Abstract
ABSTRACTAimWe apply a novel approach in a spatial network context to identify factors influencing a parasite–host system and to distinguish focal areas for conservation of interacting species.LocationTwenty river networks in southern Europe (Spain)MethodsSpatial stream network (SSN) models were applied to analyse and predict density and biomass of interacting species in river networks. Density of an endangered freshwater mussel (parasite) and biomass data of its host fish were response variables for models with fixed‐effect biotic and abiotic predictors and three random effect models for spatial covariance. Universal kriging with the SSN models was used to obtain predictions for parasite density and host biomass for the entire study region.ResultsSpatial stream network (SSN) models fitted separately for parasite density and host biomass explained 75% and 77% of the variance, respectively. Predictors explained 5% of the variance for the parasite and 14% for the host. Host biomass was the most important predictor of parasite density. The tail‐up and tail‐down spatial covariances fitted to the residual variance explained more than a half of the total variance in both models. Significant biotic and abiotic predictors differed between the parasite and host models. Combining model predictions for parasite density and host biomass identified areas where different strategies might be employed to conserve biotic interactions.Main conclusionsConservation of biotic interactions requires consideration of respective ecologies of the interacting species. In a network environment, connectivity of habitats can be an important determinant for occurrence of biotic interactions. Spatially explicit analyses, such as the SSN, can identify focal areas for conservation of biotic interactions. Conservation focused on biotic interactions, as opposed to a single species, could yield benefits to the focal species, the biotic community with which they occur and the ecosystem that supports them.
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