Differences in the nesting sites microhabitat ...

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Differences in the nesting sites microhabitat characteristics of two syntopic species of Messor harvester ants in a phytosociological homogeneous grassland area a

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L. Solida , D.A. Grasso , A. Testi , G. Fanelli , M. Scalisi , V. a

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Bartolino , A. Mori & A. Fanfani

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Dipartimento di Biologia Animale e dell'Uomo, Università di Roma “Sapienza”, Viale dell'Università 32, 00185, Roma, Italy b

Dipartimento di Biologia Evolutiva e Funzionale, Università di Parma, Via Usberti 11/A, 43124, Parma, Italy c

Dipartimento di Biologia Vegetale, Università di Roma “Sapienza”, P.le A. Moro 5, 00185, Roma, Italy d

Ministero Istruzione Università e Ricerca, P.le Kennedy 20, Roma, Italy Available online: 24 Jun 2011

To cite this article: L. Solida, D.A. Grasso, A. Testi, G. Fanelli, M. Scalisi, V. Bartolino, A. Mori & A. Fanfani (2011): Differences in the nesting sites microhabitat characteristics of two syntopic species of Messor harvester ants in a phytosociological homogeneous grassland area, Ethology Ecology & Evolution, 23:3, 229-239 To link to this article: http://dx.doi.org/10.1080/03949370.2011.570379

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Ethology Ecology & Evolution 23: 229–239, 2011

Differences in the nesting sites microhabitat characteristics of two syntopic species of Messor harvester ants in a phytosociological homogeneous grassland area

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L. SOLIDA 1 , D.A. GRASSO 2,5 , A. TESTI 3 , G. FANELLI 3 , M. SCALISI 4 , V. BARTOLINO 1 , A. MORI 2 and A. FANFANI 1 1

Dipartimento di Biologia Animale e dell’Uomo, Università di Roma “Sapienza”, Viale dell’Università 32, 00185 Roma, Italy 2 Dipartimento di Biologia Evolutiva e Funzionale, Università di Parma, Via Usberti 11/A, 43124 Parma, Italy 3 Dipartimento di Biologia Vegetale, Università di Roma “Sapienza”, P.le A. Moro 5, 00185 Roma, Italy 4 Ministero Istruzione Università e Ricerca, P.le Kennedy 20, Roma, Italy Received 9 June 2010, accepted 8 November 2010

Physiological tolerance of species to temperature, moisture or chemicalphysical properties of the soil could be important in determining the distribution and abundance of ant nests. In the present study we investigated the possible differences in the nesting site microhabitat characteristics of two syntopic species of harvester ants of the genus Messor living in a Mediterranean homogeneous grassland area belonging to a single phytosociological association known as “Vulpio ligusticae-Dasypyretum villosi”. We tested to see whether the activity of the colonies of the two species directly altered the microhabitat characteristics of the nesting sites. Microhabitat characteristics were assessed quantifying several abiotic factors (light, temperature, soil moisture, soil pH, nitrogen) by means of the Ellenberg Bioindication Model. The model represents a simple way of interpreting the vegetation pattern in terms of ecological factors from the perspective of the plants and can be considered an effective and promising approach to link animal and plant ecology. Our data showed significant differences in the nesting site microhabitat characteristics partially due to a different capacity of the two species to alter nesting site proprieties. Possible differences in the physiological tolerance of these species to moisture gradients could be crucial in determining the distribution and abundance of their nests. KEY WORDS:

Messor ants, coexistence, Ellenberg bioindication model, ant-plant interactions, abiotic parameters.

5 Corresponding author: Donato A. Grasso, Dipartimento di Biologia Evolutiva e Funzionale, Università di Parma, Via Usberti 11/A, 43124 Parma, Italy (E-mail: [email protected]).

ISSN 0394-9370 print/ISSN 1828-7131 online © 2011 Dipartimento di Biologia Evoluzionistica dell’Università, Firenze, Italia DOI: 10.1080/03949370.2011.570379 http://www.informaworld.com

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INTRODUCTION

The interactions between abiotic and biotic factors may affect several parameters of ant community composition, such as species richness and abundance and the outcome of competition of coexisting species (TILMAN 1982; FOLGARAIT 1998; PALMER 2003; DUNN et al. 2007; BLÜTHGEN & FELDHAAR 2010). Competition is considered one of the strongest driving forces in determining community composition (HARDIN 1960; HÖLLDOBLER & WILSON 1990; RIBAS & SCHOEREDER 2002), but other biotic factors, such as predation and parasitism, can be important in shaping species distribution and co-occurrence (FEENER 2000; ORR et al. 2003). As regards abiotic factors, the physiological tolerance of species to temperature, moisture or chemical-physical properties of the soil could be important in determining the distribution and abundance of ant nests, especially in arid and semiarid areas, where physical factors impose severe restrictions (DUNSON & TRAVIS 1991; JOHNSON 1992, 2000a; RETANA & CERDÁ 2000). Hence, in order to assess the microhabitat parameters associated to the nesting ecology, to the distribution of the colonies and to the community structure of ants in a particular area, it is important to take into account many biotic and abiotic interconnected constraints (FOLGARAIT 1998). Ants seem to prefer, for example, certain soil types over another, probably due to a combination of characteristics such as facility of tunnelling, chamber construction and water-holding capacity (JOHNSON 1998, 2000b). This preference could be observed in the first stage of colony foundation if newly-mated queens chose specific soils where to nest (WAGNER et al. 1997; JOHNSON 1998). It is also known that ground-nesting ants can directly modify the nesting site microhabitat characteristics; their activity may in fact alter the physical and chemical properties of the soil, for example pore sizes and moisture (WAGNER et al. 2004; CAMMERAAT & RISCH 2008; CERDÀ & JURGENSEN 2008; FROUZ & JILKOVÁ 2008). In the present study we investigated possible differences in the nesting sites microhabitat characteristics of two syntopic species of harvester ants of the genus Messor, M. wasmanni (Krausse 1909) and M. minor (André 1881), in a natural reserve where many colonies of the two species occur in close proximity. Under the assumption that our study was performed in a homogeneous grassland area, representing a single phytosociological association (FANELLI 1998; PIGNATTI et al. 2001), we tried to answer the following questions: 1. Did differences exist in the microhabitat characteristics of the nesting sites of the two species? 2. Did the activity of the two species directly affect the microhabitat characteristics of the nesting sites?

MATERIALS AND METHODS The study area The investigated site is located in the Presidential Estate of Castelporziano (30 m a.s.l.), an area covering 6200 ha along the west coast of Latium (Roma, Central Italy) and characterised by a xeric region climate, inferior Mediterranean thermotype. Rainfall ranges from 129 mm (November) to 12 mm (July) and air temperature ranges from 4 ◦ C (January) to 30 ◦ C (July) (data provided by the Castelporziano meteorological station). The soil is mainly sandy and of alluvial nature with both recent and ancient dune formations.

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Grassland areas represent one of the main environments inside the Estate. These areas, where Messor species find a suitable habitat to nest (CASTRACANI et al. 2010; SOLIDA et al. 2010), are characterised by high frequency of Dasypyrum villosum (Poaceae) and Vulpia ligustica (Poaceae) and by the presence of other arid and semi-arid adapted plant species (PIGNATTI et al. 2001). Our study was carried out in a typical grassland area known as “Coltivati” (25 ha), where livestock graze during the year. The plant community of this site belongs to a single phytosociological association reported as “Vulpio ligusticae-Dasypyretum villosi” (FANELLI 1998). Previous observation showed that ant colonies of the two examined species were equally present in Coltivati (FANFANI et al. 2006; CASTRACANI et al. 2010).

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Sampling protocol A two-stage random sampling was performed. In the first stage, a sampling unit of 900 m2 was randomly selected inside Coltivati. Under the assumption that our study was performed in a homogeneous grassland area, representing a single phytosociological association, a single first-stage unit was selected and investigated (grid), as we preferred to increase the number of second-stage sampling units (plots) instead of increasing the first-stage sampling size. The grid was subdivided into 900 plots of 1 m2 each. We first took a census of all second-stage sampling units in order to locate and map, by means of accurate visual inspection, the position of the nests of the two examined species in the grid. A total of 15 nests of M. wasmanni and 18 nests of M. minor were found for a total of 33 occupied plots. According to WHITFORD & DIMARCO (1995), we assigned a control site (CS) to each nest that represents a plot randomly chosen among those located 3–4 m distant from the observed colony. This distance is considered adequate to identify an area unaffected by nest activity (WHITFORD & DIMARCO 1995). Excluding all the plots occupied by the nests of the two species, we randomly selected 170 second-stage units among the 900 available in the grid. For all the 203 sampled plots, the plant community composition was detected and the Ellenberg bioindication model applied as a method to measure the microhabitat characteristics. Ellenberg bioindication model (EBM) The model (ELLENBERG 1979) represents a synthetic and effective approach to analyse and express ecosystem complexities (PIGNATTI et al. 2001; FANELLI et al. 2006) by the definition of several ecological parameters, the Ellenberg indicator values (EIVs). EIVs consist in a set of scores for Central European plant species expressing the average realised niche along the gradients of solar exposure or light (L), temperature (T), continentality of climate (K), soil moisture (F), soil pH (pH) and nitrogen (N). Patterns in vegetation can be interpreted and calibrated with direct measurements of ecological factors. However, this is time-consuming and often difficult because the target measurement is in many cases not obvious. For instance, in woodlands it is necessary to measure light requirement in the period of development of seedlings and not of adult trees. These limitations can be shortcut by means of Ellenberg indicators that represent not only an easy way of interpreting the vegetation pattern in terms of ecological factors but, more important, as long as they represent the realised niche of species, a way to assess the ecological factors from the perspective of the plants. EIVs for the species of the Italian flora derive from a large database of phytosociological observations that allow us to calculate objectively such values (FANELLI et al. 2006). In this database, all the species of the Italian flora are reported together with ecological and ecophysiological measurements. Limitations and strengths of the Ellenberg approach have been debated, but many studies show the validity of this tool and the agreement between indicators and environmental variables (SCHAFFER & SYKORA 2000; EWALD 2003). In our study, the EBM was applied during May when all the herbaceous plants in the grid were in flower. For each sampled plot, the occurrence and percentage of coverage of each plant species was carried out following the sampling procedure described in the Braun-Blanquet method

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(BRAUN-BLANQUET 1964). The EBM assigns to each plant species the value of the five EIVs that finally represent the overall requirements for a plant to grow on a specific soil. To apply the EBM, we transformed the relative percentage of coverage of the plant species listed in each plot in the weighted mean of each EIV according to: 

(i · xi)/



xi,

where xi represents the plant coverage in the plot and i the relative EIV. The indicator “climate” (K) was excluded from the analyses because it was not possible to obtain sensitive variations of this parameter in the scale of observation.

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Data analysis To investigate the assumption that the studied grassland area represents a single phytosociological association (FANELLI 1998; PIGNATTI et al. 2001), we estimated the confidence interval of each EIV in the 170 second-stage sampling units. In this way we excluded all the plots occupied by the colonies of the two species since, for definition, nest activity may affect microhabitat characteristics (WHITFORD & DIMARCO 1995). To investigate the presence of possible differences in the microhabitat characteristics of the nesting sites of the two species, a detrended correspondence analysis (DCA) was applied on EIVs. DCA permitted us to order and to investigate the local variation through these selected environmental variables. DCA is an extension of canonical correspondence analysis, characterised by detrending to remove all systematic dependence between axes and rescaling, to avoid packing of points at the end of the environmental gradients. Species have been treated as factors and fitted onto the nest ordination. Species centroids and standard deviation ellipses were identified. A test statistic R was computed on 1000 permutations of the two species sampled, and the significance level was calculated (CLARKE & WARWICK 1994). Moreover, to investigate which among the considered EIVs possibly identify differences in the nesting site microhabitat characteristics between the two species, a one-way multivariate analysis of variance (MANOVA) was applied. To check whether the activity of the colonies directly altered the microhabitat characteristics of the nesting sites, we computed a paired t-test searching for differences between EIVs associated to nesting soils and CS. To control problems of multiple significance testing, significant levels were recalculated according to the false discovery rate (FDR) procedure (BENJAMINI & YEKUTIELI 2001). DCA was performed using the statistical software R (see http://www.r.project.org) and functions from the package Vegan (OKSANEN et al. 2008), paired t-test and MANOVA using the software STATISTICA package (Version 6.0, StatSoft 2001, Tulsa, USA).

RESULTS

The application of the EBM to the total of sampled plots highlighted the presence of 48 botanical species listed in Appendix with the relative EIVs (PIGNATTI et al. 2001; FANELLI et al. 2006). The 95% confidence intervals for the investigated area of Coltivati EIVs provided the following results: pH = 5.75–5.80, N = 5.00–5.10, F = 3.36–3.41, T = 6.47–6.53, L = 8.01–8.02. Graphically, the DCA showed that the points associated with the two ant species formed in the bi-dimensional plane almost shifted groups, with DCA1 to explain 76% of the variance whilst DCA2 18% (Fig. 1). The significance test based on 1000 permutations confirms that the two species nested on soils partially different in the microhabitat characteristics described by means of the EBM (R = 0.33, P < 0.01). Regarding the contribution of the single EIVs, MANOVA showed significant differences for three of

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Fig. 1. — Ordination plot, with the first and second detrended correspondence axes (DCA1 and DCA2), of the ant nesting sites (points) according to the Ellenberg indicator variables (arrows). Centroids and standard deviation ellipses of the two ant species are shown.

the five EIVs considered, specifically for pH, light and moisture gradient (Table 1). In particular the vegetation, on the nesting sites of M. wasmanni in respect to M. minor, required lower values of pH (mean ± SE): 5.66 ± 0.03/5.90 ± 0.04; moist soils (F): 3.49 ± 0.05/3.32 ± 0.03 and a higher solar exposure (L): 8.08 ± 0.01/8.02 ± 0.01. The paired t-test showed significant differences between nesting sites and CS only for M. wasmanni and only for two of the five EIVs considered: pH (t-test: − 2.81; P = 0.015; df = 12) and light (t-test: 4.28; P = 0.001; df = 12), i.e. only the activity of M. wasmanni colonies altered soil proprieties; in particular M. wasmanni nesting sites were just slightly acid and with a higher solar exposure than the surrounding CS (Table 2). By contrast the vegetation on the nesting sites of M. minor would seem to have the same niche requirements of the surrounding environment.

DISCUSSION

The present study represents an ecological integrative approach involving insect and plant sciences. Interactions between ants and plants are related and act at a

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Table 1.

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F test values and associated significance levels of each parameter extracted from Ellenberg model to explain microhabitat segregations between the nesting sites of the two species M. wasmanni and M. minor (NS = P > 0.05). Parameters

F1,57

P

pH

21.25

< 0.01

N

1.91

NS

F

5.67

< 0.05

T

0.32

NS

L

8.49

< 0.01

Table 2. Averaged values (± SE) and paired t-test probability of EIV associated with nesting sites and CS for the two examined species recalculated according to the FDR procedure. M. wasmanni

M. minor

Parameters

FDR α

Ant nest

CS

L

0.050

8.08 ± 0.01

8.01 ± 0.01

0.001

pH

0.033

5.66 ± 0.03

5.81 ± 0.04

0.015

P

Ant nest

CS

P

8.02 ± 0.01

8.01 ± 0.01

NS

5.90 ± 0.04

5.76 ± 0.05

NS

F

0.027

3.49 ± 0.05

3.36 ± 0.03

NS

3.32 ± 0.03

3.38 ± 0.04

NS

T

0.024

6.54 ± 0.05

6.58 ± 0.05

NS

6.55 ± 0.05

6.48 ± 0.05

NS

N

0.022

5.02 ± 0.08

4.98 ± 0.07

NS

4.98 ± 0.10

5.10 ± 0.08

NS

df = 12; FDR α, significant level; NS = P > FDR α.

very fine scale of observation (WHITFORD & DIMARCO 1995; BROWN & HUMAN 1997; RÍOS-CASANOVA et al. 2006). Ants, for example, possibly altering soil properties and microclimate, could determine microhabitat characteristics suitable for peculiar plant composition (BOULTON et al. 2003, 2005; WAGNER et al. 2004). Vegetation in the same way, reflecting microclimate gradients or soil attributes as textural variation, can be utilised as a predictor of ant species composition, abundance and distribution at a local scale (BESTELMEYER & SCHOOLEY 1999; BONTE et al. 2003; RIBAS et al. 2003). Inside the study area of Coltivati, as well as in other Mediterranean areas, Messor species represent a main element of the ant fauna, probably favoured by both cattle grazing and agricultural human land activities (BESTELMEYER & WIENS 2001; CASTRACANI et al. 2010). As previously mentioned, the study area represents a homogeneous habitat characterised by a single phytosociological association reported as “Vulpio ligusticae-Dasypyretum villosi” (FANELLI 1998; PIGNATTI et al. 2001). According to this assumption, the confidence intervals showed that the variability of the EIVs for Coltivati (25 ha) was very low. Interestingly, as we moved from a scale of observation of 25 ha to microhabitat level (plot of 1 m × 1 m) the EBM was revealed to be a sensible tool to underline small environmental heterogeneities that may be crucial for species coexistence, especially in homogeneous habitat.

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Our results showed in fact significant differences in the microhabitat characteristics of the nesting sites of the two examined species, partly due to a different attitude of M. wasmanni and M. minor toward altering the nesting site abiotic proprieties. In particular, M. wasmanni nesting areas were characterised by a higher abundance of more acidophilus and heliophilous plant species, such as Vulpia myuros, and at the same time by moist soil. A possible explanation for these aspects was that M. wasmanni workers, larger and stouter than those of M. minor (SOLIDA et al. 2007), dug acidic, almost pure sand from deeper layers of the soil and spread it above ground, thus altering the physical-chemical microenvironment. Moreover, a characteristic behaviour of the workers of this species, exhibited at the beginning of the activity season, was to thin out the vegetation from the nesting area. Possibly, this abundant spread of sand with scarce vegetation was unfavourable for M. minor, which seemed to prefer dense swards of grassland. It would be interesting to verify and to quantify whether the observed microhabitat differences represent the outcome of a competitive mechanism (JOHNSON 2000a; KNADEN & WEHNER 2005). Coexistence could occur, for example, when syntopic species show asymmetrical competitive abilities, with the subordinate ones able to live outside the high-quality territories, being driven out by the dominant species, or close to their thermal physiological limits (CERDÁ et al. 1997; DIETRICH & WEHNER 2003; GRASSO et al. 2004). In this context, the present investigation, providing information on differences in the microhabitat characteristics between M. wasmanni and M. minor, represents an important step to shed light on the mechanisms promoting the niche shift between these two coexisting species (SOLIDA et al. 2010). Regarding our last finding, significant differences in the moisture gradient between the nesting sites of the two species, field observations do not suggest any preference of newly mated queens for specific soils to nest in (WAGNER et al. 1997; JOHNSON 1998). After nuptial flights, following September rains, we observed queens of both species starting to dig indifferently near intra- or interspecific colonies, and in some cases we found them digging into the interspaces between tunnels of old and wellestablished colonies (unpubl. data). Furthermore, the soil in the studied area remained extremely uniform, moist and easy to dig for many days after the emergence of the winged individuals. The water content should not therefore be considered a limiting factor as in other arid environments (JOHNSON 1998, 2000b). Consequently, it is unlikely to explain differences in moisture gradient as a result of an initial choice by wingless queens of a suitable site in which to nest. We are more inclined to believe that the first stage of colony foundation follows a random pattern, also because we often observed several queens of both species digging a nest chamber a few centimetres apart (pers. obs.). Possibly, the physiological tolerance of these species to moisture gradients could be crucial in determining the distribution and abundance of their nests (JOHNSON 1992, 2000a; RETANA & CERDÁ 2000). To conclude, the EBM (to our knowledge used here for the first time to link animal and plant ecology) is a valid tool to characterise microhabitat features of ant nest sites, allowing one to consider simultaneously many different abiotic parameters. The model is particularly effective when the variables are difficult or impossible to measure directly, especially in homogeneous habitat where environmental gradients are characterised by small differences.

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ACKNOWLEDGEMENTS We are grateful to the “Segretariato Generale della Presidenza della Repubblica” and to the Director of Castelporziano Estate for the hospitality in the guest-house. We are grateful also to all the undergraduate students indispensable for the field work. This research has been supported by grants assigned to A. Fanfani (FIL-2008) and to D.A. Grasso (FIL-2008). Luigi Solida was supported by a PhD fellowship issued from the University of Parma and by a grant from the “Accademia Nazionale delle Scienze, detta dei XL”. We wish to thank Patricia de Angelis for reviewing the English text. All research conducted complied with the current legislation in Italy.

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APPENDIX List of the plant species sampled in the grid with the associated Ellenberg indicator values (L, T, F, pH, N).

Plant species

L

T

F

pH

N

LF

Anagallis arvensis

8

7

4

6

6

A

Anthemis arvensis

8

7

3

6

4

A

Anthemis mixta

8

6

3

5

4

A

Bromus racemosum

8

6

6

8

6

A

Bunias erucago

8

6

4

6

6

A

Capsella rubella

8

6

5

6

7

A

Carduus nutans

8

6

4

7

6

B

Cerastium glomeratum

8

6

5

6

6

A

Cerastium ligusticum

8

6

3

6

4

A

Coleostephus myconis

8

6

4

6

6

A

Crepis setosa

8

7

4

6

6

A

Cynodon dactylon

9

7

4

6

6

P

Cynosurus echinatus

8

7

3

6

4

A

Dasypyrum villosum

8

7

4

6

6

A

Draba muralis

6

7

5

6

7

A

Echium plantagineum

8

7

4

6

6

A

Erodium moschatum

8

7

4

6

7

A

Festuca arundinacea

8

5

6

7

6

P

Gaudinia fragilis

8

6

4

6

6

A (Continued)

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APPENDIX

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(Continued). Plant species

L

T

F

pH

N

LF

Geranium molle

8

6

4

6

6

A

Hordeum leporinum

9

9

3

5

3

A

Lolium multiflorum

8

6

4

7

7

A

Lotus tenuis

9

7

6

7

7

P

Lupinus angustifolius

8

6

3

5

3

A

Medicago arabica

8

6

5

6

7

A

Medicago hispida

8

7

4

6

6

A

Ornithopus compressus

8

7

3

5

4

A

Pallenis spinosa

8

8

3

8

3

A

Poa annua

8

7

6

5

7

A

Poa trivialis

8

6

6

7

7

P

Polycarpon tetraphyllum

8

7

6

5

7

A

Raphanus raphanistrum

8

6

3

5

5

A

Rumex acetosella

8

5

3

5

3

P

Rumex pulcher

8

6

4

6

7

P

Silene gallica

8

7

3

6

4

A

Stachys ocymastrum

8

7

4

8

6

A

Trifolium glomeratum

9

7

3

6

4

A

Trifolium nigrescens

8

6

4

6

6

A

Trifolium repens

8

6

5

6

7

P

Trifolium resupinatum

9

7

5

6

6

A

Trifolium subterraneum

8

6

4

6

5

A

Trifolium squarrosum

11

9

2

3

2

A

Trifolium vesiculosum

8

7

4

6

6

A

Veronica arvensis

8

6

5

6

6

A

Vulpia ciliata

9

7

3

6

3

A

Vulpia geniculata

8

6

3

6

4

A

Vulpia ligustica

8

6

4

6

5

A

Vulpia myuros

9

7

3

5

3

A

Life form (LF): annual (A), biennial (B), perennial (P).