Volume 12, Issue 1 (5-2024)
Ecol Iran For 2024, 12(1): 99-112 |
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Javanmiri Pour M. (2024). A Study on the Structure Complexity Index and Stand Quality in Managed Mixed Habitats in Kheyrud Fores. Ecol Iran For. 12(1), 99-112. doi:10.61186/ifej.12.1.99
URL: http://ifej.sanru.ac.ir/article-1-526-en.html
URL: http://ifej.sanru.ac.ir/article-1-526-en.html
Forestry and Forest Economics Dept., Faculty of Natural Resources, University of Tehran. Karaj-Iran
Abstract: (1146 Views)
Extended Abstract
Background: As a forest evolves, it undergoes various processes that lead to the creation of complex structures and diversity. The heterogeneity of the structural conditions and species diversity increase as living and fallen trees accumulate in population structures. These processes are mainly related to the growth and death of trees, which occur in stages starting from youth, progressing through maturity, and culminating in structural complexity. By examining the complexity of a forest, forest experts can manage and change the complexity and diversity of the forest. This study compares the index of structural complexity in managed mixed stands in Hyrcanian forests to determine the effect of management interventions on this index.
Methods: For this study, five one-hectare rectangular sample plots were selected in parcels 305, 306, 309, 310, and 311 located in the Grozbon section of Kheyrud forest situated 6 km east of Nowshahr in the Hyrcanian forest belt of Iran. The Gorzbon section has an area of 1001 hectares. The diameters of all trees above the counting limit were measured using complete inventory in one-hectare sample plots. In addition, we calculated the heights of the trees, the abundance of old trees, the abundance and volume of dry trees, the canopy gaps, the Mingling index, and the Gini coefficient. The structure complexity index was determined using a set of variables related to the most important structural features of forest stands. Single selection indices and the multivariate complexity index were calculated in four steps. Finally, the complexity index of the structure was determined between zero and 100 by adding up each variable. The numerical value of the index is close to 100 and zero in the forest stands with the highest and the least complexities in the structure, respectively.
Results: The study examined 1836 trees in five sample plots across five parcels. The highest density of trees was 564 trees per hectare in plot 306. Mamrez was the dominant species in stands 306, 305, and 310 while beech was the dominant species in stands 309 and 311. The maximum average diameter, head volume, and height were 32.5 cm, 458 m3, and 41 m, respectively, for the sample plot 309. The distribution curve of tree abundance across different diameter classes showed a decreasing exponential distribution in the reverse J shape, with differences observed between the studied stands. The largest number of trees in small-diameter classes (15 and 20 cm) were found in cluster 306, with 283 and 137 trees, respectively. The lowest number of trees in the primary classes were 33 and 31 trunks in stand 309. Comparing the volume of trees in diameter classes showed that the volume distribution in all diameter classes was significant in parcel 309, where the volumes in thick and very thick classes were 296 and 83 m3 per hectare, respectively. Parcels 306 and 307 had no quantity of trees in the very thick class. The sample piece 309 had the highest value of complexity index, with a numerical value of 85 while the lowest value of this index (66) was found in the sample piece 305. The ANOVA test with a probability of 5% (P = 0.05) showed significant differences in the abundance and amount of tree volume, the abundance of old trees, the ratio of clear area to forest area, the abundance and volume of dry trees, tree height, and the Mingling index when comparing the studied characteristics to determine the structural complexity index among different populations.
Conclusion: The habitats that have been studied have an average complexity index of 0.75. The highest and the lowest indexes belong to parcels 309 (0.85) and 306 (0.66), respectively. The other habitats have an intermediate level of complexity, which indicates the presence of different evolutionary stages in the forest, ranging from young to old. To illustrate the contribution of different structural features to the complexity and diversity of a forest, imagine a hypothetical forest in both complex and simple states. The complex forest has a wider range of tree sizes and potentially ages, including large trees, while the simple forest has a large number of smaller trees and no large trees, potentially lacking old-age trees. The complex forest includes at least two tree species while the simple forest consists of only one species. The complex forest also has larger erect and decumbent angiosperms on the ground while the simple forest lacks large decumbent angiosperms. Finally, the distribution of trees and canopies, or conversely clearings, is spatially variable in the complex forest, leading to structural heterogeneity in the area. To increase diversity and complexity, measures such as thinning or leaving trees with habitat importance such as thick and old trees, and standing and fallen dry trees in selective cuts can be taken to preserve or restore structural complexity, species diversity, and heterogeneity.
Background: As a forest evolves, it undergoes various processes that lead to the creation of complex structures and diversity. The heterogeneity of the structural conditions and species diversity increase as living and fallen trees accumulate in population structures. These processes are mainly related to the growth and death of trees, which occur in stages starting from youth, progressing through maturity, and culminating in structural complexity. By examining the complexity of a forest, forest experts can manage and change the complexity and diversity of the forest. This study compares the index of structural complexity in managed mixed stands in Hyrcanian forests to determine the effect of management interventions on this index.
Methods: For this study, five one-hectare rectangular sample plots were selected in parcels 305, 306, 309, 310, and 311 located in the Grozbon section of Kheyrud forest situated 6 km east of Nowshahr in the Hyrcanian forest belt of Iran. The Gorzbon section has an area of 1001 hectares. The diameters of all trees above the counting limit were measured using complete inventory in one-hectare sample plots. In addition, we calculated the heights of the trees, the abundance of old trees, the abundance and volume of dry trees, the canopy gaps, the Mingling index, and the Gini coefficient. The structure complexity index was determined using a set of variables related to the most important structural features of forest stands. Single selection indices and the multivariate complexity index were calculated in four steps. Finally, the complexity index of the structure was determined between zero and 100 by adding up each variable. The numerical value of the index is close to 100 and zero in the forest stands with the highest and the least complexities in the structure, respectively.
Results: The study examined 1836 trees in five sample plots across five parcels. The highest density of trees was 564 trees per hectare in plot 306. Mamrez was the dominant species in stands 306, 305, and 310 while beech was the dominant species in stands 309 and 311. The maximum average diameter, head volume, and height were 32.5 cm, 458 m3, and 41 m, respectively, for the sample plot 309. The distribution curve of tree abundance across different diameter classes showed a decreasing exponential distribution in the reverse J shape, with differences observed between the studied stands. The largest number of trees in small-diameter classes (15 and 20 cm) were found in cluster 306, with 283 and 137 trees, respectively. The lowest number of trees in the primary classes were 33 and 31 trunks in stand 309. Comparing the volume of trees in diameter classes showed that the volume distribution in all diameter classes was significant in parcel 309, where the volumes in thick and very thick classes were 296 and 83 m3 per hectare, respectively. Parcels 306 and 307 had no quantity of trees in the very thick class. The sample piece 309 had the highest value of complexity index, with a numerical value of 85 while the lowest value of this index (66) was found in the sample piece 305. The ANOVA test with a probability of 5% (P = 0.05) showed significant differences in the abundance and amount of tree volume, the abundance of old trees, the ratio of clear area to forest area, the abundance and volume of dry trees, tree height, and the Mingling index when comparing the studied characteristics to determine the structural complexity index among different populations.
Conclusion: The habitats that have been studied have an average complexity index of 0.75. The highest and the lowest indexes belong to parcels 309 (0.85) and 306 (0.66), respectively. The other habitats have an intermediate level of complexity, which indicates the presence of different evolutionary stages in the forest, ranging from young to old. To illustrate the contribution of different structural features to the complexity and diversity of a forest, imagine a hypothetical forest in both complex and simple states. The complex forest has a wider range of tree sizes and potentially ages, including large trees, while the simple forest has a large number of smaller trees and no large trees, potentially lacking old-age trees. The complex forest includes at least two tree species while the simple forest consists of only one species. The complex forest also has larger erect and decumbent angiosperms on the ground while the simple forest lacks large decumbent angiosperms. Finally, the distribution of trees and canopies, or conversely clearings, is spatially variable in the complex forest, leading to structural heterogeneity in the area. To increase diversity and complexity, measures such as thinning or leaving trees with habitat importance such as thick and old trees, and standing and fallen dry trees in selective cuts can be taken to preserve or restore structural complexity, species diversity, and heterogeneity.
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