Browsing by Author "Sivrikaya F."

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An innovative tool for mapping forest fire risk and danger: case studies from eastern Mediterranean
(2023-01-01) Sağlam B.; Boyatan M.; Sivrikaya F.
Forest fires are one of the most important factors for forest ecosystem and cause ecosystem destruction such as decreasing forest area, biodiversity in the Mediterranean region. Türkiye located in Mediterranean region is exposed to hundreds of fires every year, which damage forest. Mapping forest fire risk and danger constitutes an important basis for preventing fire damages. Geographical Information System is used for mapping forest fire risk and making the accurate and fast decision. This study is designed to develop a GIS-based decision support systems (DSS) to produce a forest fire risk and danger map for Türkiye. DSS uses topography, stand structure and anthropogenic factors for mapping forest fire risk and danger. DSS was developed using the C-sharp (C#) programming language with the help of Add-in in the ArcGIS. DSS has been successfully tested on case study sites in Kozan and Milas Forest Enterprises in Türkiye. In conclusion, the DSS has contributed to the forest managers to fight forest fire effectively. This study will make an important contribution to both the General Directorate of Forestry, which is in the position of implementing it, and the scientific community.
Analysis of the Climate Signal in Subannual Width Measurements of Pinus nigra Tree Rings in Kastamonu Province, Turkey
(2023-08-03) Majeed M.; Stoica E.; Meko D.M.; Touchan R.; Sivrikaya F.; Alexandru A.M.; Arimon L.C.; Kvaratskhelia R.; Maglakelidze S.; Pacaldo J.M.; Deeksha
Comparative study of the analytical hierarchy process, frequency ratio, and logistic regression models for predicting the susceptibility to Ips sexdentatus in Crimean pine forests
(2022-11-01) Sivrikaya F.; Özcan G.E.; Enez K.; Sakici O.E.
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.
COMPARISON OF BIOMASS ESTIMATION APPROACHES BASED ON INVENTORY DATA: A CASE STUDY IN KAPIKAYA FOREST, TURKEY
(2022-05-01) Sivrikaya F.; Işik M.
The aim of this study is to evaluate different above-ground biomass (AGB) considering different estimation approaches and to investigate if there are significant differences between the AGB estimations of these approaches using analysis of variance. In this study, the capabilities of three approaches including Biomass Conversion and Expansion Factor (BCEF) method, Biomass Conversion and Expansion Factor based on Tree Species (BCEFTS) method and Allometric Equation (AE) method were evaluated in estimation of AGB using forest inventory data in Kapikaya Forest District (FD) located in the city of Kahramanmaras in Turkey. The AGB values estimated by three approaches were 587362.4 tons, 587679.0 tons and 834112.3 tons for the BCEF, BCEFTS, and AE approaches, respectively. According to result of the analysis of variance, there was a significant difference between the AGB estimations of three approaches. AGB estimation of the AE approach was statistically different from the estimations of BCEF and BCEFTS.
Determination of some factors leading to the infestation of Ips sexdentatus in crimean pine stands
(2022-09-01) Özcan G.E.; Sivrikaya F.; Sakici O.E.; Enez K.
Large infestations of bark beetles result in the death of many trees in large forest areas. Ecological-based modeling approaches that include the factors causing infestations are important for accurately predicting whether these infestations will occur, suggesting ways to avoid large infestations, and understanding sustainable forest management. In the present study, the effects of some stand characteristics and topographical and climatological factors on the of Ips sexdentatus infestation at pure and mixed Crimean pine stands were evaluated. Ten factors were considered as important for predicting the predisposition of a pine forest to infestation: stand structure, site index, crown closure, stand age, aspect, slope, elevation, maximum temperature, precipitation, and solar radiation. Ten conditioning layers were overlayed separately with a beetle infestation map using geographic information system (GIS) to investigate how the beetle damage changed according to these factors and how much damage it caused. Binary logistic regression analysis was used to determine how combinations of the 10 factors affected beetle infestations and which of the factors were most damaging. It was found that the stand structure, crown closure, site index, stand age, slope, elevation, maximum temperature, precipitation, and solar radiation were definite factors in I. sexdentatus infestation; the aspect was not found to be a strong factor. The crown closure was the most significant factor affecting I. sexdentatus infestation followed by maximum temperature, elevation, slope, precipitation, solar radiation, stand age, site index, and stand structure. The crown closure, stand structure, maximum temperature, solar radiation, and forest stand area variables were significantly included in the logistic regression model.
Investigation of some factors affecting habitat selection and nest size of Formica rufa
(2023-10-01) Yilmaz M.; Özcan G.E.; Sivrikaya F.; Enez K.
Investigation of some factors affecting habitat selection and nest size of Formica rufa
(2023-10-01) Yilmaz M.; Özcan G.E.; Sivrikaya F.; Enez K.
Modeling forest fire risk based on GIS-based analytical hierarchy process and statistical analysis in Mediterranean region
(2022-05-01) Sivrikaya F.; Küçük Ö.
This study proposed an integrated approach to generating a forest fire risk map. It used geographic information system–based multiple criteria decision analysis (GIS-MCDA) with the analytic hierarchy process (AHP) and a statistical index (SI). The research was carried out at the Mersin Regional Directorate of Forestry (RDF) in the eastern Mediterranean region of Turkey. Four main criteria, the forest structure, topography, environment, and climate, and 16 subcriteria were used to create the fire risk map. The weight of each criterion was determined using the AHP. The AHP model revealed that environmental factors are the most influential in igniting forest fires, followed by the forest structure. In order to evaluate the results, 990 historical forest fire ignition points were obtained from the Mersin RDF. According to the forest fire risk map, more than 85% of the ignition points were in areas classified as having an extreme or high risk for forest fires. The findings show that the study area is highly prone to forest fires. The relative operating characteristic curve and area under the curve were used to validate the accuracy of the fire risk map. This validation revealed a very high accuracy of 0.775 for the AHP model, indicating a high accuracy in forest fire risk mapping, and the map produced was consistent and reliable. The AHP model and its results will assist decision makers in taking necessary precautions to prevent forest fires and to minimize fire damage, particularly in the eastern Mediterranean region.