جستجوی مقالات مرتبط با کلیدواژه « forest » در نشریات گروه « کشاورزی »

Estimating forest tree structural attributes such as height and diameter at breast height (DBH) is crucial for understanding the structure and management of forest resources. One important method for estimating these parameters is the individual tree detection (ITD) method using appropriate remote sensing data, such as airborne LiDAR data. However, it should be noted that different ITD methods have various limitations and capabilities and react differently to changes in forest tree species and the vertical structure of the canopy.

This study presents a hybrid individual tree detection method that combines raster-based and point-based methods in a multi-scale framework to identify single trees from LiDAR data. In this method, tree crown scale levels are obtained from morphological filters in the canopy height model (CHM). Segmentation is then performed using a multi-scale method, and the results are merged. To better separate adjacent and understory trees, the point cloud inside the segments is analyzed using the probability density function, and tree crown segments are modified. After detecting single trees, DBH and height parameters were estimated using ground control data and extracted features from LiDAR data with machine learning algorithms, including random forest (RF), support vector machine (SVM), and cubist (CB), in the form of 10-fold nested cross-validation (10-fold NCV). The Boruta feature selection algorithm was used to identify the most important metrics based on the LiDAR point cloud, which played an effective role in improving the performance of machine learning algorithms. Due to limited access to LiDAR and ground data from Iran’s forests, this study uses the NEWFOR single tree detection benchmark dataset, collected from forests of the Alpine region with a combination of different tree species and vertical canopy structures.

Although understory trees cannot be extracted with the same accuracy as overstory trees, the results of this study showed that, on average, the developed multi-scale individual tree detection (MSITD) method detected 89% of the tree crowns in the highest height layer and the highest number of small overstory trees with a detection rate of 48% in the lowest height layer (2-5 meters). The analysis of the machine learning algorithms’ results in estimating forest structural attributes showed that, despite slight differences in performance, the SVM algorithm performed better than the RF and CB algorithms in estimating both height and DBH attributes. For the height attribute, the mean values of RMSE, rRMSE, and R2 in the SVM algorithm were 1.75 m, 9%, and 0.85, respectively. For the DBH attribute, the values obtained for RMSE, rRMSE, and R2 were 4.74 cm, 19%, and 0.78, respectively.

The evaluation of the results showed that the methods presented in this study for identifying single trees and estimating forest tree structural attributes have high potential for practical applications.

Accurate digital elevation models (DEMs) are crucial for effective forest planning and management. Various methods exist for generating DEM data, with handheld mobile laser scanners being the most efficient and precise approach. The raw point clouds obtained from these scanners require several preprocessing steps, one of which involves separating ground and non-ground points. Errors in this part of the process can lead to the generation of an inaccurate digital model with high uncertainty and errors. Various algorithms, such as voxel-based segmentation, simulation filters, and deep learning-based approaches, have been developed for this purpose. This study evaluates the performance of the OBS algorithm in automatically separating ground points from non-ground points in handheld laser scanner data. The study area comprised five different sections within the Karaj Botanical Garden, covering a total area of 7.2 hectares. These areas contained forest stands characterized by heterogeneous structures and multi-story tree layers. Data were acquired using a handheld GeoSLAM laser scanner. To generate a reliable reference for evaluating the algorithm's results, ground points were manually separated. The performance of the algorithm was evaluated by comparing it with the manually separated ground truth using statistical metrics, including Matthew's correlation coefficient, Kappa coefficient, and Intersection over Union (IoU). The statistical metrics across the five study areas demonstrated the effectiveness of the OBS algorithm in separating ground points from non-ground points, with Matthew's correlation coefficient, Kappa coefficient, and IoU values of 0.895, 0.891, and 0.902, respectively. Additionally, the optimal voxel size for the algorithm was determined to be within the range of 15 to 22 centimeters.We conclude that the OBS algorithm, when configured with optimal input parameters, provides high performance in automatically separating ground points from non-ground points, especially in heterogeneous forested environments. The importance of configuring the optimal input parameters is also highlighted.

Soil erosion reduces the fertility of upstream lands and damages downstream lands through sedimentation. A field survey was conducted to investigate the performance of each structure in the Nakarood watershed to evaluate the effect of watershed operations on erosion and sedimentation. The watershed operations carried out include coastal wall, spillway, and stone-mortar and biological operations. In addition, taking into account the factors affecting erosion and sedimentation (terrain structure, specific peak discharge and uncovered lands), the EPM model, GIS, and SPSS software were used for the analysis. The results showed that the three factors of land construction (r=0.8), flood (r=0.47) and land use (r=037) had the greatest impact on erosion and sedimentation in the region. Also, the factor of land construction and then flood have more effectiveness. According to the correlation results, these three factors had a significant correlation with erosion, so that the land construction of the area has a significant correlation with erosion (r=0.8) and is determined to be the main factor. Also, rainfed lands under biological treatment have been more effective in reducing erosion and sedimentation in the region. Also, the comparison between before and after watershed operations for different uses showed that erosion and sedimentation decreased more in rainfed agriculture. In general, land use changes significantly affect soil erosion. Therefore, it is very important to take necessary measures to reduce erosion and sedimentation and to preserve the soil of the region. In addition, biological and structural programs and remedial structural operations should be implemented in the watershed to manage water and soil resources and increase the effectiveness of watershed operations in reducing erosion and sedimentation and increasing the land cover layer.

Plant reproduction is highly sensitive to stressors caused by both biotic and abiotic factors in nature. The success of plant establishment in the wild depends on various factors such as drought, grazing, availability of water and soil resources, and the mutual interactions among individuals, especially during the seedling stage. The concept of nurse plants, their effects, competition, facilitation, and the facilitative role in land restoration were explained using scientific sources. Through forest surveys and scientific resources, nurse plants and target plants in southern Iran were identified, and the role of each was examined with available scientific references. For this purpose, along the Persian Gulf and the Sea of Oman, accessible pathways were chosen to investigate vegetation cover up to an altitude of 1250 meters above sea level in sample plots of one hectare (100 * 100 meters). Sampling was conducted beneath the canopy of other trees or shrubs, and the plants were identified using scientific sources. The results of this study revealed that nine species belonging to eight genera and six families were identified as nurse plants, and seven species belonging to six genera and six families were identified as target plants. Among the nurse plant group, the genus Ziziphus Mill. from the family Rhamnaceae was the most diverse. Among the target plant group, the most diverse genus was Pistacia L. belonging to the family Anacardiaceae. Further research is recommended to explore the facilitative effects of nurse plant species and suitable methods for their use in the ecological restoration of dry areas in southern Iran in relation to the implementation of restoration and forest development projects.

Endophytic fungi are fungi that are present in plant tissue at the time of sampling without obvious symptoms. There are several reports that the use of endophytic fungi improves grain yield, increases cold and drought tolerance, resistance to plant pathogens and herbivorous insects. Therefore, these fungi can be used as a biocontrol agent in the protection of crops. Endophytic fungi are a rich source of active metabolites that have the potential to be used in medicine, agriculture, and industry, so this study was conducted to isolate endophytic fungi from hornbeam trees and their morphological and molecular identification from the forests of Sari.

In this study, to identify endophytic fungi from healthy branches of hornbeam trees during autumn 2019 and summer and autumn 2020 of the forests of Sari city were sampled. In the laboratory, each branch sample was kept for 24 months at 24 ° C and continuous darkness after disinfection and culture on PDA medium. Morphological features and sequencing of the ITS region were performed to confirm the morphological identification and sequencing of the relevant dendrogram using version 7.1 of Bioedit software.

In this study, 9 genera and species were identified. Fungal species includ:Alternaria alternata (OM117707), Aspergillus flavus (OM488258), Botryosphaeria dothidea (OM141395), Diaporthe eres (OM131770), Fusarium acuminatum(OM131729),Fusarium sambucinum (OM142129),Mucor fragilis (OM017151), Neofusicuccum parvum (OM017148), Fulvia fulva (OM124921).

In general, the aim of this research was to identify the fungal endophytes of Beech trees based on morphological and molecular data from the forests of Mahdasht, Tabaghdeh, Darabkala and Imamzadeh Zaid Sari located in Mazandaran province.

Protection of forests, rangelands and other natural ecosystems in Iran is facing challenges and currently the natural areas of the country are not in favorable conditions. Some of the problems and mega global challenges that affect various natural areas in the world. This group of challenges include climate change, desertification, land degradation, global warming, deficiency of fresh water and increasing demand for energy. The second group of challenges that are specific to Iran at the national level and have affected the natural environments include lakes drying up, land subsidence, salinity and alkalinity of underground water, desertification and consequently the particulate matter air pollution. Also, the breakdown of the natural hydrology systems of the watersheds and changes in the usage of the natural areas are two man-made super challenges affecting the natural environments of Iran. In this article, the major challenges related to Iran's natural areas and the relevant national and regional challenges at the level of natural ecosystems are discussed. Finally, in order to deal with the challenges raised, the necessary solutions to protect and support Iran's natural areas as better as possible are presented. This includes paying attention to these challenges as one of the basic requirements for applying and implementing ecosystem-based management in the natural areas.

Wildfires in natural resources cause huge human, financial, environmental and ecotourism losses to countries every year. The average of annual fire aria in the world's forests is estimated at four million square kilometers. These wildfires lead to the destruction of vegetation, global warming, air pollution, destruction of environmental diversity, and intensifying the phenomenon of desertification. Various natural and human factors (intentional and non-intentional) are effective in the occurrence and spread of fires in the forests and pastures. Ecoterrorism and environmental terrorism are two common approaches for intentional arson attacks in natural resources. One of the important and relatively new act of environmental terrorism is the phenomenon of pyroterrorism or deliberate destructive fires in forests and pastures. Simplicity, low risk, low financial cost and small number of required actors, weakness of governments in quick containment, high advertising range and inflicting significant damages are among the attractions of such operations for saboteurs. In order to minimize the damage caused by natural and intentional fires, the following defense measures are recommended: equipping the institutions responsible for extinguishing forest and pasture fires with advanced and up-to-date firefighting equipment and facilities, attracting the active participation of local people and training firefighters. Forest dwellers and pastoralists in identifying and extinguishing fires in forests and pastures, improving management practices of forests and pastures, monitoring information about threats and using new technologies in the field of security and fire extinguishing.

Myzocallis coryli (Goetze) (Hemiptera: Aphididae) is a major hazelnut pest in Iran. This aphid attacks the stems and leaves of Corylus avellana L. hazelnut trees, and as the population grows, it causes the leaves of hazelnut trees to dry and fall, reducing the quality of the nuts. The use of entomopathogenic fungi in the management of hazelnut aphid has been prioritized in order to reduce negative environmental consequences. The isolates IRAN 715C, DEMI001, M14, and V245 from the fungus Metarhizium anisopliae were employed in this work to assess on the adults of M. coryli. To assess the toxicity of four isolates, the Probit tool in SPSS 21 software was employed with a fatal dose of 50% of the LC50. The LC50 values for DEMI001, IRAN715C, M14, and V245 isolates on adults of M. coryli in laboratory and field settings were 1.9×106, 2.34×106, 0.469×106, 1.79×106 and 7150×106, 101000×106, 4860×106, 14700×106 con/ml, respectively. According to the findings of this investigation, isolated M14 is particularly efficient on adult filbert aphids. In addition, a larger concentration of fungal suspensions is required in the field to suppress adult aphids than in the laboratory. The additive or synergistic effects were not seen when assessing the interaction between two effective isolates. As a result, the use of isolate M14 in the hazelnut aphid integrated management program (IPM) is suggested.

In this study, we investigated the effects of forest operation on runoff and sediment using small-scale plots. The runoff and sediment samples were collected from 36 sample plots with dimensions of one by two meters in different areas of the operation. We used the Multi-Layer Perceptron (MLP) for modeling, with 65% of the data for training, 10% for validation, and 25% for testing. We evaluated the accuracy of the model using the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), and compared our results with optimized models obtained through trial and error. We collected information and produced runoff and sediment maps using GIS. Our results showed that the most important factors affecting runoff production were soil bulk density, rainfall intensity, slope, rainfall values, percentage of grass cover, and canopy cover percentage. For sediment, the most important factors were rainfall intensity, soil bulk density, slope percentage, and surface cover percentage. The MSE and R values for runoff modeling were 0.009 and 0.9 in the training stage and 0.01 and 0.82 in the test stage, respectively. For sediment modeling, the MSE and R values were 0.01 and 0.86 in the training stage and 4.3 and 0.8 in the test stage, respectively. Our results showed that neural networks have high capability in modeling runoff and sediment in forest lands. We also conducted an overlap analysis to measure the accuracy, precision, and efficiency of the results and methods presented in our study. Therefore, the proposed model can be used to combine ANN and GIS in the simulation and modeling of runoff and sediment in forest areas."

Sediment of eroded soils have different effect on environment based on amount of materials and elements. Nitrogen is an important nutrient that use a lot in agriculture and excessive use of this cause reduce the waters quality.

This project aim is measurement and comparison of soil nitrogen pollution in different land use and relation between each land use drainage pollution when weather is rainy in area of Bostankar river that is located in Shirod city one of the functions of Tonekabon of Mazandaran province. Because of this, soil was sampled from six land use; forest, Orange garden, Kiwi garden, Flower garden, Rice and Tea farms at winter and spring. Then, a water sample was taken from these lands' drainages. Eventually, for checking of Bostankar river situation, water samples wat also taken at 15 points along the river. Amount of total nitrogen, soluble and clinging were measured at water and soil samples.

Results showed that nitrogen amount in drainages at spring were increased than winter, that reason of this matter can be agriculture activities like fertilization and tillage in this period of time. Maximum and minimum nitrogen amount in spring relate to Flower garden and forest, equal 6.60 and 0.30 mg/lit, respectively.

For controlling the nitrogen output and nitrogen pollution at area of study soil, amount of nitrogen fertilizer use should be based on plant need and soil test result.

Today, livestock outflows from the forests of the north of the country have created environmental and social challenges and problems that have caused concern to natural resource policy makers.  The re-emergence of livestock and ranchers illegally in the forests for various reasons has created disputes and tensions with conservation systems. In this regard, the present study was conducted to analyze the key drivers affecting the return of livestock in the forests of Golestan province. The sample population in the study consisted of 20 ranchers returning to the forest and were purposefully selected. After collecting information, using the cross-effects technique and using MicMac software, 27 indices extracted from the Delphi method were analyzed. The results of the dispersion of indicators in the axis of impact and effectiveness, indicate the instability of the livestock exit system from the forests of the province and its organization, based on which five variables were identified. Findings obtained from the effect-matrix direct dependence and dispersion of indicators showed that the lack of accurate implementation of the provisions of the plan in the forest, lack of support from government agencies in the area of ​​housing, lack of alternative job opportunities and diversification of income sources, lack of pasture Natural resources for livestock and the high cost of complementary inputs, non-timely payment of salaries by people subject to the plan by the government, various procedures and instructions contrary to the plan, lack of proper planning in housing and livestock farms, as the most important effective indicators and Strategies were evaluated in the return of livestock to forest areas. According to the obtained results, the compilation and preparation of a 10-year transformation document in order to organize the settled forest households is the most important proposal with a forward-looking approach to the subject under study.

Changes in land quality factors were investigated according to the change in land use of two conventional cropping systems in Khuzestan (Dimcheh region, periodic cultivation system, sugarcane, forest, and deforesting in Zaras region). The results showed that by the change of forest land use, organic carbon from 0.93 to 0.55%, cation exchange capacity (CEC) from 19.6 to 13.3 cmol/kg, C/N from 7.4 to 3.8%, the mean weight diameter of aggregate (MWD) from 1.7 to 1.3%, and microbial respiration from 0.11 to 0.06 mg of CO2 /gr of soil per day decreased and in contrast, the dispersible clay from 4.6 to 19.3% increased. PCA analysis for the parameters showed that five factors justified more than 90% of the variance in the values of FC, PWP, AW, and AF. In the Dimcheh region, the average volumetric moisture content of FC from 31.3% to 27.3%, available water from 12.9% to 9.8%, dispersible clay from 56.1% to 12.3%, and bulk density reduced from 1.6 to 1.4%, organic carbon from 0.45 to 0.78%, C/N from 6.3 to 10.0%, microbial respiration from 0.01 to 0.04 mg of CO2 /gr soil per day and MWD of aggregates increased from 0.77 to 1.3 mm. Five factors including FC, AW, BD, DC, and OM explained more than 90% of the variance.

Investigation of soil attributes is one of the ways to evaluate and manage forest ecosystems. Altitude is considered as one of the effective factors on the soil quality, especially soil organic carbon (OC). However, variation of the soil OC stocks at different altitudes of Arasbaran forests is still unknown. Therefore, this study was conducted to examine the spatial distribution of OC values, and some other chemical properties in different soil depths affected by altitude in Arasbaran forests.

In this study, a factorial experiment was conducted in a randomized complete block design in three replications. Overall, 60 soil samples were collected on a north slope of the region at four different altitude ranges, including 0–600, 600–1200, 1200–1800, and 1800–2400 m, and from five soil depths of 0–20, 20–40, 40–60, 60–80, and 80–100 cm. Then, the amounts of OC, cation exchange capacity (CEC), dilute-acid-soluble and hot-water-soluble carbohydrates, calcium carbonate, available phosphorus and potassium as well as soil acidity (pH) were determined in the soil samples.

The results showed the significant effect of soil depth, altitude and their interaction on most of the studeid soil properties. In fact, with increasing elevation and soil depth, the amount of OC, CEC, and dilute-acid-soluble carbohydrates increased and decreased, respectively, and a very strong correlation was found between them. Additionally, on average more than 50% of the OC was allocated to the top 20 cm of the soils at all four elevations that reduced averagely about 79% with increasing soil depth to the depth of 80–100 cm. Moreover, the highest increase rate of OC contents with altitude of about 9% was observed between the elevation ranges of 600–1200 and 1200–1800 m. Furthermore, with increasing altitude and soil depth, other soil properties such as pH, calcium carbonate, and available potaium showed a decraese of about 2%, 16%, and 16%, and an increase of around 4%, 16%, and 18%, respectively. In addition, with increasing soil depth, the amount of soil available phosphorus increased; meanwhile, the effect of altitude on this parameter was not significant.

Based on the findings of this study, soil OC stocks and overall the quality of Arasbaran forest soils are significantly affected by the factors of altitude and soil depth so that surface soils of higher elevations in the study area are of higher quality in terms of OC content, CEC, and dilute-acid-soluble carbohydrates, which should be given more attention. In fact, considering the significant role of these soils in carbon sequestration, these areas should be preserved intact and undisturbed through proper management as well as various protection practices.