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Biodiversity and Conservation

, Volume 25, Issue 3, pp 555–568 | Cite as

Climate change impacts on endemic, high-elevation lichens in a biodiversity hotspot

  • Jessica L. Allen
  • James C. Lendemer
Original Paper

Abstract

Previous studies of the impacts of climate change on lichens and fungi have focused largely on alpine and subalpine habitats, and have not investigated the potential impact on narrowly endemic species. Here, we estimate the impacts of climate change on high-elevation, endemic lichens in the southern Appalachians, a global diversity hotspot for many groups of organisms, including lichens. We conducted extensive field surveys in the high elevations of the region to accurately document the current distributions of eight narrowly endemic lichen species. Species distribution modeling was used to predict how much climatically suitable area will remain within, and north of, the current range of the target species under multiple climate change scenarios at two time points in the future. Our field work showed that target species ranged from extreme rarity to locally abundant. Models predicted over 93 % distributional loss for all species investigated and very little potentially suitable area north of their current distribution in the coming century. Our results indicate that climate change poses a significant threat to high-elevation lichens, and provide a case study in the application of current modeling techniques for rare, montane species.

Keywords

Species distribution modeling Rare species Mountain top extinction Spruce-fir Symbiosis 

Notes

Acknowledgments

We thank Drs. Robert Anderson, Richard Harris, and Erin Tripp for helpful discussion regarding this project. We would also like to thank Sean McKenzie and Jenna Dorey for their field work assistance. We appreciate the work of Gary Kauffman (USFS), Paul Super (GSMNP), Ed Corey (NCSP), and Blue Ridge Parkway for the issuance of permits. This research was supported by the National Science Foundation Graduate Research Fellowship, Highland Biological Station Science and Society Fellowship, the Southern Appalachian Botanical Society, and the City University of New York Doctoral Student Research Grant. The second author was supported by NSF DEB#1145511.

Supplementary material

10531_2016_1071_MOESM1_ESM.docx (12 kb)
Supplementary material 1 (DOCX 13 kb)

References

  1. Aiello-Lammens ME, Boria RA, Radosavljevic A, Vilela B, Anderson RP (2015) spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography. doi: 10.1111/ecog.01132 Google Scholar
  2. All Taxa Biodiversity Inventory (ATBI) (2014) http://www.dlia.org/smokies-species-tally. Accessed Nov 2014
  3. Anderson RP, Gonzalez I (2011) Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with Maxent. Ecol Model 222:2796–2811CrossRefGoogle Scholar
  4. Anderson RP, Raza A (2010) The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. J Biogeogr 37:1378–1393CrossRefGoogle Scholar
  5. Aptroot A, van Herk CM (2006) Further evidence of the effects of global warming on lichens, particularly those with Trentepohlia phycobionts. Environ Pollut 146:293–298CrossRefPubMedGoogle Scholar
  6. Arnold AE, Miadlikowska J, Higgins KL, Sarvate SD, Gugger P, Way A, Hofstetter V, Kauff F, Lutzoni F (2009) A phylogenetic estimation of trophic transition networks for ascomycetous fungi: are lichens cradles of symbiotrophic fungal diversification? Syst Biol 58:283–297CrossRefPubMedGoogle Scholar
  7. Austin MP (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modeling. Ecol Model 157:101–118CrossRefGoogle Scholar
  8. Belinchón R, Yahr R, Ellis CJ (2015) Interactions among species with contrasting dispersal modes explain distributions for epiphytic lichens. Ecography 38:762–768CrossRefGoogle Scholar
  9. Bjerke JW (2011) Winter climate change: ice encapsulation at mild subfreezing temperature kills freeze-tolerant lichens. Environ Exp Bot 72:404–408CrossRefGoogle Scholar
  10. Braun EL (1950) Decidous forests of eastern North America. Blakiston, PhiladelphiaGoogle Scholar
  11. Brodo IM, Sharnoff SD, Sharnoff S (2001) Lichens of North America. Yale University Press, New Haven and LondonGoogle Scholar
  12. Colwell RK, Brehm G, Cardelús CL, Gilman AC, Longino JT (2008) Global warming, elevational range shifts, and lowland biotic attrition in the wet tropics. Science 322:258–261CrossRefPubMedGoogle Scholar
  13. Crabtree D, Ellis CJ (2010) Species interaction and response to wind speed alter the impact of projected temperature change in a montane ecosystem. J Veg Sci 21:744–760Google Scholar
  14. Culatta KE, Horton JL (2014) Physiological response of southern Appalachian high-elevation rock outcrop herbs to reduced cloud immersion. Castanea 79:182–194CrossRefGoogle Scholar
  15. Culberson CF, Kristinsson H (1970) A standardized methods for the identification of lichen products. J Chromatogr 46:85–93CrossRefGoogle Scholar
  16. DePriest P (1984) Southern Appalachian lichens: an indexed bibliography. National Park Service, Southeast Regional Office, AtlantaGoogle Scholar
  17. Dey JP (1978) Fruticose and foliose lichens of the high-mountain areas of the southern Appalachians. Bryologist 81:1–93CrossRefGoogle Scholar
  18. Dirnböck T, Essl F, Rabitsch W (2011) Disproportional risk for habitat loss of high-altitude endemic species under climate change. Glob Change Biol 17:990–996CrossRefGoogle Scholar
  19. Dobrowski SZ (2010) A climatic basis for microrefugia: the influence of terrain on climate. Glob Change Biol 17:1022–1035CrossRefGoogle Scholar
  20. Dullinger S, Gattringer A, Thuiller W, Moster D, Zimmermann NE, Guisan A, Willner W, Plutzar C, Leitner M, Mang T, Caccianiga M, Dirnböck T, Ertl S, Fischer A, Lenoir J, Svenning JC, Psomas A, Schmatz DR, Silc U, Vittoz P, Hülber K (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nat Clim Change 2:619–622CrossRefGoogle Scholar
  21. Elith J, Graham CH (2009) Do they? How do they? Why do they differ? On finding reasons for differing performances of species distribution models. Ecography 32:66–77CrossRefGoogle Scholar
  22. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697CrossRefGoogle Scholar
  23. Elith J, Graham CH, Anderson RP, Dudık M, Ferrier S, Guisan A et al (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151CrossRefGoogle Scholar
  24. Ellis CJ (2013) A risk-based model of climate change threat: hazard, exposure, and vulnerability in the ecology of lichen epiphytes. Botany 91:1–11CrossRefGoogle Scholar
  25. Ellis CJ, Eaton S, Theodoropoulos M, Coppins BJ, Seaward MRD, Simkin J (2014) Response of epiphytic lichens to 21st centry climate change and tree disease scenarios. Biol Conserv 180:153–164CrossRefGoogle Scholar
  26. Harsch MA, Hulme PE, McGlone MS, Duncan RP (2009) Are treelines advancing? A global meta-analysis of treeline response to climate warming. Ecol Lett 12:1040–1049CrossRefPubMedGoogle Scholar
  27. Henderson A, Hackett DJ (1986) Lichen and algal camouflage and dispersal in the psocid nymph Trichadentotecnum fasciatum. Lichenologist 18:199–200CrossRefGoogle Scholar
  28. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  29. Hodkinson BP, Lutzoni F (2009) A microbiotic survey of lichen-associated bacteria reveals a new lineage from the Rhizobiales. Symbiosis 49:163–180CrossRefGoogle Scholar
  30. Jin S, Yang L, Danielson P, Homer C, Fry J, Xian G (2013) A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sens Environ 132:159–175CrossRefGoogle Scholar
  31. Kelly AE, Goulden ML (2008) Rapid shifts in plant distribution with recent climate change. Proc Natl Acad Sci USA 105:11823–11826CrossRefPubMedPubMedCentralGoogle Scholar
  32. Kenis M, Auger-Rozenberg MA, Roques A, Timms L, Péré C, Cock MJ, Settele J, Augustin S, Lopez-Vaamonde C (2009) Ecological effects of invasive alien insects. In: Langor D, Sweeny J (eds) Ecological impacts of non-native invertebrates and fungi on terrestrial ecosystem. Springer, Dordrecht, pp 21–24CrossRefGoogle Scholar
  33. Klanderud K (2008) Species-specific responses of an alpine plant community under simulated environmental change. J Veg Sci 19:363–372CrossRefGoogle Scholar
  34. Klanderud K, Totland Ø (2005) Simulated climate change altered dominance hierarchies and diversity of an alpine biodiversity hotspot. Ecology 86:2047–2054CrossRefGoogle Scholar
  35. Kramer-Schadt S, Niedball J, Pilgrim JD, Schröder B, Lindenborn J, Reinfelder V, Stillfried M, Heckmann I, Scharf AK, Augeri DM, Cheyne SM, Hearn AJ, Ross J, Macdonald DW, Mathai J, Eaton J, Marshall AJ, Semiadi G, Rustam R, Bernard H, Alfred R, Samejima H, Duckworth JW, Breitenmoser-Wuersten C, Belant JL, Hofer H, Wilting A (2013) The importance of correcting for sampling bias in MaxEnt species distribution models. Divers Distrib 19:1366–1379CrossRefGoogle Scholar
  36. Laseter SH, Ford CR, Vose JM, Swift LW (2012) Long-term temperature and precipitation trends at the Coweeta Hydrologic Laboratory, Otto, North Carolina, USA. Hydrol Res 43:890–901CrossRefGoogle Scholar
  37. Lendemer JC (2011) A review of the morphologically similar species Fuscidea pusilla and Ropalospora viridis in eastern North America. Opusc Philolichenum 9:11–20Google Scholar
  38. Lendemer JC, Allen JL (2014) Lichen biodiversity under threat from sea-level rise in the Atlantic Coastal Plain. Bioscience 64:923–931CrossRefGoogle Scholar
  39. Lendemer JC, Allen JL (2015) Reassessment of Hypotrachyna virginica, an endangered, endemic Appalachian macrolichen, and the morphologically similar species with which it has been confused. Proc Acad Natl Sci Phila 164:279–289CrossRefGoogle Scholar
  40. Lendemer JC, Harris RC (2013) Buellia sharpiana (Physciaceae, lichenized Ascomycetes), another new species from the Great Smoky Mountains of eastern North America. Castanea 78:148–153CrossRefGoogle Scholar
  41. Lendemer JC, Harris RC, Tripp EA (2013) The lichens and allied fungi of Great Smoky Mountains National Park: an annotated checklist with comprehensive keys. Mem N Y Bot Gard 104:1–152Google Scholar
  42. Liu C, White M, Newell G (2013) Selecting thresholds for the prediction of species occurrence with presence-only data. J Biogeogr 40:778–789CrossRefGoogle Scholar
  43. Lomba A, Pellissier L, Randin C, Vicente J, Moreira F, Honrado J, Guisan A (2010) Overcoming the rare species modeling paradox: a novel hierarchical framework applied to an Iberian endemic plant. Biol Conserv 143:2647–2657CrossRefGoogle Scholar
  44. Martinez-Meyer E (2005) Climate change and biodiversity: some considerations in forecasting shifts in species’ potential distributions. Biodivers Inform 2:42–55CrossRefGoogle Scholar
  45. McCune B, Dey J, Peck J, Helman K, Will-Wolf S (1997) Regional gradients in lichen communities of the Southeast United States. Bryologist 100:145–158CrossRefGoogle Scholar
  46. McManamay RH, Resler LM, Campbell JB, McManamay RA (2011) Assessing the impacts of the balsam woolly adelgid (Adelges piceae Ratz.) and anthropogenic disturbance on the stand structure and mortality of Fraser Fir [Abies fraseri (Pursh) Poir.] in the Black Mountains, North Carolina. Castanea 76:1–19CrossRefGoogle Scholar
  47. Merow C, Smith MJ, Silander JA (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36:1058–1069CrossRefGoogle Scholar
  48. Mitchell RJ, Liu Y, O’Brien JJ, Elliott KJ, Starr G, Miniat CF, Hiers JK (2014) Future climate and fire interactions in the southeastern region of the United States. For Ecol Manag 3271:316–326CrossRefGoogle Scholar
  49. Muscarella R, Galante PJ, Soley-Guardia M, Boria RA, Kass JM, Uriarte M, Anderson RP (2014) ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol Evol 5:1198–1205CrossRefGoogle Scholar
  50. Noss RF, LaRoe ET III, Scott JM (1995) Endangered ecosystems of the United States: a preliminary assessment of loss and degredation. Department of the Interior, Washington DCGoogle Scholar
  51. Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol Syst 37:637–669CrossRefGoogle Scholar
  52. Peterson AT, Soberón J, Pearson RG, Anderson RP, Martinez-Meyer E, Nakamura M, Araújo MB (2011) Ecological niches and geographic distributions. Monogr Popul Biol 49:1–314Google Scholar
  53. Phillips SJ, Dudik M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161–175CrossRefGoogle Scholar
  54. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259CrossRefGoogle Scholar
  55. Pickering J, Kays R, Meier A, Andrew S, Yatskievych R (2003) The Appalachians. In: Mittermeier RA, Mittermeier CG, Gil PR, Pilgrim J (eds) Wilderness—Earth’s last wild places. Conservation International, Washington, DC, pp 458–467Google Scholar
  56. QGIS Development Team (2014) QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org
  57. R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0. http://www.R-project.org
  58. Radosavljevic A, Anderson R (2014) Making better MAXENT models of species distributions: complexity, overfitting and evaluation. J Biogeogr 41:629–643CrossRefGoogle Scholar
  59. Raxworthy CJ, Pearson RG, Rabibisoa N, Rakotondrazafy AM, Ramanamanjato JP, Raselimanana AP, Wu S, Nussbaum RA, Stone DA (2008) Extinction vulnerability of tropical montane endemism from warming and upslope displacement: a preliminary appraisal for the highest massif in Madagascar. Glob Change Biol 14:1703–1720CrossRefGoogle Scholar
  60. Richardson AD, Denny EG, Siccama TG, Lee X (2003) Evidence for a rising cloud ceiling in eastern North America. J Clim 16:2093–2098CrossRefGoogle Scholar
  61. Rollins AW, Adams HS, Stephenson SL (2010) Changes in forest composition and structure across the red spruce-hardwood ecotone in the central Appalachians. Castanea 75:303–314CrossRefGoogle Scholar
  62. Rull V (2009) Microrefugia. J Biogeogr 36:481–484CrossRefGoogle Scholar
  63. Shcheglovitova M, Anderson RP (2013) Estimating optimal complexity for ecological niche models: a jackknife approach for species with small sample sizes. Ecol Model 269:9–17CrossRefGoogle Scholar
  64. Søchting U (2004) Flavoparmelia caperata—a probable indicator of increased temperatures in Denmark. Graph Scr 15:53–56Google Scholar
  65. Spasojevic MJ, Bowman WD, Humpries HC, Seastedt TR, Suding KN (2013) Changes in alpine vegetation over 21 years: are patterns across a heterogeneous landscape consistent with predictions? Ecosphere 4:art117Google Scholar
  66. Thuiller W, Albert C, Araújo MB, Berry PM, Cabeza M, Guisan A, Hickler T, Midgley GF, Paterson P, Schurr FM, Sykes MT, Zimmermann NE (2008) Predicting global change impacts on plant species’ distributions: future challenges. Perspect Plant Ecol 9:137–152CrossRefGoogle Scholar
  67. U.S. Fish and Wildlife Service (USFWS) (1998) Recovery plan for the spruce-fir moss spider. Atlanta, GeorgiaGoogle Scholar
  68. Warren DL, Seifert SN (2011) Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol Appl 21:335–342CrossRefPubMedGoogle Scholar
  69. Wear DN, Greis JG (2011) The Southern Forest Future Project: summary report. General Technical Report SRS-GTR-168. USDA-Forest Service, Southern Research Station, AshevilleGoogle Scholar
  70. White RD, Patterson KD, Weakley A, Ulrey CJ, Drake J (2003) Vegetation classification of Great Smoky Mountains National Park. Report submitted to BRD-NPS Vegetation Mapping Program. NatureServe, DurhamGoogle Scholar
  71. White PB, van de Gevel SL, Soulé PT (2012) Succession and disturbance in an endangered red spruce-Fraser fir forest in the southern Appalachian Mountains, North Carolina, USA. Endanger Species Res 18:17–25CrossRefGoogle Scholar
  72. Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, NCEAS Predicting Species Distributions Working Group (2008) Effects of sample size on the performance of species distributions models. Divers Distrib 14:763–773Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Institute of Systematic BotanyThe New York Botanical GardenBronxUSA
  2. 2.Biology DepartmentThe City University of New York Graduate CenterNew YorkUSA

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