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Journal of Environmental Science and Health, Part B:Pesticides, Food Contaminants, and Agricultural WastesPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/lesb20

The effect of glyphosate on the growth andcompetitive effect of perennial grass species in semi-natural grasslandsChristian Damgaarda, Beate Strandberga, Solvejg K. Mathiassenb & Per Kudskb

a Department of Bioscience, Aarhus University, Silkeborg, Denmarkb Department of Agroecology, Aarhus University, Slagelse, DenmarkPublished online: 13 Oct 2014.

To cite this article: Christian Damgaard, Beate Strandberg, Solvejg K. Mathiassen & Per Kudsk (2014) The effect ofglyphosate on the growth and competitive effect of perennial grass species in semi-natural grasslands, Journal ofEnvironmental Science and Health, Part B: Pesticides, Food Contaminants, and Agricultural Wastes, 49:12, 897-908, DOI:10.1080/03601234.2014.951571

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The effect of glyphosate on the growth and competitive effectof perennial grass species in semi-natural grasslands

CHRISTIAN DAMGAARD1, BEATE STRANDBERG1, SOLVEJG K. MATHIASSEN2 and PER KUDSK2

1Department of Bioscience, Aarhus University, Silkeborg, Denmark2Department of Agroecology, Aarhus University, Slagelse, Denmark

Biodiversity within European semi-natural biotopes in agro-ecosystem is declining, and herbicide drift from neighbouring fields isconsidered as an important factor for the decline. The aim of the present study was to investigate whether the growth andcompetitive interactions in a model system of two perennial grass species, Festuca ovina and Agrostis capillaris, are affected by sub-lethal doses of glyphosate in field margins. In a glasshouse experiment with ample nitrogen, the interspecific competitive interactionswere found to be significantly affected by glyphosate; the competitive effect of F. ovina on A. capillaris increased and the competitiveeffect of A. capillaris on F. ovina decreased with increasing doses of glyphosate. Furthermore, the importance of interspecificcompetition increased with the glyphosate dose. The results of the study of competitive interactions are in agreement with theobserved plant community dynamics at the field site where F. ovina was found to be more dominant in plots treated with a relativelyhigh dose of glyphosate. Importantly, the effects of glyphosate on the plant community dynamics critically depended on the effect ofglyphosate on the plant competitive interactions. The study concludes that the current practice in the environmental risk assessmentof non-target effects of herbicides, where single species are tested in the greenhouse, may be inadequate for assessing the effect ofherbicides in semi-natural plant communities. The presented methods can be used for assessing the importance of competitiveinteractions for the sensitivity of non-target plants to herbicides in risk assessment.

Keywords: Agro-ecosystem, herbicide, environmental risk assessment, interspecific competition, state-space model.

Introduction

Biodiversity within European agricultural areas is declin-ing,[1–6] see also Andreasen and Stryhn.[7] A number of fac-tors, often summarized as the intensification of agriculturalpractices and loss of habitats, are responsible for thedecline. Specifically, the repeated applications of pesticidesare assumed to play an important role. In the agro-ecosys-tem, small natural and semi-natural biotopes in the vicinityof agricultural fields play an important role for maintainingbiodiversity,[8–10] providing dispersal corridors,[11] and arean important cause of various ecosystem services such aspollination.[10,12] Therefore, in order to manage biodiversityin agro-ecosystems it will be useful to be able to predict theeffect of a non-sprayed border zone in field margins on bio-diversity in the neighbouring natural and semi-naturalhabitats.Within a natural plant community, plants will compete

with conspecific plants (intraspecific competition) as well

as with plants belonging to other species (interspecificcompetition) for limited resources,[13,14] and it has beendemonstrated that competition plays an important part inthe composition of plant communities.[15,16] Plant speciesrespond very differently to exposure to herbicides, rangingfrom no effect to complete growth inhibition, permanentlyor temporarily. Thus, it can be anticipated that herbicidedrift will affect interspecific competition by inhibitinggrowth of some plant species more than others, and severalstudies have indicated that herbicide spray drift may be amajor factor that affects both flora and fauna of fieldboundaries and hedgerows.[17,18–20] Jensen[21,22] showedthat herbicide vapours also have the potential to affectplants. Besides a direct effect on growth and fecundity,more subtle effects may be observed from herbicide drift.Blackburn and Boutin[23] found effects on seed germina-tion and seedling growth, with seven out of 11 speciesexposed to glyphosate near seed maturity.Being the most widely used herbicide worldwide, the

potential effect of glyphosate on natural plant communi-ties has received much attention. Marrs et al.[24,25] foundthat spray drift from glyphosate resulted in sub-lethal butsignificant effects such as flower suppression and plantdamage, and argued that spray drift may have long-termimpacts on plant communities. The hypothesis that

Address correspondence to Christian Damgaard, Department ofBioscience, Aarhus University, Vejlsøvej 25, DK-8600 Silke-borg, Denmark; E-mail: cfd@dmu.dkReceived May 7, 2014.

Journal of Environmental Science and Health, Part B (2014) 49, 897–908Copyright © Taylor & Francis Group, LLCISSN: 0360-1234 (Print); 1532-4109 (Online)DOI: 10.1080/03601234.2014.951571

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herbicide drift may affect interspecific plant competitionwas corroborated in a greenhouse competition experiment,where Capsella bursa-pastoris (shepherd’s-purse) andGeranium dissectum (cut-leaved cranesbill) were foundmore likely to coexist at low doses of the herbicide meco-prop-P.[26] Watrud et al.[27] studied the effect of glyphosatedrift on a constructed mixed-species mesocosmos commu-nity comprising transgenic oilseed rape resistant to glypho-sate, non-transgenic oilseed rape and three annual weedspecies. They found that the weed species Digitaria sangui-nalis became dominant in the untreated mesocosms aftertwo years, whereas transgenic oilseed rape remained domi-nant species in the glyphosate-exposed mesocosms, sup-porting the hypothesis that herbicide drift can havesignificant impacts on plant community structure.In a long-term field experiment at the Kalø experimen-

tal site (Appendix S1), it was observed that Festuca ovina(sheep’s fescue) was relatively more abundant than Agro-stis capillaris (common bent grass) in glyphosate-treatedplots.[19] This observation lead us to investigate the possi-ble effect of glyphosate on the competitive interactions ofthe two species in a glasshouse experiment with amplenitrogen, where it was observed that the competitiveeffect of Festuca ovina on A. capillaris increased with theglyphosate dose.[19,28] In addition, using the data fromthe Kalø experimental site, we demonstrated an interac-tion effect between nitrogen and glyphosate on the impor-tance of demographic parameters and overall ecologicalsuccess of the two plant species.[29,30] Following up onthese previous findings, the aim of this study was tomodel the effect of glyphosate specifically on the competi-tive interactions between F. ovina and A. capillaris underfield conditions.More specifically, our research objectives were to (i)

model the growth and competitive effect of F. ovina andA. capillaris in a semi-natural grassland at variable dosesof glyphosate, (ii) test whether the growth and competitiveeffect of the two plant species were affected by glyphosate,(iii) calculate the importance of competition relative to theeffect of glyphosate as a function of the glyphosate dose,and (iv) discuss whether it is necessary to apply speciesinteraction models in the environmental risk assessment ofpesticides.

Materials and methods

The data for this analysis of the effect of glyphosate on thecompetitive interactions of F. ovina and A. capillaris weresubsets of the plots at the Kalø experimental site (seeAppendix S1 in Supporting Information), i.e. the 40 plotsthat did not receive nitrogen. The reasons for only analy-sing a subset of the plots were twofold: (i) the aim of theresearch was to understand the effect of glyphosate on thecompetitive effect of F. ovina and A. capillaris, and if thepossible interacting effect of nitrogen should have been

included in the model, then the empirical competitionmodel would be too complicated (including too many freeparameters) to fit the data;[29] and (ii) in the nitrogentreated plots, the abundance of couch grass (Elytrigiarepens) increased significantly over the study period tobecome a dominant species by the end of the period.[31]

Since this increasing abundance of E. repens interfereswith the growth and competitive effect of F. ovina and A.capillaris in a non-trivial way, it was decided to omit thenitrogen-treated plots from the present analysis. Conse-quently, four glyphosate treatments (0, 14.4, 72 and 360 ga.e. ha–1) were analysed in this study. The applied doseswere equal to 0, 1, 5 and 25% respectively of the recom-mended maximum dose of 1440 g a.e. ha–1 for pre- andpost-harvest treatments, which are the most common usesof glyphosate in Denmark.[32] The plots were treated withglyphosate for the first time on August 24, 2001, and sincethen they have been treated with glyphosate once everyyear in spring (mid-ultimo May).See Appendix S1 for more details of the field site and

treatments.F. ovina and A. capillaris are perennial grasses. They

both have a caespitose growth form, but the turfsformed by F. ovina generally are denser than thoseformed by A. capillaris. In comparison to A. capillaris,which is deciduous, F. ovina is productive through thewinter when temperatures are above zero. Furthermore,F. ovina has narrow, curled and waxy leaves whereas A.capillaris has broader flat leaves without any wax cover.In a previous experiment (see Appendix S2), it wasobserved that F. ovina was more tolerant to glyphosatethan A. capillaris.

Sampling

The competitive interactions between F. ovina and A.capillaris were studied using permanently positioned 0.5-m£ 0.5-m quadrats that were placed within each of the plotsin June 2007. We were interested in studying the change incover and vertical density of the two grasses and the com-petitive interactions, and therefore the quadrate was notplaced randomly but in such a way that both F. ovina andA. capillaris were noticeably abundant in the quadrate andwith variable cover of the two species.Plant cover and vertical density (defined as the number

of times the pins touch a specific species) of all vascularplant species within the quadrats were measured non-destructively by the pin-point method,[33,34] using a pin-point frame with the same dimension as the quadrate. Theframe had 25 pin-positions regularly placed at a distanceof 10 cm. At each position, a sharply pointed pin with adiameter of 0.5 mm was passed vertically through the veg-etation. The sampling was performed twice a year for thethree-year period 2007–2009: approximately two weeksafter application of herbicide in the spring (t1), and at theend of the growing season (t2).

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In the subsequent analysis of the competitive growth,survival and establishment of F. ovina and A. capillaris,the data were grouped into three classes: F. ovina, A. capil-laris, and an aggregated class of all other vascular plantspecies, denoted here as “other species.”

Competition model

The possibly important role of interspecific competitiveinteractions has been investigated in a multitude of studiesusing different methods. Space limitation precludes areview of the existing methods for measuring competition,but in order to test hypotheses on the role of plant compe-tition in determining plant community structures, it is criti-cal to measure the effect of neighbouring plants on plantperformance at variable local abundances of the compet-ing species in their natural habitat.[35–37] Such studies ofplant competition have been performed under the headingof neighbourhood analyses where the effect of the distancebetween individual neighbouring plants on plant perfor-mance was quantified.[38,39] However, light-open naturalherbal and grassland communities are dominated by spe-cies with individuals of variable sizes that form a densecover, thus making it difficult to distinguish individualplants. Here a novel method for measuring competitiondirectly in natural and semi-natural light-open habitatswas applied. The importance of this method is that it doesnot depend on the recognition of individual plants;instead, the effect of plant–plant interactions is measuredfrom repeated pinpoint measurements in permanentlypositioned plots.[33,34,40]

The idea underlying the method of measuring competi-tion is to express the vertical density at the end of thegrowing season as a function of the cover at the beginningof the growing season and the cover at the beginning ofthe growing season as a function of the vertical density atthe end of the previous growing season.[37,40] Analogous toa standard competition experiment, where biomass perarea is correlated to density,[41,42] the vertical density inthe presented method is correlated to cover. This patternof correlation between cover and vertical density of differ-ent species is the “signal” that is picked up in the presentedcompetition model. That is, the vertical density of a speciesat the end of the growing season will reflect the growth ofthe species within the pinpoint frame, which will dependon the cover of the species in the beginning of the season,availability of resources, and the cover of other competingspecies in the beginning of the season. The resources thatare obtained by competitive growth during the growingseason are assumed to be allocated into occupying spacethe following growing season, and a plant species thatgrows to a relatively high vertical density at the end of thegrowing season is expected to have a relatively high plantcover the following year. However, the occupation ofspace is hindered by the presence of other plant species,assuming that the process of occupying space the following

growing season is a competitive process. In addition, justas it is important to experimentally vary both density andproportions in a standard competition experiment to pre-dict the ecological effect of competitive interactions,[36] itis important in the presented method to consciously sam-ple from the variation in cover of the investigated specieswhen positioning the plots.The pinpoint data on plant cover and vertical density

were analysed in a state-space model,[43] which allowsdetailed modelling of ecological processes during andbetween growing seasons by the use of latent variables, i.e.variables that are not observed but inferred from measuredvariables. As the estimated latent variables are less influ-enced by sampling variance, the modelling of ecologicalprocesses through time will be less biased by samplingerror compared with a standard regression model. Fur-thermore, the separation of process and sampling varianceenables ecological predictions without confounding thetwo sources of variation.[43]

The competitive interactions in the plant community atdifferent treatments were analysed by describing howcover and vertical density of F. ovina, A. capillaris and theaggregated class of other species found at the plots co-varyduring the growing season. The modelled relationshipbetween plant cover and vertical density is indicated inFigure 1. The competitive growth among plant specieswas modelled by describing how plant cover at t1 influen-ces the vertical density of the species at t2, and the survivaland establishment of different species the following yearwas modelled by describing how plant vertical density atthe end of the growing season (t2) of different species influ-ences the cover of the species the following year at t1. Theunderlying assumption of the method used here was thatthe species-specific measure of vertical density at the endof the growing season might be used as a measure ofgrowth or the ecological success of the species during thegrowing season. The vertical density was expected todepend on abiotic and biotic environment and the cover ofother species that compete for resources such as light,water and nutrients. Furthermore, it was assumed that,everything else being equal, a plant species that grows to arelatively high vertical density had a relatively high coverthe following year, i.e. plants allocated resources intooccupying space the following year.[37, 40]

The ecological processes are investigated in two processequations (P1 and P2), which are separated in time(Fig. 1). Both process equations consist of four terms. Thefirst term models the intraspecific relationship betweencover and vertical density, i.e. the relationship betweenspecies cover in the beginning of the growing season andthe vertical density of the same species at the end of thegrowing season. The second and third terms model thenegative effect of other species, and the last term modelsthe process variation.More specifically, it is assumed that the vertical density

of species i at the end of the growing season (t2) is an

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increasing function of the plant cover of species i at thebeginning of the season (t1), a function of the plant coverof species j and k at the beginning of the season and theglyphosate dose, and the competitive growth of plant spe-cies i is modelled as

P1: Yi;t2;y;r D ai zrð ÞXi;t1;y;rbj �exp ¡ cj zrð ÞXj;t1;y;r

dj� �

�exp ¡ ck zrð ÞXk;t1;y;rdk

� �C eP1;i;y;r;(1)

where the state of plant cover of species i at time t in year yand pin-point frame r is denoted by Xi,t,y,r, the state of thevertical density of species i at time t in year y and pin-pointframe r is denoted by Yi,t,y,r, zr is the glyphosate dose in thepin-point frame r, and eP1;i;y;r »N.0; s2

P1;i/ is the residualprocess variation during the growing season of species iacross different years and pin-point frames. Glyphosate isassumed to affect the vertical density of species i at the endof the season in two different ways: (i) either by affectinggrowth directly by altering the relationship between thecover and the vertical density of species i, i.e. the functionai.zr/; or (ii) by affecting the competitive effect of species jand k, i.e. cj.zr/ and ck.zr/.

[44] Two simplifying assump-tions were made: (i) The competitive effect of a species wasassumed to be independent of the affected species, e.g. F.ovina had the same competitive effect on both A. capillarisand the aggregated class of other species, and (ii) all func-tions of the glyphosate dose, i.e. ai.zr/; cj.zr/; ck.zr/; wereassumed to be linear, u.z/D uconstant C uslopez: That is, dif-ferent ecological hypotheses concerning the effect of glyph-osate on growth and competitive effects may be tested byexamining the slope of linear function.

In order to assure variance homogeneity, both sides ofEq. (1) were square root transformed when the model wasfitted to the data.It is assumed that perennial species with a relatively

large vertical density have a relatively larger plant coverthe following year, and the plant cover of species i in yearyC1 is therefore an increasing function of the vertical den-sity of species i in the year t, a function of the vertical den-sity of species j and k in the year t and a function of theglyphosate dose, and the survival and establishment ofspecies i the following year was modelled as

P2: logit.Xi;t1;yC 1;r/D logit.ai.zr/Yi;t2;y;rbi

�exp.¡ cj.zr/Yj;t2;y;rdj/�exp.¡ ck.zr/Yk;t2;y;rdk //C eP2;i;y;r;

(2)

where eP2;i;y;r »N.0; s2P2;i/ is the residual process variation

from one growing season to the next of species i across dif-ferent years and pinpoint frames. Correspondingly, as for(P1), different hypotheses on the effects of environmentalgradient on survival and establishment and the plant–plantinteractions may be tested. Note that the parameters inboth process equations, (P1) and (P2), have the same nota-tion; this does not mean that the parameters of the twoprocesses are identical, but that the parameters with thesame notation have an analogous interpretation.The mean of the observed cover and vertical densities

are modelled by latent variables by the following measure-ment equations. Thus, the observed cover is modelledusing the binomial distribution,

M1: ui;t;y;reBinomial .n;Xi;t;y;r/; (3)

Fig. 1. Graphical model of the studied processes in the field experiment. The latent variables of the states of the investigated ecologi-cal success components cover (Xi,t) and vertical density (Yi,t) through the growing season (square boxes), and the associated observa-tions of cover (ui,t) and vertical density (vi,t) of species i at time t (rounded boxes). Cover and vertical density are measured twiceduring the growing season: approximately two weeks after herbicide application in the spring (t1), and at the end of the growing sea-son (t2). The two processes and two measurement equations (see text) have been denoted by P andM respectively.

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where Xi;t;y;r is the latent variable for mean cover of speciesi at time t in year y at frame r, and u is the observed num-ber of grid points where the species is hit by a pin in thesame pin-point frame with n grid points.The vertical densities are modelled using a generalised

Poisson distribution,

M2 : vi;t;y;regP.Yi;t;y;r; rM2;i/; (4)

where Yi;t;y;r is the latent variable for the mean vertical den-sity of species i at time t in year y at frame r, v is theobserved number of times the species is hit in the samepin-point frame, and gP is the generalised Poisson distri-bution where rM2;i is the degree of under dispersion.variance=mean/¡ 1 compared with the Poisson distribu-tion when measuring the number of times a pin hits a spe-cific species in the pin-point frame.

Estimation and statistical inference

The joint Bayesian posterior distribution of parametersand latent variables for the cover (Xi,t) and the verticaldensity (Yi,t) were calculated using the MCMC (Metrop-olis–Hastings) run of 120,000 iterations with a burn-inperiod of 20,000 iterations and a multivariate normalcandidate distribution.[45] The prior distributions ofall parameters and latent variables were assumed tobe uniformly distributed in their specified domains.0:0001< 0:999; 0:5< b; d< 2; 0:01< sP1;i; sP2;i; 0:5< rM2;i < 5/:In the initial explorations of model, the relative informa-tive priors of b, d, and rM2;i were found to be necessary inorder to ensure a successful fitting procedure. Plots ofdeviance and sampling chains of all parameters and latentvariables were inspected to check the fitting and mixingproperties of the used sampling procedure.The statistical inferences of different treatments were

assessed using the calculated 95th percentile of marginalposterior distribution of parameters of interest (credibilityintervals) or calculating P-values of one-sided tests byinserting into the empirical cumulative distribution func-tion of the marginal posterior distributions.More compound hypotheses were tested using the joint

posterior distribution of all parameters; the importance ofcompetition at different glyphosate doses was calculatedusing the deviance of full model with respect to changes inspecies abundance and the glyphosate dose.[28]

The importance of competition measures the relativereduction of plant population by competition comparedwith the reduction due to other forces such as unfavoura-ble abiotic conditions or the application of herbicide.[46] Ifthe importance of competition is relatively high, then thismeans that the population dynamics of the species is con-trolled to a relatively high degree by competitive interac-tions compared with the effect of unfavourable abioticconditions.[28] The importance of interspecific competition

relative to the effect of glyphosate within growing seasons(P1) is calculated as

j@XjYi.Xj; z/j

j@XjYi.Xj; z/jC j@zYi.Xj; z/j ; (5)

and the importance of interspecific competition relative tothe effect of glyphosate between growing seasons (P2) iscalculated as

j@YjXi.Yj; z/jj@YjXi.Yj; z/jC j@zXi.Yj; z/j : (6)

Equations (5) and (6) linearize absolute change in verticaldensity and cover, respectively, for both positive and nega-tive changes in both glyphosate dose and cover or verticaldensity respectively. This means that the equations quantifywhether a change in the glyphosate dose or a change incover or vertical density has the largest effect on the mea-sured change in the ecological success of two species.[28]

All calculations were done usingMathematica.[47]

Results

The cover and vertical density data measured in the perma-nently positioned plots (Fig. 2) were analysed using theempirical state-space competition model. The fit of themodel was judged to be acceptable (Fig. 3), and the mixingproperty of the MCMC-chain was, based on visual inspec-tions, judged to be satisfactory, although there was consider-able co-variation between the marginal distributions ofsome of the parameters.The Bayesian marginal posterior distributions of all the

parameters are summarized in Table 1. The effect ofglyphosate on the competitive effect of species is summa-rized by the parameter cslope, and glyphosate was found tohave a significant positive effect on the competitive effectof F. ovina (Table 1) within growing seasons (one-sidedtest of cslope, P1 D 0; P < 0.0001) and a significant negativeeffect on the competitive effect of A. capillaris withingrowing seasons (one-sided test of cslope, P1 D 0; P <

0.0001). Thus, the previous observation in the greenhouseexperiment that the competitive interactions of F. ovinaand A. capillaris were affected by glyphosate in such a waythat F. ovina became a stronger competitor with increasingglyphosate doses[19] was confirmed under field conditions,and is consequently a likely explanation for the relativedominance of F. ovina in the glyphosate-treated plots.There was no significant effect of the applied glyphosatedoses on the competitive effect of the aggregated class ofother species (Table 1).The effect of glyphosate on plant growth without the

effect of intra- and interspecific competition was measuredby the parameter aslope. Glyphosate was found to have a

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significant positive effect on the growth of A. capillaris andthe aggregated class of other species in the absence of inter-specific competition (Table 1, aslope deviated significantlyfrom zero). The growth of F. ovina was not significantlyaffected by the applied glyphosate doses.The possible curvature of the effect of cover and vertical

density on growth and competitive effect was modelled byb and d respectively. There were significant non-linear

effects of both cover and vertical density on growth andcompetitive effect (Table 1; parameters b and d deviatedsignificantly from 1). In the cases where the effect of curva-ture was significant, the parameter was less than one, indi-cating a saturating effect of either cover or verticaldensity. This non-linearity makes difficult to interpret theresults of marginal posterior distribution except in thecases of the above-mentioned slope parameters.

Fig. 2.Mean cover and mean vertical density per pin of Festuca ovina (solid line), Agrostis capillaris (stripped line) and the aggregatedclass of other vascular species (dotted line). The pin-point measurements were performed twice a year: in the spring approximatelytwo weeks after herbicide application (t1), and at the end of the growing season (t2) for three years during the period 2007–2009. Thetreatments included four glyphosate treatments (0, 1, 5 and 25% of label rate of 1,440 g glyphosate ha–1). The standard deviations areindicated by bars.

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Consequently, to further characterize the effect of glypho-sate on the interspecific competitive interactions and eco-logical success of studied species, the importance ofinterspecific competition relative to the effect of glyphosatewas calculated using the deviance of full model withrespect to changes in the abundance of competing speciesand the glyphosate dose.[28] The most noticeable effect ofglyphosate on the importance of interspecific competitionwas that the importance of competitive effect of F. ovinaon A. capillaris within growing seasons increased with thelevel of glyphosate (Fig. 4), and that the importance of thecompetitive effect of A. capillaris on F. ovina betweengrowing seasons increased with the glyphosate dose(Fig. 4).

Discussion

The interspecific competitive interactions between F. ovinaand A. capillaris in semi-natural grassland were signifi-cantly affected by the applied dose rates of glyphosate.Within the growing season, the competitive effect,sensu,[44] of F. ovina on A. capillaris increased and thecompetitive effect of A. capillaris on F. ovina decreasedwith the increasing glyphosate dose (Table 1). This findingis, as far as we know, the first direct demonstration thatherbicides may alter the competitive effect of plant speciesperformed in a semi-natural plant community. Further-more, the presented modelling approach allows a quantita-tive estimation and prediction of the effect of glyphosate

Fig. 3. Residual plots as a function of the expected cover and vertical density per pin respectively. Note that during the fitting proce-dure both structural equations were transformed by the square root and logit transformation respectively to ensure variancehomogeneity.

Table 1. The calculated percentiles of the marginal posterior distribution of parameters. The parameters are explained in the textconnected to Eqs. (1)–(4) and reported by the calculated percentiles (median and 95% credibility interval) of their marginal posterior.

Festuca ovina Agrostis capillaris Other speciesParameterPercentiles 2.5 50 97.5 2.5 50 97.5 2.5 50 97.5

Measurement Eq. (2)rM2 3.365 4.397 4.975 0.837 1.383 3.201 0.501 0.539 2.289Process Eq. (1) – during the growing seasonaconstant 50.395 62.828 77.224 76.442 105.461 127.876 57.072 92.399 150.441aslope ¡1.289 ¡0.372 1.237 57.557 82.392 96.147 4.883 21.632 41.503b 0.552 0.790 1.309 1.433 1.537 1.737 0.878 1.060 1.240cconstant 0.612 0.835 0.965 0.161 1.940 2.641 ¡0.688 0.128 0.638cslope 0.114 0.139 0.159 ¡0.509 –0.342 ¡0.082 ¡0.081 0.132 0.542d 0.504 0.568 0.732 0.718 1.369 1.922 0.523 1.082 1.987sP 2.015 2.413 2.855 0.014 0.032 0.105 0.089 0.837 1.230Process Eq. (2) – among growing seasonsaconstant 0.088 0.108 0.138 0.047 0.483 1.072 0.014 0.359 0.786aslope ¡0.002 0.000 0.001 ¡0.201 ¡0.084 0.082 0.055 0.117 0.199b 0.500 0.509 0.548 0.505 0.914 1.728 0.506 0.868 1.834cconstant 0.413 2.279 4.335 ¡0.017 0.015 0.057 ¡0.034 0.013 0.095cslope ¡0.122 0.001 0.202 ¡0.002 0.002 0.007 ¡0.013 ¡0.003 0.009d 0.503 1.509 1.976 0.503 0.575 0.831 0.503 0.589 0.874sP 0.616 0.770 0.973 1.233 2.553 3.049 0.951 2.566 3.092

Bold numbers indicate that a parameter of interest deviated significantly from zero (two-sided test).

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on plant community dynamics in field margins with a simi-lar plant community.The finding is in agreement with previous findings in a

greenhouse competition experiment, where glyphosate wasfound to affect the interspecific competition.[19,28] Further-more, it must be concluded that herbicide modification ofinterspecific competitive relationships is an important eco-logical process that was partly responsible for the observedplant community changes observed at the Kalø experimen-tal plot, where the ratio between the cover of A. capillarisand F. ovina was 0.28, 0.45, 0.45 and 0.13 in plots receivingno nitrogen and glyphosate concentrations of 0, 1, 5 and25% of the recommended glyphosate dose respectively.[31]

Furthermore, the importance of interspecific competitionrelative to the effect of glyphosate on plant growth wasfound to increase with the glyphosate dose (Fig. 4).The positive effect of low dosages of glyphosate on the

growth of A. capillaris may be explained by a higher levelof disturbance and turnover rate in the glyphosate-treatedplots, and consequently a reduced effect of intraspecificcompetition. An alternative explanation could be that low

doses of glyphosate stimulated the growth of A. capillaris,i.e. caused hormesis. Growth stimulation by glyphosatehas been documented in several studies[48] and has beenshown to be sustained over time.[49]

In the present study, we have only considered the effectof glyphosate on the growth and competitive effect ofplant species, and there may be additional effects of herbi-cide on fecundity and germination that may affect plantcommunity dynamics.[23] Evaporation of water in the timespan from droplet formation to deposition on plants infield margins will lead to significantly higher herbicide con-centrations in the droplets drifting into natural systemsthan in this experiment, and several studies have shownthat an increased glyphosate concentration will enhanceactivity.[50,51] Thus, effects of the doses applied in the pres-ent study may be lower than exposure to similar doses inthe form of drift. There is, however, no reason to assumethat a lower glyphosate concentration will change the dif-ferential response of two morphologically very similar spe-cies, F. ovina and A. capillaris.The cover and vertical density of the relatively narrow

leaved F. ovina were likely to be overestimated in compari-son with the relatively broad leaved A. capillaris,[52] butsince this was done in a systematic way, we do not expectthat this overestimation will affect our conclusions oncompetitive interactions. In addition, it could be arguedthat the measured competitive interactions may be partlydue to the effects of variable abiotic or biotic factors in dif-ferent plots or between years, and while such confoundingeffects cannot generally be ruled out, two conditions pointto the fact that it was indeed the effect of competition thatwas measured. These are that the (i) variation in the coverof two species was not systematically biased along theglyphosate dose gradient, and (ii) possible impact of differ-ential abiotic and biotic conditions between plots and thetwo years is expected to be measured by the process errorterm rather than by the competition parameters.When observing changes in the abundance of different

species in natural plant communities along an environ-mental gradient, it is common to refer to competition asthe cause for observed changes. However, the complicatedtask of actually measuring the competitive interactions innatural plant communities has only been attempted in sur-prisingly few studies.[39,40,53,54] The experimental design inthe present study has been specifically developed for mea-suring and quantifying competitive interactions in naturalplant communities that are dominated by perennial plantswhere it is difficult to distinguish individual plants.[37] Theanalysis of data on cover and vertical density of F. ovinaand A. capillaris in the described competition model allowsan understanding of competitive growth and survival pro-cesses that occur during and between growing seasons andestimates the effect of glyphosate on competitive growth,survival and establishment. Furthermore, it enables thetesting of precisely formulated hypotheses on the effects ofglyphosate on plant community dynamics.

Fig. 4. Importance of interspecific competition between Festucaovina and Agrostis capillaris relative to the effect of glyphosateon plant growth; see Eqs. (5) and (6) as a function of the glypho-sate treatment. The importance of interspecific competition wasevaluated when the cover was 0.5 and the vertical density was 1per pin. The absolute value of the importance of competitiondepends on the units used in Eqs. (5) and (6), which are unitchange in cover or vertical density/unit change in cover or verti-cal density C change in % of label rate (1,440 g a.e. ha–1).

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In conclusion, the presented results indicate that plantcommunities in semi-natural grassland are affected bysub-lethal glyphosate doses, and that the effect of glypho-sate on the community structure is partly caused by alteredplant–plant interactions. These suggest that the currentpractice in the environmental risk assessment of effects ofherbicides,[55,56] where a single species is tested in thegreenhouse, may be insufficient for predicting the effectsof herbicides on non-target plants in field margins andother semi-natural habitats bordering agricultural fields.Competitive interactions, as shown in the present project,also need to be considered in order to make a credible eco-logical prediction on the risk of effects on non-targetplants, and the Bayesian approach presented in this papercould be a valuable tool for studying and better under-standing the effects of sub-lethal herbicide doses on semi-natural and natural plant communities. Initially, moreexperiments with binary mixtures of plant species exposedto sub-lethal herbicide doses are required to generate addi-tional data on competitive interactions but eventuallyinformation on herbicide susceptibility from assays of sin-gle species in combination with information on competi-tive indices of plant species should be sufficient to predicteffects on single plant species for different scenarios (com-positions of plant community and herbicides).We expect that the demonstrated modelling approach

could also be used more generally for predicting effects ofweed control strategies on the botanical composition ofagro-ecosystem. For example, the model can be used topredict shifts in weed flora towards glyphosate-tolerantweed species that indiscriminate use of glyphosate inglyphosate-resistant crops eventually will lead to, as shownfor fields cultivated with glyphosate-resistant cotton.[57]

Worldwide natural areas are threatened by invasiveplant species.[58] In areas infected by invasive species, res-toration methods, including targeted use of herbicides, arebeing evaluated.[59] A better understanding of the effect ofpotential herbicides on interspecific competition betweennative and invasive plant species could assist the choice ofrestoration method. We suggest that small-scale experi-ments applying the methods and model presented in thispaper could provide the insight required to optimize therestoration strategy.

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Appendix S1. The Kalø experimental site

The Kalø experimental site was established to investigatethe ecological processes, including establishment, survivaland competitive interactions in semi-natural grasslandsexposed to low dosages of fertilizer and pesticide in a con-trolled but relatively realistic way. Consequently, plantspecies composition and abundance have not been con-trolled following the initial seeding except for woody spe-cies (trees and bushes) that are removed every year priorto application of herbicide to keep the area as grassland.

The experiment was established in 2001 on a formeragricultural field on dry and nutrient poor sandy soil.[1]

The field laid fallow a couple of years prior to the start ofthe experiment. The field is quadrangular and surroundedby small parts of forest on two sides (south and west) andseparated from the neighbouring fields by 5-m broadhedgerows on the other sides. In spring 2001, the area wasdeep-ploughed down to 60 cm to minimize establishment

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from the soil seed bank and prepared for the experiment byharrowing and rolling. Thirty-one grassland species weresown in April 2001. The species selected were equally cov-ering different life form strategies.[2]

Treatments

The experimental manipulations were set up as a random-ized block design with 10 replicates of each of the 12 treat-ments (Fig. S1). The treatments include four glyphosatetreatments (0, 14.4, 72 and 360 g a.i. ha–1 equal to 0, 1, 5and 25% of label rate of 1,440 g glyphosate ha–1) and threenitrogen treatments (0, 25 and 100 kg N ha–1). All plotsreceive phosphorus (53 kg ha–1), potassium (141 kg ha–1),sulphur (50 kg ha–1 and copper (0.7 kg ha–1) every year.The RoundupBio� formulation of glyphosate is used forthe experiment. Each plot is 7 £ 7 m with a buffer zone of1.5 m surrounding the plot. A buffer zone of 10 m sepa-rates the experiment from the surrounding vegetation. Thebuffer zones were also sown with the seed mixture.

Spraying equipment for experimental applications isused for the application of herbicide. The beam is 3 mwith 0.5 m between the nozzles that are Lurmark Lo-driftLD 015 Green nozzles with a pressure of 2.0 bars. Thewind speed on the days selected for spraying is very low(0–2 m s–1) and there is no rain, neither is rain expectedduring the days following the day of spraying. Fertilizersare spread by hand. The plots were treated by glyphosatefor the first time on August 24, 2001, and since then thesehave been treated with herbicide and fertilizer once everyyear in spring (mid-ultimo May).

References[1] Bruus Pedersen, M.; Aude, E.; Tybirk, K. Adskillelse af effekter

af herbicider og kvælstof pa�vegetation og leddyr i hegn og

græslandsvegetation. Bekæmpelsesmiddelforskning fra Miljøstyr-elsen; Miljøstyrelsen, 2004; 103 p.

[2] Grime, P. Plant Strategies, Vegetation Processes, and EcosystemProperties; Hoboken, NJ: Wiley, 2001.

Appendix S2. Dose-response on single species

The susceptibility of Agrostis capillaris and Festuca ovina toglyphosate was examined in a pot experiment. Seeds of thetwo species were sown in 2-L pots in a potting mixture com-prising soil, sand and peat (2:1:1 by weight), including allnecessary micro and macro nutrients. The pots were placedin a glasshouse. After germination, the number of plants perpot was reduced to the same number for each plant species.

Five glyphosate doses (Roundup Bio, Monsanto CropScience,Denmark, 360 g a.e. L–1) were applied at 4 to 6 tillerstage using a laboratory pot sprayer. The sprayer wasequipped with two ISO-02 nozzles operating at a pressure of3 bars and a velocity of 5.6 km h–1 delivering a spray volumeof 151 L ha–1. The doses ranged from 22.5 to 360 g a.e. ha–1.Plants from three replicates of each treatment were har-vested three to four weeks later.

The fresh weight data were subjected to a non-linearregression analysis using a log-logistic dose-responsemodel as described by Seefeldt et al.[1] ED10, ED50 andED90 doses were calculated. The assumption that logisticdose response curves could be fitted to the data wasassessed by a test for lack of fit comparing the residual

Fig. S1. Experimental design at the Kalø experimental plot with 12 experimental treatments, including four glyphosate treatments (0,14.4, 72 and 360 g a.i. ha–1 equal to 0, 1, 5 and 25% of label rate of 1,440 g glyphosate ha–1) and three nitrogen treatments (0, 25 and100 kg N ha–1).

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sum of squares of an analysis of variance and the non-linear regression. The estimated ED10, ED50 and ED90doses (Table S1) showed that A. capillaris was more sus-ceptible to glyphosate than F. ovina.

References[1] Seefeldt, S.S.; Jensen, J.E.; Furst, E.P. Log-logistic analysis of

dose-response relationships. Weed Techol. 1995, 9, 218–227.

Table S1. Estimated ED10, ED50 and ED90 doses (g a.i. ha–1)of glyphosate on A. capillaris and F. ovina in single speciesexperiments. Figures in parentheses are 95% confidenceintervals.

ED10 ED50 ED90

A. capillaris 18.0 (10.8–25.2) 36.0 (28.8–46.8) 75.6 (61.2–86.4)F. ovina 36.0 (10.8–57.6) 115.0 (79.2–151.0) 374.0 (256.0–486.0)

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