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Annals of Forest Science

, Volume 71, Issue 2, pp 201–210 | Cite as

The incorporation of extreme drought events improves models for beech persistence at its distribution limit

  • Ervin Rasztovits
  • Imre Berki
  • Csaba Mátyás
  • Kornél Czimber
  • Elisabeth Pötzelsberger
  • Norbert Móricz
Original Paper

Abstract

Context

Projections of species distribution models under future climate are usually based on long-term averages. However, singular extreme drought events presumably contribute to the shaping of distribution limits at the retreating low-elevation xeric limits.

Methods

The objectives of this study were to set up a distribution model based on extreme drought events (EDM), which uses sanitary logging information as a proxy of vitality response of beech, and compare it with the results of classical species distribution models (SDMs).

Results

Predictions of the EDM for 2025 were in agreement with those of the SDM, but EDM predicted a more serious decline in all regions of Hungary towards the end of the century.

Conclusion

These results suggest that the predicted increase in frequency and severity of drought events may further limit the distribution of beech in the future.

Keywords

Beech Trailing edge Climate change Xeric limit Predictive modelling 

Notes

Acknowledgments

We would like to acknowledge Dr Tibor Szép who helped in providing the occurrence and sanitary logging data. We also thank Prof. Dr Hubert Hasenauer for his personal communication regarding the methods of modelling.

Funding

This research was funded by the Austrian–Hungarian Transboundary Cooperation 2007–2013 (‘FaKlim’ project—L00044), by TÁMOP-4.2.2.A-11/1/KONV-2012–0013 and by the FORGER (‘Towards the Sustainable Management of Forest Genetic Resources in Europe’—289119) project.

Supplementary material

13595_2013_346_MOESM1_ESM.pdf (29 kb)
Online Resource 1 (PDF 28 kb)
13595_2013_346_MOESM2_ESM.pdf (503 kb)
Online Resource 2 (PDF 503 kb)

References

  1. AGROTOPO (2002) AGROTOPO database of RISSAC, HAS, BudapestGoogle Scholar
  2. Aranda I, Forner A, Cuesta B, Valladares F (2012) Species-specific water use by forest tree species: from the tree to the stand. Agric Water Manag 114:67–77CrossRefGoogle Scholar
  3. Araújo MB, Pearson RG, Thuiller W, Erhard M (2005) Validation of species-climate impact models under climate change. Glob Chang Biol 11:1504–1513CrossRefGoogle Scholar
  4. Austin MP (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol Model 157:101–118CrossRefGoogle Scholar
  5. Betsch P, Bonal D, Breda N, Montpied P, Peiffer M, Tuzet A, Granier A (2011) Drought effects on water relations in beech: the contribution of exchangeable water reservoirs. Agric Forest Meteorol 151:531–543CrossRefGoogle Scholar
  6. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Chapman & Hall, New YorkGoogle Scholar
  7. Budyko MI (1974) Climate and life. Academic, OrlandoGoogle Scholar
  8. Chow GC (1960) Tests of equality between sets of coefficients in two linear regressions. Econometrica 28:591–605CrossRefGoogle Scholar
  9. Czúcz B, Gálhidy L, Mátyás C (2010) Limiting climating factors and potential future distribution of beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Mattuscha) Liebl.) forests near their low altitude–xeric limit in Central Europe. Ann For Sci 68:99–108CrossRefGoogle Scholar
  10. Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S, Guisan A, Hijmans RJ, Huettmann JR, Lehmann A, Li J, Lucia G, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMC, Peterson AT, Phillips SJ, Richardson KS, Scachetti-Pereira R, Schapire RE, Soberón J, Williams S, Wisz MS, Zimmermann NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151CrossRefGoogle Scholar
  11. Ellenberg H (1986) Vegetation Mitteleuropas mit den Alpen, 4th edn. Fischer, StuttgartGoogle Scholar
  12. Franke J, Köstner B (2007) Effects of recent climate trends on the distribution of potential natural vegetation in Central Germany. Int J Biometeorol 52:139–147PubMedCrossRefGoogle Scholar
  13. Gálos B, Lorenz P, Jacob D (2007) Will dry events occur more often in Hungary in the future? Environ Res Lett 2:034006CrossRefGoogle Scholar
  14. Gärtner S, Reif A, Xystrakis F, Sayer U, Bendagha N, Matzarakis A (2008) The drought tolerance limit of Fagus sylvatica forests on limestone in southwestern Germany. J Veg Sci 19:757–768CrossRefGoogle Scholar
  15. Geßler A, Keitel C, Kreuzwieser J, Matyssek R, Seiler W, Rennenberg H (2007) Potential risks for European beech (Fagus sylvatica L.) in a changing climate. Trees 21:1–11CrossRefGoogle Scholar
  16. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186CrossRefGoogle Scholar
  17. Guo Q, Liu Y (2010) ModEco: an integrated software package for ecological niche modelling. Ecography 33:637–642CrossRefGoogle Scholar
  18. Halász G (ed) (2006) Magyarország erdészeti tájai [Forest regions of Hungary]. Állami Erdészeti Szolgálat, Budapest (In Hungary)Google Scholar
  19. Hay LE, Wilby RL, Leavesley GH (2000) A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. J Am Water Resour Assoc 36:387–398CrossRefGoogle Scholar
  20. Horvat I, Glavac V, Ellenberg H (1974) Vegetation Südosteuropas. Fischer, Stuttgart, 768 ppGoogle Scholar
  21. Jump AS, Hunt JM, Peñuelas J (2006) Rapid climate change-related growth decline at the southern range edge of Fagus sylvatica. Glob Chang Biol 12:2163–2174CrossRefGoogle Scholar
  22. Keuler K, Lautenschlager M, Wunram C, Keup-Thiel E, Schubert M, Will A, Rockel B, Boehm U (2009) Climate Simulation with CLM, Scenario A1B run no.1, Data Stream 2: European region MPI-M/MaD. World Data Cent Clim. doi: 10.1594/WDCC/CLM_A1B_1_D2 Google Scholar
  23. Kramer K, Degen B, Buschbom J, Hickler T, Thuiller W, Sykes MT, de Winter W (2010) Modelling exploration of the future of European beech (Fagus sylvatica L.) under climate change—range abundance genetic diversity and adaptive response. For Ecol Manag 259:2213–2222CrossRefGoogle Scholar
  24. Kursar TA, Engelbrecht BMJ, Burke A, Tyree MT, El Omaru B, Giraldo JP (2009) Tolerance to low leaf water status of tropical tree seedlings is related to drought performance and distribution. Funct Ecol 23:93–102CrossRefGoogle Scholar
  25. Lakatos F, Molnár M (2009) Mass mortality of beech in Southwest Hungary. Acta Silv Lign Hung 5:75–82Google Scholar
  26. Lemoine D, Jacquemin S, Granier A (2002) Beech (Fagus sylvatica L.) branches show acclimation of xylem anatomy and hydraulic properties to increased light after thinning. Ann For Sci 59:761–766CrossRefGoogle Scholar
  27. Leuschner C, Voss S, Foetzki A, Clases Y (2006) Variation in leaf area index and stand leaf mass of European beech across gradients of soil acidity and precipitation. Plant Ecol 186:247–258CrossRefGoogle Scholar
  28. Löw M, Herbinger K, Nunn AJ, Häberle KH, Leuchner M, Heerdt C, Werner H, Wipfler P, Pretzsch H, Tausz M, Matyssek R (2006) Extraordinary drought of 2003 overrules ozone impact on adult beech trees (Fagus sylvatica). Trees 20:539–548CrossRefGoogle Scholar
  29. Maravelias CD, Haralabous J, Papaconstantinou C (2003) Predicting demersal fish species distributions in the Mediterranean Sea using artificial neural networks. Mar Ecol Prog Ser 255:249–258CrossRefGoogle Scholar
  30. Mátyás C (2007) What do field trials tell about the future use of forest reproductive material? In: Koskela J, Buck A, Teissier Du Cros E (eds) Climate change and forest genetic diversity: implications for sustainable forest management in Europe. Bioversity International, Rome, pp 53–69Google Scholar
  31. Mátyás C, Vendramin GG, Fady B (2009) Forests at the limit evolutionary-genetic consequences of environmental changes at the receding (xeric) edge of distribution. Ann For Sci 66:800–803CrossRefGoogle Scholar
  32. Mátyás C, Berki I, Czúcz B, Gálos B, Móricz N, Rasztovits E (2010) Future of beech in Southeast Europe from the perspective of evolutionary ecology. Acta Silv Lign Hung 6:91–110Google Scholar
  33. Péczely G (1979) Éghajlattan. [Climatology] Nemzeti Tankönyvkiadó, Budapest, in HungarianGoogle Scholar
  34. Peñuelas J, Ogaya R, Boada M, Jump AS (2007) Migration invasion and decline changes in recruitment and forest structure in a warming-linked shift of European beech forest in Catalonia (NE Spain). Ecography 30:829–837CrossRefGoogle Scholar
  35. Piovesan G, Biondi F, di Filippo A, Alessandrini A, Maugeri M (2008) Drought-driven growth reduction in old beech (Fagus sylvativa L.) forests of the central Apennines, Italy. Glob Chang Biol 14:1–17Google Scholar
  36. Rice K, Matzner S, Byer W, Brown J (2004) Patterns of tree dieback in Queensland, Australia: the importance of drought stress and the role of resistance to cavitation. Oecologia 139:190–198PubMedCrossRefGoogle Scholar
  37. Sala A, Piper F, Hoch G (2010) Physiological mechanisms of drought-induced tree mortality are far from being resolved. New Phytol 186:274–281PubMedCrossRefGoogle Scholar
  38. Schär C, Vidale PL, Lüthi D, Frei C, Häberli C, Liniger MA, Appenzeller C (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427:332–336PubMedCrossRefGoogle Scholar
  39. Svenning JC, Skov F (2004) Limited filling of the potential range in European tree species. Ecol Lett 7:565–573CrossRefGoogle Scholar
  40. Thuiller W, Araujo MB, Pearson RG et al (2004) Biodiversity conservation—uncertainty in predictions of extinction risk. Nature 430:34CrossRefGoogle Scholar
  41. Tsoar A, Allouche O, Steinitz O, Rotem D, Kadmon R (2007) A comparative evaluation of presence-only methods for modelling species distribution. Divers Distrib 13:397–405CrossRefGoogle Scholar
  42. Xin Y, Guoan T, Chenchao X, Fengdong D (2007) Terrain revised model for air temperature in mountainous area based on DEDM’s, a case study in Yaoxian county. J Geogr Sci 17:399–408CrossRefGoogle Scholar
  43. Zeileis A, Leisch F, Hornik K, Kleiber C (2002) Strucchange, an R package for testing for structural change in linear regression models. J Stat Softw 7:1–38Google Scholar
  44. Zimmermann NE, Yoccoz NG, Edwards TC, Meier ES, Thuiller W (2009) Climatic extremes improve predictions of spatial patterns of tree species. Proc Natl Acad Sci U S A 106:19723–19728PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© INRA and Springer-Verlag France 2013

Authors and Affiliations

  • Ervin Rasztovits
    • 1
  • Imre Berki
    • 1
  • Csaba Mátyás
    • 1
  • Kornél Czimber
    • 2
  • Elisabeth Pötzelsberger
    • 3
  • Norbert Móricz
    • 4
  1. 1.Institute of Environmental and Earth SciencesUniversity of West HungarySopronHungary
  2. 2.Institute of Geomatics and Civil EngineeringUniversity of West HungarySopronHungary
  3. 3.Institute of Silviculture, Department of Forest- and Soil SciencesUniversity of Natural Resources and Applied Life Sciences ViennaViennaAustria
  4. 4.Energy DepartmentAustrian Institute of TechnologyViennaAustria

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