Mapping the spatial distribution of forest growth characteristics using different geostatistical methods (Case study: District no. 3, Sangdeh- Sari)

Document Type : Scientific article

Authors

1 Ph.D. Student Forestry, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resource University, Sari, Iran

2 Associate Prof., Department of Forestry, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

3 Associate Prof., Department of Forestry, Faculty of Forest Sciences, Gorgan Agricultural Sciences and Natural Resources University, Gorgan, Iran

4 Assistant Prof., Department of Forest Economics and Planning, Faculty of Forestry Economics and Forest Planning, University of Freiburg, Freiburg, Germany

5 Prof., Department of Forestry and Natural Resources, Faculty of Natural Resources and Environment, University of Georgia, Athens, USA

Abstract

Investigation on spatial distribution of tree growth characteristics in different forest stands, has a fundamental role in assessing possible harvest planning considering potential of the stands. The aim of this study is mapping the spatial distribution of forest characteristics such as stand volume growth, diameter, growth, ingrowth) and determining the amount of tree mortality in the district three of Sangdeh  region within a period of 5 years. Two methods of Ordinary Kriging (OK) and weighted Inverse Distance (IDW) interpolation were applied for mapping. For this purpose, we calculated the increment using direct measurement in 130 permanent sample plots. The results of this study showed that the mean volume increment, diameter increment, ingrowth and annual mortality were 5.65 cubic meters per hectare per year, 0.48 cm, 3.5 and 4.2 stems per hectare per year, respectively. For volume increment, the IDW method by power one and with a root mean square error 0.29 cubic meters per hectare per year, for diameter increment, ingrowth and annual mortality the ordinary Kriging method with a root mean square error 0.219 cm per year, 1.4 and 2.8 nha-1y-1 showed better results, respectively. Overall the results showed that geostatistical methods are efficient methods for mapping forest growth characteristics.

Keywords

References

-Aertsen, W., Kint, V., Wilpert, K.V., Zirlewagen, D., Muys, B. and Orshoven, J.V., 2012. Testing novel cytokinins for improved in vitro adventitious shoots formation and subsequent ex vitro performance in Pinus radiate. Forestry, 85(4): 539-550.
- Akhavan, R., Karami Khorramabadi, M. and Soosani, J., 2012. Application of Kriging and IDW methods in mapping of crown cover and density of coppice oak forests (Case study: Kakareza region, Khorramabad). Iranian Journal of Forest, 3(4): 305-316 (In Persian).
- Akhavan, R., Kia Daliri, H. and Etemad, V., 2015. Geostatistically estimation and mapping of forest stock in a natural unmanaged forest in the Caspian region of Iran. Caspian Journal of Environmental Sciences, 13(1): 61-76.
- Akhavan, R. and Klein, K., 2010. Performance Kriging estimated and mapping volume forest plantation (Case study: Ramsar Beneshky plantation). Iranian Journal of Forest and Poplar Research, 2(17): 303-318 (In Persian).
- Amini, M., Namiranian, M., Sagheb Talebi, Kh. and Amini, R., 2009. Investigation on the homogenity of diameter increment models in Fagus orientalis L. trees. Journal of Wood and Forest Science and Technology, 16(4): 1-23 (In Persian).
- Anonymous, 2000. Forest Management Plan of Sangdeh, district No. 3. Published by Forests, Range and Watershed Manegemnt Organization, 115p.
- Bayat, M., Namiranian, M., Zobeiri, M. and Fathi, J., 2014. Determining growth increment and density of trees in forest using permanent sample plots (Case study: Gorazbon district of Kheyroud Forest). Iranian Journal of Forest and Poplar Research, 21(3): 424-438 (In Persian).
- Burkhart, H.E., 1990. Status and future of growth and yield models: 409-414. In: LaBau, V.J. and Cunia, T. (Eds.). State-of-the-art Methodology of Forest Inventory: A Symposium Proceedings. USDA Forest Service, Pacific Northwest Forest Experiment Station, Portland, 414p.
- Cao, Q.V., 2014. Linking individual-tree and whole-stand models for forest growth and yield prediction. Cao Forest Ecosystems, 1(18): 1-8.
- Fahlvik, N., Elfving, B. and Wikström, P., 2014. Evaluation of growth models used in the Swedish forest planning system Heureka. Silva Fennica, 48(2): 1-17.
- Gholami, Gh. 2004. Comparing method for estimating allowable cut rates in uneven-aged forestry method, M.Sc. thesis, Sari Agricultural Sciences and Natural Resources University, 106p (In Persian).
- Gonzalez-Benecke, C.A., Gezan, S.A., Samuelson, L.J., Cropper Jr.W.P., Leduc, D.J. and Martin, T.A., 2014. Estimating Pinus palustris tree diameter and stem volume from tree height, crown area and stand-level parameters. Journal of Forestry Research, 25(1): 43-52.
- Guisan, A. and Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135: 147-186.
- Hassani Pak, A.A., 1992. Geostatistic. Tehran University Press, Tehran, 314p (In Persian).
- Johnston, K., Ver Hoef, J.M., Krivoruchko, K. and Lucas, N., 2003. Using ArcGIS Geostatistical Analyst. Environmental Systems Research, Analyst; Environmental Systems Research Institute: Redlands, CA, USA, pp. 81-112.
- Jokar, M., Feghhi, J., Heshmat Alvaezin, S.M., Namiranian, M. and Etemad, V., 2013. Determination of the volume increment of beech Caspian Switzerland control method. Forest and Range Quarterly Journal, 97: 40-45 (In Persian).
- Khorankeh, S., Fallah, A., Jalilvand, H. and Espahbodi, K., 2011. Determination of Acer volutinum growth diameter in eastern Mazandaran forest. Proceedings of Conference on the Roadmap and Supply of Raw Materials Wood and Paper Industry Development. Mazanderan, 22-23 Nov. 2011: 12-17 (In Persian).
- Khosh Akhlagh, R., Nafar, M., Sharifi, A., Matinkhah, H. and Farahmand, K., 2012. Economic analysis and optimization of northern forests (Shafarood, district no. 16). Development and Agricultural Economics, 17: 115-138.
- Kravchenko, A.N. and Bullock, D.G., 1999. A comparative study of interpolation methods for mapping soil properties. Journal of Agronomy, 91: 393-400.
- Laslett, G.M., McBratney, A.B., Pahl, P.J. and Hutchinson, M.F., 1987. Comparison of several spatial prediction methods for soil pH. Journal of Soil Science, 38: 325-341.
- Legendre, P. and Fortin, M.J., 1989. Spatial pattern and ecological analysis. Plant Ecology, 80: 107-138.
- Miller, J., Franklin, J. and Aspinall, R., 2007. Incorporating spatial dependence in predictive vegetation models. Ecological Modelling, 202: 225-242.
- Montes, F., Hernandez, M.J. and Canellas, I., 2005. A geostatistical approach to cork production sampling in Quercus suber forests. Canadian Journal Forest Research, 35: 2787-2796.
- O’Rourke, S., Gabrielle, E. and Kelly, G.E., 2015. Spatio-temporal modelling of forest growth spanning 50 years- the effects of different thinning strategies. Procedia Environmental Sciences, 26: 101-104.
- Pastur, G.J., Cellini, J.M., Lencinas, M.V. and Peri, P.L., 2008. Stand growth model using volume increment/basal area ratios. Journal of Forest Science, 54: 102-108.
- Robinson, T.P. and Metternicht, G., 2006. Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and Electronics in Agriculture, 50: 97-108.
- Saghafiyan, B., Razmjo, H. and Ghermez Cheshmeh, B., 2012. Investigated regional variations in annual rainfall using geostatistical method (case study: Fars provianc). Journal of Water Resources Engineering, 4: 29-38 (In Persian).
- Zobeiri, M., 2005. Inventory and Measurement of Forest. University of Tehran Press, Tehran, 320p (In Persian).

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