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The changes in spatial distribution of intertidal Zostera noltii seagrass beds were studied with multispectral visible-infrared remote sensing in Bourgneuf Bay (France) over a 14-year period, between 1991 and 2005. Six SPOT satellite images acquired at low tide were calibrated using in situ spectroradiometric data and processed with the Normalized Difference Vegetation Index (NDVI). A steady and linear increase in meadow areas was observed between 1991 and 2005 with total surfaces colonized by Z. noltii increasing from 208 to 586 ha, respectively. A greater increase in the densest part of the meadow (NDVI > 0.4) was also observed: it represented only 15% of total meadow surfaces in 1991 vs. 35% in 2005. The seagrass expansion took place mainly towards the lower part of the intertidal zone, while in the upper intertidal zone the meadow appeared strictly limited by the +4 m (Lowest Astronomical Tide) bathymetric level. The influence of Z. noltii above-ground biomass variations on spectral reflectance was analyzed experimentally by spectrometry. Z. noltii displays a characteristic steep slope from 700 to 900 nm, increasing with increasing biomass. A quantitative relationship obtained experimentally between NDVI and the dry weight of leaves was used to produce a biomass distribution map. The distribution of Bourgneuf Bay intertidal seagrass beds is certainly constrained by the water turbidity and we suggest that tidal flat accretion could be a significant variable explaining the observed expansion downwards. With very limited spatial interactions, oyster aquaculture cannot be considered as a threat, while a recent increase in recreational hand fishing of Manila clams within the beds could become problematic.
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Increase in seagrass distribution at Bourgneuf Bay (France) detected by spatial
remote sensing
Laurent Barille
*, Marc Robin
, Nicolas Harin
, Annae
¨lle Bargain
, Patrick Launeau
´de Nantes, Equipe Mer-Molecules-Sante
´EA 2160, Faculte
´des Sciences et des Techniques, B.P. 92 208, 44322 Nantes Cedex 3, France
´de Nantes, LETG Littoral, Environnement, Te
´tection, Ge
´omatique (GEOLITTOMER), UMR CNRS 6554, chemin la Censive du Tertre, B.P. 81227, 44312 Nantes Cedex 3,
Bio-Littoral, Faculte
´des Sciences et des Techniques, B.P. 92 208, 44322 Nantes Cedex 3, France
´de Nantes, Laboratoire de Plane
´tologie et Ge
´odynamique, Faculte
´des Sciences et des Techniques, B.P. 92 208, 44322 Nantes Cedex 3, France
1. Introduction
Historically, information on seagrass distribution has been
obtained by field mapping and aerial photography. However, these
methods do not allow synoptic coverage for large stands of
seagrass. Aerial photography with its high spatial resolution may
remain relevant up to macroscale meadows (Kendrick et al., 2000;
McKenzie et al., 2001), but the specific spectral properties of
seagrass, related to the reflected sunlight in the visible and near-
infrared parts of the electromagnetic spectrum (Fyfe, 2003), cannot
be exploited with panchromatic photographs. The advances in
satellite remote sensing, with higher spatial and spectral resolu-
tion, as well as repeatability, now provides opportunities for cost-
effective qualitative and quantitative mapping, particularly for
large, monospecific meadows (Zacharias et al., 1992; Dekker et al.,
2006; Phinn et al., 2008). This study examined the spatial
distribution and the development of Zostera noltii Hornem.
seagrass beds in the intertidal area of Bourgneuf Bay (France)
using multispectral remote sensing. Multispectral imagery with
low spectral resolution (limited number of broad spectral bands)
has been successfully used to detect temporal changes in large and
remote seagrass beds (Ward et al., 1997; Dekker et al., 2005), and
appears well suited to assess the areal extent and spatial variations
of monospecific meadows. Intertidal Z. noltii beds are common in
the Northern Hemisphere, widely distributed along the north-
eastern coasts of the Atlantic, extending from the north of United
Kingdom to Mauritania (Green and Short, 2003). This species
colonizes sandy-muddy soft bottoms of shallow sheltered bays,
and has developed the most extensive western European meadow
in Arcachon Bay along the Atlantic coast, covering an area of ca.
70 km
in 1984 (Auby and Labourg, 1996).
Monospecific intertidal seagrass beds provide simplified case-
study for remote-sensing applications. The discrimination with
other benthic species is not an issue as critical as it can be in
rocky environments since macroalgae usually do not grow on
soft bottom sediments, while the absence of water column,
Aquatic Botany xxx (2009) xxx–xxx
* Corresponding author. Tel.: +33 02 51 12 56 55; fax: +33 02 51 12 56 68.
E-mail address: (L. Barille
Article history:
Received 27 February 2009
Received in revised form 14 November 2009
Accepted 17 November 2009
Available online xxx
Seagrass distribution
Shellfish ecosystem
Visible-infrared remote sensing
Zostera noltii
The changes in spatial distribution of intertidal Zosteranoltii seagrass beds were studied with multispectral
visible-infrared remote sensing in Bourgneuf Bay (France) over a 14-year period, between 1991 and 2005.
Six SPOT satellite images acquired at low tide were calibrated using in situ spectroradiometric data and
processed with the Normalized Difference Vegetation Index (NDVI). A steady and linear increase in
meadow areas was observed between 1991 and 2005 with total surfaces colonized by Z. noltii increasing
from 208 to 586 ha, respectively. A greater increase in the densest part of the meadow (NDVI >0.4) was
also observed: it represented only 15% of total meadow surfaces in 1991 vs. 35% in 2005. The seagrass
expansiontook place mainly towards the lower part of theintertidal zone, while in the upper intertidalzone
the meadow appeared strictly limited by the +4 m (Lowest Astronomical Tide) bathymetric level. The
influence of Z. noltii above-ground biomass variationson spectral reflectance was analyzedexperimentally
by spectrometry. Z. noltii displays a characteristic steep slope from 700 to 900 nm, increasing with
increasingbiomass. A quantitative relationship obtainedexperimentally between NDVI and the dry weight
of leaves was used to produce a biomass distribution map. The distribution of Bourgneuf Bay intertidal
seagrass beds is certainly constrained by the water turbidity and we suggest that tidal flat accretion could
be a significant variable explaining the observed expansion downwards. With very limited spatial
interactions, oyster aquaculture cannot be considered as a threat, while a recent increase in recreational
hand fishing of Manila clams within the beds could become problematic.
ß2009 Elsevier B.V. All rights reserved.
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´, L., et al., Increase in seagrass distribution at Bourgneuf Bay (France) detected by spatial remote
sensing. Aquat. Bot. (2009), doi:10.1016/j.aquabot.2009.11.006
Contents lists available at ScienceDirect
Aquatic Botany
journal homepage:
0304-3770/$ – see front matter ß2009 Elsevier B.V. All rights reserved.
considerably reduces the complexity of light interactions at the
air–water interface and through the water column (Dekker et al.,
2006). This situation is therefore favorable to retrieve biomass or
abundance from remote sensing images. This can be achieved
using empirical relationships between a spectral index and
seagrass biomass measurements (Armstrong, 1993; Mumby
et al., 1997), but has seldom been applied to multispectral
imagery. This is mostly due to the fact that benthic environments
are inherently heterogeneous and that a low spectral resolution
does not allow a rigorous deconvolution of spectral signatures for
mixed pixels with different type of vegetation.
In this study we document the application of a satellite image
time-series to map changes of intertidal seagrass beds over a 14-
year period, on the north-west coast of France. SPOT multispectral
imagery (visible near-infrared) combined with in situ spectro-
radiometric field measurements were used to obtain spatial
distribution maps from which observed changes are discussed in
the context of local threats. In spite of the monospecific nature of
the intertidal seagrass beds studied, a comparison between
spectral reflectance of other benthic photoautotrophs was
performed. Eventually, we propose a quantitative relationship
between a vegetation index and Z. noltii above-ground biomass,
which may be applied to monospecific meadows. This relationship
was applied to one image and the resulting biomass distribution
map was critically evaluated.
2. Materials and methods
2.1. Study site
Bourgneuf Bay, located south of the Loire estuary on the French
Atlantic coast (4780
N, 2810
W) (Fig. 1), is a macrotidal bay with a
maximum tidal amplitude of 6 m during spring tides, receiving
freshwater inputs from a 980 km
watershed, which includes
350 km
of marshes adjacent to the bay. The bay total surface area
is 340 km
, of which 100 km
are constituted by the intertidal
zone. It is a site of extensive aquaculture of the oyster Crassostrea
gigas (Thunberg), ranking sixth in France with a production of 8600
metric tons on 1000 ha of intertidal cultures (2001 data). Oysters
are grown in plastic bags placed on racks, 70 cm from the bottom.
This bay is highly turbid with annual mean concentrations of
suspended particulate matter ranging from 27 to 129 mg l
according to a south–north gradient and with maximum values
during spring tides. Z. noltii beds occur in the western part of
the bay, protected from the Atlantic swell by Noirmoutier Island
(Fig. 1). There is a striking geomorphological analogy with their
location in the southward Marennes-Ole
´ron Bay (45855
W), where they are similarly protected by Ole
´ron Island
(Guillaumont, 1991). Early studies mentioned the presence of
intertidal meadows in Bourgneuf Bay (Gehu, 1976; Gruet, 1976),
while regional reports roughly located seagrasses based on field
observations (Bredin and Me
´tais, 1982). Z. noltii has never been
found in the Bourgneuf Bay subtidal zone, whereas some sparse
stands of Zostera marina were found there 40 years ago (Gruet,
1976). The latter species was observed during this study, forming
isolated patches in intertidal pools, generally near oyster-
farming sites. Z. noltii grows as monospecific stands in sandy-
muddy sediment, stretching out along the shoreline, in areas
unoccupied by oyster-farming (Fig. 1).
2.2. Satellite imagery
Six SPOT multispectral satellite images were chosen according
to optimal imaging criteria for the acquisition of seagrass
Fig. 1. Bourgneuf Bay (France) showing the location of the main Zostera noltii beds ($). Note the presence of oyster-farming sites in the intertidal zone. The dotted rectangle
indicates the portion of SPOT scenes displayed in Fig. 5.
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´et al. / Aquatic Botany xxx (2009) xxx–xxx
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sensing. Aquat. Bot. (2009), doi:10.1016/j.aquabot.2009.11.006
distributional data (Orth and Moore, 1983): tidal stage, plant
growth, sun angle, and atmospheric conditions. They were
acquired at low tide, during spring tides cycle, with the satellite
acquisition coinciding on the French Atlantic coast with low tides
around noon (Table 1). All the images were acquired for cloud-free
conditions (<10%) and an almost zenithal sun. They covered a
period ranging from mid-August to mid-September, and one image
was taken in mid-October. The Z. noltii biomass cycle in Western
Europe is characterized by a unimodal distribution, with a
maximum development in summer (Philippart, 1995; Auby and
Labourg, 1996; Vermaat and Verhagen, 1996) and Bourgneuf Bay
seagrass beds follow a similar pattern (Harin, pers. comm.). The
images, therefore, encompass the period of maximum above-
ground biomass that can be remotely sensed. It was decided to
process the October 1997 image in spite of the delay to catch the
maximum biomass, because an important variation occurred
between 1996 and 1998. SPOT images were calibrated to
reflectance with the empiric line method (Smith and Milton,
1999), using bright (white) and dark (black) references on the field
and the image (dry sand in the upper beach, 4784
45N, 282
and non-turbid water pond, 4784
7N, 288
W). Spectral responses of
the targets were obtained with a GER 3700 (Geophysical and
Environmental Research Corporation) field portable spectroradi-
ometer, measuring the radiance (mW cm
) between
350 and 2550 nm. They were resampled to SPOT-HRV sensor
spectral resolution and regressions were calculated between in situ
targets reflectance and target digital numbers retrieved from each
image. More details of the calibration are provided in Me
´der et al.
(2003a). The scenes were registered in the French coordinates
system Lambert II, using an array of control points scattered over
the body of the images. The intertidal zone is delimited at its lower
range by the 0 m LAT (Lowest Astronomical Tide).
2.3. Field and laboratory spectrometry
Prior to image processing, field spectral measurements were
obtained with a GER 3700 spectroradiometer. Spectral responses of
the main macrophytes and sediments found in the intertidal area
within and outside seagrass beds were recorded in the visible near-
infrared range between 400 and 900 nm, as absorption by residual
water of the intertidal flats is strong over 900 nm. The spectral
sampling interval is 1.5 nm for this wavelength range with a Full
Width Half Maximum of 3 nm. Seagrass leaves and macroalgae
thalli were piled on a black background in several layers to obtain a
pure signal. After a spectral resampling to SPOT-HRV sensor
spectral resolution, mean reflectances (n= 5) for each spectral
band were compared with analysis of variance (ANOVA) and a
posteriori Tukey-tests. Spectra of benthic diatom biofilms, experi-
mentally obtained by Me
´der et al. (2003b), were added for
spectral comparison. The influence of variation in Z. noltii biomass
on reflectance spectra was investigated in November 2005 and July
2006 through an experimental addition and removal of leaves to
and from an 80 cm
surface matching the spectroradiometer Field-
Of-View (FOV). The measurements ranged from an unvegetated
substratum to overfilling the FOV with seagrass leaves, progres-
sively adding several layers to detect a saturation process. Leaves
were subsequently dried at 60 8C for 48 h and weighed (dry
weight: DW). Biomasses were reported in relation to surface area
and expressed by surface unit, in mg DW m
. The data were
modeled by an hyperbolic function of Michaelis–Menten type:
+ biomass), where NDVI
are two parameters, respectively the NDVI at saturation and
the biomass at which the NDVI reaches half of its maximum value.
Microscopic examinations revealed that the leaves were colonized
by the diatom Cocconeis scutellum Ehrenberg and it was decided to
keep this microscopic epiphyte to conform to the remotely sensed
field situation.
2.4. Image processing
The Normalized Difference Vegetation Index (NDVI; Tucker,
using red (XS2: 610–680 nm) and near-infrared (XS3: 780–
890 nm) SPOT spectral bands: NDVI = [
(XS3) +
(XS2)].This index was chosen among various vegeta-
tion index because it provided very similar results with soil-
corrected indices such as SAVI (Huete, 1988), MSAVI (Qi et al.,
1994) or TSAVI (Baret et al., 1989). In a preliminary study on
microphytobenthos spatial distribution in Bourgneuf Bay (Me
der et al., 2003a), a micro- ormacrophyte distinction was achieved
using threshold values, determined using spectrometric knowl-
edge, image analysis and ground-truthing. This method was
combined here with a Geographical Information System (GIS)
overlay processing (Fig. 5), to focus on intertidal seagrass beds,
using bathymetric data (exclusion of subtidal area), and substrate
information (exclusion of rocky areas with macroalgae). Never-
theless, confusion between low coverage of seagrass and
sediment colonized by microphytobenthos remained possible
in the intertidal zone. A threshold on the NDVI range was therefore
applied, using their respective spectral features and the knowl-
edge gained from previous studies of microphytobenthos in
Bourgneuf Bay (Me
´der et al., 2003a; Combe et al., 2005).
Moreover, in situ spectral measurements of bare sediments were
collected within the meadow, and their NDVI calculated. Above
this threshold, the NDVI range was related to Z. noltii biomass
variation and it was subdivided into two classes to visualize the
densest areas of the meadows, arbitrarily chosen above an NDVI
value of 0.4. A quantitative relationship was established with the
spectrometric data between NDVI and biomass, after a spectral
resampling from GER 3700 to SPOT spectral resolution. The
relationship was then applied to the September 2005 image
calibrated in NDVI. It was thus assumed that each pixel was
homogeneous and that seagrass/sediment spectral mixing was
characterized by surfacic (linear) mixtures (vs. intimate mixtures,
Combe et al., 2005). Indeed, the experimental NDVI–biomass
relationship is characterized firstly by surfacic mixtures between
seagrass and sediment (linear portion of the relationship), while
above a saturation threshold corresponding to 100% seagrass
coverage, the spectral responses are characterized by intimate
mixtures (increasing leaves layers). Synchronous ground truth
data were not available to test the accuracy of the resulting
biomass distribution map. However, two transects perpendicular
to the shoreline were applied on the biomass map, in the main
seagrass stands, with a systematic random sampling every 36 m
(n= 39). To assess the consistency of the mean biomass retrieved
from the image, it was compared with September 2006 biomass
measurements, sampled in situ with a 12.5 cm sediment core, and
also with data available from nearby ecosystems of the French
Atlantic coast.
Table 1
Satellite imagery used to assess Z. noltii spatial distribution in Bourgneuf Bay
(France). U.T. = universal time.
Acquisition date Pixel
Time of
Time of low
tide (U.T.)
SPOT 2 August 28, 1991 20 11:37 11:39
SPOT 2 August 20, 1993 20 11:33 11:35
SPOT 2 September 16, 1996 20 11:30 11:47
SPOT 1 October 18, 1997 20 11:11 12:37
SPOT 1 September 21, 1998 20 11:27 11:15
SPOT 5 September 18, 2005 10 11:29 9:58
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sensing. Aquat. Bot. (2009), doi:10.1016/j.aquabot.2009.11.006
3. Results
3.1. Spectral reflectance
Field reflectance spectra of the main benthic photoautotrophs
of Bourgneuf Bay intertidal zone presented different overall shapes
in the visible near-infrared (NIR) range between 400 and 900 nm
(Fig. 2A). Both seagrass species, Z. noltii and Z. marina, are
characterized by a common reflectance between 500 and 600 nm,
but share this spectral feature with green macroalgae (Chlor-
ophyta). NIR reflectances, however, allow discrimination between
these two types of vegetation. Moreover, Z. noltii has a distinct NIR
spectral response compared to Z. marina, with a characteristic
steeper increasing slope from 700 to 900 nm (Fig. 2A). Brown
macroalgae of the Fucus species are very common on the rocky
areas of the bay. They can be easily discriminated by their high NIR
reflectance and a flat spectral form in the visible, due to their
efficient pigment absorption. Benthic diatoms have a distinct
spectral response in the visible compared to seagrasses and a lower
NIR reflectance. Nevertheless, after a spectral resampling from
1.5 nm (spectroradiometer, 327 spectral bands from 400 to
900 nm) to the ca. 100 nm SPOT three spectral bands (Fig. 2B),
the differences disappeared in the first two spectral bands in the
visible (ANOVA, respectively p= 0.86 and p= 0.76) while it
remained significant in the NIR (ANOVA, p<0.05). However, the
two seagrass species could no longer be discriminated for these
wavelengths (Tukey-test, p= 0.62). Moreover, the overall shape of
their degraded spectral signature tended to resemble that of
benthic diatoms, knowing that NIR distinction between angios-
perms and microalgae may be attenuated by biomass variation,
particularly at low Zostera cover.
The analysis of Z. noltii spectra for a wide range of biomass
confirmed this hypothesis. At the lowest biomass, with a few
leaves on the sediment, Z. noltii has a spectral response similar to
that of a benthic diatom biofilm on a muddy substrate (Fig. 3;
compare with Combe et al., 2005,Fig. 5). However, a distinction
can be made as soon as the characteristic Z. noltii NIR slope is
observed, as shown in Fig. 3, with the spectrum indicated by the
thick arrow. With increasing biomass, the seagrass reflected more
light in the NIR wavelength range, with increasing positions of the
NIR slope, while the 675 nm absorption band, due to chlorophyll a,
is deepening. An NDVI of 0.21 was calculated from the first
spectrum clearly identifiable as an angiosperm response. In situ
Fig. 2. Spectral signatures of the main intertidal vegetation in Bourgneuf Bay: the
seagrasses Zostera marina and Zostera noltii, the ubiquitous pheophyte Fucus
vesiculosus, the chlorophyte Ulva sp. and benthic diatoms. (A) Each spectrum
acquired at the spectral resolution of a GER 3700 spectroradiometer and (B)
averaged spectra (n= 5) degraded at SPOT spectral resolution. Histograms
represent the position of SPOT spectral bands in the visible and the NIR.
Confidence intervals not represented for clarity.
Fig. 3. Spectral signatures of increasing biomass of Zostera noltii leaves on natural
sediment. Thin arrows correspond to muddy-sandy substrate with a few seagrass
leaves (lowest fractional cover <5%). These spectra can be confused with spectra of
benthic diatom biofilms (Me
´der et al., 2003a). The thick arrow indicates the NIR
slope increase, characteristic of Zostera noltii.
Fig. 4. (A)Relationship between NDVI and Z. noltii above-ground biomass, obtained
at two different dates (black square: November 2005; empty square: July 2006). The
data were fitted with the saturation curve (solid black line, r
= 0.98):
NDVI = (0.87 biomass)/(112.49 + biomass). These data are compared with the
relationship obtained by Guillaumont (1991), dashed line and (B)inverse empirical
relationship: biomass = 610.61 (NDVI)
(n= 31, r
= 0.97), used to calibrate the
2005 SPOT image in biomass.
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´, L., et al., Increase in seagrass distribution at Bourgneuf Bay (France) detected by spatial remote
sensing. Aquat. Bot. (2009), doi:10.1016/j.aquabot.2009.11.006
spectral measurements of the sediment within the meadow but
without seagrass, systematically showed a discernible 675 nm
absorption band associated to a 632 nm diagnostic absorption,
revealing the presence of benthic diatoms, but the NDVI obtained
from each field spectrum never exceeded 0.2 (mean = 0.13;
S.D. = 0.04).
The relationships between NDVI and Z. noltii biomass,
observed at two different dates, are consistent with the
early data of Guillaumont (1991) (Fig. 4A). It was described
by a significant saturation function (r
= 0.98, p<0.001):
NDVI = (0.87 biomass)/(112.49 + biomass). The NDVI increases
linearly up to the biomass at which it reaches half of its maximum
value, K
= 112.49 g DW m
, and begins to saturate above this
value. An inverse empirical relationship: Biomass = 610.61
(n= 31, r
= 0.97) was calculated for SPOT image
calibration, pooling all the data (Fig. 4B).
3.2. Development of seagrass beds
SPOT images calibrated in NDVI were analyzed following
simple decision rules (Table 2). Seagrass beds were mapped using
the 0.2–0.7 NDVI range, excluding the values for which low
seagrass coverage can be confused with microphytobenthos. An
increase in meadow areas is observed between 1991 and 2005
(Fig. 5), with total surfaces colonized by Z. noltii of 208 and 586 ha,
respectively (Table 3). This evolution can be described by a
significant linear relationship (not shown, r
= 0.90). A greater
increase was also observed in the densest part of the meadow
(NDVI >0.4): it represented only 15% of total meadow surfaces in
1991 vs. 35% in 2005 (Fig. 5 and Table 3). The examination of the
evolution of the dense meadow areas for the main stand of
Bourgneuf Bay indicated that the seagrass extension took place
mainly towards the lower part of the intertidal zone, while in the
upper intertidal zone the meadow appeared strictly limited by the
+4 m LAT bathymetric level (Fig. 6). At the maximal extension in
2005, the meadow reached its lowest limit downwards around the
isobath +2 m LAT.
The calibration of the September 2005 image with the biomass-
NDVI relationship showeda pattern with maximum biomass around
+3.5 m LAT and lower biomass in the upper intertidal and lower
intertidal zones (Fig. 7). The biomass range varied from 29 to
312 g DW m
, and the mean biomasses retrieved from the image in
the two transects (Fig. 7), were, respectively, 129.7 g DW m
(southern transect, S.D. = 82.2 g DW m
,n= 39) and 153.2 g
DW m
(northerntransect, S.D. = 70.5 g DW m
,n= 3 9). The mean
biomass measured in situ in September 2006 in the southern stand,
150.9 g DW m
(S.D. = 65.9 g DW m
,n= 11), was not significant-
ly different from the value obtained in 2005 (t-test, p= 0.75).
4. Discussion
4.1. Seagrass spectral reflectance
Both seagrass species were spectrally distinct from macro- and
microalgae, particularly at NIR wavelengths. This NIR distinction
was still present at SPOT-HRV sensor spectral resolution, while no
differences could be detected in the visible range. This confirms the
relevance of the 700–900
m wavelength range for mapping
intertidal vegetation compared to submerged vegetation with a
low NIR signal (Armstrong, 1993). However, residual water layers
on the tidal flats affect NIR reflectance as soon as 800
et al., 2005). At high spectral resolution, Z. noltii may be
distinguished from Z. marina using their respective NIR slope
features, which might be related to the influence of epibionts (Fyfe,
2003). Indeed, Armstrong (1993) reported a similar slope increase
in NIR reflectance for a Thalassia testudinum leaf fouled by algal
epiphytes vs. a green unfouled one. The same pattern was observed
for Posidonia australis (Fyfe, 2003). The Z. noltii NIR specific
response may be due to the diatom Cocconeis scutellum, which
forms a monolayer of cells at the leaf surface (Lebreton et al., 2009).
However, diatom biofilms are partially transparent and their
spectral response is fundamentally influenced by the substratum
in the NIR (Me
´der et al., 2003b). It was beyond the scope of this
work to analyze this phenomenon further, but we suggest that Z.
noltiiC. scutellum represents an attractive duo for future
spectroscopic studies of epiphytism.
Field investigations in 2005 showed that Z .noltii was the main
living macrophyte in the mapped intertidal area, while a few
senescent drifting macroalgae were occasionally present. The
summer development of filamentous green macroalgae observed
in the southern Marennes-Ole
´ron meadow (Barille
´, pers. comm.,
2006) did not occur in Bourgneuf Bay. The spectral detection of
vegetation equated to the detection of Z. noltii, even though
confusion with microphytobenthos could occur at the lowest
reflectance values. The NDVI threshold proposed in this study, to
discriminate seagrass from benthic diatoms, may not be restrictive
enough for the angiosperm. However, high biomass benthic
diatoms biofilms do not occur in the sandy-muddy meadow,
contrary to the eastern mudflats of the bay, where mesoscale
epipelic assemblages, characterized by NDVI values up to 0.3, have
previously been remotely sensed with SPOT multispectral images
´der et al., 2003a). This threshold may also erroneously detect
seagrass when sparse macroalgae are found attached to endofau-
nal bivalve shells, which may happen in the bay. The validity of this
threshold should be tested in future investigations, since it has a
strong influence on total surface estimation. A higher spectral
resolution would allow a finer discrimination using characteristic
absorption features in the visible wavelength range. A number of
analytical techniques are available for estimating biomass from
reflectance spectra (Murphy et al., 2005) but their application at
the ecosystem level depends on the availability of hyperspectral
images. Simple multispectral band-ratio indices should be
compared with other hyperspectral indices, such as the Red Edge
Inflection Point, commonly used for terrestrial vegetation (Black-
burn, 1999), and those estimated from the derivative analysis
(Demetriades-Shah et al., 1990), or retrieved after Gaussian
deconvolution (Barille
´et al., 2007). The actual NDVI-based biomass
calibration applied to the SPOT image provided biomass values
consistent with field data, though not synchronous. However, they
are also consistent with summer maximal above-ground biomass
measured in nearby ecosystems, namely the southern Arcachon
Bay (110–150 g DW m
) and the northern Morbihan Gulf (70–
120 g DW m
)(Auby and Labourg, 1996). Nevertheless, the
robustness of this quantitative relationship should be tested over
an annual cycle to account for pigment variability linked to the
irradiance seasonal cycle (Jime
´nez et al., 1987). In addition, the
reflectance saturation process at increasing biomass must be
further investigated, since it will set a limit on the detection of the
highest biomass.
4.2. Seagrass beds at Bourgneuf Bay
A significant linear increase in seagrass areal extent was
observed over a 14-year period from 1991 to 2005, with a
Table 2
Decision rules used to characterize Z. noltii seagrass beds with the Normalized
Difference Vegetation Index (NDVI).
NDVI range Description
1 to 0 Turbid water and bare sediment
0 to 0.2 Sediment with microphytobenthos and/or low Z noltii cover
0.2 to 0.7 Z. noltii with biomass variations
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Fig. 5. Evolution of the spatial distribution of Zostera noltii seagrass beds from 1991 to 2005. Seagrasses are mapped using the 0.2–0.7 NDVI range, excluding the values for
which low seagrass coverage can be confused with microphytobenthos biofilms. The densest part of the meadows was identified by an NDVI range from 0.4 to 0.7. Map
coordinates in Lambert II extended.
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concomitant higher increase in the densest part of the meadow.
Similar increase in seagrass cover has been reported for the nearby
Brittany region (Hily et al., 2003) and in the Wadden Sea (Reise and
Kohlus, 2008). This trend diverges from the overall decline in
seagrass habitats recognized worldwide (Short and Wyllie-
Echeverria, 1996; Orth et al., 2006). A posteriori interpretations
trying to relate this expansion with partial historical data is not
straightforward and the plausibility of explanatory mechanisms is
presented Table 4. The Bourgneuf Bay environment is character-
ized by limited direct freshwater inputs from the adjacent marshes
and cultivated land upstream (annual average daily-flow rate of
the main outlet <6m
´-Boyer et al., 1997). The influence
of the Loire River, which may be crucial with respect to the fluvial
discharge (annual average of ca. 1000 m
) remains controver-
sial (Gouleau, 1975; Barille
´-Boyer et al., 1997 but see Froidefond
et al., 2003). Nutrients of the Loire River did not show a significant
increase from 1985 to 2003 (RNO, 2003) except for nitrates, which
steadily increased up to 1998 and then declined. This decline may
have limited the periphyton load on the seagrass leaves, therefore
improving the light conditions. Suspended particulate matter
concentrations within the bay did not show any trend in the past
two decades, with semi-diurnal tidal variations equivalent to the
annual variability (Haure and Baud, 1995). A possible explanation
of the bed extension can be linked to the tidal flat accretion
estimated by Gouleau (1975) at +0.01 m year
, a conservative
estimate obtained during drought periods with low fluvial
discharges. A 14 cm positive accretion, estimated for this study,
may have increased the duration of emersion and thus improved
the seagrass light history conditions in the mid-intertidal zone, as
suggested by the observed expansion downwards. Vermaat and
Verhagen (1996) have shown that Z. noltii photosynthesis largely
during low tide in a similar turbid estuary. Meanwhile, the upper
limit of the meadow remained almost unchanged, with a marked
Table 3
Development of the total surface in hectares (ha) and percentage of the densest part
of the meadow of Zostera noltii seagrass bed in Bourgneuf Bay from 1991 to 2005,
estimated by multispectral remote sensing. The densest part of the meadows was
characterized by NDVI values >0.4 (see Fig. 5).
Years Total surface (ha) Fraction of dense meadow (%)
1991 208 17
1993 236 8
1996 249 19
1997 313 30
1998 423 32
2005 586 34
Fig. 6. Spatial evolution of the dense Zostera noltii meadow areas (NDVI >0.4) from 1991 to 2005 for the main stand of Bourgneuf Bay. Map coordinates in Lambert II extended.
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delimitation probably reflecting a physiological threshold above
which the negative effects of desiccation cannot be counter-
balanced (Keller and Harris, 1966). Light availability is probably
one of the most significant factors explaining Z. noltii spatial
distribution in Bourgneuf Bay, being severely restricted by
turbidity and reaching its highest values around low tide,
according to a typical tidal resuspension process. The potential
positive co-influence of a temperature and carbon dioxide increase
linked to global climate change (Short and Neckles, 1999) remains
hypothetical but, in Bourgneuf Bay, the increase in water
temperature has already boosted the reproduction of cultivated
oysters, with an unexpected proliferation of feral populations
disseminated from oyster-farming sites (Cognie et al., 2006;
Dutertre et al., in press). The annual changes in insolation do not
show however a similar increasing pattern. The 14-year expansion
described in this study has to be confirmed since Z. noltii meadows
can be highly dynamic over short time scales (Philippart and
Dijkema, 1995; Charpentier et al., 2005). Nevertheless, Bourgneuf
Bay is an open coastal bay less sensitive to large fluctuations and
extreme events than enclosed systems (Frederiksen et al., 2004).
The observed gradual linear increase indicates that the 1999
winter storm, which broke sea dikes and spilled heavy fuel oil from
Fig. 7. Spatial distribution of the above-ground biomass of Zostera noltii beds in Bourgneuf Bay. Calibration of the September 2005 SPOT image with the biomass–NDVI
relationship (Fig. 4B). The biomass range varied from 29 to 312 g DW m
, and the mean biomasses retrieved from the image in the two transects T1 and T2 were respectively
129.7 g DW m
, (S.D. = 82.2 g DW m
,n= 39) and 153.2 g DW m
(S.D. = 70.5 g DW m
,n= 39). Map coordinates in Lambert II extended.
Table 4
Possible explanatory mechanisms for the downward expansion of Zostera noltii beds from 1998.
1. More light (a) A trend exists in increasing light fluxes at the water surface No trend detected (1970–2005)
(b) Tidal emersion pattern changes, due to local accretion Local accretion observed
(c) Attenuation declines due to less resuspension, less
phytoplankton or less periphyton
Periphyton reduction plausible: reduction in
nutrient load observed
2. Higher temperature Net photosynthesis increases due to changing temperature Not very plausible (optimum curve)
3. Sediment becomes suitable Absence of previously intense bioturbation No data
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the Erika into the bay (Laubier et al., 2004), did not significantly
affect the seagrass abundance, as confirmed by field observations.
The analysis of recent SPOT images, along with historical aerial
photographs (back to 1932, Gle
´marec et al., 1997) should bring a
wider temporal perspective of Z. noltii variations in the bay.
Eventually, the absence of a previously intense bioturbation, which
may have limited the spread of intertidal seagrass before 1998
(Philippart, 1994; Dumbauld and Wyllie-Echeverria, 2003),
remains hypothetical (Table 4).
4.3. Local threats for Z. noltii seagrass beds
Oyster aquaculture is a significant coastal activity in the bay.
Oyster-farming structures occupy ca. 10% of the intertidal area, and
seagrass beds are surrounded by oyster-farming sites. In the
northern part of the bay, these sites are closely connected with the
lower distribution range of Z. noltii beds, but overlapping remain
limited (Fig. 7). However, the possible extension or redistribution
of farming sites in the vicinity of seagrasses should be considered
carefully. Despite the generally negative impact of aquaculture
(Short and Wyllie-Echeverria, 1996; Orth et al., 2006), interactions
between seagrass and bivalves are not only unilateral and
detrimental (Alexandre et al., 2005; Dumbauld et al., 2009). In
the similar context of a shellfish ecosystem, Ward et al. (2003) did
not observe any detectable losses of Z. marina beds, despite an
increase in the number of oyster racks. In fact, two positive
feedback interactions have already been identified. Suspension-
feeding bivalves produce a considerable amount of biodeposits
(pseudofaeces and faeces) consisting of a fraction of organic
particles, bound with mucus. The mineralization of these
biodeposits, along with bivalve dissolved excretion, releases
significant amounts of nutrients at the water-sediment interface
(Smaal and Prins, 1993). In the Baltic Sea, Reusch et al. (1994)
showed that the growth of Z. marina was stimulated by the
nutrients released by Mytilus edulis beds. Seagrass may also
become a trophic resource for cultivated bivalves, following the
decomposition of above- and below-ground plant tissues. The
oyster Crassostrea virginica can use refractory C and N from marine
angiosperms after bacterial mediation of detrital complexes
(Crosby et al., 1990). In Bourgneuf Bay, the diet of Crassostrea
gigas, studied in the eastern part of the bay by stable isotope
analysis, was characterized by a substantial contribution of plant
detritus (Decottignies et al., 2006).
A more worrying anthropogenic factor in this bay is the
increasing recreational hand fishing of endofaunal bivalves during
low tide in the Z. noltii beds. In the past 3–4 years, there has been a
significant increase, although not quantified, in a wild population
of Manila clam, Ruditapes phillipinarum. This highly prized
resource, which can be sold at 20 euros per kg, is exploited by
ca. 50 professionals, but also attracts thousands of amateurs,
leading to very destructive practices using various types of rake.
Moreover, the seagrass beds are accessible even during some neap
tides, so there can be almost daily direct mechanical damage. The
repeated stamping is such that wide paths of bare muddy sediment
have been created in the meadows, which can even be detected by
remote sensing. This threat, already mentioned a decade ago (den
Hartog and Hily, 1997), should now be seriously considered but the
current lack of data hampers a rigorous assessment.
Other factors could have a potential impact, although presum-
ably less harmful than the previous one. Bourgneuf Bay intertidal
seagrass should be protected against benthic trawling by a regional
restriction limiting this activity to one nautical mile from the
shoreline, beyond their lower intertidal limits. Examinations of
aerial photographs do not show the characteristic lines of bare
sediment within the beds, resulting from destruction of the habitat
along dredge tracks (Hily et al., 2003). Eventually, the effect of
biomass consumption by the Brent goose Brenta bernicla should be
addressed. Indeed, Bourgneuf Bay is a significant wintering site on
the French Atlantic coast (Mahe
´o, 1994), with a population
reaching ca. 8000 individuals in some years.
The authors wish to thank the CNES (Centre National d’Etudes
Spatiales) for the ISIS program regarding the use of SPOT satellite
products. Two anonymous referees as well as Jan Vermaat, co-
editor of Aquatic Botany provided extensive and constructive
comments, for which we are grateful. Annae
¨lle Bargain was
supported by a PhD scholarship from the Ministe
`re Franc¸ais de la
Recherche et de l’Enseignement Supe
Alexandre, A., Santos, R., Serra
˜o, E., 2005. Effects of clam harvesting on sexual
reproduction of the seagrass Zostera noltii. Mar. Ecol. Prog. Ser. 298, 115–122.
Armstrong, R.A., 1993. Remote sensing of submerged vegetation canopies for
biomass estimation. Int. J. Remote Sens. 14, 621–627.
Auby, I., Labourg, P.-J., 1996. Seasonal dynamics of Zostera noltii Hornem. in the bay
of Arcachon (France). J. Sea Res. 35, 269–277.
Baret, F., Guyot, G., Major, D.J., 1989. TSAVI: a vegetation index which minimizes soil
brightness effects on LAI and APAR estimation. In: Proceedings of the 12th
Canadian Symposium on Remote Sensing, Vancouver, Canada, pp. 1355–1358.
´-Boyer, A.-L., Haure, J., Baud, J.-P., 1997. L’ostre
´iculture en baie de Bourgneuf.
Relation entre la croissance des huı
ˆtres Crassostrea gigas et le milieu naturel:
`se de 1986 a
`1995. Ifremer, Rapports scientifique et techniques de la
direction des ressources vivantes, DRV/RA/RST/97-16.
´, L., Me
´der, V., Combe, J.P., Launeau, P., Rince
´, Y., Carre
`re, V., Moranc¸ais, M.,
2007. Comparative analysis of field and laboratory spectral reflectances of
benthic diatoms with a modified Gaussian model approach. J. Exp. Mar. Biol.
Ecol. 343, 197–209.
Blackburn, G.A., 1999. Relationships between spectral reflectance and pigment
concentrations in stacks of deciduous broadleaves. Remote Sens. Environ. 70,
Bredin, D., Me
´tais, M., 1982. Hivernage de la bernache cravant en baie de Bourgneuf
(Hiver 1981/1982). Rapport L.P.O. Corderie Royale, Rochefort.
Charpentier, A., Grillas, P., Lescuyer, F., Coulet, E., Auby, I., 2005. Spatio-temporal
dynamics of a Zostera noltii dominated community over a period of fluctuating
salinity in a shallow lagoon, Southern France. Estuar. Coast. Shelf Sci. 64, 307–
Cognie, B., Haure, J., Barille
´, L., 2006. Spatial distribution in a temperate coastal
ecosystem of the wild stock of the farmed oyster Crassostrea gigas (Thunberg).
Aquaculture 259, 249–259.
Combe, J.P., Launeau, P., Carrere, V., Despan, D., Me
´der, V., Barille
´, L., Sotin, C., 2005.
Mapping microphytobenthos biomass by non-linear inversion of visible-infra-
red hyperspectral images. Remote Sens. Environ. 98, 371–387.
Crosby, M.P., Langdon, C.J., Newell, R.I.E., 1990. Importance of refractory plant
material to the carbon budget of the oyster Crassostrea virginica. Mar. Biol.
100, 343–352.
Decottignies, P., Beninger, P., Rince
´, Y., Riera, P., 2006. Trophic interactions between
two introduced suspension-feeders, Crepidula fornicata and Crassostrea gigas,
are influenced by seasonal effects and qualitative selection capacity. J. Exp. Mar.
Biol. Ecol. 342, 231–241.
Dekker, A.G., Brando, V.B., Anstee, J.M., 2005. Retrospective seagrass change detec-
tion in a shallow coastal tidal Australian lake. Remote Sens. Environ. 97, 415–
Dekker, A., Brando, V., Anstee, J., Fyfe, S., Malthus, T., Karpouli, E., 2006. Remote
sensing of seagrass ecosystem: use of spaceborne and airborne sensors. In:
Larkum, A.W.D., et al. (Eds.), Seagrass: Biology, Ecology and Conservation.
Springer, pp. 347–359.
Demetriades-Shah, T.H., Steven, M.D., Clark, J., 1990. High resolution derivative
spectra in remote sensing. Remote Sens. Environ. 33, 55–64.
den Hartog, C., Hily, C., 1997. Les herbiers de Zoste
`res. In: Dauvin, J.C. (Ed.), Les
´noses marines et littorales franc¸aises des co
ˆtes Atlantiques, Manche et Mer
du Nord, synthe
`se, menaces et perspectives. Laboratoire de Biologie des Inver-
´s Marins et Malacologie–Service du patrimoine naturel/IEGB/MNHN,
Paris, pp. 140–144.
Dumbauld, B.R., Ruesink, J.L., Rumrill, S.S., 2009. The ecological role of bivalve
shellfish aquaculture in the estuarine environment: a review with application
to oyster and clam culture in West Coast (USA) estuaries. Aquaculture 290, 196–
Dumbauld, B.R., Wyllie-Echeverria, S., 2003. The influence of burrowing thalassinid
shrimps on the distribution of intertidal seagrasses in Willapa Bay, Washington,
USA. Aquat. Bot. 77, 27–42.
Dutertre, M., Beninger, P., Barille
´, L., Papin, M., Haure J., in press. Rising water
temperature, reproduction and recruitment of an invasive oyster, Crassostrea
gigas, on the French Atlantic coast. Mar. Environ. Res.
L. Barille
´et al. / Aquatic Botany xxx (2009) xxx–xxx
G Model
AQBOT-2282; No of Pages 10
Please cite this article in press as: Barille
´, L., et al., Increase in seagrass distribution at Bourgneuf Bay (France) detected by spatial remote
sensing. Aquat. Bot. (2009), doi:10.1016/j.aquabot.2009.11.006
Frederiksen, M., Kause_Jensen, D., Holmer, M., Laursen, J.S., 2004. Long term change
in area distribution of eelgrass (Zostera marina) in Danish coastal waters. Aquat.
Bot. 78, 167–181.
Froidefond, J.M., Doxaran, D., Miller, P., 2003. Ope
´ration 2. Acquisition et traitement
d’images satellites. Programme Interre
´gional Loire Grandeur Nature. Loire
Estuaire. Cellule de Mesures et de Bilans.
Fyfe, S.K., 2003. Spatial and temporal variation in spectral reflectance: Are seagrass
species spectrally distinct? Limnol. Oceanogr. 48, 464–479.
Gehu, J.-M., 1976. Approche phytosociologique synthe
´tique de la ve
´tation des
vases sale
´es du littoral atlantique franc¸ais. Coll. Phytosoc. 4, 395–462.
´marec, M., Le Faou, Y., Cuq, F., 1997. Long-term changes of seagrass beds in the
Glenan archipelago. Oceanol. Acta 20, 217–227.
Gouleau, D., 1975. Les premiers stades de la se
´dimentation sur les vasie
`res littorales
atlantiques; ro
ˆle de l’e
´mersion. The
`se de Doctorat. Universite
´de Nantes, France.
Green, E.P., Short, T.F., 2003.World Atlas of Seagrasses. University of CaliforniaPress.
Gruet, Y., 1976. Re
´partition des herbiers de Zostera (Monocotyle
´dones marines) sur
l’estran des co
ˆtes de Loire-Atlantique et du nord de la Vende
´e. Bull. Soc. Sci. Nat.
Ouest Fr. 74, 86–90.
Guillaumont, B., 1991. Utilisation de l’imagerie satellitaire pour les comparaisons
spatiales et temporelles en zone intertidale. In: Elliot, M., Ducrotoy, J.-P.
(Eds.), Estuaries and Coasts: Spatial and Temporal Intercomparisons. ECSA19
Symposium, Olsen & Olsen, pp. 63–68.
Haure, J., Baud, J.P., 1995. Approche de la capacite
´trophique dans un bassin
´icole (baie de Bourgneuf). Rapport Direction Ressources Vivantes IFREMER
Hily, C., van Katwijk, M.M., den Hartog, C., 2003. Seagrass distribution in Western
Europe. In: Short, F., Green, E. (Eds.), The World Atlas of Seagrasses. California
University Press, USA, pp. 38–47.
Huete, A.R., 1988. A soil adjusted vegetation index (SAVI). Remote Sens. Environ. 25,
´nez, C., Niell, F.X., Algarra, P., 1987. Photosynthetic adaptation of Zostera noltii
Hornem. Aquat. Bot. 29, 217–226.
Keller, M., Harris, S.W., 1966. The growth of eelgrass in relation to tidal depth. J.
Wildlife Manage. 30, 280–285.
Kendrick, G.A., Hegge, B.J., Wyllie, A., Lord, D.A., 2000. Changes in seagrass cover on
Success and Parmelia banks Western Australia between 1965 and 1995. Estuar.
Coast. Shelf Sci. 50, 341–353.
Laubier, L., Le Moigne, M., Flammarion, P., Thybaud, E., Cossa, D., 2004. The
monitoring programme of the ecological and ecotoxicological consequences
of the Erika oil spill. Aquat. Living Resour. 17, 239–541.
Lebreton, B., Richard, P., Radenac, G., Bordes, M., Bre
´ret, M., Arnaud, C., Mornet, F.,
Blanchard, G.F., 2009. Are epiphytes a significant component of intertidal
Zostera noltii beds? Aquat. Bot. 91, 82–90.
McKenzie, L., Finkbeiner, M.A., Kirkman, H., 2001. Methods for mapping seagrass
distribution. In: Short, F.T., Coles, R.G. (Eds.), Global Seagrass Research Methods.
Elsevier, pp. 101–121.
´o, R., 1994. Brent geese in France. In: Van Nugteren, J. (Ed.), Brent Geese in the
Wadden Sea. LVBW, Harligen, pp. 189–192.
´der, V., Launeau, P., Barille
´, L., Rince
´, Y., 2003a. Cartographie des peuplements
du microphytobenthos par te
´tection spatiale visible-infrarouge dans un
`me conchylicole. C. R. Biol. 326, 377–389.
´der, V., Barille
´, L., Launeau, P., Carre
`re, V., Rince
´, Y., 2003b. Spectrometric
constraint in analysis of benthic diatom biomass using monospecific culture.
Remote Sens. Environ. 88, 386–400.
Mumby, P.J., Green, E.P., Edwards, A.J., Clark, C.D., 1997. Measurement of seagrass
standing crop using satellite and digital airborne remote sensing. Mar. Ecol.
Prog. Ser. 159, 51–60.
Murphy, R.J., Tolhurst, T.J., Chapman, M.G., Underwood, A.J., 2005. Estimation of
surface chlorophyll-a on an emersed mudflat using field spectrometry: accura-
cy of ratios and derivative-based approaches. Int. J. Remote Sens. 26, 1835–
Orth, R.J., Carruthers, T.J.B., Dennison, W.C., Duarte, C.M., Fourqurean, J.W., Heck,
K.L., Hughes, A.R., Kendrick, G.A., Kenworthy, J.W., Olyarnik, S., Short, F.T.,
Waycott, M., Williams, S.L., 2006. A global crisis for seagrass ecosystem.
BioScience 56, 987–996.
Orth, R.J., Moore, K.A., 1983. Submersed vascular plants: techniques for analyzing
their distribution and abundance. Mar. Technol. Soc. J. 17, 38–52.
Philippart, C.J.M., 1994. Interactions between Arenicola marina and Zostera noltii on
a tidal flat in the Wadden Sea. Mar. Ecol. Prog. Ser. 111, 251–257.
Philippart, C.J.M., 1995. Seasonal variation in growth and biomass of an intertidal
Zostera noltii stand in the Dutch Wadden Sea. Neth. J. Sea Res. 33, 205–218.
Philippart, C.J.M., Dijkema, K.S., 1995. Wax and wane of Zostera noltii in the Dutch
Wadden Sea. Aquat. Bot. 49, 255–268.
Phinn, S., Roelfsema, C.M., Dekker, A.G., Brando, V.E., Anstee, J., 2008. Mapping
seagrass species, cover and biomass in shallow waters: an assessment of
satellite multi-spectral and airborne hyper-spectral imaging systems in Mor-
eton Bay (Australia). Remote Sens. Environ. 112, 3413–3425.
Qi, J., Chebouni, A., Huete, A.R., Kerr, Y., Soroooshian, S., 1994. A modified soil
adjusted vegetation index. Remote Sens. Environ. 47, 1–25.
Reise, K., Kohlus, J., 2008. Seagrass recovery in the Northern Wadden Sea? Helgol.
Mar. Res. 62, 77–84.
Reusch, T.B.H., Chapman, A.R.O., Gro
¨ger, J.P., 1994. Blue mussels Mytilus edulis do
not interfere with eelgrass Zostera marina but fertilize shoot growth through
biodeposition. Mar. Ecol. Prog. Ser. 108, 265–282.
RNO, 2003. Re
´seau National d’Observation de la qualite
´du milieu marin. IFREMER
et Ministe
`re de l’Ecologie et du De
´veloppement Durable (ISSN 1620-1124).
Short, F.T., Neckles, H.A., 1999. The effects of global change on seagrasses. Aquat.
Bot. 63, 169–196.
Short, F.T., Wyllie-Echeverria, S., 1996. Natural and Human-induced Disturbance of
seagrasses. Environ. Conserv. 23, 17–27.
Smaal, A.C., Prins, T.C., 1993. The uptake of organic matter and the release of
inorganic nutrients by bivalve suspension feeder beds. NATO ASI Series G 33,
Smith, G.M., Milton, E.J., 1999. The use of the empirical line method to calibrate
remotely sensed data to reflectance. Int. J. Remote Sens. 20, 2653–2662.
Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitor-
ing vegetation. Remote Sens. Environ. 8, 127–150.
Vermaat, J.E., Verhagen, F.C.A., 1996. Seasonal variation in the intertidal sagrass
Zostera noltii Hornem.: coupling demographic and physiological patterns.
Aquat. Bot. 52, 259–281.
Ward, D.H., Morton, A., Tibbitts, T.L., Douglas, D.C., Carrera-Gonzalez, E., 2003. Long-
term spatial change in eelgrass distribution at Bahia San Quintin, Baja Califor-
nia, Mexico, using satellite imagery. Estuaries 26, 1529–1539.
Ward, D.H., Markon, C.J., Douglas, D.C., 1997. Distribution and stability of eelgrass
beds at Izembeck Lagoon, Alaska. Aquat. Bot. 58, 229–240.
Zacharias, M., Niemann, O., Borstad, G., 1992. An assessment and classification of
multispectral bandset for the remote sensing of intertidal seaweeds. Can. J.
Remote Sens. 18, 263–274.
L. Barille
´et al. / Aquatic Botany xxx (2009) xxx–xxx
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... As water levels in plants can vary on a daily basis obtaining the dry weight of a plant is more accurate than the fresh, or wet, weight. Studies appear to use of mix of both wet (Fyfe et al., 1999;Simms, 2003;Reigl et al., 2005;Stekoll et al., 2006) and dry weight (Andréfouët et al., 2004;Barillé et al., 2010;Quintino et al., 2010) biomass measurements. ...
... The removal of samples (i.e. not in-situ) for spectral reflectance sampling is a common method that has been used to derive representative macroalgal spectral profiles for spectral library comparison studies (Kutser et al., 2006b;Uhl et al., 2013;Kotta et al., 2014;Chao Rodríquez et al., 2017) and for the training of hyperspectral remote sensing classifiers Barillé et al., 2010;Casal et al., 2013;Dierssen et al., 2015). To better understand the effects of sample removal on changes (or lack thereof) in spectral response a small pilot study was conducted to compare the spectral properties of A. nodosum that was first measured in-situ before being cut and then taken to the measurement area, following an analytical method developed by Kotta et al. (2014). ...
... Spectral resolution is defined by the number and width of bands present within a sensor. A sensor can still cover a large portion of the EM yet have a low spectral resolution if only a small number of wide bands are used (Govender et al., 2007;Barillé et al., 2010). Conversely, many higher spectral resolution sensors (i.e. ...
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Increasing interest in the sustainable management of Irish macroalgal resources requires the development of a cost-effective and efficient methodology for quantifying the distribution of key species. Remote sensing provides a mapping solution that allows for large areas to be covered and is increasingly being applied to a range of macroalgal mapping research questions. Of interest to this research were the commercially and ecologically important intertidal brown fucoid, Ascophyllum nodosum and subtidal kelp communities (often dominated by Laminaria hyperborea). Using a spectroradiometer, the spectral reflectance signatures of common canopy-forming intertidal macroalgae were sampled across four seasons during 2018. Classification and regression tree (CART) analysis showed that it was possible to discriminate between the three macroalgal groups and also between all sampled spectrally similar brown species in all seasons, aside from in winter. Intra-specific variation in spectral response of A. nodosum thalli was observed across the seasons and should potentially be accounted for in the creation of a spectral library. A pushbroom hyperspectral drone survey showed that, using a Maximum Likelihood Classifier (MLC), it was possible to accurately map A. nodosum distribution ((Overall Accuracy (OA) 94.7 %) along with other dominant canopy-forming species. The accurate mapping of multiple species corroborated the results found using the spectroradiometer and highlighted the potential of this technology for intertidal resource mapping. Further work was undertaken at a separate site to compare the ability of two multispectral remote sensing platforms (drone and plane) to accurately map A. nodosum. Using MLC, the drone was found to produce a more accurate (OA 92 %) and higher taxonomic resolution map than the plane (OA 78.9 %) which could only identify a mixed A. nodosum and fucoid class. Experience gained from this research contributed to the creation of a comprehensive guide for using drones to map intertidal macroalgae which detailed the current technology and key challenges associated with mapping within the intertidal zone. Vessel-mounted multibeam sonar was used to map a subtidal kelp bed. Three different acoustic frequencies (200, 300, 400 kHz), each logging water column data, were used to determine whether there was an optimum frequency for the accurate estimation of canopy height and extent. Each of the three frequencies provided slightly different estimates of canopy height and extent. A drop-down camera validated the presence of the kelp bed (dominated by L. hyperborea) but further research is required to determine the source of the variation between the three survey frequencies.
... The NDVI appears to have identified known eelgrass meadows (Olesen et al., 2015) but no attempt was made to distinguish eelgrass from macroalgae (see section 2.2.3). High NDVI values in known eelgrass meadow locations could also result from the accumulation of detached, drifting macroalgae (Barillé et al., 2010). ...
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Changes in the distribution of coastal macrophytes in Greenland, and elsewhere in the Arctic are difficult to quantify as the region remains challenging to access and monitor. Satellite imagery, in particular Sentinel-2 (S2), may enable large-scale monitoring of coastal areas in Greenland but its use is impacted by the optically complex environments and the scarcity of supporting data in the region. Additionally, the canopies of the dominant macrophyte species in Greenland do not extend to the sea surface, limiting the use of indices that exploit the reflection of near-infrared radiation by vegetation due to its absorption by seawater. Three hypotheses are tested: I) 10-m S2 imagery and commonly used detection methods can identify intertidal macrophytes that are exposed at low tide in an optically complex fjord system in Greenland impacted by marine and land terminating glaciers; II) detached and floating macrophytes accumulate in patches that are sufficiently large to be detected by 10-m S2 images; III) iceberg scour and/or turbid meltwater runoff shape the spatial distribution of intertidal macroalgae in fjord systems with marine-terminating glaciers. The NDVI produced the best results in optically complex fjord systems in Greenland. 12 km2 of exposed intertidal macrophytes were identified in the study area at low tide. Floating mats of macrophytes ranged in area from 400 m2 to 326,800 m2 and were most common at the mouth of the fjord. Icebergs and turbidity appear to play a role in structuring the distribution of intertidal macrophytes and the retreat of marine terminating glaciers could allow macrophytes cover to expand. The challenges and solutions presented here apply to most fjords in Greenland and, therefore, the methodology may be extended to produce a Greenland-wide estimate of intertidal macrophytes.
... Several works already documented the crucial role of megaherbivores (waterfowls, turtles, and dugongs) on seagrass ecosystem structure, biomass, and primary production (Scott et al., 2018). Also, there are numerous examples of the potential of Earth Observation (EO) to study seagrass EBVs worldwide (Barillé et al., 2010;Calleja et al., 2017;El-Hacen et al., 2020;Zoffoli et al., 2020). However, to our knowledge, combined analyses of longterm dynamics in herbivorous population and remotelysensed seagrass distribution have never been attempted. ...
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Taking into account trophic relationships in seagrass meadows is crucial to explain and predict seagrass temporal trajectories, as well as for implementing and evaluating seagrass conservation policies. However, this type of interaction has been rarely investigated over the long term and at the scale of the whole seagrass habitat. In this work, reciprocal links between an intertidal seagrass species, Zostera noltei, and a herbivorous bird feeding on this seagrass species, the migratory goose Branta bernicla bernicla, were investigated using an original combination of long-term Earth Observation (EO) and bird census data. Seagrass Essential Biodiversity Variables (EBVs) such as seagrass abundance and phenology were measured from 1985 to 2020 using high-resolution satellite remote sensing over Bourgneuf Bay (France), and cross-analysed with in situ measurements of bird population size during the goose wintering season. Our results showed a mutual relationship between seagrass and Brent geese over the four last decades, suggesting that the relationship between the two species extends beyond a simple grass-herbivore consumptive effect. We provided evidence of two types of interactions: (i) a bottom-up control where the latesummer seagrass abundance drives the wintering population of herbivorous geese and (ii) an indirect top-down effect of Brent goose on seagrass habitat, where seagrass development is positively influenced by the bird population during the previous wintering season. Such a mutualistic relationship has strong implications for biodiversity conservation because protecting one species is beneficial to the other one, as demonstrated here by the positive trajectories observed from 1985 to 2020 in both seagrass and bird populations. Importantly, we also demonstrated here that exploring the synergy between EO and in situ bird data can benefit seagrass ecology and ecosystem management.
... The use of multispectral sensors provides a notably improved ability in spectral signature distinction compared to RGB sensors, offering higher spectral resolution to detect specific organisms through the isolation of key parts of the electromagnetic spectrum from non-overlapping bands (Tait et al., 2019). Moreover, the infrared band is commonly used for exposed marine vegetation detection through remote sensing, with many studies using the Normalized Difference Vegetation Index (NDVI) for monitoring seagrass meadows, macroalgae and microphytobenthos, among others (Barilléet al., 2010;Brito et al., 2013;Kohlus et al., 2020;Meĺeder et al., 2020;Zoffoli et al., 2020;Romań et al., 2021;Zoffoli et al., 2021). Therefore, the overall aim of this study was to determine potential applications and limitations of multispectral remote sensing onboard UAV and satellites in order to detect and monitor R. okamurae on the Andalusian coasts in the optically Mechanical removal of R. okamurae beachings on Los Lances and Atlanterra beaches (Tarifa, Spain) during the 2021 summer (A-D) R. okamurae beaching and its removal with heavy machinery (6.213 tons in only two months); (E) the same beach after seaweed removal. ...
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Rugulopteryx okamurae is a species of brown macroalgae belonging to the Dictyotaceae family and native to the north-western Pacific. As an Invasive Alien Species (IAS), it was first detected in the Strait of Gibraltar in 2015. Since then, R. okamurae has been spreading rapidly through the submerged euphotic zone, colonizing from 0 to 50 m depth and generating substantial economic and environmental impacts on the Andalusian coasts (southern Spain). More than 40% of marine IAS in the European Union (EU) are macroalgae, representing one of the main threats to biodiversity and ecosystem functioning in coastal habitats. This study presents a monitoring pilot of beached R. okamurae and fresh R. okamurae down to 5 m depth in Tarifa (Cadiz, Spain), combining multispectral remote sensing data collected by sensors on-board Unmanned Aerial Vehicles (UAVs) and satellites, and how this information can be used to support decision-making and policy. We used an UAV flight carried out at Bolonia beach (Tarifa, Spain) on 1st July 2021 and Sentinel-2 (S2) and Landsat-8 (L8) image acquisitions close to the drone flight date. In situ data were also measured on the same date of the flight, and they were used to train the supervised classification Super Vector Machine (SVM) method based on the spectral information obtained for each substrate cover. The results obtained show how multispectral images allow the detection of beached R. okamurae, and the classification accuracy for water, land vegetation, sand and R. okamurae depending on the image resolution (8.3 cm/pixel for UAV flight, 10 m/pixel for S2 and 30 m/pixel for L8). While the UAV imagery precisely delimited the area occupied by this macroalgae, satellite data were capable of detecting its presence, and able to generate early warnings. This study demonstrates the usefulness of multispectral remote sensing techniques to be incorporated in continuous monitoring programmes of the marine IAS R. okamurae in coastal areas. This information is also key to supporting regional, national and European policies in order to adapt strategic management of invasive marine macrophytes.
... Several methods have been used to interpret remote sensing images for mapping coral reefs and seagrasses [2,6], including the Principal Component Analysis (PCA) method applied to Landsat-TM and SPOT images [7,8]; the Normalized Difference Vegetation Index (NDVI) [9]; Leaf Area Index (LAI) combined with field optical properties measurement data [10,11]; and Object-based Classification method [12]. However, after analyzing and classification based on these indexes, it turns out that most of the above methods have not considered water depth, whereas the light intensity is absorbed and reduced exponentially when passing through the water column [13]. ...
The use of remote sensing images for the interpretation of underwater substrate objects depends on their reflectance spectrum of different water depths. Thus, the water column correction step is important in the interpretation. Two commonly used water column correction methods are Lyzenga’s depth invariant index (DII) method and Sagawa’s bottom reflectance index (BRI) method. To evaluate the role of each method in Khanh Hoa waters, Tuan Le water, with a high seagrass coverage and moderate turbidity, and Thuy Trieu Lagoon, with high biodiversity of seagrass species and turbidity water, were selected as representatives. 70% of the survey data was used for ground training data of seagrass (dense and patchy), muddy-sand and sand features and the interpretation of both methods, whereas the remaining 30% of the survey data was used for validation of the mapping results. The maximum likelihood classification approach was used to extract the seagrass map and evaluated by overall accuracy as well as the Kappa coefficient. The processing results show that, in Tuan Le water, using the DII method gives an accuracy of 82.1% and the BRI of 80.1%; and in Thuy Trieu Lagoon, the DII method has an accuracy of 80.67% and the BRI of 80.0%. These results demonstrate that both methods have high accuracy results in both areas, but the method of BRI gives better results.
... In the case of intertidal seagrass beds, the periodic absence of the water column provides additional remote sensing options for characterising seagrass AGB. Access to wavelengths of light which are highly attenuated by water makes common vegetation indices which rely upon near infrared reflectance, including the Normalised Difference Vegetation Index (NDVI), viable in intertidal environments [95,98]. Additionally, recent research has suggested that Synthetic Aperture Radar (SAR) data improve the accuracy of seagrass mapping, including AGB estimates, by providing information on surface structure which complements optical remote sensing data [99,100]. ...
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Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability.
Tidal variations make the water bodies in satellite remote sensing images on different shooting dates have different inundation ranges and depths. Although the underwater substrates do not change, the spectral properties differ due to attenuation effects. These differences have an impact on the results when multi-temporal remote sensing images are used to analyze seagrasses. This paper proposes a remote sensing mapping method for seagrasses taking the tidal influence, using the seagrasses growth area in Xincun Bay, Hainan Province, China as a case study. a) The seagrasses growth area was determined from remote sensing images. The seagrasses were divided into two types: the seagrasses exposed to water surface or tidal flats (non-submerged seagrasses) and the seagrasses submerged in water (submerged seagrasses). b) The spectral features of seagrasses in Sentienl-2 image were analyzed. We found that the spectral characteristics of non-submerged seagrasses were similar to terrestrial vegetation and these seagrasses could be extracted by using NDVI. The submerged seagrasses spectral was different, forming a reflection peak at the first vegetation red edge band (i.e.705 nm) in Sentinel-2 images. This reflection peak was used to design the Submerged Seagrasses Information Index (SSII) for extracting underwater seagrass. c) The extraction results of non-submerged seagrasses and submerged seagrasses were merged to map the seagrasses in the study area. The experimental results show that the mapping method proposed in this study can fully consider the influence of tidal changes in remote sensing images on seagrasses identification. The SSII constructed based on Sentinel-2 images extracted submerged seagrasses effectively. This study will provide references to remote sensing mapping of seagrasses and integrated ecological management in coastal zones.
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Klima Aldaketa eta Itsasertzari buruzko Mugaz gaindiko V. Biltzarra. Laburpen zabalak V Congreso transfronterizo sobre Cambio Climático y Litoral. Abstracts extendidos V Congrès transfrontalier sur le Changement Climatique et Littoral. Abstract étendue V Cross border conference on climate and coastal change. Extended abstracts
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Klima Aldaketa eta Itsasertzari buruzko Mugaz gaindiko V. Biltzarra. Laburpen zabalak V Congreso transfronterizo sobre Cambio Climático y Litoral. Abstracts extendidos V Congrès transfrontalier sur le Changement Climatique et Littoral. Abstract étendue V Cross border conference on climate and coastal change. Extended abstracts
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The surrounding waters of Tulehu Village are coastal areas with ecosystems such as seagrass, adjacent to marine natural resources (mangroves, macroalgae, fish, mollusks, etc.). Seagrass in the coastal waters of Tulehu has spread widely, but information about seagrass communities in these waters is limited. This research was conducted to describe the species composition, density, frequency of occurrence, percentage of coverage, importance value, biomass, and distribution of pattern of seagrass in the area. The method used is the quadratic linear transect method. The results of the study showed that there are four seagrass species Cymodocea rotundata, Halodule pinifolia, Halophila ovalis, and Thalassia hemprichii. The highest values of density, frequency of occurrence, percentage of coverage, importance value, and biomass were found for H. pinifolia. The lowest values for density, percentage of coverage, and biomass were found for H. ovalis, while T. hemprichii had the lowest values for frequency of occurrence and importance. Spatial distribution based on density, percentage of coverage and biomass have the values of >10 stands m-2 , >40% and >200 g m-2 , respectively.
Aerial photographs and in situ data of the Glenan archipelago permit the establishment of a cartography of its Zostera marina seagrass beds. Due to the exceptionally clear water, it was possible to distinguish submerged structures, such as rocks, sand dunes, maerl beds and seagrass meadows on the photographs. The distribution of Zostera meadows was incorporated into a geographical information database through scanning, and then compared with historical data. Ten aerial photographic surveys, made over a sixty-year period from 1932 to 1992, were available. The earliest of these surveys showed the seagrass beds to be in good condition. Low cover in 1952 suggests that the Zostera meadows within the studied area were subject to severe destructions, presumably due to the 'wasting disease', which caused a general breakdown of the North-Atlantic populations during the 1930s. During the 1970s, the distribution of Zostera beds increased; this was followed by a gradual decline during the 1980s and early 1990s. For the investigation of the environmental circumstances under which Zostera beds are fluctuating, the Glenan site is unique. This site being relatively remote from direct anthropogenic disturbances (light irradiance decline, sewage inputs), the causes of such fluctuations during this 60-year period can be more easily identified. Z. marina is a boreal species naturally affected by climate changes and in particular by global warming, which was at a maximum during the 1940s and 1950s. Various human activities, such as scallop dredging, maerl exploitation, yachting and anchoring, should also be considered. However, these anthropogenic disturbances were of limited importance in comparison with the dramatic decline and recovery of the seagrass beds as a result of climate fluctuations.
The growth of eelgrass (Zostera marina) in relation to tidal depth was studied on three areas of South Humboldt Bay, California, in 1960 and 1962. Six contours of bay bottom between +1.0 and -1.5 feet in relation to mean lower-low tide were sampled. The upper limit of eelgrass growth was at or slightly above +1.0 foot. This contour was exposed to air about 15 percent of the time. The percent of eelgrass coverage, mean turion length, and eelgrass biomass per square foot all increased with increases in tidal depth. The density of turions per square foot and the number of leaves per turion did not vary with depth. The optimum depth for eelgrass production at Humboldt Bay appears to be at about -1.0 foot. Over 90 percent of the total eelgrass biomass and about 60-70 percent of the eelgrass acreage in South Humboldt Bay occur at or below mean lower-low tide.
Des images de l'Île de Vancouver, en Colombie-Britannique, ont été acquises à partir d'un scanneur multibande aéroporté fonctionnant dans huit bandes configurées pour la télédétection des zones intertidales. Des courbes de radiance, des corrélations entre bandes spectrales et des analyses des composantes principales ont été utilisées dans l'étude de deux zones littorales physiquement et biologiquement distinctes. On a montré que cinq des huit bandes spectrales apportaient de l'information unique concernant l'identification des algues en zones intertidales. La classification des cinq bandes en question a démontré que l'on pouvait identifier différents genres d'algues, y compris les chlorophytes (algues vertes) qui ont des spectres identiques.