The marine-terrestrial transfer of salmon (Oncorhynchus spp.) provides a substantial pulse of nutrients to receiving ecosystems along the Pacific coast of North America and has been shown to enhance productivity and isotopic signatures of conifers and other riparian vegetation. An explicitly spatial, within-watershed investigation of the influence of salmon on conifers has never been previously investigated. In a small salmon-bearing watershed in Haida Gwaii, Canada, the transfer and distributional pattern of salmon carcasses into the riparian zone by black bears provided a spatial basis for investigating the influence of salmon on Sitka spruce tree ring growth and nitrogen isotopic signatures (δ15N) across a gradient of salmon carcass densities in relation to salmon escapement.
Annual growth was found to be highest in the high salmon carcass zone and δ15N signatures closely tracked the known distribution of salmon carcasses at distances into the forest and upstream. Tree diameter demonstrated a positive relationship with δ15N signatures for trees with and without salmon carcass influence. Using an information theoretics approach with general linear mixed models (GLMMs), we show that salmon abundance, mean annual temperature and the interaction terms salmon abundance*temperature and salmon abundance*distance into the forest best predict tree growth. In addition, spatial variables (distance into forest and upstream) and their interaction are the strongest predictors of δ15N signatures. However patterns observed in individual trees, particularly those at increased distance into the forest, suggest positive relationships with historical salmon abundance.
Using a replicated spatial sampling design across a sharp gradient in salmon nutrient loading, our study provides clear evidence that the temporal pattern in an allochthonous nutrient source and an interaction with temperature and spatial location influences conifer growth. Although salmon abundance has been previously linked to annual conifer growth and δ15N levels, our approach demonstrates the need to incorporate additional predictors including tree size and opens up the prospect of their dual use as historical proxies for salmon abundance.
