Physical and biogeochemical correlates of spatio-temporal variation in the δ13C of marine macroalgae
Mackey, AP, Hyndes, GA, Carvalho, MC & Eyre, BD 2015, 'Physical and biogeochemical correlates of spatio-temporal variation in the δ13C of marine macroalgae', Estuarine, Coastal and Shelf Science, vol. 157, pp. 7-18.
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Carbon isotope ratios (13C/12C) can be used to trace sources of production supporting food chains, as δ13C undergoes relatively small and predictable increases (∼0.5‰) through each trophic level. However, for this technique to be precise, variation in δ13C signatures of different sources of production (baseline sources) must be clearly defined and distinct from each other. Despite this, δ13C in the primary producers of marine systems are highly variable over space and time, due to the complexity of physical and biogeochemical processes that drive δ13C variation at the base of these foodwebs. We measured spatial and temporal variation in the δ13C of two species of macroalgae that are important dietary components of grazers over temperate reefs: the small kelpEcklonia radiata, and the red alga Plocamium preissianum, and related any variation to a suite of physical and biogeochemical variables. Patterns in δ13C variation, over different spatial (10 s m to 100 km) and temporal scales (weeks to seasons), differed greatly between taxa, but these were partly explained by the δ13C of dissolved inorganic carbon (DIC) and light. However, while the δ13C in E. radiata was not related to water temperature, a highly significant proportion of the spatio-temporal variation in δ13C of P.preissianum was explained by temperature alone. Accordingly, we applied this relationship to project (across temperate Australasia) and forecast (in time, south-western Australia) patterns in P. preissianum δ13C. The mean projected δ13C for P.preissianum in the study region varied by only ∼1‰ over a 12-month period, compared to ∼3‰ over 2000 km. This illustrates the potential scale in the shift of δ13C in baseline food sources over broad scales, and its implications to food web studies. While we show that those relationships differ across taxonomic groups, we recommend developing models to explain variability in δ13C of other baseline sources to facilitate the interpretation of variation in δ13C of consumers in food webs, particularly where data for baselines are absent over broad scales.