Abstract Introduction: An understanding of landscape change and forest dynamics based on topographical parameters and human activities is important for the sustainable management of forest ecosystems. Objective: Update the analysis of land-use/land-cover changes in the Gümüşhane Forest Enterprise in northeastern Turkey. Materials and methods: Forest improvement changes over the last 26-year period (1987-2013) were analyzed in terms of land-use/land-cover classes using forest management plans. The temporal transitions among the land use and cover types were also documented and evaluated based on topographical parameters and distance from settlements using elevation maps and ring buffers. Results and discussion: This period showed rapid forest improvement with an increase of 50,910 ha, amounting to a 1.58 % annual improvement rate. While the most highly forested elevation zone (66.6 % - 40,124 ha) was located between 1,501 and 2,000 m, the highest forestation rate (22.4 % - 13,509 ha) was found at a distance of over 500 m from settlement areas between 1971 and 2013. In terms of fragmentation, on the other hand, Gümüşhane forests were fragmented by an areal increase in productive forest areas between 1971 and 2013. Conclusions: Important data on the dynamics of forest ecosystems in Gümüşhane Forest Enterprise were obtained. There is a strong link between land use changes and forest cover, social pressure, settlement distance, and elevation class.

Resumen Introducción: Conocer el cambio del paisaje y la dinámica del bosque con base en los parámetros topográficos y las actividades humanas es importante para el manejo sostenible de los ecosistemas forestales. Objetivo: Actualizar el análisis de los cambios en el uso del suelo y cobertura terrestre en Gümüşhane Forest Enterprise en el noreste de Turquía. Materiales y métodos: Los cambios en las mejoras forestales en un periodo 26 años (1987-2013) se analizaron de acuerdo con las clases de uso de suelo y cobertura terrestre utilizando planes de manejo forestal. Las transiciones temporales entre el uso del suelo y los tipos de cobertura se documentaron y evaluaron con base en los parámetros topográficos y la distancia de los asentamientos, utilizando mapas de elevación y buffers de anillo. Resultados y discusión: El periodo mostró una rápida mejoría forestal con un incremento de 50,910 ha y tasa de mejora anual de 1.58 %. Mientras que la zona de elevación más arbolada (66.6 % - 40,124 ha) se localizó entre 1,501 y 2,000 m, la tasa de forestación más alta (22.4 % - 13,509 ha) se encontró a una distancia de más de 500 m de las áreas de asentamiento entre 1971 y 2013. Los bosques de Gümüşhane se fragmentaron debido a un aumento de áreas forestales productivas entre 1971 y 2013. Conclusiones: Se obtuvieron datos importantes sobre la dinámica de los ecosistemas forestales en Gümüşhane Forest Enterprise. Existe un fuerte vínculo entre los cambios en el uso de suelo y la cubierta forestal, la presión social, la distancia de los asentamientos y la clase de elevación.

Diameter at breast height (DBH) is the simplest, most common and most important tree dimension in forest inventory and is closely correlated with wood volume, height and biomass. In this study, a number of linear and nonlinear models predicting diameter at breast height from stump diameter were developed and evaluated for Oriental beech (Fagus orientalisLipsky) stands located in the forest region of Ayancık, in the northeast of Turkey. A set of 1,501 pairs of diameter at breast height-stump measurements, originating from 70 sample plots of even-aged Oriental beech stands, were used in this study. About 80 % of the otal data (1,160 trees in 55 sample plots) was used to fit a number of linear and nonlinear model parameters; the remaining 341 trees in 15 sample plots were randomly reserved for model validation and calibration response. The power model data set was found to produce the most satisfactory fits with the Adjusted Coefficient of Determination, R2adj (0.990), Root Mean Square Error, RMSE (1.25), Akaike’s Information Criterion, AIC (3820.5), Schwarz’s Bayesian Information Criterion, BIC (3837.2), and Absolute Bias (1.25). The nonlinear mixed-effect modeling approach for power model with R2adj(0.993), AIC (3598), BIC (3610.1), Absolute Bias (0.73) and RMSE (1.04) provided much better fitting and precise predictions for DBH from stump diameter than the conventional nonlinear fixed effect model structures for this model. The calibration response including tree DBH and stump diameter measurements of the four largest trees in a calibrated sample plot in calibration produced the highest Bias, -5.31 %, and RMSE, -6.30 %, the greatest reduction percentage.