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The predicted effects of climate change on local species distributions around Beijing, China

  • Lichun Mo
  • Jiakai Liu
  • Hui Zhang
  • Yi XieEmail author
Original Paper

Abstract

To assist conservationists and policymakers in managing and protecting forests in Beijing from the effects of climate change, this study predicts changes for 2012–2112 in habitable areas of three tree species—Betula platyphylla, Quercus palustris, Platycladus orientalis, plus other mixed broadleaf species—in Beijing using a classification and regression tree niche model under the International Panel on Climate Change’s A2 and B2 emissions scenarios (SRES). The results show that climate change will increase annual average temperatures in the Beijing area by 2.0–4.7 °C, and annual precipitation by 4.7–8.5 mm, depending on the emissions scenario used. These changes result in shifts in the range of each of the species. New suitable areas for distributions of B. platyphylla and Q. palustris will decrease in the future. The model points to significant shifts in the distributions of these species, withdrawing from their current ranges and pushing southward towards central Beijing. Most of the ranges decline during the initial 2012–2040 period before shifting southward and ending up larger overall at the end of the 88-year period. The mixed broadleaf forests expand their ranges significantly. The P. orientalis forests, on the other hand, expand their range marginally. The results indicate that climate change and its effects will accelerate significantly in Beijing over the next 88 years. Water stress is likely to be a major limiting factor on the distribution of forests and the most important factor affecting migration of species into and out of existing nature reserves. There is a potential for the extinction of some species. Therefore, long-term vegetation monitoring and warning systems will be needed to protect local species from habitat loss and genetic swamping of native species by hybrids.

Keywords

Climate change Classification and regression tree Plant distribution Scenario A2 and B2 Simulation analysis 

Notes

Acknowledgements

This research was supported by the Fundamental Research Funds for the Central University (2018RD001).

Compliance with ethical standards

Conflict of interests

The authors declare that they have no conflict of interests.

References

  1. Bachelet D, Neilson RP, Lenihan JM, Drapek RJ (2001) Climate change effects on vegetation distribution and carbon budget in the United States. Ecosystems 4:164–185CrossRefGoogle Scholar
  2. Bakkenes M, Alkemade JRM, Ihle F (2002) Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050. Glob Change Biol 8:390–407CrossRefGoogle Scholar
  3. Bertin RI (2008) Plant phenology and distribution in relation to recent climate change. J Torrey Bot Soc 135:126–146CrossRefGoogle Scholar
  4. Bonis NR, Kuerschner WM (2012) Vegetation history, diversity patterns, and climate change across the Triassic/Jurassic boundary. Paleobiology 38:240–264CrossRefGoogle Scholar
  5. Britton JR, Cucherousset J, Davies GD, Godard MJ, Copp GH (2010) Non-native fishes and climate change: predicting species responses to warming temperatures in a temperate region. Freshw Biol 55:1130–1141CrossRefGoogle Scholar
  6. Brundu G, Richardson DM (2016) Planted forests and invasive alien trees in Europe: a code for managing existing and future plantings to mitigate the risk of negative impacts from invasions. NeoBiota 30:5–47CrossRefGoogle Scholar
  7. Camenen E, Porte AJ, Benito Garzon M (2016) American trees shifts their niches when invading Western Europe: evaluating invasion risks in a changing climate. Ecol Evol 6:7263–7275CrossRefGoogle Scholar
  8. Cao MC, Zhou GS, Weng ES (2005) Application and comparison of generalized models and classification and regression tree in simulating tree species distribution. Acta Ecol Sin 25(8):2031–2040 (in Chinese) Google Scholar
  9. Costion CM, Simpson L, Pert PL, Carlsen MM, Kress WJ, Crayn D (2015) Will tropical mountaintop plant species survive climate change? Identifying key knowledge gaps using species distribution modelling in Australia. Biol Cons 191:322–330CrossRefGoogle Scholar
  10. Dieleman CM, Branfireun BA, Mclaughlin JW, Lindo Z (2015) Climate change drives a shift in peatland ecosystem plant community: implications for ecosystem function and stability. Glob Change Biol 21:388–395CrossRefGoogle Scholar
  11. Duarte CM, Losada IJ, Hendriks IE, Mazarrasa I, Marbà N (2013) The role of coastal plant communities for climate change mitigation and adaptation. Nat Clim Change 3:961–968CrossRefGoogle Scholar
  12. Dukes JS, Pontius J, Orwig D, Garnas JR, Rodgers VL, Brazee N, Cooke B, Theoharides KA, Stange EE, Harrington R, Ehrenfeld J, Gurevitch J, Lerdau M, Stinson K, Wick R, Ayres M (2009) Responses of insect pests, pathogens, and invasive plant species to climate change in the forests of northeastern North America: what can we predict? Can J For Res 39:231–248CrossRefGoogle Scholar
  13. Dyderski MK, Paz S, Frelich LE, Jagodzinski AM (2018) How much does climate change threaten European forest tree species distributions? Glob Change Biol 24:1150–1163CrossRefGoogle Scholar
  14. Elmendorf SC, Henry GHR, Hollister RD, Fosaa AM, Gould WA, Hermanutz L, Hofgaard A, Jonsdottir IS, Jorgenson JC, Levesque E, Magnusson B, Molau U, Myers-Smith IH, Oberbauer SF, Rixen C, Tweedie CE, Walker MD (2015) Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns. Proc Natl Acad Sci 112:448–452CrossRefGoogle Scholar
  15. Erasmus BFN, Vanjaarsveld SA, Chown SL (2002) Vulnerability of South African animal taxa to climate change. Glob Change Biol 8:679–693CrossRefGoogle Scholar
  16. Feurdean A, Tămaş T, Tanţău I, Fărcaş S (2014) Elevational variation in the biotic response to repeated climate changes in the Carpathians. Georev Sci Ann Stefan Cel Mare Univ Suceava Geogr Ser 20(2):1Google Scholar
  17. Filipe Dos Santos CA, Leitao AE, Pais IP, Lidon FC, Ramalho JC (2015) Perspectives on the potential impacts of climate changes on coffee plant and bean quality. Emir J Food Agric 27:152–163CrossRefGoogle Scholar
  18. Gao X, Shi Y, Han Z, Wang M, Wu J, Zhang D, Xu Y, Giorgi F (2017) Performance of RegCM4 over major river basins in China. Adv Atmos Sci 34:441–455CrossRefGoogle Scholar
  19. Gomez JM, Gonzalez-Megias A, Lorite J, Abdelaziz M, Perfectti F (2015) The silent extinction: climate change and the potential hybridization-mediated extinction of endemic high-mountain plants. Biodivers Conserv 24:1843–1857CrossRefGoogle Scholar
  20. Gottfried M, Pauli H, Futschik A, Akhalkatsi M, Barancok P, Benito Alonso JL, Coldea G, Dick J, Erschbamer B, Fernandez Calzado MR, Kazakis G, Krajci J, Larsson P, Mallaun M, Michelsen O, Moiseev D, Moiseev P, Molau U, Merzouki A, Nagy L, Nakhutsrishvili G, Pedersen B, Pelino G, Puscas M, Rossi G, Stanisci A, Theurillat J, Tomaselli M, Villar L, Vittoz P, Vogiatzakis I, Grabherr G (2012) Continent-wide response of mountain vegetation to climate change. Nat Clim Change 2:111–2115CrossRefGoogle Scholar
  21. Guisan A, Thuiller W, Zimmermann NE (2017) Habitat suitability and distribution models with application R. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  22. Hao ZQ, Dai LM, He HS (2001) Potential response of major trees pieces to climate warming in Changbai Mountain, northeast China. Chin J Appl Ecol 12(5):653–658 (in Chinese) Google Scholar
  23. Hill MO, Preston CD (2015) Disappearance of boreal plants in southern Britain: habitat loss or climate change? Biol J Lin Soc 115:598–610CrossRefGoogle Scholar
  24. Hoveka LN, Bezeng BS, Yessoufou K, Boatwright JS, Van der Bank M (2016) Effects of climate change on the future distributions of the top five freshwater invasive plants in South Africa. S Afr J Bot 102:33–38CrossRefGoogle Scholar
  25. IPCC (2014) [Intergovernmental Panel on Climate Change]. Observed changes and their causes. In: Pachauri RK, Meyer LA (eds) Climate change 2014: synthesis report, contribution of working Group I, II and III to the fifth assessment report of the intergovernmental panel on climate change. Core writing team, IPCC. Switzerland. www.ipcc.ch/pdf/assessment-report/ar5/syr/SYR_AR5_FINAL_full_wcover.pdf. Accessed on 12 Dec 2018
  26. Iverson LR, Prasad AM (2001) Potential change in tree species richness and forest community types following climate change. Ecosystems 4:186–199CrossRefGoogle Scholar
  27. Jiang W, Yang X, Cheng Y (2014) Spatial patterns of vegetation and climate on the Chinese Loess Plateau since the last glacial maximum. Quat Int 334–335:52–60CrossRefGoogle Scholar
  28. Liu N, Jing Y, Lloyd H, Sun Y (2012) Assessing the distributions and potential risks from climate change for the Sichuan Jay (Perisoreus internigrans). Condor 114:365–376CrossRefGoogle Scholar
  29. Maclean IMD, Hopkins JJ, Bennie J, Lawson CR, Wilson RJ (2015) Microclimates buffer the responses of plant communities to climate change. Glob Ecol Biogeogr 24:1340–1350CrossRefGoogle Scholar
  30. Magyari EK, Jakab G, Balint M, Kern Z, Buczkó K, Braun M (2012) Rapid vegetation response to late glacial and early Holocene climatic fluctuation in the South Carpathian Mountains (Romania). Quat Sci Rev 35:116–130CrossRefGoogle Scholar
  31. McCarty JP (2001) Ecological consequences of recent climate change. Conserv Biol 115(2):320–331CrossRefGoogle Scholar
  32. Nie Q, Xu J (2013) The relationship between vegetation coverage and climate elements in Yellow River Basin, China. No. e153v1. PeerJ PreePrinterGoogle Scholar
  33. Richards WH, Koeck R, Gersonde R, Kuschnig G, Fleck W, Hochbichler E (2012) Landscape-scale forest management in the municipal watersheds of Vienna, Austria, and Seattle, USA: commonalities despite disparate ecology and history. Nat Areas J 32:199–207CrossRefGoogle Scholar
  34. Rouge M, Richardson DM, Lavorel S (2001) Determinants of distribution of six Pinus species in Catalonia, Spain. J Veg Sci 12:491–502CrossRefGoogle Scholar
  35. Saenz-Romero C, Lamy J-B, Ducousso A, Musch B, Ehrenmann F, Delzon S, Cavers S, Chałupka W, Dağdaş S, Hansen JK, Lee SJ, Liesebach M, Rao HM, Psomas A, Schneck V, Steiner W, Zimmermann NE, Kremer A (2017) Adaptive and plastic responses of Quercus petraea populations to climate across Europe. Glob Change Biol 23:2831–2847CrossRefGoogle Scholar
  36. Scheffer BR, Meester LD, Bridge TCL, Hoffmann AA, Pandolfi JM, Corlett RT, Butchart SHM, Pearce-Kelly P, Kovacs KM, Dudgeon D, Pacifici M, Rondinini C, Foden WB, Martin TG, Mora C, Bickford D, Watson JEM (2016) The broad footprint of climate change from genes to biomes to people. Science 354(6313):aaf7671CrossRefGoogle Scholar
  37. Seebens H, Essl F, Dawson W, Fuentes N, Moser D, Pergl J, Pysek P, van Kleunen M, Weber E, Winter M, Blasius B (2015) Global trade will accelerate plant invasions in emerging economies under climate change. Glob Change Biol 21:4128–4140CrossRefGoogle Scholar
  38. Shafer SL, Bartlein PJ, Thompson RS (2001) Potential changes in the distribution of western north America tree and shrub taxa under future climate scenarios. Ecosystems 4:209–215CrossRefGoogle Scholar
  39. Shen M, Piao S, Dorji T, Liu Q, Cong N, Chen X, An S, Wang S, Wang T, Zhang G (2015) Plant phenological responses to climate change on the Tibetan Plateau: research status and challenges. Natl Sci Rev 2:454–467CrossRefGoogle Scholar
  40. Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor MMB (2007) Change 2007: the physical science basis: working group i contribution to the fourth assessment report of the IPCC, vol 4. Cambridge University Press, Cambridge, pp 1–21Google Scholar
  41. Sunday JM, Bates AE, Dulvy NK (2012) Thermal tolerance and the global redistribution of animals. Nat Clim Change 2:686–690CrossRefGoogle Scholar
  42. Tanţău I, Feurdean A, De Beaulieu J, Reille M, Fărcaş S (2014) Vegetation sensitivity to climate changes and human impact in the Harghita Mountains (Eastern Romanian Carpathians) over the past 15 000 years. J Quat Sci 29:141–152CrossRefGoogle Scholar
  43. Thomas CD, Cameron A, Green RE (2004) extinct ion risk from climate change. Nature 427:145–148CrossRefGoogle Scholar
  44. Thuiller W, Araújo MB, Lavorel S (2003) Generalized models versus classification tree analysis: a comparative study for predicting spatial distributions of plant species at different scales. J Veg Sci 1:669–680CrossRefGoogle Scholar
  45. Tomiolo S, van der Putten WH, Tielboerger K (2015) Separating the role of biotic interactions and climate in determining adaptive response of plants to climate change. Ecology 96:1298–1308CrossRefGoogle Scholar
  46. United Nations Environment Programme (UNEP) (2015) Minimizing the scale and impact of climate change. www.unep.org/annualreport/2014/en/pdf/climate_change.pdf. Accessed on 12 Dec 2018
  47. Valdes AE (2015) Forced adaptation: plant proteins to fight climate change. Front Plant Sci 5:762Google Scholar
  48. Vayssières MP, Plant RE, Allen-Diaz BH (2000) Classification trees: an alternative non-parametric approach for predicting species distributions. J Veg Sci 11:679–694CrossRefGoogle Scholar
  49. Vishwas C, Ramesh S, Mir M (2018) Assessing the impacts of climates change on distribution of major non-timber forest plants in Chitwan Annapurna Landscape, Nepal. Resources 7(4):66CrossRefGoogle Scholar
  50. West RM (2012) Generalised additive models. In: Tu Y, Greenwood DC (eds) Modern methods for epidemiology. Springer, Dordrecht, pp 261–278CrossRefGoogle Scholar
  51. Woodward FI, Williams BG (1987) Climate and plant distribution at global and local scales. Vegetation 69:189–197CrossRefGoogle Scholar
  52. Yi S, Saito Y, Zhao Q, Wang P (2003) Vegetation and climate changes in the Changjiang (Yangtze River) Delta, China, during the past 13,000 years inferred from pollen records. Quat Sci Rev 22:1501–1519CrossRefGoogle Scholar

Copyright information

© Northeast Forestry University 2019

Authors and Affiliations

  1. 1.School of Economies and ManagementBeijing Forestry UniversityBeijingPeople’s Republic of China
  2. 2.School of Nature ConservationBeijing Forestry UniversityBeijingPeople’s Republic of China

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