Controlling for anthropogenically induced atmospheric variation in stable carbon isotope studies

Increased use of stable isotope analysis to examine food-web dynamics, migration, transfer of nutrients, and behavior will likely result in expansion of stable isotope studies investigating human-induced global changes. Recent elevation of atmospheric CO2 concentration, related primarily to fossil fuel combustion, has reduced atmospheric CO2 delta C-13 (C-13/C-12), and this change in isotopic baseline has, in turn, reduced plant and animal tissue delta C-13 of terrestrial and aquatic organisms. Such depletion in CO2 delta C-13 and its effects on tissue delta C-13 may introduce bias into delta C-13 investigations, and if this variation is not controlled, may confound interpretation of results obtained from tissue samples collected over a temporal span. To control for this source of variation, we used a high-precision record of atmospheric CO2 delta C-13 from ice cores and direct atmospheric measurements to model modern change in CO2 delta C-13. From this model, we estimated a correction factor that controls for atmospheric change; this correction reduces bias associated with changes in atmospheric isotopic baseline and facilitates comparison of tissue delta C-13 collected over multiple years. To exemplify the importance of accounting for atmospheric CO2 delta C-13 depletion, we applied the correction to a dataset of collagen delta C-13 obtained from mountain lion (Puma concolor) bone samples collected in California between 1893 and 1995. Before correction, in three of four ecoregions collagen delta C-13 decreased significantly concurrent with depletion of atmospheric CO2 delta C-13 (n >= 32, P <= 0.01). Application of the correction to collagen delta C-13 data removed trends from regions demonstrating significant declines, and measurement error associated with the correction did not add substantial variation to adjusted estimates. Controlling for long-term atmospheric variation and correcting tissue samples for changes in isotopic baseline facilitate analysis of samples that span a large temporal range.