43) for fin whales only. Mixing models were rerun where sprat and herring age classes were pooled but correlations between source posterior

distributions were greater (< −0.50), providing justification for the stratification of fish isotopic data by age. In Bayesian inference, given data (D) and a model (M) the probability from the posterior distribution is presented as Pr(D|M). Assuming that the model includes all major diet sources, both fin and humpback whale diets included large proportions GSK1120212 purchase of fish. Krill comprised a greater proportion of the diet of fin whales than in humpback whales (Pr(D|M) = 0.979). For fin whales, krill species were collectively the most dominant (maximum a posteriori probability estimate, low–high 95% credibility intervals) diet component (0.46, 0.22–0.59). Both fin and humpback whales were found to have a preference for age 0 sprat (0.22, 0.00–0.37 and 0.30, 0.01–0.38, respectively) and herring (0.17, 0.01–0.35 and 0.22, 0.02–0.36, respectively) (Fig. 4). The probability that krill comprised a greater proportion than the next most abundant component (age 0 sprat) was 0.996 (Fig. 3, 4). While there was a high probability that age 0 sprat were more abundant in fin whale diet solution than either age 1 (0.696) or age 2 (0.786), the probability that sprat was greater

selleck inhibitor than herring when posterior age class distributions were pooled was very low, Pr(D|M) = 0.318 (Fig. 3, 4). Krill exhibited a wide range in δ13C which is consistent with a high degree of spatio-temporal variability within the sample (Fig. 2). Despite this, however, the mixing model solutions show unambiguous isotopic

separation between fish and krill, leading to reduced uncertainty when partitioning diet sources (Fig. 3). A prior assessment of likely diet components of fin and humpback whales in the CS was made, based on the best available evidence from the literature and field observations. This guided the selection of sources MCE公司 for the isotope mixing model. A caveat of this approach was that sources used in the mixing models were unlikely to be an exhaustive representation of the species diversity in the diet of fin and humpback whales which may feed on other fishes, e.g., anchovy (Engraulis encrasicolus), pilchard (Sardina pilchardus), mackerel or blue whiting (Micromesistius poutassou), or indeed other species of zooplankton, e.g., Calanus spp. or Thysanoessa spp. However, there was no evidence from the literature, or from field observations indicating that these species are preyed upon by fin and humpback whales in the CS or contiguous waters. While a sufficient sample size was obtained for fin whales (n = 21), it should be noted that results for humpback whales are based on a small sample (n = 4) and should therefore be interpreted with caution. A potential source of bias in our results is the differential tissue turnover rate between krill and fish muscle.