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INTERUNIVERSITY PROGRAMME
ADVANCED MASTER OF SCIENCE IN
‘TECHNOLOGY FOR INTEGRATED WATER
MANAGEMENT’
Academic year 2015-2016
Spatially extended engineering effect of oyster reefs
(Crassostrea gigas) on morphology and sediment composition
of intertidal areas
by Jonas Van Acker
Promoter: Prof. dr. Tom Ysebaert, Prof. dr. Colin Janssen
Tutor: dr. Brenda Walles
Master's dissertation submitted in partial fulfilment of the requirements
for the degree of Master of Science in ‘Technology for Integrated Water
Management’
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INTERUNIVERSITY PROGRAMME
ADVANCED MASTER OF SCIENCE IN
‘TECHNOLOGY FOR INTEGRATED WATER
MANAGEMENT’
Academic year 2015-2016
Spatially extended engineering effect of oyster reefs
(Crassostrea gigas) on morphology and sediment composition
of intertidal areas
by Jonas Van Acker
Promoter: Prof. dr. Tom Ysebaert, Prof. dr. Colin Janssen
Tutor: dr. Brenda Walles
Master's dissertation submitted in partial fulfilment of the requirements
for the degree of Master of Science in ‘Technology for Integrated Water
Management’
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Preface
This manuscript is written as fulfillment of the final part of my master thesis to graduate
as advanced master in Technology for Integrated Water Management (TIWM). The
research executed is part of the NWO project EMERGO which studies the eco-
morphological functioning and management of tidal flats. The internship was guided by
company’s NIOZ (Royal Netherlands Institute of Sea Research) and IMARES –
Wageningen UR (Institute for Marine Resources and Ecosystem studies).
The goal of this thesis is to provide better insight in the role of Crassostrea gigas reefs
as ecosystem engineers, acting beyond their reef boundaries. The main focus will be
on the morphological section of these exerted effects since my colleague Rick Leong
will tackle the biological part of this ecological functioning.
I would like to start by thanking my supervisors Tom Ysebaert and Brenda Walles for
their utmost support and guidance during fieldtrips, countless meetings and with the
suggestions and corrections on my thesis.
Big thanks go to Jim van Belzen and Bas Oteman for giving me repeated technical
advice and guidance and especially for doing so outside of the working schedule.
My colleagues and friends Karin, Rick, Michiel, Gabriella, Sam and the people from the
NIOZ house also deserve a big thank you. Karin, thank you for the countless times you
helped with the fieldwork and your endless positive attitude. Rick, thanks for the good
colleagueship and statistical insights.
Thank you Ad van Gool and Jeanet Allewijn for arranging my administration, including
my stay in Yerseke.
I would like to express my gratitude to Lodewijk de Vet from Deltares / TU Delft for
providing data and insight.
I am very grateful to my parents, grandparents and Andrea, my girlfriend. The non-stop
mental support always gave me strength to pursue my goals.
Many more have my gratitude. Thanks to the support of a lot of people I was able to
finish my master degree.
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Abstract
Keywords: Ecosystem engineering, Ecosystem functions, Coastal protection, Oyster
reefs, Morphology, Sediment characteristics, Digital elevation maps, Low altitude
remote sensing
Oysters are ecosystem engineers that change their environment by forming hard
substrate in an otherwise soft sediment environment. From a coastal protection
perspective, the wave dampening effects and the protected area make oyster reefs
interesting structures for ecosystem-based coastal defence schemes. However, there
is still a lack of knowledge on extended effects concerning physical (hydrology,
morphology) and biological (biodiversity) changes. Insights in the sediment composition
of the area affected by reefs offer new perspectives on the impact biogenic oyster reefs
have on their surroundings.
In order to bring forward this investigation, the elevation and sediment composition of
six reefs located at three different sites, all situated in the Oosterschelde estuary (the
Netherlands) were analysed. Digital elevation maps (DEMs) were drawn and reef
properties along with the influence zone created by the reefs were determined and
correlated among each other. Sediment composition was compared between
morphologically influenced and non-influenced zone. As an additional segment of this
manuscript, RTK measurements were compared to low altitude remote sensing by
using drone imaging to determine the elevation accuracy.
Reef characteristics showed strong linear correlations with the variables representing
the morphologically impacted area. The strongest predictor for the influenced zone
appeared to be a combination of reef area and reef height. For sites that showed
morphological effects originating from the reef, sediments composed out of coarser
material in the influence zone and finer material in the non-influenced zone. Obtained
results were counterintuitive, however possibly explained by a combination of physical
disturbances, local tidal flat dynamics and environmental parameters such as waves
and currents.
The findings of this research provide insights on the morphological impact of oyster
reefs in a dynamic environment, contributing to management schemes for coastal
protection using soft-engineering techniques. The facilitation of this research by means
of replacing RTK measurements with drone imaging was initiated and shows promising
results.
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Trefwoorden: Ecosysteemfuncties, Kustbescherming, Oesterriffen, Sediment
karakteristieken, Digitale hoogtekaarten, Lage afstand ‘remote sensing’
Oesters zijn biobouwers (“ecosysteem engineers”) die hun omgeving aanpassen door
hard substraat te vormen in een omgeving bestaande uit zacht sediment. Deze
biologische structuren tonen veel overeenkomsten (golfdempingsvermogen,
beschermde zone door de fysische aanwezigheid van het rif) met de artificiële
structuren die gebruikt worden als techniek voor kustbescherming. Er is nog een
gebrek aan kennis over de fysische (hydrologie, morfologie) en biologische
(biodiversiteit) invloed van oesterriffen die optreedt tot buiten de perimeter van het rif
zelf. De studie van deze invloedzone met betrekking tot sedimentsamenstelling geeft
meer inzicht in het effect dat deze biologische riffen hebben op hun omgeving.
De morfologische veranderingen en de sedimentsamenstelling rondom zes oesterriffen
werd bestudeerd, gelegen op drie verschillende locaties in de Oosterschelde
(Nederland). Digitale hoogtekaarten werden geconstrueerd en de eigenschappen van
de riffen werden onderling vergeleken en vergeleken ten opzichte van de invloedzone
die het rif veroorzaakte doormiddel van regressie analyse. Voor verder onderzoek te
faciliteren werden RTK metingen vergeleken met lage afstand ‘remote sensing’ met als
doel de vervanging van RTK metingen op lange termijn door drones.
Eigenschappen van het rif toonden sterke lineaire relaties met de zone die werd
gedefinieerd als invloedzone van het rif. Het model dat de beste resultaten gaf voor de
beschrijving van deze invloedzone betrof een combinatie van de oppervlakte en de
hoogte van het rif. Verder werd grover sediment gevonden in deze invloedzone en
fijner sediment in de niet beïnvloede zone. Deze onverwachte resultaten kunnen
mogelijks verklaard worden door een combinatie van externe storingen (door de mens
veroorzaakt), lokale sedimentatie/erosiepatronen en omgevingsparameters zoals
golven en stromingen.
Bevindingen van dit onderzoek geven inzicht in de morfologische veranderingen die
oesterriffen uitoefenen in een dynamische omgeving. Deze veranderingen kunnen
bijdragen aan een meer ecologische en duurzame vorm van kustbescherming. Verder
toont het gebruik van drones voor het creëren van hoogtekaarten een goed resultaat
en kunnen in de toekomst de tijdrovende RTK metingen vervangen.
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List of figures
Figure 1: Hydrodynamic characteristics which affect oyster performance ......................... 14
Figure 2: Example of a dense oyster reef (upper picture), patchy reef (middle picture)
and mixed reef (lower picture). .......................................................................................... 15
Figure 3: Sedimentation patterns behind a submerged breakwater. .................................. 17
Figure 4: Deposition and erosion zone behind a groyne (upper figure). Velocity field
around a groyne (lower figure). ....................................................................................... 18
Figure 5: Synergy of different ecosystem engineers to promote coastal protection. .......... 19
Figure 6: Overview of the three study sites: Yerseke, Viane and Roggenplaat. ................. 22
Figure 7: Image of reefs at the three study sites. Upper images showing aerial views
from Y1 (left) and V3 (right). Lower picture shows reef R2. ................................................. 23
Figure 8: Dgps data points as Rijksdriehoek coordinates in meters from a studied reef
at Yerseke. ....................................................................................................................... 24
Figure 9: Overview of reef variables. ................................................................................. 26
Figure 10: Example of an aerial drone image (reef V3). ..................................................... 27
Figure 11: Schematic overview of sampling design. .......................................................... 29
Figure 12: Frequency distribution graphs for current patterns for the three study sites
(left figure). Graph expressing current speed (m/s)/direction (degrees) of 10 tidal cycles
(right figure) ...................................................................................................................... 32
Figure 13: DEM for the studied reefs. ............................................................................... 35
Figure 14: Regression between reef area and influenced area at 3 cm above natural
background slope.. ........................................................................................................... 36
Figure 15: Regression between L2D and Li,4cm. ................................................................. 37
Figure 16: Sd50 boxplot per reef site. ............................................................................... 38
Figure 17: Average sediment variables (%) per reef site. .................................................. 39
Figure 18: Comparison of sediment variables between non-influenced and influenced
zone defined as 3 cm above natural slope. ....................................................................... 40
Figure 19: Elevation (m) measured with Dgps compared to elevation measured by
drone at 0.1 m interpolation with a = 0.1 m (left figure). Error in elevation (m) plotted
over x and y coordinates (middle figure). Dgps datapoints as black dots and
interpolated area from drone data in color expressed over x and y coordinates (right
figure). .............................................................................................................................. 41
Figure 20: Example of digital elevation models created by Dgps data and drone-
imaging. ............................................................................................................................ 42
Figure 21: Tidal flat dynamics for Roggenplaat and Viane. ............................................... 44
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List of tables
Table 1: Environmental conditions .................................................................................... 27
Table 2: Sediment variables and their meaning ................................................................ 30
Table 3: Description of study site. ..................................................................................... 31
Table 4: Wave characteristics of the three study sites ....................................................... 33
Table 5: Reef characteristics of studied reefs and influenced areas by those reefs.. ......... 34
Table 6: Linear regression between reef variables and influenced zone.. ......................... 37
Table 7: Stepwise linear regression using forward and backward substitution using
Akaike Information Criterion. ............................................................................................. 38
Table 8: Overview and comparison of influence areas (Ai) of Y1, V2 and V3. ..................... 41
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List of symbols and explanations
Reef characteristics
L [m] length of the reef (maximum distance within reef contour)
L2D [m] maximum distance within reef contour perpendicular to the
dominant direction of the morphologically influenced zone
H [m] height of the reef
P [m] reef perimeter
Ar [m²] reef area
Characteristics of morphologically influenced area
Li [m] maximum distance within morphologically influenced area,
parallel to dominant direction of the morphologically influenced
zone
Ai [m²] morphologically influenced area
Sediment characteristics
Scoarse [%] coarse sediment fraction (500 – 1000 µm)
Smedium [%] medium sediment fraction (250 – 500 µm)
Sfines [%] fine sediment fraction (125 – 250 µm)
Svfines [%] very fine sediment fraction (63 – 125 µm)
Ssilt [%] silt sediment fraction (< 63 µm)
Sd50 [µm] median grain size
Parameter used for drone/Dgps comparison
a [m] maximum distance between Dgps point and corresponding
drone data points
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Table of contents
Preface 4
Abstract 5
List of figures 7
List of tables 8
List of symbols and explanations 9
Table of contents 10
1. Introduction 12
2. Background 13
2.1. Ecosystem engineers 13
2.2. Pacific oyster reefs 13
2.3. Ecosystem functions and services of oysters 16
2.3.1. Changes in hydrodynamics and morphology 16
2.3.2. Utilizing ecosystem functions for coastal defence schemes 18
3. Work objectives 20
4. Material and methods 21
4.1. Study area 21
4.2. Studied species 22
4.3. Study sites 22
4.4. Data collection and data analysis of the studied reefs 23
4.4.1. Environmental conditions at the reef site 23
4.4.1.1. Erosion rate 23
4.4.1.2. Current speed and direction 24
4.4.1.3. Wind characteristics 24
4.4.2. Bathymetry 24
4.4.2.1. Bathymetry data collection via Dgps 24
4.4.2.2. Bathymetry maps from Dgps data 25
4.4.2.3. Statistical analysis of reef characteristics 26
4.4.2.4. Bathymetry data collection via drone 26
4.4.2.5. Drone data validation 27
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4.4.3. Sediment sampling 28
4.4.3.1. Sampling design 28
4.4.3.2. Sediment sample collection 29
4.4.3.3. Particle size analysis 29
4.4.3.4. Sediment statistical analysis 30
5. Results 31
5.1. Site characterization 31
5.1.1. Local tidal flat dynamics 31
5.1.2. Local current patterns 31
5.1.3. Wind characteristics 33
5.2. Reef characteristics 33
5.3. Morphological effects on surrounding 35
5.3.1. Oyster reef effects on vertical elevation 35
5.4. Effects on sediment characteristics 38
5.5. Alternative method of creating digital elevation models (DEMs) with drone
imaging 40
6. Discussion 43
7. Conclusions 46
8. References 47
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1. Introduction
In shallow estuarine and coastal areas, a number of organisms are present which
create, modify or maintain the habitats in which they live. These organisms are known
as ecosystem engineers (Jones et al., 1994). Marsh vegetation (Bouma et al., 2005),
mangroves (Kathiresan & Bingham, 2001), coral reefs, bivalve reefs (Walles et al.,
2014) and dense vegetation of kelps and sea grasses (Hastings et al., 2007) are
examples of ecosystem engineers which modify their environment by their physical
structure (i.e. autogenic engineering), affecting flow patterns, wave energy and
sediment dynamics (e.g. Bouma et al., 2014).
Oysters are ecosystem engineers that exert various ecosystem services. The Pacific
oyster Crassostrea gigas forms a hard substrate in an otherwise soft-sediment
environment providing habitat for several other species. They are both autogenic and
allogenic ecosystem engineers as they can change the physical (hydrology and
morphology) and biological (biodiversity) environment through their physical structure
and biological activity (Ysebaert, 2016). As filter feeders they change resources
(suspended matter such as sediment and algae) from one physical state (i.e. pelagic)
into another state (biodeposits) (Troost 2009; Jones et al. 1994). The physical structure
and produced biodeposits change local hydrology, sediment dynamics and sediment
composition, which affects the local biodiversity (Reise 2002; Hollander et al. 2015; van
der Zee et al. 2012). Whereas most literature focusses on the ecosystem engineering
effect within the boundaries of ecosystem engineers, in case of oysters this is the reef
structure, effects in morphology and biodiversity can also be observed on larger spatial
scales outside of their own occurrence as demonstrated by van der Zee et al. (2012),
Walles et al. (2014) and Donadi et al., (2014). On the lee side of natural oyster reefs,
an elevated area was observed by Walles et al. (2014) which was in the same order or
magnitude as the size of the reef itself. They subscribe this elevated area to the wave
dampening effects of the reefs. As oyster reefs dampen waves, resulting in a protected
(elevated) area, they are recognized as interesting structures for ecosystem-based
coastal defence schemes. However, there is still a lack of knowledge on the extended
effects concerning sediment composition and biodiversity. Insight in the sediment
composition of the area affected by reefs offers new perspectives on the impact
biogenic oyster reefs have on their surroundings.
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2. Background
2.1. Ecosystem engineers
Ecosystem engineers can be found around the world in different environments:
freshwater, terrestrial and marine. The most commonly used example of allogenic
engineers that alter their environment by physical changing is the beaver. Through the
creation of dams, wetlands are formed creating more heterogeneity in the landscape
(Jones et al., 1994). Another allogenic engineer is the lugworm, Arenicola marina,
which is common in intertidal areas. This benthic invertebrate destabilizes the sediment
by bioturbation (Donadi et al., 2015). An important example of an autogenic engineer is
the marsh plant Spartina anglica. This herbaceous perennial plant reduces
hydrodynamics which alter the sediment transport, resulting in sediment deposition
within a plant patch. Through this mechanism, the plant patch increases in height,
which leads to a decreased inundation stress (positive feedback loop) (Balke et al.,
2012). These patches attenuate waves and provide protection against erosion by
preventing resuspension of the sediments (Li et al., 2009; Ysebaert, 2016). These traits
can also be found in biogenic reefs in soft-sediment environments (Crooks, 1998; van
der Zee et al.; 2015; Ysebaert, 2016). Within this thesis I focus on the ecosystem
engineering effect of the Pacific oyster Crassostrea gigas which induce morphological
(i.e. biogeomorphology) changes to their environment by their physical occurrence and
biological activity.
2.2. Pacific oyster reefs
Oysters have a pelagic larval phase after which they settle on hard substrate growing
out towards adult oysters, Figure 1. Oyster reefs consist out of individual oysters
cemented together, creating large robust structures that stay largely intact, even in
post-mortem state. Reef development of Pacific oysters in the intertidal zone is
restricted by tidal emersion time with a growth ceiling around 55% emersion (Walles et
al., 2015; Walles et al., 2016a; Walles et al., 2016b).
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Figure 1: Hydrodynamic characteristics (suitable substrate, wave action/flow velocity and inundation period)
which affect oyster performance (settlement, growth, survival, growth and reproduction) (Walles et al., 2011).
Oyster reefs are usually categorized into dense, patchy or mixed reefs (oysters and
mussels combined), Figure 2 (Troost, 2009).
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Figure 2: Example of a dense oyster reef (upper picture), patchy reef (middle picture) and mixed reef (lower
picture). Photo credits for upper and lower picture: Rick Leong. The middle picture is taken from Google
Earth.
Local engineering effects of biogenic reefs have been well documented in literature
(Reise, 2002; Hollander et al., 2015; Walles et al., 2015; Housego & Rosman, 2015).
Filtered particles are transformed into faecal and pseudofaecal biodeposits which can
accumulate in the reef and its surroundings (Newell, 2004; Ostroumov, 2005;
Ulanowicz & Tuttle, 1992; Leeuwen, et al., 2010). The physical presence of hard
structures on soft sediment translates into changed environmental conditions. The
structures increase bed shear stress resulting in wave height reduction (Reise, 2002;
Housego & Rosman, 2015). Locally, within patches of reef, changes in sediment
composition and organic matter result into a species shift (Hollander et al., 2015). For
oyster reefs in specific, within the reef, organic matter is increased. This increase in
organic matter, along with the fact that these reefs offer refuge against predation and
act as substrate for sessile organisms to settle on, results into a higher species
richness and abundance (Hollander et al., 2015). Some examples of organisms that
are positively affected by oyster reefs include the polychaetes Lanice conchilega
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(Kochmann, Buschbaum, Volkenborn, & Reise, 2008), Nereimyra puncata, Nephtys
caeca, and Arenicola marina, and the bivalves Mya truncata and Corbula gibba
(Hollander et al., 2015). However, effects do not only occur on a local scale. Extended
effects influence areas beyond the reef itself. Investigation on this subject was done by
van der Zee et al. (2012) by documenting the sediment organic matter content, silt
content and redox around mussel beds and mixed mussel/oyster bed in the Wadden
Sea. According to their study, there exists a correlation between the distance from the
reef and the organic matter, silt content and redox, translating further in an increased
abundance off certain bird species foraging on benthos. In the direction towards the
reef starting from the lee side, the organic matter and silt content increased and redox
decreased (van der Zee et al., 2012).
As extended ecosystem engineering effects can affect consumer-resource dynamics
beyond the boundaries of the reef structure (van der Zee et al., 2012), it is from a
management point of view important to understand these effects when implementing
reefs in coastal management.
2.3. Ecosystem functions and services of oysters
Oysters provide provisioning, regulating, supporting and cultural services. As a
provisioning role, oysters bring in large revenues commercially by using oysters for
consumption, jewellery and building material (lime). Regulative functions such as the
trapping of sediments and the filtration capacity are already mentioned but oysters also
regulate by performing carbon sequestration and storage as well as erosion control
(Meyer, et al., 1997) and the physical protection of the coastlines from storm surges
and waves. Their supporting functions promote the enhancement of nutrients cycling
as well as to provide nursery habitats for certain species (Crooks, 1998; Reise, 2002;
Ysebaert, 2016).
2.3.1. Changes in hydrodynamics and morphology
Autogenic engineering effects of bivalve reefs result in changes in the local hydrology
which effects the sedimentation patterns as described by Chamberlain, et al. (2001),
Walles et al. (2014) and Ysebaert (2016). Sediments can be transported via two
different processes. These processes include current-related transport which can be
translated into gravity-, wind-, wave-, tide- and density-driven currents, and wave-
related transport which occurs by the oscillatory motion of the water either created by
short waves with decreasing water depth or via the combination of both currents and
short waves. The transport of sediments in coastal waters is strongly affected by high-
frequency waves which induce an oscillatory force on the particles. These short waves
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stir the sediment and transport occurs trough the mean current (Van Rijn, n.d.). The
deposition of these particles is mostly defined by their settling speed (Sanford &
Kineke, n.d.).
Pacific oyster reefs (Crassostrea gigas) mainly occupy the lower intertidal (Walles et
al., 2015). This indicates that reefs will be submerged for long periods (55%) of the tidal
cycle. For the submerged time period, oyster reefs can be considered as submerged
breakwaters (Figure 3). Depending on the wave height, water depth and height of the
reef, waves will be dissipated. When there is a regular wave motion, currents will be
decreased at the lee side of the structure (Armono, 2004; Van Rijn, 2013b). Since
particulate matter deposits more easily with reduced current speeds, sedimentation is
facilitated (law of Stokes), (Wright, et al. 2012). However, when waves are irregular, the
current speed induced by those waves on the lee side of such a structure can be
relatively large (Van Rijn, 2013b).
When the reef is emerged, wave action results into a shift in wave-angle. This effect
can also be observed when analyzing sedimentation patterns around a groyne. When
currents perpendicular to the groyne occur, the shift in wave-angle induces diffraction
which results into particular zones of erosion and sedimentation (Figure 4) (Ouillon &
Dartus, 1997).
Repeated emersion and submersion periods result into the consequent sedimentation
and erosion zone formation which can be quantified as described by Walles et al.
(2014).
Figure 3: Sedimentation patterns behind a submerged breakwater (Van Rijn, 2013a).
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Figure 4: Deposition and erosion zone behind a groyne (upper figure). Velocity field around a groyne (lower
figure). (Ouillon & Dartus, 1997).
2.3.2. Utilizing ecosystem functions for coastal defence schemes
Many coastal ecosystems are subject to negative sediment budgets resulting in coastal
erosion, partly due to extensive human activity. This, along with sea-level rise and
increased storminess leads towards the necessity of mitigating measures resulting in
high costs (Van Rijn, 2013a). Beach nourishments are extensively used around the
world along sandy coasts and are considered a better alternative than the construction
of hard structures for protection against erosive effects and have the perception of
being more ecologically sound as a solution. However, in short term, by replenishing
the sand, a large proportion of the flora and fauna present prior to the suppletion is
destroyed by the thick layer of sand and the natural equilibrium is temporarily put out of
place (Speybroeck et al., 2006). With sand nourishments, the fill sediment often
contains a high proportion of shells of which the fragments may become dissolved
leading to a hard layer through the process of cementation (Speybroeck et al., 2006).
These mitigation examples for counteracting erosion are temporary solutions and
continuous maintenance is necessary to keep up with the dynamic natural systems
resulting in high costs. Hard structures often also result in subsidence and noticeably,
areas behind such structures are lower than undisturbed areas where the sediment
budget is still intact (Ysebaert, 2016). Submerged hard engineering structures could
even result to negative effects on the shoreline oriented at the lee side of these
structures resulting in coastal erosion. Alternative solutions include building-with-nature
rather than building-on-nature and can be classified under the term ‘soft’ defense
structures (Temmerman et al., 2013; Bouma et al., 2014). These solutions aim at
providing a self-sustaining system based on feedback loops as reaction to changes in
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the physical environment (Ysebaert, 2016). Examples of these ‘soft’ defense structures
include salt marshes, wetlands, mangroves, and biogenic reefs.
By using oyster reefs as a strategy within coastal defence schemes, the regulating
functions of these organisms become the main focus. The effects that the physical
structure of the reef has can be compared to artificial reefs, already in use for the sole
purpose of coastal protection (Armono, 2004; Ranasinghe, et al., 2006; Soliman, et al.,
2011; Van Rijn, 2013b; Bonaldo et al., 2014). In an optimal system, it would not be
oyster reefs alone providing the stability against coastal erosion and storm surges
(Figure 5). Bouma et al. (2014) express the importance of a good synergy between
various ecosystem engineers. Here, the regulating functions oyster reefs would be
complementary to the functions exerted by seagrasses and marshes creating an
optimum use of ecosystem services for a specific purpose (Temmerman et al., 2013;
Bouma et al., 2014). This technique is becoming more and more recognized.
Figure 5: Synergy of different ecosystem engineers to promote coastal protection (Ysebaert, 2016).
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3. Work objectives
The aim of this thesis is to provide a better understanding in certain regulating
functions of oyster reefs, outside the boundaries of the reef. For this purpose, six oyster
reefs were studied in the Oosterschelde, SW Netherlands. This thesis will start by
defining the influenced area by means of morphological changes. These changes will
be explained by looking at the reef characteristics as well as the general trends from
dominating currents, waves and erosion rates. Once the influenced zone is
established, sediment characteristic variables will be compared between the influenced
and non-influenced zone to gain better insight of the effects on the sedimentation at the
lee side of oyster reefs. Our first hypothesis is that, based on literature (Armono, 2004;
Soliman et al., 2011; Van Rijn, 2013b) and physical laws (Wright et al., 2012), (Law of
Stokes), the sediment composition on the lee side of such an oyster reef will comprise
of higher percentages of fine materials compared to the non-influenced and thus less
protected zone.
A second objective of this thesis is to provide for a comparison between two methods
of vertical elevation determination. Here, Differential GPS (Dgps) measurements will be
compared to elevation models created by drone imaging for accuracy with the purpose
of determining the influenced area of oyster reefs by drone imaging. The goal of this
side-study is to eventually replace or minimize extensive (i.e. time-consuming) Dgps
measurements by drone imaging, potentially reducing time and costs for further
research on this or related topics.
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4. Material and methods
4.1. Study area
The Oosterschelde is situated in the Southwest of the Netherlands. This large tidal
basin of about 350 km² is comprised of tidal flats, mudflats, gullies and salt marshes.
This system was subjected to radical changes since 1987 when the Delta works were
finished as a safety measure resulting from the disastrous flood of 1953. These works
implied the construction of a storm surge barrier in the mouth and two
compartmentalization dams. As a consequence, tidal volumes decreased and sediment
exchange with the North sea became near to impossible (de Ronde et al., 2013). Wave
action along with the decrease of tidal stream velocities led to an inability of bringing
sand from the channels back on top of the tidal flats which resulted in net erosion of the
intertidal zone (van Berchum & Wattel, 1997; Kessel, 2004). The disappearance of
these tidal flats will eventually result in increased risk of dike bursts and flooding during
storms in consequence of stronger waves (van Zanten & Adriaanse, 2008; de Ronde et
al., 2013). The general prediction, in which sea level rise is included, proclaims 40 % of
the intertidal areas gone by 2050 including a complete loss of the intertidal zones with
exposure time 60-100% (de Ronde et al., 2013). Eventually, this trend will lead towards
a total loss of the intertidal areas (Kessel, 2004). This phenomenon translates further
into a possible shift of species (Kessel, 2004; van Zanten & Adriaanse, 2008; Cozzoli
et al., 2013), potentially meaning for the Oosterschelde that for instance conditions will
favour the growth of Pacific oysters (Crassostrea gigas) at the expense of cockles
(Kessel, 2004). This decrease in emersion time will also result into a shorter timeframe
for water birds, especially waders to forage on the tidal flat during low tide, leading to a
decrease in bird numbers, in particular in winter when there is a higher need of
resources (de Ronde et al., 2013). Many of the areas at risk of disappearance are of
great importance for the preservation of different species of wader birds, such as the
Oystercatcher, Grey Plover and Knot (Natura 2000).
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4.2. Studied species
Up until the start of the 1960’s, the Oosterschelde was a hotspot for the farming of
European flat oysters (Ostrea Edulis). Most of the flat oyster parcels were no longer
vital after the harsh winter of 1962-1963. The remaining parcels had to cope with the
disease ‘Bonamia ostrea’, causing lethal infections in the oysters (Kessel, 2004). As
alternative, the Pacific oyster (Crassostrea gigas) was introduced from British Columbia
in 1964 (Troost, 2009). Mild winters during following years and the warm summer of
1976 provided possibilities for the Pacific oyster to spread out along the Oosterschelde.
In addition, reduced exposure time resulting from sediment starvation favored growing
conditions for these oysters. About 15 ha of intertidal area was covered by Pacific
oysters in 1980. Within 10 years, the oyster-covered area was about fifteen times
larger. This explosive expansion is probably due to the favorable conditions for the
oyster larvae in 1989 (Kessel, 2004). The rapid expansion (Smaal et al., 2009) of these
reefs leads to the need for better understanding of their ecological functioning.
4.3. Study sites
Three sites containing natural Crassostrea gigas reefs were selected in the
Oosterschelde: Yerseke, Viane and Roggenplaat, Figure 6. Each site contained at
least one dense Crassostrea gigas reef. As reefs are mainly located in the low
intertidal, only allowing a short timeframe to work in, reefs near the low water line were
excluded.
Figure 6: Overview of the three study sites: Yerseke, Viane and Roggenplaat. Black points indicate reef
locations. Original image is taken from Hesselink, et al. (2003).
23
In total, six reefs of two different sizes were studied (small ≤ 10 m and big > 10 m).
Yerseke contained one big reef, Viane two small reefs and one big reef and
Roggenplaat one small and one big reef. The big reef located at Roggenplaat however,
consisted out of three smaller reefs that were considered as one big reef since the
distance in between was less than 2.5 m (Figure 7).
Figure 7: Image of reefs at the three study sites. Upper images showing aerial views from Y1 (left) and V3
(right). Lower picture shows reef R2.
4.4. Data collection and data analysis of the studied reefs
4.4.1. Environmental conditions at the reef site
4.4.1.1. Erosion rate
Trends in the tidal flat dynamics (erosion or sedimentation) of the three sites were
studied using LIght Detection And Ranging of Laser Imaging Detection And Ranging
(LIDAR) data obtained by Rijkswaterstaat. For describing the general erosion patters of
the study site, ten random pixels were chosen in arcGIS at each site for which
differences in vertical elevation over the years were averaged.
24
4.4.1.2. Current speed and direction
Predominant current directions were obtained by analysing data gathered from
hydrodynamic model runs (pers. Comm. L. de Vet). Matlab was used to write a custom
script to process data which resulted in current speed and vector angle in time along
with a frequency distribution graph for the month of August 2014.
4.4.1.3. Wind characteristics
The Oosterschelde is too shallow to produce groundswell. Therefore, the wave
patterns completely depend on local wind fetches which produce short period waves.
These wind fetches were analysed using Windguru (www.windguru.com) archive with
available data from 2006 up to 2015. Days with hard wind (≥ 6 Bft) were used to
describe general dominant wave directions. For each study site, nearest location
available on Windguru was used for performing the analysis.
4.4.2. Bathymetry
4.4.2.1. Bathymetry data collection via Dgps
Measurements of elevation of the reefs and the surrounding areas were taken using a
differential GPS with a vertical measure accuracy of 13 mm (Leica GS12, Leica
Geosystems AG, Switzerland, correction signal: SmartNet, Leica Geosystems, the
Netherlands). Contours of the reef were measured on the sediment directly adjacent to
the reef. Reef height was gathered by measuring at different locations on top of the
reef. X, y, z coordinates were taken to the point that spatial coverage was satisfactory
(Figure 8). Smaller intervals within measurements were used when special features
such as depressions occurred.
Figure 8: Dgps data points as Rijksdriehoek coordinates in meters from a studied reef at Yerseke.
390020
390030
390040
390050
390060
390070
390080
390090
390100
390110
390120
62880 62900 62920 62940 62960 62980 63000
y (m
)
x (m)
Reef
Reef contour
surrounding
25
4.4.2.2. Bathymetry maps from Dgps data
Vertical elevation data from each reef, reef contour and surrounding reef area was
used to create 3-dimensional surface maps by linear interpolation on a Cartesian grid.
To investigate morphological effects caused by reef influence, the natural background
slope of the tidal flat was deducted from the interpolated data points. For each
investigated reef area, the natural background was obtained using a 2-dimensional
polynomial regression curve, created by the Curve fitting Toolbox of Matlab. For each
reef, perimeters were drawn on the surface maps along with contour lines at 1, 2, 3 and
4 cm elevation. Due to equipment inaccuracy, results from elevation at 1 and 2 cm
should be looked at as indicative. Characteristics of the investigated reef areas and
their respective influence zones were obtained by analyzing scaled images using
SketchAndCalcTM. In this study we define reef length (L) as the maximum distance
within the perimeter of the reef. Reef area is considered as Ar and reef perimeter as P.
L2D is introduced as the maximum length of the reef perpendicular to the dominant
direction of the morphologically influenced area. Height of the reef (H) was considered
as the highest point measured on the reef relative to the average elevation of the reef
contour. Maximum distance of the zone influenced by the reef (Li) was determined by
the maximum distance within the morphologically influenced zone, parallel to the
dominant direction of this elevated area. Morphologically influenced area is annotated
as Ai. In Figure 9, an overview is presented indicating all measured reef variables.
26
Figure 9: Overview of reef variables. Hypothetical reef is drawn along with the morphologically impacted
area. Example shows how reef variables are defined via SketchAndCalcTM. Dominant direction of the
morphologically influenced area is shown by means of an arrow. L: reef length; L2D: maximum Length of the
reef perpendicular to the dominant direction of the morphologically influenced area; Li: maximum distance
within the morphologically influenced zone, parallel to the dominant direction of this elevated area; Ar: reef
area; P: reef perimeter; Ai: morphologically influenced area.
4.4.2.3. Statistical analysis of reef characteristics
Additional data was obtained by adding reefs R1, R2 and R4 (connoted in this thesis as
‘R1, Walles’; ‘R2, Walles’; ‘R4, Walles’) investigated by Walles et al. (2014) which showed a
defined influenced area at 1, 2, 3 and 4 cm elevation above natural background slope.
By using linear regression models, these characteristics were tested for correlation.
Furthermore, a stepwise linear regression with forward and backward substitution was
performed to investigate the parameters that create the best fit using Akaike
Information criterion (AIC). All analyses were performed with ‘R’ statistical software (R
Development Core Team).
4.4.2.4. Bathymetry data collection via drone
To investigate the accuracy of Low Altitude drone imaging, a DJI inspire 1 quadcopter
equipped with a Zenmuse X3 camera was used to take high resolution images. Two
imaging campaigns were performed, one in April 2016 at Yerseke and one in June
2016 at Viane, covering three of the studied reefs (Y1, V2, V3). No drone flights were
executed at Roggenplaat. Weather conditions at time of flight are summarized for both
sites in Table 1. To ensure a spatial resolution of 1 cm, flight altitude was kept at 18 m
27
and the flight speed was maintained at lower value to provide a minimum of 70% image
overlap. Digital elevation maps (DEMs) were constructed with software Agisoft
Photoscan (St Petersburg, Russia). Obtained point cloud was georeferenced using at
least seven ground control points for each site (Figure 10). Each ground control point
was measured using a Dgps (Leica GS12, Leica Geosystems AG, Switzerland,
correction signal: SmartNet, Leica Geosystems, the Netherlands).
Figure 10: Example of an aerial drone image (reef V3). White spots with black crosses are ground referencing
points.
Table 1: Environmental conditions
Site Coordinates in RD new
(m)
Date
(dd/mm/yy)
Time
Wind
speed
(Bft)*
Wind direction* Weather
conditions
Yerseke 62,972.820 390,042.131 21/04/16 midday 3 NE Sunny, no
clouds
Viane 59,512.487 403,614.965 01/06/16 morning 2 N Clouds,
fog
* Data obtained from archive from www.windguru.com at nearest location to site.
4.4.2.5. Drone data validation
Points measured with the Dgps were utilized to investigate the validity of the point
cloud originating from low altitude remote sensing. Two datasets for each location were
derived from the point cloud by means of interpolation at 1 m and 0.1 m level.
Interpolated points within a certain distance (a) of each Dgps point were averaged and
compared to the respective Dgps point by means of linear correlation to the 1:1 line
(RMSE was determined from the data points excluding reef data points). To be able to
compare Dgps and drone data points, the same coordinate system had to be used for
28
both data sets. Drone coordinates (x, y) were converted from WGS 84 to RD New
using the project tool (data management toolbox) from arcGIS. Conversion formula for
the z-coordinates from WGS84 to RD New was not found thus the projection was done
using the Curve fitting Toolbox of Matlab.
Obtained drone data points were further processed in the same way as was done with
Dgps data for the creation of bathymetry maps. Morphologically influenced areas by
oyster reefs obtained from Dgps measurements and drone data were compared per
site and per elevation above natural slope of the sand flat. This comparison was
performed by a visual observation of the direction of the influenced area obtained by
both data sources, followed by the quantification of the overlapping areas elevated 1, 2,
3 and 4 centimetres above the natural slope of the sandflat.
4.4.3. Sediment sampling
4.4.3.1. Sampling design
To investigate spatial effects of biogenic reefs on larger scales, random points were
generated around the reef. Walles et al. (2014) showed a correlation between the
impacted area beyond the reef and the length of the reef in longitudinal direction with
the elevated area (i.e. sediment plume). Since the dominant direction was largely
unknown for most of the reefs investigated, the boundary condition for the random
sampling points is defined as the maximum distance (L) between two points on the
contour of the reef. The reef is then contoured by a rectangle with base L and as height
two times the furthest point on the contour perpendicular to L (Figure 11).
For practical reasons, minimum distance between each point was restricted to 40 cm.
The amount of samples followed a logarithmic function proportional to L. The number
of samples ranged from 24 for very small reefs (L = 1 m) to 120 for big reefs (L = 350
m). This amount is chosen in order to have a full coverage with smaller reefs and
minimum coverage with larger reefs. The custom program for the sample design was
written in ‘R’ statistical software (R Development Core Team).
29
Figure 11: Schematic overview of sampling design. Length as the maximum distance within the reef contour.
Green line signifies maximum distance to reef contour, perpendicular to L.
4.4.3.2. Sediment sample collection
Three centimeters of the top sediment layer was taken with a 100 mL plastic syringe
with enlarged opening. The removed layer was stored in a plastic vial with screwcap.
Upon arrival at the lab, samples were immediately cleaned from the outside, weighed
and stored in the freezer at -20 degrees Celsius. Once frozen, the samples were
freeze-dried and weighed.
Water content resulting from weighing differences was not reliable since residual water
was still present on top of the sediment at some locations. This variable will thus not be
used in the proceedings of this thesis.
4.4.3.3. Particle size analysis
Freeze-dried sediment samples were homogenized by shaking vigorously. Particle size
and composition was analyzed using laser diffraction techniques by Malvern
Mastersizer 2000 (0.02 µm-2000 µm detection range). MWTL protocol was utilized and
sediment samples were analyzed at NIOZ, Yerseke.
30
4.4.3.4. Sediment statistical analysis
Sediment variables used for further statistical analysis are given in Table 2.
Table 2: Sediment variables and their meaning
Variable Explanation
Scoarse Coarse sand fraction (500-1000 µm)
Smedium Medium sand fraction (250-500 µm)
Sfines Fine sand fraction (125-250 µm)
Svfines Very fine sand fraction (63-125 µm)
Ssilt Silt % (<63 µm)
Sd50 Median grainsize D50 in µm
Sediment average particle size results were analyzed per site and location using
Kruskal-Wallis test followed by dunn’s multiple comparison as post-hoc test to
investigate significant differences using Bonferroni p-value adjustment. For comparing
the significance for sediment variables between influenced and non-influenced zone,
student’s t-test was used. All statistical analyses were performed using ‘R’ statistical
software (R Development Core Team).
31
5. Results
5.1. Site characterization
5.1.1. Local tidal flat dynamics
Of the three studied sites, reefs situated in Viane were located lowest in the intertidal
zone followed by reefs at Yerseke and Roggenplaat. An overview of the three study
sites along with their respective erosion rates is presented in Table 3. Yerseke and
Viane showed net erosion (1.40 and 0.85 cm/year respectively) while the area around
the studied reefs at Roggenplaat showed net accretion (0.67 cm/year) over the period
of 2010 to 2013.
Table 3: Description of study site.
Reef sites Coordinates in RD New
(m)
[Zmin,Zmax]
(m+NAP)**
Sedimentation/erosion
(cm/year)*
reefs studied
Yerseke 62,972.820 390,042.131 [-1.50, -1.19] - 1.40 Y1
Viane 59,512.487 403,614.965 [-1.68, -1.23] - 0.85 V1, V2, V3
Roggenplaat 46,122.526 411,221.288 [-1.12, -0.75] + 0.67 R1, R2
* Calculated with Lidar data from 2010 and 2013 obtained from Rijkswaterstaat.
** Zmin, Zmax are taken from all data points excluding reef data points
5.1.2. Local current patterns
All three sites showed two characteristic peaks in the flow velocity (Figure 12, right
image). Flow velocity was highest at Yerseke followed by Roggenplaat and Viane. For
every study site, the main peaks in flow velocity occurred at 3 hours before high tide
and right after high tide. Yerseke showed generally a very strong shift in angle at mid-
tide indicating the presence of two well defined flow directions. At Yerseke, the peak
flows are directed towards SSE during flood tide and NNW during ebb tide. For Viane,
main peaks in flow velocity were directed towards ESE during flood tide and WNW
during ebb tide. At Roggenplaat, peaks in flow direction were predominantly towards
ESE during flood tide and WNW during ebb tide. For sites Viane and Roggenplaat, the
angle of flow shifts when the flow is still close to its maximum resulting in a more
elaborate spectra of flow directions with still a relatively high flow velocity (Figure 12,
left image).
32
Figure 12: Frequency distribution graphs for current patterns for the three study sites (left graph). Current
speed (m/s) expressed by colour scale, frequency expressed as percentage. Graph expressing 10 tidal cycles,
current speed (m/s) and current direction (right graph). Angle indicates the direction of flow at a certain time
with 0° representing a current flow towards the east, 90° to the north, -90° to the south and ±180° to the west.
33
5.1.3. Wind characteristics
Table 4 shows that wind blows predominantly from the SW for the three study sites.
The analysis over 10 years’ time shows that Roggenplaat showed the most days (480)
with hard wind (≥ 6 Bft), followed by Viane (221) and Yerseke (111).
Table 4: Wave characteristics of the three study sites
Reef sites Wave direction
range (wind ≥ 6 Bft)
Dominant wave
direction
(wind ≥ 6 Bft)
Frequency over 10 years
(days ≥ 6 Bft)
Yerseke S-NW SW 111
Viane S-NW SW 221
Roggenplaat S-NW SW 480
5.2. Reef characteristics
Overall, studied reefs ranged from 2.9 m up to 20.6 m in length and between 0.21 and
0.64 m in height. The area and perimeter of the investigated reefs varied between 3.56
m² and 188.61 m² and 7.18 m and 57.27 m respectively (Table 5). The reefs at
Yerseke (Y1) and Viane (V1, V2, V3) showed an irregular shape. Reefs at Roggenplaat
had a more aligned shape as well as strong vertical elevation on a short distance.
34
Table 5: Reef characteristics of studied reefs and influenced areas by those reefs. L2D as the maximum length of the reef perpendicular to the direction of the elevated area. Li as the
maximum distance between the reef perimeter and the elevated contour line, perpendicular to L2D.
Reef parameters Morphological influence zone
Location Reef Surface
area (m²)
Perimeter
(m)
Length
(m)
L2D
(m)
Reef top
(m + NAP)
Height
(m to
background)
Surface area
(m²)
Li
(m)
Direction
elevated
area
1 cm 2 cm 3 cm 4 cm 1 cm 2 cm 3 cm 4 cm
Yerseke 1 188.61 57.27 20.6 17.00 -0.762 0.533 297.49 149.78 93.92 44.15 17.00 10.53 8.82 5.74 n.d.*
Viane
1 3.63 8.59 3.10 3.10 -0.944 0.348 9.45 7.09 4.63 1.76 2.77 2.48 2.34 1.40 N
2 14.56 15.57 4.70 3.70 -1.015 0.480 44.09 26.95 18.32 13.73 5.27 4.31 3.62 3.09 NE
3 75.45 41.3 14.3 13.17 -0.855 0.636 480.36 405.29 341.72 226.77 24.42 20 17.79 16.74 NE
Roggen-
plaat
1 6.15 10.03 4.10 3.51 -0.664 0.356 45.47 33.74 25.02 16.50 4.44 3.86 3.48 3.00 S
2 a 3.56 7.18 2.89 2.89 -0.711 0.213 66.23 38.55 21.91 13.06 11.31 4.77 5.50 3.73
S 2 b 9.55 12.4 3.85 3.85 -0.682 0.297 54.10 39.57 24.91 15.47 11.20 8.66 7.84 6.24
2 c 20.83 18.98 8.14 8.14 -0.540 0.429 107.19 65.62 47.74 31.74 12.66 10.89 10.79 9.00
* no real influenced zone found.
35
5.3. Morphological effects on surrounding
5.3.1. Oyster reef effects on vertical elevation
Morphologically influenced areas at the reefs of Viane ranged in direction from North to
Northeast, while studied oyster reefs at Roggenplaat had an influence zone directed
towards the South (Figure 13). The investigated reef located at Yerseke did not show a
clear influence zone because the elevation differences of the surrounding sediment
were too small to show effects.
Figure 13: DEM for the studied reefs. Coordinates are in meters (RD New coordinate system), elevation is
represented in meters by a colour scale, black dots stand for reef contour and the 1, 2, 3 and 4 cm elevation
above natural slope is represented by a blue, green, yellow and red line respectively. Reef V3 is the reef on the
right side of the respective figure and reef R2 comprises of the three reefs in the centre of the corresponding
figure. Tidal current frequency distribution graphs are presented above each DEM as an indication for the
dominant current direction. These graphs can be seen enlarged in Figure 12.
Most reef variables showed strong linear correlations with their respective influence
zone, Table 6. The area of the reef, perimeter of the reef and the L2D value showed the
strongest linear relationships with an elevated area defined as 3 cm above the natural
background slope. The area of the reef seems the best explaining variable for the 3 cm
defined influenced area with an R² of 0.971 (p < 0.001) (Figure 14).
36
Figure 14: Regression between reef area and influenced area at 3 cm above natural background slope. Reef Y1
was left out of consideration. R1,Walles, R2,Walles, R4,Walles were obtained from Walles et al. (2014).
The maximum distance (Li) from the contour line to the perimeter perpendicular to L2D
also showed strong relationships with the respective reef parameters. Li showed the
strongest linear correlation with L2D, defined with the contour line elevated 4 cm above
the natural background slope (R² = 0.931, p < 0.001), presented in Figure 15.
Perimeter and area of the reef also showed strong correlations with Li. The reef studied
at Yerseke was left out of consideration since, as mentioned before, no real influence
zone could be determined.
V1
V2
V3
R1 R2,a R2,b R2,c
R1,Walles
R2,Walles
R4,Walles
R² = 0.9706
0
100
200
300
400
500
600
0 20 40 60 80 100 120
Ai,
3cm
(m
²)
Ar (m²)
Reef area to influenced area at 3 cm
37
Figure 15: Regression between L2D and Li,4cm. Reef Y1 was left out of consideration. R1,Walles, R2,Walles, R4,Walles
were obtained from Walles et al. (2014).
Table 6: Linear regression between reef variables and influenced zone. Highest R² values are underlined.
R² (p-values <0.05)
Ai, 1 cm Ai, 2 cm Ai, 3 cm Ai, 4 cm Li, 1 cm Li, 2 cm Li, 3 cm Li, 4 cm
Area 0.928 0.941 0.971 0.968 0.808 0.923 0.906 0.930
Perimeter 0.924 0.925 0.955 0.941 0.828 0.928 0.906 0.928
L2D 0.887 0.876 0.911 0.891 0.851 0.924 0.921 0.931
H 0.493 0.494 0.563 0.540 0.404 0.494 0.563 0.540
Data from three isolated oyster reefs (R1,R2,R4) studied by Walles et al. (2014) was included in
this table.
Stepwise linear regression models are shown in Table 7 and explain that reef area and
reef height are better predictors for morphologically impacted area (p < 0.01). Li, 4 cm
seems to be represented by a combination of reef perimeter, L2D and reef height (p <
0.001).
V1
V2
V3
R1 R2,a
R2,b
R2,c
R1,Walles
R2,Walles
R4,Walles
R² = 0.9311
0
5
10
15
20
25
0 2 4 6 8 10 12 14 16 18
Li, 4
cm
(m)
L2D (m)
Regression of L2D and Li,4cm
38
Table 7: Stepwise linear regression using forward and backward substitution using Akaike Information
Criterion.
Linear model Ai, 3 cm AIC Linear model Li, 4 cm AIC
Ai, 3 cm = Ar + P + L2D+H 69.48 Li, 4 cm = Ar + P+ L2D + H 16.18
Ai, 3 cm = Ar + P + H 68.80 Li, 4 cm = P + L2D + H 14.20
Ai, 3 cm = Ar + H 68.13
Data from three isolated oyster reefs (R1,Walles,R2,Walles,R4,Walles) studied by Walles et al. (2014)
was included in this table.
5.4. Effects on sediment characteristics
Sediment Sd50 data (Figure 16) showed significant differences between Yerseke and
the other sites (p < 0.001), except for V3. V1, V2 and V3 did not show any significant
difference among each other (p > 0.05). R1 and R2 showed significant difference
between each other (p < 0.05) and the rest of the sites (p < 0.001).
Figure 16: Sd50 boxplot per reef site.
39
Figure 17: Average sediment variables (%) per reef site.
In general, all sites showed a high fine sediment fraction and very low coarse sediment
fraction (Figure 17). Medium and very fine sediment fraction along with silt content
showed large differences between sites. Higher medium fraction sediment found at
Roggenplaat along with lower very fine sediment fraction indicated a general average
larger sediment size in comparison with the other locations. This information can also
be derived from the Sd50 presented as a boxplot in Figure 16.
Morphologically influenced areas by Crassostrea gigas reefs were compared to non-
influenced areas by differences of sediment variables in those areas. In Figure 18,
three centimetres above the natural background slope was chosen to represent the
morphologically influenced zone to compare sediment variables. As mentioned before,
Yerseke did not show clear influential zone. Sediment data of this site will thus not be
used to make further conclusions. For the reefs at Roggenplaat, R1 showed significant
differences between influenced and non-influenced zone for sediment variables Sfines
and SVfines with both variables being higher at the non-influenced zone. R2 only
showed significant differences between the respective areas for Svfines which was
higher in the non-influenced zone. All sediment characteristics, except for Scoarse,
seem to follow a similar pattern when comparing influenced and non-influenced zone.
For these three reefs, the non-influenced zone comprises of a lower Sfines fraction and
higher Svfines- and silt fraction compared to the influence zone (p < 0.05).
0
10
20
30
40
50
60
70
80
Y1 V1 V2 V3 R1 R2
Ave
rage
sed
imen
t va
riab
les
(%)
Average sediment variables per site
Scoarse (%)
Smedium (%)
Sfines (%)
Svfines (%)
Ssilt (%)
40
Figure 18: Comparison of sediment variables between non-influenced and influenced zone defined as 3 cm
above natural slope. When ‘*’ sign is indicated above a certain variable, significant difference (p < 0.05) was
found between morphologically influenced and non-influenced area.
5.5. Alternative method of creating digital elevation models (DEMs) with
drone imaging
From DEMs created by the data cloud originating from drone images, largest errors
occurred from measurements either on the reef itself or on the contour (Figure 19).
This is a logical result since there are large differences in elevation on short range,
created by the distinct roughness of the reef. As expected, interpolation of drone data
with smaller grid cells (0.1 m as to 1 m) resulted in a better estimation of the
morphologically impacted area (Table 8). Noticeable is that the vertical range of data
points (excluding reef data points) is very limited at Yerseke as there is no clear
influenced zone. The impacted area by the other two reefs (V2, V3) show high
resemblances morphologically as well as direction (Figure 20) and size of this area
created by these reefs. Best results were obtained for Viane when drone data was
interpolated every ten centimetres (root mean square error of estimate = 0.0378 m).
41
Figure 19: Elevation (m) measured with Dgps compared to elevation measured by drone at 0.1 m interpolation
with a = 0.1 m (left figure). Error in elevation (m) plotted over x and y coordinates (middle figure). Dgps
datapoints as black dots and interpolated area from drone data in color expressed over x and y coordinates
(right figure).
Table 8: Overview and comparison of influence areas (Ai) of Y1, V2 and V3.
Elevation
(cm)
Reef Ai,Dgps
(m²)
Ai,drone,1
(m²)
Ai,drone,0.1
(m²)
𝐴𝑖, 𝑑𝑟𝑜𝑛𝑒, 1
𝐴𝑖, 𝐷𝑔𝑝𝑠∗ 100
(%)
𝐴𝑖, 𝑑𝑟𝑜𝑛𝑒, 0.1
𝐴𝑖, 𝐷𝑔𝑝𝑠∗ 100
(%)
1
Y1 284.01 115.79 145.95 40.77 51.39
V2 44.09 38.08 40.43 86.37 91.70
V3 480.36 431.43 461.26 89.81 96.02
2
Y1 149.78 69.97 88.47 46.72 59.07
V2 26.95 21.74 26.81 80.67 99.48
V3 405.29 337.02 377.42 83.16 93.12
3
Y1 93.92 44.96 60.12 47.87 64.01
V2 18.32 16.38 17.18 89.41 93.78
V3 341.72 270.80 291.11 79.25 85.19
4
Y1 44.15 31.16 34.14 70.58 77.33
V2 13.73 10.55 12.29 76.84 89.51
V3 226.77 197.71 203.14 87.19 89.58
42
Figure 20: Example of digital elevation models created by Dgps data and drone-imaging. Elevation is
represented by a colour scale, units are in meters. Pink line represents the contour line at 3 cm above natural
background. Pink lines which connect to the reef are considered as influenced zones by that reef. Black dots
represent reef contour.
43
6. Discussion
The aim of this thesis was to expand insights on the morphological effects of Pacific
oyster reefs (Crassostrea gigas) on the environment beyond their own boundaries
since there is only limited knowledge currently available on this topic. For this study, six
reefs were studied in the Oosterschelde. In accordance with Walles et al. (2014), we
found elevated areas adjacent to the reef which can be subscribed to the reef presence
(Figure 13). These elevated areas are most likely not the result of a sole environmental
force in play but more likely to be a complex interplay between currents, waves and
suspended matter, present in the water column, as well as local morphological
conditions. However, the theoretical part alone often does not suffice in fully explaining
these effects. Yerseke for example showed signs of reef deterioration by fishing
activities along with wave disturbances coming from a channel to the North of this reef
which is frequently used by mussel and oyster vessels. These local disturbances could
explain why no real morphologically influenced zone was found at this location. The
other five reefs did not show clear signs of external (i.e. human-induced) disturbances.
After investigating the general current patterns for each study site (Figure 12; Figure
13), it is visible that the morphologically impacted area is not a direct result from a
certain dominant current direction originating from tidal action. Seemingly, the effect of
current speed on elevated areas is composed of a combination of both flood and ebb
tidal patterns since the elevated zone is in all study sites perpendicular to the dominant
current patterns.
The effect of waves mainly results in accretion of sediments on the lee side of the reef,
defined by a dominant wave direction (Alferink, 2016). The dominant short-period wave
action based upon low pressure wind systems corresponded with the morphologically
impacted area at Viane (predominant wind/wave direction: SW; Morphologically
influenced area: N-NE). Along with the fact that predominant wave action occurs from
the southwest and that Viane is situated in an ‘erosional hotspot’ (de Ronde et al.,
2013) (Figure 21), the elevated area at those reefs (V1, V2, V3) in the lee side results
from the sheltering capacity by the physical presence of the reefs.
For Roggenplaat, the elevated area due to reef presence was opposite to the
predominant wave action. However, this does not mean that wave action is of less
importance here. The fact that predominant wave action occurs from the southwest
explains the sediment flow towards the Northeast on the Roggenplaat where accretion
occurs (Figure 21). The southern situated elevated area of both reefs (R1, R2) at this
study site could be explained by the physical reef structure, blocking the sediment flow
in Northern direction.
44
Figure 21: Tidal flat dynamics for Roggenplaat and Viane. Negative (Positive) number signifies erosion
(sedimentation) in centimetres between the period 1990 - 2010 (de Ronde et al., 2013). The reef locations are
represented by a black cross.
The morphologically influenced zone, characterized by a dominant direction can be
quantified (Ai, Li) and shows good correlations with the area of the reef (Ar), reef
perimeter (P) and maximum length of the reef perpendicular to the dominant direction
(L2D). All reef characteristics showed individual positive linear correlations with each
variable from the morphologically influenced zone.
The first hypothesis put forward implied that higher fractions of sediments with smaller
grain size would be found on the lee side of the reef since, theoretically, calmer
conditions are created in this area resulting in accretion zones (point 2.3.1 of this
thesis). However, counterintuitive results were obtained, especially for reefs located at
Viane. At most of the investigated sites, it was already visible during field campaigns
that coarser sand was found on the lee side of the reefs and clayish cohesive sediment
was found on the exposed side (V1, V2, V3, R2). For Viane, an alternative hypothesis
could be that erosion has occurred in such a way that a cohesive clayish layer is
reached on the exposed sides of the reef and that either sedimentation occurred at the
sheltered side or that prior sediments are being withheld by the physical presence of
45
the reef. This could potentially explain the result of coarser sediments on the lee side
and finer material on the exposed side of those reefs (V1, V2, V3).
However, this topic ends with an open question of whether this new hypothesis can be
substantiated with more proof. Taking historical cores from the sediment around the
reefs located at Viane and Roggenplaat can possibly be a first step towards a thorough
answer to this unsolved question.
As for the second part of this thesis, i.e. the facilitation of further research, drone
imaging inclined towards the possibility of using this technique in related research.
Morphologically impacted areas by Crassostrea gigas reefs showed similar direction
and shape on digital elevation maps created by Dgps compared to these maps created
with data originating from drone imaging. The quantification of these areas showed
promising results when an interpolation of 0.1 m was utilized and even better results
are to be expected when weather conditions are more favourable. Overall, for
determining the morphologically impacted area resulting from Crassostrea gigas reefs,
this technique shows high promise as alternative to extensive Dgps measurements.
46
7. Conclusions
Crassostrea gigas reefs exert multiple ecosystem services including regulating
functions that change local hydrology and thus morphology. The changes made by the
reefs in morphology result in general in defined elevated areas on the lee side of such
reefs. The direction and size of the morphologically impacted areas are dependent of
reef characteristics, position of the reef on the tidal flat and environmental parameters
(currents, waves, suspended matter in water column) as well as physical disturbances
(fishing, shipping routes). To facilitate further insights on the morphological effects of
oyster reefs or related organisms, low altitude remote sensing via drones is showing
promise to offer a quick and reliable alternative to conventional Dgps bathymetry
mapping techniques.
The initial hypothesis that sediment with finer grain size would collect on the lee side of
the reef was proven differently for study site Viane and Roggenplaat (Yerseke did not
show a morphologically influenced zone and is thus excluded) at which counterintuitive
results were found at each reef. Larger fractions of ‘very fines‘ were found at the non-
influenced zone compared to the influenced zone of reefs R1, R2, V1, V2, V3 . For V1, V2,
V3, higher fractions of silt were located at the morphologically non-influenced zone
compared to the influenced zone. This result could possibly be explained by the fact
that Viane is located at an ‘erosive hotspot’ (de Ronde et al., 2013) of which the
physical presence of the reef shelters the sediment on the lee side (directed towards
the Northeast), preventing it to flow away by the dominant wave action occurring from
the Southwest. Alternative hypothesis for Roggenplaat entails that these reefs are
located in an accretion zone of which the sediment moves towards the Northeast.
Here, the flow of sediment is blocked by the reefs creating an elevated area directed
towards the South. For both locations, deeper sediment cores could offer more insight
to reinforce this theory.
The confirmation of this hypothesis would mean that oyster reefs not only provide
elevated areas in accretion zones, they also protect certain areas in an erosive
environment. This piece of information can be of vital importance for managing soft-
engineering coastal defense schemes.
47
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