Ecological Modelling 222 (2011) 626–636

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Ecological Modelling
journal homepage: www.elsevier.com/locate/ecolmodel

Prediction of germination rates of weed species: Relationships between

germination speed parameters and species traits
Antoine Gardarin a , Carolyne Dürr b , Nathalie Colbach a,∗
a
INRA, AgroSup Dijon, Université de Bourgogne, UMR 1210 Biologie et Gestion des Adventices, 21000 Dijon, France
b
INRA, UMR 1191 Physiologie Moléculaire des Semences, 49000 Angers, France

a r t i c l e i n f o a b s t r a c t

Article history: In fields, the timing of weed emergence flushes is mostly related to the timing and rate of seed germina-
Received 1 February 2010 tion, which depend on seed dormancy level, soil temperature and water potential conditions as well as
Received in revised form soil tillage and crop sowing date. Seed germination parameters are essential in weed dynamics models
15 September 2010
to account for the effects of soil conditions on weed demography. Since these parameters are difficult
Accepted 7 October 2010
to measure, our objective was to test the possibility of estimating them from easily accessible informa-
Available online 17 November 2010
tion. Seed germination parameters (germination lag-time, time to mid-germination and mid-germination
rate) were measured or collected from the literature for 25 weed species with contrasted seed character-
Keywords:
Base temperature
istics. Correlations were then searched for between these parameters and morphological, chemical and
Dormancy physiological seed traits as well as seed dormancy level. The dormancy level was positively correlated
Germination lag with speed of germination parameters. Earliness of germination was positively correlated with seed lipid
Germination rate content and the seed area to mass ratio. Germination was also earlier and faster in species with a high
Lipid content base temperature for germination. These relationships explained about half the observed variability in
Area to mass ratio germination speed parameters but should be further tested before being used to predict the germination
Seed behaviour of weed species in the field in different seasons.
© 2010 Elsevier B.V. All rights reserved.

1. Introduction ulated by a large number of different weed species. Such models

should therefore be extended to a wider flora in order to predict
Models to quantify the effects of cropping systems on weed the effects of integrated weed control strategies on whole weed
dynamics are necessary to develop innovative cropping systems to communities in the long term.
reduce the use of herbicides and preserve the biodiversity of fauna In weed dynamics models, germination is usually modelled as
and flora (Freckleton and Stephens, 2009). Such models consist of a function of hydro-thermal conditions, the proportion of non-
a succession of key life stages (e.g. non-dormant seeds, germinated dormant seeds, and parameters that are specific to the species being
seeds, emerged seedlings, etc.) linked by functions that depend on modelled (Colbach et al., 2005), including base temperature and
the effects of the cropping system in interaction with the climate base water potential for germination (described in detail in a pre-
and soil environment (Vleeshouwers and Kropff, 2000; Colbach vious study, Gardarin et al., 2010b). Seasonal variations in seed
et al., 2006; Sester et al., 2007). Weed seed germination (starting dormancy (i.e. the inability to germinate even in favourable con-
with the uptake of water by the quiescent dry seed and terminat- ditions) over time have also been widely studied in many weeds
ing with the elongation of the embryonic axis, Bewley, 1997) is a (Lonchamp et al., 1984; Baskin and Baskin, 1989; Bouwmeester
key process because it determines both the amount of weeds that and Karssen, 1993) and are related to variations in the amplitude
could potentially emerge and the timing of their appearance in the of the permissive range of temperatures and water potentials for
field. To date, weed dynamics models have been developed only for germination (Batlla and Benech-Arnold, 2007). However, few stud-
a very small number of species even though fields are often pop- ies have compared germination rates of weed seeds while taking
into account variations in their dormancy in the soil (as opposed
to dry-stored seeds in laboratory conditions), as such studies are
expensive and time-consuming.
∗ Corresponding author at: UMR 1210 Biologie et Gestion des Adventices, INRA,
An innovative approach would be to correlate species traits to
17 rue Sully, BP 86510, 21065 Dijon cedex, France. Tel.: +33 03 80 69 30 33;
predict the behaviour of a wide range of species (Keddy, 1992).
fax: +33 03 80 69 32 62.
E-mail addresses: Antoine gardarin@yahoo.fr (A. Gardarin), Following the definition of Violle et al. (2007), a trait is any mor-
carolyne.durr@angers.inra.fr (C. Dürr), Nathalie.Colbach@dijon.inra.fr (N. Colbach). phological, physiological or phenological feature measurable at

0304-3800/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.ecolmodel.2010.10.005
 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636 627

Table 1
Correlations found in the literature between seed traits and the germination rate of wild or cropped species.

Seed traits or other characteristics Correlation with the seed germination rate Species studied Source

Seed physical characteristics

Spherical, multicoloured or Negative 400 species of the British Isles flora Grime et al. (1981)
mucilaginous seeds
Presence of a pappus, Positive 400 species of the British Isles flora Grime et al. (1981)
hygroscopic awns or hairs, or
conical shape
Mass Negative 400 species of the British Isles flora Grime et al. (1981)
Mass No effect 64 wetlands species Shipley et Parent, 1991
Mass Negative (weak tendency) Abutilon theophrasti Baloch et al. (2001)
Mass No consistent pattern in the populations and Lithospermum arvense, Anchusa arvensis Milberg et al. (1996)
species studied
Mass Positive Alopecurus myosuroides Colbach and Dürr (2003)
Seed chemical characteristics
Lipid content Negative in anoxic conditions 12 cropped species Raymond et al. (1985)
Soluble sugar contents High fructose accumulation rate and raffinose Phaseolus aureus, Glycine max, Kuo et al. (1988)
decreasing rate during germination increased Gossypium arboreum
germination rate
Soluble sugars contents Negative Glycine max Obendorf et al. (2008)
(raffinose and stachyose)
Other
Base temperature for seedling Positive 30 cropped species Angus et al. (1981)
emergence in the field

the individual level. Seed traits have been linked with seedling mung bean, three species contrasted in their raffinose saccharide
establishment in wild species (Weiher et al., 1999). Based on this contents. Al-Ani et al. (1985) showed for crop species with a wide
principle, model parameters which are difficult to measure could be range of seed lipid contents that a high seed lipid content increased
inferred from easily accessible seed traits using generic functions their sensitivity to low oxygen partial pressure during germination.
established with a few contrasting model species representative In addition to these traits, germination speed varies consider-
of the diversity of the weeds (Gardarin et al., 2009). We already ably with the level of seed dormancy, more in weed species than
established such relationships for the prediction of pre-emergence in crop species. Slow germination rates (i.e. the proportion of ger-
seedling growth (Gardarin et al., 2010a). minated seeds per unit of time) have been shown to be correlated
A critical analysis of existing germination literature led to with low final germination percentages of highly dormant seeds
the identification of several seed characteristics related to ger- (Courtney, 1968; Vleeshouwers, 1997; Colbach et al., 2006). Highly
mination. Table 1 summarizes various inter and intra-specific dormant seeds also present long germination lags (i.e. the time from
relationships found in the literature between morphological, chem- water uptake to the first germinated seed in the seed lot) and lower
ical and physiological seed characteristics on the one hand, and germination rates (Shipley and Parent, 1991).
the seed germination rate on the other. The seed germination rate The objective of the present study was to search for relationships
was found to be correlated with the species base temperature for between the parameters influencing germination speed (i.e. ger-
germination. According to Angus et al. (1981), the thermal time nec- mination lag-time, time to mid-germination and mid-germination
essary for germination and emergence of crop species decreased rate) and morphological, chemical and physiological seed traits.
with an increase in species base temperature. Similar correlations Relationships were searched for using germination experiments
have been reported for the growth of different kinds of organisms on 14 weed species in which the above-mentioned traits were con-
(e.g. insects, arachnids, Trudgill et al., 2005) and could be relevant trasted and which were representative of the weed flora found
for weed seed germination. Secondly, based on the study of 400 in north-western European cropping systems. Their seeds were
species of Britannic flora, Grime et al. (1981) observed that the buried and then excavated in different seasons in the field to
germination rate was associated with the shape of the seed, and account for variations in seed dormancy over time. They were then
that smaller and more elongated seeds had higher germination put to germinate in light vs. darkness to account for light condi-
rates. The intra-specific effect of seed mass on germination rate tions for surface vs. buried seeds in the field. The experiments were
differs with the species studied and no clear pattern is apparent completed with data from the literature to increase the number of
(Milberg et al., 1996; Baloch et al., 2001). A maize seed imbibition species analysed.
model revealed that the proportion of the imbibed seed surface
was strongly correlated with the seed imbibition rate (Bruckler, 2. Material and methods
1983a,b) and consequently with the germination rate. Therefore,
if we assume that the amount of water required by a given seed Experiments consisted in burying seed bags and then excavating
depends on its mass, the area to mass ratio could influence the seed them every two or six months over a period of two years in order
imbibition rate. Finally, the seed germination rate may also depend to measure changes in seed germinability due to variations in seed
on reserve mobilization, which is necessary for germination and dormancy level.
early seedling growth. The composition of the seed reserves, their
protein, lipid and soluble sugar contents, varies greatly between 2.1. Seed burial and recovery
genera and families (Earle and Jones, 1962; Kuo et al., 1988). It
is often suggested, although to our knowledge not demonstrated, Seeds of 14 weed species commonly found in fields in
that a high soluble sugar content in the seed reserves supplies north-western Europe with intensive cropping systems, and with
rapidly available energy for the embryo and favours rapid germi- contrasting seed traits (seed mass, nature of reserves, etc.) were
nation (Dierking and Bilyeu, 2009). Kuo et al. (1988) observed an collected at full maturity in 2006 in fields near Dijon (47.317◦ N,
increase in germination rates in relation with the disappearance 5.017◦ E, 220 m altitude) in Burgundy, France, except Arabidopsis
of raffinose and accumulation of fructose in cotton, soybean and thaliana for which no seeds could be harvested in 2006. Imme-
 628
Table 2
Species studied, experimental conditions for the seed lot burial and germination experiments, and range of germination speed parameters estimated from fitting equation.

Species Presence of Burial date Periodicity Germination Periods where final

A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636

soil (100 g) of seed germination
in the bags recovery percentages were

Temperature Light conditions Range of final Range of lag time Range of time to Range of Low High
(◦ C) germination TT0 (◦ C days) mid-germination germination rates
proportions m TT50 (◦ C days) at
mid-germination
(◦ C−1 days−1 )
Capsella bursa-pastoris (L.) Medik. No 16 June 2 months 15 Light and dark 0.06–0.58 12–73 26–91 0.0059–0.1422 June November
Galium aparine L. Yes 18 July 2 months 15 Light and dark 0.07–1 25–101 30–192 0.0004–0.0100 April November
Matricaria perforata Mérat No 18 July 2 months 15 Light and dark 0.46–0.99 18–66 33–85 0.0050–0.1026 July 06 Aug.06–June 08
Amaranthus hybridus L. No 13 September 2 months 25 Light and dark 0.09–1 10–35 14–79 0.0011–0.8199 October April
Polygonum lapathifolium L. Yes 27 September 2 months 25 Light and dark 0.07–0.99 14–77 23–97 0.0005–0.0795 September March
Arabidopsis thaliana (L.) Heynhnh No 18 July 6 months 15 Light 0.95–0.97 37–79 61–107 0.0157–0.0220 July 06–April 08
Avena fatua L. Yes 4 July 6 months 15 Light 0.11–0.98 26–55 28–91 0.0021–0.0506 April June
Papaver rhoeas L. No 4 July 6 months 15 Light 0.11–0.32 81–103 106–127 0.0016–0.0240 July 06–October April 08
07
Echinochloa crus-galli Beauv. No 1 August 6 months 15 Light 0.24–0.98 38–45 40–74 0.0074–0.0304 October May
Chenopodium album L. No 18 September 6 months 15 Light 0.09–0.56 31–46 33–111 0.0016–0.0123 October May
Fallopia convolvulus Loeve Yes 27 September 6 months 20 Light 0.08 56 79 0.0026 September April 08
06–October 07
Polygonum aviculare L. No 2 October 6 months 20 Light 0–0.04 Not estimated Not estimated Not estimated October
06–March 08
Ambrosia artemisiifolia L. No 11 October 6 months 20 Light 0.53–0.89 18–31 31–38 0.0188–0.0469 October April
Digitaria sanguinalis (L.) Scop. No 11 October 6 months 25 Light 0.13–0.90 30–31 30–46 0.049–0.6134 October May
 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636 629

diately after collection, samples of 100–300 seeds were placed in

nylon (Tergal) bags (mesh size 400 ␮m). For large seeds, 100 g of
field soil (15% moisture content) was added to prevent direct con-
tact between the seeds (Table 2). Seed bags were placed at the
bottom of openwork baskets, with three bags of one species per
basket. The baskets were filled with soil and, in 2006, were buried
at a depth of approximately 30 cm corresponding to the bottom
of the ploughed layer. Every two months over the next two years,
two baskets (six bags) of five species (Table 2) were randomly cho-
sen to be excavated, one for germination tests in the light and
another one for the tests in the dark. In the latter case, immedi-
ately after excavation, the basket was placed in two opaque bags
without removing the soil from the bags to keep them in continuous
darkness. For these five species, seeds were recovered frequently
in order to precisely detect seasonal variations in the seed germi-
nation rate. For the other nine species, one basket was recovered
(only for germination tests in the light) approximately every six
months to study germination when seeds were either most or least
Fig. 1. Meaning of the different germination time-course parameters Example of
dormant (Table 2). Galium aparine: seeds were recovered on 29th January 2009 and germinated in the
dark (symbols) with fitted time-course Eq. (2).
2.2. Seed germination tests
for one month. The remaining ungerminated seeds were dissected
The seed germinability of each species was assessed after seed (crush test, Sawma and Mohler, 2002) to distinguish viable dormant
collection, at the beginning of the burial experiment, and then at seeds from unviable seeds.
each recovery date. For the species recovered every two months, The total number of viable seeds set to germinate was the sum
germination was studied in either constant light or in total dark- of the number of germinated seeds (before addition of gibberellin)
ness. If necessary, seeds were manually recovered one by one from plus the number of viable seeds remaining at the end of the exper-
the soil with which they were mixed. One hundred seeds from iment (germinated after addition of gibberellin and viable seeds
each bag were laid out on pleated paper (pleated strips, 113 g m−2 , identified in the crush test).
doublefolds, 110 mm × 20 mm). The pleated paper was placed in a
plastic box with 40 mL of deionised water to obtain non-limiting 2.4. Germination time courses
water conditions. There were three boxes per species and light
condition at every recovery date. Boxes were closed hermetically A germination time course is considered here as the cumulated
to avoid water loss and placed in an incubator at a temperature proportion of germinated seeds with thermal time after the addi-
close to the optimum temperature of each species (Montégut, 1975; tion of water. The three seed lots exhumed from each basket were
Webster, 1979, Table 2). The incubators were illuminated with considered as pseudo-replicates and were pooled for data analysis.
six fluorescent lighting tubes (Osram, L 18 W/77, 20 ␮mol m−2 s−1 Germination time courses were determined for each combination
each). of the factors concerned (species, exhumation date and light con-
Seeds were set to germinate at constant temperature. The ampli- dition). For each germination time course, the thermal time TT[i]
tude of alternating temperature can have a major effect on the (◦ C days) was calculated each day i, after addition of water, with
germination rate and final percentage of the species (Baskin and the following equation (Garcia-Huidobro et al., 1982):
Baskin, 1998; Taab and Andersson, 2009). In our study, the effect
of alternating temperatures on the speed of germination was indi- TT[i] = TT[i − 1] + (T [i] − Tb ) (1)
rectly accounted for via the integration of the percentage of total where T[i] is the temperature (◦ C) of day i and Tb the base temper-
germinating seeds in the statistical analyses as an explanatory vari- ature (◦ C) for germination of the corresponding species (Table 3).
able (see Section 2.7). Base temperatures were either measured in a previous study using
Seed bags destined for germination in darkness were handled the x-intercept method (Gardarin, 2008) or taken from the lit-
in a dark room lit by a green inactinic lamplight with no stimu- erature. No data were available for Papaver rhoeas and Fallopia
lating effect on germination, as shown by Colbach et al. (2002). convolvulus. For these species, base temperature was estimated at
Boxes were wrapped in two sheets of aluminium foil and placed 0.8 and 4.3 ◦ C, respectively, using a relationship between the date of
in the same incubator. The germination conditions of each species emergence onset of the species in spring and the base temperature
are summarised in Table 2. The temperature of each incubator was proposed by Gardarin et al. (2010b).
recorded and used for data analysis (see Section 2.4). The cumulated proportion of germinated seeds G[i] was calcu-
Seed germination was assessed daily during the first week after lated as the number of seeds having germinated up to day i divided
water was added and then regularly until the end of germina- by the total number of viable seeds. An equation adapted from
tion, over a period of at least four weeks. Seeds set to germinate Weibull (1959) was fitted to G[i] with thermal time TT[i] for each
in darkness were observed under green light. Germination assess- germination time course (Fig. 1):
ment consisted in counting (and eliminating) the number of newly
G[i] = 0, if TT[i] < TT0 ,
germinated seeds, i.e. those with a protruding root. ⎡  b ⎤
TT [i] − TT0
2.3. Seed viability tests ⎢ −logn (2)·
TT50 − TT0 ⎥
G[i] = m ⎢1 − e ⎥ + error, if TT[i] ≥ TT0 (2)
⎣ ⎦
After the final measurement, ungerminated seeds were treated
with gibberellin (0.29 mmol L−1 ) and, if required by the species,
stratified to overcome dormancy according to the literature where m is the final proportion of germinated seeds equivalent
(Webster, 1979). Seed germination was then recorded each week to the proportion of non-dormant seeds. TT0 is the germination
630 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636

Table 3
Seed traits measured in 25 weed species.

Species Seed dry mass Area Area-mass ratio Lipid content Protein content Base temperature
(± SD, mg) (± SD, mm2 ) (± SD, mm2 /mg) (± SD, %) (± SD, %) (± SE, ◦ C)

Alopecurus myosuroides 2.3 ± 0.67 6.523 2.8 14.5 ± 0.46 22.7 ± 0.03 0.06
Amaranthus hybridus 0.4 ± 0.07 1.4 3.7 8.5 ± 0.04 15.5 ± 0.10 8.8 ± 1.110
Amaranthus retroflexus The traits measured in A. hybridus were used since A. hybridus and A. retroflexus are very similar and frequently 15.021
considered as a belonging to the same single species.
Ambrosia artemisiifolia 4.6 ± 1.30 5.1 ± 0.88 1.1 22.3 ± 0.08 9.5 ± 0.00 3.6 ± 1.114
Arabidopsis thaliana (L.) Heynh. 0.029 0.123 5.5 41.9 23.5 ± 0.05 3.011
Avena fatua 18.5 ± 6.66 17.523 0.9 8.9 ± 0.18 8.4 ± 0.02 2.2 ± 1.213 , 0.48
Beta vulgaris ssp. vulgaris 12.5 15.6 1.3 21.3 ± 1.72 23.7 ± 0.34 3.515
Capsella bursa-pastoris 0.1 ± 0.02 0.4 23
3.1 39.1 ± 0.28 23.3 ± 0.03 4.5 ± 1.714
Centaurea cyanus 5.3 5.2 ± 1.18 1.0 28.4 ± 0.27 16.9 16 2.2 ± 0.514
Chenopodium album 0.6 1.4 ± 0.18 2.5 9.4 ± 0.09 14.2 ± 0.13 5.8 ± 0.513 , 228
Datura stramonium 7.2 ± 1.14 7.8 ± 0.96 1.1 32.1 ± 0.05 18.416,24 10.44
Digitaria sanguinalis 0.6 ± 0.09 2.0 ± 0.29 3.5 4.3 ± 0.28 16.6 ± 0.13 9.9 ± 2.522,19,25
Echinochloa crus-galli (L.) P. 2.2 ± 0.46 4.1 ± 0.71 1.8 6.3 ± 0.12 13.5 ± ± 0.08 6.2 ± 0.614
Beauv.
Fallopia convolvulus (L.) A. Löve 6.5 ± 1.39 7.4 ± 0.47 1.1 3.5 ± 0.10 14.6 ± 0.05 4.3
Galium aparine 7.4 ± 2.39 5.4 ± 1.72 0.7 3.7 ± 0.08 11.5 ± 0.08 2.526
Geranium dissectum 2.1 ± 0.36 2.3 ± 0.24 1.1 21.4 ± 0.80 24.2 ± 0.13 −1.5 ± 1.314
Matricaria perforata 0.3 ± 0.08 0.223 0.8 19.4 ± 0.13 15.3 ± 0.00 2.0 ± 0.714
Papaver rhoeas 0.1 0.323 2.4 43.6 ± 0.24 23.0 ± 0.03 0.8
Polygonum aviculare 1.5 ± 0.59 3.1 ± 1.27 2.1 4.2 ± 0.28 11.9 ± 0.03 0.017
Polygonum lapathifolium 2.0 ± 0.58 5.0 2.5 5.5 ± 0.01 11.0 ± 0.01 5.8 ± 1.014
Polygonum persicaria 1.99,18,20,28 The traits of Polygonum lapathifolium were used since these two species are relatively close. 3.228
Solanum nigrum 0.83,7,9 1.823 2.4 25.12,7,24 18.32,7,24 11.5 ± 0.713
Spergula arvensis 0.43,5,9,20,28 0.623 0.3 11.51 14.59 3.727
Stellaria media 0.4 0.8 ± 0.08 2.1 5.91 17.92,24 1.412
Veronica hederifolia 3.5 ± 1.48 4.0 ± 1.09 1.1 15.6 ± 0.27 15.6 ± 0.01 0.2 ± 0.214

Sources: 1 (Aitzetmüller et al., 2003); 2 (Barclay and Earle, 1974); 3 (Benvenuti et al., 2001); 4 (Benvenuti and Macchia, 1993); 5 (Bouwmeester and Karssen, 1992); 6 (Colbach
et al., 2002); 7 (Earle and Jones, 1962); 8 (Fernandez-Quintanilla et al., 1990); 9 (Flynn et al., 2006); 10 (Granger and Guillemin, 2004); 11 (Granier et al., 2002); 12 (Grundy
and Mead, 2000); 13 (Guillemin et al., 2008); 14 (Gardarin et al., 2010b); 15 (Gummerson, 1986); 16 (Jones and Earle, 1966); 17 (Kruk and Benech-Arnold, 2000); 18 (Lutman
et al., 2002); 19 (Masin et al., 2005); 20 (Milberg et al., 2000); 21 (Oryokot et al., 1997); 22 (Sartorato and Pignata, 2008); 23 (Sevic, 2003); 24 (Schroeder et al., 1974); 25
(Steinmaus et al., 2000); 26 (Van der Weide, 1993); 27 (Vleeshouwers, 1997); 28 (Vleeshouwers and Kropff, 2000).

lag, i.e. the thermal time (◦ C days) from the addition of water for 18 species (including 11 new species), resulting in a total of 25
to the first germination. TT50 is the time to mid-germination, i.e. species. Finally, there were up to four different sources of data (from
the thermal time necessary to obtain m/2 germinated seeds. b is our experiments or from the literature) for each species.
a shape parameter correlated with the germination rate at mid-
germination. Fitting was carried out using proc NLIN of SAS (SAS 2.6. Seed trait measurements
Institute Inc., Cary, North Carolina, USA, 1999). R2 were calculated
as 1 − (sum of error squares)/(total corrected sum of squares). No Seed traits were measured on samples taken from the same seed
fitting was done when less than 5% of the seeds germinated. lots as those buried in the soil. The seed dry mass of each species
The germination rate at mid-germination (v50 , in ◦ C−1 days−1 ) was measured individually on 100 seeds dried at 80 ◦ C for 48 h.
was calculated using the derivative of Eq. (2) at mid-germination Individual photos of 100 seeds were taken with a camera (pixel
TT50 : size between 2.25 and 4.18 ␮m depending on the species) and the
morphological features were computed on a binary image using
m · b · logn (2)
v50 = (3) the method previously described by Muracciole et al. (2007). Seed
2 · (TT50 − TT0 ) area, in two dimensions, was then determined by image analysis
(Majumdar and Jayas, 2000; Muracciole et al., 2007).
2.5. Germination time courses taken from literature For seed composition analyses, seeds enclosed in thick seed
coats were dehulled. The outer seed coat of Avena fatua L., Alopecu-
To increase the number and range of species analysed, additional rus myosuroides and Echinochloa crus-galli, and the floral parts of
data were taken from the literature. We only used germination time Beta vulgaris ssp. vulgaris were removed. Seeds of other species were
courses obtained in similar conditions to the protocol described in kept intact and their dispersule (i.e. the seed or the fruit with all its
Sections 2.1–2.3 (optimal temperature and water potential condi- attached structures) was analysed. Seeds were dried at 80 ◦ C for
tions) and for which the final proportion of germination (level of 48 h and two seed samples were taken from each species. Seeds
dormancy) was known. However, for most of the species, germina- weighing less than 3 mg were milled to fine powder in a rotary
tion was measured on seed lots which had not been buried in the grinder (ZM 200, Retsch) and a ball mill (diameter 10 mm, Pro-
soil. Details on these supplementary time courses are summarized labo) was used for larger seeds. Nitrogen content was measured
in Table 4. When available, values for germination parameters (TT0 , using the Dumas procedure (Hansen, 1989) and multiplied by 6.25
TT50 and v50 ) were taken directly from the paper concerned. Oth- to estimate the seed protein content (Mariotti et al., 2008). Lipid
erwise, the parameters were estimated graphically. Germination content was determined, following Jensen et al. (1972) by dis-
speed parameters expressed per day or per hour were converted solving seed lipids in hexane:isopropanol (3:2, v/v), centrifuging
into thermal time using the base temperature given in the same and collecting the supernatant, then evaporating the solvent with
paper if possible. a rotary evaporator. The lipids remaining in the tube were then
The final dataset consisted in germination time courses mea- weighed. Missing trait values were completed with data from the
sured for 14 species buried in the field completed by literature data literature.
 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636 631

Table 4
Seed germination data used to increase our experimental dataset.

Species Source Seed storage characteristics Germination Other germination Number of Range of final
temperature conditions germination germination
(◦ C) kinetics proportions

Alopecurus myosuroides Colbach et al. (2006) Buried in the soil and recovered 15 Light and dark 12 0.08–0.95
after 1, 4, 5, 13, 16, 17 and 23
months
Amaranthus retroflexus Ghorbani et al. (1999) Storage at ambient temperature 20 and 30 Light 2 0.40–0.80
Amaranthus retroflexus Gardarin (2008) Storage at ambient temperature 30 and 27.5 Light 2 0.97–1
See also Granger and
Guillemin (2004)
Amaranthus retroflexus Oryokot et al. (1997) Storage at 5 ◦ C From 12 to 33 Light 1 1
Ambrosia artemisiifolia Gardarin (2008) Storage at ambient temperature 27.5 3 weeks of 1 0.60
stratification at
4 ◦ C—light
Avena fatua Fernandez-Quintanilla Storage at ambient temperature 15 and 20 Light 2 0.71–0.80
et al. (1990)
Avena fatua Gardarin (2008) Storage at ambient temperature 10 Light—imbibition 1 0.71
See also Guillemin et al. with KNO3 (1%)
(2008)
Beta vulgaris ssp. vulgaris Sester et al. (2006) Buried in the soil and recovered 15 Light and dark 12 0.05–0.67
after 1, 4, 5, 13, 16, 17 and 23
months
Capsella bursa-pastoris Gardarin (2008) Storage at ambient temperature 30 Light 1 0.58
Centaurea cyanus Gardarin (2008) Storage at ambient temperature 20 Light—imbibition 2 0.79–0.81
with KNO3 (1%)
Centaurea cyanus Unpublished—seeds from Storage at ambient temperature 15 Light 6 0.89–0.98
cultivated field, Chizé,
France (2006)
Chenopodium album Gardarin (2008) Storage at ambient temperature 25 Light—imbibition 3 0.29–0.88
See also Guillemin et al. with KNO3 (1%)
(2008)
Chenopodium album Vleeshouwers and Kropff Buried in the soil From 5 to 30 Light 1 1
(2000)
Datura stramonium Unpublished—seeds from Storage at 4 ◦ C and low air 25 Light 3 0.94–0.96
experimental plots, Dijon, moisture content
France, 2006
Echinochloa crus-galli Gardarin (2008) Storage at ambient temperature 22.5 Light 1 0.85
Galium aparine Van der Weide (1993) Buried in the soil From 4 to 18 Light 1 1
Geranium dissectum Gardarin (2008) Storage at 4 ◦ C and low air 15 Light 5 0.97–1
moisture content
Polygonum lapathifolium Gardarin (2008) Storage at ambient temperature 30 Light 1 0.73
Polygonum persicaria Vleeshouwers (1997) Buried in the soil 15, 20 and 25 Light 3 0.95
Polygonum persicaria Vleeshouwers and Kropff Buried in the soil From 5 to 30 Light 1 1
(2000)
Solanum nigrum Gardarin (2008)
See also Guillemin et al., Storage at ambient temperature 30 Light 1 0.48
2008
Solanum nigrum Wagenvoort and Opstal Storage at ambient temperature 20 Light 1 0.70
(1979)
Spergula arvensis Vleeshouwers and Kropff Buried in the soil From 5 to 30 Light 1 1
(2000)
◦
Stellaria media Grundy et al. (2000) Storage at 4 C 14, 16 and 18 Light 3 0.86–1
Stellaria media Unpublished—seeds from Storage at 4 ◦ C and low air 15 Light 6 0.05–0.12
experimental plots, Dijon, moisture content
France, 2004
Veronica hederifolia Gardarin (2008) Storage at 4 ◦ C and low air 15 Dark 1 0.56–0.70
moisture content

2.7. Relationships between germination speed parameters and to a multiplicative model, which more satisfactorily accounts for
seed traits multiplicative interactions between the factors:
logn (germination parameter) = intercept
Linear models were used to study relationships between the

+ ˛trait logn (trait) + seed reserves categories effect

seed germination speed parameters (TT0 , TT50 , b and v50 ) on the

traits catégories (4)

one hand, and seed traits, dormancy and experimental conditions
+ logn (trait) · category effect + logn (m) + light effect + error
(light vs. darkness) on the other hand. Seed traits consisted in seed
mass, area, lipid and protein content, area to mass ratio and the traits·categories

species base temperature for germination. For the analysis of the where ˛trait are regression parameters. Base temperature was
effect of lipid content, two groups of species were distinguished: transformed by adding the constant 2 to obtain positive values
lipid-rich seeds (seed lipid content superior to 30%) and lipid-poor and make the logn -transformations possible. The contribution of
seeds. Seed dormancy was added to the model as a covariable and each effect to the variance explained by the model was computed
was characterized by the final proportion of germinated seeds m. using type III sum of squares. Statistical analyses were performed
Explained and explanatory quantitative variables were logn - using PROC REG (option BACKWARD) of SAS (SAS Institute Inc.,
transformed before analysis, the linear model thus being equivalent Cary, North Carolina, USA, 1999). Only factors that were significant
632 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636

at ˛ = 0.05 were kept. Models comprising the significant variables 3.3. Interspecific variations in germination speed parameters
were then compared using Akaike’s Information Criterion (AIC)
and the model with the lowest AIC was considered to be the best The germination time courses also varied widely in the different
(Akaike, 1973). The elimination of variables stopped when the AIC species even when species were compared at their lowest levels of
did not change by more than the absolute value of 2 and included dormancy. Fig. 3 shows germination time courses obtained when
the lowest number of variables. dormancy was lowest during the two years of the experiment.
Species such as Echinochloa crus-galli or Papaver rhoeas germinated
more slowly and in lower proportions than Amaranthus hybridus or
3. Results M. perforata. The species also differed considerably in their values of
TT0 and TT50 . Even when the final proportion of seed germination
3.1. Fitting the non-linear equation to observations of was 1, A. hybridus seeds only took 16 ◦ C days to reach mid-
germination time courses germination while Arabidopsis thaliana seeds required 61 ◦ C·days.
When completing the experimental results with 74 germina-
The data consisted of a total of 111 observed germination time tion time courses taken from the literature (Table 4), giving a total
courses for which Eq. (2) could be fitted (example Fig. 1), with R2 dataset of 185 germination time courses for 25 weed species, inter-
values between 0.96 and 1. However, some species presented a specific variations increased. TT50 varied from 11 to 436 ◦ C days.
very high level of dormancy at one or several recovery dates and The germination rate v50 varied from a proportion of 0.0004 (Gal-
did not germinate sufficiently (proportion less than 0.05) to allow ium aparine) to 0.82 (Amaranthus hybridus) germinated seeds per
the calculation of germination course parameters. For this reason unit of thermal time. In both datasets (our experiment with buried
Polygonum aviculare was excluded from all analyses. seeds and data from the literature), germination speed parame-
ters remained comparable for a given species; for instance, in both
datasets, Ambrosia artemisiifolia and Centaurea cyanus reached mid-
3.2. Seasonal variations in germination speed parameters
germination at approximately 33◦ C days and Chenopodium album at
70◦ C days.
Important seasonal variations were observed in the final ger-
mination proportions due to seasonal changes in seed dormancy 3.4. Seed traits
levels (Table 2). These were most visible when seeds were recov-
ered every two months. The seed dormancy level varied widely Seed traits for comparing species were either measured in the
depending on the time of burial and on the species concerned present study or, when available, taken from the literature. The
(Table 2, Fig. 2): the maximum variations in the final germination measured trait values are summarized in Table 3. Seed dry mass
proportion were observed in Polygonum lapathifolium, from 0.07 to varied widely, from 0.02 mg in Arabidopsis thaliana to 18.6 mg
0.99 depending on the burial dates, while in Matricaria perforata in Avena fatua. Species also displayed contrasted seed reserves.
the germination proportion was always high. For the latter species, Monocotyledonous species had low lipid contents, from 4 to
the estimation of germination speed parameters was thus possible 14%. Four dicotyledonous species (Arabidopsis thaliana, Capsella
at each recovery date: the germination lag (TT0 ) and the time to bursa pastoris, Datura stramonium and Papaver rhoeas) presented
mid-germination (TT50 ) increased in spring when the final propor- a seed lipid content above 30% and their protein contents were
tion of germinated seeds (i.e. the proportion of non-dormant seeds) also among the highest. These species were grouped for statistical
and the germination rate (v50 ) at mid-germination decreased, and analysis as lipid-rich seeds while the other species were considered
vice-versa during summer. as lipid-poor seeds.

Fig. 2. Variations in the lag time TT0 ( ), time to mid-germination TT50 ( ), germination rate v50 ( ) and final germination percentage () of Matricaria perforata. Seeds
were buried 30 cm deep in June 2006 and were recovered every two months to assess their germination at 15 ◦ C in the light. Each dot represents the mean of three seed bags
each containing 100 seeds.
 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636 633

Fig. 3. Fitted germination time courses in the light and at optimal temperatures (see Table 2) when species were at their lowest dormancy level. Seeds were buried 30 cm
deep in 2006 and were recovered every two or six months to study their germinability (the date of recovery is indicated after each species name). Polygonum aviculare and
Fallopia convolvulus were not represented because their seeds remained strongly dormant throughout the experiment. Symbols only serve to differentiate curves and do not
represent actual data points.

Table 5
Correlation between species traits, dormancy level, and germination speed parameters. Regression parameters and R2 of linear model [4] analysed with PROC GLM of SAS.

Explanatory variable

Proportion of Base Seed lipid content (g g−1 ) Area to mass Total R2

non-dormant temperature for ratio of seeds
seedsa germination (◦ C) (mm2 mg−1 )
Intercept logn (m) logn (Tb + 2) logn (lipid), if logn (lipid), if logn
lipid content lipid content (area/mass)
<0.30 ≥0.30

Predicted variables
Germination lag (◦ C days)
logn (TT0 ) 3.56 −0.18 −0.39 −0.23 −1.19 −0.30
Partial R2 0.07 0.08 0.13 0.08 0.41
◦
Time to mid-germination ( C days)
logn (TT50 ) 4.45 −0.25 −0.79 −0.29 −0.86 ns
Partial R2 0.07 0.33 0.16 0.46

Germination rate at mid-germination (◦ C−1 day−1 )

logn (v50 ) −4.77 1.07 1.53 0.50 0.56 ns
Partial R2 0.27 0.25 0.05 0.59

ns: not significant.

a
Proportion of germinated viable seeds in the seed lot for which germination parameters were determined.

Base temperatures for germination ranged from −1.5 ◦ C (Gera-

nium dissectum) to 15.0 ◦ C (Amaranthus hybridus). They were below
5 ◦ C in autumn and winter germinating species and reached 10 ◦ C
in summer germinating species.

3.5. Relationships between seed traits, dormancy and

germination speed parameters

Seed traits and dormancy level explained 41–59% of the vari-

ability in germination speed parameters (Table 5). For each of the
parameters TT0 , TT50 and v50 , the same seed traits were included in
each model with a highly significant effect. Germination was earlier
and faster in non-dormant seeds lots, i.e. TT0 and TT50 decreased
and v50 increased with an increase in the values of m (proportion
of non-dormant seeds). The effect of seed dormancy was great-
est for v50 (high partial R2 ), which justified the introduction of m
as a covariable. Base temperature for germination was similarly Fig. 4. Time from the addition of water to mid-germination (parameter TT50 ) as a
correlated with germination, i.e. TT0 and TT50 decreased and v50 function of species base temperature for germination. Germination results on filter
increased with an increase in the species base temperature (Fig. 4). paper with seeds exhumed at a depth of 30 cm in the field every two or six months
() and data compiled from the literature (♦). Each base temperature value corre-
Base temperature was the factor that explained the largest propor-
sponds to one species, the data points for a given species correspond to different
tion of variance in TT0 and TT50 . seed recovery dates.
634 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636

The higher the seed lipid content, the earlier and faster the ger- over, specific protein contents (such as those involved in repairing
mination, the highest slope being for lipid-rich seeds (exceeding processes and reserves mobilization, Bewley, 1997) could be more
30% lipid content). Lipid content was highest for TT0 and TT50 . appropriate for establishing correlations with germination charac-
Germination lag was the only parameter that increased with an teristics.
increase in the seed area to mass ratio, although the contribution The second seed trait to be positively correlated with germi-
of this factor was small. nation, TT0 , was the area to mass ratio. We hypothesized that
The other seed traits (seed mass and protein content) and the germination timing partly depended on the time required for seed
effect of seed exposure to light during germination had no sig- imbibition. Imbibition should be faster in seeds with a large area for
nificant influence on the germination speed parameters analysed. water to enter relative to seed water demand, probably linked to
Although the shape parameter b of the Weibull equation varied seed mass. However, although logical, the present correlation only
between species, no consistent relationship was found with any of explains a small proportion of the variability in the germination
the seed traits described in Section 3.4. rate and should be tested on a larger number of species.
Results of fitting to the Eq. (4) were analogous, whether the Germination was also shown to be faster in species with a high
whole data set (including literature data, Table 5) was used, or only base temperature for germination. This effect could a priori appear
data from the species we studied in our experiments (results not as an artefact resulting from the use of thermal time with differ-
shown). However, the effects of seed lipid content and of the sur- ent base temperatures, because less thermal time is accumulated
face to mass ratio were not significant when only the species we to reach a given proportion of germination when thermal time is
studied were used because of the smaller range of these traits in summed with an increased base temperature. However, this corre-
our species panel. In all cases, the values of the different regression lation remained unchanged when the analysis was performed with
parameters were very similar to those shown in Table 5. time units expressed in days, independently of the calculation of
thermal time (results not shown). Moreover, a similar correlation
has already been reported for the emergence of crop species (Angus
4. Discussion et al., 1981) and the development of invertebrates (Trudgill et al.,
2005). This relationship indicates that species requiring high tem-
The combination of extensive germination experiments and perature germinate faster than those germinating earlier at low
the critical selection of previous results from the literature pro- temperatures. This could be considered as an ecological adapta-
duced a dataset of germination time courses for a large number tion of late germinating species to develop faster and to compete
of weed species with contrasted germination characteristics and with early germinating species. Thus, both types of species achieve
seed traits. To our knowledge, the present summary quantita- germination and subsequently grow and develop in quite a similar
tive analysis of such a dataset for weed seed germination has time considering the range of temperatures in which they each ger-
not previously been attempted. Many general conclusions based minate in field conditions. In order to explain this trade-off between
on analyses of the present dataset are not new and are con- base temperature and thermal time required for a particular pro-
sistent with earlier reports in the literature. For instance, the cess, Trudgill et al. (2005) suggested a mechanism based on the fact
relationships between germination time-course parameters and that enzymes are more efficient at high temperatures.
dormancy observed here have already been reported in literature In the present analysis, germination speed parameters were
for a large range of species (Lonchamp and Gora, 1980; Baskin and not correlated with the presence vs. absence of light during the
Baskin, 1985; Bouwmeester, 1990). Similar approaches have been experiment. However, numerous studies have reported faster ger-
attempted in the past but only at an intraspecific scale (Hilhorst mination in the light for several weeds (Jensen, 1995; Milberg,
and Toorop, 1997; Batlla et al., 2003). The novelty of the present 1997; Colbach et al., 2002; Batlla and Benech-Arnold, 2005). In
work was to quantify these relationships for predictive purposes at the present work, the effect of light on the speed of germina-
the multi-species scale. tion was taken into account indirectly via the correlation with the
Our comprehensive dataset also enabled us to compare a vari- proportion of germinated seeds, which was usually higher when
ety of species, and our general observations are also consistent the seeds were exposed to light. Indeed, the role of light as a
with those of previous studies. The earlier and faster germination dormancy-terminating factor favouring an increment in percent-
of Amaranthus hybridus than in Galium aparine confirmed observa- age germination of light-requiring species is widely reported in the
tions by Lauer (1953). The main result of the present work was to literature (Andersson et al., 1997; Milberg and Andersson, 1998;
correlate interspecific differences in germination timing and rates Benech-Arnold et al., 2000). The analysis of seasonal variations in
with species traits. A relationship between earliness of germination the final germination percentages was the objective of a different
and the seed lipid content was found, which to our knowledge, has study and was not analysed here.
not previously been observed. However, a reverse correlation was Although several of the factors we studied had a highly sig-
found between seed lipid content and germination rate, but at low nificant effect, a large proportion of variability in germination
dioxygen concentrations (Al-Ani et al., 1985; Raymond et al., 1985). remained unexplained. Part of this variability may result from
The relationship between TT0 and TT50 and lipid content observed genetic differences in seed germination timing between seed popu-
here was valid for species over a large range of seed lipid contents, lations (e.g. Christal et al., 1997), but the main source of variability
varying from 3.5% (Fallopia convolvulus) to 43.6% (Papaver rhoeas). between seed lots is seed production conditions (Andersson and
This trait appears to be relatively constant in a given species. Indeed, Milberg, 1998; Luzuriaga et al., 2006; Swain et al., 2006), e.g. crop
the seed lipid contents measured here are similar to those reported sowing date, soil fertilization, or climatic conditions. The model
in the literature (Earle and Jones, 1962; Jones and Earle, 1966; resulting from our study could be improved by the study of other
Barclay and Earle, 1974). seed traits such as soluble sugar contents or seed coat characteris-
In contrast, no relationship was found with seed protein content. tics that control the entry of water into the seed during imbibition.
This characteristic was less contrasted than lipid content among the Such relationships could be used to estimate germination speed
species we studied. Moreover, total seed protein content strongly parameters for species that were not analysed in the present study.
depends on seed production conditions (Fawcett and Slife, 1978). Nor did we consider seasonal variations in base temperature within
For instance, we measured a seed protein content of 23% in Capsella a species associated with changes in dormancy in the present study,
bursa-pastoris, whereas values of 12% (Schroeder et al., 1974) and as we did not have sufficient data to use other values than a constant
33% (Jones and Earle, 1966) were reported in the literature. More- one. Such variations have been described only in a small num-
 A. Gardarin et al. / Ecological Modelling 222 (2011) 626–636 635

ber of species (Batlla and Benech-Arnold, 2007) and are difficult Bouwmeester, H.J., Karssen, C.M., 1992. The dual role of temperature in the regula-
to extrapolate to the wide range of weed species we studied. tion of the seasonal changes in dormancy and germination of seeds of Polygonum
persicaria L. Oecologia 90, 88–94.
The weed flora present in a particular field result from several Bouwmeester, H.J., Karssen, C.M., 1993. Seasonal periodicity in germination of seeds
factors linked with the cropping system in interaction with seed of Chenopodium album L. Ann. Bot. 72, 463–473.
germination. The date of seed germination, and then emergence, Bruckler, L., 1983a. Rôle des propriétés physiques du lit de semences sur l’imbibition
et la germination. I. Élaboration d’un modèle du système “terre-graine”.
is important for future crop-weed competition and the ability of Agronomie 3, 213–222.
the weed to replenish the seedbank. Relationships for predicting Bruckler, L., 1983b. Rôle des propriétés physiques du lit de semences sur l’imbibition
germination behaviour aimed at being integrated as part of a com- et la germination. II. Contrôle experimental d’un modèle d’imbibition des
semences et possibilités d’applications. Agronomie 3, 223–232.
prehensive weed dynamics model including many other life cycle Christal, A., Davies, D.H.K., Gardingen, P.R.v., Brown, K., 1997. Germination ecology
processes. Multi-species weed dynamics models could be used to of Stellaria media. Brighton crop protection conference: weeds. In: Proceedings
evaluate different crop management techniques, as well as to pre- of an International Conference, Brighton, UK, 17–20 November, pp. 485–490.
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dict the long-term shifts in weed flora resulting from modifications
blackgrass (Alopecurus myosuroides) germination and shoot elongation. Weed
in cropping systems in a large range of environmental conditions. Sci. 51, 708–717.
Colbach, N., Chauvel, B., Dürr, C., Richard, G., 2002. Effect of environmental conditions
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Colbach, N., Dürr, C., Roger-Estrade, J., Colbach, N., 2005. How to model the effects
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The present work was financed by INRA (Département Environ-
Colbach, N., Dürr, C., Roger-Estrade, J., Chauvel, B., Caneill, J., 2006. ALOMYSYS: mod-
nement et Agronomie) and the Region of Burgundy. The authors elling black-grass (Alopecurus myosuroides Huds.) germination and emergence,
are grateful to Hugues Busset, Émilie Cadet and Arnaud Coffin for in interaction with seed characteristics, tillage and soil climate—I. Construction.
their technical assistance, Christophe Salon and Anne-Lise Santoni Eur. J. Agric. 24, 95–112.
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(UMR LEG), Annick Matejicek (UMR BGA) and Lionel Bretillon and Appl. Ecol. 5, 675–683.
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the Station Nationale d’Essais des Semences and Vincent Murracciole not required for efficient soybean seed germination. J. Plant Physiol. 166,
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