Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem

Abstract

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change.

Salmonid species diversity predicts salmon consumption by terrestrial wildlife

“…Following similar studies of coastal bears in our study area, we used MixSIAR (Stock & Semmens, ) to estimate annual dietary contributions from plants, salmon, and intertidal foods by incorporating the δ13C and δ15N values from each of these potential dietary categories with those from the bears. As no reliable trophic discrimination factors (TDFs) exist for bear hair (Hopkins & Kurle, ), we followed recent bear hair stable‐isotope studies (Hopkins, Ferguson, Tyers, & Kurle, ; Hopkins & Kurle, ) and used TDF values from laboratory rats fed known diets of plants or animals (Appendix S1, Kurle, Koch, Tershy, & Croll, ). Given potential biases possible when not accounting for differences in digestible elemental concentrations in food sources, we evaluated models with and without concentration dependence (Koch & Phillips, ).…”

The Utility of Combining Stable Isotope and Hormone Analyses for Marine Megafauna Research

“…Estimating animal trophic levels and foraging locations has been the classic application of stable isotope data measured in animal tissues for ecological purposes Epstein, 1978, 1981;Hobson and Welch, 1992). The development of progressively more sophisticated analytical methods, such as stable isotope mixing models (SIMMs) that incorporate multiple parameters, including stable isotopes of elements besides carbon and nitrogen such as sulfur, oxygen, and hydrogen, have allowed for increasingly detailed estimations of animal ecological niche space using stable isotope data (Jackson et al, 2011;Newsome et al, 2012;Hopkins and Kurle, 2016;Rossman et al, 2016;Bowes et al, 2017;Hopkins et al, 2017). There now exist a wide array of modeling frameworks and metrics for categorizing diet, trophic niche, and trophic structure (Bearhop et al, 2004;Layman et al, 2007;Jackson et al, 2011;Newsome et al, 2012;Stock et al, 2018).…”

Exploring source differences on diet-tissue discrimination factors in the analysis of stable isotope mixing models

“…For example, recent field-based studies have applied different DTDFs through arithmetic corrections to distinguish between diet types 34 , whereas others have applied linear models to discern consumer and prey differences in DTDFs 40 . Similarly, in recent field research, Bastos et al 41 explored the use of different DTDFs in mixing models for an omnivorous fish, Jenynsia multidentata, that relied on herbivorous and carnivorous diets within coastal habitats in southern Brazil, whereas Hopkins et al 4 used variable correction factors for DTDFs to account for diet differences when they estimated the diets of grizzly bears, Ursus arctos, from the Greater Yellowstone Ecosystem. In addition, Healy et al 44 recently provided an alternative method that takes phylogenetic relatedness into account, an approach that promises to be useful where reliable proxy data are available.…”

“…Stable isotope mixing models are important tools in trophic ecology studies to quantitatively estimate the composition of consumer diets 1 – 4 . Recently, Bayesian inference-based isotope mixing models have risen to prominence in providing robust inferences on consumer diets by addressing challenges such as the occurrence of multiple prey sources in food webs 5 , 6 , the uncertainties associated with measurement, source and mixture process errors 1 , 7 , 8 , the incorporation of concentration dependences 9 and the use of prior information for both sources and mixtures 10 – 12 .…”