Effects of forest stand diversity on arthropod diversity ...share.bebif.be/data/forbio/Gobin_MasterThesis_2014.pdfSamenvatting Recentelijk is de interesse aanzienlijk gestegen met

Faculteit Bio-ingenieurswetenschappen

Academiejaar 2013 – 2014

Effects of forest stand diversity on arthropod diversity

Masterproef

Ritchie Gobin

Promotor: Dr. Ir. Jan Mertens

Co-promotor: Prof. Dr. Ir. Kris Verheyen

Tutor: Nuri Nurlaila Setiawan

Masterproef voorgedragen tot het behalen van de graad van

Master of Science in de biowetenschappen: land- en tuinbouwkunde




Masterproef

Ritchie Gobin






Foreword

Nature is a recipe of patterns and it‟s supplements all gathered in many diverse systems

called ecosystems. These patterns can be very intriguing once brought to our attention. This

is just a needle in a haystack of what the word provides to human-beings.

I have always been fascinated in what seems at first sight chaotic yet can or cannot be

explained by simple survival theories.

This work has primarily been made possible through the existence of the FORBIO-project.

Prof. Dr. Ir. Kris Verheyen, my co-promotor, is supervising the FORBIO-project. My interest in

this project was easily triggered by the presentation on the „Startersdag in het Bos- &

Natuuronderzoek‟ in Brussels by Nuri Nurlaila Setiawan, a PhD student and also my tutor for

this work. Nuri and Kris made my participation possible in this fascinating project in Gedinne.

The consent of my promotor Dr. Ir. Jan Mertens was a great relief and a start sign for a most

interesting learning process. His patience and clear judging together with the driving force of

Nuri are appreciated.

The two sites in Gedinne weren‟t easy to reach which made the fieldwork rather difficult. Still

with the group atmosphere from Nuri and Mathias Dillen, a PhD student, we managed to

finish each our fieldwork within the expected time.

Through the progress of this work I was surprised by the help from the people from the

laboratory of University Ghent in Gontrode. Pallieter De Smedt (PhD student) learned me to

look at details of the Earth‟s fauna that I could never have thought to be so mind-expanding.

Through the determination process Pallieter and Nuri kept me on track whenever the

arthropods seemed unidentifiable while together with Luc Willems, the laboratory supervisor,

they provided me with the right material to work efficiently. Through the writing process of

this thesis I could count of unlimited information from Kris and Nuri.

Futhermore I would like to thank Drukkerij Ansa Print bvba for printing this work and Paperas

bvba for binding this work.

Abstract

Recently forest diversity has gained interest accountable to global warming problems

and its consequences for ecosystem services humanity relies on. Until this day few

research is done to reveal the effects of tree diversity on arthropod diversity in

forests. The establishment of the FORBIO-project (Belgium), part of a large scale

network of forest biodiversity and ecosystem functioning research (TreeDivNet),

made the investigation of these effects possible. The FORBIO-site in Gedinne

(Wallonia) consists of five tree species Fagus sylvatica, Quercus petraea, Larix x

eurolepis, Pseudotsuga menziesii and Acer pseudoplatanus planted in monocultures,

two , three and four tree species arrangements. Arthropods were caught during July

and August 2013 with a modified aspirator and accordingly identified into orders and

trophic levels. The identification data, acquired from 176 sampled trees and 44 plots,

were tested on differences in arthropod diversity of above ground arthropods in

monocultures and mixed tree stands.

There was no significant difference in arthropod diversity between tree arrangements

however individual trees did show significant differences where Acer pseudoplatanus

(lowest arthropod diversity) and Quercus petraea (highest arthropod diversity)

diverged most from the three other species. The abundance of trophic levels

suggested strong influences of abiotic factors of the surrounding landscape between

the two study areas. There were significant differences in the arthropod diversity

between the two study areas confirming that arthropod diversity measured with the

Shannon index was able to detect differences in arthropod diversity, while trophic

levels indicated differences in communities.

Keywords

Biodiversity, arthropods, ecosystem functioning, trophic levels, mixed tree arrangement,

forest, experimental design

Samenvatting

Recentelijk is de interesse aanzienlijk gestegen met de actuele problematiek met

betrekking tot de opwarming van de aarde en de gevolgen voor de

ecosysteemdiensten die de mensheid geniet. Tot nog kort is weinig onderzoek

uitgevoerd om effecten van diversiteit in plantverband op geleedpotigen (Arthropoda)

te onderzoeken in bossen. Het FORBIO-project, deel van een globaal onderzoek

naar biodiversiteit in bossen en ecosysteem functies (TreeDivNet), geeft kansen om

deze effecten te onderzoeken.

De FORBIO-site in Gedinne (Wallonia) is, met haar vijf verschillende boomsoorten

Fagus sylvatica, Quercus petraea, Larix x eurolepis, Pseudotsuga menziesii en Acer

pseudoplatanus, aangeplant in plantverbanden van monocultuur, twee soorten, drie

soorten en vier soorten. De geleedpotigen werden gevangen in juli en augustus 2013

met een gemodificeerde stofzuiger. De gevangen geleedpotigen zijn gedetermineerd

tot op orde en onderverdeeld in trofische niveaus. De determinatie gegevens van

bovengronds levende geleedpotigen, verkregen uit 176 boom stalen in 44 plots

werden getest op verschillen in monoculturen en diverse plantverbanden. Het

voorkomen van het totaal aantal geleedpotigen en hun trofische niveaus zijn

ruimtelijk gevisualiseerd.

De diversiteit van geleedpotigen vertoonde geen significante verschillen tussen de

vier verschillende plantverbanden terwijl voor verschillende boomsoorten er wel

significante verschillen zijn waargenomen. Acer pseudoplatanus en Quercus petraea,

vertoonden respectievelijk de laagste en hoogste diversiteit aan geleedpotigen. Het

is aannemelijk dat, gezien de jonge bomen, de condities nog niet stabiel zijn en de

gemeenschappen zich nog ontwikkelen. Toekomstig onderzoek zal uitwijzen of

populaties verschillen in diversiteit van geleedpotigen zullen optreden in de vier

verschillende plantverbanden. Uit de beschrijving van trofische niveaus bleek een

groot verschil in beide studiegebieden, Gribelle en Gouverneur, wat mogelijks te

maken heeft met ander abiotische factoren typerend voor het studiegebied.

7

Table of contents

Foreword ............................................................................................................................... 4

Abstract ................................................................................................................................. 5

Samenvatting ........................................................................................................................ 6

List of figures ......................................................................................................................... 9

List of tables .........................................................................................................................11

1 Introduction .......................................................................................................................12

2 Literature ...........................................................................................................................13

2.1 Biodiversity .................................................................................................................13

2.1.1 Definition ..............................................................................................................13

2.1.2 Relevance of biodiversity for human life on earth .................................................14

2.1.3 Forms of biodiversity ............................................................................................16

2.2 Biodiversity and ecosystem functioning (BEF) ............................................................18

2.2.1 Biodiversity and ecosystem functioning hand in hand ..........................................18

2.2.2 BEF relationships and research ...........................................................................19

2.2.3 Drylands ecosystem functioning research ............................................................21

2.2.4 Grasslands ecosystem functioning research ........................................................22

2.2.5 Forest ecosystem functioning research ................................................................23

2.3 Arthropod diversity in forest vegetation .......................................................................24

2.3.1 Arthropod morphology and taxonomy ..................................................................24

2.3.2 Trophic levels and functional groups ....................................................................25

2.3.3 Associated arthropod diversity in tree stands .......................................................28

3 Materials and methods ......................................................................................................31

3.1 Study area ..................................................................................................................31

3.1.1 Plots ....................................................................................................................34

3.1.2 Site condition .......................................................................................................35

3.2 Fieldwork in Gedinne ..................................................................................................38

3.2.1 Arthropod sampling method .................................................................................38

3.2.2 Daily sampling .....................................................................................................40

3.3 Identification of the arthropods ....................................................................................40

3.4 Data analysis of the sampled arthropods ....................................................................43

3.4.1 Acquiring a balanced design ................................................................................43

3.4.2 Defining the variables and forms of data ..............................................................45

3.4.3 Overview of analyses ...........................................................................................45

4 Results ..............................................................................................................................46

4.1 Weather variability in Gedinne ....................................................................................46

4.2 Arthropod diversity linked to the tree arrangement [1] .................................................47

4.3 Diversity of arthropods linked to the tree species [2] ...................................................49

4.3.1 Differences in arthropod diversity between sites Gribelle and Gouverneur [3] ......51

8

4.4 Comparison of arthropod abundances ........................................................................51

4.4.1 Comparison of arthropod abundance based on their orders .................................51

4.4.2 Comparison of arthropod abundance based on trophic levels [4] .........................52

4.4.3 Diversity of arthropods based on Shannon index in Gribelle and Gedinne ...........54

4.4.4 Arthropod abundance of trophic levels .................................................................56

4.4.5 Analysis of trophic levels linked to their tree arrangements [5] .............................61

4.4.6 Analysis of trophic levels in Gribelle and Gouverneur ..........................................62

5 Discussion .........................................................................................................................63

5.1 Arthropod classification ...............................................................................................63

5.2 Differences in Gribelle and Gouverneur ([3], [5]) .........................................................63

5.3 Arthropod diversity between tree arrangements ([1], [4]) ............................................64

5.3.1 Shannon‟s index differences between the tree arrangements [1] .........................64

5.3.2 Trophic levels differences in the tree arrangements [4] ........................................64

5.4 Arthropod diversity linked to tree species [2] ...............................................................65

6 Conclusion ........................................................................................................................67

7 References ........................................................................................................................68

Table of content ..................................................................................................................... 3

List of appendices ................................................................................................................. 4

A.1.1 Overview of the sites in Gedinne .......................................................................... 6

A.2 Weather conditions during the fieldwork ...................................................................... 7

Appendix B ...........................................................................................................................10

B.1 Overview of the analyses in this work .........................................................................10

B.2 Analysis of Shannon index applied on orders linked to the tree arrangement .............11

B.2.1 Test for normality of tree arrangement groups .....................................................11

B.3 Analysis of Shannon index applied on orders linked to the tree species .....................12

B.4 Comparison of arthropod diversity in the sites ............................................................15

B.5 Analysis of trophic levels linked to tree arrangement ..................................................17

B.5.1 Test for normality and variances within tree arrangements ..................................17

B.5.2 Kruskal-Wallis test on trophic levels ....................................................................19

B.5.3 Differences between Gribelle and Gouverneur based on trophic levels ...............20

9

List of figures

Figure 1. Schematic representation of a framework for testing BEF by Guy F. Midgley

(Midgley, 2012).....................................................................................................................18

Figure 2. Early hypotheses of biodiversity and ecosystem process relationships by Loreau et

al. (Loreau et al., 2002) ........................................................................................................19

Figure 3. Hypothetical relationships between biodiversity and ecosystem function with a

positive correlation (Schwartz et al., 2000) ...........................................................................20

Figure 4. Semiochemically mediated interactions among members of four trophic levels,

based on a composite of examples in the literature. The interactions between trophic levels

are indicated with arrows. The bold solid lines indicate attraction with various biochemicals or

body odors (e.g. 1, 4, 6). Thin solid lines with arrows (e.g. 3, 5, 7, 9). Thin dashed lines show

interference effects in other interactions (e.g. 2, 12, 19) (Price et al., 2011). ........................26

Figure 5. Location of the nine research projects that make up the TreeDivNetwork, the

largest terrestrial ecology project of its type (Verheyen, 2012). .............................................31

Figure 6. Map of the three locations of the FORBIO-project in Belgium (Verheyen et al.,

2013). The black points indicate the position of the site. .......................................................32

Figure 7. Plot 9 with mixed tree species Quercus petraea (red), Acer pseudoplatanus

(yellow) and Pseudotsuga menziesii (lila). ............................................................................35

Figure 8. Plots 21 till 29 on the site Gouverneur surrounded with its fence. The trees have not

yet reached higher than the surrounding vegetation. The picture is taken while waiting for a

weather depression to pass by (24 July 2013). .....................................................................36

Figure 9. Plots 30 till 42 on the site Gouverneur surrounded with its fence. The trees have

reached higher than the surrounding vegetation in most plots (24 July 2013). ......................36

Figure 10. Sampling an Acer pseudoplatanus on the site Gouverneur with the aspirator with

a first swift on the tree stem from bottom to the top (yellow arrow). ......................................39

Figure 11. Example of the material of a sample in the Petri dish ready for the first

identification round. The label is number respectively with project name (Gedinne, G),plot

number (plot 34), tree identification number (28) and tree species from the sample (Quercus

petraea, Q). ..........................................................................................................................41

Figure 12. Arthropod diversity based on the Shannon index between tree arrangements

respectively from monocultures (1 species) till 4 species tree arrangements. The bold

horizontal line represents the median of the Shannon index for each tree arrangement. The

separate dots are outliers. ....................................................................................................48

Figure 13. Boxplot visualizing differences in means of arthropod Shannon‟s diversity Index

between tree species marked by their genera in the x-axis. The red dot presents the means

10

of each species. Each tree species represents 40 tree samples (n = 40). The letters a, b, c,

d, e indicate which tree species do not significantly (p > 0,05) differ. ....................................50

Figure 14. Comparison of the number of arthropod individuals (y-axis) classified into orders

(x-axis) found in respectively Gribelle and Gouverneur. The total number of individuals for

each order is mentioned above each bar. .............................................................................52

Figure 15. Bar charts explaining the relative arthropod presence per trophic level (x-axis) on

the sites Gribelle and Gouverneur. Each bar represents the mean of 88 samples

independent of tree arrangement nor tree species. The error bars are the standard deviations

for a sampled tree. ...............................................................................................................53

Figure 16. Scatter plot of tree samples visualizing differences in variation between the sites

Gribelle and Gedinne. The exponential Shannon index in the y-axis and the arthropod

abundance in the x-axis. The sample colour indicates the site. ............................................55

Figure 17. Arthropod individuals sampled in Gedinne. Each bar shows the arthropod

abundance of each trophic level with the arthropod abundance of each order within the

column of the trophic level. ...................................................................................................56

Figure 18. Hemipteran predator of the Nabidae family (top) with developed rostrum, Jumping

plant lice (Hemipteran herbivore) and a winged booklice of the Psocoptera order. The orange

lines are the lines of millimetre paper (Zooming range ≈ x15). ..............................................59

Figure 19. Bar chart with the average arthropod individuals present per plot (y-axis) for all

four tree arrangements on both sites in Gedinne. The bars with one species tree

arrangement represent 14 plots (n = 56 samples), the bars with 2, 3 and 4 species tree

arrangements represent 10 plots (n = 40 samples). The error bars indicate the standard

deviation of the data for each bar. ........................................................................................61

11

List of tables

Table 1. Experimental studies that investigate the hypothesis of a possible relation between

biodiversity and ecosystem functioning edited from Schwartz et al.. The type of response

curve is illustrated in Figure 3 (Schwartz et al., 2000). ..........................................................21

Table 2. Summary of characters of the FORBIO-project sites Zedelgem, Gedinne and

Hechtel-Eksel (Verheyen, Ponette & Muys, 2011). ...............................................................33

Table 3. Overview of the characteristics of the trees planted on the FORBIO-project sites in

Gedinne (Verheyen et al., 2010). ..........................................................................................34

Table 4. Summary of plots with different tree arrangements. The asterisk indicates the extra

Fagus sylvatica plots with different provenance. ...................................................................34

Table 5. Sampling dates in Gedinne with a summary of the weather conditions. ..................40

Table 6. Balanced design for statistical analysis with the variable tree arrangement in

Gedinne (Gouverneur and Gribelle). .....................................................................................43

Table 7. Sampled tree species respectively in Gribelle, Gouverneur and in Gedinne in total.

The numbers followed by the letter a represent additional Fagus sylvatica trees provenances

from Germany and France with each half of the sampled trees. ...........................................44

Table 8. Balanced design for statistical analysis with the variable tree species. ...................44

Table 9. Variables used in the statistical analysis. ................................................................45

Table 10. Conversion of common the Shannon index into the true diversity or the effective

number of species edited from L. Jost (Jost, 2009). .............................................................54

Table 11. Herbivore individuals count in all samples in Gribelle and Gouverneur. Orders, and

if specified more detailed families information, are ranked according to their abundance. ....57

Table 12. Parasite individuals counted in all samples in Gribelle and Gouverneur. Orders and

if specified more detailed families information are ordered according to their abundance. ....58

Table 13. Predator individuals counted in all samples in Gribelle and Gouverneur. Orders

and if specified more detailed families information are ranked according to their abundance.

.............................................................................................................................................60

Table 14. Decomposer individuals counted in all samples in Gribelle and Gouverneur. Orders


.............................................................................................................................................60

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1 Introduction

Since long scientists have been interested in how populations are being regulated to

understand and predict nature‟s behaviour (Hairston, Smith & Slobodkin, 1960). Biodiversity

has kept scientists concerned with numerous questions such as how natural ecosystems

reach equilibriums whilst providing ecosystem services for human beings. Disturbances may

exceed the rate at which ecosystems evolve making ecosystem services unreliable

(Johnston et al., 2007). The Convention of Biodiversity in 1992 was one of many efforts

made to temper negative human impact in the interests of conserving nature‟s ecosystems

and their diversity.

Biodiversity levels are under constant dynamics reacting on multiple factors. Measurement in

certain scales is suggested to influences these levels (Moran & Southwood, 1982) giving way

for questions such as how study area should be designed to detect effects. The TreeDivNet

platform promotes cooperation between grouped projects in young and older forests. The

main goal of these projects is to investigate the relation between tree species diversity and

ecosystem functioning. In this network the FORBIO-project was set up in Belgium. As the

need for measuring diversity in this project arose, a certain way of monitoring had to be

chosen. Arthropods represent about 78% (1,3 to 1,6 million species) of all described species

in the Animalia kingdom on Earth (Orlóci, Anand & Pillar, 2002; Zhang, 2013). Moreover

research on arthropod diversity in tropical forests suggested that plant diversity can be a

predictor for arthropods species richness (Basset et al., 2012). These findings enforce why

arthropod diversity could provide insights in biodiversity in general.

The aim of this master thesis was to investigate if the biodiversity of arthropods is higher

when tree species are mixed in comparison to monocultures in experimental designs of

juvenile woodlands.

The aspirator method was applied to obtain arthropods from 44 plots with tree arrangements

from monocultures up to four species. The acquired 176 samples were identified into orders

and trophic levels.

Two classifications in arthropods were made to represent arthropod diversity differences

between tree arrangements, tree species and sites. The classification in trophic levels is

expanded in the results. In section results each analysis was provided with an overview of

the data for better insight. The significant differences were highlighted for further discussion.

The conclusion summarized significant findings in the FORBIO-sites in Gedinne.

The accompanied Appendix provided extra information handled in this master thesis and is a

helping guide particularly for the interpretations of data through the process of reading.

13

2 Literature

2.1 Biodiversity

2.1.1 Definition

Biological diversity was first formulated by Thomas Lovejoy in 1980. It‟s now widely used

synonym was introduced five years later by Walter Rosen in preparation of the global

Convention on Biological Diversity (CBD) (O‟riordan & Stoll-Kleeman, 2002; Wilson & Peter,

1988). There are several definitions of biodiversity. The following definition is mentioned to

clarify the word in a simple and straight forward way.

“Biodiversity is the variety of life in all kinds of levels of organisation, classified by

evolutionary and ecological criteria or simply a synonym for „Life on Earth‟.” (Ahlfinger, Gibbs,

Harrison, Laverty & Sterling, 2008; UNEP, 2013).

2.1.1.1 Global

In the past initiatives have been taken by global environmental organisations to protect Earth

from biodiversity loss. The African “Conservation of Nature and Natural Resources”

established in 1948 now known as the International Union for Conservation of Nature (IUCN)

and the “Convention on Wetlands of International Importance especially as Waterfowl

Habitat” known as the Ramsar or Wetlands convention, started in 1971, entered into force in

1975 (Ramsar Convention Secretariat, 2008).

Undoubtedly the global Convention on Biological Diversity (CBD), held in Rio de Janeiro in

1992, was a big step to a global conservation and sustainable use of biological diversity. For

the first time governments worldwide agreed upon three goals, the conservation of

biodiversity in general, the sustainable character of conservation and a fair and honest

sharing of benefits accumulated through the use of genetic resources. In this convention

biological diversity is defined as:

“the variability among living organisms from all sources including, terrestrial, marine and

other aquatic ecosystems and the ecological complexes of which they are part; this includes

diversity within species, between species and of ecosystems.” (CBD, 1992)

14

2.1.1.2 Europe

In Europe Natura 2000 was initiated as a response to the Habitat Directive (1992) and the

Birds Directive (1979) to halt the loss of biodiversity by 2010. Meanwhile in 2001-2005 the

Millenium Ecosystem Assessment was organised. Here scientists reviewed the conditions

and trends of ecosystems and their services. The BISE (Biodiversity Information System for

Europe) gives a similar definition such as the definition given by the CBD.

“Biodiversity – the variety of ecosystems, species and genes – is the world‟s natural capital.

It is integral to sustainable development by providing vital goods and services, such as food,

carbon sequestration, and seas and water regulation that underpin economic prosperity,

social well-being and quality of life.” (European Commission, 2010)

Unlike the definition of CBD, the BISE clearly mentions sustainability, the ability to maintain

something over a period of time without diminishing it (Lélé & Norgaard, 1996). Nevertheless

both definitions are parallel. This sustainable development requires society to think differently

in perspectives of consumption and production patterns (European Commision, 2013).

2.1.2 Relevance of biodiversity for human life on earth

It is clear that several organisations are concerned with conservation of biodiversity, however

the reasons why we humans should be concerned about it is clarified in this paragraph.

193 Parties, gathered in the CBD, agree that biodiversity must be recognized as the

foundation of economic productivity, prosperity and sustainable development (CBD, 2011).

Together with climate change, loss of biodiversity is the most critical global environmental

threat and gives rise to substantial economic and welfare losses (European Commission,

2010). What follows is a clear citation of the Millenium Ecosystem Assessment explaining

how exploitation of ecosystem services has affected biodiversity until this day.

“Over the past 50 years, humans have changed ecosystems more rapidly and extensively

than in any comparable period of time in human history, largely to meet rapidly growing

demands for food, fresh water, timber, fiber, and fuel. This has resulted in a substantial and

largely irreversible loss in the diversity of life on Earth.” (Millennium Ecosystem Assessment,

2005)

In this phrase the word ecosystem should be interpreted as a dynamic complex of plant,

animal and micro-organism communities and their non-living environment interacting as a

functional unit (CBD, 2013).

15

Ecosystem services encompass all the processes through which natural ecosystems help

sustain human life on Earth. The results of ecosystem services can be goods essential for

our survival such as food, medicine, industrial products. Examples of ecosystem services

are the buffering of water in the soil to prevent floods, the containment of carbon in woods

that filter the air, the purification of air and water, the pollination of crops and fruit trees, etc.

(Campbell et al., 2008). Certain ecosystem services result from less obvious processes such

as the heritage of DNA resources nature provides to breed new cultivars and the advantages

of pest control services (Naeem et al., 1999). These services give a realisation in how far an

ecosystem contributes to human life and the further existence of it.

Monetary values give way to estimate the contribution of ecosystem services to human life

on Earth. Ecologist Robert Costanza and his colleagues estimated the value of Earth's

ecosystem services around $33 trillion a year (Campbell et al., 2008). This validation must be

seen as a decision making tool justifying and setting priorities for programs, policies and

actions which restore ecosystem services (King & Mazzotta, 2000).

Through time the influences related to human activity have shown degradation of

ecosystems. The appearance of human interaction has causes ecosystem processes to

accelerate or change mostly in a disadvantage to the ecosystem‟s condition and its balanced

out state. Degradations of ecosystems also hinder the human well-being on its own.

According to the Millennium assessment the degradation of ecosystems will be met,

considering the higher demands they are facing in the future (Corvalan et al., 2005).

16

2.1.3 Forms of biodiversity

The CBD mentions 3 types of biodiversity in its definition, the difference in individual species

(species diversity), the genetically uniqueness of species (genetic diversity) and the more

complex differences in ecosystems (ecosystem diversity) (CBD, 1992). Although genetic

diversity is fundamental for future adaptive evolution (Colwell, 2009), only the species and

ecosystem biodiversity are explained in this paragraph. Additionally community diversity will

be mentioned for its contribution to this literature.

2.1.3.1 Species diversity

To understand species diversity it is futile to get an idea how species are gained or lost on

Earth. Species are considered as populations or series of populations who are able to

exchange genes in natural conditions. Under this definition species are not able to breed

independently with other species. Thus why the creation of new species happens generally

due to geographic differentiation over a long period of time (Wilson and Peter, 1988).

Species diversity can be measured as two components being species richness and species

evenness. Species richness is a measure for the amount of different species of a certain

taxon (eg. arthropods) or life form (eg. trees) while evenness is a measure explaining the

quantity or abundance of one species. A known formulation containing these two

measurements can provide several biodiversity indices.

Species diversity can be quantified by applying a formula on a certain dataset resulting in a

dimensionless biodiversity indices (Help, Herman, & Soetaert, 1998) however higher levels

of classification (genera, families, orders) can also be considered (Colwell, 2009). The

meaning of this number is rather useful to compare local measurements.

Examples of biodiversity indices are the Simpson index and the Shannon index, both

common in use. The indices take in account the abundance and the richness of each

species. The Shannon-Wiener or Shannon‟s index is less sensitive to changes in evenness

and more sensitive for detecting rare species in comparison with Simpson‟s Index (Colwell,

2009). Nonetheless the Shannon index is still a preferable measurement tool for ecological

diversity since individual species are the products of natural selection (Chapman & Reiss,

1999).

Although the two presented diversity indices are and have been widely used scientists argue

about the lack in representing varying similarities and dissimilarities between species

(Leinster & Cobbold, 2012; Pavoine, Ollier & Pontier, 2005) and do not take communities into

account (Colwell, 2009). Furthermore Jost (2009) gives examples were diversity indices do

not suffice in presenting the actual biodiversity. On the other hand recent research still finds

biodiversity indices to be a flexible way of interpreting complex systems. They are of potential

interest to interpret varying sites or forest types (Cheng, 2004).

17

2.1.3.2 Ecosystem diversity

It is useful to have a better look at the meaning of the word ecosystem. The word was first

introduced by Arthur Transley in 1935. An ecosystem was the word which had to explain the

relation between a community of organisms and its environment (J. L. Chapman, M. J. Reiss,

1999). Differences in physical characters of the environment, species and the interactions of

both give a certain diversity to an ecosystem (Ahlfinger et al., 2008).

Ecosystems are interrelated with many parameters influencing the ecosystem diversity.

Since there is no agreement of system on how to describe diversity in global scales diversity

is rather analysed local or regional and then mainly in terms of vegetation (Groombridge &

Jenkins, 2002) This local and regional diversity indicated to have a potential role in

maintaining multiple ecosystems through the current global change (Duffy, 2009).

2.1.3.3 Forms of diversity within a community

There are different ways of interpreting the word community. Communities are naturally

occurring groups or populations that interact in a particular environment (Price, Denno,

Eubanks, Finke, & Kaplan, 2011). The word „community‟ can be implemented as a subgroup

of a larger community which makes the term rather ambiguous. To avoid confusion several

other terms such as guilds, functional types and trophic levels are applied as subgroups of a

community (Cohen & Łuczak, 1992; Root, 1967).

Functional diversity or the variety of species that fulfil different functional roles in a

community or ecosystem. To understand functional diversity at its fullest some basic terms

will be cleared up. Assuming that a change in species richness and composition, or

biodiversity, could influence ecosystem properties or species‟ responses to environmental

conditions, there would be a need to determine their contribution to an ecosystem. This

contributions are functional traits (Hooper et al., 2005). There are two kinds of functional

traits. The functional effect traits are used in biodiversity and ecosystem functioning studies

because they may affect ecosystem properties (Hooper et al., 2005). Species with similar

effects on a specific ecosystem are grouped together in a functional type or functional group.

Functional types are just like guilds part of a community. It is with these functional types

scientist attempt to quantify functional diversity(Hooper et al., 2005; Petchey & Gaston,

2006).

18

2.2 Biodiversity and ecosystem functioning (BEF)

2.2.1 Biodiversity and ecosystem functioning hand in hand

Linking biodiversity to ecosystem functions has been a long term vision for the past two

decades and keeps gaining field (Balvanera et al., 2006). Ecosystem functions are defined

as the biological, geochemical and physical processes and components occurring within an

ecosystem (Maynard et al., 2013). The CBD describes two consequences of biodiversity

loss, a long-term or permanent qualitative or quantitative reduction in components of

biodiversity and their potential to provide goods and services (CBD Secretariat, 2004). These

components of diversity can be genes, species, ecosystems, etc. depending in which scale

biodiversity is described. The influence of human interaction with nature has more than often

led to a loss of biodiversity (Corvalan et al., 2005) and a discontinuance of ecosystem

function products or ecosystem services (Duffy, 2009; Schwartz et al., 2000) . Furthermore

the consequences of these human interactions are amplified through shortcomings in

management (Naeem et al., 1999).

A well studied example of ecosystem functioning is the measureable component biomass

production. Biomass production gives an idea of the primary productivity and can be an

indicator for carbon fixation. Biomass production characteristics differ between plant species,

thus pointing out the importance of the differences between species (Loreau, Naeem, &

Inchausti, 2002).

In Figure 1 Midgley (2012) has presented a framework for testing BEF relations. The

framework shows three groups, abiotic drivers, biodiversity and ecosystem function. The

question marks linking these three groups are being investigated.

Figure 1. Schematic representation of a framework for testing BEF by Guy F. Midgley

(Midgley, 2012)

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Before looking into results of researches it is important to separate observational studies

from experimental studies. Observational studies only give the option to observe the effects

of a certain stand (plot) while experimental studies allow the researcher to give a certain

treatment to a stand (plot).

As an example, an observational study can be done in a forest in a certain stage of

succession while in experimental studies the place and choice of trees will be chosen and

fixed. In experimental studies the effect of treatment is easier noticed compared to

observational studies due to slower dynamics of forest ecosystems in a state of

succession(Parish & Antos, 2006). This qualifies experimental studies to much rather show

causal results in forest ecosystems (Caspersen & Pacala, 2001).

2.2.2 BEF relationships and research

Several researches have been done to find a fitting relation between biodiversity and

ecosystem functioning. Over time these researches have shown allot of variety in results.

Figure 2 shows a few possibilities of type of relations. On the x-axis biodiversity is quantified

while the y-axis represents one ecosystem process per graph. The first point represents the

zero situation, with no biodiversity there are no ecosystem processes. The natural level of

biodiversity is indicated with the second point.

Figure 2. Early hypotheses of biodiversity and ecosystem process relationships by Loreau et

al. (Loreau et al., 2002)

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Schwartz et al. (2000) narrows these hypothetical relations down to a linear (Type A) or a

redundant (Type B) relationship (Figure 3) and all its forms in between. The y-axis describes

the ecosystem function similar to ecosystem process (Figure 2).

To proof these hypotheses right the ecosystem function must depend on native species and

more important, the maintenance of the ecosystem processes must depend on numerous

species implying conservation of diversity in the system (Schwartz et al., 2000).

Figure 3. Hypothetical relationships between biodiversity and ecosystem function with a

positive correlation (Schwartz et al., 2000)

Several researches (Table 1) found linear relations (type A) with biodiversity and ecosystem

functions such as biomass (S. Naeem et al, 1995; van der Heijden et al., 1998), CO2 flux (S.

Naeem et al., 1994; McGrady-Steed et al., 1997) whilst other experimental studies indicated

redundant relations (type B) for biomass (Tilman and Downing, 1994; Symstad et al., 1998).

In 26 out of the 28 experimental studies the hypothetical relationships in Figure 3 were

confirmed (Schwartz et al., 2000).

Schwartz et al. (2000) used a theoretical model to analyse the linkage of species numbers

with ecosystem stability. This model didn‟t reveal significant increases of ecosystem stability

beyond the first few species. He reasons that high species richness does not contribute

significantly because of dominance in most communities where these few species provide

the majority of biomass (Schwartz et al., 2000).

A rapid turnover of species is suggested to mask differences in diversity when quantified with

diversity indices such as the Shannon‟s and the Simpson‟s diversity Index. These

differences, rather in quality, can lead to maximum functioning and stability over time

(Schwartz et al., 2000).

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Table 1. Experimental studies that investigate the hypothesis of a possible relation between

biodiversity and ecosystem functioning edited from Schwartz et al.. The type of response

curve is illustrated in Figure 3 (Schwartz et al., 2000).

In an unrelated study also in grassland ecosystems a turnover of species was also

suggested to help explain different results, because of different areas and methodologies,

towards the patterns and structuring processes in grassland ecosystems (Chase et al.,

2000).

2.2.3 Drylands ecosystem functioning research

Drylands are characterized as areas with typically longer periods of drought where average

rainfall is below the potential moisture losses through evaporation and transpiration (FAO,

2004). The importance of drylands rises knowing it represents at least 40% of Earth‟s land

(Maestre et al., 2012). This landmass supports 38% of the human population (Maestre et al.,

2012). In a global research 224 soils of dryland ecosystems have been analysed over all

continents except for Antarctica. 14 functions related to carbon, nitrogen and phosphorous

cycles have been analysed and tested for a positive relations with biodiversity. In this

research biodiversity was quantified as the species richness of perennial vascular plants

growing on the soils.

A schematic representation of a framework for testing BEF is illustrated in Figure 1. This BEF

scheme is based on research in drylands. This model keeps several parameters in account

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such as disturbance, climate and physicochemical influences which represent the abiotic

drivers. Under biodiversity Midgley (2012) considers groups of species which have a similar

function in the ecosystem. Notice the species being grouped by their trophic level: consumer

species, decomposer species and producer species.

Maestre et al. (2012) found that the relationship between species richness and ecosystem

multi-functionality rises steeper with fewer than 5 species and increases incrementally with

the addition of more species. This suggests that ecosystem multifunctionality is well

established with relatively few species (Maestre et al., 2012).

In addition Midgley (2012) points out that these analyses were unable to clarify how

biodiversity across trophic levels, conjuncted by abiotic drivers, determines ecosystem

function as earlier shown in Figure 1 (Midgley, 2012).

2.2.4 Grasslands ecosystem functioning research

Studies in grasslands found a linear relationship between productivity and diversity in

experimental grassland communities. In this research the log scale of plant species richness

has shown a weak but accelerating loss of productivity with loss of species (Hector et al.,

2001).

The BIODEPTH project study was established to investigate relations between biodiversity

and grassland ecosystem functioning. There were eight different locations in Europe with

different environmental factors. These experiments were setup as experimental design with

certain characteristics. The sites were prepared, for selected seed species to grow, by

removing all of the present vegetation and the seedbank with various methods such as

steam sterilisation, continuous weeding and the application of heat or methyl-bromide. The

borders of the plots were either sown in with slow growing grass (Switzerland, Germany,

Ireland, UK, Sweden, Portugal) or not separated at all (Greece) (Spehn et al., 2005).

Five levels of species richness are applied in the plots, this means monocultures up to

diversity mixtures with 5 species. Furthermore the species richness was analysed by

estimated ground cover and biomass samples.

Ecosystem functions such as root biomass, decomposition rate, photosynthetically active

photon flux density (PPFD), soil nitrogen were measured through certain protocols (Spehn et

al., 2005).

The analysis of grassland data indicated that ecosystem multi-functionality requires greater

numbers of species. In all analysed experiments there was found a positive relationship

between number of ecosystem processes and number of species influencing overall

functioning. Different species can influence different functions. This makes studies of

individual processes in isolation underestimate the levels of biodiversity needed to maintain

multifunctional ecosystems (Hector & Bagchi, 2007).

In a meta-analysis on the data of 17 grassland biodiversity experiments (BIODEPTH project

included) Isbell et al. concludes that even more species are needed to maintain ecosystem

functioning then previously suggested (Isbell et al., 2011).

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2.2.5 Forest ecosystem functioning research

Forests are valuable for numerous ecosystem services and conserve 70% of the terrestrial

biodiversity on earth. Moreover around 1,6 billion people depend on these forests for their

livelihoods (IUCN, 2013). Forests consist of self-organizing and regulating systems with

multiple natural processes acting independent to both internal and external drivers

(Thompson et al., 2009). The results of these processes are forest ecosystem services such

as regulating water regimes and water quality, provisioning of organic material (soil

enrichment), carbon sequencing, limiting of erosion, regulating of climate and air quality,

providing habitat for species, etc.

The capacity to sustain natural processes and their results (ecosystem services) is referred

to as the resistance of an ecosystem (Cleland, 2012). An increase of biodiversity in all levels

(stand, landscape, ecosystem, bioregional) have not always indicated to maintain resistance

in planted and semi-natural forests. In boreal pine forests, with naturally low species

diversity, resilience occurs (Thompson et al., 2009). Resilience is the capacity of an

ecosystem to adapt to a certain disturbance keeping its original state (Cleland, 2012; Holling,

1973).

Boreal forests are adapted to high disturbance because of a wide genetic variability within its

few species (Thompson et al., 2009) where the functioning of boreal forests is more tied to its

species composition rather than its climate (Chapin & Danell, 2001). During this succession

in the 10-30 years the species richness of vascular plants increase. In warmer sites

intermediate deciduous trees are part of the succession while in more northern boreal forests

few coniferous species of dwarf shrubs persist in the understory. Both cases show a

decrease of vascular plant species diversity while non-vascular plants generally increase

through the progress of succession in boreal forest (Chapin & Danell, 2001; Cleve & Viereck,

1981).

In the understory of a temperate beech forest, most plant traits showed a positive correlation

with the age of the forest. This study indicates that succession can support higher functional

diversity (Campetella et al., 2011) however knowledge of interactions between these traits is

rather sparse (Petchey & Gaston, 2006).

Primary forests or old-growth forests generally have a greater biodiversity then planted and

semi-natural forests. These differences in biodiversity make planted and semi-natural forests

more vulnerable for disturbances (Thompson et al., 2009) thus they need more specific

management measures. Some important management guidelines are setting natural forests

and processes as a model (Niemela, 1999; Thompson et al., 2009), controlling invasive

species and reducing reliance on non-native trees for wood production (Thompson et al.,

2009). The management should drive maintenance and recovery of goods and services. The

conservation of biodiversity must be ensured in this management in forests since forests

show potential in tempering global change (Nadrowski, Wirth & Scherer-Lorenzen, 2010;

Thompson et al., 2009).

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Global changes such as drought and presumed decreasing precipitation are suggested to

diminish growth limitations of forests, yet the higher CO2 levels and higher temperatures

would predict an increase in growth for trees on higher altitudes were open taiga systems

can be replaced by boreal forests (Thompson et al., 2009).

Climate change can influence long-,mid- and short-term processes in forests. Short-term

processes are directly influenced by the frequency of storms and wildfires, herbivory, species

migration (Thompson et al., 2009). All these findings indicate the need for more research into

forest ecosystems (Bengtsson et al., 2000; Verheyen, Carnol & Branquart, 2010) with special

attention for successional diversity of the forest (Caspersen & Pacala, 2001).

Investigating forest ecosystem functions is a long-term deal. The development of forests is

significantly longer than any other ecosystem. There for it is important to monitor

experimental sites over numerous years for ecological long-term research. The results from

these researches are crucial to understanding forest development (Harvard Corporation,

2011). Doing research on experimental sites however one must be aware that most

ecosystem services are still evolving. For example the net ecosystem productivity is usually

found to be positive between the age of 15 and 800 years. This would imply that carbon

dioxide accumulation does not override carbon outputs (carbon output of soils included) in

roughly the first 15 years. These numbers are dependant of various factors such as climate,

nitrogen deposition (Luyssaert et al., 2008) and type of management (Gelman et al., 2013)

however effects of management are not always significant (Hoover, 2011).

2.3 Arthropod diversity in forest vegetation

Arthropods represent about 78% of all described species in the Animalia kingdom on earth

representing at least 1,3 million species (Zhang, 2013). Most researches deal with the

damage in forests caused by arthropods. A research in arthropod diversity in tropical forests

suggested that plant diversity can be a predictor for arthropods species richness and this not

only for herbivore arthropods (Basset et al., 2012). These findings enforce why arthropod

diversity is of importance in diversity research thus why it is involved in the hypothesis of this

work.

2.3.1 Arthropod morphology and taxonomy

Arthropods (Arthropoda) can be separated in five groups based on common ancestors (de

Jong, 2013; UCMP, 2004):

chelicerata (sea spiders, horseshoe crabs, scorpions, ticks, mites and spiders)

myriapoda (centipedes and millipedes)

trilobites (fossil group)

hexapoda (insects and their wingless, six legged relatives)

crustacea (crabs, lobsters, shrimps, barnacles, and many others)

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Typical morphologic characterisations of arthropods are bilateral symmetry in body and

mouth parts, segmented body, hard exoskeleton, jointed legs and multiple pairs of legs

(UCMP, 2004). Arthropods can further be classified in orders, families, genera and species.

In the past arthropods were classified based on degrees of similarity between species. The

study of relationships based on degrees of similarity is referred to as phenetics. Recently

however cladistics, the study of species classified by their pathways of evolution, are

implemented for the classification of organisms based on ancestors-descendants

relationships (Opperdoes, 1997). Eventually cladistics became general in use for systematic

work with the emergence of the polymerase chain reaction (PCR) amplifying DNA-

sequencing and the quick evolution of computer programs capacity (Manktelow, 2010). It is

because of this system that former groups are now classified under different names.

The Hemiptera can be divided into suborders Homoptera and Heteroptera. These suborders

were based on the morphology of the front pair of wings (Meyer, 2009). The ancestor-

descendants relationships however resulted in four suborders instead of two being

Cicadomorpha (including cicada families), Fulgoromorpha, Sternorrhyncha (including the

psyllid and aphid families) and Heteroptera (de Jong, 2013; Dietrich, 2005).

2.3.2 Trophic levels and functional groups

As earlier mentioned, biodiversity can be expressed not based on an individual species but

on the functions of certain species or their traits. It is convenient to make certain

classification of ecological groups. Guilds are groups of species that profit from the same

class of resources in a similar way or species that overlap significantly in their niche

requirements (Root, 1967; Simberloff, 2009). These groups act independent to taxonomical

differences between species (Root, 1967). Wilson (1999) names these guilds alfa guilds with

certain similar characters. Alfa guilds are distinct by their diet or type of nutrition. Each guild

lives from its typical resource. These species occur together with unlimited resources, while

limited resources induce competition between these species (Wilson, 1999).

Looking at energy flows in an ecosystem it can be more interesting to consider trophic levels

instead of guilds however some scientists find this concept to imprecise (Burns, 1989).

Trophic interactions have been studied by ecologists which resulted in controversial

(Hairston et al., 1960) and counter controversial research (Murdoch, 1966) in the past. The

hypothesis that trophic structure of an ecosystem controls the fraction of energy consumed

has continued research ever since (Hairston, Jr. & Hairston, Sr., 1993).

In every trophic level organisms share the same type of nutrition. Examples of trophic levels

are plants, herbivores, parasitoids (or parasites) and carnivores (or predators) (Price et al.,

2011). P.W. Price (2011) has set up an example of a food-web with four of these trophic

levels in Figure 4 indicating the complexity of communities. In this community the

decomposers are not integrated however they are involved and dependant of all these

trophic levels for detritus (waste products of animals and plants). Chemical communication is

http://www.faunaeur.org/full_results.php?id=15867



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proven present for certain insects. Moreover these signals can be interfered or regulated by

third individuals (Price et al., 2011). The complexity of this matters shows that trophic levels

must be viewed between species rather than higher taxa. Additionally the connection

between above ground and below ground trophic levels is poorly studied (Bardgett, Wardle &

Yeates, 1998).

Figure 4. Semiochemically mediated interactions among members of four trophic levels,

based on a composite of examples in the literature. The interactions between trophic levels

are indicated with arrows. The bold solid lines indicate attraction with various biochemicals or

body odors (e.g. 1, 4, 6). Thin solid lines with arrows (e.g. 3, 5, 7, 9). Thin dashed lines show

interference effects in other interactions (e.g. 2, 12, 19) (Price et al., 2011).

All these factors explain why several theories are described to explain the regulating

processes of communities yet none have really become widely accepted. Bottom-up effects

from plants and top-down effects are briefly explained.

Bottom-up effects are changes in population dynamics of higher trophic levels caused by the

primary trophic level, the host plants (Price et al., 2011). An example is the Sycamore aphid

(Drepanosiphum platanoides) reacting on the soluble nitrogen availability in the leaves of

Acer pseudoplatanus (Dixon & Mckay, 1970). The top-down effect is caused by influences of

natural enemies on lower trophic levels.

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2.3.2.1 Herbivores

Sap feeders or fluid feeding arthropods extract fluids from a plant as their primary diet while

leaf chewers and leaf minners obtain the organic matter. All these groups belong to the

herbivores trophic level 2 in Figure 4. The Hemiptera order inherits all phloem feeders within

the Insecta class. Hemipteran mesophyll feeding insects (certain Heteropterans and

Thysanopterans) are also considered sap feeders (Wheeler, 2001) together with cicadas

feeding from the xylem of plants (Price et al., 2011).

Several species of the Thysanoptera and Lepidoptera insect orders also consume saps but it

is not an essential component of their diet. Besides phloem feeders there are nectar and fruit

feeders tending to be rather mutualistic then antagonistic with its hosts (Douglas, 2006).

2.3.2.2 Parasites

Parasites harm their hosts without killing them while parasitoids destroy their hosts through

the development. Moreover their body size is relatively large compared to their host and they

usually host within the same taxonomic class (Doutt, 1959). Especially insects are known to

live in or on their host plant and thus inflict damage to their host (Campbell et al., 2008; Price

et al., 2011). The complexity of parasites unravels when higher trophic levels are considered.

Figure 4 indicates various interactions between herbivores, parasitoids and hyperparasitoids

including interactions within their trophic levels (Price et al., 2011).

A few orders of arthropods such as the Diptera and Acari order contain parasites species

with vertebrates as hosts (O‟Donoghue, 2009a, 2009b) while several parasitoid species in

orders such as Hymenoptera are of significant economic importance (Doutt, 1959).

Parasites are dependent of certain trophic levels for their nutrition. Research on interactions

with herbivores proofs that parasitoids (from the Hymenoptera order) decrease when climate

variability increases. This suggests that the regulating role of parasitoids weakens, predicting

more herbivory outbreaks in the future (Stireman et al., 2005). As already mentioned the right

management may temper certain changes in climate (Nadrowski et al., 2010; Thompson et

al., 2009).

2.3.2.3 Predators

Typical groups with predacious behaviour are spiders (Araneae order), Opiliones order,

Coccinellidae (lady bugs) and Carabidae (Ground beetles) (Coleoptera order). Arthropod

orders with multiple functions (e.g. Diptera) within them usually have divers subgroups (e.g.

Suborder, superfamily, family) with their according diets.

2.3.2.4 Decomposers

Detritivores have the same resources as decomposers (Capinera, 2008). Decomposers drive

important ecosystem functions such as organic matter turnover and nutrient cycling. The

abundant character of decomposers enforced these functions. Furthermore research has

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suggested synergistic effects from decomposers to the food quality and availability of aphids

(Eisenhauer, Hörsch, Moeser & Scheu, 2010).

An example of familiar arthropod decomposers are the Collembola. Most Collembola species

are soil or litter dwellers, whilst only few species live on the surface or in the vegetation

(mainly Entomobryidae and Symphypleona). They feed themselves with a variety of

resources like fungi, bacteria, exoskeletons and primarily vegetable litter or detritus

(Castaño-Meneses, 2004; Sharma, 1964).

2.3.3 Associated arthropod diversity in tree stands

The associated diversity is the surplus of biodiversity gained from a planned diversity. In a

planned diversity a site is planted or kept with respectively plants or animals for a certain

purpose (Vandermeer, 2011). The considered elements of the planned diversity in this

paragraph are tree species.

Some studies show positive effects on associated arthropod diversity in not only a greater

diversity of species but also diversity in genes of plants in a planned diversity. In the studies

to determine the influence of genotypic diversity a single plant species is considered with

variable genotypic diversity. For example research of genotypic variations of Oenothera

biennis have shown relationships between arthropod richness, evenness and proportional

diversity (McArt, Cook-Patton & Thaler, 2012).

In a study on ground-dwelling arthropods the expected relationship between genotypic

diversity of Populus tremuloides and arthropod diversity wasn‟t achieved. The environmental

stress, more specific well-watered or limited-watered blocks, was substantially responsible

for changes in the associated ground-dwelling arthropods diversity (Kanaga et al., 2009).

Studies on pest control however were beneficial for analysis of effect on associated diversity.

Many of these studies resulted in the use of biological predators to suppress pest species in

agroecosystems (Cabello et al., 2009; Snyder & Ives, 2009; Winder, 1990). In the south of

the Appalachian, mountains measurements of arthropods indicated high differences in

environmental conditions between young developing forest patches (Shure & Phillips, 1991)

All these studies point out different factors to take in account which complicates the research

to identify if species are linked to a planned diversity.

2.3.3.1 Insect herbivory in forest stands

Through evolution plant and herbivorous insects have made adaptations for survival. Plants

have developed defensive mechanisms in their morphology and chemical compounds.

Secondary metabolites (chemical compounds not involved in primary processes of the plant)

are the result of selective evolution in which herbivory is an important factor. Herbivory can

occur in different ways and can be caused by different functional groups. It can cause plant

species to stop expanding, eliminate certain plant species or work as a selective tool (Price

et al., 2011). Several parameters can influence herbivore behaviour of arthropods in which

http://eol.org/pages/8634/overview/

http://eol.org/pages/2765766/overview/

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plant barriers are suggested to play an important role in insect herbivory. Various factors

such a mechanical and allelochemical defences which depend of the plant species are of

particular interest when considering insect herbivory (Price et al., 2011).

Certain mechanical defences have indicated how certain functional groups of herbivorous

insects feed from them. Research on leaf strength indicated two significant negative

correlations between the density of insects and the force to tear, and work to sheer leafs.

The mechanical trait, punch strength of leafs, however did not indicate a significant

correlation with the density of sucking insect where chewing insects did (Peeters, Sanson &

Read, 2007).

Atmospheric nitrogen deposition is thought to be a predictable or explanatory factor for

spatial patterns of herbivorous insects in a research done in the northern east of the USA.

The results for birch trees at 1200 m height indicated a higher leaf nitrogen level then birches

on 600 m height (Erelli, Ayres & Eaton, 1998). This shows how geographical differences can

have an impact on herbivore behaviour.

Results of herbivory are not only visible in damage to foliage but can also indirectly cause a

lower nitrogen deposition. Research on nitrogen deposition influenced by herbivores was

done in 2 sites with Quercus petraea (60%) and Fagus sylvatica (40%),deciduous forest, and

Picea abies (90%),coniferous forest. Excretions of phytophagous insects such as

Lepidopterous larvae and aphids promoted growth of epiphytic micro-organisms. Trees

infested with epiphytic micro-organisms showed a lower deposition of inorganic nitrogen

(NO3- and NH4+) during June and July (Stadler, Solinger, & Michalzik, 2001). Influences of

lower deposition on tree growth behaviour weren‟t analysed in this research however chronic

atmospheric nitrogen inputs can increase the nutritive value of foliage (Erelli et al., 1998)

which is favoured by herbivores.

Differences in nitrogen are also indicates in species of successional boreal forest (. Early

succesional species generally have higher rates of nutrient uptake and growth, are more

palatable to herbivores, and have higher litter quality than late successional species (Chapin

& Danell, 2001)

Polyphagous insects tend to adapt their diet targeting a constant dry matter intake. Since dry

matter is highest in the shoots of the above biomass of a tree (Mátyás & Varga, 1983) this

will be their preferred habitat. When different tree species are involved the polyphagous

insect (a scavenging moth larvae) consume the tree species with lower quality foliage at

faster rates then high quality foliage. This change in consumption is referred to as

compensatory feeding (Myers & Virginia, 2000; Slansky & Wheeler, 1992).

However Jactel & Brockerhoff found increases in herbivory of oligophagous insects in

monocultures compared to mixed tree stands yet effects of polyphagous insects on herbivory

showed variable results. Furthermore taxonomically distant tree species showed greater

30

diversity effects in herbivory in tree arrangements with more distant taxonomical trees (Jactel

& Brockerhoff, 2007).

Research of a cereal aphid, a pest species, indicates that the density of polyphagous

predators was lower where aphid density was highest (Winder, 1990). In the same order

(Hemiptera) polyphagous predatory Heteroptera (e.g. Nabidae and Reduviidae) show

potential influence in controlling aphids and psyllids in agroecosystems (Cabello et al., 2009;

Cardinale et al., 2003).

2.3.3.2 Predatory arthropods in forest stands

The bottom-up regulation theory in trophic levels has been explained in paragraph 2.3.2.

Following this perspective, predators can show different behavioural patterns. In theoretical

models predators within the same guild (alpha guilds) can live together in which case the

prey distribution is assumed equally. When prey shortage occurs intraguild predation and

cannibalism is likely to be in favour between species with a shared prey. In the first case one

predator species (intraguild predator) will feed from the other (intraguild prey). These

changes in interactions make it possible for the shared prey to become more abundant in

presence of intraguild predators. Another possibility is a relaxed predation. This theory does

not always proof itself in experimental studies (Price et al., 2011).

In experimental sites in Finland ground-dwelling arthropods (ants, spiders, opilionids,

carabids, staphilionids) were analysed to determine differences in abundance of arthropods.

Ants seemed to occur randomly. Abundance of staphylinids, opilionids and carabids varied

greatly between monocultures and different tree species while spiders and ants did not show

much differences in abundance. Effects of tree age were rather small compared to the

effects of plot size. Analysis on tree species levels showed more variability in effects of

divers stands on predator abundance (Vehviläinen, Koricheva & Ruohomäki, 2008).

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3 Materials and methods

3.1 Study area

The FORBIO project is, included in the TreeDivNet network together with similar projects, the

largest project on ecosystem research worldwide. The projects consist of observational and

experimental sites with planted forest communities and their species in certain

arrangements. TreeDivNet enables the sharing of knowledge and datasets over all research

projects. The network aims to strenghten cooperation, support the exchange of experiences

and share results to promote meta-analyses (Verheyen, 2012).

Over 600,000 trees were planted over nine different locations in Finland (1999), Panamá

(2001), Borneo (2002), Germany (2003 and 2005), France (2007-2008), Canada (2009),

China (2009) and the FORBIO project in Belgium (2009). Figure 5 shows the location of the

projects in the TreeDivNet network with their according supervising researchers.

Figure 5. Location of the nine research projects that make up the TreeDivNetwork, the

largest terrestrial ecology project of its type (Verheyen, 2012).

32

In Belgium 22% of land is covered with forests, Wallonia (16845 km²), the southern part of

Belgium represents 78% of these forest in Belgium (Koninklijke Belgische

Bosbouwmaatschappij, 2000).

Figure 6 illustrates the three locations of the FORBIO-project in Zedelgem, Hechtel-Eksel

and Gedinne. The town name their location was obtained for the three locations part of the

FORBIO- project in Belgium. Sites in Zedelgem and Hechtel-Eksel were respectively planted

in 2009 and 2011. The two sites in Gedinne, named Gribelle and Gouverneur, were planted

in April-May 2010 (Table 2).

Figure 6. Map of the three locations of the FORBIO-project in Belgium (Verheyen et al.,

2013). The black points indicate the position of the site.

33

The study area consists of 2 sites named Gribelle and Gouverneur presented in Appendix A-

I. These sites are property of the village Gedinne located in Wallonia. The tree species

applied in the FORBIO project in Gedinne are Acer pseudoplatanus (sycamore maple), Larix

x eurolepis (hybrid larch), Pseudotsuga menziesii (Douglas-fir), Quercus petraea (sessile

oak) and Fagus sylvatica (common beech) with different provenance. Fagus sylvatica is also

planted in the site at Zedelgem (West-Flanders) while Pseudotsuga menziesii and Quercus

petraea are included in the project in Hechtel-Eksel (Limburg). The former tree species on

the site was spruce until 2005 (see Table 2).

Table 2. Summary of characters of the FORBIO-project sites Zedelgem, Gedinne and

Hechtel-Eksel (Verheyen, Ponette & Muys, 2011).

34

3.1.1 Plots

Both sites of the experiment (4,5 ha each) have been planted with trees in a certain

arrangements and with different diversity level, ranging from one until four different tree

species. Each site consists of 22 plots with the size of 42 x 42 m² (28 x 28 trees). Due to site

constraints, some plots in Gouverneur were smaller (42 x 37.5 m²) and planted with less

trees (25 x 28 trees).

There were twenty different species combination in both sites with two additional

monocultures of Fagus sylvatica of French and German provenance. The details on

provenances of Fagus sylvatica are illustrated in Table 3.

Table 3. Overview of the characteristics of the trees planted on the FORBIO-project sites in

Gedinne (Verheyen et al., 2010).

Plot numbers in Gribelle started from 1 until 20 with 2 additional monoculture Fagus sylvatica

(plots 43 and 44) of different provenance. Plot numbers 21 until 42 with plot 38 and 42 being

Fagus sylvatica of different provenance are established in Gouverneur. Appendix A-I in

represent respectively experimental plots arrangements in Gribelle and Gouverneur with its

plot number acquired by GPS point location.

The following Table 4 summarized indicates a balanced distribution with ten plots for every

tree arrangement with four monoculture plots of Fagus sylvatica trees with provenances

indicated with an asterisk.

Table 4. Summary of plots with different tree arrangements. The asterisk indicates the extra

Fagus sylvatica plots with different provenance.

Tree arrangement Gribelle Gouverneur Total

1 species 5+2* 5+2* 10+4*

2 species 5 5 10

3 species 5 5 10

4 species 5 5 10

Total 22 22 44

35

All trees of the FORBIO project have been given a tree identification number (Tree_ID) in a

database. Four sub-plots including each 16 trees with presentable trees have been assigned

to each plot. In plots with monocultures the sub-plots were symmetrically chosen.

The sub-plots assigned to plots with mixed stands of two, three and four species were

selected based on the most diverse and equally possible combination of tree species. An

example of these sub-plots is given in Figure 7. Every colour represents a tree species. In

monocultures the schematic representation will typically be in one colour. The sub-plots

consist of four squares of each four trees, with the most different tree species depending of

the tree arrangements.

Figure 7. Plot 9 with mixed tree species Quercus petraea (red), Acer pseudoplatanus

(yellow) and Pseudotsuga menziesii (lila).

3.1.2 Site condition

In the end of July and start of August certain plots were overgrown with ferns partly rising

above the tree canopy of deciduous tree species. These plots were mainly positioned along

borders of the sites. Examples are Plots 1, 2, 18, 19, 21, 22, 24, 40 and parts of plot 27, 37,

41, 43 where Fagus sylvatica, Acer pseudoplatanus and Quercus petraea were partly

overgrown due to a slower growth compared to Larix x eurolepis and Pseudotsuga menziesii.

Out of observations the trees in plots on the right in Gouverneur were smaller the left plots

illustrated in Figure 8 and Figure 9.

36

Figure 8. Plots 21 till 29 on the site Gouverneur surrounded with its fence. The trees have not

yet reached higher than the surrounding vegetation. The picture is taken while waiting for a

weather depression to pass by (24 July 2013).

Figure 9. Plots 30 till 42 on the site Gouverneur surrounded with its fence. The trees have

reached higher than the surrounding vegetation in most plots (24 July 2013).

In Gribelle there were birches with heights of max. ≈2 meter between the blocks of plots 1 to

9, 10 to 17 including plot 43 and 44 and 18 to 20. This indicated the semi-natural aspect of

the sites. Every year the sites are mowed, however the samples were taken in mid-summer

before mowing.

37

The applied tree species in the setup were Acer pseudoplatanus (sycamore maple), Fagus

sylvatica (common beech) with autochthon and foreign genetics, Larix x eurolepis(Hybrid

larch), Pseudotsuga menziesii (Douglas-fir), Quercus petraea (sessile oak).

The general condition of trees in Gouverneur seemed more developed then trees in Gribelle.

The coniferous trees (Larix x eurolepis and Pseudotsuga menziesii) showed generally faster

growing patterns than the deciduous trees (Fagus sylvatica, Quercus petraea and Acer

pseudoplatanus) on both sites.

From field observations (5 August 2013) the Acer pseudoplatanus species were damaged

particularly in Gribelle where the first year sprouts may have suffered from the late freezing

last winter. Nevertheless most of these trees indicated sprouts at the bottom of their stem.

The tree that appeared to be developed the best was Larix x eurolepsis. On Pseudotsuga

menziesii potential damage was visible in the young numerous sprouts yet the main stem

and side branches were usually viable in contrast with Acer pseudoplatanus.

38

3.2 Fieldwork in Gedinne

The measurement of the trees in the field must represent the plot in the best possible way.

The word sample is defined as a synonym for a measurement of one tree while sampling will

be utilised to describe the measurement itself.

To improve the objectivity of the sampling method, trees were selected in the subplots in an

assigned list prior to the arrival on the field. This to ensure a random selection. How these

samples were gathered is explained in paragraph 3.2.1.

In every plot a certain amount of trees must be sampled to represent the plot. For

convenience the unique tree codes as illustrated in the cells of Figure 7 and have been

replaced by own chosen digits to avoid errors in a complex tree code notation in the field. In

the data-analysis these chosen codes have been linked again to their unique codes.

3.2.1 Arthropod sampling method

There are different ways of gathering arthropods. In this project there was chosen to use a

sampling mothod with the „aspirator gun‟. The aspirator method is used to collect fragile and

fast arthropods (Tóth, 2000). This indicated that a large part of arthropods will be excluded in

these samples.

Arthropod sampling in Gouverneur and Gribelle was conducted using a modified Black &

Decker Aspirator of the type AV 1205 acquired from the company BioQuip Products (BioQuip

Products Inc., 2003). Two batteries of 12V were sufficient to take samples for a full day.

The filter cloth (the use is described in the procedure) was recovered from old sheer curtains

(Dutch: transparante gordijnen) in the laboratory in Gontrode. The distance between two

threads was between 0,2 and 0,3 mm with 9 holes per mm².

To take a sample from a tree, or simply sample, the next procedure was followed.

The tree from the assigned list was retrieved in the field. An alternative tree was

selected when the assigned tree was not viable or deceased.

The aspirator‟s modified tube was covered with the curtain cloth, as a filter, making a

reservoir inside the transparent tube so arthropods and organic materials can be

stored.

The aspirator was enabled working from the bottom on the stem to the top, continued

with the big branches followed by the smaller branches.

Special attention was given to the bottom of the leaves in the repeated down-upwards

movements.

39

All the trees were treated with the aspirator over an average time span of 30 seconds,

this was sufficient to cover most above ground branches of the trees.

Figure 10. Sampling an Acer pseudoplatanus on the site Gouverneur with the aspirator with

a first swift on the tree stem from bottom to the top (yellow arrow).

A clipper was used to close the filter cloth while the aspirator kept running to avoid the

escape of arthropods and in particular flying arthropods.

The filter cloth was labelled accordingly for further efficient identification and the

actual sampled tree ID was confirmed or replaced in the assigned list on the field.

40

3.2.2 Daily sampling

All samples were taken in mid-summer in the months July and August 2013. With six days of

sampling all 176 samples were gathered from the 44 plots. The sampling took around 30

hours on the field of which most time was spend locating the assigned tree in the plots. Table

5 gave a summary of details for each day. The details on weather conditions are described in

paragraph A.2 in Appendix A on page 7. In Appendix A-II the weather conditions are

summarized.

Table 5. Sampling dates in Gedinne with a summary of the weather conditions.

Date Site Samples Plots Time[hh.mm] Weather

23 July 2013 Gouverneur 24 28 till 33 12.00-16.00 Sunny

24 July 2013 Gouverneur 24 21 till 24, 26, 27 10.00-16.00 Variable

25 July 2013 Gouverneur 40 25, 34 till 42 10.00-17.00 Variable/Sunny

26 July 2013 Gribelle 12 1 till 3 13.30-16.00 Sunny

5 August 2013 Gribelle 52 10 till 20, 43, 44 09.30-16.00 Sunny

6 August 2013 Gribelle 24 4 till 9 09.30-14.00 Variable/Sunny

3.3 Identification of the arthropods

There were a few questions to answer before starting the identification. Due to the lack of

professional skills in identifying certain arthropods, in particular larvae stadia of the

arthropods, there was decided to identify the arthropods up till family taxon, where this

seemed useful, to group the individuals into trophic levels.

The direct identification of arthropods after sampling was not possible due to field

circumstances. The next procedure was followed to identify the arthropods.

All filter clothes were gathered daily and put in a freezer at an average temperature of

-18°C which ensured intact arthropod bodies for an efficient identification.

The arthropods were removed when fully paralyzed (> 4 hours).

The sample container was labelled accordingly with the labelled filter cloth.

The filter cloth was opened and all material was carefully gathered into the labelled

sample container.

A solution of 30% water and 70% alcohol was added until all material was soaked.

The microscope was set up and the solution with all material was added into a Petri

dish. All leftovers were added by spraying solution inside of the sample container

(see Figure 11).

41

Figure 11. Example of the material of a sample in the Petri dish ready for the first

identification round. The label is number respectively with project name (Gedinne, G),plot

number (plot 34), tree identification number (28) and tree species from the sample (Quercus

petraea, Q).

All troublesome organic materials were removed for efficient identification and

counting of the arthropods.

All arthropods were identified into orders and individually counted.

The arthropods were brought into labelled plastic vials with the same solution for

possible further identification into families or other classifications. Each time the Petri

dish was thoroughly checked for remaining arthropods.

The labelled plastic vials were closed and gathered in a box for every five plots or 20

samples.

The second round of identification was then continued for further classification into

trophic functional groups. This ensured a second counting diminishing the chance for

calculating errors.

All labels were checked and gathered into boxes for later consultance.

All 176 tree samples were submitted for a screening with an optical microscope. For the

identification an optical microscope (Motic DM Digital Stereo Microscope Series) (Motic

Microscopes, 2010) was used with a zoom range (x10 till x40) sufficient to identify the

arthropods (> 0,2 mm) caught in the filter cloth. All identifications were done in the ForNaLab

of University Ghent in Gontrode. The time span of the identification of all arthropods sampled

in Gedinne was roughly in between 100 and 120 hours.

42

The arthropods were digitalised in tables Excel 2007. First arthropods were separated into

orders continued with a more thorough look at the unidentified arthropods. After the first

round of identification the arthropods were divided into subgroups relevant for resource

based ecological grouping since the literature showed that identification into taxa such as

orders does not take similarities in trophic levels within communities in account (see

paragraph 2.1.3.1). The whereabouts of the tropic levels have been explained in the

literature in paragraph 2.3.2 on page 25.

All identified arthropods could be classified in the following eleven orders:

Hemiptera

Collembola

Acari (former order, recently named as Infraclass (de Jong, 2013))

Opiliones

Araneae

Thysanoptera

Hymenoptera

Lepidoptera

Coleoptera

Neuroptera

Psocoptera

The classification into orders and trophic levels was possible through several sources of

information. In particular the larvae stadia could be identified into orders with the syllabus

from Theodore Heijerman (Heijerman, 2011) and the identification experience of Pallieter De

Smedt and Nuri Nurlaila Setiawan. What follows is a list of all used sources to identify the

arthropods.

Beuk, P. (2013). Diptera.info. Retrieved December 12, 2013, from http://www.diptera.info

Chinery, M. (2012). Nieuwe insecten gids. (G. Meesters, Ed.) (Ninth revi., p. 320). Utrecht:

Tirion Uitgevers.

De Jong, Y. S. D. M. (2013). Taxon tree. Fauna Europaea. Retrieved December 04, 2013,

from http://www.faunaeur.org/taxon_tree.php?id=0,1,54070,2

Grau, A., & Köhler, D. (2010). Heteropterologie - Die Wanzen Europas. Retrieved October

22, 2013, from http://heteropterologie.de/familienbestimmung.php

Heijerman, T. (2011). Handleiding Faunacursus Onderdeel Systematiek & Diagnostiek

(Zoölogisch deel Flora & Fauna, BIS-10306). Wageningen: Wageningen University.

43

3.4 Data analysis of the sampled arthropods

The main goals of this work was to analyse the differences in arthropod diversity in different

tree arrangements. The Shannon Index for was introduced to quantify the arthropod diversity

based on their taxonomical orders. The values of the Shannon index were tested on

differences between the four tree arrangements (per plot) and differences between tree

species (per individual trees).

Non-parametric Kruskal-Wallis tests and Wilcoxon Signed Rank Tests were applied to detect

differences in medians where residuals of the raw data were not normally distributed. When

the raw or transformed data approached normality, an analysis of variance (ANOVA) and t-

tests were performed to detect differences in means (Zar, 2010).

The open source program R Studio (RStudio Inc., 2012) was used to analyse the acquired

data from the identified arthropods in all 176 samples. The full details of all analyses were

added in Appendix B in the accompanying Appendix of this work. The graphical presentation

of data was made possible with the software of Microsoft Excel 2007 and RStudio (Microsoft

Corporation, 2008; RStudio Inc., 2012).

During the analysis of the data with .csv files (Comma separated values) the point (.) was

used as decimal sign instead of the comma (,) and thus it will be applied for all numbers with

decimal signs in this work.

3.4.1 Acquiring a balanced design

Balanced designs have the same number of data in each defined group for implementation

of statistical comparisons. With equal groups statistical tests have the most power (Zar,

2010). The second advantage was the possibility to perform several post-hoc tests on the

data. As an example the use the post-hoc Tukey test for a parametric one way analysis of

variance or simply one way ANOVA was possible due to this balanced design.

To get a balanced model the Fagus sylvatica plots with difference provenance (plot 28, 42,

43 and 44) were excluded from the data. This adjustment resulted in two balanced models

ready for statistical analysis. A summary of these balanced designs is demonstrated in

Table 8 and Table 6.

Table 6. Balanced design for statistical analysis with the variable tree arrangement in

Gedinne (Gouverneur and Gribelle).

Tree arrangement Plots (samples)

1 species 10 (40)

2 species 10 (40)

3 species 10 (40)

4 species 10 (40)

44

The FORBIO-project in Gedinne is separated in two sites Gribelle and Gouverneur. Four

trees per plot were sampled with the aspirator. In the plots with a 3 species tree arrangement

the best possible choice of tree species to sample were chosen to balance the numbers of

tree species in Gouverneur and Gribelle. The sampled trees are summarized in Table 7.

Table 7. Sampled tree species respectively in Gribelle, Gouverneur and in Gedinne in total.

The numbers followed by the letter a represent additional Fagus sylvatica trees provenances

from Germany and France with each half of the sampled trees.

Tree species Gribelle Gouverneur Total

Acer pseudoplatanus 16 16 32

Fagus sylvatica 15+8 a 17+8 a 32+16 a

Larix x eurolepis 17 15 32

Pseudotsuga menziesii 16 16 32

Quercus petraea 16 16 32

Total 88 88 176

Table 8. Balanced design for statistical analysis with the variable tree species.

Tree species Samples

Acer pseudoplatanus 32

Fagus sylvatica 32

Larix x eurolepis 32

Pseudotsuga menziesii 32

Quercus petraea 32

45

3.4.2 Defining the variables and forms of data

During the analysis various variables were used to perform tests with. The calculated

Shannon index substituted twelve values of arthropod orders, simplifying our model to

perform parametric one way ANOVA test (Table 6). With this operation allot of information

on individual orders is lost however it gives more insight into the general trends of diversity

between different tree arrangements. Here these variables are explained in Table 9.

Table 9. Variables used in the statistical analysis.

Variable name Explanation

H

The calculated Shannon index based on the abundance and richness

of the arthropod orders.

exp_H

The exponential value of the Shannon index H represents the true

diversity of the arthropod orders or the effective number of orders

(Jost, 2006).

Species_Number

The grouping factor for different tree arrangements (monocultures,

two species, three species and four species).

Genus_ID

Grouping factor containing different tree species Acer

pseudoplatanus, Fagus sylvatica, Larix x eurolepis, Pseudotsuga

menziesii, Quercus petraea which are unique with their genera name

Acer, Fagus, Larix, Pseudotsuga and Quercus in Gedinne.

Site

The grouping factor with the sitename. There are two sites, Gribelle

and Gouverneur.

3.4.3 Overview of analyses

Five statistical analyses have been performed. The statistical analyses are summarized in

Appendix B-I in a schematic model. The numbers from 1 until 5 are each time mentioned in

the title that handles the particular analysis.

46

4 Results

4.1 Weather variability in Gedinne

The weather during the fieldwork was rather variable on certain days. On page 7 of the

accompanied Appendix the weather conditions are described and illustrated in Appendix A-II.

Furthermore the means and medians are illustrated in the boxplots in Appendix A-III and

Appendix A-IV. Both graphs indicate a similar trends. Although 24 July was not an ideal day

for sampling this was not the day with the least arthropods caught nor with the lowest

diversity in arthropods. The samples taken on 26 July had a higher mean and median

compared to other sampling dates yet only presented 12 samples whilst the other days

represented at least double as much samples (see Table 5).

Since on most days various amounts of samples and less than 30 samples (n < 30) were

taken no further statistical analysis was performed in identifying differences in means or

medians due to unbalanced designs (Zar, 2010).

The values of samples acquired from Gribelle show particularly more outliers in Appendix A-

III while the boxes (50% of the data) on 5 and 6 August in Appendix A-IV describe a larger

area indicating larger varieties.

47

4.2 Arthropod diversity linked to the tree arrangement [1]

To detect differences in arthropod diversity the means of the Shannon‟s Indices were

calculated for every sampled tree based on the amount of arthropods found in every order.

The normality of residuals was described graphically in R Studio with Q-Q plots. These plots

show how good the data fit with a normal distributed function in the graphs in Appendix B-II

and Appendix B-III. The tails don‟t not seem to follow normality however the center is close to

normality in all four tree arrangements. According to Zar (2010) an ANOVA with slightly non-

normal data still has power when homogeneity of the data is met together with a significant

result in the ANOVA (Zar, 2010).

The differences in medians of the four applied tree arrangements (with each 10 plots) in

Table 6 were tested with a non-parametric Kruskal-Wallis rank sum test since the data was

not normally distributed.

The equality of variation was tested and confirmed with the Levene‟s test for homogeneity of

variance. The overview of the analysis with R Studio was added in Appendix B-IV on page

12 of the accompanied Appendix.

To test the equality of variances a Levene‟s Test for homogeneity was executed with H

(Shannon index) as the response variable and Species_Number as the factor defining the

groups. The p-value (p = 0.2428) of this test was higher than the significance level (p = 0.05).

Based on a significance level of 0.05 the Null hypothesis is kept. The variance of the

calculated Shannon index within all tree arrangements are equal (H0).

A Kruskal-Wallis test with the Shannon index (H) as dependent variable and tree

arrangement (Species_Number) as response variable resulted in a detainment of the null

hypothesis (H0), the medians of the Shannon index in all tree arrangements are equal based

on a significance level of 0.05 (p = 0. 0.3785 > 0.05). Figure 12 illustrates the medians of the

four tree arrangements

48

Figure 12. Arthropod diversity based on the Shannon index between tree arrangements

respectively from monocultures (1 species) till 4 species tree arrangements. The bold

horizontal line represents the median of the Shannon index for each tree arrangement. The

separate dots are outliers.

49

4.3 Diversity of arthropods linked to the tree species [2]

During the fieldwork 176 trees were sampled with an equal ratio in tree species. Since five

different tree species are planted in Gedinne the arthropod data was grouped by tree species

to detect differences in arthropod diversity (quantified with the Shannon index) between tree

species. An ANOVA was implemented to compare the means of the five tree species. The

tree species Acer pseudoplatanus, Fagus sylvatica, Larix x eurolepis, Pseudotsuga menziesii

and Quercus petraea are the five groups of the independent variable Genus_ID. A summary

of the balanced design used for the ANOVA is given in Table 8. The full details of the

analysis are added in the accompanied Appendix B (B.3).

Similar to the tests for difference in arthropod diversity in tree arrangements the normality

and homogeneity of variances was tested on a 0,05 significance level. The Shapiro-

Wilkinson test for normality indicated that one of the five tree species was not normally

distributed. The variance within the five tree species were equal. The p- value 0,0446 for

testing the normality of the Shannon index grouped by Acer pseudoplatanus was close to

accepting normality (p > 0,05).

The Acer pseudoplatanus data can either be excluded or the parametric ANOVA can be

executed without completing the condition for normality with the Shapiro-Wilkinson test. If

biostatistical data is slightly non-normal but the data within the tree species are homogenous

the analysis of variance can be applied (Lantz, 2013; Zar, 2010). In cases of doubt the result

of the applied F test must be highly significant to make conclusions (Zar, 2010).

The Q-Q plot of the residuals of the Acer pseudoplatanus data confirmed that the data was

close to normal distribution. The parametric one way ANOVA was performed on the data with

the Shannon index (H) as dependent variable and the tree species (Genus_ID) as

independent or response variable in R Studio (RStudio Inc., 2012). The p-value (p = 0.00006

< 0.05) of this F test executed in R Studio resulted in the rejection of the null hypothesis with

a high significance. The means of the Shannon index differ in different tree species.

50

The Tukey post-hoc multiple comparison of means analysis indicated differences between

tree species. The test found significant difference in Shannon‟s indices between Quercus

petraea - Acer pseudoplatanus (p = 0.00002 < 0.05), Quercus petraea - Fagus sylvatica (p =

0.0188 < 0.05), Larix x eurolepis - Acer pseudoplatanus (p = 0.00002 < 0.05), and least

significant Pseudotsuga menziesii - Acer pseudoplatanus (p = 0.0473 < 0.05).

Figure 13. Boxplot visualizing differences in means of arthropod Shannon‟s diversity Index

between tree species marked by their genera in the x-axis. The red dot presents the means

of each species. Each tree species represents 40 tree samples (n = 40). The letters a, b, c,

d, e indicate which tree species do not significantly (p > 0,05) differ.

51

4.3.1 Differences in arthropod diversity between sites Gribelle and

Gouverneur [3]

The two former analyses are based on data from both sites. In this paragraph the differences

in means of the Shannon index will determined between the sites Gribelle and Gouverneur.

In the accompanied Appendix (Appendix B, page 16), Appendix B-VII illustrated the

residuals of the Shannon index data separated respectively by the sites Gribelle and

Gouverneur. The data representing 88 samples for each site was assumed normal because

of the high amount of data values (n = 88). Furthermore the points of the residuals in the

graphs are mainly within the boundaries (dotted red lines) to assume normality of the

residuals.

Appendix B-VIII illustrated that the variances of the data with Shannon index (H) values

grouped by their site are equal (H0) based on the Levene's Test for Homogeneity of

Variance.

The two sample t-test determined a difference between the means of the Shannon indices in

Gribelle and Gouverneur. The calculated mean values of the two groups Gribelle and

Gouverneur indicated that the mean of Shannon index is higher in Gribelle than in

Gouverneur (H1, alternative hypothesis).

4.4 Comparison of arthropod abundances

4.4.1 Comparison of arthropod abundance based on their orders

The two sites are compared in total arthropod individuals grouped by their taxonomic orders

in Figure 14. The four most abundant orders were Hemiptera, Araneae, Collembola and

Diptera presenting more than 83% of all arthropods in the 176 samples taken in Gedinne.

The Hemiptera (553 towards 226 individuals) and Diptera (255 towards 111 individuals)

arthropods occurred at least twice as much in Gouverneur while the Collembola and Araneae

respectively occur twice (260 compared to 644) and three times (97 compared to 297) as

much in Gribelle. All arthropods were grouped into their orders. Particularly in the Diptera

order several flies (47 out of 366 Diptera individuals) were not identified in further

classification due to their tormented bodies and/or insufficient experience in identification.

The 47 unidentified arthropods represent 12% of the Diptera and about 1.5% of all

arthropods.

52

0 100 200 300 400 500 600 700

Hemiptera

Acari

Opiliones

Araneae

Collembola

Thysanoptera

Coleoptera

Hymenoptera

Diptera

Lepidoptera

Neuroptera

Psocoptera

Sum of arthropod individuals

Ord

ers

of art

hro

pods

found in

all

sam

ple

s Gouverneur Gribelle

Figure 14. Comparison of the number of arthropod individuals (y-axis) classified into orders

(x-axis) found in respectively Gribelle and Gouverneur. The total number of individuals for

each order is mentioned above each bar.

4.4.2 Comparison of arthropod abundance based on trophic levels [4]

In the literature four trophic levels are discussed in 2.3.2, a more detailed description of these

groups linked to the data is provided in paragraph 4.4.4. Figure 15 illustrates the trophic

levels in both sites Gribelle and Gouverneur. The herbivores were largely present in

Gouverneur while predators and decomposers are more abundant in Gribelle.

As a first condition to determine if a parametric test can be implemented in the data the

homogeneity of the data of the four trophic levels was tested with four Levene‟s Tests for

Homogeneity of Variance (center = median) (Appendix B-XIV). The p-values of all four

trophic levels were higher than 0.05, indicating that within each trophic level the variances

were equal for each of the four tree arrangement (H0).

The Normal Probability Plots of the residuals of the herbivore data in Appendix B-XIII

submitted in the accompanied Appendix (page 20) followed the linear model much better

than the residuals of the raw data in Appendix B-XII. However the data tended to sequence

rather irregularly between -2 and -1 on the x-axis. These observations led to performing an

non-parametric Wilcoxon Signed Rank Test to determine the differences in medians of the

trophic levels in Gribelle and Gouverneur.

53

Figure 15. Bar charts explaining the arthropod abundance presence per trophic level (x-axis)

on the sites Gribelle and Gouverneur. Each bar represents the sum of 88 samples

independent of tree arrangement nor tree species.

54

The Wilcoxon Signed Rank Tests, four times executed for each trophic level, indicated

significant differences(p = 0.00036 < 0.05) in the medians of data of the herbivores in both

sites. The medians of the data of the decomposer trophic level differed also significantly ( p =

0.000028 < 0.05)

4.4.3 Diversity of arthropods based on Shannon index in Gribelle and

Gedinne

The arthropod diversity in the samples was quantified with the Shannon index using the

formula in Table 10. In this formula p represents the quotient of arthropod individuals in the

order and the amount of individuals found in that order. The number of arthropod orders is

the meaning of n in the formula, which is 11 for this dataset. The index was calculated for all

176 samples via R Studio with the vegan package (Oksanen et al., 2013).

In the literature questions arise in the use of diversity indices in paragraph 2.1.3.1. To

answer these shortages L. Jost (2006) brings up the term effective number of species. The

effective number of species is given by the exponential value of the Shannon index (H) (Jost,

2009). A more detailed description is given in Table 10.

Table 10. Conversion of common the Shannon index into the true diversity or the effective

number of species edited from L. Jost (Jost, 2009).

Index H Diversity in terms of pi

Shannon entropy H ≡

S

1i

ii plnp

exp (

S

1i

ii plnp )

The conversion of the Shannon index or the effective number of orders in case of the data

makes it easier to interpret these values.

55

The exponential values of the calculated Shannon‟s Indices are presented on the y-axis in

Figure 16. 9 out of 88 data points from the data in Gribelle showed an expected effective

number of species equal or higher than 6. Furthermore eight data points (out of 88) had

higher abundance in Gribelle. The data points of Gouverneur seem generally less scattered

compared to Gribelle.

0

1

2

3

4

5

6

7

0 10 20 30 40 50 60 70 80

Eff

ectiv

e u

mber of ord

ers

, Exp (H

)

Arthropod abundance

Gribelle

Gouverneur

Figure 16. Scatter plot of tree samples visualizing differences in variation between the sites

Gribelle and Gedinne. The exponential Shannon index in the y-axis and the arthropod

abundance in the x-axis. The sample colour indicates the site.

56

4.4.4 Arthropod abundance of trophic levels

The grouping of arthropods is taxonomically defined however a different approach in

grouping was made to get a rather ecological insight of the biodiversity level. The analysis of

differences in orders is not likely to provide us valuable information on these diversity levels.

The presented ecological groups of arthropods were closely related to Rootian guilds sharing

the same resources (Root, 1967; B. J. Wilson, 1999) yet no distinction was made in how they

feed on these resources. These kind of groups of species feeding on the same type of food

are part of the same trophic level (Price et al., 2011).

Hemiptera

HemipteraAcari Acari

Opiliones

Araneae

Collembola

Thysanoptera

Coleoptera

Hymenoptera

Hymenoptera

Diptera

Diptera

DipteraLepidoptera

Neuroptera

Psocoptera

0

100

200

300

400

500

600

700

800

900

1000

Herbivores Predators Parasites Decomposers

Art

hro

po

d in

div

idu

als

Trophic level

Figure 17. Arthropod individuals sampled in Gedinne. Each bar shows the arthropod

abundance of each trophic level with the arthropod abundance of each order within the

column of the trophic level.

57

4.4.4.1 Herbivores

The sap feeders and leaf miners mentioned in the literature were grouped together in the

trophic level herbivores even though they have different ways of feeding. Hemipteran sap

feeders were particularly present in Gouverneur. All identified Hemiptera were part of

suborders Heteroptera, Sternorrhyncha and Cicadomorpha formerly known as the

Heteroptera and Homoptera (Chinery, 2012; de Jong, 2013). The suborder Heteroptera

included both predaceous and herbivorous species. Predaceous species of the Diptera

identified with their developed robust rostrum are handled in paragraph 4.4.4.3. The

remaining 50 Heteropteran sap feeding individuals represented more than 5% of all

herbivores visible in Table 11.

The identified Homoptera (former suborder) were separated into aphids (Aphidoidae),

jumping plant lice (Psylloidae) and cicadas (Suborder Cicadomorpha) which included all

Homoptera found in Gedinne. These three groups are considered as the same trophic

functional group, the herbivores. The sap feeders represent almost 82% of the herbivores.

Additionally members of the Thysanoptera order were added to the herbivores. More than

half of the thrips individuals were found within the endosperm of grass seeds of the

vegetation surrounding the stem of the juvenile trees. The Thysanoptera order described

about 13% of all herbivore individuals.

Table 11. Herbivore individuals count in all samples in Gribelle and Gouverneur. Orders, and

if specified more detailed families information, are ranked according to their abundance.

Order Subgroup Individuals % Individuals

Hemiptera

Aphidoidae families 593 64.74%

Suborder Cicadomorpha 73 7.97%

Heteropteran suborder families 50 5.46%

Psylloidae families 33 3.60%

Total sapfeeding Hemiptera 749 81.77%

Thysanoptera Herbivorous families 126 13.76%

Lepidoptera Lepidoteran larvae and adults 41 4.48%

Total herbivore individuals 916 100%

Lepidopteran individuals found in Gedinne were very small (approximately 5-7 mm adults)

and about 50%, 20 out of 41, of the individuals were caterpillars or Lepidopteran larvae.

Useful identification characters were three pair of footed segments, a strongly developed

pseudopodia around their last segments and a proboscis (Dutch: roltong) (Heijerman, 2011).

Table 11 shows that the Lepidopteran larvae and adults present less than 5% (4.16%) of the

herbivorous arthropods in the tree samples.

58

4.4.4.2 Parasites

The identification showed that the appearance of arthropods can differ through evolution of

stadia particularly with Insecta. Parasites can have one or different hosts through their

evolution and live in or on the host they feed from (Chinery, 2012; Doutt, 1959). For example

the identified Hymenoptera adults (mainly parasitoids) were abundant while larvae (feeding

on plants) were seldom (3 out of 156 individuals) and not necessarily related to the caught

adults. Most of the adult Hymenoptera were identified as parasitic wasps from families

Ichneumonidae and Platygastridae (Beuk, 2013; Chinery, 2012).

The adult wasps had antenna similar to mosquitoes. A closer observation gave the chance to

observe either 4 wings (Hymenoptera) or 2 wings with 2 halters(Diptera) identifying them

easily into their appropriate order.

The mosquitoes just like the flies are part of the Diptera order. This order was by far the most

complex to identify into families with similar diets. The mosquitoes in most cases

recognizable by their long antenna and legs were considered parasites representing more

than 40% of their group. Predators and decomposers of the Diptera order found in the

samples are mentioned respectively in paragraph 4.4.4.3 and 4.4.4.4.

The Acari order was separated into predacious mites and parasitic mites(ticks) however

more than 95% of the Acari were ticks.

As the parasites are a complicated group, which is explained in paragraph 2.3.2.2 in the

literature, I have chosen to simplify certain groups, in particular the mosquitoes who have

diverse feeding behaviour within families and the Hymenoptera where all Hymenoptera

excluded by the easily identifiable Formidae family (ants) are considered parasitoids Further

more parasites and parasitoids are considered as the same group. parasitoids Hymenoptera

are however different from parasites in the way that they destroy their hosts through the

development. Moreover their body size is relatively large compared to their host and they

usually host within the same taxonomic class (Doutt, 1959).

Table 12. Parasite individuals counted in all samples in Gribelle and Gouverneur. Orders and

if specified more detailed families information are ordered according to their abundance.


Diptera Mosquitoes 171 42.86 %

Hymenoptera Parasitoid wasp families 156 39.10 %

Acari Ixodidae 72 18.05 %

Total parasite individuals 399 100.00 %

59

4.4.4.3 Predators

Clearly separated orders who are primarily predaceous are the Araneae (Spiders), Opiliones

and Neuroptera. The Araneae, the order of the spiders were abundant on both sites Gribelle

and Gouverneur. Individual sizes were approximately between 1-10 mm, legs included. The

two orders Opiliones and Acari, from the same class as the Araneae, presented less than 1%

of the predaceous individuals on both sites.

The Hemipteran predators, members of the families Nabidae and Reduviidae of which the

Nabidae also known as damsel bugs were most present. Figure 18 shows a Nabidae species

found in one of the samples.

Figure 18. Hemipteran predator of the Nabidae family (top) with developed rostrum, Jumping

plant lice (Hemipteran herbivore) and a winged booklice of the Psocoptera order. The orange

lines are the lines of millimetre paper (Zooming range ≈ x15).

60

The presence of numerous predatory flies in the samples suggested the need for further

identification into families. A notably amount of predaceous families were present such as

Empididae, Dolichopodidae, Asilidae, Phoridae, Syrphidae and Hybotidae with a percentage

of almost 20% of all the predators identified (Table 13).

Table 13. Predator individuals counted in all samples in Gribelle and Gouverneur. Orders



Araneae Araneae families 394 62.44 %

Diptera

Empididae 64 10.14 %

Dolichopodidae 42 6.66 %

Asilidae and Phoridae 12 1.90 %

Syrphidae 2 0.32 %

Hybotidae 1 0.16 %

Total predator Diptera 121 19.18 %

Coleoptera

Carabidae 37 5.86 %

Coccinellidae 16 2.54 %

Total predator Coleoptera 53 8.40 %

Hemiptera Nabidae and Reduvidae 30 4.75 %

Neuroptera Neuropteran larvae 15 2.38 %

Hymenoptera Formicidae 13 2.06 %

Acari Predatory families 3 0.48 %

Opiliones Opiliones families 2 0.32 %

Total predator individuals 631 100.00 %

4.4.4.4 Decomposers

Detritivores have the same resources as decomposers (Capinera, 2008) which is why they

are not separately handled. Scavengers are also included in this ecological group. The

Collembola order, the Sepsidae family, the Drosophilidae family and the Psocoptera order

(see Figure 18) were classified as decomposers based on their diet. The Sepsidae, more

specific Sepsis spp., found in the samples, generally feed themselves with ruminant dung

(Pont & Meier, 2002). The few observed Drosophilidae are mainly found on rotting fruit and

vegetal materials (Chinery, 2012) which is why they were rather classified as decomposers

instead of herbivores. The Collembola (≈ 95% of all arthropods) were notably present in the

tree samples.

Table 14. Decomposer individuals counted in all samples in Gribelle and Gouverneur. Orders


Order Family Individuals % Individuals

Collembola Collembola families 904 94.36 %

Diptera Sepsidae and Drosophilidae 27 2.82 %

Psocoptera Psocoptera families 27 2.82 %

Total decomposer individuals 958 100.00 %

61

4.4.5 Analysis of trophic levels linked to their tree arrangements [5]

The different tree arrangements (treatments), from monocultures and up to 4 different

species per plot, were used as grouping factor to detect differences between their trophic

levels. The composition of species in the tree arrangements were not taken in account.

Arrangements of two and three species have 10 (= C25 = C3

5) different combinations while

monocultures and four species tree arrangements have 5 (= C15 = C4

5 ) possible

combinations.

Figure 19 describes differences in average arthropod individuals with plot as a unit for the

four trophic levels herbivores, predators, parasites and decomposers for all four tree

arrangements in Gedinne. The y-axis shows the average expected number of individuals per

plot. This value, gained by dividing the sum of each trophic level in the fourteen monoculture

plots by 14, compares plots with different tree arrangements. The three other arrangements

(2 species, 3 species and 4 species) have each ten plots (see Table 4) thus why the sum of

trophic levels was divided by 10. This adjustment resulted in an estimation of the abundance

of the trophic levels with its arrangement. Decomposers and herbivores are notably present

in Gedinne compared to the parasites and predators (Figure 19). In the monocultures (1

species) and two species arrangements herbivores and decomposers were notably present.

0

5

10

15

20

25

30

35

40

45

1 species 2 species 3 species 4 species

Ave

rage

in

div

idu

als

pe

r p

lot

Tree arrangement

Herbivores Predators

Parasites Decomposers

Figure 19. Bar chart with the average arthropod individuals present per plot (y-axis) for all

four tree arrangements on both sites in Gedinne. The bars with one species tree

arrangement represent 14 plots (n = 56 samples), the bars with 2, 3 and 4 species tree

arrangements represent 10 plots (n = 40 samples). The error bars indicate the standard

deviation of the data for each bar.

62

The variances of the trophic levels grouped by their tree arrangements were tested with the

Levene‟s Test for Homogeneity of Variance (center = median) (Appendix B-XIV, page 14)

was performed in R Studio with the lawstat package (Gel, Gastwirth & Depends, 2012;

RStudio Inc., 2012). The results of Levene‟s test in Appendix B-XIV indicated that the

variances of respectively herbivores, predators, parasites and decomposers arthropods

grouped by tree arrangement are equal (H0), with a significance level of 0.05 .

To detect differences in trophic levels the raw data had to be tested for normality of each

trophic level and equality of the variances of each trophic level within the four tree

arrangements. In the accompanied Appendix B (page 17) the test results to check the

remaining condition (normality of the residuals of the data) to perform a parametric ANOVA

are given in Appendix B-IX.

All trophic levels in respectively one, two, three and four species tree arrangement clearly

indicated non-normal distributed data. A natural logarithmic transformation succeeded

to normalize the residuals of the data of the herbivores. Residuals of the transformed data of

herbivores, with highest abundance in Gedinne, indicated the best fit out of all four trophic

levels however the sequencing of the points in the four illustrated plots (Appendix B-IX) were

not continuous between norm Quantiles -2 and -0.5 on the x-axis thus why there was chosen

to perform a non-parametric Kruskal-Wallis test.

The Kruskal-Wallis test (Appendix B-XI, page 19) was preformed to identify differences

between the medians of respectively herbivores (p = 0.4785), predators (p = 0.7768),

parasites (p = 0.6246) and decomposers (0.1289). None of the four trophic levels indicated

significant differences in their medians (p < 0.05) between the four tree arrangements in

Gedinne.

4.4.6 Analysis of trophic levels in Gribelle and Gouverneur

The FORBIO-project in Gedinne consists of two sites Gribelle and Gouverneur with the same

tree arrangements and species. The analysis of differences between trophic levels separated

into the site Gribelle and Gouverneur was not preformed for the following reasons. The high

variance differences in the data excluded the non-parametric ANOVA or a non-parametric

Kruskal-Wallis test.

63

5 Discussion

In titles in this paragraph are, if relevant, accompanied with a number between brackets [].

The number indicates the kind of analysis illustrated in a scheme submitted in the Appendix

(Appendix B-I, page 10).

5.1 Arthropod classification

The sampled arthropods have been classified into taxonomic orders however the

classification into trophic levels was more time consuming. The results of a more thorough

identification still left some question marks for certain families and subgroups of orders

sharing the same type of diet. The best fitting groups had to be selected based on the

sometimes poor literature about the ecology and diets in particular of certain insect groups.

Literature also provides that trophic levels are rather viewed in species level then higher taxa

(Price et al., 2011).

5.2 Differences in Gribelle and Gouverneur ([3], [5])

The overview of arthropods in Figure 16 indicated more diverging values of arthropod

individuals in Gribelle. In general the samples above 30 arthropod individuals show less than

5 effective number of orders present. As the effective number of orders was higher the

number of arthropods for each order decreased. The samples with highest abundances have

a low effective number of orders. In both trophic levels and the Shannon index there were

found significant differences between sites. The analysis of differences within the sites based

on trophic levels was not possible due to their distribution. The growth and development of

the trees and the adaptation to the new conditions of the ecosystem (sites planted in 2010)

are suggested as favourable factors to gain samples.

Analysis [3] and [5] (Appendix B-I on page 10 of the accompanied Appendix) both indicated

significant differences. These differences can have several causes. Some variables are the

differences in heights, Gouverneur (421 to 427 m) is located at a ≈ 50 m higher altitude

compared to Gribelle (367 to 376 m) (Table 2). Furthermore the terrain in Gribelle gradually

decreases (see the depression line in Appendix A-I in 0, page 6) with several correlations

such as a decreasing pH, an increasing total P concentration (Ptot ) and an increasing C/N

ratio (Verheyen et al., 2010). Research on gradients in topographic relief indicates that

topographic relief influences the plant species richness (O‟Brien, Field & Whittaker, 2000).

Chances for more plants and thus more variability in plant hosts may change communities to

become more specialized .

64

5.3 Arthropod diversity between tree arrangements ([1], [4])

5.3.1 Shannon‟s index differences between the tree arrangements [1]

The main goals of this work was to analyse the differences in arthropod diversity between

four tree arrangements. The Shannon index was introduced to analyse the arthropod

diversity. Tests were performed on differences between the four tree arrangements. A non-

parametric Kruskal-Wallis test did not show differences in the medians of the Shannon index

between tree arrangements on a 0.05 significance level. The nature of the non normal data

has often led to weaker statistical tests.

Greater above ground biomass of the planted trees in Gedinne ought to increase the

arthropod individuals in the samples. This would prevent high amounts of zero values in the

raw data (separation in orders) resulting in better fitting models for statistical analyses with

more power (ANOVA) (Zar, 2010). In the years to come the growth of the trees will create

better chance to acquire arthropods while a higher resilience of the sites to variable abiotic

factors may reveal the effects of plantdiversity.

5.3.2 Trophic levels differences in the tree arrangements [4]

The classification into trophic levels narrows down the data information from eleven groups

to four groups, however these four groups have similar diets and thus this classification

describes the community better then the Shannon index (Colwell, 2009; Leibold, Chase,

Shurin & Downing, 1997; Pavoine et al., 2005). The four trophic levels lose information and

seemed are more generalised (4 trophic levels compared to 11 orders) yet they can provide

a better understanding of other levels of biodiversity and similarities between species

independent of the much argued biodiversity indices (Colwell, 2009; Leinster & Cobbold,

2012; Pavoine et al., 2005).

The amount of herbivores found in Gribelle were significantly different from those found in

Gouverneur. In both order and trophic level classification these differences were visible and

statistically proven based on significance level of 0.05.

This suggests that abiotic factors were interfering differently in Gouverneur and Gribelle.

Differences in growth in Gribelle and Gouverneur (see paragraph 3.1.2) could explain the

significant difference in herbivore arthropods since especially polyphagous insects benefit

from this growth (Mátyás & Varga, 1983) yet these data have not been analysed so far in

Gedinne. The higher abundance of predators, which was not found to be significant however,

present in Gribelle suggests that herbivorous species had more chance of being regulated by

the sampled predators. These two factors amplify each other.

The decomposers (≈ 95% Collembola) group appeared in variable amounts which did not

seem connected with the herbivores, predators or parasites trophic levels. Collembola are

65

rather found below-ground, yet certain species live above-ground on bark of trees (Bardgett,

Wardle & Yeates, 1998; Hopkin, 2002), suggesting they may rather be connected or

regulated by below-ground trophic levels or the combination of the two (Van der Putten et al.,

2001). The large presence of Collembola suggests they have sufficient food resources above

ground. Furthermore it is not uncommon to find Collembola on the bark and stumbs of trees

(Shaw et al., 2007). There is a possibility that excluded arthropods, who can‟t be caught with

the aspirator method, in particular ground-dwelling arthropods consist of species in the

trophic levels controlling these decomposers. It is after all the Collembola that represent

almost 95%.

The changes in these trophic levels over time may reveal similar or changing patterns for

future analyses and meta-analyses on this experimental design which is one of the essences

of the classification in trophic levels as a foundation. Furthermore a set plot size can narrows

down the patterns populations show on larger scales while the period of sampling is also

variable in time (Lambin, Krebs, Moss, & Yoccoz, 2002) which can lead to specious

correlations (Price et al., 2011).

Figure 15 demonstrates the ratio‟s of trophic levels. The low ratio herbivores-predators in

Gribelle compared to Gouverneur indicated that communities in both study areas were

functioning differently at the moment of sampling July and August 2013.

In the tree arrangements the relative abundance of arthropods is higher in Gouverneur then

in Gribelle for the trophic level herbivores, while decomposers were significantly more

present in Gribelle..

In future research this analysis, based on trophic levels, may help interpreting data from

other researches in Gedinne such as „Assessment of pest and pathogen attack on trees in

more or less diverse forest stands‟ in the FORBIO- sites in Gedinne.

5.4 Arthropod diversity linked to tree species [2]

During the fieldwork 176 trees were sampled with a equal ratio in tree species (32 samples

for each tree species). Differences in arthropod diversity (quantified by the Shannon index)

between tree species were detected with an ANOVA. The goal of this test was to identify

which tree species attract the most diverse arthropod populations. The tree species differed

significantly in their means which was assumed visually in Figure 13. The differences

between tree species were more pronounced than the differences between tree

arrangements, this has also been confirmed in similar research part of the TreeDivNet in

Finland (Vehviläinen et al., 2008). The scale of tree species level (one tree) is much smaller

compared to the plot size (28 x 28 trees). It would appear that these differences become

mitigated in larger scales such as the plot size.

66

Out of all tree species Quercus petraea indicated the highest Shannon index. Sessile oak is

a land rase which makes it more probable for various amount of arthropods to recognize their

habitat on this particular tree species.

67

6 Conclusion

After three years of tree growth (2010-2013) no significant differences were found in

arthropod diversity based on Shannon‟s index on tree level in diverse tree arrangements

compared to monocultures. However the temporal aspect of the sampling method suggested

a need for periodic measurements to reveal certain fluctuations in diversity. Particularly the

development of the tree canopy and thus a higher chance to sample more arthropods can

provide a surplus for data for a more efficient analysis.

Significant differences in arthropod diversity have been found between tree species level.

Acer pseudoplatanus and Quercus petraea had a significantly higher arthropod diversity

compared to Larix x eurolepis, Pseudotsuga menziesii and Fagus sylvatica. Acer

pseudoplatanus samples indicated lower arthropod diversity levels, while the arthropod

diversity on Quercus petraea was highest.

The analysis of the data classified into trophic levels did not indicate significant difference in

the four different tree arrangements in Gedinne. However the herbivore and decomposer

trophic levels were significantly different on the sites Gribelle and Gouverneur. Significantly

higher amounts of herbivorous species in Gouverneur suggested a preferable nutritive value

of its vegetation. The higher abundance of predators, not significantly, present in Gribelle

may indicate differences in regulations between the communities in both sites.

It is plausible that arthropod diversity was mitigated between tree arrangements due to the

scale of the considered plots. The development of future measurements can clarify if this

mitigation continues in different tree arrangements, or alternatively, if differences are still

evolving. Based on the trophic level classification, it is likely that the plot sizes for analysis of

arthropods are too small to detect differences in communities with their trophic levels. The

Shannon index detected differences more easily on individual tree scale, which were smaller

compared to plot scale.

In conclusion the two classifications ( i.e. taxonomic orders and trophic levels) have each

provided futile information to describe the diversity on the FORBIO-sites in Gedinne. The

fieldwork and identification was of a relatively acceptable time span for a yearly analysis. The

FORBIO-project in Gedinne indicates much potential for future research. However both sites,

Gribelle and Gouverneur, should not be seen as similar sites regardless of their distance to

each other (≈ 5 km).

68

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Appendix

Ritchie Gobin






3

Table of contents

Table of contents ................................................................................................................... 3

List of appendices ................................................................................................................. 4

A.1.1 Overview of the sites in Gedinne .......................................................................... 6

A.2 Weather conditions during the fieldwork ...................................................................... 7

Appendix B ...........................................................................................................................10

B.1 Overview of the analyses in this work .........................................................................10

B.2 Analysis of Shannon index applied on orders linked to the tree arrangement .............11

B.2.1 Test for normality of tree arrangement groups .....................................................11

B.3 Analysis of Shannon index applied on orders linked to the tree species .....................12

B.4 Comparison of arthropod diversity in the sites ............................................................15

B.5 Analysis of trophic levels linked to tree arrangement ..................................................17

B.5.1 Test for normality and variances within tree arrangements ..................................17

B.5.2 Kruskal-Wallis test on trophic levels ....................................................................19

B.5.3 Differences between Gribelle and Gouverneur based on trophic levels ...............20

4

List of appendices

Appendix A-I. Map of the 22 plots established in both Gribelle and Gouverneur with

according colours explaining the different tree arrangements. The colour represents the level

of tree diversity from monoculture (white) up to mixed tree stands with 4 species (dark

colour). .................................................................................................................................. 6

Appendix A-II. Tables of the weather conditions. Dates 23, 24, 25 July 2013 are the weather

conditions for the fieldwork in Gouverneur, while 26 July, 5 August and 6 August 2013 are

the dates of the fieldwork in Gribelle. Every hour the temperature (Temp.) the wind direction

(Dir.) and the average windspeed (Moy.) was measured. Additionally in Charleville‟s weather

station the rainfall (Prec.) was measured. Tables modified from Meteorologic.net

(“Meteorologic.net,” 2013). .................................................................................................... 8

Appendix A-III. Boxplot representing the medians (bold horizontal line) closed in by 50%

(rectangle) of the data of arthropod abundance (y-axis) for a six dates (x-axis). The small

circles are the outliers of the data. The black points represent the means. ............................ 9

Appendix A-IV. Boxplot representing the medians (bold horizontal line) closed in by 50% of

the effective number of orders for every day of fieldwork. ..................................................... 9

Appendix B-I. Overview of all statistical analyses performed, the number between brackets []

is mentioned in the titles of results (paragraph 4, page 46) in the main work. The plots with

an asterisk are the Fagus sylvatica with different provenance. The trophic levels represent

four different groups (herbivores, predators, parasites and decomposers). ..........................10

Appendix B-II. Graphs representing the residuals in 1 species (left) and 2 species (right) tree

arrangement compared with a fitting line of a normal distributed function. ............................11

Appendix B-III. Graphs representing the residuals in 3 species (left) and 4 species (right) tree

arrangements compared with a fitting line of a normal distributed function. ..........................11

Appendix B-IV. Test results of the Levene‟s Test for homogeneity of Variance and Kruskal-

Wallis rank sum test H as the response variable and Species_Number as the factor defining

the groups. ...........................................................................................................................12

Appendix B-V. Analysis of orders linked to tree species. Respectively the tests for normality

of the data grouped by independent variable Genus_ID (the genera of the trees) and

dependent variable H (Shannon index), Levene‟s Test for Homogeneity of Variance and the

ANOVA results are illustrated. The significant p-values ( < 0.05) are printed bold. ...............13

5

Appendix B-VI. Post-hoc Tukey multiple comparisons of means test (95% family-wise

confidence level executed on the one way ANOVA results with significant p-value. The

significant p-values( < 0.05) are printed bold. .......................................................................14

Appendix B-VII. Normal Probability Plots illustrating the residuals of the Shannon index data

in respectively Gribelle (top) and Gouverneur (bottom). The red line represents a normal

distribution. ...........................................................................................................................15

Appendix B-VIII. Test results of the Levene‟s test and then Wilcoxon Rank Signed Test wtih

dependent variable H (Shannon index) and Site as independent variable. Significant p-values

are printed in bold. ................................................................................................................16

Appendix B-IX. Normal Probability Plots were the red line represents a normal distribution.

The points are the natural logarithm of the herbivore data for the four tree arrangements (1

species, 2 species, 3 species and 4 species). ......................................................................17

Appendix B-X. Levene‟s Test for Homogeneity of Variance (center = median) on all four

trophic levels grouped by tree arrangement (Species_Number). ..........................................18

Appendix B-XI. Kruskal-Wallis test results of the four trophic levels herbivores, predators,

parasites and decomposers. The p-values are indicated in bold. ..........................................19

Appendix B-XII. Normal Probability Plot of the residuals of the arthropod individuals in

Gouverneur indicating an exponential pattern. .....................................................................20

Appendix B-XIII. Normal Probability Plot of the residuals of the natural logarithm of the

arthropod individuals in Gouverneur. ....................................................................................20

Appendix B-XIV. Levene‟s Test for Homogeneity of Variance (center = median) with each of

the four trophic levels as dependent variable grouped by the site. ........................................21

Appendix B-XV. Wilcoxon rank sum test with continuity correction with as dependent variable

the trophic level and Site as grouping variable. Significant p-values (< 0.05) are printed bold.

.............................................................................................................................................21

6

A.1.1 Overview of the sites in Gedinne

Appendix A-I. Map of the 22 plots established in both Gribelle and Gouverneur with

according colours explaining the different tree arrangements. The colour represents the level

of tree diversity from monoculture (white) up to mixed tree stands with 4 species (dark

colour).

7

A.2 Weather conditions during the fieldwork

Following Appendix A-II give the daily overview of the weather conditions measured in a

nearby (8-9 km) weather station in Gedinne. More detailed information was acquired from the

closest weather station in Charleville about 23 km from Gedinne. The first measurement day

had the highest temperatures with few wind breezes. It was a preferable day to take

arthropod samples.

24 July was the least productive day to take samples due to the rainy afternoon. This caused

a delay of two hours before the sky cleared up with increasing temperatures around 14h (see

Appendix A-II, 24 July). At this point sampling was continued.

On 25 July the fieldwork moved on quickly in Gouverneur because of agreeable weather and

experience in the routine of the sampling method with the 12V aspirator.

illustrates the rainfall in the Precipitation (Prec.) Column of the measurements in weather

station of Charleville however while sampling in Gedinne in the afternoon on 26 July it was a

sunny afternoon in Gribelle which corresponded to the protocols for measurements.

Temperatures on 5 August were between 25 °C and 30 °C with a maximum of 20 km/h wind

speed. On this day with stable weather 52 trees were sampled over 13 plots in Gribelle.

The last day of sampling in Gribelle the weather was variable taking the last samples around

14h30 in the afternoon. From this point on the identification of arthropods could commence.

8

Appendix A-II. Tables of the weather conditions. Dates 23, 24, 25 July 2013 are the weather

conditions for the fieldwork in Gouverneur, while 26 July, 5 August and 6 August 2013 are

the dates of the fieldwork in Gribelle. Every hour the temperature (Temp.) the wind direction

(Dir.) and the average windspeed (Moy.) was measured. Additionally in Charleville‟s weather

station the rainfall (Prec.) was measured. Tables modified from Meteorologic.net

(“Meteorologic.net,” 2013).

9

Appendix A-III. Boxplot representing the medians (bold horizontal line) closed in by 50%

(rectangle) of the data of arthropod abundance (y-axis) for a six dates (x-axis). The small

circles are the outliers of the data. The black points represent the means.

Appendix A-IV. Boxplot representing the medians (bold horizontal line) closed in by 50% of

the effective number of orders for every day of fieldwork.

10

Appendix B

B.1 Overview of the analyses in this work

Appendix B-I. Overview of all statistical analyses performed, the number between brackets []

is mentioned in the titles of results (paragraph 4, page 46) in the main work. The plots with

an asterisk are the Fagus sylvatica with different provenance. The trophic levels represent

four different groups (herbivores, predators, parasites and decomposers).

11

B.2 Analysis of Shannon index applied on orders linked to

the tree arrangement

B.2.1 Test for normality of tree arrangement groups

Appendix B-II. Graphs representing the residuals in 1 species (left) and 2 species (right) tree

arrangement compared with a fitting line of a normal distributed function.

Appendix B-III. Graphs representing the residuals in 3 species (left) and 4 species (right) tree

arrangements compared with a fitting line of a normal distributed function.

12

Appendix B-IV. Test results of the Levene‟s Test for homogeneity of Variance and Kruskal-

Wallis rank sum test H as the response variable and Species_Number as the factor defining

the groups.

Levene's Test for Homogeneity of Variance (center = median)

Df F value Pr(>F)

group 3 1.407 0.2428

156

Kruskal-Wallis rank sum test

Kruskal-Wallis chi-squared = 3.0861, df = 3, p-value = 0.3785

B.3 Analysis of Shannon index applied on orders linked to

the tree species

The normality of data and the homogeneity of the variances of data were tested respectively

with the Shapiro-Wilkinson test for normality (n < 2000) and the Levene‟s Test for

Homogeneity of Variance.

The normality of residuals was confirmed graphically in Q-Q plots in R Studio (RStudio Inc.,

2012). The tails did not seem to follow normality however the center was close to normality in

all four tree arrangements. According to Zar (2010) an ANOVA with slightly non-normal data

still has power when homogeneity of the data is met together with a significant result in the

ANOVA.

H0: The means of the Shannon index in all tree species are equal.

µ Acer pseudoplatanus = µ Fagus sylvatica = µ Larix x eurolepis = µ Pseudotsuga menziesii = µ Quercus petraea

H1: There is a difference in the means of the Shannon index between the tree species.

µ Acer pseudoplatanus ≠ µ Fagus sylvatica ≠ µ Larix x eurolepis ≠ µ Pseudotsuga menziesii ≠ µ Quercus petraea

13

Appendix B-V. Analysis of orders linked to tree species. Respectively the tests for normality

of the data grouped by independent variable Genus_ID (the genera of the trees) and

dependent variable H (Shannon index), Levene‟s Test for Homogeneity of Variance and the

ANOVA results are illustrated. The significant p-values ( < 0.05) are printed bold.

Test for normality of H grouped by Genus_ID:

Genus_ID: Acer

Shapiro-Wilk normality test

W = 0.932, p-value = 0.0446 < 0,05 => no normal distribution according to the

Shapiro-Wilk normality test.

Genus_ID: Fagus


W = 0.9391, p-value = 0.07042

Genus_ID: Larix


W = 0.9751, p-value = 0.6513

Genus_ID: Pseudotsuga


W = 0.9683, p-value = 0.4539

Genus_ID: Quercus


W = 0.9541, p-value = 0.1885

Levene‟s Test for Homogeneity of Variance (center = median) of H grouped by

Genus_ID:

Df F value Pr(>F)

group 4 1.6137 0.1735

155

14

Appendix B-VI. Post-hoc Tukey multiple comparisons of means test (95% family-wise

confidence level executed on the one way ANOVA results with significant p-value. The

significant p-values( < 0.05) are printed bold.

One way ANOVA results:

Df Sum Sq Mean Sq F value Pr(>F)

genus 4 4.32 1.08 6.6037 6.21E-05 ***

Residuals 155 25.3494 0.1635

Post-hoc Tukey multiple comparisons of means test

(95% family-wise confidence level)

Relation diff lwr upr p adj

Fagus-Acer 0.175182 -0.10387 0.454239 0.417053

Larix-Acer 0.281172 0.002115 0.560228 0.047301

Pseudotsuga-Acer 0.314077 0.035021 0.593133 0.018854

Quercus-Acer 0.498797 0.21974 0.777853 0.00002

Larix-Fagus 0.105989 -0.17307 0.385045 0.832325

Pseudotsuga-Fagus 0.138895 -0.14016 0.417951 0.645316

Quercus-Fagus 0.323614 0.044558 0.60267 0.014167

Pseudotsuga-Larix 0.032906 -0.24615 0.311962 0.997552

Quercus-Larix 0.217625 -0.06143 0.496681 0.20357

Quercus-Pseudotsuga 0.184719 -0.09434 0.463776 0.361817

15

B.4 Comparison of arthropod diversity in the sites

Appendix B-VII. Normal Probability Plots illustrating the residuals of the Shannon index data

in respectively Gribelle (top) and Gouverneur (bottom). The red line represents a normal

distribution.

Gribelle

Gouverneur

16

Appendix B-VIII. Test results of the Levene‟s test and then Wilcoxon Rank Signed Test wtih

dependent variable H (Shannon index) and Site as independent variable. Significant p-values

are printed in bold.

Levene's Test for Homogeneity of Variance (center = median):

Df F value Pr(>F)

group 1 0.2313 0.6312

158

Results of Welch Two Sample t-test:

t = -2.7794, df = 158, p-value = 0.006107

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

-0.3180804 -0.0538104

sample estimates:

mean in group Gouverneur mean in group Gribelle

1.078436 1.264382

17

B.5 Analysis of trophic levels linked to tree arrangement

B.5.1 Test for normality and variances within tree arrangements

Appendix B-IX. Normal Probability Plots were the red line represents a normal distribution.

The points are the natural logarithm of the herbivore data for the four tree arrangements (1

species, 2 species, 3 species and 4 species).

18

Appendix B-X. Levene‟s Test for Homogeneity of Variance (center = median) on all four

trophic levels grouped by tree arrangement (Species_Number).

Herbivores ~ Species_Number

Df F value Pr (>F)

group 3 0.6191 0.604

156

Predators ~ Species_Number

Df F value Pr (>F)

group 3 0.4722 0.702

156

Parasites ~ Species_Number

Df F value Pr (>F)

group 3 0.4556 0.714

156

Decomposers ~ Species_Number

Df F value Pr (>F)

group 3 1.1954 0.314

156

All four tests indicated a p-value higher than 0.05. The variances of the data of the

herbivores, predators, parasites and decomposers are equal (H0) based on a significance

level of 0.05.

19

B.5.2 Kruskal-Wallis test on trophic levels

Non-parametric Kruskal-Wallis tests were executed since the data indicated non-normal

distribution. The Kruskal-Wallis test tested if the medians of the four tree arrangements in

each trophic level (four tests) showed differences (H1) or were the same (H0).

Appendix B-XI. Kruskal-Wallis test results of the four trophic levels herbivores, predators,

parasites and decomposers. The p-values are indicated in bold.

Dependent variable: Herbivores

Response variable: Species_Number


Dependent variable: Predators



Dependent variable: Parasites



Dependent variable: Decomposers



All four p-values are higher than the 0.05 significance level. The null hypothesis(H0) is

retained, there are no significant differences in medians of trophic levels between tree

arrangements, and this for all four trophic levels herbivores, predators, parasites and

decomposers.

20

B.5.3 Differences between Gribelle and Gouverneur based on

trophic levels

Appendix B-XII. Normal Probability Plot of the residuals of the arthropod individuals in

Gouverneur indicating an exponential pattern.

Appendix B-XIII. Normal Probability Plot of the residuals of the natural logarithm of the

arthropod individuals in Gouverneur.

21

Appendix B-XIV. Levene‟s Test for Homogeneity of Variance (center = median) with each of

the four trophic levels as dependent variable grouped by the site.

Herbivores ~ Site

Df F value Pr(>F)

group 3 0.6683 0.5726

172

Predators ~ Site

Df F value Pr(>F)

group 3 0.8701 0.4578

172

Parasites ~ Site

Df F value Pr(>F)

group 3 0.628 0.5978

172

Decomposers ~ Site

Df F value Pr(>F)

group 3 1.2838 0.2816

172

Appendix B-XV. Wilcoxon rank sum test with continuity correction with as dependent variable

the trophic level and Site as grouping variable. Significant p-values (< 0.05) are printed bold.

data: Herbivores by Site W = 5071.5, p-value = 0.00036

alternative hypothesis: true location shift is not equal to 0

data: Predators by Site

W = 3690, p-value = 0.5873


data: Parasites by Site

W = 4361.5, p-value = 0.1409


data: Decomposers by Site

W = 2472.5, p-value = 0.000028


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