Controlling spatial forest structure with spatial simulation in forest management planning: a case study from Turkey

Decision Support Systems (DSS) is widely used to develop spatially explicit forest management plans through the integration of spatial parameters. As a part of this study, a simulation-based spatial DSS, the ETÇAPSimülasyon program was developed and tested in a case study area. The system has the capability to control the spatial structure of forests based on a geodatabase. Geographical Information Systems (GIS) was used to generate the database, using spatial parameters including opening size, block size and green-up delay in addition to other attribute data such as the empirical yield table and the product assortment table. Based on the simulation technique, a spatial forest management model was developed to link strategic planning with tactical planning on a stand base and to present results with a number of performance indicators. One important component of the model determined all spatial characteristics with spatial parameters and patch descriptions. A stand growth and yield simulation model (BARSM) based on the relationship between current and optimal basal area development was also generated to project future stand characteristics and analyze the effects of various silvicultural treatments. A number of spatial forest management strategies were developed to generate spatially implementable harvest schedules and perform spatial analyses. The forest management concept was enhanced by employing a spatial simulation technique to help analyzing the ecosystem structure. Spatial characteristics for an on-the-ground forest management plan were then developed. The model was tested in Altınoluk Planning Unit (APU) using a spatial simulation technique based on various spatial parameters. The results indicated that the spatial model was able to satisfy the spatial restriction requirements of the forest management plan

Assessment of the interactions among net primary productivity, leaf area index and stand parameters in pure Anatolian black pine stands: A case study from Türkiye

Aim of study: To examine the relationships between net primary productivity (NPP) and leaf area index (LAI) and modeling these parameters with stand parameters such as stand median diameter (dg), dominant height (htop), number of trees (N), stand basal area (BA) and stand volume (V). Area of study: Pure Anatolian black pine (Pinus nigra J.F. Arnold) stands in semi-arid climatic conditions in the Black Sea backward region of Türkiye. Material and methods: In this study, the Carnegie-Ames-Stanford Approach model was used to calculate NPP; LAI, dg, htop, N, BA and V were calculated in 180 sample plots. The relations between NPP and LAI with stand parameters were modeled using multiple regression analysis, support vector machines (SVM) and deep learning (DL) techniques. Relationships between NPP and LAI were investigated according to stand developmental stages and crown closure classes. Main results: The highest level of relations was obtained in the stands containing the a-b developmental stages (r=0.84). The most successful model in modeling NPP with stand parameters was obtained by DL method (model R2=0.64, test R2=0.51). Although DL method had higher success in modeling LAI with stand parameters, SVM method was found to be more successful in terms of model-test fit, and modeling success in independent data set. Research highlights: Grouping parameters affecting NPP and LAI increased the level of correlation between them. In modeling NPP and LAI in relation to stand parameters, machine learning algorithms performed better than linear approach. The overfitting problem can be eliminated substantially by including arguments such as early stopping, network reduction and regularization in the network structure

Global warming and renewable energy sources for sustainable development: A case study in Turkey

Renewable energy sources have been important for humans since the beginning of civilization. For centuries and in many ways, biomass has been used for heating and cooking. Many centuries ago mankind was already utilizing the clearly visible power of water for mechanical drive purposes, as was also the case with wind. On the other hand, Turkey, with its young population and growing energy demand per person, its fast growing urbanization, and its economic development, has been one of the fast growing power markets of the world for the last two decades. It is expected that the demand for electric energy in Turkey will be 300 billion kWh by the year 2010 and 580 billion kWh by the year 2020. Turkey is heavily dependent on expensive imported energy resources that place a big burden on the economy and air pollution is becoming a great environmental concern in the country. In this regard, renewable energy resources appear to be the one of the most efficient and effective solutions for clean and sustainable energy development in Turkey. Turkey's geographical location has several advantages for extensive use of most of these renewable energy sources. This article presents a review of the potential and utilization of the renewable energy sources in Turkey.Energy utilization Renewable energy Geothermal Hydropower Solar Biomass

Turkish Guideline for Diagnosis and Treatment of Allergic Rhinitis (ART)

Object: To prepare a national guideline for Oto-rhinolaryngologist who treat allergic rhinitis patient