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European Journal of Agronomy 13 (2000) 111–124

Modelling vertical and lateral seed bank movements duringmouldboard ploughing

Nathalie Colbach a,*, Jean Roger-Estrade b, Bruno Chauvel a, Jacques Caneill c

a Unite d’Agrononomie-Malherbologie, INRA, 17 Rue Sully, BV 1540, 21034 Dijon Cedex, Franceb Unite d’Agronomie, INRA-INA PG, 78850 Thi6er6al-Grignon, France

c Departement des Sciences et Techniques Agronomiques, ENESAD, 26 Bd du Dr Petitjean, 21036 Dijon Cedex, France

Received 19 February 1999; received in revised form 12 August 1999; accepted 27 October 1999

Abstract

The vertical distribution of weed seeds in the soil is of fundamental importance because seedling emergence dependson seed depth. The lateral displacement of the earth during mouldboard ploughing contributes to the dispersal of theweeds inside the tilled field. In order to model vertical and lateral seed displacements during ploughing, an existingmodel describing soil particle movements for different ploughing characteristics (depth and width) and soil structureswas tested on a multilocal field trial. The trials were carried out in 1996 and 1997 and comprised two soil texturesand three soil structures; tillage was performed with a mouldboard plough at varying ploughing widths and depths.Seeds were simulated by beads that were introduced immediately before ploughing with an auger at different depthsand lateral positions (relative to the future passage of the coulter) within and just below the ploughed horizon. Lateraldisplacement and the final vertical position of the beads were measured and compared to the simulations obtainedwith the model. The model correctly simulated the final vertical seed co-ordinate and lateral seed displacement as afunction of soil structure, ploughing width and depth and initial seed position, if ploughing depth is lower thanploughing width. If, however, the former exceeds the latter and/or if the furrows are not properly rotated, the modeldoes not simulate the seed movements correctly. The model was then used to calculate seed transfer matricesdescribing vertical seed movements between seed bank layers for different conditions and plough modes and todetermine the optimal ploughing mode for a given seed bank distribution. For instance, if most seeds are located inthe top layer ploughing should be as deep as possible, with a low depth to width ratio to maximise soil inversion andseed burial. If, however, the seeds are concentrated in the bottom layer, the model can be used to decide howshallowly to plough in order to avoid disturbing the deeper seeds and what ploughing width to associate to this depthin order to minimise soil inversion and leave as many seeds as possible undisturbed. Ways of improving the modelare suggested, particularly the necessity to simulate the effect of a skim coulter. © 2000 Elsevier Science B.V. Allrights reserved.

Keywords: Mouldboard ploughing; Soil structure; Weed management; Seed bank; Seed dispersal

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* Corresponding author. Tel.: +33-3-80693033; fax: +33-3-80693222.E-mail address: [email protected] (N. Colbach).

1161-0301/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved.

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N. Colbach et al. / Europ. J. Agronomy 13 (2000) 111–124112

1. Introduction

One of the most important reasons for soiltillage is weed management (Moss and Clarke,1994). Among the various possible soil tillageoperations, mouldboard ploughing is widely usedin most European cropping systems. In weedmanagement, mouldboard ploughing is of specialinterest because of its important effect on thevertical distribution of the seeds in the soil. Thevertical seed bank distribution is of fundamentalimportance because seedling emergence either de-creases continuously with seed depth (Froud-Williams et al., 1983; Dyer, 1995) or increaseswith slight burial and then decreases at greaterdepth (Mohler and Galford, 1997). Simulta-neously, the lateral displacement of the earth dur-ing ploughing contributes to the dispersal of theweeds inside the tilled field.

It is, therefore, essential to improve our under-standing of the effect of mouldboard ploughingon seed bank movements in order to define effi-cient soil management rules for weed control,leading to a decrease in chemical herbicides. Thisis the reason why many weed demography modelsinclude sub-models illustrating the effect of soiltillage on seed bank dynamics (Aarts, 1986; Doyleet al., 1986; Jordan et al., 1995). Many of thesesub-models are either based directly on the workof Cousens and Moss (1990) or developed bysimilar methods and include a quantification ofthe vertical seed bank movement during plough-ing. Cousens and Moss divided the seed bank ofthe tilled horizon into four horizontal sub-layersand estimated the proportion of seeds movedbetween layers during mouldboard ploughing.This model was deduced from statistical relation-ships observed in one experimental situation.Parameters well known to have a great effect onsoil displacement during ploughing such asploughing depth or width (Henin et al., 1969;Kouwenhoven and Terpsta, 1972) or pre-tillagesoil structure (Coulomb et al., 1993) were nottaken into account. It is thus difficult to extrapo-late Cousens and Moss’ model to other soil tex-tures and structures or to variations in tillagedepth or width.

No mechanistic model has yet been developedspecifically for weed seed movements, but Roger-Estrade and coworkers (Roger-Estrade, 1995;Roger-Estrade and Manichon, 1998) proposed amodel for vertical and lateral movements of soilparticles, depending on their initial vertical andlateral position, on ploughing depth and width aswell as soil structure. Consequently, the objectivesof this paper were: (1) To evaluate the suitabilityof this model to predict weed seed movements inthe soil and, therefore, the distribution of seeds inthe seed bank, a multilocal field trial was set up toobserve seed movements under various conditionsand to compare these observations to the simula-tions obtained with Roger-Estrade’s model. Asthis model is not limited to the most relevantvariable for weed seed position, i.e. vertical seeddisplacement, but integrates both vertical and lat-eral movements, observations and subsequentevaluations must, of course, take into accountboth dimensions. (2) To calculate vertical seedtransfer matrices, like those established byCousens and Moss (1990), for different conditionsand plough modes and to determine the optimalploughing mode for a given seed bank distribu-tion. This second objective is only feasible if themodel is deemed acceptable for weed seed move-ments.

2. Material and methods

2.1. Modelling seed displacement during ploughing(Roger-Estrade, 1995; Roger-Estrade andManichon, 1998)

To model the seed displacement during plough-ing, the representation of the furrow movementduring ploughing shown on Fig. 1 was used. Theprinciple of the furrow rotation first appeared inthe literature in Bousfield (1880) and has sincethen been adopted by numerous authors (Ashby,1934; Sohne, 1959; Henin et al., 1969). Roger-Estrade improved this model and introduced itinto a larger model describing the changes in soilstructure under the influence of cropping systems(Roger-Estrade, 1995).

N. Colbach et al. / Europ. J. Agronomy 13 (2000) 111–124 113

In the plane perpendicular to the direction ofthe plough, the furrow of soil cut by the mould-board plough follows the movement described inFig. 1. This movement comprises two successiverotations of the furrow and ceases when the fur-row is settled on the previously rotated furrow(Fig. 1A). The inclination angle between the fur-row and the plough pan only depends on plough-ing width and depth, i.e. the sine of this angleequates to the ratio of tillage depth to width.Actually, the furrow breaks up during this move-ment and partially falls on the plough pan. Thisphenomenon is modelled by Roger-Estrade byseparating the furrow into slices which slidedownwards until they reach the plough pan (Fig.1B). The number of slices depends on the mechan-ical soil behaviour: it is low in the case of poorfragmentation when the ploughed soil is dry orcompacted; and it increases with the fragmenta-

tion of the soil, when ploughing occurs in goodmoisture conditions and/or when the ploughedsoil is uncompacted. Using this relationship it ispossible to calculate the final vertical and lateralco-ordinates of any point of the furrow as afunction of its co-ordinates before ploughing andof ploughing depth and width as well as soilstructure.

2.2. The field trials

To evaluate the above described model fieldtrials were set up in two situations: (a) The fieldchosen at the INRA experimental station in theDijon area in 1997 (5°2% E, 47°20% N) was on aneutric cambisol (FAO). The texture of theploughed horizon (0–30 cm) was: clay 39%, silt55% and sand 6%. The field had been cropped forseveral years with small grain cereals that were

Fig. 1. Soil movement during ploughing according to Roger-Estrade (1995) explained as a succession of a rotation of the wholefurrow (A), followed by a breakup into slides and their translation, with the number of slides decreasing with soil compaction (B).


Fig. 2. Profile view of the beads introduced with an auger into the ploughed layer and their relative position to the future passageof the coulter. The beads marked are located beneath the ploughed layer and are not moved by the plough.

always sown and harvested in dry conditions,inducing a low risk of compaction. (b) The secondfield, used in 1996, was located at the INRAexperimental station in Grignon (1°58% E, 48°51%N). The soil was an orthic luvisol (FAO) and thetexture was: clay 26%, silt 58% and sand 16%. Forthe last two decades the crop rotation had beenmaize/winter wheat. Therefore, one harvest in twotook place in autumn when conditions are fre-quently wet, thus inducing a high risk of soilcompaction. The aim of this choice was to obtaintwo contrasted types of soil behaviour duringploughing, with an uncompacted, fragmentarysoil structure in Dijon and a compacted structurein Grignon. In order to extend this range of soilstructures and mechanical soil behaviours, an ex-treme, severely compacted situation was createdon one part of the Dijon field (later on calledDijon II as opposed to Dijon I, i.e. the uncom-pacted part of the field) by rolling the whole areain wet conditions with a heavy tractor, just beforeploughing.

The initial soil structure was assessed just be-fore ploughing. Three-metre-wide and 50-cm-deepobservation pits were dug perpendicular to thetillage direction, and the soil structure of theploughed layer was described using the methodproposed by Manichon (Manichon, 1982, 1987).This method is based on the description of themorphology of the clods created by the action oftillage tools. The clod size, their distribution andinternal structural porosity are evaluated in situ.Mean bulk density of the ploughed layer was also

measured with a rubber balloon type density ap-paratus with a piston.

Seeds were simulated by cubic plastic beads (ofabout 1 mm3) that are more easily observed andrecovered than weed seeds while being similarlydispersed by ploughing (Rottele and Koch, 1981;Moss, 1988). Immediately before ploughing, thesebeads were mixed with soil and introduced withan auger (diameter 5 cm) within and just belowthe ploughed layer (Fig. 2). Every 5 cm down to adepth of 30 cm in Grignon and 40 cm in Dijon, adifferent bead colour was used, with a total of sixto eight colours depending on the location. Fur-thermore, beads of yet another colour were dis-persed on the soil surface to simplify therecognition of the limits between adjacent furrowsafter ploughing. Each vertical hole resulting fromthe auger was considered as a replication and six(Grignon) to eight (Dijon) replications were made(for each structure location), introducing thebeads every w+5 cm (w=plough width) in thedirection perpendicular to the future tillage direc-tion, thus resulting in different lateral positionsrelative to the future passage of the plough, withonly one replication per future furrow. The deep-est beads were not moved by tillage, and markedthe initial lateral position of the beads.

Soil tillage was performed with a three-bottommouldboard plough (Huart 370E with a univer-sal-type mouldboard) without a skim-coulter,with two adjoining passages at Grignon and fourper soil structure at Dijon. The ploughing widthwas 40 cm (16 in.) in Grignon and 35 cm (14 in.)


in Dijon. Soil moisture at ploughing was mea-sured by randomly choosing a dozen soil samplesfrom the freshly ploughed furrows and calculatingthe ratio of their dry weight to their fresh weight;mean soil moisture was 30% (S.D. 1.8%) at Dijonand 24% (S.D. 1.5%) at Grignon.

After ploughing, a 50-cm-deep pit was dugperpendicular to the tillage direction, immediatelyin front of the original position of the beads. Thepit covered the complete width of the tilled field.The form and location of the displaced furrowswere drawn following the procedure described byCoulomb et al. (1993). The actual ploughingdepth was measured for each furrow. The soil wasthen removed in the direction of the tillage tolocate the initial position of the beads, marked bythe unmoved beads located below ploughingdepth. The actual initial lateral position (relativeto the passage of the coulter) was measured foreach vertical hole. The removal of the soil wascontinued to discover the new position of thebeads. Lateral displacement and the final verticalposition were then measured as shown on Fig. 1and compared to the simulations obtained withthe model. The situation was slightly different inGrignon where all lateral co-ordinates were mea-sured relatively to a common origin and lateraldisplacements were then deduced.

2.3. Statistics

The model was evaluated, using the formulagiven by Mayer and Butler (1993) for the coeffi-cient of determination or modelling efficiency:

r2=1−%(zi− zi)2

%(zi− zi)2

where zi are observed values (with mean zi) and zi

simulated values. Another quality indicator whichis often used in statistical literature is the mean-squared error of prediction (MSEP); as the dataused to evaluate the model were independent ofthe data used to develop the model, MSEP wasestimated as simply the average squared deviationbetween the model prediction and observations(Wallach and Goffinet, 1987, 1989). To obtain an

error measure of the same unit as both observa-tions and simulations, the square root of MSEPwas used.

3. Results and discussion

3.1. E6aluation of ploughing model

3.1.1. Description of furrows after ploughing andchoice of model input 6ariables

Observations and measurements of the initialsoil structure verified that the produced experi-mental situations indeed ranked as wished, i.e.with the most compacted structure at Dijon II,the less compacted one in Dijon I and Grignonbeing intermediate. In Dijon II the soil structureappeared homogeneous, massive, without any ap-parent structural porosity; mean bulk density was1.49 Mg m−3 with an S.D. of 0.03. Because ofthis compacted soil structure the furrows werenearly unfragmented. Therefore, only two transla-tion slides were used in the simulations. In DijonI the soil structure was fragmentary, characterisedby the dominance of fine earth with some clods ofwhich the diameter did not exceed 5 cm; meanbulk density was significantly lower than in DijonII (1.29 Mg m−3, with an S.D. of 0.10). Furrowfragmentation was high enough to obtain asmooth soil surface and little void between adja-cent furrows; therefore, five translation slides wereused for the simulations. The Grignon profileshowed a spatially variable soil structure: frag-mentary zones alternated with compacted soil vol-umes. The degree of fragmentation of the furrowand soil surface roughness were intermediate be-tween Dijon I and II. Consequently, simulationswere performed with three translation slides.

At Grignon the tillage depth was a uniform 25cm and the furrows had been properly rotated sothat the inclination angle of the furrows (angle Ain Fig. 1) was about 40° as foreseen by the model.At Dijon the measurements of the actual plough-ing depth performed for every furrow showed thatthe ratios of ploughing width to depth variedbetween furrows. Consequently, furrow inclina-tion also varied considerably. At Dijon II thetillage depth ranged from 29 to 33 cm. Because of


this large ploughing depth (relative to the plough-ing width) the average inclination angle was closeto 90° (sin A close to 1). At Dijon I the ploughingdepth, ranging from 33 to 37 cm, exceeded insome furrows the ploughing width. In this treat-ment the furrow inclination angle was close to 90°in most of the furrows. However, some furrowsdid not complete their first rotation, either be-cause the depth was too great to accomplish thatmovement or because their rotation movementwas blocked by their too-deeply ploughed neigh-bour furrow. This situation probably resultedfrom the fact that the plough worked in a verycompacted clayey soil, so that the actual workingdepth of the plough was very difficult to control.

The input value for ploughing width was 40 cmfor the Grignon data and 35 cm at Dijon. What-ever the location, the input value for tillage depthin the model was the measured ploughing depthof each furrow when this value was lower than theploughing width. When this was not the case thedepth to width ratio exceeded 1 and it was impos-sible to calculate the sine; the inclination angle inthe model was then set at 90°.

By removing the soil in the direction of the soiltillage the furrows could be observed at variouslongitudinal positions. No supplementary fissuresor variations in the inclination angle or in thedegree of fragmentation of the furrows at the level

of auger penetration were observed. Therefore,the use of an auger to introduce the beads did notseem to influence furrow rotation and distortion.

3.1.2. Analysis of model performancesAt a first look, the final vertical co-ordinate

(the distance to the plough pan) and the lateraldisplacement were not excessively well simulatedby the model (Table 1): modelling efficiency (r2)was only slightly higher than 0.6, mean error(MSEP) was rather large, even compared to theobserved range of variations. No systematic over-or under-estimation (mean of residuals close tozero) was found. Fig. 3, comparing observed andsimulated values for the final vertical co-ordinateand the lateral displacement respectively, rein-forces this first impression, showing large dis-crepancies between simulated and observedvalues, even though the points were generallydistributed around the equation representingequality of simulated and observed values.

If however, the replications located in thosefurrows identified by the above described analysisof furrow characteristics (i.e. too deeply ploughedfurrows or furrows that had been rotated by lessthan 90°) were eliminated, the model performanceincreased dramatically (Table 1): in that casemodelling efficiency was high, mean error consid-erably decreased and again, there still was neither

Table 1Evaluation of Roger-Estrade’s model by analysing prediction accuracy of lateral displacement and final vertical coordinate ofdisplaced beads. Synthesis of three situations: Dijon I, Dijon II (1997) and Grignon (1996)a

MSEPNumber ofCase r2Mean ofEvaluated outputpoints variable residuals (cm) (cm)

All points 155 Lateral 12.0−1.1 0.69displacementFinal vertical 8.20.63–0.5coordinate

Lateral 0.85−1.4Elimination of furrows with ploughing depth 73 8.7\width and without completed 1st rotation displacement

Final vertical 4.4–1.1 0.85coordinate

a Residual= zi−zi, where zi are observed values (with mean zi) and zi simulated values; modelling efficiency r2= 1−(�(zi−zi)2/

�(zi−zi)2) (Mayer and Butler, 1993); MSEP=�(zi−zi)

2/n with n=number of observations (Wallach and Goffinet, 1987, 1989); ",mean significantly different from zero at a=5%.


Fig. 3. Comparison of final vertical seed coordinates (A) and of lateral seed movements (B) simulated by the mouldboard ploughmodel (Roger-Estrade, 1995) and observed on three field trials. Each point represents beads of a given colour and replication.

systematic over- nor under-estimation. If theresiduals were analysed separately for each loca-tion it appeared that the errors for lateral dis-placement were significantly higher at Grignon(mean of absolute residual values=7.9 cm) thanat Dijon (4.5 cm). However, this particularity wasprobably related to the different measurementsystem used at Grignon where, whatever the

beads, all lateral co-ordinates were establishedrelative to one common origin, with an error riskincreasing with the distance from this origin.

These results show that Roger-Estrade’s modelcorrectly simulates the final vertical seed co-ordi-nate as well as lateral seed displacement as afunction of soil structure, ploughing width anddepth and, of course, initial seed position, if


ploughing depth is lower than ploughing width.If, however, the former exceeds the latter and/or ifthe furrows are not properly rotated, the modelcannot be used. This restricts the possible use ofthe proposed model, but admittedly, under fieldconditions, ploughing is usually performed with aploughing depth lower than the ploughing width.

The model gives the position of the seeds imme-diately after ploughing. At least in compactedstructures the soil settles considerably later on,either because of superficial tillage for soil bedpreparation or because of climatic interferencesuch as alternation of dry and humid or cold andwarm conditions. The seed displacement modelfor ploughing must, therefore, be completed by afurther model describing the degradation andcompression of the furrows after tillage.

3.2. Using the model for simulation of the 6erticalweed seed distribution

3.2.1. Determination of 6ertical seed transfermatrixes

As shown by the model evaluation, Roger-Estrade’s model can be used to simulate seedmovements and final seed positions immediatelyafter tillage. Most existing weed demography

models are only dealing with vertical seed trans-fers and positions as they do not simulate hori-zontal movements (Colbach and Debaeke, 1998).Among the few authors who attempted to quan-tify the effects of soil tillage on vertical seedmovements, Cousens and Moss (1990) proposed acompartmental model. In this model the tilledhorizon is divided into four 5-cm-thick horizontallayers that are considered as compartments. Theseed content of one compartment j of the post-tillage seed bank can be predicted from the seedcontent of the four layers of the initial seed bankand a vertical seed transfer matrix. Each coeffi-cient of this matrix represents the proportion ofseeds of layer i moved to layer j during soil tillage.

Roger-Estrade’s model can be used to deter-mine such vertical seed transfer matrices. In orderto compare the result with the model of Cousensand Moss, similar tillage conditions, i.e. settledsoil (resulting from a high number of translationslides), a plough depth and width of 20 and 30.5cm, respectively, are used for the simulation.Table 2 gives the proportions of seeds movedbetween layers during soil tillage for the matricespresented by Cousens and Moss and calculatedwith Roger-Estrade’s model. It appears that thismodel predicts a homogeneous distribution of theseeds of each layer among the four tilled layerswhereas Cousens and Moss’ model foresees that alarge proportion of the initially superficial seeds isburied in the two deepest layers. This is notsurprising as these authors added a skim-coulterto their mouldboard plough, thus ensuring thatsuperficially located seeds, residues and soil clodsare buried close to the plough pan, whereas sim-ply ploughing tends to distribute seeds more orless homogeneously among the layers (Fig. 4).This appears to be an interesting strategy in thecase of a field with a superficial soil layer heavilyinfested by weed seeds where the aim is to limitimmediate seedling emergence. Therefore, the de-scription of the soil and seed movements due to askim-coulter should necessarily be added toRoger-Estrade’s model.

However, despite this deficiency, Roger-Estrade’s model has several advantages overCousens and Moss’ model: in contrast to thelatter, the first uses ploughing depth and width as

Table 2Proportion of seeds moved from layer i to layer j by amouldboard plough (depth 20 cm; width: 30.5 cm) in case ofa seedbank divided into four 5-cm-thick horizontal layers

Final Initial layer I

1 2Layer j 3 4

Aa

0.02 0.21 0.371 (top) 0.290.102 0.260.11 0.270.120.200.300.403

0.46 0.21 0.184 (bottom) 0.48

Bb

0.24 0.24 0.241 (top) 0.240.26 0.262 0.26 0.26

3 0.26 0.26 0.26 0.260.244 (bottom) 0.24 0.24 0.24

a According to Cousens and Moss (1990).b According to the plough model (Roger-Estrade, 1995) in

the case of a fragmented soil structure (ten translation slides).


Fig. 4. Seed distribution after ploughing in the case of a soil with a superficial weed seed infestation. Simulations were performedwith the vertical transfer matrixes proposed by Cousens and Moss (1990) or calculated with Roger-Estrade’s model (Roger-Estrade,1995).

well as soil structure as input variables and is notrestricted to a 20-cm-deep four-layer seed bank.Indeed, not only can different ploughing modessuch as deeper or wider ploughing be simulated,but, much more importantly, the seed bank canbe divided into more numerous, thinner layers.This is essential if the plough model is to beintroduced into models describing the demogra-phy of species such as blackgrass (Alopecurusmyosuroides Huds.) for that only seeds locatedclose to soil surface can successfully emerge andgive rise to seedlings and seed-producing adults(Barralis, 1968; Naylor, 1972) whereas seed germi-nation and mortality rates vary considerably withseed depth (Barralis, 1970; Horng and Leu, 1978;Ballare et al., 1988; Cussans et al., 1996).

The separation of the seed bank into horizontallayers is easy in the case of highly fragmented soilwhere the post-tillage soil surface is smooth. Butthis separation is considerably more complicatedif the soil structure is compacted and theploughed soil surface rough, i.e. when furrows arepoorly fragmented. In this case (as on theGrignon and Dijon II trials), the layers are

defined as shown on Fig. 5, i.e. depending on thedistance of the seeds to soil surface. The layers arethus almost horizontal in the case of highly frag-mented soil structure (Fig. 5A), they appear to bemore ‘zigzagged’ when the fragmentation is lim-ited (Fig. 5B). This procedure of subdividing theseed bank appeared more relevant as most physi-cal conditions that are important for weed seedevolution depend on the distance to the surface.For instance, for many weed species (Barralis,1970; Bouwmeester and Karssen, 1989; Bai et al.,1995; Benvenuti, 1995; Jensen, 1995) and evensome cropped species occurring as volunteers(Pekrun et al., 1997a,b; Pekrun and Lutman,1998), the amount and quality of light is essentialfor the onset of germination and these factorswere shown to decrease with depth (Benvenuti,1995).

Roger-Estrade’s model was then used to calcu-late vertical transfer matrices for 30-cm-deep seedbanks divided into 1-cm-thick layers. These ma-trixes were calculated for different soil structuresas well as ploughing depths and widths and thenapplied to various initial seed distributions.


3.2.2. SimulationsIn the case of an initial superficial seed infesta-

tion, if the aim is to bury as many seeds aspossible, then ploughing is, of course, advisedinstead of superficial tillage or direct drilling, butsoil structure influences the efficiency of this oper-ation via its effects on the final vertical seeddistribution: in the case of a fragmented structure(Fig. 6A) ploughing distributes the seeds homoge-neously among the ploughed layers, regardless ofploughing width. Hence, the proportion of seedsfound at a given depth only depends on tillagedepth; the deeper the ploughing, the less seeds arefound at a given depth (and, therefore, close tothe soil surface). The situation is not as simple inthe case of a compacted structure (Fig. 6B) whereploughing width also influences seed distributionand both tillage depth and width must be rea-soned together. Indeed, Fig. 6B shows that thedeepest ploughing does not necessarily result inthe lowest superficial seed content and that, infact, a high ratio of ploughing width to depth(with a high inclination of the furrow) is necessaryto bury superficial seeds. In contrast, in the caseof a low width to depth ratio (with a low inclina-tion of the furrow) the superficial seed concentra-tion after deep tillage can be as high as that aftera more shallow tillage with a high width to depthratio.

If most seeds are, however, located in thedeeper soil layers (Fig. 6C and D), then shallowploughing (or even superficial tillage) is advised tolimit superficial seed content, whatever the soilstructure. Again, seeds are distributed homoge-neously among the ploughed layers in the case ofthe fragmented structure whereas the seed profileis highly irregular for the compacted structurewith, moreover, an influence on the ploughingwidth. However, in contrast to the above de-scribed situation with an initially superficial seedconcentration, ploughing depth remains the mostimportant factor, even for compacted structures.Indeed, if the layers containing the weed seeds arenot disturbed it is unlikely that these seeds arecarried back to the soil surface, except that somemovement can take place as a result of soil faunaactivity for instance, albeit on a small scale. Ifthough shallow tillage is not a possible option,then at least ploughing with a low width to depthratio should be attempted to decrease the propor-tion of exhumed seeds.

In this discussion the aim of ploughing was tominimise seed content close to the soil surface tolimit weed seedling emergence immediately aftertillage (Yenish et al., 1992). This is, however, notalways the objective of tillage, even when itsultimate aim is weed control. If ploughing pre-cedes the seeding of a crop by several months (asin the case of clay soils to be sown with spring

Fig. 5. Subdivision of seed bank into layers before and after ploughing, depending on soil structure. Each layer comprises all thepoints located at equal distance from the soil surface which is defined as the nearest part of the contour of the furrow. Thus, eachlayer has the shape of the surface of the freshly ploughed field: horizontal in case of a highly fragmented soil or rough (‘zigzagged’)when fragmentation due to the plough is poor.


crops) in some cases it can be more advantageousto maximise superficial seed content in order tomake as many seeds as possible emerge beforecrop seeding and thus deplete the seed bank, i.e.the stale seedbed technique (Leblanc and Cloutier,

1996). Such a strategy would, of course, onlywork with relatively non-dormant seeds (such asPoa annua L., Orlando et al. (1995)) that respondto tillage by emerging immediately. This strategywould, on the other hand, be disastrous in the

Fig. 6. Seed distributions before and after ploughing based on simulations performed with the vertical transfer matrixes calculatedwith Roger-Estrade’s model (Roger-Estrade, 1995). (A) Case of a highly fragmented soil structure with a superficial weed seedinfestation. (B) Case of a highly compacted soil structure with a superficial weed seed infestation. (C) Case of a highly fragmentedsoil structure with a deeply located weed seed infestation. (D) Case of a highly compacted soil structure with a deeply located weedseed infestation.


Fig. 6. (Continued)

case of species such as Polygonum persicaria L.(Orlando et al., 1995) that emerge predominantlyin spring; the seed bank dormancy would havedecreased between tillage and seeding and theseeds concentrated in the top layers would just beready for emergence at crop seeding.

4. Conclusion

The evaluation of Roger-Estrade’s modelshowed that it is not only appropriate for soilclod displacement, but is also adequate to predictvertical and lateral weed seed bank movements


and to quantify soil tillage effects for a variety ofsoil structures and ploughing modes. However,this model does not foresee the use of a skim-coulter, a tool that would considerably improvethe burial of initially superficial weed seeds. Fur-ther studies are, therefore, currently being under-taken by the authors to model the effects of thisadditional implement to the mouldboard plough.Another necessary addition to this ploughingmodel describing seed positions immediately aftertillage concerns the long-term seed movementsunder the influence of superficial soil tillage andclimate. This especially concerns compacted soilstructures where important soil and, therefore,weed seed movements occur when the formerlycompacted furrows break up and the soil settleson the plough pan.

Despite these considerations the model can al-ready be used to optimise soil tillage for weedmanagement by indicating the optimal ploughingdepth and width, depending on the soil structureand the initial vertical seed distribution in the soil,as shown by the various simulations. Further-more, due to the quantification of the soil tillageeffects on vertical seed positions and to the modelability to distinguish layers of varying numbersand thicknesses, Roger-Estrade’s model can beused to manage by soil tillage weed species withcontrasting germination and emergence require-ments. To optimise this weed management the soiltillage model should be combined with furthermodels describing biological processes such asseed mortality, dormancy and seedling emergence.These processes not only depend on vertical seedposition, but also on soil properties such as tem-perature, humidity, light penetration, oxygen con-tent, etc., which are also influenced by soil tillage(Mohler and Galford, 1997).

The range of possible soil tillage solutionscould, of course, also be increased by proposingother techniques such chisel ploughing or varioussuperficial interventions. To evaluate the relativeperformances and advantages of these differenttillage options, models similar to the ploughingmodel would then be necessary for these othertillage implements.

Roger-Estrade’s model also constitutes a firststep on the way to weed demography models

integrating intra-field variability as, besides verti-cal seed movements, lateral displacements are de-scribed. Therefore, it is now already possible tobuild models describing lateral (perpendicular tothe direction of the soil tillage) intra-field variabil-ity and thus describe lateral weed dispersal andvariations in weed densities. To accomplish com-plete horizontal variability, both in the directionand perpendicular to the direction of tillage andother agricultural interventions, it is, however,necessary to tackle longitudinal seed movementsduring tillage.

Acknowledgements

The authors thank Jacques Troizier, Head ofthe Experimental Centre at Grignon, and histeam, and Luc Biju-Duval and his colleagues ofthe Experimental Station of INRA-Dijon, forconducting the field trials.

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