TECHNICAL REPORTS

1918

Th e phenoxyacetic acid herbicide MCPA (2-methyl-4-chlorophenoxyacetic acid) is frequently detected in groundwater beneath Danish agricultural fi elds. We investigated spatial variation in microbial MCPA mineralization potential in a fl at agricultural fi eld of fi ne sandy soil (USDA classifi cation: Humic Dystrudept) located on the Yoldia plains of Northern Jutland, Denmark. Samples for determination of MCPA mineralization and sorption were collected from the Ap and Bs horizons at 51 sampling sites located in a 200 × 220 m grid. Spatial variation in sorption was low in both horizons (distribution coeffi cient, 0.36–4.16 L kg−1). Sorption correlated strongly with soil organic carbon content in both horizons (CV, 93 and 83%, respectively) and negatively with soil pH. [Ring-14C]-MCPA mineralized readily in the Ap horizon, with 49 to 62% of the 14C-MCPA being converted to 14CO

2 during the 67-d incubation

period. With the subsoil, mineralization of 14C-MCPA varied considerably between samples (0.5–72.8%). At neither depth was there correlation between 14C-MCPA mineralization and sorption, soil pH, organic carbon content, clay content, number of colony-forming units (CFU), pseudomonad CFU, or any of the four microbial activity parameters measured. Th e presence of microbial genes encoding for the TfdA enzyme was quantifi ed using real-time polymerase chain reaction. No correlation was found between MCPA mineralization potential and the natural background number of tfdA genes present in the soil samples. Th e degradation kinetics suggests that the high 14C-MCPA mineralization rate detected in soil samples was linked to growth of the MCPA-degrading soil microbial community.

Spatial Variation in 2-Methyl-4-chlorophenoxyacetic Acid Mineralization and Sorption

in a Sandy Soil at Field Level

L. Fredslund* Geological Survey of Denmark and Greenland

F. P. Vinther University of Aarhus

U. C. Brinch Geological Survey of Denmark and Greenland, Biotech Research and Innovation Centre

L. Elsgaard University of Aarhus

P. Rosenberg Geological Survey of Denmark and Greenland

C. S. Jacobsen Geological Survey of Denmark and Greenland, University of Copenhagen

The presence and activity of pesticide catabolizing soil

microorganisms in agricultural fi elds is known to be infl uenced

by biotic and abiotic soil properties (Bending et al., 2001; Bending

et al., 2003; Nunan et al., 2002; Walker et al., 2001). Microbial

processes in the soil generally exhibit considerable spatial variation

(Nunan et al., 2002), although the factors responsible for this spatial

heterogeneity generally remain unclear.

Th e degradation of most pesticides in soil is enzymatically

catalyzed by microorganisms (Topp et al., 1997) and generally fol-

lows zero-order or fi rst-order kinetics. Th is indicates that they are

degraded by co-metabolism along with the general metabolic activi-

ties of the soil community and hence provide little or no energy to

the organisms involved. Repeated application of a pesticide to a soil

for a period of several years may result in enhanced biodegradation,

thereby indicating adaptation of the soil microbial community (Jen-

sen and Petersen, 1952) and proliferation of organisms able to use

the compound as an energy source (Bending et al., 2001).

As the indigenous soil microbial community adapts to repeated

exposure to a pesticide, the presence and capacity of the degrading

microorganisms in a soil are mainly determined by the pesticide

application history at the site (Sorensen et al., 2003; Sorensen and

Aamand, 2003). It does not explain the intra-fi eld spatial varia-

tion in degradation rate, however. Th e latter has been attributed to

parameters such as general metabolic diversity and microbial bio-

mass, growth-linked versus co-metabolic degradation mechanisms,

and soil pH and to intrinsic soil properties such as Ctotal

/Ntotal

ratio

and water-extractable potassium (Bending et al., 2001; Rasmussen

et al., 2005; Walker et al., 2001; Walker et al., 2002).

Abbreviations: ASA, arylsulfatase activity; CFU, colony-forming units; Ct, cycle

threshold; 2,4-D, 2,4-dichlorophenoxyacetic acid; FDA, fl uorescein diacetate hydrolysis;

ISR, in situ soil respiration; MCP, 2-methyl-4-chorophenol; MCPA, 2-methyl-4-

chlorophenoxyacetic acid; Corg

, organic carbon; PCR, polymerase chain reaction; SIR,

substrate-induced respiration; TSA, tryptic soy broth agar.

L. Fredslund, U.C. Brinch, P. Rosenberg, and C.S. Jacobsen, Dep. of Geochemistry,

Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, DK-1350

Copenhagen, Denmark; F.P. Vinther and L. Elsgaard, Univ. of Aarhus, Faculty of

Agricultural Sciences, Inst. of Agroecology and Environment, DK-8830 Tjele, Denmark;

U.C. Brinch, Biotech Research and Innovation Centre (BRIC), Fruebjergvej 3, DK-

2100 Copenhagen, Denmark; C.S. Jacobsen, Dep. of Natural Sciences, Faculty of Life

Sciences, Univ. of Copenhagen, Thorvaldsensvej 40, DK-1871 Frederiksberg, Denmark.

Copyright © 2008 by the American Society of Agronomy, Crop Science

Society of America, and Soil Science Society of America. All rights

reserved. No part of this periodical may be reproduced or transmitted

in any form or by any means, electronic or mechanical, including pho-

tocopying, recording, or any information storage and retrieval system,

without permission in writing from the publisher.

Published in J. Environ. Qual. 37:1918–1928 (2008).

doi:10.2134/jeq2006.0208

Received 30 May 2006.

*Corresponding author (lf@geus.dk).

© ASA, CSSA, SSSA

677 S. Segoe Rd., Madison, WI 53711 USA

TECHNICAL REPORTS: VADOSE ZONE PROCESSES AND CHEMICAL TRANSPORT

Fredslund et al.: Field-Level Variation in MCPA Mineralization and Sorption 1919

Th e phenoxyacetic acid herbicide MCPA (2-methyl-4-chlo-

rophenoxyacetic acid) has been widely used to control a range of

broadleaf weeds in agricultural fi elds and uncultivated areas over

the past 50 years (Caux et al., 1995). Th e substance is highly water

soluble with low retention in soil (Kd, 0.3–1.0 L kg−1), thus pos-

ing the risk that it may leach to and contaminate the groundwater

(Helweg, 1987; Socias-Viciana, 1999). Under aerobic conditions,

MCPA degrades rapidly (half-life, 3–16 d) (Muller, 1997; Th or-

stensen and Lode, 2001). Even though the MCPA mineralization

potential of agricultural soils generally seems to be high when

studied in the laboratory, MCPA is nevertheless detected in Dan-

ish groundwater beneath agricultural fi elds and in creeks. During

the period 1993 to 2003, MCPA was detected in 9.3% of 118

groundwater wells monitored in Denmark (GEUS, 2004).

Th e degradation of phenoxyacetic acid herbicides such as

2,4-dichlorophenoxyacetic acid (2,4-D), MCPA, and related

compounds has been studied intensively, and detailed knowledge

is available about the catabolic pathways that these compounds

follow (Bollag et al., 1967; Gaunt and Evans, 1971; Pieper et al.,

1988). Th e fi rst step in the degradation of MCPA is mediated

by the TfdA enzyme (a ketoglutarate dioxygenase). Th is converts

MCPA to 2-methyl-4-chorophenol (MCP) by oxidation of α-ke-

toglutarate to succinate. Th e gene encoding for the TfdA enzyme

is known to be carried within the tfdA-F gene cluster, which was

fi rst identifi ed on the conjugative plasmid pJP4 in Alcaligenes eutrophus (Ralstonia eutropha) JMP134 (Don and Pemberton,

1981; Don and Pemberton, 1985). Based on sequence similarity

analysis, it has recently been proposed to subdivide the tfdA genes

into three classes: Class I contains those genes that are closely

related to the pJP4 plasmid, and Classes II and III cover all other

groups (Itoh et al., 2004). Class I, II, and III tfdA genes encode

enzymes that convert 2,4-D to 2,4-dichlorophenol.

Th e phenoxyacetic acid herbicide 2,4-D, which is closely

related to MCPA, is degraded by specifi c bacteria able to use

it as a source of C and energy and by other microorganisms

in co-metabolic pathways (Robertson and Alexander, 1994).

Spatial variation in 2,4-D mineralization has been found to

be inversely proportional to scale over the range fi eld scale to

microhabitat scale (<1 cm3) due to the uneven distribution

of degrading bacteria and the C necessary for co-metabolism

(Gonod et al., 2003).

Little information is available about spatial variation in

the microbial degradation of MCPA. In microcosm studies

of MCPA degradation in topsoil and subsoil from a sandy

agricultural fi eld, Baelum et al. (2006) found a shift in cata-

bolic tfdA genes from the Class I tfdA genes that were initially

dominant in the soil to the Class III tfdA genes that were re-

sponsible for the observed mineralization of MCPA.

Th e objective of the present study was to examine variation

in microbial MCPA mineralization potential at fi eld level and

to relate this to relevant biotic and abiotic parameters, includ-

ing soil sorption of MCPA, and to the initial presence of tfdA

genes as measured by quantitative real-time polymerase chain

reaction (PCR).

Materials and Methods

Field DataTh e study site was a fl at, fi ne sandy agricultural fi eld classifi ed

as a Humic Dystrudept according to the USDA classifi cation sys-

tem. Th e fi eld was located in the northern part of Jutland, Den-

mark (52°27′E, 43°21′N) on the Yoldia plains. During recent

years, the fi eld has received around 10,000 kg animal manure

ha−1 yr–1 and has mainly been cultivated with cereals. Th e herbi-

cide MCPA had been applied to the fi eld by farmers several times

during the 10-yr period before the study. A regular 35-point grid

covering approximately 3 ha was established in the fi eld. Th e

distance between grid points was approximately 35 m. At four

randomly selected grid points, an additional sampling point was

established at a distance of 5 m from the grid point in each direc-

tion along the grid, resulting in a total of 51 sampling points in

the fi eld. Th e geographic location of each grid point was deter-

mined using a GPS with a precision of approximately 1 m.

Soil Sampling and StorageAt each grid point, approximately 10 kg of soil was sampled

from the topsoil layer (Ap horizon; 5–25 cm soil depth inter-

val) and from the subsoil (Bs horizon; 40–60 cm soil depth

interval). Th e samples were brought to the laboratory in closed

plastic containers, and each container was mixed in a large

end-over-end shaker for 10 min. Each soil sample was sieved

through a 4-mm mesh, with the mesh being carefully cleaned

between samples to avoid cross-contamination. For analysis

of microbial activity, 200-g aliquots were kept in closed inert

Rilsan plastic bags (Rotek A/S, Sdr. Felding, Denmark) at 4°C

for a maximum of 10 d. For analysis of pesticide sorption, the

soils were air-dried at room temperature and stored under dry

conditions. For all other uses (mineralization analysis, colony-

forming unit [CFU] counts, and DNA extraction), the sieved

soil was stored at –20°C for up to several months before being

processed consecutively. Seven days before use, the soil samples

were acclimatized at 10°C (Mortensen and Jacobsen, 2004).

Th e results of the pedologic and geochemical analyses per-

formed on the soil samples are summarized in Table 1.

Soil CharacteristicsTh e soil texture, classifi ed as clay (<2 μm), silt (2–63 μm),

and sand (63–500 μm), was measured in the 102 individual

soil samples by chemical dispersion with Na2PO

7 followed by

hydrometric determination of clay and silt and by wet sieving

of sand as described by Gee and Bauder (1986). Total organic

Table 1. Major soil characteristics shown for the two horizons studied at the test site.

Ap horizon (5–25 cm) Bs horizon (40–60 cm)

Parameter Mean† Range Mean† Range

Clay (%) 3.6 2.6–4.3 2.4 1–7.4

Silt (%) 9.5 2.9–17.5 7.0 1.9–51.0

Sand (%) 85.0 76.7–93 90.1 44.5–96.9

Corg

(g kg−1) 12 5–23 2 0–7

pH (CaCl2) 6.2 5.2–6.7 5.4 4.3–6.4

† n = 51.

1920 Journal of Environmental Quality • Volume 37 • September–October 2008

carbon (Corg

) content was determined on ball-milled sub-

samples using a LECO CNS-1000 analyzer with an infrared

detector (LECO Corporation, St. Joseph, MI).

CFU CountsFrozen 15-g soil samples in glass vials were thawed at 10°C

in the dark for 7 d, corresponding to the time used for ac-

climatization of soil samples before the mineralization experi-

ments. Soil suspensions were prepared by blending 10.0 g soil

with 100 mL 0.9% NaCl for 60 s. Large soil particles were

allowed to settle for 15 min before sampling of 1.0 mL soil

suspension for a 10-fold dilution series in 0.9% NaCl.

Total viable counts of bacteria in the samples were made by

drop-plating on 1/300 tryptic soy broth agar (TSA) plates. Th e

bacterial pseudomonad population in each sample was estimat-

ed from triplicate plate counts on Gould S1 agar plates (Gould

et al., 1985). Th e plates were incubated at 20°C for 72 h.

Microbial Activity MeasuresIn situ soil respiration (ISR) was measured using a dynamic

chamber method as described by Vinther et al. (2007). Arylsulfa-

tase activity (ASA) was measured on 2-g soil samples as described

by Elsgaard et al. (2002) and Vinther et al. (2007). Fluorescein di-

acetate (FDA) hydrolysis was measured according to the method of

Schnurer and Rosswall (1982). Substrate-induced respiration (SIR)

was measured using the method of West and Sparling (West and

Sparling, 1986) as described by Vinther et al. (2007). All microbial

activity measurements where made on nonfrozen soil samples in

connection with or shortly after sample collection (10 d max).

Mineralization ExperimentsA stock solution of ring-labeled 14C-MCPA was prepared by

dissolving analytical grade MCPA (99.5% purity) purchased from

Dr. Ehrenstorfer GmbH (Augsburg, Germany) in Milli-Q water

(Millipore, Billerica, MA) and adding trace amounts of [Ring-14C]-

MCPA (159.7 μCi mmol–1) purchased from IZOTOP (Budapest,

Hungary) to achieve an initial radioactivity in each microcosm of

approximately 50,000 dpm and a fi nal MCPA concentration of 20

mg L–1. To ensure the complete dissolution of the MCPA and to

avoid disturbance of the soil pH, the pH of the stock solution was

adjusted to 6.5 with NaOH. Th e radiochemical purity of [Ring-14C]-MCPA was >95% according to the manufacturer.

Th e mineralization of MCPA was estimated in sieved (>4 mm)

soil in 100-mL bottles with airtight glass lids. Microcosms were

prepared in triplicate for each soil sample using 10.0 g soil (dry

weight). Th e soil moisture content was adjusted to 90% of the soil

water-holding capacity with sterile Milli-Q water (corresponding

to approximately 9% H2O after MCPA spiking). Th e microcosms

were spiked with 500 μL of the MCPA stock solution to obtain

a fi nal concentration of 1.0 mg MCPA kg−1 soil (dry weight). A

sterile 3-mL glass vial containing 2.0 mL 0.5 M NaOH was placed

in each microcosm to capture the CO2 produced during miner-

alization of the MCPA as described by Larsen et al. (2000). Th e

microcosms were incubated at 10°C in the dark.

Th e NaOH in the microcosm CO2 traps was sampled at

Days 8, 15, 22, 29, 39, 43, 52, 57, and 67. Th e 14CO2 content

was determined using a Wallac 1409 liquid scintillation counter

after mixing with 10 mL of OptiPhase Hisafe 3 scintillation

cocktail (Wallac, Turku, Finland). Radioactivity was converted

to percentage mineralization of the MCPA in the microcosms.

Sorption ExperimentsSorption of [Ring-14C]-MCPA was determined on all 102

soil samples in triplicate. Air-dried samples were sieved to <2

mm before initiation of the sorption experiments. Th e sorption

experiments were performed in 13-mL Pyrex vials with Tefl on

screw-caps. A sample to solution ratio of 1:1 was used with a

liquid phase consisting of 0.01 M CaCl2, as recommended in

the OECD guidelines for sorption studies (OECD, 2000). Th e

MCPA concentration was 250 μg kg−1, and each vial contained

20,000 dpm 14C-MCPA mL–1. Th e vials were incubated on an

orbital shaker at 10°C for 96 h. Th is was followed by centrifu-

gation (30 min at 2700 × g) and removal of the supernatant.

Th e 14C in the supernatant was measured by liquid scintillation

counting as described for the mineralization experiments, and

the distribution coeffi cient (Kd) was calculated. Th e pH was

measured on one of each set of triplicate soil subsamples after

dilution in 0.01 M CaCl2. Th e spatial variation in MCPA sorp-

tion and mineralization was visualized on contour maps pro-

duced by ordinary kriging with the Surfer version 7.00 surface

mapping system (Golden Software, Inc., Golden, CO).

DNA ExtractionFrozen 15-g soil samples in glass vials were thawed at 10°C

in the dark for 7 d to acclimatize the soil microorganisms before

DNA extraction. Whole-community DNA was extracted from

0.5-g (wet weight) soil samples using the FastDNA SPIN kit for

soil (Bio101 Inc., Carlsbad, CA). Th e protocol recommended

by the manufacturer was followed with two modifi cations. Th e

beat-beating step was modifi ed to four 30-s pulses at speed 4

instead of one 30-s pulse at speed 5.5 in the FastPrep FP 120

instrument (Bio101 Inc.). A freeze-thaw step was included with

freezing of the samples for 1 h at –80°C and thawing for 30

min at 30°C. Each DNA sample was eluted in 100 μL RNase/

DNase-free water (Bio101 Inc.) and stored at –80°C.

Real-Time Quantitative PCRTh e forward primer 5′-GAGCACTACGC(G/

A)CTGAA(T/C)TCCCG-3′ and the reverse primer 5′-GTC-

GCGTGCTCGAGAAG-3′ were used to yield a 210–base-

pair DNA fragment. Th e primers were purchased from MWG

Biotech (Ebersberg, Germany). Th e primer set was designed

on the basis of 22 Class I and Class III tfdA genes retrieved

from GenBank (Baelum et al., 2006).

Th e mixture used for the real-time PCR consisted of the

QuantiTect SYBR green PCR kit (QIAGEN, Crawley, UK)

containing deoxynucleoside triphosphate mix, HotStar Taq

DNA polymerase, PCR buff er, Rox, and 2.5 mM MgCl2.

Th e reaction mixtures contained 0.4 μM of each primer, 12.5

μL of the respective SYBR green mix, 25.0 μg bovine serum

Fredslund et al.: Field-Level Variation in MCPA Mineralization and Sorption 1921

albumin (Amersham Bioscience, Buckinghamshire, United

Kingdom), 1.0 μL of 1:10-diluted DNA extract, and RNase/

DNase-free water to a fi nal volume of 25 μL.

Duplicate PCR was performed on DNA extracted from

each of the 51 topsoil samples and 27 of the subsoil samples.

Standards for the quantitative PCR were prepared using the

phenoxy acid degrader Ralstonia eutropha AEO106, which car-

ries the pRO101 plasmid. After inoculation into 0.5 g topsoil in

amounts of 8 × 106, 8 × 105, 8 × 104, 8 × 103, 8 × 102, 8 × 101,

and 8 × 100 cells g soil–1, the DNA was extracted from the soil as

described previously. Th e extracts were diluted 10-fold to reduce

the eff ect of humic acid disturbances. Th e DNA extracted from

Pseudomonas cepacia DBO1 (pRO101) (Harker et al., 1989) was

used as a positive control for the real-time PCR reaction.

Real-time PCR was performed using an iCycler iQ (Bio-Rad,

Hercules, CA) under the following conditions: 6 min at 95°C;

50 cycles of 45 s at 94°C, 30 s at 64°C, and 2 min at 72°C; 6

min at 72°C. To obtain a specifi c melting profi le of the real-time

PCR products, an 80-cycle protocol of 45 s at 58°C; 30 s at

58°C to 98°C, increasing 0.5°C every cycle; and 45 s at 58°C

was performed after the real-time PCR. Th e melting profi le

was used to confi rm the presence of the specifi c product and to

determine whether the PCR product was composed of DNA

sequences of more than one length. Th e size of the PCR products

was confi rmed by gel electrophoresis of 8 μL PCR product on a

1.5% agarose gel in 1× Tris-acetate-EDTA buff er. Th e gels were

stained in ethidium bromide and visualized under UV light.

Principal Component AnalysisTh e correlation between real-time PCR cycle threshold (Ct)

and soil properties and MCPA mineralization was investigated

by partial-least-squares regression (Espensen, 2002) using Mat-

Lab (Mathworks Inc., 2006) with the PLS-toolbox software

(Eigenvector Research Inc., 2006). Th e partial-least-squares

regression models were validated using cross-validation with

the leave-one-out procedure. Outliers were identifi ed based on

their infl uence on the model (leverage) together with their pre-

diction residuals. Th e following variables were included in the

principal component analysis: accumulated 14C mineralization

on all sampling days, Corg

, soil pH, clay content, total CFU,

pseudomonad CFU, microbial activity parameters (ASA, FDA,

and SIR), sorption Kd, and tfdA real-time PCR Ct.

Results

CFU Counts and Microbial ActivityTh e mean CFU count on drop-plated 1/300 TSA was 1.1

× 107 CFU g soil–1 (2.0 × 106 to 1.0 × 108 CFU g soil–1) in the

topsoil samples and 4.3 × 106 CFU g soil–1 (9.6 × 103 to 4.5 ×

107 CFU g soil–1) in the subsoil samples. Th e mean count for

the pseudomonad subpopulation on Gould S1 agar was 2.5 ×

105 CFU g soil–1 (2.1 × 104 to 4.4 × 106 CFU g soil–1) in the

topsoil samples and 4.8 × 103 CFU g soil–1 (0–1.2 × 105 CFU

g soil–1) in the subsoil samples.

Th e microbial biomass (CFU and SIR) and activity (ISR,

ASA, and FDA) decreased by one to two orders of magnitude

from the topsoil to the subsoil (Vinther et al., 2007), and the

CV of these parameters was considerably higher in the subsoil

than in the topsoil (98–465% and 25–255%, respectively). In

general, the spatial distribution of the above microbiological

parameters (ISR, SIR, ASA, FDA, total CFU, and pseudo-

monad CFUs) corresponded to the spatial distribution of clay

and Corg

, as described in detail by Vinther et al. (2007).

MCPA Mineralization ExperimentsTh e accumulation of 14CO

2 in all topsoil samples followed

a sigmoidal curve, comprising a lag phase with little or no

mineralization, a steep segment with rapid MCPA mineraliza-

tion, and a plateau after mineralization had ceased.

Th e mineralization of MCPA varied little between topsoil

samples, all of which exhibited a lag phase of <7 d and a simi-

lar maximal mineralization rate of approximately 2% d−1 (Fig.

1A). Th e plateau was reached approximately 20 d after addi-

Fig. 1. Accumulated mineralization of [14C-Ring]-2-methyl-4-chlorophenoxyacetic acid (MCPA) during the 67-d incubation period shown for all 51 samples. Each sample was determined in triplicate with the variation being indicated by vertical bars. (A) Ap horizon. The mean value for each sampling day is also indicated (closed triangle). (B) Bs horizon. Representative samples (±SD) are shown for each of four groupings (A, B, C, and D) selected on the basis of their diverse but distinct patterns of MCPA mineralization.

1922 Journal of Environmental Quality • Volume 37 • September–October 2008

tion of MCPA. By the end of the incubation period (Day 67),

49.4 to 62.2% of the MCPA had mineralized (Table 2).

Th e mineralization of MCPA varied considerably in the 51

subsoil (Bs horizon) samples, with total mineralization at Day 67

ranging from 0.5 to 72.8%. Based on their MCPA mineraliza-

tion curves, the subsoil samples could be roughly divided into

four groups (Fig. 1B). Nine soil samples were characterized by a

sigmoidal mineralization curve comprised of a lag phase of ap-

proximately 15 d and a steep segment that reached a plateau after

approximately 40 d, with fi nal mineralization at Day 67 being 58

to 72.8% (Group A). Twenty-fi ve soil samples were characterized

by a sigmoidal mineralization curve comprised of a lag phase of

approximately 22 d and a slope that just reached a plateau at the

end of the 67-d incubation period, with fi nal mineralization be-

ing 52 to 71% (Group B). Eight soil samples were characterized

by a nonsigmoidal mineralization curve comprised of a lag phase

of approximately 22 d followed by linear mineralization, with

fi nal mineralization at Day 67 being 14 to 40%. Finally, nine soil

samples failed to exhibit any signifi cant mineralization (<2%)

during the 67-d incubation period.

Total accumulated mineralization of MCPA was >50%

in all of the topsoil samples and most of the subsoil samples.

2-Methyl-4-chlorophenoxyacetic acid mineralization potential

did not correlate with any of the soil parameters or microbio-

logic activity parameters tested (Table 3).

Th e spatial distribution of MCPA mineralization diff ered

between topsoil and subsoil samples (Fig. 2). Th us, as can be

seen from the contour plot of mineralization potential, there

is little variation among the topsoil samples (Ap horizon; CV

5%) but considerable variation among the subsoil samples (Bs

horizon; CV 56%). In the subsoil, areas of high and low min-

eralization potential are interspersed throughout the fi eld.

Soil Sorption of MCPASorption of MCPA to the topsoil and subsoil samples

varied within a limited and low range. Th us, Kd of the topsoil

samples ranged from 0.36 to 2.25 L kg−1 (mean, 1.04 L kg−1),

whereas that of the subsoil samples ranged from 0.03 to

4.16 L kg−1 (mean, 0.41 L kg−1) (Table 2). Th e CV was 49%

within topsoil samples but 175% within subsoil samples.

In the topsoil (Ap horizon), Kd for MCPA sorption to

soil correlated signifi cantly with clay content and Corg

content

(r = 0.60 and 0.93, respectively) (Table 3). In the subsoil (Bs

horizon), in contrast, Kd for MCPA correlated signifi cantly

with Corg

content (r = 0.83) but not with clay content. In the

Ap and Bs horizons, Kd correlated negatively with soil pH

(r = –0.54 and –0.57, respectively).

From the contour maps of the spatial distribution of the

MCPA sorption (Fig. 2), it can be seen that Kd was highest in

the northwestern corner of the fi eld and lowest toward the cen-

tral and southern part of the fi eld in the Bs horizon. Because Kd

correlated strongly with Corg

content, the contour maps for Kd

are similar to those for Corg

presented in Vinther et al. (2007).

Real-Time PCR of tfdA GenesReal-time PCR analysis revealed a low background level of

tfdA genes in the subsoil (2.5 × 102 to 2.0 × 104 tfdA gene cop-

ies g soil–1) and an even lower level in the topsoil. In view of this

discrepancy, it is suspected that the measurements of background

level in the topsoil are biased by PCR-inhibiting substances in the

soil DNA extracts. Th us, although the results show the intrafi eld

variation in the natural tfdA gene content within each horizon,

the results from the two horizons are not directly comparable.

In view of this, we decided to present the real-time PCR results

in terms of the Ct for PCR amplifi cation of tfdA gene templates

rather than converting these values to the absolute number of

tfdA genes. Th e conversion of Ct to the absolute number of tfdA

genes (assuming one copy per cell) is expressed by the equation

y = −4.17x + 44.41, where y is Ct, −4.17 is the slope constant,

and 44.41 is the y intercept. Th e formula is derived from the real-

time PCR standard curve (Fig. 3).

Mean accumulated 14CO2 resulting from MCPA mineraliza-

tion is shown versus mean real-time PCR Ct for each soil sample

Table 2. Sorption coeffi cient (Kd) and accumulated 14C-MCPA mineralization

at Day 67 in the Ap and Bs horizons.

Ap horizon (5–25 cm) Bs horizon (40–60 cm)

Parameter Mean† Range SD CV Mean† Range SD CV

% %

Kd (L kg−1) 1.04 0.36–2.25 0.5 49 0.41 0.03–4.16 0.7 175

14C mineralization (%) 57.0 49.4–62.0 2.8 5 46.2 0.5–72.8 25.9 56

† n = 51.

Table 3. Linear correlation matrix for [14C-Ring]-2-methyl-4-chlorophenoxyacetic acid (MCPA) sorption (Kd) and total accumulated 14C-

mineralization versus soil parameters and microbial activity in the Ap and Bs horizons.

Parameter Clay Corg

† pH ISR‡ CFU§ Pseudomonas SIR¶ ASA# FDA††

Ap horizon

Kd MCPA 0.60*** 0.93*** −0.54** – 0.29 0.24 – – –

14C mineralization −0.22 −0.08 0.19 0.12 0.10 0.06 −0.23 −0.03 −0.24Bs horizon

Kd MCPA 0.13 0.83*** −0.57** – 0.44** −0.10 – – –

14C mineralization 0.12 −0.06 0.09 – −0.17 0.13 0.06 0.11 –

** Signifi cant at the 0.01 probability level.

*** Signifi cant at the 0.001 probability level.

† Total organic carbon.

‡ In situ soil respiration.

§ Colony-forming units.

¶ Substrate-induced respiration.

# Arylsulfatase activity.

†† Fluorescein diacetate hydrolysis.

Fredslund et al.: Field-Level Variation in MCPA Mineralization and Sorption 1923

on each sampling day in Fig. 4.

Th e Ct tended to be low in topsoil

samples that started mineralizing

early (at Day 8), indicating a high

background level of tfdA genes

(Fig. 4A). During the steep seg-

ment of the mineralization curves

from Days 8 to 15, this diff erence

disappeared. Th us, there was no

apparent correlation between fi nal

mineralization level and the initial

presence of tfdA genes in the soil.

With the subsoil samples, no

correlation was found between

MCPA mineralization at the in-

dividual sampling points and the

background level of tfdA genes

(Fig. 4B).

Principal Component AnalysisPrincipal component analysis

did not reveal any parameters that

signifi cantly accounted for the

variation in MCPA mineraliza-

tion in the Ap horizon samples.

With the Bs horizon samples,

principal component analysis

was able to explain 77% of the

variation in Ct using 95% of the

variation in the following six parameters (in descending order

of impact): accumulated MCPA mineralization at Day 15,

Corg

, pH, accumulated mineralization at Day 39, CFU count

on TSA, and pseumonad CFU count on Gould S1 agar. Th ree

identifi ed outliers were removed from the data matrix. Th e abil-

ity of the model to predict Ct is illustrated in Fig. 5.

Discussion

Pedological and Geochemical AnalysesTh e CV was considerably higher for soil texture, pH, and C

org

content in the subsoil (CV, 15–145%) than in the topsoil (CV,

6–41%). In a similar investigation by Röver and Kaiser (1999), in

contrast, the coeffi cients of variation for moisture parameters, total

pore space, pH, and Corg

were found to be low (<10%). Th e diff er-

ences between our fi ndings and those of Röver and Kaiser (1999)

are probably attributable to diff erences in the geological history of

the two sites. In soils with a long history of cultivation, spatial het-

erogeneity is generally low. Although the soil investigated by Röver

and Kaiser (1999) was a luvisol developed from loess (loamy silt),

the soil investigated in the present study is raised seafl oor from the

Yoldia Sea and hence is more likely to be spatially heterogeneous.

MCPA MineralizationMineralization of MCPA in the topsoil (Ap horizon) was

in good accordance with previous studies on mineralization

of this phenoxyacetic acid herbicide in agricultural soils. Th e

studies report a short lag phase of 1 to 10 d (Crespin et al.,

2001; Jensen et al., 2004), a high maximal MCPA mineraliza-

tion rate (Baelum et al., 2006), and high total accumulated

mineralization when the plateau phase is reached (Helweg,

1987; Jensen et al., 2004; Th orstensen and Lode, 2001).

Fig. 2. Contour plots of total [14C-Ring]-2-methyl-4-chlorophenoxyacetic acid (MCPA) mineralization (left) and MCPA sorption coeffi cient (right) in the Ap and Bs horizons. Note the diff erence in scale in the contour plots. For the unit and range of each parameter see Table 2.

Fig. 3. Real-time polymerase chain reaction (PCR) standard curve based on triplicate tfdA measurements on R. eutropha AEO 106 (pRO101) amended in a 10-fold dilution series with subsequent DNA extraction from a sandy reference soil. Natural background levels of tfdA genes in topsoil and subsoil samples were determined using this standard curve (r = 0.998; PCR effi ciency, 73.8%). The relationship between cycle threshold (Ct) and the absolute number of tfdA genes (assuming one copy per cell) is expressed by the equation y = −4.17x + 44.41, where y is Ct, −4.17 is the slope constant, and 44.41 is the y intercept.

1924 Journal of Environmental Quality • Volume 37 • September–October 2008

High intrafi eld spatial variation in pesticide degradation

rate in topsoil has been reported for the insecticide carbofuran

(Parkin and Shelton, 1992), the triazine herbicides metribuzin

and simazine (Walker and Brown, 1983), and the phenylurea

herbicides isoproturon (Beck et al., 1996; Bending et al., 2001;

Bending et al., 2003; Parkin, 1993; Walker et al., 2001; Walker

et al., 2002) and chlorotoluron (Walker et al., 2002).

Intrafi eld spatial variation in MCPA mineralization has not

previously been studied in detail. Our fi nding that mineraliza-

tion of MCPA exhibits very little spatial variation in topsoil is

not unexpected because MCPA is considered to be an easily

degradable herbicide.

Th e high rate of MCPA mineralization and the sigmoidal

nature of the mineralization curve indicate growth and multiplica-

tion of the bacteria initially present in the soil samples. Because the

mineralization of MCPA follows approximately fi rst-

order kinetics after an initial lag phase in all topsoil

samples, it is presumably linked to growth of the

degrading organisms. Th e presence of the phenoxya-

cetic acid herbicide 2,4-D in concentrations as low

as 50 μg L–1 has been shown to cause limited growth

of a 2,4-D degrader in soil (Jacobsen and Pedersen,

1992). In the present study and in previous studies,

we have rarely found total mineralization rates ex-

ceeding 70% (Baelum et al., 2006; Mortensen and

Jacobsen, 2004), indicating that a high proportion

of the 14C in the MCPA assimilated by the soil mi-

croorganisms is converted to new microbial biomass.

Th is provided further evidence for growth-linked

degradation of MCPA.

Th e mineralization potential of most samples

from the Bs horizon was high. Th is indicates that

the subsoil microbiota must have been exposed to

phenoxyacetic acid herbicides previously because

the ability to degrade them is acquired through

repeated exposure and resultant adaptation of the

bacterial community (Robertson and Alexander,

1994). Th e latter authors found that degradation

of 2,4-D is growth linked, with approximately

10% of the mineralized carbon being incorpo-

rated into microbial biomass, thereby confi rming

the original fi nding of Jensen and Petersen (1952)

that repeated application of the herbicide en-

hances the degradation rate due to acclimatization

of the phenoxyacetic acid herbicide-degrading

microbial population.

Th e number of MCPA-degrading bacteria in

the subsoil samples is likely to be less than 10% of

that in the topsoil samples due to the general olig-

otrophic conditions, as is refl ected by the total soil

bacteria CFU on TSA and the pseudomonad CFU.

Th e longer lag phase of MCPA mineralization in the

subsoil samples is probably attributable to the low

bacterial density caused by the oligotrophic condi-

tions because mineralization of MCPA is based on

growth of the degrading community.

Th e spatial variation in MCPA mineralization

potential in the Bs horizon was high, but no correlation was

found to any of the parameters tested. Th e mineralization pat-

terns seen with subgroups A and B of the subsoil samples sug-

gest that mineralization is based on growth and multiplication

of the degrading bacteria, whereas that seen with subgroup C

indicates co-metabolic mineralization or limitation of the degrad-

ing organisms by lack of nutrients or enhanced predation. Th is

is supported by the fi ndings of Bending et al. (2001) that areas

where isoproturon degrades rapidly are characterized by higher 14C-isoproturon mineralization and higher 14C microbial biomass

(indicating growth-linked degradation) than areas where it de-

grades slowly.

In a fi eld study, Gonod et al. (2003) found that 2,4-D min-

eralization potential was extremely heterogeneous among mil-

Fig. 4. Mean accumulated 14C-MCPA mineralization (%) versus mean real-time polymerase chain reaction (PCR) cycle threshold (Ct) for the formation of PCR product on each day of the 14CO

2 sampling days (8, 15, 22, 29, 39, and 67). (A): Ap

horizon. (B) Bs horizon.

Fredslund et al.: Field-Level Variation in MCPA Mineralization and Sorption 1925

limeter-size soil aggregates and that intrafi eld spatial variation was

high at the microhabitat scale. In a later study of the variability of

potential aerobic microbial 2,4-D mineralization at spatial scales

ranging from fi eld to microhabitat level (cm-scale) in a cultivated

topsoil (Gonod et al., 2006), it was found that 2,4-D mineraliza-

tion was spatially structured in hotspots at the microhabitat (cm)

scale, with the variation increasing from fi eld to meter scale, and

further from meter to centimeter scale. Th e authors attributed this

variation to the presence of organic compounds supporting growth

and co-metabolism of the 2,4-D in the degrading microorganisms.

Our results based on sampling distances of 5 or 35 m in the 3-ha

sampling grid suggest that MCPA degradation potential is homog-

enously distributed in topsoil at the fi eld level. Th e distribution was

also homogenous at a smaller scale because there was little variation

between triplicate 10-g subsamples of each topsoil sample.

Heterogeneous herbicide exposure of the underlying subsoil

due to preferential streaming of drainage water could explain

the intrafi eld variation in MCPA mineralization seen in the Bs

horizon samples. Th e mineralization of MCPA has previously

been shown to vary between triplicate soil samples from the

same B horizon sampling point (Baelum et al., 2006). In the

present study the soil samples were very carefully mixed on col-

lection, and the variation between triplicate samples was found

to be very low for all but 6 of the 51 Bs horizon samples.

Because no correlation was found between MCPA miner-

alization and sorption or soil pH, biodegradation of MCPA at

the study site is not determined by these parameters.

In a parallel study by Vinther et al. (2007), mineralization

and sorption of the pesticides glyphosate, metribuzin, and

triazinamin were determined in the same fi eld samples used in

the present study. It was concluded that the spatial distribu-

tion of 14C mineralization in the Ap horizon diff ered for the

three pesticides because the mineralization rate was high only

for glyphosate. Mineralization of glyphosate correlated posi-

tively with all measured soil and microbiological parameters,

whereas mineralization of metribuzin and triazinamin gener-

ally correlated negatively with these parameters. Th e positive

correlation between mineralization of glyphosate and the

measured soil and microbiological parameters was assumed

to be due to the strong affi nity of glyphosate to clay particles

and humus components in the soil, which again would lead

to close contact between the glyphosate and the degrading

organisms present in the soil (which degrade glyphosate co-

metabolically). Degradation of metribuzin and triazinamin is

also thought to occur by co-metabolism, although degrada-

tion was very low, with a maximum of 3.1% (Vinther et al.,

2007). In the present study, degradation of MCPA in the

topsoil seemed to support growth of the degrading microor-

ganisms in the topsoil, whereas that in the subsoil followed

growth-linked kinetics or occurred co-metabolically, thereby

resulting in slower degradation kinetics. Th e intersample

variation in subsoil MCPA mineralization could be attribut-

able to diff erences in exposure of the subsoil to phenoxyacetic

acid herbicides because exposure has probably been limited to

certain parts of the soil matrix.

CFU Counts and Microbial ActivityMineralization of MCPA did not correlate with soil mi-

crobial activity or CFU counts. Th is fi nding is in line with the

results of the parallel analysis of the spatial variation in me-

tribuzin and triazinamin mineralization at the same site (Vin-

ther et al., 2007); as in the present study, no signifi cant correla-

tion was found to any of the microbiological parameters tested.

However, variation in glyphosate mineralization was found to

correlate positively with the microbial activity parameters SIR,

ASA, FDA, and ISR (Vinther et al., 2007). Th e sigmoidal na-

ture of the MCPA mineralization curves for all topsoil samples

(Fig. 1) indicates that MCPA is mineralized by a population

of microorganisms that are able to use MCPA for growth. We

have previously seen growth of microbial degraders during min-

eralization of MCPA in a sandy soil (Baelum et al., 2006).

Soil Sorption of MCPATh e MCPA sorption (expressed as K

d) found in this study

lies within the range previously reported for MCPA (Helweg,

1987; Socias-Viciana, 1999). Variation at the fi eld scale was

slightly lower in the Ap horizon (CV 49%) than in the Bs ho-

rizon (75%). Variation in Corg

content was also higher in the Bs

horizon. In general, variation in all the parameters tested tend-

ed to be greatest in the undisturbed soil layers of the fi eld. Th e

sorption of MCPA was highly signifi cantly correlated to Corg

content in both horizons and to clay content in the Ap horizon.

Soil organic carbon and soil clay and mineral composition

have been shown to infl uence adsorption of MCPA and 2,4-D

(Ogram et al., 1985; Th orstensen et al., 2001). In a long-term fi eld

experiment on soils amended with diff erent types and amounts of

organic matter, Haberhauer et al. (2001) found that the origin of

the soil organic matter seems to be crucial for the sorption behavior

of MCPA and that sorption is inversely correlated to pH.

Examining 10 soils diff ering in clay and Corg

content, Bo-

lan and Baskaran (1996) found that Kd for 2,4-D increased

with increasing soil Corg

, whereas the rate of degradation

decreased. At a soil Corg

content exceeding 120 g kg−1, how-

ever, Kd and degradation rate increased, suggesting enhanced

microbial activity in these soils. In a sandy soil, MCPA min-

eralization was found to correlate strongly with Kd after the

addition of artifi cial sorbents (crushed peat and activated

carbon) (Jensen et al., 2004). Th e authors concluded that it is

Fig. 5. Correlation between predicted cycle threshold (Ct) (partial-least-squares regression model) and measured Ct.

1926 Journal of Environmental Quality • Volume 37 • September–October 2008

important to take the bonding strength of MCPA into con-

sideration when estimating pesticide degradation in soil.

Acidic pesticides sorb to organic soil colloids in a pH-depen-

dent manner, with sorption being greatest under acidic condi-

tions where the pesticides are sorbed in their neutral form (We-

ber, 1972). At pH of 5.4 to 6.2 (the mean values found in the

present study), MCPA is anionic (pKa = 3.07), and electrostatic

repulsion between the anionic herbicide and negatively charged

soil particles could reduce sorption (Helweg, 1987).

Walker et al. (1989) measured sorption and degradation

rates of chlorsulfuron and metsulfuron-methyl in soils taken

from diff erent depths and found sorption of both herbicides

to be inversely correlated with soil pH and positively corre-

lated with Corg

content. Th ey suggested that soil pH was the

main determinant of sorption in most soils. Several authors

have suggested that soil pH is a determinant of herbicide bio-

degradation because pH tends to be higher at sites where the

degradation rate is particularly high than at sites where it is

slower (Cox et al., 1996; Walker et al., 2001).

In the present study, Kd for MCPA correlated negatively

with pH (CV, –0.54 and –0.57 in the Ap and Bs horizons,

respectively). Our detailed study of one fi eld supports the

overall fi ndings that Corg

content and soil pH are the main

determinants of MCPA sorption in sandy soils (Haberhauer

et al., 2001; Th orstensen et al., 2001).

Real-Time PCR of tfdA GenesOur initial hypothesis that high background tfdA levels would

be refl ected in a short lag-phase before onset of mineralization was

not confi rmed. Real-time PCR analysis of tfdA genes involved in

MCPA catabolism revealed only a weak correlation between a high

background level of tfdA genes and a high initial MCPA degrada-

tion rate in individual samples. Total MCPA degradation at the

end of the 67-d incubation period was not linked to the initial

presence of tfdA genes in the samples. Th us, although biodegrada-

tion of MCPA at fi eld scale is high in samples with a high initial

level of tfdA genes, the fact that the initial level of tfdA genes is low

does not preclude mineralization potential being high.

Th e tfdA primers used to enumerate the background level

of tfdA genes were designed on the basis of tfdA-I and tfdA-III

type sequences retrieved from GenBank (Baelum et al., 2006).

Th e lack of correlation between the tfdA gene level in a sample

and its MCPA mineralization potential may be due to the initial

presence of other classes of tfdA genes because the identifi ed tfdA

genes vary (Fulthorpe et al., 1995; Smejkal et al., 2001). Whether

or not all the tfdA gene alleles that mediate MCPA catabolism are

targeted in the present real-time PCR analysis is unclear.

Th e presence or absence of other genes involved in the meta-

bolic pathway of MCPA probably explains the discrepancy be-

tween the tfdA gene level in a sample and its MCPA mineraliza-

tion potential. Both 2,4-dichlorophenol and dichlorocatechol

could have been produced and sorbed to the soil because the

genes necessary for metabolism of these intermediary products

were not present within the microorganisms in the samples.

Th us, the background level of tfdA-I and tfdA-III genes may not

refl ect the full potential of a soil sample to mineralize MCPA.

Soil microcosm experiments on sandy soils from the Dan-

ish outwash plain in southern Jutland have recently shown that

formation of the phenolic metabolite MCP in topsoil is associ-

ated with the presence of tfdA genes belonging to the tfdA Class

I. After a lag phase, mineralization of the MCPA ring structure

was initiated by the multiplication of organisms carrying the tfdA

Class III genes (Baelum et al., 2006). From analysis of tfdA func-

tional genes, Baelum et al. (2006) and de Lipthay et al. (2002)

concluded that the number of copies of a catabolic gene in soil

before contaminant exposure might not necessarily refl ect the

size of the specifi c degrader population. In the present study, the

DNA was extracted from the soil before application of MCPA.

Th us, the results do not refl ect the likely increase in the signal

caused by growth of microorganisms harboring tfdA genes.

It is known that a population of tfdA gene bearing bacteria can

be maintained even if a soil is not exposed to phenoxyacetic acid

herbicides for a period of many years (Baelum et al., 2006). Th e

present study shows that tfdA genes are present in detectable num-

bers in topsoil and subsoil samples throughout an agricultural fi eld.

ConclusionTh e main fi nding of this study is that the mineralization of

MCPA in a sandy soil with low MCPA sorption capacity could

not be predicted from microbial activity, tfdA gene pool size, or

geochemical parameters. Mineralization of MCPA was found to

follow growth-linked degradation kinetics in topsoil but followed

growth-linked kinetics or occurred co-metabolically in the subsoil.

Th is contrasts with mineralization and sorption of the pesticides

glyphosate, metribuzin, and methyltriazinamin at the same site, all

of which were biodegraded co-metabolically (Vinther et al., 2007).

Spatial variation in MCPA sorption was low in the topsoil

and the subsoil, with Kd ranging from 0.36 to 4.16 L kg−1.

Sorption correlated strongly with soil Corg

in both horizons

and negatively with soil pH. No signifi cant correlation could

be established between MCPA sorption and MCPA mineral-

ization potential.

We conclude that MCPA mineralization potential is high

and homogenously distributed in the topsoil (Ap horizon)

but exhibits considerable variation in the subsoil (Bs horizon).

Th is is the fi rst study to report that MCPA mineralization

potential varies considerably in subsoil. We suggest that this

variation is attributable to diff erences in prior exposure of the

subsoil to phenoxyacetic acid herbicides because this is lim-

ited to certain parts of the soil matrix.

AcknowledgmentsWe thank Mette Andersen, Pia Jakobsen, and other

members of the technical staff at GEUS and DIAS who

participated in the KUPA project. We thank Jacob Bælum

for sharing his experience with the tfdA real-time PCR. Th is

work was funded by the Danish Ministry of the Environment

and the Danish Ministry of Food, Agriculture and Fisheries

through Act-157-2000.

Fredslund et al.: Field-Level Variation in MCPA Mineralization and Sorption 1927

ReferencesBaelum, J., T. Henriksen, H.C.B. Hansen, and C.S. Jacobsen. 2006.

Degradation of 4-chloro-2-methylphenoxyacetic acid in top- and subsoil is quantitatively linked to the class III tfdA gene. Appl. Environ. Microbiol. 72:1476–1486.

Beck, A.J., G.L. Harris, K.R. Howse, A.E. Johnston, and K.C. Jones. 1996. Spatial and temporal variation of isoproturon residues and associated sorption/desorption parameters at the fi eld scale. Chemosphere 33:1283–1295.

Bending, G.D., S.D. Lincoln, S.R. Sorensen, J.A.W. Morgan, J. Aamand, and A. Walker. 2003. In-fi eld spatial variability in the degradation of the phenyl-urea herbicide isoproturon is the result of interactions between degradative Sphingomonas spp. and soil pH. Appl. Environ. Microbiol. 69:827–834.

Bending, G.D., E. Shaw, and A. Walker. 2001. Spatial heterogeneity in the metabolism and dynamics of isoproturon degrading microbial communities in soil. Biol. Fertil. Soils 33:484–489.

Bolan, N.S., and S. Baskaran. 1996. Biodegradation of 2,4-D herbicide as aff ected by its adsorption-desorption behaviour and microbial activity of soils. Aust. J. Soil Res. 34:1041–1053.

Bollag, J.M., C.S. Helling, and M. Alexander. 1967. Metabolism of 4-chloro-2-methylphenoxyacetic acid by soil bacteria. Appl. Microbiol. 15:1393–1398.

Caux, P.Y., R.A. Kent, V. Bergeron, G.T. Fan, and D.D. Macdonald. 1995. Environmental fate and eff ects of MCPA: A Canadian perspective. Crit. Rev. Environ. Sci. Technol. 25:313–376.

Cox, L., A. Walker, and S.J. Welch. 1996. Evidence for the enhanced biodegradation of isoproturon in soils. Pestic. Sci. 48:253–260.

Crespin, M.A., M. Gallego, M. Valcarcel, and J.L. Gonzalez. 2001. Study of the degradation of the herbicides 2,4-D and MCPA at diff erent depths in contaminated agricultural soil. Environ. Sci. Technol. 35:4265–4270.

de Lipthay, J.R., J. Aamand, and T. Barkay. 2002. Expression of tfdA genes in aquatic microbial communities during acclimation to 2,4-dichlorophenoxyacetic acid. FEMS Microbiol. Ecol. 40:205–214.

Don, R.H., and J.M. Pemberton. 1981. Properties of six pesticide degradation plasmids isolated from Alcaligenes paradoxus and Alcaligenes eutrophus. J. Bacteriol. 145:681–686.

Don, R.H., and J.M. Pemberton. 1985. Genetic and physical map of the 2,4-dichlorophenoxyacetic acid degradative plasmid Pjp4. J. Bacteriol. 161:466–468.

Eigenvector Research Inc. 2006. PLS-Toolbox. Version 4.0. Eigenvector Research Inc., Wenatchee, WA.

Elsgaard, L., G.H. Andersen, and J. Eriksen. 2002. Measurement of arylsulphatase activity in agricultural soils using a simplifi ed assay. Soil Biol. Biochem. 34:79–82.

Espensen, K.H. 2002. Multivariate data analysis–In practice. 5th ed. Camo Process AS, Oslo, Norway.

Fulthorpe, R.R., C. Mcgowan, O.V. Maltseva, W.E. Holben, and J.M. Tiedje. 1995. 2,4-dichlorophenoxyacetic acid-degrading bacteria contain mosaics of catabolic genes. Appl. Environ. Microbiol. 61:3274–3281.

Gaunt, J.K., and W.C. Evans. 1971. Metabolism of 4-chloro-2-methylphenoxyacetate by a soil pseudomonad–Preliminary evidence for metabolic pathway. Biochem. J. 122:519–526.

Gee, G.W., and J.W. Bauder. 1986. Particle-size analysis. p. 383–409. In A. Klute (ed.) Methods of soil analysis. Part 1. 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI.

GEUS. 2004. Grundvandsovervågning 1998–2003 (In Danish with English Summary). Geological Survey of Denmark and Greenland. Ministry of the Environment, Copenhagen, Denmark.

Gonod, L.V., J. Chadoeuf, and C. Chenu. 2006. Spatial distribution of microbial 2,4-dichlorophenoxy acetic acid mineralization from fi eld to microhabitat scales. Soil Sci. Soc. Am. J. 70:64–71.

Gonod, L.V., C. Chenu, and G. Soulas. 2003. Spatial variability of 2,4-dichlorophenoxyacetic acid (2,4-D) mineralisation potential at a millimetre scale in soil. Soil Biol. Biochem. 35:373–382.

Gould, W.D., C. Hagedorn, T.R. Bardinelli, and R.M. Zablotowitz. 1985. New selective media for enumeration and recovery of fl ourescent pseudomonads from various habitats. Appl. Environ. Microbiol. 49:28–32.

Haberhauer, G., L. Pfeiff er, M.H. Gerzabek, H. Kirchmann, A.J.A. Aquino, D. Tunega, and H. Lischka. 2001. Response of sorption processes of MCPA to the amount and origin of organic matter in a long-term fi eld experiment. Eur. J. Soil Sci. 52:279–286.

Harker, A.R., R.H. Olsen, and R.J. Seidler. 1989. Phenoxyacetic acid degradation by the 2,4-dichlorophenoxyacetic acid (tfd) pathway of plasmid Pjp4–mapping and characterization of the tfd regulatory gene. Tfdr. J. Bacteriol. 171:314–320.

Helweg, A. 1987. Degradation and adsorption of 14C-MCPA in soil–Infl uence of concentration, temperature, and moisture content on degradation. Weed Res. 27:287–296.

Itoh, K., Y. Tashiro, K. Uobe, Y. Kamagata, K. Suyama, and H. Yamamoto. 2004. Root nodule Bradyrhizobium spp. harbor tfdA and cadA, homologous with genes encoding 2,4-dichlorophenoxyacetic acid-degrading proteins. Appl. Environ. Microbiol. 70:2110–2118.

Jacobsen, C.S., and J.C. Pedersen. 1992. Mineralization of 2,4-dichlorophenoxyacetic acid (2,4-D) in soil inoculated with DBO1 (pRO101), AEO106 (pRO101) and JMP134 (pJP4): Eff ects of inoculation level and substrate concentration. Biodegradation 2:253–263.

Jensen, H.L., and H.I. Petersen. 1952. Detoxication of hormone herbicides by soil bacteria. Nature 170:39–40.

Jensen, P.H., H.C.B. Hansen, J. Rasmussen, and O.S. Jacobsen. 2004. Sorption-controlled degradation kinetics of MCPA in soil. Environ. Sci. Technol. 38:6662–6668.

Larsen, L., S.R. Sorensen, and J. Aamand. 2000. Mecoprop, isoproturon, and atrazine in and above a sandy aquifer: Vertical distribution of mineralization potential. Environ. Sci. Technol. 34:2426–2430.

Mathworks Inc. 2006. MatLab. Version 7.3. Mathworks Inc., Natick, MA.

Mortensen, S.K., and C.S. Jacobsen. 2004. Infl uence of frozen storage on herbicide degradation capacity in surface and subsurface sandy soils. Environ. Sci. Technol. 38:6625–6632.

Muller, M.D. 1997. Conversion reactions of various phenoxyalkanoic acid herbicides in soil: II. Elucidation of the enantiomerization process of chiral phenoxy acids from incubation in a D-2O/soil system. Environ. Sci. Technol. 31:1960–1967.

Nunan, N., K. Wu, I.M. Young, J.W. Crawford, and K. Ritz. 2002. In situ spatial patterns of soil bacterial populations, mapped at multiple scales, in an arable soil. Microb. Ecol. 44:296–305.

OECD. 2000. Guidelines for Testing Chemicals. TG 106 Adsorption/desorption using a batch equilibrium method. Environmental Health and Safety Division, OECD Environment Directorate, Paris.

Ogram, A.V., R.E. Jessup, L.T. Ou, and P.S.C. Rao. 1985. Eff ects of sorption on biological degradation rates of (2,4-dichlorophenoxy)acetic acid in soils. Appl. Environ. Microbiol. 49:582–587.

Parkin, T.B. 1993. Spatial variability of microbial processes in soil–A review. J. Environ. Qual. 22:409–417.

Parkin, T.B., and D.R. Shelton. 1992. Spatial variability of carbofuran degradation in soil. J. Environ. Qual. 21:672–678.

Pieper, D.H., W. Reineke, K.H. Engesser, and H.J. Knackmuss. 1988. Metabolism of 2,4-dichlorophenoxyacetic acid, 4-chloro-2-methylphenoxyacetic acid, and 2-methylphenoxyacetic acid by Alcaligenes eutrophus Jmp134. Arch. Microbiol. 150:95–102.

Rasmussen, J., J. Aamand, P. Rosenberg, O.S. Jacobsen, and S.R. Sorensen. 2005. Spatial variability in the mineralisation of the phenylurea herbicide linuron within a Danish agricultural fi eld: Multivariate correlation to simple soil parameters. Pest Manage. Sci. 61:829–837.

Robertson, B.K., and M. Alexander. 1994. Growth-linked and cometabolic biodegradation–Possible reason for occurrence or absence of accelerated pesticide biodegradation. Pestic. Sci. 41:311–318.

Röver, M., and E.-A. Kaiser. 1999. Spatial heterogeneity within the plough layer: Low and moderate variability of soil properties. Soil Biol. Biochem. 31:175–187.

Schnurer, J., and T. Rosswall. 1982. Fluorescein diacetate hydrolysis as a measure of total microbial activity in soil and litter. Appl. Environ. Microbiol. 43:1256–1261.

Smejkal, C.W., T. Vallaeys, S.K. Burton, and H.M. Lappin-Scott. 2001. Substrate specifi city of chlorophenoxyalkanoic acid-degrading bacteria is not dependent upon phylogenetically related tfdA gene types. Biol. Fertil. Soils 33:507–513.

Socias-Viciana, M.M. 1999. Sorption and leaching of atrazine and MCPA in natural and peat-amended calcareous soils from Spain. J. Agric. Food Chem. 47:1236–1241.

Sorensen, S.R., and J. Aamand. 2003. Rapid mineralisation of the herbicide isoproturon in soil from a previously treated Danish agricultural fi eld. Pest Manage. Sci. 59:1118–1124.

Sorensen, S.R., G.D. Bending, C.S. Jacobsen, A. Walker, and J. Aamand. 2003.

1928 Journal of Environmental Quality • Volume 37 • September–October 2008

Microbial degradation of isoproturon and related phenylurea herbicides in and below agricultural fi elds. FEMS Microbiol. Ecol. 45:1–11.

Th orstensen, C.W., and O. Lode. 2001. Laboratory degradation studies of bentazone, dichlorprop, MCPA, and propiconazole in Norwegian soils. J. Environ. Qual. 30:947–953.

Th orstensen, C.W., O. Lode, O.M. Eklo, and A. Christiansen. 2001. Sorption of bentazone, dichlorprop, MCPA, and propiconazole in reference soils from Norway. J. Environ. Qual. 30:2046–2052.

Topp, E., T. Vallaeys, and G. Soulas. 1997. Pesticides: Microbial degradation and eff ects on microorganisms. p. 547–575. In J.D. van Elsas, J.K. Jansson, and J.T. Trevors (ed.) Modern soil microbiology. Marcel Dekker, New York.

Vinther, F.P., U.C. Brinch, L. Elsgaard, L. Fredslund, B.V. Iversen, S. Torp, and C.S. Jacobsen. 2007. Field-scale variation of microbial activity and soil properties in relation to sorption and degradation of pesticides in a sandy soil. J. Environ. Qual. (in press).

Walker, A., R.H. Bromilow, P.H. Nicholls, A.A. Evans, and V.J.R. Smith. 2002. Spatial variability in the degradation rates of isoproturon and

chlorotoluron in a clay soil. Weed Res. 42:39–44.

Walker, A., and P.A. Brown. 1983. Spatial variability in herbicide degradation rates and residues in soil. Crop Prot. 2:17–25.

Walker, A., E.G. Cotterill, and S.J. Welch. 1989. Adsorption and degradation of chlorsulfuron and metsulfuron-methyl in soils from diff erent depths. Weed Res. 29:281–287.

Walker, A., M. Jurado-Exposito, G.D. Bending, and V.J.R. Smith. 2001. Spatial variability in the degradation rate of isoproturon in soil. Environ. Pollut. 111:407–415.

Weber, J.B. 1972. Interaction of organic pesticides with particulate matter in aquatic and soil systems. p. 55–120. In R.F. Gould (ed.) Fate of organic pesticides in the aquatic environment. Adv. Chem. Ser. 111. Am. Chem. Soc., Washington, DC.

West, A.W., and G.P. Sparling. 1986. Modifi cations of the substrate-induced respiration method to permit measurement of microbial biomass in soils of diff ering water contents. J. Microbiol. Methods 5:177–189.