scholarly journals Assessing Wood and Soil Carbon Losses from a Forest-Peat Fire in the Boreo-Nemoral Zone

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 880
Author(s):  
Andrey Sirin ◽  
Alexander Maslov ◽  
Dmitry Makarov ◽  
Yakov Gulbe ◽  
Hans Joosten
Keyword(s):  
Soil Carbon ◽  
Stand Structure ◽  
Peat Soil ◽  
Burned Area ◽  
Tree Biomass ◽  
Carbon Loss ◽  
Forest Stand Structure ◽  
Peat Fire ◽  
Peat Fires ◽  
Carbon Losses

Forest-peat fires are notable for their difficulty in estimating carbon losses. Combined carbon losses from tree biomass and peat soil were estimated at an 8 ha forest-peat fire in the Moscow region after catastrophic fires in 2010. The loss of tree biomass carbon was assessed by reconstructing forest stand structure using the classification of pre-fire high-resolution satellite imagery and after-fire ground survey of the same forest classes in adjacent areas. Soil carbon loss was assessed by using the root collars of stumps to reconstruct the pre-fire soil surface and interpolating the peat characteristics of adjacent non-burned areas. The mean (median) depth of peat losses across the burned area was 15 ± 8 (14) cm, varying from 13 ± 5 (11) to 20 ± 9 (19). Loss of soil carbon was 9.22 ± 3.75–11.0 ± 4.96 (mean) and 8.0–11.0 kg m−2 (median); values exceeding 100 tC ha−1 have also been found in other studies. The estimated soil carbon loss for the entire burned area, 98 (mean) and 92 (median) tC ha−1, significantly exceeds the carbon loss from live (tree) biomass, which averaged 58.8 tC ha−1. The loss of carbon in the forest-peat fire thus equals the release of nearly 400 (soil) and, including the biomass, almost 650 tCO2 ha−1 into the atmosphere, which illustrates the underestimated impact of boreal forest-peat fires on atmospheric gas concentrations and climate.

scholarly journals Remote Sensing Mapping of Peat-Fire-Burnt Areas: Identification among Other Wildfires

2022 ◽  
Vol 14 (1) ◽  
pp. 194
Author(s):  
Andrey Sirin ◽  
Maria Medvedeva
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Radiation Power ◽  
Fire Detection ◽  
Moisture Index ◽  
Peat Fire ◽  
Landsat 5 Tm ◽  
Burnt Areas ◽  
Peat Fires ◽  
Carbon Losses

Peat fires differ from other wildfires in their duration, carbon losses, emissions of greenhouse gases and highly hazardous products of combustion and other environmental impacts. Moreover, it is difficult to identify peat fires using ground-based methods and to distinguish peat fires from forest fires and other wildfires by remote sensing. Using the example of catastrophic fires in July–August 2010 in the Moscow region (the center of European Russia), in the present study, we consider the results of peat-fire detection using Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) hotspots, peat maps, and analysis of land cover pre- and post-fire according to Landsat-5 TM data. A comparison of specific (for detecting fires) and non-specific vegetation indices showed the difference index ΔNDMI (pre- and post-fire normalized difference moisture Index) to be the most effective for detecting burns in peatlands according to Landsat-5 TM data. In combination with classification (both unsupervised and supervised), this index offered 95% accuracy (by ground verification) in identifying burnt areas in peatlands. At the same time, most peatland fires were not detected by Terra/Aqua MODIS data. A comparison of peatland and other wildfires showed the clearest differences between them in terms of duration and the maximum value of the fire radiation power index. The present results may help in identifying peat (underground) fires and their burnt areas, as well as accounting for carbon losses and greenhouse gas emissions.

Can peat soil support a flaming wildfire?

2019 ◽  
Vol 28 (8) ◽  
pp. 601 ◽  
Author(s):  
Shaorun Lin ◽  
Peiyi Sun ◽  
Xinyan Huang
Keyword(s):  
Heat Flux ◽  
Ignition Temperature ◽  
Peat Soil ◽  
Pine Needles ◽  
Wildland Fires ◽  
External Radiation ◽  
Ignition Energy ◽  
Peat Fire ◽  
Peat Fires ◽  
Minimum Heat

Smouldering wildfire in peatlands is one of the largest and longest-lasting fire phenomena on Earth, but whether peat can support a flaming fire like other surface fuels is still unclear. Our experiments demonstrate the successful piloted flaming ignition of peat soil with moisture up to 100 wt-% under external radiation, indicating that flames may rapidly spread on peatland before transitioning to a conventional smouldering peat fire. Compared with smouldering ignition, flaming ignition of peat is more difficult, requiring a higher minimum heat flux and tripling the ignition energy. The propensity for flaming increases with a drier peat and greater external heating. We also found that the flaming ignition temperature increases from 290 to 690°C as the peat moisture increases to 100 wt-%. Flames from peat soil are much weaker than those of pine needles and wood, and they eventually transition to smouldering. The heat of flaming is estimated to be 13MJkg−1, close to the heat of smouldering. The measured CO/CO2 ratio of flaming peat fires is less than 0.02, much smaller than 0.2 for smouldering peat fires. This research helps understand the development of peat fire and the interaction between flaming and smouldering wildland fires.

scholarly journals Carbon Stocks in the Small Estuarine Mangroves of Geza and Mtimbwani, Tanga, Tanzania

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Edmond Alavaisha ◽  
Mwita M. Mangora
Keyword(s):  
Soil Carbon ◽  
Stand Structure ◽  
High Capacity ◽  
Stand Density ◽  
Carbon Stocks ◽  
Forest Stand ◽  
Ecological Resilience ◽  
Mangrove Forests ◽  
Mangrove Species ◽  
Forest Stand Structure

Mangrove forests offer important ecosystem services, including their high capacity for carbon sequestration and stocking. However, they face rapid degradation and loss of ecological resilience particularly at local scales due to human pressure. We conducted inventory of mangrove forests to characterise forest stand structure and estimate carbon stocks in the small estuarine mangroves of Geza and Mtimbwani in Tanga, Tanzania. Forest structure, above-ground carbon (AGC), and below-ground carbon (BGC) were characterised. Soil carbon was estimated to 1 m depth using loss on ignition procedure. Six common mangrove species were identified dominated byAvicennia marina(Forsk.) Vierh. andRhizophora mucronataLamarck. Forest stand density and basal area were 1740 stems ha−1and 17.2 m2 ha−1for Geza and 2334 stems ha−1and 30.3 m2 ha−1for Mtimbwani. Total ecosystem carbon stocks were 414.6 Mg C ha−1for Geza and 684.9 Mg C ha−1for Mtimbwani. Soil carbon contributed over 65% of these stocks, decreasing with depth. Mid zones of the mangrove stands had highest carbon stocks. These data demonstrate that studied mangroves are potential for carbon projects and provide the baseline for monitoring, reporting, and verification (MRV) to support the projects.

scholarly journals Forest stand structure and coarse woody debris determine the biodiversity of beetle communities in Mediterranean mountain beech forests

2021 ◽  
pp. e01637
Author(s):  
Francesco Parisi ◽  
Michele Innangi ◽  
Roberto Tognetti ◽  
Fabio Lombardi ◽  
Gherardo Chirici ◽  
...  
Keyword(s):  
Coarse Woody Debris ◽  
Stand Structure ◽  
Woody Debris ◽  
Forest Stand ◽  
Beech Forests ◽  
Forest Stand Structure

Stand-Level Forest Structure and Avian Habitat: Scale Dependencies in Predicting Occurrence in a Heterogeneous Forest

2008 ◽  
Vol 54 (1) ◽  
pp. 36-46
Author(s):  
Katherine Manaras Smith ◽  
William S. Keeton ◽  
Therese M. Donovan ◽  
Brian Mitchell
Keyword(s):  
Forest Structure ◽  
Stand Structure ◽  
Site Occupancy ◽  
Territory Size ◽  
Weight Of Evidence ◽  
Habitat Models ◽  
Point Counts ◽  
Forest Stand Structure ◽  
Habitat Scale

Abstract We explored the role of stand-level forest structure and spatial extent of forest sampling in models of avian occurrence in northern hardwood-conifer forests for two species: black-throated blue warbler (Dendroica caerulescens) and ovenbird (Seiurus aurocapillus). We estimated site occupancy from point counts at 20 sites and characterized the forest structure at these sites at three spatial extents (0.2, 3.0, and 12.0 ha). Weight of evidence was greatest for habitat models using forest stand structure at the 12.0-ha extent and diminished only slightly at the 3.0-ha extent, a scale that was slightly larger than the average territory size of both species. Habitat models characterized at the 0.2-ha extent had low support, yet are the closest in design to those used in many of the habitat studies we reviewed. These results suggest that the role of stand-level vegetation may have been underestimated in the past, which will be of interest to land managers who use habitat models to assess the suitability of habitat for species of concern.

scholarly journals Tree height integrated into pantropical forest biomass estimates

2012 ◽  
Vol 9 (8) ◽  
pp. 3381-3403 ◽  
Author(s):  
T. R. Feldpausch ◽  
J. Lloyd ◽  
S. L. Lewis ◽  
R. J. W. Brienen ◽  
M. Gloor ◽  
...  
Keyword(s):  
East Africa ◽  
Carbon Storage ◽  
Stand Structure ◽  
Forest Biomass ◽  
Small Diameter ◽  
Tree Height ◽  
Total Biomass ◽  
Guiana Shield ◽  
Tree Biomass ◽  
Continental Scale

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

scholarly journals Estimating Annual Soil Carbon Loss in Agricultural Peatland Soils Using a Nitrogen Budget Approach

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0121432 ◽  
Author(s):  
Emilie R. Kirk ◽  
Chris van Kessel ◽  
William R. Horwath ◽  
Bruce A. Linquist
Keyword(s):  
Soil Carbon ◽  
Nitrogen Budget ◽  
Carbon Loss
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