Successful invasive species increase their spreading success by trading-off nutritional and metabolic resources allocated to reproduction and range expansion with other costly body functions. One proposed mechanism for the reallocation of resources is a trade-off with the immune function and the regulation of oxidative status. Relying on a panel of blood-based markers of immune function and oxidative status quantified in an invasive species (Egyptian goose) and two native competing species (mallard and mute swan) in Germany, we tested the hypothesis that the invasive species would have (i) lower investment in immune function, (ii) lower levels of oxidative damage, and (iii) no higher antioxidant defences compared to the native species. We found lower levels of adaptive immune markers (lymphocytes and immunoglobulin Y), in the invasive species compared to the two native species. Innate immune profile was generally similar between Egyptian geese and mallards. By contrast, mute swans showed higher levels of heterophils and lysozymes, and lower levels of bacteria killing ability compared to both Egyptian geese and mallards. Mute swans also showed higher levels of haemolysis and haemagglutination, but lower levels of monocytes and haematocrit compared to Egyptian geese. Reactive oxygen metabolites, a marker of oxidative damage, were higher in mallards and lower in Egyptian geese compared to the other waterfowl species, while levels of antioxidants were generally similar among the three species. Our results point to a reduced investment in adaptive immune function in the invasive species as a possible resources-saving immunological strategy due to the loss of co-evolved parasites in the new colonised habitats, as observed in a previous study. A lower investment in immune function may benefit other energy-demanding activities, such as reproduction, dispersal, and territoriality, while maintaining relatively higher innate immunity is beneficial since invasive species mainly encounter novel pathogens. Results pointed out also other important species-specific differences in baseline immune status, supporting previous findings on the relationship between species’ body mass and immune profile.

Adult individuals of the study species were live-trapped in June and July 2016 in the Rhine and Mosel area in Western Germany (50.4° N, 7.6° E; Fig. S1). All individuals in this study were locally breeding and mostly in the phase of guiding goslings/ducklings at the time of sampling. Birds were caught using either loops or landing nets. Each bird was individually ringed, and body mass and sex were recorded. A blood sample from each bird was collected, either from the vena metatarsalia plantaris superficialis or the vena ulnaris, using a needle of 0.06 mm diameter. Blood samples were kept cool during field procedures, then centrifuged for 15 minutes to separate plasma from red blood cells which were stored separately in liquid nitrogen within 8 hours from blood collection. At the end of fieldwork, samples were stored at -80 °C until laboratory analyses.

The dataset included 74 actively reproducing individuals of which 28 were Egyptian geese, 10 were mallards, and 36 were mute swans. We collected blood samples from both female and male Egyptian geese (females = 12; males = 16) and mute swans (females = 21; males = 15), and only female mallards (Table 1).

We performed generalized linear models (GLMs) to assess the differences between species for each single marker. Therefore, for each model, we included one marker as a dependent variable and species as an independent variable. Family distribution of the models was chosen according to the nature of the data: quasibinomial distribution for proportion data, quasipoisson distribution for discrete data, gaussian or gamma for continuous non-negative data. We checked for normal distribution of residuals by means of Q-Q plots. If the distribution of model residuals was not normal, we log-transformed the dependent variables after which we performed again the model diagnostics. We also screened the models for the presence of outliers relying on the Cook’s distance with a fixed threshold of 0.25. When we detected outliers, we removed them and re-run the model.

Subsequently, we implemented GLMs testing for the interaction between species and sex on a subset of the original dataset including only Egyptian geese and mute swan (the mallard was excluded because we sampled only females). Following the previous procedures, we removed outliers when detected, we log-transformed the data when necessary; we performed the model diagnostics by visual inspection of Q-Q plots. We explored the effect of interactions by likelihood ratio tests run for each GLM.

Finally, to evaluate the robustness of our results, we compared standardized effect sizes between species, also including comparisons between same sex individuals, for each immune-physiological marker. Standardized effect sizes are analytical tools that enable to compare the magnitude and the direction of a biological effect (Garamszegi, 2006). We used means, standard deviations and sample sizes of immune-physiological markers of each species to calculate Hedges’ g effect sizes, which is a measure of how much one group differs from another one, accounting for small sample sizes (Cooper et al., 2009). We displayed effect sizes in forest plots comparing pairs of species by means of the forest function of the package metafor in R. We calculated the effect sizes and their confidence intervals in R using the compute.es package. The effect size is significant when the confidence interval does not include zero.