1

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’

2

3

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’

4

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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