| Yazarlar |
Prof. Dr. Fatih SİVRİKAYA
Türkiye |
Doç. Dr. Gonca Ece ÖZCAN
Kastamonu Üniversitesi, Türkiye |
Prof. Dr. Korhan ENEZ
Kastamonu Üniversitesi, Türkiye |
Doç. Dr. Oytun Emre SAKICI
Kastamonu Üniversitesi, Türkiye |
| Özet |
| The six-toothed bark beetle Ips sexdentatus is one of the most important pests of coniferous trees that can cause extensive tree mortality, and change the structure and composition of forest ecosystems. Many abiotic and biotic factors affect the infestation of bark beetles. Early detection of forest stands predisposed to bark beetle infestations will benefit from reducing the impacts of possible infestations. The study focused on the production and comparison of Ips sexdentatus susceptibility maps using the analytical hierarchy process (AHP), frequency ratio (FR), and logistical regression (LR) models. The research was carried out in the Crimean pine forests of the Taşköprü Forest Enterprise in Kastamonu City in the Western Black Sea region of Türkiye. The eight main criteria used to produce the map were the stand structure, site index, crown closure, stand age, slope, elevation, maximum temperature, and solar radiation. The map of the infested stands was used for the models' validation. Crown closure was determined as the one of the most important factors in all three models. The receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to determine the accuracy of the maps. The validation results showed that the AUC for the FR model was 0.747, for the AHP model was 0.716, and for the LR model was 0.638. The results revealed that the FR model was more accurate than the other models in producing an I. sexdentatus susceptibility map. Besides, the AHP model was also reasonably accurate. This study could help decision makers to produce bark beetle susceptibility maps easily and rapidly so they can take the necessary precautions to slow or prevent infestations. |
| Anahtar Kelimeler |
| Bark beetle infestation | Crimean pine | GIS | Ips sexdentatus | ROC curve | Susceptibility |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale |
| Dergi Adı | ECOLOGICAL INFORMATICS |
| Dergi ISSN | 1574-9541 |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | İngilizce |
| Basım Tarihi | 11-2022 |
| Cilt No | 71 |
| Sayı | 1 |
| Doi Numarası | 10.1016/j.ecoinf.2022.101811 |
| Makale Linki | https://www.sciencedirect.com/science/article/pii/S1574954122002618 |
| Atıf Sayıları | |
| WoS | 7 |
| SCOPUS | 6 |
| Google Scholar | 10 |
