Estimating charcoal content in forest mineral soils

Kurth, Valerie J.; MacKenzie, M. Derek; DeLuca, Thomas H.

doi:10.1016/j.geoderma.2006.08.003

Cited by 72 publications

(58 citation statements)

References 12 publications

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“…Charcoal C concentrations reported by Kurth et al [12] range from 14 to 26% of total C in the upper 10 cm of Ponderosa pine forest mineral soils. Boreal Saskatchewan forest soils range from 18 to 22% of total C in the A horizon [28].…”

Section: Charcoal Characterizationmentioning

confidence: 83%

“…Soil texture may explain the variation in charcoal contribution to total C in mineral soils. Higher percentages of silt plus clay correspond to a higher percentage of total C as charcoal C. For example, based on data from a Ponderosa pine forest [11,12,29], our evaluation indicates charcoal C as percentage of total C is positively correlated with silt plus clay concentration In the boreal transition zone of Saskatchewan, lacustrine soils with 85% silt plus clay have 22% of total C as charcoal C, while fluvial soils consisting of 41% silt plus clay have only 18% of total C as charcoal C [28]. Similarly, Sierra Nevada sandy loams and one silty loam contained 10-15% of total C as charcoal C [13], whereas the Siskiyou-LTEP loam and clay loams had 20% charcoal C. Soil organic C, in general, is stabilized by clay and silt [30][31][32].…”

Section: Charcoal Characterizationmentioning

confidence: 99%

“…Mean residence time for charcoal can reach over 10,000 years in terrestrial and aquatic sediments, whereas humic acids have a residence time of about 3,000 years [4,5]. Charcoal C composes 10 to 50% of soil organic C [4,[11][12][13]. Charcoal incorporation into forest mineral soils influences N cycling in boreal and temperate forest soils by increasing net nitrification [4,11,14].…”

Section: Introductionmentioning

confidence: 99%

“…For wildfires, the chronosequence approach has been used to estimate charcoal dynamics. Changes in charcoal C from wildfires in forest floor and mineral soils were analyzed in Swedish boreal and dry Ponderosa pine forests using chronosequences to represent recent fire history [12,20]. Forest soils in the Swedish forest showed no relationship between soil charcoal content and time since fire [20].…”

Section: Introductionmentioning

confidence: 99%

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Long and Short-Term Effects of Fire on Soil Charcoal of a Conifer Forest in Southwest Oregon

Pingree

Homann

Morrissette

et al. 2012

Forests

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Abstract:In 2002, the Biscuit Wildfire burned a portion of the previously established, replicated conifer unthinned and thinned experimental units of the Siskiyou Long-Term Ecosystem Productivity (LTEP) experiment, southwest Oregon. Charcoal C in pre and post-fire O horizon and mineral soil was quantified by physical separation and a peroxide-acid digestion method. The abrupt, short-term fire event caused O horizon charcoal C to increase by a factor of ten to >200 kg C ha −1

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Section: Charcoal Characterizationmentioning

confidence: 83%

Section: Charcoal Characterizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Long and Short-Term Effects of Fire on Soil Charcoal of a Conifer Forest in Southwest Oregon

Pingree

Homann

Morrissette

et al. 2012

Forests

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“…In the springtime, fragmented microscopic particles could also have been transported by running water, both horizontally and vertically. It is thus likely that fragmented microscopic charcoal particles are present at greater depths in the soil (Carcaillet, 2001) and could have been detected by other methods than the one used here (see Kurth et al, 2006). Hence, from our calculations it seems that the amount of macroscopic charcoal particles produced during the Stállo period in sub-alpine and alpine areas has dramatically declined over time, probably due to various chemical and physical factors, but more research is needed to evaluate the magnitude and causes of this loss.…”

Section: Charcoal Concentrations and Dispersal: Theory Vs Evidencementioning

confidence: 98%

Charcoal Dispersal from Alpine Stallo Hearths in Sub-Arctic Sweden: Patterns Observed from Soil Analysis and Experimental Burning

Hörnberg¹,

Liedgren²

2012

ACH

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To evaluate dispersal patterns and concentrations of macroscopic charcoal particles around Stállo settlements in sub-arctic Scandinavia, their distributions following experimental burning and soil concentrations around an alpine Stállo settlement dating between AD 700 and 1150 were recorded. After the burning 98% of recorded particles were 0.1-0.5 mm long, 90% were dispersed within 40 m of the fire, their mean concentration 40 m from the fire was 0.14±0.08 particles/cm 2 and the concentration decreased with increasing distance. At the settlement, 95% of recorded charcoal particles were 0.1-0.5 mm long, 94% were within 40 m of the hearths, the mean concentration declined with increasing distance, and concentrations were much lower than expected from the experimental burning (e.g. 17.6±2.4 particles/cm 2 , 40 m away). In conclusion: biological archives used for charcoal analysis in archaeological and vegetation history studies should be located ≤40 m from settlements, and data obtained from charcoal analyses should be interpreted cautiously.

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Assessing soil carbon vulnerability in the Western USA by geospatial modeling of pyrogenic and particulate carbon stocks

et al. 2017

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To predict how land management practices and climate change will affect soil carbon cycling, improved understanding of factors controlling soil organic carbon fractions at large spatial scales is needed. We analyzed total soil organic (SOC) as well as pyrogenic (PyC), particulate (POC), and other soil organic carbon (OOC) fractions in surface layers from 650 stratified‐sampling locations throughout Colorado, Kansas, New Mexico, and Wyoming. PyC varied from 0.29 to 18.0 mg C g−1 soil with a mean of 4.05 mg C g−1 soil. The mean PyC was 34.6% of the SOC and ranged from 11.8 to 96.6%. Both POC and PyC were highest in forests and canyon bottoms. In the best random forest regression model, normalized vegetation index (NDVI), mean annual precipitation (MAP), mean annual temperature (MAT), and elevation were ranked as the top four important variables determining PyC and POC variability. Random forests regression kriging (RFK) with environmental covariables improved predictions over ordinary kriging by 20 and 7% for PyC and POC, respectively. Based on RFK, 8% of the study area was dominated (≥50% of SOC) by PyC and less than 1% was dominated by POC. Furthermore, based on spatial analysis of the ratio of POC to PyC, we estimated that about 16% of the study area is medium to highly vulnerable to SOC mineralization in surface soil. These are the first results to characterize PyC and POC stocks geospatially using stratified sampling scheme at the scale of 1,000,000 km2, and the methods are scalable to other regions.

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Estimating charcoal content in forest mineral soils

Cited by 72 publications

References 12 publications

Long and Short-Term Effects of Fire on Soil Charcoal of a Conifer Forest in Southwest Oregon

Long and Short-Term Effects of Fire on Soil Charcoal of a Conifer Forest in Southwest Oregon

Charcoal Dispersal from Alpine Stallo Hearths in Sub-Arctic Sweden: Patterns Observed from Soil Analysis and Experimental Burning

Assessing soil carbon vulnerability in the Western USA by geospatial modeling of pyrogenic and particulate carbon stocks

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