a. a. vahedi

Fine woody debris (FWD) is a significant reservoir of carbon and bioenergy in the Hyrcanian forests. Therefore, monitoring changes in FWD biomass on the forest floor is essential for sustainable management, particularly concerning carbon dioxide emissions and carbon trading in both international and domestic markets. The primary objective of this research is to develop optimal allometric equations for accurately monitoring FWD in one of the beech (Fagus orientalis Lipsky) communities within the Hyrcanian forests of Iran.

This study was conducted in the Shastkolateh research forest in Gorgan County, Iran. A random stratified method was employed for direct sampling and weighing of FWD. The FWD was categorized into three diameter classes: 1-2.5 cm, 2.5-4.5 cm, and 4.5-7.5 cm. For each diameter class, length and degree of decay were measured randomly in pure beech and mixed beech stands. Total weight was measured destructively using digital scales. To estimate biomass values of FWD, a power function allometric model based on curve estimation analysis was utilized. The middle diameter, length, dry wood density, and degree of decay of the weighed FWD were introduced as explanatory variables in the model input matrix. These explanatory variables were combined in various ways as independent variables in a log-transformed model. Model validation was conducted using adjusted regression coefficients (Adj.R²), variance inflation factors (VIF), and residual mean square (RMS). A t-test evaluated the significance of parameters in each model, while the fitting of a Loess curve between standardized residuals and estimations was used to assess the validity of the models.

Model development indicated that incorporating middle diameter (D) and length (L) of FWDs into the exponential function of the log-transformed model increased variance explanation from 38% to 73% and reduced RMS from 0.6 to 0.26. Adding wood density (ρ) did not significantly enhance model accuracy or validity. Including degree of decay as a dummy variable slightly improved model accuracy, resulting in the top-ranked model with the highest variance explanation (Adj.R² = 0.78) and lowest RMS (0.22). Furthermore, introducing the biomass surrogate (D² × L × ρ) along with degree of decay considerably increased accuracy, yielding a second-ranked model (Adj.R² = 0.75; RMS = 0.24). Although some parameters were not statistically significant (P > 0.05), no collinearity was detected among the models presented (VIF < 5). The goodness-of-fit data indicated that the Loess curve remained linear around the zero line, with changes in residuals aligning with estimation changes around this line. Findings suggested that biomass estimation for Diospyros lotus L. and unidentified species may be unreliable due to standardized residuals falling outside the zero line range, indicating interdependence in error estimation for these species. Conversely, biomass estimates for F. orientalis and Carpinus betulus L. appeared reliable, with variations not being interdependent.Conclusion In summary, biomass distribution and changes in FWD values exhibit significant variations based on middle diameter and length. Due to limited ranges of decay and dry wood density, these additional variables did not substantially enhance accuracy in log-transformed models. Approximately 22% to 25% of variance remains unexplained when estimating FWD biomass using selected optimal models, particularly regarding errors (standardized residuals). This discrepancy is most pronounced for D. lotus and unidentified species. Overall, the models developed in this research for pure beech and mixed beech-hornbeam forests demonstrate broad applicability within the study area. 

Fine woody debris (FWDs) is considered as one of the prominent carbon sinks in forest ecosystems because of having chief roles for carbon cycle and green economy in association with their contribution for carbon sequestration. Therefore, estimating the FWDs carbon stock with high accuracy and certainty is essential in management. The goal of this study was to use quadratic mean diameter (QMD) of the FWDs in order to increase accuracy of their carbon storage estimation.

The plots with areas of 20 × 20 m2 were randomly located within one hectare of pure beech and mixed beech (Beech-hornbeam) stands in the Hyrcanian forests in Kheiroodkenar, Nowshahr. In line with the sides of square plots that were considered as transects (16 transects in total), the diameter of woody debris intersecting the transects was measured. Three diameter classes (including 1-2.5, 2.5-4.5, 4.5 -7.5 cm) were separated on the basis of diameter distribution in the stands. Using graphical estimation based on fitting power function of FWD diameter distribution, area under curve of each class was calculated to obtain QMD. The slope of linear logarithm model was used to calculate the area under curve of the stands that was obtained from logarithmic conversion of fitted power function.

Considering the negative fitting slope in pure beech stands (b=-1.57) and mixed stands (b=-2.03), the results indicated higher frequency of FWD distribution within the diameter classes in pure beech stands. QMD values of each diameter class in each stand had higher values with no significant differences compared to arithmetic mean and median of diameter distribution. The values were 1.63, 3.47 and 5.73 cm in the predefined classes, respectively, in pure beech stand and were 1.57 and 3.36 cm in the first and second classes, respectively, in the mixed stand.

Although the difference was not significant, it is evident that the estimation of biomass and carbon stock using QMD values in computational relationships based on line transect (parameter obtained by multiplication of number of FWDs in each diameter class and square of QMDs) had higher precision and it is expected that in in large scales (compartment, district, division) show higher values.

Given the significance of fine woody debris (FWDs) in the context of the carbon cycle, climate change, and its implications for renewable energy and economic development, it is imperative to obtain accurate information on the dispersion of FWDs volume stock for effective management of Hyrcanian forests in Iran.

This study was conducted in the Kheiroud forest in Nowshahr county, Iran, employing cluster sample plots distributed along the altitude range of 100-1815 meters above sea level (m.a.s.l.). Circular sample plots were established within each cluster, employing a line transect with a constant azimuth of 150 degrees and a radius length of 7.32 meters. Three diameter classes (1-2.5 cm, 2.5-4.5 cm, and 4.5-7.5 cm) were measured based on line-intersected fallen woods. The coordinates of the samples were recorded, and kriging and inverse distance weighted (IDW) methods were utilized to elucidate the autocorrelation of FWDs volume stock. Stand type, aspect variations, and altitudinal range were considered as main factors in the multiple-way ANOVA.

The findings revealed that the mean FWDs volume stock for each diameter class was 2.14, 6.01, and 16.23 m3/ha in the studied forest. Notably, fluctuations in the FWDs at the third diameter class were less pronounced than in other diameter classes. The goodness of fit data between observations and estimations indicated that both Kriging and IDW techniques estimated responses with low accuracy (R2 = 0.16; RMSE = 6.32) and no accuracy (R2 = 0.04; RMSE = 21.17; R2 = 0.03; RMSE = 37.11). Geostatistical techniques demonstrated that FWDs volume stock cannot be considered a regional variable, lacking autocorrelation and spatial correlation. Consequently, ANOVA results, based on observed power and partial eta squared, revealed that the interaction of altitude, stand type, and aspect did not significantly influence variations in FWDs volume stock (P > 0.05). Pairwise comparisons based on the LSD test indicated that the marginal mean of FWDs in the first diameter class was significantly different only along the altitude (P < 0.05).

In conclusion, the observed variation in FWDs volume stock at different diameter classes appears to be random and independent of the considered interactions. However, complex ecological and biological factors likely contribute to the dispersion of FWDs volume stock in the studied forest.

Since dead trees contain significant amounts of organic matter, they play an essential role in forest dynamics. In the present study, the changes in soil carbon stock were studied in relation to the dead tree features and its soil beneath in mixed broadleaf stands of Loveh forest in Golestan province, Iran using the Principal Component Analysis (PCA) and random forest model. For this purpose, the characteristics of 15 dead trees consisting of hornbeam, oak, Cappadocian maple, and ironwood were recorded in three decay classes 3 to 5, and the soil beneath them was collected from a depth of 0 to 15. The random forest model was implemented based on the relationship between the dependent variable (carbon stock) and the independent variables (effective factors) using the randomForest package in R software. The results showed that using the studied parameters, the random forest model justifies about 54% of the changes in soil carbon stock. According to the final model, the carbon stock of the soil beneath of dead tree is most affected by the three parameters of C/N ratio, nitrogen (%), and soil pH, so in a general trend with the increase of C/N ratio and nitrogen (%) and the decrease of pH, the amount of soil carbon stock around the dead tree has been increased. The present study's findings indicate that dead trees provide great potential for soil carbon storage, especially when faced with an old-growth forest ecosystem.

The unique characteristics of Caucasian oak (CO) stands, located at high altitudes in the Hyrcanian forests, provide valuable insights into the variations of organic carbon (OC) and soil nutrients (NPK), as well as biological and physical changes within these habitats. Understanding these variations is crucial for effective forest management and conservation efforts. To this end, the current study established four 20 x 20 m2 sample plots in each of the CO habitats of Panomehsar in Lavij, Kolanga in Neka, and Tuskestan in Gorgan. Soil samples were collected from two depths (0-15 cm and 15-30 cm) in each plot and analyzed in the laboratory. Biophysical characteristics of trees, such as breast height diameter, total height, average crown diameter, density, and physiographical units, were also recorded.The results showed that OC and nitrogen (N) levels in both soil layers were not significantly different across the study forests (p > 0.05), while available phosphorus (P) and potassium (K) levels varied significantly among them (p < 0.05). There were no significant correlations between OC and N levels in the soil layers, or with the biophysical attributes of the trees based on Pearson tests. The findings indicated that OC and NPK variations were independent of each other, with no significant relationship between them observed in the study sites. Moreover, the nature of OC variations was found to be slow, making it challenging to discern the impact of tree species on these variations within the stands.In conclusion, the study sheds light on the slow nature of OC variations in CO stands and highlights the need for careful consideration of their effects on management and conservation efforts.

The current research aimed to assess the fluctuations of Soil Organic Carbon (SOC) variations in different types of forest stands along the gradient of altitude, and identify the influential factors for the its variations. Based on the random design, four plots with the surface area of 400 m2 in different stand types were established. Soil sampling up to 15cm depth in center and the corners of the each plots were taken. The biophysical attributes of trees as well as physiographical units were measured and recorded within each plot. The results of one-way ANOSIM analysis indicated the lack of similarity of SOC between pure and mixed beech stands (R≅ 0.5) and no significant difference between other stands. The results of the two-way PERMANOVA test also showed that the amount of SOC is independent of the effects of slope and the elevation gradient. The SIMPER test illustrated that the trends of soil organic carbon and soil bulk density were inverse among the stands and the gradient of altitude. However, their trends were not symmetric based on the pairwise comparisons. As a general conclusion, the fluctuations of soil organic carbon in the different types of forest stands are independent of the altitude gradient, stand type and biophysical factors, and the relative abundance of various tree species did not have a significant contribution to the variability of the soil carbon storage of the studied stands.

Establishment and growth of tree regeneration in association with the canopy gap (CG) and its related parameters such as topography and surrounding tree diversity guarantee turnover and dynamics of forest ecosystems. This research was conducted in the control parcel within the third district of Glandroud forests in Mazandaran province and aimed to clarify influences of gap area with respect to the species diversity of surrounding trees and physiography on the density and height responses for established regeneration of oriental beech (Fagusorientalis Lipsky) in various growth stages, in order to suggest an optimum gap size for the mentioned regenerations. After measuring and calculating area of each CG using radial method, the gap sizes were classified based on full census. The established regeneration was divided into three classes of 1.3–2.5 cm (saplings), 2.5–5 cm (thickets), and > 5 cm (pole- or advanced regenerations). Following statistical tests, results generally showed that the variation of density of saplings, thickets and poles was not significantly correlated with the CG size and other associated parameters. However, significant difference among the CG size classes was observed for height of saplings in relation with physiographic units and frequency of marginally surrounding trees. In addition, height of thickets and pole individuals were significantly affected by gap size and frequency of surrounding trees. The findings indicated that all CG size classes consisting of an area less than 200 m2 and the maximum area of 1000 m2 are the environmentally and ecologically optimum areas for beech regeneration based on establishment proportion of growth stages recruitment in the forest ecosystem, taking account of frequency of surrounding trees and physiographic units.

During the marking operations planning in forest ecosystems, designing the canopy gap size (CGS) is not clearly possible and a marker can only be capable of calculating the expanded gap size (EGS) that will be created by cutting and felling trees. Therefore, the main goal of the current study was to provide a solution to this problem on the basis of accurate prediction for CGS, before applying selection methods, through developing regression models for predicting the CGS in Glandroud forests. On the basis of full inventory for measuring the area of canopy and expanded gaps using radial technique, calculating the species diversity indices and observations of physiographic units, the regression models were developed for estimating the CGS as the response in the research. The results showed that the site fraction occupied by expanded gaps has one hectare more than the fraction occupied by the canopy gaps. Furthermore, the results of correlation tests showed that the CGS had significant relationship with the Shannon diversity and species dominance indices. The results of analyses indicated that multiple linear regression log-transformed from the power function including EGS, correlated species diversity indices of gaps surrounding trees predicted the responses with statistically acceptable certainty and accuracy.

One of the most prominent issues indicating the future quality and quantity of natural forest ecosystems is spatial pattern and distribution of disturbances consequences manifested as canopy gaps (CGs). The main purpose of this study was to illustrate the CGs distribution pattern in one of the Hyrcanian mixed-beech (Fagus orientalis Lipsky) forests, so-called preserved Glandroud forests. All CGs areas were measured based on full callipering on the basis of the radius method, and the coordinate of each CG was recorded in the forest. The univariate Ripley’s L-function, mark correlation function (MCF), and density function (DC) in turns were used for analyzing the spatial patterns, size correlation, and frequency of the CGs distribution at the observation scale. Furthermore, the statistical significance of all ordination analyses was tested by the Monte Carlo permutation method. The results showed that the frequency of small gaps (0-2 R), medium gaps (2-5 R), and in turns were almost 32%, 49% in the study forest. Only the small CGs distribution was clustered at a specified distance of 14–20 meters, though the other CGs size classes were completely randomly distributed in the forest. Integrating whole CGs size classes on the basis of Ripley’s L-function showed that the CGs spatial pattern in the studied forest was clustered at a distance of 40 m. According to the mark correlation function (MCF) and density correlation (DC) analyses, there in turns were found that the location and number of size classes in each aggregation were totally significantly independent and random based on the specific distance in the forest. Pertaining to these results, it is possible to introduce mosaics consisting of forest stands which may include specified tree stands with various tree species composition, different developmental stages, and structures in the forest. Therefore, each mosaic can be a base area for monitoring disturbances consequences and implementing optimum managements.

Forest trees biomass estimation with the highest accuracy is the basis of forest management with respect to the sustainable development and that is also one of the most important fundamental issues of C sequestration for international communities to work the global warming out. Modeling bole biomass of maple trees through allometric equations and artificial neural network (ANN) was carried out in Sasunsi forests of Chamestan to achieve the highest accurate prediction of studied biomass. After felling of 20 individual trees from different diameter classes, each part of bole which had been converted was weighed and one disc was taken. Then, the samples with constant volume extracted from each disk were taken to lab and they were oven-dried at 105ú C for 24 hours. To develop the model, power function was basic allometric equation and transfer function of Log-sigmoid and of Tan-sigmoid was introduced in the various topologies of network of FFBP. The results showed that the exponential multiple regression including diameter and height with correction factor of CF = 1.04 was the optimal allometric model (S = 0.23). Pertaining to the least mean squared error of test associated with training and validation of data in the different epoch as well as average standard deviation was the main indicator for selection the best model in ANN. Furthermore, the results showed that the model having input layers of diameter and height with one-hidden layer and number of 10 neurons including tansig function is the best model (S = 0.1) for bole-mass prediction.