1.Coristine, L. E. & Kerr, J. T. Habitat loss, climate change, and emerging conservation challenges in Canada. Can. J. Zool. 89, 435–451 (2011).Article
Google Scholar
2.Proctor, M. F. et al. Population fragmentation and inter-ecosystem movements of grizzly bears in Western Canada and the Northern United States. Wildl. Monogr. 180, 1–46 (2012).Article
Google Scholar
3.Festa-Bianchet, M. Status of the grizzly bear (Ursus arctos) in Alberta: Update 2010. Wildlife Status Report No. 37. (Alberta Sustainable Resource Development, Fish and Wildlife Division, Alberta Conservation Association, Edmonton, Alberta, Canada, 2010).4.Berland, A., Nelson, T., Stenhouse, G., Graham, K. & Cranston, J. The impact of landscape disturbance on grizzly bear habitat use in Foothills Model Forest, Alberta, Canada. For. Ecol. Manag. 256, 1875–1883 (2008).Article
Google Scholar
5.Nielsen, S. E., Cranston, J. & Stenhouse, G. B. Identification of priority areas for grizzly bear conservation and recovery in Alberta, Canada. J. Conserv. Plan. 5, 38–60 (2009).
Google Scholar
6.Boulanger, J. & Stenhouse, G. B. The impact of roads on the demography of grizzly bears in Alberta. PLoS ONE 9, e115535 (2014).ADS
PubMed
PubMed Central
Article
CAS
Google Scholar
7.Acevedo-Whitehouse, K. & Duffus, A. L. J. Effects of environmental change on wildlife health. Philos. Trans. R. Soc. B Biol. Sci. 364, 3429–3438 (2009).Article
Google Scholar
8.Stephen, C. Toward a new definition of animal health: Lessons from the Cohen Commission and the SPS agreement. Optim. Online 43, 1–8 (2013).
Google Scholar
9.Stephen, C. Toward a modernized definition of wildlife health. J. Wildl. Dis. 50, 427–430 (2014).PubMed
Article
Google Scholar
10.Wittrock, J., Duncan, C. & Stephen, C. A determinants of health conceptual model for fish and wildlife health. J. Wildl. Dis. 55, 285–297 (2019).PubMed
Article
Google Scholar
11.Stephen, C. The Pan-Canadian approach to wildlife health. Can. Vet. J. 60, 145–146 (2019).PubMed
PubMed Central
Google Scholar
12.Ricklefs, R. E. & Wikelski, M. The physiology/life- history nexus. Trends Ecol. Evol. 17, 462–468 (2002).Article
Google Scholar
13.Dammhahn, M., Dingemanse, N. J., Niemelä, P. T. & Réale, D. Pace-of-life syndromes: A framework for the adaptive integration of behaviour, physiology and life history. Behav. Ecol. Sociobiol. 72, 62 (2018).Article
Google Scholar
14.Réale, D. et al. Personality and the emergence of the pace-of-life syndrome concept at the population level. Philos. Trans. R. Soc. B Biol. Sci. 365, 4051–4063 (2010).Article
Google Scholar
15.Lovegrove, B. G. The influence of climate on the basal metabolic rate of small mammals: A slow-fast metabolic continuum. J. Comp. Physiol. B Biochem. Syst. Environ. Physiol. 173, 87–112 (2003).CAS
Article
Google Scholar
16.Garshelis, D., Gibeau, M. & Herrero, S. Grizzly bear demographics in and around Banff National Park and Kananaskis Country, Alberta. J. Wildl. Manag. 69, 277–297 (2005).Article
Google Scholar
17.Ferguson, S. H. & Mcloughlin, P. D. Effect of Energy Availability, Seasonality, and Geographic Range on Brown Bear Life History. Ecography (Cop.) 23, 193–200 (2000).Article
Google Scholar
18.Brewis, I. A. & Brennan, P. Proteomics Technologies for the Global Identification and Quantification of Proteins. Advances in Protein Chemistry and Structural Biology Vol. 80 (Elsevier, 2010).
Google Scholar
19.Cox, J. & Mann, M. Is proteomics the new genomics?. Cell 130, 395–398 (2007).CAS
PubMed
Article
Google Scholar
20.Lu, P., Vogel, C., Wang, R., Yao, X. & Marcotte, E. M. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat. Biotechnol. 25, 117–124 (2007).CAS
PubMed
Article
Google Scholar
21.Vidova, V. & Spacil, Z. A review on mass spectrometry-based quantitative proteomics: Targeted and data independent acquisition. Anal. Chim. Acta 964, 7–23 (2017).CAS
PubMed
Article
Google Scholar
22.Hoofnagle, A. N. et al. Multiple-reaction monitoring-mass spectrometric assays can accurately measure the relative protein abundance in complex mixtures. Clin. Chem. 58, 777–781 (2012).CAS
PubMed
PubMed Central
Article
Google Scholar
23.Addona, T. A. et al. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nat. Biotechnol. 27, 633–641 (2009).CAS
PubMed
PubMed Central
Article
Google Scholar
24.Percy, A. J., Chambers, A. G., Yang, J., Hardie, D. B. & Borchers, C. H. Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility. Biochim. Biophys. Acta 1844, 917–926 (2014).CAS
PubMed
Article
Google Scholar
25.Michaud, S. A. et al. Molecular phenotyping of laboratory mouse strains using 500 multiple reaction monitoring mass spectrometry plasma assays. Commun. Biol. 1, 1–9 (2018).CAS
Article
Google Scholar
26.Burke, H. B. Predicting clinical outcomes using molecular biomarkers. Biomark. Cancer 8, BIC.S33380 (2016).Article
Google Scholar
27.Zhang, A., Sun, H., Wang, P. & Wang, X. Salivary proteomics in biomedical research. Clin. Chim. Acta 415, 261–265 (2013).CAS
PubMed
Article
Google Scholar
28.Wilson, A. E. et al. Development and validation of protein biomarkers of health in grizzly bears. Conserv. Physiol. 8, coaa056 (2020).PubMed
PubMed Central
Article
Google Scholar
29.Zmijewski, M. A. & Slominski, A. T. Neuroendocrinology of the skin: An overview and selective analysis. Dermatoendocrinol. 3, 3–10 (2011).CAS
PubMed
PubMed Central
Article
Google Scholar
30.Slominski, A. T., Zmijewski, M. A., Plonka, P. M., Szaflarski, J. P. & Paus, R. How UV light touches the brain and endocrine system through skin, and why. Endocrinology 159, 1992–2007 (2018).CAS
PubMed
PubMed Central
Article
Google Scholar
31.Slominski, A. T. et al. Sensing the environment: Regulation of local and global homeostasis by the skin neuroendocrine system. Adv. Anat. Embryol. Cell Biol. 212, 1–98 (2012).Article
Google Scholar
32.Esmaili, S., Hemmati, M. & Karamian, M. Physiological role of adiponectin in different tissues: A review. Arch. Physiol. Biochem. 126, 67–73 (2018).PubMed
Article
CAS
Google Scholar
33.Ishaq, S., Kaur, H. & Bhatia, S. Clusterin: It’s implication in health and diseases. Ann. Appl. Bio-Sciences 4, R30–R34 (2017).Article
Google Scholar
34.Bali, S. & Utaal, M. S. Serum lipids and lipoproteins: A brief review of the composition, transport and physiological functions. Int. J. Sci. Rep. 5, 309 (2019).Article
Google Scholar
35.Linder, M. C. Ceruloplasmin and other copper binding components of blood plasma and their functions: An update. Metallomics 8, 887–905 (2016).CAS
PubMed
Article
PubMed Central
Google Scholar
36.Dietzel, E., Floehr, J. & Jahnen-dechent, W. The biological role of fetuin-B in female reproduction. Ann. Reprod. Med. Treat 1(1), 1003 (2016).
Google Scholar
37.Helliwell, R. J. A., Adams, L. F. & Mitchell, M. D. Prostaglandin synthases: Recent developments and a novel hypothesis. Prostaglandins Leukot. Essent. Fat. Acids 70, 101–113 (2004).CAS
Article
Google Scholar
38.Meyer, E. J., Nenke, M. A., Rankin, W., Lewis, J. G. & Torpy, D. J. Corticosteroid-binding globulin: A review of basic and clinical advances. Horm. Metab. Res. 48, 359–371 (2016).CAS
PubMed
Article
Google Scholar
39.Hoter, A., El-Sabban, M. E. & Naim, H. Y. The HSP90 family: Structure, regulation, function, and implications in health and disease. Int. J. Mol. Sci. 19, 2560 (2018).PubMed Central
Article
CAS
Google Scholar
40.Bruschi, M. et al. Annexin a1 and autoimmunity: From basic science to clinical applications. Int. J. Mol. Sci. 19, 1–13 (2018).Article
CAS
Google Scholar
41.Bogdan, A. R., Miyazawa, M., Hashimoto, K. & Tsuji, Y. Regulators of iron homeostasis: New players in metabolism, cell death, and disease. Trends Biochem. Sci. 41, 274–286 (2016).CAS
PubMed
Article
Google Scholar
42.Dieplinger, H. & Dieplinger, B. Afamin—A pleiotropic glycoprotein involved in various disease states. Clin. Chim. Acta 446, 105–110 (2015).CAS
PubMed
Article
Google Scholar
43.Ricklin, D., Reis, E. S., Mastellos, D. C., Gros, P. & Lambris, J. D. Complement component C3—The “Swiss Army Knife” of innate immunity and host defense. Immunol. Rev. 274, 33–58 (2016).CAS
PubMed
PubMed Central
Article
Google Scholar
44.Bteich, M. An overview of albumin and alpha-1-acid glycoprotein main characteristics: Highlighting the roles of amino acids in binding kinetics and molecular interactions. Heliyon 5, e02879 (2019).PubMed
PubMed Central
Article
Google Scholar
45.Tóthová, C. & Nagy, O. Transthyretin in the evaluation of health and disease in human and veterinary medicine. In Pathophysiology—Altered Physiological States (ed. Gaze, D. C.) (IntechOpen, 2017). https://doi.org/10.5772/57353.Chapter
Google Scholar
46.Willis, E. L., Kersey, D. C., Durrant, B. S. & Kouba, A. J. The acute phase protein ceruloplasmin as a non-invasive marker of pseudopregnancy, pregnancy, and pregnancy loss in the giant panda. PLoS One 6, e21159 (2011).ADS
CAS
PubMed
PubMed Central
Article
Google Scholar
47.Floehr, J. et al. Association of high fetuin-B concentrations in serum with fertilization rate in IVF: A cross-sectional pilot study. Hum. Reprod. 31, 630–637 (2016).CAS
PubMed
Article
Google Scholar
48.Khalkhali-Ellis, Z. Maspin: The new frontier. Clin. Cancer Res. 12, 7279–7283 (2006).CAS
PubMed
PubMed Central
Article
Google Scholar
49.Chim, S. S. C. et al. Detection of the placental epigenetic signature of the maspin gene in maternal plasma. Proc. Natl. Acad. Sci. U.S.A. 102, 14753–14758 (2005).ADS
CAS
PubMed
PubMed Central
Article
Google Scholar
50.Carillon, J., Rouanet, J. M., Cristol, J. P. & Brion, R. Superoxide dismutase administration, a potential therapy against oxidative stress related diseases: Several routes of supplementation and proposal of an original mechanism of action. Pharm. Res. 30, 2718–2728 (2013).CAS
PubMed
Article
Google Scholar
51.Demers, N. & Bayne, C. Immediate increase of plasma protein complement C3 in response to an acute stressor. Fish Shellfish Immunol. 107, 411–413 (2020).CAS
PubMed
Article
Google Scholar
52.Bourbonnais, M. L., Nelson, T. A., Cattet, M. R. L., Darimont, C. T. & Stenhouse, G. B. Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of alberta, canada. PLoS One 8, e83768 (2013).ADS
PubMed
PubMed Central
Article
CAS
Google Scholar
53.Zedrosser, A., Bellemain, E., Taberlet, P. & Swenson, J. E. Genetic estimates of annual reproductive success in male brown bears: The effects of body size, age, internal relatedness and population density. J. Anim. Ecol. 76, 368–375 (2007).PubMed
Article
Google Scholar
54.Pop, M. I., Iosif, R., Miu, I. V., Rozylowicz, L. & Popescu, V. D. Combining resource selection functions and home-range data to identify habitat conservation priorities for brown bears. Anim. Conserv. 21, 352–362 (2018).Article
Google Scholar
55.Pagano, A. M. et al. High-energy, high-fat lifestyle challenges an Arctic apex predator, the polar bear. Science 359, 568–572 (2018).ADS
CAS
PubMed
Article
Google Scholar
56.Wasser, S. K. et al. Scat detection dogs in wildlife research and management: Application to grizzly and black bears in the Yellowhead Ecosystem, Alberta, Canada. Can. J. Zool. 82, 475–492 (2004).Article
Google Scholar
57.Cristescu, B., Stenhouse, G. B., Symbaluk, M., Nielsen, S. E. & Boyce, M. S. Wildlife habitat selection on landscapes with industrial disturbance. Environ. Conserv. 43, 327–336 (2016).Article
Google Scholar
58.Naves, J., Wiegand, T., Revilla, E. & Delibes, M. Endangered species constrained by natural and human factors: The case of brown bears in northern Spain. Conserv. Biol. 17, 1276–1289 (2003).Article
Google Scholar
59.Munro, R. H. M., Nielsen, S. E., Price, M. H., Stenhouse, G. B. & Boyce, M. S. Seasonal and diel patterns of grizzly bear diet and activity in west-central Alberta. J. Mammal. 87, 1112–1121 (2006).Article
Google Scholar
60.Nielsen, S. E., Boyce, M. S. & Stenhouse, G. B. Grizzly bears and forestry: I. Selection of clearcuts by grizzly bears in west-central Alberta, Canada. For. Ecol. Manag. 199, 51–65 (2004).Article
Google Scholar
61.Larsen, T. A., Nielsen, S. E., Cranston, J. & Stenhouse, G. B. Do remnant retention patches and forest edges increase grizzly bear food supply?. For. Ecol. Manag. 433, 741–761 (2019).Article
Google Scholar
62.Nielsen, S. E., Stenhouse, G. B. & Boyce, M. S. A habitat-based framework for grizzly bear conservation in Alberta. Biol. Conserv. 130, 217–229 (2006).Article
Google Scholar
63.Wilson, A. E. et al. Population-level monitoring of stress in grizzly bears between 2004 and 2014. Ecosphere 11, e03181 (2020).Article
Google Scholar
64.Graham, K. & Stenhouse, G. B. Home range, movements, and denning chronology of the grizzly bear (Ursus arctos) in west-central Alberta. Can. Field-Nat. 128, 223–234 (2014).Article
Google Scholar
65.Blanchard, B. M. & Knight, R. R. Movements of yellowstone grizzly bears. Biol. Conserv. 58, 41–67 (1991).Article
Google Scholar
66.McLoughlin, P. D., Case, R. L., Gau, R. J., Ferguson, S. H. & Messier, F. Annual and seasonal movement patterns of barren-ground grizzly bears in the central northwest territories. Ursus 11, 79–86 (1999).
Google Scholar
67.Kadowaki, T. et al. Adiponectin and adiponectin receptors in insulin resistance, diabetes, and the metabolic syndrome. J. Clin. Investig. 116, 1784–1792 (2006).CAS
PubMed
Article
Google Scholar
68.Rivet, D. R., Nelson, O. L., Vella, C. A., Jansen, H. T. & Robbins, C. T. Systemic effects of a high saturated fat diet in grizzly bears (Ursus arctos horribilis). Can. J. Zool. 95, 797–807 (2017).CAS
Article
Google Scholar
69.Rigano, K. S. et al. Life in the fat lane: Seasonal regulation of insulin sensitivity, food intake, and adipose biology in brown bears. J. Comp. Physiol. B Biochem. Syst. Environ. Physiol. 187, 649–676 (2017).CAS
Article
Google Scholar
70.Lee, Y. S. et al. Adipocytokine orosomucoid integrates inflammatory and metabolic signals to preserve energy homeostasis by resolving immoderate inflammation. J. Biol. Chem. 285, 22174–22185 (2010).CAS
PubMed
PubMed Central
Article
Google Scholar
71.Ráez-bravo, A. et al. Acute phase proteins increase with sarcoptic mange status and severity in Iberian ibex (Capra pyrenaica, Schinz 1838). Parasitol. Res. 114, 4005–4010. https://doi.org/10.1007/s00436-015-4628-3 (2015).Article
PubMed
Google Scholar
72.Agra, R. M. et al. Orosomucoid as prognosis factor associated with inflammation in acute or nutritional status in chronic heart failure. Int. J. Cardiol. 228, 488–494 (2017).PubMed
Article
Google Scholar
73.Mugahid, D. A. et al. Proteomic and transcriptomic changes in hibernating grizzly bears reveal metabolic and signaling pathways that protect against muscle atrophy. Sci. Rep. 9, 1–16 (2019).Article
CAS
Google Scholar
74.Vella, C. A. et al. Regulation of metabolism during hibernation in brown bears (Ursus arctos): Involvement of cortisol, PGC-1α and AMPK in adipose tissue and skeletal muscle. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 240, 110591 (2020).CAS
Article
Google Scholar
75.Jansen, H. T. et al. Hibernation induces widespread transcriptional remodeling in metabolic tissues of the grizzly bear. Commun. Biol. 2, 336 (2019).PubMed
PubMed Central
Article
CAS
Google Scholar
76.Phoebus, I., Segelbacher, G. & Stenhouse, G. B. Do large carnivores use riparian zones? Ecological implications for forest management. For. Ecol. Manag. 402, 157–165 (2017).Article
Google Scholar
77.Nielsen, S. E., McDermid, G., Stenhouse, G. B. & Boyce, M. S. Dynamic wildlife habitat models: Seasonal foods and mortality risk predict occupancy-abundance and habitat selection in grizzly bears. Biol. Conserv. 143, 1623–1634 (2010).Article
Google Scholar
78.Bielli, P. & Calabrese, L. Cellular and molecular life sciences structure to function relationships in ceruloplasmin: A ‘moonlighting’ protein. Cell. Mol. Life Sci. 59, 1413–1427 (2002).CAS
PubMed
Article
Google Scholar
79.Pagano, A. M. et al. Energetic costs of locomotion in bears: Is plantigrade locomotion energetically economical?. J. Exp. Biol. 221, jeb175372 (2018).PubMed
Article
Google Scholar
80.Kurki, S., Nikula, A., Helle, P. & Linden, H. Landscape fragmentation and forest composition effects on grouse breeding success in boreal forests. Ecology 81, 1985–1997 (2000).
Google Scholar
81.Graham, K., Boulanger, J., Duval, J. & Stenhouse, G. Spatial and temporal use of roads by grizzly bears in west-central Alberta. Ursus 21, 43–56 (2010).Article
Google Scholar
82.McLellan, B. N. & Shackleton, D. M. Grizzly bears and resource-extraction industries: Effects of roads on behaviour, habitat use and demography. J. Appl. Ecol. 25, 451–460 (1988).Article
Google Scholar
83.Massey, A. J. et al. Relationship between hair and salivary cortisol and pregnancy in women undergoing IVF. Psychoneuroendocrinology 74, 397–405 (2016).CAS
PubMed
Article
Google Scholar
84.Benn, B. & Herrero, S. Grizzly bear mortality and human access in Banff and Yoho National Parks, 1971–98. Ursus 13, 213–221 (2002).
Google Scholar
85.Nielsen, S. E. et al. Modelling the spatial distribution of human-caused grizzly bear mortalities in the Central Rockies ecosystem of Canada. Biol. Conserv. 120, 101–113 (2004).Article
Google Scholar
86.Pagano, A. M., Peacock, E. & Mckinney, M. A. Remote biopsy darting and marking of polar bears. Mar. Mammal Sci. 30, 169–183 (2014).Article
Google Scholar
87.Berland, A., Nelson, T., Stenhouse, G., Graham, K. & Cranston, J. The impact of landscape disturbance on grizzly bear habitat use in the Foothills Model Forest, Alberta, Canada. For. Ecol. Manag. 256, 1875–1883 (2008).Article
Google Scholar
88.Stenhouse, G. et al. Grizzly bear associations along the eastern slopes of Alberta. Ursus 16, 31–40 (2005).Article
Google Scholar
89.Nielsen, S. E., Munro, R. H. M., Bainbridge, E. L., Stenhouse, G. B. & Boyce, M. S. Grizzly bears and forestry: II. Distribution of grizzly bear foods in clearcuts of west-central Alberta, Canada. For. Ecol. Manag. 199, 67–82 (2004).Article
Google Scholar
90.Cattet, M., Boulanger, J., Stenhouse, G., Powell, R. A. & Reynolds-Hogland, M. J. An evaluation of long-term capture effects in ursids: Implications for wildlife welfare and research. J. Mammal. 89, 973–990 (2008).Article
Google Scholar
91.McDermid, G. J. Remote Sensing for Large-Area, Multi-Jurisdictional Habitat Mapping. PhD Thesis. University of Waterloo: Canada. 258p (2005).92.Smulders, M. et al. Quantifying spatial-temporal patterns in wildlife ranges using STAMP: A grizzly bear example. Appl. Geogr. 35, 124–131 (2012).Article
Google Scholar
93.Sorensen, A. A., Stenhouse, G. B., Bourbonnais, M. L. & Nelson, T. A. Effects of habitat quality and anthropogenic disturbance on grizzly bear (Ursus arctos horribilis) home-range fidelity. Can. J. Zool. 93, 857–865 (2015).Article
Google Scholar
94.Franklin, S. E., Peddle, D. R., Dechka, J. A. & Stenhouse, G. B. Evidential reasoning with Landsat TM, DEM and GIS data for landcover classification in support of grizzly bar habitat mapping. Int. J. Remote Sens. 23, 4633–4652 (2002).ADS
Article
Google Scholar
95.Gessler, P. E., Moore, I. D., McKenzie, N. J. & Ryan, P. J. Soil-landscape modelling and spatial prediction of soil attributes. Int. J. Geogr. Inf. Syst. 9, 421–432 (1995).Article
Google Scholar
96.Wilson, J. P. & Gallant, J. C. Terrain Analysis: Principles and Applications (Wiley, 2000).
Google Scholar
97.Riley, S. J., DeGloria, S. D. & Elliot, R. A Terrain ruggedness index that quantifies topographic heterogeneity. Int. J. Sci. 5, 23–27 (1999).
Google Scholar
98.Stoneberg, R. P. & Jonkel, C. J. Age determination of black bears by cementum layers. J. Wildl. Manag. 30, 411–414 (1966).Article
Google Scholar
99.Matson, G. M., Van Daele, L., Goodwin, E., Aumiller, A., Reynolds, H.V. & Hristienko, H. A Laboratory Manual for Cementum Age Determination of Alaskan Brown Bear First Premolar Teeth. 1–52 (Matson’s Laboratory, Milltown, MT, 1993).100.Nielsen, S. E. et al. Environmental, biological and anthropogenic effects on grizzly bear body size: Temporal and spatial considerations. BMC Ecol. 13, 1 (2013).CAS
Article
Google Scholar
101.Bourbonnais, M. L. et al. Environmental factors and habitat use influence body condition of individuals in a species at risk, the grizzly bear. Conserv. Physiol. 2, 1–14 (2014).Article
CAS
Google Scholar
102.Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article
Google Scholar
103.Cattet, M. et al. The quantification of reproductive hormones in the hair of captive adult brown bears and their application as indicators of sex and reproductive state. Conserv. Physiol. 5, 1–21 (2017).Article
CAS
Google Scholar
104.Cattet, M. et al. Can concentrations of steroid hormones in brown bear hair reveal age class?. Conserv. Physiol. 6, 1–20 (2018).Article
CAS
Google Scholar
105.Carlson, R. et al. Development and application of an antibody-based protein microarray to assess stress in grizzly bears (Ursus arctos). Conserv. Physiol. 4, 1–17 (2016).Article
CAS
Google Scholar
106.Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical information-Theoretic Approach (Springer, 2002).MATH
Google Scholar
107.Grueber, C. E., Nakagawa, S., Laws, R. J. & Jamieson, I. G. Multimodel inference in ecology and evolution: Challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).CAS
PubMed
Article
Google Scholar
108.Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J 9, 378–400 (2017).Article
Google Scholar
109.R Core Team. R: A language and environment for statistical computing. https://www.R-project.org/ (R Foundation for Statistical Computing, Vienna, Austria, 2020). More