Vol.1, No.2, 48-56 (2011) Open Journal of Ecology
Copyright © 2011 SciRes. OPEN ACCESS
Assessment of Posidonia oceanica (L.) Delile
conservation status by standard and putative
approaches: the case study of Santa Marinella meadow
(Italy, W Mediterranean)*
Alice Rotini1, Carla Micheli2, Luigi Valiante3, Luciana Migliore1*
1Department Biology, Tor Vergata University, Rome, Italy; *Corresponding Author: luciana.migliore@uniroma2.it
2ENEA, Centro Ricerche Casaccia, Rome, Italy;
3ECON s.r.l., Naples, Italy;
Received 10 June 2011; revised 4 July 2011; accepted 15 July 2011.
The conservation status of the Posidonia oce-
anica meadow at Santa Marinella (Rome) was
evaluated through both standard (bed density,
leaf biometry, “A” coefficient, Leaf Area Index,
rhizome production) and biochemical/genetic
approaches (total phenol content and Random
Amplified Polymorphic DNA marker). The bio-
chemical/genetic results are in agreement with
those obtained by standard approaches. The
bed under study was ranked as a disturbed one,
due to its low density, and high heterogeneity in
leaf biometry, LAI values, “A” coefficient and
primary production. This low quality ranking is
confirmed by both mean phenol content in pla-
nts, quite high and scattered, and by the low
genetic variability in the meadow, with a very
high similarity of specimen at a local scale.
Hence, these two putative approaches clearly
identify the endangered conservation status of
the meadow. They link plant biodiversity and
ecophysiology to ecosystem ‘health’. Further-
more, they are repeatable and standardizable
and could be usefully introduced in meadows
monitoring to check environmental quality.
Keywords: Posidonia oceanica; Genetic Variability;
Environmental Indicator; RAPD; Seagrass
Monitoring; Total Phenols
Posidonia oceanica (L.) Delile (PO) is the dominant
endemic seagrass in the Mediterranean Sea, where it
forms meadows which play a crucial role in coastal
ecosystem dynamics. They produce high amount of
oxygen and organic compounds, sustain food nets, and
act as a nursery/refuge for several species. Furthermore
they preserve coastal systems trapping sediments into
the matte and reducing hydrodynamics [1]. PO is re-
garded as a key species, being listed in the Habitat Di-
rective 92/43/EEC.
Throughout most of the Mediterranean Sea, natural
processes and human activities are responsible for a
widespread PO meadow regression [2-3]. The identifica-
tion of ‘new diagnostic tools’ to monitor the meadows
conservation status is a critical issue. Standard monitor-
ing indicators are several [4-10]; according to Montefal-
cone [11] standard monitoring indicators can be classified
as structural descriptors at individual level (shoot
phenology and biomass), at population level (bed density
and coverage) or at community level (leaves epiphytes).
However, many of them suffer of a lack in sensitivity and
often to obtain significant information it’s necessary to
use a combination/integration of indicators [12]. The
identification of approaches providing early and ecologi-
cally relevant information, useful for policy and man-
agement, is still a critical issue.
Recently two putative approaches were proposed
[13-15]: phenolic compounds and Random Amplified
Polymorphic DNA (RAPD) markers. If conveniently
modified, these well known methods can clearly iden-
tify PO alterations.
Phenolic compounds, as in terrestrial plants [16], can
work as biochemical markers of environmental stress
*This work is dedicated to the memory of the late Professor Eugenio
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
Copyright © 2011 SciRes. OPEN ACCESS
(total phenol determination is an easy and rapid assay).
They are a class of secondary metabolites widely dis-
tributed in terrestrial [17] and aquatic plants [18-19].
Phenolic compounds are present in roots, stems, rhi-
zomes, leaves, flowers and fruits playing several struc-
tural and physiological roles, including the defense of
plants. High phenol concentrations were found in PO
leaves exposed to different environmental pressures:
competition with the invasive seaweed Caulerpa taxifo-
lia [20-21], contamination by metals [22], proximity to
intensive fish aquaculture [23]. The increase of phenolic
compounds represents a generic response to different
environmental stress and thus can be used to screen the
meadow health state. Total phenol concentration varies
in leaves with season due to leaves’ short lifespan [21,24]
and with depth. On the opposite, levels of synthesis and
accumulation of phenolic compounds are more stable in
rhizomes [15,24].
The decline of PO can be facilitated by low genetic
diversity which results from a restricted gene flow, as
suggested by trinucleotide [25-26] and dinucleotide [27]
microsatellites. Low genetic diversity may result in low
resistance, low resilience and limited adaptability to
environmental changes [13,28-29]. RAPD markers
have been used to assess the pattern of genetic diversity
and the genetic structure of rare and endangered plants.
They provide information for the conservation of en-
dangered plants [30]. Moreover, they have been suc-
cessfully used to assess genetic diversity of other sea-
grasses [31-32]. RAPDs revealed both the intra-population
variability in P. australis [33], and the high genetic ho-
mogeneity in Cymodocea nodosa from Northern Atlan-
tic [34]. They have been used to compare the genetic
diversity of Cymodocea nodosa and P. oceanica popu-
lations in the Mediterranean Sea [35]. Furthermore,
RAPD markers revealed a decreased genetic diversity
in PO along an anthropogenic disturbance gradient,
both at small within a meadow and at Mediterranean
scale [13]. Analogous trends were found in others sea-
grasses [36].
Hence, total phenol content in rhizome and RAPD
markers in leaves are inexpensive and uncomplicated
methods, potentially useful for PO meadows monitor-
The aim of this study is to describe the conservation
status of a specific meadow by comparing the results of
phenol content and RAPDs (putative approaches) to the
standard ones. The superimposition of results will con-
firm that the putative methods can detect alterations in
the meadow and properly contribute to assess the
meadow “health status”.
To this end, plants from the Santa Marinella meadow
(Rome, Italy, W Mediterranean), collected in Spring
2004, were analyzed to obtain the quantification of
phenolic compounds and RAPD marker profile.
2.1. Study Site and Sampling
The study was conducted on the PO meadow of Santa
Marinella (Rome, Italy; Figure 1), a Site of Community
Importance (according to Habitat Directive 92/43/EEC).
This meadow, spanning from Capo Linaro to Santa Sev-
era, for a 13.5 km coastline and covering a surface of
1,800 ha, can be considered a “pure bed”, i.e. mono-
specific, with patched distribution and a regressive limit,
characterized by the presence of dead matte. The lower
limit is at –20 m depth [37]. This meadow is under an-
thropogenic impact, mainly intensive agriculture and
land use, causing increased water turbidity and fine
sediment input. The streams and watercourses flowing in
Santa Marinella sea stretch are responsible of pollutant,
fine sediment and nutrient input to the sea [38-40].
Sampling was carried out in late spring 2004; 30 sam-
pling stations were randomly chosen in the central area
of the meadow (about 5 ha), on a relatively homogene-
ous topography. The bathymetric values of the sampling
area ranged from 7.5 to 13.5 m depth (see Supplemental
Data for sampling site information).
Samples were obtained by SCUBA diving. In each
sampling station shoots were collected for phenologi-
cal/lepidochronological analyses (15) and for phenol
determination (3 orthotropic). Furthermore, in 4 selected
stations (Figure 1), 5 orthotropic shoots per site were
sampled for RAPD marker analyses.
In § 3.2 are shown some data from the Talamone
meadow (Tuscany, Italy; 30 sampling sites at compara-
ble depth), which is considered well preserved according
to phenological and lepidochronological analysis [24].
All these samples were analysed in our laboratory by the
same experimental protocol (unpublished data by L.
Migliore, personal communication).
2.2. Phenological and Lepidochronological
Shoot density was evaluated in situ by counting the
number of shoots using 40 × 40 cm standard quadrates,
five measurements at each site. The value obtained is
expressed as number of shoots/m2.
Number and biometry of leaving leaves (foliar shoots)
were determined, on 10 shoots for sampling site, ac-
cording to Giraud [41]. “A” coefficient (percentage of
leaves with lost apex) and Leaf Area Index (LAI, leaf
surface area per shoot, cm2/shoot) were also calculated.
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
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Figure 1. Sampling area’s map in the Santa Marinella meadow (Rome, Italy), showing the 30 sampling stations and the bottom
characteristics. Stations where genetic analysis was performed are indicated by stars instead of dots.
Lepidochronological analysis was carried out on 5
shoots for sampling site, according to standard methods
[42], in order to estimate the annual primary production
of the rhizomes, expressed as mg rhizome (dry weight,
d.w.) produced per shoot per year.
2.3. Total Phenols
Total phenol determinations were carried out in du-
plicate on 3 different rhizomes for each sampling site
according to Migliore et al. [15]. Shoots were main-
tained under dark and stored at –20˚C until processing.
Plants were first rinsed in 0.1 Triton-X (Sigma) and then
in distilled water to remove epiphytes and contaminants.
Phenolic compounds were extracted according to Le-
grand [43] modified for PO on 100 mg (fresh weight,
f.w.) of basal, intermediate and apical sections of the
rhizome. Quantification of total phenols was performed
by spectrophotometry [λ = 724 nm, chlorogenic acid
(Sigma) as standard] using the Booker and Miller [44]
method. The amount of protein, known to interfere with
Folin-Ciacolteau reagent (Sigma), was determined by
the Bradford assay.
2.4. Genetic Analysis
Genetic analysis was carried out in duplicate on 5
plants from the 4 selected station. The plants were
washed in distilled water and the young leaves stored in
liquid nitrogen at 180˚C until processing. Extraction of
genomic DNA was carried out according to the protocol
of Dellaporta et al. [45]. The PCR amplification was
performed (Perkin Elmer 2400) using 10 primers; se-
quences are reported in table 1. The primers (10 mM)
were chosen for their capacity for discriminating bands
and scoring them as present/absent; they gave high re-
producibility of electrophoresis pattern in both the signal
intensity and the number of bands.
All the experiments, including the PCR amplification
and electrophoresis conditions, were carried out accord-
ing to Micheli et al. [13].
2.5. Statistical Analysis
One-way ANOVA test was utilized to evaluate differ-
ences in total phenol content between Talamone and
Santa Marinella meadows and among rhizome sections
from the two sampling sites. Parametric hypotheses were
Box-plots were utilized to show the distribution of bed
density, leaf biometry and phenol content data; the box
contains 50% data (the extremes of each box are the Q1
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
Copyright © 2011 SciRes. OPEN ACCESS
and Q3, 1st and 3rd quartiles), the internal horizontal
segment represents the median of the distribution (Q2
value, 2nd quartile), “whiskers” range from the lowest to
the highest value.
All the RAPD data were elaborated using NT-SYS-pc
(Numerical Taxonomy and Multivariate Analysis System)
computer package. The bands were recorded as present
(1) or absent (0) and assembled in a data matrix table.
Then similarity coefficients (Dice index) were obtained
(Simqual data matrix, NT-SYS-pc) and their average and
standard deviation were calculated. The Nei’s coeffi-
cients of similarity between each pair of samples were
used to construct a dendrogram using the unweighted
pair group method with arithmetic averages (UPGMA).
3.1. Standard Monitoring Approaches
The absolute density throughout the Santa Marinella
meadow is reported in Figure 2A and Supplemental
Data; the mean value for the meadow is 342.8 leaves
shoots/m2. According to the classification proposed by
Pergent et al. [46] and modified by Buia et al. [47], this
meadow is considered a “disturbed bed”.
The leaf biometry (i.e. number, length and width) was
also recorded (Figure 2B-D) to calculate LAI values per
shoot (see Supplemental Data for the complete data set).
LAIs range from 120 to 68.6 and they probably represent
the highest values all the year round, as LAI is maxi-
mum at the end of spring and a minimum in late autumn
or at the beginning of winter [48]. Santa Marinella LAI
values are comparable to those found in other Tyrrhenian
meadows [49-51].
The “A” coefficient shows heterogeneous values be-
tween stations (see Supplemental Data), from a mini-
mum of 25% to a maximum of 80%, suggesting a high
spatial heterogeneity in mechanical stress or grazing in
the meadow. Both “A” coefficient (r = –0.63; p < 0.01)
and LAI/shoot (r = –0.56; p < 0.02) seems negatively
related to depth, although the range of bathymetric val-
ues is narrow (Figure 3A and B).
The mean value of the rhizome production is 41.3 mg
(d. w.)/shoot/yr, ranging from 26 to 59 (see Supplemen-
tal Data); values are lower than those registered in
meadows with same morphological characteristics [39]
and no relationship with depth was found.
3.2. Putative Approach I: Phenols Content
The total phenol mean content in the entire rhizome is
18.7 mg/g (f. w.), ranging from 8.8 to 30.2 mg/g (Figure
4A). In all rhizomes a decrease in total phenol concen-
tration from the apical to the basal section is found; dif-
ferences are statistically significant (ANOVA, F = 38.1,
p0.01; Figure 4B).
These data have been compared with total phenol
content, quantified in plants from the Talamone (Tuscany,
Italy; see § 2.1) meadow. In Talamone’s plants the total
phenol mean content is 5.62 mg/g f. w. (n = 72; SE 0.15)
Figure 2. Density (A) and leaves biometry (B-D) reported as box-plots. The box contains 50% data, the horizontal segment repre-
sents the median, ‘whiskers’ range from the lowest to the highest recorded value.
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
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and a decreasing apical-basal gradient was found. Ac-
cording to phenological and lepidochronological analy-
sis Talamone meadow was judged as “well preserved”
[39]. Phenol content in Santa Marinella plants is signify-
cantly higher and more scattered than in Talamone plants
(Figure 4) as regard both the entire rhizome and the
three sections.
The high phenol values can be related to the endan-
gered plant health status in Santa Marinella meadow and,
being the total phenols analysis repeatable, inexpensive
and uncomplicated method, it could be useful introduced
in the set of test to state the conservation of PO mead-
The high phenol values can be related to the endan-
gered plant health status in Santa Marinella meadow and,
being the total phenols analysis repeatable, inexpensive
and un-complicated method, it could be useful introd-
uced in the set of test to state the conservation of PO
3.2. Putative approach II: RAPD markers
Ten RAPD primers generated a total of 111 bands,
with fragments ranging in size from 150 to 300 bp. 55
of the 111 bands were polymorphic among the 20 in-
dividuals; the overall percentage of polymorphism in
the Santa Marinella meadow was 61.1%. The percent-
age of polymorphic bands in each station varies from
6% to 11.6%, demonstrating a low variability in the
specimens. Primer BY15 generated the highest number
of polymorphic fragments (82.4%), distinguishing sa-
mples on the basis of the total of molecular products
amplified. Primers DN5, BY12 and UB28 also revealed
high polymorphism (ranging from 54.6% to 66.7%).
UPGMA cluster analysis (Figure 5) confirmed that
similarity between samples is very high (the lowest ge-
netic similarity being 0.82). The average of all similarity
coefficients among the samples is 0.87 ± 0.03. More-
over, samples from the same station always cluster in a
Figure 3. “A” Coefficient A) and LAI/shoot; B) variation with depth (m).
Figure 4. Mean total phenol content in the entire rhizome A) and in each rhizome section;B) , bars indicate standard deviations),
recorded in both Santa Marinella (SM) and Talamone (T) meadows. Significant differences between Santa Marinella and Talamone
were found both in the entire rhizome (F = 656.6; p < 0.01) and among sections (indicated by a star; = p < 0.01).
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
Copyright © 2011 SciRes. OPEN ACCESS
Figure 2. UPGMA phenogram constructed from matrix of RAPD-based genetic distances among PO plants from
the Santa Marinella meadow. It is worth to note that each cluster gathers individuals from the same area of the
group (Figure 5). The Mantel test, comparing Nei’s dis-
tance and cophenetic matrices, revealed a strong and sta-
tistically significant correlation between genetic and geo-
graphic distance (r = 0.9, p0.01).
The genetic analysis conducted in Santa Marinella
meadow demonstrates a low variability in each specimen
resulting in a high similarity value within the population
(0.87). This result suggests a restricted gene flow within
A. Rotini et al. / Open Journal of Ecology 1 (2011) 48-56
Copyright © 2011 SciRes. OPEN ACCESS
the population, i.e. the predominance of the clonal
growth. The 0.87 similarity value is much higher than
the one found for the Monterosso al Mare meadow (0.66)
[13], where natural and anthropogenic pressures were
low (being part of the bed inside the ‘Cinque Terre’ Na-
tional Park, Liguria, Italy) [52-53]. The value is even
higher than the one found at the Mediterranean basin
scale (0.81) [13].
These results confirm that RAPDs, as the total phe-
nols, give sound informations on the meadow. The ap-
proach is repeatable and uncomplicated, and it could be
useful introduced in the set of test to state the conserva-
tion of PO meadows.
In this study we demonstrate that the measure of total
phenols and RAPD diversity (putative approaches) in
PO, give the same picture of the meadow conservation
as the classical measure of density, leaf biometry, LAI
and rhizome production. According to standard indica-
tors, the Santa Marinella meadow is defined “disturbed
bed”, under regression, showing high spatial heterogene-
ity and low productivity; likewise, the high levels of
total phenols identify the endangered conservation status
of the meadow, showing to be a possible biomarkers of
environmental quality. Additional research will be nec-
essary to state the level of phenol concentration in dif-
ferent meadows under different environmental condi-
tions and to define thresholds for classifying the differ-
ent level of perturbation. Furthermore, a similar protocol
was successfully applied on another seagrass (Zostera
noltii), opening interesting perspectives on the applica-
tion of the phenol content on a large number of marine
phanerogames. The endangered conservation status of
the meadow is also identified by the low genetic vari-
ability (as RAPD markers). Although genetic variability
is low in some other cases [35] and can depend on dif-
ferent processes, this measure can properly contribute to
assess the meadow conservation.
The two putative approaches should be used together
with the standard techniques to better depict the conser-
vation status of the meadows. This is in agreement with
the epidemiological approach, i.e. the use of various
lines of evidence indipendently, validated by weight of
evidence [54-55]. This epidemiological approach has
been successfully applied in estuarine ecosystems, to
evaluate that the changes produced in a community
structure were due to environmental pressure and not to
natural variability [56].
Furthermore, this picture of the Santa Marinella
meadow (2004 samples) represents a baseline for future
comparison, to state possible changes occurring in the
Santa Marinella meadow as a response of the continuous
anthropogenic pressure in the area.
These results highlight the interest on both the two
putative tools, which are able to link plant ecophysiol-
ogy and biodiversity to ecosystem ‘health’. The most
remarkable feature of these approaches is their feasibil-
ity and unexpensiveness that make easy the introduction
in meadows monitoring. Furthermore, we wish to apply
the two putative approaches on other PO meadows and
other seagrasses to validate the methods for broader ap-
plication; after such studies the proposed methodologies
might be reccomended for seagrass meadow monitoring.
The authors are gratefull to Francesca Romana Onofri, who kindly
revised and improved the manuscript, and to the anonymous reviewer
who upgraded the manuscript.
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