Australian climate–carbon cycle feedback reduced by soil black carbon

Lehmann, Johannes; Skjemstad, J. O.; Sohi, Saran; Carter, John; Barson, Michele; Falloon, Pete; Coleman, Kevin; Woodbury, Peter B.; Krull, Evelyn S.

doi:10.1038/ngeo358

Cited by 342 publications

(219 citation statements)

References 27 publications

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“…Spectroscopic characterization shows that combustion temperature affects the degree of aromaticity and the size of aromatic sheets, which in turn determine short-term mineralization rates 22,[34][35][36] . To reconcile the observations of decomposability with the old radiocarbon ages of fire-derived carbon deposits 37,38 , it has been suggested that physical protection and interactions with soil minerals play a significant part in black-carbon stability over long periods of time 39 .…”

Section: Soil Humic Substancesmentioning

confidence: 99%

Persistence of soil organic matter as an ecosystem property

Schmidt

Torn

Abiven

et al. 2011

Nature

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Globally, soil organic matter (SOM) contains more than three times as much carbon as either the atmosphere or terrestrial vegetation. Yet it remains largely unknown why some SOM persists for millennia whereas other SOM decomposes readily-and this limits our ability to predict how soils will respond to climate change. Recent analytical and experimental advances have demonstrated that molecular structure alone does not control SOM stability: in fact, environmental and biological controls predominate. Here we propose ways to include this understanding in a new generation of experiments and soil carbon models, thereby improving predictions of the SOM response to global warming.Understanding soil biogeochemistry is essential to the stewardship of ecosystem services provided by soils, such as soil fertility (for food, fibre and fuel production), water quality, resistance to erosion and climate mitigation through reduced feedbacks to climate change. Soils store at least three times as much carbon (in SOM) as is found in either the atmosphere or in living plants 1 . This major pool of organic carbon is sensitive to changes in climate or local environment, but how and on what timescale will it respond to such changes? The feedbacks between soil organic carbon and climate are not fully understood, so we are not fully able to answer these questions 2-7 , but we can explore them using numerical models of soil-organic-carbon cycling. We can not only simulate feedbacks between climate change and ecosystems, but also evaluate management options and analyse carbon sequestration and biofuel strategies. These models, however, rest on some assumptions that have been challenged and even disproved by recent research arising from new isotopic, spectroscopic and molecularmarker techniques and long-term field experiments.Here we describe how recent evidence has led to a framework for understanding SOM cycling, and we highlight new approaches that could lead us to a new generation of soil carbon models, which could better reflect observations and inform predictions and policies.

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Section: Soil Humic Substancesmentioning

confidence: 99%

Persistence of soil organic matter as an ecosystem property

Schmidt

Torn

Abiven

et al. 2011

Nature

Self Cite

4,741

106

3,153

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“…The impact of this poorly constrained site history, at the time scale of stable C formation, on stable C concentration is potentially important. In particular, black C (BC) can represent an important part of the stable C pool (Lehmann et al, 2008). If most of stable C is due to BC, its concentration would be much more related to site history (for instance occurrence of fires during the last millennia) than present pedoclimatic parameters.…”

Section: Estimating the Stable Soil C Pool Using Ltbf Datamentioning

confidence: 99%

Quantifying and isolating stable soil organic carbon using long-term bare fallow experiments

et al. 2010

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Abstract. The stability of soil organic matter (SOM) is a major source of uncertainty in predicting atmospheric CO 2 concentration during the 21st century. Isolating the stable soil carbon (C) from other, more labile, C fractions in soil is of prime importance for calibrating soil C simulation models, and gaining insights into the mechanisms that lead to soil C stability. Long-term experiments with continuous bare fallow (vegetation-free) treatments in which the decay of soil C is monitored for decades after all inputs of C have stopped, provide a unique opportunity to assess the quantity of stable soil C. We analyzed data from six bare fallow experiments of long-duration (>30 yrs), covering a range of soil types and climate conditions, and sited at Askov (Denmark), Grignon and Versailles (France), Kursk (Russia), Rothamsted (UK), and Ultuna (Sweden). A conceptual three pool model dividing soil C into a labile pool (turnover time of a several years), an intermediate pool (turnover time of a several decades) and a stable pool (turnover time of a several centuries or more) fits well with the long term C decline observed in the bare fallow soils. The estimate of stable C ranged from 2.7 g C kg −1 at Rothamsted to 6.8 g C kg −1 at Grignon. The uncertainty Correspondence to: P. Barré (barre@geologie.ens.fr) associated with estimates of the stable pool was large due to the short duration of the fallow treatments relative to the turnover time of stable soil C. At Versailles, where there is least uncertainty associated with the determination of a stable pool, the soil contains predominantly stable C after 80 years of continuous bare fallow. Such a site represents a unique research platform for characterization of the nature of stable SOM and its vulnerability to global change.

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“…Continued efforts to improve accuracy in ecosystem and global C accounting, especially in the context of changes in historic disturbance regimes, depends on the availability of information on PyC stocks and distribution in burned forests (Lehmann et al, 2008;Stockmann et al, 2013;Santín et al, 2015b). Additional data are needed to advance the research community's ability to quantify fire's impact on forest C and PyC.…”

Section: Additional Data Needsmentioning

confidence: 99%

Quantifying Changes in Total and Pyrogenic Carbon Stocks Across Fire Severity Gradients Using Active Wildfire Incidents

et al. 2018

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Positive feedbacks between wildfire emissions and climate are expected to increase in strength in the future; however, fires not only release carbon (C) from terrestrial to atmospheric pools, they also produce pyrogenic C (PyC) which contributes to longer-term C stability. Our objective was to quantify wildfire impacts on total C and PyC stocks in California mixed-conifer forest, and to investigate patterns in C and PyC stocks and changes across gradients of fire severity, using metrics derived from remote sensing and field observations. Our unique study accessed active wildfires to establish and measure plots within days before and after fire, prior to substantial erosion. We measured pre-and post-fire aboveground forest structure and woody fuels to calculate aboveground biomass, C and PyC, and collected forest floor and 0-5 cm mineral soil samples. Immediate tree mortality increased with severity, but overstory C loss was minimal and limited primarily to foliage. Fire released 85% of understory and herbaceous C (comprising <1.0% of total ecosystem C). The greatest C losses occurred from downed wood and forest floor pools (19.3 ± 5.1 Mg ha −1 and 25.9 ± 3.2 Mg ha −1 , respectively). Tree bark and downed wood contributed the greatest PyC gains (1.5 ± 0.3 Mg ha −1 and 1.9 ± 0.8 Mg ha −1 , respectively), and PyC in tree bark showed non-significant positive trends with increasing severity. Overall PyC losses of 1.9 ± 0.3 Mg ha −1 and 0.5 ± 0

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Australian climate–carbon cycle feedback reduced by soil black carbon

Cited by 342 publications

References 27 publications

Persistence of soil organic matter as an ecosystem property

Persistence of soil organic matter as an ecosystem property

Quantifying and isolating stable soil organic carbon using long-term bare fallow experiments

Quantifying Changes in Total and Pyrogenic Carbon Stocks Across Fire Severity Gradients Using Active Wildfire Incidents

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