Dynamic growth and yield model including environmental factors for Eucalyptus nitens (Deane & Maiden) Maiden short rotation woody crops in Northwest Spain

Published Date
May 2015, Volume 46, Issue 3, pp 387–407

Article

First Online: 

04 February 2015

DOI: 10.1007/s11056-015-9467-7

Cite this article as: 

González-García, M., Hevia, A., Majada, J. et al. New Forests (2015) 46: 387. doi:10.1007/s11056-015-9467-7

Abstract

A dynamic model consisting of two projection functions, dominant height and basal area, was developed for the prediction of stand growth in Eucalyptus nitens bioenergy plantations aged 2–6 years and with stockings of 2,300 and 5,600 trees ha−1. The data came from 40 permanent sample plots, representing site quality variability across the distribution area of E. nitens crops. Three inventories were carried out to collect tree data and determine stand variables. Additionally, edaphic, physiographic and climatic information were obtained and included in the model. For both functions, an ADA growth model was selected, which achieved high accuracy. The corresponding growth curves developed in this study had values of 5, 8, 11 and 14 m for dominant height and 4, 14, 24 and 34 m2 ha−1 for basal area at the base age of 4 years. The inclusion of environmental factors (i.e. soil and climatic variables) as parameters in the model resulted in good estimations and increased the model’s flexibility to adapt to small variations in site conditions. The model developed here is thus shown to be useful for simulating the growth of E. nitens crops when environmental information is available. A prediction function was fitted for use in stands without diameter inventories or not previously occupied by E. nitens, and including environmental variables improved its accuracy. Biomass mean annual increment varied from 3.25 to 18.45 Mg ha−1 year−1 at the end of the rotation, projected as between 6 and 12 years depending on site quality.

References

1. Bailey RL, Clutter JL (1974) Base-age invariant polymorphic site curves. For Sci 20:155–159
2. Barrio-Anta M, Castedo-Dorado F, Diéguez-Aranda U et al (2006) Development of a basal area growth system for maritime pine in northwestern Spain using the generalized algebraic difference approach. Can J For Res 36:1461–1474. doi:10.1139/x06-028CrossRef
3. Barrio-Anta M, Sixto-Blanco H, De Vinas ICR, Castedo-Dorado F (2008) Dynamic growth model for I-214 poplar plantations in the northern and central plateaux in Spain. For Ecol Manag 255:1167–1178CrossRef
4. Bertalanffy LV (1949) Problems of organic growth. Nature 163:156–158CrossRefPubMed
5. Bertalanffy LV (1957) Quantitative laws in metabolism and growth. Q Rev Biol 32:217–231CrossRef
6. Booth TH, Pryor LD (1991) Climatic requirements of some commercially important eucalypt species. For Ecol Manag 43:47–60. doi:10.1016/0378-1127(91)90075-7CrossRef
7. Bravo F, Álvarez-González JG, del Rio M et al (2011) Growth and yield models in Spain: historical overview, contemporary examples and perspectives. For Syst 20:315–328
8. Bravo-Oviedo A, Tomé M, Bravo F et al (2008) Dominant height growth equations including site attributes in the generalized algebraic difference approach. Can J For Res 38:2348–2358. doi:10.1139/X08-077CrossRef
9. Bravo-Oviedo A, Roig S, Bravo F et al (2011) Environmental variability and its relationship to site index in Mediterranean maritime pine. For Syst 20:50–64
10. Breusch TS, Pagan AR (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47:1287. doi:10.2307/1911963CrossRef
11. Castedo-Dorado F, Diéguez-Aranda U, Barrio-Anta M, Álvarez-González JG (2007) Modelling stand basal area growth for radiata pine plantations in northwestern Spain using the GADA. Ann For Sci 64:609–619CrossRef
12. Cieszewski CJ (2001) Three methods of deriving advanced dynamic site equations demonstrated on inland Douglas-fir site curves. Can J For Res 31:165–173CrossRef
13. Cieszewski CJ (2002) Comparing fixed- and variable-base-age site equations having single versus multiple asymptotes. For Sci 48:7–23
14. Cieszewski CJ (2003) Developing a well-behaved dynamic site equation using a modified Hossfeld IV function Y-3 = (ax(m))/(c + x(m-1)), a simplified mixed-model and scant subalpine fir data. For Sci 49:539–554
15. Cieszewski CJ (2004) GADA derivation of dynamic site equations with polymorphism and variable asymptotes from Richards, Weibull, and other exponential functions. University of Georgia, Athens
16. Cieszewski CJ, Bailey RL (2000) Generalized algebraic difference approach: theory based derivation of dynamic site equations with polymorphism and variable asymptotes. For Sci 46:116–126
17. Cieszewski CJ, Bella IE (1989) Polymorphic height and site index curves for lodgepole pine in Alberta. Can J For Res 19:1151–1160. doi:10.1139/x89-174CrossRef
18. Cieszewski CJ, Harrison M, Martin SW (2000) Practical methods for estimating non-biased parameters in self-referencing growth and yield models. University of Georgia PMRC-TR 2000-7
19. Clutter JL (1963) Compatible growth and yield models for loblolly pine. For Sci 9:354–371
20. Clutter JL, Fortson JC, Pienaar LV et al (1983) Timber management: a quantitative approach. Wiley, New York
21. Durbin J, Watson GS (1951) Testing for serial correlation in least squares regression. II. Biometrika 38:159–178. doi:10.2307/2332325CrossRefPubMed
22. FAO (1981) El Eucalyptus en la repoblación forestal. Food and Agriculture Organization of the United Nations, Rome
23. FAO (1991) Digitized soil map of the world. Volume 1: Africa. Volume 2: North and Central America. Volume 3: Central and South America. Volume 4: Europe and West of the Urals. Volume 5: North East Asia. Volume 6: Near East and Far East. Volume 7: South East Asia and Oceania. Release 1.0
24. Fischer G, Prieler S, van Velthuizen H (2005) Biomass potentials of miscanthus, willow and poplar: results and policy implications for Eastern Europe, Northern and Central Asia. Biomass Bioenergy 28:119–132CrossRef
25. Fontes L, Bontemps JD, Bugmann H et al (2010) Models for supporting forest management in a changing environment. For Syst 19:8–29
26. García O (1988) Growth modelling—a (re)view. N Z For 33:14–17
27. Gee GW, Bauder JW (1996) Particle size analysis. In: Klute A (ed) Methods of soil analysis: part 1, 2nd edn. American Society of Agronomy, Madison, pp 383–411
28. González-García M, Hevia A, Majada J, Barrio-Anta M (2013) Above-ground biomass estimation at tree and stand level for short rotation plantations of Eucalyptus nitens (Deane & Maiden) Maiden in Northwest Spain. Biomass Bioenergy 54:147–157. doi:10.1016/j.biombioe.2013.03.019CrossRef
29. González-García M, Almeida AC, Hevia A, Majada J, Beadle C (2015) Application of a process-based model for predicting the productivity of Eucalyptus nitens bioenergy plantations in Spain. Glob Change Biol Bioenergy. Under review
30. Harvey AC (1976) Estimating regression models with multiplicative heteroscedasticity. Econometrica 44:461. doi:10.2307/1913974CrossRef
31. Hossfeld JW (1822) Mathematik für Forstmänner. Ökonomen und Cameralisten, Gotha
32. Krumland B, Eng H (2005) Site index systems for major young-growth forest and woodland species in northern California. California Department of Forestry and Fire Protection, California
33. Laureysens I, Bogaert J, Blust R, Ceulemans R (2004) Biomass production of 17 poplar clones in a short-rotation coppice culture on a waste disposal site and its relation to soil characteristics. For Ecol Manag 187:295–309. doi:10.1016/j.foreco.2003.07.005CrossRef
34. Lundqvist B (1957) On height growth in cultivated stands of pine and spruce in Northern Sweden. Medd Fran Statens Skogfoesk 47:1–64
35. McDill ME, Amateis RL (1992) Measuring forest site quality using the parameters of a dimensionally compatible height growth function. For Sci 38:409–429
36. Mehlich A (1953) Determination of P, Ca, Mg, K, Na, and NH4. Raleigh, North Carolina Soil Test Division
37. Myers R (1986) Classical and modern regression with applications. Duxbury Press, Masssachusetts
38. Newnham RM (1988) A modification of the Ek-Payandeh nonlinear regression model for site index curves. Can J For Res 18:115–120CrossRef
39. Ni C, Liu C (2008) Evaluating behaviours of factors affecting the site index estimate on the basis of a single stand using simulation approach. Can J For Res 38:2762–2770. doi:10.1139/X08-095CrossRef
40. Nunes L, Patricio M, Tomé J, Tomé M (2011) Modeling dominant height growth of maritime pine in Portugal using GADA methodology with parameters depending on soil and climate variables. Ann For Sci 68:311–323CrossRef
41. Oliver CD, Larson BC (1996) Forest stand dynamics. Wiley, New York
42. Pallardy SG, Kozlowski TT (1979) Relationships of leaf diffusion resistance of Populus clones to leaf water potential and environment. Oecologia 40:371–380. doi:10.1007/BF00345333CrossRef
43. Parresol BR, Vissage JS (1998) White pine site index for the southern forest survey. Res. Pap. SRS-10. US Deparment of Agriculture, Forest Service, Southern Research Station, Asheville
44. Peech M (1947) Methods of soil analysis for soil-fertility investigations. Department of Agriculture, Washington
45. Pérez S, Renedo CJ, Ortiz A et al (2006) Energy evaluation of the Eucalyptus globulus and the Eucalyptus nitens in the north of Spain (Cantabria). Thermochim Acta 451:57–64CrossRef
46. Pérez-Cruzado C, Merino A, Rodríguez-Soalleiro R (2011a) A management tool for estimating bioenergy production and carbon sequestration in Eucalyptus globulus and Eucalyptus nitens grown as short rotation woody crops in north–west Spain. Biomass Bioenergy 35:2839–2851. doi:10.1016/j.biombioe.2011.03.020CrossRef
47. Pérez-Cruzado C, Muñoz-Saez F, Basurco F et al (2011b) Combining empirical models and the process-based model 3-PG to predict Eucalyptus nitens plantations growth in Spain. For Ecol Manag 262:1067–1077CrossRef
48. Pérez-Cruzado C, Blanco-Souto A, López-Sánchez CA et al (2013) Calidad de estación y productividad en plantaciones forestales de Eucalyptus nitens (Deane & Maiden) Maiden en el noroeste de España. Actas 6o Congr. For. Esp. CD-Rom
49. Pérez-Cruzado C, Sánchez-Ron D, Rodríguez-Soalleiro R et al (2014) Biomass production assessment from Populus spp. short-rotation irrigated crops in Spain. GCB Bioenergy 6:312–326. doi:10.1111/gcbb.12061CrossRef
50. Pienaar LV, Turnbull KJ (1973) The Chapman-Richards generalization of Von Bertalanffy’s growth model for basal area growth and yield in even—aged stands. For Sci 19:2–22
51. Richards FJ (1959) A flexible growth function for empirical use. J Exp Bot 10:290–301. doi:10.1093/jxb/10.2.290CrossRef
52. Sánchez-Palomares O, Sánchez SF, Carretero-Carrero M (1999) Modelos y cartografía de estimaciones climáticas termopluviométricas para la España peninsular. INIA, Ministerio de Agricultura, Pesca y Alimentación, Madrid
53. SAS Institute Inc. (2004a) SAS/ETS® 9.1 user’s guide. Cary. NC
54. SAS Institute Inc. (2004b) SAS/STAT® 9.1 user’s guide. Cary. NC
55. Sims REH, Maiava TG, Bullock BT (2001) Short rotation coppice tree species selection for woody biomass production in New Zealand. Biomass Bioenergy 20:329–335. doi:10.1016/S0961-9534(00)00093-3CrossRef
56. Tewari VP, Álvarez-González JG, García O (2014) Developing a dynamic growth model for teak plantations in India. For Ecosyst 1:9. doi:10.1186/2197-5620-1-9CrossRef
57. Tomé M, Ribeiro F, Soares P (2001) O modelo Globulus 2.1. Universidad Técnica de Lisboa-ISA, Relatórios Técnico-científicos do GIMREF no 1
58. Trnka M, Trnka M, Fialová J et al (2008) Biomass production and survival rates of selected poplar clones grown under a short-rotation on arable land. Plant Soil Environ 54:78–88
59. White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48:817–838. doi:10.2307/1912934CrossRef
60. Wright L (2006) Worldwide commercial development of bioenergy with a focus on energy crop-based projects. Biomass Bioenergy 30:706–714CrossRef
61. Vanclay JK (1994) Modelling forest growth and yield: applications to mixed tropical forests. CAB International, Wallingford

For further details log on website :
http://link.springer.com/article/10.1007/s11056-015-9467-7