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Ips sexdentatus’un Duyarlılığının Maksimum Entropi (MaxEnt) ile Modellenmesi

Year 2024, , 16 - 27, 23.04.2024
https://doi.org/10.24011/barofd.1387342

Abstract

İklim değişimi ve buna bağlı faktörlerden en çok etkilenen ormanlardır. İklim değişikliği, konukçu ağaçların ve bunlarla ilişkili olan zararlıların dağılımlarında değişikliğe neden olmaktadır. Ekoloji ve koruma alanındaki planlamacılara yol gösterecek uygulamalar için türlerin coğrafi dağılımlarını belirleyen tahmine dayalı modeller önemlidir. Orman ekosistemlerinde ciddi olumsuzluklara neden olan kabuk böceklerinin her yıl artarak devam eden zararlarının önemli sonuçlar meydana getireceği beklenmektedir. Bu nedenle orman ekosistemlerinde bulunan kabuk böceği türlerinin potansiyel dağılımlarının belirlenmesi sürdürülebilir orman yönetimi açısından oldukça önemlidir. Bu türlerin salgınlarını iklim, topoğrafik ve meşcere parametreleri önemli ölçüde etkilemektedir. Bu çalışmada, Maksimum Entropi (MaxEnt) yaklaşımı kullanılarak 19 farklı biyoiklimsel değişken ile kapalılık, yükselti ve eğim değişkenlerini dikkate alarak Ips sexdentatus’un zararına ilişkin potansiyel duyarlılık haritası oluşturulmuştur. Modelin doğruluğu alıcı çalışma karakteristiği (ROC) analizi ile değerlendirilmiş eğitim verilerinde eğri altında kalan alan (Area Under Curve, (AUC)) 0,846; test verilerinde ise 0,855 olarak hesaplanmıştır. Ips sexdentatus’un duyarlılık haritasında model sonucunu en çok etkileyen parametrenin kapalılık olduğu ve modelin %68.5’ini oluşturduğu belirlenmiştir. Bunun yanında kapalılık, eğim ve en nemli ayın yağış miktarı değişkenlerinin toplu olarak modelin %88.4’ünü oluşturduğu görülmüştür. Ayrıca, çalışma alanının % 51.6’sı Ips sexdentatus istilası açısından riskli kategoride yer almaktadır. Bu çalışmanın sonuçları Ips sexdentatus’un izlenmesi ve mücadele stratejilerinin belirlenmesine katkı sağlayacaktır. Aynı zamanda diğer salgın yapma potansiyeline sahip kabuk böceği türlerinin yönetimi için bir öngörü oluşturacaktır.

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Modeling the Susceptibility of Ips sexdentatus with Maximum Entropy (MaxEnt)

Year 2024, , 16 - 27, 23.04.2024
https://doi.org/10.24011/barofd.1387342

Abstract

Forests are most affected by climate change and related factors. Climate change causes changes in the distribution of host trees and their associated pests. Predictive models that determine the spatial distributions of species are important for applications that will guide planners in the field of ecology and conservation. It is predicted that the ever-increasing damage of bark beetles, which cause significant negativities in forest ecosystems, will have serious consequences. Therefore, determining the potential distributions of bark beetle species in forest ecosystems is important for sustainable forest management. Climate, topographic and stand parameters significantly affect the epidemics of these species. In this study, a potential susceptibility map for the damage of Ips sexdentatus was created using the Maximum Entropy (MaxEnt) approach, taking into account 19 different bioclimatic, crown closer, elevation, and slope variables. The accuracy of the model was evaluated by receiver operating characteristic (ROC) analysis. AUC was 0.846 in the training data, and it was calculated as 0.855 in the test data. In the susceptibility map of Ips sexdentatus, it was determined that the variable that most affected the model result was crown closure, which constituted 68.5% of the model. In addition, it was observed that the variables of crown closure, slope, and precipitation of the wettest month collectively included 88.4% of the model. In addition, 51.6% of the study area is in the risk category regarding I. sexdentatus invasion. The results of this study will contribute to monitoring Ips sexdentatus and determining control strategies. It will also provide insight for the management of other bark beetle species with epidemic potential.

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  • Buotte, P.C., Hicke, J.A., Preisler, H.K., Abatzoglou, j.T., Raffa, K.F., Logan, J.A. (2016). Climate influences on whitebark pine mortality from mountain pine beetle in the Greater Yellowstone Ecosystem. Ecological Applications, 26(8), 2507-2524. https://doi.org/10.1002/eap.1396
  • Choi, W.I., Park, Y S. (2019). Monitoring, assessment and management of forest insect pests and diseases. Forests, 10(10), 865. https://doi.org/10.3390/f10100865
  • Craig, E., Bland, R., Ndirangu, J., Reilly, J.J. (2014). Use of mid-upper arm circumference for determining overweight and overfatness in children and adolescents. Archives of disease in childhood, 99(8), 763-766. https://doi:10.1136/archdischild-2013-305137
  • Dale, V. H., Joyce, L.A., McNulty, S.M., Neilson, R.P., Ayres, M.P., Flannigan, M.D., Hanson, P.J., Irland, L.C., Lugo, A.E., Peterson, C.J., Simberloff, D., Swanson, F.J., Stocks, B.J., Wotton, B.M. 2001. Climate change and forest disturbances: climate change can affect forests by altering the frequency, intensity, duration, and timing of fire, drought, introduced species, insect and pathogen outbreaks, hurricanes, windstorms, ice storms, or landslides. BioScience, 51(9), 723-734. https://doi.org/10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
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  • Evangelista, P.H., Kumar, S., Stohlgren, T.J., Young, N.E. (2011). Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US. Forest Ecology and Management, 262(3), 307-316. https://doi.org/10.1016/j.foreco.2011.03.036
  • Fitzgibbon, A., Pisut, D., Fleisher, D. (2022). Evaluation of Maximum Entropy (Maxent) machine learning model to assess relationships between climate and corn suitability. Land, 11(9), 1382. https://doi.org/10.3390/land11091382
  • Gil, L., Pajares, J.A. (1986). Los escolıtidos de las conıferas en la Penınsula Ibérica. Monografıas INIA, (53), 194. González-Hernández, A., Morales-Villafaña, R., Romero-Sánchez, M.E., Islas-Trejo, B., Pérez-Miranda, R. (2020). Modelling potential distribution of a pine bark beetle in Mexican temperate forests using forecast data and spatial analysis tools. Journal of Forestry Research, 31(2), 649-659. https://doi.org/10.1007/s11676-018-0858-4
  • Hansen, B.B., Grøtan, V., Herfindal, I., Lee, A.M. (2020). The Moran effect revisited: spatial population synchrony under global warming. Ecography, 43(11), 1591-1602. https://doi.org/10.1111/ecog.04962 Jactel, H., Koricheva, J., Castagneyrol, B. (2019). Responses of forest insect pests to climate change: not so simple. Current Opinion in Insect Science, 35, 103-108. https://doi.org/10.1016/j.cois.2019.07.010
  • Jaime, L., Batllori, E., Margalef-Marrase, J., Navarro, M. Á. P., Lloret, F. (2019). Scots pine (Pinus sylvestris L.) mortality is explained by the climatic suitability of both host tree and bark beetle populations. Forest Ecology and Management, 448, 119-129. https://doi.org/10.1016/j.foreco.2019.05.070
  • Jeger, M., Bragard, C., Caffier, D., Candresse, T., Chatzivassiliou, E., Dehnen-Schmutz, K., Gilioli, G., Miret, J.A.J., MacLeod, A., Navarro, M.N., Niere, B., Parnell, S., Potting, R., Rafoss, T., Rossi, V., Urek, G., Van Bruggen, S., Werf, W.V., West, J., Winter, S., Kertész, V., Aukhojee, M., Grégoire, J.C. (2017). Pest categorisation of Ips sexdentatus. EFSA Journal, 15(11), 4999. https://doi.org/10.2903/j.efsa.2017.4999.
  • Jenkins, M.J., Hebertson, E.G., Munson, A.S. (2014). Spruce beetle biology, ecology and management in the Rocky Mountains: an addendum to spruce beetle in the Rockies. Forests, 5(1), 21-71. https://doi.org/10.3390/f5010021
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There are 54 citations in total.

Details

Primary Language Turkish
Subjects Zoology (Other)
Journal Section Research Articles
Authors

Gonca Ece Özcan 0000-0003-0141-1031

Early Pub Date March 29, 2024
Publication Date April 23, 2024
Submission Date November 7, 2023
Acceptance Date February 8, 2024
Published in Issue Year 2024

Cite

APA Özcan, G. E. (2024). Ips sexdentatus’un Duyarlılığının Maksimum Entropi (MaxEnt) ile Modellenmesi. Bartın Orman Fakültesi Dergisi, 26(2), 16-27. https://doi.org/10.24011/barofd.1387342


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