Schmitz, O. J., Krivan, V. & Ovadia, O. Trophic cascades: the primacy of trait-mediated indirect interactions. Ecol. Lett. 7, 153–163 (2004).
Google Scholar
Creel, S. & Christianson, D. Relationships between direct predation and risk effects. Trends Ecol. Evol. 23(4), 194–201 (2008).
Google Scholar
Ritchie, E. G. et al. Ecosystem restoration with teeth: what role for predators?. Trends Ecol. Evol. 27(5), 265–271 (2012).
Google Scholar
Terborgh, J. & Estes, J. A. Trophic Cascades: Predators, Prey, and the Changing Dynamics of Nature (Island Press, 2010).
Creel, S. & Winnie, J. A. Responses of elk herd size to fine scale spatial and temporal variation in the risk of predation by wolves. Anim. Behav. 69, 1181–1189 (2005).
Google Scholar
Fischhoff, I. R., Sundaresan, S. R., Cordingley, J. & Rubenstein, D. I. Habitat use and movements of plains zebra (Equus burchelli) in response to predation danger from lions. Behav. Ecol. 18, 725–729 (2007).
Google Scholar
Latombe, G., Fortin, D. & Parrott, L. Spatio-temporal dynamics in the response of woodland caribou and moose to the passage of grey wolves. J. Anim. Ecol. 83, 185–198 (2014).
Google Scholar
Prugh, L. R. et al. Designing studies of predation risk for improved inference in carnivore-ungulate systems. Biol. Conserv. 232, 194–207 (2019).
Google Scholar
Creel, S., Winnie, J. A. & Christianson, D. Glucocorticoid stress hormones and the effect of predation risk on elk reproduction. PNAS 106(30), 12388–12393 (2009).
Google Scholar
Dulude-de Broin, F., Hamel, S., Mastromonaco, G. F. & Côté, S. D. Predation risk and mountain goat reproduction: evidence for stress-induced breeding suppression in a wild ungulate. Funct. Ecol. 34(5), 1003–1014 (2020).
Google Scholar
Moberg, G. P. & Mench, J. A. The Biology of Animal Stress: Basic Principles and Implications for Animal Welfare (CABI Publishing, 2000).
Boonstra, R. The ecology of stress: a marriage of disciplines. Funct. Ecol. 27, 7–10 (2013).
Google Scholar
Sheriff, M. J., Dantzer, B., Delehanty, B., Palme, R. & Boonstra, R. Measuring stress in wildlife: techniques for quantifying glucocorticoids. Oecologia 166, 869–887 (2011).
Google Scholar
Kelley, K. W. Immunological consequences of changing environmental stimuli. In Animal Stress (ed. Moberg, G. P.) 193–223 (American Physiological Society, Bethesda, 1985).
Mӧstl, E. & Palme, R. Hormones as indicators of stress. Domest. Anim. Endocrinol. 23, 67–74 (2002).
Google Scholar
Ursin, H. & Eriksen, H. R. The cognitive activation theory of stress. Psychoneuroendocrinology 29(5), 567–592 (2004).
Google Scholar
Lovallo, W. R. Individual differences in reactivity to stress. In Stress and Health. Biological and Psychological Interactions (ed. Lovallo, W. R.) 203–225 (Sage, 2016).
Patchev, V. K. & Patchev, A. V. Experimental models of stress. Dialogues Clin. Neurosci. 8(4), 417–432 (2006).
Google Scholar
Mills, J. L. Scientific Principles of Stress (University of the West Indie Press, 2012).
Henry, J. P. Biological basis of the stress response. Integr. Physiol. Behav. Sci. 27, 66–83 (1992).
Google Scholar
Wu, Y., Patchev, A. V., Daniel, G., Almeida, O. F. X. & Spengler, D. Early-life stress reduces DNA methylation of the Pomc gene in male mice. Endocrinology 155(5), 1751–1762 (2014).
Google Scholar
Novais, A., Monteiro, S., Roque, S., Correia-Neves, M. & Sousa, N. How age, sex and genotype shape the stress response. Neurob. Stress 6, 44–56 (2017).
Google Scholar
Romero, L. M. & Gormally, B. M. G. How truly conserved is the “well-conserved” vertebrate stress response?. Integr. Comp. Biol. 59(2), 273–281 (2019).
Google Scholar
Millspaugh, J. J. & Washburn, B. E. Use of fecal glucocorticoid metabolite measures in conservation biology research: considerations for application and interpretation. Gen. Comp. Endocrinol. 138, 189–199 (2004).
Google Scholar
Romero, L. M. Physiological stress in ecology: lessons from biomedical research. Trends Ecol. Evol. 19(5), 249–255 (2004).
Google Scholar
Johnstone, C. P., Reina, R. D. & Lill, A. Interpreting indices of physiological stress in free-living vertebrates. J. Comp. Physiol. B 182, 861–879 (2012).
Google Scholar
Mayer, E. A., Knight, R., Mazmanian, S. K., Cryan, J. F. & Tillisch, K. Gut microbes and the brain: paradigm shift in neuroscience. J. Neurosci. 34, 15490–15496 (2014).
Google Scholar
Sharon, G., Sampson, T. R., Geschwind, D. H. & Mazmanian, S. K. The central nervous system and the gut microbiome. Cell 167, 915–932 (2016).
Google Scholar
Mohajeri, M. H., La Fata, G., Steinert, R. E. & Weber, P. Relationship between the gut microbiome and brain function. Nutr. Rev. 76, 481–496 (2018).
Google Scholar
Bravo, J. A., Forsythe, P., Chew, M. V., Escaravage, E. & Savignac, H. M. Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. PNAS 108(38), 16050–16055 (2011).
Google Scholar
Beauclercq, S. et al. A multiplatform metabolomic approach to characterize fecal signatures of negative postnatal events in chicks: a pilot study. J Anim. Sci. Biotechnol. 10, 21 (2019).
Google Scholar
Jianguo, L., Xueyang, J., Cui, W., Changxin, W. & Xuemei, Q. Altered gut metabolome contributes to depression-like behaviors in rats exposed to chronic unpredictable mild stress. Transl. Psychiatry 9, 1–14 (2019).
Google Scholar
Valerio, A., Casadei, L., Giuliani, A. & Valerio, M. Fecal metabolomics as a novel non-invasive method for short-term stress monitoring in beef cattle. J. Proteome Res. 19(2), 845–853 (2020).
Google Scholar
Nicholson, J. K. et al. Host-gut microbiota metabolic interactions. Science 336, 1262–1267 (2012).
Google Scholar
Nicholson, J. K., Connelly, J., Lindon, J. C. & Holmes, E. Metabolomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1, 153–161 (2002).
Google Scholar
Lindon, J. C., Nicholson, J. K. & Holmes, E. The Handbook of Metabonomics and Metabolomics (Elsevier, 2007).
Matysik, S., Le Roy, C. I., Liebisch, G. & Claus, S. P. Metabolomics of fecal samples: a practical consideration. Trends Food Sci. Technol. 57, 244–255 (2016).
Google Scholar
Nicholson, J. K. & Lindon, J. C. Metabonomics. Nature 455, 1054–1056 (2008).
Google Scholar
Viant, M. R. Environmental metabolomics using 1H-NMR spectroscopy. Methods Mol. Biol. 410, 137–150 (2008).
Google Scholar
Ellis, D. I., Dunn, W. B., Griffin, J. L., Allwood, J. W. & Goodacre, R. Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics 8(9), 1243–1266 (2007).
Google Scholar
Worley, B. & Powers, R. Multivariate analysis in metabolomics. Curr. Metabolomics 1(1), 92–107 (2013).
Google Scholar
Rivas-Ubach, A. et al. Ecometabolomics: optimized NMR-based method. Methods Ecol. Evol. 4(5), 464–473 (2013).
Google Scholar
Chen, M. X., Wang, S. Y., Kuo, C. H. & Tsai, I. L. Metabolome analysis for investigating host-gut microbiota interactions. JFMA 118(1), S10–S22 (2019).
Emwas, A. H. M. The Strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. In Metabonomics. Methods in Molecular Biology (ed. Bjerrum, J. T.) 1277, 161–193 (Human Press, 2015).
Emwas, A. H. M. et al. NMR spectroscopy for metabolomics research. Metabolites 9(7), 123 (2019).
Google Scholar
Nicholson, J. K., Connelly, J., Lindon, J. C. & Holmes, E. Metabonomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1, 153–161 (2002).
Google Scholar
Wiles, G. J., Allen, H. L. & Hayes, G. E. Wolf Conservation and Management Plan for Washington (Washington Department of Fish and Wildlife, 2011).
Schmitz, O. J. & Trussell, G. C. Multiple stressors, state-dependence and predation risk-foraging trade-offs: toward a modern concept of trait-mediated indirect effects in communities and ecosystems. Curr. Opin. Behav. 12, 6–11 (2016).
Google Scholar
Brown, J. A. Mortality of Range Livestock in Wolf-Occupied Areas of Washington. Thesis. Washington State University, Pullman, WA, USA (2015).
Fieberg, J. & Kochanny, C. O. Quantification of home range overlap: the importance of the utilization distribution. J. Wildl. Manag. 69, 1346–1359 (2005).
Google Scholar
Robert, K., Garant, D. & Pelletier, F. Keep in touch: does spatial overlap correlate with contact rate frequency?. J. Wildl. Manag. 76(8), 1670–1675 (2012).
Google Scholar
Angel, S. P. et al. Climate change and cattle production: impact and adaptation. J. Vet. Med. Res. 5(4), 1134 (2018).
Brosh, A. et al. Energy cost of cows’ grazing activity: use of the heart rate method and the global positioning system for direct field estimation. J. Anim. Sci. 84, 1951–1967 (2006).
Google Scholar
Provenza, F. D. Postingestive feed-back as an elemental determinant of food preference and intake in ruminants. J. Range Manag. 48, 2–17 (1995).
Google Scholar
Provenza, F. D. Acquired aversions as the basis for varied diets of ruminants foraging on rangelands. J. Anim. Sci. 74, 2010–2020 (1996).
Google Scholar
Howery, L. D., Provenza, F. D., Ruyle, G. B. & Jordan, N. C. How do animals learn if rangeland plants are toxic or nutritious?. Rangelands 20, 4–9 (1998).
Davitt, B. B. & Nelson, J. R. Methodology for the determination of DAPA in feces of large ruminants. In Proceedings of the Western States and Provinces Elk Workshop (ed. Nelson, R.W.) 133–147 (Edmonton, 1984).
Church, D. C. Digestive Physiology and Nutrition of Ruminants I (Oxford Press, 1969).
Sato, S. Leadership during actual grazing in a small herd of cattle. Appl. Anim. Ethol. 8, 53–65 (1982).
Google Scholar
Frair, J. L. et al. Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philos. Trans. R. Soc. B 365, 2187–2200 (2010).
Google Scholar
Deda, O., Gika, H. G., Wilson, I. D. & Theodoridis, G. A. An overview of fecal preparation for global metabolic profiling. J. Pharm. Biomed. 113, 137–150 (2015).
Google Scholar
Landakadurai, B. P., Nagato, E. G. & Simpson, M. J. Environmental metabolomics: an emerging approach to study organism responses to environmental stressors. Environ. Rev. 21, 180–205 (2013).
Google Scholar
Wiklund, S. et al. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 80, 115–122 (2008).
Google Scholar
Wishart, D. S. et al. HMDB: a knowledgebase for the human metabolome. Nucl. Acids Res. 37, D603–D610 (2009).
Google Scholar
Frair, J. L. et al. Scale of movement by elk (Cervus elaphus) in response to heterogeneity in forage resources and predation risk. Landsc. Ecol. 20, 273–287 (2005).
Google Scholar
Valerio, A. Stress-Mediated and Habitat-Mediated Risk Effects of Free-Ranging Cattle in Washington. Dissertation. Washington State University, Pullman, WA (2019).
Winnie, J. & Creel, S. Sex-specific behavioral responses of elk to spatial and temporal variation in the threat of wolf predation. Anim. Behav. 73, 215–225 (2007).
Google Scholar
Bundy, J. G., Davey, M. P. & Viant, M. R. Environmental metabolomics: a critical review and future perspectives. Metabolomics 5, 3–21 (2009).
Google Scholar
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