Setting: - Universitetet i oslofolk.uio.no/hjermann/thesis/thesis_intro.doc · Web viewSpatial ecology of the bush-cricket Decticus verrucivorus: Movement, metapopulation dynamics

Dag Øystein Hjermann

Spatial ecology of the bush-cricket Decticus verrucivorus: Movement, metapopulation dynamics and genetic variation in patchy and linear habitats

Dr. scient. thesis

Division of Zoology, Department of Biology,

Faculty of Mathematics and Natural Sciences

University of Oslo, 2000

List of papersPaper I: Hjermann, D. Ø. Do bush-crickets avoid the habitat edge? Microhabitat selection

in the wart-biter (Decticus verrucivorus). Manuscript.

Paper II: Hjermann, D. Ø. 2000. Analyzing habitat selection in animals without well-

defined home ranges. Ecology 81: 1462-1468.

Paper III: Hjermann, D. Ø. The condition of individual bush-crickets influence their spatial

distribution. Manuscript.

Paper IV: Hjermann, D. Ø. Why does emigration increase with decreasing patch size? An

experimental test of the boundary encounter rate hypothesis. Manuscript.

Paper V: Hjermann, D. Ø. and Ims, R. A. 1996. Landscape ecology of the wart-biter

Decticus verrucivorus in a patchy landscape. Journal of Animal Ecology 65: 768-

780.

Paper VI: Hjermann, D. Ø., Ims R. A. and Bondrup-Nielsen, S. Patterns and processes

underlying population genetic structure in anthropogenic linear habitats: Four

hypothetical scenarios and one case study. Manuscript.

Paper V is reprinted by courtesy of Blackwell Scientific Publications

Contents

Overview and synthesis

Preface 1

Scope of the thesis 3

Scaling of processes and patterns in ecology and metapopulation ecology 5

Study species and study areas 6

The wart-biter 6

Meadows - the wart-biter's natural habitat in Norway 8

The study areas 9

Movement behaviour - a "missing link" in metapopulation ecology 11

Use of area depending on habitat size 12

Use of area depending on habitat shape 15

Deciding to emigrate 16

Statistical problems in the analysis of movement behaviour 18

Interpreting occupancy patterns 19

The wart-biters in the Frogn study area 19

Metapopulation models - the good, the bad and the ugly 21

Estimating dispersal parameters from patch occupancy patterns 24

Interpreting genetic variation: invasion of new landscape elements 25

References 27

Individual papers


Preface

When it was time to plan my Master thesis in 1991, I found out that this Ims guy

seemed quite all right to me. I mustered enough courage to knock on his office door to ask if

he was willing to supervise me. He took the time to talk with me there and then (I found out

later that he always does). I only knew he worked with small mammals, so I was a bit

surprised when he asked if I wanted to work with wart-biters. - Wart-biters? I replied. He

explained that it was a quite large bush-cricket. – Well, I knew that, I replied. (I didn't.) I

went out of his office with a supervisor and a theme for my Master thesis. I had no idea

(fortunately!) that I would be defending a thesis on the wart-biter nine years later.

First, Rolf deserves a big THANK YOU. Rolf is the supervisor everybody should

have. On the professional level, he has original research ideas, plenty of knowledge of

natural history as well as ecological theory, and a lot of statistical expertise. On the personal

level, he has been a pleasure to have as a supervisor. He has never had too little time to talk

when I've knocked on his door; he has always given enthusiastic response on my own ideas;

he even did quite much of the "farming" work for the Evenstad papers (III and IV). Rolf is

simply a very nice and unselfish person that is almost unable to tell people "no". (He spends

at least half of the year in the field instead.)

I would also like to thank Søren. The reader should know that he and Rolf did far

more field work than myself for Paper VI, and crawling along the road verges of highway

with heavy traffic isn't that pleasant. Søren and Halvor Knutsen also spent much time in the

allozyme lab for this paper, and I thank them for being my patient lab teachers. Nigel

Yoccoz has learnt me a lot about statistics - and wart-biters - and he collected the French

sample in paper VI.

Then there is a bunch of other people to thank. First, my mother and father learned

me to appreciate nature, both the mountains around Lærdal and the sea in Vestfold. Being

the youngest in a big family, my brothers and sisters are also greatly responsible for my

interest in nature and nature’s mysteries - especially Rudi, who dragged me up in the

mountains from the time I was old enough to walk. (He even was in the local bird-watcher’s

society, although I have a vague idea that this society also had a strong interest for “birds”

with two legs and mammae). The time as an undergraduate student of biology was a fantastic

time with discussions, private and organized field excursions, and countless parties. For me,

this time was proof that common introductory biology courses for both ecologists and

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molecular biologists (such as “Bio101”) is a necessary part of the biology education, both

socially and scientifically. I can’t avoid mentioning my “mates” Jostein and John, but I don’t

have enough space to mention the rest – you know who you are! During field work, I have

enjoyed working and living together with a lot of nice people including Live, Inger, Anne,

Wendy, Naomi, Harry and Gry. During the last years, when most old student friends had

dispersed into computer and teacher jobs, fellow entomologists Steve and Guldborg formed

much of of my social life at work. I also spent many enjoyable hours together with Jonathan

working (not always so intensely) with his reindeer data; thanks for the cooperation! A

considerable amount of time was spent in e-mail discussions with Yngve, Trygve, Trond-

Inge, Thomas and the rest of the members of the intellectual forum "Søplegjengen", an

activity which undoubtedly has enhanced my linguistic and rhetoric capabilities.

Finally, I whole-heartedly thank Nils Christian Stenseth for supporting me during

all these years, including giving me small jobs during one year of unemployment (after my

Master) and, not least, offering me to work on his marine ecology group as a post doc. I also

thank Jogeir Stokland who gave me the opportunity to work at NIJOS, which has been an

interesting and rewarding experience and a valuable insight into “the world outside Blindern”.

I also thank the Norwegian Research Council for supplying a million kroner or so for my

doctorate and the Nansen Foundation for financial support for Paper VI.

Finally, I am deeply thankful to my wife Irene. When we started on our dr. theses

just a few months apart, I was a bit worried about how we would handle the stress of writing

dissertations simultanously. Now, we have produced not only two (almost) finished theses,

but also our beautiful daughter Inga. Because of you and your unique way of keeping our

relationship strong, it has actually been four very nice years. I thank you for sharing your life

with me.

Oslo, November 2000

Dag Ø. Hjermann

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Scope of the thesisThis thesis deals with spatial ecology, using a bush-cricket, the wart-biter Decticus

verrucivorus, as a study species. The papers do not tell a comprehensive "story" but are

somewhat loosely knitted together around some key words. First, spatial variation is the

lowest common denominator of all the papers. This thesis covers spatial variation on scales

varying by five orders of magnitude, from movement behavior on a 5-10 meter scale to

genetic variation on 50 km-scale (the papers are arranged according to spatial scale; Tab. 1).

Movement behaviour is the focus of four papers (I- IV) and a fundamental part in the

underlying processes of the last two. Finally, since the wart-biter is patchily distributed,

metapopulation theory (Hanski & Gilpin 1997) is the ground foundation for much of my

thinking and the conceptual framework for papers IV and V. The core of this theory is a

drastic but useful simplification of the real world: the multitude of processes that governs the

spatial distribution of a patchily distributed species can be reduced to merely two: local

extinctions and recolonizations.

First, in Paper I and III, I analyse movements within small habitat patches1. Within-

patch movement may ultimately influence both extinction and colonization rates. Paper II is

1 In this thesis, I mean exactly the same by "patch" and "habitat island": an area of

suitable habitat (for a given species) surrounded by unsuitable habitat, usually large enough to

contain one population and so far from other patches that movements between patches does

not affect local population dynamics substantially. In other words, I always mean coarse-3

Table 1. Short overview of the papers in this thesis.

Scale of process

Paper Process / pattern Spatial Temporal

I Movement within natural habitat patches < 15 m 1-2 h - 3 weeks

II Movement within patches Statistical methodology

III Movement within experimental patches < 15 m 1-2 h - 3 weeks

IV Movement between experimental patches 15 - 300 m 1-2 h - 3 weeks

V Occupancy, extinction and immigration of patches 50 - 6000 m 1-3 years

VI Invasion and genetic variation of linear habitats 0.2 - 55 km 5-20 years


a methodological paper where I describe the statistical method I have used in the analysis of

Paper I. In Paper IV, I study emigration and movement between patches and the mechanisms

that leads to emigration. In Paper V, the pattern of occupancy in an agricultural area is

analysed from a metapopulation perspective. The final paper is about the effect of

colonization history on population genetic patterns. It differs somewhat from the other

papers, both in its focus on larger spatial and temporal scales and in its focus on genetics.

Although not often explicitely mentioned, conservation biology is at the root of this

thesis. The destruction, degradation and fragmentation of natural and semi-natural habitats,

including the meadow habitats studied in this thesis, makes metapopulation and landscape

ecology more than just academic disciplines. Many species are forced to try to survive in

habitat patches that are very small and isolated from each other compared to the landscape in

which they evolved. Theory often suggests that when habitat destruction goes beyond a

critical threshold, the landscape becomes unsuitable for an accelerating number of species

(e.g., Andrén 1994, 1999; Bascompte and Sole 1996). As there may be a considerable time

lag from a species is doomed to extinction (because of habitat destruction) and the extinction

itself (the "extinction debt"; Tilman et al. 1994; Pimm et al. 1995; Loehle and Li 1996;

Cowlishaw 1999), we do not know how many species that "are waiting for their turn" at

present. Metapopulation and landscape ecology may help discovering and understanding the

threats to biodiversity before it is too late.

grained patchiness when I use the word "patch".

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Scaling of processes and patterns in

ecology and metapopulation ecologyIn metapopulation biology, processes are typically divided in two types based on

scale: processes within each population, and processes between populations (Tab. 2).

However, one should not forget that this is a simplification. First, the definition of

population is, to some extent, arbitrary, and must be defined on basis of the spatial scale of

some process (Addicott et al. 1987). E.g., we can define a population as the spatial area

within which 95 % of matings occur between animals that both were born inside that area.

However, a definition of the population that is suitable for population genetics is not

necessarily suitable for population dynamics and vice versa. Moreover, the scale of each

process vary between years and between different landscapes (e.g., depending on the degree

of fragmentation). Thus, the framework of Tab. 2 can be extremely difficult to apply in

practice.5

Table 2. Processes and patterns in a metapopulation perspective.

Hierarchal level Processes Patterns

Populations (most individuals interact with other individuals in the same population)

Birth/death of individuals (depends on intra- and interspecific competiton, predation etc.)

Immigration

Local movement (including emigration)

Local population size

Distribution of individuals within patch

Metapopulations (most individuals mate within populations; interactions between populations not large enough to influence local dymanics)

Local extinctions (stochastic or deterministic)

Recolonization of empty patches

Distribution of absence/presence on habitat islands (depends on area, isolation and patch quality)

Collections of metapopulations(practically all individuals mate within metapopulations; interactions between metapopulations not large enough to influence metapopulation dynamics)

Invasions due to spread

Invasions/exclusions due to altered large-scale conditions (e.g. climate change)

Exclusions due to stochastic global extinction of metapopulations

Distribution pattern, differences in density among regions

Geographic patterns of genotype frequencies


In some cases, however, populations are quite easy to identify and it is easy to

classify processes as within-patch and between-patch. A typical example is animals that live

in discrete, well-defined patches with room for one population and sufficiently remote from

each other (compared to the species' dispersal capacities) that we can assume the populations

to behave independently of each other. When metapopulation theory and other theories

including space emerged, ecologists naturally looked for such systems to test the predictions

of the theory. Wiens (1995) has pointed out that before space was built into ecological

theory, ecologists tended to seek homogenous study areas to test theories of population

dynamics, predator-prey systems, competition and so on. To a large degree, the same thing

has happened in the flourishing growth of empirical metapopulation studies in the 1990s, only

that the "ideal" of the completely homogenous study area was replaced by another "ideal",

collections of quite small, sharply defined, homogenous areas. The wart-biter systems I have

studied in Papers I-V are good examples of such systems, either naturally occuring (as in

Paper I and V) or artificial (as in Paper III and IV). There is nothing wrong with seeking

relatively simple systems where it is practically possible to test certain theories. However, it

should be kept in mind that many, or most, species live in patches that vary continuously in

quality, i.e., source-sink systems (Pulliam 1988). Thomas & Kunin (1999) have proposed a

framework that is able to incorporate source-sink-dynamics in metapopulation structures. To

complicated matters even further, patches need not be stable in time (e.g., Stelter 1997),

patches need not have well-defined edges, and patch quality can vary a lot in time, so that

former sources can become sinks and vice versa (Boughton 1999).

Study species and study areas

The wart-biter

The wart-biter (Decticus verrucivorus (Linneaeus)) is one of the largest large bush-

crickets (Ortoptera: Tettigoniidae) of Northern Europe (body length: 24-38 mm for females,

26-44 mm for males; Harz 1960). It is a continental species that prefer hot summers; it is

widespread in large parts of Eurasia, including most of Central and Southern Europe and

parts of Iran, Pakistan and China (Samways and Harz 1982). In England, there are only a

few populations in the extreme south. In Norway, it is found along the coast from the

Swedish border to Rogaland and in some parts of the lowlands of eastern Norway (such as

southern Telemark and southern Østerdal).

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The wart-biter is winged, but unprovoked flight is extremely uncommon; Ander

(1947) reported to have seen wart-biters flying longer distances (at least 20-30 m) twice

during a period of 17 years. It sometimes alights when disturbed, but then usually flies only

2-3 meters, infrequently up to 20 m in windy weather (personal observation). Some

individuals also use the wings to enhance jumping when it travels through non-habitat with

little or no vegetation (personal observation). It lives on the ground in open habitats with

quite low vegetation; I will discuss its habitat requirements in depth below.

It is possible to rear wart-biters on purely plant food (Ragge 1965), but in nature

they are partly carnivorous; adults eat 25-70 % animal food such as acridid grasshoppers and

other insects (Nagy 1950, Harz 1960, Bellman 1985, Cherrill 1989, Thorens and Nadig

1997). Because adults in some habitats need to hide in tussocks to avoid predators, this may

decrease their opportunities to hunt (Cherrill 1989).

The wart-biter hatches in April/May and goes through seven instars (Ingrisch 1978a;

Holst 1986). In Norway, the first adults appear in late June to late July, depending on

weather conditions in spring and early summer. Probably because of the competition for

virgin females, males become adult a couple of weeks before the females (Wedell 1992).

Adult males stridulate (sing) to attract females, often climbing up on high vegetation to make

the sound reach further. It needs a body temperature of 23-25 C to sing (Nielsen 1938), i.e.,

almost only in sunshine in Norway, and they sing mainly in the morning (9-12 a.m.) and to a

lesser degree in the afternoon (around 3 p.m.). Females can approach singing males and vice

versa, and each sex may turn down sexual invitations from individuals of the other sex, at

least for the moment. However, it is more common thaT females tun down males than vice

versa (personal observation). During mating, the male transfer a spermatophore which is

attached externally to the female's genitalia. The spermatophore is quite large (9-10 % of the

males' weight), it consists of an large sperm-free spermatophylax that the female eats after

mating, and an ampulla with sperm that she eats after the spermatophylax (Wedell & Arak

1989). It has been suggested that the spermatophylax is a parental investment in bush-

crickets, but in the wart-biter, it has low protein concentration (4.2 %), and does not increase

female fecundity (Wedell & Arak 1988). Rather, it appears to be a mating investment evolved

by sperm competion with other males. If the spermatophylax is large, more sperm is released

from the sperm ampulla because it takes longer time before it is eaten (Wedell 1991).

The abundance of wart-biters has declined in Northern Europe the last decades

(Ingrisch 1979; Holst 1986; Bengt Ehnström, personal communication). The reason for this

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is changes in landscapes and agricultural practices that makes unfertilized meadows and

grasslands less common (see next chapter). The wart-biter is regarded as one of England's

most acutely threatened insect species, and there is considerable effort to save it from

extinction, including a captive breeding and reintroduction program (Cunningham et al.

1997).

Meadows - the wartbiter's natural habitat in Norway

The wart-biter lives on the ground in open habitats with quite low vegetation. The

vegetation must not be too tall (at most 30-40 cm in my own experience). In Norway,

various types of unfertilized meadows and grassland are suitable habitats (personal

observation). The nitrophilous vegetation in fertilized meadows is too dense and tall for the

species. However, it is also absent from meadows that are cut very short (Weidemann et al.

1990) or intensively grazed by, e.g., horses (personal observation). South-facing or flat

habitats are preferred (Oschmann 1973; Ingrisch 1979; Cherril and Brown 1990a; Paper V).

Probably, the reason for these habitat requirements is the wart-biter's temperature

requirements. The species have extremely high optimum temperatures: instar development

and survival is optimal at around 35 C, and not possible below 20 C, while the temperature

optimum for adults is 36-40 C (Ingrisch 1978a,b). They lay their eggs in the ground in

places with little or no vegetation where the soil heats up quickly in spring (dry, fine-grained

substrate is preferred). Instars and adults spend much time basking in the sun to increase

body temperature, positioned so that the side of the body is perpendicular to the sun's

direction (personal observation).

In Norway, the wart-biter appears to be a follower of agriculture, which has a 5000

year history in our country. Its primary habitat type in Scandinavia, unfertilized meadows,

has been in decline for many years. The meadows are fertilised and cultivated to increase

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Table 3. For some groups, the proportion of species on the Norwegian Red List that have the cultural landscape and meadows, respectively, as their main habitat. “Meadows” include "natural" unfertilized meadows for grazing or harvesting, and dry meadows. The cultural landscape is a wider term that in addition to meadows includes trees in the agricultural landscape, fields, stone walls, farmyards etc. The data are assembled from DN (1999a, 1999b).

Red-listed species Total in Norway

Taxon No. of species Cultural landscape% (no. of species)

MeadowsApprox. %

No. of species

Fungi 763 25 (189 ) 14 6000

Mosses and liverworts 216 25 (54) 20 1064

Vascular plants 255 37 (94) 32 1775

True bugs 82 38 (31) 38 445

Beetles 778 18 (141) 18 3430

Butterflies and moths 540 58 (312) 33 2111


grass yields, encroached by bushes because of lack of grazing/cutting, and turned into forest,

corn fields and housing estates. In Sweden, the area of unfertilized meadows for grazing was

reduced by 85 % from 1850 to 1966, while the area of traditionally managed meadows for

cutting has been reduced by 99.9 % (Edelstam 1995). There have been a similar trend in

Norway. With the decline in unfertilized meadows, a significant part of the biological

diversity is also in decline. In Norway, 874 red-listed species (28.5 % of the Norwegian Red

List) are associated with the cultural landscape (DN 1999b). Many of those have meadows as

their primary habitat (Tab. 3). Also, around 70 species of birds are in decline because of

changes in the cultural landscape (DN 1994).

The study areas

We studied the natural distribution of wart-biters in two systems: in scattered

meadows in an agricultural area, i.e., the "traditional" wart-biter habitat, and in roadsides

along a major highway, which may be the most imortant habitat for this speciesin the future.

In addition, we used an experimental area where wart-biters originally were absent.

The first location for our work with the wart-biter was an agricultural landscape in

Frogn, ca. 40 km from Oslo in the direction of Gothenburg (Paper I, V; see map in Paper V).

This area (ca. 6 km2) is dominated by agricultural fields (with wheat, barley, rye, oats,

vegetables and strawberries) with quite large patches of spruce and oak forests. The area is

mostly confined by spruce forest. Most wart-biter habitats are small meadow patches in the

fields where the soil is too shallow to be plowed because of rocky outcrops. Many of these

meadows were grazed before. Grazing and harvesting fodder is non-existent in the area now

(except for some horsegrazing, which usually renders the vegetation extremely short). It is

not known whether the vegetation is stable, and if not, how rapidly bushes and trees

encroaches that patches; some of the farmers cut bushes and trees to avoid shadow on the

fields. Some roadsides as well as one patch of humid meadow are also suitable wart-biter

habitats.

This area can be said to examplify a landscape where the original wart-biter habitat

exists because of the geological properties of the area, i.e., the combination of fertile soil

(suitable for agriculture) and rocky outcrops. Rocky outcrops in forests are too isolated too

be suitable wart-biter habitat, and in lowland agricultural landscapes without rocky outcrops,

there are usually few potential wart-biter habitats because of modern agricultural practices.

In south-eastern Norway, unfertilized meadows that are managed by traditional farming are

most common at higher altitudes, where sheep and dairy farming is common. However, the 9


climate tend to be too cold for the wart-biter in these areas. Thus, as a combination of

geological and economical factors, there are few wart-biter habitats left in meadows.

However, roadsides that are managed properly, i.e., cut a couple of times each

summer, have a type of vegetation that appears to be suitable wart-biter habitat. The wart-

biter also seems to require that the roadside width are above of a certain limit; I have never

observed populations in roadsides less than 1.5-2 m wide, and the probability of occupancy

seems to increase up to 3-4 m width. Such broad roadsides are common along major, modern

highways and sometimes along train lines. In Paper VI, we studied the wart-biter populations

that have established along a stretch of a major Norwegian highway, E18 between

Holmestrand and Larvik. This is an area with intensive agriculture and rapid urban

development. There are very few meadows suitable for wart-biters left in this area, and the

number is steadily decreasing. Large parts of the road has been built 5-20 years ago and cuts

through forests and large fields. The roadsides along this road currently seem to be the most

important wart-biter habitat in the area. The climatic conditions are similar as in the Frogn

area.

At last, we used an area at Evenstad field station in Østerdalen, around 150 km

north of Oslo (Paper III, IV). The vegetation was suitable meadow vegetation. Compared to

the two other locations, the mean temperature through the year is substantially colder, but the

climate is also more continental, and summers can be quite hot. Wart-biters were collected

from other places and released in the area at the start of the experiment.

Movement behaviour

- a "missing link" in metapopulation ecologyEl lobo es una cosa incognoscible. Lo que se tiene en la trampa

no es mas que dientes y forro. El lobo propio no se puede

conocer. Lobo o lo que sabe el lobo. Tan como preguntar lo que

saben las piedras. Los arboles. El mundo.

Cormac McCarthy: The Crossing 2

Behaviour is the key to dispersal rate between patches in two ways. (I here assume

we talk about species that have enough physical and "mental" control over their movements

to stay within the natal patch if they want to. This excludes for instance many aquatic species

2 The wolf is an unknowable thing. What one has in the trap is nothing but teeth

and fur. The wolf itself cannot be known. Wolf or what the wolf knows. It's like asking

what the stones know. The trees. The world.

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that follow the water movements as plankton in part of their life cycle.) First, some animals

decide to leave their "home" patch, i.e., they decide to emigrate. Which factors influences

how many animals that emigrate, which animals that decide to do it, and when they do it?

This is the subject of Paper IV. Second, after the animals have left the natal patch, they try to

locate another patch while moving through the matrix (which often is drawn as a big white

area in metapopulations maps, but seldom is so completely devoid of structure as such

drawings seem to indicate). Which factors influence the path they follow, and more

specifically: how much of the path trajectory results from innate movement patters (i.e. how

often and how much they change direction), and how much depends on sensory information

that they gather while moving? In this thesis, I have ignored this subject as much as possible,

although I could not avoid making some assumptions about this in Paper V. It is, however, a

question that is both extremely important, and in many cases extremely difficult to resolve

(more on this in the chapter about Metapopulation models.)

In much more indirect manner, movement behaviour also influences the probability

of local extinction, the other basic process of metapopulations. First, movement behaviour

may influence intraspecific competition, which in turn influences population size and thereby

the risk of extinction. Second, the emigration rate can be so high (relative to immigration

rate) that the risk of extinction is considerably increased. The first topic is related to the

themes of Paper I and III, the second in Paper IV.

Animals have presumably evolved movement behaviours that are optimal (within

the constraints set by movement speed, the amount of body resources not devoted to

reproduction, etc.). Animals can also be expected to make the best use of sensory

information, often through indirect cues. In this connection, "optimal" means "optimal for

the individual's fitness", or more precisely, the evolutionary stable strategy (ESS). In the case

of dispersal rate, the ESS strategy may often be very close to the dispersal rate that

maximizes metapopulation occupancy (Hamilton and May 1977; but also see Lemire and

Lessard 1997 for a different conclusion). I am not aware of similar theoretical studies of

within-patch movement of animals that seek to maximise fitness (which in males often means

to maximise the number of matings).

However, the wart-biter's landscape has changed a lot only through the last decades,

so it evolved in a landscape that was quite different from the current landscape. Movement

behaviour (and other types of behaviour) can turn from adaptive to maladaptive when the

landscape changes. This is relevant for within-patch movement, the decision of emigration,

11


and the search strategy during movement between patches. E.g., if the species evolved in a

fragmented landscape that is less fragmented than the current landscape, it probably has a

"too high" dispersal rate, because its dispersal strategy is adjusted to the "old" level of

dispersal mortality, which probably was lower than the current one. In addition, the link

between an individual's sensory "input" (e.g., how often an individual encounters the habitat

edge) and its behavioural "output" (e.g., the choice between staying and emigrating) may be

“tuned” to be optimal in habitat patches looking quite differently than the patches in which

the animals live today. E.g., suppose that the mechanism for "setting" the migration rate at a

optimum level is that animals decides to disperse after encountering the edge a certain

number of times. When patch size decreases, the dispersal rate will increase markedly. Thus,

when the landscape is fragmented, the optimal dispersal rate decreases, while the actual

dispersal rate may increase, leading to a large gap between optimal and actual dispersal

strategies. Natural selection will reduce this gap, but the metapopulation may go extinct in

the process.

Use of area depending on habitat size

In classical metapopulation theory, the patch is usually treated as a point with zero

dimensions in space; i.e., all local processes are assumed to be non-spatial, and can be

essentially fully understood by "classical" population dynamics of closed populations with

some stochasticity thrown in (i.e., refs.). However, movement also plays a role within

patches. For a species that (in part) is regulated by intraspecific competition and lives in a

patch where resources are evenly distributed, any movement behaviour that leads to spatial

variation in density will result in "inefficient" space use, in the sense that the population size

at equilibrium is lower than it could be if the density did not vary in space. (For patches

where resources are not evenly distributed, the "optimal" space use is where the pattern of

species density corresponds to the pattern of in resource density.) E.g., if animals tend to

aggregate in clumps although there is no variation in resources, animals experience a higher

density than the real overall density, which leads to higher intraspecific competition thereby

lower population size. This may in turn influence the probability of local (and global)

extinction.

In the Frogn study area, the wart-biter occupies patches of a wide range of sizes,

from large meadows of 1000 m2 to two-meter-wide road verges. In paper I, I investigated

how wart-biters select habitat within the patch in two patches of different size (as well as in

one road verge; see the next chapter). The positions of individually marked insects were

12


mapped with intervals of 30 minutes to two hours during a three-week period. The data were

analysed using two different methods that shed light on microhabitat selection on two

different scales: which microhabitats the adult animals choose for each "move" (i.e., between

two observations), and which microhabitats the adults use by large. The first question relates

to the adult animal's decisions during the three-week study period and must be analysed using

special methods (Paper II), while the latter question relates to the animals' decisions during all

life stages, including where the females decide to lay their eggs and where the instars decide

to move. On the latter scale, we found that the edge was avoided in both patches. The pattern

indicated a negative edge effect for distances up two meters, and was strikingly similar

between patches (Paper I, Fig. 3a). By analysing habitat selection for each move, the same

pattern prevailed in the large patch, while in the small patch it seemed that both the edge and

the interior were avoided (Paper I, Fig. 3b). The results showed a considerable degree of

aggregation in both patches, and that large parts of the patches were effectively empty

because of movement behaviour.

However, without replicates of patches of the same size, it is difficult to conclude

that differences in behaviour result from patch size alone. In addition, vegetation differences

between edge and interior are confounding factors. In the large patch, the pattern of edge

avoidance was quite consistent between habitat types, but this was not the case for the small

patch. As a complementary study to Paper I, I therefore set up an experiment with patches

created experimentally on Evenstad field station (Paper III and IV). Here, eight patches in

three different sizes were "carved" out by mowing a larger area, and animals caught

elsewhere were released in equal densities and tracked much the same way as in Paper I. The

animals were of two different "qualities": animals reared in the laboratory, and animals

caught as adults. Unexpectedly, animals of the latter group appeared to be in better

condition: they moved more, both within and between islands, males sang more often and

more loudly, and females' ranges overlapped with the most active males. In this experiment,

the overall use of the edge zone (here defined to be 1 m wide) corresponded to the area of the

edge, with one exception: Lab-reared (low-quality) animals (of both sexes) in medium-sized

patches (8 x 4 m) stayed more in the edges than expected.

Why did paper I and III yield so different results with regard to edge use? Since the

results of Paper I indicate that animals avoid the edge per se and not the type of vegetation

found in the edge, I suggest that positive phonotaxis (that singing males attract each other) is

a likely explanation that also agree well with other studies of wart-biter behaviour (Keuper et

13


al. 1986, Weidemann et al. 1990). So why did not wart-biters avoid the edges in Paper III as

well? The answer is likely to be the difference in the range of patch sizes and shapes: the

smallest patch in Paper I was 390 m2, while the largest patch in Paper II was 80 m2. In

addition, the patches of Paper III were "semi-linear" (the large ones measured 16 x 5 m).

Weidemann et al. (1990) found that wart-biter males aggregate in clumps (a kind of "leks").

Because of the limited patch width and the relatively high density of wart-biters, the patches

in Paper III were probably just large (and wide) enough to make room for a wart-biter clump,

there simply was no room left outside the clumps. Weidemann et al. (1990) also found that

the distribution of males within clumps was significantly more regular than a random

distribution, indicating male-male interference, which also was reported by Keuper et al.

(1986) for this species. In Paper III, the inferior males probably avoided the interior because

they were deterred by males singing loud and frequently. The similar distribution of females

may similarly have been caused by female-female interferential competition for "sexy" males.

This hypothesis is more uncertain, since other authors have not reported this for the female

wart-biters; however, it is (weakly) supported by my own observations of outright kicking

fights between females. In the large patches, however, the inferior animals used the interior

as much as the edge, perhaps because there were more room between superior animals.

Papers I and III both have weaknesses in different ways. For Paper I, the lack of

replication (imposed by the time constraints of a single field worker) is a severe drawback.

The main drawback of Paper III is the small size (and semi-linear shape) of the patches; the

"large" patches of this study were smaller than the smallest non-linear occupied patches

observed in the Frogn landscape (around 100 m2; Paper V). Animal ranges did not increase

from the medium to the large patches in the experimental patches (Paper III, Fig. 6),

indicating that the movement of each individual, at least, was not constrained by patch size.

However, the addition of larger and less linear patches would have been preferable3.

Nevertheless, I find that the unexpected difference between inferior and superior animals to

be interesting, and to my knowledge the first Orthopteran example of spatial segregation

according to social status in what appears to be a lek-like system. Another striking feature of

both Paper I and III is the unexpected similarity between the sexes in many aspects of

3 Indeed, my original experiment included patch sizes up to 20x 20 m. I tried to

implement this experiment twice: first in a meadow owned by Oslo City, which ended up

being cut by a farmer, and then in a grassland at The Agricultural University at Ås, which

unfortunately had too dense vegetation for the wart-biters' taste.

14


movement behaviour and microhabitat selection. One possible explanation for this could be

that because the males' contribute a spermatophore (see Study species) and mate relatively

infrequently, and we can expect more symmetrical mating behaviour than the common

pattern of "reluctant females, ardent males" (Krebs and Davies 1987:169). However, Nina

Wedell (e.g., Wedell & Arak 1989; Wedell 1991) has concluded that the spermatophore has a

mating function and no effect on fecundity. A simpler and perhaps more likely hypothesis is

that males simply adjust their movements to the spatial pattern of females.

Use of area depending on habitat shape

Linear habitats are a striking feature of landscapes modified by man, and for many

species, linear habitats become increasingly important for the preservation of species in the

landscape (Paper VI and references therein). Quite few studies, however, have compared

linear and non-linear habitats (in contrast with the attention devoted to linear landscape

elements as movement corridors). For the wart-biter in Norway, roadsides and similar

habitats (e.g., verges along train tracks, grassy areas around highway intersections) seem to be

making up an increasing part of the wart-biter habitat. The strong increase in this type of

areas does not outweigh the loss of "traditional" farmland habitats, but it certainly decreases

the negative impact landscape change and the probability of regional extinction of the

species.

A wide-held belief in landscape ecology is that long narrow habitats are inferior

relative to non-linear patches of same size, amongst other things because of edge effects; this

has also been confirmed by some studies (e.g., Major et al. 1999). However, the situation

seemed to be turned around in the Frogn area, where the smallest occupied roadsides were

smaller than the smallest occupied non-linear patches, and the number of singing males

indicated a higher density of animals in the road verges (Paper I). The pattern of wart-biter

movements in this habitat (Paper I; also see previous chapter) indicated that in the roadside

edges were not avoided; actually, they were preferred. The preference for edges may be

caused by differences in microclimate (the roadside sloped towards the east, but was flatter

near the edges). Anyway, these results indicates an edge response that differs form the non-

linear patches in the same area, and may indicate a more "effective" use of the habitat area,

i.e., that a smaller fraction of the habitat is effectively empty.

15


Deciding to emigrate

Which factors influences the emigration rate, and more specifically: How does

habitat area and shape influence emigration rate? These questions are obviously of great

importance in metapopulation biology, and essential for predictive models. In a much-cited

paper, Stamps et al. (1987) described a model where animals move around the patch on

random. Each time an animal encounters the patch edge, it is hypothesised to leave the patch

with some probability x, and to bounce off the edge with probability 1-x. Given this model,

emigration rate decreases with increasing patch area because animals encounter the edge

more frequently. The predictions from this hypothesized mechanism (I will call it "the

boundary encounter rate hypothesis") have often been found to be quite adequate in a

metapopulation context. E.g., in a study of a metapopulation of the bush-cricket Metrioptera

bicolor, Kindvall (1999) developed a simulation model based on observed daily movement

distances in the habitat, daily movement rates in non-habitat, and probabilities of emigration

at the boundary towards several types of non-habitat. Non-habitat movement rates and the

emigration probabilities were estimated by experimentally releasing animals in the forest and

on borders, respectively. By comparing with data from long-term observations, he found that

this model predicted long-term net displacement distances and emigration rates quite

accurately. Haddad (1999) did a similar kind of analysis to predict how movement rates of

butterflies through corridors were affected by the corridor's width and length, using a

simulation model which departed from correlated random walks only at habitat boundaries.

In the Evenstad experiment (Paper IV; also see Use of area depending on habitat

size), I clearly found that emigration rate increased with patch area. The ratios of the

dispersal rates of the small, medium and large patches were 3.1 : 2.2 : 1, which fit quite well

to the prediction that emigration rate is proportional to the edge/area ratio, as the boundary

encounter rate hypothesis predicts (Stamps et al. 1987).

However, since the wart-biters adopted fairly stable ranges, we would also expect

that wart-biters that stayed in the edge zone would be more inclined to emigrate compared to

those who stayed more in the patch interior. However, I found no indication that this was

true. Therefore, although my observations agree with the boundary encounter rate

hypothesis, they do not agree with the underlying behavioural mechanism that this hypothesis

assumes. I propose social cohesion as an alternative hypothesis: the social interactions

between the animals function as glue that keeps them as a group. If there are few animals in

a patch, there are fewer interactions and the force that keeps them staying is weaker, and they

16


are more inclined to move away from the patch. In the case of the wart-biter, the song of the

males is presumably the most important social interaction. An important difference between

this hypothesis and the boundary encounter rate hypothesis is that the social cohesion

hypothesis predicts that the emigration rate depends on the population size, not on the patch

area. As a kind of support for this hypothesis, I found that there seemed to be a connection

between the net emigration rate the first three days of the experiment (when emigration rates

where high due to the unfamiliar habitat) and the emigration rate the following two weeks.

Those patches that happened to be left by many individuals in the start of the experiment

tended to be left by even more individuals later. Of course, this is not conclusive evidence

for this hypothesis.

Except for patch size, I found that a much larger proportion of migrants (individuals

that emigrated at least once) among males than among females (61 versus 21 %). This was

the only behavioural parameter for which we found a clear difference between the sexes.

Also, I found that animals in good condition and with high movement activity migrated far

more than other animals. E.g., 56% of the animals with movement activity above the median

migrated, while only 30% of the others. Since condition and movement activity was closely

correlated, it is impossimle to separate the effects of those factors. Thus, it did not seem that

the inferior animals were forced to leave the patch; on the contrary, the typical migrant was a

sexually attractive male that probably sought to increase his fitness even further. It is worth

noting that after the initial bout of migration, which lasted for around three days, the

migration activity was quite low for an extended period, but then increased again towards the

end of the season. It seems likely that this was an adaptive strategy for males: after having

secured some reproduction "at home", they emigrated, hoping to find other patches with

females that had not been mated (and they did!). The difference between the sexes may

indicate that males' fitness is more limited by the number of matings than the females' fitness

are, in spite of the male's investment spermatophore. This view is supported by Wedell

(1992).

Statistical problems in the analysis of movement behaviour

I encountered a statistical problem when I were about to analyse the movement data:

the observed use of habitat with regard to, say, vegetation type, must be compared to the

availability of the different vegetation types. Of course, we could assume that the entire

habitat island was available. On a large time-scale, this is not wrong: in the course of for

instance the entire season, the entire habitat patch may be more or less equally available to the 17


wart-biters. However, it was clear that many wart-biters only transversed a small portion of

the habitat island during the two-three weeks of the study, and it would be entirely wrong to

assume that they could select microhabitat from the entire habitat in the 1-2 hours between

recordings. The answer to this problem was Arthur et al's (1996) paper on how to estimate

habitat selection when availability changes. In this paper, they used the 99 th percentile of

observed movement distances as the radius within which all parts of the habitat were equally

available. In my case, this would lead to an overestimation on the amount of habitat close to

the habitat edge because of the limited size of the habitat patches. Moreover, my observation

intervals were not constant, in part because not all animals were found during each searching

bout, and movement lengths also depended on temperature. I therefore modified their

method by letting availability vary as a continuous function of distance from last observation,

time, and other variables. This modification is reported as a separate paper (Paper II),

including analysis of part of the data from paper I as a worked example.

Interpreting occupancy patterns

The wart-biters in the Frogn study areaIf it looks like a duck, and quacks like a duck, we have at least to

consider the possibility that we have a small aquatic bird of the

family Anatidae on our hands.

Douglas Adams: Dirk Gently's Holistic Detective Agency

In Paper V in this thesis, Rolf A. Ims and I studied the distribution of wart-biters in

the Frogn study area. During the two years of the study, we found wart-biter populations in

only 27 and 16 patches of the area, respectively, although 70 patches seemed to contain

suitable habitat for the species. We basically asked two questions about this pattern. First, is

it a metapopulation? Second, assuming the answer to be "yes", can we calculate the average

dispersal distance based on the pattern of occupancy alone? The latter question will be

discussed in a later chapter. Regarding the first question, we found that many aspects of the

wart-biter distribution agreed well with the metapopulation concept. First, we found that the

probability that a patch was occupied increased with patch area and decreased with the degree

of isolation relative to occupied patches. Those two factors, when log-transformed, appeared

to have additive effects on occupancy, i.e., a patch of a given area became more likely to be

occupied when isolation decreased. The latter is an important point when dealing with short-

term data where little or no turnover is observed, because we might also observe significant

effects of area and isolation if a species is in the process of invading an area, assuming that

18


patches that are smaller then a certain size cannot sustain a population. We would not expect

the effects of area and isolation to be additive, however, so the fact that they are additive in

our study indicates turnover. Second, we observed some actual turnover. Third, we found

that small, but little isolated patches tended to harbour single animals that presumably had

dispersed to these patches earlier the same year. These facts together strongly suggest a

metapopulation-like structure.

However, not everything conformed to a classical metapopulation. First, it is not

clear whether the largest patches were susceptible to extinction. Thus, the system may have

some patches that practically can be looked upon as mainlands. However, a metapopulation

model is not "harmed" by the inclusion of patches with extinction rates practically equal to

zero; its predictive power is not diminished. Thus, this is largely a point of semantics.

Second, a patch occupied in the first year was so small and isolated that it "should not" have

been occupied, i.e., according to the metapopulation model we used, it was extremely

unlikely to be occupied. Just how "outlying" this patch is depends partly on which model that

is used, however (more on metapopulation models in the next chapter). Even if it is a single

patch, a single outlier that we are unable to explain is enough to declare, with a high degree

of certainty, that the model we have used is wrong. Although all models in principle are

wrong, this makes the predictive power of the model somewhat questionable. A possible

explanation for this patch is the time lag inherent in metapopulations; the probability that a

patch is occupied does not depends on the isolation relative to occupied patches for a period

of time up to this moment, not the isolation in this moment. (The outlier patch is close to a

large patch that was unoccupied in 1992 and 1994, but might have been occupied shortly

before our study. Later, the large patch has become occupied, while the outlier became

extinct in 1994.) Finally, we do not know whether the metapopulation is in dynamic

equilibrium, i.e., whether the proportion of occupied patches is without a temporal trend.

However, observations from the years following this study (unpublished data) do not suggest

any such trend, and the landscape is fairly stable.

As a conclusion, I reformulate the first question of this chapter: Is there a model

(verbal or mathematical) that is simpler than the metapopulation model, and can explain the

observed patterns? I cannot answer anything but "no". However, we have little direct

evidence of turnover, and we know little about recolonization and extinction rates. Also, we

have no clue about what causes extinctions, i.e., the relative importance of demographic

stochasticity, temporal environmental variation, deterministic extinctions (e.g., because of

19


vegetation succession) and high emigration rates. Such knowledge would of course be very

important in a conservation context.

20


Metapopulation models - the good, the bad and the uglyI'm astounded by people who want to "know" the universe when

it's hard enough to find your way around Chinatown.

Woody Allen

Metapopulation models have evolved and radiated into countless forms from Levins'

original model. As far as single-species models are concerned, the main trend has been

towards increasing complexity and increasing realism. Part of the reason is that

metapopulation ecology has developed from a purely theoretical concept to a highly applied

discipline of conservation biology. Increasingly, politicians and landscape managers demand

specific advice regarding reserve and landscape design, which cannot be answered without a

realistic model. Unfortunately, both of the main processes in metapopulations are infamously

difficult to model realistically, and it is easy to end up with models with a lot of parameters.

In addition, many of the parameters are notoriously difficult to estimate. In structured

metapopulation models, for instance, local population dynamics is explicitely modelled (e.g.,

using the logistic growth equation). Thus, one does not only need estimates of maximum

growth rate (R) and carrying capacity (K), but one also needs to know (or assume) the

relationship between population size and the probability of extinction (i.e., demographic

stochasisity). Unless very precies estimates are available from a species that have been

studied in detail through a number of years, such models are often of limited value and. Also,

small differences in models structure can have a large influence on predictions. E.g., Mills et

al. (1996) used four different programs to analyse population viability based on the same data

set, and found that there were large deviations between predictions from each program

because of such apparent details as idiosyncracies of the input format and how density

independence is incorporated.

Part of the problem is that the available data commonly is snapshot or semi-snapshot

patterns of occupancy, i.e., data on which patches that are occupied in one or a few years,

respectively. If turnover is low, extinctions and recolonizations can be so infrequent that it is

impossible to fit independent models of extinction and recolonization (as done by Sjögren

Gulve and Ray 1996). Thus, one has to rely on the snapshot/semi-snapshot occupancy

patterns. Thus, the question is how to squeeze maximum information out of the following

data (in the most extreme case): the area of each patch, the distances between patches, and

which patches that are occupied in a single year. We obviously need a model.

21


Metapopulation models for interpretation of snapshot or semi-snapshot patterns can

be arranged in a continuum from mechanistic to phenomenological models. Basically, in a

mechanistic model, the processes (in metapopulation studies: immigration and emigration)

that link predictor variables (patch areas and distances between patches) to observed patterns

(occupancy of habitat islands) are modelled, based on ecological theory. Thus, the

parameters in the model have some direct interpretation in relation to the processes that are

assumed to case the pattern. In contrast, in phenomenological models the link between

predictor variables and the observed pattern is a statistical model that is chosen simply

because it appears to fit the data well. Thus, the estimated parameters have no direct

ecological interpretation. The most successful metapopulation model may be Ilkka Hanski's

incidence function model (IFM; Hanski 1994). Here, occupancy is mechanistically described

as a function of extinction and colonization probabilities, which in turn are more or less

phenomenologically described as functions of population size (or patch area) and the number

of immigrants, respectively. Both the last functions can be said to be partly mechanistic

(since they use functions that ecologically makes sense) and partly phenomenological (since

the parameters have no direct ecological meaning). At last, the number of immigrants is

described as a function of the distance to other patches and their areas. The entire model has

five parameters. Hanski recommends that one, the average dispersal distance, is estimated

using dispersal data, while the other four are estimated by fitting the model to the pattern of

occupancy. Thus, the number of immigrants and the probabilities of colonization and

extinction can be predicted for any habitat patch on basis of the estimated parameters. The

IFM has been applied in a number of studies with good results (Hanski and Thomas 1994;

Hanski et al. 1996; Wahlberg et al. 1996). Finally, a purely phenomenological approach to

wart-biter occupancy is to use logistic regression to model the probability of occupancy as a

function of patch area and isolation. One example of this kind is Thomas et al. (1992), who

studied the distribution of occupied and vacant butterfly habitats.

Paper V in this thesis is another example of a purely phenomenological approach

applied to the wart-biters of the Frogn study area. The approach is actually idendical to the

study of Thomas et al. (1992), except that we used a theoretical dispersal function (the

negative exponential, the same as in IFM) as a basis to calculate isolation indices for each

patch. This study is based on patch occupancy data for two successive generations of wart-

biters, i.e., typical semi-snapshot data. We assumed that the probability of occupancy in a

single year was a logistic function of log(isolation index), log(area) and variables of habitat

22


quality (describing vegetation and slope). Thus, the number of parameters that must be

estimated is [number of habitat quality variables + 3], with an additional parameter to

estimate (average dispersal distance) if isolation indices are estimated using the theoretical

dispersal function. The parameters were estimated by fitting the model to the occupancy

data.

Purely phenomenological models like the logistic regression and more

mechanistically based models like IFM appear very different. First, the mathematical

formulations of the models seem totally unrelated to each other. However, it is easy to show

that in much of parameter space they may be quite similar. Second, mechanistic models

based on ecological theory have parameters that have some meaning with regard to the

ecological processes of extinction and recolonization, while the meaning of the parameters of

the logistic models are not readily interpreted in terms of those processes (they are easily

interpreted in terms of occupancy; see Discussion in Paper V). Therefore, mechanistic

models can be used to simulate the metapopulation during time and how patch destruction

affects metapopulation viability. It is also easy to analyse the effect of destroying patches

using statistical models (i.e., a phenomenological approach); just keep the estimated

parameters and calculate new isoclines after patch removal. With a statistical model and

some additional information, it is also possible to deduce curves of per-year colonization and

extinction rates. One advantage of statistical models is that their properties are well-known.

Another advandage may be increased robustness and precision of estimates due to a lower

number of parameters in the model (e.g., three in a logistic model vs. four in the IFM if there

are no habitat quality variables).

Generally, whichever type of model that is used, estimating parameters from

snapshot or semi-snapshot patterns of occupancy involve several caveats. First, these models

assume that there is no trend in the proportion of occupied patches, i.e., that the

metapopulation is in a state of dynamic quasi-stability. Obviously, predicting the risk of

global extinction assuming dynamic stability becomes a meaningless effort if this assumption

does not hold. If the metapopulation is on its way to deterministic extinction (because

patches have become too small and/or too isolated from each other) such a flawed analysis

will only obscure the fact that some action must be taken. Breaking this assumption can also

lead to very biased estimates also if the metapopulation is not extremely far from stability.

E.g., Kindvall (1995) found that Hanski's model yielded turnover rates 2-6 higher than

observed, probably because the assumption of stability did not hold because new patches had

23


been created recently before the study. Another caveat is that without knowledge of local

dynamics, there may be an unknown source-sink structure in the population. Predictions

about the effects of destroying patches may be far too optimistic regarding the removal of

patches that in reality are source patches (and too pessimistic regarding the removal of sink

patches). A third and related caveat is the assumption that migration rate is equal and not

affected by for instance patch area. Small populations can be sinks simply because of high

emigration rates (Kuusaari et al. 1998; Paper IV). Finally, even though there is no trend in

the proportion of occupied patches, temporal heterogeneity in patterns and processes may

lead to erroneous conclusions in studies based on a few years data. E.g., extinctions (or

recolonizations, for that matter) may occur largely during infrequent years of unfavourable

weather, and it can be difficult to foresee the extinction pattern if we have not observed such

a year (e.g., Weiss et al. 1988; Solbreck 1991). One example that shows the susceptibility of

data from one or a few years (how data from one or a few years can lead astray) is the

Euphydryas editha metapopulation studied by Boughton (1999). Here, former sources

became extinct due to an unusual frost, and were recolonized from the former pseudosinks.

Estimating dispersal parameters from patch occupancy patterns

Spatial ecology with predictive power depends on at least some data on dispersal

between populations. However, such data may be very difficult to collect. Therefore, it

would be incredibly useful to be able to estimate dispersal indirectly, using the pattern of

occupied and unoccupied patches as the only raw data. Theoretically, this is possible if we

make three assumptions. The first one is that the number of dispersers from an island is

proportional to the area of the patch. The second is that dispersal does only depend on

distance, i.e. that it does not depend on features in the landscape outside the patches. The

third assumption is the form of the dispersal function, i.e., the probability that an individual

that leaves a patch arrives at another patch as a function of the distance between the patches.

In our case (Paper V), we assumed the negative-exponential function c = exp(-D/D').

Biologically, the assumptions behind this function is that animals spread by simple diffusion,

and dispersers are "lost" at a constant rate during dispersal (Turchin 1998:188). Alternative

functions could be the power function or the Gaussian function, which assumes that the ratio

between long and short-range dispersers is higher and lower, respectively (Turchin

1998:192). E.g., Hill (1996) found that dispersal lengths of butterflies in a patchy landscape

was well explained by the power function (see also Kot et al. 1996 and references therein).

As shown in Paper V, we found a good agreement between the observed average dispersal

24


distance (37 m, calculated from male dispersal only) and the average dispersal distance

estimated using the pattern of occupancy (36-42 m, depending on the number of habitat

variables included in the model). However, one case of good agreement does not exactly

guarantee that average dispersal distance can be estimated in this way in general. Moreover,

even if the average dispersal distance is can be estimated adequately, this number may not be

of much use as long as the form of the dispersal function is uncertain, since the tails of this

function is very important when predicting the future of the metapopulation. Thus, it is very

uncertain to which degree it is practically useful to estimate dispersal parameters from the

occupancy patterns. Nevertheless, for many species that disperse as spores, seeds, etc., it can

be practically impossible to estimate dispersal rates. In addition it can be very difficult to

estimate the probability that a new population can be established in an empty patch as a

function of the number of dispersers that arrive. Thus, it would be interesting to find out,

e.g., using simulation, how accurately a dispersal curve can be derived given the number of

patches and the size of the geographic area that has been sampled.

Interpreting genetic variation: invasion of new landscape

elementsAs mentioned before in this synthesis, roadsides are a habitat type that is becoming

increasingly important for the wart-biter. The wart-biter seems to require roadsides of a

certain width; I have never observed populations in roadsides less than 2 m wide, and the

probability of occupancy seems to increase up to 3-4 m width. Such broad roadsides are most

common along major highways built the last 20 years. Thus, the invasion and use of such

roadsides is of great interest for the conservation of the wart-biter. Roadsides, if properly

managed, are potentially important habitat for many other insect species as well as plants.

For instance, it is believed that 80% of the butterfly species of the Netherlands can use

roadside habitat (Anonymous 1995, cited in Forman and Alexander 1998). In addition, the

creation of these new habitats can be exploited as experiments on a larger scale than any

ecological research project can afford. First, they provide case studies of invasion of new

habitat, a field of ecology that has received quite much attention recently (e.g., Kareiva

1996). Secondly, they can be used to study gene flow and genetic differentiation in linear

habitats, an area of many theoretical, but few empirical studies (Paper VI).

In Paper VI, Søren Bondrup-Nielsen, Rolf Anker Ims and I discuss different ways

that anthropogenic linear habitats can be created and be invaded by a species. We include 25


both linear habitats that are engineered by human beings (e.g., roadsides) and linear habitats

that have been created by destroying most of a once non-linear habitat (e.g., clearcutting a

forest except for river margins). To investigate how these different scenarios affect spatial

genetic patterns, we do a simulation study where we follow the gene frequencies of two loci

in a row of populations, starting out with different initial patterns of spatial genetic patterns,

as well as varying population sizes and migration rates. Using standard analyses of genetic

structuring, such as overall Fst and correlation analyses (spatial autocorrelation as well as

correlation and crosscorrelation between loci), such data can help estimating migration rates,

effective population sizes, and/or the age since populations were established. In some cases,

genetic data can also be used as a rear-view mirror, since some types of initial conditions

(specifically, concurrent genetic gradients in two loci) can be detected by the presence of

correlation between loci for around fifty generations after establishment of populations.

As a case study, we studied the distribution and genetic variation of wart-biters

along a stretch of a major Norwegian highway (E18 Holmestrand - Larvik). Large parts of

this road has been built 5-20 years ago, and currently it seems to be the most important wart-

biter habitat in the area along the road, which is intensively developed for farming and

housing. As genetic markers we used one allozyme loci (ME) as well as the amount of black

pigmentation on the wings (wing melanism, WM). We found quite strong correlation

between loci as well as spatial autocorrelation within loci. In light of the simulation results,

the most likely explanation appears to be that ME and WM varied geographically in similar

ways before the corridor populations established. Based on simulation results, it also seems

likely that the average effective population size is in the order of 60 individuals and that

migration rate (between neighbouring sample points) is above 0.05. Although these values

does not seem entirely improbable, it must be emphasized that this way of using the

simulation results is somewhat speculative.

26


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Ander, K. (1947). Flygförmågan hos våra hopprätvinger [Flight ability of our Orthoptera].

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List of papersPaper I: Hjermann, D. Ø. Do bush-crickets avoid the habitat edge? Microhabitat selection

in the wart-biter (Decticus verrucivorus). Manuscript.

Paper II: Hjermann, D. Ø. 2000. Analyzing habitat selection in animals without well-

defined home ranges. Ecology 81: 1462-1468.

Paper III: Hjermann, D. Ø. The condition of individual bush-crickets influence their spatial

distribution. Manuscript.

Paper IV: Hjermann, D. Ø. Why does emigration increase with decreasing patch size? An

experimental test of the boundary encounter rate hypothesis. Manuscript.

Paper V: Hjermann, D. Ø. and Ims, R. A. 1996. Landscape ecology of the wart-biter

Decticus verrucivorus in a patchy landscape. Journal of Animal Ecology 65: 768-

780.

Paper VI: Hjermann, D. Ø., Ims R. A. and Bondrup-Nielsen, S. Patterns and processes

underlying population genetic structure in anthropogenic linear habitats: Four

hypothetical scenarios and one case study. Manuscript.

Paper V is reprinted by courtesy of Blackwell Scientific Publication

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Paper 1

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Paper 2

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Paper 3

35


Paper 4

36


Paper 5

37


Paper 6

38


39

Box 1: Guesstimating migration rates from observations of patches with single males

In Paper V, we each year categorized patches into three types: patches with no observations or

wart-biters at all, patches with observations of single males, and patches with observations of at least two

animals. We can use the data in the middle group to give us a rough idea about migration rates per area in

occupied patches. I here demonstrate this for the 1992 data from Frogn (Paper V). I use only data for the

patches that are smaller than the smalles patch with populations any of the years, i.e., patches that

appeared to be to small for establishment of a population (<120 m 2). I sorted these patches by connectivity

value (sensu Paper V), then calculated the running mean of connectivity value and the observed

probability of observing a male on the patch. The result is the "observed" line in the figure below.

Now, the connectivity value of patch i was calculated using two basic assumptions: the density

of wart-biters and the migration rate is the same on all occupied patches (i.e., the migration rate does not

depend on area, contrary to what I showed in Paper II). Then, the number of emigrant males from a patch

equals [patch area]*[density of wart-biters]*[migration rate], or [no. of emigrant males] = area*C, where

C is the number of emigrants per area. What we want is to estimate C. To find how many of the

emigrants from patch j that reaches another patch i, we multiply with a function ci,j that depends only on

the distance between i and j. The rest of the emigrants ends up somewhere else or dies. The expected

number of emigrants that reaches i from j is therefore areaj*C*ci,j. To find the expected number of

emigrants that reaches i from anywhere, we sum up this product for all patches j, i.e. [the number of

immigrants] = areaj*C*ci = C*areaj*ci (since C is a constant). However, I have defined connectivity

as areaj*ci (Paper V). Thus, by assuming different values of C we can plot the expected number of

immigrants in the same graph as the observed numbers of males (see below).

Probability of immigration of a male to an empty patch. The "observed numbers" are running

means of eight islands sorted by connectivity value.

We here see that for the right-hand part of the graph, C values around 0.0025 - 0.005 appears to

fit quite well. For lower connectivity values, the observed values is higher, though. This may have two

reasons. Low connectivity means that the surrounding patches are small and/or far away. However, Paper

II clearly indicates that emigration rate is higher on small patches. In addition, long-distance migration

may be more common that the negative exponential function (which we used for ci,j) indicates, and

moreover, we assumed that no migrants moved longer than 400 m. I therefore think that C = 0.0025 -

0.005 might be a plausible estimate, i.e., one male emigrant per 2-400 m 2 of habitat. The estimate is

probably closest to the truth for medium and large patches.


Box 2: Guesstimating extinction and colonization probabilities from a logistic

regression model

Based on the rough estimate of male emigration rate described in Box 1, we can

calculate both extinction and colonization rates, given a couple of assumptions more. As in

Box 1, we assume that dispersers are independent and that the probability of dispersing from

one place to another follow the negative exponential distribution. Let us also assume that the

emigration rate of males is 2.9 times the emigration rate females is equal that of males (which

is what we found in Paper II). Then, the probability of immigration by one individual, two

individuals and one individual of each sex, respectively, is as depicted in the figure below.

Next, we assume that the colonization probability equals the extinction probability

on the 50% isocline of probability of occupancy (which implies that the metapopulation is in

equilibrium). It is then easy to calculate the probability of extinction as a function of area

(see figure of H. comma).

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Setting: - Universitetet i oslofolk.uio.no/hjermann/thesis/thesis_intro.doc · Web viewSpatial ecology of the bush-cricket Decticus verrucivorus: Movement, metapopulation dynamics