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Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği

Year 2019, Volume: 20 Issue: 2, 218 - 223, 15.09.2019

Ercan Oktan

https://doi.org/10.17474/artvinofd.535526

Abstract

Yaprak alan indeksi (YAİ), orman ekosistemlerinin temel yapısal
karakterlerinin ortaya konmasında önemli faktörlerin başında gelmektedir. Çünkü
YAİ meşcerenin tepe çatısında oluşan birçok biyolojik ve fiziksel sürecin
değişimini ortaya koyabilmektedir. Bu bağlamda, YAİ değerlerinin belirlenmesi
ormancılık açısından önem taşımaktadır. YAİ’nin hesaplanmasında doğrudan ve
dolaylı birçok yöntem kullanılmaktadır. Bu çalışmada doğrudan belirlenme
yöntemi kullanılmıştır. Bunun için farklı bakılarda, aynı yükseklik, aynı eğim
ve yaklaşık aynı kapalılıkta (0,9-1,0) meşcerelerden toplam 45 adet ağaçtan
alınan 180 sürgünde ölçümler yapılmıştır. Buna göre kuzey ve güney olarak
farklı bakılardan alınan ağaçlarda yapılan YAİ değerleri farklı (güney
bakılardaki ağaçlarda  (σ =
0,971) ve kuzey bakılardaki ağaçlarda  (σ = 0,93))
bulunmuştur. YAİ değerleri kuzey bakıdan alınan örneklerde daha yüksek
çıkmıştır. Bu sonuca göre, silvikültürel müdahalelerin yapılacağı meşcerelerden
aynı meşcere yapısında olsa dahi farklı şiddette uygulamaların yapılması
gerektiği önerilmiştir. 

Keywords

Abies cilicica Yaprak Alan İndeksi Silvikültür Kapalılık Verimlilik

References

  • Asner, G.P., Scurlock, J.M.O., Hicke, J.A. (2003). Global synthesis of leaf area index observations: implications for ecological and remote sensing studies. Global Ecol. Biogeogr., 12;191–205.
  • Bagnaresi, U., Giannini, R., Grassi, G., Minotta, G., Paffetti, D., Pini Prato, E. ve Proietti Placidi, A.M., 2002. Stand Structure and Biodiversity in Mixed, Uneven-aged Coniferous Forests in the Eastern Alps, Forestry, 75, 356-364.
  • Baizyldayeva, U.B., Uskenbayeva, R.K., Amanzholova, S.T. (2013), Decision Making Procedure: Applications of IBM SPSS Cluster Analysis and Decision Tree. World Applied Sciences Journal 21 (8), pp. 1207-1212.
  • Behera, S.K., Behera, M.D., Tuli, R. (2015). An indirect method of estimating leaf area index in a tropical deciduous forest of India. Ecological Indicators 58, pp. 356–364.
  • Bonan, G.B. (1993). Importance of leaf area index and forest type when estimating photosynthesis in Boreal forest. Remote Sensing of Environment. 43, pp. 303-314.
  • Bréda, N.J.J. (2003).Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. Journal of Experimental Botany, Vol. 54, No. 392, pp. 2403-2417.
  • Chen, J.M., Black, T.A. (1992). Foliage area and architecture of plant canopies from sunfleck size distributions. Agricultural and Forest Meteorology, 60, pp. 249-266.
  • Chianucci, F., Cutini,A., Corona, P., Puletti, N. () .Estimation of leaf area index in understory deciduous trees using digital photography. Agricultural and Forest Meteorology 198–199, pp. 259–264.
  • Clark, D.B., Olivas, P.C., Oberbauer, S.F., Clark, D.A., Ryan, M.G. (2008). First direct landscape‐scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity. Ecology Letters, 11, pp. 163–172.
  • Fang. H., Li, W., Wei, S., Jiang, C. (2014). Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods. Agricultural and Forest Meteorology 198–199, pp. 126–141.
  • Gower, S.T., Kucharik, C.J., Norman, J.M. (1999). Direct and indirect estimation of leaf area index, fAPAR and net primary production of terrestrial ecosystems. Remote Sens. Environ., 70;29–51.
  • Hall, R.J., Davidson, D.P., Peddle, D.R. (2003). Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta. Can. J. Remote Sensing, Vol. 29, No. 3, pp. 411–427, 2003.
  • Jonckheere, I., Fleck, S., Nackaerts, K., Muysa, B., Coppin, P., Weiss, M., Baret, F. (2004). Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology 121: 19–35.
  • Jose, S., Gillespie, A.R. (1997). Leaf area-productivity relationships natural disturbances. Among mixed-species hardwood forest communities of the central hardwood region. Forest Science. 43(1), pp. 56-64.
  • Kara, Ö., Şentürk, M., Bolat, İ., Çakıroğlu, K. (2011). Kayın, Göknar ve Göknar-Kayın Meşcerelerinde Yaprak Alan İndeksi ile Toprak Özellikleri Arasındaki İlişkiler. Journal of the Faculty of Forestry, Istanbul University, 61 (1), pp. 47-54.
  • Kucharik, C.J., Norman, J.M., Gower, S.T. (1998). Measurements of branch area and adjusting leaf area index indirect measurements. Agricultural and Forest Meteorology 91: 69-88.
  • Law, B.E., Van Tuyl, S., Cescatti, A., Baldocchi, D.D. (2001).Estimation of leaf area index in open-canopy ponderosa pine forests at different successional stages and management regimes in Oregon. Agricultural and Forest Meteorology 108, pp. 1–14.
  • Liu, Z., Jin, G., Qi, Y. (2012). Estimate of leaf area index in an old-growth mixed broadleaved-Korean pine forest in northeastern China. PLoS ONE 7(3): e32155. doi:10.1371/journal.pone.0032155.
  • Magurran, A.E., 1988. Ecological Diversity and Its Measurement, Princeton University Press, 179, Princeton, New Jersey.
  • Magurran, A.E., 2004. Measuring Biological Diversity, Blackwell Publishing Company, Madlen, USA.
  • Marshall, J.D., Waring, R.H. (1986). Comparison of methods of estimating leaf-area indexin old-growth Douglas-fir. Ecology, 67(4), pp. 975-979.
  • Mason, E.G., Diepstratenb, M., Pinjuvc, G.L., Lasserred, J.P. (2012).Comparison of direct and indirect leaf area index measurements of Pinus radiata D. Don. Agricultural and Forest Meteorology 166– 167, pp. 113– 119.
  • McAllister, D.M., (2005). Remote Estimation of Leaf Area Index in Forested Ecosystems. University of Calgary, Department of Geomatics Engineering, Master Thesis, 244p.
  • Nagler, P.L., Glenn, E.P., Thompson, T.L., Huete, A. (2004). Leaf area index and normalized difference vegetation index as predictors of canopy characteristics and light interception by riparian species on the Lower Colorado River. Agricultural and Forest Meteorology 125, pp. 1–17.
  • Neves, F.S., Sperber, C.F., Campos, R.I., Soares, J.P., Ribeiro, S.P. (2013). Contrasting effects of sampling scale on insect herbivores distribution in response to canopy structure. Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 61 (1): 125-137.
  • Peper, P.J., McPherson, E.G. (1998). Comparison of five methods for estimating leaf area index of open-grown deciduous trees. Journal of Arboriculture. 24(2):98-111.
  • Price, J.C., Bausch, W.C. (1995). Leaf Area Index Estimation from Visible and Near-Infrared Reflectance Data. Remote Sens. Environ. 52, pp. 55-65.
  • Sampson, D.A., Allen, H.L. (1995). Direct and indirect estimates of Leaf Area Index (LAI) for lodgepole and loblolly pine stands. Trees 9, pp. 119-122.
  • Song, Y.Y., Lu, Y., (2015).Decision tree methods: applications for classification and prediction, Shanghai Arch Psychiatry. Apr 25; 27(2), pp. 130–135.
  • Sumida, A., Nakai, T., Yamada, M., Ono, K., Uemura, S., Hara, T. (2009). Ground-based estimation of leaf area index and vertical distribution of leaf area density in a Betula ermanii forest. Silva Fennica 43(5), pp. 799–816.
  • Turner, D.P., Acker, S.A., Means, J.E., Garman, S.L. (2000). Assessing alternative allometric algorithms for estimating leaf area of Douglas-fir trees and stands. Forest Ecology and Management 126, pp. 61-76.
  • Yang,W., Tan,B., Huang, D., Rautiainen, M., Shabanov, N.V., Wang, Y., Privette, J.L., Huemmrich, K.F., Fensholt, R., Sandholt, I., Weiss, M., Ahl, D.E., Gower, S.T., Nemani, R.R., Knyazikhin, Y., Myneni, R.B. (2006). MODIS Leaf Area Index Products: From Validation to Algorithm Improvement. Ieee Transactıons on Geoscıence and Remote Sensıng, vol. 44, no. 7, pp. 1885-1899.
  • Van Pelt, R., Sillett, S.C., Kruse, W.A., Freund, J.A., Kramer, R.D. (2016). Emergent crowns and light-use complementarity lead to global maximum biomass and leaf area in Sequoia sempervirens forests. Forest Ecology and Management 375, pp. 279–308.
  • Waring, R.H. (1983). Estimating forest growth and efficiency in relation to canopy leaf area. Advanced Ecology Research. 13, pp. 327-354.
  • Watson DJ. (1947). Comparative physiological studies in the growth of field crops. I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Annals of Botany 11, 41-76.

Determination of Leaf Area Index in Taurus Fir (Abies cilicica Car.): Case Study of Adana-Kozan

Year 2019, Volume: 20 Issue: 2, 218 - 223, 15.09.2019

Ercan Oktan

https://doi.org/10.17474/artvinofd.535526

Abstract

Leaf area index is one of the most important factors
in presenting the basic structural characteristics of forest ecosystems.
Because, leaf area index can reveal the change of many biological and physical
processes in the canopy. So, determination of the leaf area index is very
important in forestry. In calculation of the leaf area index many direct and
indirect methods are used. In this study direct method was used in calculation.
For this purpose, measurements were made in 180 shoots taken from a total of 45
trees from different stands at the same altitude, aspect and have the same
slope gradient and approximately same canopy closure (0.9-1.0). Obtained
results showed that leaf area index was higher in the samples taken from North
aspect ( (σ = 0,93))  then South (  (σ = 0,971)). Obtained results indicated that
silvicultural treatments at different intensity should be carried out even if
the stands were in the same stand structure.

Keywords

Abies cilicica Leaf Area Index Silviculture Canopy closure Productivity

References

  • Asner, G.P., Scurlock, J.M.O., Hicke, J.A. (2003). Global synthesis of leaf area index observations: implications for ecological and remote sensing studies. Global Ecol. Biogeogr., 12;191–205.
  • Bagnaresi, U., Giannini, R., Grassi, G., Minotta, G., Paffetti, D., Pini Prato, E. ve Proietti Placidi, A.M., 2002. Stand Structure and Biodiversity in Mixed, Uneven-aged Coniferous Forests in the Eastern Alps, Forestry, 75, 356-364.
  • Baizyldayeva, U.B., Uskenbayeva, R.K., Amanzholova, S.T. (2013), Decision Making Procedure: Applications of IBM SPSS Cluster Analysis and Decision Tree. World Applied Sciences Journal 21 (8), pp. 1207-1212.
  • Behera, S.K., Behera, M.D., Tuli, R. (2015). An indirect method of estimating leaf area index in a tropical deciduous forest of India. Ecological Indicators 58, pp. 356–364.
  • Bonan, G.B. (1993). Importance of leaf area index and forest type when estimating photosynthesis in Boreal forest. Remote Sensing of Environment. 43, pp. 303-314.
  • Bréda, N.J.J. (2003).Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. Journal of Experimental Botany, Vol. 54, No. 392, pp. 2403-2417.
  • Chen, J.M., Black, T.A. (1992). Foliage area and architecture of plant canopies from sunfleck size distributions. Agricultural and Forest Meteorology, 60, pp. 249-266.
  • Chianucci, F., Cutini,A., Corona, P., Puletti, N. () .Estimation of leaf area index in understory deciduous trees using digital photography. Agricultural and Forest Meteorology 198–199, pp. 259–264.
  • Clark, D.B., Olivas, P.C., Oberbauer, S.F., Clark, D.A., Ryan, M.G. (2008). First direct landscape‐scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity. Ecology Letters, 11, pp. 163–172.
  • Fang. H., Li, W., Wei, S., Jiang, C. (2014). Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods. Agricultural and Forest Meteorology 198–199, pp. 126–141.
  • Gower, S.T., Kucharik, C.J., Norman, J.M. (1999). Direct and indirect estimation of leaf area index, fAPAR and net primary production of terrestrial ecosystems. Remote Sens. Environ., 70;29–51.
  • Hall, R.J., Davidson, D.P., Peddle, D.R. (2003). Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta. Can. J. Remote Sensing, Vol. 29, No. 3, pp. 411–427, 2003.
  • Jonckheere, I., Fleck, S., Nackaerts, K., Muysa, B., Coppin, P., Weiss, M., Baret, F. (2004). Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology 121: 19–35.
  • Jose, S., Gillespie, A.R. (1997). Leaf area-productivity relationships natural disturbances. Among mixed-species hardwood forest communities of the central hardwood region. Forest Science. 43(1), pp. 56-64.
  • Kara, Ö., Şentürk, M., Bolat, İ., Çakıroğlu, K. (2011). Kayın, Göknar ve Göknar-Kayın Meşcerelerinde Yaprak Alan İndeksi ile Toprak Özellikleri Arasındaki İlişkiler. Journal of the Faculty of Forestry, Istanbul University, 61 (1), pp. 47-54.
  • Kucharik, C.J., Norman, J.M., Gower, S.T. (1998). Measurements of branch area and adjusting leaf area index indirect measurements. Agricultural and Forest Meteorology 91: 69-88.
  • Law, B.E., Van Tuyl, S., Cescatti, A., Baldocchi, D.D. (2001).Estimation of leaf area index in open-canopy ponderosa pine forests at different successional stages and management regimes in Oregon. Agricultural and Forest Meteorology 108, pp. 1–14.
  • Liu, Z., Jin, G., Qi, Y. (2012). Estimate of leaf area index in an old-growth mixed broadleaved-Korean pine forest in northeastern China. PLoS ONE 7(3): e32155. doi:10.1371/journal.pone.0032155.
  • Magurran, A.E., 1988. Ecological Diversity and Its Measurement, Princeton University Press, 179, Princeton, New Jersey.
  • Magurran, A.E., 2004. Measuring Biological Diversity, Blackwell Publishing Company, Madlen, USA.
  • Marshall, J.D., Waring, R.H. (1986). Comparison of methods of estimating leaf-area indexin old-growth Douglas-fir. Ecology, 67(4), pp. 975-979.
  • Mason, E.G., Diepstratenb, M., Pinjuvc, G.L., Lasserred, J.P. (2012).Comparison of direct and indirect leaf area index measurements of Pinus radiata D. Don. Agricultural and Forest Meteorology 166– 167, pp. 113– 119.
  • McAllister, D.M., (2005). Remote Estimation of Leaf Area Index in Forested Ecosystems. University of Calgary, Department of Geomatics Engineering, Master Thesis, 244p.
  • Nagler, P.L., Glenn, E.P., Thompson, T.L., Huete, A. (2004). Leaf area index and normalized difference vegetation index as predictors of canopy characteristics and light interception by riparian species on the Lower Colorado River. Agricultural and Forest Meteorology 125, pp. 1–17.
  • Neves, F.S., Sperber, C.F., Campos, R.I., Soares, J.P., Ribeiro, S.P. (2013). Contrasting effects of sampling scale on insect herbivores distribution in response to canopy structure. Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 61 (1): 125-137.
  • Peper, P.J., McPherson, E.G. (1998). Comparison of five methods for estimating leaf area index of open-grown deciduous trees. Journal of Arboriculture. 24(2):98-111.
  • Price, J.C., Bausch, W.C. (1995). Leaf Area Index Estimation from Visible and Near-Infrared Reflectance Data. Remote Sens. Environ. 52, pp. 55-65.
  • Sampson, D.A., Allen, H.L. (1995). Direct and indirect estimates of Leaf Area Index (LAI) for lodgepole and loblolly pine stands. Trees 9, pp. 119-122.
  • Song, Y.Y., Lu, Y., (2015).Decision tree methods: applications for classification and prediction, Shanghai Arch Psychiatry. Apr 25; 27(2), pp. 130–135.
  • Sumida, A., Nakai, T., Yamada, M., Ono, K., Uemura, S., Hara, T. (2009). Ground-based estimation of leaf area index and vertical distribution of leaf area density in a Betula ermanii forest. Silva Fennica 43(5), pp. 799–816.
  • Turner, D.P., Acker, S.A., Means, J.E., Garman, S.L. (2000). Assessing alternative allometric algorithms for estimating leaf area of Douglas-fir trees and stands. Forest Ecology and Management 126, pp. 61-76.
  • Yang,W., Tan,B., Huang, D., Rautiainen, M., Shabanov, N.V., Wang, Y., Privette, J.L., Huemmrich, K.F., Fensholt, R., Sandholt, I., Weiss, M., Ahl, D.E., Gower, S.T., Nemani, R.R., Knyazikhin, Y., Myneni, R.B. (2006). MODIS Leaf Area Index Products: From Validation to Algorithm Improvement. Ieee Transactıons on Geoscıence and Remote Sensıng, vol. 44, no. 7, pp. 1885-1899.
  • Van Pelt, R., Sillett, S.C., Kruse, W.A., Freund, J.A., Kramer, R.D. (2016). Emergent crowns and light-use complementarity lead to global maximum biomass and leaf area in Sequoia sempervirens forests. Forest Ecology and Management 375, pp. 279–308.
  • Waring, R.H. (1983). Estimating forest growth and efficiency in relation to canopy leaf area. Advanced Ecology Research. 13, pp. 327-354.
  • Watson DJ. (1947). Comparative physiological studies in the growth of field crops. I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Annals of Botany 11, 41-76.
There are 35 citations in total.

Details

Primary Language Turkish
Subjects Forest Industry Engineering
Journal Section Research Article
Authors

Ercan Oktan 0000-0001-6136-8392

Publication Date September 15, 2019
Acceptance Date October 24, 2019
Published in Issue Year 2019 Volume: 20 Issue: 2

Cite

APA Oktan, E. (2019). Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, 20(2), 218-223. https://doi.org/10.17474/artvinofd.535526
AMA Oktan E. Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği. ACUJFF. September 2019;20(2):218-223. doi:10.17474/artvinofd.535526
Chicago Oktan, Ercan. “Toros Göknarı (Abies Cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 20, no. 2 (September 2019): 218-23. https://doi.org/10.17474/artvinofd.535526.
EndNote Oktan E (September 1, 2019) Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 20 2 218–223.
IEEE E. Oktan, “Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği”, ACUJFF, vol. 20, no. 2, pp. 218–223, 2019, doi: 10.17474/artvinofd.535526.
ISNAD Oktan, Ercan. “Toros Göknarı (Abies Cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 20/2 (September 2019), 218-223. https://doi.org/10.17474/artvinofd.535526.
JAMA Oktan E. Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği. ACUJFF. 2019;20:218–223.
MLA Oktan, Ercan. “Toros Göknarı (Abies Cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, vol. 20, no. 2, 2019, pp. 218-23, doi:10.17474/artvinofd.535526.
Vancouver Oktan E. Toros Göknarı (Abies cilicica Car.)’nda Yaprak Alan İndeksinin Belirlenmesi: Adana Kozan Yöresi Örneği. ACUJFF. 2019;20(2):218-23.
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