Understory dynamics after disturbance accelerate succession from spruce to beech-dominated forest—the Siggaboda case study
It is assumed that climate change will favour European beech (Fagus sylvatica L.) to Norway spruce (Picea abies [L.] Karst.) at its northern range margins due to climate change and induced disturbance events.
An old-growth mixed forest of spruce and beech, situated near the northern beech margin, was studied to reveal effects of disturbances and response processes on natural forest dynamics, focussing on the understory.
We carried out analyses on understory dynamics of beech and spruce in relation to overstory release. This was done based on a sequence of stand and tree vitality inventories after a series of abiotic and biotic disturbances.
It became apparent that beech (understory) has a larger adaptive capacity to disturbance impacts and overstory release (68 % standing volume loss) than spruce. Understory dynamics can play a key role for forest succession from spruce to beech-dominated forests. Disturbances display an acceleration effect on forest succession in the face of climate change.
Beech is poised strategically to replace spruce as the dominant tree species at the study area. Due to an increasing productivity and a lower risk of stand failure, beech may raise into the focus of forestry in southern Sweden.
KeywordsFagus sylvatica Picea abies Climate change Canopy disturbance Interspecific competition Storm Drought Bark beetle
Dr. Tomasz Czajkowski (Thünen Institute of Forest Ecosystems Eberswalde), Heiko Rubbert, Dr. Thomas Kompa, Frauke Koch, Friederike Kampf, René Grippert (Göttingen University) and Dr. Lars Droessler (SLU Alnarp) supported us in field work. We thank all for the outstanding assistance.
This study was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG: RO 910/10, BO 1906/3), the Thure Rignells Foundation (Tranemåla Erik och Ebba Larssons samt Thure Rignells Stiftelse, Bengt Ljungström) and was conducted in co-operation with the Broadleaf Program (Ädellövprogrammet) of the Swedish Agricultural University (SLU), Southern Swedish Forest Research Centre at Alnarp (Prof. Dr. Magnus Löf, Prof. Dr. Jörg Brunet).
- Atkinson D (2000) Root characteristics: why and what to measure. In: Smit AL, Bengough AG, Engels C, Van Noordwijk M, Pellerin S, Van De Geijn SC (eds) Root methods: a hand book. Springer, Berlin Heidelberg New York, pp 2–32Google Scholar
- Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon W-T, Laprise R, Magaña Rueda V, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton, P (2007) Regional climate projections. In: Solomon SD, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (Eds.) Climate change 2007: the physical science basis. Contribution of Working Group I to the 4th assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 848–940Google Scholar
- Ellenberg H (1988) Vegetation ecology of central Europe. Cambridge University Press, Cambridge, United Kingdom, 731 ppGoogle Scholar
- Eriksson M (2007) The bark beetle Ips typographus (L.) on patches of dead or dying host trees: estimating the colonization success and risk of consequential tree deaths. PhD Dissertations in Biology no. 46, University of Joensuu, Finland, 68 ppGoogle Scholar
- FAO [Food and Agriculture Organization] (2006) World reference base for soil resources 2006. World Soil Resources Reports 103, FAO, Rome, Italy, 122 ppGoogle Scholar
- Grodzki W (2010) The decline of Norway spruce Picea abies (L.) Karst. stands in Beskid Śląski and Żywiecki: theoretical concept and reality. Beskydy 3:19–26Google Scholar
- Lind P, Kjellström E (2008) Temperature and precipitation changes in Sweden, a wide range of model-based projections for the 21st century. Swedish Meteorological and Hydrological Institute. Report RMK no. 113, Norrköpping, Sweden, 50 ppGoogle Scholar
- Meyer P (2005) Network of Strict Forest Reserves as reference system for close to nature forestry in Lower Saxony, Germany. For Snow Landsc Res 79:33–44Google Scholar
- Meyer P, Ackermann J, Balcar P, Boddenberg J, Detsch R, Förster B, Fuchs H, Hoffmann B, Keitel W, Kölbel M, Köthke C, Koss H, Unkrig W, Weber J, Willig J (2001) Untersuchung der Waldstruktur und ihrer Dynamik in Naturwaldreservaten. IHW publisher, Eching, Germany, 107 pp [in German]Google Scholar
- Nagel J, Duda H, Hansen J (2006) Forest simulator BWINPro7. Forst und Holz 61:427–429 [in German]Google Scholar
- Nikulin G, Kjellström E, Hansson U, Strandberg G, Ullerstige A (2011) Evaluation and future projections of temperature, precipitation and wind extremes over Europe in an ensemble of regional climate simulations. Tellus 63A:41–55. doi: 10.1111/j.1600-0870.2010.00466.x
- Petterson H (1955) Die Massenproduktion des Nadelwaldes. Mitt Forstl Forsch-Anst Schwedens 45:392–580 [in German]Google Scholar
- Raab B, Vedin H (eds) (1995) Climate, lakes and rivers. The National Atlas of Sweden. SNA, Stockholm, SwedenGoogle Scholar
- Sjörs H (1999) The background: geology, climate and zonation. In: Rydin H, Snoeijs P, Diekmann M (Eds.) Swedish Plant Geography. Acta Phytogeogr Suec 84:5–14Google Scholar
- StatSoft Inc (2009) STATISTICA for Windows, version 9.0. Available from http://www.statsoft.com (accessed 28 December 2011)
- WeatherOnline (2011) Climate Robot: Växjö/Kronoberg (186 m). Available from http://www.weatheronline.co.uk/Sweden/VaexjoeKronob.htm (accessed 28 December 2011)
- Yue C, Kohnle U, Hein S (2008) Combining tree- and stand-level models: a new approach to growth prediction. For Sci 54:553–566Google Scholar