Compared with disturbance maps produced at annual or multi-year time steps, monthly mapping of forest harvesting can provide more temporal details needed for studying the socio-economic drivers ...(e.g., differentiating salvage logging and slash-and-burn from other timber harvesting) of harvesting and characterizing the associated intra-annual carbon and hydrological dynamics. Frequent cloud cover limits the application of optical remote sensing in timely mapping of forest changes. The freely available Sentinel-1 synthetic aperture radar (SAR) sensor provides an unprecedented opportunity to achieve more frequent mapping of forest harvesting than ever before (i.e., at monthly interval). The unique landscape pattern of forest harvesting from Sentienl-1 data (i.e., how a harvested patch contrasts to surrounding intact forests) holds critical information for harvesting mapping but have not been fully explored. In this study, we propose a deep learning-based (i.e., U-Net) approach using the landscape pattern from Sentinel-1 data to produce monthly maps of forest harvesting in two deforestation hotspots - California, USA and Rondônia, Brazil – for as long as three years. Our results show that (1) our proposed approach is reliable (mean F1 scores (the geometric mean of user's and producer's accuracies) 0.74–0.78; mean IoU (the area of intersection over union between the prediction part and target part) 0.59–0.65) for monthly forest harvesting mapping with Sentinel-1 data, outperforming the traditional object-based approach (0.38–0.43 in IoU). The varying harvesting pattern from Sentinel-1 data can be recognized by the U-Net bottleneck block as whole entities, which is the key advantage of our proposed approach; (2) multi-temporal SAR filtering is helpful for improving the accuracies of our proposed approach (increased F1 and IoU for 0.04 and 0.06, respectively); (3) our proposed model can be trained using samples collected during a particular time period over one location and be fine-tuned using sparse local samples from a new area to achieve optimal performance, and hence can greatly reduce training data collection effort when applied to new study sites; (4) forest harvesting maps produced using our approach revealed substantial variations in monthly harvesting activities: in Rondônia, most of the forest harvest occurred in July/August (the dry season) and about 14% of the dry season harvesting were followed by fires (i.e., slash-and-burn); in California, the rates of forest harvesting were relatively stable, but abnormally high values could occur due to salvage logging after big fires. Our novel approach for mapping forest harvesting at monthly interval represents an important step towards timely monitoring of forest harvesting and assisting stakeholders in developing sustainable strategy of forest management, especially for regions with frequent cloud cover.
•A novel approach for monthly forest harvesting mapping from Sentinle-1 data.•A deep learning-based approach using the landscape pattern from Sentinel-1 data.•The proposed approach with high transferability between two study sites.•Implemented in the cloud computing environment as a full pipeline.•Produced forest harvesting maps revealed dynamics in monthly harvesting activities.
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•WEPP modeling was conducted on paired, nested watersheds with forest managements.•WEPP-simulated daily streamflow was in close agreement with observed values.•WEPP captured water and ...sediment yields and changes due to harvesting practices.•Results demonstrated WEPP’s potential as a decision-aid tool in forest management.
The Water Erosion Prediction Project (WEPP) model was applied to seven paired, nested watersheds within the Mica Creek Experimental Watershed located in northern Idaho, USA. The goal was to evaluate the ability of WEPP to simulate the direct and cumulative effects of clear-cutting and partial-cutting (50% canopy removal) on water and sediment yield. WEPP was modified to better represent changes in the Leaf Area Index during post-harvest forest vegetative recovery. Good agreement between simulated and observed streamflow was achieved with minimal to no calibration over a 16-year (1992–2007) period. For the seven watersheds and the entire study period, the overall Nash-Sutcliffe Efficiency (NSE), Kling-Gupta efficiency (KGE), and deviation of runoff volume (DV) between observed and simulated daily streamflow ranged 0.58–0.71, 0.67–0.81, and −4% to 9%, respectively. Good agreement between predicted and observed suspended sediment yield was achieved through the calibration of a single channel critical shear stress parameter. For sediment yield, NSE, KGE, and DV ranged 0.62–0.97, 0.43–0.97, and −2% to 2%, respectively, for the calibration period, and 0.61–0.93, 0.42–0.95, and −24% to 13%, respectively, for the period of model performance assessment. Regression analysis of observed- and WEPP-simulated increase in water and sediment yield following clear-cut treatment was similar; however, the WEPP-simulated increase was lower compared to observations particularly from the partial-cut watershed. The variability in the critical shear parameter for different stream channels in the study watersheds was directly related to the observed mean particle size on the stream bed and suggests that applications of the WEPP model in ungauged basins could potentially set the critical shear parameter based on particle size. Overall, the simulated results demonstrate the potential of WEPP as a modeling tool for forestland watershed management, particularly for estimating the effects of forest harvest on hydrograph fluctuations and consequently, stream sediment transport.
The role of natural (non-plantation) production forests is increasingly recognized in conservation of forest biodiversity globally. Government and other forest stakeholders in Nepal are, however, ...still reluctant to promote active management of production forests for fear of negative impacts on forest biodiversity. Moreover, Nepal's government is converting production forests into protected areas thus restricting the area available for multiple uses. To assess the implications of forest management practices on forest biodiversity at landscape level, we compared the richness and composition of tree species among regularly harvested community forests, irregularly harvested community forests, protected area and national forests in sub-tropical forested landscape of Nepal using tree species inventory and assessment of key environmental variables. Results showed that regularly harvested community forests could be effective in supporting tree species richness and composition compared to other management regimes. Results supported the hypothesis that high forest disturbance and no disturbance do not support tree species diversity and composition. In addition, this study found that regularly managed community forests also protect ecologically important and vulnerable tree species. Some possible explanations for the better performance of these community forests could be tenure security, frequency and regularity of silvicultural operations and sensitivity of forest users to the ecological aspects of forest management. Our study reaffirmed the need for active forest management at the local level to contribute to global conservation initiatives such as sustainable forest management, reducing emissions from deforestation and forest degradation in developing countries (REDD+) and biodiversity conservation. Better compliance with forest management plans and capacity development of local forestry stakeholders in forest management operations are suggested for managing forests outside protected areas that is, in national and community forests.
•Active management of natural production forests is beneficial to tree species richness and composition.•High forest disturbances and no disturbances both do not support tree species richness.•Regularly harvested community forests found more effective in supporting tree species richness.•Sensitivity of local users plays critical role to maintain biodiversity outside protected areas.•Capacity development of stakeholders is crucial to materialise multi-functionality of the natural forests in Nepal.
•A reliable simulated annealing for optimal stand-level forest harevesting schedule.•Harvesting ages and planting density were introduced as control variables.•Comparison with a reliable method for a ...fixed-ages model assured the reliability.•One neighborhood search method was less robust than other two methods.•Additional control variables virtually reduced the dimensionality.
Identifying optimal harvesting (thinning and clearcutting) schedule for a forest stand (stand-level) is of great importance to forest managers and researchers. However, providing highly reliable optimal harvesting schedules still requires considerable computation time. This study aimed to develop a simulated-annealing-based method to provide a highly reliable optimal schedule for harvesting in a short time. In practice, the optimal number of harvesting events in a rotation may not be large. Therefore, 1) treating harvesting ages as well as the thinning intensity as control variables, and 2) searching the optimal number of thinning events iteratively, the dimension of the scheduling problem was virtually reduced. The method was developed through a comparison with a reliable method for a model with fixed harvesting ages. Three candidate neighborhood methods were developed and compared with each other. One neighborhood method was less robust than the other two methods. We further developed a method to optimize the planting density simultaneously with the harvesting schedule. Introduction of planting density as a control variable reduced computation time by decreasing the optimal number of harvesting for several cases. The developed method provided optimal schedules with much less time than the previous method for most cases.
This study evaluated the effectiveness of Sentinel-2 (S2) as a tool for early detection and estimation of forest harvesting in the Piemonte Region, which can be used by the regional forest ...administration. The priority was the detection, at the regional scale, of annual forest cover changes with the following goals: i) mapping of irregular (in respect of the regional Forestry Regulation) forest cuts; ii) quantification of the intensity of the silvicultural interventions. Results are expected to support forest police controls. The proposed procedure is based on a supervised classification approach based on Random Forest algorithm. Accuracy of harvested areas detection proved to be high (overall accuracy 98%). Characterization of the occurred forest cuts was obtained computingthe local coefficient of variationof the normalized difference vegetation index (NDVI) after harvesting, that showed to be a good predictor of forest harvesting intensity.
To explore the carbon sequestration potential of hardwood forests in the eastern United States, the forest vegetation simulator (FVS) and life cycle assessment (LCA) were integrated to analyze the ...forest carbon dynamics for the four subregions of the eastern United States: northeast (NE), mid-Atlantic (MA), southeast (SE), and north central (NC). This study quantitatively assessed current forest management practices for timber production and their associated life-cycle environmental impacts. The system boundary was selected to be consistent with the A1 module (extraction and upstream production) required by an Environmental Product Declaration (EPD) for wood products. The results indicate that uneven-aged (UA) forest management yields higher carbon stocks and growth than even-aged (EA) management across all subregions. In contrast, clearcutting under EA management results in higher carbon removal. It was found that fuel consumption-related greenhouse gas (GHG) emissions for manual and mechanized harvesting systems for both management types ranged between 9.13 and 12.15 kg of CO2 equivalent per cubic meter (kg CO2e/m3), with an average of 11 kg CO2e/m3 of hardwood timber harvested across all subregions. It is estimated that 63–187 megajoules (MJ) of energy is needed to produce 1 m3 of hardwood sawlogs. The extraction and loading processes contributed more to the total GHG emissions than the felling and processing within the system boundary. The study concludes that UA management led to higher forest carbon and net carbon balance (excluding carbon stock) compared to EA management in the eastern U.S. hardwood forests. Forest management strategies should be determined based on the ecological goal of increasing forest carbon stock and the economic goal of maximizing revenue from the timber market. The findings of this study have implications for policymakers and forest managers in mitigating climate change and carbon sequestration through sustainable forest management for timber production.
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•LCA was integrated with FVS to analyze the carbon sequestration potential of hardwood forests in the eastern United States.•GHG emissions from manual and mechanized harvesting systems ranged from 9.13 to 12.15 kg CO2e/m3.•Uneven-aged management resulted in a forest carbon balance of 7.72 kg/m2 and a net carbon balance of 1.69 kg/m2 for the 9.99 × 1011 m2 hardwood forests in the eastern United States annually.•Even-aged management yielded a carbon balance of 6.20 kg/m2 and a net carbon balance of 0.91 kg/m2 for the 9.99 × 1011 m2 hardwood forests in the eastern United States annually.•The Fire and Fuels Extension of FVS did not account for soil carbon, encompassing both dead tree roots and live tree fine roots.
Globally, carbon‐rich mangrove forests are deforested and degraded due to land‐use and land‐cover change (LULCC). The impact of mangrove deforestation on carbon emissions has been reported on a ...global scale; however, uncertainty remains at subnational scales due to geographical variability and field data limitations. We present an assessment of blue carbon storage at five mangrove sites across West Papua Province, Indonesia, a region that supports 10% of the world's mangrove area. The sites are representative of contrasting hydrogeomorphic settings and also capture change over a 25‐years LULCC chronosequence. Field‐based assessments were conducted across 255 plots covering undisturbed and LULCC‐affected mangroves (0‐, 5‐, 10‐, 15‐ and 25‐year‐old post‐harvest or regenerating forests as well as 15‐year‐old aquaculture ponds). Undisturbed mangroves stored total ecosystem carbon stocks of 182–2,730 (mean ± SD: 1,087 ± 584) Mg C/ha, with the large variation driven by hydrogeomorphic settings. The highest carbon stocks were found in estuarine interior (EI) mangroves, followed by open coast interior, open coast fringe and EI forests. Forest harvesting did not significantly affect soil carbon stocks, despite an elevated dead wood density relative to undisturbed forests, but it did remove nearly all live biomass. Aquaculture conversion removed 60% of soil carbon stock and 85% of live biomass carbon stock, relative to reference sites. By contrast, mangroves left to regenerate for more than 25 years reached the same level of biomass carbon compared to undisturbed forests, with annual biomass accumulation rates of 3.6 ± 1.1 Mg C ha−1 year−1. This study shows that hydrogeomorphic setting controls natural dynamics of mangrove blue carbon stocks, while long‐term land‐use changes affect carbon loss and gain to a substantial degree. Therefore, current land‐based climate policies must incorporate landscape and land‐use characteristics, and their related carbon management consequences, for more effective emissions reduction targets and restoration outcomes.
We present blue carbon (C) assessment from 255 plots covering undisturbed and land‐use change‐affected mangroves (0‐, 5‐, 10‐, 15‐ and 25‐year‐old post‐harvest as well as 15‐year‐old aquaculture ponds) across West Papua Province, Indonesia. Undisturbed mangroves stored total ecosystem C‐stocks of 182–2,730 (1,087 ± 584) Mg C/ha, with variation driven by hydrogeomorphic settings. Forest harvesting did not significantly affect soil C‐stocks, despite increased dead wood density, but it removed nearly all live biomass. Aquaculture conversion removed 60% of soil and 85% of live biomass C‐stocks. Mangroves left to regenerate for 25 years reached the same level of biomass carbon compared to undisturbed forests.
•Total annual area in clearcuts was largest in Georgia and Florida’s Coastal Plains.•Road systems delivered the most sediment at low BMP implementation levels.•High BMP levels were more effective ...when applied to areas with higher erosion rates.•The BMP+ level reduced overall sediment delivery by 83% compared to BMP–.
Over 390,000 ha of forestland are clearcut annually (1–2%) across the Coastal Plain region of the southeastern U.S. where forestland occupies approximately 30 million hectares in the region. Extensive periods of high-water tables, wet-weather and harvesting, rutting, erodible soils, and drainage networks typical of the Coastal Plain increase the potential for erosion and stream sedimentation. To mitigate these impacts, water quality forestry Best Management Practices (BMPs) were developed for erosion and sediment control and are recommended and approved by all southeastern state forestry agencies for application during and after harvests. The goal of this study was to estimate erosion and sedimentation from silvicultural operations in the Coastal Plain under three different and previously recognized levels of BMP implementation including BMP– (<80%), BMP-standard (80%–90%), and BMP+ (>90%), where 90% represents average implementation. A total of 35 recent clearcut sites were evaluated in the Coastal Plain of 12 southeastern states. Erosion was estimated via the USLE-Forest model at five operational features, including decks, stream crossings, haul roads, skid trails, and harvest areas only, which were classified into one of three BMP levels. Sediment traps were utilized on a subset of Coastal Plain sites in Virginia and North Carolina so that sediment delivery ratios (unitless) could be calculated. Clearcut area estimates were obtained from the United States Forest Service (USFS), Forest Inventory and Analysis (FIA) Program. The percent areas comprised within each operational feature were multiplied by total clearcut areas in the Coastal Plain region so that erosion and sedimentation estimates could be expanded to a regional scale. Examination of the different levels of BMP implementation revealed estimated sedimentation rates of 0.5 Mg ha−1 yr−1 and 0.4 Mg ha−1 yr−1 at the BMP-standard and BMP+ levels, respectively. The range of overall estimated sediment masses at the BMP-standard and BMP+ levels most accurately reflects the current state of BMP application in the Coastal Plain. BMPs were most obviously effective at mitigating erosion and potential sediment delivery from Coastal Plain skid trails and haul roads. The highest level of BMP implementation (BMP+) at forest roads and skid trails mitigated approximately 95% of sediment compared to BMP–. Overall sediment removal efficiencies were 77% for BMP-standard and 83% for BMP+ respectively when compared to BMP–. Conclusively, this study demonstrates that forestry BMPs are highly effective at mitigating erosion and stream sedimentation when appropriately applied in the southeastern Coastal Plain.
Abstract
The article presents the results of a study of the process of operation of the Mounty 4000 machine in mountain conditions. The main goal of the research is to establish production rates for ...harvesting when using Mounty 4000 machines in mountainous areas. The need for research in this direction is due to the lack of such data in the current regulations, as well as in the scientific literature. To study the operation of the Mounty 4000, a passive production experiment was carried out in the mountainous regions of Bulgaria. The obtained data on the rates of output and operating time of the Mounty 4000 allows you to make scientifically based decisions in the selection of effective technical means from a large number of alternatives for forest harvesting technologies in mountainous areas.
Life cycle analysis is used to assess the energy requirements and greenhouse gas (GHG) emissions associated with extracting UK forest harvesting residues for use as a biomass resource. Three forest ...harvesting residues were examined (whole tree thinnings, roundwood and brash bales), and each have their own energy and emission profile. The whole forest rotation was examined, including original site establishment, forest road construction, biomass harvesting during thinning and final clear-fell events, chipping and transportation. Generally, higher yielding sites give lower GHG emissions per ‘oven dried tonne’ (ODT) forest residues, but GHG emissions ‘per hectare’ are higher as more biomass is extracted. Greater quantities of biomass, however, ultimately mean greater displacement of conventional fuels and therefore greater potential for GHG emission mitigation. Although forest road construction and site establishment are “one off” events they are highly energy-intensive operations associated with high diesel fuel consumption, when placed in context with the full forest rotation, however, their relative contributions to the overall energy requirements and GHG emissions are small. The lower bulk density of wood chips means that transportation energy requirements and GHG emissions are higher compared with roundwood logs and brash bales, suggesting that chipping should occur near the end-user of application.
► GHGs and fuel consumption assessed for UK clear-fell conifer forest residues. ► Energy use and GHG emissions for forest road construction characterised. ► Lower energy requirements and GHG emissions per ODT for higher yielding sites. ► Transport energy and GHG emissions higher for wood chip than roundwood or brash bales. ► Results useful in predicting GHG mitigation potential from UK commercial conifer forest residues.
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