Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models

Abstract

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

Figure 1. Stable isotope inputs to the hierarchical mixing model for B.C. wolves.

Data derived from three regions (mainland, inner islands adjacent to the coast, outer islands). Prey items from each region have unique means (solid dots) and standard deviations (dashed lines) in each isotope dimension. For wolves (n = 64), symbols are used to depict group (pack) membership.

Figure 2. Ternary plots of posterior estimates of the proportional contribution of three prey types to the diet of wolves.

Shown are posteriors for each region (aggregated across individuals) and medians (symbols denote group membership for individual wolves).

Figure 3. Estimated posterior density for the standard deviation parameters controlling the variation in diet across three scales (sub-population, social group, individual).

Posterior densities are estimated from the model with the lowest DIC value, with medians indicated by dashed lines.

Figure 4. Region-specific posterior contributions of three prey items consumed by coastal wolf populations (deer, marine mammals, salmon).

Posterior densities are drawn from the model with the lowest DIC value. Dashed lines depict the global median across three regions (mainland, inner islands adjacent to the coast, outer islands).

Figure 5. Posterior distributions of variation in individual diets for island and mainland wolves (median represented with dashed line).

The variability for each region represents the deviation in diet from the social group (pack) diet.