Analyzing the response curves of box tree (Buxus hyrcana Pojark.) species in relation to environmental variables in Hyrcanian forests

Document Type : Scientific article

Authors

1 MSc. Student, Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, I. R. Iran.

2 Assistant Professor, Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, I. R. Iran.

Abstract

In the present study, the response curve of box tree to some edaphic characteristics (texture, nitrogen content, carbon content and pH) and physiographic factors (slope, aspect, and altitude) were analyzed in the Hyrcanian forests using random forest algorithm. For this purpose, 857 sample plots (400 m2) were established in the large habitats of B. hyrcana as selective method. The response curve of B. hyrcana Pojark showed that acidity and altitude are the most important and aspect and silt content are the least important variables. Also, based on the ecological optimum values for each variable showed that the Buxus tree is lime- and moisture-demanding species, which is present in low altitudes, steep slopes and light soils with high nitrogen content that can be used for the management decisions. The results and methods presented in the paper can also be applied to conserve and restore the other rare and endangered species.

Keywords


- Aertsen, W., V. Kint, J. Van Orshoven, K. Özkan, & B. Muys, 2010. Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests. Ecological modelling, 221(8): 1119-1130.
- Ahmadi, K., S. J. Alavi, & M. Tabari Kouchaksaraei, 2015. Evaluation of oriental beech (Fagus orientalis L.) site productivity using generalized additive model (Case study: Tarbiat Modares University Forest Research Station). Iranian Journal of Forest, 7(1): 17-32. (In Persian)
- Alavi, S. J., Z. Nouri, & G. H. Zahedi Amiri, 2017.The Response Curve of Beech Tree (Fagus Orientalis Lipsky.) in Relation to Environmental Variables Using Generalized Additive Model in Khayroud Forest, Nowshahr. Journal of Forest and Wood Science and Technology, 24(1): 29-51. (In Persian)
 
 
- Alavi, S. J., Z. Nouri, & G. H. Zahedi Amiri, 2017. Determining the most important environmental variables affecting on oriental beech (Fagus orientalis Lipsky.) site productivity using random forest technique in Khayroud forest, Nowshar. Iranian Journal of Forest, 8(4): 477-492. (In Persian)
- Asadi, H., S. M. Hosseini, & O. Esmailzadeh, 2012. Persistent soil seed bank in Khybus protected area. Journal of Forest and Wood Products (JFWP), Iranian Journal of Natural Resources, 65(2): 131-145. (In Persian)
- Asadi, H., O. Esmailzadeh, S. M. Hosseini, Y. Asri, & H. Zare, 2016. Application of Cocktail method in vegetation classification. Taxonomy and Biosystematics, 8 (28): 21-38. (In Persian)
- Austin, M. P., & M.J. Gaywood, 1994. Current problems of environmental gradients and species response curves in relation to continuum theory, J. Veg. Sci. 5, 473-482.
- Bakhshi Khaniki, G., & B. Mohammadi, 2012. Ecological Study of Some Species of the Genus Salsola (Chenopodiaceae) in Golestan Province, NCMBJ, 2 (6): 45-52. (In Persian)
- Bale, C. L. J., B. Williams, & J. L. Charly, 1998. The impact of aspect on forest structure and floristic in some eastern Australian sites, Forest Ecology and Management. 110: 363-377.
- Beauregard, F., & S. de Blois, 2014. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution Models, PloS one, 9(3): e92642.
- Beazley, L., E. Kenchington, F. J. Murillo, C. Lirette, J. Guijarro, A. McMillan, & A. Knudby, 2016. Species Distribution Modelling of Corals and Sponges in the Eastern Arctic for Use in the Identification of Significant Benthic Areas. Ocean and Ecosystem Sciences Division, Maritimes Region, Fisheries and Oceans, Bedford Institute of Oceanography, Canada, 197 p.
- Birks, H.J, 2012. Overview of Numerical Methods in Palaeolimnology, In Tracking Environmental Change Using Lake Sediments, Springer Netherlands, 19-92.
- Breiman, L, 1996. Bagging predictors. Machine Learning; 24(2): 123–40.
- Carvalho, M.C. L.R, Gomide. R.M.D, Santos. J.R.S, Scolforo. L.M.T.D, Carvalho. & J.M.D, Mello, 2017. Modeling Ecological Niche OF Tree Species IN Brazilian Tropical Area, Cerne, 23(2), pp.229-240.
- Cutler, D. R., T. C. Edwards Jr, K. H. Beard, A. Cutler, K. T. Hess, J. Gibson, & J. J. Lawler, 2007. Random forests for classification in ecology, Ecology, 88(11): 2783-2792.
- Giannini, T. C. R., R. Lira-Saadeb, A. M. Ayalac, Saraivad. & I, Alves-Santosa, 2011. Ecological niche similarities of Peponapis bees and non-domesticated cucurbita species, Journal of Ecological Modelling, Ecomod, 222 (12): 2011-2018.
- Guisan, A., N. Zimmermann, 2000. Predictive Habitat Distribution Models in ecology, Ecological Modelling, 135(2): 147-186.
- HabibiKaseb, H., 1992. Fundamental of Forest Soil Science. University of Tehran Publication, Tehran, 424 P. (In Persian)
- Hosseinzadeh, S., & O. Esmailzadeh, 2017. Floristic Study of Buxus hyrcana Stands in the Western Forests of Haraz District, Amol, Iranian Journal of Applied Ecology; 6 (1):1-13 (In Persian)
- Iturrate‐Garcia, M. M., J. O'Brien, O. Khitun, S. Abiven, P. A. Niklaus, & G. Schaepman‐Strub, 2016. Interactive effects between plant functional types and soil factors on tundra species diversity and community composition, Ecology and Evolution, 6(22): 8126-8137.
- Jalili, A., & Z. Jamzad, 1999. Red Data Book of Iran Research Institute of Forest and Rangelands, Tehran, 748 p.
- Jongman, E., & S. R. R. Jongman, (1995). Data analysis in community and landscape ecology. Cambridge university press, Cambridge, 275p.
- Moisen, G. G., & T. S. Frescino, 2002. Comparing five modelling techniques for predicting forest characteristics, Ecological modelling, 157(2): 209-225. ‏
- Noroozi, J., W. Willner, H. Pauli, & G. Grabherr, 2014. Phytosociology and ecology of the high‐alpine to subnival scree vegetation of N and NW Iran (Alborz and Azerbaijan Mts.), Applied Vegetation Science, 17(1): 142-161.
- Oliveira, S., F. Oehler, J. San-Miguel-Ayanz, A. Camia, J. M. Pereira, 2012. Modeling Spatial Patterns of Fire Occurrence in Mediterranean Europe Using Multiple Regression and Random Forest, Forest Ecology and Management, 275: 117-129.
- Pino-Mejías, R., M.D. Cubiles-de-la-Vega, M. Anaya-Romero, A. Pascual-Acosta, A. Jordán-López, & N. Bellinfante-Crocci, 2010. Predicting the potential habitat of oaks with data mining models and the R system, Environmental Modelling & Software, 25(7): 826-836.
- Recknagel, F., 2001. Applications of machine learning to ecological modellin, Ecological Modelling, 146(1-3): 303-310.
- Roodi, Z., H. Jalilvand, & O. Esmailzadeh, 2012. Edaphic effects on distribution of plant ecological groups (Case study: Sisangan Buxus (Buxus hyrcana Pojark.) forest reserve), Journal of Plant Biology, 13(4): 39-56. (In Persian)
- Sabeti, H., 1994. Forests, trees and shrubs of Iran. Yazd University publication. Yazd. 886 p. (In Persian)
- Seidling, W., & R. Fischer, 2008. Deviances from expected Ellenberg indicator values for nitrogen are related to N throughfall deposition in forests, ecological indicators, 8(5): 639-6-46.
- Shirk, A. J., S. A. Cushman, K. M. Waring. Wehenkel, A. Leal-Sáenz, C. Toney, & C. A. Lopez-Sanchez, 2018. Southwestern white pine (Pinus strobiformis) species distribution models project a large range shift and contraction due to regional climatic changes, Forest Ecology and Management, 4(11): 176-186.
- Soleimannejad, L., A. Eslam Bonyad, R. Naghdi, & H. Latifi, 2019. Classification of quantitative attributes of Zagros forest using Landsat 8-OLI and Random Forest algorithm (Case study: protected area of Manesht forests), Journal of Forest Research and Development, 4(4): 415-434. (In Persian)
- Vincenzi, S., M. Zucchetta, P. Franzoi, M. Pellizzato, F. Pranovi, G. A. De Leo, & P. Torricelli, 2011. Application of a Random Forest Algorithm to Predict Spatial Distribution of the Potential Yield of Ruditapes Philippinarum in the Venice Lagoon, Italy, Ecological Modelling, 222(8): 1471-1478.
- Zarrinkafsh, M. K., 1992. Forestry Soil interaction of soil and plants regarding ecological factors ecosystems. Research Institute of Forest and Rangelands, Tehran. 361 p. (In Persian)