Department of Biology TEREC: Terrestrial Ecology

Academic year 2017/2018 The importance of spatial patterns of arenaria (Marram Grass) for communities and size distributions.

Paulien Vanhauwere

Promotor: Prof. Dr. Dries Bonte Copromotor: Dr. Martijn L. Vandegehuchte Mentor: Drs. Jasmijn Hillaert

© May 10 Faculty of Sciences – Terrestrial Ecology

All rights reserved. This thesis contains confidential information and confidential research results that are property to the UGent. The contents of this master thesis may under no circumstances be made public, nor complete or partial, without the explicit and preceding permission of the UGent representative, i.e. the supervisor. The thesis may under no circumstances be copied or duplicated in any form, unless permission granted in written form. Any violation of the confidential nature of this thesis may impose irreparable damage to the UGent. In case of a dispute that may arise within the context of this declaration, the Judicial Court of Gent only is competent to be notified.

2 TABLE OF CONTENTS

I. Introduction ...... 5

Ecosystem services and multifunctionality ...... 5

Ammophila arenaria, central species in foredune ecosystems ...... 6

Plant spatial patterns ...... 6

Spatial configuration and fragmentation ...... 8

Spatial configuration and body size ...... 8

This study as part of a bigger framework ...... 8

Research questions ...... 9

Aim ...... 9

II. Materials and Methods ...... 10

Collecting data ...... 10

Fieldwork ...... 10

Identification of invertebrates in the collected samples ...... 13

Length measurements ...... 13

Calculation of proportion and spatial autocorrelation of Ammophila arenaria...... 14

Data analysis ...... 14

Exploratory graphs, ordinations and PERMANOVA ...... 14

Mixed linear model...... 15

III. Results ...... 17

Effect of Ammophila arenaria pattern on community structure ...... 17

Exploratory graphs: Species richness and abundances ...... 17

Community structure: NMDS-ordination and PERMANOVA ...... 18

Effect of Ammophila arenaria pattern on size distribution of ...... 20

Exploratory graphs: length distribution ...... 20

Mixed linear models ...... 23

IV. Discussion ...... 25

3 Effect of Ammophila arenaria pattern on community structure ...... 25

Species richness and Abundances ...... 25

Plant spatial pattern and plant vitality in relation to species composition ...... 26

Effect of Ammophila arenaria pattern on invertebrate size distribution ...... 27

Length distribution graphs and Plant spatial patterns related to invertebrate body length ...... 27

Importance to conservation ...... 30

Remark ...... 30

Importance of Ammophila arenaria vegetation and arthropod communities in dune formation...... 30

V. Conclusion ...... 32

VI. Summary...... 33

English summary ...... 33

Nederlandse samenvatting ...... 33

Samenvatting voor leken ...... 34

VII. Acknowledgments ...... 35

VIII. References ...... 35

IX. Appendix ...... 40

4 I. Introduction

Ecosystem services and multifunctionality Ecosystems are increasingly negatively impacted by several threats and pressures, mostly human induced like habitat fragmentation, habitat degradation and climate change. To predict the impact of those pressures, there is a need for a deeper understanding of ecosystem functioning. Developing ecosystem knowledge and engaging in adaptive management will enable humans to facilitate ecosystems that remain or become sustainable and resilient. Resilience, includes the ability to recover from disruptive events and the ability to cope with disturbances. Ecosystem resilience is highly important because it is closely linked to ecosystem services (Myers 1996), which are goods and services provided by ecosystems that are beneficial to people, communities and infrastructure. If ecosystem resilience declines, so will ecosystem services.

Coastal foredunes have the capacity to act as one of the most important natural defenses for coastlines from storms and floods by preventing erosion and inhibiting the disappearance of coastal habitats (Provoost et al. 2014). Threats, like storms, will become more frequent (Beniston et al. 2007) due to sea level rise caused by climate change (van Ypersele & Marbaix 2004). Global sea level has been rising at higher rates in the recent past and will continue to rise because of thermal expansion of the ocean and melting of glaciers (Stocker et al. 2013). Furthermore, climate change can be an important driver of processes which can change species interactions (Van der Putten 2012) and the environment.

Biodiversity is linked to the surrounding landscape characteristics and plays a key (but not exclusive) role in maintaining ecological and economic ecosystem services by stabilizing ecosystem processes over time and supporting ecosystem resilience (Loreau & de Mazancourt 2013; Myers 1996). Different species use space differently and together fulfill a greater variation of functional traits. Because can be linked to ecosystem function a positive feedback can occur where decreasing biodiversity can lead to a lower ecosystem functioning and loss in ecosystem quality, which in turn can result in a loss in biodiversity (Honnay et al. 2010). This can then continue habitat degradation through a loss of self- organizing spatial patterns. Thus, habitat fragmentation and degradations can have a negative impact on ecosystem functioning via its negative impact on biodiversity. In this study we only focus on the change in species composition depending on environmental factors, which is called beta-diversity (Whittaker 1972). Biodiversity, can be used as biological indicators for environmental changes (Clausen 1986). We choose to further focus on invertebrates because they have a short lifetime and thus adjust rapidly to changes in the environment. Moreover, in comparison to vertebrates, the effects of fragmentation are to a lower extent investigated. The obtained information can then be used for management and restoration purposes.

5 The purpose of this work is to contribute to the knowledge of dune ecosystem functioning. Here, we consider Ammophila arenaria (Marram Grass) as key species and hypothesize that the spatial configuration of A. arenaria plays an important role in coastal defense and structuring biodiversity. We try to explain possible variation in invertebrate body size as a function of plant spatial patterns. To our knowledge, the relationship between ecosystem resilience and biodiversity as expressed by vegetation patterns has not been investigated. Ammophila arenaria, central species in foredune ecosystems Dune formation depends on the interaction of sand supply, inland winds and obstacles. Obstacles, like , trap the sand. The interaction of these three factors can cause physical changes in sand flow (determined by topology) and vegetation development (dependent on sand dynamics and biotic interactions). Both processes determine resistance and resilience of dunes. Sand dynamics are sand fluxes determined by wind speed, grain size, moisture content, fetch length and beach and dune morphology. Ammophila arenaria has a dominant role in dune formation (Huiskes 1979). The ecological requirements of the grass are well documented (Huiskes 1977; Huiskes 1979; McLachlan 1991; Weeda et al. 1994), which make it a suitable species for our research. Spatial patterns of A. arenaria depend on and contribute to sand dynamics, which in turn influence the vitality of the grass. When A. arenaria occur in higher densities, wind velocity will reduce and induce a local positive feedback on the fixation of mobile sand. On the other hand, large-scale increase in plant coverage has a negative feedback on A. arenaria vitality as it reduces sand dynamics. A. arenaria has the capacity to rapidly outgrow burial of sand and needs a high input of sand to escape from root pathogens, as suggested by the escape hypothesis (Vandegehuchte et al. 2010). Thus, A. arenaria populations need a balance between vegetated patches and bare sand. The populations also have the power to rise with the sea level (Weeda et al. 1994), which make the dunes with A. arenaria an effective natural coastal defense structure. Plant spatial patterns Mechanisms as both consumer-resource, disturbance-recovery processes and scale-dependent feedback can give possible explanations for observed large-scale spatial patterns (Rietkerk & van de Koppel 2008). Self-organized spatial patterns are a general phenomenon and should lead to an increased resilience where there is a balance between bare sand and vegetated patches (Rietkerk & van de Koppel 2008). Such pattern can be a predictor of ecosystem functioning as plant cover and area are related to multifunctionality of the ecosystem (Berdugo et al. 2017). The patterns affect functional traits of associated species and their capacity to cope with changing environmental conditions (Liu et al. 2016). Loss of this balance can be ruinous and lead to catastrophic shifts at which dunes become either hyperdynamic and barren, or hyperstatic and fixed (Figure 1). Processes that promote mobilization or stabilization (Figure 2). Hyperstatic dunes for example result in a loss of biodiversity (Arens et al. 2012) which can be linked to a loss in ecosystem functioning as mentioned above.

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Figure 1: Impact of biotic and abiotic factors on Marram grass dunes and their effectiveness of fencing in the coastline. Processes that promote mobilization and stabilization can be consulted in Figure 2. (adjusted from Pisman n.d.).

Figure 2: Processes which promote mobilization on the right site and processes which promote stabilization on the left site (adjusted from Arens et al. 2012).

7 Spatial configuration and fragmentation Habitat fragmentation is a process in which habitat falls apart in many small, isolated patches throughout an entire landscape. This changes the habitat configuration (Fahrig 2003) and can lead to habitat loss (lower amount of suitable habitat). In many previous studies (see cited by Fahrig 2003), no distinction was made between the effects of habitat loss and change in the connectivity between habitats. Here we analysed both separately by looking at both proportion of habitat and spatial autocorrelation of the habitat. Spatial configuration and body size How species of different size and mobility find resources in their habitat affects mechanisms controlling biodiversity patterns across spatial scales and taxa (Ritchie & Olff 1999). Formerly, spatial heterogeneity was considered a main driver in understanding biodiversity dynamics across spatiotemporal scales, but recently individual movement is also regarded as one of the key mechanisms (Jeltsch et al. 2013; Liu et al. 2016; Maestre et al. 2005; Myers 1996). Mobility of organisms can connect resources, genes and processes between various locations and maintain coexistence in communities which alters food web interactions and biodiversity (Jeltsch et al. 2013). Because it is considered that the highest impact of fragmentation would occur at a small scale (Cattarino et al. 2016), this study is focused on foraging, the daily movement between patches. Habitat fragmentation and loss are driving changes in body size due to the availability of resources and the type of movement of species (Henle et al. 2004; Holling 1992). Body size is correlated to many functional traits and influences the physiology, ecology and functioning of an individual as described in the metabolic theory of ecology (Brown et al. 2004). For example body size is linked to behaviour (foraging, anti-predator behaviour, intra-interspecific interactions…) (Dial et al. 2008; Massol et al. 2017). As such, body size is the functional link between the individual processes (survival, reproductive rate, interactions with other species) and ecological processes of an ecosystem (Kalinkat et al. 2015; Petchey & Belgrano 2010; Brousseau et al. 2018). Different trade-offs are involved in the size determination of a species. Advantages of small individuals include a superior locomotion performance (e.g. manoeuvrability), (Dial et al. 2008), lower energy requirements and a shorter developmental time. Larger on the other hand, can cover larger distances, have greater fecundity and are more resistant to starvation (Chown & Gaston 2010; Peters 1986; Taylor et al. 1982). This study as part of a bigger framework This thesis study is part of the doctorate of Jasmijn Hillaert at TEREC UGent. One of the objectives of her research project to make a theoretical model of the impact of landscape fragmentation on body size distributions of a consumer species feeding on a resource species. This empirical study will validate the model with field data and focus on how the landscape configuration affects the size distribution in aboveground biodiversity. More research will be continued and extended in a future doctorate and in the Ensuring Dune Resilience against Climate Change (ENDURE) project. ENDURE is an interregional project (EU Interreg) with partners in England, France, Belgium and The Netherlands. It aims to improve adaptation capacity to climate change and puts the focus on two Seas coastal sand dunes (Anon 2017). The intercontinental collaboration is very important because climate change is a global issue and its impacts are not limited to national borders. All the information gained by project partners on different

8 small aspects of the dune ecosystem can be integrated into one big framework which is essential to understand evolutionary and ecological dynamics of dune functioning. Research questions This research addresses many questions.

• Is there a link between resilience of ecosystems and aboveground biodiversity? How are these factors related?

• Can plant spatial patterns be a driver of biodiversity? How does the spatial configuration of the vegetation shape the community structure?

• How do differences in spatial organization, and thus differences in resources, influence and . and communities, using body length as master trait? Can theoretical predictions be an accurate presentation of nature phenomena? Aim By investigating how the spatial pattern in Marram grass affects aboveground biodiversity, this research contributes to our understanding of dune ecosystem functioning where body size is used as functional link between individual processes and ecological processes of an ecosystem. Furthermore, we tackle the lack of experimental studies which evaluate and optimise the theoretical models by the validation of an individual, consumer based model of the relationship between spatial structure and size distribution. Altogether, this can improve coastal management and make it more sustainable, which directly enriches dune health and ecosystem services. As such, we aim to optimize ecosystem resilience and preserve the dune-specific biodiversity.

9 II. Materials and Methods

Collecting data Fieldwork The fieldwork was executed in July 2017. The study area concerned the foredunes of the Belgian coastline located between 51°05'-51°21'N, 2°32'-3°21'E. Within this area the biodiversity of invertebrates was sampled.

Figure 3: Overview of the fifteen sample locations along the Belgian coastline.

Selection of Sampling sites Sampling was done along the whole Belgian coastline (Figure 3). The locations were chosen based on Google Earth satellite images where the availability of foredunes could visually be detected. The available habitat was split up into fifteen locations (Figure 3). For more precise localization of the sample locations, GPS-coordinates (projection system WGS84) of the two most distant sites within a location are presented in Appendix 1. Some locations such as Oostende, Het Zwin 2 and to a lesser extent Oostduinkerke-bad were situated more inland but still belonged to the Ammophila arenaria vegetation we were looking for. The location Duinbergen is a small chunk of isolated dunes, therefore the sampling sites within this area lay closer to each other. Part of the sites in De Panne and Wenduine Konijnenpad

10 were situated behind a small walking dike. Therefore, fresh A. arenaria patches were scarcer. At each location, fifteen sites dominated by A. arenaria, were sampled for invertebrates. However, not in every location we succeeded in finding fifteen suitable sites, because the remaining area was in a later successional state. In Oostende we could only sample eleven sites and in Het Zwin 2 we sampled only eight sites. By selecting the sites per location, we deliberately covered a wide variation of A. arenaria proportion and connectiveness of A. arenaria within the site. Another criterion in selecting the sites was isolation of A. arenaria versus mosdune, other grasses or shrubs which may also provide resources. The distance between each sample site was approximately 25 meters. The Google Earth maps were not detailed enough at small scale thus we chose the specific sites in the field. However, this was not a fully random process because the observer is knowledgeable in their choosing.

Data collection Once the sample site was decided, a stick was placed to mark the center. A 5 meter long rope was attached to the stick to demarcate a 10 meter diameter site. The center of each site was marked and labelled more permanently by attaching duct tape to the central A. arenaria tussock. Furthermore, a GPS-coordinate was stored. We chose to mark the tussocks with duct tape to make relocating the site easier for further research. Next, invertebrates were collected with an net of 40 cm diameter by sweeping through the vegetation within the site (N). In addition, invertebrates were collected manually from the central A. arenaria tussock for 5 minutes (M). Both samples were preserved on 70% ethanol for further identification and measurements in the lab. Furthermore, a soil sample was taken near the central tussock. In further research, this soil sample will be used to get an indication of the productivity of the soil. Information about the sample site was noted in a logbook. This includes (1) the date, (2) the weather, (3) the estimation of the proportion and spatial autocorrelation of A. arenaria, (4) the number of , (5) the amount of litter, (6) the presence of Senecio inaequidens (Narrow-leaved Ragwort). Inflorescences, Litter and Narrow-leaved Ragwort were divided into four categories: Not present, Low presence, Average presence and Abundant. Finally, a picture of the sampling site and of the central A. arenaria tussock was taken.

Sampling method in bullet points (Figure 4): • Demarcate of a 10 meters diameter site • Take GPS-coordinate

• Mark the center of the site with duct tape • Collect arthropods by sweeping (N)

• Collect arthropods manually in the central tussock (M) • Collect a soil sample

• Labelling (net and hand caught, soil sample and the central tussock) • Take notes • Take a picture of the site and tussock

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Figure 4: Sampling method; Demarcation of a 10 meter diameter site; Taking a GPS-coördinate; Collecting samples.

12 Labelling of the samples The label starts with a unique number, followed by three letters of the location name of the site, the site number and the way the data was collected (net: N; manually: M). For the soil sample the letter S was added. All parameters are separated by an underscore. e.g. Sample 14 of invertebrates collected manually in site 13 in De Panne: 14_DEP1_13_M. Abbreviations of the localities can be found in Appendix 1. Identification of invertebrates in the collected samples Due to a lack of time we focused on a limited number of species groups. (Fulgoromorpha), (Cicadomorpha), (Coleoptera) and (Arachnida) were considered. Plant- and leafhoppers were analyzed together. The chosen groups of species were abundant in our samples, including some dune-specific species and were feasible to identify at family level and were ecologically diverse. Adult planthoppers, leafhoppers and beetles were identified at least to family level using the following identification keys: van Veen & Zeegers 1988; Muilwijk et al. 2015; Baugnée et al. 2011; Chinery 1986; Benisch 2018; Natuurpunt 2018; Biedermann & Niedringhaus 2009; Kunz et al. 2011. A reference collection has been created (Figure 5). For the weevils, Pol Limbourg, an expert in weevils, was consulted to identify to species level (Hassler & Reinheimer 2013). All planthopper, leafhopper and beetle species were noted down as morphospecies. Juvenile and adult spiders were identified almost all to species level by Dries Bonte. A list of all the species we found can be consulted in Appendix 2 Appendix 3. A stereomicroscope: Wild M3Z Heerbrugg, type-S, zoom: 10x40x was used to carry out the identifications. Within the beetle community further distinctions was made based on trophic level: herbivores or predators. All omnivores were categorized as predator.

Figure 5: reference collection of all the collected species.

Length measurements Body size was characterized by measuring length, which was measured to the nearest 0.5 mm using an ocular micrometer on the same stereomicroscope mentioned above. For each species the largest zoom possible was chosen to reduce the measurement-error. In advance, each zoom level was calibrated. Length was measured for all adult planthoppers, leafhoppers and beetles. The length includes the distance from the frons on the head of the to the end of the abdomen, including reproductive

13 organs. Antennae and wings were always excluded from the length measurement. The measurements of planthoppers, leafhoppers and some beetles were done dorsally, other beetles were measured laterally. Within each species, the same position was used. Length was the only proximate used for body size. The individuals all have a similar shape, wings excluded, therefore the body length will strongly correlate to body mass. Once the length of the individuals is known, biomass can be estimated through body-size regressions available in the literature, which are defined per insect group (Ganihar 1997; Brady & Noske 2006; Sample et al. 1993). Calculation of proportion and spatial autocorrelation of Ammophila arenaria. Landscape information is based on the Digikart (Provoost et al. 2008). The map dates from June 2007 and has a minimal resolution of one by one meter. Ammophila arenaria is a separate vegetation class within the Digikart. The A. arenaria vegetation is extracted from aerial photographs based on the color reflection in combination with height information from LiDAR. The statistics software R was used to calculate parameters that characterize the landscape. Packages used for general grid operations are: raster (Hijmans et al. 2017) and rgdal (Bivand et al. 2018). Furthermore, ClassStat from the SDMTools package was used to calculate the class statistics for some patch types in a matrix of data (VanDerWal et al. 2014). The degree of cover was calculated as the ratio of the number of cells containing A. arenaria to the total number of cells within a certain buffer. A second parameter extracted from Digikart is autocorrelation. This gives information about the spatial correlation of A. arenaria within the sites. To calculate the spatial autocorrelation, pairs of values separated by a certain distance are compared. This enables us to study patterns of dependency in space (de Smith 2015). The data is grid-based which make it suitable to use a join count function from the package spdep (Bivand et al. 2013). Join count is a collection of functions to create spatially weighted matrix objects. The function STD_DEVIATE is a landscape-scale measurement was used to estimate the spatial autocorrelation. This measure is a z- score of the expected joins subtracted from the observed joins deviated by the expected standard deviation. STD_DEVIATE can be positive or negative, where a negative number reflects an autocorrelation between 0-0.5. A number equal to zero reflects an autocorrelation of 0.5, where the distribution of the habitat type is random. In this case, the vegetation is regularly spread over the matrix. A positive number reflects an autocorrelation between 0.5-1, where 1 stands for a highly clustered vegetation. The spatial autocorrelation is thus used to describe the connectedness of the different clusters of grass. The landscape parameters were calculated for buffers of 5m, 10m, 20m and 50m. Data analysis Exploratory graphs, ordinations and PERMANOVA Data manipulation was done with the packages dplyr (Wickham et al. 2017) and tidyr (Wickham & Henry 2018). First explanatory graphs were made in R base graphics using the package ggplot. Those graphs gave an idea about which species appear in which sites and their abundances. Further visualization of the data was done with multivariate statistics of the packages vegan (Oksanen et al. 2014) and lattice (Sarkar 2008). Non-metric MDS was used, which is based on ranks and is the most robust unconstrained ordination technic in community ecology (Minchin 1987). We decided, based on Appendix 4, to use landscape information for a buffer of 20m. A scale of 20m covers more variation along the spatial autocorrelation axis and still covers a wide range of habitat proportions. Only 100% cover by A. arenaria

14 is not included. At this scale, parts from outside the foredunes, like bare sand from the beach, will also be included and thus the maximum coverage where data is available is a cover of 90%.

To test if there were any significant environmental factors which could explain part of the variation in the species community, a Permutational multivariate analysis of variance (PERMANOVA) was carried out. The PERMANOVA included the parameters prop.landscape, spatial.autocorrelation, and litter. The distance matrix is based on Bray-Curtis dissimilarity. This dissimilarity is based on counts at each site and reflects the dissimilarity in invertebrate species composition between two different sites (Bray & Curtis 1957). For each community, different landscape-scales (buffers of 5m, 10m, 20m and 50m) were considered. For each scale, a full and reduced model was performed.

Reduced model: dataset ~ proportion landscape + spatial autocorrelation

Full model: dataset ~ proportion landscape + spatial autocorrelation + inflorescence + litter

There was only a small difference between effects of the proportion landscape values and autocorrelation between the reduced and the full model. Finally, only the full model was considered because this includes information about the quality of Marram grass. The significant effects were spread all over the communities (plant- and leafhoppers, herbivorous beetles, predatory beetles and spiders) and over the landscape-scales. We decided on a landscape-scale with radius 20m, where proportion and spatial autocorrelation of Marram grass could explain most variation in the community structure except for the largest scale. We avoided the latter as there are high chances that vegetation other than Marram vegetation or bare sand were included. Even more, other sites would be included because the distances between the sample places was approximately 25 meters. The stronger effect of habitat configuration on larger scales, can maybe be partly explained by a smaller error in the detection of A. arenaria.

Multivariate analyses and PERMANOVA were conducted (i) at community level, for the plant- and leafhopper, herbivorous beetle, predatory beetle and communities, and (ii) for all the communities lumped together, and (iii) at species level where we only looked at the most abundant species (which occur in more than ten of our samples). A significance level of P<0.05 was used. Mixed linear model Because we were dealing with data that have a nested structure (sites within locations) and therefore have a complex error structure, mixed linear models (lmer) from the package lme4 (Bates et al. 2015) were used. This type of model can also handle a dependent variable which has a Gaussian distribution. Mixed linear models were performed for planthopper, leafhopper, herbivorous beetle and predatory beetle communities. At the species level, only the species of which more than 50 individuals were present in our samples, were selected. These species included Neophilaenus lineatus, Psammotettix maritimus, jocobaeae, sulphureus, two Chrysomelidae spec (kever 58 and 9), Demetrias monostigma and marginellus. Moreover, we checked if they had an occurrence, spread over the different sites and locations. We applied stronger criteria than for the PERMANOVA, because not enough samples were available for some sexes (Figure 9) or there was no spread over the different locations. As before, different landscape-scales (radius 5m, 10m, 20m and 50m) and a reduced and full model were considered.

15 Reduced model: body length ~ proportion Marram + spatial autocorrelation + proportion Marram*spatial autocorrelation + (1|location)

Full model: body length ~ proportion landscape + spatial autocorrelation + inflorescence + litter + proportion Marram*spatial autocorrelation + (1|location)

Prop.landscape and STD_deviate are continuous variables. Litter and inflorescence are discrete ones in which the four categories not present, low presence, average presence and abundant are represented respectively as 0, 0.25, 0.75 and 1. The change of characters to values is unimportant and was only implemented to bypass a statistic problem. It does not bias our data or results. Location is a random variable to correct for location effect. Model selection is based on the Akaike information criterion (AIC). AIC-values deal with the trade-off between the goodness of fit of the model and the simplicity of the model. Hereby, the lowest AIC represents, the ‘best’ model. Note that the ‘best’ model is based on all the models provided but the value tells nothing about the quality of the ‘best’ model. For each ‘best’ model an ANOVA is done using the package lmerTest (Kuznetsova et al. 2017). The option ddf=’Satterthwaite’ immediately corrects the degrees of freedom in an F-test. We need to correct for the effective sample size if we want to calculate the standard errors of the fixed variables. Because of dependency, the effective sample size is not the same as the total sample size. The type III test corrects for variation shared among predictors and only the unique effect of the separated parameters is considered. This can indicate something about the effect of size distribution of the sampled arthropods on landscape configuration. A summary of the model provided us with a significance test which compared all the different levels to the intercept. P<0.05 was used for significance level.

All scripts and data are stored on github: https://github.ugent.be/pmvhauwe/ThesisCodePaulienVH.

16 III. Results

Effect of Ammophila arenaria pattern on community structure Exploratory graphs: Species richness and abundances We started the analysis by creating some exploratory graphs to get a better view on species abundances and species richness within the sites and between locations. First, we looked at the difference in trapping method (Table 1). Table 1 shows that plant- and leafhopper species are particularly found by sweeping through the vegetation and Figure 6 illustrates that using a sweeping net leads to the highest abundances in plant- and leafhoppers. This contrasts with the spider data where most species and the highest abundances per species are found with hand catches. In beetles both trapping methods contribute more equally to the total number of species. The total number of species found for plant- and leafhoppers, beetles and spiders over all sites are respectively 20, 86 and 44 species.

Table 1: Number of species found per trapping method. M: manual; N: net; total: total number of species per group present in our dataset; shared: species which are trapped by both methods; M unique: species only found in hand catches; N unique: species only found in net catches.

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Figure 6: Abundances of species per trapping method. Different species are indicated in different gray colors and separated by a black line.

The highest number of species per site for plant- and leafhoppers, beetles and spiders is respectively 6, 11 and 7 species. The most species-rich locations for plant- and leafhoppers are Het Zwin, De Haan Vossenslag and Blankenberge Duinse polders. For beetles, Het Zwin, Wenduine Harendijke and Lombardsijde are found to be the most species-rich and for spiders with a head start Wenduine Harendijke, then De Haan Zwarte Kiezel and Lombardsijde are following. If we only consider dune- specific species (indicated with an asterix in Appendix 2 and Appendix 3) the highest number of species for plant- and leafhoppers, beetles and spiders was found in respectively Het Zwin, Lombardsijde/Oostduinkerke_bad and Wenduine Harendijke. Including the abundances of the dune- specific species the highest species abundance for plant-and leafhoppers was found in De Haan Zwarte Kiezel, for beetles and spiders this was in Bredene. Complete graphs as well as the spread of the different species over the different sites are added in Appendix 7. For this analysis, no distinction between ecological groups (herbivorous species and predatory species) is made. Community structure: NMDS-ordination and PERMANOVA Ordinations give a graphical representation of the variation that can be explained by the abundance of the different species. On top of the ordinations environmental parameters were fitted (Figure 7, Figure 8, Appendix 6). These ordinations can be interpreted as follow: the closer two sites to each other, the more similar their community structure and the lower their beta-diversity. If a species and site are next

18 to each other, the species will be abundant in that site. When two species are close to each other, they will often occur together in a site. The position of a site or species in relation to the arrow gives information about the importance of that arrow for the site or species but the position of the species in the ordination is dependent on the species in other samples and independent on the information of the environmental parameters. For example, beetle 15 (k15) is mostly found in places with a high amount of litter (Figure 8). The position of the arrows is an indication of the correlation between an environmental variable and the variation in species community. If two arrows point in the same direction, considered parameters are higher correlated with each other. For example, for the ordination of predatory beetles (Figure 7) spatial autocorrelation and proportion are correlated thus sites with a higher proportion landscape will also be higher in spatial autocorrelation. Litter and inflorescent often point in the opposite way and seems to be independent from each other. Trophic levels, herbivorous species and predatory species, are separated in the data.

The PERMANOVA output is presented in Table 2.

Figure 7: NMDS-ordination of the full model on scale 20 (buffer 20 meter) for the predatory beetle community (ordinations for plant- and leafhoppers, herbivorous beetles and spiders can be consulted in Appendix 6). Species are indicated in red and the different sites in black.

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Figure 8: NMDS-ordination of the full model on scale 20 (radius 20 meter), communitywide. Species are indicated in red and the different sites in black.

Table 2: PERMANOVA output, the considered models are the full models (included: proportion, spatial autocorrelation, inflorescence and litter) in which vegetation structure parameters are based on a buffer of 20m. Only significant parameters were included. DF: degrees of freedom. For the full output, please consider Appendix 7. Effect of Ammophila arenaria pattern on size distribution of arthropods. Exploratory graphs: length distribution The distributions of the measurements of the head-abdomen length of each invertebrate species, hereafter called length distribution, are studied. The length distributions considering the most abundant plant- and leafhoppers revealed in some species a difference in length depending on the sex (Figure 9). Further analysis is done separately for each sex. For beetles we did not separate sexes. The range of lengths found for plant- and leafhopper species is 1-8 mm with outliers of almost 9 mm. Length

20 distribution of the most abundant beetles can be found in Appendix 7. The length distribution of beetles covered a range of 1-9 mm with outliers up to almost 12mm. Length for both predatory and herbivorous beetles included small and big beetles. Quite a lot of outliers are present.

Figure 9: Differences in length distribution between female and male plant- and leafhoppers. This is only checked for species which occur at least ten times in our samples. cicade 1 = Neophilaenus lineatus; cicade 2 = Doratura spec; cicade 3 = Philaenus spumarius; cicade 4 = Conosanus obsoletus; cicade 8 = Fam. Cicadellidae; cicade 12 = Psammotettix maritimus; cicade 13 = Javesella pellucida; cicade 22 = Muirodelphax aubei.

The graphs where length was plotted against the proportion and spatial autocorrelation of Ammophila arenaria were done at the community level and for the most frequently encountered species. A possible negative relationship between proportion A. arenaria and the length distribution can visually be detected for the female morphotypes ‘cicade 12’ and ‘cicade 8’ and for the male morphotype ‘cicade 12’ (Figure 10). Similar results were found for the relationship of spatial autocorrelation to body length (Figure 10). A slightly positive trend could be detected for the male morphotype ‘cicade 4’ (Figure 10), when you look at the proportion A. arenaria and for the male ‘cicade 13’ (Figure 11) when you consider the spatial autocorrelation. For all the other species and at community level no clear relationships could be detected. More graphs can be found in Appendix 7.

Only the species with an abundance higher than fifty individuals spread over different sites and locations were considered for further analysis. This hold for ‘cicade 1’ and ‘cicade 12’. For the latter we do get significant relationship with proportion and spatial autocorrelation of A. arenaria, as was predicted from Figure 10 and Figure 11.

21

Figure 10: Length distribution of male and female plant- and leafhoppers, which occur at least ten times in our samples, plotted on the proportion of Ammophila arenaria. Only graphs were included where there might be a relationship. cicade 4 = Conosanus obsoletus; cicade 8 = Fam. Cicadellidae; cicade 12 = Psammotettix maritimus.

Figure 11: Length distribution of male and female plant- and leafhoppers, which occur at least ten times in our samples, plotted on the spatial autocorrelation of Ammophila arenaria. Only graphs were included where there might be a relationship. cicade 8 = Fam. Cicadellidae; cicade 12 = Psammotettix maritimus; cicade 13 = Javesella pellucida.

22 Mixed linear models The reduced model, on the smallest scale (buffer 5m) turned out to be best model, based on the AIC- value (Table 3). Exceptions included the herbivorous beetles morphotypes ‘kever 58’ and ‘kever 9’ (Chrysomelidae spec), where a buffer of 20m give the best model. The reduced model includes the proportion and spatial autocorrelation of Ammophila arenaria and the interaction between both. For the full community of plant- and leafhoppers, herbivorous beetles and the female species Neophilaenus lineatus (Figure 12) the full model was preferred, which additionally contained inflorescences and litter. The Anova analysis revealed significant effects for the plant- and leafhopper community, the females of N. lineatus and for male and female of Psammotettix maritimus (Figure 12, Table 3). Body length of plant- and leafhoppers increased significantly with the amount of litter and plant- and leafhoppers were larger (but not significantly compared to the intercept, which is no litter) when litter cover increased. In female N. lineatus species body length increases significantly with the number of inflorescence and decreases with increasing litter cover. Body length of male P. maritimus species increases significantly with spatial autocorrelation. Body length of P. maritimus females additionally increased significantly with the proportion of A. arenaria and there was a negative interaction between the effects of spatial autocorrelation and proportion of A. arenaria. There is a clear difference in response of length depending on the sex. Male species had less or no environmental parameters which could explain variation in length. lmer tests can be found in Appendix 7.

Table 3: Mixed linear model summary of the significant output. F: female, M: male, model: best model based on AIC values, z: reduced model with proportion, spatial autocorrelation of Ammophila arenaria and the interaction between both included, NumDF: numerator degrees of freedom, DenDF: denominator degrees of freedom. For the full output, please consider Appendix 7.

23

Figure 12: Left: Adult, Neophilaenus lineatus ©Walwyn; Right: Adult, Psammotettix maritimus © Kunz

24 IV. Discussion

Effect of Ammophila arenaria pattern on community structure Species richness and Abundances Our results demonstrate that both net and hand catches contribute to the species richness (Table 1, Figure 6). It is further clear that both sampling methods are useful. For plant- and leafhopper one can decide on doing only net captures and for spiders only hand catches but it is clear for beetles, both trapping methods are needed, as they complement to each other. Which species will be caught with which method is most likely linked with their ecology. For example, Tetragnatha extensa and Neoscona adianta are both spiders that make a wheel-shaped web and could mostly be found by sweeping through the vegetation.

Places with high species richness were Het Zwin, Wenduine Harendijke and Lombardsijde. The first two are fixed dunes and Lombardsijde is intermediate (Figure 13). This looks to confirm the biodiversity- stability theory although it consider species diversity (Loreau & de Mazancourt 2013). Higher biodiversity is found in a more stable ecosystem, in dune landscapes this are the fixed dunes. Stable dunes has a low succession rate and are less resilient to disturbances (Isermann 2011). This kind of dunes we do not want to achieve in a resilient foredune ecosystem. If only dune-specific species were considered, the highest number of species for plant-and leafhopper, beetles and spiders was found in respectively Het Zwin, Lombardsijde/Oostduinkerke_bad and Wenduine Harendijke. Still more species seem to be found in fixed dunes which is in contrast with our hypothesis that more dynamic dunes would harbor more dune- specific species. It seems that the preference for fixed habitat is higher but the most species-rich place is community-dependent. It is not unlikely that arthropods find more resources linked to a higher plant diversity. This would open habitat for specialist species linked to other plants than A. arenaria. Or it might be that they enjoy more shelters because of the higher amount of litter. A preference for a less disturbed habitat by climatological conditions might be also an explanation. The effect of disturbance on the species richness depends on the productivity of the system (Kondoh 2001) and is thus more complex than the intermediate disturbance hypothesis (Connell 1978). However, including the abundances of the dune-specific species, the highest species abundance for plant-and leafhopper was found in De Haan Zwarte Kiezel, for beetles and spiders this was in Bredene. These are intermediate dunes and especially for beetles all the places with static dunes had low species abundances. From our result it seems that species abundance is a better indicator for vital dune habitat than species richness. The different stadia of the dunes (dynamic, intermediate, stable) (Figure 13) still seem to reflect what we encountered in the field. According to Provoost et al. (2014), the most vulnerable dunes were Oostende-Raversijde and Wenduine. Looking at our data, those two locations were low to intermediate in species richness depending on the community considered. The high litter cover locally present, which is used as an indication for non-vital A. arenaria vegetation, confirms the fixed state of those dunes. Furthermore, a low number of inflorescence is observed, which can be an indicator of A. arenaria that is dying off. The newly emerged A. arenaria tussocks do not have any inflorescences yet and non-vital A. arenaria stop flowering (Weeda et al. 1994). Vital tussocks have many inflorescences. On the other side in De Haan Zwarte Kiezel, a dynamic place, low amount of litter and a variable number of inflorescences was found.

25

Figure 13: Different fixation types of Marram dunes along the Belgian coast (Provoost et al. 2014). The classification is based on the presence of bushes, mosses, Ammophila arenaria, pioneer vegetation and mobile sand. The combination of more mosses and lower amount of mobile sand are an indicator of fixed dunes (brown). Red are dynamic dunes with a vital A. arenaria population and green are semi-dynamic dunes. Purple shows dunes which are very small (<100m width). Plant spatial pattern and plant vitality in relation to species composition Top-down as well as bottom-up forces shape the herbivore community (Gripenberg & Roslin 2007). Many studies focus on top-down effects, how herbivores shape the plant community diversity and species richness (e.g. Augustine & McNaughton 1998). Research on bottom-up effects mostly cover the effect of plant diversity on the herbivore community (Scherber et al. 2010). However, plant taxonomic diversity would not be the most important in explaining species diversity as the vegetation heterogeneity might be more important than previously thought (Brose 2003). To a lesser extinct, research is performed which studies how the spatial pattern of plants effect species composition in aboveground biodiversity. The output of the PERMANOVA (Table 2) over all communities shows that plants with a high number of inflorescences have a significantly distinct species composition. These are the species that chose vital A. arenaria patches. Further research can maybe reveal some indicator species for vital A. arenaria by looking into those species´ composition in more detail. The distinct species composition might be caused by a specific species or cluster of species. This might be linked to their ecology. Indicator species can be useful to improve management (Maes & Bonte 2006), ecosystem resilience and to be ahead of the consequences of Climate Change. (Bonte et al. 2004) shows that the interaction of patch connectivity

26 and area has an important effect on the species distribution but also when patch area is not variable, our findings suggest that connectivity is important as spider communities in better connected patches, have a significantly different species composition. A decrease in community similarity by habitat fragmentation has been detected before in Dormann et al. (2007). The effects of connectivity seems to be greater for spiders than in beetles which agrees with Bailey et al. (2010). Predatory beetle communities have a significant distinct species composition when the number of inflorescences is high. A. arenaria tussocks with high inflorescence were usually dense, vital tussocks. Because of the high structure, it is not unlikely that more niches are available and thus a higher species richness is present. It might be that there are also more prey species which enhance the species richness in the predator community. In the ordinations the arrows of litter and inflorescence are often directed in the opposite direction, which is understandable. The arrow of litter point towards a high amount of litter which can be found in fixed, unhealthy foredunes and the arrow of inflorescence points towards a high number of inflorescences which indicates healthy A. arenaria. Effect of Ammophila arenaria pattern on invertebrate size distribution Length distribution graphs and Plant spatial patterns related to invertebrate body length Plant spatial patterns affect consumers via resource availability and the foraging behavior of animals (Tilman 1988). Size distribution is used as index, as it is linked to a diverse number of functional traits (Peters 1986), to consider the impact of habitat fragmentation on arthropod communities. We hypothesize a different species composition in fragmented areas (low plant cover and low plant connectivity) where we expect larger species because of a bigger movement effort. The difference in length between male and female plant- and leafhoppers was most clear for Neophilaenus lineatus and the Doratura spec. (Figure 9), where the females are consistently bigger than the males. To a smaller extent this was also observed for Psammotettix maritimus and Javesella pellucida. These observations are in line with (Biedermann & Niedringhaus 2009), if there is a sex dimorphisme in body size, females are bigger than males. Only for the family (e.g. Javesella pellucida) there is no sex differences mentioned. All our measurements look a bit larger than the size range mentioned in Biedermann & Niedringhaus (2009) but the same proportions in size range or differences between males and females are observed. It might be that they used a slightly different measuring method. For the other morphotypes, there was no clear difference between sexes and they had no or a low sample size for one or both sexes.

Both a possible positive and negative relationship between A. arenaria cover and the body length of plant- and leafhoppers could be detected (Figure 10). This also held for the relationship between spatial autocorrelation and body length (Figure 11). However, only the morphotype ‘cicade 12’ was quite abundant in our samples and delivers the highest reliability. Cicade 12 (Psammotettix maritimus) shows a slightly negative trend which means that when the cover of A. arenaria is higher and the connectivity between A. arenaria entities is higher, the plant- and leafhoppers are expected to be smaller. This is in

27 line with Taylor et al. (1982), which states that smaller individuals cross large distances at a higher energetic cost compared to bigger individuals. For beetle species there is no clear trend (Appendix 7). The output of the mixed linear models on community level (Table 3) shows only a strong significant signal for litter in plant- and leafhoppers. Results indicate that larger plant- and leafhoppers are found within a habitat with a high litter cover but the differences between other litter covers was not significant. This might be driven by some generalist species which can find a higher plant diversity and thus more food in fixed dunes. At species level bigger females of N. lineatus species are found in places with a low amount of litter and a high number of inflorescences. These conditions indicate a vital A. arenaria population. Within the four categories of litter, the largest N. lineatus females can be found when there is no litter observed. Often the A. arenaria tussocks without litter are not dense, and have just emerged after been buried by sand. From field observations we expected those tussocks to be more isolated but this was not confirmed by our results, as there is no effect of spatial autocorrelation on body length. This spatial configuration can be more advantageous for mobile individuals. As mobility increases with body size (Taylor et al. 1982), bigger individuals can be expected. Furthermore, the A. arenaria is high in quality and is a good food resource. Within the four categories of inflorescence, the smallest N. lineatus females can be found when there is no inflorescence present. No inflorescence can be observed, as mentioned above, in newly regrown healthy patches but also in stabile dune with non-vital A. arenaria which can explain the small size. It looks like the highest priority for these species is the quality of the food and to a lower extenct the quality of the habitat. In our results the proportion of A. arenaria and amount of litter are not correlated. For the female P. maritimus species the spatial autocorrelation, proportion of A. arenaria and the interaction between proportion and autocorrelation are strongly significant. Thus, with a high cover and high connectivity of A. arenaria, which means a low amount of habitat fragmentation and loss on a small scale, P. maritimus females turned out to be bigger. A high spatial autocorrelation is naturally when the cover is high. The interaction of cover and connectivity of A. arenaria on body length is slightly negative, the effect of the amount of cover becomes less strong if connectivity increase and vice versa. For the male P. maritimus species, only the spatial autocorrelation was significant and had a slightly positive relationship. Thus, more connected grass patches harbors larger individuals which is in contrast to the trade-off between size and mobility (Taylor et al. 1982). However, this agrees with the findings of the theoretical model when movement is uninformed (Hillaert 2018), see below. Male species seems to react less or not to the tested environmental parameters compared to females. For females it is important to find good vital A. arenaria to rear their offspring. For males it can be expected that finding a good healthy female to copulate is the most important and males thus seems less directly linked to habitat configuration.

It seems like species closely linked to the A. arenaria vegetation react strongly to habitat quality parameters like proportion and spatial autocorrelation of A. arenaria, which is in line with our expectations. Psammotettix maritimus is an example of such a monophagous species. On the other hand, the generalist Neophilaenus lineatus, seems to be limited by resource quality. Large individuals can only develop if there are enough resources available. The results suggest that food quality is not correlated to the spatial autocorrelation or percentage habitat. Generalists use a broad range of resources whereby they can experience the landscape as continuous (Van Nouhuys 2005). However, in this study we strive to include only sites with a homogenous vegetation of A. arenaria. Another

28 explanation might be found in wing dimorphism as, P. maritimus is a brachypterous (short-winged) specialist and N. lineatus is a macropterous (long-winged) generalist. Having short wings, which is energetically less cost-efficient, results in a lower flight capacity and thus in a high cost to travel distances (Roff 1994). This can result in a higher dependence on the connectivity and available quantity of their habitat. Wing dimorphism in insects is maintained by the trade-off between mobility and reproductive success (Crnokrak & Roff 2000; Guerra 2011; Steenman et al. 2015) and is known within species and even within one population. We only encountered wing dimorphism in the family Delphacidae. Travelling short distances, plant- and leafhoppers are good jumpers, for long distance most species are capable of actively flying. However, to cover very large distances they use wind dispersal and as this is passive there is no directed dispersal (Biedermann and Niedringhaus 2009). These two species are caught in relative high quantities which make them good species to focus further research on.

The availability and the spatial configuration of resources and the mobility of species to travel between resources are suggested to drive selection on body size (Holling 1992). According to the outcome of the model of (Hillaert 2018), which looks at the effect of landscape-scale on the optimal body size for consumer species, female species of Neophilaenus lineatus are partially informed by their environment as the proportion and autocorrelation of A. arenaria were not significant in explaining body size variation. Size variation that can be explained through a higher proportion A. arenaria would reflect species which are uninformed about their environment and have a random walk. Our results suggest that this is the case for Psammotettix maritimus. This is in contrast with the expectances in (Hillaert 2018; Gray et al. 2015) that informed movement is found for specialist species. The habitat considered in this research consists of only A. arenaria which might decrease the advantage of being well informed and be able to detect the host species. In P. maritimus females the effect of landscape configuration is stronger than in males. Thus, the selection of landscape configuration seems to be larger in females. In this case we would hypothesize that females move more informed through the landscape than males.

Beetle species did not show any preferences for food or habitat quality which could be detected through body size. Those beetle species included Demetrias monostigma, a predatory beetle, associated with dune landscape (Weeda et al. 1994) and abundant in many samples and Chrysomelidae species. The latter are monophagous or oligophagous herbivore species and use as adult as well as larvae often the same host resources (Strauss 1988). The examined beetles seem to include appropriate species for our research: they include monophagous species and dune-specific species. However, there seems to be a difference in importance of landscape configuration for beetles and plant- and leafhoppers according to our results. Also within plant- and leafhoppers, the reaction to landscape parameters is different. For monophagous plant- and leafhoppers it seems that spatial processes are more important than for generalists. According to Pandit et al. (2009) the importance of environmental and spatial processes in structuring the species community depends on the degree of habitat specialization and the scale at which the processes act. Plant- and leafhoppers, which are vascular feeders (Biedermann & Niedringhaus 2009), can be more specialized herbivores than many coleopteran species. This would mean that also between plant- and leafhoppers and herbivorous beetles a difference can be found in habitat specialization. No differences are detected between herbivorous and carnivorous beetles. However, there is a lot of evidence that species at high trophic levels are more sensitive to habitat fragmentation

29 than lower trophic levels (Van Nouhuys 2005), but the effect of habitat fragmentation can strongly depend between species. More species should be included in our analysis. Importance to conservation The distribution of habitat can affect species (mostly specialists) and thus species composition at small spatial scales. As habitat fragmentation increases and thus connectivity decreases specialist species (mostly rare species) can become rarer (Bonte et al. 2004). Every species has its own function in the ecosystem and a certain species richness is required to accomplish ecosystem services. Furthermore, information on litter cover can be used as a fast and easy tool to get an indication of the vitality of A. arenaria and as such the dune ecosystem health. Remark All analyses were conducted by using landscape information from old maps. Eleven years can change local presence of A. arenaria severely but the landscape context will be the same. Once the new maps are available, the analysis should be done again. The new analysis will contain more data, because certain data was omitted thanks to a lack of A. arenaria at that specific place on the map of 2007. In this study, the site selection was not conducted in a fully random way, we could have tried to decide on the sample sites based on the Digikart, this could provide a better spread of the landscape grid. All possible sites could be selected considering the restriction to include a wide range of proportion and connectivity possibilities. Fifteen sites per locations could then be generated using an algorithm. One important condition is the availability of recent landscape maps.

Furthermore, a small error is found in how the best model was selected. The datasets on which the mixed linear model is based is not identical between the different models, which is a requirement for AIC selection. We started from one big dataset for plant- and leafhoppers and beetles and one big dataset for spiders. Then different subsets were made depending on the scale and the community. This resulted in all slightly different datasets, because at small scale some sites did not contain any A. arenaria or for each community not every site was represented by a species of that specific community. This may have had an impact on our output. Awareness of this mistake is needed.

Improvements can be made but our results should be quite robust to any noise within the data thanks to a good sample size, 214 places with a net- and hand- caught sample, spread along the entire Belgian coast. Importance of Ammophila arenaria vegetation and arthropod communities in dune formation. This research focused on the link between aboveground community structure and the spatial configuration of Ammophila arenaria. Many other interactions with the spatial structure of A. arenaria can be considered (Appendix 5). Sand fluxes and soil properties are abiotic factors that influence the spatial structure of A. arenaria. These can impact biodiversity, links between above- and belowground interactions, the quality of A. arenaria and ultimately the ability of A. arenaria to fixate sand and increase dune resilience. By collecting information for all these links, feedback reactions can be studied and knowledge about ecosystem functioning can be improved.

30 The sampling of the sites goes on. Root samples were additionally collected in spring 2018 and will be analyzed to gain information about the level of root infection by pathogens such as root-feeding nematodes. Also, the collected soil samples will be analyzed to provide more information on the productivity. This extra information will contribute to a better understanding of all the interactions contributing to the spatial structure of A. arenaria (Appendix 5), in dune ecosystem functioning.

Furthermore, to get more insight into sand dynamics in function of A. arenaria configuration, an additional direct measurement of sand dynamics can be conducted by placing sand cups into the sample sites and collecting them after a fixed period. Ideally all these data should be collected at the same period. In that way the climatological circumstances are the same.

Also, the effect of the exotic species Senecio inaequidens (Narrow-leaved ragwort) can be considered. However, the Belgian biodiversity platform stated that, at that moment (last update was in 2010) S. inaequidens does not pose a threat to indigenous species and plant communities. Senecio inaequidens, is been labelled as medium risk and the Belgian coastline was indicated as one of the habitats with a higher vulnerability (Branquart et al. 2010). Furthermore, the species has a high dispersal potential and seems to have become more present in the foredunes in the last years. Thus, it can be useful to investigate how S. inaesuidens affects the biodiversity and plant spatial pattern in dune ecosystems. Also, the role of Longitarsus jacobaeae, a Chrysomelidae beetle which was quite often present in our samples, as possible biological control for ragwort can be investigated (Windig 1993).

Expanding the existing model to a multitrophic model which includes above- and belowground herbivores, plant pathogens and their antagonists as they will all affect the interaction with the vegetation (Van der Putten et al. 2001). Also, predators should be included.

31 V. Conclusion

How species experience habitat fragmentation at small foraging scales and thus the distribution in resources, depends on how mobile they are. The movement of species is affected by their body size (Taylor et al. 1982). The effect of habitat fragmentation (reflected in the spatial autocorrelation of A. arenaria) and habitat loss (reflected in the proportion of available A. arenaria) are distinguished. Next to proportion and connectivity of A. arenaria also litter and inflorescences of A. arenaria were included. Especially no or a low amount of litter, often in combination with high abundance of inflorescences, can be a fast and easy tool to detect vital A. arenaria patches. Our results imply the existence of patterns in vertebrate species communities related to spatial configuration and vitality of the plants. These patterns differ among different groups of arthropods and are species- and sex- dependent. The latter emphasizes the importance of using a wide range of animals to adjust management. Furthermore, there seems to be a difference in effect on specialists and generalists. As the distribution of habitat (connectivity) can affect species (mostly specialists, which are often rare species) and thus species composition at small spatial scales, conservation should prevent further habitat fragmentation and so possible species extinction. Every species has its own function in the ecosystem and a certain species richness is required to accomplish ecosystem services.

32 VI. Summary

English summary Nowadays, habitat fragmentation and climate change are hot topics. Fragmentation adjusts plant spatial patterns and changes the movement of individual organisms. Because body size and movement are correlated, a shift in body size can be expected as response to fragmentation. Body size can be seen as a universal master trait as metabolic theory of ecology shows the relationship of body size to many functional traits and thus provides a functional link between individual processes and ecosystem processes. In this study, we focus on the impact of fragmentation (defined as plant cover and plant connectivity) at the foraging scale. We use Ammophila arenaria (Marram Grass) as key species and hypothesize that the spatial configuration of A. arenaria plays an important role in dune resilience (and thus ecosystem services as coastal defense) and structuring invertebrate communities. The relationship between hypothetical resilience and biodiversity is lacking, by our knowledge, in the literature. Field data were recorded in July 2017, in fragmented dunes along the Belgian coastline. Considered invertebrate groups are plant- and leafhoppers, beetles and spiders. Results from this study suggest the importance of connectivity for spider communities and the Importance of vital dunes (high inflorescence number) for predatory beetles and for all the invertebrate groups lumped together. Variation in body size could only be explained for some leafhopper species. Our results suggest a different effect between specialists and generalists. Specialists were more susceptible to spatial patterns of the vegetation and generalists to habitat quality. In both cases, effect on females is stronger than that of males. Results are also linked to how organisms are informed about their environment, according to a theoretical model. With this study we provide an empirical link between plant spatial pattern and aboveground biodiversity in foredune ecosystems. This can result in a better management of coastal dunes and thus ecosystem resilience, which enhances its crucial function as protection of our coastline. Nederlandse samenvatting De impact van de mens op de natuur resulteert vandaag de dag veelal in een versnippering van habitat, habitatdestructie en in klimaatsveranderingen. Versnippering verandert het ruimtelijk patroon van onder andere planten en hierdoor ook de manier waarop herbivoren zich bewegen doorheen het landschap. Door de connectie van ruimtelijk gebruik van individuen en de grootte van die individuen, kan er verwacht worden dat de wijziging van habitat ook leidt tot een verandering in lichaamsgrootte. Lichaamsgrootte is een gemakkelijk meetbare indicator. Daarbij toont de metabolische theorie in de ecologie aan dat lichaamsgrootte gekoppeld is met vele karakteristieken van het individu en is daardoor een interessant hulpmiddel ter illustratie van een mogelijks verband tussen veerkrachtige ecosystemen en biodiversiteit.

In deze studie bekijken we de bedekkingsgraad en de ruimtelijke autocorrelatie van de vegetatie als twee verschillende aspecten van versnippering. Onze veldstudie vindt plaats langsheen de volledige Belgische kustlijn in de voorduinen waar Ammophila arenaria (Helmgras) een dominante rol heeft. We testen of ruimtelijke patronen in A. arenaria een belangrijke structurerende rol hebben in het definiëren van een veerkrachtig ecosysteem en gemeenschappen van ongewervelden. Een mogelijks verband tussen deze

33 laatste twee is bij ons weten nog niet onderzocht. In de zomer van 2017 werden invertebraten ingezameld. De onderzochte soortengroepen omvatten cicaden, kevers en spinnen. Bevindingen bij ons onderzoek suggereren het belang van een samenhangend habitat voor spinnengemeenschappen, het belang van gezonde en vitale duinen voor predatore kevers en ook voor alle soortengemeenschappen samen. Het belang van ruimtelijke patronen of van de gezondheidstoestand van het helmgras kon slechts voor enkele soorten een verandering in lichaamsgrootte verklaren. De resultaten lijken afhankelijk te zijn van de soort, het geslacht en of soorten al dan niet specialist of generalist zijn. Bij enkele cicaden konden we lichaamsgrootte verklaren met onze geteste parameters. Specialisten toonden ons een sterkere correlatie met de vegetatiestructuur. Voor generalisten leek dan de habitatkwaliteit en dus de voedselkwaliteit van groot belang. Het verband met vrouwelijke individuen was sterker. Zij moeten immers zorgen dat de nakomelingen op een geschikte plek kunnen opgroeien. Deze resultaten zijn ook bekeken op het verband tussen de individuen en de mate waarin ze informatie uit het landschap gebruiken om zich te oriënteren.

Deze studie kan bijdragen tot een beter kustbeheer. Dit kan leiden tot een veerkrachtiger duinecosysteem en dus een betere zee-werende functie. Samenvatting voor leken De mens heeft een grote invloed op zijn omgeving. We zetten het landschap veelal naar onze hand met versnippering als gevolg. Bijvoorbeeld de aanleg van een weg doorheen een bos, die het bos opsplitst in twee delen. Dit kan vergeleken worden met een aangelegd pad als doorsteek naar zee, welke de duinen opsplitst. De structuur van het landschap verandert en de inspanning die dieren moeten leveren om zich door het landschap te verplaatsen wordt daardoor groter. Deze inspanning is afhankelijk van de grootte van de soort en van het individu. Doordat lichaamsgrootte gemakkelijk meetbaar is en het ons veel weet te zeggen over het individuele dier gebruiken we dit als een graadmeter om het effect van de ruimtelijke structuur van planten nader te bekijken. Deze studie is gedaan in de versnipperde duinen langsheen de volledige Belgische kustlijn waar cicaden, kevers en spinnen werden verzameld. Soort, geslacht en afhankelijkheid van het duinlandschap lijken invloed te hebben op de onderzoeksresultaten. De soorten die sterk afhankelijk zijn van dit type van vegetatiestructuur zijn gevoeliger voor de wijzigingen in die vegetatie. Voor de soorten die niet enkel alleen in dit duinentype voorkomen leek dan weer de voedselkwaliteit van groot belang te zijn. Een andere conclusie is de vaststelling dat vrouwtjes sterker reageren op veranderde omgevingsfactoren. Zij moeten immers een goede plek vinden om hun kroost groot te brengen. Deze resultaten zijn ook bekeken op het verband tussen de individuen en de mate waarin ze informatie uit het landschap gebruiken om zich te oriënteren.

Deze studie kan bijdragen tot het beter beheren van de duinen om zo bijvoorbeeld een betere bescherming te vormen tegen hevige stormen.

34 VII. Acknowledgments

I would like to thank Dries Bonte, my promotor for guiding me in my thesis work, for always being available for questions and for indentifying all spiders. Also, Jasmijn Hillaert, my mentor, to answer all my questions and support my work. I thank my co-promotor Martijn L. Vandegehuchte for helping me interpreting the results and getting me started in the field. Furthermore, I am grateful for all the help I got from externals, friends and family during this project. In particular, I thank Hans Matheve for analyzing the aerial pictures, Pol Limbourg, who did the identifications of the weevils, Pieter Vantiegem helping with the identifications of arthopods in my samples, Geert De Knijf for giving useful comments on a previous version, and Femke Batsleer for supporting me with the data analysis and encouraging me during the thesis project. Finally, I thank my parents for being a big support. VIII. References

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39 IX. Appendix

Appendix 1: Location, Abbreviation of the location name, GPS-coordinates of the two most distinct sites within a location, Number of sample sites within a location, Number of sample sites used in analyses for abundances and in analyses for ordinations and linear models. *Because of a problem with the GPS in the field only from 7 locations GPS-coordinates were saved. Later, based on the pictures taken, the missing GPS-coordinates were collected during another field day in the of Spring 2018. ** The number of sample sites is lower than the actual number of sampled places. The reason for this is that some sites did not contain any planthopper, leafhopper, beetle or spider.

Location Abbrevia- GPS- GPS- Number of Number of tion coordinate of coordinate of sample sample sites the first site the last site sites used in the analyses **

De Panne DEP1 N51° 05.410' N51° 05.935' 15 15 E2° 32.968' E2° 34.504'

Oostduinkerke-bad ODK_BAD N51° 07.737' N51° 07.958' 15 15 E2° 39.279' E2° 39.955'

Oostduinkerke ODK N51° 08.116' N51° 08.367' 15 15 E2° 40.489' E2° 41.332'

Lombardsijde LOM_BAD N51° 09.454' N51° 09.670' 15 15 E2° 44.251' E2° 44.966'

Westende WTN N51° 09.757' N51° 09.966' 15 13 E2° 45.176' E2° 45.765'

Oostende OST N51° 14.246' N51° 14.428' 11 10 E2° 55.729' E2° 56.245'

Bredene BRE N51° 15.190' N51° 15.399' 15 15 E2° 58.068' E2° 58.666'

De Haan Vossenslag DHN1 N51° 15.970' N51° 16.083' 15 14 E3° 00.079 E3° 00.305' *

De Haan Zwarte DHN_K N51° 16.928' N51° 17.231' 15 14 Kiezel E3° 02.351' E3° 03.046'

Wenduine WDN N51° 17.555' N51° 17.954' 15 15 Konijnenpad E3° 03.760' E3° 04.456'

Wenduine BKN_W N51° 18.530' N51° 18.726' 15 15 Harendijke E3° 05.991' E3° 06.571'

40 Blankenberge NPT N51° 19.253' N51° 19.434' 15 15 Duinse Polders E3° 08.693' E3° 09.456'

Duinbergen DUI N51° 20.582' N51° 20.656' 15 14 E3° 14.837' E3° 15.218'

Het Zwin 2 ZWN2 N51° 21.785' N51° 21.818' 8 8 E3° 20.288' E3° 20.492'

Het Zwin ZWN N51° 21.915' N51° 21.968' 15 15 E3° 20.694' E3° 21.293'

Appendix 2: Spider species; used abbreviations and full scientific names. *Dune specific species.

Abbreviation Family Species name Abundance agrocupr Liocranidae Agroeca cuprea (Menge, 1873) 1 aranspec Araneidae Araneus spec. (Clerck, 1757) 27 arctperi Lycosidae Arctosa perita (Latreille, 1799)* 4 barymari Baryphyma maritima (Crocker & Parker, 1970)* 61 bathgrac Linyphiidae Bathyphantes gracilis (John Blackwall, 1841) 3 bolyalti Linyphiidae Bolyphantes alticeps (Sundevall, 1833)* 1 ceraroma Linyphiidae Ceratinopsis romana (O. P.-Cambridge, 1872)* 1 cercprom Araneidae Westring, 1851) 3 clubcomt Clubionidae Clubiona comta (C. L. Koch, 1839) 2 clubfris Clubionidae Clubiona frisia (Wunderlich & Schuett, 1995)* 5 clubsubt Clubionidae Clubiona subtilis (L. Koch, 1867) 6 clubspec Clubionidae Clubiona spec. (Latreille, 1804) 59 drasspec Gnaphosidae Drassodes spec. (Westring, 1851) 1 enopspec Theridiidae Enoplognatha spec. (Pavesi, 1880) 2 enteeryt Linyphiidae Entelecara erythropus (Westring, 1851) 12 erigatra Linyphiidae Erigone atra (Blackwall, 1833) 2 erigspec Linyphiidae Erigone spec. (Audouin, 1826) 23 leptspec Linyphiidae Lepthyphantes spec. (Menge, 1866) 2 mangacol Araneidae Mangora acalyha (Walckenaer, 1802) 6 marpnivo Salticidae Marpissa nivoy (Lucas, 1846)* 3 masogall Linyphiidae Maso gallicus (Simon, 1894)* 4 metoprom Linyphiidae Metopobactrus prominulus (O. P.-Cambridge, 1872)* 6 neosradi Araneidae Neoscona adianta (Walckenaer, 1802)* 39 nericlat Linyphiidae Neriene clathrate (Sundevall, 1830) 1 neripelt Linyphiidae Neriene peltate (Wider, 1834) 2 oedoapic Linyphiidae Oedothorax apicatus (Blackwall, 1850) 3 ozyptila Thomisidae Ozyptila atomaria (Panzer,1801) 1 philfall Philodromidae Philodromus fallax (Sundevall, 1833)* 4

41 philspec Philodromidae Philodromus spec. (Walckenaer, 1826). 1 piralati Lycosidae Pirata latitans (Blackwall, 1841) 2 stemline Linyphiidae Stemonyphantes lineatus (Linnaeus, 1758)* 5 steospec Theridiidae Steatoda spec. (Sundevall, 1833). 1 synavena Salticidae Synagelis venator (Lucas, 1836)* 6 tenutenu Linyphiidae Tenuiphantes tenuis (Blackwall, 1852) 13 tetrexte Tetragnathidae Tetragnatha extensa (Linnaeus, 1758) 24 thanstri Philodromidae Thanatus striatus (C. L. Koch, 1845)* 18 therspec Theridiidae Theridion spec. (Walckenaer, 1805) 6 tibespec Philodromidae Tibellus spec. (Simon, 1875) 60 xeromini Lycosidae Xerolycosa miniat (C. L. Koch, 1834)*a 1 xystsabu Thomisidae Xysticus sabulosus (Hahn, 1832)* 1 xystspec Thomisidae Xysticus spec. (C. L. Koch,1835). 4 zelopede Gnaphosidae Zelotes pedestris (C. L. Koch, 1837)* 1 zelosero Gnaphosidae Zelotes serotinus (L. Koch, 1866)* 1 zygispec Araneidae Zygiella spec. (F.O.P.-Cambridge, 1902). 1 Total 427

Appendix 3: Planthopper (°), leafhopper (**) and beetle species; morphotype, family; full scientific names (only for those species which their identification was completed up to species level; abundances; trophic level: Predator (P), Herbivore (H), Omnivore species are indicated as predator. *Dune and/or sand specific species.

Morphotype Family Species name Abundance Trophic_level cicade 1** Aphrophoridae Neophilaenus lineatus (Linneus, 1758) 581 H cicade 2** Cicadellidae Doratura spec. (Sahlberg, 1871)* 23 H cicade 3** Aphrophoridae Philaenus spumarius (Linnaeus, 1758) 43 H cicade 4** Cicadellidae Conosanus obsoletus (Kirschbaum, 1858) 14 H cicade 8** Cicadellidae 13 H cicade 12** Cicadellidae Psammotettix maritimus (Perris, 1857)* 91 H cicade 13° Delphacidae Javesella pellucida (Fabricius, 1794) 20 H cicade 16** Cicadellidae 3 H cicade 21** Cicadellidae 6 H cicade 22° Delphacidae Muirodelphax aubei (Perris, 1857)* 16 H cicade 24** Aphrophoridae 1 H cicade 25** Cicadellidae 1 H cicade 29° Delphacidae Gravesteiniella boldi (Scott, 1870)* 9 H cicade 31** Cicadellidae 2 H cicade 33° Tettigometridae 1 H cicade 35° Delphacidae Stenocranus major (Kirschbaum, 1868) 1 H cicade 38** Cicadellidae 1 H cicade 39** Cicadellidae 1 H cicade 40° (Fabricius, 1781) 3 H cicade 41° Delphacidae 2 H

42 kever 1 Nitidulidae 8 H kever 2 Malachiidae Anthocomus rufus (Herbst, 1786) 17 P kever 3 Malachiidae (Olivier 1790) 55 P kever 4 Nitidulidae 1 H kever 5 Nitidulidae 5 H kever 6 Carabidae 1 P kever 7 Staphylinidae 11 P kever 8 Anthicidae 8 P kever 9 Chrysomelidae 67 H kever 10 Byrrhidae 11 H kever 11 Chrysomelidae Longitarsus jacobaeae (Waterhouse, 1858) 69 H kever 12 Tenebrionidae (Linnaeus, 1758)* 58 H kever 13 Carabidae Demetrias monostigma (Samouelle, 1819)* 154 P kever 14 Staphylinidae 1 P kever 16 Byrrhidae 2 H kever 17 Chrysomelidae 30 H kever 18 Chrysomelidae 36 H kever 19 Chrysomelidae 1 H kever 20 Phalacridae 5 H kever 21 Anthicidae 2 P kever 22 Oedemeridae 2 H kever 24 Byrrhidae 2 H kever 25 Nitidulidae 9 H kever 26 Carabidae 2 P kever 27 Cantharidae 17 H kever 28 Staphylinidae 13 P kever 30 Cerambycidae 2 H kever 32 Chrysomelidae 1 H kever 33 Chrysomelidae 1 H kever 35 Chrysomelidae Leptinotarsa decemlineata (Say, 1824) 2 H kever 36 Cantharidae 1 H kever 37 Carabidae 1 P kever 38 Chrysomelidae 1 H kever 39 Scarabaeidae Phyllopertha horticola (Linnaeus, 1758) 1 H kever 41 Carabidae 4 P kever 42 Tenebrionidae 5 P kever 43 Chrysomelidae Longitarsus ochroleucus (Marsham, 1802) 2 H kever 44 Chrysomelidae 1 H kever 45 Carabidae 2 P kever 46 Lagriidae Lagria hirta (Linnaeus, 1758) 8 H kever 47 Carabidae 1 P kever 48 Carabidae 1 P kever 49 Chrysomelidae Psylliodes marcida (Olivier, 1789)* 19 H

43 kever 50 Oedemeidae Oedemera spec (Olivier, 1789). 4 H kever 51 Chrysomelidae 2 H kever 52 Carabidae 1 P kever 53 Anthicidae 2 P kever 54 Chrysomelidae 1 H kever 56 Elateridae 1 P kever 57 Nitidulidae 1 H kever 58 Chrysomelidae 89 H kever 59 Tenebrioidae 1 P kever 60 Carabidae 2 P kever 61 Chrysomelidae 1 H kever 63 Byrrhidae 2 P kever 64 Byrrhidae 3 P kever 65 Carabidae 1 P kever 66 Chrysomelidae 13 H kever 67 Carabidae 1 P kever 68 Dasytidae Psilothrix viridicoeruleus (Geoffroy, 1785) 3 P kever 69 Chrysomelidae 1 H kever 70 Carabidae 3 P kever 71 Chrysomelidae 1 H lieveheersbeestje 1 Coccinellidae Coccinella septempunctata (Linnaeus, 1758) 33 P lieveheersbeestje 2 Coccinellidae Coccinella undecimpunctata (Linnaeus 1758) 10 P lieveheersbeestje 3 Coccinellidae Hippodamia variegate (Goeze, 1777) 8 P lieveheersbeestje 4 Coccinellidae Anatis ocellate (Linnaeus 1758) 3 P lieveheersbeestje 5 Coccinellidae Tytthaspis 16-punctata (Linnaeus 1760) 1 P lieveheersbeestje 6 Coccinellidae Propylea 14-punctata (Linnaeus 1758) 7 P lieveheersbeestje 7 Coccinellidae Harmonia axyridis (Pallas, 1773) 2 P lieveheersbeestje 8 Coccinellidae Platynaspis luteorubra (Goeze, 1777)* 1 P lieveheersbeestje 9 Coccinellidae Psyllobora 22-punctata (Linnaeus, 1758) 1 P snuitkever 1 Ceutorhynchus obstrictus (Marsham, 1802) 12 H snuitkever 2 Curculionidae Larinus planus (Gyllenhal, 1835) 1 H snuitkever 3 Curculionidae Microplontus rugulosus (Herbst, 1795) 1 H snuitkever 4 Curculionidae Sitona lineatus (Linnaeus, 1758) 18 H snuitkever 5 Curculionidae ovatus (Linnaeus, 1758)* 5 H snuitkever 7 Curculionidae Sitona hispidulus (Fabricius, 1777) 1 H snuitkever 8 Curculionidae Sitona lepidus (Gyllenhal, 1834) 6 H snuitkever 9 Curculionidae quadrimaculatus (Linnaeus, 1758) 1 H snuitkever 11 Curculionidae Pissodes castaneus (De Geer, 1775) 1 H snuitkever 13 Curculionidae Magdalis memnonia (Gyllenhal, 1837) 1 H snuitkever 14 Curculionidae Curculio glandium (Marsham, 1802) 1 H snuitkever 15 Curculionidae Otiorhynchus atroapterus (De Geer, 1775) 3 H snuitkever 16 Curculionidae Baris cuprirostris (Fabricius, 1787) 1 H snuitkever 18 Curculionidae Philopedon plagiatum (Schaller, 1783)* 3 H

44 Total 1729

Appendix 4: The spread of the data over different proportions and spatial autocorrelations of Marram grass for different scales (areas with a buffer of 5m, 10m, 20m and 50m were considered).

Appendix 5: Schematic presentation of possible interactions in dune ecosystems with a focus on plant spatial pattern of Ammophila arenaria.

Appendix 6: NMDS-ordinations of the full model on scale 20 (radius 20 meter) for the plant- and leafhopper, herbivorous and predatory beetle community. Species are indicated in red and the different sites in black.

45

46

Appendix 7: More graphs and analysis can be found on the google drive below. https://drive.google.com/open?id=1F4HQiBoRykB-GyCcVCqfbYwiIDTCKxay

47