Search Results (31)

Semi-Mediterranean (SM) and semi-arid (SA) regions, exemplified by the Kurdo-Zagrosian forests in western Iran and northern Iraq, have experienced frequent wildfires in recent years. This study proposes a modified Non-Negative Matrix Factorization (NMF) method for detecting fire-prone areas using satellite-derived data in SM and SA forests. The performance of the proposed method was then compared with three other already proposed NMF methods: principal component analysis (PCA), K-means, and IsoData. NMF is a factorization method renowned for performing dimensionality reduction and feature extraction. It imposes non-negativity constraints on factor matrices, enhancing interpretability and suitability for analyzing real-world datasets. Sentinel-2 imagery, the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and the Zagros Grass Index (ZGI) from 2020 were employed as inputs and validated against a post-2020 burned area derived from the Normalized Burned Ratio (NBR) index. The results demonstrate NMF’s effectiveness in identifying fire-prone areas across large geographic extents typical of SM and SA regions. The results also revealed that when the elevation was included, NMF_L1/2-Sparsity offered the best outcome among the used NMF methods. In contrast, the proposed NMF method provided the best results when only Sentinel-2 bands and ZGI were used. Full article

The generation of aerial and unmanned aerial vehicle (UAV)-based 3D point clouds in forests and their subsequent structural analysis, including tree delineation and modeling, pose multiple technical challenges that are partly raised by the calibration of non-metric cameras mounted on UAVs. We present a novel method to deal with this problem for forest structure analysis by photogrammetric 3D modeling, particularly in areas with complex textures and varying levels of tree canopy cover. Our proposed method selects various subsets of a camera’s interior orientation parameters (IOPs), generates a dense point cloud for each, and then synthesizes these models to form a combined model. We hypothesize that this combined model can provide a superior representation of tree structure than a model calibrated with an optimal subset of IOPs alone. The effectiveness of our methodology was evaluated in sites across a semi-arid forest ecosystem, known for their diverse crown structures and varied canopy density due to a traditional pruning method known as pollarding. The results demonstrate that the enhanced model outperformed the standard models by 23% and 37% in both site- and tree-based metrics, respectively, and can therefore be suggested for further applications in forest structural analysis based on consumer-grade UAV data. Full article

Forest roads have been recognized as one of the significant contributors to soil erosion processes in forested areas. The construction and maintenance of forest roads can cause severe environmental impacts, including soil erosion, sedimentation, and degradation of aquatic ecosystems. The main objective of the present study is to analyze the impact of forest road networks on soil erosion and sedimentation in the context of the Zagros forestlands, Iran. This study aims to assess the soil erosion and sedimentation on forest roads in four case studies in the Zagros forestlands. This study collected data using field surveys and SEDMODL equations to determine input factors and sedimentation and erosion rates. This study found that roadside erosion is strongly correlated with geological factors, road width, and precipitation factors. The height changes of 144 benchmarks were recorded during one study year (2021–2022) on four study roads, and the measured results of erosion benchmarks indicated an average soil erosion of 3, 2.6, 4.7, and 3.5 mm per year around the Bideleh, Kohian, Nazi, and Tabarak roads, respectively. This study measured soil erosion and sedimentation at three distances (5, 15, and 25 m) from the road, and found a significant difference in the height changes of the benchmarks at varying distances from the study roads. A hot-spot analysis was conducted using GIS 10.8, and the results indicated that a significant portion of the studied forest roads had very high erosion production and hot spots. The results of the hot-spot analysis indicated that 30.8%, 22.6%, 39.8%, and 14.5% of the study forest roads, Nazi, Tabarak, Bideleh, and Kohian roads, respectively, are identified as areas with very high erosion production and hot spots. These results highlight the need for effective management strategies to minimize the impact of erosion on road infrastructure and the surrounding environment. Overall, this study provides important insights into the soil erosion and sedimentation on forest roads, and the findings presented here can be used to inform future road construction and maintenance. Full article

Wildfires present a major global environmental issue, exacerbated by climate change. The Iranian Northern Zagros Forests, characterized by a Mediterranean climate, are particularly vulnerable to fires during hot, dry summers. This study investigates the impact of climate change on forest fires in these forests from 2006 to 2023. The analysis revealed significant year-to-year fluctuations, with notable fire occurrence in years 2007, 2010, 2021, and 2023. The largest burned area occurred in 2021, covering 2655.66 ha, while 2006 had the smallest burned area of 175.27 ha. Climate variables such as temperature, humidity, precipitation, wind speed, heat waves, and solar radiation were assessed for their effects on fire behavior. Strong correlations were found between higher average temperatures and larger burned areas, as well as between heat waves and increased fire frequency. Additionally, higher wind speeds were linked to larger burned areas, suggesting that increased wind speeds may enhance fire spread. Multiple linear regression models demonstrated high predictive accuracy, explaining 84% of the variance in burned areas and 69.6% in the variance in fire frequency. These findings document the growing wildfire risk in the Northern Zagros region due to climate change, highlighting the urgent need to integrate scientific research with policies to develop effective wildfire management strategies for sustainable forest management. Full article

Annually, the oak forests of the Zagros Mountains chains in western Iran and northeastern Iraq face recurring challenges posed by forest fires, particularly in the Kurdo–Zagrosian forests in western Iran and northeastern Iraq. Assessing fire susceptibility relies significantly on vegetation conditions. Integrating in situ data, Remote Sensing (RS) data, and Geographical Information Systems (GIS) integration presents a cost-effective and precise approach to capturing environmental conditions before, during, and after fire events, minimizing the need for extensive fieldwork. This study refines and applies the Zagros Grass Index (ZGI), a local vegetation index tailored to discern between grass-covered surfaces and tree canopies in Zagros forests, identifying the grass masses as the most flammable fuel type. Utilizing the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product as input from 2013 to 2022, the ZGI aims to mitigate the influence of tree canopies by isolating NDVI values solely attributable to grass cover. By incorporating phenological characteristics of forest trees and grass species, the ZGI outperforms NDVI in mapping grass-covered areas crucial for the study region’s fire susceptibility assessment. Results demonstrate a substantial overlap between ZGI-based maps and recorded fire occurrences, validating the efficacy of the index in fire susceptibility estimation. Full article

The Zagros forests in Iran are currently experiencing an exacerbation of climate-induced mortality, placing the Persian squirrel, a keystone species reliant on these ecosystems, in jeopardy. Addressing this imminent threat, our research employed a spatial prioritization methodology, integrating assessments of habitat suitability and mortality risk. Utilizing a weighted ensemble approach, incorporating the strengths of diverse models and expert rules, we discerned that approximately 62% of surveyed forests are at risk, with 7% classified as high risk and 17% as very high risk. Notably, 83% of the forests exhibited varying degrees of habitat suitability, with 11% and 12% demonstrating high and very high suitability, respectively. Employing a conservation prioritization framework, we systematically categorized habitats into priority classes, with 8%, 17%, 29%, and 46% assigned to very high, high, moderate, and low conservation priority classes, respectively. Significantly, areas classified as very high priority demand immediate restoration efforts due to ongoing mortality, while other priority classes underscore the importance of protection and prevention in unaffected habitats. Acknowledging the irreversible nature of current climatic conditions in the Zagros forests, our strategic emphasis aligns with conservation triage principles, prioritizing the preservation of intact habitats yet to succumb to irreversible mortality. Full article

Pollarding oak trees is a traditional silvopastoral technique practiced across wide areas of the northern Zagros mountains, a unique and vast semi-arid forest area with a strong cultural and ecological significance. So far, the effects of pollarding on tree structure in terms of DBH (diameter at breast height)~H (height) relationships within the typical pollarding cycle, which often lasts 4 years, has not been scientifically described. Here, we combine field inventories of DBH with H obtained from photogrammetric UAV flights for the first time to assess DBH~H relationships within this system. We conducted the research at six pollarded forest sites throughout the Northern Zagros. The sampling encompassed all three main species of coppice oak trees. In the case of multi-stem trees, we used the maximum DBH of each tree that formed a unique crown. A linear relationship between UAV and extracted H and the maximum DBH of pollarded trees explained a notable part of the variation in maximum DBH (R² = 0.56), and more complex and well-known nonlinear allometries were also evaluated, for which the accuracies were in the same range as the linear model. This relationship proved to be stable across oak species, and the pollarding stage had a notable effect on the DBH~H relationship. This finding is relevant for future attempts to inventory biomass using remote sensing approaches across larger areas in northern Zagros, as well as for general DBH estimations within stands dominated by pollarded, multi-stem coppice structures. Full article

The livelihood of many households and communities in the Central Zagros of Iran is strongly dependent on income from forests. While this has led to the widespread over-utilization of forests, poverty levels have remained high and rural development low. The objective of this study was to understand how households utilize forests and to what extent forests contribute to household income and alleviate poverty in order to develop strategies to raise families out of poverty and offer development perspectives to communities that avoid destructive forest utilization. To do so, semi-structured interviews were conducted in five rural communities, community poverty was quantified using several indices (e.g., the Census Ratio Index, Poverty Gap Index), the level of rural development was quantified using socio-economic indicators, and an inferential model was developed that combines household dependence on forests with the level of rural development to provide development perspectives. Local households earned income from nine livelihood strategies that involve forests. Forest-dependent strategies provided the second highest economic share (18.1%) of household income, averaging IRR 27.7 million (USD 657) annually, and moved 12% of households above the poverty line (76% still remained below). Without forest income, most indices of poverty decreased, income inequality increased by 11%, and poverty depth increased 1.54-fold. The low development index of most villages indicates that rural villagers are heavily dependent on forests to meet their livelihood. Our conceptual model indicates that communities should pursue different development strategies that consider whether households depend on forests to meet their livelihood or derive more supplemental income. Full article

The increase in environmental and human-related changes (e.g., increase in the carbon cycle flux of plants) has increased the dynamism of ecosystems. Examining fluctuations in net primary production (NPP) is very important in adopting correct strategies for ecosystem management. The current study explores the spatiotemporal variations in NPP and its association with agricultural droughts in Iran’s ecosystems over 20 years (2000–2020). Mann–Kendall and Sen’s slope methods in each pixel were used to track changes in trends. Drought upsets the terrestrial carbon cycle balance. In this study, Vegetation Health Index (VHI) used to assess drought that extracted from different bands of images satellite. Then, the relationship between NPP rates and agricultural droughts was investigated through running Pearson correlation. The results demonstrated that Iran’s annual share of carbon sequestration is 1.38 kg*C/m²/year. The highest carbon sequestration rate was recorded in Caspian Hyrcanian forests. In contrast, the lowest rate was observed in the Arabian Desert and East Sahero-Arabian xeric shrublands in southwestern Iran. Moreover, the highest photosynthesis variations were recorded in Arabian Desert and East Sahero-Arabian xeric shrublands and Tigris–Euphrates alluvial salt marsh, while the lowest changes were registered in Badghyz and Karabil. In total, 34.2% of the studied pixels showed a statistically significant rising or falling trend. Sen’s slope estimator demonstrated that the sharpest negative trend in carbon sequestration belonged to Caspian Hyrcanian mixed forests (−12.24 g*C/m²/year), while the sharpest positive trend was observed in Azerbaijan shrub desert and steppe (12.29 g*C/m²/year). The results of the Pearson correlation revealed significant correlations between NPP and VHI in different ecosystems with coefficients ranging from −0.93 to 0.95. The largest area with a positive correlation (33.97%) belonged to the Zagros Mountains forest steppe. Identification of areas with the greatest carbon sequestration changes could result in prioritizing varied ecosystems management for carbon sequestering. It can be also utilized in environmental planning such as scaling up ecosystem values or estimating current and past ecological capacity. Full article

Wildfire has significant impact on plant phenology. The plants’ phenological variables, derived from time series satellite data, can be monitored and the changes in satellite imagery may be used to identify the beginning, peak, and end of the growing season. This study investigated the use of remote sensing data and land surface phenology (LSP) parameters to evaluate the impacts of fire. The LSP parameters included the start of growing season (SOS), the length of the growing season (LOS), the end of the growing season (EOS), maximum greenness of the season (Gmax), and minimum greenery in the season (Gmin) in the fire-impacted, semiarid oak forests of Iran. These LSP parameters were extracted from multitemporal normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI2) data, acquired from MODIS sensor images in Zagros of the Ilam province in western Iran. By extracting LSP indices from the NDVI and EVI2 data, the indices were compared between burned forest areas, areas surrounding the burned forests, and unburned areas and for timesteps representing pre-fire, fire (i.e., year of fire), and post-fire (i.e., 2 years) conditions. It was found that for the burned area, there were significant differences in Gmax and the day that Gmax occurred. Furthermore, there was also a significant difference in Gmin between the pre- and post-fire conditions when NDVI was used and a significant difference between Gmax when EVI2 was used. The results also showed that in both time series there was a significant difference between the burned and control area in terms of Gmax. In general, the results showed that the fire had a negative effect on LSP, but in the two years after the fire, there were signs of forest restoration. This study provides necessary information to inform forest and resource conservation and restoration programs. Full article

The present study models the effect of climate change on the distribution of Persian oak (Quercus brantii Lindl.) in the Zagros forests, located in the west of Iran. The modeling is conducted under the current and future climatic conditions by fitting the machine learning method of the Bayesian additive regression tree (BART). For the anticipation of the potential habitats for the Persian oak, two general circulation models (GCMs) of CCSM4 and HADGEM2-ES under the representative concentration pathways (RCPs) of 2.6 and 8.5 for 2050 and 2070 are used. The mean temperature (MT) of the wettest quarter (bio8), solar radiation, slope and precipitation of the wettest month (bio13) are respectively reported as the most important variables in the modeling. The results indicate that the suitable habitat of Persian oak will significantly decrease in the future under both climate change scenarios as much as 75.06% by 2070. The proposed study brings insight into the current condition and further projects the future conditions of the local forests for proper management and protection of endangered ecosystems. Full article

Forests remain an important resource in Iran, as most of the livelihood activities of local communities, especially in the semi-arid environment of the Zagros forests, are dependent on forest resources. The aim of this study was to identify the type and extent of forest dependency. Semi-structured interviews and questionnaires were used to collect data from 170 households in Central Zagros. Results show that using firewood for fuel and non-fuel uses, harvesting edible and medicinal plants, agriculture and horticulture, and livestock grazing were the main forest livelihood activities undertaken by the households in the study area. On average, each household harvested 18.08 cubic meters of oak per year for water heating (bathing), baking bread, heating, cooking, heating milk and buttermilk, agricultural tools, house building, warehouses and shelters, fencing, branches for livestock, charcoal and harvesting firewood for sale. Of rural households, 72% used edible plants, and 86% used medicinal plants. Age, job, residence status, number of livestock, crop farming and household size were found to be correlated with forest dependency. Findings from this study contribute broadly to an integrated understanding of the bio-human dimensions of forest ecosystems, with specific reference to the study area. Full article

Drought has serious effects on forests, especially semi-arid and arid forests, around the world. Zagros Forest in Iran has been severely affected by drought, which has led to the decline of the most common tree species, Persian oak (Quercus brantii). The objective of this study was to determine the effects of drought on the anatomical structure of Persian oak. Three healthy and three declined trees were sampled from each of two forest sites in Ilam Forest. Discs were cut at breast height, and three sapwood blocks were taken near the bark of each tree for sectioning. The anatomical characteristics measured included fiber length (FL), fiber wall thickness (FWT), number of axial parenchymal cells (NPC), ray number (RN), ray width (RW), and number of calcium oxalate crystals. Differences between healthy and declined trees were observed in the abundance of NPC and in RN, FL, and FWT, while no differences occurred in the number of oxalate crystals. The decline had uncertain effects on the FL of trees from sites A and B, which showed values of 700.5 and 837.3 μm compared with 592.7 and 919.6 μm in healthy trees. However, the decline resulted in an increase in the FWT of trees from sites A and B (9.33 and 11.53 μm) compared with healthy trees (5.23 and 9.56 μm). NPC, RN, and RW also increased in declined individuals from sites A and B (28.40 and 28.40 mm⁻¹; 41.06 and 48.60 mm⁻¹; 18.60 and 23.20 μm, respectively) compared with healthy trees (20.50 and 19.63 mm⁻²; 31.60 and 28.30 mm⁻²; 17.93 and 15.30 μm, respectively). Thus, drought caused measurable changes in the anatomical characteristics of declined trees compared with healthy trees. Full article

Forest nationalization policies in developing countries have often led to a reduction in local forest ownership rights and short- or long-term exploitative behaviors of stakeholders. The purpose of this research is to quantify the effect of Iran’s Forest Nationalization Law (FNL) in a part of Zagros Forest over a 68-year time period (1955–2022) using 1955 historical aerial photos, 1968 Corona spy satellite photography, and classification of multi-temporal Landsat satellite images. A past classification change detection technique was used to identify the extent and the pattern of land use changes in time. For this purpose, six periods were defined, to cover the time before and after the implementation of FNL. A 0.27% deforestation trend was identified over the period after the FNL. Dense and open forested area has decreased from 7175.62 ha and 68,927.46 ha in 1955 to 5664.26 ha and 59,223.38 ha in 2022. The FNL brought decisive changes in the legal and forest management systems at the state level, mainly by giving their ownership to the state. Accordingly, the FNL and the related conservation plans have not fully succeeded in protecting, rehabilitating, recovering, and developing the sparse Zagros Forest ecosystems, as their most important goals. Full article

Monitoring tree decline in arid and semi-arid zones requires methods that can provide up-to-date and accurate information on the health status of the trees at single-tree and sample plot levels. Unmanned Aerial Vehicles (UAVs) are considered as cost-effective and efficient tools to study tree structure and health at small scale, on which detecting and delineating tree crowns is the first step to extracting varied subsequent information. However, one of the major challenges in broadleaved tree cover is still detecting and delineating tree crowns in images. The frequent dominance of coppice structure in degraded semi-arid vegetation exacerbates this problem. Here, we present a new method based on edge detection for delineating tree crowns based on the features of oak trees in semi-arid coppice structures. The decline severity in individual stands can be analyzed by extracting relevant information such as texture from the crown area. Although the method presented in this study is not fully automated, it returned high performances including an F-score = 0.91. Associating the texture indices calculated in the canopy area with the phenotypic decline index suggested higher correlations of the GLCM texture indices with tree decline at the tree level and hence a high potential to be used for subsequent remote-sensing-assisted tree decline studies. Full article