Scale-dependent intraspecific competition of Taurus cedar (Cedrus libani A. Rich.) saplings in the Southern Turkey.

Better understanding of the competitive interaction at the early development stages of the stand is crucial to help schedule silvicultural treatments for young stands and for the better management of the future stands. We used scale-dependent analysis to improve our understanding of sapling dynamics in the pure Taurus cedar (Cedrus libani A. Rich.) stands in Southern Turkey. Using data from nine plots established at the western Taurus Mountains, diameter, height, and crown radii of saplings were compared, and spatial point pattern analyses were performed. We found significant differences for the mean diameter and height, and crown radii of saplings among the plots. Univariate pair correlation function showed that sapling pattern was regular only at small scales (r < 0.4 m) but was predominantly random. Bivariate pair correlation function revealed no evidence of spatial interaction between tall saplings and short saplings. Univariate mark correlation function revealed that strong intraspecific competition was detected at small scales (up to 0.55 m). This distance is reasonable for the juvenile age tending of Taurus cedar saplings and should be under consideration during silvicultural treatments to use the site productivity more efficiently.

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.

Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model.

Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium, an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium. Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdagi Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine-scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species' distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine-scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.

Land use pattern at Alacam mountainous range land (submediterranean-Turkey) due to edaphic and physiographical factors.

Soil degradation is perceived as a major threat in the Mediterranean region due to land use pattern and projected climate change. As the high altitudinal mountainous lands are sensitive lands, the land use patterns atAlaçam mountains were investigated in this study. The assessment of land use distribution is arranged with the altitude, exposure, slope and bedrock parameters. The spatial database of project was created using GRASS GIS open source software (GRASS Development Team, 2008). The scanned land use and main rock map of the project area rectified, digitized, and attributes of land use and bedrocks were entered into the database tables. Also raster SRTM3 data were imported into these databases for making physiographical factor (elevation, slope, aspect) maps. Our findings illustrated thatthe whole area of Alaçam mountains is 282 480 ha where most of the area of the mass is located between 700-1300 m asl with 200 585 ha corresponding to 71% of the whole area. We detected two kinds of mis-land use; (1) agricultural activities applied at the slopes above 17% (representing 35 220 ha) and agricultural activities applied on metamorphic rocks (representing 872 ha). Total misuse of lands reached 36 092 ha comprised 12.77% of the whole area.

Determination of incoming solar radiation in major tree species in Turkey.

Light requirements and spatial distribution of major forest tree species in Turkey hasn't been analyzed yet. Continuous surface solar radiation data, especially at mountainous-forested areas, are needed to put forward this relationship between forest tree species and solar radiation. To achieve this, GIS-based modeling of solar radiation is one of the methods used in rangelands to estimate continuous surface solar radiation. Therefore, mean monthly and annual total global solar radiation maps of whole Turkey were computed spatially using GRASS GIS software "r.sun" model under clear-sky (cloudless) conditions. 147498 pure forest stand point-based data were used in the study for calculating mean global solar radiation values of all the major forest tree species of Turkey. Beech had the lowest annual mean total global solar radiation value of 1654.87 kWh m(-2), whereas juniper had the highest value of 1928.89 kWh m(-2). The rank order of tree species according to the mean monthly and annual total global solar radiation values, using a confidence level of p < 0.05, was as follows: Beech < Spruce < Fir species < Oak species < Scotch pine < Red pine < Cedar < Juniper. The monthly and annual solar radiation values of sites and light requirements of forest trees ranked similarly.