Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi

Yıl 2024, Cilt: 25 Sayı: 2, 220 – 232, 28.06.2024

https://doi.org/10.18182/tjf.1441012

Öz

After a forest fire, a mosaic structure of areas burned to varying degrees is created. Predicting whether partially burned and potentially viable trees will die is crucial for post-fire timber production and silvicultural planning. A good understanding of the processes of fire occurence and fire damage to trees is essential for precise prediction of post-fire tree mortality. The degree of damage to different parts of the tree, morphological characteristics, fire behavior characteristics, and secondary mortality factors can be taken into account when making predictions and are usually modeled using logistic regression. These models provide mortality estimates at a certain level of accuracy and can be used for individual trees or stand level. The aim of this review is to provide guidelines for post-fire mortality modeling research. To this end, our review provides information on the mechanisms of post-fire tree mortality, variables and measurements used in mortality modeling, model construction and application, summarizes the literature for future studies, and discusses the strengths and weaknesses of the topic.

Anahtar Kelimeler

Fire ecology, Fire damage, Fire injury, Cambium damage, Logistic regression

Kaynakça

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Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi

Yıl 2024, Cilt: 25 Sayı: 2, 220 – 232, 28.06.2024

https://doi.org/10.18182/tjf.1441012

Öz

Bir orman yangınından sonra, farklı derecelerde yanmış alanlardan oluşan mozaik bir yapı meydana gelmektedir. Kısmen yanmış ve yaşama ihtimali olan ağaçların ölüp ölmeyeceğinin tahmin edilmesi, yangın sonrası odun üretimi ve silvikültürel planlamalar için önemlidir. Yangın sonrası ağaçların canlılık durumlarının doğru şekilde tahmin edilebilmesi ise yangının meydana gelme süreçlerinin ve sonrasında ağaçlara nasıl zarar verdiğinin iyi bilinmesine bağlıdır. Tahminler yapılırken ağacın farklı kısımlarındaki zarar derecesi, morfolojik özellikler, yangın davranışı özellikleri ve ikinci dereceden ölüm etkenleri dikkate alınabilir. Genellikle lojistik regresyon yöntemi kullanılarak modellenmektedir. Bu modeller belirli doğruluk düzeyinde canlılık durumu tahminleri sağlamaktadır ve bireysel ağaçlar için oluşturulabileceği gibi meşcere düzeyinde de değerlendirilebilir. Bu derlemenin amacı, yangın sonrası canlılık durumu modelleme çalışmaları için kılavuz nitelinde bilgiler sunmaktır. Bu amaçla, orman yangınları sonrasındaki ağaç ölüm mekanizmaları, canlılık durumu modellemelerinde kullanılan değişkenler ve ölçme yöntemleri, modellerin oluşturulması ve oluşturulan modellerin nasıl kullanılabileceği hakkında bilgiler verilmiş, bundan sonra yapılacak çalışmalar için literatür özetlenerek konunun iyi ve eksik yönleri tartışılmıştır.

Anahtar Kelimeler

Yangın ekolojisi, yangın hasarı, yangın zararı, kambiyum zararı, lojistik regresyon.

Kaynakça

  • Adams, H.D., Williams, A.P., Xu, C., Rauscher, S.A., Jiang, X., McDowell, N.G., 2013. Empirical and process-based approaches to climate-induced forest mortality models. Frontiers in Plant Science, 4: 438. https://doi.org/ 10.3389/fpls.2013.00438
  • Agee, J. K., 1993. Fire ecology of Pacific Northwest Forests. Island press, California, ABD.
  • Alexander, M.E., Cruz, M.G., Taylor, S.W., 2020. Crown scorch height. In: Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires (Ed: Manzello S.L.), Springer, Gaithersburg, USA, pp.197-201. https://doi.org/10.1007/978-3-319-51727-8_72-1
  • Anderegg, W.R., Hicke, J.A., Fisher, R.A., Allen, C.D., Aukema, J., Bentz, B., Hood, S., Lichstein, J.W., Macalady, A.K., McDowell, N., Pan, Y., Raffa, K., Sala, A., Shaw, J.D., Stephenson, N.L., Tague, C. Zeppel, M., 2015. Tree mortality from drought, insects, and their interactions in a changing climate. New Phytologist, 208 (3): 674-683. https://doi.org/10.1111/nph.13477
  • Andrews, P., Bevins, C., Seli, R., 2008. BehavePlus fire modelling system, version 4.0: user’s guide. USDA Forest Service, General Technical Report, RMRS-GTR-106WWW Revised.
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  • McDowell, N.G., Beerling, D.J., Breshears, D.D., Fisher, R.A., Raffa, K.F., Stitt, M., 2011. The interdependence of mechanisms underlying climate-driven vegetation mortality. Trends in Ecology & Evolution, 26(10): 523-532. https://doi.org/10.1016/j.tree.2011.06.003
  • McHugh, C.W., Kolb, T.E., 2003a. Ponderosa pine mortality following fire in northern Arizona. International Journal of Wildland Fire, 12 (1): 7-22.
  • McHugh, C.W., Kolb, T.E., 2003b. Corrigendum to: ponderosa pine mortality following fire in northern Arizona. International Journal of Wildland Fire, 12(2): 245-245. https://doi.org/10.1071/WF02054
  • McHugh, C.W., Kolb, T.E. Wilson, J.L., 2003. Bark beetle attacks on ponderosa pine following fire in northern Arizona. Environmental Entomology, 32(3): 510-522.
  • Michaletz, S., Johnson, E., 2008. A biophysical process model of tree mortality in surface fires. Canadian Journal of Forest Research, 38 (7): 2013-2029. https://doi.org/10.1139/X08-024
  • Michaletz, S.T., Johnson, E.A., 2006. A heat transfer model of crown scorch in forest fires. Canadian Journal of Forest Research, 36(11): 2839-2851. https://doi.org/10.1139/X06-158
  • Michaletz, S.T., Johnson, E.A., 2007. How forest fires kill trees: a review of the fundamental biophysical processes. Scandinavian Journal of Forest Research, 22(6): 500-515. https://doi.org/10.1080/02827580701803544
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  • Pausas, J.G., Keeley, J.E., 2017. Epicormic resprouting in fire-prone ecosystems. Trends in Plant Science, 22 (12): 1008-1015. https://doi.org/10.1016/j.tplants.2017.08.010
  • Peterson, D.L., 1985. Crown scorch volume and scorch height: estimates of postfire tree condition. Canadian Journal of Forest Research, 15(3): 596-598.
  • Peterson, D.L., Ryan, K.C., 1986. Modeling postfire conifer mortality for long-range planning. Environmental Management, 10(6): 797-808.
  • Peterson, D.L., Arbaugh, M.J., 1989. Estimating postfire survival of Douglas-fir in the Cascade Range. Canadian Journal of Forest Research, 19(4): 530-533.
  • Pounden, E., Greene, D.F., Michaletz, S.T., 2014. Non‐serotinous woody plants behave as aerial seed bank species when a late‐summer wildfire coincides with a mast year. Ecology and Evolution, 4 (19): 3830-3840. https://doi.org/10.1002/ece3.1247
  • Quevedo, L., Rodrigo, A., Espelta, J.M., 2007. Post-fire resprouting ability of 15 non-dominant shrub and tree species in Mediterranean areas of NE Spain. Annals of Forest Science, 64 (8): 883-890. https://doi.org/10.1051/forest:2007053
  • Raymond, C.L., Peterson, D.L., 2005. Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA. Canadian Journal of Forest Research, 35(12): 2981-2995. https://doi.org/10.1139/X05-206
  • Reed, C.C., Hood, S.M., 2024. Nonstructural carbohydrates explain post-fire tree mortality and recovery patterns. Tree Physiol, 44(2). https://doi.org/10.1093/treephys/tpad155
  • Regelbrugge, J.C., Conard, S.G., 1993. Modeling tree mortality following wildfire in Pinus ponderosa forests in the central Sierra-Nevada of California. International Journal of Wildland Fire, 3(3): 139-148.
  • Reinhardt, E.D., Keane, R.E., Brown, J.K., 1997. First order fire effects model: FOFEM 4.0 user's guide. USDA Forest Service, General Technical Report, PB-97-133011/XAB; FSGTR/INT-344.
  • Reinhardt, E.D., Crookston, N.L., 2003. The fire and fuels extension to the forest vegetation simulator. USDA Forest Service, General Technical Report, RMRS-GTR-116.
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  • Ryan, K.C., 1982a. Evaluating potential tree mortality from prescribed burning, Site preparation and fuels management on steep terrain: proceedings of a symposium, Washington State University, Spokane, 15-17 February, Washington, pp. 15-17.
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Toplam 91 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Orman Ekosistemleri, Orman Yetiştirme
BölümDerleme
Yazarlar

Coşkun Okan Güney EGE ORMANCILIK ARAŞTIRMA ENSTİTÜSÜ MÜDÜRLÜĞÜ, ORMAN YANGINLARI ARAŞTIRMALARI BAŞMÜHENDİSLİĞİ 0000-0003-4664-8024 Türkiye

Aylin Güney İZMİR KATİP ÇELEBİ ÜNİVERSİTESİ 0000-0002-8955-2770 Türkiye

Erken Görünüm Tarihi28 Haziran 2024
Yayımlanma Tarihi28 Haziran 2024
Gönderilme Tarihi21 Şubat 2024
Kabul Tarihi5 Nisan 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 25 Sayı: 2

Kaynak Göster

APAGüney, C. O., & Güney, A. (2024). Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry, 25(2), 220-232. https://doi.org/10.18182/tjf.1441012
AMAGüney CO, Güney A. Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry. Haziran 2024;25(2):220-232. doi:10.18182/tjf.1441012
ChicagoGüney, Coşkun Okan, ve Aylin Güney. “Orman yangınları sonrasında ağaçların canlılık durumlarının Tahmin Edilmesi”. Turkish Journal of Forestry 25, sy. 2 (Haziran 2024): 220-32. https://doi.org/10.18182/tjf.1441012.
EndNoteGüney CO, Güney A (01 Haziran 2024) Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry 25 2 220–232.
IEEEC. O. Güney ve A. Güney, “Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi”, Turkish Journal of Forestry, c. 25, sy. 2, ss. 220–232, 2024, doi: 10.18182/tjf.1441012.
ISNADGüney, Coşkun Okan – Güney, Aylin. “Orman yangınları sonrasında ağaçların canlılık durumlarının Tahmin Edilmesi”. Turkish Journal of Forestry 25/2 (Haziran 2024), 220-232. https://doi.org/10.18182/tjf.1441012.
JAMAGüney CO, Güney A. Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry. 2024;25:220–232.
MLAGüney, Coşkun Okan ve Aylin Güney. “Orman yangınları sonrasında ağaçların canlılık durumlarının Tahmin Edilmesi”. Turkish Journal of Forestry, c. 25, sy. 2, 2024, ss. 220-32, doi:10.18182/tjf.1441012.
VancouverGüney CO, Güney A. Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry. 2024;25(2):220-32.

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