Search Results (327)

The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of vegetation to a mulch layer) in 2020 and targeted herbicide treatment of woody vegetation, with the aim of reducing vegetation height by encouraging a native herbaceous groundcover beneath the transmission lines. We measured vegetation structure (cover and height) and composition (species presence in 15 × 2 m plots), at 12 transects, 90 m in length on the transmission line corridor, to determine if management goals were being achieved and to determine how the vegetation and fire hazard (based on the overall fuel hazard assessment method) varied among the treated corridor, the forest edge environment, and the natural forest. The results showed that vegetation structure and composition in the treated zones had been modified to a state where herbaceous plant species were dominant; there was a significantly (p < 0.05) higher native grass cover and cover of herbs, sedges, and ferns in the treated zones, and a lower cover of trees and tall woody plants (>1 m in height) in these areas. For example, mean native grass cover and the cover of herbs and sedges in the treated areas was 10.2 and 2.8 times higher, respectively, than in the natural forest. The changes in the vegetation structure (particularly removal of tall woody vegetation) resulted in a lower overall fuel hazard in the treated zones, relative to the edge zones and natural forest. The overall fuel hazard was classified as ‘high’ in 83% of the transects in the treated areas, but it was classified as ‘extreme’ in 75% of the transects in the adjacent forest zone. Importantly, there were few introduced species recorded. The results suggest that fuel management has been successful in reducing wildfire risk in the transmission corridor. Temporal monitoring is recommended to determine the frequency of ongoing fuel management. Full article

Biochar is an amendment that can enhance both soil fertility and sequester carbon. However, its historical applications continue to be underexplored. In this overview, we investigate the formiguer method of burning woody biomass to create agricultural biochar for use as fertilizer in Catalonia, Spain, within the context of historical biochar use. A literature review targeted searches of scholarly databases to compare the formiguer method to Amazonian terra preta and other traditional biochar use. We identified sources covering biochar properties, soil impacts, and historical agricultural practices within the Iberian Peninsula and briefly described the main methods or treatments used during this process. Past research demonstrates that the formiguer method, which involves pyrolytic combustion of biomass within soil mounds, improves microbial activity, increases soil phosphorus and potassium availability from soil structure, and leads to long-term carbon stabilization, even though it can result in short-term decreases in soil organic carbon and nitrogen losses. Despite being abandoned in Europe with the rise of chemical fertilizers, the use of formiguers exemplifies a decentralized approach to nutrient and agroecosystem management. The literature highlights the relevance that these traditional biochar practices can have in informing modern soil management and sustainable agricultural strategies. Understanding the formiguer can offer critical insights to optimize contemporary biochar applications and historical techniques into future sustainability frameworks. Full article

This study investigates the composition, abundance, and seasonal variability of airborne pollen in Siirt, a transitional region between the Irano-Turanian and Mediterranean phytogeographical zones in southeastern Türkiye. The main objective was to assess pollen diversity and its relationship with meteorological parameters over a two-year period (2022–2023). Airborne pollen was collected using a Hirst-type volumetric pollen and spore trap; a total of 18,666 pollen grains/m³ belonging to 37 taxa were identified. Of these, 70.67% originated from woody taxa and 29.33% from herbaceous taxa. Peak concentrations occurred in April, with the lowest levels in December. The dominant taxa, all exceeding 1% of the total, were Pinaceae (31.00%); Cupressaceae/Taxaceae (27.79%); Poaceae (18.42%); Moraceae (4.23%); Amaranthaceae (2.42%); Urticaceae (2.13%); Quercus (1.55%); Fabaceae (1.29%); and Rumex (1.02%). Spearman’s correlation analysis revealed significant relationships between daily pollen concentrations and meteorological variables such as temperature, humidity, precipitation, and wind speed. These findings highlight that both climatic conditions and the surrounding vegetation, shaped by regional land cover, play a crucial role in determining pollen dynamics. In conclusion, this study provides the first aerobiological baseline for Siirt and contributes valuable data for allergy-risk forecasting and long-term ecological monitoring in southeastern Türkiye. Full article

This study investigates the anthropogenic transformation of small- and medium-sized river basins within the Caspian Sea catchment. The basins of seven rivers—Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan—were selected as key study areas. For both the broader Caspian region, particularly its southwestern sector, and the selected study sites, trends in land cover types were analyzed, natural resource use practices were assessed, and population density dynamics were examined. Furthermore, a range of indices were calculated to quantify the degree of anthropogenic transformation, including the coefficient of anthropogenic transformation, the land degradation index, the urbanity index, the degree of anthropogenic transformation, coefficients of absolute and relative tension of the ecological and economic balance, and the natural protection coefficient. The study was conducted using geoinformation research methods and sets of geodata databases—the global LandScan population density database, the GHS Population Grid database, the ESRI land cover type dynamics database, and OpenStreetMap (OSM) data. The analysis was performed using the geoinformation programs QGIS and ArcGIS, and a large amount of literary and statistical data was additionally analyzed. It is shown that within the studied region, there has been a decrease in the number and density of the population, as a result of which the territories of river basins are experiencing an increasing anthropogenic impact, the woody type of land cover is decreasing, and the agricultural type is increasing. The most anthropogenically transformed river basins are Karachay, Haraz, and Gorgan. Full article

Woody plant encroachment (WPE) is transforming grasslands globally, yet accurately mapping this process remains challenging. State-funded, publicly available high-resolution aerial imagery offers a potential solution, including the USDA’s National Agriculture Imagery Program (NAIP) and NSF’s National Ecological Observatory Network (NEON) Aerial Observation Platform (AOP). We evaluated the accuracy of land cover classification using NAIP, NEON, and both sources combined. We compared two machine learning models—support vector machines and random forests—implemented in R using large training and evaluation data sets. Our study site, Konza Prairie Biological Station, is a long-term experiment in which variable fire and grazing have created mosaics of herbaceous plants, shrubs, deciduous trees, and evergreen trees (Juniperus virginiana). All models achieved high overall accuracy (>90%), with NEON slightly outperforming NAIP. NAIP underperformed in detecting evergreen trees (52–78% vs. 83–86% accuracy with NEON). NEON models relied on LiDAR-based canopy height data, whereas NAIP relied on multispectral bands. Combining data from both platforms yielded the best results, with 97.7% overall accuracy. Vegetation indices contributed little to model accuracy, including NDVI (normalized digital vegetation index) and EVI (enhanced vegetation index). Both machine learning methods achieved similar accuracy. Our results demonstrate that free, high-resolution imagery and open-source tools can enable accurate, high-resolution, landscape-scale WPE monitoring. Broader adoption of such approaches could substantially improve the monitoring and management of grassland biodiversity, ecosystem function, ecosystem services, and environmental resilience. Full article

Riparian forests are important for maintaining aquatic biodiversity, yet they face increasing pressure from logging activities. This study assessed the functional diversity of Ephemeroptera, Plecoptera, and Trichoptera (EPT) in 30 Amazonian first-order streams across three riparian forests: pristine, selectively logged, and conventionally logged. We evaluated four habitat attributes linked to ecosystem functioning (canopy cover, water temperature, sediment organic matter, and small woody debris) and calculated two indices of functional diversity: richness and divergence. Functional diversity was highest in pristine streams, intermediate in selectively logged streams, and lowest in conventionally logged streams. Functional richness and divergence declined significantly in conventionally logged forests, indicating a loss of ecological traits and potential reductions in ecosystem functions. We also observed that canopy cover, sediment organic matter, and woody debris were positively associated with EPT functional diversity, while water temperature had a negative association. These findings highlight that conventional logging leads to the functional homogenization of aquatic insect assemblages, compromising key ecological processes. Selective logging that maintains riparian buffers may preserve functional diversity, even though these differences may be influenced by site-specific environmental conditions. Our results underscore the importance of conserving riparian integrity to sustain the resilience and functioning of tropical stream ecosystems in logged landscapes. Full article

Soil erosion and surface runoff on forest road slopes are major environmental concerns, especially in harvested areas, making effective mitigation strategies essential for sustainable forest management. The study compared the effectiveness of three selected woody species on forest road slopes as a possible mitigating action for runoff and soil erosion in harvested sites. Plots measuring 2 m × 3 m were set up with three species—alder (Alnus glutinosa (L.) Gaertn.), medlar (Mespilus germanica L.) and hawthorn (Crataegus monogyna Jacq.)—on the slopes of forest roads. Within each plot, root abundance, root density, canopy percentage, canopy height, herbaceous cover percentage, and selected soil characteristics were measured and analyzed. Root frequency and Root Area Ratio (the ratio between the area occupied by roots in a unit area of soil) measurements were conducted by excavating 50 × 50 cm soil profiles at a 10-cm distance from the base of each plant in the four cardinal directions. The highest root abundance and RAR values were found in hawthorn, followed by alder and medlar in both cases. The same order of magnitude was evidenced in runoff (255.42 mL m⁻² in hawthorn followed by 176.81 mL m⁻² in alder and 67.36 mL m⁻² in medlar) and the reverse order in terms of soil erosion (8.23 g m⁻² in hawthorn compared to 22.5 g m⁻² in alder and 50.24 g m⁻² in medlar). The results of the study confirm that using plant species with dense and deep roots, especially hawthorn, significantly reduces runoff and erosion, offering a nature-based solution for sustainable forest road management. These results highlight the need for further research under diverse ecological and soil conditions to optimize species selection and improve erosion mitigation strategies. Full article

Pedicularis hallaisanensis is a strictly biennial, hemiparasitic herb endemic to Republic of Korea and listed as an endangered species. Its populations are limited to high-altitude habitats, with recent surveys confirming survival only in Gayasan. This study aimed to assess the population size and ecological traits of P. hallaisanensis to inform conservation strategies. We established 23 quadrats at 1400–1410 m above sea level and collected microhabitat data (air temperature, soil moisture, electroconductivity, vegetation cover, and species richness) from 2022 to 2024. Flora composition and pollinator species were surveyed, with bumblebees (Bombus ignitus, B. hypocrita sapporoensis) identified as the most frequent pollinators. General linear mixed models and Pearson’s correlation analysis showed a strong positive relationship between species richness and population size and between vegetation cover and stem height. The study area’s average temperature was 6.3 °C below Republic of Korea’s national average, suggesting that climate change could disrupt the microclimatic conditions necessary for this species’ survival. The findings highlight the importance of maintaining plant diversity and controlling invasive woody species to sustain P. hallaisanensis populations. Targeted conservation measures, including habitat management and ex situ propagation, are recommended to safeguard this vulnerable species. Full article

Forest fires are a critical ecological disturbance that significantly impact vegetation dynamics, biodiversity, and ecosystem services. This study investigates the impacts of forest fires in the Ghalahmah Mountains, Saudi Arabia, using remote sensing data and fire impact models to assess fire severity, environmental drivers, and post-fire vegetation recovery. The research integrates Landsat 8, Sentinel-2, and DEM data to analyze the spatial extent and severity of a 2020 fire event using the Relativized Burn Ratio (RBR). Results reveal that high-severity burns covered 49.9% of the affected area, with pre-fire vegetation density (NDVI) and moisture (NDWI) identified as key drivers of fire severity through correlation analysis and Random Forest regression. Post-fire vegetation recovery, assessed using NDVI trends from 2021 to 2024, demonstrated varying recovery rates across vegetation types. Medium NDVI areas (0.2–0.3) recovered fastest, with 134.46 hectares exceeding pre-fire conditions by 2024, while high NDVI areas (>0.3) exhibited slower recovery, with 26.55 hectares still recovering. These findings underscore the resilience of grasslands and shrubs compared to dense woody vegetation, which remains vulnerable to high-severity fires. The study advances fire ecology research by combining multi-source remote sensing data and machine learning techniques to provide a comprehensive understanding of fire impacts and recovery processes in semi-arid mountainous regions. The results suggest valuable insights for sustainable land management and conservation, emphasizing the need for targeted fuel management and protection of ecologically sensitive areas. This research contributes to the broader understanding of fire ecology and supports efforts to post-fire management. Full article

Wood ash, a byproduct of woody biomass power generation, has potential as an alternative K fertilizer due to its high K content and pH-raising properties. However, concerns remain about heavy metal contaminants like Cr and the limited understanding of element dynamics in soil–solution–crop systems after wood ash’s application. This study examined the effects of 1% (w/w) wood ash on element dynamics and komatsuna (Brassica rapa var. perviridis) uptake in low-K soil through a pot experiment. XRD was used to analyze mineral composition, SEM-EDS to observe surface and elemental properties, and XANES to examine Cr speciation in wood ash. Soil solution analysis covered macro- and micronutrients, heavy metals, anions, pH, and DOC, while crop element concentrations and aboveground dry weight were also quantified. The chemical speciation of Cu and Cr in a soil solution was modeled using Visual MINTEQ. Wood ash significantly increased K concentrations (from 17 mg/L to 650 mg/L) in the soil solution, along with Ca, Mg, P, and Mo, while reducing Ni, Mn, Zn, and Cd levels. Komatsuna K uptake surged from 123 mg/kg to 559 mg/kg, leading to a 3.31-fold biomass increase. Notably, the Cd concentration in the crops dropped significantly from 0.709 to 0.057 mg/kg, well below the Codex standard of 0.2 mg/kg. Although Cu and Cr concentrations rose in the soil solution, crop uptake remained low due to >99% complexation with fulvic acid, as confirmed by Visual MINTEQ modeling. This study confirms that wood ash is an effective K fertilizer, but emphasizes the need for risk mitigation strategies to ensure safe and sustainable agricultural application. Full article

Small landscape elements are critical in ecological systems, encompassing vegetated and non-vegetated features. As vegetated elements, hedgerows contribute significantly to biodiversity conservation, erosion protection, and wind speed reduction within agroecosystems. This study focuses on the semi-automatic extraction of hedgerows by applying the Object-Based Image Analysis (OBIA) approach to two multispectral satellite datasets. Multitemporal image data from PlanetScope and Copernicus Sentinel-2 have been used to test the applicability of the proposed approach for detailed land cover mapping, with an emphasis on extracting Small Woody Elements. This study demonstrates significant results in classifying and extracting hedgerows, a smaller landscape element, from both Sentinel-2 and PlanetScope images. A good overall accuracy (OA) was obtained using PlanetScope data (OA = 95%) and Sentinel-2 data (OA = 85%), despite the coarser resolution of the latter. This will undoubtedly demonstrate the effectiveness of the OBIA approach in leveraging freely available image data for detailed land cover mapping, particularly in identifying and classifying hedgerows, thus supporting biodiversity conservation and ecological infrastructure enhancement. Full article

Afforestation and reforestation (A/R) of non-agricultural and marginal saline lands by promoting fast-growing and salinity-tolerant woody species are crucial strategies to overcome land degradation and vegetation cover scarcity. To obtain basic information before using Populus alba clones in such degraded areas, morpho-physiological and cellular responses to salt stress were investigated. The experiment was conducted in a nursery where cuttings of three P. alba clones (MA-104, MA-195 and OG) were grown for 90 days in 100 mM NaCl versus a non-saline control. A global approach highlighting clonal differences in terms of dry mass production and plant physiological performance was achieved by comparing plant water status, gas exchange, ionic selectivity, osmotic adjustment and chloroplast ultrastructure under the two treatments. Dry mass production and eco-physiological processes were reduced in response to salt stress, with substantial clonal variation. Clone MA-104 exhibited salinity-tolerant behaviour in contrast to clone MA-195 and OG’s medium or sensitive behaviour towards the stress. Tolerance mechanisms may be attributed to enhanced stomatal control and osmotic adjustment, thereby enabling the maintenance of turgor in plants subjected to salt stress. The chloroplast ultrastructure also showed modifications that are often involved in adaptation to salinity stress. Full article

Wetland ecosystems are sensitive to climate variation, yet tracking vegetation type and structure changes through time remains a challenge. This study examines how Landsat-derived vegetation indices (NDVI and EVI) correspond with lidar-derived canopy height model (CHM) changes from 2000 to 2018 across the wetland landscape of the Peace–Athabasca Delta (PAD), Canada. By comparing CHM change and NDVI and EVI trends across woody and herbaceous land covers, this study fills a gap in understanding long-term vegetation responses in northern wetlands. Findings show that ~35% of the study area experienced canopy growth, while 2% saw a reduction in height. CHM change revealed 11% ecotonal expansion, where shrub and treed swamps encroached on meadow and marsh areas. NDVI and EVI correlated significantly (p < 0.001) with CHM, particularly in shrub swamps (r² = 0.40, 0.35) and upland forests (NDVI r² = 0.37). However, EVI trends aligned more strongly with canopy expansion, while NDVI captured mature tree height growth and wetland drying, indicated by rising land surface temperatures (LST). These results highlight the contrasting responses of NDVI and EVI—NDVI being more sensitive to moisture-related changes such as wetland drying, and EVI aligning more closely with canopy structural changes—emphasizing the value of combining lidar and satellite indices to monitor wetland ecosystems in a warming climate. Full article

We evaluated the effects of different fire regimes on the ground-ant community from a savanna (Cerrado) reserve in southern Brazil, where a process of woody encroachment has been taking place. Ants are a dominant faunal group in tropical savannas. Over ~8 years, experimental plots were protected from fire or burned every one or two years. An additional treatment (adaptive) included annual fires and a reduction in woody biomass to increase fuel loads. Ants were collected prior to the first prescribed fire and again four times. We expected that fire would increase the diversity and overall abundance of open-savanna ant specialists, depending on the extent of changes in vegetation structure. Changes in litter depth, grass cover and bare ground in burned plots were most evident 88 months after the first fire and did not differ between fire regimes. Similarly, overall ant species richness and occurrence neither differed between fire treatments nor from the control. However, burned plots showed a significant increase in the richness and occurrence of open savanna specialists, and a decrease in species most typical of dense savanna or dry forests. As ant responses did not differ between the annual, biennial, and adaptive treatments, we suggest that a fire return interval of two years is enough for reverting the loss of open savanna ant specialists in areas that have been protected from fire for decades. Full article

The precise spatially explicit data on land cover and land use changes is one of the essential variables for enhancing the quantification of greenhouse gas emissions and removals, which is relevant for meeting the goal of the European economy and society to become climate-neutral by 2050. The accuracy of the machine learning models trained on remote-sensed data suffers from a lack of reliable training datasets and they are often site-specific. Therefore, in this study, we proposed a method that integrates the bi-temporal analysis of the combination of spectral indices that detects the potential changes, which then serve as reference data for the Random Forest classifier. In addition, we examined the transferability of the pre-trained model over time, which is an important aspect from the operational point of view and may significantly reduce the time required for the preparation of reliable and accurate training data. Two types of vegetation losses were identified: woody coverage converted to non-woody vegetation, and vegetated areas converted to sealed surfaces or bare soil. The vegetation losses were detected annually over the period 2018–2021 with an overall accuracy (OA) above 0.97 and a Kappa coefficient of 0.95 for all time intervals in the study regions in Poland and Norway. Additionally, the pre-trained model’s temporal transferability revealed an improvement of the OA by 5 percentage points and the macroF1-Score value by 12 percentage points compared to the original model. Full article