How large is large: estimating ecologically meaningful isotopic differences in observational studies of wild animals

In ecological studies of wildlife movements and foraging, bio-logging and isotopic data are routinely collected and increasingly analyzed in tandem. Such analyses have two shortcomings: (1) small sample size linked with the number of telemetric tags that can be deployed, and (2) the observational nature of isotopic gradients. Wildlife ecologists are thus put in a statistical conundrum known as the small n, large p problem.

Using shrinkage regression, which directly addresses the issue of accurately estimating effects from sparse data, we studied what counts as a biologically meaningful isotopic difference (a prerequisite to delineate isoscapes) in the southern elephant seal (Mirounga leonina), a large and elusive marine predator.

Seals foraging in Antarctic waters had a lower carbon isotopic value (by ≈ 2‰) than seals foraging either in the interfrontal zone or on the Kerguelen Plateau. The latter two foraging strategies were indistinguishable on the sole basis of δ(13) C values with our data.

Shrinkage regression is a conservative statistical technique that has wide applicability in isotopic ecology to help separate robust biological signals from noise.