Ben-Gurion University of the Negev
Jacob Blaustein Institute for Desert Research
Albert Katz International School for Desert Studies
Linking Landscape and Species Diversities:
The Case of Woody Vegetation Patchiness and
Beetle Species Turnover
Thesis submitted in partial fulfillment of the requirements for the degree of
“Master of Science”
By Yuval Berger
February 2006
Ben-Gurion University of the Negev Jacob Blaustein Institute for Desert Research
Albert Katz International School for Desert Studies
Linking Landscape and Species Diversities:
The Case of Woody Vegetation Patchiness and
Beetle Species Turnover
Thesis submitted in partial fulfillment of the requirements for the degree of
“Master of Science”
By Yuval Berger
Under the Supervision of:
Prof. Moshe Shachak
Marco and Louise Mitrani Department of Desert Ecology
Dr. Elli Groner
Marco and Louise Mitrani Department of Desert Ecology
Author’s Signature………………………………….. Date…………………….
Approved by Supervisor……………………………. Date…………………….
Approved by Supervisor……………………………. Date…………………….
Approved by the Director of the School …………… Date……………………. Table of contents
Acknowledgements iii
Abstract vi
List of Figures vii
List of Tables xi
1. Introduction 1
Conceptual framework for discussing biodiversity 1
Landscape Diversity 2
Species diversity 3
Environmental factors, landscape diversity and species turnover 4
Ecosystem engineers 8
Woody vegetation as ecosystem engineers 12
Purpose of this work 15
Hypotheses 16
2. Filtering as a linkage between patchiness and species turnover – theoretical considerations 17 Definitions 17
The model 20
3. Methods 26
Experimental design 26
Focal group and specimen identification 30
Study sites 30
Scale definition 33
i Dominance 34
Patch contrast 34
Assemblage contrast 35
General Patterns 43
4. Results 44
Dominance 44
Sunfleck contrast 50
Assemblage contrast 56
5. Discussion 73
Research hypotheses 73 Canopy removal, grazing and species composition in Mediterranean woodland 75 Combined effects of grazing and canopy removal on woody-open assemblage contrast in Mediterranean woodland 77
Inhibition and facilitation of beetle activity by ecosystem engineering 79
Canopy removal, grazing and species composition in desert shrub-land 81 Assemblage contrast response to engineering under different environmental conditions 83
Linking landscape and species diversities 88
6. References 90
7. Appendices 106
ii Acknowledgements
This work couldn't have been completed hadn't it been for the help of many
and it is a pleasant duty to thank them here. My mother Yael, my sister Rachel (Weu),
my friends Gali, Oren, Maya, Ofek, Laurie, Sigal and Anat, were all ready to offer
their care and support when such was needed.
Dr. Elli Groner introduced me to the fields of community ecology and
ecological entomology, and was an inexhaustible source of advice during the entire
period of my study. His wife Zoe and he did their best to make me feel at home in
Sede-Boker right from the very beginning and always offered their help both in
academic and personal issues. Prof. Moshe Shachak shared with me his vast scientific
and life experience, introduced me to the world of ecosystem ecology and led me
through the process of developing the conceptual framework of this study. Studying
under his supervision was a unique intellectual experience, which helped me in
developing my ecological and scientific thinking. I consider the stormy scientific
discussions taking place in his office one of the most important components of my
academic education.
I was privileged to have known and be taught by Prof. Yael Lubin. Yael was a
member of my academic committee, a PI in the research project accommodating my
study, and was more than once a source of sound advice. In addition she willingly
volunteered to help in field work. I consider Yael a role model when it comes to
interpersonal relations, ethics, tuition and science.
Mrs. Yael Kaplan and Mrs. Dorit Levin were always there to insure that red
tape will not stand in the way scientific progress. Both exercised a most
accommodating attitude and were extremely helpful. Marc Goldberg made sure that
technical issues will be of little obstacle and as many of my fellow students I enjoyed
iii the reliable technical infrastructure that Marc has managed so well. During my research I enjoyed the cooperation of the Israel Nature and National Parks Authority
(INNPA). Dr. Yehoshua Shkedi manages the Adulam LTER station and was always
willing to help. Ilan Shifman is the park ranger in Adulam and played a most valuable
role in coordinating grazing with sampling. Dr. Linda Whittaker from the science
division of the INNPA led me in my first steps through the maze of multivariate
analysis. In Avdat I enjoyed the friendship and help of Jumaa Zanoun, who kept an
eye on the station at all times.
Dr. Marti Jane Anderson from the University of Auckland placed her excellent
computer programmes at public disposal and by doing so raised an unparalleled
contribution to my study. Dr. Vladimir Chikatunov from the Tel-Aviv University
helped identifying the beetles of Adulam. Dr. Bertrand Boeken readily discussed with
me theoretical and methodological aspects of my work and supplied me with valuable
insights. Prof. Burt Kotler unknowingly contributed to the development of my
research question as submitting an assignment in his course "Classic readings in
Ecology and Evolution" I realised the importance of species composition and
turnover. Prof. Mike Irwin, Dr. Sol Brand, Dr. Yaron Ziv, Dr. Yoram Ayal, Dr. Ariel
Novoplansky, Dr. Pedro Berliner and Ido Filin gave me useful advice on academic
and scientific issues. My lab mates and friends in Sede-Boker helped either in field
work or in advice, amongst them are Moran Segoli, Efrat Shefer, Ofri Gabai, Alagie
Manjang, Amadou Camara, Bimala Shrestha, Diana Milman, Efrat Elimelech, Efrat
Gavish, Vania Portugal, Natela Mirzoyan, Felix Cervants, Adriana Guarerro, Evelin
Farfan, Oren Shelef, Reuma Arusi and Yafei Wang. Iris Musli ,Yonatan
Rosenzweig, Amram Tzabari , Hofesh Maoz, Ilana Dolev, and Nimrod Musli all
helped in field and laboratory work. The Mitrani Department of Desert Ecology
iv granted me with partial fellowship in my first year of study. Special thanks to Prof.
Uzi Motro, who encouraged me to pursue the scientific path.
v Abstract
Biodiversity refers to the diversity of landscape entities (e.g. patches), species
entities (e.g. communities) and resources (e.g. light). This work focused on the
relation between patchiness (landscape diversity) and species turnover, which is a
component of species diversity. To link between the two diversity forms I considered
species assemblages as landscape entities, and species turnover between them was as
a private case of contrast between landscape entities termed assemblage contrast.
A conceptual model was used for describing species turnover and
environmental filtering of species in a patchy landscape. The model has shown that
the level of environmental filtering in a patchy landscape determines the assemblage
contrast between different patch types.
A field experiment examined the connection between patchiness induced by
ecosystem engineering and species turnover under different environmental conditions.
Abiotic patchiness caused by woody vegetation served as a model for patchiness
induced by ecosystem engineering, and beetles (Coleoptera) served as a focal group
for measuring species turnover. Two study sites, Adulam and Avadat (Israel), were
used to represent two different ecosystems (Mediterranean woodland and desert
shrub-land correspondingly). Experimental manipulations included canopy removal of
woody vegetation and grazing. Beetles were sampled using pitfall traps. Dominance
and woody-open assemblage contrast were calculated for beetle assemblages.
Patchiness resulting from ecosystem engineering was shown to affect assemblage
contrast, due to different mechanisms under different environmental conditions.
Keywords: Landscape diversity, Species diversity, Assemblage contrast,
Environmental filtering, Ecosystem engineers, Mediterranean woodland, Desert
shrub-land, LTER, Woody vegetation, Coleoptera, Canopy removal, Grazing, Pitfall
traps, Bray-Curtis distance, PERMANOVA, Non-metric multidimensional scaling.
vi List of figures
Figure 1.1 – Ecosystem engineering and its connection to species turnover 11
Figure 2.1 – Filtering and species turnover in a landscape with two patch types 21 Figure 3.1 – LTER stations in the research programme titled " Biodiversity patterns and processes in water-limited ecosystems: a unifying approach" 26
Figure 3.2 – Illustration of a single block in the experimental design 29 Figure 3.3 œ Assemblage contrast between hypothetical samples of table 3.1 calculated using Bray-Curtis distance 37 Figure 3.4 – Five scenarios where assemblage contrast between two patch types is being observed 40 Figure 4.1 – Dominance values for each patch type and treatment combination in Adulam 45 Figure 4.2 – Combined effect of removal treatment and patch type on dominance in Adulam 46 Figure 4.3 - Interaction between removal treatment and patch type effects on dominance in Adulam 47 Figure 4.4 – Dominance values for each patch type and treatment combination in Avdat 2005 48 Figure 4.5 – Woody-open sunfelck contrast under different combinations of removal treatment and grazing regime combination in Adulam 50 Figure 4.6 – Effect of removal treatment on woody-open sunfleck contrast in Adulam 51 Figure 4.7 – Woody-open Sunfleck contrast values for each treatment combination in Avdat 52 Figure 4.8 - Effect of removal treatment on woody-open sunfleck contrast in Avdat 53 Figure 4.9 – Interaction between removal treatment and grazing regime effects on woody-open sunfleck contrast in Avdat 54 Figure 4.10 – Non-metric multidimensional scaling ordination in Adulam showing all combinations of removal treatments, grazing regimes and patch types 56
vii Figure 4.11 – Non-metric multidimensional scaling ordination in Adulam showing the effects of canopy removal and grazing regime on species assemblages of open and woody patches 57 Figure 4.12 – Non-metric multidimensional scaling ordination in Adulam showing species assemblages of woody and open patches under different combinations of removal treatments and grazing regimes 59 Figure 4.13 – Distance based redundancy analysis (marginal test, Bray-Curtis distance) of species effect on variation in species composition in Adulam 62 Figure 4.14 – Distance based redundancy analysis (conditional test, Bray- Curtis distance) of species effect on variation in species composition in Adulam 63 Figure 4.15 – Non-metric multidimensional scaling ordination of Adulam showing activity of selected species 64
Figure 4.16 - Incidence abundance graphs of uncut plots in Adulam 65
Figure 4.17 - Incidence abundance graphs of removal plots in Adulam 66 Figure 4.18 – Non-metric multidimensional scaling ordination in Avdat 2005 showing all combinations of removal treatments, grazing regimes and patch types 67 Figure 4.19 – Non-metric multidimensional scaling ordination in Avdat 2005 by patch types 68 Figure 4.20 – Distance based redundancy analysis (marginal test, Bray-Curtis distance) of species effect on variation in species composition in Avdat 2005 70 Figure 4.21 – Comparison of species effect on variation in species composition between Adulam and Avdat 2005 showing distance based redundancy analysis results (marginal test, Bray-Curtis distance) for the 10 most contributing species at each station 71 Figure 4.22 – Distance based redundancy analysis (conditional test, Bray- Curtis distance) of species effect on variation in species composition in Avdat 2005 72 Figure 4.23 - Incidence abundance graphs comparing open and woody patches in Avdat 2005 72
viii Figure 7.1.1 – Non-metric multidimensional scaling ordination in Avdat '04 showing all combinations of removal treatments, grazing regimes and patch types 106
Figure 7.2.1 – Effect of treatment combination on beetle activity in Adulam 107 Figure 7.2.2 – Effect of treatment combination on beetle activity in Adulam showing trophic groups 107 Figure 7.2.3 – Combined effect of patch type and removal treatment on beetle activity in Adulam 108 Figure 7.2.4 – Combined effect of patch type and grazing regime on beetle activity in Adulam 108
Figure 7.2.5 –Effect of removal treatment on detritivore activity in Adulam 109
Figure 7.2.6 –Effect of grazing regime on detritivore activity in Adulam 109 Figure 7.2.7 – Combined effect of patch type and removal treatment on detritivore activity in Adulam 110 Figure 7.2.8 – Combined effect of patch type and grazing regime on detritivore activity in Adulam 110
Figure 7.2.9 – Effect of treatment combination on beetle activity in Avdat 111 Figure 7.2.10 – Effect of treatment combination on beetle activity in Avdat showing trophic groups 111 Figure 7.3.1 – Effect of treatment combination on beetle species richness in Adulam 112 Figure 7.3.2 – Effect of treatment combination on beetle species richness in Adulam showing trophic groups 112
Figure 7.3.3 – Effect of patch type on beetle species richness in Adulam 113
Figure 7.3.4 – Effect of patch type on herbivore species richness in Adulam 113 Figure 7.3.5 – Combined effect of patch type and removal treatment on predator species richness in Adulam 114 Figure 7.3.6 – Effect of treatment combination on beetle species richness in Avdat 115 Figure 7.3.7 – Effect of treatment combination on beetle species richness in Avdat showing trophic groups 115
ix Figure 7.3.8 – Effect of removal treatments on herbivore species richness in Adulam 116
Figure 7.5.1 – Aspect preference of Opatrum libani and Tentyria herculeana 121
x List of Tables Table 3.1 - A hypothetical sampling matrix representing 11 samples of five species 37
Table 4.1 – Three way ANOVA of dominance for beetle assemblages Adulam 48
Table 4.2 - Three way ANOVA of dominance for beetle assemblages in Avdat 49
Table 4.3 – Two way ANOVA of woody-open sunfleck contrast in Adualm 54
Table 4.4 – Two way ANOVA of woody-open sunfleck contrast in Avdat 55 Table 4.5 – PERMANOVA of Adulam ground dwelling beetle assemblage contrast 57 Table 4.6 – Post hoc analysis of Adulam ground dwelling beetle assemblage contrast 60 Table 4.7 – PERMANOVA of Avdat ground dwelling beetle assemblage contrast 68 Table 4.8 – Post hoc analysis of Avdat ground dwelling beetle assemblage contrast 69
Table 7.1.1 – PERMANOVA of Avdat '04 ground dwelling beetle assemblage 106 Table 7.4.1 – List of species and morpho-species collected and identified during Adulam 2004 sampling session 117 Table 7.4.2 – List of species and morpho-species collected and identified during Avdat 2005 sampling session 119
xi 1. Introduction
Conceptual framework for biodiversity
The unprecedented loss of species and their habitats as a result of environmental change has accelerated biodiversity studies (Ehrlich and Wilson 1991). Recent works have illustrated the importance of biodiversity for ecosystem function (Bengtsson et al.
1997, Schlapfer and Schmid 1999). Wall et al. (2001) counted three benefits of biodiversity: goods obtained from genes, species and landscapes; ecosystem services such as purification of air and water and renewal of soil fertility and natural environments providing recreation and inspiration of culture.
Studying the processes generating biodiversity requires understanding of its components. Biodiversity refers to the number, differences and organisation of a variety of entities in an ecosystem (Gaston 1996). Shachak et al.(2005) suggested a conceptual framework for biodiversity studies. The framework considers biodiversity entities, their relationships and function. Biodiversity entities include landscape, species and resources.
Landscape entities are patches in space. Species entities are groups of organisms defined by the taxonomy of their members. Resources are forms of energy and matter required for the functioning of species. Diversity components consist of numbers, differences and organisations. Numbers relate to quantities or proportions of the ecosystem entities, differences relate to several entities and their disparities and organisations relate to hierarchies and relations formed between entities.
Some biodiversity questions are integrative, examining the connection between two or more diversity components. This work will examine the connection between
1 patchiness, a phenomenon of landscape diversity, and species turnover, a phenomenon of species diversity.
Landscape Diversity
Heterogeneity of a given environmental property can come in the form of gradient or in the form of patches (Kolasa and Rollo 1991). If changes in the given property in space are abrupt rather than gradual than the heterogeneity will be referred to as patchiness rather then as a gradient.
Examination of biodiversity in patchy ecosystems requires identification of the way diversity components are expressed in them. Landscape diversity components are suggested to be the number of patches, the differences among them their size and shape, and their spatial configuration (Shachak et al. unpublished). Differences in a patchy landscape refer to the contrast between the different patch types (e.g. Wijesinghe and
Hutchings 1999). Patch contrast reveals how different two patches are in pronouncing the property that defines them (Cadenasso et al. 2003).
Patchiness and patch characteristics were discussed from a variety of perspectives: The effect of spatial arrangement of host plant patches on cabbage butterfly population size decreases as dispersal distance grew (Fahrig and Paloheimo 1988). Host population patchiness was shown to effect the persistence of an epidemic (Hagenaars et al. 2004). Patch size affects the nesting success of birds in riparian forests (Peak et al.
2004). Boeken et al. (2004) have shown that shrub patches inhibit germination of Stipa capensis.
2 Another aspect of patchiness receiving recent attention is the linkage between patchiness and species diversity. Ritchie and Olff (2005) suggested a model that predicts species diversity using the spatial organization and size of patches in the ecosystem.
Boeken et al. (2005) showed that increasing landscape heterogeneity changes species composition of desert herbaceous plants. When patchiness affects species composition it also affects species turnover. This work will examine the role of patchiness in generating species turnover both theoretically and experimentally.
Species diversity
Two key concepts are used when discussing species diversity. Species richness is the number of species found in an ecosystem. Species turnover, a term originally relating to temporal scales, is commonly used to denote the change of species composition in space (e.g. Schoener 1983, Rusch and Vandermaarel 1992) and will be mentioned in that context in this work.
Species turnover describes whether the same species are found when moving from one point in the system space to another. It relates to differences between species assemblages in the system. Whittaker (1960) coined three terms in relation to plant species diversity: alpha-diversity, beta-diversity and gamma-diversity. Alpha-diversity of a system was defined as the number of species found in a single sample of that system.
Gamma-diversity is the species richness of the ecosystem. Beta-diversity was defined as
"the extent of change in community composition, or degree of community differentiation, in relation to a complex gradient of environment, or a pattern of environments"
(Whittaker 1960), which makes it synonymous to species turnover. Beta-diversity is
3 either calculated as the difference or the ratio between gamma and alpha diversities (see
Veech et al. 2002).
Environmental factors, landscape diversity and species turnover
Many environmental factors were suggested to influence species turnover, and the examples below illustrate the variety of possible mechanisms suggested for that phenomenon. Stressful water chemistry reduces species turnover of aquatic invertebrates
(Heino et al. 2003). Species turnover of plant species within various landscapes is greater if intervals between fires are longer (Uys et al. 2004). Burning disturbance induces higher species turnover of plant species in Alaskan forests than logging (Rees and Juday 2002). Species composition of moths in montane forests is correlated with temperature which was therefore suggested to determine their species turnover (Brehm et al. 2003). Species turnover of new world owls is a function of latitude and is greater close to the equator (Koleff et al. 2003). Distance from a farm predicts levels of species turnover in Norwegian grasslands and heaths (Vandvik and Birks 2004). Species turnover of vascular plants in the Faroe Islands peaks in mid altitudes (Fosaa 2004). In contrast, plant species turnover in the Qilianshan Mountains in China decreases with altitude
(Wang et al. 2003). In western Norway species turnover of vascular plants peak more than once along an altitudinal gradient (Odland and Birks 1999). Species turnover of liverworts and lichens in an Alaskan forest is highest for tree bases and disturbed patches of forest floor and lowest for logs (Mills and Macdonald 2004). Edge effect induces higher species turnover in forest birds (Kruger and Lawes 1997). Species turnover of
4 monkey beetles (Scarabaeidae: Hopliini) between sites subjected to grazing disturbance is higher than between undisturbed sites (Colville et al. 2002).
The above examples show that species turnover is sensitive to change in a large range of environmental factors. This sensitivity allows using species turnover as an indicator for those factors which most affect the community. Because areas with high species turnover are by definition areas where species composition changes over a short interval in space, they actually represent boundaries between communities. Any division of an ecosystem to landscape units should therefore take into account patterns of species turnover; suggested boundaries between landscape units should overlap with areas of high species turnover. If they don't then it necessarily means that the factors used to determine those boundaries have little effect on community processes in the system, and are therefore of little importance ecologically. An example for the above rationale was found in the work of McDonald et al. (2005), who measured species turnover to assess the WWF (World Wildlife Fund) definition of ecoregions in North America. Although ecoregions are assumed to contain relatively homogenous species assemblages, with high species turnover between them, McDonald et al. found that in some cases species turnover levels were not related to ecoregion boundaries, which raises doubts about the way those boundaries were being defined.
The difficulty in delineating ecoregions results from the lack of a coherent theory suggesting a linkage between patchiness defined by an environmental factor and the species turnover observed in the ecosystem. An important step towards such a theory was made by Heegaard (2004), who examined whether the continuum concept (see Austin
1985) can explain species turnover. The continuum concept suggests that species
5 continuously replace each other along an environmental gradient. As environmental conditions change along the gradient and become inhibiting for one species it is gradually being replaced by another species, better adapted to the new conditions. Heegaard suggested that according to the continuum concept high levels of species turnover should occur when environmental gradients are compressed to a relatively small spatial scale.
Compression of the environmental gradient to a narrow spatial scale leads to a narrower habitat range for species, and therefore increases the rate of their replacement by others, i.e. species turnover. Because boundaries between patches are by definition areas where environmental gradients are compressed within a very small spatial range, patchy ecosystems are likely to demonstrate high levels of species turnover.
Acknowledging the role of environmental filtering (Keddy 1992) in patchy ecosystems allows further development of theory for linking patchiness and species turnover. In patchy ecosystems abiotic conditions change abruptly between adjacent patches. Species are therefore subjected to different processes of environmental filtering
(see chapter too for further detail) in adjacent patches which may result in different species assemblages. The patches at hand may therefore differ not only in the abiotic property defining them but also in the composition of the species assemblages they accommodate. That difference in species composition can be viewed as a private case of patch contrast and will therefore be referred to in this work as assemblage contrast. Put in species diversity terms assemblage contrast is the species turnover occurring between two adjacent patches. Therefore, if abiotic patchiness results in assemblage contrast, which is a form of species turnover, then abiotic patchiness will increase species turnover in the ecosystem.
6 This work will contain a theoretical component suggesting a model for describing the causative connection between patchiness and species turnover. That model will use environmental filtering as a key concept for linking species and landscape diversity and will describe the connection between patchiness and species turnover conceptually.
In addition to the theoretical component, this work will contain an experimental component, testing the connection between abiotic patch contrast and assemblage contrast. As species turnover is a form of difference, it is likely to relate to the differences between patches. If abiotic patchiness affects species turnover then abiotic patch contrast should correlate with assemblage contrast. Assume an ecosystem with two patch types demonstrating opposite extreme levels of the abiotic property defining them. Most species are expected to be adapted to the conditions of only one patch type. The proportion of those patch dependent species (specialists) will be high and result in high assemblage contrast. The proportion of the generalist, patch independent species
(generalists ) will be low, resulting in low similarity between patch type assemblages, thus further contributing to assemblage contrast. Therefore, an increase in patch contrast is expected to result in an increase in assemblage contrast. To demonstrate how assemblage contrast can be examined in relation to abiotic patch contrast, this work will test whether assemblage contrast measured in the field corresponds with patch contrast of a selected abiotic property.
7 Ecosystem engineers
Abiotic patchiness may not only affect species in the ecosystem but may also be affected by them. A possible scenario is that an organism affects landscape diversity by creating abiotic patchiness, which in turn affects species diversity.
Jones et al. (1994) suggested the concept ecosystem engineers (EE) for organisms that modulate the availability of resources to other species, by causing physical state changes in biotic or abiotic materials. They divided EE into two groups- allogenic engineers, which change the environment by transforming resources from one physical structure to another, and autogenic engineers which change the environment by their own structure.
Some examples of allogenic EE mentioned by the authors were fiddler crabs affecting soil properties (Bertness 1985), desert snails facilitating nitrogen cycling
(Shachak et al. 1987), bagworm larvae transforming rock to soil and facilitating nutrient cycling (Wessels and Wessels 1991) and termites changing soil composition (Lal 1991).
Among the examples used for autogenic EE were microalgea enhancing melting and breaking of ice (Buynitski 1968, Arrigo et al. 1991), and marine phytoplankton enhancing the warming of surface water (Townsend et al. 1992).
The EE concept is used to describe the impact of organisms on the environment.
For example, earthworms altering soil properties (Jimenez and Decaens 2004), chironomid larvae altering sediment properties (Olafsson and Paterson 2004), caddisflies larvae regulating particle flow during floods (Cardinale et al. 2004), sockeye salmon affecting algae density and sediment properties (Moore et al. 2004), zokors (Rodentia) altering soil properties (Zhang et al. 2003), crayfish affecting sand and gravel erosion
8 (Statzner et al. 2000), frog (Rana sp.) tadpoles modulating sediment accrual (Flecker et al. 1999), blackfly larvae transforming organic suspension to sedimented fecal pellets
(Wotton et al. 1998) and pikas modulating nutrient availability to plants (Aho et al.
1998). Every species modulates its physical environment and is an EE. Practically study focuses only on key engineers, i.e, engineers that significantly affect the ecosystem.
As discussed previously, abiotic patchiness may affect species diversity. If the effects of an EE on the environment are patchy it is expected to result in assemblage contrast and therefore contributes to the overall species turnover in the system. Figure
1.1 describes the role of an ecosystem engineer in filtering and species turnover.
Consider the species pool of a country like Israel with an area of about 2x1010m2. The species pool contains organisms functioning as key ecosystem engineers, for example porcupines (Hystrix indica) creating patches of relatively high soil moisture whilst digging for bulbs (Shachak et al. 1991), and organisms that do not, such as annual plant species. Next in spatial hierarchy are areas of 104-107m2, such as Avdat or Mt.Meron
LTER stations. Those areas are subjected to different environmental conditions (e.g. climate), which function as environmental filters (sensu Keddy 1992) and control the flow of species from the species pool of the higher spatial scale (2x1010m2) to those of the lower spatial scale (104-107m2). As a result of that filtering the species pool of each area contains species that can tolerate its environmental conditions (stage 1 in figure 1.1).
For example, the woody flora of each of the above sites is dominated by different species adapted to the different climates; Quercus spp. in Mt. Meron and Hammada scoparia in
Avdat. As some of the species at each of the lower scale species pools are ecosystem engineers they introduce an additional set of environmental conditions which also
9 function as environmental filters (stage 2 in figure 1.1) controlling the flow of species to the area's species pool. For example, desert snails create nitrogen rich habitat by producing depositions of nitrogen rich feces, and by doing so facilitate the presence of higher plants (Jones and Shachak 1990). Each of the areas at the scale of 104-107m2 is comprised of areas of a lower spatial scale (~ 104m2), for example a watershed with different environmental conditions as affected by land use, topography, lithology etc. As in the case of the higher spatial scale, those environmental conditions function as environmental filters and control the flow of species from the species pool of the higher spatial scale (in this case 104-107m2) to those of the lower spatial scale (~104) so that the species pool of each area contains species that can tolerate its environmental conditions
(stage 3 in figure 1.1). At this scale, conditions induced by the ecosystem engineers again serve as additional environmental filters (stage 4 in figure 1.1). Each of the areas at the spatial scale of ~ 104 contains patches created by ecosystem engineers (engineered patches) and background patches. Environmental conditions not induced by ecosystem engineers serve as an environmental filter between the species pool and the species assemblage of the background patches, and environmental conditions induced by ecosystem engineers serve as a filter between the species pool and the species assemblage of engineered patches (stage 5 in figure 1.1). If the two filtering processes are not identical, the two patch types will differ in their assemblages, and assemblage contrast will be observed between them. Therefore, by inducing patchiness EE cause assemblage contrast, which is a form of species turnover, thus contributing to species turnover in the system (stage 6 in figure 1.1). This work will have a theoretical component (chapter 2), examining the connection between patchiness, filtering and species turnover, and an
10 experimental component (see chapters 3 and 4) testing the above connection in two different ecosystems.
10 Species Pool (~ 2*10 m2 )
Non Ecosystem Engineers Ecosystem Engineers
Environmental 1 2 Conditions
4 7 Species Pool (10 m 2 -10 m 2 )
Non Ecosystem Engineers Ecosystem Engineers
Environmental 3 4 Conditions
4 Species Pool (~ 10 m2 ) Non Ecosystem Engineers Ecosystem Engineers 5
4 4 Background patch (< 10 m 2 ) Engineered patch (< 10 m2 ) assemblage assemblage 6 Species Turnover
Figure 1.1 – Ecosystem engineering and its connection to species turnover. See text for further details.
11 Woody vegetation as ecosystem engineers
Hydrology supplies evidence for ecosystem engineering by trees and few examples are brought herein. Trees may increase runoff by causing fog-drip (Reiter and
Beschta 1995). Evapotranspiration and water recharge of Norway spruce (Picea abies) determines the level of soil water storage in forest ecosystems (Jost et al. 2005)
Evapotranspiration by trees attenuates accumulation and melting of snow, thus decreasing deep soil water storage (Harr 1976). Trees enhance water infiltration in a fragmented agricultural landscapes in eastern Australia (Eldridge and Freudenberger
2005). Soil chemistry in forests in northern Turkey varies according to the tree species producing the litter layer (Sariyildiz et al. 2005).
Soil science also provide evidence for ecosystem engineering by trees - soil organic matter, provided by trees, serves as storage of nutrients and increases water- holding capacity (Perry 1998). Trees growing in "tree islands" above tree line in the Front
+ - Range of Colorado decrease the level of composites such as NH4 and KCl in the soil
(Seastedt and Adams 2001).
In arid and semi arid environments woody vegetation grows in patches (Noy-Meir
1985). Ecosystem engineering by woody vegetation in arid and semi-arid ecosystems results in patchiness of several abiotic factors. Windblown soil grains are captured by shrubs and accumulate beneath them (Coppinger et al. 1991), thus forming patches of fine grained soil. Soil in shrub patches in rangelands is cooler comparing to soil in the uncovered matrix (Pierson and Wight 1991). Because soil temperature correlates with evaporation of soil water (Hillel 1980) patchy shrub cover can also result in patchiness in soil moisture (Breshears et al. 1998). In the Negev desert shrub-land in Israel shrub
12 patches serve as sinks for runoff and soil originating in the surrounding crust patches
(Shachak et al. 1998, Oren 2001). A possible mechanism for that effect could be the role of litter deposited by the shrubs, which reduces runoff and soil erosion (Boeken and
Orenstein 2001).
The abiotic patchiness caused by patchiness of woody vegetation affects community structure and species diversity and few examples are brought herein. Woody vegetation in the upper Sil basin in north western Spain creates a shaded environment inhibiting the development of herbaceous species (Fernandez-Alaez et al. 2005). Boeken et al. (2004) found that shrubs in the Negev desert create patches of reduced soil temperature and by doing so, inhibit germination of Stipa capensis. Oren (2001) found that in the Negev desert in Israel plant density and species richness in shrub patches is higher comparing to adjacent uncovered crust patches. When proportion of shrub patches in Negev desert shrub-land was changed it results in a change in species composition of herbaceous species community (Boeken et al. 2005). Manjang (2005) found that species composition of herbaceous species assemblages responds to patchiness of woody vegetation in Mediterranean woodland. This work will further explore the effect of woody vegetation patchiness on species diversity, and test whether, in addition to plants, such patchiness affects animal species diversity.
Ecosystem engineering by woody vegetation, and its effect on species diversity, is expected to depend on rainfall amount. Michalet et al. (2003) examined understory assemblages of two tree species, Abies alba and Picea abies, in the Alps along a rainshadow gradient and found that association between canopy species and understory assemblages increases towards the xeric end of the gradient. They suggested that under
13 drier conditions canopy plays a more important role in attenuating environmental stress, and therefore has a greater effect on understory species composition. Following the rationale of Michalet et al. both abiotic contrast and assemblage contrast are expected to be higher as rainfall stress increases. However, theoretical examination of ecosystem engineering importance in determining community processes suggests that the trend described by Michalet et al. does not reflects the whole picture; discussing the factors determining densities of prey and plant species, Bruno et al. (2003) suggested that the importance of stress amelioration by organisms (and hence of ecosystem engineering) increases with the increase in environmental stress, becomes maximal between medium and high levels of environmental stress, but then declines towards the extreme end of the stress gradient. Authors suggested that at extreme levels of environmental stress amelioration of abiotic stress by organisms is no longer effective. Ecosystem engineering processes therefore become less important under extreme stress, and abiotic stress becomes the most important factor in determining prey and plant densities. The above rationale can be valid for any effect of EE on community processes, and not only for prey and plant densities. It is also important to note that the above relates to the engineering capacity of the EE's and not to their density or dominance.
It is therefore expected that when tested under harsher rainfall stress than that tested by Michalet et al. effects of woody vegetation ecosystem engineering will be weaker closer to the dry end of the rainfall gradient. This is especially likely considering the fact that woody species in extreme environments such as deserts are small shrubs rather than trees, and any effect they might have is further diminished due to their low biomass and volume relative to woody species in more benign environments. Therefore,
14 when tested in Israel woody vegetation ecosystem engineering is likely to result in higher levels of abiotic and assemblage contrast under higher rainfall levels, rather than lower ones.
Purpose of this work
In my work I will examine by a conceptual model the connection between patchiness, filtering and species turnover. I will examine experimentally how patchiness of woody vegetation affects species diversity of ground dwelling beetles from the perspective of the models. The above will take place at two study sites, Adulam and
Avdat, with 400 mm and 100 m annual rainfall regimes respectively. At each site will refer to two types of patches, "woody" patches (covered by woody vegetation), and
"open" patches (open patches) and will refer to the species assemblages found in them as landscape entities with contrast between them.
A change in species diversity at a site could be a result of inter specific interactions or ecosystem engineering. Using patchiness in the proportion of direct sun- light at ground level as an example of ecosystem engineering by woody vegetation I will test whether changes in beetle diversity are related to trophic or engineering effects (see methods for further detail). If woody vegetation patchiness modulates patchiness in light, and at the same time creates patterns of beetle diversity that cannot be explained by trophic interactions, then it suggests that beetle species turnover could be a result of ecosystem engineering by woody vegetation.
15
Hypotheses
My work focuses on two main hypotheses related to the relationship between abiotic contrast generated by woody vegetation as EE and species assemblage contrast of beetles. As described above, an increase in abiotic patch contrast is expected to increase assemblage contrast, therefore -
Hypothesis 1: Assemblage contrast correlates with patch contrast.
My prediction is that high contrast in light between "open" patches and "woody" patches will correspond with assemblage contrast between those two patches.
Under lower rain fall levels woody vegetation in Israel develops smaller canopy and biomass. As canopy plays a role in blocking sun light from reaching the ground, it is therefore expected that in area of low rainfall more sunlight will penetrate the canopy and reach the ground. Therefore, patch contrast in direct sunlight is expected to decrease with rainfall. As discussed above, assemblage contrast is expected to decrease with patch contrast. Woody-open assemblage contrast is therefore also expected to decrease with rainfall. Considering all of the above my second hypothesis is -
Hypothesis 2: Higher levels of patch and assemblage contrast will be observed in higher rainfall ecosystems in Israel.
My prediction is that the Adulam site will demonstrate higher levels of patch contrast
(measured as sunfleck, see methods sectiom for further detail) and assemblage contrast
(measured using Bray-Curtis distance, see methods section for further detail) than in
Avdat.
16 2. Filtering as a linkage between patchiness and species turnover – theoretical considerations
Definitions:
Filtering
Keddy (1992) suggested that species a assemblage of a given community is a non- random subset of a larger species pool. That subset is determined by the environmental conditions where the community is found. Keddy described those environmental conditions as a filter deleting from the community every species in the species pool that cannot tolerate those conditions. That process of deletion will be refered herafter as filtering (see glossary in box 2.1), which will be regarded minimal when no deletion takes place. When discussed in this chapter all filtering processes are assumed to have been taken place.
Patchiness and patch types
A useful definition of the term "patch" is one of the challenges facing anyone discussing landscape diversity. Addressing that difficulty Wiens (1976) described patches as being "distinguished by discontinuities in environmental character states from their surroundings". In accordance with Wiens' description this work will define patch as follows: A patch is an area distinct from its surroundings in the way it expresses a given environmental trait . For example, areas used by gazelles for marking their territory by droppings are enriched with nutrients (McClain et al. 2003) and are therfore patches differing from their surroundings in the level of nutrient concentration. A patch type
17 refers to all patches that are similar in the trait that defines them. Considering the example brought above, all areas enriched in nutrients by gazelle droppings belong to one patch type, and the area surrounding them belongs to another. Based on a definition suggested by Ostfeld et al. (1997) patchiness is defined in this work as a form of spatial heterogeneity in which different patch types may be discerned. The examples given above refer to patchiness in soil nutrient concentration. It is important to note the difference between patchiness and a gradient; what defines patchiness from a gradient is that the changes in space in the level of the concerned property are abrupt rather than gradual.
Differences in a patchy landscape refer to the contrast between the different patch types (e.g. Wijesinghe and Hutchings 1999). The term patch contrast refers to the magnitude of difference between adjacent patches in the trait that defines them. For example, if one patch of soil contains 30% soil organic matter (SOM) and an adjacent patch contains 55% than the SOM contrast between the two patches is 25%.
Species Turnover
Species turnover in considered here synonymous to beta-diversity (Whittaker
1960, and see discussion of species diversity in the introduction) and refers to the change of species composition in space. Rosenzweig (1995) commented that beta diversity appears in "a growing thicket of observations" but lacks theoretical perspective. Hansson
(1997) contributed to species turnover theory suggesting that physical patchiness results in functional patchiness, i.e. patchiness of species assemblages dependent on the physical feature. Functional patchiness nessecarily increases species turnover, as species
18 composition changes from one functional patch to another. Presented here is a conceptual model for explaining species turnover in relation to patchiness .
Box 2.1. Glossary
Assemblage contrast - The magnitude of difference in species composition between adjacent species assemblages
F iltering - Deletion of certain species, at a local scale, from a larger scale species pool that do not tolerate local scale environmental conditions
Patch - An area distinct from its surroundings in the way it expresses a given environmental trait Patch contrast - The magnitude of difference between adjacent patches in the abiotic trait that defines them. Patch type - All patches that are similar in the trait that defines them Patchiness - A form of spatial heterogeneity in which different patch types may be discerned. Species assemblage - All species found in a given locality
Species pool - A number of species at a large scale from which small scale species assemblages are generated
Species turnover - The change of species composition in space
19 The model
The rationale of the model will first be demonstrated for a landscape of two patch types (Figure 2.1). Consider a landscape of only two patch types, A and B, differing in an abiotic property. The species assemblages of the different patch types are defined by their species composition. Species turnover (beta diversity) between assemblages of different patches reflects the difference in species composition between those patches. It can therefore be considered as a case of patch contrast between species assemblages and is referred to as assemblage contrast. The term assemblage contrast is suggested as it reflects that, as any other patch contrast, species turnover is a spatial phenomenon.
The conditions of each patch type function as a filter, controlling species flow from the landscape species pool to the assemblages of the patch types. That control takes the form of deleting species that cannot tolerate patch type conditions from the patch type species assemblage (see Keddy 1992 for further discussion of filtering). That filtering results in a species assemblage comprised of all the species that can potentially be found in the patch type. The species assemblages of each patch type contain specialists that can only be found in one patch type, and generalists found in both patch types (represented by the gray rectangle in figure 2.1). The species turnover between the two patch types
(i.e. assemblage contrast) depends on the proportion of generalists and specialists in the system. In a case where all species in the landscape are generalists there is no assemblage contrast between the two patch types. If all species are specialists the assemblages of the two patch type do not have common species and assemblage contrast is maximal. The proportion of generalists and specialists in the landscape is a function filtering intensity, which is reflected in the proportion of the landscape species pool found in the patch type
20 assemblage. In a case where all species are generalists filtering intensity in both patch types is minimal so that all species of the landscape species pool flow to the assemblages of each of the two patch types. In a case where all species are specialists, each of the species is found either in the assemblage of patch type A or in that of patch type B, but never in both. If the proportion of generalist species is a function of filtering intensity and assemblage contrast depends on that proportion, than assemblage contrast is a function of filtering.
Figure 2.1 – Filtering and species turnover in a landscape with two patch types. White rectangle
represents species found only in patch type A. Black rectangle represents species found
only in patch type B. Gray rectangle represents generalist species found in both patch types.
21 A mathematical examination using the conventional diversity apportioning models reveals that the connection described above is valid for any number of patch types. Gamma diversity is comprised of alpha diversity and beta diversity. Apportioning gamma diversity to alpha and beta diversity is suggested to be either additive or multiplicative (Veech et al. 2002). I will demonstrate the connection discussed above on both additive and multiplicative apportioning models. The purpose of examining both models is not to compare between them but to show that connection between patchiness, filtering and species turnover is valid regardless of the apportioning model chosen.
Taking into account both additive and multiplicative models, gamma can therefore be expressed either as: g = a + b (2.1)
or as: g = a ∂ b (2.2) where is the mean number of species found in a single sample and denotes the species turnover between samples.
Following the additive model is expressed as: b = g -a (2.3a) and as: a = g - b (2.3b)
Following the multiplicative model is expressed as:
g b = (2.4) a
22 Examining the effect of patchiness on species turnover requires synthesis between diversity apportioning models as presented above and the concept of species filtering.
Assume a landscape comprised of patches differing in a physical property.
Assume that patches are classified to n distinct patch types. Rather than relate to an entity consecutive in space, a will now denote the number of species found in a patch type, which is represented by several disconnected patches. The average alpha diversity can be expressed as:
1 n a = ƒa i (2.5) n i=1
- where a i denotes the number of species found in the i-th patch type (see box 2.2 for all annotations used herein).
In this model g represents the landscape species pool (higher scale) and ai represents the number of species in the assemblage of the i-th patch type (lower scale).
Patch types can be estimated for the intensity of their filtering. If all the species of the landscape are found in a given patch type then no filtering has occurred in it. If no species of the landscape are found in a patch type then maximal filtering has occurred.
Filtering value f for patch type i is expressed by the ratio:
a f = 1- i (2.6) i g
f ranges from 0-1, receiving the value of 0 implies no filtering. When filtering is 1, it implies 0 flow of species into the patch. The average filtering for all patch types can be expressed as:
23 a f = 1- (2.7) g
The gamma, alpha and beta diversities allow examination of the relation between environmental filtering and assemblage contrast. Following the additive model of diversity apportioning, a substitution of eqn (2.3b) in eqn (2.7), when a is being used fora gives:
g - b f = 1- (2.8) g
Thus, b = g ∂ f (2.9)
The additive model suggests that assemblage contrast () is a function of average filtering and the slope of the function depends on the species pool.
Following the multiplicative model of diversity apportioning, a substitution of eqn (2.2) in eqn (2.7), when a is being used fora gives:
1 f = 1- (2.10) b
Thus,
1 b = (2.11) 1- f
The multiplicative model therefore suggests that assemblage contrast is an increasing non-linear function of average filtering. Assemblage contrast rises sharply at high values of filtering.
24
Box 2.2. Annotations used in species diversity model for patchy landscapes
Annotation Definition
n Number of patch types in the landscape
g The number of species found in the entire landscape
a i The number of species found in patch type i
a The average number of species found in a patch type
b Assemblage contrast, the species turnover between patch types
fi Filtering in patch type i
f Average filtering in the landscape
The above analysis indicates that assemblage contrast (i.e. species turnover between different patch types) is an increasing monotonic function of environmental filtering caused by patchiness. This is true regardless of the diversity apportioning model considered. The conclusion is that in patchy ecosystems environmental filtering contributes to species turnover, and therefore to species diversity.
25 3. Methods
Experimental design
This work used the experimental design of a research programme titled " Biodiversity patterns and processes in water-limited ecosystems: a unifying approach", headed by Prof.
Moshe Shachak of the Jacob Blaustein Institute for Desert Research. The programme examines species filtering processes induced by woody ecosystem engineers at five LTER
(Long Term Ecological Research) stations along the rainfall gradient in Israel (figure 3.1).
Mt. Meron
Reammaat tH Haa-Nnadiivv
Adulam
Lehavim
Avdat
Figure 3.1 – LTER stations in the research programme titled " Biodiversity patterns and processes in water-limited ecosystems: a unifying approach"
26 The experimental design for each station in the project was similar. The basic experimental unit is a plot of one dunam (1000 m2). Plots were subjected to one of two canopy removal treatments; in removal plots woody vegetation was removed to ground level and. In uncut plots woody vegetation was not removed. In addition, two grazing regimes were practiced - for each removal treatment, half of the plots were subjected to grazing of goats or of a mixed herd of goats and sheep (depending on the station), the other half were fenced to exclude grazing livestock (hereafter exclusion).
Number of plots, time of removal and species of woody vegetation differed between stations and will be discussed as part of the study site description. The experiment was conducted in a block design with each block containing all four possible combinations of grazing regime and removal treatment (figure 3.2).
Two patch types were defined in each treatment: The first type contains woody patches where ground surface is under the canopy of a woody plant or had been so before removal. The second type contains open patches were woody vegetation did not cover ground surface before the beginning of the experiment. In each plot three woody patches and three open patches were selected by the field personal. An effort was made that patches will be evenly distributed within the plot. Optimal distribution was sometimes compromised as soil depth did not always allow digging traps at optimal locations. Three pitfall traps were placed in each patch (figure 3.2). Pitfall traps were dry plastic cups of 10 cm deep and 10cm in diameter fit into the ground with cup rim at ground level. Inadequate soil depth was also the reason why distances amongst traps differed amongst patches. Distance between traps might influence species richness of sampled assemblages but was not found to influence their species composition or their abundance (Ward et al. 2001). Melbourne (1999) found that pitfall traps are sensitive to changes in species diversity measures resulting from a change in habitat structure. Melbourne suggested the dilution hypothesis, stating that
27 habitats with more complex structures have a greater surface and can therefore accommodate a larger number of individuals. Honék (1988) suggested that pitfall trapping is sensitive to microclimate affects on habitat preferences of arthropods.
Detection of beetle response to habitat structure and microclimate makes pitfall traps a useful tool for the purpose of this work, which concentrates on small scale landscape diversity effects on beetle species diversity. Melbourne (1999), however, suggested that because the pathway of certain species can be more tortuous at certain habitat layouts (e.g. when continuously circumventing grass in dense grassland, Crist et al. 1992) there are certain habitats where those species are more likely to be trapped regardless of their habitat preference. Any result of pitfall trapping should therefore be scrutinised in view of that limitation.
Ahearn (1971) suggested that pheromones produced by female darkling beetles (Tenebrionidae) captured in pitfall traps might cause an aggregation of male specimens in the traps, which might bias results. However, when experimentally tested in Eleodes obsolete no such effect was detected (McIntyre 1998).
Every sampling session took place once a year in the spring for five consecutive days. Spring was chosen as it was assumed that both winter and summer faunas will be represented, which will maximize species richness (Groner, personal communication) During the sampling session traps were left open and were emptied every day. All invertebrates caught were preserved in 70% alcohol with trap, patch type, patch, removal treatment, grazing regime, block, site and sampling session recorded. An exception was made for several easily identified specimens, which were recorded in the field and then released after being marked with a dot of nail-polish.
Marking of released specimens was essential to prevent recaptured individuals from being counted more than once during data analysis. Vertebrates caught in the traps were released.
28 Uncut Removal g n i z a r G n o i s u l c x E
- Open patch - Uncut tree/shrub - Pitfall trap
- Woody patch - Grazing livestock - Exclusion fence
Figure 3.2 – Illustration of a single block in the experimental design.
29 Focal group and specimen identification
Beetles (Coleoptera) were chosen as the focal group for several main reasons:
they are relatively abundant, which allows quantitative data analysis, they are very
diverse (Evans and Bellamy 2000), easily captured and their taxonomy in Israel is
relatively known. In addition they contain three trophic groups, detritivores,
herbivores and predators, which allows examining whether community response to
experimental manipulations is trophic (herbivores responding to loss of food source
after canopy removal), or a response to a change in abiotic conditions (in which case
it may also be observed in detritivores). Specimens were identified to the species or
morpho-species level with assistance of Elli Groner (Blaustein Institutes for Desert
Research. Ben Gurion University, personal communication) and Vladimir Chikatunov
(Department of Zoology, Faculty of life Sciences, Tel-Aviv University, personal
communication). Each species was also identified by its trophic group using Johnson
and Triplehorn (2004).
Study sites:
Because one of the goals of this work was examining the landscape-species
diversity relations under different environmental conditions, my research took place at
two study sites, Adulam and Avdat LTER stations, rather than just one.
Unless otherwise noted the description of Adulam and Avdat study sites
brought herein is based on Sheresta (2005) and Camara (2005) respectively.
Adulam LTER station is located at the Adulam nature reserve in the Judean
low land region (lat.: 31o60’N and long: 34 o 90’E). The area is characterized by low
hills with an altitude of 250-400 m. and narrow wadis. The Adulam nature reserve
covers an area of 500 hectares (5,000 dunams) and lies between the settlements
Nechusha and Zafririm. The geology of the area consists of chalk and naari strata of
30 the Eocene period. The chalk is covered with light rendzina soil and the naari - with brown rendzina. The reserve is surrounded by agricultural land to north, and afforested pine tree stands to the south (Shifman and Kuller 2002). The area is characterized by Mediterranean climate with mild, rainy winters, and hot dry summers with high solar radiation and high rates of evaporation. Mean annual rainfall in the area is 400 mm, occurring mostly during winter, between November to
March. Winter minimum mean temperature of the area is 60 c and summer maximum mean temperature is 330 c. The vegetation of the area is typically Mediterranean-type where prevalent woody species are Quercus calliprinos, Pistacia lentiscus and
Phillyrea latifolia. Historical sites in the area, such as the ruins of Midras, provide evidence for historical periods during which the region was extensively used by local dwellers. The area has been subjected to anthropogenic disturbances such as fire, grazing pressure, agriculture and wood-cutting for fuel and shelter for thousands of years. Since the declaration of the reserve (1950) human activity was excluded from the area. The land cultivated in the past (valleys) is now covered with woody vegetation; mostly sclerophylous species. In recent years a mixed herd of goats and sheep was re-introduced to the reserve as a management tool, mainly to help prevent accumulation of dry vegetation that supports wildfires. The tudy site in Adulam is divided by a wadi , with three blocks (see figure 3.2) on the south facing slope of the wadi and three on the north facing one. Removal of canopy in Adulam took place in
October 2002 and was not repeated due to administrative and financial constrains. woody patches in Adulam were patches covered by Quercus calliprinos, Pistacia lentiscus or Phillyrea latifolia. Sampling took place in April 2004.
The Avdat LTER station is located in the the Central Negev highlands 13 km south of the Sede Boker Campus along the Beer-Sheva-Eilat highway (lat: 30° 47' N, long: 34°
31 46' E.). The elevation of the study area ranges between 600 and 700 mm. The
substrate consists of loess, sandy wadis, rocky slopes (chalk) and ancient agricultural
terraces. The mean annual temperature of the Central Negev highlands is 170C to
190C. Annual rainfall of approximately 95 mm. Vegetation is dominated by dwarf
shrubs (Hamada scoparia). Common herbaceous species in the area include Schismus
arabicus, Plantago coronopus, Astragalus tribuloides and Malva aegyptica. There is
evidence of runoff agriculture by the Nabateans (approx. 0-300 AD) in the form of
agricultural terraces in the study area. Bedouin, currently inhabiting the area, practice
sedentary pastoralism. Grazing in the area is mainly by goats, sheep and camels. The
study site in Avdat consisted of five blocks (see figure 3.2). Canopy removal in Avdat
took place in February 2004 and again in February 2005. Woody patches in Avdat
were patches covered by Hamada scoparia. Because an area covered by the canopy of
a single Hamada scoparia cannot accommodate three pitfall traps a triplet of closely
neighbouring shrubs was considered as one woody patch, and one pitfall trap was
placed under each of the three shrubs. The first sampling took place in April 2004.
However, because sampling occurred only few weeks after the first removal, results
could not be compared with results in Adulam, where sampling occurred more than a
year after canopy was removed. In addition results were less likely to reflect a
response to experimental manipulations. Additional sampling therefore took place in
April 2005 and results of that sampling are the ones discussed in this work.
Significant results of assemblage contrast analysis for Avdat 2004 will appear in
appendix 1 but will not be discussed.
32 Scale definitions
At each station two main scales were mostly used. The first is the treatment
combination containing all plots subjected to a given combination of removal
treatment and grazing regime. For example, all grazed plots where canopy was not
removed belong to one treatment combination (uncut*grazing), whereas all ungrazed
plots where canopy was removed belong to another treatment combination
(removal*exclusion) etc. It is very likely that because sampling took place for only
five days not all species were captured, therefore, rather than using the term species
pool, the term apparent species pool will be used to denote all species captured at a
given scale. The apparent species pool of each treatment combination is comprised of
all the species sampled in it. For example all species found in ungrazed plots where
canopy had been removed comprised the removal*exclusion apparent species pool.
Second in scale hierarchy were the apparent species pools of each patch type within
each treatment combination. For example, all the species found in woody patches in
ungrazed plots where canopy had been removed comprised the
removal*exclusion*woody apparent species pool, which is nested within the apparent
species pool of the removal*exclusion treatment combination. Because of the low
number of individuals captured in a single patch, all single patches, regardless of their
type or treatment, are highly dissimilar in their species composition. Therefore, single
patches could not be considered as true replicates. To solve that problem I have
considered each three patches of the same type and within the same plot to be a single
sample. That sampling unit was referred to as patch type in plot (hereafter PTP) and
served in this work as the basic replicate for analysis of the apparent species pools of
each patch type within each treatment combination. The apparent species pool of each
33 patch type within each treatment combination was therefore represented by five PTP's
in Avdat and by six in Adulam.
Dominance
Dominance index (Turner 1989) was calculated for each PTP to see whether
individuals are evenly distributed amongst species. The index Do is calculated as
follows:
n Do = ln(n) + ƒ Pi ln(Pi ) (3.1) i=1
Where n is the number of species in a sample and Pi is the proportion of individuals in
the sample belonging to the ith species. The index approaches the value of 0 as
individuals are more evenly distributed between species.
Patch contrast
One of the abiotic properties which represent vegetation cover is sunfleck, the
fraction of ground level area receiving direct sun light. Measurements of sunfleck
were taken in August 2005. For sunfleck measurements I used “SUNFLECK PAR
Ceptometer” (Decagon Devices, Inc., Pulliman, Washington, USA). Measurements
were taken for photon flux at the photosynthetic active radiation waveband (PAR).
Sunfleck measurements were as follows: at each plot threshold value of photon flux
was reset for half the photon flux value measured in an exposed area in the time of
measurement. Two pairs of adjacent patches, one woody and one open, were then
selected. In each pair sunfleck was measured for each patch as follows: the device
was placed on the ground with the centre of the light wand adjacent to the centre of
the patch. In woody patches I assured that the light wand was placed opposite to the
34 direction of the sun at the time of measurement. The output was the fraction of area receiving photon flux beyond the threshold value. Patch contrast was then calculated for each pair of patches as the difference in sunfleck between the two patches. I used general linear model (GLM) to analyse the sunfleck contrast between the patch types under each treatment combination.
Assemblage contrast
Species turnover was calculated using dissimilarity indices. Many of the similarity indices used for calculating differences in species composition are based on binary (presence/absence) data, without taking abundance into account (Koleff et al.
2003). Those indices however omit important ecological information. For example, two samples containing two competing species, the first being dominated by one species and the second by another, will be treated by such indices as identical, though it is clear that communities in those samples are not the same. In addition those indices are not suitable for studying mobile organisms in the small scale used in this work; single individuals of a species of one habitat may be found in samples of the other as a result of random drift. Indices relying on binary data sets will treat such species as ubiquitous, though they function and are part of community processes in only one habitat. In such a case the calculated value for assemblage contrast will be lower than the actual one. Species with only one captured individual (singletons) present another problem. Such species are found by default in only one habitat and there is no way of telling whether they prefer that habitat or are potentially ubiquitous.
Presence absence indices will treat such species just as they treat abundant ones, and as singletons always appear in only one habitat, they are bound to increase assemblage contrast even if actual assemblage contrast is lower. Therefore, rather then using a presence absence index for calculating assemblage contrast and internal
35 variation, I used Bray-Curtis distance (Bray and Curtis 1957), which is abundance
sensitive, and is frequently used in ecological research. (e.g. Damasceno-Junior et al.
2005, Huff et al. 2005).
Bray-Curtis distance between two samples i and j is calculated as:
k ƒ| xik - x jk | = k =1 dij k (3.2) ƒ(xik +x jk ) k =1 where xik and xjk denote the number of individuals of a given species k captured in
samples i and j respectively. The higher dij is, the lower the similarity between the
assemblages of i and j.
An important feature of Bray-Curtis distance is that it differentiates between
cases where species are part of the community in both of the compared habitats and
cases where individuals of a species are highly abundant in one habitat but randomly
drift to the other. Table 3.1 shows a set of 11 hypothetical samples each containing
the same five species. The difference between sample 10 and sample 11 is a
quantitative one. Both samples contain high numbers of the same species, and all
species can therefore be said to be present at both sites. In contrast, if samples 1 and
11 represent adjacent habitats then the case is different – the number of individuals of
a given species found in one habitat is negligible comparing to that found in the other.
It is therefore very likely that the few individuals captured in sample 1 do not use that
location as habitat and were moving between patches of their habitat, which is
represented by sample 11 (to be referred to hereafter as random drift). The sampled
species are therefore not likely to be a part of community processes in the habitat of
sample 1. I performed a simulation in which I calculated the similarities of the
samples of the hypothetical table 3.1.The simulation demonstrates how the Bray-
Curtis distance measure discriminates between cases where species presence in two
36 compared samples is due to random drift and cases where it is due to ubiquity of the
species. Figure 3.3 demonstrates the above by showing how the Bray-Curtis distance
values rise steeply from scenarios where species are ubiquitous to scenarios where
individuals in one sample were likely to have randomly drifted from the habitat of the
other.
Table 3.1 - A hypothetical sampling matrix representing 11 samples of five species. Entries are numbers of captured individuals.
Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Sample 11 Species A 1 2 3 4 5 6 7 8 9 10 11 Species B 1 2 3 4 5 6 7 8 9 10 11 Species C 1 2 3 4 5 6 7 8 9 10 11 Species D 1 2 3 4 5 6 7 8 9 10 11 Species E 1 2 3 4 5 6 7 8 9 10 11
Assemblage Cnontrast between Samples of Table 2
0.9
0.8 0.7 likelihood e
c for n
a 0.6 t random drift
s i D
0.5 s i t r 0.4 u C - y 0.3 likelihood a r
B 0.2 for ubiquity 0.1 0 1 1 1 1 1 1 1 1 1 1 2 3 4 5 6 7 8 9 1 v v v v v v v v v v v v v v v v v v 0 s s s s s s s s s s s s s s s s s s v . . . 9 . 8 . 7 . 6 . 5 . 4 . 3 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . s 11 10 10 . 11 Compared Samples
Figure 3.3 œ A ssemblage contrast between hypothetical samples of table 3.1 calculated using Bray-Curtis distance. Compared samples are assumed to represent adjacent habitats.
Examining patchiness effect on species assemblages present methodological
obstacles that call for a unique ANOVA model. Unlike conventional ANOVA models
37 withing and between variation are not in a quantitative measure (e.g. temperature etc.) but a qualitative one (species composition). Scenarios in which variation within patch types is equal to or greater than variation between them are the ones where patch type does not affect species composition significantly. Assume two patch types 1 and 2.
Figure 3.4 demonstrates five scenarios in which assemblage contrast is being observed between those two patch types. Scenarios I-III have similar, high, level of assemblage contrast and scenarios IV and V have a lower one. However, only in scenarios I and V the observed patchiness is the main cause for assemblage contrast.
Scenario I represents the simple case where filtering by the different patch types is the main cause for assemblage contrast.
In scenario II there is an additional factor, unrelated to the patchiness pattern, creating assemblage contrast. When patches are being grouped by that factor assemblage contrast between the newly formed groups is just as high as the one between the two patch types. In such a scenario there is therefore another factor, which is just as important as the patch type in defining the niche (sensu Hutchinson
1959) of the species, hence their filtering.
In scenario III assemblage contrast is an artifact of high variabilty among single patches. Such variability can either be explained by the irrelevence of the patch type for filtering, or by high ecological equivalance (sensu Hubbell 2005). In such a scenario any division of single patches into two groups will result in high assemblage contrast.
In scenario IV there is an additional factor, which plays a greater role than the patch type in species filtering. Grouping the patches by that factor will result in a higher assemblage contrast than the one between patch types.
38 Scenario V demonstrates a case where the assemblage contrast is observed not because species are being replaced by others, but because species assemblage of one patch type is a subset of that of the other patch type.
39
I Patch type 1 Patch typ e 2 II Patch type 1 Patch typ e 2
A B C D A C
A B C D A C
A B C D B D
A B C D B D
III Patch type 1 Patch typ e 2 IV Patch type 1 Patch typ e 2
A E A A C
B F A A C
C G B D B
D H B D B
V Patch type 1 Patch typ e 2
A B
B B
A B
B B
Figure 3.4 – Five scenarios where assemblage contrast between two patch types is
observed. Each letter denotes an assemblage of species. Dashed and tortuous
lines represent alternative divisions resulting in species turnover. Note that only in two cases, I and V, patch type is the main cause for species turnover in the system.
40 The above example demonstrates that the variation in species composition within patch types (hereafter internal variation) should be taken into account before determining whether patch type affects species turnover. Therefore for statistical analysis of assemblage contrast I used PERMANOVA (Anderson 2001, Anderson
2005). PERMANOVA is a programme for permutational multivariate analysis of variance, receiving as input a matrix of samples and species, with species abundances as entries (e.g. table 3.1), the dissimilarity index preferred by the user and a file containing the experimental design. It then calculates the internal variation within each level of the examined factor (in this case patch type) and the average difference in species composition between different levels of the factor. It calculates a statistic
(F) based on those two values and performs permutation to see the probability of achieving the value of F randomly (p value). I considered p≤0.05 to indicate that assemblage contrast is mainly affected by the tested factor and is therefore significant.
For graphic presentation of samples and further examination of results I performed Non-metric Multidimensional Scaling – NMS (ter Braak 1995) using PC-
ORD software (McCune and Mefford 1997). NMS is a distance based ordination method and is therefore suitable for analysis and presentation of differences between samples. Using ordination plots is necessary to distinguish btween cases represented in scenario I and cases represented by scenario V, both in which assemblage contrast is significant.
To explore the role of individual species in creating assemblage contrast I also used distance based redundancy analysis (McArdle and Anderson 2001) based on
Bray-Curtis distance. I used DISTLM forward programme (Anderson 2003) to make two tests. I first tested what is the contribution of each species to the variation in species composition irrespectively of the contribution of other species (hereafter marginal contribution). I then tested the cumulative contribution of each species, i.e.
41 the contribution to the variation in species composition not explained by other species. To demonstrate the difference between the two types of contribution consider the following example – assume two species both distinctly preferring a given patch type A over a given patch type B. Both may have similar, and high, marginal contribution to the variation in species composition. However, the assemblage contrast between patch types A and B can easily be explained by either one of those species alone, with the other species not revealing new patterns in species composition. In such a case the first species to be considered will show high cumulative contribution to the variation in species composition, whereas the other shows a negligible one. The procedure I used, known as forward selection, begins with calculating the contribution of the species with the highest marginal contribution, it than finds which of the remaining species has the greatest contribution to the variation not explained by the first species, ranks it second to the first species and calculates its cumulative contribution to the variation in species composition (i.e. the proportion of variation it explains and is not already explained by the first species). It repeats that procedure until all species are ranked by their cumulative contribution.
The output is a list of species ranked by their cumulative contribution to variation in species composition and showing the contribution values of each species.
Contribution values of all species sum up to 1.
In addition I used incidence-abundance graphs (Boeken et al. 2005)showing for each species the number of samples where it was found against the average number of individuals of that species in a sample containing the species. This allowed me to further explore the mechanism behind patterns of assemblage contrast, as will be demonstrated in the discussion.
42 General patterns
Activity and species richness patterns of ground dwelling beetles in my study
sites were analysed using General linear model (GLM). This analysis is not directly
related to my research questions and is brought for mere illustration of major
community patterns in the study sites. Analysis was done for the entire ground
dwelling beetle community and for each trophic group separately. As discussing the
results of that analysis extends beyond the scope of this work, significant results of
activity and species richness analysis will be presented in appendices 2 and 3
respectively but will not be discussed.
43 4. Results
In Adulam a total of 821 individuals were captured in 432 pitfall traps during
five days. 64 species and morpho-species were identified, representing 24 families.
The dominant families were Tenebrionidae (darkling beetles), Carabidae (ground
beetles), and Cleridae (checkered beetles). In Avdat 2005 sampling session a total of
896 individuals were captured in 360 pitfall traps during five days. A total of 66
species and morpho-species were identified representing 28 families. The most
dominant families were Tenebrionidae, Curculionidae (weevils), and Meloidae
(blister beetles). Lists of species recorded in the above sampling session appear in
appendix 4. As sampling took place for only five days it could be that not all species
in the region were sampled. It could also be that because of the relatively short
trapping session there was not enough time for certain species to be trapped in their
entire habitat, and were captured only in few traps. This might have resulted in high
levels of internal variation in some apparent species pools. Results should be
scrutinised in view of that limitation.
.
Dominance
In Adulam, dominance, which is the inverse of evenness, changes between
treatment combinations (Figure 4.1) It is especially increased by canopy removal
(Table 4.2 Fig 4.2). This effect is slightly stronger for woody patches (Fig 4.2).
Dominance in woody patches doesn't change significantly between grazing and
exclusion but is higher for grazing in open patches (figure 4.3, table 4.1), this effect
however is by far weaker than the effect of canopy removal mentioned above. In
44 contrast, dominance in Avdat does not respond to removal treatment, grazing regime
or patch type (Table 4.2, Figure 4.4).
Adulam Mean Dominance for PTP
1 0 .9 0.8 a 0 .7 a e c
n 0.6 a
n i 0.5 a b m a b o 0.4
D 0.3 b 0.2 b 0.1 b b 0 RReemmoovvaall RRememovoavlal RReemmoovvaall Reemmoovvall CUonnctruotl CUonncturot l CUonncturtol UConncutrtol GGrraazziningg GGrarzaizningg Exxccllutsioionn Exxclustioionn Grrazing Graziing EExxcclulustiion EExxcclulustiioonn ooppeenn wwoooddyy ooppeenn wwoody ooppeenn wwoody open wooooddyy
Figure 4.1 – Dominance values for each patch type and treatment combination in Adulam. V ertical bars denote 0.95 confidence intervals. Samples not sharing a letter are significantly different.
45
Adulam, Mean Dominance for PTP by Removal Treatment*Patch Type; LS Means Current effect: F(1, 40)=4.3406, p=.04365 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals
0.8
0.7 Woody 0.6
0.5
e 0.4 c n a n i 0.3 m
o Open
D 0.2
0.1
0.0
-0.1 -0.2 Open Removal Uncut Woody Removal Treatment
Figure 4.2 – Interaction between removal treatment and patch type effects on dominance in Adulam
46
Adulam, Mean Dominance for PTP by Grazing Regime*Patch Type; LS Means Current effect: F(1, 40)=17.605, p=.00015 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 0.7
0.6 Open
0.5
0.4 e c n a n
i 0.3 m o D 0.2 Woody
0.1
0.0
-0.1 Open Grazing Exclusion Woody Grazing Regime
Figure 4.3 – Interaction between grazing regime and patch type effects on dominance in Adulam
47
Avdat '05 Mean Dominance for PTP
0.8
0.7
0 .6
e e c c 0.5
n n a a n 0.4 o n
i m o
m 0.3 D o D
0.2
0 .1
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion open woody open woody open woody open woody
Figure 4.4 – Dominance values for each patch type and treatment combination in Avdat 2005. Vertical bars denote 0.95 confidence intervals.
Table 4.1 – Three way ANOVA of dominance for beetle assemblages Adulam.
Significant effects denoted in bold characters.
SS Degr. of MS F p
Freedom
Intercept 4.996 1 4.996 112.823 < 0.001 Removal 1.477 1 1.477 33.352 < 0.001 Grazing 0.137 1 0.137 3.091 0.086 Patch type < 0.001 1 < 0.001 0.001 0.979 Removal*Grazing 0.004 1 0.004 0.090 0.765 Removal*Patch type 0.192 1 0.192 4.341 0.044 Grazing *Patch type 0.780 1 0.780 17.605 < 0.001 Removal*Grazing*Patch type 0.090 1 0.090 2.050 Error 1.771 40 0.044
48
Table 4.2 - Three way ANOVA of dominance for beetle assemblages in Avdat.
Significant effects denoted in bold characters
of Degr. SS freedom MS F p Intercep t 2.555 1 2.555 56.281 < 0.001 Removal 0.008 1 0.008 0.184 0.671 Grazing 0.014 1 0.014 0.318 0.577 Patch type 0.037 1 0.037 0.812 0.375 Removal*Grazing 0.009 1 0.009 0.201 0.658 Remova l*Patch type 0.003 1 0.003 0.067 0.797 Grazing*Patch type 0.017 1 0.017 0.379 0.543 Remova l*Grazing*Patch 0.003 1 0.003 0.077 0.784 type Error 1.271 28 0.045
In Adulam removal is the main factor increasing dominance. Most individuals in removal plots belong to a small number of species. Grazing regimes also affect dominance though not as strong as removal; in woody patches grazing decreases dominance whereas in open patches it increases it. In contrast Avdat dominance was not affected by either patch type or any treatment (fig. 4.4).
49 Sunfleck contrast
Removal treatment of woody vegetation significantly decreased sunfleck
open-woody patch contrast in Adulam, while grazing regime had no effect (table 4.3,
figures 4.5 and 4.6). Sunfleck contrast in Avdat is significantly higher in uncut plots
(figure 4.8). Sunfleck contrast changes significantly between uncut and removal only
under grazing (figure 4.9, table 4.4)
Adulam Mean Open-Woody Sunfleck Contrast for Treatment Combination
104
102
) b ab %
( 100
t s a r t 98
n ab
o
c a
k 96 c e l f n
u 94 s
92
90 Removal Grazing Removal Exclusion Uncut Grazing Uncut Exclusion
Figure 4.5 – Open-woody sunfleck contrast under different combinations of removal treatment and grazing regime combination in Adulam. Vertical bars denote 0.95 confidence intervals. Samples not sharing a letter are significantly different.
50
Adulam Mean Sunfleck Contrast by Removal Treatment; LS Means Current effect: F(1, 39)=11.979, p=.00132 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 102
101
100 ) % ( t 99 s a r t n o 98 c k c e l f 97 n u S 96
95
94 Removal Uncut
Removal Treatment
Figure 4.6 – Effect removal treatment on woody-open sunfleck contrast in Adulam.
51
Avdat Mean Open-Woody Sunfleck Contrast for Treatment Combination
100
90 b ) 80 % (
t 70 s a r
t 60 n o
c 50
k ab
c 40 e l f
n 30
u ab
s 20 10 a 0 Removal Grazing Removal Exclusion Uncut Grazing Uncut Exclusion
Figure 4.7 – Woody-open Sunfleck contrast values for each treatment combination in Avdat. Vertical bars denote 0.95 confidence intervals. Samples not sharing a letter are significantly different.
52
Avdat, Mean Sunfleck Contrast for Sample by Removal Treatment; LS Means Current effect: F(1, 32)=30.053, p=.00000 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 80
70
60 ) %
( 50
t s a r t 40 n o C
k 30 c e l f n
u 20 S 10
0
-10 Removal Uncut
Removal Treatment
Figure 4.8 – Effect of removal treatment on woody-open sunfleck contrast in Avdat.
53
Avdat, Mean Sunfleck Contrast for Sample by Removal Treatment*Grazing Regime; LS Means Current effect: F(1, 32)=11.647, p=.00176 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 120
100 Grazing
80
) % ( t
s 60 a r t
n o 40 C
k c e
l f 20 n u
S Exclusion 0
-20
-40 Removal Uncut Exclusion Grazing Removal Treatment
Figure 4.9 – Interaction between removal treatment and grazing regime effects on woody-
open sunfleck contrast in Avdat
Table 4.3 – Two way ANOVA of woody-open sunfleck contrast in Adualm. Significant effect shown in bold characters.
SS Degr. of MS F p Freedom Intercept 462581.0 1 462581.0 41108.69 < 0.001 Removal 135.7 1 135.7 12.06 0.0019 Grazing 4.4 1 4.4 0.39 0.536 Removal*Grazing 9.8 1 9.8 0.87 0.356 Error 495.1 44 11.3
54 Table 4.4 – Two way ANOVA of woody-open sunfleck contrast in Avdat. Significant effects denoted in bold characters.
SS Degr. of MS F p Freedom Intercept 52598.76 1 52598.76 75.239 < 0.001 Removal 22113.51 1 22113.51 31.632 < 0.001 Grazing 955.51 1 955.51 1.367 0.25 Removal*Grazing 8570.26 1 8570.26 12.259 0.001 Error 25167.23 36 699.09
In both sites removal significantly decreased sunfleck contrast. In Avdat removal decreased sunfleck contrast only under grazing. Grazing has increased sunfleck contrast in control plots in Avdat.
55 Assemblage contrast
Statistical analysis (PERMANOVA) of Adulam beetle assemblage contrast is
shown in tables 4.5 and 4.6 (results are referred to in detail further on). Non-metric
multidimensional scaling of Adulam beetles are shown in figures 4.10 – 4.12.
NMS - Adulam
2
1.5
1 0.5
0
-0.5
-1
-1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
R emoval, Grazing,open Removal, Grazing,woody Removal, Exclusion,open Removal, Exclusion,woody Uncut,Grazing,open Uncut,Grazing,woody Uncut,Exclusion,open Uncut,Exclusion,woody
Figure 4.10 – Non-metric multidimensional scaling ordination in Adulam showing all combinations of removal treatments, grazing regimes and patch types. Samples are PTP's. See additional fig ures for detailed presentation.
56 Table 4.5 – PERMANOVA of Adulam ground dwelling beetle assemblage contrast.
Significant effects are shown in bold characters. Analysis based on Bray-Curtis dista nce (No transformation, no standardisation). Source df SS MS F P(perm)
Removal 1 22701.94 22701.94 8.567 0.001 Grazing 1 6428.291 6428.291 2.426 0.015 Patch Type 1 8965.994 8965.994 3.384 0.005 Removal*Grazing 1 2123.686 2123.686 0.801 0.623 Removal*Pa tch Type 1 11807.43 11807.43 4.456 0.001 Grazing *Patch Type 1 6513.616 6513.616 2.458 0.019 Removal*G razing *Patch Type 1 1661.053 1661.053 0.627 0.819 Residual 40 105996.8 2649.92 Total 47 166198.8
Adulam NMS – Effects of Grazing and Removal on Woody and Open Assemblages
I Open Patches by Removal Treatment II Woody Patches by Removal Treatment 2 2 1.5 1.5 1 1 0.5 0.5 0 0 -0.5 -0.5 -1 -1 -1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
Removal Uncut Removal Uncut
III O pen Patches by Grazing Regimes IV Woody Patches by Grazing Regimes 2 2 1.5 1.5 1 1 0.5 0.5 0 0 -0.5 -0.5 -1 -1 -1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
Grazing Exclusion Grazing Exclusion
Figure 4.11 – Non-metric multidimensional scaling ordination in Adulam showing the effects of
canopy removal (1st row) and grazing regime (2nd row) on species assemblages of open patche s (1st column) and of woody patches (2nd column). Samples are PTP's.
57 Canopy removal and grazing had different effects on the different patch types
(table 4.5 figure 4.11). Canopy removal changes the species composition of woody assemblages, resulting in a new species assemblage in woody patches where canopy was removed which is segregated from that of the uncut woody patches (figure
4.11.II). In contrast, canopy removal does not change species composition of open assemblages (figure 411.I). Grazing changes the species composition of open assemblages. It creates a unique assemblage in the grazed open patches, which hardly overlaps that of the ungrazed (exclusion) open patches (figure 4.11.III). In contrast, grazing does not affect species composition in woody patches (figure 4.11.IV).
58 Adulam NMS – Woody & Open Assemblages under Different Treatment Combinations
I Uncut X Exclusion II Removal X Exclusion 2 2
1.5 1.5
1 1
0.5 0.5
0 0
-0.5 -0.5
-1 -1
-1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
III Uncut X Grazing IV Removal X Grazing 2 2
1.5 1.5
1 1
0.5 0.5
0 0
-0.5 -0.5
-1 -1
-1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
open woody
Figure 4.12 – Non-metric multidimensional scaling ordination in Adulam showing species assemblages of woody and open patches under different combinations of removal treatments and grazing regimes. Samples are PTP's.
59 Table 4.6 – Po st hoc analysis of Adulam ground dwelling beetle assemblage contrast. Significant effects shown in bold characters
Internal Internal Treatment*Patch Open/Woody Variation Variation Grazing type Interaction Treatment Assemblage of of Regime within each Contrast Open Woody grazing regime Patches Patches 0.85 Exclusion Uncut 0.87 0.77 (p>0.05) p<0.01 0.85 Exclusion Removal 0.79 0.41 (p<0.005) 0.97 Grazing Uncut 0.74 0.85 (p<0.005) p<0.05 0.5 Grazing Removal 0.57 0.48 (p>0.05)
In exclusion plots, a significant woody-open assemblage contrast appears only
where canopy has been removed (table 4.6, figures 4.12.I and 4.12.II). In exclusion
uncut plots woody samples are slightly different in species composition than open
ones (figure 4.12.I), but the high levels of internal variation between samples within
each patch type are close to the level of woody-open assemblage contrast causing it to
be non significant (table 4.6). This means that the main cause for woody-open
assemblage contrast in exclusion uncut plots is high variation in species composition
between samples that is unrelated to the patch type, and that the affect of patch type
on species composition has negligible contribution to woody-open assemblage
contrast. In exclusion plots where canopy was removed woody patches had a unique
assemblage with a low level of internal variation (table 4.6, fig 4.12.II).
Under grazing a significant woody-open assemblage contrast appears only in
uncut plots (table 4.6), where woody and open assemblages are segregated (figure
4.12.III). Grazed plots subjected to canopy removal had overlapping woody and open
assemblages (figure 4.12.IV) and a low, non significant, assemblage contrast (table
4.6).
60 The two most abundant species in Adulam, Opatrum libani and Tentyria herculeana (Tenebrionidae), both detrivorous, are also the two species having the greatest effect on variation in species composition (figure 4.13). O. libani shows the highest cumulative contribution to variation in species composition which is more than three times greater than that of the second contributing species, Microlestes syriacus (figure 4.14). Herbivores hardly affect variation in species composition in
Adulam (figures 4.13 and 4.14). Note, however, that unlike O. libani, T. herculeana makes little cumulative contribution to the variation in species composition (figure
4.14). This could be explained by the highly similar habitat preferences of those two species (figures 4.15 – 4.17), so that T. herculeana does not cause a new variation pattern not caused by O. libani.
.
61
Marginal Contribution to Variation in Adulam Species Composition (10 most contributing species) 0.25 D
n 0.2 o i t a i r a v
d
e 0.15 n i a
l D p x e
f o
0.1 P n o
i P t
r P P D o
p H P P o r 0.05 P
0 Opatrum Tentyria Anotylus Silvanus Microlestes Bombidion Blaps cribosa Brachicerus Nargus Ocypus mus libani herculeana complanatus abeillei syriacus rugicolla junix mohamme
Figure 4..193 – – D Disistatannccee bbaasseedd rreedundancyy aannaallyyssiiss ((mmaarrggininaal lt etsets,t ,B Brarya-yC-Curutirst ids idstiasntacnec) eo)f osfp ecies species effect on variation in species composition in Adulam. Letters denote trophic effect on variation in species composition in Adulam. Letters denote trophic group; D- group; D-detritivore, H-herbivore, P-predator. detritivore, H-herbivore, P-predator.
62
Cumulative Contribution to Variation in Adulam Species Composition
Tentyria herculeana (D) 1% Opatrum libani (D) 23%
Microlestes syriacus (P) 7% 61 others 62% Anotylus complanatus (P) 7%
Figure 4.14 – Distance based redundancy analysis (conditional test, Bray-Curtis distance) of species effect on variation in species composition in Adulam. Letters denote trophic group; D-detritivore, P-predator.
Species assemblages of removal open grazed and removal woody patches are
characterised by the two most abundant species: O. libani and T. herculeana. (figure
4.15), and dominated by them (figures 4.16 and 4.17). O. libani also dominates uncut
open grazed patches (figure 4.16). Two other relatively abundant species, Anotylus
complanatus (Staphylinidae) and Microlestes syriacus (Carabidae) are also shown in
the relevant figures for mere comparison.
63
Adulam NMS – Activity of Selected Species
I Opatrum libani II Tentyria herculeana 2 2
1.5 1.5
1 1
0.5 0.5
0 0
-0.5 -0.5
-1 -1
-1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
III Anotylus complanatus IV Microlestes syriacus 2 2
1.5 1.5
1 1
0.5 0.5
0 0
-0.5 -0.5
-1 -1
-1.5 -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
Absence Activity
Figure 4.15 – Non-metric multidimensional scaling ordination of Adulam showing activity (individuals/(trap*day)) of selected species (see text for details). Size of bubble approximately illustrates activity level, calculated as number of individual/trap*day. Samples are PTP's. See figure 4.10 for patch type and treatment of each sample.
64
Adulam, Uncut Grazing open Adulam, Uncut Grazing woody Incidence-Abundance (n=20) Incidence-Abundance (n=13) 25 25
20 20 e e c c n 15 n 15 a a d d n n u 10 u
b 10 b A A 5 5
0 0 0 0.2 0.4 0.6 0.8 1 0 0.1 0.2 0.3 0.4 0.5 0.6 Incidence Incidence
Adulam, Uncut Exclusion open Adulam, Uncut Exclusion woody Incidence-Abundance (n=19) Incidence-Abundance (n=17) 25 25
20 20 e e c c n 15 n 15 a a d d n n u 10 u 10 b b A A 5 5
0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 0.2 0.4 0.6 0.8 1 Incidence Incidence
Opatrum libani Tentyria herculeana Microlestes syriacus Anotylus complanatus
Figure 4.16 – Incidence-abundance graphs of uncut plots in Adulam. Each point is a species. Incidence is expressed by the proportion of samples containing the species. Abundance is expressed by the mean number of individuals for a sample containing the species. Filled diamonds represent species other than those uniquely denoted in the legend. See text for explanation on uniquely denoted species.
65
Adulam, Removal Grazing open Adulam, Removal Grazing woody Incidence-Abundance (n=21) Incidence-Abundance (n=13) 25 25
20 20 e e c
c n 15 n 15 a a d d n n u 10 u 10 b b A A 5 5
0 0 0 0.2 0.4 0.6 0.8 1 1.2 0 0.2 0.4 0.6 0.8 1 Incidence Incidence
A dulam, Removal Exclusion open Adulam, Removal Exclusion woody Incidence-Abundance (n=22) Incidence-Abundance (n=16) 25 25 20 20 e e c c n n 15
15 a a d d n n u u 10 10 b b A A 5 5 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 0.2 0.4 0.6 0.8 1 Incidence Incidence
O patrum libani Tentyria herculeana Microlestes syriacus Anotylus complanatus
Figure 4.17 – Incidence-abundance graphs of removal plots in Adulam. Each point is a species. Incidence
is expressed by the proportion of samples containing the species. Abundance is expressed by the mean number of individuals for a sample containing the species. Filled diamonds represent species other than those uniquely denoted in the legend. See text for explanation on uniquely
denoted species.
Statistical analysis (PERMANOVA) of Avdat beetle assemblage contrast is
shown in tables 30 and 31. Non-metric multidimensional scaling of Avdat beetles is
shown in figures 4.14 and 4.15. A significant woody-open assemblage contrast is
found in Avdat but it is not sensitive to either canopy removal or grazing regime
(table 4.7). Open and woody assemblages in Avdat are significantly different (table
4.8). Although having a certain degree of overlap on the ordination plot, there are also
areas in the plot unique either to the woody assemblage or to the open one (figure
4.19).
66
NMS - Avdat '05
1.5
1
0.5
0
-0.5
-1
-1.5 -1 .5 -1 -0.5 0 0.5 1 1.5 2
Removal, Grazing,open Removal, Grazing,woody Removal, Exclusion,open Removal, Exclusion,woody Uncut,Grazing,open Uncut,Grazing,woody Uncut,Exclusion,open Uncut,Exclusion,woody
Figure 4.18 – Non-metric multidimensional scaling ordination in Avdat 2005 showing all co mbinations of removal treatments, grazing regimes and patch types. Samples are PTP's.
67
NMS - Avdat '05 by Patch Type
1.5
1
0.5
0
-0.5
-1
-1.5 -1.5 -1 -0.5 0 0.5 1 1.5 2
open woody
Figure 4.19 – Non-metric multidimensional scaling ordination in Avdat 2005 by patch
types. Delineations denote areas in the plot unique to only one patch type. Samples
are PTP's.
Table 4.7 – PERMANOVA of Avdat ground dwelling beetle assemblage
contrast. Analysis based on Bray-Curtis distance, No transformation, no s tandardisation. Significant effects are shown in bold characters. Source df SS MS F P(perm) Remo val 1 1903.369 1903.369 0.605 0.891 Grazing 1 1591.933 1591.933 0.506 0.939 Patch Type 1 5309.853 5309.853 1.688 0.043 Removal*Grazing 1 4171.262 4171.262 1.326 0.167 Remo val*Patch Type 1 2343.863 2343.863 0.745 0.740 Grazing *Patch Type 1 1832.174 1832.174 0.582 0.912 Remo val*Grazing 1 2120.228 2120.228 0.674 0.840 *Patch Type Residual 32 100692.100 3146.629 Total 39 119964.800
68
Table 4.8 – Post hoc analysis of Avdat ground dwelling beetle assemblage contrast.
Open/Woody Internal Variation of Internal Variation of Assemblage Contrast Open Patches Woody Patches
0.779 (p<0.05) 0.782 0.745
In contrast to Adulam, assemblage contrast In Avdat cannot result from habitat preferences of one or two species. Redundancy analysis shows that in Avdat, as opposed to Adulam, the variation in species composition results from the cumulative effect of many species. Values of marginal contribution to variation in species composition are low and are relatively similar even for the ten most contributing species (Figures 4.20). Similarly, values of cumulative contribution to variation in species composition are low and are relatively similar even for the ten most contributing species (figure 4.22). This is a different pattern than that found at
Adulam, where a few species have a relatively high marginal effect on variation in species composition (Figure 4.21). Examination of incidence-abundance graphs of
Avdat shows that the same species are relatively abundant in both patch types.
Species assemblages of both woody and open patches both display high relative abundances of the same species and morpho species - Scleron multistriatum,
Gonocephalum perplexum, Sepidium tricuspidatum, Scyd5019 (Scydomidae) and
Meloid5006 (Meloidae) (fig 4.23).
69
Marginal Contribution to Variation in Avdat Species Composition (10 most contributing species) 0.05 D
0.045 D n 0.04 o
i H H t
a P i 0.035 H H D r
a D D v
d 0.03 e n i a l 0.025 p x e
f 0.02 o
n
o 0.015 i t r o
p 0.01
o r P 0.005
0 Hiontis Sfr-sp. Col-bro Scyd5019 Lampyris Chrys5024 Aploc5078 Mesostena Sepidium Pimelia bohmi tentyrioides nervosa punctata tricuspidatum
Figure 4.20 – Distance based redundancy analysis (marginal test, Bray-Curtis distance) of species effect on variation in species composition in Avdat 2005. Letters denote trophic group; D- detritivore, H-herbivore, P-predator.
70
Marginal Contribution to Variation in Species Composition, Adulam vs. Avdat (10 most contributing species in each station)
0.25 n o i t 0.2 a i r a v
d e
n 0.15 i a l
p x e
f
o 0.1
n o i t r o p 0.05 o r P
0 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th species species species species species species species species species species
Adulam Avdat
Figure 4.21 – Comparison of species effect on variation in species composition between Adulam and Avdat 2005 showing distance based redundancy analysis results (marginal test, Bray- Curtis distance) for the 10 most contributing species at each station.
71
Cumulative Contribution to Variation in Avdat Species Composition Hiontis tentyrioides (D) 5% Adelostoma grandis (D) 4% (H) nr-brown(H) Col-gre 3% 4% Mesostena punctata (D) 3% (H) white spotted 3%
Aploc5078 (H) 3%
Pimelia grandis (D) 3% Sepidium tricuspidatum (D) 56 others 3% 66% cruc5079 (H) 3%
Figure 4.22 – Distance based redundancy analysis (conditional test, Bray-Curtis distance) of species effect on variation in species composition in Avdat 2005. Letters denote trophic group; D-detritivore, H-herbivore.
Avdat, open patches Avdat, woody patches Incidence-Abundance (n=53) Incidence-Abundance (n=52) 10 10 9 9 8 8 7 7 e e c c 6 6 n n a a d d 5 5 n n u u b b 4 4 A A 3 3 2 2 1 1 0 0 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 Incidence Incidence
Scleron multistriatum Gonocephalum perplexum Scyd5019 Sepidium tricuspidatum Meloid5006
Figure 4.23 - Incidence abundance graphs comparing open and woody patches in Avdat 2005. Each point is a species. Incidence is expressed by the proportion of samples containing the species. Abundance is expressed by the mean number of individuals for a sample containing the species. Five relatively abundant species are uniquely denoted.
72 5. Discussion
Biodiversity is a phenomenon combined of several components; organisms,
landscape entities and resources (Shachak et al. 2005). This study demonstrated the
usefulness of discussing biodiversity from an integrative perspective, which links two
of those components, species and landscape entities. It examined species-turnover, a
phenomenon related to species diversity, by connecting it to landscape diversity. That
connection was manifested by acknowledging that species assemblages are landscape
entities, and that species turnover is therefore an expression of contrast between
landscape entities. The above rationale allows testing whether a given pattern of
patches results in a corresponding pattern of in species assemblages, thus testing the
effect of that patchiness on species diversity. Using patchiness in woody vegetation
cover as a model, this study experimentally examined how manipulations on patches
affect species turnover. This study provides new insights regarding the process of
woody vegetation as ecosystem engineering. Examining, theoretically, the concept of
environmental filtering and conventional concepts of species diversity, this study
suggests a theory for explaining species-turnover in patchy environments.
Results and conclusions of field work must however be examined in view of
the limitations of the sampling sessions. Conclusions regarding lack of effects, due to
insignificant results, might be an outcome of an artifact. This is because the caused
by the relatively short sampling session
Research hypotheses
Results indicate that both research hypotheses are rejected. Hypothesis 1
states that abiotic patch contrast correlates with assemblage contrast. This can only be
valid for grazing plots in Adulam, where the decrease in sunfleck contrast after
73 removal is coupled with a decrease in woody-open assemblage contrast. Removal in exclusion plots in Adulam, which decreased sunfleck contrast, did not change the level of assemblage contrast. Moreover, it has resulted in a significant woody-open assemblage contrast not being observed in the uncut plots. This suggests that grazing is part of the mechanism behind assemblage contrast in Adualm. In Avdat woody- open assemblage contrast was not affected by changes in sunfleck contrast.
Examination of redundancy analysis indicates that woody-open assemblage contrast in Avdat is not caused only by herbivores. Detritivore species, such as Hiontis tentyrioides, Adelostoma grandis and mesostena punctata, contribute to the variation in species composition at least at the same extant as herbivore species. This means that even if there are herbivorous species feeding on shrubs, the mechanism behind woody-open assemblage contrast could not be explained simply by an aggregation of those species in woody patches. The fact that non-herbivore species contribute to the assemblage contrast, together with the fact that assemblage contrast does not respond to sunfleck contrast, suggests that another process of ecosystem engineering, other than modulation of light and shade, is involved in creating the woody-open assemblage contrast. Considering all of the above, hypothesis 1 can only be accepted under certain circumstances, but not as a rule, and is therefore rejected.
Hypothesis 2 states that higher levels of abiotic and assemblage contrast will be observed in less stressful ecosystems. This is true for sunfleck contrast. However, the woody-open assemblage contrast in uncut exclusion plots in Avdat was significant whereas in the same plots in Adulam it wasn't. Woody-open assemblage contrast in removal grazing plots in Avdat was higher comparing to Adulam. Assemblage contrast is therefore not necessarily higher in more benign environments and hypothesis 2 is therefore being rejected. Processes underlying assemblage contrast in
74 the study sites and explanations for the rejection of both hypotheses will be suggested further on in this chapter.
Canopy removal, grazing and species composition in a Mediterranean woodland
In Adulam, canopy removal altered beetle species composition of woody patches, creating two segregated assemblages, one of uncut woody patches and one of woody patches where canopy was removed with no overlap between the two assemblages on the ordination plot (figure 4.11.II). This corresponds with previous studies, suggesting that the presence of canopy affects beetle and other arthropod species composition. Five environmental variables tested in water bodies in Swedish wetlands showed that degree of shading was most important in affecting species composition of diving-beetle (Dytiscidae) assemblages (Lundkvist et al. 2001). Two distinct groups of species are found in that area, one group found in large un-shaded ponds and one found in shaded forest ponds (the other four variables tested were permanence, age, size and water chemistry of the ponds). Mature conifer stands in
Finland have beetle assemblages dominated by forest specialists whereas areas where trees were cut have assemblages dominated by generalists (Pietkainen et al. 2003).
Canopy shading apparently affects thermoregulation. The forest dwelling predacious tiger beetle Cicindela sexguttata was found to be active in open un-shaded patches, and to depend on solar radiation level of those patches for maintaining its optimal body temperature (Schultz 1998). Shade may also affect activity pattern.
Two beetle species of the genus Cicindela differ in their shade preference, with C. circumpicta spending 70% of its activity time in shade and C. togata only 20%, a pattern not explained by trophic mechanisms as the potential prey of both species is
75 mostly found in shaded areas (Hoback et al. 2001). Based on the above studies, and considering that the most obvious effect of tree canopy removal is a change in shading contrast (figure 4.6), it is likely that in Adulam the main factor affecting beetle species composition is shading.
In woody patches where canopy was removed, species assemblage was dominated by few species (figure 4.2) and had a low level of internal variation (figure
4.11.II). In woody patches where canopy was not removed, activity was divided more evenly between species (figure 4.2) with a relatively high level of internal variation among samples (figure 4.11.II).
Grazing changed species composition of the open patches (figure 4.11.III) but did not change that of woody patches (figure 4.11.IV). Under grazing the species assemblage of open patches was almost completely separated from that of the ungrazed open patches (figure 4.11.III). Grazed open patches were dominated by fewer species comparing to ungrazed ones (figure 4.3). My results correspond with previous studies indicating the effect of grazing on beetle species composition. Heavy grazing affected species composition of ground beetles (Carabidae) in Scottish moorlands (Gardner et al. 1997) and Scottish woodlands (Petit and Usher 1998) by providing habitats for species preferring open and disturbed areas. Reindeer grazing on lichens affected species composition of both ground beetles (Carabidae) and weevils (Curculionidae) (Suominen et al. 2003). The explanation given was that grazing created open habitats where species preferring relatively warm and dry microclimates could be active, and by the fact that grazing increased diversity of plant species causing diversity of herbivorous beetles. In Adulam grazing was not shown to affect tree shading (table 4.3). However, it could be that during the sampling season
(April) grass in the open patches was dense and tall enough to induce significant shading. If that was the case then trampling and consumption of grass by grazing
76 livestock would have led to different shading levels in the open patches subjected to
grazing and those protected from it. Such a difference may result in a change in
species composition between open patches under grazing and ungrazed open patches.
The idea that grazing affects beetle species composition by reducing shading caused
by grass is supported by the fact that the two most abundant species, Opatrum libani
and Tentyria herculeana (Tenebrionidae), which dominate grazed open patches and
prefer them over ungrazed ones (figure 4.15), also prefer the south-facing aspect in
the study site over the north-facing one (App. 5), suggesting that levels of solar
radiation affect their habitat choices.
Another possible explanation is that open patches were richer in nutrients due
to the fertilising effect of dung. An increase in nutrient availability could have led to a
change in herbaceous plant species composition resulting in a change in herbivore
species composition.
Combined effects of grazing and canopy removal on woody-open
assemblage contrast in Mediterranean woodland
Both grazing and canopy removal in Adulam affected beetle species
composition. This resulted in a complex pattern of woody-open assemblage contrast
(figure 4.12). Assemblage contrast caused by woody-open patchiness occurred either
under grazing alone or canopy removal alone, but was not observed when both
treatments were combined or absent (table 4.6). In areas where canopy was not
removed, grazing changed the open beetle assemblage (figures 4.11), segregating it
from the woody one to create woody-open assemblage contrast (figure 4.12.III, table
4.6). In plots where canopy was not removed but subjected to grazing, woody-open
patchiness was the main reason for observed heterogeneity in species composition
77 (table 4.6). By contrast, in similar plots where grazing was excluded woody-open patchiness was not the main cause for the observed heterogeneity in species composition (table. 4.6).
Grazing in plots where canopy was removed resulted in convergence of woody and open assemblages (figure 4.12.IV) Therefore, no significant woody-open assemblage contrast was observed in plots subjected to both canopy removal and grazing. This process represents a special case of biotic homogenization (sensu
McKinney and Lockwood 1999). Biotic homogenization takes place when intensive disturbance results in dominance of few fugitive species (i.e. species favouring disturbed environments and excluded from climax communities, Hutchinson 1951) leading to a decline in species diversity. In Adulam the disturbance comes in the form of canopy removal (in woody patches) and grazing (in open patches). Woody patches were canopy was removed and open patches subjected to grazing are therefore disturbed environments. The two most abundant species (O. libani and T. herculeana,) are found in disturbed patches and dominate their assemblages. Thus, they dominate the assemblages of grazed open patches and removed woody patches.
They were hardly present in the undisturbed plots but were found in the disturbed patches in plots subjected to one of the two disturbances (either grazing or canopy removal), or both (figures 4.16 and 4.17). Whenever grazing was introduced they were found in open patches, and whenever canopy was removed they were found in woody ones. Therefore, in plots subjected to only one disturbance, either grazing or canopy removal, they were found in only one patch type, either open or woody, and were hardly found in the other. This resulted in a landscape where the species assemblage of one patch type (depending on the disturbance) was dominated by O. libani and T. herculeana whereas that of the other patch type hardly contained them, leading to a woody-open assemblage contrast. By contrast, when both disturbances
78 occur the two species dominate both open and woody patches (fig 4.17). Dominance
of the entire ecosystem by the same two species leads to biotic homogenization, and
therefore to the elimination of woody-open assemblage contrast.
Inhibition and facilitation of beetle activity by ecosystem engineering
The two fugitive species in Adulam, O. libani and T. herculeana, dominated
and preferred woody patches, but only after canopy was removed (figures 4.15 and
4.17). In woody patches where canopy was not removed those species were absent
(figures 4.15 and 4.16). Therefore activity of those two species was both inhibited
and facilitated by woody vegetation.
Co-occurrence of inhibition and facilitation by woody vegetation was shown
for plants (Callaway and Walker 1997). In plants, inhibition by trees comes in the
form of competition for light or root-space (Callaway and Walker 1997). Facilitation
by trees can come in the form of soil enrichment with nutrients (e.g. Walker and
Chapin 1986, Callaway et al. 1991) or attenuating irradiance levels by shading
(Shirley 1945).
This study, however, demonstrated a case where the inhibition mechanism
does not result from inter-specific interactions. Both O. libani and T. herculeana are
detritivorous beetles. Therefore, unlike in the case of plants, competition for resources
between those species and woody vegetation did not inhibit their activity.
Furthermore, as those species are not herbivorous, inhibition of their activity
(measured as number of individuals/(day*trap) ) could not be explained by trophic
response to inhibition of understory growth by the canopy. This means that inhibition
of their activity by canopy has to be a result of an abiotic effect, i.e. of ecosystem
engineering (sensu Jones et al. 1994). Those results are important as they show that,
79 in addition to plants, co-occurrence of facilitation and inhibition by woody ecosystem engineers is also observed for animals (in this case beetles).
The absence of those species from the natural, undisturbed, woody patches indicates that the net effect of tree ecosystem engineering on their activity is negative.
However, their preference and dominance of woody patches where canopy was removed reveals that their activity was inhibited by canopy but facilitated by another affect of tree ecosystem engineering unrelated to the canopy. This facilitation is explained by the fact that both O. libani and T. herculeana are Darkling beetles
(Tenebrionidae), which are known to feed on detritus (Alsopp 1980). It is therefore not surprising that O. libani and T. herculeana concentrate around litter accumulations found on the ground in woody patches.
The inhibiting effect of canopy, however, could theoretically be explained in more than one way. Reduction of predation risk was suggested to determine habitat preference of tenebrionid beetles in desert shrub-land (Groner and Ayal 2001). One explanation for the inhibition of O. libani and T. herculeana activity by canopy could therefore be that there is intensive presence of small insectivorous predators under fully developed canopy, which causes those two species to prefer patch types where canopy is absent or recovering from removal. Another explanation has to do with thermoregulation. Tenebrionid beetles were found to prefer high body temperatures
(Seely et al. 1988) which increase the digestive efficiency of their symbiotic gut microflora (Crawford 1988). Tenebrionid beetles were also found to regulate their body temperature by shifting their activity from one micro-habitat to another (Ward and Seely 1996). It could therefore be that O. libani and T. herculeana avoid areas with fully developed canopy as they need a certain degree of solar radiation (or
80 corresponding heat emission from ground exposed to it) to maintain a desired body temperature level.
The first explanation, reduction of predation risk, requires further study of insectivore habitat preferences in Adulam. The second explanation, related to behavioural thermoregulation, is supported by the fact that both species were more active on the south facing aspect in the study site than on the north facing one (App.
5). It is likely that O. libani and T. herculeana prefer woody patches because of the availability of food in the form of litter accumulation, but avoid those patches with fully developed canopy as it prevents effective thermoregulation.
A question remains regarding the presence of the fugitive species in the open patches. O. libani, and to a lesser extent T. herculeana, dominated woody patches where the canopy was removed. O. libani and T. herculeana dominance of canopy- removed woody patches was observed both under grazing and when grazing was excluded. However, O. libani and T. herculeana dominated the adjacent open patches only under grazing. In removal plots where grazing did not occur, O. libani and T. herculeana did not dominate open patches (fig 4.17). This means that the activity of
O. libani and T. herculeana in open patches is dependent on grazing rather than on drift from neighbouring highly populated woody patches. As was mentioned before, it could be that grass during the sampling season also provides significant shading. It may therefore be that the difference between grazed and ungrazed open patches is also significant for the thermoregulation of those two species.
Canopy removal, grazing and species composition in a desert shrub-land
As in the case of Adulam, woody vegetation in Avdat affected species composition of ground dwelling beetles. Species assemblages of woody patches in
81 Avdat were significantly different than those of the open patches (table 4.7), with certain areas of the ordination plot being unique either to woody patches or to open ones (figure 4.19).
However, unlike in Adulam, the significant woody-open assemblage contrast in Avdat was not affected by either grazing or canopy removal (table. 4.7), and levels of woody-open assemblage contrast were similar irrespective of grazing or canopy removal. This implies that, unlike in Adulam, the effect of woody vegetation on assemblage contrast in Avdat was not induced by the canopy. Rather, it was induced by a component of the woody patch that persists after canopy removal. Such a component could be the litter patch created on the ground surrounding the shrub.
Litter patches may attract detritivores specializing on woody vegetation litter and thus create woody-open assemblage contrast. In Avdat the species creating the assemblage contrast were not only detritvores, but were also herbivores and predators (figures
4.20 and 4.22). Therefore, litter as a source of food for detritivores is not the only explanation for woody-open assemblage contrast in Avdat. Litter accumulations have additional effects on the ecosystem in semi-arid shrub-land (Boeken and Orenstein
2001). It has a positive affect on plant biomass and it was suggested that litter may provide structure for stopping the outflow of seeds. Accumulation of litter reduces runoff regardless of canopy presence.
The increase in plant biomass associated with litter accumulations may create special niches for herbivore species in the woody patches. This, in turn may further contribute to the woody open assemblage contrast. The effect of litter accumulation on runoff may also affect woody-open assemblage contrast, absorbing runoff by litter can result in soil moisture patchiness. Soil moisture may affect habitat preference of species of all trophic groups. Patchiness in soil moisture, created by patchiness of litter may affect patch preferences of many species regardless of their trophic group.
82 Species less tolerant to moisture stress may be attracted to the woody patches. This
may explain why herbivores and predators also contributed to woody-open
assemblage contrast in Avdat.
A question remains why, in contrast to Adulam, experimental manipulations
(grazing and canopy removal) did not affect assemblage contrast in Avdat even
though the manipulations had a significant affect on shading contrast (figures 4.7 –
4.9). It could be that the main factor affecting species composition in Avdat is soil
moisture, and that it is affected mainly by the presence of litter. In such a case,
species are not expected to respond to canopy or changes in shading level.
As the experimental manipulations are not likely to affect litter directly it
could be that the effect of experimental manipulations on litter patches is delayed, and
will be significant in the future. Woody-open assemblage contrast might therefore
show a different response to grazing and removal in the future.
As in Adulam, results suggest that litter patchiness plays an important role in
determining assemblage contrast. This explains why hypothesis 1, assuming a
correlation between abiotic contrast in a single property and assemblage contrast was
rejected. If several abiotic factors (in this case litter and shade) have different effects
on species composition, but create highly overlapping patches, patch contrast
observed in only one of the factors may not explain observed assemblage contrast.
Assemblage contrast response to engineering under different
environmental conditions
I used patchiness created by woody vegetation and ground dwelling beetle
assemblage contrast as a model for examining landscape diversity relation to species
turnover. Woody plants are ecosystem engineers (Jones et al. 1997 and see more
83 examples further on in this section). Using them as a model for species-landscape diversity relationship provides additional insights about ecosystem engineering. My study took place at two different points along the rainfall gradient in Israel. It provides insights regarding the response of beetle assemblage contrast to ecosystem engineering under different environmental conditions.
Ecosystem engineers are organisms that modulate the availability of resources for other species by causing physical state changes in biotic or abiotic materials
(Jones et al. 1994). That modulation introduces environmental conditions facilitating the activity of certain species and inhibiting that of others. Therefore, ecosystem engineers create environmental filtering (sensu Keddy 1992), preventing the presence of those species in the regional species pool that are unsuitable, and facilitating the presence of the suitable ones (for further discussion of environmental filtering see chapter 2).
In the literature we find many examples suggesting filtering effect of organisms. George and Bazzaz (1999) examined three tree species and found that only for one species seedlings can emerge from the fully developed fern stratum. The successful development of the two other species requires that either the fern stratum or the overstory canopy be disturbed. This implies that understory ferns in a deciduous forest function as environmental filters for tree seedlings. Bruun et al.
(2005) found that The arctic fox (Alopex lugopus) creates nutrient rich microhabitats around its dens, which facilitate short-lived nutrient demanding grasses and forbs.
Holes dug by the European bee-eater (Merops apiaster) provide habitats for secondary cavity nesters and unique species of darkling beetles that induce filtering for those species (Casas-Criville and Valera 2005). The retreats built by larvae of net- spinning stream caddisflies (Hydropsyche orientalis) provided refuge from high
84 velocity streams for the nymphs of the mayfly Ephemerella setigera (Nakano et al.
2005), therefore inducing filtering of mayfly species.
When examining ecosystem engineering by woody vegetation most studies concentrated on the relationship between woody species and plant community.
Ecosystem engineering effects of Ziziphus lotus, a shrub found in semi-arid coastal areas in Spain, such as promoting the accretion of sand, litter, and sand-blown particles, lowering temperatures, shading, and protecting from herbivores with thorny branches, were suggested to facilitates other plant species (Tirado and Pugnaire
2005). Maltez-Mouro et al. (2005) found that oaks (Quercus spp.) affect soil Zinc levels and suggested that variation in understory species composition may result from that effect. Species assemblages of uncut areas in commercial tree stands consisted of shade-tolerant species and therefore differed in their composition from those of canopy gaps (Schumann et al. 2003). This indicates that shading by mature trees determines sapling species composition.
Much less, however, is known about the effect of woody vegetation on arthropod assemblages. My study indicates that ecosystem engineering by woody vegetation may result in filtering of beetle species. Whenever there was a significant assemblage contrast between woody and open patches (figures 4.12 and 4.19) it was caused not only by herbivorous species, but also by detritivore species (figures 4.13,
4.14, 4.20 and 4.22.). This means that at least some species (the detritivores), which do not feed on living plants, showed preference for a specific patch type due to its abiotic properties, and not as a trophic response to the presence of trees and shrubs.
The preference of some species for one patch type over the other, resulting in assemblage contrast, is therefore a result of environmental filtering by woody vegetation. As discussed in previous sections, shade and litter deposition are
85 suggested as the main effects of woody vegetation engineering on beetle-species turnover.
As my study took place in two sites, one of relatively stressful physical conditions (Avdat), and one of more benign ones (Adulam) it can shed light on the assemblage response to engineering under different levels of environmental stress.
This is important because even though engineering has been studied extensively (e.g.
Flecker et al. 1999, Tanner 2001, Creed and Reed 2004, Bouma et al. 2005, Valdivia-
Hoeflich et al. 2005) very little is known on the changes in the effect of engineers along environmental gradients. Bertness et al (1999) and Bruno et al. (2003) suggested that ecosystem engineering has a greater effect on primary consumer densities in stressful environments. In addition to a quantitative change, as in the case of density, there can also be a qualitative change, where the mechanism of influence, rather than its magnitude, changes along the gradient. A change in the mechanism linking ecosystem engineering and species diversity was found for grass in tidal marshes with different levels of salinity stress. In freshwater marshes tussocks created by ecosystem engineers increase species diversity by creating microhabitats that protect species from competitive exclusion (Crain and Bertness 2005). In salt marshes the mechanism was different; tussocks increase species richness by creating a microhabitat with reduced environmental stress allowing the survival of more species
(Fogel et al. 2004). Ecosystem engineering effect on species diversity may therefore result from different mechanisms at different points along an environmental gradient.
My study examined ecosystem engineering effects on beetle species turnover, and also showed that the mechanism behind such effects changes with environmental conditions. In Mediterranean woodland, ecosystem engineering contributed to species turnover by strongly affecting microhabitat preferences of few highly abundant species (see discussion of O. libani and T. herculeana in previous sections).
86 In contrast, in a more stressful habitat (desert shrub-land) species turnover was due to an accumulation of minute responses of many species to ecosystem engineering.
Species in areas of high environmental stress are mostly generalists (Willmer et al. 2000). Towards the extreme dry end of the rainfall gradient ecosystem engineering does not cause species to prefer only one microhabitat and avoid others.
Species filtering in the desert affects the level of activity of species more than it affects their presence and absence. Many species show only slight differences in their activity between the engineered microhabitat and the background. The small differences in activity, appearing in many species, add up to create a significant assemblage contrast.
In contrast, where environmental conditions are less stressful more species can rely on only one microhabitat for supplying their needs. Those species specify on a given microhabitat and are filtered out of others. In a Mediterranean woodland a few relatively abundant species either dominated the engineered microhabitat or were absent from it. The preference of abundant species for one microhabitat over the other, in that ecosystem, was the main cause for assemblage contrast. Along a rainfall gradient the change in ecosystem engineering effects on species turnover is therefore one of mechanism rather then magnitude.
The fact that the change was qualitative, rather than quantitative explains why hypothesis II was rejected. Hypothesis II stated that higher levels of assemblage contrast will be observed in ecosystems of higher rainfall. However, when different mechanisms operate in different environments it is necessary to standardise either for the mechanism or for the environmental conditions before assuming about the quantitative difference. Therefore, as the change in assemblage contrast between different physical conditions is qualitative, no increase or decrease in its levels can be predicted a-priori.
87
This work also introduces new insights regarding disturbance under different
environmental conditions. Polis et al. (2005) suggested that in low productivity
environments there should be low population growth rate resulting in a low recovery
rate from disturbances. However, my study shows that for assemblage contrast the
opposite trend exists. In a less productive ecosystem (desert shrub-land) assemblage
contrast is resilient to disturbances (grazing and removal) whereas in the more
productive one (Mediterranean woodland) it is sensitive to them. As was discussed
previously, the woody-open assemblage contrast in desert shrub-land is likely to be
determined by patchiness in litter, but the effect of experimental manipulations on
litter may be delayed. My results, suggest that assemblage contrast becomes more
resilient to disturbance towards the poor end of the productivity gradient.
Linking landscape and species diversities
Understanding species diversity requires an examination of other levels of
diversity. Bird species richness in Australia and North America was shown to be
positively correlated with the diversity of tree and shrub heights (Recher 1969). A
similar connection was found between the diversity of ground level microhabitats in
woodlands and the species richness of soil mites (Anderson 1978). Such observations
indicate that there is a mechanism linking landscape diversity and the coexistence of
species. Mathematical modeling has shown that in a diverse landscape competing
species have different distribution patterns according to their microhabitat preferences
(Shigesada et al. 1979). This prevents competitive exclusion, allows the coexistence
of species and therefore increases species richness. Experimental evidence for the
connection between landscape and species diversity was found in the study of Boeken
88 et al. (2005). Using annual plant species in desert shrub-land as a model, the authors found that a change in frequency and number of patch types affects the species richness and species composition. Both the addition of patches and the creation of new patch types resulted in the appearance of new species and an increase in species richness. The studies of Shigesada et al. and Boeken et al. indicate that in a patchy landscape some species are dependent on certain patch types. Therefore the distribution pattern of such species should also be patchy. Species depending on a given patch type can form distinct species assemblages. Such a phenomena was described as functional patchiness (Hansson 1997), i.e. patchiness in species composition resulting from physical patchiness. The contribution of patchiness to species diversity is therefore a result of species turnover between different functional patches. Such a linkage between patchiness and species turnover was found in the study of Hewitt et al. (2005), where patches of mollusk shell debris in marine soft sediment were shown to increase beta diversity of benthic fauna.
My study examined the relationship between species turnover and patchiness. Both the experimental and theoretical aspects of my study demonstrate that considering species assemblages as landscape entities, and quantifying contrast between them, is important for understanding the relationship between patchiness and species turnover. The experimental aspect indicates that the creation of a landscape mosaic by an ecosystem engineer contributes to species turnover. Results of my study provide evidence for the creation of functional patchiness by ecosystem engineering.
In addition, the conceptual model presented (see section 2) illustrates the causative connection between environmental filtering, patchiness and species turnover. The model also suggests that filtering by different patch types in the landscape causes species turnover. This study provides a theory for explaining species turnover in patchy environments, supported by field work results.
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105 7. Appendices
Appendix 1
Assemblage contrast analysis of Avdat 2004 sampling session
Table 7.1.1 – PERMANOVA of Avdat '04 ground dwelling beetle assemblage. Significant effects are shown in bold characters. Analysis based on Bray-Curtis distance No transformation, no standardisation.
Source df SS MS F P(perm) Removal 1 7310.199 7310.199 2.06 0.009 Grazing 1 4594.98 4594.98 1.295 0.216 Patch Type 1 3420.762 3420.762 0.964 0.476 Removal*Grazing 1 2734.892 2734.892 0.771 0.722 Removal*Patch Type 1 2759.609 2759.609 0.778 0.686 Grazing *Patch Type 1 1606.87 1606.87 0.453 0.961 Removal*Grazing *Patch Type 1 3267.215 3267.215 0.921 0.537 Residual 32 113576.4 3549.263 Total 39 139270.9
NMS - Avdat '04
2 1.5 1 0.5 0 -0.5 -1 -1.5 -1.5 -1 -0.5 0 0.5 1 1.5 2
Removal, Grazing,open Removal, Grazing,woody Removal, Exclusion,open Removal, Exclusion,woody Uncut,Grazing,open Uncut,Grazing,woody Uncut,Exclusion,open Uncut,Exclusion,woody
Figure 7.1.1 – Non-metric multidimensional scaling ordination in Avdat '04 showing all combinations of removal treatments, grazing regimes and patch types. Samples are PTP's.
106
Appendix 2 Effect of experimental manipulations on activity of ground dwelling beetles.
Adulam Mean Activity for PTP
3
2.5 )
y 2 a d * h c t
a 1.5 p ( / . d n I 1
0.5
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion open woody open woody open woody open woody
Figure 7.2.1 – Effect of treatment combination on beetle activity in Adulam. Vertical bars denote 0.95 confidence intervals.
Adulam Activity by Trophic Group
12
10
8 ) y a d * h
c 6 t a p ( / .
d 4 n I 2
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion open woody open woody open woody open woody Patch Type and Treatment Detritivores Herbivores Predators
Figure 7.2.2 – Effect of treatment combination on beetle activity in Adulam showing trophic groups.
107 Adulam Mean Beetle Activity for PTP by Removal Treatment*Patch Type; LS Means Current effect: F(1, 35)=8.4142, p=.00640 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 2.5
Removal 2.0 ) y
a 1.5 d * h c t a p
( 1.0 / l a u d i v i
d 0.5 n I
0.0 Uncut
-0.5 open w oody Uncut Removal Patch Type
Figure 7.2.3 – Combined effect of patch type and removal treatment on beetle activity in Adulam.
Adulam Mean Beetle Activity for PTP by Grazing Regime*Patch Type; LS Means Current effect: F(1, 35)=5.8061, p=.02137 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 2.2
2.0
1.8 Grazing 1.6 ) y a
d 1.4 * h c t
a 1.2 p ( / l
a 1.0 u d i v i 0.8 d n I 0.6 Exclusion 0.4
0.2
0.0 open w oody Exclusion Grazing Patch Type
Figure 7.2.4 – Combined effect of patch type and grazing regime on beetle activity in Adulam.
108 Adulam Mean Detritivore Activity for PTP by Removal Treatment; LS Means Current effect: F(1, 35)=34.504, p=.00000 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 1.8
1.6
1.4
) 1.2 y a d *
h 1.0 c t a p
( 0.8 / l a u d
i 0.6 v i d n I 0.4
0.2
0.0
-0.2 Uncut Removal Removal Treatment
Figure 7.2.5 –Effect of removal treatment on detritivore activity in Adulam.
Adulam Mean Detritivore Activity for PTP by Grazing Regime; LS Means Current effect: F(1, 35)=5.5206, p=.02456 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 1.4 1.3 1.2 1.1 ) y
a 1.0 d *
h 0.9 c t a p
( 0.8 / l a
u 0.7 d i v i
d 0.6 n I 0.5 0.4 0.3 0.2 Exclusion Grazing
Grazing Regime
Figure 7.2.6 –Effect of grazing regime on detritivore activity in Adulam.
109 Adulam Mean Detritivore Activity for PTP by Removal Treatment*Patch Type; LS Means Current effect: F(1, 35)=10.649, p=.00246 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 2.5
2.0 Removal ) y
a 1.5 d * h c t a p
( 1.0 / l a u d i v i
d 0.5 n I
0.0 Uncut
-0.5 open w oody Uncut Removal Patch Type
Figure 7.2.7 – Combined effect of patch type and removal treatment on detritivore activity in Adulam.
Adulam Mean Detritivore Activity for PTP by Grazing Regime*Patch Type; LS Means Current effect: F(1, 35)=8.6259, p=.00583 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 1.8
1.6 Grazing 1.4
1.2 ) y a
d 1.0 * h c t
a 0.8 p ( / l
a 0.6 u d i v i 0.4 d n I 0.2
0.0 Exclusion
-0.2
-0.4 open w oody Exclusion Grazing Patch Type
Figure 7.2.8 – Combined effect of patch type and grazing regime on detritivore activity in Adulam.
110
Avdat '05 Mean Activity for PTP
4
3.5
3
) y
a 2.5 d * h c t
a 2 p ( / .
d n
I 1.5
1
0.5
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion Open Woody Open Woody Open Woody Open Woody
Figure 7.2.9 – Effect of treatment combination on beetle activity in Avdat. Vertical bars denote 0.95 confidence intervals.
Avdat '05 Activity by Trophic Group
1.8 1.6 1.4
) 1.2 y a
d 1 * h c t 0.8 a p ( / . 0.6 d n I 0.4 0.2 0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion Open Woody Open Woody Open Woody Open Woody
Detririvores Herbivores Predators
Figure 7.2.10 – Effect of treatment combination on beetle activity in Avdat showing trophic groups.
111
Appendix 3 Effect of experimental manipulations on species richness of ground dwelling beetles.
Adulam Mean Species Richness for PTP
9
8 7 s
e i
c 6
e p S
5 f o
r
e 4 b m
u 3
N 2
1 0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion open woody open woody open woody open woody
Figure 7.3.1 – Effect of treatment combination on beetle species richness in Adulam. Vertical bars denote 0.95 confidence intervals.
Adulam Species Richness by Trophic Group
25
s 20 e i c e p
S 15
f o
r e
b 1F0igure 7.3.3 – Effect of patch type on beetle species richness in Adulam. m u N 5
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion open woody open woody open woody open woody
Detritivores Herbivores Predators
Figure 7.3.2 – Effect of treatment combination on beetle species richness in Adulam showing trophic groups.
112
Adulam, Mean Species Richness for PTP by Patch Type LS Means Current effect: F(1, 40)=5.1514, p=.02869 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 7.0 6.5
6.0 s e i c 5.5 e
p S
f
o 5.0
r e
b
m 4.5 u
N 4.0
3.5 3.0 open w oody
Patch Type
Figure 7.3.3 – Effect of patch type on beetle species richness in Adulam.
Adulam, Mean Herbivore Species Richness for PTP by Patch Type; LS Means Current effect: F(1, 40)=7.1053, p=.01103 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 2.0
1.8
1.6
1.4 s e i c
e 1.2 p S
f
o 1.0
r e b 0.8 m u N 0.6
0.4
0.2
0.0 open w oody
Patch Type
Figure 7.3.4 –Effect of patch type on herbivore species richness in Adulam.
113 Adulam, Mean Predator Species Richness for PTP by Removal Treatment*Patch Type LS Means Current effect: F(1, 40)=4.3921, p=.04248 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 3.5
3.0 Uncut
2.5 s e i c e
p 2.0 S
f o
r
e 1.5 b m u N 1.0 Removal 0.5
0.0 open w oody Uncut Removal Patch Type
Figure 7.3.5 – Combined effect of patch type and removal treatment on predator species richness in Adulam.
114 Avdat '05 Mean Species Richness for PTP
16
14
12 s e i
c 10 e p S
f
o 8
r e b
m 6 u N 4
2
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion Open Woody Open Woody Open Woody Open Woody
Figure 7.3.6 – Effect of treatment combination on beetle species richness in Avdat. Vertical bars denote 0.95 confidence intervals.
Avdat '05 Mean Species Richness for PTP by Trophic Group 12
10 s e i 8 c e p S
f
o 6
r e b
m 4 u N
2
0 Removal Removal Removal Removal Uncut Uncut Uncut Uncut Grazing Grazing Exclusion Exclusion Grazing Grazing Exclusion Exclusion Open Woody Open Woody Open Woody Open Woody
Detririvores Herbivores Predators
Figure 7.3.7 – Effect of treatment combination on beetle species richness in Avdat showing trophic groups.
115
Avdat '05 Herbivore Species Richness for PTP by Removal Treatment; LS Means Current effect: F(1, 28)=9.8936, p=.00391 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals 6.5
6.0
5.5 s e i
c 5.0 e p s
f
o 4.5
r e b
m 4.0 u N
3.5
3.0
2.5 Uncut Removal
Removal Treatment
Figure 7.3.8 –Effect of removal treatments on herbivore species richness in Avdat.
116
Appendix 4
Species and morpho-species identified during Adulam 2004 and Avdat 2005 sampling
sessions.
Table 7.4.1 – List of species and morpho-species collected and identified during
Adulam 2004 sampling session. Asterisk denotes a morpho-species.
T rophic Family Genus Species Abundance g roup Anobiidae Ptinus regosicollis 1 Anthicidae Microhoria keifensis 4 Gnathoncus rotundatus 1 Histeridae Margarinotus graecus 1 Nargus lanellatus 2 Leiodidae Nargus mohammedis 3 Nargus notaticollis 2 Mycetophagidae Typhaea stercorea 2 Maladera syriaca 8 Detritivores Onthophagus bytinskii 2 Scarabidae Pachydema abeillei 1 Sisifus schaefferi 1 ? scarabid280* 1 Adesmia cancellata 16 Adesmia ulcerosa 7 Blaps cribosa 17 Tenebrionidae Blaps indagator 1 Opatrum libani 423 Tentyria herculeana 70 Zophosis punctata 1 Byrrhidae ? Byr-sp1* 1 Longitarsus parvulus 1 Chrysomelidae Marsuelia dilativentris 1 ? hapoel* 1 Brachicerus junix 41 ? 5mm-245* 1 ? 7mm-hairy246* 1 Herbivores Curculionidae ? am-ball243* 1 ? curculionid266* 1 ? cruclionid271* 1 Cardiophorus megathorax 1 Elateridae Cardiophorus sacratus 1 Drasterius bimaculatus 1 Glaphyridae Pygopleurus orientalis 1
117
Table 7.4.1. continued
T rophic Family Genus Species Abundance g roup Trichomeloe caelatus 2 Trichomeloe sericellus 7 Herbivores Meloidae ? meloid150* 12 ? meloid252* 2 Acinopus laevigatus 1 Bombidion rugicolla 4
Calathus melanocephalus 1
Carabidae Laemostenus cordicollis 1
Microlestes syriacus 54
Microlestes maurus 2
Paratachys bistriatus 1 Cicindelidae ? cicindelid231a* 3 ? clerid177* 20 Cleridae ? clerid229* 2 Coccinelidae Lithophilus marginatus 6 Cucujidae Silvanus abeillei 11 P redators Lampyridae Lampyris nervosa 1 Mycetophagidae Typhaea stercorea 1 Euconnus jordanensis 1 Scydmaenus saulcyanus 1 Scydmaenidae Acrotona fungi 1 Anotylus complanatus 39 Anotylus inustus 13 Atheta mucronata 2 Atheta sp1* 1 Staphylinidae Micropeplus fulvus 1 Ocypus mus 7 Quedius ochripennis 1 Sepedophilus immaculatus 2
118
T able 7.4.2 – List of species and morpho-species collected and identified during Avdat 2005 sampling session. Asterisk denotes a morpho-species.
T rophic Family Genus Species Abundance g roup Anobidae ? anob5081* 2 Anthicidae ? Anthicid5002* 1 Cisidae ? nr-brown5021* 9 Histiridae Sfrinus Sfr-sp.* 17 Lathridiidae ? Lathridiid5067* 1 Scydmaenidae ? Scyd5019* 64 Adelostoma grande 19 Adesmia dilatata 8 Adesmia metalica 51 Erodius edomitus 4 D etritivores Gonocephalum perplexum 89
Hyontis tentyrioides 12 Mesostena punctata 4
Micispa philistina 7 Tenebrionidae Pimelia bohmi 4 Pimelia grandis 2 Scleron multistriatum 137 Sepidium tricuspidatum 123 Zophosis complantana 1 Zophosis punctata 1 ? Teneb5069* 1 Julodis orondi 1 Buprestoidea Julodis rothi 1 ? Acamol5073* 1
? Buprest5077* 1
Cerambycidae ? Cerambycid5004* 3
? weevil5005* 1
? weevil-gr5023* 2
? bl-head5045* 4 ? bl-head5050* 6 Brachycerus Bra-gav* 2 H erbivores Brachycerus Bra-zig* 26 Keonigius hairy-keonig.* 1 Curculionidae Keonigius keonigius5031* 2 Keonigius Keo-sp.* 1 Porocleonus candidus 12 ? cruc.5072* 1 ? Cur1* 2 ? CUR2* 2 ? CUR3* 7 ? CUR4* 19 ? CUR5082* 1
119
Table 7.4.2. continued
Trophic Family Genus Species Abundance group ? Chrys2029* 1 ? Chrys5024* 6 Chrysomelidae ? Chrys5041* 10 Colaphellus Col-gre* 8 ? Car-meg* 1 Elateridae ? Elaterid5083* 3 Herbivores ? Meloid5007* 27 Meloidae ? Meloid5006* 95 Melyridae ? Aploc5078* 4 ? Mord5018* 28 Mordellidae ? Mordellid5011* 1 Nitulidae ? Nitulid5071* 1 Scolytidae ? Scolytid5060* 1 Carabidae ? cyminid5038* 1 green- Cleridae 7 Predators ? bright5054* Coccinelidae ? Lithophilus5014* 6 Drilidae ? Drilid5070* 1 Lampyridae Lampyris nervosa 1
120
Appendix 5
Aspect preference of Opatrum libani and Tentyria herculeana
Mean Activity for Plot of Opatrum libani and Tentyria herculeana in Adulam
2.5
) y
a 2 d * p>0.05 h c t
a 1.5 p
( / s
l a 1 u d
i p<0.05
v i
d 0.5 n I 0
Opatrum libani Tentyria herculeana
Northern aspect Southern aspect
Figure 7.5.1 – Aspect preference of Opatrum libani and Tentyria herculeana
121