Modelling the site index of Pinus pinaster plantations in Turkey using ecological variables

Cezmi Özel , Şükrü Teoman Güner , Mehmet Türkkan , Selda Akgül , Özdemir Şentürk

Journal of Forestry Research ›› 2020, Vol. 32 ›› Issue (2) : 589 -598.

PDF
Journal of Forestry Research ›› 2020, Vol. 32 ›› Issue (2) : 589 -598. DOI: 10.1007/s11676-020-01113-x
Original Paper

Modelling the site index of Pinus pinaster plantations in Turkey using ecological variables

Author information +
History +
PDF

Abstract

The determination of site productivity in forest ecosystems plays a crucial role in resource management. This study was carried out to identify relationships between site characteristics and height growth of Corsican maritime pine (Pinus pinaster Ait.) plantations in Turkey. Sixty-nine sample plots > 20 years of age were selected from locations with different inclinations, aspects, elevations, slope positions and site class. Soil samples were taken at various depths. Height and age were measured on a dominant tree after felling in each plot. Physical and chemical properties of the soil were determined. Relationships between site index (SI25) and physiographic factors, climatic attributes as well as soil properties were evaluated using correlation analysis and multiple regression analysis. Site index was significantly related with annual precipitation, mean spring rainfall, rainfall June to September, rainfall of the driest month, length of the dry period, mean maximum temperature, mean temperature of the warmest month, stoniness of the soil, sand, silt, clay, pH, electrical conductivity, and available water capacity. Multiple regression accounted for 57.9% of variations in height growth. The models obtained can be used to determine the site index of potential areas in Turkey for maritime pine. It can be said that the productivity of maritime pine may decline in the future due to global climate change.

Keywords

Pinus pinaster / Afforestation / Ecology / Site index

Cite this article

Download citation ▾
Cezmi Özel, Şükrü Teoman Güner, Mehmet Türkkan, Selda Akgül, Özdemir Şentürk. Modelling the site index of Pinus pinaster plantations in Turkey using ecological variables. Journal of Forestry Research, 2020, 32(2): 589-598 DOI:10.1007/s11676-020-01113-x

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Aertsen W, Kınt V, Orshoven J, Özkan K, Muys B. Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests. Ecol Model, 2010, 221: 1119-1130.

[2]

Akgül S. Bio-climatic evaluations on the growth of maritime pine (Pinus pinaster Ait.) in Turkey, 2010, İzmit: Poplar and Fast Growing Forest Trees Research Institute Press 133 (in Turkish)

[3]

Akman Y. Climate and bioclimate, 1990, Ankara: Palme Press 350 (in Turkish)

[4]

Ali A, Yan ER. Functional identity of overstorey tree height and understorey conservative traits drive aboveground biomass in a subtropical forest. Ecol Indic, 2017, 83: 158-168.

[5]

Álvarez-González JG, Ruíz González AD, Rodríguez Soalleıro R, Barrıo Anta M. Ecoregional site index models for Pinus pinaster in Galicia (northwestern Spain). Ann For Sci, 2005, 62(2): 115-127.

[6]

Álvarez-Álvarez P, Khouri EA, Cámara-Obregón A, Castedo-Dorado F, Barrio-Anta M. Effects of foliar nutrients and environmental factors on site productivity in Pinus pinaster Ait. stands in Asturias (NW Spain). Ann For Sci, 2011, 68: 497-509.

[7]

Atalay İ. Ecoregions of Turkey, 2002, İzmir: Meta Press 266 (in Turkish)

[8]

Bartoń K (2016) MuMIn: multi-model ınference. R Package Version 1.15.6, p. Model Selection and Model Averaging Based on Information Criteria (AICc and alike)

[9]

Birler AS. industrial forest plantations, 2009, İstanbul: Düzce University Press 256 (in Turkish)

[10]

Brandl S, Falk W, Rötzer T, Pretzsch H. Assessing site productivity based on national forest inventory data and its dependence on site conditions for spruce dominated forests in Germany. For Syst, 2019 28 2 12

[11]

Bravo F, Montero G. Site index estimation in Scots pine (Pinus sylvestris L.) stands in the High Ebro Basin (northern Spain) using attributes. Forestry, 2001, 74(4): 395-406.

[12]

Bravo F, Lucà M, Mercurio R, Sidari M, Muscolo A. Soil and forest productivity: a case study from Stone pine (Pinus pinea L.) stands in Calabria (southern Italy). iForest, 2011, 4: 25-30.

[13]

Bravo-Oviedo A, Montero G. Site index in relation to edaphic variables in stone pine (Pinus pinea L.) stands in south west Spain. Ann For Sci, 2005, 62: 61-72.

[14]

Bravo-Oviedo A, Roig S, Bravo F, Montero G, Del-Rio M. Environmental variability and its relationship to site index in Mediterranean maritime pine. For Syst, 2011, 20(1): 50-64.

[15]

Bueis T, Bravo F, Pando V, Turrion MB. Relationship between environmental parameters and Pinus sylvestris L. site index in forest plantations in northern Spain acidic plateau. iForest, 2016, 9: 394-401.

[16]

Çepel N, Dündar M, Günel A. Relationship between edaphic and physiological attributes and growth of Scotch pine in important forest areas, 1977, Ankara: The Scientific and Technological Research Council of Turkey Press 165 (in Turkish)

[17]

Chen HYH, Krestov PV, Klinka K. Trembling aspen site index in relation to environmental measures of site quality at two spatial scales. Can J For Res, 2002, 32: 112-119.

[18]

Corona P, Scotti R, Tarchiani N. Relationship between environmental factors and site index in Douglas-fir plantations in central Italy. For Ecol Manag, 1998, 110: 195-207.

[19]

Diéguez-Aranda U, Álvarez González JG, Barrio Anta M, Rojo Alboreca A. Site quality equations for Pinus sylvestris L. plantations in Galicia (northwestern Spain). Ann For Sci, 2005, 62: 143-152.

[20]

Eckhart T, Pötzelsberger E, Koeck R, Thom D, Lair GJ, Loo MV, Hasenauer H. Forest stand productivity derived from site conditions: an assessment of old Douglas-fir stands (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) in Central Europe. Ann For Sci, 2019, 76: 19.

[21]

Eimil-Fraga C, Rodríguez-Soalleiro R, Sánchez-Rodríguez F, Pérez-Cruzado C, Álvarez-Rodríguez E. Significance of bedrock as a site factor determining nutritional status and growth of maritime pine. For Ecol Manag, 2014, 331: 19-24.

[22]

Eimil-Fraga C, Sánchez-Rodríguez F, Álvarez-Rodríguez E, Rodríguez-Soalleiro R. Relationships between needle traits, needle age and site and stand parameters in Pinus pinaster. Trees, 2015, 29(4): 1103-1113.

[23]

Ercanlı İ, Günlü A, Altun L, Başkent EZ. Relationship between site index of oriental spruce [Picea orientalis (L.) Link] and ecological variables in Maçka. Turkey Scand J For Res, 2008, 23: 319-329.

[24]

GDM (2016) Meteorological data. https://www.mgm.gov.tr/. Accessed 15 June 2019

[25]

GDMRE (2019) 1:500,000 Scale Geological Inventory Map Series of Turkey.

[26]

Gülsoy S, Çınar T. The relationships between environmental factors and site index of Anatolian black pine (Pinus nigra Arn. Subsp. pallasiana (Lamb.) Holmboe) stands in Demirci (Manisa) district, Turkey. Appl Ecol Env Res, 2019, 17(1): 1235-1246.

[27]

Gülsoy S, Suel H, Çelik H, Özdemir S, Özkan K. Modeling site productivity of Anatolian black pine stands in response to site factors in Buldan district, Turkey. Pak J Bot, 2014, 46(1): 213-220.

[28]

Güner ŞT, Yücel E. The relationships between growth of Pinus sylvestris ssp. hamata forests with ecological factors in Central Anatolia. Biol Div Conserv, 2015, 8(3): 6-19.

[29]

Güner ŞT, Çömez A, Özkan K, Karataş R, Çelik N. Modelling the productivity of Anatolian black pine plantations in Turkey. J Fac For Istanbul Univ, 2016, 66(1): 159-172. In Turkish)

[30]

Güner ŞT, Özel C, Türkkan M, Akgül S. Changes in carbon concentration of tree components for maritime pine plantations in Turkey. Turk J For Res, 2019, 6(2): 167-176.

[31]

Günlü A, Yılmaz M, Altun L, Ercanlı İ, Küçük M. Relationships between site index and some edaphic and physiographic factors of pure oriental spruce (Picea orientalis Link.) in Artvin Genya Mountain. Turk J For, 2006, 7(1): 1-10. (in Turkish)

[32]

Güvendi E (2005) The correlations among the height growth and some soil and land form features related to the maritime pine plantation stands in Sinop-Merkez. Master of Science Thesis, Karadeniz Technical University, Trabzon, p 92. https://www.mta.gov.tr/v3.0/hizmetler/500bas. Accessed 12 Mar 2019 (in Turkish)

[33]

IUSS Working Group WRB (2015) World reference base for soil resources 2014, update 2015. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO, Rome, p 192

[34]

Kahyaoğlu NÖ (2005) Correlations among the height growth and some ecological features related to the maritime pine plantation stands in Sinop-Bektasa. Master of Science Thesis, Karadeniz Technical University, Trabzon, p 83 (in Turkish)

[35]

Kandemir A, Mataracı T. Güner A, Kandemir A, Menemen Y, Yıldırım H, Aslan S, Ekşi G, Güner I, Çimen . Pinus L. Illustrated Flora of Turkey 2, 2018, İstanbul: Nezahat Gökyiğit Botanical Garden Press 324 354

[36]

Karataş R, Arslan M, Güner ŞT, Çömez A, Özkan K. Relationships between the growth of Quercus vulcanica and site properties in the Lakes District in Turkey, 2013, Eskişehir: Research Institute for Forest Soil and Ecology Press 67 (in Turkish)

[37]

Kroetsch D, Wang C. Carter MR, Gregorich EG. Particle size distribution, in section VI. Soil physical analysis, section Ed. By Angers D.A., Larney, F.J. Soil sampling and methods of analysis, 2008 2 Boca Raton: CRC Press 713 725

[38]

Moisen GG, Frescıno TS. Comparing five modelling techniques for predicting forest characteristics. Ecol Model, 2002, 157: 209-225.

[39]

Moreno-Fernández D, Álvarez-Gonzálezc JG, Rodríguez-Soalleirod R, Pasalodos-Tatoa M, Cañellasa I, Montesa F, Díaz-Varelae E, Sánchez-Gonzáleza M, Crecente-Campof F, Álvarez-Álvarezg P, Barrio-Antag M, Pérez-Cruzadoc C. National-scale assessment of forest site productivity in Spain. For Ecol Manag, 2018, 417: 197-207.

[40]

Özcan BG. Growth and Yield of (Pinus pinaster Ait.) Plantations, 2003, İzmit: Poplar and Fast Growing Forest Trees Research Institute Press 155 (in Turkish)

[41]

Özkan K, Gülsoy S, Mert A. Interrelations between height growth and site characteristics of Pinus nigra Arn. ssp. pallasiana (Lamb.) Holmboe. Malays For, 2008, 71: 9-16.

[42]

Özyuvacı N. Meteorology and climatology, 1999, Istanbul: Istanbul University Faculty of Forestry Press 369 (in Turkish)

[43]

Romanyà J, Vallejo VR. Productivity of Pinus radiata plantations in Spain in response to climate and soil. For Ecol Manag, 2004, 195: 177-189.

[44]

Saraçoğlu Ö. Two variable relationships between site index and site characteristics in the unevenaged fir stands of Blacksea Region. J Fac For Istanbul Univ, 1989, A39(2): 122-138. (in Turkish)

[45]

Seynave I, Gégout JC, Hervé JC, Dhôte JF, Drapier J, Bruno É, Dumé G. Picea abies site index prediction by environmental factors and understorey vegetation: a two-scale approach based on survey databases. Can J For Res, 2005, 35: 1669-1678.

[46]

Şimşek Y, Tulukçu M, Toplu F, Akkan A, Avcıoğlu E. Studies on the growth of fast growing exotic species introduced to Turkey, 1985, Ankara: Turkish Forest Research Institute Press 128 (in Turkish)

[47]

TS 8336 (1990) Soils-determination of organic matter. Turkish Standards Institution Press, Ankara, p 4 (in Turkish)

[48]

TS 8335 ISO 10693 (1996a) Soil quality-determination of carbonate content-volumetric method. Turkish Standards Institution Press, Ankara, p 8 (in Turkish)

[49]

TS ISO 11265 (1996b) Soil quality-determination of electrical conductivity. Turkish Standards Institution Press, Ankara (in Turkish)

[50]

TS ISO 10390 (2013) Soil quality-determination of pH. Turkish Standards Institution Press, Ankara, p 7 (in Turkish)

[51]

Team RDC (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

[52]

Yener İ, Altun L. Predicting site index for oriental spruce (Picea orientalis L. (Link)) using ecological factors in the eastern black sea, Turkey. Fresenius Environ Bull, 2018, 27(5): 3107-3116.

[53]

Yuan ZQ, Wang SP, Ali A, Gazol A, Ruiz-Benito P, Wang XG, Lin F, Ye J, Hao ZQ, Loreau M. Aboveground carbon storage is driven by functional trait composition and stand structural attributes rather than biodiversity in temperate mixed forests recovering from disturbances. Ann For Sci, 2018, 75: 67.

[54]

Yılmaz M (2005) Studies on Some Site Factors Affecting the Growth (productivity) of the Beech in Pure Oriental Beech (Fagus orientalis Lipsky) Ecosystems in East Karadeniz Region. PhD Dissertation, Karadeniz Technical University, Trabzon, p 188 (in Turkish)

AI Summary AI Mindmap
PDF

138

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/