Characterizing and predicting plant phenology in species-rich grasslands

Characterizing and predicting plant phenology inspecies-rich grasslands

P. Ansquer, R. Al Haj Khaled, P. Cruz, J.-P. Theau, O. Therond and M. Duru

UMR INRA-ENSAT 1248 AGIR, Castanet Tolosan, France

Abstract

The use of plant phenology for determining the timing

of management practices is poorly understood in

species-rich grasslands. The objectives were to assess

the effect of management practices on the dates at

which phenological stages occur and to compare

different methods of calculating the growing degree-

days in order to predict them. Dates at which pheno-

logical stages of plant species occurred were recorded

and plant strategy for resource capture and use was

assessed through measurements of the dry matter

content of leaves in two experiments in regions with

contrasting climatic conditions. In Experiment 1, con-

ducted near Toulouse, France, a set of 31 species was

sown in pure stands at two levels of N availability. In

Experiment 2, a network of 18 permanent grasslands,

located in the French Pyrenees, was studied. In both

experiments, the dry matter content of leaves, and

flowering and ripening times, were measured. In

Experiment 1, the dates on which a given phenological

stage occurred were correlated with one another, and

the grass species showed a significant ranking of dry

weight of leaves for these dates. In Experiment 2, the

difference between average flowering times of plant

communities was shown to be around 40 d and resulted

more from the species composition of the plant com-

munity than from their sensitivity to management

practices. Plant communities were significantly ranked

by dry weight of leaves for their flowering time. The

minimum and maximum base temperatures which

minimized the growing degree-days between the two

locations were 0 and 25�C, respectively, and the most

appropriate date from which to start to accumulate

temperatures was found to be 1 February.

Keywords: phenology, grass, dicotyledon, nitrogen,

cutting, grazing

Introduction

An accurate knowledge of the phenological progression

of species in plant communities is important for the

management of herbage resources (Lieth and Radford,

1971) because it governs the accumulation rate of

herbage. Indeed, knowledge of phenological stages of

the species that make up grassland communities are

needed to determine cutting and grazing management

to meet targets of herbage production and to manage the

population dynamics of desirable or undesirable species

(Manske, 1998). However, dates on which phenological

stages occur for species within species-rich grasslands

are not well understood. In addition, dates on which

phenological stages occur depend on prevailing envi-

ronmental conditions, especially temperature.

In temperate areas, sexual reproduction occurs in

spring for most grassland species. Three phenological

stages have been identified as the key to managing the

dynamics of growth and the demography of grassland

species: the start of stem elongation, flowering and seed

ripening. Removing the reproductive apices early in

spring by cutting or grazing induces vegetative re-

growth in most grass species (Gillet, 1980; Robson et al.,

1988). Because the reproductive component usually

represents the greatest part of the yield in temperate

grasslands, this practice decreases the annual herbage

production by reducing the number of stems in grasses

(Duru et al., 2002). This effect can vary in strength

according to the proportion of apices removed. Fur-

thermore, flowering coincides with the peak of biomass

production (Robson et al., 1988) after which the herb-

age mass tends to decrease. In the case of non-removal

of the apex in spring, late defoliation allows sexual

reproduction of grassland species. Populations of desir-

able and undesirable species, which depend exclusively

on sexual reproduction to maintain their populations,

can be limited according to whether hay-making occurs

before or after seed dispersal (Magda et al., 2003). Seed

Correspondence to: M. Duru, Institut National de la Recher-

che Agronomique UMR 1248 AGIR, Chemin de Borde

Rouge, BP 52627, 31326 Castanet Tolosan, France.

E-mail: [email protected]

Received 26 May 2008; revised 16 October 2008

doi: 10.1111/j.1365-2494.2008.00670.x � 2009 Blackwell Publishing Ltd. Grass and Forage Science, 64, 57–70 57

ripening can be considered a key stage, as it is easier to

measure than seed dispersal, and relevant in preventing

the reproduction of undesirable species.

Temperature is the most important factor influencing

the phenological stages of perennial plants. Air tem-

perature is used to determine growing degree-days

(GDD). Annual differences in flowering times are

usually associated with differences in average temper-

atures (Schemske et al., 1978). Fitter et al. (1995)

showed that high spring temperatures advanced flow-

ering by an average of 4 d �C)1. There is no consensus,

however, on a well-defined method for calculating the

average daily temperature for determining temperature

thresholds (base temperatures) or for the date on which

to start accumulating temperatures. Furthermore, it has

been reported that not all species have the same

response to variation in temperature (Fitter et al.,

1995).

Little is known about the direct effect of nutrients and

defoliation regimes on phenological stages for species-

rich grasslands. A study of two Mediterranean forbs has

shown that application of phosphorus advanced the

flowering time for about half the species studied

(Pagnotta et al., 1997), and nitrogen (N) application

did the same for annual grasses but had the opposite

effect on forbs (Cleland et al., 2004). Nevertheless, the

effect was less than 4 d. On the other hand, comparison

of grazed and ungrazed plots shows that grazing did not

influence the time of flowering and fruiting (Diaz et al.,

1994), and that grazing has a more significant effect on

the number of flower units than on flowering time

(Bergmeier and Matthas, 1996). In other respects,

management can have an indirect effect through

changes in the abundance of species with different

flowering times. Indeed, Sosebee and Weibe (1973)

showed that the dates, when species reach their

phenological stages, are related to plant growth rates

and the capture and use of nutrients. Because these

latter variables are correlated with leaf traits (Weiher

et al., 1999), it can be hypothesized that there is an

ecological basis to ranking species on the basis of the

dates at which phenological stages occur. Thus a leaf

trait may be used to understand the effect of manage-

ment practices on plant phenology at the community

level.

The objectives of this study were to assess the effect of

management practices (the direct effect of nutrient

availability or its indirect effect through changes in

species composition) on the dates at which phenological

stages occur and to predict them by comparing different

methods for calculating GDD. Two experiments were

undertaken in regions of contrasting climatic condi-

tions. One experiment, sited in the plains, was con-

ducted to compare pure stands of species with or

without N fertilizer and the other, in the mountains,

was conducted on a set of permanent grasslands

differing in their nutrient availability and defoliation

regime (grazing vs. cutting).

For the first objective, three questions were ad-

dressed: (a) Is there an effect of N availability on

flowering and ripening times for grasses and dicotyle-

donous species and on the time of reaching a stem

height of 10 cm for grasses? (b) Are there significant

relationships between plant phenology and dry matter

content of leaf (LDMC) in order that it can be

considered to be a good predictor of plant strategy for

resource use? (Wilson et al., 1999) and (c) Is such a

relationship also found at the plant community level?

For the second objective, there were two questions: (d)

Are the different phenological stages linked to each

other? and (e) Can the flowering stages of a species be

predicted using the same method of calculating GDD at

any location?

Questions (a), (b) and (d) were examined in Exper-

iment 1 with species growing in pure stands. Questions

(a) and (c) were examined in Experiment 2, which

included a set of permanent grasslands composed

mainly of species studied in Experiment 1. To answer

question (e), the species ranking between the two

experiments was compared. Methodological aspects and

practical implications are also considered.

Materials and methods

Experiment 1

Experimental design

Experiment 1 was a small-plot experiment of thirty-one

monocultures of grass and dicotyledonous species car-

ried out at the Toulouse Research Centre of INRA,

France (43�5¢N, l1�43¢E, 150 m a.s.l.). The soil is a

fluvisol developed on alluvial sediments, a tertiary

deposit from the Pyrenees (Al Haj Khaled, 2005). Mean

annual temperature is 13�C and mean annual rainfall is

700 mm.

Nineteen grass and twelve dicotyledonous species

(Table 1) were sown in pure stands on 27 October 2000

in a randomized block design, with three replicates. The

species were chosen according to their significant

contribution to the biomass of permanent grasslands

in the Pyrenees. The seeds of all the species were

collected in their native habitat in the Central Pyrenees

(Erce valley; 42�51¢N, 1�17¢E, 600–1000 m a.s.l.; see

Experiment 2). For each species, seeds collected in

different grasslands were pooled together before being

sown in Experiment 1. Each plot consisted of eight rows

(1Æ2 m long and 15 cm apart). Each species was grown

with two levels of nitrogen (N) supply, denoted N0 and

N1, respectively, with three replications. The N

58 P. Ansquer et al.

� 2009 Blackwell Publishing Ltd. Grass and Forage Science, 64, 57–70

https://www.researchgate.net/publication/233574915_Grazing_and_the_Phenology_of_Flowering_and_Fruiting_in_a_Montane_Grassland_in_Argentina_A_Niche_Approach?el=1_x_8&enrichId=rgreq-224ceebf5fe8c827c2518afc36904512-XXX&enrichSource=Y292ZXJQYWdlOzIyNzc1Mzk4MDtBUzo5NzQ0OTAxNjI5OTUzNEAxNDAwMjQ1MDY0NjU2


https://www.researchgate.net/publication/233574904_Grazing_and_the_phenology_of_flowering_and_fruiting_in_a_montane_grassland_in_Argentina_A_niche_approach?el=1_x_8&enrichId=rgreq-224ceebf5fe8c827c2518afc36904512-XXX&enrichSource=Y292ZXJQYWdlOzIyNzc1Mzk4MDtBUzo5NzQ0OTAxNjI5OTUzNEAxNDAwMjQ1MDY0NjU2


Table 1 Leaf dry matter content in treatment N1 of Experiment 1 and phenological stages for the studied species in Experiments 1

and 2.

Abbreviation

Leaf dry matter

content (g kg)1)

in Experiment 1†

Flowering date

(Julian days)Ripening date

(Julian days)

Experiment 1 Experiment 2 Experiment 1 Experiment 2

Grasses

Agrostis capillaris L. AGR 242 175 183 187 233

Anthoxanthum

odoratum L.

ANT 222 95 112 124 187

Arrhenatherum

elatius(L.) Beauv.

ARR 218 137 160 165 204

Avenula pubescens

(Huds.) Dumort

AVE 250 161 x 168 x

Brachypodium

pinnatum(L.) Beauv.

BRAP 313 161 x 191 x

Brachypodium

sylvaticum

(Huds.) Beauv.

BRASYL 286 175 x 204 x

Briza media L. BRI 274 145 161 171 207

Cynosurus cristatus L. CYN 280 130 159 150

Dactylis glomerata L. DACT 225 133 150 151 199

Deschampsia cespitosa

(L.) Beauv.

DESC 266 175 x 204 x

Festuca arundinacea

Schreb.

FETARU 221 149 157 162 230

Festuca ovina L. FETOVI 257 149 x 161 x

Festuca rubra L. FETRU 245 133 157 157 206

Holcus lanatus L. HOL 198 130 152 150 196

Lolium perenne L. LOL 196 140 150 157 197

Molinia caerulea L.

(Moench)

MOL 301 171 197 204 311

Phleum pratense L. PHL 245 174 179 200 268

Poa trivialis L. POATRI 221 142 149 157 199

Trisetum flavescens (L.)

Beauv

TRI 241 157 163 200 236

Dicotyledons

Achillea millefolium L. ACH 161 161 160 221 268

Centaurea nigra L. CEN 139 115 135 180 219

Chaerophyllum aureum L. CHAR 232 128 135 156 214

Crepis biennis L. CREP 127 131 134 155 184

Heracleum sphondylium L. HER 204 145 155 153 193

Picris hieracioides L. PIC 153 84 99 91 214

Plantago lanceolata L. PLA 156 130 142 159 198

Ranunculus acris L. RANA 208 124 126 155 205

Rhinanthus minor L. RHI 180 98 126 140 191

Rumex acetosa L. RUA 125 104 140 154 186

Rumex obtusifolius L.

ssp. pyrenaicum

(Lamarck)

RUO 167 80 95 155 206

† treatment N1, i.e. non-limiting nitrogen nutrition.

x, Species not found in Experiment 2.

Plant phenology of species-rich grasslands 59


applications were 120 and 40 kg ha)1 in the summer of

2001, 150 and 0 kg ha)1 in the spring of 2002, and 120

and 0 kg ha)1 in the autumn of 2002 for levels N1 and

N0 respectively. The level N1 is considered to be non-

limiting for growth and represents a constant and

reproducible standard used as a control treatment in

field experiments (Al Haj Khaled et al., 2005). All the

treatment plots received 150 kg P (CaHPO4) ha)1 year)1

and 150 kg K (KCl) ha)1 year)1. Plots were irrigated

with a sprinkler system in order to maintain soil

moisture close to field capacity on the basis of weekly

calculation of the balance between rainfall and evapo-

transpiration. Soil and plant analyses showed that the

plants did not suffer any limitation in phosphorus,

potassium or water (data not shown). All the plots were

weeded by hand. In 2002, the average daily tempera-

tures from 1 January to 16 March and 21 July (the

latter two dates being when plants were 10 cm high and

were ripening, respectively – observed on the earliest

species) were 7Æ7�C and 12Æ7�C respectively. Daily

minimum and maximum air temperatures are given

in Figure 1.

Plant sampling and measurements

The first stage studied was the ‘10-cm stem’ (R10). This

stage was monitored in 2002 on the nineteen grass

species, whereas those stages of flowering and seed

ripening were observed on all thirty-one species. Tillers

were monitored from 12 March to 10 June 2002. Twice

weekly, fifteen tillers per species (five per replicate) and

per level of N were harvested by cutting at ground level.

After dissection of the tiller, the height of the apex was

measured from the cutting level (ground level) to the

bottom of the reproductive apex. A stage was reached

when a proportion of 0Æ50 of apices of harvested tillers

achieved a height of 10 cm. The date at which the R10

stage was reached was estimated for each grass species

by linear interpolation of recorded data for the height of

the apex. Flowering and seed ripening were monitored

on the plots and were noted when 0Æ50 of all the

reproductive tillers of the population reached these

stages.

The ratio of leaf dry mass to fresh mass of leaf

saturated in water, termed ‘LDMC’ (expressed in

mg g)1) was measured during three growth cycles

corresponding to three different seasons (spring, sum-

mer and autumn) as described in more detail by Al Haj

Khaled et al. (2005), following the protocol described by

Garnier et al. (2001) and Cornelissen et al. (2003). The

last fully expanded leaf (i.e. the youngest adult leaf)

was cut between 10:00 and 16:00 hours, and measure-

ments were made once the leaf had become saturated

in water.

Data analysis

Analysis of variance (ANOVAANOVA) of the effects of N on

the phenological stages was conducted using a general

linear model followed by a least significant difference

test of mean values, using SPSS 10Æ0 for Windows

(SPSS Inc., Chicago, IL, USA). All the data were

log-transformed to meet the normality criterion

required for the ANOVAANOVA. The Spearman rank test

was performed to compare the similarity of the

species rankings established between levels of N for

phenological stages and LDMC values. Data analysis

on phenological stages was carried out on separate

growth forms of grass and dicotyledonous species

as proposed by Al Haj Khaled et al. (2005) on the

basis of their differing LDMC values at the vegetative

stage.

–10

–5

0

5

10

15

20

25

30

35

1/1

11/1

21/1

31/1

10/2

20/2 2/

312

/322

/3 1/4

11/4

21/4 1/

511

/521

/531

/510

/620

/630

/610

/720

/7

Date

Dai

ly t

emp

erat

ure

(°C

)

Figure 1 Daily minimum (open symbols) and maximum temperatures (full symbols), averaged at a scale of 10 d for Auzeville

(square) and Erce (circle).



Experiment 2

Experimental design

A network of grassland communities was subjected to

different management practices and the network was

located in the area where the seeds were harvested for

Experiment 1. The experimental design consisted of a

set of eighteen grassland communities sampled on four

livestock farms in the Pyrenees in the Erce valley (see

Experiment 1). Substrate types varied from alluvium in

the bottom of the valley to shale or granite on the

slopes. Mean annual temperature was 10�C and annual

rainfall was 1080 mm (mean values of 5 years). Daily

minimum and maximum air temperatures measured at

650 m a.s.l. are given in Figure 1. During the experi-

ment, it was verified that there was no difference with

measurements made at 950 m a.s.l. The eighteen

grassland communities were chosen to represent the

field diversity in terms of defoliation management

(grazing and ⁄ or cutting) and nutrient availability.

There were three defoliation regimes combined with

two levels of fertility assessed empirically through

fertilizer management practices applied and the nutri-

ent index estimated in the previous year. The higher

and lower levels of fertility were denoted 1 and 0

respectively. The defoliation regimes were meadows

(treatments M0 and M1) mowed twice a year (first cut

on day 174 of the year on average) then grazed in

autumn, meadows (treatments GM0 and GM1) grazed

in spring (at day 107 of the year on average) then cut,

and pastures (treatments P0 and P1) which were only

grazed on day 132 of the year on average for the first

time (Appendix Table 1). Each treatment was replicated

three times (three different paddocks). Within each

paddock, a 35-m2 plot was fenced off to make all the

plant measurements.

Plant sampling and measurements

The biomass was evaluated by harvesting ten quadrats

(0Æ25 m · 0Æ75 m) to ground level at the peak of

biomass production (end of spring). All the biomass

samples from the same community were pooled and all

the different species were identified and separated. The

floristic composition of each community was obtained

from the list of species and their relative specific

abundance corresponds to their oven-dry mass divided

by the total sampled dry biomass. All the studied

grasslands were dominated by grass species (minimum

0Æ40 of the total standing biomass). The most frequent

species were Holcus lanatus L., Dactylis glomerata L. and

Lolium perenne L. (see Appendix Table 1 for more

details). In most of the grasslands (fifteen of eighteen),

the dominant species was a grass species. Nine grass and

seven forb species represented the pool of dominant

species in the set of studied grasslands (contributing

between 0Æ40 and 0Æ90 of the total biomass; see

Appendix Table 1).

Traits and phenological stages were measured on

each species, contributing at least 0Æ80 of the total

biomass in each community. For all the treatments,

measurements were made on sixty species (including

nineteen grass species). Measurements of LDMC were

made following the same protocol as in Experiment 1

and species were sampled during the vegetative period,

i.e. from mid-April to mid-May. The identified species

were monitored once a week to estimate the different

phenological stages. Flowering and seed-ripening stages

were determined when about 0Æ10 of each population

reached the peak of these stages (i.e. more than 0Æ50 of

the flowers being at the anthesis stage). Mean commu-

nity values (leaf and phenological traits) were calcu-

lated by weighting each specific trait value by the

corresponding specific abundance (Garnier et al., 2004).

Assessment of management practices

Nutrient availability was assessed through plant nutri-

ent indices. This method allows the nutrient availability

for plant growth to be assessed more rigorously than

from fertilizer management practices (Lemaire and

Gastal, 1997). These indices concern N (NNi) and

phosphorus (NPi). NNi was calculated as the ratio

between the actual N concentration in the plant (Na,

expressed as a percentage) and the critical N concen-

tration in the plant (Nc, expressed as a percentage)

which corresponds to: Nc = 4Æ8 (DM))0Æ32 (DM in

t ha)1) as reported by Lemaire and Gastal (1997). NPi

was computed as proposed by Duru and Ducrocq

(1997). In order to compare the eight plant communi-

ties for their nutrient status, an average index (Ni) was

calculated with the values of these two indices accord-

ing to Duru and Ducrocq (1997). A value of Ni = 1

means that herbage growth is not limited by nutrients.

The defoliation regimes were assessed through the yield

ratio [difference in herbage mass before and after

cutting (or grazing) ⁄ herbage mass before cutting (or

grazing)], averaged over the two or three cuts (or

grazings) of the growing season.

Data analysis

Because the herbage utilization rate, the nutrient

availability, the altitude and aspect (through their effect

on temperature) can have an effect on a plant trait,

which can be direct or indirect, through differences in

the abundance of the different species, two methodo-

logical approaches were used. To assess a direct effect,

treatments were paired in order to differ by only one of



the three factors and to obtain the greatest number of

common species: M1 and GM1 to assess the effect of

altitude and aspect; GM1 and P1 for herbage utilization

rate, and P1 and P0 for nutrient availability. Then an

ANOVAANOVA was performed at the species level within each

pair to study if there was a difference in flowering time

for species which was common to both treatments.

These comparisons were also made at a plant commu-

nity level for the flowering date of grasses, the aggre-

gated LDMC and the plant functional type.

To assess the distribution of flowering times within a

plant community, a functional diversity index (FD) was

calculated (Mason et al., 2003):

FD ¼ ð2=pÞ � arctan 5V

V ¼XN 0

i¼1

wi � ðln xi � ln �xÞ2 and ln �x ¼XN 0

i¼1

wi � ln xi

where xi is the flowering time for the species i.

Calculation of GDD

Two methods were used to calculate GDD as suggested

in the literature (McMaster and Wilhelm, 1997).

GDD = [Tmax ) Tmin) ⁄ 2 ) Tbase]:

• method 1 (thresholds defined for the mean daily

temperature): (Tmax ) Tmin) ⁄ 2 = Tbase_min or

Tbase_max if (Tmax + Tmin) ⁄ 2 < Tbase_min or >Tbase_max

respectively;

• method 2 (thresholds defined for the minimum and

the maximum daily temperature): Tmin = Tbase_min

and Tmax = Tbase if Tmin < Tbase_min or Tmax >

Tbase_ max respectively.

Based on Otto et al. (2007), several values of Tbase_min

(0, 2Æ5 and 5�C) for both methods, and Tbase_max (16, 18

and 20�C) and (20, 22Æ5 and 25�C) for methods 1 and 2,

respectively, and several dates for initializing GDD,

from 1 January to 1 March, were tested to calculate

GDD and to compare them for both locations (L):

GDDL1 = aGDDL2 + b. Then, these results were used to

find those resulting in a = 1 and b = 0.

Results

Experiment 1 – phenology of species growing inpure stands

Rankings of species for different phenological stages

were compared under standard conditions, i.e. in non-

limiting growth conditions (treatment N1). Rankings of

grass species, based on the start of stem elongation

(R10), were significantly correlated with those based on

flowering (r = 0Æ54; P £ 0Æ05, n = 19) and ripening

times (r = 0Æ65; P £ 0Æ01) (Figure 2). Rankings of

species between flowering and ripening stages were

also similar for all the groups of species studied

(P £ 0Æ001). Moreover, flowering and ripening stages

were strongly correlated when considering growth

forms separately (r = 0Æ92 for grass species; r = 0Æ78

for dicotyledonous species) or for all the species

(r = 0Æ93; n = 31).

Flowering dates ranged from day 80 (Taraxacum

officinalis L.) to day 175 (Agrostis capillaris L., Brachypo-

dium sylvaticum L. and Molinia caerulea L.) in the year

(Table 1). For the set of species studied, dicotyledonous

species flowered significantly earlier than grasses

(P £ 0Æ001).

For grass species, there were no significant effects of

N availability at the flowering and ripening stages. The

R10 stage, however, was significantly advanced (10 d

on average) in conditions of higher N availability

(P £ 0Æ01, n = 19). Average days in the year (s.e.m.)

were 112 (20) d (i.e. 22 April) and 122 (18) d (i.e. 2

May) for treatments N1 and N0 respectively. The effect

of N depended on the species. The highest variation was

observed for H. lanatus and the lowest for Deschampsia

cespitosa L. and Festuca rubra L. For grass species, the R10

dates were spread over around 2 months on treatment

N1 (P £ 0Æ001, n = 19; Figure 2). Although the date of

the R10 stage was delayed on treatment N0, the species

ranking was quite similar (r = 0Æ76; P £ 0Æ001; n = 19)

between the two N treatments.

Dates on which each of the three phenological stages

(R10, flowering and ripening) occurred for grass species

were significantly correlated with LDMC (Table 2). An

increase in LDMC of 100 g kg)1 delayed dates at which

0

50

100

150

200

250

150 200 250 300 350LDMC (g kg-1)

Day

of

the

year

Figure 2 Experiment 1 (pure stands): relationships between

Julian days (Y) and leaf dry matter content (X, g kg)1) for

phenological stages of grass species – start of stem elongation

with apex height of 10 cm [d; Y = 0Æ46X + 56 (R2 = 0Æ44)],

flowering [h; Y = 0Æ32X + 72 (R2 = 0Æ32)] and ripening

[j; Y = 0Æ51X ) 13 (R2 = 0Æ68)] at the high level of nitrogen

supply (N1).



phenological stages occurred by around 32 d (flowering

stage) up to 51 d (R10 and ripening stages) (see

equation, Figure 2).

Experiment 2 – phenology of species growingin plant communities in their naturalenvironment

Comparison of life forms for their phenological stages

A correlation was found between the flowering dates of

grass and dicotyledonous species co-existing in the

same plant community (r2 = 0Æ62). Dicotyledonous

species flowered earlier than grass species and this

difference was greater at earlier flowering dates (Fig-

ure 3). This trend was due to the flowering dates of

grasses which flowered early (between days 150 and

155: D. glomerata, H. lanatus and L. perenne) being

correlated with those of dicotyledonous species (Rumex

acetosa L., Chaerophyllum aureum L., Trifolium pratense

and Trifolium repens L.), which flowered between day

125 and 140, while grass species which flowered later

(between days 157 and 180: A. capillaris and F. rubra)

were correlated with dicotyledonous plants which

flowered at almost the same time (Leontodon hispidus,

Stellaria graminea L. and Knautia arvensis L.). On the

other hand, the species which deviated most from the

average were never abundant.

Ripening and flowering dates were also significantly

correlated for grass and dicotyledonous species when

taking the average value for each species of the six

treatments (Figure 4). Correlations for grass and dicot-

yledonous species were 0Æ53 (n = 17) and 0Æ68

(n = 38) respectively. Grass species [day 158 (18) in

year] flowered on average later than dicotyledonous

species [137 (24) in year] but the ripening stage

occurred at the same time for grass species [day 215

(32) in year] and dicotyledonous species [day 215 (27)

in year].

Effects of plant nutrient status, utilization rate and

environment variables

Four of the six treatments that differed by only one

factor: altitude and aspect (treatments M1 and GM1),

herbage utilization rate (treatments GM1 and P1),

nutrient availability (treatments P1 and P0) were

selected (Table 3). At the level of the species, there

was only an effect of altitude and aspect for three

species among ten comparisons and there was no effect

Table 2 Correlations (r and probability thresholds from

Spearman rank test) between leaf dry-matter content (LDMC)

and phenological stages for separate growth forms (grass and

dicotyledonous species) or for all species in Experiment 1 (pure

stands in non-limiting growth conditions). R10 is the date at

which the reproductive apex reaches 10 cm in height (n is the

number of studied species).

Growth form Plant stages n LDMC

Grasses R10 19 0Æ80***

Flowering 0Æ57*

Ripening 0Æ63**

Dicotyledons Flowering 12 0Æ14 NS

Ripening 0Æ07 NS

All species Flowering 31 0Æ58**

Ripening 0Æ51**

NS, not significant; *, P £ 0Æ05; **, P £ 0Æ01; ***, P £ 0Æ001.

110

130

150

170

190

110 130 150 170 190Flowering time (DOY) of dicotyledons

Flo

wer

ing

tim

e (D

OY

) fo

r g

rass

es

Figure 3 Experiment 2: relationship between flowering times

(Julian days) of grass and dicotyledonous species (R2 ) 0Æ62***)

at the plant community level for meadows (j), grazed

meadows ( ) and pastures (h).

0

50

100

150

200

250

300

350

0 50 100 150 200 250

Flowering date (DOY)

Rip

peni

ng d

ate

(DO

Y)

Figure 4 Experiment 2: relationship at the species level

between dates (DOY: day of the year) at which flowering and

ripening stages occurred for grass (j, R2 = 0Æ68***) and

dicotyledonous (h, R2 = 0Æ53**) species; data of each species

were averaged between treatments.



of nutrient availability and herbage utilization rate. This

means that differences in flowering time at the level of

the plant community would be mainly due to the

species composition of the plant community rather than

due to variation in management practices or abiotic

conditions. At the level of the plant community, the

weighted flowering dates of grasses occurred from day

153 up to day 174 in the year for the four treatments.

There was a significant difference in flowering dates

between treatments, except between treatments GM1

and M1. The treatments were ranked in the same way

for LDMC (Table 3). Considering all the six treatments,

there was a significant correlation (r2 = 0Æ79) between

the weighted flowering times and the LDMC, weighted

for grass species (Figure 5).

The spread of flowering dates, assessed through the

functional diversity index for flowering time (FD), was

significantly negatively correlated (r = 0Æ61, P < 0Æ01)

with the plant nutrient status. It was greatest for the

treatment having the lowest plant nutrient status for both

grass species as well all the species (Table 3). Including

the dicotyledonous species greatly broadened the range

of dates when plants flowered. To illustrate what FD

represents, two examples, indicating the proportion of

species that flowered over a period of 15 d, are given. For

an FD of 0Æ03 (grassland Rives: see Appendix Table 1),

0Æ93 flowered between 15 May and 1 June, and 0Æ07

between 15 June and 1 July; for an FD of 0Æ31 (grassland

Routies), the values were 0Æ28 between 15 May and 1

June, 0Æ24 between 1 June and 15 June, 0Æ08 between 15

June and 1 July, and 0Æ40 between 15 July and 1 August.

Comparison of flowering dates between thetwo experiments

On the basis of data given in Table 1, flowering dates of

those species which were studied in pure stands

(Experiment 1) were compared with those found in

plant communities (Experiment 2). A high correlation

was observed for grass (r2 = 0Æ91, n = 11, P < 0Æ001)

and dicotyledonous species (r2 = 0Æ83, n = 9,

Table 3 Effect of treatments at species and plant community levels for four of the six treatments that differed by only one

factor: altitude and aspect (treatments M1 and GM1), herbage utilization rate (treatments GM1 and P1), nutrient availability

(treatments P1 and P0) for flowering date as influenced by altitude and aspect, herbage utilization rate and plant nutrient status

at a species level and flowering date, functional diversity index and leaf dry matter content (LDMC) in Experiment 2.

Treatments

M1 GM1 P1 P0

Characterization of treatments

Herbage utilization rate 0Æ76a 0Æ72a 0Æ50b 0Æ48b

Plant nutrient index 0Æ67a 0Æ71a 0Æ74a 0Æ56b

Altitude (m) – aspect‡ 600-BV 900 S-W 1000 S-W 1000 S-W

Flowering date (days of year) at species level

Altitude and aspect (n = 10)† 131 136

Herbage utilisation rate (n = 10)§ 137 141

Plant nutrient status (n = 9)§ 161 174

At plant community level (grasses)

Flowering dates (DOY) (aggregated value) 153c 152c 161b 174a

Functional diversity index for flowering time 0Æ05b 0Æ02b 0Æ05b 0Æ14a

LDMC (g kg)1) (aggregated value) 203c 200c 217b 234a

†Significant differences for three species among ten species.

‡S-W: south-west-facing slope; BV: bottom of valley; n: number of species compared (grass or dicotyledonous species).

§No significant differences.

Values with the same letter in a row are not significantly different at P < 0Æ05.

140

150

160

170

180

190

190 210 230 250LDMC (g kg-1)

Flo

wer

ing

time

(DO

Y)

Figure 5 Relationship between flowering time (Julian days)

and leaf dry matter content (LDMC) (R2 = 0Æ79***) for grass

species in meadows (j), grazed meadows ( ) and pastures

(h).



P < 0Æ001), and for all species (r2 = 0Æ90) (Figure 6a).

Species flowered earlier in Experiment 1 because of its

lower altitude. The same trend was found for the

ripening stage (data not shown). When using method 1

for calculating GDD [with (Tmax ) Tmin) ⁄ 2 = 0 and

18�C if (Tmax + Tmin) ⁄ 2 < Tbase_min and >Tbase_max

respectively], GDD were on average lower for Experi-

ment 2, and the correlation with flowering date was not

increased (Figure 6b): r2 was lower (0Æ84), the slope

was very different from 1; only the intercept was lower

for a Tbase_min daily temperature of 1. Considering

Tbase_min or Tbase_max and other dates for starting the

calculation of GDD had little effect on the results.

Method 2 gave a higher r2 value (0Æ95) and the method

made it possible to find a value of Tbase_max giving a

slope of 1, and a Tbase_min and starting date of GDD to

make the intercept 0. For the former, a value of 24Æ5�Cwas found, and, for the latter, it depended on a

combination of dates and Tbase_min (Figure 7).

Discussion

Relationships between the differentphenological stages

The sequence and timing of flowering and seed ripening

seem to be developmentally fixed within the life cycle

of an individual (Rathcke and Lacey, 1985). This could

explain why the flowering and ripening times are

advanced when the stem elongation starts earlier.

Nutrient availability, as provided by the contrasting N

treatments in Experiment 1 and large differences in

plant nutrient indices in Experiment 2, did not lead to

significant differences in flowering and ripening times,

in agreement with previous observations (Dickinson

and Dodd, 1976). Sensitivity of the start of stem

elongation to growing conditions, particularly N avail-

ability, could be explained by the fact that stem

elongation is both a growth and a development stage

(Gillet, 1980; Duru et al., 2000). The results show that

the species ranking was similar among the different

phenological stages of species growing in pure stands

(Experiment 1) and those growing in plant communi-

ties (Experiment 2, Figure 6a). This was also true for

the R10 of grasses (Experiment 1).

Consequently, making observations at the flowering

stage gives relevant information on the other stages, at

least for the species studied. Notwithstanding the

stability of species ranking for their phenological stages,

a high variability in the interval between R10 and

flowering stages, according to N availability, was found.

In other words, greater differences in the time needed

to reach the R10 stage (Figure 2) can be expected in

Experiment 2 (grassland communities) than in Exper-

iment 1 (pure stands). Indeed, high N-fertilizer

50

100

150

200

50 100 150 200Flowering time (DOY) in Experiment 1

Flo

wer

ing

tim

e (D

OY

)in

Exp

erim

ent

2

0

500

1000

1500

2000

2500

0 500 1000 1500 2000 2500Flowering time (GDD) in Experiment 1

Flo

wer

ing

tim

e (G

DD

)in

Exp

erim

ent

2

(a)

(b)

Figure 6 Relationships between (a) flowering times ex-

pressed in Julian days for a set of species growing in pure stands

(Experiment 1, Y) and in plant communities (X, Experiment 2)

[Y = 0Æ88X + 31Æ3 (R2 = 0Æ90***)] and (b) flowering times

expressed in growing degree-days for a set of species growing

in pure stands (Y, Experiment 1) and in plant communities (X,

Experiment 2) [Y = 0Æ84X + 113 (R2 = 0Æ84***)]; grass (j)

and dicotyledonous (h) species; dotted line is 1:1 line.

–200–150–100–50

050

100150200

1/1 11/1 21/1 31/1 10/2 20/2 1/3

Date

Gro

win

g d

egre

e-d

ays

Figure 7 Simulations used to determine the temperature

Tbase_min and the date for initializing the temperature sum.

Curves represent the intercept of the equation GDDAuz =

aGDDErce + b according to day of the year where Auz and

Erce are the two locations used for detemining growing

degree-days (GDD) to reach flowering times of a set of

species; curves were established for Tbase_min = 0�C (d), 2Æ5�C(m) and 5�C (j). GDD was fitted using third-order polynomial

functions.



application rates were applied in Experiment 1 so that

species had a similar nutrient status. On the other hand,

there was a wide range in plant nutrient status between

grassland communities (Experiment 2). In the latter,

species having high LDMC values were mostly pre-

valent in low fertility grasslands as reported by Duru

et al. (2005) and Wilson et al. (1999).

Predicting phenology using a thermal time-scale

Expressing the flowering times in GDD instead of Julian

days provided a satisfactory way of calculating them.

Comparison of the two locations revealed that the

method of calculation for the date for initializing GDD

and the Tbase_min and Tbase_max values gave the same

GDD for 26 species. Better results were found when

calculating the Tbase before computing the average daily

temperature, with a starting date of 1 February and

when Tbase_min and Tbase_max were around 0�C and 25�Crespectively.

The date of 1 February (northern hemisphere) was

found by Peacock (1976) as the approximate date at

which there is a change in assimilate allocation for

grasses, which is probably related to change in day-

length. Furthermore, it is approximately the date which

minimizes the year-to-year variability in GDD for a

given phenological stage for a large range of species

(Sparks et al., 2000). An air temperature of 25�C was

found to be best for Tbase_max, and this has also been

found to be the same for photosynthesis (Woledge,

1979). In spite of these encouraging results, more data

are required to validate them.

Convergence in plant traits between plantfunctional groups

A significant difference in the timing of flowering

between grass and dicotyledonous species was found, as

reported previously (Negi et al., 1992). The earliest

flowering dates usually observed for dicotyledonous

species increased the spread of these dates for a plant

community, especially when it was composed of early-

flowering grass species. It was shown clearly, however,

that there is a similarity between grass and dicotyle-

donous species within a given community (Figure 2a);

e.g. D. glomerata and H. lanatus with Rumex acetosa L. for

plots having low LDMC values, F. rubra and A. capillaris

with Centaurea nigra L. and Picris hieracioides L. for plots

having high LDMC values. This means that in the

grasslands studied, defoliation regime and nutrient

availability acted as strong filters that impose very

similar plant traits which determine specific local

community structure and composition (Holdaway and

Sparrow, 2006). Consequently, for each combination of

environmental factors, there is group of species with

similar traits that tend to occur together more often

than would be expected by chance.

The convergence in plant traits between plant func-

tional groups within a plant community in response to

ecological gradients is in agreement with the conver-

gence observed previously for agronomic characteris-

tics. The similarity found between grass and

dicotyledonous species within a set of plant communi-

ties for leaf:stem ratio (Calviere and Duru, 1999) and

digestibility of plant parts (Duru, 1997) means that the

plant traits studied are relevant as ‘response and effect’

traits (Hooper et al., 2002). Although a genotype effect

upon the phonological stages cannot be excluded, it can

be assumed to be low because the same species were

found in the same valley over the range of altitudes

studied.

Factors affecting the dates at whichphenological stages occurred in plantcommunities

The results showed that there were large differences in

flowering time (up to 40 d: Figure 4) between plant

communities in relation to management practices

because of defoliation and nutrient availability. These

differences resulted clearly from the species composi-

tion of the plant community and not from a direct effect

of management on the flowering time of the species.

Indeed, enhancing nutrient availability favours species

having a strategy of resource capture, i.e. low LDMC

values (Weiher et al., 1999), which are those having the

earliest plant phenology (Experiment 1). In the condi-

tions of this study, where a part of each plot was fenced,

defoliation practices would only have had a slight effect

on the flowering time of a given species, as observed

elsewhere (Bergmeier and Matthas, 1996). On the

other hand, high utilization rates of herbage favour

species also having a resource-capture strategy. The

range of environmental conditions encountered in

Experiment 2 (aspect and altitude) was not wide

enough to lead to differences in flowering time

although it is known that the reproductive phase can

be slightly modified by temperature (Humphreys et al.,

2006). These findings were in agreement with Louault

et al. (2005) who found that plots with one grazing

event per year, when compared with four grazing

events and one cutting event, were dominated by one

plant type that is strongly competitive for light and has

a lower LDMC value. The results of this study strength-

en the view that phenological stages are related to plant

strategy (c.f. Sosebee and Weibe, 1973) for resource

capture and resource use, assessed through LDMC

values (Wilson et al., 1999). This was found both at

the level of the plant species (Experiment 1) and of the



https://www.researchgate.net/publication/230361368_Leaf_and_Stem_In_Vitro_Digestibility_for_Grasses_and_Dicotyledons_of_Meadow_Plant_Communities_in_Spring?el=1_x_8&enrichId=rgreq-224ceebf5fe8c827c2518afc36904512-XXX&enrichSource=Y292ZXJQYWdlOzIyNzc1Mzk4MDtBUzo5NzQ0OTAxNjI5OTUzNEAxNDAwMjQ1MDY0NjU2

plant community (weighted trait) (Experiment 2). For

grasses growing in pure stands, this correlation was

particularly strong at the start of stem elongation.

Management implications

Examining the relationships between phenological

stages and plant strategies for resource capture and

use through LDMC values showed how this foliar trait

responds to changes in management practices in two

ways, i.e. by delaying or advancing the dates on which

phenological stages occur, and by spreading out these

dates for the different species that make up a plant

community. In this way, any practice that will decrease

LDMC values will advance the dates at which pheno-

logical stages occur. This could be due to an increase in

nutrient availability as well as an increase in herbage

removal rate. Such management practices favour plant

communities composed of fast-growing species (Werger

et al., 2002) which can compete very successfully for

light (Weiher et al., 1999). As previously reported, the

phenological stages of the different species in species-

rich plant communities are spread out over time (Henry

et al., 2001; Quin et al., 2003) (Table 2). There is,

however, generally a phenological peak (Martinkova

et al., 2002). Nevertheless, the results show that the

magnitude of the peak depends on nutrient resources.

In this way, increasing nutrient availability reduced the

spread of flowering times within a plant community.

The results provide useful information for guiding

defoliation practices at each of the three key phenolog-

ical stages. The start of stem elongation, which is

probably related to photoperiod, is a key variable,

because defoliation after this stage leads to a leafy

regrowth with a slower herbage growth rate than for

reproductive growth (Duru et al., 2002; Magda et al.,

2003). The results indicate that the current manage-

ment of meadows, grazed on average on day 107 of the

year (around 580 GDD), results in the suppression of

most of the grass apices (day 88 of the year at Auzeville;

Figure 2), because these grasslands are composed of

grass species which usually have a low LDMC value.

Flowering occurs shortly before the achievement of

ceiling yield (Robson et al., 1988) so that delaying cutting

until after this time will also delay regrowth and decrease

herbage quality without increasing the dry matter yield.

In this way, the meadows, which were composed mainly

of D. glomerata, H. lanatus and L. perenne, were on average

cut on day 174 of the year, i.e. more than 20 d after

flowering (see Appendix Table 1).

Control of undesirable species by limiting seed dis-

persal can be achieved by choosing a critical period to

cut for hay using knowledge of this phenological stage.

For example it was observed that meadows containing

species such as R. acetosa and C. aureum, which are

regarded as injurious weed species, were sometimes cut

after the seed-ripening stage of these species.

Acknowledgments

This text was part of Work Package 5 of the EU project

VISTA (Vulnerability of Ecosystem Services to Land Use

Change in Traditional Agricultural Landscapes) (Con-

tract n�EVK2-2001-15 000356).

References

ALL HAJAJ KHALEDHALED R. (2005) L’evaluation des caracteristiques

agronomiques d’especes par leurs traits de vie comme etape

prealable au diagnostic des communautes a flore complexe

(Evaluation of the agronomic characteristics of species from

their life-history traits in complex plant communities). Ph.D.

thesis, Nancy: INPL.

ALL HAJAJ KHALEDHALED R., DURUURU M., THEAUHEAU J.P., PLANTUR EUXLANTUREUX S.

and CRUZRUZ P. (2005) Variation of leaf traits through

seasons and N availability levels and its consequences for

ranking grassland species. Journal of Vegetation Science, 16,

391–398.

BERGMEIERE RGMEI ER E. and MATTHASATTHAS U. (1996) Quantitative

studies of phenology and early effects of no grazing in

Cretan phrygana vegetation. Journal of Vegetation Science,

7, 229–236.

CALVI EREALVI E RE I. and DURUURU M. (1999) The effect of N and P

fertilizer application and botanical composition on the

leaf ⁄ stem ratio patterns in spring in Pyrenean meadows.

Grass and Forage Science, 54, 255–266.

CLELANDLELAND M. A., SMITHM ITH M. D., ANDELMANNDE LM AN S. J., BOWLESO WLE S

C., CAR NE YARNEY K. M., HOR NE RORNER-DEVI NEE VINE M. C., DR AKERAKE J. M.,

EME RYMERY S. M., GRAMLINGRAM LING J. M. and VANDERMASTANDERMAST D. B.

(2004) Invasion in space and time: non-native species

richness and relative abundance respond to inter-annual

variation in productivity and diversity. Ecology Letters, 7,

947–957.

CORNELISSENORNELISSEN J.H.C., LAVORELAVOR EL S., GARNIERARNIE R E., DIAZIAZ S.,

BUCHMANNUCHM ANN N., GURVICHURVI CH D.E., REI CHE ICH P.B., TERTE R STEEGETEEGE

H., MORGANORGAN H.D., VAN DE RVAN DER HEIJDENEI JDE N M.G.A., PAUSASAUSAS

J.G. and POO RTE ROORTER H. (2003) A handbook of protocols for

standardised and easy measurement of plant functional

traits worldwide. Australian Journal of Botany, 51,

335–380.

DIAZIAZ S., ACOSTACOSTA A. and CABIDOABI DO M. (1994) Grazing and

the phenology of flowering and fruiting in a montane

grassland in Argentina: a niche approach. Oikos, 70,

287–295.

DIC KI NSONICKINSON C.E. and DODDODD J.L. (1976) Phenological

pattern in the shortgrass prairie. American Naturalist, 96,

367–378.

DURUURU M. (1997) Leaf and stem in vitro digestibility for

grasses and dicotyledons of meadow plant communities

in spring. Journal of the Science of Food and Agriculture, 74,

175–185.

DURUURU M. and DUC ROCQUCROCQ H. (1997) A nitrogen and

phosphorus herbage nutrient index as a tool for assessing

the effect of N and P supply on the dry matter yield of















permanent pastures. Nutrient Cycling in Agro-ecosystems,

47, 59–69.

DURUUR U M., DELPRATELPRAT V., FABREABR E C. and FE UI LL E RACEUILLERAC E.

(2000) Effect of nitrogen fertiliser supply and winter

cutting on morphological composition and herbage

digestibility of a Dactylis glomerata L. sward in spring.

Journal of the Science of Food and Agriculture, 80, 33–42.

DURUUR U M., DUCROCQUCRO CQ H., FABREABRE C. and FEUILLERACEUILLERAC E.

(2002) Modelling net herbage accumulation of an

orchardgrass sward. Agronomy Journal, 94, 1244–1256.

DURUUR U M., TALLOWINALLO WI N J. and CRUZRUZ P. (2005) Functional

diversity in low-input grassland farming systems:

characterisation, effect and management. Grassland

Science in Europe, 10, 199–210.

FI TTERITTE R A.H., FI TTE RITTER R.S.R., HARRI SARRIS I.T.B. and WI LL IA-ILL I A-

MSONMSON M.H. (1995) Relationships between first flowering

date and temperature in the flora of a locality in central

England. Functional Ecology, 9, 55–60.

GARNIERAR NI ER E., SHIPLEYHIPLEY B., ROUME TOUM ET C. and LAURENTAURENT G.

(2001) A standardized protocol for the determination of

specific leaf area and leaf dry matter content. Functional

Ecology, 15, 688–695.

GARNIERAR NI ER E., CORTE ZO RTEZ J., BI LL E SILL ES G., NAVASAVAS ML., ROUME TOUM ET

C., DEBUSSCHEEBUSSC HE M., LAURENTAURE NT G., BLANCHARDLANCHARD A.,

AUBRYUBRY D., BELLMANNELLMANN A., NEILLEI LL G. and TO USSAINTOUSSAINT J.P.

(2004) Plant functional markers capture ecosystem

properties during secondary succession. Ecology, 85,

2630–2637.

GI LLE TILLET M. (1980) Les graminees fourrageres (Forage grasses).

Paris, France: Gauthier-Villars.

HENRYENRY M., STEVENSTEVENS H. and CARSONAR SO N W.P. (2001)

Phenological complementarity, species diversity and

ecosystem function. Oikos, 92, 291–296.

HOLDAWAYOLDAWAY R.J. and SPARROWPARROW A.D. (2006) Assembly rules

operating along a primary riverbed-grassland

successional sequence. Journal of Ecology, 94, 1092–1102.

HOO PE ROOPER D. U., SOLANOLAN M., SY KE SYKES M. T., DIAZI AZ S., GESSNERESSNER

M. O., BUCHMANNUCHMANN N., DEGR ANGEEGRANGE V., GRIM ER IME P., HULOTULOT

F., MERMILLODERMI LLO D-BLONDINLONDIN F., ROYOY J., SPE HNPEHN E. M. and

PEE R VANE ER VAN L. (2002) Species diversity, functional diversity

and ecosystem functioning. In: Loreau M., Naeem S. and

Inchausti P. (eds) Biodiversity and ecosystem functioning –

synthesis and perspectives, pp. 195–208. New York, USA:

Oxford University Press.

HUMPHREYSUM PHRE YS M.W., YADAVADAV R.S., CAIRNSAIRNS A.J., TURNERURNE R

L.B., HUMPHREYSUM PHRE YS J. and SKØTKØT L. (2006) A changing

climate for grassland research. New Phytologist, 169, 96.

LEM AI REEMAIRE G. and GASTALASTAL F. (1997) N uptake and

distribution in plant canopies. In: Lemaire G. (ed.)

Diagnosis of the nitrogen status in crops, pp. 3–44. Berlin,

Germany: Springer-Verlag.

LIE THIETH H. and RADFORDADFORD J.S. (1971) Phenology, resource

management and synagraphic computer mapping.

BioScience, 21, 62–69.

LOUAULTO UA U LT F., PI LLARILLAR V.D., GARNI ERARNIER E. and SO USSANAOUSSANA J.F.

(2005) Plant traits and functional types in response to

reduced disturbance in a semi-natural grassland. Journal

of Vegetation Science, 16, 151–160.

MAGDAAGDA D., THEAUHEAU J.P., DURUURU M. and COLENOOLE NO F. (2003)

Hay-meadows production and weed dynamics as

influenced by management. Journal of Range Management,

56, 127–132.

MANSKEANSKE L.L. (1998) General description of grass growth and

development and defoliation resistance mechanisms, Range

Management Report DREC 98-1022, Dickinson, ND,

USA: NDSU Dickinson Research Extension Centre.

MARTINKOVAARTI NKOVA J., SMI LAUERMILAUE R P. and MIHULKAIHULKA S. (2002)

Phenological pattern of grassland species: relation to the

ecological and morphological traits. Flora, 197, 290–302.

MASONASON W.H., MACACGI LL I VRAYILL IVRAY K., STEELTEEL J.B. and WI LSO NILSON

J.B. (2003) An index of functional diversity. Journal of

Vegetation Science, 14, 571–578.

MCCMASTE RASTER G.S. and WI LHE LMILHELM W.W. (1997) Growing

degree-days: one equation, two interpretations.

Agricultural and Forest Meteorology, 87, 291–300.

NEGIEGI G.C.S., RIKHAR II K HARI H.C. and SINGHINGH S.P. (1992)

Phenological features in relation to growth forms and

biomass accumulation in an alpine meadow of the

Central Himalayas. Vegetatio, 101, 161–170.

OTTOTTO S., MASINA SI N R., CH I STEHISTE G. and ZANINA NI N G. (2007)

Modelling the correlation between plant phenology and

weed emergence for improving weed control. Weed

Research, 47, 488–498.

PAGNOTTAAGNOTTA M. A., SNAY DO NNAYDON R. W. and COCKSOCKS P. S. (1997)

The effects of environmental factors on components and

attributes of a Mediterranean grassland. Journal of Applied

Ecology, 34, 29–42.

PEACOCKE ACO CK J.M. (1976) Temperature and leaf growth in four

grass species. Journal of Applied Ecology, 13, 225–232.

QUI NUIN G., DUU G., LUOUO Y., DONGONG G. and MAA J. (2003) A re-

examination of the relationships among phenological

complementarity, species diversity and ecosystem

function. Botanical Bulletin of Academia Sinica, 44, 239–

244.

RATHCKEATHCKE B. and LACE YACEY E.P. (1985) Phenological patterns

of terrestrial plants. Annual Review of Ecology and

Systematics, 16, 179–214.

ROBSONOBSON M.J., RYLEYLE G.J.A. and WOLE DGEOLEDGE J. (1988) The

grass plant – its form and function. In: Jones M.B. and

Lazenby A. (eds) The grass crop, the physiological basis of

production, pp. 25–84. London, UK: Chapman and Hall.

SCHE MSKECHEM SKE D.W., WI LLSONILLSON M.F. and MELAMPYELAMPY M.N.

(1978) Flowering ecology of some spring woodland

herbs. Ecology, 59, 351–366.

SOSEBE EOSE BEE R.E. and WE IBEE IBE W. (1973) Effect of phonological

development on radio phosphorus translocations from

leaves in crested wheat grass. Oecologia, 13, 103–112.

SPARKSPARKS T.H., JEFFREEEFFREE E.P. and JEFFR EEEFFREE C.E. (2000) An

examination of the relationship between flowering times

and temperature at the national scale using long-term

phenological records from the UK. International Journal of

Biometeorology, 44, 82–87.

WEIHEREI HE R E., VAN DERAN DER WERFE RF A., THOMPSONHOM PSON K., RODE RIC KODER ICK

M., GARNIERARNIE R E. and ERIKSSONRIKSSON O. (1999) Challenging

Theophrastus: a common core list of plant traits for

functional ecology. Journal of Vegetation Science, 10, 609–

620.

WERGERERGE R M.J.A., HIRO SEI ROSE T., DURI NGURING H.J., HE ILEI L G.W.,

HIKOSAKAIKOSAKA K., ITOTO T., NACHINSHO NHORACHI NSHONHOR U.G. and

NAGAMATSUAGAMATSU D. (2002) Light partitioning among species



and species replacement in early successional grasslands.

Journal of Vegetation Science, 13, 615–626.

WI LSONILSON P.J., THOMPSONHO MPSO N K. and HODGSONO DG SON J G. (1999)

Specific leaf area and leaf dry matter content as

alternative predictors of plant strategies. New Phytologist,

143, 155–162.

WOLEDGEOLE DGE J. (1979) Effect of flowering on the

photosynthetic capacity of ryegrass leaves grown with

and without natural shading. Annals of Botany, 44, 197–

207.

Appendix

Table A1 Characteristics of grasslands studied in Experiment

2 [altitude, aspect and mode of management (M: meadows,

GM: meadows grazed in spring, P: pastures) and their dominant

species.



Gra

ssla

nd

nam

e

Alt

itu

de

(ma.s

.l.)

Asp

ect†

Pla

nt

nu

trie

nt

ind

ex

Man

agem

en

t

Rate

of

herb

age

uti

lizati

on

Pro

po

rtio

n

of

gra

ss

specie

s–

Weig

hte

d

LD

MC

for

gra

sses

Su

mo

f

ab

un

-

dan

ces

Gra

sses§

Dic

oty

led

on

s

AG

RA

NT

AR

RD

AC

FE

SH

OL

LO

LM

OL

PO

AC

EN

CH

AP

ICP

LA

RA

NR

UM

An

gla

du

re600

BV

0Æ7

9M

0Æ8

70Æ2

4200

90†

34

21

Mou

laqu

e600

BV

0Æ7

5M

0Æ8

20Æ8

8203

78

34

51

2

Vil

leA

jas

1‡

600

BV

0Æ7

0M

0Æ8

70Æ7

7208

79

24

13

5

Le

Carr

e600

BV

0Æ6

1M

0Æ7

90Æ8

1212

71

41

23

Cam

pagn

e600

BV

0Æ6

7M

0Æ8

30Æ6

1212

49

51

42

5

Vil

leA

jas

2600

BV

0Æ5

3M

0Æ6

70Æ7

5206

64

25

41

3

Cam

plo

ng

1900

S-W

0Æ8

6G

M0Æ7

60Æ7

3202

80

12

34

5

Riv

esT

err

ass

e600

BV

0Æ6

8G

M0Æ7

70Æ8

2201

79

32

15

4

Cost

eB

as

1800

S-W

0Æ7

2G

M0Æ6

20Æ6

1199

75

21

53

4

Cam

plo

ng

2900

S-W

0Æ5

9G

M0Æ7

20Æ7

2206

75

21

54

3

Rou

ties

900

S-W

0Æ5

5G

M0Æ6

20Æ3

8210

55

54

32

1

Cost

eB

as

2800

S-W

0Æ6

8G

M0Æ6

70Æ4

3214

50

43

15

2

Gir

on

sas

11000

S-W

0Æ8

0P

0Æ4

70Æ7

0227

83

21

34

Peych

ePeti

t1

950

S-W

0Æ8

3P

0Æ4

10Æ9

2205

69

21

34

Lass

us

1900

S-W

0Æ8

3P

0Æ6

30Æ8

5209

74

1

Gir

on

sas

21000

S-W

0Æ4

1P

0Æ4

30Æ3

9240

41

21

3

Peych

ePeti

t2

950

S-W

0Æ5

6P

0Æ4

90Æ4

7238

47

13

24

Lass

us

2900

S-W

0Æ6

3P

0Æ5

10Æ4

7224

42

31

2

†S-W

:so

uth

-west

slope-f

aci

ng;

BV

:bott

om

of

vall

ey.

‡W

hen

the

field

nam

eis

foll

ow

ed

by

the

nu

mber

1an

d2,

itco

rresp

on

ds

totw

osu

b-p

lots

inth

esa

me

gra

ssla

nd

field

.

§H

iera

rch

yof

the

five

dom

inan

tsp

eci

es

that

con

trib

ute

at

least

0Æ0

5of

the

tota

lbio

mass

ineach

plo

tis

indic

ate

dby

nu

mbers

inco

lum

ns

(1co

rresp

on

ds

toth

em

axim

um

speci

es

abu

ndan

ce).

Fu

lln

am

e

of

speci

es

are

:A

gros

tis

cap

illa

ris

L.(A

GR

),A

nth

oxa

nth

um

odor

atu

mL.

(AN

T),

Arr

hen

ath

eru

mel

ati

us

(L.)

Beau

v.

(AR

R),

Da

ctyl

isgl

omer

ata

L.

(DA

CT),

Fes

tuca

rub

raL.

(FE

S),

Hol

cus

lan

atu

sL.

(HO

L),

Lol

ium

per

enn

eL

.(L

OL),

Mol

inia

caer

ule

aL.

(Moen

ch)

(MO

L),

Poa

triv

iali

sL.

(PO

A),

Cen

tau

rea

nig

raL.

(CE

N),

Ch

aer

oph

yllu

ma

ure

um

L.

(CH

A),

Pic

ris

hie

raci

oid

esL

.(P

IC),

Pla

nta

gola

nce

ola

taL.

(PLA

),R

an

un

culu

s

acr

isL.

(RA

N)

an

dR

um

exa

ceto

saL.

(RU

M).

–Su

mof

pro

port

ion

sof

the

five

dom

inan

tgra

sssp

eci

es

isin

dic

ate

dfo

reach

gra

ssla

nd

nam

e.



Characterizing and predicting plant phenology in species-rich grasslands

Documents

Transcript of Characterizing and predicting plant phenology in species-rich grasslands