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The Long-Term Effect of Biochar on Soil Microbial Abundance, Activity and Community Structure Is Overwritten by Land Management

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Soil amendment with biochar can modify soil microbial abundance, activity and community structure. Nevertheless, the long-term evolution of these effects is unknown and of critical importance because biochar persists in soil for centuries. We selected nine charcoal kiln sites (CKS) from forests (four sites) and croplands (five sites) and determined the microbial properties of their topsoil, largely enriched with charcoal for >150 years. Adjacent soils were used as references unaffected by charcoal production. Soils were incubated in controlled conditions and emissions of CO2 were measured for 138 days. At day 68, an aliquot was sampled from each soil to determine microbial abundance and community structure by phospholipid fatty acid (PLFA) analysis. Before the extraction, one standard PLFA (C21:0 PC) was added to the soil to test the influence of charcoal on PLFAs recovery. The content of uncharred SOC and pH explained a main part of the variance of soil CO2 emissions, which supports the view that charcoal had a limited effect on soil respiration. The recovery of C21:0 PC was increased in presence of aged charcoal, which contrasts with the decreased recovery recorded shortly after biochar application. This underlines that properties of charcoal evolve dramatically over time, and that a long-term vision is critical in the perspective of amending soils with biochar. Land-use had an overriding control on the microbial community structure, surpassing the effect of a vast amount of charcoal present in the soil. In forests, 10 PLFAs from gram positive and general bacteria were significantly different between CKS and adjacent reference soils, whereas in croplands only four PLFAs from fungi, gram negative bacteria and actinomycetes were significantly affected. These results suggest that the long-term effect of charcoal on soil microbiota is overwritten by management practices. Biochar properties must therefore be regarded altogether with soil conditions to correctly design a successful soil amendment with biochar. Additionally, the absence of a relationship between individual PLFAs and charcoal-C supports the idea that the long-term effect of charcoal is related to a modification of soil ecological niche (e.g., nutrient availability, pH) rather than to an alteration of the source of organic C available to biota.
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ORIGINAL RESEARCH
published: 12 July 2019
doi: 10.3389/fenvs.2019.00110
Frontiers in Environmental Science | www.frontiersin.org 1July 2019 | Volume 7 | Article 110
Edited by:
Hannes Schmidt,
University of Vienna, Austria
Reviewed by:
Carsten W. Mueller,
Technical University of
Munich, Germany
Anne Daebeler,
University of Vienna, Austria
*Correspondence:
Brieuc Hardy
b.hardy@cra.wallonie.be
Specialty section:
This article was submitted to
Soil Processes,
a section of the journal
Frontiers in Environmental Science
Received: 02 December 2018
Accepted: 25 June 2019
Published: 12 July 2019
Citation:
Hardy B, Sleutel S, Dufey JE and
Cornelis J-T (2019) The Long-Term
Effect of Biochar on Soil Microbial
Abundance, Activity and Community
Structure Is Overwritten by Land
Management.
Front. Environ. Sci. 7:110.
doi: 10.3389/fenvs.2019.00110
The Long-Term Effect of Biochar on
Soil Microbial Abundance, Activity
and Community Structure Is
Overwritten by Land Management
Brieuc Hardy 1,2
*, Steven Sleutel 3, Joseph E. Dufey 1and Jean-Thomas Cornelis 4
1Earth and Life Institute—Environmental Sciences, Université Catholique de Louvain, Louvain-la-Neuve, Belgium,
2Département Agriculture et Milieu Naturel—Unité Fertilité des Sols et Protection des Eaux, Centre Wallon de Recherches
Agronomiques, Gembloux, Belgium, 3Department of Environment, Faculty of Bioscience Engineering, Ghent University,
Ghent, Belgium, 4TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech (GxABT), University of Liège (ULiège),
Gembloux, Belgium
Soil amendment with biochar can modify soil microbial abundance, activity and
community structure. Nevertheless, the long-term evolution of these effects is unknown
and of critical importance because biochar persists in soil for centuries. We selected nine
charcoal kiln sites (CKS) from forests (four sites) and croplands (five sites) and determined
the microbial properties of their topsoil, largely enriched with charcoal for >150 years.
Adjacent soils were used as references unaffected by charcoal production. Soils were
incubated in controlled conditions and emissions of CO2were measured for 138 days.
At day 68, an aliquot was sampled from each soil to determine microbial abundance and
community structure by phospholipid fatty acid (PLFA) analysis. Before the extraction,
one standard PLFA (C21:0PC) was added to the soil to test the influence of charcoal
on PLFAs recovery. The content of uncharred SOC and pH explained a main part of
the variance of soil CO2emissions, which supports the view that charcoal had a limited
effect on soil respiration. The recovery of C21:0 PC was increased in presence of aged
charcoal, which contrasts with the decreased recovery recorded shortly after biochar
application. This underlines that properties of charcoal evolve dramatically over time,
and that a long-term vision is critical in the perspective of amending soils with biochar.
Land-use had an overriding control on the microbial community structure, surpassing
the effect of a vast amount of charcoal present in the soil. In forests, 10 PLFAs from
gram positive and general bacteria were significantly different between CKS and adjacent
reference soils, whereas in croplands only four PLFAs from fungi, gram negative bacteria
and actinomycetes were significantly affected. These results suggest that the long-term
effect of charcoal on soil microbiota is overwritten by management practices. Biochar
properties must therefore be regarded altogether with soil conditions to correctly design
a successful soil amendment with biochar. Additionally, the absence of a relationship
between individual PLFAs and charcoal-C supports the idea that the long-term effect of
charcoal is related to a modification of soil ecological niche (e.g., nutrient availability, pH)
rather than to an alteration of the source of organic C available to biota.
Keywords: preindustrial charcoal kiln sites, historical charcoal hearths, black carbon, aged biochar, soil
respiration, phospholipid fatty acids (PLFA), black carbon quantification, land use
Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
INTRODUCTION
Biochar application to soil is a carbon negative technology used
to tackle climate change while sustainably improving soil fertility
(Lehmann et al., 2006). There is a general agreement that the low
degradability of biochar, like other types of black carbon (BC),
derives mainly from its specific chemistry, which is dominated by
fused aromatic ring structures (Haumaier and Zech, 1995; Glaser
et al., 2000; Brodowski et al., 2005). Despite its intrinsic low
biodegradability, the introduction of biochar to soil does often
result in an increase in CO2emissions in the short-term (Sagrilo
et al., 2014). Among explanatory factors, the positive priming
of biochar on the decomposition of native soil organic matter
(SOM) (Maestrini et al., 2014) and the abiotic release of CO2
from the reaction of carbonates in the biochar after amendment
to acidic soil (Bruun et al., 2014) were identified. Nevertheless,
the main source of the increase in CO2emissions from a
biochar amended soil seems to be the microbially mediated
decomposition of labile biochar constituents (e.g., Cross and
Sohi, 2011; Hilscher and Knicker, 2011). In a meta-analysis of
46 studies, Sagrilo et al. (2014) showed that large additions of
biochar to soil considerably increased CO2emissions, whereas a
low input of biochar relative to native soil organic carbon (SOC)
content did not significantly affect emissions. Fabbri et al. (2012)
related the mineralization rates of 20 biochars to their chemical
composition and found biochars with higher concentrations
of proteins and sugars (from incomplete transformation by
pyrolysis) to be associated with the largest mineralization rates.
In contrast, biochars produced at a higher temperature resulted
in lower CO2emissions (Fabbri et al., 2012), probably related to
an increasing degree of aromaticity and aromatic condensation
(Keiluweit et al., 2010; Wiedemeier et al., 2015) and the relative
decrease of the labile fraction of biochar. Accordingly, biochar
application has contrasting effects on soil biology depending on
its amount and quality as well as initial soil properties (Lehmann
et al., 2011).
Overall, the net increase in CO2release following the
application of biochar to soil appears to be a short-lived effect,
while for incubations over a longer time period (>200 days),
the average emission of CO2is usually not or even negatively
affected for large application rates (Sagrilo et al., 2014). To
explain this result, Sagrilo et al. (2014) proposed that a major
part of the labile fraction of biochar might have been consumed
over 200 days. Another possible explanation is that N deficiency
eventually occurs after prolonged incubation of biochar amended
soil (Ameloot et al., 2015), as most biochars have high C:N
ratios. In their survey, Sagrilo et al. (2014) showed that soils
with a C:N ratio <10 were much more subject to an increase
in CO2emissions after addition of biochar, which corroborates
this assumption.
Despite an already overwhelming number of studies on the
effect of biochar on soil biology and greenhouse gas emissions,
most data originate from short-term experiments in laboratory
conditions (Sagrilo et al., 2014). Insights in the long-term effects
of biochar remain lacking (Maestrini et al., 2014; Sagrilo et al.,
Abbreviations: CKS, Charcoal kiln site; LU, Land use; K/R, Kiln vs. reference soil.
2014), although biochar persists in soil for centuries (Singh et al.,
2012) and therein lies exactly its premise to abate net CO2-
emission. Since properties of biochar change over time (Joseph
et al., 2010), long-term implications of biochar soil amendment
are very likely to differ from short-term effects. For instance,
positive priming has only been observed shortly after addition of
fresh biochar to soil and does not seem to last over long periods of
time (Hamer et al., 2004; Wardle et al., 2008; Zimmerman et al.,
2011). More importantly, on long timescales after the addition
of biochar to soil, a decrease of metabolic quotient (defined
as microbial activity reported to soil biomass) or even a lower
absolute amount of respired C was observed in BC rich terra
preta soils (Jin, 2010; Liang et al., 2010). Nevertheless, data from
the Amazonia cannot be extrapolated to other soil and climate
conditions with very different land-use histories. Additionally,
several types of organic and inorganic household wastes other
than biochar were involved in the genesis of terra preta soils
(Glaser, 2007), which makes it nearly impossible to isolate the
effect of biochar from the effect of these other inputs.
Worldwide, many sites can be found where biomass-derived
black carbon was deposited centuries ago during charcoal
production. Among historical charcoal deposits, pre-industrial
charcoal kiln sites (CKS), also referred to as “historical charcoal
hearths,” have the potential to be used as a proxy for the long-term
effect of biochar additions on soil properties. Particularly, CKS in
deforested areas that converted to croplands present themselves
as a natural long-term field experiment with replications of
biochar application in agricultural soil (Hardy et al., 2017a;
Kerré et al., 2017). As biochar application is mainly intended
to cropland soils, these sites represent a critical source of
information to unravel the long-term fate of biochar in soil and
its effect on soil properties.
Very few studies have studied carbon turnover and soil
biology at historic charcoal kiln sites in comparison with adjacent
charcoal-free soils. Kerré et al. (2017) measured a smaller total
of CO2emissions from CKS soil than in adjacent reference soils
and a smaller mineralization of fresh maize SOM (traced by
13C isotopic signature) when added to a pre-industrial CKS soil.
They related it to an increased sorption of dissolved organic
carbon (DOC), with a preferential adsorption of the DOC rich
in aromatics.
In this work, we aimed to assess long-term implications of
charcoal enrichment at pre-industrial charcoal kiln sites on the
soil microbial biomass, activity and community structure, with a
special focus on the relationship between soil microbial activity
and community structure and the contents of charcoal-C and
uncharred SOC. We did so by relating laboratory-based CO2
emission measurements and phospholipid fatty acid (PLFA)-
based assessments of the microbial biomass and community
structure to relative amounts of charcoal-C and of uncharred
SOC in soil, determined by differential scanning calorimetry
(DSC). Soil conditions may strongly interact with the impact of
biochar on soil biological activity (e.g., Blackwell et al., 2010).
Therefore, we specifically selected sites with contrasting land uses
(forests and croplands) but with an otherwise comparable soil
texture and mineralogy to infer to what extent land use interacts
with the effect of charcoal on biological soil properties.
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
MATERIALS AND METHODS
Soil Samples
The topsoil of nine pre-industrial CKS on Haplic or Albic Luvisol
(IUSS Working Group WRB, 2014) located within the Belgian
loess belt were sampled in April 2012. At the study sites, mean
annual precipitations vary between 864 and 937 mm, while mean
annual temperature varies between 9.6 and 10C. According to
the WRB classification, soil texture was defined as silt or silt loam
(IUSS Working Group WRB, 2014). Four sites were located in
forests (Hardy et al., 2016) and five in croplands (Hardy et al.,
2017a), in areas that had been deforested for cultivation after
charcoal production. Because the parent material (loess deposit)
is identical in the nine sites, we assumed that land use was the
main soil forming factor that differentiated cropland from forest
sites. The sampled forest soils are all very acidic, even in presence
of charcoal, which differs sharply from cropland soils that are
frequently limed and had pH values close to neutral. For each site,
soil properties of the organo-mineral (A) horizon of the CKS was
compared to that of directly adjacent reference soil. For cropland
sites, soil samples were taken to the depth of the plow layer (0–
25 cm) instead, similar to kiln and reference soils. For forest sites,
the full depth of the A horizon was sampled, which is up 40–
50 cm deep for charcoal-rich A horizons at CKS, whereas Ah
horizons were limited to the top 5 to 10 cm for the reference soils.
Soil Physico-Chemical Properties
Soil pH was measured in water (pH-H2O) and in 1M KCl (pH-
KCl) at a 1:5 soil:solution mass ratio. Elemental C and N contents
were measured by dry combustion (vario MAX, Elementar). The
inorganic C content was measured by the modified-pressure
calcimeter method on finely ground subsamples (<200 µm)
(Sherrod et al., 2002). Inorganic C content was always null
or below the detection limit (<0.2 g kg1). Therefore, total C
was considered to correspond to total organic C (TOC), which
includes charcoal-C. The potential CEC was determined by
percolation of 1M ammonium acetate (naturally buffered at pH
7) on soil columns (Metson, 1956). Ammonium was desorbed
with a 1.33 M KCl solution and measured by colorimetry
(ISO7150/1). Exchangeable Ca2+, Mg2+, K+, and Na+were
measured in the extract by inductively coupled plasma-atomic
emission spectroscopy (ICP-AES 6500 duo, Thermo Scientific).
We calculated the base saturation of the soil as the ratio between
the sum of exchangeable Ca2+, Mg2+, K+, and Na+and the
CEC. Plant-available P was extracted with a 0.5 M ammonium
acetate0.02 M EDTA solution at pH 4.65 at a 1:5 soil:solution
mass ratio (Lakanen and Erviö, 1971), and extracts were analyzed
by ICP-AES.
Quantification of Charcoal-C Content
Differential scanning calorimetry (DSC) was used to determine
the contents of charcoal-C and uncharred SOC in soil. The
methodology of charcoal-C quantification is detailed by Hardy
et al. (2017a). Briefly, between 15 and 25 mg of soil ground to
powder were scanned with a DSC 100 (TA Instruments) under
a flow of 50 ml min1synthetic air from room temperature to
600C, at a heating rate of 10C min1(Leifeld, 2007). The
fraction of charcoal-C content was determined based on the
height of three peaks derived from the combustion of charcoal
relative to the main peak resulting from the combustion of
uncharred organic matter (Leifeld, 2007). Prior to analysis, forest
soils were buffered at pH 7 by equilibration with 1 M ammonium
acetate (naturally buffered at pH 7) and then saturated with Ca2+
by agitation in a solution of 1M CaCl2. This pretreatment aimed
to deprotonate most carboxylic acids present at the surface of
charcoal, and to saturate carboxylate anions with Ca2+.Hardy
et al. (2017b) showed that the presence of Ca decreases the
thermal stability of the O-rich fraction of charcoal. This then
prevents peaks from overlapping, which would otherwise bias
the quantification of BC content. Agricultural soil samples were
scanned without preliminary preparation because their pH-H2O
was already close to neutral, and because they were already nearly
saturated with Ca2+as they are limed frequently.
Incubation Experiment
For each sample, 120 g of dry soil sieved at 2mm was weighed in
steel cylinders of 100 cm3, closed by a porous nylon membrane
on the bottom. Soil cores were saturated by the addition of
demineralized water and were then left in a pressure pan until
a pF of 2.5 was reached, approximately corresponding to field
capacity for an undisturbed soil. Equilibration lasted 2 weeks.
Each rewetted soil was then split into three subsamples of similar
sizes that were incubated in hermetic jars of 500 ml for 138 days in
a climatic room, at a constant temperature of 20 ±1C. To follow
CO2emissions over time, an open recipient with 25 ml of 0.5 M
NaOH was placed in the center of each jar, to trap CO2. Electrical
conductivity (EC) of the NaOH solution decreases linearly with
the amount of CO2consumed and was measured after 3, 5,
10, 17, 24, 31, 38, 45, 52, 61, 68, 75, 90, 97, 115, 124, and 138
days to determine the amount of emitted CO2from the soil
(Rodella and Saboya, 1999). For each EC measurement, jars were
left open to allow renewal of the headspace air. We calculated
that O2consumption between two measurements never exceeded
10% of the total volume of O2in the jar, which guarantees that
O2was not deficient for microbial respiration. The incubations
were stopped at 138 days because, at day 68, the pattern of CO2
emissions from the soil had reached a constant rate and an aliquot
was sampled from each soil core for PLFA analysis.
Microbial Biomass and
Community Structure
The aliquots from triplicates of the same soil were pooled
together to limit the number of PLFA measurements to one for
each soil. Directly after sampling from the incubation jars, soils
were freeze-dried and stored at 80C. During transport, freeze-
dried samples were kept cold in dry ice. PLFA were extracted
at the Department of Soil Management of Ghent University,
according to the procedure described in detail by Sleutel et al.
(2012), with the exception that we introduced a known amount
of 1,2-dihenarachidoyl-sn-glycero-3-phosphocholine (C21:0 PC;
Avanti Polar Lipids Inc.), a PLFA standard absent from soil, to test
whether the presence of charcoal decreases the PLFA extraction
efficiency, as it was observed for fresh biochars (Gomez et al.,
2014). Thirty µg of C21:0 PC were added to each sample before
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
the start of the PLFA extraction (Gomez et al., 2014). We assumed
that charcoal interacts similarly with C21:0 PC and with PLFA
naturally present in soil.
Briefly, 4 g of freeze-dried soil was mixed with 3.6 ml
phosphate buffer (pH 7.0), 4 ml chloroform and 8 ml methanol.
After centrifugation, phospholipids in the solution of the
supernatant were separated from neutral and glycolipids
by sequential elution of chloroform and acetone on silica
columns (Chromabond, Macherey-Nagel GmbH, Düren,
Germany). Phospholipids were recuperated with methanol and
saponified to obtain fatty acids. These were dried, dissolved in
a methanol:toluene mixture and transformed into fatty acid
methyl esters by methylation with 0.2 M methanolic KOH.
The concentration of PLFA biomarkers was determined by gas
chromatography-mass spectroscopy (GC-MS) with a Thermo
Focus GC combined with a Thermo DSQ quadrupole MS
(Interscience BVBA) in electron ionization mode. Soil PLFA
concentrations provide quantitative information on total
microbial biomass and microbial community structure. We
considered that PLFAs iC15:0, aC15:0, iC16:0, iC17:0, and
aC17:0 were representative for Gram-positive (G+) bacteria,
and PLFAs C16:1ω7c, C18:1ω7c, and cyC17:0 for Gram-negative
(G-) bacteria. PLFAs C15:0, C17:0, and cyC19:0 were considered
as markers for general bacteria, and PLFAs 10MeC16:0 and
10MeC18:0 as markers for actinomycetes. PLFAs C18:2ω6,9c,
C18:1ω9c, C18:2c9,1, and C18:3c9,12,15 were considered
as indicators of fungi, and PLFAs C20:4ω6,9,12,15c and
C20:5ω3,6,9,12,15c of protozoa (Sleutel et al., 2012).
STATISTICS AND DATA ANALYSIS
Soil Properties
The complete set of soil properties was analyzed by permutational
multivariate analysis of variance using the adonis function of the
vegan R package (Oksanen et al., 2019) to test the effect of land
use (LU, forest or cropland), CKS (K/R, kiln or reference site) and
the interaction “LU ×K/R” on soil properties. Data were analyzed
in R 3.3.1 (R Core Team, 2012).
Metabolic Quotient
The metabolic quotient (qCO2) of soils was calculated as the ratio
between daily emissions of CO2and the total amount of PLFA in
soil after 68 days of incubation.
C-Mineralization Rates
A double exponential model generally fits experimental data
of carbon loss from soil incubated under controlled conditions
well, and was often used to model CO2fluxes from biochar, or
from a biochar amended soil (e.g., Cheng et al., 2008; Hilscher
and Knicker, 2011; Singh et al., 2012). Such model assumes the
cumulatively emitted C, Cmin(t) (g kg1) at time t(yr), to derive
from two discrete pools of carbon in soil, one fast-cycling and one
slow-cycling pool:
Cmin(t)=X1 expk1t+X2 expk2t(1)
with X1 being the fast-cycling pool of OC (g kg1), k1 being the
decay rate of X1 (yr1), X2 being the slow-cycling pool of OC (g
kg1) and k2 being the decay rate of X2 (yr1). Carbon loss over
the time of incubation was calculated by the difference between
the initial SOC content and the cumulated amount of CO2
emitted. Equation (1) was fitted to the experimental cumulative C
data in Matlab R2016a ( R
MathWorks) by non-linear regression.
Estimates of the half-life of both the fast-cycling and slow-cycling
C pools are provided by ln(2)/K.
Microbial Community Structure
To examine the relative composition of the microbial community
in the different soil samples, PLFA concentrations were converted
to percentages of the total PLFA concentration of the respective
soil sample. The effect of K/R, LU and the interaction “LU
×K/R” on soil microbial community structure was tested
by permutational multivariate analysis of variance on the
complete set of PLFA markers using the adonis function
of the vegan R package (Oksanen et al., 2019). The soil
microbial community structure was also explored by principal
component analysis (PCA) in R 3.3.1 (R Core Team, 2012),
with the package factoextra (Kassambara and Mundt, 2017).
Only the 18 PLFAs most abundant at the scale of the dataset
were kept in order to have a sufficient number of degrees
of freedom to run the PCA. To explore the relationship
between environmental variables and soil community structure,
soil properties were fitted to the principal components of
the PCA using the function envfit from vegan R package
(Oksanen et al., 2019).
To further investigate possible differences between CKS
and adjacent reference soils, all individual PLFAs were tested
with bivariate paired t-tests, separately for cropland and forest
soils. No correction of the p-value for repetitive testing was
applied because methods that were tested (Boneferroni, Holm,
and Benjamini-Hochberg) were too conservative, leading to
insignificant results in 100 percent of cases.
RESULTS
Raw data is readily available as Supplementary Material.
The dataset contains soil physico-chemical properties, results
from the PLFA extraction and emissions of CO2from the
incubation experiment.
Soil Properties
The permutational multivariate analysis of variance detected a
significant effect for both K/R (r² =0.146, P<0.001) and LU
(r² =0.621, P<0.001) on soil properties, with a significant
interaction LU ×K/R (r² =0.075, p=0.01). This underlines
that the effect of CKS on soil properties depends on land use.
Looking at soil properties individually, all of them differed (P<
0.05) between forests and croplands except exchangeable Mg2+
(Table 1). Cropland soils contained less total OC, charcoal-C
and uncharred SOC compared to forest soils. They also have a
smaller C:N ratio and CEC. Cropland soils all had a pH close to
neutral, which contrasts the very acidic forest soils. Accordingly,
the exchange complex of cropland soils was saturated with
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
TABLE 1 | Soil physico-chemical properties of kiln (K) and reference (R) soils from cropland and forest.
Land use Depth Site K/R Total OC Char-C Uncharred SOC C:N CEC BS pHH2O pHKCl Pav Ca2+Mg2+K+
cm g kg1g kg1g kg1- cmolckg1% - - mg kg1cmolckg1cmolckg1cmolckg1
Cropland 0–25 1 K 38.4 18.3 20.1 18.0 21.5 100 5.80 5.10 41.8 19.9 2.60 0.38
0–25 R 15.5 1.4 14.1 10.9 12.8 100 6.10 5.90 54.3 13.5 2.29 0.47
0–25 2 K 31.1 16.2 14.9 15.8 13.4 99.1 6.10 5.40 23.8 11.4 1.38 0.40
0–25 R 14.1 1.9 12.2 12.0 9.6 94.9 6.10 5.40 28.6 7.5 1.15 0.40
0–25 3 K 34.7 16.3 18.4 17.5 16.8 93.0 6.56 5.73 5.71 13.9 0.16 1.52
0–25 R 16.4 1.2 15.2 11.2 10.9 100 6.85 5.78 4.47 9.4 0.15 1.54
0–25 4 K 20.6 7.0 13.6 15.0 12.4 100 7.56 7.05 93.23 14.3 0.47 1.32
0–25 R 12.1 0.3 11.8 11.0 9.9 100 7.39 6.64 72.36 9.5 0.47 1.16
0–25 5 K 26.7 9.0 17.7 16.2 15.7 100 8.09 7.50 103.88 22.2 0.55 0.58
0–25 R 11.4 0.5 10.9 11.6 10.0 100 8.29 7.79 110.70 20.5 0.53 0.56
Mean sd K 30.3 6.9 13.4 5.0 16.9 2.6 16.5 1.2 16.0 3.6 98.4 3.1 6.8 0.9 6.2 1.0 53.7 3.0 16.3 4.5 1.03 1.0 0.84 0.5
Mean sd R 13.9 2.1 1.1 0.7 12.8 1.8 11.3 0.5 10.6 1.3 99.0 2.3 6.9 0.9 6.3 0.9 54.1 0.8 12.1 5.2 0.92 0.8 0.82 0.5
Forest 0–46 6 K 96.1 61.5 34.6 24.4 29.5 5.2 4.0 3.3 12.9 1.11 0.18 0.17
0–6 R 69.7 4.5 65.2 15.6 17.9 15.8 3.4 3.0 161.8 2.00 0.50 0.27
0–59 7 K 93.0 73.8 19.2 27.2 33.6 28.6 5.0 3.8 14.1 8.53 0.76 0.16
0–10 R 79.3 0.0 79.3 15.8 20.0 12.0 3.9 3.1 130.6 1.47 0.43 0.42
0–45 8 K 85.2 50.4 34.8 27.8 25.3 7.2 4.3 3.4 15.9 1.30 0.28 0.16
0–7 R 70.6 0.4 70.2 15.6 16.2 19.1 4.0 3.2 100.1 1.97 0.60 0.46
0–38 9 K 68.4 29.6 38.8 22.3 23.8 5.3 4.0 3.1 43.2 0.69 0.19 0.32
0–7 R 70.2 0.0 70.2 13.9 29.5 5.2 3.9 3.0 257.9 1.24 0.38 0.41
Mean sd K 85.7 12.4 53.8 8.7 31.8 8.6 25.4 2.6 28.1 4.4 11.6 11.4 4.3 0.5 3.4 0.3 21.5 4.5 2.9 3.7 0.35 0.27 0.20 0.07
Mean sd R 72.5 4.6 1.2 2.2 71.2 5.9 15.2 0.9 18.4 1.7 14.5 3.8 3.8 0.3 3.1 0.1 163 68 1.7 0.37 0.48 0.09 0.39 0.08
ANOVA LU P-value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.097 <0.001 0.11 0.01
K/R P-value <0.001 <0.001 <0.001 <0.001 <0.001 0.49 0.65 0.86 0.01 0.14 0.98 0.69
LU x K/R P-value 0.65 <0.001 <0.001 0.002 0.14 0.66 0.38 0.53 0.006 0.44 0.73 0.60
Analysis of variance (ANOVA) was performed on the dataset to test the effect of land use (LU), kiln site (K/R) and their interaction (LU x K/R). P-values <0.05 are highlighted in gray.
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
exchangeable “base” cations (Ca2+, Mg2+, K+), whereas forest
soils were very desaturated.
K/R furthermore affected the contents of TOC, charcoal-
C and uncharred SOC, the C:N ratio and CEC. A significant
interaction with LU existed for charcoal-C (P<0.001) and
uncharred SOC (P<0.001) contents, the C:N ratio (P=
0.002) and the concentration of available P (P=0.006), which
indicates that the effect of K/R on these properties depends on
land use. The topsoil contents of total OC and charcoal-C were
always larger at CKS than at adjacent reference sites regardless
of land use, but the difference was larger in forest. Charcoal-C
constituted about a third of total C in cropland soil and half of
the total C in forest soil (Table 1). The soil C:N ratio and CEC
were also systematically higher at CKS. In forest soils, uncharred
SOC content was smaller at CKS than in adjacent reference
soils, whereas it is slightly larger at CKS in cropland soils. The
effect of CKS on the concentration of available P also strongly
depended on land use. In croplands, CKS and reference soils
have similar contents of available P and exchangeable K, whereas
these were significantly lower in forest CKS soils. In forest,
CKS soils also have slightly higher pHH2O and pHKCl values,
whereas pH values are very similar to that of reference soils
in croplands.
C-Mineralization Rates, Microbial
Abundance and Metabolic Quotient
In croplands, the absolute cumulative CO2emissions from CKS
soil were similar to that from adjacent reference soils. In contrast,
CO2emissions from forest CKS soils were much smaller than
that from adjacent reference soils (e.g., Figure 1A). If, however,
CO2emissions are expressed per unit of total C, they are
systematically smaller in CKS soil than in adjacent reference soil,
regardless of land use (Figure 1B). Data of C loss from CO2
emissions were fitted with double exponential models, which
consider the contribution of two pools of C to CO2emissions,
one fast-cycling and one slow-cycling. The models fitted the data
particularly well (>0.999). In croplands, the fast-cycling C
pool had a similar computed size and half-life in the CKS and
the reference soil (Table 2). In contrast, the computed size of
the fast-cycling pool in forests was about half of that in the
reference soil, but both had comparable turnover. In croplands,
the slow-cycling C pool in the CKS soils had an estimated
mean half-life of 22.2 years, more than twice as long as the
reference soils’ half-life (9.9 years). The slow-cycling C pool of the
forest CKS soils had a mean half-life of 61.3 years, again, about
double that of the adjacent reference soils’ slow C pool half-life
(32.5 years).
Total PLFA biomass is strongly (p<0.001) affected by LU,
K/R and the interaction LU ×K/R. The overall amount of total
PLFA is larger in forests than in croplands, whereas the effect
of K/R is antagonist depending on land use: in croplands, total
PLFA biomass in CKS soils is larger than in adjacent reference
soils but in forests it is much smaller than in adjacent reference
soils. Statistical analysis did not detect significant effects of LU,
K/R, or LU ×K/R for the qCO2.
Microbial Biomass and
Community Structure
Recovery of standard PLFA C21:0PC (added to the soil to test
whether charcoal interferes with the extraction of individual
PLFAs or not) from the soil was low (a few percent only), which
suggests that its digestion during extraction was incomplete. The
amount of C21:0 PC recovered from CKS soils was on average
43.6 ±45.9% larger (P=0.012) than from reference soils.
The permutational multivariate analysis of variance resulted
in a significant effect of LU (=0.686, P<0.001) but in a non-
significant effect of K/R (=0.030, P=0.188) on the PLFA
dataset. The r² score calculated for the interaction K/R x LU was
0.047 (P=0.098).
The distribution of the proportion of PLFAs between the
different treatments is illustrated by the principal component
analysis (Figure 2). The first component of the PCA explains
53.6% of total variance in the dataset and discriminates well-
between forest and cropland soils (r² =0.91, P<0.001).
The second axis explains 19% of total variance, and best
discriminates between CKS and reference soils (r² =0.24, P
=0.037). Scores of the fit of both PLFAs markers and soil
properties on the first and second principal components of the
PCA are presented in Table 3. Regarding PLFAs, all of them
have a significant contribution to the determination of the first
principal component (PC1) or the second (PC2) except the a
C17.0 marker that is not significantly represented. PLFAs C16.0,
C18.0, C18.1ω9c, and C.17.0 are the markers best explained by
PC2. From second principal component scores, it appears that
the microbial community structure of CKS and reference soils
differ more strongly in forests than in croplands. For forest
soils, CKS have systematically smaller scores than reference sites
in the second dimension of the PCA, whereas no systematic
difference appears for cropland soils (Figure 2). As excepted
for exchangeable Na (P=0.851) and Mg (P=0.083), the
fit of soil properties on PC1 and PC2 resulted in significant
squared correlation coefficients. TOC content, total N content,
soil pHH2O and pHKCl, exchangeable Ca and base saturation are
strongly (positively or negatively) correlated with PC1, whereas
Charcoal-C, the C:N ratio, available P and exchangeable Mg and
Na are strongly correlated to PC2 (Table 3).
Further investigation of the relative proportion of individual
PLFAs on total soil microbial biomass allowed identifying the
markers significantly (P<0.1) affected by CKS for both
land uses (Table 4). In croplands, the proportion of 10MeC16
(Actinomycetes) was larger in CKS than in reference soils
whereas the proportion of C16:1c9 (G-), C16:1c11 (Arbuscular
Mycorhizal Fungi, AMF) and C18:2c9,12 (saprotrophic fungi)
was smaller. In forests, the proportions of iC14:0 (G+),
aC16:0 (G+), C16:0 (general bacteria), iC17:0 (G+), aC17:0
(G+), C17:0 (general bacteria), C18:0 (general bacteria), and
C24:1ω9 (general eucaryotes) were larger in CKS than in
reference soils, whereas the proportion of C14:0 (general
bacteria), iC15:0 (G+) and iC16:0 (G+) was smaller. None
of the PLFAs were significantly affected for both forest and
cropland soils. Among PLFAs significantly affected in forests,
strong relationships were found with pHH2O (C14:0, iC15:0,
iC16:0, aC16:0, C16:0, C17:0, and C18:0), exchangeable Ca
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
FIGURE 1 | Mean cumulative emissions of CO2over time from kiln (K, black symbols) and reference (R, gray symbols) soils for the five study sites in cropland (circles)
and the four study sites in forest (triangles). Error bars correspond to one standard deviation. (A) Emissions of CO2per 100 g of dry soil; (B) Emissions of CO2per g of
total organic C (TOC).
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
TABLE 2 | Total PLFA microbial biomass, metabolic quotient (qCO2) at day 68 of incubation and parameters of the double exponential models fitted to data of total C
loss by CO2emissions from kiln (K) and reference (R) soils from cropland and forest during the 138 days incubation experiment.
C-mineralization
Land use Site K/R Total PLFA qCO2X1 Half-life X2 Half-life
nmol g1µgC d1nmol1gC kg1Yr gC kg1Yr
Cropland 1 K 17.1 0.152 0.139 0.076 38.3 34.8
R 16.8 0.178 0.166 0.077 15.3 13.0
2 K 15.6 0.179 0.154 0.087 31.0 29.7
R 12.1 0.223 0.130 0.073 14.0 12.7
3 K 25.2 0.147 0.138 0.059 34.6 18.6
R 19.9 0.175 0.142 0.066 16.3 9.5
4 K 18.3 0.172 0.119 0.041 20.5 12.8
R 16.1 0.187 0.116 0.057 12.0 7.9
5 K 15.6 0.220 0.159 0.046 26.5 15.0
R 18.4 0.183 0.126 0.040 11.3 6.3
Mean sd K 18.4 4.0 0.174 0.029 0.142 0.016 0.062 0.019 30.2 6.9 22.2 9.6
Mean sd R 16.7 3.0 0.189 0.019 0.136 0.019 0.063 0.015 13.8 2.1 9.9 2.9
Forest 6 K 27.8 0.130 0.231 0.085 95.9 72.0
R 55.3 0.107 0.371 0.083 69.3 33.5
7 K 15.7 0.288 0.290 0.101 92.7 56.5
R 56.5 0.270 0.560 0.107 78.8 34.4
8 K 20.8 0.151 0.111 0.075 85.1 59.6
R 55.7 0.140 0.595 0.105 70.0 27.9
9 K 25.9 0.124 0.186 0.139 68.2 56.9
R 49.2 0.102 0.257 0.078 70.0 34.1
Mean sd K 22.5 5.44 0.173 0.077 0.204 0.076 0.144 0.040 85.5 12.4 61.3 7.3
Mean sd R 46.7 13.8 0.154 0.078 0.446 0.157 0.135 0.021 72.0 4.5 32.5 3.1
ANOVA LU P-value <0.001 0.99 0.019 0.80 <0.001 <0.001
K/R P-value <0.001 0.50 <0.001 0.002 <0.001 <0.001
LU x K/R P-value <0.001 0.53 0.007 0.70 0.68 0.02
Analysis of variance (ANOVA) was performed on the dataset to test the effect of land use (LU), kiln site (K/R) and their interaction (LU x K/R). P-values <0.05 are highlighted in gray.
FIGURE 2 | Superimposition of the maps of variables (gray arrows) and individuals from the principal component analysis conducted on the 18 most abundant
phospholipid fatty acids (in percent of total PLFA concentration) of the studied soils. Kiln (K) and reference (R) soils from forest (triangles) and cropland (circles) are
represented by full and empty symbols, respectively.
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
TABLE 3 | Scores of individual PLFAs and soil properties on the first and second
components of the principal component analysis of PLFA’s microbial community
structure.
PLFAs PC1 PC2 r²Pr(>r)
iC15.0 0.804 0.594 0.71 0.003 **
aC15.0 0.976 0.218 0.62 0.001 ***
iC16.0 0.837 0.547 0.97 0.001 ***
C16.0 0.172 0.985 0.93 0.001 ***
X10MeC16 0.873 0.487 0.94 0.001 ***
iC17.0 0.723 0.691 0.36 0.034 *
aC17.0 0.676 0.736 0.11 0.438
C16.1c9 0.999 0.005 0.92 0.001 ***
C16.1c11 0.999 0.032 0.96 0.001 ***
C17.0 0.595 0.804 0.65 0.002 **
X10Me17.0 0.879 0.476 0.98 0.001 ***
cy17.0 0.999 0.012 0.91 0.001 ***
C18.0 0.214 0.976 0.85 0.001 ***
X10MeC18 0.975 0.220 0.75 0.001 ***
C18.1.w9c 0.257 0.966 0.82 0.001 ***
C18.1.w7 0.773 0.634 0.72 0.001 ***
C18.2c9.12 0.748 0.664 0.39 0.020 *
C22.0 0.799 0.600 0.48 0.008 **
SOIL PROPERTIES
OC 0.961 0.276 0.80 0.001 ***
Charcoal–C 0.298 0.954 0.60 0.001 ***
Uncharred SOC 0.716 0.698 0.87 0.001 ***
Ntot 0.947 0.322 0.83 0.001 ***
C:N ratio 0.556 0.831 0.55 0.003 **
pHH2O 0.989 0.146 0.88 0.001 ***
pHKCl 0.982 0.187 0.90 0.001 ***
Available P 0.298 0.954 0.42 0.013 *
Exchangeable Ca 0.996 0.087 0.78 0.001 ***
Exchangeable Mg 0.545 0.839 0.28 0.083
Exchangeable K 0.659 0.752 0.45 0.009 **
Exchangeable Na 0.120 0.993 0.02 0.851
Cation exchange capacity 0.644 0.765 0.64 0.002 **
Base saturation 0.985 0.174 0.89 0.001 ***
Asterisks indicate the level of significance for each score (***P0.001;
**P0.01; *P0.05).
(C14:0, iC15:0, iC16:0, aC16:0, C16:0, and C17:0), uncharred
SOC concentration (C14:0, iC15:0, iC16:0, aC16:0, C16:0, and
C18:0) and exchangeable K (iC17:0, C17:0). In contrast, no
clear relationship was found with charcoal-C concentration
for any of these PLFAs. For PLFAs significantly affected in
croplands, no clear link was found with any investigated soil
physico-chemical properties.
DISCUSSION
The Effect of Charcoal on CO2
Mineralization, Soil Microbial Abundance
and Metabolic Quotient
The small rate of respiration per unit of TOC in CKS soils
(Figure 1) and the nearly doubled turnover of the slow-cycling
C pool compared to reference soils (Table 2) confirms the
TABLE 4 | Proportion of individual PLFAs on total soil biomass that are statistically
different (P<0.1) between charcoal kiln sites (CKS) and adjacent reference soils,
according to pairwise t-tests.
PLFA Microbial
group
CKS soil Reference
soil
p-value
Mean ±s. d.
(% mol)
Mean ±s. d.
(% mol)
Cropland 10MeC16 Actinomycetes 5.30 ±0.26 4.71 ±0.39 0.004
C16:1c9 Gram negative
bact.
9.64 ±1.60 10.44 ±1.41 0.01
C16:1c11 Arbuscular
mycorrhizal
fungi
5.42 ±0.69 6.00 ±0.67 0.05
C18:2c9,12 saprotrophic
fungi
2.31 ±0.24 2.75 ±0.55 0.07
Forest iC14:0 Gram positive
bact.
0.72 ±0.16 0.43 ±0.07 0.01
C14:0 General bact. 0.58 ±0.16 0.83 ±0.18 0.02
iC15:0 Gram positive
bact.
6.16 ±1.51 7.64 ±1.59 <0.001
iC16:0 Gram positive
bact.
7.52 ±2.51 10.81 ±0.55 0.07
aC16:0 Gram positive
bact.
1.03 ±0.25 0.56 ±0.22 0.002
C16:0 General bact. 20.86 ±0.98 19.14 ±0.71 0.08
iC17:0 Gram positive
bact.
4.50 ±0.76 3.31 ±0.52 0.03
aC17:0 Gram positive
bact.
2.25 ±0.32 2.02 ±0.29 0.03
C17:0 General bact. 1.57 ±0.08 1.29 ±0.09 0.007
C18:0 General bact. 3.85 ±0.29 3.12 ±0.25 0.04
C24:1ω9 Gen.
eucaryotes
0.0053 ±0.003 0.0017 ±0.0013 0.03
well-known resistance of charcoal to biotic decomposition. A
similar decrease of the mineralization potential of SOC was
observed in soils historically enriched with BC, and the poor
degradability of BC was related to its aromatic structure (Cheng
et al., 2008; Liang et al., 2008, 2010). The low degradability
of polycyclic aromatic C for soil biota has been attributed to
the large activation energy required for cleavage of aromatic
C bonds (Plante et al., 2009). Despite being longer than that
of reference soils, average half-lives of 22.2 ±9.6 years (in
cropland) and 61.3 ±7.3 years (in forest) for the stable pool
of total C of CKS probably did not specifically represent BC.
Indeed, the computed half-life seems too short to correspond
to the half-life of charcoal that was introduced in soil >150
years ago. The decay of the slow-cycling pool, as defined by the
double exponential model, is therefore probably mainly related
to the decomposition of more stable fraction of the uncharred
SOM. Emissions of CO2from charcoal are likely minor on
the timescale of the current incubation experiment (Cheng
et al., 2008; Liang et al., 2008; Kuzyakov et al., 2009). With the
limited duration of the experiment and number of observations
available, inclusion of a third kinetic C pool was, however, not
warranted as this would over-parametrize the model and yield
non-robust predictions of decay rates of the least reactive char
pool (Bird et al., 2015).
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
Since the contribution of aged charcoal to total CO2emissions
are assumed to be low or even negligible at the timescale of our
incubation, we tried to estimate the efficiency of uncharred SOM
C-mineralization by calculating the rate of CO2emissions per
unit of uncharred SOC, assuming that charcoal’s contribution to
CO2emissions is negligible. As a result, there was no systematic
effect of CKS on soil CO2emissions per unit of uncharred SOC.
However, CO2emissions per unit of uncharred SOC correlated
strongly with soil pH-H2O (Figure 3), with r0.91 for emission
rates throughout the 138 days incubation period. This result
attests that soil acidity explains a main part of the variance
of soil CO2emissions once expressed per unit of uncharred
SOC, also indicating indirectly that CO2emissions are governed
by the content of uncharred SOM, suggesting no or a limited
effect of charcoal on C-mineralization. The large range of soil
pH mainly governed by land use thus at first sight seems to
have an overriding control on microbial respiration, surpassing
the effect of large amounts of charcoal present in the soil. The
linear increase in CO2emissions per unit of uncharred SOC
with pH is likely due to an increase in microbial abundance.
Indeed, the relationship between soil respiration rate at day 68
and PLFA content per unit of C were linearly related, particularly
in croplands (r=0.97) but also in forests (r=0.82) (Figure 4).
These results agree with those of Aciego Pietri and Brookes
(2008) who found that pH was a dominant driver of both
soil CO2emissions and total microbial C biomass along a pH
gradient from 3.7 to 8.3 in UK arable soil. Such a shift in pH
can be expected to dominantly affect the bacterial rather than
fungal population (Rousk et al., 2010). However, here the higher
soil pH of croplands (pH-H2O 5.8–8.3) vs. forests (pH-H2O
3.4–5) was accompanied by differences in soil OM quality as
well. While we did not further characterize the uncharred OC,
the smaller C:N ratio (P<0.001) of cropland R sites (11.3)
than forest sites (15.2) clearly points to a more labile OM in
croplands and a faster turnover of SOM. For instance Springob
and Kirchmann (2003) found that above a C:N ratio of 15,
German Pleistocene sandy soils quite suddenly contained a large
fraction of refractory OM with a low specific rate of N supply.
Accordingly, a close negative relationship existed between the
amount of PLFA per unit of C and the C:N ratio of SOM
(Figure 5), at least at a C:N ratio above about 12. Since a close link
also exists between total PLFA and respiration rate (Figure 4), the
increase in CO2emissions with lower a C:N ratio is most likely
related to a larger amount of total microbial biomass per unit
of uncharred SOC. Regarding microbial efficiency, the qCO2at
day 68 of incubation is similar between CKS and reference soils
(Table 2), which suggest that long-term soil charcoal enrichment
is predominantly related to the abundance of microorganisms in
soil (Figure 4).
Besides the effect of pH and SOM quality on microbial
respiration, Kerré et al. (2017) measured a smaller mineralization
of fresh SOM (traced by 13C isotopic signature) when added
to a pre-industrial CKS soil. They proposed that an increase of
the sorption of dissolved organic carbon (DOC) might explain
this decrease, because they measured a preferential adsorption of
the DOC rich in aromatics in presence of charcoal in another
experiment. This result suggests that beyond the role of pH,
FIGURE 3 | Total emissions of CO2per unit of uncharred SOC after 7 days of
incubation against soil pH measured in water (pH-H2O) for kiln (K, black
symbols) and reference (R, gray symbols) soils from cropland (circles) and
forest (triangles).
FIGURE 4 | Daily release of CO2per unit of total organic carbon (TOC) against
the content of PLFA per unit of TOC at day 68 of incubation for kiln (K, black
symbols) and reference (R, gray symbols) soils from cropland (C, circles) and
forest (F, triangles). Regression lines refer to the two different land uses.
FIGURE 5 | Total PLFA content per unit of total organic carbon (TOC) against
C:N ratio for kiln (K, black symbols) and reference (R, gray symbols) soils from
cropland (circles) and forest (triangles).
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
direct interactions of charcoal with the labile, soluble fraction
of SOM might influence the mineralization kinetics of labile
SOM. To sum up, for the soils of this study developed on
a same parent material but affected by distinct land use and
levels of charcoal enrichment, the C:N ratio, an indicator of
the degradability of SOM (thus integrating the proportion of
charcoal and uncharred SOM in soil), was closely related to
microbial abundance in soil per unit of total OC. Jointly,
microbial abundance was closely and linearly related to the rate
of soil respiration, regardless of the presence of charcoal, which
agrees with the similar microbial efficiency (expressed by the
qCO2) in CKS and adjacent reference soils. It cannot be attested
from our data that the effect of aged charcoal on soil respiration
and microbial abundance is negligible, nonetheless, most results
suggested a minor effect of charcoal, in contrast to the content
of uncharred SOM and pHH2O which explain a main fraction of
the variance for these variables. Overall, our results agree with
a (very) slow turnover of BC in soil regardless of land use and
therefore has a limited effect on total soil microbial biomass
and activity.
The Effect of Charcoal on Microbial
Community Structure
The presence of charcoal increased the recovery of the C21:0 PC
standard, that was added to the soil at the start of the extraction,
by 43.6%. This disagrees with the findings of Gomez et al.
(2014), who observed a proportional decrease in the recovery
of C21:0 PC with increasing applications of biochar. This
discrepancy might result from the deep changes in properties
of charcoal through >150 years of aging in soil (Hardy et al.,
2017b), including a shift from highly hydrophobic to hydrophilic
surfaces. This shift is attributed to the creation of a high density
of oxygenated functional groups (mainly carboxylic) at the
surface of charcoal by oxidation over time (Cheng et al., 2006).
Accordingly, Criscuoli et al. (2014) estimated that the soil of
centennial CKS was 97.3% less hydrophobic than an adjacent
reference soil. This dramatic decrease in hydrophobicity probably
attenuates the affinity of charcoal for dissolved phospholipids.
It is also likely that, over time, most sites at the surface
of charcoal reactive toward dissolved organic molecules have
become saturated. The differing recovery of the C21:0 standard
for CKS and R sites probably does not reflect a likewise impact
on extractability of PLFAs, because these are predominantly part
of living microbial cells (i.e., in cell membranes), so not as free
molecules. Nevertheless, it is clear that a comparison of absolute
contents of PLFAbetween CKS and R soils needs to be considered
with care. Assuming a non-selective impact of char presence on
the extraction of various PLFAs to their least relative abundances
could be compared between different soils.
Both the permutational multivariate analysis of variance and
the PCA illustrated that land-use had an overriding control
on microbial community structure, surpassing the effect of a
vast amount of charcoal present in the soil. The second axis of
the PCA discriminated well-between CKS and reference soils
(Figure 2), but the distance between CKS and reference soils was
much larger for forest than for cropland soils. Further analysis of
individual PLFAs highlighted that the shift affected mainly PLFAs
linked to G+and general bacteria. For most of these PLFAs,
their proportion on total PLFA biomass was strongly (either
positively or negatively) related to soil pHH2O, concentration
of exchangeable Ca2+and concentration of uncharred SOC
(data not shown). In croplands, the effect of CKS was limited,
slightly affecting four PLFAs from four distinct microbial groups
(actinomycetes, AMF, saprotrophic fungi and general eukaryotes,
Table 4). There was no clear relationship between these PLFAs
and soil physico-chemical properties. The limited effect of
charcoal enrichment in croplands might be caused by the
use of fertilizers and liming amendments that standardize soil
chemical conditions between CKS and reference soils, whereas
in forests the residual effect of charcoal production on several
soil properties is still clear (Hardy et al., 2016). Another point
to consider is the difference in the depth of sampling between
CKS and reference soils in forests. In contrast to croplands,
where limiting nutrients are compensated by the application of
fertilizers and where SOM is diluted in the plow layer due to
frequent tillage, available nutrients accumulate in the forest litter
and topsoil as a result of the biological recycling of nutrients,
related to uptake by the root system of plants and the restitution
by decomposition of forest litter and SOM (Jobbagy and Jackson,
2000). Accordingly, the difference in sampling depth in forests
might have accentuated the difference between the charcoal-rich
A horizon of CKS soils and the Ahhorizon of reference soils.
Lehmann et al. (2011) concluded that the effect of charcoal on
soil biology strongly relies on the group of microorganisms as
well as initial soil properties, which were clearly different in
both investigated land-uses here. For example, concentrations of
available P and exchangeable K were not significantly affected by
CKS in the plow layer of agricultural soils (Hardy et al., 2017a),
whereas both were strongly lowered in the A horizon of forest
soils (Hardy et al., 2016). It was also shown that charcoal had
an antagonist effects on soil pH according to land use, with an
increase of pH in very acidic forest soils (Hardy et al., 2016)
and a slight but significant decrease of pH in agricultural soil
with an acidity close to neutral. This consideration, combined
with the absence of a strong relationship with the concentration
of charcoal-C for PLFAs significantly affected by CKS at the
scale of the dataset, supports the view that the effect of aged
charcoal on microbial community structure is not mainly related
to an alteration of the source of organic C available to soil
biota but rather to a modification of the drivers of microbial
growth and activity such as the availability of nutrients (Steiner
et al., 2009; Blackwell et al., 2010), specific microhabitats in
the porosity of charcoal or a shift in pH (Rousk et al., 2010).
This is in line with the high resistance to decomposition of
the most stable fraction of charcoal that survived oxidation on
centennial timescales. Microbial analyzes of terra preta soils
have highlighted an important shift in microbial taxonomy from
adjacent soils (Kim et al., 2007; Grossman et al., 2010; Jin, 2010).
In light of our results, it can be speculated that the introduction
of various organic and inorganic inputs involved in the genesis
of terra preta soils, and contrasting land use history related to
an improved soil fertility of terra preta soils, might have had
more influence on the microbial community structure than BC
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Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
itself. A closer look to the abundance of C16:1c11, a biomarker
for AMF, stresses the dependence of the effect of charcoal
with soil conditions again, as well as the divergence between
long-term and short-term effects. In forests, the proportion of
AMF was larger in CKS soils (2.33 ±0.49%) than in adjacent
reference soils (1.97 ±0.36%). This increase might be related
to the lower availability of P. Vegetation likely responded
by a promoting development of AMF, that aids in plant P-
acquisition. A decreased abundance of AMF was observed
shortly after the addition of biochar to soil and attributed to
a temporary increase in nutrient availability, reducing the need
for symbionts (Lehmann et al., 2011). In line with this, the
proportion of AMF in CKS soils from croplands, where nutrient
availability is much larger, is significantly decreased (P=0.05,
Table 4). In croplands, the presence of charcoal in the soil might
also alter the activity of fungicides, as reported previously for
other phytopharmaceuticals such as contact herbicides (Nag
et al., 2011). Therefore, a research perspective is to study how
the presence of aged charcoal interacts with fungicides and
consequently influences the populations of beneficial AMF or
pathogen fungi responsible for soil-prone diseases.
CONCLUSIONS
In this research, preindustrial charcoal kiln sites were used as
a natural field experiment to investigate the (very) long-term
(>150 years) effect of charcoal on microbial properties of forest
and cropland soils, which is an original approach to unravel the
long-term fate of biochar in soil. The following conclusions and
research perspectives were drawn from the results:
1. Double exponential models are inadequate to capture the
long-term dynamics of charcoal-C in soil at the time scale of
our experiment, probably because aged charcoal is a negligible
source of CO2emissions from soil. Assuming that charcoal
does not contribute significantly to soil respiration, we found
that CO2emissions per unit of uncharred SOC were strongly
correlated with soil pH, which supports the idea that charcoal
is a minor or negligible driver of soil respiration that is
governed mainly by the content and quality of uncharred SOM
and soil acidity. These results agree with the long residence
time of BC in soil.
2. The C:N ratio appeared to be a good indicator of microbial
abundance in soil per unit of TOC, reflecting at the same time
the proportion of charcoal and uncharred SOC in soil as well
as their respective degradability. Jointly, microbial abundance
was closely and linearly related to the rate of soil respiration,
regardless of the presence of charcoal, which underlines the
similar metabolic quotient in CKS and adjacent reference soils.
3. The higher recovery of standard PLFA (C21:0 PC) added to
soil in presence of aged charcoal contrasts with the decreased
recovery recorded shortly after addition of biochar to the soil
(Gomez et al., 2014). This result underlines that the properties
of charcoal evolve dramatically over long periods of time.
Accordingly, many long-term effects of charcoal differ from
the short-term effects. In the perspective of amending soils
with biochar, a long-term vision is therefore critical.
4. In forests, the community structure of CKS soils was clearly
different from that of adjacent reference soils, with 10 PLFAs
from gram positive and general bacteria significantly affected.
Contrastingly, few differences with adjacent reference soils
remained in croplands, with only four PLFAs from fungi, gram
negative bacteria and actinomycetes significantly affected. In
cropland soils that are frequently fertilized and amended, the
long-term effect of biochar on soil microbiota is likely to be
overwritten by management practices. The strong interaction
between the effect of aged charcoal and soil conditions
complicates the prediction of the effects that can be expected
from an application of biochar to soil. Biochar properties must
therefore be regarded together with soil conditions in order to
correctly design a successful soil amendment with biochar.
5. The lack of a relationship between individual PLFAs and
charcoal-C content supports the idea that the long-term effect
of charcoal is mainly related to a modification of soil ecological
niche (e.g., related to a shift in pH or in nutrient availability
or the presence of microhabitats in the porous structure of
charcoal) rather than to an alteration of the source of organic
C available to biota. This assumption agrees with the low
reactivity of aged charcoal in soil.
As a research perspective, new tools in molecular biology might
allow the identification of specific microbial groups related to
the presence of charcoal, either due to an intrinsic ability to
decompose charcoal, or to specific microhabitats provided by
charcoal’s porosity. We also encourage further studies to decipher
the mechanisms by which charcoal may influence microbial
groups of high ecological or agronomic importance such as AMF
and soil-borne pathogens.
AUTHOR CONTRIBUTIONS
The work was designed by BH, J-TC, and JD. Field work was
carried out by BH and JD. Soil physico-chemical analyses and
the incubation experiment was performed by BH. SS ran PLFA
analyses. Data was analyzed by BH and SS. The manuscript was
drafted by BH and revised by SS, J-TC, and JD.
ACKNOWLEDGMENTS
We thank Jens Leifeld from the Institute for
Sustainability Sciences of the Agroscope of Zürich (Switzerland)
for his help in DSC analysis, the technical team of the Earth
and Life Institute of UCL for strong support in field work
and soil physico-chemical analyses, and the Department of
Soil Management of UGent for PLFA extraction. Funds were
provided by the General Directorate for Agriculture, Natural
Resources and Environment—Public Service of Wallonia and the
FSR (Fonds Spéciaux de Recherche) of the Université catholique
de Louvain.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fenvs.
2019.00110/full#supplementary-material
Frontiers in Environmental Science | www.frontiersin.org 12 July 2019 | Volume 7 | Article 110
Hardy et al. Long-Term Effect of Charcoal on Soil Microbiology
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2019 Hardy, Sleutel, Dufey and Cornelis. This is an open-access article
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Frontiers in Environmental Science | www.frontiersin.org 14 July 2019 | Volume 7 | Article 110
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The physiological quality of seedlings in the nursery stage is essential to guarantee their adaptation and survival to post-transplant stress in the field. This study aimed to evaluate the effects of biochar and biofertilizers on the growth and quality of Coffea arabica cv. Sarchimor-1669 plants in the nursery. The evaluated treatments were: biochar (T1), biofertilizer (T2), biochar + biofertilizer (T3), chemical fertilization (T4), and a control (T5). Biochar was applied in doses of 20 g kg-1 in the substrate. The biofertilizer used was a native microbial consortium consisting of bacteria, mycorrhizae, fungi and yeasts, which was applied in doses of 5 mL L-1 using water. The main variables under study were: dry matter content (DMC), leaf area (LA), relative growth rate (RGR), net assimilation rate (NAR) and Dickson’s quality index. The results showed significant differences (p<0.05) for all the variables evaluated. The treatments T1, T2, T3 and T4 were statistically similar, but they presented differences with respect to the control treatment. The biochar + biofertilizer mixture (T3) reached higher dry matter and leaf area per plant compared to the other treatments, with values of 8.28 g and 316.63 cm2 , respectively. This treatment also recorded higher RGR, NAR and Dickson’s quality index. The quality of the plants was positively correlated with the growth variables. It is concluded that the application of biochar and biofertilizer tends to enhance both growth and quality of coffee seedlings in the nursery. However, further research is required to evaluate higher doses and application frequencies in order to achieve conclusive results.
... Previously, Li et al. [68] and Hardy et al. [69] reported that biochar application alters the soil bacterial community composition. In the current study, biochar application demonstrated the highest relative abundance of Proteobacteria, Actinobacteria, Acidobacteriota, Chloroflexi, Firmicutes, and Bacteroidota than the control treatment. ...
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Biochar application can enhance soil health and alter soil bacterial community structure. However, knowledge relating to biochar on soil nutrients of mountainous apple orchards and then assessing its effect on soil health, especially on soil microorganisms, is still scanty. Therefore, we evaluated the responses of six biochar treatments [Ck (0), T1 (2), T2 (4), T3 (6), T4 (8), and T5 (10) Mg hm−2] with a basal dose of chemical fertilizer on the soil nutrients under potted apple trees across 3, 6, 9, and 12 months, and then investigated the responses of the rhizobacterial communities. Experimental findings demonstrated that: (i) Across the months, the biochar-applied treatment (T5) compared to the control significantly enhanced soil nutrients, including soil pH (2.12 to 2.29%), soil organic matter (35 to 40%), total nitrogen (59 to 65%), ammonium nitrogen (25 to 33%), nitrate nitrogen (163 to 169%), and the activities of urease (76 to 81%), alkaline phosphatase (30 to 33%), catalase (8.89 to 11.70%), and sucrase (23 to 29%). (ii) Compared to the control, the biochar-applied treatment (T5) had a more desirable relative abundance of the bacterial phylum Proteobacteria (35.47%), followed by Actinobacteria (8.59%), Firmicutes (5.74%), and Bacteroidota (2.77%). Similarly, the relative abundance of the bacterial genera in the T5 was Sphingomonas (8.23%) followed by RB41 (3.81%), Ellin6055 (3.42%), Lachnospiracea (1.61%), Bacillus (1.43%), Kineosporia (1.37%), Massilia (0.84%), and Odoribacter (0.34%) than the control. (iii) Among the alpha diversity, the biochar-applied treatment (T5) revealed the highest Chao1 (20%) and ACE (19.23%) indexes, while Shannon (1.63%) and Simpson (1.02%) had relatively lower indexes than the control. Furthermore, positive correlations were found between the soil nutrients and some of the abundant bacterial phyla. Overall, the findings of this research demonstrated that biochar application at 10 Mg hm−2 (T5) along with the required chemical fertilizer is beneficial to improve soil health and pave the way for sustainable production in apple orchards of the northern loess plateau.
... Biochar (BC) is a key amendment that upgrades the fertility status of soil and is carbon-rich and also has a significant amount of certain nutrients (Hardy et al. 2019). As compared to other organic amendments, it is stable in soils for a prolonged period (Ding et al. 2019). ...
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... Biochar is a carbon-rich product of the pyrolysis process intended to be used as a soil amendment to improve the physical and chemical characteristics of soil and mitigate climate change by sequestering carbon. When applied to soil, biochars, due to their large internal surface area, increase soil porosity, cation exchange capacity (CEC), and water holding capacity (WHC), improve the soil as a microbial habitat, and provide plant nutrients [1][2][3][4][5][6][7][8][9]. Biochar is a thermochemically modified product with high carbon content, large specific surface porous structure, and various surface functional groups formed during the pyrolysis of biomass under anoxic conditions at 450-550 • C (plant biomass) or 550-850 • C (animal byproducts). ...
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Sugarcane bagasse (SCB) is the fibrous lignocellulosic residue left over after crushing sugarcane to extract juice for sugar and ethanol production. In this review, a concise overview of existing thermochemical technologies for the production of biochar from SCB and its potential applications is presented and discussed. Some of the technologies used so far in this regard include pyrolysis, gasification, hydrothermal carbonization, and torrefaction. However, pyrolysis was found to be the most widely used among them. These processes can be affected by several operating conditions such as temperature, heating rate, particle size, and residence duration, with temperature being the most significant and efficient variable influencing the quality of the biochar. The yield of SCB biochar reported in the literature ranged from 14% to 56%. A higher yield of biochar can be obtained at a lower temperature than at a higher one because biochar decomposes at higher temperatures (>500 °C). SCB biochar has promising applications in agriculture and the environment, including soil amendment, adsorbent in water and wastewater treatment, supplementary cementitious material, amongst others. Some knowledge gaps were also stated in the study, such as the cost analysis and comparison of utilizing bagasse as fuel in sugar industries and for the production of biochar. Sugarcane bagasse biochar has the potential to become a highly promising carbon material with a wide range of applications in a variety of sectors.
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The physiological quality of seedlings in the nursery stage is essential to guarantee their adaptation and survival to post-transplant stress in the field. This study aimed to evaluate the effects of biochar and biofertilizers on the growth and quality of Coffea arábica cv. Sarchimor-1669 plants in the nursery. The evaluated treatments were: biochar (T1), biofertilizer (T2), biochar + biofertilizer (T3), chemical fertilization (T4), and a control (T5). Biochar was applied in doses of 20 g kg-1 in the substrate. The biofertilizer used was a native microbial consortium consisting of bacteria, mycorrhizae, fungi and yeasts, which was applied in doses of 5 mL L-1 using water. The main variables under study were: dry matter content (DMC), leaf area (LA), relative growth rate (RGR), net assimilation rate (NAR) and Dickson's quality index. The results showed significant differences (p<0.05) for all the variables evaluated. The treatments T1, T2, T3 and T4 were statistically similar, but they presented differences with respect to the control treatment. The biochar + biofertilizer mixture (T3) reached higher dry matter and leaf area per plant compared to the other treatments, with values of 8.28 g and 316.63 cm2, respectively. This treatment also recorded higher RGR, NAR and Dickson's quality index. The quality of the plants was positively correlated with the growth variables. It is concluded that the application of biochar and biofertilizer tends to enhance both growth and quality of coffee seedlings in the nursery. However, further research is required to evaluate higher doses and application frequencies in order to achieve conclusive results.
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Black carbon (BC) plays an important role in terrestrial carbon storage. Nevertheless, the effect of cultivation on long term dynamics of BC in soil has been poorly addressed. To fill this gap, we studied the chemical properties of charcoal particles extracted from preindustrial kilns in Wallonia, Belgium, along a chronosequence of land use change from forest to agricultural soil, up to 200 years of cultivation. Preindustrial charcoal samples were compared with charcoal subjected to short-term ageing in a currently active kiln. Cultivation increased association of charcoal with soil minerals, which is favored by deprotonation of carboxylic acids under liming, thereby enhancing the reactivity of charcoal towards mineral surfaces. The large specific surface area of charcoal, related to its porosity, promotes the precipitation of 2:1 phyllosilicates and CaCO3. Both ageing and cultivation decreased the resistance of charcoal to dichromate oxidation, related to an increase of the H/C of charcoal. Differential scanning calorimetry revealed the presence of three fractions of distinct thermal stability. Saturation of carboxylate groups with Ca2+ under liming decreased thermal stability of the O-rich, less thermally stable fraction of charcoal. This fraction decreased over time of cultivation, leading to the relative accumulation of the thermally most stable fraction of charcoal. This might result from the preferential loss of the O-rich fraction or the slowdown of charcoal from oxidation by association with minerals. Our results highlighted that land use significantly affects the properties of BC through the modification of soil conditions, which might influence the kinetics of BC loss from soil.
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Research on biochar has increased, but its long-term effect on the fertility of temperate agricultural soil remains unclear. In Wallonia, Belgium, pre-industrial charcoal production affected former forested areas that were cleared for cultivation in the nineteenth century. The sites of traditional charcoal kilns, largely enriched in charcoal residues, are similar to soil amended with hardwood biochar more than 150 years ago. We sampled 17 charcoal kiln sites to characterize their effect on soil properties compared with adjacent reference soils. Charcoal-C content was estimated by differential scanning calorimetry. The kiln soil contains from 1.8 to 33.1 g kg−1 of charcoal-C, which markedly increases organic C:N and C:P ratios. It also contains slightly more uncharred soil organic carbon (SOC) than the reference soil, which accords with larger total N content.We measured a small increase in nitrates in the kiln soil that might relate to greater mineralization and nitrification of organic N. Frequent application of lime raised the pH to values close to neutral, which offset the residual effect of charcoal production on soil acidity. A cation exchange capacity (CEC) of 414 cmolc kg−1 was estimated for charcoal-C, whereas that of uncharred SOC was 213 cmolc kg−1. Despite the large CEC of the kiln soil, exchangeable K+ content was no different from the adjacent soil, whereas exchangeable Ca2+ and Mg2+ contents were considerably larger. Charcoal enrichment has little effect on available, inorganic and total P, but it can form strong complexes with Cu, which reduces the availability of the metal. Biochar is very persistent in soil; therefore, long-term implications should not be overlooked.
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Previous field observations have shown increased soil carbon (C) sequestration in charcoal amended soils due to an accumulation of non-charcoal derived soil C. This study was set up to compare and analyse mineralization of non-charcoal derived C between soils that were either or not historically enriched in charcoal. Maize straw (13C-enriched) was added to samples of arable soil collected under historical charcoal kilns and corresponding adjacent control soil. The respiration was monitored in laboratory conditions for 227 days. Charcoal in soil significantly lowered total soil respiration (1905 vs. 1984 mg C kg−1). Mineralization of 13C-enriched added maize C (AMC) was unaffected by charcoal in the initial weeks after maize straw addition, however differences became significant at longer incubations yielding a markedly lower mineralized fraction in the charcoal enriched samples after 227 days (70 versus 62%, P < 0.05). A two fraction mineralization model revealed no charcoal effect on the labile fraction and its degradation but that the stable fraction of AMC was larger and degraded slower in the presence of charcoal. A soil drying-rewetting event (35 days) increased respiration to the same extent in charcoal-enriched as in adjacent soils. In contrast, the dissolved organic carbon (DOC) in pore water was significantly lower in charcoal-enriched than in adjacent soils. Microbial biomass-C (MBC) determined by fumigation-centrifugation was not significantly different between charcoal-enriched and adjacent soil (309 mg vs. 266 mg MBC kg−1). A soil adsorption experiment with DOC, extracted from a grassland soil, revealed larger DOC sorption with increasing soil charcoal concentration. This study shows that reduced C mineralization of non-charcoal C in charcoal-enriched soil is most likely related to enhanced sorption of more recalcitrant organic matter, rather than to lower MBC.
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In Wallonia, Belgium, intensive in situ charcoal production that was linked closely to pre-industrial smelting and steel-making affected a large part of the forested area in the late eighteenth century. Charcoal kiln relics can be detected under forest as domes of about 10 m in diameter, with the topsoil greatly enriched with charcoal residues. We sampled 19 charcoal kiln sites and the adjacent reference soil by soil horizon on four different soil types (Arenosols, Luvisols, Cambisols and Podzols). Data were analysed with linear mixed models to assess the effect of the charcoal kiln site on soil properties in relation to depth and soil conditions. We also addressed the evolution of soil properties over time by a comparison of the soil characteristics at a currently active kiln site. The charcoal-rich topsoil has a larger C:N ratio and cation exchange capacity (CEC) per unit of organic carbon than the reference soil. The largest CECs per unit of carbon were observed on soil with coarser textures. On acidic soil, the increase in base saturation in the subsoil reflects the past liming effect of ash produced by wood charring, whereas the topsoil is re-acidified. The acidity of carbonate-rich Cambisols, however, is not reduced. Regardless of soil type, the kiln topsoil is greatly depleted in exchangeable K+ and available P, which may be attributed to the small affinity of the exchange complex of charcoal for K+ and a decrease in P availability with time. Therefore, we recommend further research on the long-term effects of biochar on the dynamics of plant nutrients.