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Environment International

journal homepage: www.elsevier.com/locate/envint

Plant litter enhances degradation of the herbicide MCPA and increases

formation of biogenic non-extractable residues in soil

Karolina M. Nowak

a,b,⁎

, Anja Miltner

, Christian Poll

, Ellen Kandeler

, Thilo Streck

Holger Pagel

Technische Universität Berlin, Institute of Biotechnology, Chair of Geobiotechnology, Ackerstraße 76, 13355 Berlin, Germany

Helmholtz-Centre for Environmental Research –UFZ, Department of Environmental Biotechnology, Permoserstr. 15, 04318 Leipzig, Germany

University of Hohenheim, Institute of Soil Science and Land Evaluation, Department of Soil Biology, Emil-Wolﬀ-Str. 27, 70599 Stuttgart, Germany

University of Hohenheim, Institute of Soil Science and Land Evaluation, Department of Biogeophysics, Emil-Wolﬀ-Str. 27, 70599 Stuttgart, Germany

ARTICLE INFO

Handling Editor: Hefa Cheng

Keywords:

Organic amendment

Pesticide fate

Fatty acids

Amino acids

Bound residues

Risk assessment

ABSTRACT

Amendment of soils with plant residues is common practice for improving soil quality. In addition to stimulated

microbial activity, the supply of fresh soluble organic (C) from litter may accelerate the microbial degradation of

chemicals in soils. Therefore, the aim of this study was to test whether the maize litter enhances degradation of

4-chloro-2-methylphenoxyacetic acid (MCPA) and increases formation of non-toxic biogenic non-extractable

residues (bioNERs). Soil was amended with

-MCPA and incubated with or without litter addition on the top.

Three soil layers were sampled with increasing distance from the top: 0–2 mm, 2–5 mm and 5–20 mm; and the

mass balance of

-MCPA transformation determined.

Maize litter promoted microbial activity, mineralization of

-MCPA and bioNER formation in the upper

two layers (0–2 and 2–5 mm). The mineralization of

-MCPA in soil with litter increased to 27% compared to

only 6% in the control. Accordingly, maize addition reduced the amount of extractable residual MCPA in soil

from 77% (control) to 35% of initially applied

-MCPA. While non-extractable residues (NERs) were < 6% in

control soil, litter addition raised NERs to 21%. Thereby, bioNERs comprised 14% of

-MCPA equivalents. We

found characteristic diﬀerences of bioNER formation with distance to litter. While total NERs in soil at a distance

of 2–5 mm were mostly identiﬁed as

C-bioNERs (97%), only 45–46% of total NERs were assigned to bioNERs

in the 0–2 and 5–20 mm layers. Phospholipid fatty acid analysis indicated that fungi and Gram-negative bacteria

were mainly involved in MCPA degradation. Maize-C particularly stimulated fungal activity in the adjacent soil,

which presumably facilitated non-biogenic NER formation. The plant litter accelerated formation of both non-

toxic bioNERs and non-biogenic NERs. More studies on the structural composition of non-biogenic NERs with

toxicity potential are needed for future recommendations on litter addition in agriculture.

1. Introduction

Microbial degradation ultimately degrades pesticides in soil

(Kästner et al., 2014) and results in the formation of transformation

products, microbial biomass, mineralization products and non-ex-

tractable residues (NERs; Barriuso et al., 2008). NERs in soils are con-

sidered as a ‘black box’since their structural identity in most cases is

unexplained due to the complexity of the soil matrix and to the asso-

ciated analytical challenges (Barriuso et al., 2008; Kästner et al., 2014).

Special care is given to non-biogenic NERs which may contain the toxic

parent pesticide or its transformation products (Barriuso et al., 2008;

Kästner et al., 2014). The parent pesticide and/or its transformation

products can be physically sequestered within solid matrix (as NERs

type I) or covalently bound to organic matter (OM) of soil (as NERs type

II) (Barriuso et al., 1997; Barriuso et al., 2008; Kästner et al., 2014).

Physically sequestered chemicals can be remobilized from soil after

freeze-thawing or heavy rain events causing delayed environmental

pollution (Barriuso et al., 2008; Kästner et al., 2014). However, NERs

from several

C-labeled pesticides, e.g. dichlorophenoxyacetic acid

(2,4-D) (Nowak et al., 2011), metamitron (Wang et al., 2017) and

glyphosate (Muskus et al., 2019; Muskus et al., 2020) in soil could be

largely assigned to the non-toxic biogenic NERs (bioNERs). The bi-

oNERs are formed by assimilation of pesticide-derived carbon (C) into

the microbial biomass, e.g. fatty acids (FAs) and amino acids (AAs), and

https://doi.org/10.1016/j.envint.2020.105867

Received 2 March 2020; Received in revised form 22 April 2020; Accepted 3 June 2020

⁎

Corresponding author at: Technische Universität Berlin, Institute of Biotechnology, Chair of Geobiotechnology, Ackerstraße 76, 13355 Berlin, Germany.

E-mail address: [email protected] (K.M. Nowak).

Environment International 142 (2020) 105867

Available online 22 June 2020

(http://creativecommons.org/licenses/BY/4.0/).

stabilization of biomass residues in non-living OM after microbial death

(Nowak et al., 2011; Wang et al., 2017).

The addition of plant residues to agricultural topsoils is common

farming practice which improves soil physico-chemical properties,

provides habitats to mesofauna, and prevents soils from erosion (López-

Piñeiro et al., 2013; Wild et al., 2014). The soluble organic C and nu-

trients from decomposing plant residues (so-called ‘detritusphere’)

promote microbial growth and activity as well as pesticide biode-

gradation (Poll et al., 2010). Therefore, the plant residue may also re-

duce the environmental risk of applied pesticides by promoting faster

mineralization and bioNER formation (Ghani and Wardle, 2001; Shaw

and Burns, 2003; Gerhardt et al., 2009; Ditterich et al., 2013; Pagel

et al., 2016; Saleh et al., 2016).

4-chloro-2-methylphenoxyacetic acid (MCPA) represents the phe-

noxyacetic acid class of pesticides (Zaprasis et al., 2010). MCPA is

commonly used herbicide and is the third top non-agriculture pesticide

on the list of pesticide sales (US EPA, 2017). In addition, the de-

gradation pathways of MCPA are well described and this pesticide is

structurally similar to other phenoxyacetic acid herbicide 2,4-D from

which major formation of bioNERs has been documented (Nowak et al.,

2011). Poll et al. (2010) have already shown that soluble C from the

maize litter on topsoil promoted microbial conversion of

C-MCPA to

in soil. This suggests that maize litter-C input might trigger ac-

celerated NER formation as the consequence of stimulated microbial

activity in the detritusphere. Maize litter was selected as a model plant

residue, whereas MCPA was chosen as a model compound to test the

eﬀect of plant residue on the extent of bioNER or non-biogenic NER

formation during pesticide degradation in soil.

Our study aimed to clarify the inﬂuence of soluble C from decom-

posing plant residues (maize litter) on MCPA degradation and on NER

formation in soil. We hypothesized that stimulated microbial activity

promotes bioNER formation in the upper layers of soil and that the

formation of NERs diﬀers at a ﬁne mm-depth scale. This was tested in

soil microcosms without (as a control setting) and with litter addition

on top, sampled in three layers: 0–2, 2–5 and 5–20 mm. The microcosm

approach allowed the detection of small-scale gradients under con-

trolled conditions which would not be possible in the ﬁeld with many

interfering environmental factors. The general mass balance of

MCPA turnover (mineralization, extractable and NERs) was quantiﬁed.

The quantitation also included

C incorporation into microbial bio-

mass based on analyses of FAs and AAs as biomarkers for living biomass

and biomass residues in soil.

2. Material and methods

2.1. Chemicals

All chemicals used were of the highest quality commercially avail-

able. Unlabeled MCPA was obtained from Sigma Aldrich (PESTANAL®).

-MCPA (> 99 at%

C and chemical purity) was obtained from

IsoSciences (USA).

2.2. Soil and plant residues

We used topsoil from a loamy Luvisol (WRB 2006) from an agri-

cultural ﬁeld at the research station Scheyern (Germany; 48°30′N,

11°21′E; plot “A18”, Helmholtz Zentrum München). The soil was

sampled, sieved (< 2 mm) and stored in the dark at −20 °C. Before use

the soil was thawed and its initial gravimetric water content of 27% was

reduced to 18% by air drying at 20 °C during an acclimatization period

of 20 days in the dark. The acclimatized soil was then immediately used

in the microcosm experiment. In this study, we prepared a one-to-one

mixture of chopped maize leaves and stems (2–10 mm long and 1–3mm

thick) and spread it on top of the soil surface (see Section 2.3 for details

of the experimental setup; see also Photo S1). Chemical soil and litter

properties are compiled in Table 1.

2.3. Experimental design

Microbial turnover of

-MCPA, including bioNER formation in

agricultural soil amended with maize litter was investigated in re-

packed soil columns of 30 mm height. We set up two experimental

treatments: (1) soil spiked with MCPA and without litter (control) and

(2) soil spiked with MCPA and amended with litter (litter). In order to

account for the natural

C abundance in soil and litter, both treatments

were spiked either with unlabeled MCPA (reference) or

-MCPA.

Two spiking solutions were prepared by dissolution of i) unlabeled

MCPA, ii)

C-labeled MCPA in distilled water; both solutions were

adjusted to pH 5.3 with 0.1 M NaOH. These solutions were then sepa-

rately mixed with soil to obtain a ﬁnal MCPA concentration of

50 mg kg

−1

of soil dry weight (total MCPA-C: 2.243 µmol g

−1

1.495 µmol g

−1

) and a gravimetric water content of 28%. Portions of

MCPA-amended soil were ﬁlled to a height of 30 mm into stainless steel

cylinders (diameter 56 mm, height 40 mm) and compacted to a bulk

density of 1.2 g cm

−3

. A mass of 0.5 g of maize residues (rewetted with

2 mL 0.01 M CaCl

) was added on top of the soil cores for the litter

treatment. The soil cores were placed separately in airtight microcosms

(glass containers, 750 mL) and incubated at 20 °C in the dark for

65 days (litter) and for 77 days (control). Microcosms were ﬂushed

every 2–3 days with fresh ambient air to maintain suﬃcient oxygen

supply. Water losses from soil cores were determined by regular

weighing and found to be negligible. Each treatment (unlabeled and

labeled MCPA versions for control and litter amendment) was re-

plicated six times. For detailed information on the experimental set-up

and the number of replicates taken for the respective analysis please

refer to the Scheme S1 in the Supplementary Information.

2.4. Sample preparation

After removing the litter layer (which was not analyzed), the soil

cores amended with unlabeled MCPA and

-MCPA were im-

mediately frozen at −20 °C. They were then sliced using a cryostat

microtome (HM 500 M, MICROM International GmbH, Walldorf,

Germany) into the following layers: 0–2 mm (detritusphere), 2–5mm

(transition zone) and 5–20 mm (bulk soil) from top of mineral soil.

Cores without litter were sampled in the same way, although a detri-

tusphere was obviously absent. Therefore, in results and discussion

sections, for the control we refer to the speciﬁc depth (0–2, 2–5or

5–20 mm), whereas for the litter treatment 0–2 mm is termed as ‘det-

ritusphere’,2–5mmas‘transition zone’, and 5–20 mm as ‘bulk soil’.To

obtain suﬃcient material for analyses (in particular for the two upper

layers 0–2 and 2–5 mm), we combined and homogeneously mixed the

soil from the associated layers of two soil cores into one. This procedure

yielded three samples (0–2, 2–5 and 5–20 mm) per treatment and layer

derived from six replicate soil cores.

2.5. Respiration and soil organic carbon

-C production (total C and

C) from the whole soil column was

measured during the experiment at regular intervals (2–3 days) by

trapping the evolved CO

in the headspace of the microcosms in 1 M

NaOH solution. Sampling of NaOH and analysis of total CO

and

as well as measurements of amount and

C abundance of soil organic

carbon were done as described in Poll et al. (2008; 2010). Soil cores

were sampled when both soil respiration and MCPA mineralization

reached constant rates because we did not expect signiﬁcant changes in

the fate of the compound thereafter. This was the case after 65 days for

the cores with litter amendment and after 77 days for the cores without

litter amendment (control). Although the latter were incubated for a

longer time both soil respiration and MCPA mineralization were lower

in the absence of litter than in the cores with litter amendment.

K.M. Nowak, et al. Environment International 142 (2020) 105867

2.6. MCPA

Residual MCPA in soil was extracted by shaking 1.5 g soil with

7.5 mL methanol/H

O (1:1 by volume) in 15 mL centrifuge tubes

(polyethylene) on a horizontal shaker at 200 rpm for 10 min. The tubes

were then heated in a water bath to 50 °C for 60 min. After that, shaking

on the horizontal shaker (200 rpm for 10 min) was repeated and the

samples centrifuged (4500g, 10 min). 1.5 mL aliquots of the super-

natant were ﬁltered (0.45 µm syringe ﬁlters, regenerated cellulose)

directly into HPLC vials for further analysis. MCPA in the extracts was

determined by HPLC with a UV-detector (System Gold, Beckman

Instruments) at a wavelength of 228 nm using acetonitrile/water (ratio

32:68) with 20 mmol L

−1

as mobile phase at a ﬂow rate of

0.5 mL min

−1

on a 3 µm MZ Aqua Perfect C18 material column

(150 mm × 3 mm; MZ-Analysentechnik GmbH, Germany).

Identiﬁcation and quantiﬁcation was done by external calibration using

freshly prepared MCPA standards dissolved in methanol/H

O (1:1 by

volume). The detection limit of MCPA in soil was 0.05 µg g

−1

, and the

recovery of MCPA from freshly spiked soil samples was 96%.

2.7. Fatty acids (FAs)

Incorporation of

C-derived MCPA into microbial lipids was ana-

lyzed using phospholipid fatty acids (PLFAs) and in total FAs (tFAs).

PLFAs are used to assess the amount of living microbial biomass in situ

(Zelles, 1999; Kaur et al., 2005). The tFAs, which include the PLFAs and

the FAs in the non-living OM (FAs

) are indicating the stabilization of

FAs in the OM (Drenovsky et al., 2004; Nowak et al., 2011). The PLFAs

and FAs

thus provide information about presence of living and non-

living groups of microorganisms in situ, respectively (Zelles, 1999; Kaur

et al., 2005). FAs biomarkers are indicative of microbial groups: (i)

Gram-positive bacteria (iso- and anteiso-branched FAs), (ii) actinomy-

cetes (Gram-positive phylum, 10-methyl branched FAs), (iii) Gram-ne-

gative bacteria (monounsaturated FAs) and (iv) fungi + eukaryotes

(polyunsaturated FAs). Starvation of Gram-negative bacteria is in-

dicated by the presence of cyclopropyl FA (Kaur et al., 2005). Saturated

straight chain FAs are ubiquitous and thus cannot be assigned to any

speciﬁc group. They are not explicitly considered in the present study

but are included in the total contents.

The detailed extraction, puriﬁcation and derivatization procedures

were described previously (Nowak et al., 2011). Brieﬂy, PLFAs were

extracted from soil with phosphate buﬀer/methanol/chloroform (Bligh

and Dyer; 1959) and separated from neutral lipids and glycolipids over

a silica gel column (Unisil, Clarkson Chromatography Products, South

Williamsport, USA; Nowak et al., 2011). The PLFAs were then deriva-

tized using methanol/trimethylchlorosilane (9:1; v:v; Miltner et al.,

2004). The tFAs were directly derivatized in the same way as the PLFAs

and the methylated tFAs were extracted from soil with diethyl ether and

puriﬁed over silica gel columns (Mallinckrodt Baker Germany, Grie-

sheim, Germany; Miltner et al., 2004). The derivatized fatty acid methyl

esters (FAME) in both fractions were separated on a BPX-5 column

(30 m × 0.25 mm × 0.25 μm) and identiﬁed and quantiﬁed by means

of gas chromatography-mass spectrometry (GC–MS). The isotopic

composition of FAME was determined by gas chromato-

graphy–combustion–isotope ratio mass spectrometry (GC–C–irMS).

The exact analytical conditions for both chromatographic devices were

described previously (Nowak et al., 2011).

2.8. Amino acids (AAs)

In analogy to FAs, the incorporation of

C-derived MCPA into

amino acids (AAs) was analyzed in the living biomass fraction (biomass

AA; bioAAs) and in the total AA fraction (tAAs) containing both bioAAs

and AAs stabilized in OM (AAs

). Unlike to FAs, AAs biomarkers do

not provide any phylogenetic information. However, they are very

important due to their high stability and highest abundance in micro-

bial cells (Nowak et al., 2011). Based on the measured

C in the AAs,

the total amount of bioNERs can be estimated considering a 50%

abundance of proteins in the cell (for details see Section 2.9).

Total AAs (tAAs) were hydrolyzed from proteins with 6 M HCl and

puriﬁed over cation exchange resin (DOWEX 50 W-X8, 50–100 mesh)

as described previously by Nowak et al. (2011). After puriﬁcation, the

carboxyl groups of AAs were isopropylated and the amino groups tri-

ﬂuoroacetylated (Silfer et al., 1991; Miltner et al., 2009). The re-

maining impurities after ﬁrst puriﬁcation and derivatization were ex-

tracted into phosphate buﬀer (Ueda et al., 1989; Nowak et al., 2011). In

the case of bioAAs, the biomass was ﬁrst extracted from the soil with

Amberlite IRC-748 and sodium deoxycholate/polyethylenglycol mix-

ture (Miltner et al., 2009). Thereafter, biomass pellets containing AAs

were further hydrolyzed, puriﬁed and derivatized as described above.

The identity, quantity and isotopic composition of the bioAAs and tAAs

were determined by means of GC–MS and GC–C–irMS using the same

instruments and columns as for FAs analysis. All the analytical condi-

tions for AAs separation using GC–MS and GC–C–irMS were described

previously (Nowak et al., 2011).

The recovery of microbial biomass from soil is low, two independent

studies with diﬀerent soils showed that the recovery of microbial bio-

mass was about 40% (Jacobsen and Rasmussen, 1992; Miltner et al.,

2009). Therefore, the bioAAs data are underestimated and we present

the original bioAAs data in Section 3. Results. For estimating the AAs in

the non-living OM (AAs

), values for AAs in living biomass were ex-

trapolated from the measured values based on an assumed 40% ex-

traction eﬃciency for bioAAs.

2.9. Calculation of MCPA-derived

CinCO

FAs, AAs and biogenic NER

The isotopic compositions of tAAs, bioAAs, PLFAs and tFAs were

corrected for C shifts due to derivatization (Silfer et al., 1991; Boschker,

2004).

We calculated MCPA-derived

MCPA

)inCO

, soil, FAs and

AAs based on total C and

C mass balances as follows:

=++=+CCCCC C

tsoilMCPA

sc MCPA

rbulk 13 (1)

== +CFCFC C··

tttrefbulkMCPA

13 13 13

(2)

Combining Eqs. (1) and (2) leads to:

=−

−=−

−

CCFC

MCPA

treft

ref

tref

ref

13 13

(3)

Here, C

and

stand for the total amount of C and

CinCO

, soil or

Table 1

Basic characteristics of soil and corn litter. Number in parentheses represent standard errors (n = 3).

Total C Total N δ

C pH (CaCl

) sand silt clay

mg g

−1

mg g

−1

‰%%%

Soil 14.9 (0.4) 1.85 (0.02) −25.9 (0.04) 5.3 19 (0.4) 63 (0.5) 17 (0.1)

Corn litter 412 (5) 8.81 (0.20) −12.8 (0.01) n.d.

n.a.

n.a. n.a.

n.d. not determined.

n.a. not applicable.

K.M. Nowak, et al. Environment International 142 (2020) 105867

fatty acids. C

bulk

denotes the amount of C derived from soil organic

carbon (C

soil

) and non-labeled side chain MCPA

(CMCPA

sc ) and CMCPA

ris the amount of ring MCPA-C. The values

and F

ref

stand for the molar +

12 13

ratios in CO

, soil, FA or AA from

-MCPA-amended and reference samples, respectively.

The amounts of

CinCO

, soil, PLFAs, tFAs, bioAAs and tAAs are

given as percentages of the initially applied

-MCPA. The calculation

of total amounts of bioNERs formed during biodegradation of

MCPA was based on the measured content of

C-tAAs. AAs hydrolyzed

from proteins are the major constituents of microbial biomass (50% of

the total biomass carbon; Nowak et al., 2011). Therefore, a conversion

factor of two was used for estimation of the total bioNERs from

C-

tAAs concentrations.

The respiration, mineralization and

C mass balance of

-MCPA

are shown as integrated data (comprising the three layers) over the

whole soil column for control and maize litter amended soil. The FAs,

AAs and the extractable

-MCPA were measured at each diﬀerent

soil layer (0–2, 2–5 and 5–20 mm) and thus those data for control and

litter amended soil are shown for each layer separately.

2.10. Statistics

Mean and standard deviation of calculated

MCPA

values were

estimated by uncertainty propagation using second-order Taylor ex-

pansion of Eq. (3) combined with Monte Carlo simulation (Taylor,

1997; JCGM, 2008) for generating samples from a multivariate normal

distribution based on means and standard deviations of measured C

and F

ref

values. This was done using the package ‘propagate’

(Spiess, 2014) with the statistical software ‘R’(R Core Team, 2015).

We used Welch's t-test as implemented in the R package ‘BSDA’

(Arnholt, 2012) to compare soil respiration, MCPA mineralization, total

MCPA-derived C,

C-PLFAs,

C-tFAs,

C-bioAAs and

C-tAAs of soil

cores with and without litter amendment at individual sampling times

and depths, respectively. The impact of litter amendment and distance

to litter (i.e., soil layer) on extractable MCPA and sum of PLFAs con-

centrations in soil cores were tested using a linear mixed eﬀect model

(R-package ‘lme4′,Bates et al., 2014) with litter amendment and layer

as ﬁxed eﬀects and soil cores as random eﬀect. We used the R-package

‘multcomp’(Hothorn et al., 2008) to test for pairwise diﬀerences.

3. Results

3.1. The eﬀect of litter on soil respiration and microbial biomass

The mean respiration rate of control soil remained between

0.37 ± 0.04 and 0.74 ± 0.06 μmol g

−1

(Fig. S1). Soil with maize

litter amendment had the highest respiration rate (5.2 ± 0.2 μmol g

−1

) at the beginning (day 5) of the experiment. It decreased by a factor

of 5 to 0.98 ± 0.1 μmol g

−1

towards the end (Fig. S1). This re-

sulted in 114 ± 4 μmol g

−1

cumulative CO

with litter amendment

compared to 37 ± 1 μmol g

−1

cumulative CO

without litter addition

after 65 days (Fig. 1). Thus, the mean respiration rate was at maximum

7-fold higher after 5 days (t

5.3

= 61.6, p < 0.001) and cumulative

respiration was 3-fold higher after 65 days (t

5.7

= 53.1, p < 0.001)

with maize litter addition compared to control. No signiﬁcant diﬀer-

ences between soils amended with unlabeled MCPA and

-MCPA

were detected.

Without litter amendment, PLFAs and FAs

were similar in all

three soil cores. PLFAs ranged between 32 ± 3.4 and

37 ± 5.6 nmol g

−1

, whereas FAs

between 49 ± 3.0 and

61 ± 0.6 nmol g

−1

(Fig. 2; see also Table S1). PLFA indicative of

Gram-negative and Gram-positive bacteria were equally represented

within the living soil microbiome of the control. Maize litter addition

boosted tFAs concentration and changed the proportion of living and

non-living soil microbiome. In comparison to control, total PLFAs in

detritusphere were 1.6-fold higher (p < 0.001), whereas FAs

were

2.4-fold higher (p < 0.001). No signiﬁcant diﬀerences in total amounts

of PLFAs were found for transition and bulk soil and FAs

for bulk soil

due to maize litter amendment. In contrast to the control, FAs in-

dicative of Gram-negative bacteria showed an increased contribution of

this group within the living soil microbiome (PLFAs) in detritusphere

(see Fig. 2A and Table S1A; p < 0.001) and non-living microbiome

(FAs

) in detritusphere and transition zone with maize litter amend-

ment (Fig. 2B and Table S1B). Litter amendment also resulted in

boosted concentrations of fungal PLFA in detritusphere (p < 0.001)

and of FAs

in detritusphere and transition zone (p < 0.001)in

comparison with the control (Fig. 2B; see also Table S1B).

3.2. Mineralization and dissipation of

-MCPA

Cumulative mineralization of

-MCPA in soil with and without

litter expressed as a percentage of the initially added

C is shown in

Fig. 3. Mineralization of

-MCPA in control soil was low. It increased

slowly during the experiment and reached only 6% ± 4.7% of

MCPA equivalents after 77 days. Litter amendment signiﬁcantly ac-

celerated mineralization of

-MCPA following a 20-day lag phase.

On day 65, ~7 times more

-MCPA was mineralized in the presence

of litter than in the control soil (27% ± 3.8% vs. 4.1% ± 3.7%,

= 10.7, p < 0.001).

No signiﬁcant diﬀerences in the total MCPA-derived C (incl.

MCPA before extraction) and in the extractable MCPA with depth were

noticed in the control soil cores (see Fig. 4). In addition, the total

MCPA-derived C was almost completely explained by extractable MCPA

and in all layers (75–79% vs. 80–85% of initial

-MCPA equiva-

lents).

Maize litter addition to soil signiﬁcantly reduced (p < 0.001) the

amounts of extractable

-MCPA and the total MCPA-derived C

(Fig. 4). Total MCPA-derived C was accordingly 88%, 51% and 54% at

detritusphere, transition and bulk soil. Extractable

-MCPA in the

bulk soil with litter decreased to 40% ± 8% of the initial

-MCPA

equivalents. It was even more reduced to 7.7% ± 6% and 11% ± 7% in

the detritusphere and the transition zone (p < 0.001), respectively.

Like in the control, the majority of total MCPA-derived C (74%) in the

bulk soil was extractable as MCPA parent compound. In contrast to the

control, only 9% and 22% of total MCPA-derived C could be assigned to

Fig. 1. Cumulative respiration of soil (μmol g

−1

) treated with unlabeled MCPA

and

-MCPA with and without litter addition. The respiration is shown as

integrated data comprising the three layers over the whole soil column.

K.M. Nowak, et al. Environment International 142 (2020) 105867

extractable

-MCPA in the detritusphere and the transition zone

with litter, respectively. In detritusphere and transition zone of litter

treatment, the majority of MCPA-derived C was thus represented by the

C-NERs.

3.3. MCPA-derived

C in fatty and amino acids

Only slightly higher incorporation of MCPA-derived C into PLFAs in

two top layers (0–2 mm and 2–5 mm) than in the bottom layer

5–20 mm was noticed (0.17% and 0.15% vs. 0.10%; see also Fig. 5A,

Table S2). Both Gram-positive and Gram-negative bacteria equally in-

corporated the

C-MCPA derived label into their PLFAs (Table S2A).

Maize litter addition promoted the incorporation of MCPA-derived C

into PLFAs in the detritusphere and transition zone (p < 0.001). Total

C-PLFAs were about 3-fold higher in detritusphere and 2.1-fold higher

in transition zone of the litter treatment compared to these depths in the

control. The PLFA biomarkers indicate that Gram-negative bacteria

assimilated the highest amount of

C-derived MCPA in the two top

layers (Fig. 5A and Table S2A; p < 0.001). No signiﬁcant diﬀerence in

the contents of

C-FAs

between 0 and 2 mm and 2–5 mm of control

and of amended treatment was detected (Fig. 5B and Table S2A and

S2B). In contrast to the control, signiﬁcantly higher amounts of

Cin

the fungal FAs

were found in the 0–2 mm and 2–5 mm of the litter-

amended treatment (0.063% and 0.052% vs 0.007% and 0.018%;

p < 0.001).

Without litter amendment, incorporation of MCPA-derived C into

total AAs (tAAs) was low at all soil cores. It reached a maximum of

1.2% ± 0.9% in the top layer (Table S3B). The tAAs in the 5–20 mm

layer were below the detection limit. Accordingly, incorporation of

MCPA-derived C into living biomass AAs (bioAAs) was low

(0.08–0.20%, Table S3A) in all soil cores of control. In analogy to

C-

PLFAs, maize litter addition also enhanced the contents of

C-bioAAs

(2-fold) and the contents of

C-tAAs (15 to 17-fold) in the detritu-

sphere and transition zone (p < 0.001) compared with those re-

spective depths in the control (Table S3). The majority of the

C label

in the tAAs (> 71% control soil and > 92% in litter-amended soil)

Fig. 2. Sum of PLFAs (A) and of FAsOM (B) in soil amended with

-MCPA in diﬀerent soil layers (nmol g

−1

): 0–2 mm, 2–5 mm and 5–20 mm. *indicates

statistically signiﬁcant values.

K.M. Nowak, et al. Environment International 142 (2020) 105867

could be assigned to non-living AAs (

C-AAs

; Table S3B) suggesting

their stabilization in the OM pool. In contrast to the

C-bioAAs, the

contents of

C-AAs

were equally high in the detritusphere and

transition zone of the litter-amended treatment, whereas the con-

centration in the bulk soil was only one ﬁfth of the concentrations in the

detritusphere and transition zone (Table S3).

All quantiﬁable bioAAs were similarly enriched in

C in the

detritusphere and transition zone of litter treatment. Contrastingly,

only four

C-bioAAs in the bulk soil could be detected (leucine, iso-

leucine, phenylalanine and lysine; see Table S3A). The distribution

pattern of

C label within the

C-AAs

of litter amended soil was in

accordance with the distribution pattern of

C-bioAAs. The AAs car-

rying most of the label in

C-AAs

in the detritusphere were valine,

leucine, isoleucine, proline, glutamate and lysine, whereas in the

transition zone leucine, isoleucine, proline, aspartate, phenylalanine

and lysine dominated the label distribution (see Table S3B).

3.4. Mass balance of

-MCPA turnover including bioNER formation

Without litter addition, the majority of extracted

-MCPA

(~75%) was attributed to the MCPA parent compound at all depths

(Fig. 6 and Table S4). Less than 6%

-MCPA was identiﬁed as NERs,

and an even lower percentage could be identiﬁed as bioNERs.

Maize litter promoted the formation of total NERs. We found 80.3%,

40% and 13.8% of

-MCPA equivalents as NERs in detritusphere,

transition zone and bulk soil, respectively (Fig. 6 and Table S4). In the

transition zone, the NERs could almost completely be assigned to non-

toxic bioNERs (97% of total NERs). In the detritusphere and bulk soil,

bioNERs comprised only 46% and 45% of the total NERs.

At the core scale, the majority of initially applied

-MCPA in

control soil was extracted as MCPA parent compound (77%, Fig. 7, and

Table S5) followed by mineralization (6%). Only 4.6% of initially ap-

plied

-MCPA was non-biogenic NERs. The formation of bioNERs

was negligible. In contrast, litter amendment resulted in decreased

amounts of extractable parent compound (35%

-MCPA) as well as

increased mineralization (27% of initially applied

-MCPA) and

formation of NERs (21%

-MCPA). About 65% of the total

C-NERs

were explained by non-toxic bioNERs (14%

-MCPA). Total recovery

in the mass balances of

C amounted to 88% of the initial

-MCPA

equivalents for the control and to 83% for the litter-amended soil (Table

S5).

4. Discussion

4.1. Maize litter addition to soil triggered microbial activity

Low respiration, mineralization and dissipation of

-MCPA in the

control soil compared to the previous studies (Poll et al., 2010, Pagel

et al., 2016) might be due to suppressed microbial activity as a result of

storage of soil at −20 °C prior to the experiment. This is supported by

other studies: while a short and single freeze-thaw of soil did not alter

the mineralization of

C-MCPA (Mortensen and Jacobsen, 2004),

prolonged or multiple freezing negatively aﬀected the mineralization

kinetics of

C-MCPA in wetland microcosms (Vandermeeren et al.,

2016). Irrespective of the level of microbial activity, the experimental

setup allows to clearly reveal the eﬀect of litter addition on MCPA

degradation.

Maize litter addition clearly triggered the microbial activity of the

soil as reﬂected by the high initial respiration rate. It tripled cumulative

respiration and doubled the sum of tFAs in detritusphere in comparison

to 0–2 mm layer in the control soil. A similar eﬀect was observed by

Poll et al. (2010) and Pagel et al. (2016) where maize litter placed on

top of the mineral soil quadrupled respiration and tripled microbial

FAs.

4.2. Maize litter accelerated mineralization and dissipation of MCPA

The accelerated mineralization and dissipation of

-MCPA could

be related to the increased availability of soluble C which might have

been diﬀused from the maize litter on the top to the transition zone and

bulk soil. We found much lower mineralization of

-MCPA, both in

litter-amended and control soil (27% and 6%) compared to reported

values for mineralization of MCPA in the range of 40–70% (Sørensen

Fig. 3. Cumulative mineralization of

-MCPA in soil with and without litter

addition as percentages of the initially applied

-MCPA. The cumulative

mineralization is shown as integrated data comprising the three layers over the

whole soil column.

Fig. 4. The total MCPA-derived C (including

-MCPA before extraction) and

extractable

-MCPA in soil with and without litter addition in diﬀerent soil

layers: 0–2 mm, 2–5 mm and 5–20 mm expressed as percentages of the initially

added

-MCPA g

−1

of the respective soil layer. Black markers: litter treat-

ment; white markers: control.

K.M. Nowak, et al. Environment International 142 (2020) 105867

et al., 2006; Jacobsen et al., 2008; Poll et al., 2010; Nielsen et al., 2011;

Pagel et al., 2016) and 57% for

-2,4-D (Girardi et al., 2013). This

divergence might be related to diﬀerences in soil type, microbial ac-

tivity and microbial composition. In addition, mineralization showed a

much longer lag phase of about 20 days compared with only 7-day lag

phase in study by Poll et al. (2010) or no apparent lag phase by Girardi

et al. (2013) and Pagel et al. (2016). The 20-day lag in the miner-

alization of

-MCPA was presumably a combined eﬀect of the time-

dependent re-growth of microorganisms after freezing or their adap-

tation to the high MCPA application rate, which was 10-fold higher

than the recommended application rate (5 mg kg

−1

) of MCPA in agri-

culture (Saleh et al., 2016).

Along with enhanced mineralization, litter addition also inﬂuenced

the

-MCPA dissipation down to a soil depth of 20 mm, even in the

absence of downward advective transport. The amounts of extractable

-MCPA in this study (35%) were much higher than the re-

ported < 1% for extractable

C-MCPA from the litter-amended soil by

Poll et al. (2010) and Pagel et al. (2016). In these two studies; however,

mineralization of

C-MCPA was higher and about 7% of the applied

C was leached from soil. Similar to Poll et al. (2010) and Pagel et al.

(2016), we found the lowest residual MCPA concentration in the soil

layer closest to litter. Coincidently, we also found highest formation of

non-biogenic NERs (43.5%) in the detritusphere. This ﬁnding possibly

indicates the stabilization of MCPA-C in the form of parent

-MCPA

or its main transformation product 4-chloro-2-methylphenol. Low

amounts of 4-chloro-2-methylphenol are usually measured in soil after

aerobic transformation of MCPA as it has a short half-life of 3.55 days

(US EPA). We did not analyze 4-chloro-2-methylphenol; however, this

transformation product is rapidly converted to CO

or sorbed to the

solid matrix (Fava et al., 2005). 4-chloro-2-methylphenol has a slightly

stronger aﬃnity to OM than MCPA (Fava et al., 2005; Jacobsen et al.,

2008; Nielsen et al., 2011; Hiller et al., 2012; López-Piñeiro et al., 2013;

Piwowarczyk and Holden, 2013); thus it is likely that this transforma-

tion product substantially contributed to non-biogenic NER formation.

4.3. Maize addition stimulated Gram-negative bacteria and fungi

Microbial biomass formation and assimilation of

C-derived MCPA

Fig. 5. Distribution of the

C label within the PLFAs (A) and the FAsOM (B) during biodegradation of

-MCPA soil with and without litter addition in diﬀerent soil

layers: 0–2 mm, 2–5 mm and 5–20 mm. The

C-PLFAs and 13C-FAsOM are given as percentages of the initially applied

-MCPA g

−1

in the respective soil layer.

*indicates statistically signiﬁcant values.

K.M. Nowak, et al. Environment International 142 (2020) 105867

into the biomass (fatty acids and amino acids) was highest in close

proximity to the added maize litter. The addition of fresh C to the soil

not only increased the microbial biomass, but also stimulated the in-

corporation of

C into Gram-negative bacteria and fungi. The striking

contribution of fungi to the non-living soil microbiome (

C-FAs

) and

to the non-living

-MCPA degraders (

C-FAs

) in our study in-

dicates that transformation of MCPA might have been initiated by fungi

in the detritusphere. Evidence on fungal degradation of phenoxyacetic

acid herbicides was previously reported by Castillo et al. (2001) and

Lerch et al. (2009). This ﬁnding is in a good agreement with previous

studies that showed increased ergosterol concentrations and abun-

dances of fungal ITS gene fragments during accelerated MCPA de-

gradation in response to litter addition (Poll et al., 2010; Ditterich et al.,

2013; Pagel et. al., 2016, Saleh et al., 2016). Fungi are known to play a

pivotal role in the initial decomposition of complex organic substrates

in soils (de Boer et al., 2005; Strickland and Rousk, 2010). Therefore,

we assume that the fungi may have initiated MCPA degradation and

supported bacteria in the further conversion of MCPA to CO

. In ad-

dition, fungi may have also contributed to the C mobilization and

transport of litter derived C into the soil thereby supporting the growth

of bacterial MCPA degraders. Gram-negative bacteria were also the

preferential degraders of phenoxyacetic acid herbicide 2.4-D in soil as

shown by

C-stable isotope probing (Lerch et al., 2009; Nowak et al.,

2011). This is consistent with our ﬁnding that the Gram-negative bac-

teria were the main utilizers in the later degradation of

-MCPA.

However, we cannot decide whether the

C derived MCPA was directly

incorporated into the PLFAs of Gram-negative bacteria or indirectly as a

result of cross-feeding, e.g. via the fungal biomass. To clarify that, more

data on the contents of

C-PLFAs

and

C-FAs

in time course

would be necessary. In addition, labeling pattern of bioAAs and AAs

with

C was similar to that observed in the previous soil degradation

study with phenoxyacetic acid herbicide

-2,4-D (Nowak et al.,

2011). This suggests that MCPA degradation could be analogous to the

structurally similar 2,4-D.

4.4. Maize litter enhances bioNER and non-biogenic NER formation

Maize litter addition accelerated microbial turnover of

-MCPA

and also enhanced the formation of proteinaceous bioNERs. The MCPA-

derived C in proteins (based on the tAAs hydrolyzed from proteins) in

the litter-amended soil was mainly stabilized in the OM pool as pro-

teinaceous bioNERs since only a small proportion was found in the

living biomass AAs (< 8% of the

C in the total AAs). This is in

agreement with a previous study where 90% of the

C-tAAs derived

from

-2,4-D were stabilized in the non-living OM pool (Nowak

et al., 2011).

The NERs in the transition zone of litter-amended treatment were

mainly composed of harmless bioNERs which explained 97% of total

NERs. In contrast to the transition zone, the bioNERs in the detritu-

sphere and bulk soil of litter-amended soil comprised 46% and 45% of

the total NERs, respectively, and thus 54% and 55% of the NERs in

these layers was non-biogenic NERs of unknown structural identity. The

high contribution of bioNERs to the total NERs in the transition zone of

litter-amended treatment is related to an improved nutrients supply

from the maize litter placed on top. This, in turn resulted in an in-

creased microbial activity and microbial conversion of MCPA to

bioNERs. Contrary to the transition zone, the preferential formation of

non-biogenic NERs in the detritusphere could be a result of the sorption

of MCPA transformation product 4-chloro-2-methylphenol to solid

matrix. Phenolic transformation products of phenoxyacetic acids de-

gradation can be bound to solid matrix by oxidoreductive enzymes,

such as laccases and peroxidases via covalent bonding (Bollag et al.,

1991, 1992; Hatcher et al., 1993; Dec and Bollag, 1997; Xu and

Bhandari, 2003). Oxidoreductive enzymes are commonly produced by

fungi (Bollag et al., 1991). A high activity of such enzymes is thus

consistent with the high abundance of fungal biomarkers (PLFAs and

FAs

) in detritusphere. This thus may explain the high formation of

the non-biogenic NERs in the detritusphere which could have been

mediated by the fungi. The covalent binding of xenobiotics or their

transformation products to solid matrix results in the formation of

highly persistent non-biogenic NERs type II with medium or low risk

(Kästner et al., 2014). The formation of non-biogenic NERs of type II is

still favorable over the physically sequestered NERs type I since it limits

the bioavailability of toxic chemical to living organisms and prevents

the chemical from the leaching to the waters.

Integrated over the three layers, the

C-bioNERs in the litter-

amended soil amounted only to 14% of

-MCPA equivalents and

comprised about 65% of the total

C-NER. In contrast, virtually all

NERs could be assigned to bioNERs (amounting to 44% of the initially

added

C) in a previous experiment studying

-2,4-D turnover in a

diﬀerent soil (Nowak et al., 2011). The maize litter thus promoted not

only microbial activity, degradation of

-MCPA and bioNER for-

mation in soil, but also formation of non-biogenic NERs of unknown

structural identity which can be potentially toxic.

Fig. 6. Distribution of remaining

C label on extractable

-MCPA and NERs

(non-biogenic NERs and bioNERs) in control soil and with litter amendment in

diﬀerent soil layers: 0–2 mm, 2–5 mm and 5–20 mm. Proteins: 13C-tAAs, non-

proteinaceous bioNERs: other biomolecules calculated based on known 50%

content of proteins (

C-tAAs). The data are presented as percentages of the

initially applied

-MCPA g

−1

in the respective soil layer.

Fig. 7. Distribution of

C label on mineralization, MCPA, non-biogenic NERs

and biogenic NERs during degradation of

-MCPA (mass balance) in soil

with and without litter amendment. Proteins: 13C-tAAs, non-proteinaceous

bioNERs: other biomolecules calculated based on known 50% content of pro-

teins (13C-tAAs). The

C mass balance of

-MCPA is shown as integrated

data comprising the three layers and as percentages of the initially applied

MCPA to each soil column.

K.M. Nowak, et al. Environment International 142 (2020) 105867

5. Conclusions

This is the ﬁrst

C isotope labeling study that shows the eﬀect of

plant litter-soluble C on pesticide degradation at a ﬁne mm-depth scale

of soil. Maize litter accelerates microbial activity, mineralization of

MCPA and NER formation in soil. However, our results highlight strong

diﬀerences in the formation of harmless bioNERs and potentially toxic

non-biogenic NERs at the mm-scale. Beyond the detritusphere, this

ﬁnding might have important consequences for NER formation in other

highly active soil microhabitats with high C input (e.g., the rhizo-

sphere). Although plant litter addition to soil can also increase the

formation of non-biogenic NERs, it is still favorable since it promotes

the degradation of organic chemicals and reduces the extractable

fraction of the parent compound, i.e. the most mobile and available

pool. However, the type of non-biogenic NERs (type I versus type II)

formed in response to additional C input need to be analyzed in detail.

In particular, increased formation of physically sequestered NERs (Type

I) carries the risk of delayed remobilization, which might turn soils

from sinks into sources of pollutants.

CRediT authorship contribution statement

Karolina M. Nowak: Conceptualization, Data curation, Formal

analysis, Funding acquisition, Investigation, Methodology, Project ad-

ministration, Resources, Supervision, Validation, Visualization, Writing

- original draft, Writing - review & editing. Anja Miltner:

Conceptualization, Funding acquisition, Resources, Supervision,

Writing - original draft, Writing - review & editing. Christian Poll:

Conceptualization, Funding acquisition, Methodology, Resources,

Supervision, Writing - review & editing. Ellen Kandeler:

Conceptualization, Funding acquisition, Methodology, Resources,

Supervision, Writing - review & editing. Thilo Streck: Funding acqui-

sition, Resources, Supervision, Writing - review & editing. Holger

Pagel: Conceptualization, Data curation, Formal analysis,

Investigation, Methodology, Project administration, Resources,

Software, Supervision, Validation, Visualization, Writing - original

draft, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing ﬁnancial

interests or personal relationships that could have appeared to inﬂu-

ence the work reported in this paper.

Acknowledgements

We thank Ursula Günther, Steﬀen Kümmel and Matthias Gehre

(UFZ, Department of Isotope Biogeochemistry) for their valuable as-

sistance in compound-speciﬁc isotope analysis as well as Heike

Haslwimmer, Aurelia Gebauer and Elke Feiertag (Institute of Soil

Science and Land Evaluation, University of Hohenheim) for their as-

sistance in CO

, MCPA and

C analyses. We acknowledge support by

the German Research Foundation (DFG, No 980/1-1 and DFG, No 980/

3-1) and the Open Access Publication Fund of TU Berlin. This research

was also supported by the Helmholtz Centre for Environmental

Research-UFZ, the Ellrichshausen Foundation and the priority program

SPP 1315 ‘‘Biogeochemical Interfaces in Soil”as well as the

Collaborative Research Center 1253 CAMPOS (project P6, soils), both

funded by DFG (MI598/2-2, STR481/3-2, KA1590/5-2 and Grant

Agreement SFB 1253/1 2017). We also thank three anonymous re-

viewers for their scientiﬁc advice on an earlier version of this study.

Appendix A. Supplementary material

Supplementary data to this article can be found online at https://

doi.org/10.1016/j.envint.2020.105867.

References

Arnholt, A.T., 2012. BSDA: Basic Statistics and Data Analysis. 1.01. http://CRAN.R-

project.org/package=BSDA.

Barriuso, E., Houot, S., Serra-Wittling, C., 1997. Inﬂuence of compost addition to soil on

behavior of herbicides. Pest. Sci. 49, 65–75. https://doi.org/10.1002/(SICI)1096-

9063(199701)49:1<65::AID-PS488>3.0.CO;2-Z.

Barriuso, E., Benoit, P., Dubus, I.G., 2008. Formation of pesticide nonextractable (bound)

residues in soil: magnitude, controlling factors and reversibility. Environ. Sci.

Technol. 42, 1845–2185. https://doi.org/10.1021/es7021736.

Bates D., Maechler M., Bolker B., Walker, S. 2014. lme4: Linear mixed-eﬀects models

using ‘Eigen’and S4. R package version 1.1-7, < URL: http://CRAN.R-project.org/

package=lme4 >.

Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and puriﬁcation.

Can. J. Biochem. Physiol. 37, 911–917. https://doi.org/10.1139/y59-099.

Bollag, J.M., Shuttleworth, K.L., Anderson, D.H., 1991. Laccase-mediated detoxiﬁcation

of phenolic compounds. Appl. Environ. Microbiol. 54, 3086–3091. https://doi.org/

10.1128/aem.54.12.3086-3091.1988.

Bollag, J.M., Myers, C.J., Minard, R.D., 1992. Biological and chemical interactions of

pesticides with soil organic matter. Sci. Total Environ. 123–124, 205–217. https://

doi.org/10.1016/0048-9697(92)90146-J.

Boschker, H.T.S., 2004. In: Kowalchuk, G.A., Bruijn, F.J.D., Head, I.M., Akkermans, A.D.

L, Elsas, J.D.V. (Eds.), Linking microbial community structure and functioning: stable

isotope (13C) labeling in combination with PLFA analysis. Molecular microbial

ecology manual, second ed. Kluwer Academic Publisher, Dordrecht, The Netherlands,

pp. 1673–1688.

Castillo, M., Anderson, A.P., Stenströn, J., Torstenson, L., 2001. Establishment of the

white-rot fungus Phanerochaete chrysosporium on unsterile straw in solid substrate

fermentation systems intended for degradation of pesticides. World J. Microbiol.

Biotechnol. 17, 627–633. https://doi.org/10.1023/A:1012420422111.

de Boer, W., Folman, L.B., Summerbell, R.C., Boddy, L., 2005. Living in a fungal world:

impact of fungi on soil bacterial niche development. FEMS Microbiol. Rev. 29,

795–811. https://doi.org/10.1016/j.femsre.2004.11.005.

Dec, J., Bollag, J.-M., 1997. Determination of covalent and non- covalent binding inter-

actions between xenobiotic chemicals and soil. Soil Sci. 162, 858–874.

Ditterich, F., Poll, C., Pagel, H., Babin, D., Smalla, K., Horn, M.A., Streck, T., Kandeler, E.,

2013. Succession of bacterial and fungal 4-chloro-2-methylphenoxyacetic acid de-

graders at the soil-litter interface. FEMS Microbiol. Ecol. 86, 85–100. https://doi.org/

10.1111/1574-6941.12131.

Drenovsky, R.E., Elliott, G.N., Graham, K.J., Scow, M., 2004. Comparison of phospholipid

fatty acid (PLFA) and total soil fatty acid methyl esters (TSFAME) for characterizing

soil microbial communities. Soil Biol. Biochem. 36, 1793–1800. https://doi.org/10.

1016/j.soilbio.2004.05.002.

Fava, L., Orrù, M.A., Crobe, A., Barra Caracciolo, A., Bottoni, P., Funari, E., 2005.

Pesticide metabolites as contaminants of groundwater resources: assessment of the

leaching potential of endosulfan sulfate, 2,6-dichlorobenzoic acid, 3,4-dichloroani-

line, 2,4-dichlorophenol and 4-chloro-2-methylphenol. Microchem. J. 79, 207–211.

https://doi.org/10.1016/j.microc.2004.10.009.

Gerhardt, K.E., Huang, X.D., Glick, B.R., Greenberg, B.M., 2009. Phytoremediation and

rhizoremediation of organic soil contaminants: potential and challenges. Plant Sci.

176, 20–30. https://doi.org/10.1016/j.plantsci.2008.09.014.

Ghani, A., Wardle, D.A., 2001. Fate of

C from glucose and the herbicide metsulfuron-

methyl in a plant-soil microcosm system. Soil Biol. Biochem. 33, 777–785. https://

doi.org/10.1016/S0038-0717(00)00225-X.

Girardi, C., Nowak, K.M., Carranza-Diaz, O., Lewkow, B., Miltner, A., Gehre, M., Schäﬀer,

A., Kästner, M., 2013. Microbial degradation of the pharmaceutical ibuprofen and the

herbicide 2, 4-D in water and soil e use and limits of data obtained from aqueous

systems for predicting their fate in soil. Sci. Total Environ. 444, 32–42. https://doi.

org/10.1016/j.scitotenv.2012.11.051.

Hatcher, P.G., Bortiatynski, J.M., Minard, R.D., Dec, J., Bollag, J.-M., 1993. Use of high-

resolution

C-NMR to examine the enzymatic covalent binding of

C-labeled 2,4-

dichlorophenol to humic substances. Environ. Sci. Technol. 27, 2098–2103. https://

doi.org/10.1021/es00047a015.

Hiller, E., Tatarková, V., Šimonovičová, A., Bartal', M., 2012. Sorption, desorption, and

degradation of (4-chloro-2-methylphenoxy)acetic acid in representative soils of the

Danubian Lowland, Slovakia. Chemosphere 87, 437–444. https://doi.org/10.1016/j.

chemosphere.2011.12.021.

Hothorn, T., Bretz, F., Westfall, P., 2008. Simultaneous inference in general parametric

models. Biom. J. 50, 346–363. https://doi.org/10.1002/bimj.200810425.

Jacobsen, C.S., van der Keur, P., Iversen, B.V., Rosenberg, P., Barlebo, H.C., Torp, S.,

Vosgerau, H., Juhler, R.K., Ernstsen, V., Rasmussen, J., Brinch, U.C., Jacobsen, O.H.,

2008. Variation of MCPA, metribuzine, methyltriazine-amine and glyphosate de-

gradation, sorption, mineralization and leaching in diﬀerent soil horizons. Environ.

Pollut. 156, 794–802. https://doi.org/10.1016/j.envpol.2008.06.002.

Jacobsen, C.S., Rasmussen, O.F., 1992. Development and application of a new method to

extract bacterial DNA from soil based on separation of bacteria from soil with cation

exchange resin. Appl. Environ. Microbiol. 58, 2458–2462. https://doi.org/10.1128/

AEM.58.8.2458-2462.1992.

JCGM, 2008. Evaluation of measurement data - Guide to the expression of uncertainty in

measurement. Bureau International des Poids et Mesures, Joint Committee for Guides

in Metrology, http://www.bipm.org/utils/common/documents/jcgm/JCGM_100_

2008_E.pdf.

Kästner, M., Nowak, K.M., Miltner, A., Trapp, S., Schäﬀer, A., 2014. Classiﬁcation and

K.M. Nowak, et al. Environment International 142 (2020) 105867

modelling of non-extractable residue (NER) formation of xenobiotics in soil - a

synthesis. Crit. Rev. Environ. Sci. Technol. 44, 2107–2171.

Kaur, A., Chaudhary, A., Kaur, A., Choudhary, R., Kaushik, R., 2005. Phospholipid fatty

acid - a bioindicator of environment monitoring and assessment in soil ecosystem.

Cur. Sci. 89, 1103–1112. https://www.jstor.org/stable/24110962.

Lerch, T.Z., Dignac, M.-F., Nunan, N., Bardoux, G., Barriuso, E., Mariotti, A., 2009.

Dynamics of soil microbial populations involved in 2,4-D biodegradation revealed by

FAME-based stable isotope probing. Soil Biol. Biochem. 41, 77–85. https://doi.org/

10.1016/j.soilbio.2008.09.020.

López-Piñeiro, A., Peña, D., Albarrán, A., Sánchez-Llerena, J., Becerra, D., 2013. Behavior

of MCPA in four intensive cropping soils amended with fresh, composted, and aged

olive mill waste. J. Contam. Hydrol. 152, 137–146. https://doi.org/10.1016/j.

jconhyd.2013.07.003.

Miltner, A., Kindler, R., Knicker, H., Richnow, H.H., Kästner, M., 2009. Fate of microbial

biomass derived amino acids in soil and their contribution to soil organic matter. Org.

Geochem. 40, 978–985. https://doi.org/10.1016/j.orggeochem.2009.06.008.

Miltner, A., Richnow, H.H., Kopinke, F.-D., Kästner, M., 2004. Assimilation of CO

by soil

microorganisms and transformation into soil organic matter. Org. Geochem. 35,

1015–1024. https://doi.org/10.1016/j.orggeochem.2004.05.001.

Mortensen, S.K., Jacobsen, C.S., 2004. Inﬂuence of frozen storage on herbicide de-

gradation capacity in surface and subsurface sandy soils. Environ. Sci. Technol. 38,

6625–6632. https://doi.org/10.1021/es049542x.

Muskus, A.M., Krauss, M., Miltner, A., Hamer, U., Nowak, K.M., 2019. Eﬀect of tem-

perature, pH and total organic carbon variations on microbial turnover of

315

N-

glyphosate in agricultural soil. Sci, Total Environ. 658, 697–707. https://doi.org/10.

1016/j.scitotenv.2018.12.195.

Muskus, A.M., Krauss, M., Miltner, A., Hamer, U., Nowak, K.M., 2020. Degradation of

glyphosate in a Colombian soil is inﬂuenced by temperature, total organic carbon

content and pH. Environ. Pollut. 259, 113767. https://doi.org/10.1016/j.envpol.

2019.113767.

Nielsen, M.S., Baelum, J., Jensen, M.B., Jacobsen, C.S., 2011. Mineralization of the her-

bicide MCPA in urban soils is linked to presence and growth of class III tfdA genes.

Soil Biol. Biochem. 43, 984–990. https://doi.org/10.1016/j.soilbio.2011.01.014.

Nowak, K.M., Miltner, A., Gehre, M., Schäﬀer, A., Kästner, M., 2011. Formation and fate

of bound residues from microbial biomass during 2,4-D degradation in soil. Environ.

Sci. Technol. 45, 999–1006. https://doi.org/10.1021/es103097f.

Pagel, H., Poll, C., Ingwersen, J., Kandeler, E., Streck, T., 2016. Modeling coupled pes-

ticide degradation and organic matter turnover: from gene abundance to process

rates. Soil Biol. Biochem. 103, 349–364. https://doi.org/10.1016/j.soilbio.2016.09.

014.

Piwowarczyk, A.A., Holden, N.M., 2013. Phenoxyalkanoic acid herbicide sorption and the

eﬀect of co-application in a Haplic Cambisol with contrasting management.

Chemosphere 90, 535–541. https://doi.org/10.1016/j.chemosphere.2012.08.023.

Poll, C., Marhan, S., Ingwersen, J., Kandeler, E., 2008. Dynamics of litter carbon turnover

and microbial abundance in a rye detritusphere. Soil Biol. Biochem. 40, 1306–1324.

https://doi.org/10.1016/j.soilbio.2007.04.002.

Poll, C., Pagel, H., Devers-Lamrani, M., Martin-Laurent, F., Ingwersen, J., Streck, T.,

Kandeler, E., 2010. Regulation of bacterial and fungal MCPA degradation at the soil-

litter interface. Soil Biol. Biochem. 42, 1879–1887. https://doi.org/10.1016/j.

soilbio.2010.07.013.

R Core Team, 2015. R: A Language and Environment for Statistical Computing. R

Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org.

Saleh, O., Pagel, H., Enowashu, E., Devers, M., Martin-Laurent, F., Streck, T., Kandeler, E.,

Poll, C., 2016. Evidence for the importance of litter as a co-substrate for MCPA dis-

sipation in an agricultural soil. Environ. Sci. Pollut. Res. 23, 4164–4175. https://doi.

org/10.1007/s11356-015-4633-1.

Shaw, L.J., Burns, R.G., 2003. Biodegradation of organic pollutants in the rhizosphere.

Adv. Appl. Microbiol. 53, 1–47. https://doi.org/10.1016/s0065-2164(03)53001-5.

Silfer, J.A., Engel, M.H., Macko, S.A., Jumeau, E.J., 1991. Stable carbon isotope analysis

of amino acid enantiomers by conventional isotope ratio mass spectrometry and

combined gas chromatography/isotope ratio mass spectrometry. Anal. Chem. 63,

370–374. https://doi.org/10.1021/ac00004a014.

Sørensen, S.R., Schultz, A., Jacobsen, O.S., Aamand, J., 2006. Sorption, desorption and

mineralisation of the herbicides glyphosate and MCPA in samples from two Danish

soil and subsurface proﬁles. Environ. Pollut. 141, 184–194. https://doi.org/10.1016/

j.envpol.2005.07.023.

Spiess, A-N., 2014. propagate: Propagation of Uncertainty, http://CRAN.R-project.org/

package=propagate.

Strickland, M.S., Rousk, J., 2010. Considering fungal:bacterial dominance in soils –

methods, controls, and ecosystem implications. Soil Biol. Biochem. 42, 1385–1395.

https://doi.org/10.1016/j.soilbio.2010.05.007.

Taylor, J.R., 1997. An Introduction to Error Analysis: The Study of Uncertainties in

Physical Measurements, second ed. University Science Books, Sausalito, California.

Ueda, K., Morgan, S.L., Fox, A., Gilbart, J., Sonesson, A., Larsson, L., Odham, G., 1989. D-

Alanine as a chemical marker for the determination of streptococcal cell wall levels in

mammalian tissues by gas chromatography/negative ion chemical ionization mass

spectrometry. Anal. Chem. 61, 265–270. https://doi.org/10.1021/ac00178a015.

US EPA 2017. Pesticide Industry Sales and Usage: 2008 - 2012 Market Estimates. https://

www.regulations.gov/document?D=EPA-HQ-OW-2019-0583-0132.

US EPA. 4-Chloro-2-methylphenol 1570-64-5 | DTXSID5022510. https://comptox.epa.

gov/dashboard/dsstoxdb/results?search=DTXSID5022510#env-fate-transport.

Vandermeeren, P., Baken, S., Vanderstukken, R., Diels, J., Springael, Dirk, 2016. Impact

of dry-wet and freeze-thaw events on pesticide mineralizing populations and their

activity in wetland ecosystems: a microcosm study. Chemosphere 146, 85–93.

https://doi.org/10.1016/j.chemosphere.2015.11.089.

Wang, S., Miltner, A., Nowak, K.M., 2017. Identiﬁcation of degradation routes of meta-

mitron in soil microcosms using

C-isotope labeling. Environ. Pollut. 220, 927–935.

https://doi.org/10.1016/j.envpol.2016.10.078.

Wild, B., Schnecker, J., Eloy Alves, R., Barsukov, P., Bárta, J., Čapek, P., Gentsch, N.,

Gittel, A., Guggenberger, G., Lashchinskiy, N., Mikutta, R., Rusalimova, O.,

Šantrůčková, H., Shibistova, O., Urich, T., Watzka, M., Zrazhevskaya, G., Richter, A.,

2014. Input of easily available organic C and N stimulates microbial decomposition of

soil organic matter in arctic permafrost soil. Soil Biol. Biochem. 75, 143–151. https://

doi.org/10.1016/j.soilbio.2014.04.014.

Xu, F., Bhandari, A., 2003. Retention and extractability of phenol, cresol, and di-

chlorophenol exposed to two surfaces soil in the presence of horseradish peroxidase.

J. Agricul. Food Chem. 51, 183–188. https://doi.org/10.1021/jf025852s.

Zaprasis, A., Liu, Y.J., Liu, S.J., Drake, H.L., Horn, M.A., 2010. Abundance of novel and

diverse tfdA-like genes, encoding putative phenoxyalkanoic acid herbicide-degrading

dioxygenases, in soil. Appl. Environ. Microbiol. 76, 119–128. https://doi.org/10.

1128/AEM.01727-09.

Zelles, L., 1999. Fatty acid patterns of phospholipids and lipopolysaccharides in the

characterisation of microbial communities in soil: a review. Biol. Fert. Soils 29,

111–129. https://doi.org/10.1007/s003740050533.

K.M. Nowak, et al. Environment International 142 (2020) 105867