxicity compromises the innate immune response to infection, leading to a higher probability of active infection, more antibody production and an increased probability of antibody detection. In B, MeHg immunotoxicity compromises the adaptive immune response, reducing antibody detection but increasing the probability of active infection. In C, MeHg toxicity reduces host body condition, reducing the energy available to mount an immune response and increasing infection probabilities. In pathway D, MeHg toxicity reduces host body condition, altering physiologic conditions for viral replication and decreasing the probabilities of both active infection and antibody detection. Feedbacks complicate these relationships, including disease-induced reductions in body condition following influenza infection and effects of body condition on MeHg concentrations (due to concentrating of body MeHg with mass loss). (Online version in colour.)

Figure 2.

Species-level relationships between influenza prevalence and average blood mercury concentration. Points and error bars show geometric mean and standard error for each variable in raw data. Black lines show the fitted relationship from univariate GLMs; shaded areas show 95% CIs. Note the log scale of the x-axis. (a) Antibody prevalence increases with blood mercury concentrations (β = 0.198, p = 0.013). (b) There is little evidence that infection prevalence increases with blood mercury concentrations (β = 0.140, p = 0.190). (Online version in colour.)

Figure 3.

The probability of prior influenza infection increases with blood mercury concentrations. Lines show mean predictions and shaded areas show 85% CIs of predictions in early (16 October–10 December), mid (11 December–2 February) and late (3 February–16 March) winter. Points show raw data (i.e. points at bottom are birds without antibodies; points at top are birds with antibodies). Prediction lines for each panel are based on parameters for 16 October, 1 January and 16 March, respectively, and extend only within the observed range of mercury values for each age class and date. Lines show predicted values for a male northern pintail and all other variables held at their mean values across the dataset, but points for all individuals are shown. For 95% CIs, see electronic supplementary material, figure S2. (Online version in colour.)