Skip to main content
Log in

Risk and Uncertainty of Losing Suitable Habitat Areas Under Climate Change Scenarios: A Case Study for 109 Gymnosperm Species in China

  • Published:
Environmental Management Aims and scope Submit manuscript

Abstract

Taking 109 gymnosperm species in China as a case, the uncertainty and risk of losing habitat areas of gymnosperm species under future climate conditions were investigated via representative concentration pathways climate change scenarios, fuzzy set classifications and Monte Carlo techniques. Under nonrandom climate change scenarios, the richness of 109 species increased in the partial locations of northwestern and northeastern China and declined in the partial locations of eastern and central and southeastern China; the numbers of species that losing <20%, 20–40%, 40–60%, 60–80%, and over 80% of their current habitat areas were ~33–49, 36–40, 11–24, 7–9, and 2–8, respectively; ~99–105 species occupied over 80% of their total suitable areas and ~4–9 species occupied 60–80% their total suitable areas. Under random climate change scenarios, the number of species that losing various level of the habitat areas declined with enhancing probability; with a probabilities of over 0.6, the numbers of species that losing <20%, 20–40%, 40–60%, 60–80% and over 80% of their current habitat areas were ~19–28, 3–19, 0–3, 1–2, and 9–14, respectively, and the numbers of species that occupying ~20%, 20–40%, 40–60%, 60–80%, and over 80% of their total suitable areas were ~9–14, 4–11, 2–6, 1–3, and 34–45, respectively. Approximately 41% of 109 species will face extinction risks from climate change; the losing habitat areas in future climate condition will cause the varying of coniferous forest composition and the losing of ecosystem service related to the species; the uncertainty of losing distribution areas for species should not be ignored.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abramowitz M, Stegum I (1964) Handbook of mathematical functions. Dover, New York, USA

    Google Scholar 

  • Akçakaya HR, Butchart SHM, Watson JEM, Pearson RG (2014) Preventing species extinctions resulting from climate change. Nat Clim Change 4:1048–1049

    Article  Google Scholar 

  • Alexander JM, Chalmandrier L, Lenoir J, Burgess TI, Essl F, Haider S, Kueffer C, McDougall K, Milbau A, Nuñez MA, Pauchard A, Rabitsch W, Rew LJ, Sanders NJ, Pellissier L (2017) Lags in the response of mountain plant communities to climate change. Glob Change Biol 24:563–579

    Article  Google Scholar 

  • Anderson B, Borgonovo E, Galeotti M, Roson R (2014) Uncertainty in climate change modeling: can global sensitivity analysis be of help? Risk Anal 34:271–293

    Article  Google Scholar 

  • Attorre F, Alfò M, De Sanctis M, Francesconi F, Valenti R, Vitale M, Bruno F (2011) Evaluating the effects of climate change on tree species abundance and distribution in the Italian peninsula. Appl Vegetation Sci 14(2):242–255

    Article  Google Scholar 

  • Aubin I, Munson AD, Cardou F, Burton PJ, Isabel N, Pedlar JH, Paquette A, Taylor AR, Delagrange S, Kebli H, Messier C, Shipley B, Valladares F, Kattge J, Boisvert-Marsh L, McKenney D (2016) Traits to stay, traits to move: a review of functional traits to assess sensitivity and adaptive capacity of temperate and boreal trees to climate change. Environ Rev 24:164–186

    Article  Google Scholar 

  • Austin MP, Van Niel KP (2011) Improving species distribution models for climate change studies: variable selection and scale. J Biogeog 38:1–8

    Article  Google Scholar 

  • Aven T, Renn O (2015) An evaluation of the treatment of risk and uncertainties in the IPCC reports on climate change. Risk Anal 35:701–712

    Article  Google Scholar 

  • Beaumont LJ, Hughes L, Pitman AJ (2008) Why is the choice of future climate scenarios for species distribution modelling important? Eco Lett 11:1135–1146

    Article  Google Scholar 

  • Bond WJ (1989) The tortoise and the hare: ecology of angiosperm dominance and gymnosperm persistence. Biol J Linn Soc 36:227–249

    Article  Google Scholar 

  • Brodribb TJ, Pittermann J, Coomes DA (2012) Elegance versus speed: examining the competition between conifer and angiosperm trees. Int J Plant Sci 173:673–694

    Article  Google Scholar 

  • Burgman MA, Fox JC (2003) Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning. Anim Conserv 6:19–28

    Article  Google Scholar 

  • Castellanos-Acuña D, Lindig-Cisneros R, Sáenz-Romero C (2015) Altitudinal assisted migration of Mexican pines as an adaptation to climate change. Ecosphere 6(1):2. https://doi.org/10.1890/ES14-00375.1

    Article  Google Scholar 

  • Chakraborty A, Joshi PK, Sachdeva K (2016) Predicting distribution of major forest tree species to potential impacts of climate change in the central Himalayan region. Ecol Engine 97:593–609

    Article  Google Scholar 

  • Chen W, Zhang Y, Shi S, Fan Q, Zhang Z, Yang B (2013) The east-west zonal distribution of Gymnosperm floras in China and the relationship with the main climatic factors. Acta Sci Nat Univ Sunyatseni 52(5):130–139

    Google Scholar 

  • Cheng WC, Fu LK (1978) Flora reipublicae popularis Sinicae Tomus 7, Gymnospermae. Science Press, Beijing, China

    Google Scholar 

  • Crisp MD, Cook LG (2011) Cenozoic extinctions account for the low diversity of extant gymnosperms compared with angiosperms. N Phytologist 192:997–1009

    Article  CAS  Google Scholar 

  • Dullinger S, Gattringer A, Thuiller W, Moser D, Zimmermann NE, Guisan A, Willner W, Plutzar C, Leitner M, Mang T, Caccianiga M, Dirnböck T, Ertl S, Fischer A, Lenoir J, Svenning J-C, Psomas A, Schmatz R, Silc U, Vittoz P, Hülber K (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nat Clim Change 2:619–622

    Article  Google Scholar 

  • Dyderski MK, Paź S, Frelich LE, Jagodziński AM (2017) How much does climate change threaten European forest tree species distributions? Glob Change Biol 24:1150–1163

    Article  Google Scholar 

  • Engler R, Randin CF, Thuiller W, Stefan Dullinger, Zimmermann NE, Araújo MB, Pearman PB, Le Lay G, Piedallu C, Albert CH, Choler P, Coldea G, DeLamo X, Dirnböck T, Gégout J-C, Gómez-García D, Grytnes J-A, Heegaard E, Høistad F, Nogués-Bravo D, Normand S, Puşcaş M, Sebastià M-T, Sta-nisci A, Theurillat J-P, Trivedi MR, Vittoz P, Guisan A (2011) 21st century climate change threatens mountain flora unequally across Europe. Glob Change Biol 17:2330–2341

    Article  Google Scholar 

  • Fordham DA, Resit Akçakaya H, Araújo MB, Elith J, Keith DA, Pearson R, Auld TD, Mellin C, Morgan JW, Regan TJ, Tozer M, Watts MJ, White M, Wintle BA, Yates C, Brook BW (2012) Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming? Glob Change Biol 18:1357–1371

    Article  Google Scholar 

  • Fragnière Y, Bétrisey S, Cardinaux L, Stoffel M, Kozlowski G, Linder P (2015) Fighting their last stand? A global analysis of the distribution and conservation status of gymnosperms. J Biogeogr 42:809–820

    Article  Google Scholar 

  • Füssel H-M (2009) An updated assessment of the risks from climate change based on research published since the IPCC Fourth Assessment Report. Climatic Change 97(3–4):469–482

    Article  CAS  Google Scholar 

  • Greenwood O, Mossman HL, Suggitt AJ, Curtis RJ, Maclean IMD (2016) Using in situ management to conserve biodiversity under climate change. J Appl Ecol 53:885–894

    Article  Google Scholar 

  • Hülber K, Wessely J, Gattringer A, Moser D, Kuttner M, Essl F, Leitner M, Winkler M, Ertl S, Willner W, Kleinbauer I, Sauberer N, Mang T, Zimmermann NE, Dullinger S (2016) Uncertainty in predicting range dynamics of endemic alpine plants under climate warming. Glob Change Biol 22(7):2608–2619

    Article  Google Scholar 

  • IPCC (2013) Summary for Policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds). Climate Change 2013: the physical science basis. Contribution of working group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK

  • Iverson LR, Prasad AM, Matthews SN, Peters M (2008) Estimating potential habitat for 134 eastern US tree species under six climate scenarios. For Ecol Manag 254:390–406

    Article  Google Scholar 

  • Iverson LR, Schwartz MW, Prasad AM (2004) How fast and far might tree species migrate in the eastern United States due to climate change? Glob Ecol Biogeogr 13:209–219

    Article  Google Scholar 

  • Jiang S, Jiang ZH, Li W, Shen YC (2017) Evaluation of the extreme temperature and its trend in China Simulated by CMIP5 Models. Clim Change Res 13(1):11–24

    Google Scholar 

  • Jones RN (2001) An environmental risk assessment/management framework for climate change impact assessments. Nat Hazards 23(2–3):197–230

    Article  Google Scholar 

  • Kerhoulas LP, Kolb TE, Hurteau MD, Koch GW (2013) Managing climate change adaptation in forests: a case study from the U.S. Southwest. J Appl Ecol 50:1311–1320

    Article  Google Scholar 

  • Li G, Shen Z, Ying T, Fang J (2009) The spatial pattern of species richness and diversity centers of gymnosperm in China. Biodivers Sci 17(3):272–279

    Article  Google Scholar 

  • Li X, Zhu X, Wang S, Cui S, Luo C, Zhang Z, Zhang L, Jiang L, Lü W (2018) Responses of biotic interactions of dominant and subordinate species to decadal warming and simulated rotational grazing in Tibetan alpine meadow. Sci China Life Sci 61:849–859

    Article  Google Scholar 

  • Loehle C (2018) Disequilibrium and relaxation times for species responses to climate change. Ecol Mod 384:23–29

    Article  Google Scholar 

  • Lü L, Cai H, Yang Y, Wang Z, Zeng H (2018) Geographic patterns and environmental determinants of gymnosperm species diversity in China. Biodivers Sci 26(11):1133–1146

    Article  Google Scholar 

  • Ma Z, Sandel B, Svenning J (2016) Phylogenetic assemblage structure of North American trees is more strongly shaped by glacial–interglacial climate variability in gymnosperms than in angiosperms. Ecol Evol 6:3092–3106

    Article  Google Scholar 

  • Mastrandrea MD, Schneider SH (2004) Probabilistic integrated assessment of “dangerous” climate change. Science 304:571–575

    Article  CAS  Google Scholar 

  • Matthews SN, Iverson LR, Prasad AM, Peters MP, Rodewald PG (2011) Modifying climate change habitat models using tree species-specific assessments of model uncertainty and life history-factors. For Ecol Manag 262:1460–1472

    Article  Google Scholar 

  • Mina M, Bugmann H, Cordonnier T, Irauschek F, Klopcic M, Pardos M, Cailleret M, Brando P (2016) Future ecosystem services from European mountain forests under climate change. J Appl Ecol 54:389–401

    Article  Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van-Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell FB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756

    Article  CAS  Google Scholar 

  • Murphy JM, Sexton DM, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantificatin of modeling uncertainties in a large ensemble of climate change simulations. Nature 430:768–772

    Article  CAS  Google Scholar 

  • Murray KA, Verde Arregoitia LD, Davidson A, Di Marco M, Di Fonzo MMI (2014) Threat to the point:improving the value of comparative extinction risk analysis for conservation action. Glob Change Biol 20:483–494

    Article  Google Scholar 

  • Nenzén HK, Araújo MB (2011) Choice of threshold alters projections of species range shifts under climate change. Ecol Mod 222(18):3346–3354

    Article  Google Scholar 

  • Ohlemüller R, Gritti ES, Sykes MT, Thomas CD (2006) Quantifying components of risk for European woody species under climate change. Glob Change Biol 12:1788–1799

    Article  Google Scholar 

  • Olsen SL, Klanderud K (2013) Biotic interactions limit species richness in an alpine plant community, especially under experimental warming. Oikos 123:71–78

    Article  Google Scholar 

  • Pacifici M, Foden WB, Visconti P, Watson JEM, Butchart SHM, Kovacs KM, Scheffers BR, Hole DG, Martin TG, Akçakaya HR, Corlett RT, Huntley B, Bickford D, Carr JA, Hoffmann AA, Midgley GF, Pearce-Kelly P, Pearson RG, Williams SE, Willis SG, Young B, Rondinini C (2015) Asses-sing species vulnerability to climate change. Nat Clim Change 5(3):215–225

    Article  Google Scholar 

  • Peters H, O’Leary BC, Hawkins JP, Roberts CM (2015) Identifying species at extinction risk using global models of anthropogenic impact. Glob Change Biol 21:618–628

    Article  Google Scholar 

  • Pidgeon N (2012) Climate change risk perception and communication: addressing a critical moment? Risk Anal 32:951–956

    Article  Google Scholar 

  • Pittock AB, Jones RN, Mitchell CD (2001) Probabilities will help us plan for climate change. Nature 413:249

    Article  CAS  Google Scholar 

  • Preston BL (2006) Risk-based reanalysis of the effects of climate change on U.S. cold-water habitat. Clim Change 76(1–2):91–119

    Article  CAS  Google Scholar 

  • Reilly J, Stone PH, Forest CE, Webster MD, Jacoby HD, Prinn RG (2001) Uncertainty and climate change assessments. Science 293:430–433

    Article  CAS  Google Scholar 

  • Robert CP, Casella G (2004) Monte carlo statistical methods, 2nd ed. Springer-Verlag, Berlin, Heidllberg, New York, USA

    Book  Google Scholar 

  • Robertson MP, Villet MH, Palmer AR (2004) A fuzzy classification technique for predicting species distributions: applications using invasive alien plants and indigenous insects. Diver Distrib 10:461–474

    Article  Google Scholar 

  • Rogers BM, Jantz P, Goetz SJ (2017) Vulnerability of eastern US tree species to climate change. Glob Change Biol 23:3302–3320

    Article  Google Scholar 

  • Rogora M, Frate L, Carranza ML, Freppaz M, Stanisci A, Bertani I, Bottarin R, Brambilla A, Canullo R, Carbognani M, Cerrato C, Chelli S, Cremonese E, Cutini M, DiMusciano M, Erschbamer B, Godone D, Iocchi M, Isabellon M, Magnani A, Mazzola L, MorradiCella U, Pauli H, Petey M, Petriccione B, Porro F, Psenner R, Rossetti G, Scotti A, Sommaruga R, Tappeiner U, Theurillat J-P, Tomaselli M, Viglietti Viterbi DR, Vittoz P, Winkler M, Matteucci G (2018) Assessment of climate change effects on mountain ecosystems through a cross-site analysis in the Alps and Apennines. Sci Total Environ 624:1429–1442

    Article  CAS  Google Scholar 

  • Ruiz-Labourdette D, Fe Schmitz M, Pineda FD (2013) Changes in tree species composition in Mediterranean mountains under climate change: Indicators for conservation planning. Ecol Indic 24:310–323

    Article  Google Scholar 

  • Rumpf SB, Hülber K, Klonner G, Moser D, Schütz M, Wessely J, Willner W, Zimmermann NE, Dullinger S (2018) Range dynamics of mountain plants decrease with elevation. PNAS. 115(8):1848–1853

  • Stanton JC, Shoemaker KT, Pearson RG, Akçakaya HR (2015) Warning times for species extinctions due to climate change. Glob Change Biol 21:1066–1077

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorological Soc 934:485–498

    Article  Google Scholar 

  • The Research Institute of Toponomy, Chinese State Bureau of Surveying and Mapping (1997) An index to the atlas of the People’s Republic of China. Chinese map publishing house, Beijing, China

  • Thomopoulos NT (2013) Essentials of Monte Carlo simulation-statistical methods for building simulation models. Springer, New York, U.S.A, Heidelberg Dordrecht London, UK

    Book  Google Scholar 

  • Trull N, Böhm M, Carr J (2017) Patterns and biases of climate change threats in the IUCN Red List. Conserv Biol 32:135–147

    Article  Google Scholar 

  • Tylianakis JM, Didham RK, Bascompte J, Wardle DA (2008) Global change and species interactions in terrestrial ecosystems. Ecol Lett 11(12):1351–1363

    Article  Google Scholar 

  • Wang WJ, He HS, Thompson III FR, Spetich MA, Jacob S (2018) Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change. Sci Total Environ 634:1214–1221

    Article  CAS  Google Scholar 

  • Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J (2013) The inter-sectoral impact model intercomparison project ISI–MIP: project framework. PNS 111:3228–3232

    Article  CAS  Google Scholar 

  • Woodward EI, Williams BG (1987) Climate and plant distribution at global and local scales. Vege 69:189–197

    Article  Google Scholar 

  • Wu J, Shi Y (2016) Attribution index for changes in migratory bird distributions: The role of climate change over the past 50 years in China. Ecol Info 31:147–155

    Article  Google Scholar 

  • Wu J, Zhang G (2015) Can changes in the distributions of resident birds in China over the past 50 years be attributed to climate change? Ecol Evol 5(11):2215–2233

    Article  Google Scholar 

  • Wu ZY, Raven PH (1999) Flora of China, Vol 4. Cycadaceae Through Fagaceae, pp. 1–105. Science Press, Beijing & Missouri Botanical Garden Press, St. Louis

  • Xu CH, Xu Y (2012) The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble. Atmos Ocean Sci Lett 5:527–533

    Article  Google Scholar 

  • Yang Y (2015) Diversity and distribution of gymnosperms in China. Biodivers Sci 23(2):243–246

    Article  Google Scholar 

  • Ying J, Chen M, Zhang H (2003) Atlas of the gymnosperms of China. China Science & Technology Press, Beijing

    Google Scholar 

  • Ying T-S (2001) Species diversity and distribution pattern of seed plants in China. Biodivers Sci 9(4):393–398

    Google Scholar 

  • Zaniewski AE, Lehmann A, Overton JM (2002) Predicting species spatial distributions using presence—only data:a case study of native new Zealand ferns. Ecol Model 157:261–280

    Article  Google Scholar 

Download references

Acknowledgements

The work described in this paper was substantially supported by a project of the National Science and Technology Support Program of China (2012BAC19B06). Many thanks are given to instructive comments from anonymous reviewers greatly improved this manuscript. Many thanks are also given to Prof. Shaohong Wu, Dr Tao Pan and Dr Jie Pan for providing climate data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jianguo Wu.

Ethics declarations

Conflict of Interest

The author declares no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, J. Risk and Uncertainty of Losing Suitable Habitat Areas Under Climate Change Scenarios: A Case Study for 109 Gymnosperm Species in China. Environmental Management 65, 517–533 (2020). https://doi.org/10.1007/s00267-020-01262-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00267-020-01262-z

Keywords

Navigation