Investigation of the Allometric Models in Estimation of Poplar (Populus deltoides) Height

Abedi, Tooba; Abedi, Roya

[Home ] [Archive]

[ فارسی ]

Main Menu

Home

Journal Information

Articles archive

For Authors

For Reviewers

Registration

Contact us

Site Facilities

Search in website

Receive site information

Volume 8, Issue 17 (12-2020)

PEC 2020, 8(17): 157-174

Back to browse issues page

Investigation of the Allometric Models in Estimation of Poplar (Populus deltoides) Height

Tooba Abedi¹

, Roya Abedi ^*

1- Environmental Research Institute, Academic Center for Education, Culture and Research
University of Tabriz, Ahar Faculty of Agriculture and Natural Resources , royaabedi@tabrizu.ac.ir

Abstract: (3033 Views)

One of the most important issues in forest biometrics is the use of allometric functions to estimate tree height by using diameter-height models. Measuring the total height of trees is usually a complex and time-consuming process. In allometric functions, the diameter is measured directly but the height of the tree is an estimate of an allometric model, which will be more accurate if the created models were correctly designed. For this reason, diameter-height models have been considered as an important element in forest management and monitoring nowadays. Therefore, we evaluated the performance of allometric models in estimating the height of this species in the present study. For this purpose, 32 allometric models were used and the coefficient of determination, standard error, Akaike coefficient, Root Mean Square Error, percentage of Root Mean Square Error, Bias, and percent of Bias criteria were used for estimating the accuracy of each model. The results showed that five models consisting of Loetsch, Ratkowsky, Hyperbolic 2, Hyperbolic 3, and Modified Geometry were able to measure the height of poplar trees (as the dependent variable) in terms of diameter of breast height (as the independent variable) with the highest amount of coefficient of determination (0.829-0.830), The lowest amounts of standard error (1.756-1.758), RMSE (0.682- 0.747 m), the RMSE% (3.177-3.511), Bias (-0.076 to -0.331), and Bias% (0.352 -1.558). In addition, the results of the t-test showed that there was no significant difference between the predicted values of height and the actual measured values of height. Consequently, these models were able to estimate the height of poplar trees without significant difference.

Keywords: Afforestation, Poplar (Populus deltoides), Diameter-height model, Modelling

Full-Text [PDF 254 kb] (629 Downloads)

Type of Study: Research | Subject: Special
Received: 2020/02/1 | Accepted: 2020/09/14 | Published: 2021/03/12

References

1. Bates, D.M.&D.G. Watts, 1980. Relative curvature measures of nonlinearity. Journal of the Royal Statistical Society, Series B, 42: 1–16.

2. Buford, M.A. 1986. Height–diameter relationship at age 15 in loblolly pine seed sources. Forest Science, 32: 812–818.

3. Burk, T.E.&H.E. Burkhart, 1984. Diameter distributions and yields of natural stands of loblolly pine. Blacksburg, Vir¬ginia Polytechnic Institute and State University, Blacksburg Publishing: 46.

4. Burkhart, H.E&M.R. Strub, 1974. A model for simulation of planted loblolly pine stands. In: Fries J. (ed.): Growth Models for Tree and Stand Simulation. Stockholm. Royal College of Forestry, Research Note, 30: 128–135.

5. Cameron, A.C.& F.A.G. Windmeijer, 1997. An R-squared measure of goodness of fit for some common nonlinear regression models. Journal of Economy, 77: 329–342.

6. Chapman, D G. 1961. Statistical problems in dynamics of exploited fisheries populations.In: Neyman J, editor. Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, Vol. 4, 1 53–1 68. Berkeley, CA: University of California Press.

7. Curtis, R.O. 1967. Height-diameter and height-diameter-age equations for second-growth Douglas-Fir. Forest Science, 13: 365 –375.

8. Eby, M., S.O. Oyamakin& A.U. Chukwu, 2017. A new nonlinear model applied to the height-DBH relationship inGmelina arboreaWayne. Forest Ecology and Management, 397: 139–149.

9. Ercanli, I., A. Gunlu & E.Z. Baskent, 2015. Mixed effect models for predicting breast height diameter from stump diameter of Oriental beech in Gölda˘g. Scientia Agricola, 72(3): 245-251.

10. Farr, W.A., D.J. De Mas &J.E. Dealy, 1989. Height and crown width related to diameter for open-grown western hemlock and Sitka spruce. Canadian Journal of Forest Research, 19: 1203–1207.

11. Guo, X.&X. Zhang, 2010. Performance of 14 hybrid poplar clones grown in Beijing, China. Biomass and Bioenergy, 34: 906–911.

12. Huang, S., S.J. Titus&D.P. Wiens, 1992. Comparison of nonlinear height–diameter functions for major Alberta tree species. Canadian Journal of Forest Research, 22(9): 1297-1304.

13. Kalbi, S., A. Fallah, P. Bettinger, Sh. Shataee & R. Yousefpour, 2017. Mixed-effects modeling for tree height prediction models of Oriental beech in the Hyrcanian forests. Journal of Forest Research, 29: 1195-1204.

14. Larson, B.C. 1986. Development and growth of even-aged stands of Douglas-fir and grand fir. Canadian Journal of Forest Research, 16: 367–372.

15. Larsen, D.R.&D.W. Hann, 1987. Height-diameter Equations for Seventeen Tree Species in Southwest Oregon. Oregon State University, Increment for Models of Forest Growth. Research Paper INT-164, Published by U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, Utah, USA, 23p

16. Loetsch, F., F. Zöhrer & K.E. Haller, 1973. Forest Inventory. Munich, BLV Verlagsgesellschaft: 469.

17. Lumbres, R.I.C., Y.J. Lee, F.G.Calora Jr&M.R. Parao, 2013. Model fitting and validation of six height–DBH equations for Pinus kesiyaRoyle ex Gordon in Benguet Province, Philippines. Forest science and Technology, 9(1): 45-50.

18. Lumbres, R.I.C., Y.J. Lee, Y.O. Seo,S.H. Kim, J.K. Choi & W.K. Lee, 2011. Development and validation of nonlinear height–DBH models for major coniferous tree species in Korea. Forest Science and Technology, 7(3): 117-125.

19. Meyer, H.A. 1940. A mathematical expression for height curves. Journal of Forestry, 38: 415–420.

20. Moffat A.J., R.W. Matthews &J.E. Hall, 1991. The effects of sewage sludge on growth and foliar and soil chemistry in pole-stage Corsican pine at Ringwood Forest, Dorset, UK. Canadian Journal of Forest Research, 21: 902–909.

21. Navroodi, I.H., S.J. Alavi, M.K. Ahmadi & M. Radkarimi, 2016. Comparison of different non-linear models for prediction of the relationship between diameter and height of velvet maple trees in natural forests (Case study: Asalem Forests, Iran). Journal of Forest Science, 62(2): 65-71.

22. Pearl, R.& L.J. Reed, 1920.On the rate of growth of the population of United States since 1790 and its mathematical representation. Proceedings of the National Academy of Science of the United States of America, 6: 275–288.

23. Peng, Ch., L. Zhang, X. Zhou & Q. Dang, 2004. Developing and evaluating tree height-diameter models at three geographic scales for black spruce in Ontario. Northern Journal of Applied forestry, 21 (2): 83-92.

24. Petras, R., M. Bošeľa, J. Mecko, J. Oszlányi & I. Popa, 2014. Height-diameter models for mixed-species forests consisting of spruce, fir, and beech. Folia Forestalia Polonica, Series A, 56(2), 93–104.

25. Piao, D., M. Kim, G.M. Choi, J. Moon, H. Yu,W.K. Lee, S.W. Wang, S.W. Jeon, Y. Son, Y.M. Son & G. Cui, 2018. Development of an Integrated DBH EstimationModel Based on Stand and Climatic Conditions. Forests 9(155): 1-18.

26. Prodan, M. &S.H. Gardiner, 1968. Forestbiometrics. Pergamon Press, Oxford, 447 p.

27. Ratkowsky, D. 1990. Handbook of nonlinear regression models. Marcel Dekker, New York, NY.

28. Ratkowsky, D.A.& T.J. Reedy, 1986. Choosing near-linear parameters in the four-parameter logistic model for radioligand and related assays. Biometrics, 42: 575-582.

29. Richards, F.J. 1959. A flexible growth function for empirical use. Journal of Experimental botany, 10: 290 –300.

30. Saramaki, J. 1992. Growth and yield prediction model of Pinus kesiya (Royle Ex Gordon) in Zambia. Forestelia Fennica Acta, 230, 68.

31. Schnute, J. 1981. A versatile growth model with statistically stable parameters. Canadian Journal of Fisheries and Aquatic Sciences, 38(9): 1128-1140.

32. Schreuder, H.T., W.L. Hafley&F.A. Bannett, 1979. Yield prediction for unthinned natural slash pine stands. Forest Science, 25: 25–30.

33. Sibbesen, E. 1981. Some new equations to describe phos¬phate sorption by soils. European Journal of Soil Science, 32: 67–74.

34. Stage, A.R. 1963. A mathematical approach to polymorphic site index curves for grand fir. Forest Science, 9(2): 167-180.

35. Stage, A.R. 1975. Prediction of height increment for models of forest growth. Research Paper INT-164. Ogden, Inter mountain Forest and Range Experiment Station, USDA Forest Service: 20.

36. Stoffels A.&J. Van Soest, 1953. The main problems in sample plots. 3. Height regression. Ned Bosbouwtijdschr, 25: 190- 199.

37. Watts, S.B. 1983. Forestry Handbook for British Columbia. 4th Ed. Vancouver, University of British Columbia: 773.

38. Winsor, C.P. 1932. The Gomperz curve as growth curve. Proceedings of the National Academy of Sciences of the United States of America, 18: 1-8.

39. Wykoff, W., N. Crookston &A. Stage, 1982. User’s guide to the stand prognosis model. Ogden, Utah: US.

40. Yang, R.C., A.Kozak & J.H.G. Smith, 1978. The potential of Weibull type functions as flexible growth curves. Canadian Journal of Forest Research 8(4): 424-431.

41. Zeide, B. 1989. Accuracy of equations describing diameter growth. Canadian Journal of Forest Research, 19(10): 1283- 1286.

42. Zhang, X., A. Duan, J. Zhang & C. Xiang, 2014. Estimating Tree Height-Diameter Models with the Bayesian Method. The Scientific World Journal, 3:683-691.

Send email to the article author

Add your comments about this article

Mendeley

Zotero

RefWorks

Abedi T, Abedi R. Investigation of the Allometric Models in Estimation of Poplar (Populus deltoides) Height. PEC 2020; 8 (17) :157-174
URL: http://pec.gonbad.ac.ir/article-1-657-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 8, Issue 17 (12-2020)

Back to browse issues page

Persian site map - English site map - Created in 0.06 seconds with 37 queries by YEKTAWEB 4679