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Relationship Between Salmon And Tree

Naiman and Helfield have been studying pacific salmon (Onchorhyncus spp.) in Alaskan rivers. They exploited chemical differences between the nitrogen in marine and freshwater environments to trace the origin of nutrients in forests bordering the streams.

relationship between salmon and tree

Side-by-side with salmon, Sitka spruce (Picea sitchensis), for example, take 86 years, rather than their usual 300 to reach 50 cm thick. One might even infer past salmon populations from the nitrogen in tree rings, Naiman believes.

Studies of fish-eating animals had shown that salmon transport marine nitrogen upstream, says freshwater ecologist Alan Hildrew, of Queen Mary and Westfield College, London, UK. Its effect on trees is another piece of the picture.

But, he adds, from a study of only two rivers it is difficult to know whether nutrients from salmon make the land around the river more fertile, or whether more fertile rivers attract salmon. "There might be some intrinsic difference between sites that have salmon and sites that don't," he points out.

Following the biorhythm of the bears, he began staying up all night and sleeping by day. He determined that under cover of darkness, six bears were working the stream for the biblical 40 days and 40 nights of the salmon run. As he watched them methodically hauling fish after fish into the deep bush, he conceived a whole new understanding of the flow of life between the land and the sea.

As the bodies of spawning salmon break down, nitrogen, phosphorus and other nutrients become available to streamside vegetation. According to Robert Naiman of the University of Washington, streamside vegetation gets just under 25 percent of its nitrogen from salmon. Other researchers report up to 70 percent of the nitrogen found in riparian zone foliage comes from salmon. One study concludes that trees on the banks of salmon-stocked rivers grow more than three times faster than their counterparts along salmon-free rivers and, growing side by side with salmon, Sitka spruce take 86 years, rather the usual 300 years, to reach 50 cm thick.

Scientists have long known that nitrogen content in a tree can be measured from its growth rings, and several research projects explore the link between nitrogen, tree rings and the size of past salmon runs. Using an increment borer, researchers extract small pencil-shaped samples of wood from the cores of ancient trees. The cross section of growth rings in core samples is then measured to determine nitrogen content. Sources of soluble nitrogen, as are found in sap residues, are removed to ensure an accurate determination of marine-derived nitrogen at the time of ring formation.

So next time you enjoy a good salmon dinner, thank a tree. If you are lucky enough to encounter an ancient monarch like a huge Sitka spruce while hiking along an emerald stream bank, thank a fish as well!

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.

Ecological linkages between marine and terrestrial communities are important processes structuring coastal ecosystems. One of the most geographically broad linkages that has received increased attention in recent decades is the role of migrating salmon (Oncorhynchus spp.) to coastal watersheds [1]. In addition to the contribution of salmon carcasses to primary productivity in lakes and streams [2, 3], salmon also comprise a substantial component of the diet in a diversity of marine and terrestrial taxa including pinnipeds and bears as well as an extensive history of use by First Nations [4]. Despite the increased attention and numerous publications, there remains ambiguity and large knowledge gaps regarding the relationship between salmon and receiving ecosystems.

The ecological consequences of salmon-derived nutrients to riparian vegetation include increased plant growth rates [17, 18], enrichment of foliar nitrogen [8, 10, 14] and altered plant community diversity [8, 10, 19]. Because nitrogen is often a limiting nutrient in temperate forests of the Pacific Northwest [20], it is possible that short and/or long term differences in salmon returns to spawning rivers would co-vary with primary productivity in the riparian zone and if so, annual growth rings of these old-growth trees might contain historical information on relative abundance of salmon. The recent identification of nitrogen isotopes in small quantities of wood from individual tree rings [9] offers an additional direct assessment of the isotopic enrichment of marine-derived nutrients over time [21].

In this study, our objectives are to: 1) characterize the spatial pattern of annual growth (tree ring width) and nitrogen isotopic signatures (δ15N) in trees across replicated gradients of salmon carcass densities, 2) identify the temporal signatures (1947-2000) of radial growth and nitrogen isotope signatures in relation to known yearly salmon escapement and 3) assess the predictors of both tree ring growth (index) and δ15N levels using an information theoretics approach that relies on general linear mixed models (GLMMs). Potential predictors of growth and δ15N values in annual tree rings included environmental (temperature, precipitation and salmon abundance), spatial (distance into forest and distance upstream) and total nitrogen as variables. Our replicated transects perpendicular to the stream channel across sharp gradients in carcasses and throughout the length of the stream along a broad range of salmon spawning densities allowed multiple paired comparisons of growth and nitrogen isotope signatures of trees. Although not directly exploring the use of tree ring data as a proxy for historical salmon abundance in this study, our results are useful for evaluating tree ring growth and δ15N values as potential proxies.

Each spruce was cored at breast height using a 1.2 cm 40 cm increment borer, measured for diameter at breast height (dbh) and distance from the stream and distance upstream from the estuary. Presence or absence of salmon carcass remnants around the base of the tree ( 5 m radius) was recorded. Cores were oven dried at 60oC for at least four weeks, mounted on plastic sheaths, sanded with fine-grade sandpaper and digitally scanned. Images of cores were used to individually measure tree ring widths to the nearest 0.001 mm using Coorecorder ( ) with problematic rings visually assessed under a dissecting microscope. Tree ring series were crosschecked for accuracy using default settings in COFECHA [26]. Individual tree ring series were then fitted to a single smoothing spline with a 50% frequency cutoff of 100 years, a procedure that removes age-related growth trends in individual series, using the program ARSTAN [27]. The use of a 100-year spline as opposed to the default 32-year spline is that mid to high frequency variations are retained in trends less than 100 years and long-term growth related trends are removed (e.g. [18]). We refer to this metric as the ARSTAN-modified growth index or growth index in subsequent analyses.

Temporal data included salmon abundance (escapement) data for Bag Harbour (1947-2000; Fisheries and Oceans Canada) modified using a three-year running average from the previous three years. This three-year average with a one-year lag [28] was used as a conservative temporal estimate of potential salmon nutrient input. Precipitation and temperature data were obtained from nearby Sandspit for the majority of years, with data from Tlell or alternatively Masset used when Sandspit data were not available (Environment Canada National Climate Data and Information Archive, ). Total precipitation and mean maximum monthly temperature data were generated from September in the previous growth year to October of the growth year for any given tree ring, as these periods more closely reflect the biological year [29, 30].

We assessed the influence of salmon abundance and other potential predictors on tree growth using the ARSTAN-modified growth index and δ15N isotopic enrichment separately, using an information theoretics approach. Predictors were selected due to their availability but most importantly, their possible influence on tree growth and δ15N values. For both model sets, response variables were first examined with all potential predictor variables to determine the nature of the potential relationship. Predictor variables were also examined for collinearity. Statistical analyses were performed using SPSS v.20 (IBM, USA).

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