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    Determining indicator plant species of Pinus brutia Ten. Site index classes using interspecific correlation analysis in Antalya (Turkey)
    (Univ Federal Lavras-Ufla, 2023) Ozdemir, Serkan; Cinar, Tunahan
    Background: We performed a vegetation study in Antalya, where the Mediterranean climate prevails, in order to determine the indicator plant species of red pine (Pinus brutia Ten.). Red pine can be widely distributed from sea level to 1200 meters. Its main distribution is in the main Mediterranean vegetation zone between 500-1000 meters. However, the variation of the habitat factors may be low in this range. Therefore, the productivity relationships of species such as red pine, whose sustainable use is important, cannot be directly explained by environmental variables. In such cases, it is important to determine the indicator plant species. For this reason, indicator plant species of red pine productivity (site index class I) were determined by using interspecific correlation analysis (ICA) in the study. Then, using principal components analysis, the relationship of indicator plant species with the variables of elevation, slope, aspect and soil depth was revealed. In the principal components analysis, the plant species that were determined as an indicator were also added to the graph as a class variable, and the effects of the variables on the indicator plant species were also investigated.Results: The results of the ICA showed that Dryopteris flix-mas (L.) Schott, Abies cilicica (Antoine & Kotschy) Carriere, Cedrus libani A. RICH and Colutea cilicica Boiss. & Bal. species were negative indicators of red pine productivity. On the other hand, Cistus creticus L. and Smilax aspera L. species were positive indicators of productivityConclusions: Interspecific correlation analysis is a useful tool to determine the ecological properties of species that have a local distribution or a vertical distribution in a narrow altitude range. It also offers practical and effective results, especially for species with high commercial value such as red pine.
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    Identifying Areas Prone to Windthrow Damage and Generating Susceptibility Maps Utilizing a Novel Vegetation Index Extracted from Sentinel-2A Imagery
    (Springer, 2023) Cinar, Tunahan; Ozdemir, Serkan; Aydin, Abdurrahim
    Forests can be significantly affected by windthrow damage, which negatively impacts the process of forest utilization. Therefore, it is important to identify areas with potential windthrow damage and include them in the planning processes. Based on this idea, a windthrow susceptibility map was created using windthrow data obtained from the extraordinary yield reports of Turkiye-Zonguldak Forest Regional Directorate (FRD) for the years 2017-2022. Firstly, Sentinel-2A satellite images from one week before (pre-windthrow) and one week after (post-windthrow) the occurrence dates of each of the 325 windthrow events were acquired. Subsequently, a cloud mask was applied using the Python programming language in Google Earth Engine (GEE), and the Normalized Difference Fraction Index (NDFI) was calculated. Each identified damage area was saved as a polygon vector data format, and within each polygon, a point was assigned for every 100 m2, resulting in a total of 929 windthrow areas. Data related to wind speed, slope, precipitation, elevation, and distance-to-road variables were obtained for each point. Then, the component values of the axis with the highest variance explanation ratio were modeled using the Random Forest (RF) method. Ultimately, the predictive values of the model were extrapolated to the study area to generate the susceptibility windthrow map. The predictive map revealed that the southern parts of the study area had relatively higher windthrow potential. In this study, for the first time, the detection of windthrow areas was performed using NDFI, and the coefficients of environmental parameters were determined to generate a susceptibility mapping.
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    Optimization of Production Parameters of Densified Laminated Veneer Lumber Produced by Using Urea-Formaldehyde Resin
    (Zagreb Univ, Fac Forestry, 2023) Onat, Saadettin Murat; Ozdemir, Serkan
    This research aims to optimize densified laminated veneer lumber production parameters of compression ratio, press temperature, press time, and adhesive spread rate to maximize their mechanical properties. In the manufacturing process of densified laminated veneer lumber, I-77/51 American poplar clone (Populus deltoides) veneers and urea formaldehyde adhesive are used. The results showed that the compression rate and press time had the most significant impact on the mechanical properties of densified laminated veneer lumber. The optimal production conditions were determined as follows: 38 % compression, press temperature of 170 degrees C, press time of (10 +/- 3) minutes, and spread rate of 150 g/m2. Modulus of rupture, modulus of elasticity, tensile shear strength, and tensile strength perpendicular to panels surface of densified laminated veneer lumbers produced under these conditions increased by 49 %, 8 %, 71 %, and 23 %, respectively, compared to the control group of laminated veneer lumber. So, it can be said that the production parameters of densified laminated veneer lumbers can be optimized safely and effectively using Taguchi method-based grey relational analysis.