Gülci Neşe, PhD

Harvest from plantations can provide both industrial wood and forest residues for bioenergy, including stumps. The literature suggests that the choice of cutting system can affect the division between industrial wood recovery and remaining stump volume. In this study, two felling techniques - motor-manual chainsaw and feller-buncher, were compared based on stump-height-related timber value loss for four ground slope classes: high, medium, low, and flat. The economic value loss of wood material for three products - sawlogs, pulpwood, and fiber-chip wood, was determined based on the estimated volume of stumps left in the woods. The results indicated that the average stump height for the motor-manual chainsaw and feller-buncher was 17.16 cm and 8.69 cm. The economic value loss of wood material per stump was higher in felling by manual chainsaw as compared to the feller-buncher operation (log: €0.60­, paper wood: €0.29­, fiber-chip: €0.15­). However, volume loss due to high stumps could contribute to wood for bioenergy if stumps are subsequently removed. Additional research is needed to evaluate the benefits and costs of stump removal for bioenergy as part of a total supply chain to provide both industrial wood and wood for bioenergy.

The investigation of the effects of the noise generated by harvesting equipment on the environment is one of the important topics in sustainable forestry. During timber harvesting, not only workers but also wildlife are exposed to the noise generated. Exposure to noise has both direct and indirect effects on humans and wildlife. The negative effects of noise exposure can be observed depending on its intensity and duration. Noise exposure, which has various psychological and physiological effects on humans, also negatively affects plants and animals. In this study, sound measurements of the chainsaw were conducted during thinning operations within the boundaries of the Alara Forest Management Directorate in Alanya, Antalya Province. The measurement area is a Turkish red pine (Pinus brutia Ten.) stand with a canopy density of 60–65%, a slope of 30–35%, and tree diameters ranging from 20 to 35 centimeters. The noise emitted by the chainsaw during production, ranging from approximately 1 meter to 200 meters, has been modeled using a feedforward Artificial Neural Network (FANN) for sound propagation. The measurement data was used 60% for training, 20% for testing, and 20% for validation. Random trees were assigned to noise attenuation effects on the sound according to the stand characteristics of the study area. Thus, it was aimed to create a realistic sound propagation model and estimation maps. The average performance metrics of the model, RMSE and R² values, were calculated as 4.84 and 0.88, respectively. According to the sound propagation model predicted by the FANN as a static model, it is estimated that the distance at which the chainsaw could affect wildlife behavior is 400 meters or less.

The investigation of the effects of the noise generated by harvesting equipment on the environment is one of the important topics in sustainable forestry. During timber harvesting, not only workers but also wildlife are exposed to the noise generated. Exposure to noise has both direct and indirect effects on humans and wildlife. The negative effects of noise exposure can be observed depending on its intensity and duration. Noise exposure, which has various psychological and physiological effects on humans, also negatively affects plants and animals. In this study, sound measurements of the chainsaw were conducted during thinning operations within the boundaries of the Alara Forest Management Directorate in Alanya, Antalya Province. The measurement area is a Turkish red pine (Pinus brutia Ten.) stand with a canopy density of 60–65%, a slope of 30–35%, and tree diameters ranging from 20 to 35 centimeters. The noise emitted by the chainsaw during production, ranging from approximately 1 meter to 200 meters, has been modeled using a feedforward Artificial Neural Network (FANN) for sound propagation. The measurement data was used 60% for training, 20% for testing, and 20% for validation. Random trees were assigned to noise attenuation effects on the sound according to the stand characteristics of the study area. Thus, it was aimed to create a realistic sound propagation model and estimation maps. The average performance metrics of the model, RMSE and R² values, were calculated as 4.84 and 0.88, respectively. According to the sound propagation model predicted by the FANN as a static model, it is estimated that the distance at which the chainsaw could affect wildlife behavior is 400 meters or less.