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Parasites have the potential to severely reduce host reproductive success. However, the effects of endoparasites on reproductive success have not received the same amount of attention as the effects of parasites on host survival. We investigated the relationship between an avian endoparasite (gapeworm, Syngamus trachea) and both current and future reproductive success of female house sparrows (Passer domesticus) in a population on the coast of Helgeland, northern Norway. We found that the proportion of eggs in a nest that failed to develop into fledglings increased as the faecal parasitic egg count of the mothers increased. We also found that juvenile females with high numbers of parasitic eggs in their faeces had lower lifetime reproductive success as adults. However, we did not find a relationship between maternal parasite infection and clutch size or recruitment rate of offspring. To our knowledge this is the first study to find a relationship between reproductive success of an avian host and faecal egg count of an endoparasite. The present study indicates that infection by an endoparasite may be associated with lower individual reproductive success in both the short-term and long-term in a wild population of hosts. [ABSTRACT FROM AUTHOR]

Parasitic salmon lice are potentially harmful to salmonid hosts and farm produced lice pose a threat to wild salmonids. To control salmon lice infections in Norwegian salmonid farming, numbers of lice are regularly counted and lice abundance is reported from all salmonid farms every month. We have developed a stochastic space-time model where monthly lice abundance is modelled simultaneously for all farms. The set of farms is regarded as a network where the degree of contact between farms depends on their seaway distance. The expected lice abundance at each farm is modelled as a function of i) lice abundance in previous months at the same farm, ii) at neighbourhood farms, and iii) other, unspecified sources. In addition, the model includes explanatory variables such as seawater temperature and farm-numbers of fish. The model gives insight into factors that affect salmon lice abundance and contributing sources of infection. New findings in this study were that 66% of the expected salmon lice abundance was attributed to infection within farms, 28% was attributed to infection from neighbourhood farms and 6% to non-specified sources of infection. Furthermore, we present the relative risk of infection between neighbourhood farms as a function of seaway distance, which can be viewed as a between farm transmission kernel for salmon lice. The present modelling framework lays the foundation for development of future scenario simulation tools for examining the spread and abundance of salmon lice on farmed salmonids under different control regimes. [ABSTRACT FROM AUTHOR]