Stable isotopes are increasingly being used as
tracers of ecological processes potentially providing relevant
information to environmental management issues. An application
of the methodology consists in relating the stable
isotopic composition of a sample mixture to that of sources.
The number of stable isotopes, however, is usually lower
than that of potential sources existing in an ecosystem, which
creates mathematical difficulties in correctly tracing sources.
We discuss a linear programming model which efficiently
derives information on the contribution of sources to mixtures
for any number of stable isotopes and any number of
sources by addressing multiple sources simultaneously. The
model identifies which sources are present in all, present in
a subset of the samples or absent from all samples simultaneously
and calculates minimum and maximum values of
each source in the mixtures. We illustrate the model using a
data set consisting of the isotopic signatures of different plant
sources ingested by primary consumers in tropical riverine
habitat in Asia. The model discussed may contribute to extend
the scope of stable isotopes methodology to a range
of new problems dealing with multiple sources and multiple
tracers. For instance, in food web studies, if particular
organic matter sources disappear or decrease in availability
(e.g. climate change scenarios) the model allows simulation
of alternative diets of the consumers providing potentially
relevant information for managers and decision makers