Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations

1-1-2001

Demographics, movement, and resource use of the American Apollo butterfly arnassiusP clodius (Papilionidae) in Grand Teton National Park, , USA

Julia Nell Auckland Iowa State University

Follow this and additional works at: https://lib.dr.iastate.edu/rtd

Recommended Citation Auckland, Julia Nell, "Demographics, movement, and resource use of the American Apollo butterfly clodius (Papilionidae) in Grand Teton National Park, Wyoming, USA" (2001). Retrospective Theses and Dissertations. 21059. https://lib.dr.iastate.edu/rtd/21059

This Thesis is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Demographics, movement, and resource use of the American Apollo butterfly

Parnassius clodius (Papilionidae) in

Grand Teton National Park, Wyoming, USA

by

Julia Nell Auckland

A thesis submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Major: Ecology and Evolutionary Biology

Major Professor: Diane M. Debinski

Iowa State University

Ames, Iowa

2001 11

Graduate College Iowa State University

This is to certify that the Master's thesis of

Julia Nell Auckland has met the thesis requirements of Iowa State University

Signatures have been redacted for privacy lll

TABLE OF CONTENTS

CHAPTER 1. GENERAL INTRODUCTION Literature Review 1 Goals and Objectives 9 Thesis Organization 10 Literature Cited 10

CHAPTER 2. DEMOGRAPHICS AND MOVEMENT OF THE BUTTERFLY PARNASSJUS CLODJUS (PAPILIONIDAE) Abstract 15 Introduction 15 Methods 19 Results 25 Discussion 29 Acknowledgments 35 References 36 Appendix 1 41 Tables 42 Figures 46

CHAPTER 3. GENERAL CONCLUSIONS 54 Discussion 54 Literature Cited 58 CHAPTER 1. GENERALINTRODUCTION

Literature Review

Introduction

Predicting the movement of at the landscape level requires an understanding of the behavior of individuals (Wiens et al. 1993; Lima & Zollner 1996). The distribution of animals at the landscape scale is determined by within-patch behaviors, emigration rates, dispersal, and colonization (Wiens et al. 1993; Ims & Y occoz 1997). How these factors affect the transfer rates of individuals between habitat patches are the key to understanding landscape-level effects of habitat heterogeneity (Ims & Yoccoz 1997).

Metapopulation theory has been incorporated into the study of landscape ecology during the past ten years (Harrison 1993; Hanski 1997; Harrison & Taylor 1997).

Metapopulations were originally defined by Levins (1969). He developed a model to describe population dynamics in a heterogeneous landscape in which not all patches are occupied and each patch has a probability of extinction and re-colonization. Movement between patches is critical for the long-term maintenance of a metapopulation.

Butterflies have been the model species for many studies of metapopulations (Thomas

& Harrison 1992; Baguette & Neve 1994; Hanski et al. 1994; Hill et al. 1996; Nieman 1996;

Sutcliffe & Thomas 1996; Lewis et al. 1997; Brommer & Fred 1999; Roland et al. 2000).

The metapopulation approach is a useful framework for studying movements of relatively sedentary butterfly species which have fluctuating populations in heterogeneous landscapes. 2

The visibility, abundance, and short generation time of butterflies make them ideal taxa for studying movement behavior (Wiens et al. 1993). Butterflies use the landscape at multiple scales. Their movements range from the 3600 km, multi-generational migration of monarch butterflies (Danaus plexippus)(Brower 1996) to less than 100 meters in a lifetime for some

Lycaenids (Scott 1975). Butterflies have evolved life history strategies which enable them to live in multiple types of habitat and climates, from ephemeral patchy alpine clearings to contiguous tropical grasslands. Butterfly movement at the landscape scale is dependent upon resources within habitat patches, emigration, dispersal and colonization.

Within Patch Dynamics

Butterfly movement is dependent on adult nectar sources, larval host plants, and mate location (Scott 1986; Singer & Thomas 1992). The trade-offs and interactions between these

3 resources determines the spatial distribution of butterflies in a patch. Predator avoidance and puddling for minerals also play a role, but their influences tends to be minor compared to the other three factors (Watanabe 1978; Sculley & Boggs 1996). Butterfly responses to resources depends on their mating strategy, their sex, the time of day, and the weather conditions (Watanabe 1978; Scott 1986; Sharp et al. 1987).

Most species of butterflies are generalist feeders on nectar and it is an important resource (Scott 1986). Douglas (1986) says that "anecdotal" data "suggest" that butterflies spend approximately 50% of their time foraging. Butterflies are increasingly likely to emigrate from areas as nectar decreases (Kuussaari et al. 1996; Ries 1998). Conversely, immigration increases with flower abundance (Kuussaari et al. 1996; Sutcliffe and Thomas 3

1996). However, spatial _study_of Euphydryas anicia found that the distribution of nectar sources did not explain the location of male aggregations (Odendaal et al. 1988).

Hostplants affect the initial distribution of butterflies because this is where adults emerge. Movement by females is closely tied to their host plants because the larvae of most species are very host specific. Larvae may starve or grow too slowly to reach an overwintering phase if they do not have enough food (Thomas & Singer 1987). Females spend the majority of their time searching for suitable oviposition sites and tend to range farther than males as a result of their search for host plants (Scott 1986; Baguette and Neve

1994; Peterson 1997; Roland 2000). Patrolling males are often attracted to areas of high host plant density where they will wait for virgin females to emerge (Watanabe 1978; Stanton

1984; Scott 1986).

Life-history strategies of butterflies depend on the availability of their host plant species (Scott 1986). Species that use long-lived host plants or host plants that are found in stable environments tend to be more sedentary. Butterflies that use weedy plants in early successional habitats are typically much farther ranging. Spatial distribution of host plants relative to nectar may influence the movement strategies of adults.

Mate-searching strategies affect butterfly movements. Males find females either by perching in specific places or by patrolling for unmated females (Scott 1986). Perching males usually have specific places and times during which courtship takes place. Males and females may congregate in general locations ( e.g., hill tops, gulches, sun spots).

Patrolling males may have an impact on the spatial distribution of butterflies within a patch. Butterflies are good at detecting motion and color, but not pattern and shape. 4

Pheromones are usually only play a role at close range during courtship. Therefore, males must approach and investigate other butterflies to determine if they are receptive females of the same species (Scott 1986). This behavior may lead to aggregations of butterflies independently of nectar or host plant distribution.

Turchin (1989) developed a model to predict the spatial distribution of "animals that move randomly until they perceive a conspecific, at which time they bias their movement towards that individual." and found that it resulted in aggregations. Odendaal et al. (1988) examined aggregating behavior in Euphydryas anicia and found that it was not correlated with the spatial distribution of host plants or females. Aggregations seemed to result from increased turning as males approached and chased each other.

Furthermore, mated females may avoid males so that they can maximize time to search for host plants and nectar. This results in females emigrating from habitat patches more frequently and dispersing longer distances than males (Baguette and Neve 1994). More spatial analyses of butterfly distribution compared to host plants, nectar, and conspecifics is needed, especially because the importance of each resource is species specific depending on its environment and life-history strategy.

Emigration

Emigration is the movement of an individual from a habitat patch or subpopulation

(Stamps et al. 1987; Ims and Yoccoz 1997). Emigration in butterflies may occur as a result of a decline in nectar or host plants (Sutcliffe & Thomas 1996; Peterson 1997). Emigration 5

may also occur if conspecific density is low (Brussard et al. 1974; Kuussaari et al. 1996).

Specialist butterflies living in stable habitats where both nectar and host plants are available will have lower emigration rates than butterflies which use more ephemeral host plants or nectar sources (Baker 1969).

Emigration may occur as a result of simple behavioral mechanisms. Butterflies tend to move in straight lines unless they encounter an edge, stop to nectar, or interact with a conspecific (Ries 1998; Odendaal et al. 1988). As flowers, conspecifics, and host plants in a patch decrease, butterfly movements will become more linear. Therefore, distance traveled and encounters with the edges of a patch will increase, thus increasing the probability of emigration.

The probability that a butterfly will emigrate from a patch is a function of edge permeability (Stamps et al. 1987; Haddad 1999). The perceived permeability of an edge is species-specific. Edges may present psychological barriers to dispersing butterflies (Stamps et al. 1987). Edge permeability is dependent on edge type, species-specific behaviors, and possibly long-distance cues such as pheromones (Stamps et al. 1987). An edge may be

something as abrupt as an alpine meadow meeting dense forest or as subtle as a hay field adjacent to a prairie.

Many butterflies species in naturally patchy habitats have been observed to avoid

crossing edges to exit their preferred habitat. Sutcliffe and Thomas (1996) observed 91 ringlet butterflies (Aphantopus hyperantus) leaving glades surrounded by forest. Ninety-

eight percent used small gaps or corridors to emigrate through. Schultz ( 1998) released

Fender's blue butterflies (lcaricia icariodes fenderi) on edges of lupine patches and found 6 that 70% stayed within the lupine patch. Species that have adapted to continuous habitats may be more sensitive to the abrupt edges of human-altered habitats. Ries ( 1998) examined the responses of Speyeria idalia, a prairie specialist, to four edge types adjacent to prairie.

She determined the edge permeability of treelines, crops, roads, and fields adjacent to prairies for each species. S. idalia avoided crossing edges at treelines, crops, and fields.

Wood and Samways (1991) studied the effects of different landscape elements on flight pathways of 19 butterfly species in a botanical garden containing 9 habitats. They found that the 10 most common species used almost identical flight paths within the garden.

Butterflies generally avoided flying into forests and were more likely to fly over short trees

(15m) than tall (35m) trees. Two of the three species that preferred the water edge avoided flying over the water. Closely related species behaved similarly. All species tended to use edges as flight corridors.

Dispersal

Dispersal is the process of moving through the landscape matrix (lms and Y occoz

1997). A species' ability to travel between points is dependent on the attributes of the intervening habitat as well as absolute distance. Most research has focused on absolute distance of dispersal and not the permeability of the matrix through which the butterfly must travel (Roland 2000). Estimating dispersal distances in the field has proven to be a challenge. The three main methods that have been used are mark-recapture, presence/absence studies, and genetic variation.

Most studies of metapopulations in butterflies have used mark-recapture methods to 7

estimate population sizes and dispersal. The local abundance and short life span of

butterflies makes it possible to obtain good demographic and dispersal data for a site.

Roland's (2000) work with P. smintheus in alpine meadows showed that butterflies moving

through intervening forested habitat did not cover as much distance as those dispersing through meadow habitat. Sutcliffe and Thomas (1996) found that ringlet butterflies

(Aphantopus hyperantus) were more likely to move between meadows connected by open meadow habitat than those separated by forest.

Mark-recapture studies may underestimate dispersal because the probability of recapturing dispersing individuals decreases with distance (Koenig et al. 1996). Several mark-recapture studies have found median dispersal distances for "sedentary" butterfly species to be 100-200 meters (Harrison 1989; Baguette and Neve 1994; Roland et al. 2000).

However, each of these same studies also found evidence that 1-5% of the population disperses 500 to 4500 meters from where they are originally marked.

Another way of estimating dispersal in patchy landscapes is to identify patches of suitable habitat and then do presence/absence surveys each year (Harrison 1989, Hanski et al.

1994 ). These studies typically span at least several years and thorough surveys must be conducted in each patch during the flight period. This is an easy way to get minimum dispersal distance. However, this method may underestimate dispersal distance because not all dispersers will successfully colonize the patches they reach. Presence/absence monitoring of multiple habitat patches is a good way to get long term data on metapopulations dynamics.

A third way to measure dispersal distance is to assess genetic differentiation.

Analyses indicate that gene flow in butterfly populations exceeds what would be expected 8 from known dispersal data (Rosenberg 1988; Debinski 1994; Peterson 1996). This could result from underestimation of dispersal ability, "stepping stone" gene flow, or inability to detect fine-scale variation (Rosenberg 1988; Peterson 1996; Keyghobadi et al. 1999).

Keyghobadi et al. (1999) used highly variable microsatellites to analyze genetic variability at the scale of a mark-recapture study in alpine meadows

(Roland et al. 2000). They found that genetic dissimilarity was greater when populations where separated by forest than by open meadow, indicating that dispersal was limited by forest habitat.

Neve et al. (1996) also used both a mark-recapture study and a genetic analysis to estimate butterfly movement in two adjacent river valleys. Ninety-two percent of their recaptures occurred within 200 meters of the original capture point. Only one percent of the butterflies were observed to move more than a kilometer. During the two-year study, they only captured one butterfly which moved between valleys. Their genetic analysis found that butterflies within each valley were all closely related, but there were differences between the valleys. In this case, genetic data matched mark-recapture data extremely well. These two studies support theories that corridors may facilitate butterfly movement between patches.

Colonization

Colonization is the establishment of a species within an unoccupied habitat patch

(Ims & Y occoz 1997). Successful colonization is dependent not only on resource availability, but also demographic stochasticity (Harrison 1989). can colonize patches either by the arrival of multiple adults or by a gravid female laying her eggs in a 9

patch. The number of immigrants to a patch is dependent on the number of butterflies

emigrating, distance between patches, and matrix navigability.

Study of colonization is complicated because patches which seem like suitable butterfly habitat to humans may not be suitable for reasons such as microclimate, competition, or predation. Long-term presence/absence monitoring provides data on occupancy. Factors affecting successful colonization have not been specifically addressed.

Patch suitability can be tested by translocation experiments, and population trends following colonization events can be obtained from mark-recapture studies.

Goals and Objectives

Movements of individuals through the landscape are the key to maintaining metapopulations. Understanding individual movement within a patch is the first step in understanding population dynamics at the landscape scale. The goal of this research was to estimate within-patch movement and resource use of the American Apollo butterfly,

Parnassius clodius, in Grand Teton National Park, WY, USA. This species was chosen because its exists in a mosaic of habitat patches surrounded by unsuitable habitat. P. clodius is typically found in dry, sagebrush meadows surrounded by forests. These meadows have varying degrees of connectivity and isolation throughout the study area.

Parnassius clodius was studied in a large, homogeneous sagebrush meadow during three summers. The initial goal of the project was to determine movement distance of a species occurring in a heterogeneous landscape. I wanted to see how P. clodius movements within a large homogeneous patch compared to the scale of habitat heterogeneity at the landscape level. A plot-based mark-recapture approach was used to estimate movement

distances of individuals. In order to determine which resources are most important to P.

clodius movement, abundance of nectar and host plants were measured in the plots.

Additionally, flight paths of P. clodius were measured to gain insight into the movement

patterns of individuals.

Thesis Organization

This thesis presents the results of a study on the demographics, movement, and

resource use of the butterfly, Parnassius clodius (Papilionidae), in Grand Teton National

Park, Wyoming, USA. The first chapter of the thesis is primarily a literature review of

butterfly movement presented in a metapopulation framework. The second chapter of the thesis is a manuscript wp.ich will be submitted for publication to Ecological Entomology.

Authorship will be by Julia N. Auckland who designed, conducted and analyzed the research,

Diane M. Debinski who served as major advisor on the project, collaborating on the design,

implementation, and analysis of the research, and William R. Clark who assisted in research

design and demographic data analysis. The third chapter contains general conclusions from

the research.

Literature Cited

Baguette, M. & Neve, B. (1994) Adult movements between populations in the specialist butterfly Proclossiana eunomia (, Nymphalidae). Ecological Entomology, 19, 1-5. 11

Baker, R.R. (1969) The evolution of the migratory habitat in butterflies. Journal of Ecology, 38(3), 703-746.

Brommer, J.E. & Fred, M.S. (1999) Movement of the Apollo butterfly Parnassius apollo related to host plant and nectar patches. Ecological Entomology, 24, 125-131.

Brower, L.P. (1996) Monarch butterfly orientation: missing pieces of a magnificent puzzle. The Journal of Experimental Biology, 199, 93-103.

Brussard, P.F., Ehrlich, P.R., & Singer, M.C. (1974) Adult movements and population structure in Euphydryas editha. Evolution, 28, 408-415.

Debinski, D.M. (1994) Genetic diversity in a metapopulation of the butterfly Euphydras gillettii. Biological Conservation, 70, 25-31.

Douglas, M.M. (1986) The lives of butterflies. The University of Michigan Press. Ann Arbor, MI.

Haddad, N .M. (1999) Corridor use predicted from behaviors at habitat boundaries. The American Naturalist, 152, 215-227.

Hanksi, I., Kuusaari, M., & Nieman, M. (1994) Metapopulation structure and migration in the butterfly Melitaea cinxia. Ecology, 75(3), 747-762.

Hanski, I & Simberloff, D. ( 1997) The metapopulation approach, its history, conceptual domain, and application to conservation. Metapopulation biology: ecology, genetics, and evolution (ed. by I. Hanski and M. Gilpin), pp. 5-26. Academic Press, San Diego, CA, USA.

Harrison, S. (1989) Long-distance dispersal and colonization in the bay checkerspot butterfly Euphydryas editha bayensis. Ecology 70(5), 1236-1243.

Harrison, S. (1993) Metapopulations and conservation. Large-scale ecology and conservation biology (ed. by P.J. Edwards, R.M. May, and N.R. Webb), pp. 111 - 128. Blackwell Scientific Publications, Oxford, England.

Harrison, S. & and Taylor, A.D. (1997) Empirical evidence for metapopulation dynamics. Metapopulation biology: ecology, genetics, and evolution (ed. by I. Hanski and M. Gilpin), pp. 5-26. Academic Press, San Diego, CA, USA.

Hill, J.K., Thomas, C.D. & Lewis, O.T. (1996) Effects of habitat patch size and isolation on dispersal by Hesperia comma butterflies: implications for metapopulation structure. Journal of Animal Ecology, 65, 725-735. 12

lms, R.A.& Y occoz, N .A. (1997) Studying transfer processes in metapopulations: emigration, migration, and colonization. Metapopulation biology: ecology, genetics, and evolution (ed. by I. Hanski and M. Gilpin), pp. 247-265. Academic Press, San Diego, CA, USA.

Keyghobadi, N., Roland, J. & Strobeck, C. (1999) Influence of landscape on population genetic structure of the alpine butterfly Parnassius smintheus (Papilionidae). Molecular Ecology, 8,1481-1495.

Kuussaari, M ., Nieminen, M., and Hanski, I. (1996) An experimental study of migration in the Glanville fritillary butterfly Melitaea cinxia. Journal of Animal Ecology, 65 , 791- 801.

Levins, R. ( 1969) Some demographic and genetic consequences of environmental heterogeneity for biological control. Bulletin of the Entomological Society of America, 15, 23 7-240.

Lewis, O.T., Thomas, C.D., Hill, J.K., Brookes, M.I., Crane, T.P.R., Graneau, Y.A., Mallet, J.L.B., & Rose, O.C. (1997) Three ways of assessing metapopulation structure in the butterfly Plebejus argus. Ecological Entomology, 22, 283-293.

Lima, S.L. & Zollner, P.A. (1996) Towards a behavioral ecology of ecological landscapes. Trends in Ecology and Evolution, 11 , 131-135.

Odendaal, F.J., Turchin, P. & Stermitz, F.R. (1988) An incidental-effect hypothesis explains aggregation of males in a population of Euphydryas anicia. The American Naturalist, 132, 735-749.

Neve, G. , Mousson, L., & Baguette, M. (1996) Adult dispersal and genetic structure of butterfly populations in a fragmented landscape. Acta Oecologica, 17, 621-626.

Nieman, M. ( 1996) Migration of moth species in a network of small islands. Oecologia, 108, 643-651.

Odendaal, F.J., Turchin, P., & Stermitz, F. R .. (1988) An incidental-effect hypothesis explains aggregation of males in a population of Euphydryas anicia. The American Naturalist, 132, 735-749.

Peterson, M.A. (1996) Long-distance gene flow in the sedentary butterfly, Euphilotes enoptes (Lepidoptera: Lycaenidae). Evolution 50(5), 1990-1999. 13

Peterson, M.A. (1997) Host plant phenology and butterfly dispersal: causes and consequences of uphill movement. Ecology, 78, 167-180

Ries, L. ( 1998) Butterflies in the highly fragmented prairies of central Iowa: how the landscape affects population isolation. M.S. Thesis. Iowa State University. Ames, IA

Roland, J., Keyghobadi, N. & Fownes, S. (2000) Alpine Parnassius butterfly dispersal: effects oflandscape and population size. Ecology, 81(6), 1642-1653.

Rosenberg, R.H (1988) Genetic differentiation among populations of Weidermeyer's admiral butterfly. Canadian Journal of Zoology, 67, 2294-2300.

Schultz, C.B. (1998) Dispersal behavior and its implications for reserve design in a rare butterfly. Conservation Biology, 12, 284-292.

Scott, J.A. (1986) The butterflies ofNorth America: a natural history and field guide. Stanford University Press, Stanford, .

Scott, J.A. (1975) Flight patterns among eleven species of diurnal lepidoptera. Ecology, 56 (Autumn), 1367-1377.

Sculley, C.E. & Boggs, C.L. (1996) Mating systems and sexual division of foraging effort affecting puddling behaviour by butterflies. Ecological Entomology, 21, 193-197.

Sharp, M.A., Parks D.R. & Ehrlich P.R. (1974) Plant resources and butterfly habitat selection. Ecology 55(4) 870-875.

Singer, M.C. & Thomas, C.D. (1992) The difficulty if deducing behavior from resource use: an example from hilltopping in checkerspot butterflies. The American Naturalist, 140(4), 654-664.

Stamps, J.A., Beuchner, M. & Krishnan,V.V. (1987) The effects of edge permeability and habitat geometry on emigration from patches of habitat. The American Naturalist, 129(4), 533-552.

Sutcliffe, O.L. & Thomas, C.D. (1996) Open corridors appear to facilitate dispersal by ringlet butterflies (Aphantopus hyperantus) between woodland clearings. Conservation Biology, 10(5), 1359-1365.

Sutcliffe, O.L., Thomas, C.D., & Peggie, D. (1997) Area-dependent migration by ringlet butterflies generates a mixture of patchy population and metapopulation attributes. Oecologia, 109, 229-234. 14

Stanton, M.L. (1984) Short-term learning and the searching accuracy of egg-laying butterflies. Animal Behaviour, 32, 33-40

Thomas, C.D. & Harrison, S. (1992) Spatial dynamics of a patchily distributed butterfly species. Journal of Animal Ecology, 61, 437-446.

Thomas, C.D., Thomas, J. A. & Warren, M.S. (1992) Distributions of occupied and vacant butterfly habitats in fragmented landscapes. Oecologia, 92, 563-567.

Thomas, C.D.& Singer, M.C. (1987) Variation in host preference affects movement patterns within a butterfly population. Ecology 68: 1262-1267.

Turchin, P. (1989) Population consequences of aggregative movement. Journal of Animal Ecology, 58(1 ), 75-100.

Watanabe, M. (1978) Adult movements and resident ratios of the black-veined white Aporia crataegi, in a hilly region. Japanese Journal of Ecology, 28, 101-109.

Wiens, J.A., Stenseth N.C., Van Home, B., & Ims, R.S. (1993) Ecological mechanisms and landscape ecology. Oikos 66:369-380.

Wood, P.A. & Samways, M.J. (1991) Landscape element pattern and continuity of butterfly flight paths in an ecologically landscaped botanic garden, Natal, South Africa. Biological Conservation, 58, 149-166. 15

CHAPTER 2. DEMOGRAPHICS AND MOVEMENT OF THE BUTTERFLY PARNASSIUS CLOD/US

A paper to be submitted to Ecological Entomology

Julia N. Auckland, Diane M. Debinski, and William R. Clark

Abstract 1. A three year (1998-2000) mark-recapture study was conducted on the American Apollo butterfly, Parnassius clodius Menetries, in a sagebrush meadow in Grand Teton National Park, Wyoming.

2. Percent cover of the species hostplant, Dicentra uni.flora, (1999) and abundance of the primary nectar species, Eriogonum umbellatum, (1999 and 2000) were estimated. Butterfly abundance was correlated with hostplant percent cover. There was a weak positive correlation between butterfly abundance and nectar abundance in 1999, but no relationship in 2000.

3. Movement distances of Parnassius clodius were determined from the mark-recapture study. The average straight-line movement per day was 200 meters. Movement estimates in all three years were highly correlated with the average distance between the plots sampled.

4. Recapture probability was significantly lower for females than for males across all three years, but there was no difference in survival rate. Survival and recapture probability decreased over the course of each season, while the probability of moving between plots (transition probability) increased.

Introduction

The complex spatial arrangement of many natural populations has received much

attention over the past ten years. The term metapopulation has been adopted to describe 16

populations made up of multiple subpopulations (Levins 1969; Hanski & Simberloff 1997).

Metapopulations are often described as occurring in patches of suitable habitat surrounded by

a matrix of unsuitable habitat. The population dynamics of each subpopulation are mostly

independent of each other, but are weakly correlated by limited exchange of individuals.

Further development of the metapopulation concept has led to defining multiple types of metapopulations based on the pattern and extent of the exchange of individuals (Harrison &

Taylor 1997). Knowledge of patterns of animal movement within metapopulations is important, both for understanding the population dynamics of natural communities and for predicting the effects of habitat fragmentation due to human development.

Movement between habitat patches is key to understanding population processes in heterogeneous landscapes (Kareiva 1990; Turchin 1991; Wiens et al. 1993; Diffendorfer et al. 1995; Lima & Zollner 1996). Animal distribution within a metapopulation is determined by within-patch behaviors, emigration, and colonization (Wiens et al. 1993; Ims & Yoccoz

1997). Within a habitat patch, or subpopulation, the density and distribution of individuals is dependent on movements in response to resources and habitat structure (Crist & Wiens

1995). Estimation of animal movement within a patch is the first step to understanding movements at a larger scale. However, estimation of movement distance has proven to be a challenge across various taxonomic groups.

Many butterfly species exist as metapopulations, and this framework has become well accepted for studying them (Thomas & Harrison1992; Hanski & Thomas 1993; Baguette &

Neve 1994; Hill et al. 1996; Sutcliffe & Thomas 1996; Brommer & Fred 1999; Roland et al.

2000). Butterflies are an ideal species for study because of their high visibility, the ease of 17 handling them, and the extensive knowledge about them. Multiple studies have been conducted looking at movement between patches of habitat using mark-recapture methods, long-term presence-absence surveys, and genetic relationships (Thomas & Harrison 1992;

Thomas et al. 1992; Hanski & Thomas 1993; Baguette & Neve 1994; Hill et al. 1996;

Peterson 1996; Sutcliffe & Thomas 1996; Lewis et al. 1997; Brommer & Fred 1999, Roland et al. 2000). However, while many studies have examined between-patch movement of butterflies, little effort has been devoted to estimating movement abilities of butterflies within a single large patch (Thomas & Harrison 1992; Hill et al. 1996; Brommer & Fred 1999;

Roland et al. 2000; but see Ries 1998). Understanding movement within a habitat patch is key to understanding transfer processes at a larger scale (Wiens 1993; Ims & Y occoz 1997).

Understanding butterfly behavior at this local scale is necessary for predicting large- scale movement patterns and metapopulation dynamics. Knowledge of individual movement patterns may aid in explaining more difficult to predict events such as movement between patches of habitat. Butterfly distribution is determined by mate location, nectar resources, and hostplant availability (Scott 1986). Predator avoidance and puddling for minerals also play a role (Sculley & Boggs 1996). The spatial distribution of butterflies is determined by the trade-offs and interactions among acquiring these resources. Mating strategy, sex, and time of day determine which resources are the most important for butterflies (Watanabe

1978; Boggs 1986; Odendaal et al. 1988). Individual movement and behavior is determined by resource distribution and life-history strategy.

Understanding the demographic parameters of butterfly populations is critical to gaining insight into the ecological mechanisms underlying population dynamics. Estimation 18 of demographic parameters from mark-recapture studies is a common practice, especially in studies of vertebrates. Butterfly studies typically only estimate population size and the proportion of individuals recaptured (Baguette & Neve 1994; Roland 2000). However, this is under-utililization of potentially valuable information about population dynamics (Schmidt &

Anholt 1999). Recent developments in statistical theory facilitates in-depth hypothesis testing from mark-recapture data (Lebreton et al. 1992; Lebreton et al. 1993; White &

Burnham 1999). Associated programs, such as Mark, can be used to estimate survival, recapture, and transition probabilities and facilitate making comparisons between sexes, times, or groups (Hestbeck 1991; White & Burnham 1999). Transition probabilities can be estimated for movement between different areas or for changes in life stages (ex. juvenile to adult).

We used a mark-recapture study to meet three research objectives: first, to examine the relationship between P. clodius and its hostplant and nectar resources; second, to estimate movement distances of P. clodius within a meadow; and third, to model relationships among recapture, survival, and transition probability ( the probability of moving from one plot to another). Comparing movement distances within a single large patch to movement data from metapopulation studies gives valuable insight into the important role of matrix habitat in limiting butterfly dispersal. Additionally, the scale of our study was different over three consecutive summers, enabling us to examine the effect of different sampling efforts on estimates of movement distance. Demographic data were examined both within and between 19 years. We first tested the hypotheses that survival and recapture probability would be different between sexes. Next, we tested the hypotheses that survival, recapture probability, and transition (movement) probabilities would vary over time. Finally, we tested to see if transition probabilities between plots were correlated with distance.

Methods

Parnassius clodius Menetries (Lepidoptera: Papilionidae) is a medium-sized, mostly white butterfly of western Canada and the northwestern United States. It is found in open woods and meadows. In our study area, P. clodius was found in highest densities in dry, cobbly, sagebrush meadows where its hostplant species, Dicentra uniflora (Steershead)

(Fumariaceae ), is abundant (Scott 1986). D. uniflora is a small, spring ephemeral which contains poisonous alkaloids. P. clodius is thought to be capable of sequestering these alkaloids, and all life stages are probably poisonous (Scott 1986). P. clodius females lay eggs on vegetation close to the hostplant. P. clodius overwinter as eggs, and the larvae emerge in early spring and feed on their hostplant. Pupation occurs in the soil. P. clodius has one flight per year, from late June through mid-July. Females mate only one time.

During copulation the male attaches a sphragis to the female's abdomen which prevents her from mating again (Scott 1986).

This research was conducted during the Summer (June-August) in Grand Teton

National Park in northwestern Wyoming from 1998 to 2000. The rugged topography of the

Rocky Mountains creates a heterogeneous distribution of meadow and forest communities along altitudinal and moisture gradients. The meadow communities range from wet marshy 20

areas (Kindscher et al. 1998) to dry sagebrush meadows (Jakubauskas et al. 1998). The

cobbly sagebrush meadows preferred by P. clodius in Grand Teton National Park tend to occur near waterways and are typically surrounded by forests. The study site was a sagebrush meadow 5km south of Colter Bay, 1km east of US Highway 191 and parallel to

Pilgrim Creek. The site is flat with an elevation of 21 00m. The meadow is approximately

1500m x 300 min size.

We used mark-recapture methods to study a population of Parnassius clodius during three annual flight periods (1998-2000). We conducted a preliminary mark-recapture study from June 30 - July 9, 1998, using three 75 m x 75 m plots separated by 100 m and 225 m

(Figure 1). Two people captured all butterfly species in each plot for 35 minutes between

1000 and 1700 hours. Butterflies were held in glassine envelopes until the end of the survey.

Then, each captured butterfly was marked with a permanent marker on both of its hindwings indicating the day and plot in which it was caught. All butterflies where released from the center of the plot. Mated females were noted upon capture by the presence of a sphragis.

Surveys were limited to times when the temperature was above 70°F, wind was less than 10 mph, and the sun was not obscured by clouds. Plots were surveyed in a random order each day. All three plots were visited for ten consecutive days (June 30 - July 9). On July 8 - 10, two additional plots were monitored for P. clodius only. They were separated by 100m and

225m (Figure 1).

During 1999 and 2000, plots were 50 m x 50 m, surveys lasted for 20 minutes, and we captured only P. clodius. The smaller plots and shortened survey time enabled us to sample a larger area of the meadow. If weather prevented us from sampling all plots on a day, then we 21

completed the rotation on the following day. We started surveying plots a few days after the

beginning of the flight period and continued until we were catching fewer than five

butterflies per plot during the 20 minute survey period. An individual number was drawn

with a permanent marker on both hind wings of each captured butterfly. Sex of each butterfly

and mating condition of females was recorded based on morphological differences and the

presence or absence of a sphragis.

From June 28 - July 15, 1999 butterflies were captured and marked in eight plots randomly placed throughout the meadow (Figure 1). Six plots were monitored consistently

through the flight period and two additional plots were monitored during the peak of the

flight period. From June 17 - July 2, 2000 butterflies were captured and marked in six 50m x

50m plots randomly placed in the eastern half of the meadow (Figure 1). Plot placement in

2000 was spatially restricted to increase the number of recaptures.

Hostplants and nectar

During late May of 1999, the percent cover of P. clodius' hostplant, D. uniflora, was

estimated in each butterfly survey plot. Transects were placed every 5 meters within the 50 x

50 m plot, and the percent cover was estimated along each transect at 5 meter intervals using

a 0.25 m2 quadrat. During May of 2000, no hostplants were present in the study area, so we

could not repeat the same measurements.

Nectar abundance in 1999 was estimated between July 7 and July 10, just after the

peak of the flight season. Three transects were evenly placed within each 50 m x 50 m plot,

and the number of inflorescences of each flowering species was estimated in 0.5 m2 quadrats 22 spaced at 2 meter intervals along the transect. During 2000, all nectar data were collected on

June 24, just after the peak of the flight season. Sampling effort was reduced during 2000 and measurements were taken every fifth meter. Buckwheat (Eriogonum umbellatum) was the predominant nectar source in the study area during our sampling in both years, it was the only flower species which was not senescing during our count, and it was the preferred source of nectar for P. clodius (Auckland, personal observation). Thus, only E. umbellatum was used in nectar analyses. The total number of P. clodius caught in each plot on the days immediately surrounding the nectar sampling where used in the analyses. P. clodius numbers on July 9, 10, 12, and 13, 1999 and between June 22 and June 26, 2000 were compared to the mean number of inflorescences of E. umbellatumlm2 in each plot during the respective years.

The relationship between butterfly abundance and E. umbellatum abundance was analyzed using linear regression.

Movement analyses

Butterfly movement data were adjusted for capture effort at different distances (Porter

& Dooley 1993, C. Ray personal communication) and for time between captures. The number of butterflies marked in each plot was multiplied by the number of subsequent days of recapture effort to obtain the number of "butterfly days" available in each plot. Recaptures were only possible at discreet distances from any capture point because we sampled in plots.

Therefore, the number of butterflies available for resight at each distance and time were calculated from the "butterfly days" adjustment. Then the relative probability of resighting butterflies (the proportion of total "butterfly days") at each time and distance was calculated 23

by dividing the available number of butterflies recaptured at each distance and time by the total number of butterflies recaptured. This was multiplied times the number of butterflies recaptured at each time and distance interval to complete the data adjustment for variability in the number of butterflies available to be recaptured.

Next, the probability of resighting was corrected for catch effort because as distance from a release plot increases, the area sampled for recapture decreases ( area sampled = plot width/2Ilradius). For example, 100 percent of the area at 0 meters from the 50m X 50 m release plot is sampled, but if you move 100 meters away from the release point, then only 8 percent of the perimeter is sampled. So, the adjusted data were divided by the proportion of the perimeter surveyed to calculate a corrected number of recaptures at each distance and time interval.

Finally, the mean movement distance was corrected by dividing the corrected number of recaptures at each available time and distance by the total number of possible recaptures after adjustment. This proportion was then multiplied by each possible distance/day to weight the observed movement data for effort and an adjusted mean was calculated.

Program Mark analyses

We used open-population, capture-recapture models (Cormack-Jolly-Seber (CJS) models) to estimate survival (cp), recapture (p), and transition($) probabilities (Cormack

1964; Jolly 1965; Seber 1965; Hestbeck et al. 1991 ). Survival probability is the probability that an individual survives from day to day. Recapture probability is the probability that a marked individual is recaptured, given that it is alive. Transition probability is the 24

probability of moving between plots during a sampling interval (Hestbeck et al. 1991 ;

Lebreton et al. 1992). All of our estimates represent daily probabilities.

Program Mark (White & Burnham 1999) was used for all of our mark-recapture data

analyses. Program Mark estimates survival, recapture, and transition probabilities using

numerical maximum likelihood techniques. Additionally, Program Mark computes bias-

corrected versions of Akaike's information criterion (AICc) values for each model which enabled us to objectively fit models and test hypotheses (Pollock et al 1989; Burnham et al.

1995).

We used time-independent models to estimate survival, recapture, and transition probabilities for each sex. These models estimate a single rate for each parameter over each flight season and thereby obtain the most robust estimates. Comparisons of survival and recapture probability differences between males and females over all three years were made using a paired t-test, weighted by standard error (Hedges et al. 1999).

Changes in survival, recapture, and transition probability over time were analyzed in two ways. First, data were analyzed by grouping sexes together and dividing the capture- recapture period in each year into four discrete time intervals. Thus, separate estimates were calculated for each time interval. Trends over time were analyzed using a linear regression.

A second analysis was done using Program Mark to test for temporal trends in the data.

Program Mark estimated an intercept and a slope due to time for each parameter. The fit of these models was then compared to the fit of models with and without time effects using

AICc values. 25

Estimates of transition probabilities at different distances were made by placing paired

plots in ascending order according to the distance between them and then grouping them

according to distance. The mean distance of each group was then compared to the transition probability of that group. For the 1998 analysis only the main plots were used, and there were only three possible distances. There were 28 (7 groups) possible distances in 1999 and

15 (5 groups) possible distances in 2000.

Results

Mark-Recapture

During all three years, males emerged first and were captured more frequently than females (Figure 2). In 1998, we surveyed butterflies from the beginning of the flight period until the population started to decline (Figure 2a). During 1999, we covered the entire flight period of P. clodius, although we were only able to sample one day between July 4 and July 8 because of cloudy weather (Figure 2b ). Adult P. clodius emerged approximately two weeks earlier in 2000 than in 1998 or 1999. They were first observed on June 15; however, low temperatures and cloudy weather prevented surveying during the first few days of the flight

(Fig. 2c).

In 1998, we marked a total of 500 P. clodius and recaptured 119 (24%) individuals a total of 139 times during the 11-day mark-release-recapture (MRR) period (Table 1).

Seventy-seven (55%) recaptures occurred in the plots where the butterflies were originally captured. We also marked 256 other butterflies of multiple species and recaptured 18 (7%).

We limited our analyses and future research to P. clodius. 26

During l 999~ 775 P. clodius were marked and 61 (8%) individuals were recaptured

(Table 1). There was a total of 65 recapture events because four butterflies were recaptured twice. Twenty-seven (42%) of the recaptures occurred in the plot where the butterfly was previously captured.

During 2000, 488 P. clodius were marked and 85 (17%) individuals were recaptured

(Table 1). There was a total of 100 recapture events because 20 butterflies were recaptured twice, one was recaptured three times, and one was recaptured four times. Twenty-seven

(25%) of the recaptures occurred in the plot where the butterfly was previously captured.

Hostplants and Nectar

There was no significant interaction between the sexes and hostplant cover, so sexes were analyzed together. P. clodius abundance (in the six plots surveyed equally over the entire flight period) was positively correlated with percent cover of the hostplant D. uni.flora

(r2 = 0.69, p < 0.05) (Figure 3a). P. clodius abundance during the peak of the flight period

(all 8 plots surveyed equally July 9, 10, 12, and 13) not significantly correlated with hostplant coverage (r2 = 0.00, p = 0.8909)(Figure 3b ).

The 1999 data showed an insignificant relationship between nectar and butterfly abundance (Figure 4a). The assumption of equal variance of nectar abundance between plots is not met by the 1999 data and could not be corrected by transforming the data. One plot had a very high amount of nectar. When it was omitted from the analysis, the relationship between butterfly abundance and nectar was significant (Figure 4a) and the assumption of 27

equal variance was met. There was not a significant interaction between sex and nectar (p =

0. 7072). However, when analyzed separately males had a significant response to nectar (r2 =

2 0.61 , p < 0.05), while females did not (r = 0.12, p = 0.4457). The 2000 nectar data showed an insignificant relationship between P. clodius and E. umbellatum (Figure 4b). There was a significant interaction between sex and nectar (p = 0.0146). Males had an insignificant negative relationship with E. umbellatum abundance (r2 = 0.15, p = 0.4444), while females had an insignificant positive relationship (r2 = 0.00, p = 0.9177). Again, the assumption of equal variance of nectar abundance between plots was not met and the data could not be corrected by transformation. There was no significant relationship between butterfly abundance and nectar abundance when data were combined for the two years (p = 0.9259).

Movement

The mean distance moved per day by P. clodius was 200 meters when averaged among the three years. The corrected means for daily movement were much higher than the raw means in 1998 and 1999 (Table 2, Figure 5). In all years, both the raw and corrected movement distances were correlated with the mean distance between plots. Movements were recorded at the farthest distances in all three years. One marked individual in 2000 was captured 12 km from the study area. 28

Program Mark Analyses

A paired t-test, weighted by standard error, was used to compare the mean difference

in survival and recapture probability for males and females across years (Table 3) (Hedges et al. 1999). Male survival rate estimates were higher than females in 1999 and 2000.

However, there was not a statistically significant difference between male and female survival across all three years. The mean difference in survival, weighted by standard error, was 0.068 (SEn = 0.1030, Z = 0.654, P > 0.05). Male recapture probability was higher than female recapture probability in 1998 and 2000 (Table 3). The paired t-test, weighted by standard error, showed that male recapture probability across all three years was significantly higher than female recapture probability with a difference of 0.1090 (SEn = 0.0274, Z =

3.978, P < 0.05).

Detection of a difference in transition probabilities between the sexes was only possible in 2000. During 2000 female transition probability was almost double the transition probability of males (Table 3). This was a significant difference (SEn = 0.1010, Z = 2.679, P

< 0.05). Not enough females were recaptured in 1998 and 1999 to accurately estimate transition probabilities (Table 3).

Survival, recapture, and transition probabilities varied with time in all three summers

(Figures 6 and 7). Survival and recapture probability decreased over time during each of the three years, whereas transition probability increased (Figures 6 and 7). Regression analyses of these trends are significant for survival (p = 0.0230) and recapture probability (p = 0.0307) in 1999 and recapture probability in 1998 (p = 0.0501). The trend models which decrease 29 over time fit the data best in all years for both survival and recapture probability (Table 4).

Models including a temporal trend in transition probability did not have good fits in any year

(Table 4).

The relationship between transition probability and distance was only estimable in

1998 (Figure 8). The larger number of plots in 1999 and 2000 resulted in a lower number of movements between any given pair and made estimation of transition probabilities in program Mark impossible. During 1998, transition probability decreased as distance increased. However, the relationship is statistically insignificant (r2 = 0.88, p = 0.2175).

Discussion

Mark-recapture

The emergence patterns of adults followed the typical pattern for butterflies in which males emerge first and their population peaks slightly before that of females (Scott 1986).

Butterflies have evolved this staggered emergence because females must maximize the chance that there will be a male with which to mate (Thornhill & Alcock 1983; Scott 1986).

Our experimental design differed between years because there was a tradeoff between spreading plots out to improve estimates of movement distance and placing plots close together to increase the number of recaptures. Plots were closest together in 1998 and 2000, so we recaptured the largest percentage of individuals in those years and had more accurate estimates of demographic parameters from the mark-recapture data. In 1999, plots were spaced farthest apart and there were few recaptures, but a estimates of movement were obtained over a broader range of distances (Figure 5). 30

Hostplant and Nectar

There is a strong positive relationship between hostplant cover and P. clodius abundance in 1999 when examined over the entire flight period (Figure 3a). This relationship is driven by the males. Interestingly, this relationship does not hold during the peak of the flight period (Figure 3b ). This is true when analyzed for both males and females. This result suggests that at different times of the flight period, different resources are more important.

Distribution may not always be explained by the variables that we would expect. Behaviors which have evolved as a result of intraspecific mate searching competition strategies may result in what appear to be nonadaptive butterfly distributions (Thornhill & Alcock 1983;

Baguette et al. 1996).

During 2000, almost no hostplants were observed. Because adults emerged in near normal numbers, we suspect that the caterpillars emerged early in response to the early snow melt and most of the hostplants had been eaten, although sampling for larval host plants began at the same time as in 1999 (Appendix 1). The other alternative is that D. uni.flora was unable to grow at all in our study site either because of warmer, dryer weather or for some other, unknown reason and that the P. clodius observed where all immigrants. Either possibility would impact population levels of P. clodius. Long-term coupled fluctuations of abundance of P. clodius and D. uni.flora could potentially be occurring and determining the distribution and abundance of both species. Alternatively or simultaneously, climatic factors may have profound effects on growth of D. uni.flora and thereby affect population levels of P. clodius. There was a significant relationship between P. clodius abundance and the nectar source E. umbellatum in 1999 if one "outlier" plot was removed from the analysis. This plot 31

This plot had much more nectar than any of the other plots, which butterflies may not have been able to respond to proportionately. Additionally, this plot was located 10 meters from the forest edge which may have resulted in lower usage of the area. There was no significant relationship in 2000 between butterfly and nectar abundance. It is impossible to tell if the apparent trend in 1999 is typical or if there is usually no relationship for these two species.

Weather during 2000 was warmer and drier than in 1999. Therefore, different factors may have influenced P. clodius distribution in each year.

Movement

Movements of P. clodius were similar to movements estimated for P. apollo (200 m and 230 m, respectively (Brommer & Fred 1999). Scott (1975) estimated that mean P. smintheus movements were almost 200m, while Roland (2000) found them to move 145 m.

Parnassius are large butterflies and strong flyers capable of long distance movements.

Determining the appropriate sampling scale and correcting for effort is critical in estimating dispersal. However, there is an inevitable trade-off between increasing the area sampled and a decreasing the numbers of recaptures. Changing scale in each year of our study enabled us to have better estimates of demographic parameters in 1998 and 2000, but provided the best estimate of movement in 1999 (Table 2, Figure 5).

Sampling effort and observed movement distance were correlated over the three years of our research (Table 2). Our results provide further evidence that estimates of movement distance from mark-recapture data are biased by the distance over which sampling occurred

(Porter & Dooley 1993; Koenig et al. 2000). Estimates of movement were limited by the 32 scale at which we sampled. Correcting for sampling effort improved our estimates of movement, especially during the year our plots were farthest apart (1999) (Table 2, Figure 5).

While correcting for sampling effort improves estimates of movement distance, obtaining measurements of maximum dispersal distances are virtually impossible. Long distance dispersers are probably missed by most studies (Koenig et al. 2000). Recent evidence from genetic studies adds support to the evidence from field data that butterflies are capable of dispersing much greater distances than are typically observed in mark-recapture studies

(Peterson 1996; Roland et al. 2000).

While distance alone might not limit butterfly movement in large butterflies such as

Pamassians, changes in habitat type may present substantial barriers to movement. In all three years of our study, individuals were recaptured at the maximum distances sampled and one marked individual was captured 12 km outside the study area. Distances within open habitat may not significantly limit movements of P. clodius up to at least 1000 m. Forest edges probably have a greater effect on limiting dispersal than distance. When P. clodius where observed encountering forest edges, they either turned back or followed along the edge over 50% of the time (Auckland, personal observation). Behavioral observations and a mark- recapture study of the ringlet butterfly (Aphantopus hyperantus) found that they avoided flying into the forests and were more likely to move between forest glades if they were connected by open corridors (Sutcliffe & Thomas 1996). Likewise, Ries (1998) observed that the prairie specialist, Speyeria idalia, avoided crossing treeline edges 92 percent of the time and monarch butterflies (Danaus plexippus) avoided crossing them 76 percent of the time. Haddad (1999) observed that two Coliadinae species avoided forest edges, but the 33 swallowtail Papilio troilus crossed edges readily. Roland (2000) found that forests were twice as resistant to movement of Parnassius smintheus as open meadow habitat. This could be a result of butterflies either moving more slowly through forest or avoiding forest habitat.

Forested edges seem to prevent real barriers to many species of butterflies. Stamps

(1987) developed computer simulations of emigration and found that edge permeability and geometry of a patch are the most important factors affecting emigration from a patch.

Reluctance of individuals to cross edges may be the mechanism decreasing movement between patches rather than reduced movement after crossing into matrix habitat.

Program Mark analyses

Survival probability was not significantly different between females and males.

However, female recapture probability was significantly lower than male recapture probability (Table 1). From the these data, it is evident that a much lower percentage of females were recaptured than males. Many studies of butterflies have observed lower return probabilities of females than of males (Scott 1986; Sculley & Boggs 1996; Brommer & Fred

1999; Gutierrez & Thomas 2000; Roland et al. 2000). However, because this return probability is a function of both survival and recapture probability, correct analyses of these parameters is critical for understanding population biology and life-history parameters

(Lebreton et al. 1992; Schmidt & Anholt 1999). Multiple capture events are needed to be able to separate the contributions of survival and recapture probability to return probability.

The interdependence of these two estimates is typically ignored in analyses reporting lower 34 return probabilities for females. Our analyses clearly demonstrate that for P. clodius, recapture probability is lower for females independently of survival rates.

Survival and recapture probability decreased over time in all years. Transition probability trends were confounded by the strong effect of distance. However, there was a statistically insignificant increase over time in all years. This pattern likely reflects that early in the emergence the population is composed predominantly of males which stay close to areas with the best habitat. Multiple factors probably interact to increase movement as the flight season progresses. Later in the season, most females have emerged, mated, and are ranging widely in search of hostplants. Also, as the population ages, the probability of a male finding an unmated female in the meadow decreases. Simultaneously, nectar resources in the dry sagebrush meadow begin to senesce towards the end of the flight period while nectar lasts longer in more mesic adjacent habitats. Therefore, decreased mating probability and increased need for nectar may combine to increase the likelihood that males will leave the meadow. Butterflies are increasingly likely to emigrate as nectar decreases (Kuussaari et al.

1996; Ries 1998). Increasing movement of both sexes combined with an increasing proportion of females in the population results in recapture probability decreasing over time.

Survival probability decreases as the entire population ages. Analysis of temporal variation can explain some of the variance in data and can be used to gain insight into life history strategies of organisms (Gould & Nichols 1998)

Individual movements between subpopulations and/or habitat patches within a metapopulation are the key to maintaining genetic diversity, re-colonization of areas where existing population have gone extinct, and colonization of new habitats which become 35 available due to disturbance or succession. The first step in understanding transfer processes at the landscape level is to understand responses to resources, movement, and population processes within a patch. P. clodius seems to be responding to hostplant and nectar resources differently over time within the flight period. Estimates of movement suggest that they are not limited by distance in open habitat, but that their avoidance of edges may limit emigration and, thus, dispersal.

Acknowledgments

We wish to thank B. Danielson, R. Fletcher, J. Fung, E. Hart, J. Su and E.L.V.I.S. for help and comments. Field assistance was provided by S. Foldi, D. Friederick, J. Fusek, A.

Hetrick, K. Keffer, M. Nafranowicz, M. Sanford, E. Saveraid, T. Saveraid, and D. Williams.

P. Dixon, and C. Ray helped with data analysis. Housing and research facilities were provided by the University of Wyoming National Park Research Station and H. Harlow.

This research was supported by the Iowa Agriculture and Home Economics Experiment

Station and the Environmental Protection Agency (EPA) through their Ecological

Assessment and Restoration program. Although the research described in this article has been funded in part by the EPA (through grant 96-NCERQA-lA to Debinski et al.), it has not been subjected to the Agency's peer review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred. This is Journal Paper

No. J-:XXXXX of the Iowa Agriculture and Home Economics Experiment Station, Ames,

Iowa, Project 3377, and supported by Hatch Act and State oflowa Funds. 36

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Appendix 1.

Weather data (mean daily temperature and snow depth) for all three years were examined to explain the early emergence of adults in 2000 (National Climate Data Center).

Degree days accumulation was calculated for each month from mean daily temperature

(Higley and Wintersteen, 1987). The number of degree days accumulated though May was similar in all three years (7, 14, and 24.5 chronologically 1998-2000). Degree days accumulated through June increased each year (27, 104.5, and 158.5 chronologically 1998-

2000). The winter snow melted two weeks earlier in 2000 (April 15) than in either 1998

(April 28) or 1999 (May 2). Emergence of P. clodius adults seems to be most tightly correlated with snow melt because emergence dates were similar in 1998 and 1999 despite differences in degree day accumulations. Early larval emergence following snow melt could explain both the absence of hostplants in May 2000 and the subsequent early emergence of adults the same year. The larvae of P. clodius are a dark color and pupate in the soil. These may be adaptations to the low temperatures of their alpine habitat. Because soil temperature determines their microclimate, development rates would be more dependent on the timing of snow melt than on air temperature. Once the snow melts, the sun will heat up the soil regardless of air temperature. 42

Table 1. The number of P. clodius captured and recaptured in all plots during surveys 1998-2000. Males Females Total 1998 Captured 404 96 500 Recaptured 107 12 119 % Recap 26 13 24

1999 Captured 552 223 775 Recaptured 55 6 61 % Recap 10 3 8

2000 Captured 343 145 488 Recaptured 77 8 85 % Recap 22 6 17 43

Table 2. The mean distance (meters) moved by P. clodius between recaptures (mean/move), the mean distance moved per day (mean/day), the mean distance moved per day corrected for effort at different distances ( corrected), and the mean distance between plots ( effort).

Year Mean/Move Mean/Day Corrected Effort 1998 122 77 187 236 1999 334 112 287 491 2000 146 91 132 190 Mean 200.7 93.3 202.0 305.7 44

Table 3. Daily survival rate ( cp ), recapture probabilities (p) and transition probabilities (lfT) for male and female P. clodius estimated using Program Mark (White and Burnham, 1999).

Year Estimate SE 95% CI Estimate SE 95% CI Males Females Survival 1998 0.658 0.047 0.565-0.750 0.895 0.245 0.415-1.374 1999 0.751 0.046 0.662-0.841 0.359 0.165 0.036-0.682 2000 0.820 0.029 0.762-0.878 0.569 0.148 0.280-0.859

Recapture Probability 1998 0.242 0.036 0.171-0.576 0.143 0.088 -0.029-0.315 1999 0.054 0.012 0.030-0.113 0.081 0.062 -0.039-0.202 2000 0.168 0.024 0.121-0.406 0.022 0.015 -0.008-0.052

Transition Probability 1998 0.142 0.023 0.103-0.193 0.033 0.033 -0.032-0.098 1999 0.514 0.010 0.035-0.075 0.033 0.022 0.009-0.114 2000 0.129 0.020 0.095-0.174 0.230 0.032 0.173-0.298 45 Table 4. Models fits for survival and recapture probabilities using AIC values. Four best models shown for each year. Delta 1 2 3 4 Year Model ' AICc AICc Weight #Par Deviance 1998 Phi(. )p(trend) 660.15 0.00 0.46993 3 94.66 Phi(trend)p( trend) 660.74 0.59 0.35005 4 93.21 Phi(trend)p(.) 668.03 7.88 0.00914 3 102.54 Phi(.)p(t) 670.45 10.30 0.00272 10 90.48

1999 Phi(trend)p(.) 569.50 0.00 0.44601 3 59.54 Phi(trend)p(trend) 570.76 1.26 0.23754 4 58.78 Phi(.)p(t) 578.79 9.29 0.0043 11 52.52 Phi(t)p(.) 582.97 13.47 0.00053 11 56.71

2000 Phi(. )p(trend) 863.76 0.00 0.43058 3 182.64 Phi(trend)p(trend) 865.63 1.87 0.16929 4 182.47 Phi(trend)p(.) 867.54 3.78 0.06502 3 186.42 Phi(.)p(t) 871.9 8.14 0.00736 13 170.15

1Model parameters. Phi=survival p=capture probability 2Model type: (trend)= temporal trend;(.)= constant; (t) = time dependent 3 AICc = Akaike Information Criterion 4#Par = number of parameters 46

Fig. 1. Sampling plot arrangements 1998-2000. Plots are represented by squares. Plots sampled regulary are black. Plots with lower sampling effort are outlined in black. Plots are 75m X 75m in 1998. Plots are 50m X 50m in 1999 and 2000. The meadow is white, the forest is grey, and a road runs through the study area. 47

(a) 1998 II) :::i 30 =s "C ...,._Males -2 Cl) (.) Q, 25 --e- Females Cl E cu 20 0 ..."' ... .2 -Cl) 15 .c ...C. E Cl) ::::, C. 10 s: .... Cl) .r:. en en cu ::::, 5 ... cu Cl) fol > 0 <( ,...__ 0 ..... C'? ::::t LO

(b) 1999 II) 20 ·=="b "C -2 Cl) (.) Q, - Cl E 15 cu -' 0 ...... 2"' -Cl) 10 .c ...C. E Cl) ::::, C. s: ... Cl) .r:. 5 en en cu ::::, ... cu - Cl) fol --. > 0 <( co O') 0 ..- N O') 0 ..- N C'? '<;f" LO N N C'? ;:::- ;:::- £2,...__ ::::t,...__ ,...__ ,...__ t:::,...__ ,...__ ...... co co co ;:::- ,...__ ;;:::;:::- ;:::- ;:::- ;:::- Dates

{c) 2000 .2 20 "b "C -2 Cl) (.) o. 15 Cl E cu - "' Cl) £C. 10 .c ... E Cl) 5 ~!Cl) .r:. en en

Cl) fol > 0 <( ,...__ ,...__ co O') 0 N C") '<;f" LO

Fig 2. Average number of P. clodius caught per plot censused on each date. Dates when no plots were censused are indicated by a dashed line. In 1998, plots were 75m X 75m and censused for 35 minutes. In 1999 and 2000, plots were 50mX50m and censused for 20 minutes. 48

(a) Entire emergence, 6 plots 140 ct :E: 130 ... C, C1) :::s .c cu 120 E u :::s U) C ::S 110 - =s :!o- 0 100 I- (.) • R2 = 0.6911 90 0 0.5 1

Percent cover of D. uniflora

(b) Peak emergence, 8 plots

70 ------It-ct .c- 60 - 0 C, ... :::s • C1) cu • .c (.) 50 - E u, • :::s ::s 40 - • • C =s • -;; -E 0 (.) 30 - I- • 20 +------,------.-- 0 0.5

Percent cover D. uniflora

Fig. 3. Regression of number P. clodius caught against hostplant D. uniflora percent cover. (a) for the 6 main plots in 1999 monitored throughout the flight period (F=8.95, d.f.=5, P<0.0403) (b) for the 8 plots monitored only during the peak emergence in 1999 (F=0.02, d.f.=7, P<0.8909) 49

(a) 1999 with and without outlier plot 75 Cl) :::J N 2 65 R = 0.8982 ·-"0 ci- en .Eu - en . en - 55 Q.. I ..,_ - M 0::::, - ... -, "C 45 C1) - C: .c -§, cu 0 E ::::, 35 z::::, (.)cu 25 • 0 5 10 15 20 25 30

E. umbellatum lm2

(b) 2000

0 75 Cl) 0 :::, 0 ·-"0 N 65 - • 0 CD -U NI ,N Q.. N 55 • .... C1) • 0 C: ... ::::, 45 • • C1) -, • .cE .c:- ::::, C') 35 z ; (.) 25 0 5 10 15 20 25 30

E. umbellatum lm2

Fig. 4. Regressions of numbers of P. clodius against number of inflorescences/ m2 of the primary nectar source, E. umbellatum, during the peak flight period. (a) There is not a significant relationship between P. clodius and E. umbellatum in 1999: F=0.84, d.f.=7, P=0'.3959. However if one outlier plot (open circle) is removed, then there is a significant positive correlation. The trend line fits these data. F=44.13, d.f.=6, P=0.0012. (b) F=0.38, d.f.=5, P=0.5710 50

1998 Raw Data 1998 Corrected Data

23 90 82 1600 - 0 0 C: 80 C: 1400 Q) Q) ::::, 70 ::::, 1200 C" 60 C" 16 Q) Q) 1000 ... 50 - ... LL LL 800 40 'C 'C Q) 600 Q) 23 30 82 5 0 400 ,.,,Q) 20 -...Q) 10 ... 200 .c 0 0 0 (.) 0

Distance Moved per Day (meters)

1999 Raw Data 1999 Corrected Data

30 28 1800 0 0 8 C: C: 1600 Q) 25 Q) ::::, ::::, 1400 C" C" 1200 Q) 20 Q) ...... 1000 LL 15 LL 'C 800 5 2 'C Q) Q) 10 8 600 3 0 3 Q) 400 Q) 5 -... ,.,, ... 200 0 0 0 .c 0 0 (.) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) l!) 0 <':'

2000 Raw Data 2000 Corrected Data

46 1200 50 46 20 0 0 45 C: 17 C: Q) 1000 10 Q) 40 ::::, ::::, 35 C" 800 C" Q) Q) 30 ...... LL 10 LL 25 20 600 17 'C 'C 20 Q) 3 G) 400 15 10 10 0 Q) ,.,,Q) 10 -... 200 .c 5 0 0 0 (.) 0 R)r;;:, r;;:,'pr;;:, r;;:,r;;:, ":,r;;:, ,P ":,r;;:, <;)r;;:, ~r;;:, r;;:,'pr;;:, r;;:,r;;:, ":,r;;:, ":,r;;:, <;)r;;:, ~r;;:, ...._, ...... __,'V .__,'1; .__,OJ .__,":5 ...._, .__,...... __,'V .__,'1; .__,OJ .__,":5 ":, " ":, " ...._r;;:,"' ...._":i '1,r;;:, '1,":, ":,r;;:, ...._r;;:, ...._":i '1,r;;:, '1,":, ":,r;;:, Distance Moved per Day (meters) Distance Moved per Day (meters) Fig. 5. Histogram of distance moved per day by recaptured Parnassius clodius. The number over each bar denotes the number of butterfly recaptures adjusted for the number of days between recaptures. The corrected frequency adjusts for the time available for recapture and the sampling effort at different distances. 51

1.0 1998 0.8 >, ------:c 0.6 ------____ Capture .cCV ------0 0.4 Survival a.a.. 0.2 ------Transition 0.0 ------0 N I.() r-- co CV) r-- r-- r-- r-- -co - - --

1.0 ...... 1999 0.8 ' ' :c 0.6 ' .cCV ' 0 0.4 ' a.a.. ' 0.2 ' ' "' 0.0 co 0 N co co 0 N "'q" N ("') r-- r-- r-- r-- -co -CD ------r-- r-- r--

1.0 2000 0.8 ------.c 0.6 ------CV --- .c --- -- 0 0.4 a.... 0.2 0.0 0 N CV) "'q" I.() CD r-- CX) CJ) 0 N N N N N N N N N N ("') r-- -CD -co --co co ------co co CD co co co CD -

Fig. 6. Program Mark temporal models. Slope and intercept estimates are from the trend model for the parameter shown, combined with constant estimates of the other parameters in each model. Transition probability trend models were unestimable in 1999 and 2000. 52

1.0 l 1998 0.8 >, :t= .c 0.6 ca .c 0 0.4 L. Q. 0.2 0.0 0 1 2 3 4

1.0 0.8 >, :t= 0.6 :cca .c 0.4 L.0 Q. 0.2 0.0 0 1 2 3 4

1.0 2000 0.8 >, :t= .c 0.6 ca .c esurvival 0 0.4 L. Q. 0.2 Transition 0.0 0 2 3 4 Time Intervals

Fig. 7. Parameter estimates over equal time intervals. Trend lines are shown for illustrative purposes only. 53

0.3 ------.0 ca 0.2 - • -8I- C. • C 0.1 - en 2 C R = 0.8878 I- 0 +---....,,----,------"'• 0 100 200 300 400 500

Distance between plots

Fig. 8. Regression of distance between plots against movement transition probabilities of Parnassius clodius for 1998 (F=7.9, d.f.=2, P<0.2175) 54

CHAPTER 3. GENERAL CONCLUSIONS

A preliminary understanding of butterfly metapopulations has been achieved in the past 15 years. Multiple studies have found similar behaviors within patches; different aspects of emigration rates have been studied; dispersal distances have been estimated for multiple species; and colonization events have been observed in multiple landscapes. However, little research has been done on the mechanisms which determine movements of butterflies within a patch.

Infrequent, long-distance movements have been observed in many mark-recapture studies (Brussard et al. 1974, Baguette and Neve 1994, Kuussaari et al. 1996, Harrison 1989,

Peterson 1996, Roland et al. 2000). Viewed alone, each study suggests that long-distance dispersal is a rare event. The examination of multiple studies with similar results implies that long-distance dispersal events regularly occur in many butterfly metapopulations. Additional evidence of regular long-distance dispersal comes from the recent research on genetic variation (Rosenberg 1988, Debinski 1994, Peterson 1996, Keyghobadi et al. 1999).

However, there is the possibility that an inability to detect genetic variation at local scales has biased these results in earlier studies (Keyghobadi et al. 1999). Genetic analysis is a promising tool for determining long term movement patterns through the landscape.

The results of our movement estimation are similar to those of other studies. P. clodius movements averaged 200 meters. However, in all three years, butterflies moved between the furthest plots surveyed ( distances of approximately 1000m). One marked individual in 2000 was recovered 12 kilometers from the study area. Our data add to the 55 number of studies finding infrequent, but regular occurrences of long-distance dispersal.

These events may be the key to colonization of patches in which populations have gone extinct due to demographic or climatic stochasticity

Valuable insight was gained into movement patterns by recording flight paths of individuals. We tracked individuals for ten minutes and recorded the length, time, and bearing of their flight. After completing the observations, individuals were captured and their sex was recorded. These data were not presented in Chapter 2 because our sample size was small (n=20). Males and females behaved very differently. Males tended to fly in large circles, stopping every 15 - 50 m to either investigate other butterflies or to feed on nectar.

Females moved more linearly. The would typically spend 5 - 10 minutes on vegetation ovipositing, then fly rapidly for 80 - 150 meters in a straight line before landing again.

Butterflies of both sexes that approached the meadow edge would either tum back or follow along the forest approximately 50 percent of the time (personal observation). Once P. clodius entered the forest, they would cease searching behavior and fly rapidly in a straight line. This is similar to the results seen by Ries (1998) at prairie edges. I think that landscape level dispersal of P. clodius is more restricted by edge permeability (Stamps et al. 1987) than by decreased movement within the surrounding forest. Furthermore, these behaviors correspond with dispersal patterns observed by Roland (2000) for Parnassius smintheus.

As noted by Koenig et al. (2000), all estimates of dispersal from marked animals are limited by study area size. Multiple correction and curve fitting techniques have been used to adjust for the "unknown tail" of dispersal distributions. Although these adjustments help, they are, in many ways, arbitrary. There is no way of knowing how far animals that leave the 56 study area truly go. I think that the key to determining true dispersal distances lies in combining mark-recapture techniques with radio-telemetry data and genetics research.

When examined over the entire 1999 flight period, P. clodius abundance was significantly correlated with percent cover of their hostplant, Dicentra uni.flora. However, this relationship did not hold during the peak of the flight period. At the peak of the flight period, nectar appears to be a more important resource. During 2000, no data on hostplant abundance could be collected and there was not a significant relationship between nectar abundance and P. clodius numbers during the peak of the flight period. During both 1999 and 2000, P. clodius were observed in more mesic adjacent habitats for over a week after leaving the drier study area where all flowers had senesced. The data show that hostplants were the most important resource to P. clodius during the 1999 flight season. However, changes in correlations at different times of the flight period suggest that nectar may determine spatial distribution of butterflies in the meadow during the emergence peak. The hostplant, D. uni.flora tends to be scattered throughout the meadow, whereas nectar seemed to have a more clumped distribution. Therefore, there may be little cost to P. clodius to centering their movements around nectar even if the hostplant is the most important resource to their fitness. Furthermore, personal observations suggest that need for nectar may force individuals to emigrate to more mesic habitats at the end of the flight period. As summarized by Sharp et al. (1974), "The problem of the influence of plant associations on butterfly distribution seems to be one of scale. The range of the animals, the distribution of particular plants important to them and the predictability of their environment all play a part in 57 determining what the pattern of habitat selection will be for each butterfly population". More research is needed on butterfly responses to nectar and hostplants for multiple species because the relationships between butterflies and their larval host plants and nectar sources is variable depending on time, resource configuration, sex, and species.

A thorough demographic analysis of mark-recapture data enabled us to test hypotheses and gain further insight into our data. Using Program Mark, we were able to detect temporal trends and differences between the sexes in survival, recapture, and movement transition probabilities. At times, these estimates were limited by our data.

However, sometimes even in data limited cases the same trends were repeated over all three years.

So, although not always statistically significant, our analyses gave insight into possible patterns and potential mechanisms.

Finally, although the absence of hostplants in the plot during 2000 was frustrating, it raises interesting questions on the dynamics between P. clodius and its hostpant, D. uniflora.

Long-term population "cycling" of abundance of P. clodius and D. uniflora could potentially be occurring and determining the distribution and abundance of both species. Alternatively or simultaneously, climatic factors may have profound annual effects on growth of D. uniflora and thereby affect population levels of P. clodius. 58

Literature Cited

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Brussard, P.F., Ehrlich, P.R., & Singer, M.C. (1974) Adult movements and population structure in Euphydryas editha. Evolution, 28, 408-415.

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Harrison, S. (1989) Long-distance dispersal and colonization in the bay checkerspot butterfly Euphydryas editha bayensis. Ecology 70 (5), 1236-1243.

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