Testing foraging optimization models in brown bears: Time for a paradigm shift in nutritional ecology?

Author:

Mikkelsen Ashlee J.1ORCID,Hobson Keith A.23,Sergiel Agnieszka4ORCID,Hertel Anne G.15ORCID,Selva Nuria4ORCID,Zedrosser Andreas16

Affiliation:

1. Department of Natural Sciences and Environmental Health University of South‐Eastern Norway Bø Norway

2. Environment and Climate Change Canada Saskatoon Saskatchewan Canada

3. Department of Biology University of Western Ontario London Ontario Canada

4. Institute of Nature Conservation, Polish Academy of Sciences Krakow Poland

5. Department of Biology Ludwig Maximilians University of Munich Planegg Germany

6. Department of Integrative Biology University of Natural Recourses and Applied Life Sciences Vienna Austria

Abstract

AbstractHow organisms obtain energy to survive and reproduce is fundamental to ecology, yet researchers use theoretical concepts represented by simplified models to estimate diet and predict community interactions. Such simplistic models can sometimes limit our understanding of ecological principles. We used a polyphagous species with a wide distribution, the brown bear (Ursus arctos), to illustrate how disparate theoretical frameworks in ecology can affect conclusions regarding ecological communities. We used stable isotope measurements (δ13C, δ15N) from hairs of individually monitored bears in Sweden and Bayesian mixing models to estimate dietary proportions of ants, moose, and three berry species to compare with other brown bear populations. We also developed three hypotheses based on predominant foraging literature, and then compared predicted diets to field estimates. Our three models assumed (1) bears forage to optimize caloric efficiency (optimum foraging model), predicting bears predominately eat berries (~70% of diet) and opportunistically feed on moose (Alces alces) and ants (Formica spp. and Camponotus spp; ~15% each); (2) bears maximize meat intake (maximizing fitness model), predicting a diet of 35%–50% moose, followed by ants (~30%), and berries (~15%); (3) bears forage to optimize macronutrient balance (macronutrient model), predicting a diet of ~22% (dry weight) or 17% metabolizable energy from proteins, with the rest made up of carbohydrates and lipids (~49% and 29% dry matter or 53% and 30% metabolizable energy, respectively). Bears primarily consumed bilberries (Vaccinium myrtillus; 50%–55%), followed by lingonberries (V. vitis‐idaea; 22%–30%), crowberries (Empetrum nigrum; 8%–15%), ants (5%–8%), and moose (3%–4%). Dry matter dietary protein was lower than predicted by the maximizing fitness model and the macronutrient balancing model, but protein made up a larger proportion of the metabolizable energy than predicted. While diets most closely resembled predictions from optimal foraging theory, none of the foraging hypotheses fully described the relationship between foraging and ecological niches in brown bears. Acknowledging and broadening models based on foraging theories is more likely to foster novel discoveries and insights into the role of polyphagous species in ecosystems and we encourage this approach.

Funder

Robert Bosch Stiftung

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

Reference72 articles.

1. Arnemo J. M. andA. L.Evans.2017.“Biomedical Protocols for Free‐Ranging Brown Bears Wolves Wolverines and Lynx.”Inland Norway University of Applied Sciences 1–18.https://brage.inn.no/inn‐xmlui/bitstream/handle/11250/2444409/Biomedical%20Protocols%20Carnivores%202017.pdf?sequence=1.

2. Predicting bilberry and cowberry yields using airborne laser scanning and other auxiliary data combined with National Forest Inventory field plot data

3. Spatial patterns in brown bear Ursus arctos diet: the role of geographical and environmental factors

4. The Ecology of Individuals: Incidence and Implications of Individual Specialization

5. Can concentrations of steroid hormones in brown bear hair reveal age class?

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