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Understanding how nutrients flow through food webs is central in ecosystem
ecology. Tracer addition experiments are powerful tools to reconstruct
nutrient flows by adding an isotopically enriched element into an
ecosystem, and tracking its fate through time. Historically, the design
and analysis of tracer studies have varied widely, ranging from
descriptive studies to modeling approaches of varying complexity.
Increasingly, isotope tracer data is being used being used to compare
ecosystems and analyze experimental manipulations. Currently, a formal
statistical framework for analyzing such experiments is lacking, making it
impossible to calculate the estimation errors associated with the model
fit, the interdependence of compartments, or the uncertainty in the diet
of consumers. In this paper we develop a method based on Bayesian Hidden
Markov Models, and apply it to the analysis of $^{15}$N-NH$_4^+$ tracer
additions in two Trinidadian streams in which light was experimentally
manipulated. Through this case study, we illustrate how to estimate N
fluxes between ecosystem compartments, turnover rates of N within those
compartments and the associated uncertainty. We also show how the method
can be used to compare alternative models of food web structure, calculate
the error arround derived parameters, and make statistical comparisons
between sites or treatments.
368 views reported since publication in 2020.