Skip to main content

Advertisement

Log in

Soil water storage appears to compensate for climatic aridity at the xeric margin of European tree species distribution

  • Original Paper
  • Published:
European Journal of Forest Research Aims and scope Submit manuscript

Abstract

Based on macroecological data, we test the hypothesis whether European tree species of temperate and boreal distribution maintain their water and nutrient supply in the more arid southern margin of their distribution range by shifting to more fertile soils with higher water storage than in their humid core distribution range (cf. soil compensatory effects). To answer this question, we gathered a large dataset with more than 200,000 plots that we related to summer aridity (SA), derived from WorldClim data, as well as soil available water capacity (AWC) and soil nutrient status, derived from the European soil database. The soil compensatory effects on tree species distribution were tested through generalized additive models. The hypothesis of soil compensatory effects on tree species distribution under limiting aridity was supported in terms of statistical significance and plausibility. Compared to a bioclimatic baseline model, inclusion of soil variables systematically improved the models’ goodness of fit. However, the relevance measured as the gain in predictive performance was small, with largest improvements for P. sylvestris, Q. petraea and A. alba. All studied species, except P. sylvestris, preferred high AWC under high SA. For F. sylvatica, P. abies and Q. petraea, the compensatory effect of soil AWC under high SA was even more pronounced on acidic soils. Soil compensatory effects might have decisive implications for tree species redistribution and forest management strategies under anthropogenic climate change. Therefore, soil compensatory effects deserve more intensive investigation, ideally, in studies combining different spatial scales to reduce the uncertainty associated with the precision of soil information.

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

Abbreviations

AWC:

Available water capacity

DTOL:

Tolerances to drought

EQ:

Ellenberg’s climate quotient

EQm:

Modified EQ

ESDB:

European soil database

LogEQm:

Decimal logarithm from EQm

RSC:

Relative site constancy

SA:

Summer aridity

SDM:

Species distribution model

STOL:

Tolerances to shade

SNS:

Soil nutrient status

References

  • Alonso-Ponce R, López Senespleda E, Sánchez Palomares O (2010) A novel application of the ecological field theory to the definition of physiographic and climatic potential areas of forest species. Eur J For Res 129:119–131

    Article  Google Scholar 

  • Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43:1223–1232

    Article  Google Scholar 

  • Attorre F, Alfò M, de Sanctis M et al (2011) Evaluating the effects of climate change on tree species abundance and distribution in the Italian peninsula. Appl Veg Sci 14:242–255

    Article  Google Scholar 

  • Austin MP (1980) Searching for a model for use in vegetation analysis. Vegetatio 42:11–21

    Article  Google Scholar 

  • Austin MP, Nicholls AO, Margules CR (1990) Measurement of the realized qualitative niche: environmental niches of five Eucalyptus species. Ecol Monogr 60:161–177

    Article  Google Scholar 

  • Bailey RG (1987) Suggested hierarchy of criteria for multi-scale ecosystem mapping. Landsc Urb Plan 14:313–319

    Article  Google Scholar 

  • Barbet-Massin M, Jiguet F, Albert CH et al (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol Evol 3:327–338

    Article  Google Scholar 

  • Barnes BV, Pregitzer KS, Spies TA et al (1982) Ecological forest site classification. J For 80:493–498

    Google Scholar 

  • Beauregard F, de Blois S (2014) Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models. PLoS ONE 9:e92642

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Benito-Garzón M, Ruiz-Benito P, Zavala MA (2013) Interspecific differences in tree growth and mortality responses to environmental drivers determine potential species distributional limits in Iberian forests. Global Ecol Biogeogr 22:1141–1151

    Article  Google Scholar 

  • Bertrand R, Perez V, Gégout J-C (2012) Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France. Glob Change Biol 18:2648–2660

    Article  Google Scholar 

  • Binkley D, Vitousek P (1989) Soil nutrient availability. In: Pearcy RW, Ehleringer JR, Mooney HA et al (eds) Plant physiological ecology field methods and instrumentation. Springer, Dordrecht, pp 75–96

    Chapter  Google Scholar 

  • Blume H-P, Brümmer GW, Fleige H et al (2016) Scheffer/Schachtschabel soil science. Springer, Berlin, Heidelberg

    Book  Google Scholar 

  • Bohn U, Neuhäusl R, Gollub G, Hettwer C, Neuhäuslova Z, Raus T, Schlüter H, Weber H (2003) Map of the natural vegetation of Europe, scale 1:2500000. Parts 1–3. Landwirtschaftsverlag, Münster-Hiltrup

  • Bradbury IK, Malcolm DC (1977) The effect of phosphorus and potassium on transpiration, leaf diffusive resistance and water-use efficiency in Sitka spruce (Picea sitchensis) seedlings. J Appl Ecol 14:631–641

  • Bréda N, Huc R, Granier A et al (2006) Temperate forest trees and stands under severe drought. A review of ecophysiological responses, adaptation processes and long-term consequences. Ann For Sci 63:625–644

    Article  Google Scholar 

  • Brus DJ, Hengeveld GM, Walvoort DJ et al (2011) Statistical mapping of tree species over Europe. Eur J For Res 131:145–157

    Article  Google Scholar 

  • Bussotti F, Pollastrini M (2017) Observing climate change impacts on European forests: what works and what does not in ongoing long-term monitoring networks. Front Plant Sci 8:1–5

  • Cajander AK (1949) Forest types and their significance. Acta For Fennica 56:1–71

    Google Scholar 

  • Caudullo G, Tinner W, de Rigo D (2016) Picea abies in Europe: distribution, habitat, usage and threats. In: San-Miguel-Ayanz J, de Rigo D, Caudullo G, Houston Durrant T, Mauri A (eds) European atlas of forest tree species. Publ. Off. EU, Luxembourg, p e012300+

    Google Scholar 

  • Coudun C, Gégout J-C, Piedallu C et al (2006) Soil nutritional factors improve models of plant species distribution. An illustration with Acer campestre (L.) in France. J Biogeogr 33:1750–1763

    Article  Google Scholar 

  • Czúcz B, Gálhidy L, Mátyás C (2011) Present and forecasted xeric climatic limits of beech and sessile oak distribution at low altitudes in Central Europe. Ann For Sci 68:99–108

    Article  Google Scholar 

  • Diekmann M, Michaelis J, Pannek A (2015) Know your limits—the need for better data on species responses to soil variables. Basic Appl Ecol 16:563–572

    Article  Google Scholar 

  • Dolos K, Bauer A, Albrecht S (2015) Site suitability for tree species. Is there a positive relation between a tree species’ occurrence and its growth? Eur J For Res 134:609–621

    Article  Google Scholar 

  • Dubuis A, Giovanettina S, Pellissier L et al (2013) Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables. J Veg Sci 24:593–606

    Article  Google Scholar 

  • Ducousso A, Bordacs S (2004) EUFORGEN technical guidelines for genetic conservation and use for pedunculate and sessile oaks, Quercus robur and Q. petraea. European Forest Genetic Resources Programme, International Plant Genetic Resources Institute, Rome  

  • Dullinger S, Gattringer A, Thuiller W et al (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nat Clim Change 2:619–622

    Article  Google Scholar 

  • Ellenberg H (1988) Vegetation ecology of central Europe. Cambridge University Press, Cambridge

    Google Scholar 

  • Ellenberg H, Leuschner C (2010) Vegetation Mitteleuropas mit den Alpen. Verlag Eugen Ulmer, Stuttgart

    Google Scholar 

  • Ewald J, Hédl R (2014) Spatial modeling of vegetation potential: an introduction. Folia Geobot 49:309–312

    Article  Google Scholar 

  • Falk W, Mellert KH (2011) Species distribution models as a tool for forest management planning under climate change: risk evaluation of Abies alba in Bavaria. J Veg Sci 22:621–634

    Article  Google Scholar 

  • Falk W, Mellert K, Bachmann-Gigl U et al (2013) Bäume für die Zukunft: baumartenwahl auf wissenschaftlicher Grundlage. LWF aktuell 94:8

    Google Scholar 

  • Fang J, Lechowicz MJ (2006) Climatic limits for the present distribution of beech (Fagus L.) species in the world. J Biogeogr 33:1804–1819

    Article  Google Scholar 

  • Fischer R, Lorenz M, Granke O et al Forest condition in Europe: 2010 technical report of ICP forests. Executive Report. ICP Forests and European Commission, Hamburg

  • Franklin J (2010) Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Freeman EA, Moisen G (2008) Presence absence: an R package for presence-absence model analysis. J Stat Softw 23:1–31

    Article  Google Scholar 

  • Golub GH, Heath M, Wahba G (1979) Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics 21:215–223

    Article  Google Scholar 

  • Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186

    Article  Google Scholar 

  • Halvorsen R (2012) A gradient analytic perspective on distribution modelling. Sommerfeltia 35:1–165

    Article  Google Scholar 

  • Hanewinkel M, Cullmann DA, Michiels H-G et al (2014) Converting probabilistic tree species range shift projections into meaningful classes for management. J Environ Manag 134:153–165

    Article  Google Scholar 

  • Hiederer R (2013) Mapping soil properties for Europe—spatial representation of soil database attributes. Publications Office of the European Union. EUR26082EN Scientific and Technical Research series, Luxembourg

    Google Scholar 

  • Hijmans RJ, van Etten J (2014) Raster: geographic data analysis and modeling. R package vers 2.2–31. https://CRAN.R-project.org/package=raster

  • Hijmans RJ, Cameron SE, Parra JL et al (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978

    Article  Google Scholar 

  • Hlásny T, Mátyás C, Seidl R et al (2014) Climate change increases the drought risk in Central European forests: what are the options for adaptation? For J 60:5–18

    Google Scholar 

  • Kölling C, Hoffmann M, Gulder H-J (1996) Bodenchemische Vertikalgradienten als charakteristische zustandsgrössen von waldökosystemen. Z Pflanz Bodenkunde 159:69–77

    Article  Google Scholar 

  • Kühn I (2007) Incorporating spatial autocorrelation may invert observed patterns. Divers Distrib 13:66–69

    Google Scholar 

  • Lakatos F, Molnár M (2009) Mass mortality of beech (Fagus sylvatica L.) in South-West Hungary. Acta Silvatica et Lignaria Hungarica 5:75–82

    Google Scholar 

  • Latron J, Llorens P, Gallart F (2009) The hydrology of Mediterranean mountain areas. Geogr Compass 3:2045–2064

    Article  Google Scholar 

  • Leibundgut H (1984) Unsere Waldbäume. Eigenschaften und Leben. Huber, Frauenfeld

    Google Scholar 

  • Lenoir J, Svenning J-C (2015) Climate-related range shifts–a global multidimensional synthesis and new research directions. Ecography 38:15–28

    Article  Google Scholar 

  • Lenoir J, Svenning J-C, Dullinger S et al (2012) The Alps vegetation database–a geo-referenced community-level archive of all terrestrial plants occurring in the Alps. Biodivers Ecol 4:331–332

    Article  Google Scholar 

  • Lenoir J, Hattab T, Pierre G (2017) Climatic microrefugia under anthropogenic climate change: implications for species redistribution. Ecography 40:253–266

    Article  Google Scholar 

  • Leuschner C, Köckemann B, Buschmann H (2009) Abundance, niche breadth, and niche occupation of Central European tree species in the centre and at the margin of their distribution range. For Ecol Manag 258:1248–1259

    Article  Google Scholar 

  • Ligot G, Balandier P, Fayolle A et al (2013) Height competition between Quercus petraea and Fagus sylvatica natural regeneration in mixed and uneven-aged stands. For Ecol Manag 304:391–398

    Article  Google Scholar 

  • Liu C, Berry PM, Dawson TP et al (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28(3):385–393

    Article  Google Scholar 

  • Lopez-Senespleda E, Montero G (2015) Tipificación Ecológico-Selvícola de las Principales Especies Forestales Españolas, INIA-CIFOR, Final Report, Madrid

  • Mátyás C, Ackzell L, Samuel CJA (2004) EUFORGEN technical guidelines for genetic conservation and use for Scots pine (Pinus sylvestris). European Forest Genetic Resources Programme, International Plant Genetic Resources Institute, Rome

  • Mátyás C, Berki I, Czúcz B et al (2010) Future of beech in Southeast Europe from the perspective of evolutionary ecology. Acta Silvatica et Lignaria Hungarica 6:91–110

    Google Scholar 

  • Meier ES, Kienast F, Pearman PB et al (2010) Biotic and abiotic variables show little redundancy in explaining tree species distributions. Ecography 33:1038–1048

    Article  Google Scholar 

  • Mellert KH, Ewald J (2014) Nutrient limitation and site-related growth potential of Norway spruce (Picea abies [L.] Karst) in the Bavarian Alps. Eur J For Res 133:433–451

    Article  CAS  Google Scholar 

  • Mellert KH, Göttlein A (2013) Identification and validation of thresholds and limiting nutrient factors of Norway spruce by using new nutritional levels and modern regression. Allg For Jagdztg 184:197–203

    Google Scholar 

  • Mellert KH, Fensterer V, Küchenhoff H et al (2011) Hypothesis-driven species distribution models for tree species in the Bavarian Alps. J Veg Sci 22:635–646

    Article  Google Scholar 

  • Mellert KH, Deffner V, Küchenhoff H et al (2015) Modeling sensitivity to climate change and estimating the uncertainty of its impact. A probabilistic concept for risk assessment in forestry. Ecol Model 316:211–216

    Article  Google Scholar 

  • Mellert KH, Ewald J, Hornstein D et al (2016) Climatic marginality: a new metric for the susceptibility of tree species to warming exemplified by Fagus sylvatica (L.) and Ellenberg’s quotient. Eur J For Res 135:137–152

    Article  Google Scholar 

  • Michel A, Seidling W, Lorenz M et al (2016) Forest Condition in Europe 2016. ICP Forests and European Commission, Hamburg

  • Nieto-Lugilde D, Lenoir J, Abdulhak S et al (2015) Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps. Ecography 38:578–589

    Article  PubMed  PubMed Central  Google Scholar 

  • Niinemets Ü, Valladares F (2006) Tolerance to shade, drought, and waterlogging of temperate northern hemisphere trees and shrubs. Ecol Monogr 76:521–547

    Article  Google Scholar 

  • Panagos P, van Liedekerke M, Jones A et al (2012) European soil data centre: response to European policy support and public data requirements. Land Use Policy 29:329–338

    Article  Google Scholar 

  • Peterson AT, Soberón J, Pearson RG, Anderson RP, Martínez-Meyer E, Nakamura M, Araúcho MB (2011) Ecological niches and geographic distributions (MPB-49). Princeton University Press

  • Piedallu C, Gégout J, Perez V et al (2013) Soil water balance performs better than climatic water variables in tree species distribution modelling. Glob Ecol Biogeogr 22:470–482

    Article  Google Scholar 

  • Piedallu C, Gégout J-C, Lebourgeois F et al (2016) Soil aeration, water deficit, nitrogen availability, acidity and temperature all contribute to shaping tree species distribution in temperate forests. J Veg Sci 27:387–399

    Article  Google Scholar 

  • R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria

  • Rasztovits E, Moricz N, Berki I et al (2012) Evaluating the performance of stochastic distribution models for European beech at low-elevation xeric limits. Idojárás 116:173–194

    Google Scholar 

  • Sánchez De Dios R, Hernández L, Montes F et al (2016) Tracking the leading edge of Fagus sylvatica in North-Western Iberia: holocene migration inertia, forest succession and recent global change. Perspect Plant Ecol 20:11–21

    Article  Google Scholar 

  • Serra-Diaz JM, Keenan TF, Ninyerola M et al (2013) Geographical patterns of congruence and incongruence between correlative species distribution models and a process-based ecophysiological growth model. J Biogeogr 40:1928–1938

    Google Scholar 

  • Stojanović DB, Kržič A, Matović B et al (2013) Prediction of the European beech (Fagus sylvatica L.) xeric limit using a regional climate model. An example from southeast Europe. Agr For Meteorol 176:94–103

    Article  Google Scholar 

  • Swets J (1988) Measuring the accuracy of diagnostic systems. Science 240(4857):1285–1293

    Article  Google Scholar 

  • Tegel W, Seim A, Hakelberg D et al (2014) A recent growth increase of European beech (Fagus sylvatica L.) at its Mediterranean distribution limit contradicts drought stress. Eur J For Res 133:61–71

    Article  Google Scholar 

  • Thuiller W (2013) On the importance of edaphic variables to predict plant species distributions—limits and prospects. J Veg Sci 24:591–592

    Article  PubMed  PubMed Central  Google Scholar 

  • Tsiripidis I, Bergmeier E, Fotiatidis G et al (2012) Hellenic beech forests database (Hell-Beech-DB). Biodivers Ecol 4:390

    Article  Google Scholar 

  • Walter H (1973) Vegetation of the earth in relation to climate and the eco-physiological conditions. Universities Press, London

    Google Scholar 

  • Whittaker RH (1970) Communities and ecosystems. Macmillan, London

    Google Scholar 

  • Wolf H (2003) EUFORGEN technical guidelines for genetic conservation and use for silver fir (Abies alba). European Forest Genetic Resources Programme, International Plant Genetic Resources Institute, Rome

    Google Scholar 

  • Wood S (2006) Generalized additive models: an introduction with R. CRC Press, Boca Raton

    Book  Google Scholar 

  • Wood S (2017) Mixed GAM computation vehicle with automatic smoothness estimation. R package vers 1.8–22. https://CRAN.R-project.org/package=mgcv

  • Zimmermann NE, Jandl R, Hanewinkel M et al (2013) Chapter 4 potential future ranges of tree species in the Alps. In: Cerbu GA, Hanewinkel M, Gerosa G, Jandl R (eds) Management strategies to adapt alpine space forests to climate change risks, InTech, Chapters published August 28, 2013 under CC BY 3.0 license https://doi.org/10.5772/56933

Download references

Acknowledgements

This study was funded by the Federal Ministry of Food and Agriculture as well as the Federal Environment Ministry of Germany (project number 28WB4058) and the Bavarian State Forest Administration (project number W42), an authority of the Ministry for Nutrition, Agriculture and Forestry. We acknowledge ICP Forests and the involved country representatives for providing Level-I data. Our thanks also go to Nikolaos Grigoriadis from Greece, Aleksander Marinšek, Alexey Zharov from Germany and Doganay Tolunay from Turkey for data provision. However, the Turkish data could not be used in this analysis, as the ESDB do not contain soil data from this country. Additionally, we are deeply indebted to our colleagues, Solti György, Markus Neumann and Heino Polley for providing us access to the national forest inventories of Hungary, Austria and Germany, respectively, as well as Monika Konnert (Bavarian Institution for Forest Seeding and Planting) for providing data from provenance plots. Furthermore, we thank all other contributors of vegetation databases and other data sources as well as two anonymous reviewers whose comments helped to clarify important issues.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Karl H. Mellert.

Additional information

Communicated by Agustín Merino.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 3973 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mellert, K.H., Lenoir, J., Winter, S. et al. Soil water storage appears to compensate for climatic aridity at the xeric margin of European tree species distribution. Eur J Forest Res 137, 79–92 (2018). https://doi.org/10.1007/s10342-017-1092-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10342-017-1092-x

Keywords

Navigation