Improvement in accuracy of aboveground biomass estimation in Eucalyptus nitens plantations: Effect of bole sampling intensity and explanatory variables

Forest Ecology and Management

Volumn 261, Issue 11, 2011, Pages 2016-2028

  Pérez Cruzado, César ^a   Rodríguez Soalleiro, Roque ^a  

^a UNIVERSITY OF SANTIAGO DE COMPOSTELA   (Spain)

Author keywords

Biomass; Crown variables; Eucalyptus nitens; Ratio type estimators; Wood basic density; Wood moisture

Indexed keywords

CROWN VARIABLES; EUCALYPTUS NITENS; RATIO TYPE ESTIMATORS; WOOD BASIC DENSITY; WOOD MOISTURE;

ESTIMATION; FORESTRY; MOISTURE; SAMPLING; WEIGHING; WOOD;

BIOMASS;

ABOVEGROUND BIOMASS; ACCURACY ASSESSMENT; CANOPY ARCHITECTURE; DIAMETER; ESTIMATION METHOD; EVERGREEN TREE; FUNCTIONAL MORPHOLOGY; HEIGHT; MOISTURE CONTENT; PLANTATION; REGRESSION ANALYSIS; SAMPLING; VOLUME; WOOD;

ACCURACY; BIOMASS; CROWNS; ESTIMATION; EUCALYPTUS NITENS; MOISTURE; SAMPLING; TREES; VARIABLES; WEIGHING; WOOD DENSITY;

SPAIN;

EUCALYPTUS; EUCALYPTUS NITENS;

EID: 79955037628     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2011.02.028     Document Type: Article

References (45)

1. Álvarez-González J.G., Rodríguez-Soalleiro R., Rojo-Alboreca A. Resolución de problemas del ajuste simultáneo de sistemas de ecuaciones: heterocedasticidad y variables dependientes con distinto número de observaciones. Cuadernos SECF 2007, 23:35-42.
2. António N., Tomé M., Tomé J., Soares P., Fontes L. Effect of tree, stand, and site variables on the allometry of Eucalyptus globulus tree biomass. Can. J. For. Res. 2007, 37:895-906.
3. Bartelink H.H. Allometric relationships on biomass and needle area of Douglas-fir. For. Ecol. Manage. 1996, 86:193-203.
4. Breusch T.S., Pagan A.R. A simple test for heteroscedasticity and random coefficient variation. Econometrica 1979, 47:1287-1294.
5. Briggs R.D., Cunia T., White E.H., Yawney H.W. Estimating sample tree biomass by subsampling: some empirical results. Estimating Tree Biomass Regressions and Their Error. Proceedings of the Workshop on Tree Biomass Regression Functions and Their Contribution to the Error of Forest Inventory Estimates 1987, Compiled by EH Wharton and T. Cunia. USDA For. Serv. Gen. Tech. Rep. NE-117 119-127.
6. Broad L.R. Allometry and growth. For. Sci. 1998, 44:458-464.
7. Brown I.F., Martinelli L.A., Thomas W.W., Moreira M.Z., Ferreira C.A.C., Victoria R.A. Uncertainty in the biomass of Amazonian forests: an example from Rondônia. Brazil. For. Ecol. Manage. 1995, 75:175-189.
8. Brown S. Measuring carbon in forests: current status and future challenges. Environ. Pollut. 2002, 116:363-372.
9. Carvalho J.P., Parresol B.R. Additivity in tree biomass components of Pyrenean oak (Quercus pyrenaica Willd.). For. Ecol. Manage. 2003, 179:269-276.
10. Chave J., Riéra B., Dubois M.A. Estimation of biomass in a neotropical forest of French Guiana: spatial and temporal variability. J. Trop. Ecol. 2001, 17:79-96.
11. Clark A. Predicting biomass production in the South. Predicting Growth and Yield in the Mid-South. 31st Annual Forest Symposium 1982, 119-139. J.E. Hotverdt, B.D. Jackson (Eds.).
12. Clutter J.L., Fortson J.C., Pienaar L.V., Brister H.G., Bailey R.L. Timber Management: A Quantitative Approach 1983, John Wiley and Sons, New York.
13. Cunia T. On sampling trees for biomass tables construction: Some statistical comments. Forest Resource Inventories 1979, vol. 2:643-664. Colorado State University, Fort Collins, CO.
14. Cunia T. Construction of tree biomass tables by linear regression techniques. Estimating Tree Biomass Regressions and their Error: Proceedings of the Workshop on Tree Biomass Regression Funktions and their Contribution to the Error of Forest Inventory Estimates 1987, 27-36. E.H. Wharton, T. Cunia (Eds.).
15. Gregoire T.G., Valentine H.T., Furnival G.M. Sampling methods to estimate foliage and other characteristics of individual trees. Ecology 1995, 76:1181-1194.
16. Harvey A.C. Estimating regression models with multiplicative heteroscedasticity. Econometrica 1976, 44:461-465.
17. Jenkins J.C., Chojnacky D.C., Heath L.S., Birdsey R.A. National-scale biomass estimators for United States tree species. For. Sci. 2003, 49:13-35.
18. Johansson T. Biomass equations for determining fractions of pendula and pubescent birches growing on abandoned farmland and some practical implications. Biomass Bioenergy 1999, 16:223-238.
19. Jokela E.J., Van Grup K.P., Briggs R.D., White E.H. Biomass estimation equations for Norway spruce in New York. Can. J. For. Res. 1986, 16:413-415.
20. Ketterings Q.M., Coe R., van Noordwijk M., Ambagau Y., Palm C.A. Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For. Ecol. Manage. 2001, 146:199-209.
21. Kleinn C., Pelz D.R. Subsampling trees for biomass. Estimating Tree Biomass Regressions and their Error: Proceedings of the Workshop on tree Biomass Regression Functions and their Contribution to the Error of Forest Inventory Estimates 1987, 225-227. E.H. Wharton, T. Cunia (Eds.).
22. Loomis R.M., Phares R.E., Crosby J.S. Estimating foliage and branchwood quantities in shortleaf pine. For. Sci. 1966, 12:30-39.
23. Martínez Cortizas A., Pérez Alberti A. Atlas Climático De Galicia 1999, Xunta de Galicia, Santiago de Compostela.
24. Monserud R.A., Marshall J.D. Allometric crown relations in three northern Idaho conifer species. Can. J. For. Res. 1999, 29:521-535.
25. Neter, J., Wasserman, W., Kutner, M.H., William Wasserman, M.H.K., 1989. Applied Linear Regression Models. Irwin Homewood, IL, New York.
26. Parresol B.R. Modeling multiplicative error variance: an example predicting tree diameter from stump dimensions in baldcypress. For. Sci. 1993, 39:670-679.
27. Parresol B.R. Assessing tree and stand biomass: a review with examples and critical comparisons. For. Sci. 1999, 45:573-593.
28. Parresol B.R. Additivity of nonlinear biomass equations. Can. J. For. Res. 2001, 31:865-878.
29. Parresol B.R., Thomas C.E. A density-integral approach to estimating stem biomass. For. Ecol. Manage. 1989, 26:285-297.
30. Pearson J.A., Fahey T.J., Knight D.H. Biomass and leaf area in contrasting lodgepole pine forests. Can. J. For. Res. 1984, 14:259-265.
31. Pérez-Cruzado C. Herramientas de gestión para plantaciones de Eucalyptus nitens (Deane & Maiden) Maiden con el objetivo de fijación de carbono. University of Santiago de Compostela 2009.
32. Porté A., Trichet P., Bert D., Loustau D. Allometric relationships for branch and tree woody biomass of Maritime pine (Pinus pinaster Ait.). For. Ecol. Manage. 2002, 158:71-83.
33. Reed D., Tomé M. Total aboveground biomass and net dry matter accumulation by plant component in young Eucalyptus globulus in response to irrigation. For. Ecol. Manage. 1998, 103:21-32.
34. Saint-André L., M'Bou A.T., Mabiala A., Mouvondy W., Jourdan C., Roupsard O., Deleporte P., Hamel O., Nouvellon Y. Age-related equations for above-and below-ground biomass of a Eucalyptus hybrid in Congo. For. Ecol. Manage. 2005, 205:199-214.
35. Sands P.J., Landsberg J.J. Parameterisation of 3-PG for plantation grown Eucalyptus globulus. For. Ecol. Manage. 2002, 163:273-292.
36. SAS Institute Inc, 2004. SAS/STAT 9.1 User's Guide. Cary, NC.
37. Satoo T., Madgwick H.A.I. For. Biomass 1982, 152.
38. Schaegel B.E. Boxelder (Acer negundo L.) biomass component regression analysis for the Mississippi Delta. For. Sci. 1982, 20:617-628.
39. Snowdon P., Eamus D., Gibbons P., Khanna P.K., Keith H., Raison R.J., Kirschbaum M.U.F. Synthesis of Allometrics, Review of Root Biomass and Design of Future Woody Biomass Sampling Strategies 2000, Australian Greenhouse Office, Canberra.
40. Ter-Mikaelian M.T., Korzukhin M.D. Biomass equations for sixty-five North American tree species. For. Ecol. Manage. 1997, 97:1-24.
41. Ter-Mikaelian M.T., Parker W.C. Estimating biomass of white spruce seedlings with vertical photo imagery. New Forests 2000, 20:145-162.
42. Valentine H.T., Tritton L.M., Furnival G.M. Subsampling trees for biomass, volume, or mineral content. For. Sci. 1984, 30:673-681.
43. Verwijst T., Telenius B. Biomass estimation procedures in short rotation forestry. For. Ecol. Manage. 1999, 121:137-146.
44. White H. A heterocedasticity-consistent covariance matrix estimator and a direct test for heterocedasticity. Econometrica 1980, 48:817-838.
45. Zianis D., Mencuccini M. On simplifying allometric analyses of forest biomass. For. Ecol. Manage. 2004, 187:311-332.