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Seeking snow and breathing hard – Behavioral tactics in high elevation mammals to combat warming temperatures


Autoři: Wesley Sarmento aff001;  Mark Biel aff002;  Joel Berger aff003
Působiště autorů: Wildlife Biology Program, The University of Montana, Missoula, Montana, United States of America aff001;  Glacier National Park, West Glacier, Montana, United States of America aff002;  Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado, United States of America aff003;  Wildlife Conservation Society, Bronx, New York, United States of America aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225456

Souhrn

The world glaciers and areas of persistent summer snowpack are being lost due to warming temperatures. For cold-adapted species, habitat features may offer opportunities for cooling during summer heat yet the loss of snow and ice may compromise derived thermoregulatory benefits. Herein we offer insights about habitat selection for snow and the extent to which other behavioral adjustments reduce thermal debt among high elevation mammals. Specifically, we concentrate on respiration in mountain goats (Oreamnos americanus), a species whose native distribution is currently tied to northern mountain ranges of North America, where large patches of persistent summer snow are declining, and which became extinct during geologically warmer epochs. To examine sensitivity to possible thermal stressors and use of summer snow cover, we tracked marked and unmarked mountain goats in Glacier National Park, Montana, USA, to test hypotheses about selection for cold microclimates including shade and snow during periods of relatively high temperature. To understand functional responses of habitat choices, we measured microhabitat temperatures and a component of goat physiology–breaths per minute–as an index for metabolic expenditure. Individuals 1) selected areas closer to snow on warmer summer days, and 2) on snow had a 15% mean reduction in respiration when accounting for other factors, which suggests remnant snow plays an important role in mediating effects of air temperature. The use of shade was not as an important variable in models explaining respiration. Despite the loss of 85% of glaciers in in Glacier National Park, summer’s remnant snow patches are an important reservoir by which animals reduce heat stress and potential hyperthermia. Our findings, when contextualized with behavioral strategies deployed by other high elevation mammalian taxa help frame how ambient temperatures may be modulated, and they offer a direct way by which to assess susceptibility to increasing heat in cold-adapted species.

Klíčová slova:

Body temperature – Breathing – Goats – Mammals – Mountains – Summer – Wind – Glaciers


Zdroje

1. Walther G, Post E, Convey P, Menzel A, Parmesan C, Beebee TJC, et al. Ecological responses to recent climate change. Nature. 2002;416: 389–395. doi: 10.1038/416389a 11919621

2. Barnett TP, Adam JC, Lettenmaier DP. Potential impacts of a warming climate on water availability in snow-dominated regions. Nature. 2005;438: 303–309. doi: 10.1038/nature04141 16292301

3. Derksen C, Brown R. Spring snow cover extent reductions in the 2008–2012 period exceeding climate model projections. Geophys Res Lett. 2012;39. doi: 10.1029/2012GL053387

4. Pielou EC. After the ice age: the return of life to glaciated North Americae. University of Chicago Press; 2008.

5. Quan RC, Ren G, Behm JE, Wang L, Huang Y, Long Y, et al. Why does Rhinopithecus bieti prefer the highest elevation range in winter? A test of the sunshine hypothesis. PLoS One. 2011; e24449. doi: 10.1371/journal.pone.0024449 21915329

6. Blumstein DT, Im S., Nicodemus A. Zugmeyer C. Yellow-bellied marmots (Marmota flaviventris) hibernate socially. J Mammal. 2004; 25–29.

7. Hinze A, Rymer T, Pillay N. Spatial dichotomy of sociality in the African ice rat. J Zool. 2013; 208–214.

8. MacArthur RA, Wang LC. Behavioral thermoregulation in the pika Ochotona princeps: a field study using radiotelemetry. Can J Zool. 1974; 353–358. 4819475

9. Moyer Horner L, Mathewson PD, Jones GM, Kearney MR, Porter WP. Modeling behavioral thermoregulation in a climate change sentinel. Model Behav Thermoregul a Clim Chang Sentin. 2015; 5810–5822.

10. Beever EA, Hall LE, Varner J, Loosen AE, Dunham JB, Gahl MK, et al. Behavioral flexibility as a mechanism for coping with climate changee. Front Ecol Environ. 2017; 299–308.

11. Berger J, Hartway C, Gruzdev A, Johnson M. Climate degradation and extreme icing events constrain life in cold- adapted mammals. Sci Rep. 2018;8: 1–9. doi: 10.1038/s41598-017-17765-5

12. Lent PC. Muskoxen and their hunters: A history. University of Oklahoma Press; 1999.

13. Renecker LA, Hudson RJ. Seasonal energy expenditures and thermoregulatory responses of bison and cattle. Can J Zool. 1986;64: 322–327. doi: 10.4141/cjas79-077

14. Schaller GB. Wildlife of the Tibetan steppe. University of Chicago Press; 1998.

15. Berger J, Cheng E, Kang A, Krebs M, Li L, Lu Z, et al. Sex differences in ecology of wild yaks at high elevation in the Kekexili Reserve, Tibetan Qinghai Plateau, China. J Mammal. 2014;95: 638–645. doi: 10.1644/13-MAMM-A-154

16. McKelvey KS, Copeland JP, Schwartz MK, Littell JS, Aubry KB, Squires JR, et al. Climate change predicted to shift wolverine distributions, connectivity, and dispersal corridors. Ecol Appl. 2011;21: 2882–2897. doi: 10.1890/10-2206.1

17. Inman RM, Magoun AJ, Persson J, Mattisson J. The wolverine’s niche: linking reproductive chronology, caching, competition, and climate. J Mammal. 2012;93: 634–644. doi: 10.1644/11-MAMM-A-319.1

18. Vors LS, Boyce MS. Global declines of caribou and reindeer. Glob Chang Biol. 2009;15: 2626–2633. doi: 10.1111/j.1365-2486.2009.01974.x

19. Berger J, Schaller G, Cheng E, Kang A, Krebs M, Li L, et al. Legacies of past exploitation and climate affect mammalian sexes differently on the roof of the world—the case of wild yaks. Sci Rep. 2015; 1–6. doi: 10.1038/srep08676 25728642

20. Robertshaw D. Mechanisms for the control of respiratory evaporative heat loss in panting animals in panting animals. J Appl Physiol. 2006;11: 664–668. doi: 10.1152/japplphysiol.01380.2005 16675613

21. West G, Heard D, Caulkett N. Zoo animal and wildlife immobilization and anesthesia. Second Edi. Hoboken, NJ, USA; 2014. doi: 10.1002/9781118792919

22. Cain III JW, Krausman PR, Rosenstock SS, Turner JC. Mechanisms of thermoregulation and water balance in desert ungulates. Wildl Soc Bull. 2006;34: 570–581. doi: 10.2193/0091-7648(2006)34[570:MOTAWB]2.0.CO;2

23. Speakman JR, Krol E. Maximal heat dissipation capacity and hyperthermia risk: Neglected key factors in the ecology of endotherms. J Anim Ecol. 2010;79: 726–746. doi: 10.1111/j.1365-2656.2010.01689.x 20443992

24. Long RA, Bowyer RT, Porter WP, Mathewson P, Monteith KL, Kie JG. Behavior and nutritional condition buffer a large-bodied endotherm against direct and indirect effects of climate. Ecol Monogr. 2014;84: 513–532.

25. Hamel S, Côté S. Habitat use patterns in relation to escape terrain: are alpine ungulate females trading off better foraging sites for safety? Can J Zool. 2007;85: 933–943. doi: 10.1139/Z07-080

26. Festa-Bianchet M, Côté S. Mountain goats: ecology, behavior, and conservation of an alpine ungulate. Washington D.C.: Island Press; 2008.

27. Mead JI, Martin PS, Euler RC, Long a, Jull a J, Toolin LJ, et al. Extinction of Harrington’s mountain goat. Proc Natl Acad Sci U S A. 1986;83: 836–839. doi: 10.1073/pnas.83.4.836 16593655

28. White KS, Pendleton GW, Crowley D, Griese HJ, Kris J, Mcdonough T, et al. Mountain goat survival in coastal Alaska: effects of age, sex, and climate. J Wildl Manage. 2011;75: 1731–1744. doi: 10.1002/jwmg.238

29. White KS, Gregovich DP, Levi T. Projecting the future of an alpine ungulate under climate change scenarios. Glob Chang Biol. 2018; 1136–1149. doi: 10.1111/gcb.13919 28973826

30. Hall MHP, Fagre DB. Modeled climate-induced glacier change in Glacier National Park, 1850–2100. Bioscience. 2003;53: 131. doi: 10.1641/0006-3568(2003)053[0131:MCIGCI]2.0.CO;2

31. Belt JJ, Krausman PR. Evaluating population estimates of mountain goats based on citizen science. Wildl Soc Bull. 2012;36: 264–276. doi: 10.1002/wsb.139

32. Sarmento WM, Berger J. Human visitation limits the utility of protected areas as ecological baselines. Biol Conserv. 2017;212: 316–326. doi: 10.1016/j.biocon.2017.06.032

33. Frair JL, Fieberg J, Hebblewhite M, Cagnacci F, DeCesare NJ, Pedrotti L. Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philos Trans R Soc B Biol Sci. 2010;365: 2187–2200. doi: 10.1098/rstb.2010.0084 20566496

34. Devoe J, Arrott R, Otella J, Hallender S, Hite P. Summer range occupancy modeling of non-native mountain goats in the greater Yellowstone area. Ecosphere. 2015;6: 1–20.

35. König M, Sturm M. Mapping snow distribution in the Alaskan Arctic using aerial photography and topographic relationships. Water Resour Res. 1998;34: 3471–3483.

36. Thurfjell H, Ciuti S, Boyce MS. Applications of step-selection functions in ecology and conservation. Movement Ecology. 2014. doi: 10.1186/2051-3933-2-4 25520815

37. Fortin D, Beyer HL, Boyce MS, Smith DW, Duchesne T, Mao JS. Wolves influence elk movements: Behavior shapes a trophic cascade in Yellowstone National Park. Ecology. 2005; doi: 10.1890/04-0953

38. Avgar T, Potts JR, Lewis MA, Boyce MS. Integrated step selection analysis: bridging the gap between resource selection and animal movement. Methods Ecol Evol. 2016;7: 619–630. doi: 10.1111/2041-210X.12528

39. Johnson DH. The Comparison of Usage and Availability Measurements for Evaluating Resource Preference. Ecology. 1980; doi: 10.2307/1937156

40. Beyer HL. Geospatial modelling environment [Internet]. Brisbane, Queensland; 2012. Available: http://www.spatialecology.com/gme

41. Manly BFJ, McDonald LL, Thomas DL, McDonald TL, Erickson WP. Resource selection by animals: statistical design and analysis for field studies. Technology. 2002; 221. doi: 10.1007/0-306-48151-0

42. R Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2016. Available: https://www.r-project.org/

43. Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd ed. Wiley Series in Probability and Statistics. 2000. doi: 10.1002/0471722146

44. Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008;3: 17. doi: 10.1186/1751-0473-3-17 19087314

45. Burnham KP, Anderson DR, Huyvaert KP. AIC model selection and multimodel inference in behavioral ecology: Some background, observations, and comparisons. Behavioral Ecology and Sociobiology. 2011. pp. 23–35. doi: 10.1007/s00265-010-1029-6

46. Anderson DR, Burnham KP. Avoiding Pitfalls When Using Information-Theoretic Methods. J Wildl Manage. 2002; doi: 10.2307/3803155

47. Berger J. Group size, foraging, and antipredator ploys: an analysis of bighorn sheep decisions. Behav Ecol Sociobiol. 1978; 91–99.

48. Molvar EM, Bowyer RT. Costs and benefits of group living in a recently social ungulate: the Alaskan moose. J Mammal.: 621–630.

49. Whittingham MJ, Stephens PA, Bradbury RB, Freckleton RP. Why do we still use stepwise modelling in ecology and behaviour? J Anim Ecol. 2006; doi: 10.1111/j.1365-2656.2006.01141.x 16922854

50. Hagemoen RIM, Reimers E. Reindeer summer activity pattern in relation to weather and insect harassment. J Anim Ecol. 2002;71: 883–892. doi: 10.1046/j.1365-2656.2002.00654.x

51. Witter LA, Johnson CJ, Croft B, Gunn A, Poirier LM. Gauging climate change effects at local scales: Weather-based indices to monitor insect harassment in caribou. Ecol Appl. 2012;22: 1838–1851. doi: 10.1890/11-0569.1 23092020

52. Ito TY, Miura N, Lhagvasuren B, Enkhbileg D, Takatsuki S, Tsunekawa A, et al. Preliminary evidence of a barrier effect of a railroad on the migration of Mongolian gazelles. Conserv Biol. 2005;19: 945–948.

53. Berger J, Kock MD. Type I and Type II Errors in the Real World. J Wildl Dis. 1989;25: 451–454.

54. Mccann NP, Moen RA, Harris TR. Warm-season heat stress in moose (Alces alces). Can J Zool. 2013;898: 893–898.

55. Street GM, Rodgers AR, Fryxell JM. Mid-day temperature variation influences seasonal habitat selection by moose. J Wildl Manage. 2003;79: 505–512. doi: 10.1002/jwmg.859

56. Beest FM Van, Moorter B Van, Milner JM. Temperature-mediated habitat use and selection by a heat-sensitive northern ungulate. Anim Behav. 2012;84: 723–735. doi: 10.1016/j.anbehav.2012.06.032

57. Bowyer T, Kie JG. Timing and synchrony of parturition in Alaskan moose: long-term versus proximal effects of climate. J Mammal. 1998;79: 1332–1344.

58. Monteith KL, Klaver RW, Hersey KR, Holland AA, Thomas TP, Kauffman MJ. Effects of climate and plant phenology on recruitment of moose at the southern extent of their range. Oecologia. 2015;178: 1137–1148. doi: 10.1007/s00442-015-3296-4 25820750

59. Grayson D. The Great Basin: a natural prehistory. University of California Press; 2011.

60. Voyer AG, Smith KG, Festa-Bianchet M. Dynamics of hunted and unhunted mountain goat Oreamnos americanus populations. Wildlife Biol. 2003;9: 213–218.

61. Williams J. Mammal Compensatory reproduction and dispersal in an introduced mountain goat population in Central Montana. Wildl Soc Bull. 1999;27: 1019–1024.

62. La Sorte FA, Jetz W. Projected range contractions of montane biodiversity under global warming. Proc R Soc B Biol Sci.: 3401–3410.

63. White KS, Pendleton GW, Crowley D, Griese HJ, Hundertmark KJ, McDonough T, et al. Mountain goat survival in coastal Alaska: effects of age, sex, and climate. J Wildl Manage. 2011;75: 1731–1744. doi: 10.1002/jwmg.238

64. Hamel S, Garel M, Festa-Bianchet M, Gaillard J, Côté S. Spring Normalized Difference Vegetation Index (NDVI) predicts annual variation in timing of peak faecal crude protein in mountain ungulates. J Appl Ecol. 2009;46: 582–589. doi: 10.1111/j.1365-2664.2009.01643.x

65. Williams CM, Henry HAL, Sinclair BJ. Cold truths: How winter drives responses of terrestrial organisms to climate change. Biol Rev. 2015;90: 214–235. doi: 10.1111/brv.12105 24720862

66. Forchhammer MC, Clutton-Brock TH, Lindstrom J, Albon SD. Climate and population density induce long-term cohort variation in a northern ungulate. J Anim Ecol. 2001;70: 721–729. doi: 10.1046/j.0021-8790.2001.00532.x


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