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KINETICS OF SOIL NITROGENMINERALIZATION FROM UNDISTURBED

AND DISTURBED SOIL

Ariel Ringuelet* and Omar AntonioBachmeier

Catedra de Edafologıa, Facultad de Ciencias Agropecuarias,

Av. Valparaıso s/n. C.C. 509, Cordoba 5000, Argentina

ABSTRACT

Knowledge of soil nitrogen (N) mineralization processes is

essential for modeling soil processes in agriculture. Many authors

have found discrepancies in N mineralization between disturbed

and undisturbed samples. Nevertheless, most simulation models

use a first-order kinetic model (exponential model) for all the

layers under study, devised from studies using disturbed and

superficial samples. The goal of the present study was to establish

the best kinetic model to explain and predict N mineralization as

affected by sample disturbance and soil depth in two soils of the

semiarid region of Argentina. Disturbed (D: sieved ,2 mm and

quartz mixed) and undisturbed (UD) samples from two

Haplustolls were subject to successive incubations and extractions

to assess N mineralization rates. The amount of N mineralized in

3703

DOI: 10.1081/CSS-120015916 0010-3624 (Print); 1532-2416 (Online)

Copyright q 2002 by Marcel Dekker, Inc. www.dekker.com

*Corresponding author. E-mail: [email protected]

COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS

Vol. 33, Nos. 19 & 20, pp. 3703–3721, 2002

©2002 Marcel Dekker, Inc. All rights reserved. This material may not be used or reproduced in any form without the express written permission of Marcel Dekker, Inc.

MARCEL DEKKER, INC. • 270 MADISON AVENUE • NEW YORK, NY 10016

disturbed samples was up to 200% greater than undisturbed.

Replicate D samples from the Torriorthentic had significantly

higher variability ðp , 0:05Þ than samples from the Torrifluventic.

In the latter, UD samples had a kinetic heterogeneity that was not

apparent in the D samples. These results suggest that the

incubation-technique for D samples is ineffective for these soils.

Key Words: Nitrogen; Mineralization; Undisturbed samples;

Kinetic models

INTRODUCTION

Knowledge of the quantity of N supplied to a growing crop from

mineralization of soil organic matter is important to improve the efficiency of

N fertilizer and reduce the risks of polluting water resources and atmosphere.

There exists a wide variety of chemical and biological methods to assess N

mineralization in the laboratory and in situ.[1] The question arises, whether

the mineralization on disturbed samples can adequately predict mineralization

for in situ structure soil conditions (undisturbed samples).

Stanford and Smith[2] developed an incubation method using disturbed,

dried and rewetted soil samples at 358C. They suggested that nitrogen

mineralization follows first-order (exponential) kinetics for a wide variety of

soils, where the first-order constant k was found not to differ significantly

between soils, whereas the initial pool of potentially nitrogen (N0) varied widely.

Since then, many authors have used this method, and the concept involved in it, to

study mineralization processes.

Alternatives to the exponential model have been proposed: a double

exponential model[3] with two components of potentially mineralizable nitrogen,

each representing organic pools that differ in their resistance to decomposition

(i.e., different rate constants). Bonde and Rosswall[4] modified this model by

replacing the resistant pool with a linear term that accounted for an apparently

unlimited organic pool (zero order kinetics). While exponential models can best

explain N mineralization from plant residues,[5] linear models seem to be

adequate to represent nitrogen mineralization from soil humus,[6] a more resistant

organic fraction. Simard and N’dayegamiye[7] found that the cumulative N

mineralization curves were best described by the Gompertz equation, derived

from the assumptions that the mineralization rate increases in the early stages and

the efficiency of the release process will decrease with time because of the slower

activity of the mineralizing flora or the exhaustion of mineralizable N.

RINGUELET AND BACHMEIER3704



Although many N mineralization kinetic models have been proposed, most

crop yield simulation models use first-order (exponential) kinetics for different

organic matter pools, namely litter, manure, humus, stable, fresh organic N,

active organic N, biomass, and soil organic pools.[8] This over-simplification

masks dynamic changes in N mineralization, originating from root activity,[9]

from type, placement and timing of residue input,[5] by differences in

management histories[10] and by seasonal fluctuations.[11]

Most N mineralization studies have been conducted on disturbed samples.

Some investigators have found discrepancies in N mineralization between

disturbed and undisturbed samples. Nordmeyer and Richter[12] observed that in

undisturbed samples N mineralization increases nearly linearly with time,

whereas disturbed samples show clearly a mineralization flush during the first 20

incubation days, showing that any disturbance introduced by soil preparation has

a strong influence on subsequent N mineralization. Cabrera and Kissel[13]

obtained considerable N mineralization overprediction using disturbed samples,

possibly explained by the pretreatment of soil samples prior to the incubation.

Drying and rewetting the soil is known to induce a flush of nitrogen

mineralization.[14] Mineralization rates decrease with succesive incubation

periods in undisturbed samples,[15] suggesting a mineralization–immobilization

process in soil microsites.

The purposes of the present study were to find N mineralization models that

would properly describe the data obtained with disturbed and undisturbed

samples and to determine whether the models obtained for disturbed samples

could in any way be used to predict the pool of N mineralized under undisturbed

conditions.

MATERIALS AND METHODS

Soils

The work was undertaken in soils of the Semiarid Chaco Region in

Argentina, a vast phytogeographical region where soil N is limiting and there is

scant knowledge of its dynamics.

Two soils of fluvial origin, representative of the area surrounding the Cruz

del Eje River valley, in the Province of Cordoba, Argentina, were used. One was

a coarse loam mixed thermic Torrifluventic Haplustoll, of average fertility, and

the other was a sandy-loam mixed thermic Torriorthentic Haplustoll, of low

fertility (Table 1).

The selected plots in these two soils were in bare fallow at the time of

sampling (May of 1994). A furrow-irrigated squash crop (Cucurbita pepo ) was

harvested two months earlier, without incorporating residues. Before that, there

KINETICS OF SOIL N MINERALIZATION 3705



had been alfalfa for three years, and, previously, five years of alternate

horticultural crops (tomato and squash).

Soil Sampling

Three sites for each soil were randomly chosen (Fig. 1): two cropped (CrA

and CrB), and a noncropped site (NCr). The latter was included in order to

understand the changes in N dynamics that result from soil alteration, since this

site had not been under cultivation disturbance for the last 30 years. The three

sampled sites were in a straight line perpendicular to the direction of the furrows.

The distances between the samples sites were approximately 100 m randomly

selected.

In each site, a 0:70 m £ 0:70 m area was defined, where samples were taken

at two depths: in and below the tillage layer (15–18 cm and 30–33 cm, respecti-

vely). The tillage layer depth was chosen in order that the first depth was selected

just below the tillage disturbance layer, in order to get undisturbed soil cores. The

30–33 cm sampling depth corresponds to the central layer of the AC horizon.

The effect of soil physical disturbance was assessed by taking intact cores

which were used in the incubation studies (UD) with similar soils which were

sieved to create a disturbance effect (D). There were three repetitions for each

type of sample (Fig. 1).

Subsamples in the laboratory were composite samples taken from each

depth within each sampling area. Replicates for UD were three cores taken 40

(^5) cm apart, within the sampling area.

UD samples were taken with a steel cylinder (7.5 cm diameter), and

transferred to a PVC cylinder of the same inner dimension with the help of a

Table 1. Selected Characteristics of the Soils Used in the Study

Soil Torrifluventic Haplustoll Torriorthentic Haplustoll

Depth (cm) 10–20 25–35 10–20 25–35

Organic carbon (g kg21) 17.2 8.4 9.5 5.3

Total N (g kg21) 1.8 1.2 1.2 0.9

Phosphorus (mg kg21) 19.5 20.9 7.2 1.3

pH 7.5 8.0 7.3 8.2

Clay (g kg21) 181 161 106 101

Silt (g kg21) 384 299 190 190

Sand (g kg21) 435 539 704 709

Texture class Loam Sandy loam Sandy loam Sandy loam

Bulk density (Mg m23) 1.17 1.16 1.21 1.19




plunger. A fiberglass disc, a styrofoam lid, and a plastic screen were placed at the

end of each soil column in order to keep it unaltered during transport, incubation

and leaching. Samples were covered with waterproof, oxygen-permeable low

density polyethylene film (30mm thick) to prevent moisture loss. The UD

samples from 30–33 cm were taken exactly below the 15–18 cm samples. After

removal, samples were kept at 48C until the beginning of the incubation, no more

than 72 hours later.

Disturbed Samples Conditioning

Field-moist soil samples from each depth were gently passed through a

2-mm sieve (9 mesh) and mixed with ashed, acid-washed quartz[2] sieved through

1-mm screen (18 mesh) in a 1:1 ratio (80 g soil þ 80 g quartz). The soil samples

were not dried to avoid an initial mineral N-flush, commonly evidenced after the

Figure 1. Soil sampling scheme. Above: the three sample sites within each plot for each

soil. Below: sample site ð0:70 m £ 0:70 mÞ:




drying process, in the first stages of the process.[14] The addition of quartz was

meant to maintain an adequate drainage after re-packing the soil columns. These

samples were incubated in cylinders similar to those used for the UD samples

(310 mL).

Sample Incubation

The soil samples, contained in the PVC cylinders, were initially leached

and then incubated, at a soil moisture close to field capacity up to 27 weeks.

Mineralized N from the Torrifluventic Haplustoll soil was measured on days 6,

20, 38, 65, 91, 131, and 187. In the Torriorthentic Haplustoll soil the measures

were taken on days 14, 28, 54, 94, 134, and 174.

After incubation, mineral N extractions were carried out using the nutritive

solution of Ref. [2] as extractant: aliquots of 50 mL of extraction medium

(0.5 mM of each K2SO4, MgSO4·7H2O and CaSO4·2H2O, and 1.2 mM

Ca(PO4H2)2, up to a total volume of 400 mL, were used to leach all mineralized

N. A vacuum of 20.033 MPa was applied to the UD samples to ensure full perco-

lation of the leaching solution within 24 h of initiating the extraction process.

Net mineralized N was calculated as the sum of NO3-N plus NH4-N in the

percolated solution. The concentration of NO3-N was analyzed using a specific

electrode (ORION 93-07) and the output was recorded with an ORION 901

Ionalizer.[16] The concentration of NH4-N was spectrophotometrically analyzed,

using the indophenol blue method.[16]

Soil moisture was measured periodically by weighing the soil cores plus

their containers. When necessary, enough extractive solution was added and the

cylinders were covered with low density, highly oxygen porous polyethylene, to

maintain the soil moisture close to field capacity. The incubation chamber

temperature was maintained at 308C (^18C).

Chemical and Physical Analyses

To characterize the soils, two composite samples of each soil were taken

from the three sites: one at 13–20 cm and another at 28–35 cm.

The following analyses were carried out: organic C by the Walkley and

Black method,[17] total N content by micro-Kjeldahl,[18] soil pH potentiome-

trically measured at a soil:water ratio of 1:1, particle-size using the pipette

method,[19] and extractable phosphorus by the NaHCO3 method.[20]




Statistical Methods

Mineralization potentials (N0) and rate constants (k,p,h) were estimated

using a nonlinear least squares method as described by Smith et al.[21] Data were

fit to various kinetic models (Table 2). Parameters were estimated by numeric

iteration using the Gauss–Newton algorithm (NLIN procedures of SAS).

Goodness of fit was tested by means of studentized residual versus predicted

values, by the relation sum of regression squares/total sum of the squares

(SRS/TSS), and through the asymmetric standard error of parameter estimators.

Models which did not fit any of the three individual replications were discarded.

Correlations, regressions and T-tests were also performed with SAS.[25]

RESULTS AND DISCUSSION

Quantities of Nitrogen Mineralized

Comparing D and UD treatments, the amount of N mineralized in disturbed

samples was larger than that in undisturbed samples, such as was found by other

authors.[13,15,26] However, in our study, this extra-mineralization was much

lower. In eight treatments, the D samples mineralized between 0 and 52%, based

on N mineralized by UD samples (Tables 3 and 4), and in the other three

treatments (at 30–33 cm depth samples from Torrifluventic soil), the D samples

Table 2. Kinetics Models Fitted to Data

Model Equation References

Zero-order kinetics

(lineal model)

Nm ¼ b0 þ pt Addiscott[22]

First-order kinetics

(exponential model)

Nm ¼ N0 ½1 2 exp ð2ktÞ� Stanford and Smith[2]

Exponential þ lineal

model

Nm ¼ N0 ½1 2 exp ð2ktÞ� þ pt Wedin and Pastor[23]

Gompertz model Nm ¼ N01 exp ½2h exp ð2ktÞ�

2N02 exp ð2hÞ

Simard and

N’dayegamiye[7]

Double first-order kinetics

(double exponential model)

Nm ¼ N01 ½1 2 exp ð2ktÞ�

þN02 ½1 2 exp ð2ktÞ�

Deans et al.[24]

Nm ¼ accumulated mineralized N (mg kg21) at time t; b0 ¼ intercept; p ¼ zero-order

mineralization constant; N0 ¼ potentially mineralizable N (mg kg21); k ¼ first-order

mineralization constant (days21); h ¼ proportionality constant. Semi-decomposition time

ðt1=2Þ ¼ 0:693=k:




mineralized between 167 and 200% more N. The authors cited found extra-

mineralization ranging from 80 to 343%.

In both soils, the main differences between depths were in organic C and

total N contents, and in the C/N ratio, but large differences were observed in the

Torrifluventic in comparison to the Torriorthentic in organic C content (73%

higher), total N (45% higher), and silt and clay fractions (22% higher).

These characteristics could explain the higher differences in N mineralization

between D and UD samples observed at 30 cm in the Torrifluventic soil.

Otherwise N mineralization in D samples at this depth was higher (3.5 times) than

the D samples in the Torriorthentic. At 30 cm, N fractions are more stable, protec-

Table 3. Parameters of Models Found to Best Fit ðP , 0:01Þ Expected of Data from

Cumulative Net N Mineralized (Nm) at Day 174 in the Torrifluventic Haplustoll

Sample

type Site

Depth

(cm)

Nm

(mg kg21)

N0

(mg kg21)

k

(d21)

T1/2

(d)

N0/N

(%)

Exponential Model: Nm ¼ N0ð1 2 expð2ktÞÞ

D NCr 15 212 242 0.011 63.0 13.3

D CrA 15 256 326 0.009 77.0 17.5

D CrB 15 230 268 0.011 63.0 14.8

UD CrB 15 192 347 0.004 173.2 19.0

Sample

type

Site Depth

(cm)

Nm

(mg kg21)

N0

(mg kg21)

k

(d21)

T1/2

(d)

p

Exponential þ linear model: Nm ¼ N0ð1 2 expð2ktÞÞ þ pt

D NCr 30 187 92 0.039 17.6 0.53

D CrA 30 136 61 0.157 4.4 0.41

D CrB 30 161 64 0.117 5.9 0.57

UD NCr 15 148 74 0.021 33.0 0.42

UD NCr 30 70 34 0.056 12.3 0.19

UD CrA 30 44 20 0.081 8.5 0.15

UD CrB 30 59 29 0.086 8.0 0.16

Sample

type

Site Depth

(cm)

Nm

(mg kg21)

N0

(mg kg21)

k

(d21)

h

Gompertz model: Nm ¼ N0 expð2h expðktÞÞ2 N0 exp ð2hÞ

UD CrA 15 210 289 0.015 2.17

D: Disturbed samples; UD: Undisturbed samples; NCr: Noncropped site; Cr: Cropped

sites A and B; T1/2: Mean residence time of N0; N0/N stands by the proportion of N0 over

total N.




ted by fine silt and clay[27] which are exposed upon disturbance, like the Torriflu-

ventic. In contrast, there is less effect of disturbance at 15 cm, since the surface

layer of the readily mineralizable N pool is associated to coarser fractions,

.50mm, derived from plant and root fractions, and less influenced by

disturbance.[27]

Below the tillage layer (30–33 cm), mineralizable N is high, in agreement

with reports by other authors.[28 – 31] Taking the behavior of UD samples as

illustrative of what happens under field conditions, the contribution of subsurface

samples N is approximately 23.9% of the total N mineralized at both depths, for the

Torrifluventic, and 45.8% for the Torriorthentic. This is a very important

contribution, taking into account that mineralizable N can be variable during a

crop cycle, specially in the arable layer, due to the immobilization processes

caused by incorporation and decomposition of plant residues, and root death.[32,33]

The greatest relative contribution of the surface layer in comparison to deeper

layers in the Torrifluventic can be explained by the finer texture of this soil, that

favors protection of new organic matter derived from plant residues,[34,35] and the

slower consumption of the mineralizable pool, associated to a higher C/N ratio.

In the Torriorthentic soil, variability in the quantity of mineralized N during

the incubation period was higher than the Torrifluventic soil. Differences between

soils are especially marked in D samples, which were expected to be more

Table 4. Parameters of Model Found to Best Fit ðP , 0:01Þ Expected of Data from

Cumulative Net N Mineralized (Nm) at Day 187 in the Torriorthentic Haplustoll

Sample

Type Site

Depth

(cm)

Nm

(mg kg21)

N0

(mg kg21)

k

(d21)

T1/2

(d)

N0/N

(%)

Exponential Model: Nm ¼ N0ð1 2 expð2ktÞÞ

D NCr 15 58 75 0.008 86.6 6.5

D NCr 30 42 67 0.006 115.5 7.3

D CrA 15 48 55 0.010 69.3 4.8

D CrB 15 49 79 0.005 138.6 4.3

D CrB 30 35 63 0.005 138.6 6.9

UD NCr 15 38 54 0.007 99.0 4.5

UD NCr 30 42 24 0.012 57.7 2.5

UD CrA 15 33 39 0.011 63.0 3.3

UD CrA 30 30 32 0.014 49.5 3.4

UD CrB 15 41 54 0.008 86.6 4.5

UD CrB 30 23 30 0.008 86.6 3.2

D: Disturbed samples; UD: Undisturbed samples; NCr: Noncropped site; Cr: Cropped sites

A and B; T1/2: Mean residence time of N0; N0/N stands by the proportion of N0 over total N.




homogeneous than UD samples, since they are composite samples. This may be

due to the relatively small and easily depleted N pool in the Torriorthentic.

Mineralization Kinetics

The best mineralization kinetics fit in the Torriorthentic Haplustoll either

for the UD and D samples from both depths was obtained with the exponential

model (Table 4, Fig. 2).

The N mineralization kinetics models in the Torrifluventic Haplustoll

showed more variability than the Torriorthentic soil because 4 samples also had

Figure 2. Cumulative N mineralization versus incubation time and the best fit model

(comparing exp. model, exp. þ lin model, Gompertz model, and double exp. model) for

each treatment in the Torriorthentic Haplustoll soil: (a) Noncropped site (NCr), disturbed;

(b) Cropped site A (CrA), disturbed; (c) Cropped site B (CrB), disturbed; (d) NCr site,

undisturbed; (e) Cr site, undisturbed; (f) Cr site, undisturbed. The standard deviations are

indicated by vertical bars.




the best fit with the exponential model, but others fit better with alternative

models. The D and UD samples from 15 cm depth differed with respect to the best

model (Table 3, Fig. 3). While D samples required the same kinetic model trend

(exponential), UD samples required different kinetic models (exponential þ

linear model, Gompertz model and exponential model). In this soil the

exponential þ linear model was the best fit for all the 30-cm deep samples (D and

UD; Cr and NCr). The low quantities of organic C and mineralizable N (Nm)

found in the Torriorthentic may be responsible for the smaller kinetic

heterogeneity in this soil. This low C content and the high proportion of coarse

texture fractions of the Torriorthentic (Table 1) limit the mineralizable substrate,

so the N reserve originating from humus is small and easily decomposible, fitting

Figure 3. Cumulative N mineralization versus incubation time and the best fit model

(comparing exp. model, exp. þ lin model, Gompertz model, and double exp. model) for

each treatment in the Torrifluventic Haplustoll soil: (a) Noncropped site (NCr), disturbed;

(b) Cropped site A (CrA), disturbed; (c) Cropped site B (CrB), disturbed; (d) NCr site,

undisturbed; (e) Cr site, undisturbed; (f) Cr site, undisturbed. The standard deviations are

indicated by vertical bars.




an exponential mineralization kinetic model more readily. Moreover, due to

limited carbon and energy supply in the Torriorthentic, soil microbial biomass is

likely to decline severely during the incubations experiments, whereas N

mineralization rates in situ conditions are reported to be significantly lower.[4]

The exponential kinetics at 30 cm depth suggests a great dependence of N

mineralized from the more labile N pools. Furthermore, the rate (k) values in

the UD soils were similar at 15 cm and 30 cm for both cultivated sites: 0.011 d21

(15 cm) to 0.014 d21 (30 cm) for the A site and 0.008 d21 for the B site at both

depths. This suggests that the same type of N pool was mineralized, in contrast to

the findings reported by other authors,[36,37] who found a significant decrease in k

values as depth increased.

In contrast to the Torriorthentic soil, in the Torrifluventic soil with finer

fractions (,50mm), the immobilization of N is increased, since there is a

significant physical protection of the soil organic matter.[34,35] There is also a

longer exhaustion period reflected by more linear trend for some treatments

(exponential þ linear model). Then, the kinetic depends more on substrate

quality (more or less decomposition capacity) because of protection by organic

compounds, than on substrate quantity.

Comparing the D (NCr, CrA and CrB) and UD treatments from the same

sites in the Torrifluventic soil, CrB was the only one that exhibited similar

(exponential) kinetics (Table 3, Fig. 3). Ellert and Bettany[10] obtained good fits

by applying several kinetic models to a Typic Cryoboralf, but using soil samples

with different management histories, down to a depth of 15 cm. Differences in the

cropped sites at 15 cm depth, are undoubtedly more influenced by variables such

as root activity[9] and the quantity of residue input.[5] It was demonstrated that the

decomposition of plant residues under optimal conditions can be reasonably well

described by means of first-order kinetics.[27] When applied to soils[38,39] this

model describes the decomposition of the more labile pool (plant residues), but

not the N mineralization of the humus. Mineralizable N originating from plant

residues from successive annual crops can be extremely variable under field

conditions,[40] since it is influenced by residue type and management,

environmental conditions, and field parameters.[41] Most of the root mass from

annual crops is concentrated in the upper 25 cm of the soil. The flow of N in the

root zone is variable and strongly associated with the age of the crop and the level

of mineral N in the soil, resulting in periods of either net immobilization or

mineralization.[42] Moreover, the effects of these factors could be modified by the

influence of tillage that decreases aggregate size, and exposes organic

compounds, protected in microsites by silt and clay particles from the

mineralizing action of the soil microorganisms.[43,44]

It is difficult to define the kinetics of soil N mineralization in each soil with

relatively simple models such as the ones used in most mineralization

studies.[13,45,46] Our findings reflect the existence of different mineralization




patterns for D and UD samples from most sample sites in the tillage layer in one

of the two soils studied (Torrifluventic Haplustoll). Also, there was a spatial

variability in the N mineralization pattern in undisturbed samples in the three

sites at 15 cm depth, as observed by other authors.[5,9,10]

At a depth of 30 cm, samples from the different sites had similar kinetic

parameters, and both soils had significantly smaller variation ðP , 0:05Þ among

replicates of UD samples from 30 than from 15 cm. The N mineralization patterns

with the D and UD samples from the Torrifluventic soil were fitted well with the

exponential þ linear model; in comparison, with the Torriorthentic soil the best

fit occurred with the exponential model. Therefore, the N mineralization pattern

of the Torriorthentic Haplustoll soil was different to that of the Torrifluventic

Haplustoll. The data from the former, with lower C content, fit better with the

exponential model, while the latter, with higher C content, fit better with the

exponential þ linear model.

In the UD Torriorthentic Haplustoll samples at 30 cm depth, we observed a

high correlation between the mineralization constant k (quality factor) and

organic C (R ¼ 0:99; P , 0:01), but no correlation with total N ðR ¼ 0:17Þ: On

the contrary, while the N0 parameter (quantity factor) was highly and negatively

correlated with total N content (20.995; P , 0:05); it had no relationship with

organic C. In contrast, a positive correlation between N0 and total N in the tillage

layer was observed by Cabrera and Kissel,[13] indicating that most N was

associated with more stable compounds or that it had a greater physical

protection. When total N decreases in the cultivated sites, a major qualitative

change in the N pool occurs, and relatively it becomes more labile.

Results from the present study show N mineralization follows an

exponential kinetics pattern, especially in D samples. The conditioning of D

samples creates artificial situations for quartz adittion that alter the relation

among particle fractions, increasing porosity and aeration. As a consequence,

mineralization processes are stimulated[12,13] and decomposition of plant residues

is accelerated, which can be reasonably well described by first order

kinetics.[36,37] This type of model is widely used in the simulation models

applied to soil and aims to explain decomposition in the most labile pool (plant

residues) with a rapid disappearance of mineralizable substrate.

It is very hard to differentiate discrete N pools.[45,47] The decrease in

extractable N between the third and four extractions in D treatments from 15 cm

samples demonstrates that various N pools are releasing simultaneously.

Considering site conditions, it must be recognized that the concept of potentially

mineralizable nitrogen (N0) as a homogeneous, discrete organic N pool is

unlikely.[47,48] The results show that the UD samples (undisturbed and single

samples) reflected a variability in soil nitrogen mineralization dynamics that was

hidden in the D samples (disturbed and composited samples).




Seven of the treatments had a better fit to the exp þ linear kinetics model.

In contrast to what happens with exponential kinetics, zero-order kinetics can

hold for extended periods even at higher temperatures.[49] Very often linearity is

found after several weeks, due to the fact, that incubation experiments are usually

too short to assess a significant decrease of highly recalcitrant pools.[4,50] As Paul

and Juma[51] have shown, pools which cycle slowly may contribute significantly

to N mineralization.

There are few data available for comparison with our data from below the

tilled layer. In the soils in this study, the same model kinetic trend observed in the

three sites at 30 cm could be explained from the “no” influence of cultivation at

this depth, unlike what was found at 15 cm. It is worth remembering that repeti-

tions for UD treatments are single samples, only 40 ^ 5 cm apart within the

sampling site. Nevertheless, a good correlation between the exponential þ linear

function parameters with D and UD treatments at 30 cm was found for the Torriflu-

ventic Haplustoll (Table 5). The disturbance of the 30 cm samples revealed a

pattern of N mineralization indicating stable and protected N in fractions of small

particles.[27] This is evidenced in the small magnitude of the No parameter and the

high k value, which produces very short exhaustion times for this labile pool

(Table 3), later revealing a less labile pool, expressed in the linear component.

In the 15 cm layer there seems to be a “quantity disturbance effect” in the D

samples, where an easily mineralizable N pool is observed, possibly associated

with coarser fractions. This N derives from shoot and root residues.[27] But,

because some of the 15 cm sites had a different mineralization kinetics, it may be

inferred that sample disturbance also seemed to provoke a “quality effect” in the

tillage layer which increased N transfer from a more passive pool.[14] Soil

incubations carried out with composite D samples may always fit a given model,

but our results show that it may not reflect the process as it occurs in the soil, since

Table 5. Simple Linear Correlation Coefficient Between the

Parameters of the Exponential þ Lineal Model at 30 cm Deep of

Disturbed (D) and Undisturbed (UD) Samples in the Torriorthentic

Haplustoll

kD kUD N0D N0UD pD

kD 1.000

kUD 0.880 1.000

N0D 20.968 20.970 1.000

N0UD 20.940 20.665 0.826 1.000

pD 20.565 20.105 0.342 0.812 1.000

pUD 20.985 20.784 0.911 0.911 0.700

All the coefficients are statistically significant at p , 0:01:




N dynamics in UD samples revealed a N mineralization kinetics heterogeneity

that remained hidden in the D samples. Such heterogeneity was due to

methodological differences: soil disturbance alters microbial dynamics by

modifying the access to substrates.

Despite variability in the pattern of N mineralization for each depth, the

quantity of mineralized N in the incubation period (approximately 6 months) was

similar for the three sampling sites of each soil (Tables 3 and 4). This could limit

the usefulness of kinetic models for estimating mineralized N for longer periods,

because the use of an inadequate model would generate estimation errors that

could increase with time of modeling.[24]

CONCLUSIONS

On the basis of our results it can be inferred that the quantities of

mineralized N and the changes in mineralization kinetics patterns are more

influenced by sample disturbance in the Torrifluventic than in the Torriorthentic

soil. This difference may be due to the existence of a more labile N pool (derived

from stubble incorporation and root activity) protected by fine particle fractions.

Supporting the findings of other authors, the variability in N mineralization

pattern observed in this study in UD samples of the tillage layer in the

Torrifluventic suggests that the parameters derived from models do not necesarily

represent N mineralization capacity for a given soil, if such capacity does exist

for the soil sample under given conditions. Although N mineralization and soil

texture are related, texture by itself does not define the best kinetic model fit,

because other factors, such as soil depth may be involved. These factors alter both

the quality and quantity of mineralizable substrate, and thus, the best kinetic

model fit. Therefore, the use of D samples appears ineffective for estimating N

mineralization in some soils such as the Torrifluventic Haplustol, because the

quantity and dynamics of mineralized N in UD samples is not reflected in D

samples, as had been reported by Cabrera and Kissel.[13]

The main reasons that restrict the use of undisturbed samples are the limited

number of samples that can be studied, and the difficulties associated with the

extraction of mineral N at the end of the incubation period.

ACKNOWLEDGMENTS

To Dr. Jorge Sierra (INRA, France) and Prof. Roberto Alvarez

(Radioisotopic Laboratory, School of Agriculture/UBA, Argentina), for their

valuable views and suggestions; to Dr. Edith Taleisnik for language assistance,

and to the SeCyT-UNC and CONICOR, for their financial support.




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