The Effects of Changes in the Forest Structure’s Quantitative Traits on the Leaf Area Index in Hyrcanian Forests, Golestan Province

Extended Abstract Background: The leaf area index (LAI) is one of the structural indices of forests and a key variable in the state of forest ecosystems. This index is one of the major structural indices of forests that plays an important role in the processes of evaporation and transpiration and in monitoring the growth of trees. The role of LAI is very important in the changes in the structural quantitative characteristics of forest stands. There is a general relationship between the LAI and the quantitative characteristics of the mass. The leaf area of each tree can be estimated using allometric equations of quantitative characteristics. This research focuses on the effects of changes in the quantitative characteristics, such as tree density (n.ha-1), basal area (m2.ha-1), volume (m3.ha-1), mean height (m), mean diameter at breast height (DBH, cm), crown area (m2.ha-1), and crown volume (m3.ha-1) on the LAI and preparation of their allometric equations in the broadleaf forests of Golestan province. Methods: To collect ground information on LAI, 227 circular sample plots with an area of 1000 m2 with a systematic sampling method and a 100 × 100 m grid were dismounted in five habitats from west to east (Kordkoy, Shasat Kalathe, Zarrin, Gol, Sorkhdari, and Loveh). In the center of each sample plot, the LAI was measured using a leaf harvesting trap with dimensions of 60 × 60 cm. The geographic center of each sample was recorded using a Differential Global Positioning System device. The species type, breast diameter greater than 12.5 cm, the height of trees, large diameter, and small crown diameter are measured, then as tree density (n.ha-1), basal area (m2.ha-1), volume (m3.ha-1), mean height (m), mean DBH (cm), crown area (m2.ha-1), and crown volume (m3.ha-1) located in each sample plot were calculated in each plot. To calculate the LAI, it is first necessary to measure the specific leaf area of all species in the study area. To calculate the LAI, 20 trees were separated from each tree in each habitat and five leaf samples were separated from each tree in four geographical directions. In total, more than 15,000 leaf samples were analyzed and scanned in five habitats. The area of each leaf was measured using ImageJ software. The wet and dry weight and surface area were measured simultaneously using a digital scale with an accuracy of 0.01 and then scanned with a high-resolution scanner. After scanning, the leaves were dried in an oven at 72 °C for 48 hours to obtain their dry weights. Non-linear rational function, Gaussian, hyperbolic, heat capacity, and exponential models were used to investigate the relationship between LAI and the structural characteristics of the stand. Results: The results of the analysis of descriptive statistics showed that the minimum, maximum, average, and standard deviation of the LAI were calculated for 227 samples (1.86, 13.45, 6.33, and 2.33), respectively. The results of the analysis of descriptive statistics also showed that the mean and standard deviation for the characteristics of volume (m3.ha-1), tree density (n.ha-1), basal area (m2.ha-1), crown area (m2.ha-1), crown volume (m3.ha-1), mean height (m), and mean DBH (cm) were respectively (96.96) 298 and 18.205), (24.05 and 12.82), (24.05 and 12.82), (51.148 and 54.155), (2.781 and 05.95), (41.36 and 9.97), and (25.81 and 4.93). The results of the relationships between the LAI and the quantitative characteristics of the volume (m3.ha-1), tree density (n.ha-1), basal area (m2.ha-1), crown area (m2.ha-1), crown volume (m3.ha-1), mean height (m), and mean DBH (cm) of the coefficients of determination showed (36-0.96) R2 = 0.00 with a mean square error of MSE = 0.48-2.06. Among the investigated quantitative traits, the average height, crown volume per hectare, and volume per hectare gained the highest R2 values (0.36-0.96) and the MSE (0.48-2.06) with Gaussian, Richard, and heat capacity allometric models, and the tree density trait (n.ha-1). The lowest R2 (0.36) and MSE (2.06) in the study of LAI were obtained with the Gaussian model. The results also showed large changes in the LAI for the crown volume trait up to 400 (m3.ha-1), followed by a uniform trend. For the average height of up to 40 (m), many changes were found in the LAI. For the volume trait (m3.ha-1), the LAI increased up to 800 (m3.ha-1) and then showed a uniform and even downward trend until 1200 (m3.ha-1). Conclusion: The results of this research demonstrate that the three quantitative traits, viz. crown volume (m3.ha-1), mean height, and volume (m3.ha-1), have the greatest effect on the changes in the LAI. Thus, these three traits can better explain the LAI. The LAI can estimated using the three crown volume (m3.ha-1), mean height, and volume (m3.ha-1) traits. Based on these three traits, the LAI can explained on a large scale, and the estimated results can be used in climate models and the development of appropriate climate change policies.