Fatih Sivrikaya

Spatial patterns of eastern Mediterranean climate influence on tree growth

The first large-scale network of 79 tree-ring chronologies in the Eastern Mediterranean and Near East (EMNE; 33°N–42°N, 21°E–43°E) is described and analyzed to identify the seasonal climatic signal in indices of annual ring width. Correlation analysis and cluster analysis are applied to tree-ring data and gridded climate data to assess the climate signal embedded in the network in preparation for climate field reconstructions and formal proxy/model intercomparison experiments. The lengths of the 79 combined chronologies range from 89 to 990 years. The monthly correlations and partial correlations reveal a pervasive positive association with May, June, and sometimes July precipitation, positive correlations with winter and spring (December through April) temperatures, and negative relationships with May through July temperature, although as expected, there are site-to-site exceptions to these general patterns. Cluster analysis suggests three groups of sites based on their association with climate. The chronologies for the EMNE have coherent seasonal precipitation and temperature signals across a fairly broad geographical domain. The predominant signal is a positive growth response to May–June precipitation. Collectively, the findings suggest that the network can be exploited to develop season-specific field reconstructions of precipitation and drought history in the EMNE.

A GIS-based decision support system for determining the shortest and safest route to forest fires: a case study in Mediterranean Region of Turkey

The ability of firefighting vehicles and staff to reach a fire area as quickly as possible is critical in fighting against forest fires. In this study, a Geographical Information System-based decision support system was developed to assist fire managers in determining the fastest and the safest or more reliable access routes from firefighting headquarters to fire areas. The decision support system was tested in the Kahramanmaras Forestry Regional Directoratein the Mediterranean region of Turkey. The study area consisted of forested lands which had been classified according to fire sensitivity. The fire response routing simulations considered firefighting teams located in 20 firefighting headquarter locations. The road network, the locations of the firefighting headquarters, and possible fire locations were mapped for simulation analysis. In alternative application simulations, inaccessible roads which might be closed due to fire or other reasons were indicated in the network analysis so that the optimum route was not only the fastest but also the safest and most reliable path. The selection of which firefighting headquarters to use was evaluated by considering critical response time to potential fire areas based on fire sensitivity levels. Results indicated that new firefighting headquarters should be established in the region in order to provide sufficient firefighting response to all forested lands. In addition, building new fire access roads and increasing the design speed on current roads could also increase firefighting response capabilities within the study area.

Elevation-layered dendroclimatic signal in eastern Mediterranean tree rings

The authors wish to thank the Forestry Departments in Turkey, Greece, Cyprus, Lebanon, and Syria for their great help and support in making this study possible. We would like to thank the Cyprus Meteorological Service for providing us with climate data. We thank Professor Alexandros P Dimitrakopoulos, of the Laboratory of Forest Protection, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, Greece, for his help and support. We thank Christopher Baisan, Russell Biggs, and Gurudas C Bock for their valuable assistance in the field. We also thank Russell Biggs, Victoria L Frazier, Alicia Stout, Gurudas C Bock, Jessica L Little, and Anthony P Trujillo for their assistance in sample preparation and measurement. We wish to thank the anonymous reviewers for their constructive comments and suggestions on the manuscript. Funding was provided by the US National Science Foundation under Grant Earth System History (Grant No. 0075956), ATM-GEO/ATM-Paleoclimate Program 0758486, and Paleo Perspectives on Climate Change (Award No. 1103314). V. Shishov (software development and data analysis) was supported by the Russian Science Foundation (Grant # 14-14-00219). The tree-ring data will be available at the International Tree-Ring Data Bank (ITRDB) web site (https://www.ncdc.noaa.gov/paleo/study/19016).

The importance of spatial accuracy in characterizing stand types using remotely sensed data

This study assessed the potential use of Landsat 7 ETM+ (15 and 30 m spatial resolutions) images to estimate forest stand attributes such as development stages, crown closure and stand types. The study evaluates the performance of spatial and image classification accuracies between Landsat images (15 and 30 m spatial resolutions) and the forest cover type map (FCTM) with the spatial analysis functions of Geographical Information System (GIS). As a base study, the stand parameters were determined by forest cover type generated with high spatial accuracy of infrared color aerial photography interpretation. The study compared the performance of classification accuracies of satellite images into the forest cover type map (FCTM). The result shows that crown closure was the most successfully classified stand parameters with a 0.92 kappa statistic value and 94.2% overall accuracy assessments in 30 m resolution Landsat 7 image and 0.94 and 95.8% in 15 m resolution Landsat image, respectively. The results indicate that 15 m resolution Landsat 7 image can lead to more accurate mapping of stand type with development stages and crown closures, than 30 m resolution Landsat image according to classification accuracy. However, spatial accuracy was lower than classification accuracy in both images. Spatial analysis clearly showed that the spatial accuracy might be more important than the image accuracy in classification of satellite images to determine forest cover types. This study reveals the differences between image accuracy and spatial accuracy of stand parameters in both Landsat images. The differences were quite significant and should be taken into consideration in forest inventory and land use planning.