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Predicting post-fire tree mortality

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.

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.

Kaynakça

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  • 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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  • Güney, C.O., Sarı, A., Cekim, H.O., Küçüksille, E.U., Sentürk, Ö., Gülsoy, S., Özkan, K., 2022. An advanced approach for leaf flammability index estimation. International Journal of Wildland Fire, 31(3): 277-290. https://doi.org/ 10.1071/WF21022
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  • Higgins, S.I., Bond, W.J., Trollope, W.S., 2000. Fire, resprouting and variability: a recipe for grass–tree coexistence in savanna. Journal of Ecology, 88(2): 213-229.
  • Hood, S., 2007. Scorch height, http://www.firewords.net/ definitions/scorch_height.htm Accessed: 03.04.2024. Hood, S., Bentz, B., 2007. Predicting postfire Douglas-fir beetle attacks and tree mortality in the northern Rocky Mountains. Canadian Journal of Forest Research, 37(6): 1058-1069. https://doi.org/10.1139/X06-313
  • Hood, S., Bentz, B., Gibson, K., Ryan, K. DeNitto, G., 2007a. Assessing post-fire Douglas-fir mortality and Douglas-fir beetle attacks in the northern Rocky Mountains. USDA Forest Service, General Technical Report, RMRS-GTR-199
  • Hood, S., Lutes, D., 2017. Predicting post-fire tree mortality for 12 Western US conifers using the first order fire effects model (FOFEM). Fire Ecology, 13 (2): 66-84. https://doi.org/10.4996/fireecology.130290243
  • Hood, S.M., McHugh, C.W., Ryan, K.C., Reinhardt, E., Smith, S. L., 2007b. Evaluation of a post-fire tree mortality model for western USA conifers. International Journal of Wildland Fire, 16(6): 679-689.
  • Hood, S.M., Cluck, D.R., Smith, S.L., Ryan, K.C., 2008. Using bark char codes to predict post-fire cambium mortality. Fire Ecology, 4(1): 57-73. https://doi.org/10.4996/ fireecology.0401057
  • Hood, S.M., 2010. Mitigating old tree mortality in long-unburned, fire-dependent forests: a synthesis, USDA Forest Service, General Technical Report, RMRS-GTR-238.
  • Hood, S.M., Varner, J.M., van Mantgem, P., Cansler, C.A., 2018. Fire and tree death: understanding and improving modeling of fire-induced tree mortality. Environmental Research Letters, 13 (11): 1-10. https://doi.org/10.1088/1748-9326/aae934
  • Hood, S.M., Varner, J.M., 2019. Post-fire tree mortality. In: Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires (Ed: Manzello S.L.), Springer, Gaithersburg, USA pp. 1-10. https://doi.org/10.1007/978-3-319-51727-8_252-1
  • Hood, S.M., Ragenovich, I., Schaupp, W.C., 2020. Post-fire assessment of tree status and marking guidelines for conifers in Oregon and Washington. USDA Forest Service, Pacific Northwest Region. General Technical Report, R6-FHP-RO-2020-02..
  • Hull Sieg, C., McMillin, J.D., Fowler, J.F., Allen, K.K., Negron, J.F., Wadleigh, L.L., Anhold, J.A., Gibson, K.E., 2006. Best predictors for postfire mortality of ponderosa pine trees in the Intermountain West. Forest Science, 52(6): 718-728. https://doi.org/10.1093/forestscience/52.6.718
  • Keeley, J.E., 2009. Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18 (1): 116-126. https://doi.org/10.1071/ WF07049
  • Keyser, T.L., Smith, F.W., Lentile, L.B., Shepperd, W.D., 2006. Modeling postfire mortality of ponderosa pine following a mixed-severity wildfire in the Black Hills: the role of tree morphology and direct fire effects. Forest Science, 52 (5): 530-539. https://doi.org/10.1093/forestscience/52.5.530
  • Kobziar, L., Moghaddas, J., Stephens, S.L., 2006. Tree mortality patterns following prescribed fires in a mixed conifer forest. Canadian Journal of Forest Research, 36(12): 3222-3238. https://doi.org/10.1139/X06-183
  • Lambert, S., Stohlgren, T.J., 1988. Giant sequoia mortality in burned and unburned stands. Journal of Forestry, 86(2): 44-46.
  • Liang, S., Hurteau, M.D., Westerling, A.L., 2017. Potential decline in carbon carrying capacity under projected climate-wildfire interactions in the Sierra Nevada. Scientific Reports, 7 (1): 2420. https://doi.org/10.1038/s41598-017-02686-0
  • Lowell, E. C., 2010. Effects of fire, insect, and pathogen damage on wood quality of dead and dying western conifers, USDA Forest Service, General Technical Report, PNW-GTR-816.
  • Mantgem, P.V., Schwartz, M., 2004. An experimental demonstration of stem damage as a predictor of fire-caused mortality for ponderosa pine. Canadian Journal of Forest Research, 34(6): 1343-1347. https://doi.org/10.1139/x04-001
  • 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
  • Michaletz, S.T., 2018. Xylem dysfunction in fires: towards a hydraulic theory of plant responses to multiple disturbance stressors. New Phytologist, 217(4): 1391-1393.
  • Outcalt, K.W., Wade, D.D., 2004. Fuels management reduces tree mortality from wildfires in southeastern United States. Southern Journal of Applied Forestry, 28(1): 28-34. https://doi.org/10.1093/sjaf/28.1.28
  • 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.
  • Rigolot, E., 2004. Predicting postfire mortality of Pinus halepensis Mill. and Pinus pinea L. Plant Ecology, 171(1): 139-151. https://doi.org/10.1023/B:VEGE.0000029382.59284.71
  • Rodríguez-Trejo, D.A., Castro-Solis, U.B., Zepeda-Bautista, M., Carr, R.J., 2007. First year survival of Pinus hartwegii following prescribed burns at different intensities and different seasons in central Mexico. International Journal of Wildland Fire, 16(1): 54-62. https://doi.org/10.1071/WF05061
  • 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.
  • Ryan, K.C., 1982b. Techniques for assessing fire damage to trees. Fire, its Field Effects. Intermountain Fire Council, 19-21 October, Missoula, Montana, USA, pp. 1-11.
  • Ryan, K.C., Noste, N. V., 1985. Evaluating prescribed fires, in: JE Lotan et al.(tech. coor), Proceedings - Symposium and Workshop on Wilderness Fire, USDA Forest Service Intermountain Forest and Range Experiement Station, General Technical Report INT-182. Utah State University, 230-238.
  • Ryan, K.C., Reinhardt, E.D., 1988. Predicting postfire mortality of seven western conifers. Canadian Journal of Forest Research, 18(10): 1291-1297.
  • Ryan, K.C., Amman, G.D., 1996. Bark beetle activity and delayed tree mortality in the Greater Yellowstone Area following the 1988 fires. Proceedings of the Second Biennial Conference on the Greater Yellowstone Ecosystem. The Ecological Implications of Fire in the Greater Yellowstone, International Association of Wildland Fire, Fairland, Washington, USA, pp. 151–158.
  • Ryan, K.C., 2002. Dynamic interactions between forest structure and fire behavior in boreal ecosystems. Silva Fennica, 36(1): 13-39. https://doi.org/10.14214/sf.548
  • Ryan, K.C., Jones, A.T., Koerner, C.L., Lee, K.M., 2012. Wildland Fire in Ecosystems: Effects of Fire on Cultural Resources and Archaeology, Gen. Tech. Rep. RMRS-GTR-42-vol. 3. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. 224 p. https://doi.org/10.2737/RMRS-GTR-42
  • Satio, K., 2001. Flames. In: Forest Fires Behavior and Ecological Effects, (Ed: Johnson E.A., Miyanishi K.) Academic Press, San Diego, pp. 11-54.
  • Schwilk, D.W., Knapp, E.E., Ferrenberg, S.M., Keeley, J.E., Caprio, A.C., 2006. Tree mortality from fire and bark beetles following early and late season prescribed fires in a Sierra Nevada mixed-conifer forest. Forest Ecology and Management, 232(1): 36-45. https://doi.org/10.1016/j.foreco.2006.05.036
  • Shearman, T.M., Varner, J.M., Hood, S.M., Cansler, C.A., Hiers, J.K., 2019. Modelling post-fire tree mortality: Can random forest improve discrimination of imbalanced data?. Ecological Modelling, 414, 108855. https://doi.org/10.1016/j.ecolmodel. 2019.108855
  • Sidoroff, K., Kuuluvainen, T., Tanskanen, H., Vanha-Majamaa, I., 2007. Tree mortality after low-intensity prescribed fires in managed Pinus sylvestris stands in southern Finland. Scandinavian Journal of Forest Research, 22(1): 2-12. https://doi.org/10.1080/02827580500365935
  • Stephens, S.L., Finney, M.A., 2002. Prescribed fire mortality of Sierra Nevada mixed conifer tree species: effects of crown damage and forest floor combustion. Forest Ecology and Management, 162(2): 261-271. https://doi.org/10.1016/S0378-1127(01)00521-7
  • Thies, W.G., Westlind, D.J., Loewen, M., Brenner, G., 2006. Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA. International Journal of Wildland Fire, 15(1): 19-29. https://doi.org/10.1071/WF05025
  • Thompson, M.T.C., Koyama, A., Kavanagh, K.L., 2017. Wildfire effects on physiological properties in conifers of central Idaho forests, USA. Trees, 31(2): 545-555. https://doi.org/10.1007/s00468-016-1489-z
  • Valor, T., Casals, P., Altieri, S., González-Olabarria, J.R., Piqué, M., Battipaglia, G., 2018. Disentangling the effects of crown scorch and competition release on the physiological and growth response of Pinus halepensis Mill. using δ13C and δ18O isotopes. Forest Ecology and Management, 424: 276-287. https://doi.org/10.1016/j.foreco.2018.04.056
  • Van Mantgem, P., Schwartz, M., 2003. Bark heat resistance of small trees in Californian mixed conifer forests: testing some model assumptions. Forest Ecology and Management, 178(3): 341-352. https://doi.org/10.1016/S0378-1127(02)00554-6
  • Von Gadow, K., 2000. Evaluating risk in forest planning models. Silva Fennica, 34(2): 181-191. https://doi.org/10.14214/sf.639
  • Wagner, C.E.V., 1973. Height of crown scorch in forest fires. Canadian Journal of Forest Research, 3(3): 373-378.
  • Wallin, K.F., Kolb, T.E., Skov, K.R., Wagner, M.R., 2003. Effects of crown scorch on ponderosa pine resistance to bark beetles in northern Arizona. Environmental Entomology, 32(3): 652-661. https://doi.org/10.1603/0046-225X-32.3.652
  • Woolley, T., Shaw, D.C., Ganio, L.M., Fitzgerald, S., 2012. A review of logistic regression models used to predict post-fire tree mortality of western North American conifers. International Journal of Wildland Fire, 21(1): 1-35. https://doi.org/10.1071/WF09039
Toplam 91 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Orman Ekosistemleri, Orman Yetiştirme
Bölüm Derleme
Yazarlar

Coşkun Okan Güney 0000-0003-4664-8024

Aylin Güney 0000-0002-8955-2770

Erken Görünüm Tarihi 28 Haziran 2024
Yayımlanma Tarihi 28 Haziran 2024
Gönderilme Tarihi 21 Şubat 2024
Kabul Tarihi 5 Nisan 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 25 Sayı: 2

Kaynak Göster

APA Güney, 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
AMA Güney 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
Chicago Güney, 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.
EndNote Güney CO, Güney A (01 Haziran 2024) Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry 25 2 220–232.
IEEE C. 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.
ISNAD Güney, 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.
JAMA Güney CO, Güney A. Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry. 2024;25:220–232.
MLA Güney, 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.
Vancouver Güney CO, Güney A. Orman yangınları sonrasında ağaçların canlılık durumlarının tahmin edilmesi. Turkish Journal of Forestry. 2024;25(2):220-32.