Development of a dynamic growth model for sweet chestnut coppice: A case study in Northwest Spain

Abstract Sweet chestnut coppice (Castanea sativa Mill.) is a species of great importance in the northwest of Spain, due to its potential for producing valuable timber in relatively short rotations. However, abandonment has resulted in unstable and degraded stands. Thus, there is a need to improve forestry decision making tools. The objective of this study is the development of a dynamic stand growth model for the sweet chestnut comprised of three transition functions (dominant height, basal area and number of stems per hectare). They are used to estimate rates of change in the stand between an initial point in time and a point in the future. The data comes from two inventories of an unmanaged network of plots which incorporate all the variability in conditions in the region for the study species (climate, soil, stocking, site quality etc.). ADA and GADA approaches were used to develop the three transition functions. The model achieved high accuracy (explaining >90% of variability). The model incorporates an initialization function (explaining 60% of variability) for predicting initial stand basal area in stands without diameter inventories, which can be used to establish the starting point for the simulation, and, in addition, the biomass expansion factor (BEF) for this species (expressed as a constant value of 0.60) and a new single aboveground biomass equation (explaining almost 80% of variability) were calculated. A case study shows how to apply these decision making tools for the sustainable management of sweet chestnut coppice.

[1]  M. Tomé,et al.  Height–diameter equation for first rotation eucalypt plantations in Portugal , 2002 .

[2]  Norman L. Christensen,et al.  Competition and Tree Death , 1987 .

[3]  Oscar García,et al.  Developing a dynamic growth model for teak plantations in India , 2014, Forest Ecosystems.

[4]  U. Diéguez-Aranda,et al.  Modelling mortality of Scots pine (Pinus sylvestris L.) plantations in the northwest of Spain , 2005, European Journal of Forest Research.

[5]  L. Pienaar,et al.  The Chapman-Richards Generalization of Von Bertalanffy's Growth Model for Basal Area Growth and Yield in Even - Aged Stands , 1973 .

[6]  S. Titus,et al.  A generalized logistic model of individual tree mortality for aspen, white spruce, and lodgepole pine in Alberta mixedwood forests , 2001 .

[7]  Margarida Tomé,et al.  A tree crown ratio prediction equation for eucalypt plantations , 2001 .

[8]  Chris J. Cieszewski,et al.  Developing a well-behaved dynamic site equation using a modified Hossfeld IV function y3 = (axm)/(c + xm-1), a simplified mixed-model and scant subalpine fir data , 2003 .

[9]  Margarida Tomé,et al.  Modeling dominant height growth of maritime pine in Portugal using GADA methodology with parameters depending on soil and climate variables , 2011, Annals of Forest Science.

[10]  R. H. Myers.  Classical and modern regression with applications , 1986 .

[11]  Chris J. Cieszewski,et al.  Generalized algebraic difference approach: theory based derivation of dynamic site equations with polymorphism and variable asymptotes. , 2000 .

[12]  Alberto Rojo-Alboreca,et al.  Site index curves for natural Aleppo pine forests in the central Ebro valley (Spain) , 2017 .

[13]  R. M. Newnham.  A modification of the Ek–Payandeh nonlinear regression model for site index curves , 1988 .

[14]  E. Díaz-Varela,et al.  Glacial refugia and mid-Holocene expansion delineate the current distribution of Castanea sativa in Europe , 2018 .

[15]  M. Río,et al.  Biomass models to estimate carbon stocks for hardwood tree species , 2012 .

[16]  L. Pienaar,et al.  Survival Functions for Site-Prepared Slash Pine Plantations in the Flatwoods of Georgia and Northern Florida , 1981 .

[17]  R. C. Woollons,et al.  Even-aged stand mortality estimation through a two-step regression process , 1998 .

[18]  Oscar García,et al.  The state-space approach in growth modelling , 1994 .

[19]  Robert L. Bailey,et al.  Base-Age Invariant Polymorphic Site Curves , 1974 .

[20]  R. Mäkipää,et al.  Individual tree biomass equations or biomass expansion factors for assessment of carbon stock changes in living biomass – A comparative study , 2012 .

[21]  M. Hawkins,et al.  A dynamic volume and biomass growth model system for even-aged downy birch stands in south-western Europe , 2014 .

[22]  Brian Tobin,et al.  Biomass expansion factors for Sitka spruce (Picea sitchensis (Bong.) Carr.) in Ireland , 2007, European Journal of Forest Research.

[23]  J. Majada,et al.  Management tools for Castanea sativa coppice stands in northwestern Spain , 2016 .

[24]  Juha Heikkinen,et al.  Biomass expansion factors (BEFs) for Scots pine, Norway spruce and birch according to stand age for boreal forests , 2003 .

[25]  U. Diéguez-Aranda,et al.  Development of a basal area growth system for maritime pine in northwestern Spain using the generalized algebraic difference approach , 2006 .

[26]  J. Majada,et al.  Modelling of the mechanical properties of Castanea sativa Mill. structural timber by a combination of non-destructive variables and visual grading parameters , 2012, European Journal of Wood and Wood Products.

[27]  M. Tomé,et al.  Dominant height growth equations including site attributes in the generalized algebraic difference approach , 2008 .

[28]  K. Gadow,et al.  A two-step mortality model for even-aged stands of Pinus radiata D. Don in Galicia (Northwestern Spain) , 2004 .

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

[30]  Margarida Tomé,et al.  An Individual Tree Growth Model for Juvenile Cork Oak Stands in Southern Portugal , 2009 .

[31]  R. Bailey,et al.  A Compatible Model Relating Slash Pine Plantation Survival to Density, Age, Site Index, and Type and Intensity of Thinning , 1985 .

[32]  K. Byrne,et al.  Improved estimates of biomass expansion factors for Sitka spruce. , 2004 .

[33]  C. Ni,et al.  Evaluating behaviors of factors affecting the site index estimate on the basis of a single stand using simulation approach , 2008 .

[34]  L. S. Davis.  Forest Management: To Sustain Ecological, Economic, and Social Values , 2005 .

[35]  Chris J. Cieszewski,et al.  PRACTICAL METHODS FOR ESTIMATING NON-BIASED PARAMETERS IN SELF- REFERENCING GROWTH AND YIELD MODELS , 2000 .

[36]  L. Pienaar,et al.  Yield prediction for mechanically site-prepared slash pine plantations. , 1990 .

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

[38]  Fernando Castedo-Dorado,et al.  Development of a stand density management diagram for radiata pine stands including assessment of stand stability , 2009 .

[39]  C. Cieszewski,et al.  COMPARING PROPERTIES OF SELF-REFERENCING MODELS BASED ON NONLINEAR-FIXED-EFFECTS VERSUS NONLINEAR-MIXED-EFFECTS MODELING APPROACHES , 2018 .

[40]  Chris J. Cieszewski,et al.  Three methods of deriving advanced dynamic site equations demonstrated on inland Douglas-fir site curves , 2001 .

[41]  F. Bravo,et al.  Growth and yield models in Spain: historical overview, contemporary examples and perspectives , 2011 .

[42]  J. Durbin,et al.  Testing for serial correlation in least squares regression. II. , 1950, Biometrika.

[43]  Chris J. Cieszewski,et al.  Comparing Fixed- and Variable-Base-Age Site Equations Having Single Versus Multiple Asymptotes , 2002 .

[44]  Oscar García,et al.  Evaluating forest Growth Models , 1997 .

[45]  I. Cañellas,et al.  Generalized height-diameter and crown diameter prediction models for cork oak forests in Spain , 2007 .

[46]  H. White.  A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .

[47]  U. Diéguez-Aranda,et al.  A growth model for Pinus radiata D. Don stands in north-western Spain , 2007, Annals of Forest Science.

[48]  F. crecente-campo,et al.  DYNAMIC GROWTH MODEL FOR BIRCH STANDS IN NORTHWESTERN SPAIN , 2011 .

[49]  A. Harvey.  Estimating Regression Models with Multiplicative Heteroscedasticity , 1976 .

[50]  Oscar García.  STAND GROWTH MODELS : THEORY AND PRACTICE , 2022 .

[51]  A. F. Tetto,et al.  Monte Alegre Formula behavior and adjustment to Irati National Forest, Paraná State, Brazil. , 2010 .

[52]  U. Diéguez-Aranda,et al.  Modelling stand basal area growth for radiata pine plantations in Northwestern Spain using the GADA , 2007, Annals of Forest Science.

[53]  Ulises Diéguez-Aranda,et al.  Dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain) , 2006 .

[54]  Harold E. Burkhart,et al.  Modeling dominant height growth of radiata pine (Pinus radiata D. Don) plantations in north-western Spain , 2005 .

[55]  Chris J. Cieszewski,et al.  Polymorphic height and site index curves for lodgepole pine in Alberta , 1989 .

[56]  Dynamic growth and yield model including environmental factors for Eucalyptus nitens (Deane & Maiden) Maiden short rotation woody crops in Northwest Spain , 2015, New Forests.

[57]  H. Burkhart,et al.  Modeling survival in juvenile and mature loblolly pine plantations , 1997 .

[58]  P. Álvarez-Álvarez,et al.  Influence of climate, edaphic factors and tree nutrition on site index of chestnut coppice stands in north-west Spain , 2011 .

[59]  Marc E. McDill,et al.  Measuring Forest Site Quality Using the Parameters of a Dimensionally Compatible Height Growth Function , 1992 .

[60]  Effects of soil nutrients and environmental factors on site productivity in Castanea sativa Mill. coppice stands in NW Spain , 2015, New Forests.

[61]  Juan Majada,et al.  A three level system for estimating the biomass of Castanea sativa Mill. coppice stands in north-west Spain , 2013 .

[62]  J. Majada,et al.  Stem taper function for sweet chestnut (Castanea sativa Mill.) coppice stands in northwest Spain , 2014, Annals of Forest Science.

[63]  Celia Martínez-Alonso,et al.  Carbon sequestration for different management alternatives in sweet chestnut coppice in northern Spain , 2016 .

[64]  Fernando Castedo-Dorado,et al.  Dynamic growth model for I-214 poplar plantations in the northern and central plateaux in Spain , 2008 .

[65]  L. Pienaar,et al.  Yield Prediction for Mechanically Site-Prepared Slash Pine Plantations in the Southeastern Coastal Plain , 1993 .

[66]  K. Rennolls,et al.  Timber Management-A Quantitative Approach. , 1984 .

[67]  Julio L. Bueno,et al.  Evaluation of Tree Species for Biomass Energy Production in Northwest Spain , 2018 .

[68]  H. Salminen,et al.  Evaluating estimation methods for logistic regression in modelling individual-tree mortality , 2003 .

[69]  V. Lemay,et al.  Modelling and prediction of dominant height and site index of Eucalyptus globulus plantations using a nonlinear mixed-effects model approach , 2007 .

[70]  K. Gadow,et al.  Site quality curves for birch stands in north-western Spain , 2006 .