Species Interactions in the Dynamics of Even- and Uneven-Aged Boreal Forests

Many boreal tree stands are neither clearly even-aged nor clearly uneven-aged. The stands may undergo a series of stages, during which an even-aged stand is transformed into two-storied mixed stand, and finally to multistoried or uneven-aged stand structure. The species composition often changes during the succession of stand stages. This study developed models for stand dynamics that can be used in different stand structures and species compositions. The model set consists of species-specific individual-tree diameter increment and survival models, and models for ingrowth. Separate models were developed for Scots pine, Norway spruce, and hardwood species. The models were used in a growth simulator, to give illustrative examples on species influences and stand dynamics. Methods to simulate residual variation around diameter increment and ingrowth models are also presented. The results suggest that mixed stands are more productive than one-species stands. Spruce in particular benefits from an admixture of other species. Mixed species improve diameter increment, decrease mortality, and increase ingrowth. Pine is a more beneficial admixture than birch. Simulations showed that uneven-aged management of spruce forests is sustainable and productive, and even-aged conifer stands growing on medium sites can be converted into uneven-aged mixed stands by a series of strong high thinnings.

[1]  T. Pukkala,et al.  Predicting the growth and yield of Pinus radiata in Bolivia , 2011, Annals of Forest Science.

[2]  T. Pukkala,et al.  Uneven- vs even-aged management in Finnish boreal forests , 2011 .

[3]  J. P. Skovsgaard,et al.  Conversion of Norway Spruce: A Case Study in Denmark Based on Silvicultural Scenario Modelling , 2006 .

[4]  K. Andreassen,et al.  Basal area growth models for individual trees of Norway spruce, Scots pine, birch and other broadleaves in Norway , 2003 .

[5]  Thomas Knoke,et al.  May risk aversion lead to near-natural forestry? A simulation study , 2011 .

[6]  L. Valsta,et al.  A Scenario Approach to Stochastic Anticipatory Optimization in Stand Management , 1992, Forest Science.

[7]  Jari Miina,et al.  Predicting regeneration establishment in Norway spruce plantations using a multivariate multilevel model , 2006, New Forests.

[8]  Wiktor L. Adamowicz,et al.  Timber supply implications of natural disturbance management , 1999 .

[9]  Timo Pukkala,et al.  Anticipatory vs adaptive optimization of stand management when tree growth and timber prices are stochastic , 2012 .

[10]  Timo Pukkala,et al.  Optimizing the structure and management of uneven-sized stands of Finland , 2010 .

[11]  Hannu Hökkä,et al.  Models for predicting stand development in MELA System , 2002 .

[12]  T. Pukkala,et al.  Even-aged or uneven-aged modelling approach? A case for Pinus brutia , 2012, Annals of Forest Science.

[13]  Margarida Tomé,et al.  Modelling spatial and temporal variability in a zero-inflated variable: The case of stone pine (Pinus pinea L.) cone production , 2011 .

[14]  T. Pukkala,et al.  Using optimization for fitting individual-tree growth models for uneven-aged stands , 2011, European Journal of Forest Research.

[15]  T. Pukkala,et al.  A comparison of fixed- and mixed-effects modeling in tree growth and yield prediction of an indigenous neotropical species (Centrolobium tomentosum) in a plantation system , 2013 .

[16]  Joseph Buongiorno,et al.  Predicting the growth of stands of trees of mixed species and size: A matrix model for Norway , 2008 .

[17]  T. Pukkala,et al.  A growth and yield model for even-aged Pinus brutia Ten. stands in Syria , 2011, Annals of Forest Science.

[18]  T. Kuuluvainen,et al.  Natural forest dynamics in boreal Fennoscandia: a review and classification , 2011 .

[19]  Hubert Hasenauer,et al.  Concepts Within Tree Growth Modeling , 2006 .

[20]  T. Pukkala,et al.  A model for predicting the growth of Eucalyptus globulus seedling stands in Bolivia , 2012 .

[21]  D. Hann,et al.  Impact of competitor species composition on predicting diameter growth and survival rates of Douglas-fir trees in southwestern Oregon , 2001 .

[22]  T. Pukkala,et al.  Continuous Cover Forestry in Finland – Recent Research Results , 2012 .

[23]  Growth and yield model for uneven-aged mixtures of Pinus sylvestris L. and Pinus nigra Arn. in Catalonia, north-east Spain , 2004 .

[24]  Hailemariam Temesgen,et al.  Effects of height imputation strategies on stand volume estimation , 2009 .

[25]  Timo Pukkala,et al.  Using Numerical Optimization for Specifying Individual-Tree Competition Models , 2000, Forest Science.

[26]  S. Solberg,et al.  Crown Density and Growth Relationships Between Stands of Picea abies in Norway , 2000 .

[27]  Joseph Buongiorno,et al.  MANAGEMENT OF MIXED-SPECIES, UNEVEN-AGED FORESTS IN THE FRENCH JURA: FROM STOCHASTIC GROWTH AND PRICE MODELS TO DECISION TABLES , 2005 .

[28]  Kari Mielikäinen,et al.  Koivusekoituksen vaikutus kuusikon rakenteeseen ja kehitykseen. , 1985 .

[29]  Mark Von Tress,et al.  Generalized, Linear, and Mixed Models , 2003, Technometrics.

[30]  T. Pukkala,et al.  Historical Emergence and Current Application of CCF , 2012 .

[31]  Joseph Buongiorno,et al.  Growth and yield of all-aged Douglas-fir western hemlock forest stands: a matrix model with stand diversity effects , 2005 .

[32]  A. Zingg,et al.  Comparison between the productivity of pure and mixed stands of Norway spruce and European beech along an ecological gradient , 2010, Annals of Forest Science.

[33]  Harold E. Burkhart,et al.  Modeling Forest Trees and Stands , 2012, Springer Netherlands.

[34]  Annika Kangas,et al.  On the prediction bias and variance in long-term growth projections , 1997 .

[35]  Jerome K. Vanclay,et al.  Modelling Forest Growth and Yield: Applications to Mixed Tropical Forests , 1994 .

[36]  Thomas Nord-Larsen Modeling Individual-Tree Growth from Data with Highly Irregular Measurement Intervals , 2006 .

[37]  Evaluation of mixed-effects models for predicting Douglas-fir mortality , 2012 .

[38]  T. Pukkala,et al.  A spatial yield model for optimizing the thinning regime of mixed stands of Pinus sylvestris and Picea abies , 1998 .

[39]  Hailemariam Temesgen,et al.  Analysis and comparison of nonlinear tree height prediction strategies for Douglas-fir forests , 2008 .

[40]  T. Pukkala,et al.  Productivity of mixed stands of Pinus sylvestris and Picea abies , 1994 .

[41]  Timo Pukkala,et al.  Growth and yield models for uneven-sized forest stands in Finland. , 2009 .

[42]  Kari Pasanen,et al.  Integrating variation in tree growth into forest planning , 1998 .

[43]  Jari Miina,et al.  Residual variation in diameter growth in a stand of Scots pine and Norway spruce , 1993 .

[44]  G. Baskerville Use of Logarithmic Regression in the Estimation of Plant Biomass , 1972 .

[45]  Q. V. Cao Prediction of annual diameter growth and survival for individual trees from periodic measurements , 2000 .