Patterns of Natal Recruitment in the Atlantic Puffin (Fratercula arctica)

by

S. Erin Whidden

BSc. Biology, University of New Brunswick, 2005

A Thesis Submitted in Partial Fulfillment

of the Requirements for the Degree of

Master of Science

in the Graduate Academic Unit of Biology

Supervisor: Antony Diamond, Ph.D., Biology Department and Forestry and

Environmental Management

Examining Board: Dr. Les Cwynar, Ph.D. Biology Department, Chair

Dr. Stephen Heard, Ph.D., Biology Department

Dr. Heather Major, Ph.D., Biology Department at UNBSJ

This thesis is accepted by the

Dean of Graduate Studies

THE UNIVERSITY OF NEW BRUNSWICK

January, 2016

©S. Erin Whidden, 2016

ii

ABSTRACT

Seabirds exhibit considerable variation in demographic parameters within a typical K-

selected framework. Identification of the most sensitive of these parameters for

population change is crucial for successful management and conservation. When adult

survival is high and stable in seabird populations, bottom-up forces prevail and

reproductive success and subsequent recruitment of juveniles will govern population

dynamics. Recruitment is difficult to study, requiring large samples from throughout a

metapopulation. The Atlantic puffin (Fratercula arctica) colony on Machias Seal Island

is the largest in the Gulf of Maine population, and is ideally suited to explore recruitment

in this species since the entire metapopulation is monitored. I first assessed trends in

hatch-year parameters since the 1980s and studied whether hatch year conditions for

Atlantic puffins affected the probability of natal recruitment. Despite significant declines

in hatch-year parameters (wing growth, fledging body condition, quality food delivered

to chicks, fledge date), none had a statistically significant effect on the probability of

natal recruitment. The number of islands visited between fledging and recruiting was the

only parameter with a statistically significant effect on natal recruitment. Puffins are less

likely to recruit to their natal island the more islands they visit between fledging and

recruitment age. I conclude that conditions experienced between fledge and recruitment

may be more important in the process of natal recruitment than conditions experienced by

chicks on their natal colony. These findings highlight the importance of multi-year, multi-

site metapopulation-level studies when tracking changes in seabird dynamics.

iii

DEDICATION

To Iris. May you always be inspired to learn.

iv

ACKNOWLEDGEMENTS

I would like to thank my supervisor, Dr. Tony Diamond. Your seemingly infinite

patience and thoughtful advice helped me to regain direction and push forward so many

times. Thank you for this opportunity. Thanks also to my committee members, Drs.

Linley Jesson and Graham Forbes for your encouragement and constructive criticism.

The finished product is vastly improved thanks to you.

Thanks to my lab mates for your support and for many insightful conversations, ideas and

questions. And to a collaborator, Dr. Andre Breton, whose hours of hard work sadly did

not make it into the final draft. I am a better scientist for your efforts.

Finally, I would like to thank my family. Mum, Dad, Megan, Patrick, and Shannon. Your

love, support (in all ways possible), humour, and encouragement held me together

through all I faced as a student and in life. Thanks for listening, even when you had no

idea what I was going on about.

And to the puffins - thanks for always inspiring my curiosity.

v

Table of Contents

ABSTRACT ........................................................................................................................ ii

DEDICATION ................................................................................................................... iii

ACKNOWLEDGEMENTS ............................................................................................... iv

Table of Contents ................................................................................................................ v

List of Tables .................................................................................................................... vii

List of Figures .................................................................................................................. viii

Chapter 1 : Introduction ...................................................................................................... 1

Background ..................................................................................................................... 1

Hypotheses and Predictions ........................................................................................ 4

General Methods ............................................................................................................. 8

Species Account .......................................................................................................... 8

Study Area ................................................................................................................. 10

Objective and Chapter Summary ...............................................................................11

Chapter 2 : Trends in Chick Development on Machias Seal Island between 1980 and

2014................................................................................................................................... 13

Introduction ................................................................................................................... 13

Methods......................................................................................................................... 14

Field Protocol ............................................................................................................ 14

Statistical Analyses ................................................................................................... 16

Results ........................................................................................................................... 17

Chick Development .................................................................................................. 17

Food .......................................................................................................................... 18

vi

Breeding Success ...................................................................................................... 18

Timing of Fledge ....................................................................................................... 18

Discussion ..................................................................................................................... 19

Chapter 3 : Effects of hatch year conditions on natal recruitment in Atlantic Puffins

breeding on Machias Seal Island ...................................................................................... 30 Introduction ................................................................................................................... 30

Methods......................................................................................................................... 33

Data ........................................................................................................................... 33

Statistical Analyses ................................................................................................... 35

Results ........................................................................................................................... 37

Discussion ..................................................................................................................... 38

Chapter 4 : Synthesis ........................................................................................................ 55

Bibliography ..................................................................................................................... 59

Curriculum Vitae

vii

List of Tables

Table 2-1. Yearly sample sizes for parameters spanning from 1980 to 2014. .................. 23

Table 3-1. List and descriptions of parameters included in models. ............................... 42

Table 3-2. Count of how many birds were detected (survived) for each level of number of

islands visited. The proportion of birds that survived increases as more islands are

visited. ............................................................................................................................... 41

Table 3-3. Yearly means for parameters included in models. .......................................... 43

Table 3-4. Summary of results from generalised linear models with binomial response =

recruited to MSI (natal recruitment). Models were compared using Akaike's Information

Criterion (AICc). Number of parameters in the model (K), AICc, delta AICc (difference

between AICc of current and top model), AICc weight (a measure of support for each

model; values sum to 1) and cumulative AICc weight are reported. ................................ 44

Table 3-5. Model averaged estimates of parameter effects (with shrinkage). Weighted

averages of parameters present in top models (ΔAICc < 4). ........................................... 45

Table 3-6. Summary of results from generalised linear models with binomial response =

survived to recruitment age (1), was not detected at recruitment age (0). Models were

compared using Akaike's Information Criterion (AICc). AICc, delta AICc (difference

between AICc of current and top models), AICc weight (a measure of support for each

model; values sum to 1). K = number of parameters. ...................................................... 46

Table 3-7. Estimates of parameter effects (with shrinkage) for the only supported survival

model (ΔAICc < 4)............................................................................................................ 47

viii

List of Figures

Figure 1-1. Map showing locations of puffin breeding islands in the Bay of Fundy/Gulf

of Maine metapopulation. Islands in the inset represent monitored islands, while Bird

Island (BI), Pearl Island (PI), and the Tusket and Mud Island groups (TMG) represent

puffin breeding islands that are not monitored for banded birds. The size of each dot

roughly represents the relative sizes of the breeding populations on each island. ........... 12

Figure 2-1. Trends in Atlantic Puffin (Fratercula arctica) chick growth rates on Machias

Seal Island New Brunswick from 1997 to 2014. a. Mass growth rate (g/day) measured

during the linear growth phase (10-30 days old), showed no significant trend over time. b.

Wing Chord growth rate (mm/day), also measured during the linear growth phase ,

showed a slight negative trend over time. Shown with 95% confidence limits. .............. 24

Figure 2-2. Trends in Atlantic Puffin (Fratercula arctica) fledging condition on Machias

Seal Island, New Brunswck from 1980-2013. a. Declining trends in mass (blue

diamonds) and wing chord (red squares) over time. Shown with 95% confidence

intervals, linear formula and significance value; b. Declining trend in condition index

over time. Shown with 95% confidence limits. ................................................................ 25

Figure 2-3. Different food types (g per hour) fed to Atlantic Puffin (Fratercula arctica)

chicks on Machias Seal Island, New Brunswick from 1995 to 2014. Prey categorised as

"good" food (metamorphosed fish) and "poor" food (non-fish) from 1995 to 2014.

Butterfish have been included in "poor" food because its shape makes it difficult or

impossible for puffin chicks to ingest. .............................................................................. 26

ix

Figure 2-4. Breeding success of Atlantic Puffins (Fratercula arctica) on Machias Seal

Island, New Brunswick from 1995 to 2014. Breeding success ranged from 89% in 2012

to 25% in 2013. Shown with 95% confidence limits. ....................................................... 27

Figure 2-5. Trends in Atlantic Puffin (Fratercula arctica) fledge dates on Machias Seal

Island, New Brunswck from 1980-2013. a. Increasing trend in fledge date over time; b.

No trend in the difference in fledge date from the mean within a year over time. Shown

with 95% confidence intervals. ......................................................................................... 28

Figure 2-6. Correlation matrix of parameters. Pearson correlation coefficients calculated

for the relationships between each parameter. Values above 0.50 indicate strong

collinearity. ....................................................................................................................... 29

Figure 3-1. The cumulative percentage of puffins tagged as chicks that recruited per year

from ages 5 - 7 for each year cohort form 1997 to 2006. Recruitment by cohort ranges

from 0.12 of the 2004 cohort, to 0.46 of the 2001 cohort. Lines are terminated at age 7 so

that early cohorts (which have had more time to recruit) are not over-represented; overall,

96% of birds that ever recruit, have done so by age 7 (Figure 2). ................................... 48

Figure 3-2. Resightings of banded puffins showing the proportion of all resighted birds

that were seen at a given age. Most (96%) puffins that are resighted are seen by age 7. 49

Figure 3-3. Relationships between the probability of natal recruitment to Machias Seal

Island and variables present in top models from Table 3-3 (ΔAICc < 4). Shading

represents 95% confidence limits. "Rugs" on the top and bottom of each graph represent

the actual data where point on the top rug are observations with positive residuals and

those on the bottom are observations with negative residuals. Jitter was applied to

continuous variables (i,e, all but IV) to better visualise density of the data points. ......... 51

x

Figure 3-4. Model averaged effect sizes (95% confidence intervals) of predictors for natal

recruitment models. Parameter from models in Table 3-3 with ΔAICc < 4 were used for

averaging based on AICc weights..................................................................................... 52

Figure 3-5. Relationships between the probability of survival and variables present in top

models from Table 3-5 (ΔAICc < 4). Shading represents 95% confidence limits. "Rugs"

on the top and bottom of each graph represent the actual data where point on the top rug

are observations with positive residuals and those on the bottom are observations with

negative residuals. Jitter was applied to better visualise density of the data points. ........ 53

Figure 3-6. Model averaged effect sizes (95% confidence intervals) of predictors for

survival models. Parameter from models in Table 3-5 with ΔAICc < 4 were used for

averaging based on AICc weights..................................................................................... 54

Figure 3-7. Correlation matrix for predictors. Correlation coefficients for predictors

included in the model set. Size and colour of circles indicates strength of the relationship

and corresponds to the numbers on the bottom left portion of the figure. ........................ 50

1

Chapter 1 : Introduction

Background

Seabirds are widely acknowledged as potential indicators of the health of the

marine environment (Cairns 1987; Bost and Le Maho 1993; Barrett 2002; Diamond and

Devlin 2003; Boyd et al. 2006; Frederiksen et al. 2007; Iverson et al. 2007; Parsons et

al. 2008; Einoder 2009) depending entirely on the ocean for food and coming to land

only to raise their offspring. They are abundant throughout the globe in diverse marine

environments. Despite their abundance, Paleczny et al. (2015) report that seabirds have

declined by nearly 70% from 1950 to 2010. Croxall et al. 2012 report that seabirds as a

group are declining faster than any other group of birds and are under threat from human-

induced changes in their environment due mainly to the negative impacts of commercial

fisheries and pollution. Several recent studies have also shown that seabirds are affected

by climate (Springer et al. 2007, Frederiksen et. al 2013). In the North Atlantic in

particular, Frederiksen et al. (2013) report a strong positive correlation between the

presence of suitable habitat for a low trophic-level copepod (Calanus finmarchicus) and

long-term breeding success of several seabird species feeding at a higher trophic level.

This suggests a bottom-up effect on seabirds of a changing marine climate.

The life history characteristics of seabirds make the study of them particularly

useful as the proverbial "canary in the coal mine" of changing marine ecosystems.

Consistent with a K-selected strategy, seabirds are long-lived, show delayed reproductive

maturity, and have low annual fecundity (Weimerskirch 2002). However, there is

considerable variation within this framework (Russell 1999). Life expectancy ranges

2

from roughly five years to 35. Young seabirds typically delay breeding for between two

and five years and when they breed lay one to two eggs annually, or less often

(Weimerskirch 2002). These characteristics combined with the fact that seabirds spend

the vast majority of their time at sea, where they are very difficult to monitor can make

them a challenge to study, require data collection over long time scales with large sample

sizes. Such studies are few and far between due to these logistical, financial and

dedicative requirements.

Variation in population size is of particular interest in conservation ecology

because population change is crucial for successful management and conservation,

particularly when combined with knowledge of the effects and effect sizes affecting these

demographic processes (Croxall and Rothery 1990; Skalski et al. 2005). While, in

general, changes in adult survival have the greatest impact on population growth rate in

long-lived species such as seabirds (Russell 1999; Saether and Bakke 2000; Cooch et al.

2001), adult survival tends to be insensitive to environmental change relative to

parameters such as reproduction, juvenile survival, and natal recruitment (Lebreton and

Clobert 1991). Natal recruitment is defined as the return of an individual to its place of

birth to breed. If we understand how each of the latter population parameters contributes

to population change, and the major biological and environmental effects modulating

these parameters, we will be in a better position to isolate the principal factor(s)

responsible for population changes (Perrins 1991; Russell 1999).

Hanski and Gilpin (1997) define a metapopulation as a set of local populations in

an area of suitable habitat that are separated from other occupied patches by

fragmentation, or patches of unsuitable habitat. Local populations within a

3

metapopulation are connected through infrequent dispersal, and are subject to extinction

and reoccupation. During the breeding season seabird populations generally function on a

metapopulation scale, existing in patchy environments often consisting of discrete island

populations, or breeding colonies, connected through natal and/or breeding dispersal.

Although survival probabilities and reproductive parameters have been well studied in

some metapopulations, natal dispersal and recruitment represent a major gap in our

knowledge of metapopulation dynamics in seabirds, and are important parameters for

population change.

Researchers in the Atlantic Laboratory for Avian Research (ALAR) at the

University of New Brunswick have been monitoring seabird populations on Machias Seal

Island (MSI), a migratory bird sanctuary, since 1995. MSI is home to the largest breeding

population of Atlantic puffins (Fratercula arctica, hereafter ‘puffin’) south of

Newfoundland; over 6000 pairs reproduce on the island annually (Diamond, unpublished

data). The next largest breeding population in the Gulf of Maine is the restored colony on

Seal Island National Wildlife Refuge, Penobscot Bay (Kress and Jackson 2015); in recent

years, approximately 500 pairs have nested on the island (Harris and Wanless 2011).

The Machias Seal Island puffin population has remained relatively stable since

2000 but changes seem likely because the ecosystem is changing (Croxall et al. 2012).

The fragility of the system was noted when the common and Arctic tern (Sterna hirundo

and S. paradisaea, respectively) breeding colonies on MSI experienced a complete

collapse, even though they had appeared to be the most stable seabird populations in the

area (Diamond 2009, Gaston, et al. 2009). The Arctic tern colony in particular was the

largest in North America (Devlin 2006).

4

Given the recent decline and complete breeding failure of Arctic and common

terns, and our lack of understanding of the cause or causes, it seems reasonable to

conclude that the largest population of puffins in the Gulf of Maine, and the most

important for recruitment to other colonies in the metapopulation (Breton et al. 2005),

may also be susceptible to the same forces responsible for the breeding failure and

decline of the MSI terns (Diamond and Devlin 2003). Because adult survival is high and

stable for puffins in the Gulf of Maine (Breton et al. 2005) and recruitment has been

identified for this metapopulation as the likely factor responsible for differing colony

sizes (Breton 2005), it is important to consider recruitment as a key factor affecting

population dynamics (Harris et al. 2005).

Hypotheses and Predictions

Juveniles breeding for the first time must decide where to do so based on

information gathered prior to breeding. Some information about their natal colony is

undoubtedly obtained during their hatch year. In a review of research on recruitment in

seabirds, Becker and Bradley (2007) report that fledging mass and fledging date affected

recruitment probability in common terns (Sterna hirundo), Cory's shearwater

(Calonectris diomedea), and sooty terns (Sterna fuscata). Although several studies have

reported no effect of conditions on the breeding grounds on recruitment probability in

auks (Lloyd 1979, Hedgren 1981, Harris et al. 1992), these studies were performed on

species that continue to provision and care for their young well after fledging, such as

common murres and razorbills. Any effect that conditions at the natal colony have on

5

recruitment would be more easily detected if not confounded by the extension of those

effects beyond the colony.

Hypothesis 1: Juveniles are more likely to return to MSI to breed if they left the

island as fledgers in good condition.

Chick growth and ultimately size at fledging are affected by a number of factors

including food availability (Baillie and Jones 2004), food quality (Harris and Hislop

1978), and adult foraging ranges (Anker-Nilssen and Lorentsen 1990). In this way, chick

size at fledging reflects the foraging conditions at the time of breeding. Perrins et al.

(1973) showed that mass at fledging affected survival of immature manx shearwaters

(Puffinus puffinus). The same was not found to be true for puffins on the Isle of May

(Harris and Rothery 1985), however this study was relatively short (i.e., 5 years) and

sample sizes were small (fewer than 100 chicks banded per year). In addition, conditions

were near peak for the Isle of May colony at the time of the study, so selection for

dispersal was probably weak.

During chick growth, energy is not distributed equally in the body. Oyan and

Anker-Nilssen (1996) showed that growth of body mass in puffins was most affected by

quantity of food, because energy was preferentially assigned to maintain growth of the

wings and skull. In order to account for this discrepancy, I used an index of body

condition (mass divided by wing chord; Lewis et al. 2006, Cohen et al. 2014) that

represents condition of a chick at fledging better than mass or wing chord alone. If the

value is high (chick has a large mass in relation to its wing chord), then it is likely that

foraging conditions are good, while a low value (chick mass is low in relation to wing

6

chord) indicates that development of the wing has taken priority over body tissue

development and foraging conditions are likely not as good.

Prediction 1: Index of body condition at fledge is positively related to probability of natal

recruitment.

Hypothesis 2: Juveniles that fledge MSI earlier are more likely to return to MSI to

breed.

Presumably, puffins time their arrival at the breeding colony to correspond with a

reliable source of food for themselves and their young (Lack 1968). Changes in the

marine environment can affect timing of breeding in puffins (Durant et al. 2004, Stenseth

et al. 2002). Wanless et al. (2009) showed that over a 33-year period (1970s to 2000s)

puffins at the Isle of May, Scotland, have begun breeding later and later in the season,

due in part to changes in the ocean climate. In Norway, Durant et al. (2006) found that

the nestling period was affected by sea surface temperature and salinity in March, a

reflection of the feeding conditions later in the season when adults are feeding young.

When conditions were favourable (i.e., sea surface temperature and salinity were

favourable for development of prey) the nestling period for puffins was shorter and

chicks fledged earlier. Additionally, Ydenberg et al. (1995) showed that rhinoceros auklet

(Cerorhinca monocerata, a close relative of puffins) chicks that hatched later fledged

smaller. Overall, seabirds are thought to be more successful the earlier they nest, though

whether this results in better recruitment needs more investigation.

7

Prediction 2: Fledge date and the probability of natal recruitment will covary inversely.

Hypothesis 3: Natal recruitment of young Atlantic puffins to the breeding colony on

MSI is affected by the availability of high quality food during the chick growth

period

Yearling Atlantic herring (Clupea harengus) have historically been the primary

food for puffins on MSI (Breton and Diamond 2014). However, in recent years

availability of herring on MSI has been highly variable ranging from 80% to nearly 0%

of chick diet (A. W. Diamond, unpublished data). In years when herring were presumably

unavailable, adults brought alternative food such as hake (Urophycis spp.), sandlance

(Ammodytes sp.), butterfish (Peprilus triacanthus), larval fish, and euphausiids (krill) to

their chicks. While sandlance, herring and hake are considered relatively nutritious food,

butterfish, although also high in fat, are difficult for chicks to swallow due to their shape

(S. M. Kress, personal comm.), and larval fish and krill are low in calories (A.W.

Diamond, unpublished data).

Prediction 3: Amount of quality food in the diet of chicks is positively related to

probability of natal recruitment.

8

Hypothesis 4: Natal recruitment of young Atlantic puffins to the breeding colony on

MSI is affected by the average breeding success on MSI during their hatch-year.

Young puffins may use information obtained during their hatch-year about the

overall success of their breeding colony when deciding where to settle and breed

(Danchin et al. 1998).

Prediction 4: Mean breeding success in an individual's hatch-year is positively related to

probability of natal recruitment.

To assess these non-exclusive hypotheses, I used a model selection framework in

which the global model was an additive model, and all other models were versions of the

global model with one or more predictors excluded. Biologically relevant interactions

were included. Additionally, in order to provide an alternative to the hypothesis that

conditions during the hatch year drive natal recruitment in puffins, I included in my

analysis a parameter (number of islands visited) relating not to the hatch year, but to the

pre-breeding or "prospecting" period.

General Methods

Species Account

Species account taken, unless stated otherwise, from Lowther et al. 2002.

The puffin is a member of the Alcid family of seabirds (Order Charadriiformes).

They are stout birds: 310-550 g, 26-29 cm in length as adults and showing the typical

contrasting black upper and white lower colouration of diving seabirds. They have a

large, brightly coloured bill that grows larger and more colourful with age until breeding

9

age is reached at 5 years old (Harris and Wanless 2011). Sexes are visually identical,

although males may be slightly larger and heavier than females (Friars and Diamond

2011, Harris and Wanless 2011). Puffins can live upwards of 30 years. They live and

breed throughout the North Atlantic, spending the summer breeding season on small

offshore islands from 43o - 80

o north latitude and wintering at sea.

During the summer breeding season, mated pairs occupy an earthen or rock

burrow, often returning to the same burrow year after year (Hudson 1985). Females lay a

single egg and both parents incubate the egg for 36-45 days. Chicks are born semi-

precocial (mobile and downy, but remaining in the burrow to be fed) and are fed by both

parents until fledging (leaving the nest) at 38-44 days old. Chicks fledge at night and go

directly to the sea; at this point they are completely independent of their parents. Most

young remain at sea for their first year, returning to breeding colonies (but not breeding)

in their 2nd

, 3rd

, and 4th

years. Immature individuals may visit several breeding colonies

before settling in their 5th

year (Harris 1983, Breton et al. 2005). Emigration after this

time is rare (Harris and Wanless 1991; Breton et al. 2005).

Atlantic puffin global population estimates range from 3.8 – 8.212-14 million.

The vast majority breed in the eastern North Atlantic, specifically in Iceland, Great

Britain, and Norway (Harris and Wanless 2011). Most puffins in the western Atlantic

breed off the coast of Newfoundland and Labrador. However, there is a growing

metapopulation of puffins on managed islands in the Bay of Fundy/Gulf of Maine

(BOF/GOM) region, where Machias Seal Island, the source of data for this thesis, is

located. This region represents the southern-most population of puffins in the world.

10

Study Area

Individuals were captured and biological covariates recorded on MSI in the Bay

of Fundy. MSI (44o30' N, 67

o06' W; Fig. 3) is managed by the Canadian Wildlife Service

(CWS) as a Migratory Bird Sanctuary, and monitored cooperatively by CWS and ALAR.

It is located 19 km SE of Cutler, Maine and 19 km SW of Grand Manan, New

Brunswick, at the convergence of the Gulf of Maine and the Bay of Fundy. The small,

treeless, 9.5 ha island boasts a breeding population of puffins over 6000 pairs (Diamond,

unpublished data) - far fewer than the millions found in the colonies of Newfoundland

and the eastern Atlantic (Harris and Wanless 2011), but a significant number for the

region. MSI is composed mostly of exposed bedrock and boulders with grasses and other

non-woody plants covering the interior of the island.

Other species breeding on the island are razorbill (Alca torda), common murre

(Uria aalge), Leach's storm petrel (Oceanodroma leucorhoa), spotted sandpiper (Actitis

macularius), common eider (Somateria mollissima), savannah sparrow (Passerculus

sandwichensis), great black-backed gull (Larus marinus), and herring gull (L.

argentatus). Prior to 2006, a large breeding population of common and Arctic terns

(Sterna hirundo and S. paradisaea, respectively) was also present on the island.

In a study of recruitment using only data from Machias Seal Island, recruitment of

MSI-born puffins to other colonies, a process known as natal dispersal, would be

problematic as I would be unable to distinguish between death and dispersal. Fortunately,

five of the eight breeding colonies in the Gulf of Maine puffin metapopulation, and the

vast majority (~98%, Harris and Wanless 2011) of the breeding population, are

monitored by other researchers throughout each breeding season, providing data for

11

estimating natal dispersal. Specifically, resighting of banded puffins was conducted each

year not only on MSI, but also on Petit Manan, Seal Island, Matinicus Rock, and Eastern

Egg Rock (Figure 1-1). Resighting protocols are similar across all islands.

Objective and Chapter Summary

The main objective of my study was to determine whether factors experienced by

puffins during their hatch year on Machias Seal Island affect natal recruitment. In order

to determine which parameters to include in the analysis (detailed in chapter three), I first

explored trends and inter-annual variability in hatch-year conditions over a considerable

time (up to 33 years depending on the parameter) for parameters of interest in chapter

two. In chapter three I modeled recruitment as a function of several hatch-year and one

sub-adult parameter using a generalised linear model approach with model selection

based on AIC. The results provide valuable information about the juvenile phase of

puffin life-history in the Gulf of Maine/Bay of Fundy metapopulation, as reviewed in

Chapter 4.

12

Figure 1-1. Map showing locations of puffin breeding islands in the Bay of

Fundy/Gulf of Maine metapopulation. Islands in the inset represent monitored islands,

while Bird Island (BI), Pearl Island (PI), and the Tusket and Mud Island groups (TMG)

represent puffin breeding islands that are not monitored for banded birds. The size of

each dot roughly represents the relative sizes of the breeding populations on each island.

13

Chapter 2 : Trends in Chick Development on Machias Seal Island

between 1980 and 2014

Introduction

Systematic monitoring of seabirds breeding on MSI since the 1980's provides rare

insight into changes in populations over a considerable time-scale. Many questions about

the mechanisms driving observed changes arise from a simple view of population

characteristics over time. For puffins in particular, MSI is by far the largest breeding

colony in the Bay of Fundy/Gulf of Maine metapopulation, playing host to ~6000

breeding pairs of puffins during the summer season (A.W. Diamond, personal

communication). In comparison, (Matinicus) Seal Island (the next largest colony in the

metapopulation) hosts only an estimated 600 breeding pairs (Harris and Wanless 2011).

Thus, the importance of changes in the population ecology of MSI puffins, as a source of

recruits for the remaining islands in the metapopulation (MacArthur and Wilson 1967,

Clobert et al. 2004), cannot be underestimated.

Here I describe changes over 20 years in population parameters related to chick

development (hatch date, growth rate of chicks, mass at fledge, wing chord at fledge,

fledge date, fledge date relative to others within a year, fledge date relative to others

among years, breeding success) and some post-fledge parameters (number of islands

within the metapopulation visited before recruitment age, and recruitment/dispersal). In

particular, I am interested in detecting meaningful declining trends, if any, in these

parameters over time in order to determine whether puffins on MSI may be headed

towards a similar fate to the MSI terns. As the largest (by far) breeding colony in the

14

metapopulation, and the source for the majority of dispersed birds in the region, failure of

the MSI colony could be catastrophic for the metapopulation as a whole. In particular,

MSI is important as a source of "rescue" numbers to other colonies in the region that may

at times be unable to maintain their own numbers.

Methods

Field Protocol

Growth Rates and Breeding Success

To calculate daily growth rates for puffin chicks we monitored active burrows and

measured mass and wing chord twice or thrice during the linear growth period (age 10-30

days old). We determined breeding success for the same monitored burrows (n=26-84

burrows, depending on year) as the number of young fledged per egg laid. Burrows were

not included in growth or breeding success calculations if the fate of the egg or chick was

unknown. Chicks reaching 35d and not subsequently found dead were treated as fledged.

Food

The type and amount of prey fed to chicks was determined by conducting 3-hr

“feeding watches” throughout the chick-rearing period. Items carried in from the sea by

adults were identified by researchers concealed by blinds. Amount (by mass) was

determined based on the length of each item in relation to the length of the bill,

multiplied by mass per length as determined by length/mass regressions from collected

samples.

15

Food items were categorised as "good" or "poor" based on fat content of collected

samples. With one exception (Atlantic butterfish, Peprilus triacanthus), samples could be

easily categorised as good or poor based on their fat content. Good food included

metamorphosed, or non-larval (usually one year old or 1-group), fish species (herring,

hake, and sandlance), while poor or "junk" food included invertebrates and larval fish, as

their fat content is low in comparison to other food items delivered. I made an exception

to this categorisation in the case of butterfish (sp.), which have a high fat content, but

their laterally flattened shape makes them difficult or impossible for puffin chicks to

swallow (S. M. Kress, pers. comm.), I included them in the poor category.

Fledge Parameters and Resighting

Approximately 200-400 puffin chicks per year (approximately 5-10% of fledgers

based on an average breeding success of 0.60 chicks fledged per egg laid, and a

population of 6,000 breeding pairs) were captured at night on MSI as they were fledging

from their nest burrow. Chicks are easy to capture in this way because they are (for as yet

unknown reasons) attracted to the lighthouse at the centre of the island, and as such can

be easily seen and captured in numbers on the surrounding lawn. For each individual, we

recorded the date of capture (fledge date), mass (g), and wing chord (mm) and fitted two

uniquely engraved metal bands - one a USGS band (Bird Banding Laboratory, BBL), the

other a metal field-readable band (MFR). Numbers on these bands were used to identify

individuals in subsequent years.

16

I calculated an index of fledging body condition (CI) as fledge mass(g) / fledge

wing chord (mm). Chicks with a relatively low CI were light with long wings at fledging,

whereas those with relatively high CI were heavier with shorter wings at fledging.

Although we have data spanning 1980 to 2014, we do not have all data for all

years. No data were recorded in 1981-1983. In addition, data for food fed to chicks were

available only for chicks born between 1995 and 2014, as these data were not collected

prior to 1995. Parameters of interest are presented in Table 2-1 with their corresponding

sample sizes.

Statistical Analyses

I performed simple linear regressions for continuous response variables and

logistic regressions for binomial response variables modeled as a function of year in R

version 3.1.1 (R Core Team, 2014) to examine whether fledge parameters declined over

time. In an effort to include all data for all years, separate regressions were performed

rather than a multiple regression where some data would be lost. For simplicity, linear

relationships were assumed for all regressions except breeding success (which is a

binomial parameter) in which a logistic relationship was used. The assumption of

linearity was tested by examining residuals versus predicted values plots in which the

points should be symmetrically distributed around a horizontal line. I created a

correlation matrix with corresponding correlation coefficients (values above 0.50 signify

strong collinearity) to assess the possibility of correlation between predictors. Results of

the correlation matrix are presented with correlation coefficients and regressions are

presented with their slope, correlation coefficient (or 1-residual deviance/null deviance;

17

an analogous estimate to r2 for logistic regression) and significance value (H0: slope = 0;

alpha = 0.05).

Because field protocols differed before and after 1995, I looked at trends from

both 1980 on and 1995 on to determine if there would be a difference in results. In

particular, I was concerned that earlier dates of departure of researchers from MSI prior

to 1995 might skew the data toward earlier fledge dates and lower fledge mass and wing

chord values. However, neither r2

values nor significance (and therefore interpretation)

differed between the two datasets and so the full dataset from 1980 and after is presented

here.

Results

Chick Development

There was no significant trend in chick mass growth rates (mass; Figure 2-1a.;

slope = 0.00, r2 = 0.00, p=0.94), while rate of growth in the length of the wing (wing

chord) declined slightly from 1997 to 2014 (Figure 2-1b.; slope = -0.03, r2=0.03,

p<0.001). Both mass at fledge and wing chord at fledge declined slightly over time

(Figure 2-2a.; slope = -1.11, r2=0.07, p<0.001, Figure 2-2a.; slope = -0.24, r

2=0.08,

p<0.001 respectively). Furthermore, when we combined the two parameters as a single

index of fledging condition (mass/wing chord), the same slight negative trend over time

was seen (Figure 2-2b.; slope = -0.005, r2=0.02, p<0.001). However, more interesting is

the high degree of variation from year to year, particularly in wing chord (from a high of

152mm in 1984 to a low of 129mm in 2013) and condition index (high of 2.23 in 2007

and low of 1.73 in 2013).

18

Food

Prior to 2004, the majority of food delivered to puffin chicks on MSI could

consistently be categorised as good quality based on high fat content. This proportion (by

mass calculated using length estimates and known mass per length values) varies from

59% in 2004 to nearly 100% in many other years. However, there has been a significant

decline in the amount (in grams per hour) of good food, and in fact total amount of food,

fed to MSI puffin chicks (Figure 2-3; slope = -2.68, r2

= 0.04, p < 0.001). This decline in

good food was not accompanied by an increase in poor ("junk") food fed to chicks

(Figure 2-3; slope = 0.07, r2=0.00, p=0.31). Notable however, is that very little junk food

(<4% of total food) was detected prior to 2002, while values in subsequent years were as

high as 41% of total food.

Breeding Success

During 1995 - 2014 breeding success, a combined measure of hatching success

and fledging success, measured as the number of chicks fledged per egg laid, ranged from

an overall high of 0.89 in 2012 to an overall low of 0.25 the very next year, 2013. Overall

there was a very slight but statistically significant positive trend over time (Figure 2-42-4;

slope = 0.005, p=0.05).

Timing of Fledge

During 1981 - 2013 chick fledging dates ranged from 6 July to 24 August, with

the mean fledge date occurring nearly a month later in 2013 (16 August; 15 Aug - 17

Aug, 95% CI) than in 1981 (26 July; 23 Jul - 29 Jul, 95% CI). Chicks are fledging later

over time (Figure 2-5; slope = 0.40, r2

= 0.15, p < 0.001).

19

Results of the correlation matrix are shown in Figure 2-6. Condition index and

fledge date had a Pearson correlation coefficient above 0.50 (r = 0.60). All other values

were 0.50 or less.

Discussion

Parameters relating to fledging conditions for puffin chicks on MSI show a high

degree of variation from year to year with a generally, but weakly, declining trend over

time. In a study on tufted puffins (Fratercula cirrhata) breeding on Triangle Island, B.C.

(another species for which independence begins upon fledging) Morrison et al. (2009)

found that survival of juveniles depended strongly on wing length at fledge and weakly

on mass and date at fledge. The same may be true for puffins on this side of the continent

where negative trends in several fledgling characteristics (fledging mass, wing chord,

fledge date, quality food) may be concerning. After nine years, researchers are still trying

to understand the reasons for the failure of the tern colonies on MSI. No signs of decline

were detected prior to that failure, and such changes may be more subtle than one would

expect given the consequences.

Food availability during the summer breeding season is affected by oceanic

conditions in the spring when fish species rely on the phytoplankton bloom for

development. Durant et al. (2006) reported that high salinity and low sea surface

temperatures in March in the Barents Sea resulted in a longer fledgling period for puffins

several months later. Major changes in food brought back to the colony by adults and fed

to several species of seabird chicks on MSI and other breeding islands in the western

Atlantic have been documented in recent years (Gaston et al. 2009, Breton & Diamond

20

2014, A.W. Diamond unpublished data). Similar changes have been documented across

the breeding range of puffins (Martin 1989, Barrett 2002, Baillie and Jones 2003, 2004,

Regher and Rodway 1999). Prior to 2001, <1 year old Atlantic herring (Clupea

harengus), a high-fat and energy-rich fish, were the major food source for most species

on MSI. Since that time, sandlance (Ammodytes sp.), hake (Merluccius sp.), larval fish,

and euphausiid shrimp (Meganyctiphanes norvegicus) have become more common in the

diet than herring. Abandonment of the tern colonies on MSI coincided with a switch from

herring as the dominant food source to larval fish and euphausiids, followed by declining

reproductive success, an increase in predation by gulls and finally complete abandonment

in the span of 2 years (Gaston et al. 2009, Diamond 2009). We are seeing the same shift

away from herring as the main prey fed to puffin chicks (Breton and Diamond 2014). In

addition, adults do not seem to be compensating for lack of quality by increasing their

rate or quantity of feeding. In fact, the opposite trend appears in the data with a decline in

the total amount of food brought in. On a positive note however, we do not see the same

decline in breeding success for puffins as preceded the tern collapse. In addition, Baillie

and Jones (2003) reported that puffins breeding on islands in Newfoundland and

Labrador with low abundance of their main food source (capelin Mallotus villosus) were

able to maintain breeding parameters similar to those experienced by breeders on islands

where Capelin were abundant by switching to other prey species. They concluded that

puffins in that region were resilient to large-scale changes in prey abundance.

In colonial seabirds, reproductive synchrony (how temporally closely

reproduction occurs between individuals) is crucial to reproductive success (Wittenberger

and Hunt 1985). In particular, timing of fledging is important where chicks that fledge at

21

an optimal time will have access to abundant seasonal food resources and better oceanic

weather conditions. If chicks fledge sooner or later than usual, match-up with beneficial

oceanographic conditions may not be optimal. In good years, this is likely a bigger

problem for chicks traveling with adults than for species independent at fledging (such as

puffins) who are capable of traveling greater distances for food. But in poor years when

fledgers may leave the colony in less than optimal condition, survival, challenging for

juveniles during the best of times, could be compromised.

Morrison et al. (2009) report that survival of juvenile tufted puffins was related to

wing length at fledge and to a lesser degree mass and date at fledge. A delay of nearly

one month, as has been documented here for puffins on MSI, could drastically affect their

ability to find food and survive at sea, especially in years when chicks may be fledging in

poor condition. Wanless et al. (2009) report a similar trend towards later fledge dates of

puffins breeding in the North Sea. Barrett and Rikardsen (1992) and Diamond and

Nettleship (1989) showed that later fledging dates in the Barents Sea and Northwestern

Atlantic respectively were a result of prolonged food stress.

In general, although some puffin pre-fledge characteristics on MSI remain stable

(mass growth rate, breeding success, synchrony within years), others show negative

trends (feeding and body condition) and may warrant concern. In particular changes in

food and apparent inability of adults to compensate by increasing feeding rate may be

causing puffins to fledge later and in poorer condition than is optimal. If this were the

case, we would expect to see an accompanying decline in growth rates, contrary to my

results. We may have missed seeing these effects by measuring growth rate only during

the linear growth phase (between 10 and 30 days post hatch); much growth happens after

22

this age, and in particular our method would not detect whether or not chick mass reaches

a peak and then declines before fledging, as well-fed puffin chicks often do (A.W.

Diamond, pers. comm.). If these trends continue, and a decline in breeding success

develops, puffins on MSI may be heading for the same fate as their tern neighbours.

Although the overall trends in parameters relating to pre-fledging and fledging

conditions are significant, the time trend accounts for very little of the variation in these

parameters (r2 = 2 -8%). Valuable insight would undoubtedly be gained by determining

what other forces contribute to this high degree of variation. Possibilities for further

research include the effects of oceanic conditions prior to the breeding season, and

parental quality.

23

Table 2-1. Yearly sample sizes for parameters spanning from 1980 to 2014.

Year

Mass at Fledge,

Wing Chord at

Fledge, Fledge

Date

Mass Growth

Rate, Wing Chord

Growth Rate

Breeding

Success

Feeding

Watches

1980 71

1981 25

1982 57

1983 68

1984 69

1985

1986

1987

1988 117

1989 134

1990 192

1991 152

1992 102

1993 17

1994 124

1995 267 26 25

1996 274 54 21

1997 264 16 64 10

1998 264 17 54 11

1999 267 18 84 14

2000 202 23 69 27

2001 150 18 75 22

2002 490 36 81 23

2003 394 40 74 21

2004 344 43 59 28

2005 158 34 49 49

2006 235 21 72 62

2007 255 36 71 28

2008 305 62 74 37

2009 86 64 82 40

2010 136 41 57 44

2011 169 53 63 52

2012 202 33 53 47

2013 103 39 68 53

2014 41 50 42

24

Figure 2-1. Trends in Atlantic puffin (Fratercula arctica) chick growth rates on

Machias Seal Island New Brunswick from 1997 to 2014. a. Mass growth rate (g/day)

measured during the linear growth phase (10-30 days old), showed no significant trend

over time. MGR = -0.005*YR +16.34. p = 0.94, R2 = -0.002. b. Wing Chord growth rate

(mm/day), measured during the linear growth phase, showed a slight negative trend over

time. WGR = -0.03*YR + 59.79. p < 0.001, R2 = 0.03. Data shown as means with 95%

confidence limits.

25

Figure 2-2. Trends in Atlantic puffin (Fratercula arctica) fledging condition on

Machias Seal Island, New Brunswick from 1980-2013. a. Declining trend in mass

(blue diamonds; M = -1.11*YR + 2515.92, p < 0.001, R2 = 0.07) and wing chord (red

squares; W = -0.244*YR + 630.91, p < 0.001, R2 = 0.08) over time; b. declining trend in

condition index (mass/wing chord) over time. CI = -0.005*YR + 11.42, p < 0.001, R2 =

0.02. Shown with 95% confidence intervals.

26

Figure 2-3. Food fed to Atlantic puffin (Fratercula arctica) chicks on Machias Seal

Island, New Brunswick from 1995 to 2014. Prey categorised as "good" food

(metamorphosed fish; GF = -7.03*YR + 14233.20, p < 0.001, R2 = 0.04) and "poor" food

(non-fish; PF = 0.21*YR - 29.18, p = 0.31, R2 = 0.000) from 1995 to 2014. Butterfish

have been included in "poor" food because its shape makes it difficult or impossible for

puffin chicks to ingest.

27

Figure 2-4. Breeding success of Atlantic puffins (Fratercula arctica) on Machias Seal

Island, New Brunswick from 1995 to 2014. Significant positive trend in breeding

success over time. Breeding success ranged from 89% in 2012 to 25% in 2013. Data

shown as means with 95% confidence limits (Wilson Score Interval). BS = 0.005*YR -

9.30, p = 0.04, R2 = 0.002.

28

Figure 2-5. Trends in Atlantic puffin (Fratercula arctica) fledge dates on Machias

Seal Island, New Brunswick from 1980-2013. Increasing trend in fledge date over

time; shown with 95% confidence intervals. FD = 0.40*YR - 698.53, p < 0.001, R2 =

0.13.

29

Figure 2-6. Correlation matrix of parameters. Pearson correlation coefficients

calculated for relationships between parameters (FD = fledge date (days since 1 May), CI

= condition index (mass/wing chord), BS = breeding success (chicks fledged per egg),

MGR = mass growth (grams per day), WGR = wing chord growth (mm per day), GF =

good food (grams per hour), PF = poor food (grams per hour)). Values above 0.50

indicate strong collinearity. Size of the circle and colour indicate degree of correlation.

30

Chapter 3 : Effects of hatch year conditions on natal recruitment in

Atlantic puffins breeding on Machias Seal Island

Introduction

Recruitment of individuals into the breeding population is a complex process in

seabirds. For these long-lived species where reproductive maturity is often delayed this

process can occur over several years. Danchin et al. (1991) described recruitment in long-

lived birds as a 3-stage process whereby young that have fledged the nest must 1) survive

to recruitment age; 2) choose a breeding location; and 3) become a breeder. It is often

difficult or impossible to tease apart these three stages, as most studies focus on a single

breeding colony and therefore cannot distinguish between natal dispersal and mortality.

Through a partnership between ALAR and several other organizations monitoring

seabirds in the Gulf of Maine, resighting data are available from all relevant breeding

colonies in the metapopulation (islands with more than a few pairs of breeding puffins).

With these data, it is possible to target stage 2 only in order to determine factors

influencing whether an immature puffin returns to the same colony (natal recruitment), or

settles in a different colony (natal dispersal) for breeding.

Recruitment generally involves dispersal from the natal site to varying extents

(Duncan and Monaghan 1977). Relatively few studies (e.g., Pradel et al. 1997, Crespin et

al. 2006, Votier et al. 2008, Aubry et al. 2009) have attempted to determine what factors,

be they environmental, ecological, behavioural, or physiological, may be driving natal

recruitment in seabirds. The paucity of studies is due, in part, to the difficulty of

obtaining enough data over sufficient time to measure the process. In chapter one I

31

outlined the importance of natal recruitment in understanding seabird population

dynamics, especially when adult survival is stable and thus relatively insensitive to

changes in environmental conditions (Lebreton and Pradel 2002). In populations

conforming to a metapopulation framework the processes of recruitment and dispersal

among patches can lead to local extinctions and "rescue effects" (in which dispersal to

small patches can "rescue" that patch from extinction; Hanski & Gilpin 1997). If we

understand the major biological and environmental effects modulating these processes,

we will be in a better position to isolate the principal factor(s) responsible for such

population changes (Perrins 1991, Russell 1999).

Although puffins have been studied extensively, especially in the European parts

of their breeding range, little is known about the process of recruitment. Both Harris et al.

(2005) and Breton et al. (2005) found that adult survival was similar among colonies of

puffins showing marked differences in patterns of population change. Both concluded

that recruitment must be underlying the observed patterns. Of the few estimates of natal

recruitment that have been published (Harris and Wanless 1991; Finney et al. 2003;

Breton et al. 2006a; Sandvik et al. 2008) most report considerable inter-annual variability

(e.g., ranging from 6.4% to 30.1% of the fledging cohort on the Isle of May, Scotland;

(Harris & Wanless 1991; but see Sandvik et al. 2008), but few of these studies attempted

to identify effects responsible for the observed dynamics. Notable exceptions include

Finney et al. (2003) who showed that 21% of variation in puffin recruitment was

explained by nesting density of coexisting gulls, and Breton et al. (2006a) who showed

that colony size affected natal dispersal (and conversely natal recruitment). Data from

MSI also show a substantial inter-annual variability in recruitment (Figure 3-1) Only

32

resightings of birds up to age seven were included here and in subsequent analyses (i.e.

resightings of birds age 8 and older are omitted) because 96% of all birds resighted have

been seen by age seven (Figure 3-2).

Puffins on MSI present an ideal scenario for studying the process of natal

recruitment in seabirds. Each breeding pair raises a single chick, reducing the need for

determining compensatory or confounding effects of siblings. After 38-44 days (Lowther

et al. 2002) the chick, at about two-thirds of adult mass but completely independent of its

parents, moves from the nest burrow to the sea (a process known as "fledging") where it

will remain for 1 to 3 years before returning to land for the first time. Several hundred

chicks are captured and banded each year on MSI as they transition from their burrows to

the sea. Returning birds are identified in subsequent years by their unique band numbers.

Consequently, 73% of the >8,000 puffins banded on MSI since 1995 are of known age.

Ideally, recruitment and survival should be estimated simultaneously because the

process of recruitment is dependent upon survival. However, data for this project were

too sparse for the rigorous and complex statistical analyses required to do so. The process

of survival is unavoidably linked to recruitment, thus I controlled for survival in my

analysis by assigning a binomial response that included only those individuals known to

have survived to recruitment age. In an attempt to tease apart this issue, I analysed a

similar set of models but with return rate as the binomial response. Return rate is the

product of true survival and recapture rate and as such will underestimate true survival.

For convenience, I refer to return rate as survival. I did not include number of islands

visited as a predictor in the survival models because the number of islands visited

33

increases with survival because those that do not survive cannot be observed on

additional islands. Most juvenile mortality occurs in the first two years (Harris and

Wanless 2011) and as such, birds with survival equal to zero (were not detected at

recruitment age) will almost always have number of islands visited equal to one, and

sometimes two (Table 3-1). I would expect that parameters found to be good predictors

for the recruitment models would also be good predictors in the survival models.

However, a parameter with a stronger effect in the survival models may contribute more

to the survival process than to the recruitment process.

Methods

See chapter one for description of study area and species account.

Data

Fledge Parameters and Resighting

Puffin chicks were captured at night as they were fledging. For each individual (n

= 3,142 fledglings from 1997 to 2013), we recorded the date of capture (fledge date,

"FD"; recorded as days since 1 May), mass (g), and wing chord (mm). I calculated an

index of fledging body condition, "CI", as fledge mass (g) / fledge wing chord (mm).

Chicks with a relatively low CI were light with long wings at fledging, whereas those

with relatively high CI were heavier with shorter wings at fledging. Although data exist

over a longer time period for fledge parameters, in order to minimise resighting-related

heterogeneity in the response variable due to varying resighting rates of different band

34

types (Breton et al. 2006b), I chose to use data only from individuals banded with metal

field readable bands (1997-2006).

Bands were resighted each year on all five puffin breeding islands in the

BOF/GOM metapopulation using spotting scopes and binoculars between mid-May and

mid-August by researchers concealed in blinds. Resighting was conducted consistently

throughout the breeding season in order to ensure all age-classes were represented.

An individual was considered "recruited" when it was observed on one of the

study islands during the breeding season between the ages of 5 and 7. Breton et al. 2006a

reported the probability of moving between islands to be around 2% for 5 year old

puffins in the Gulf of Maine, getting less likely with age. Birds observed on MSI were

assigned a "1" and those observed elsewhere were assigned a "0", producing the binomial

response variable used for analyses (natal recruitment vs natal dispersal; Table 3-2).

Individuals that were not observed between ages five and seven were not included in

natal recruitment analyses. This likely provides an underestimate of true recruitment as it

does not account for resighting rates that are less than one, nor does it include birds

recruiting at older ages (but see Figure 3-2). Resighting rates for birds between the ages

of three and five on MSI and on other islands are approximately 0.40 and 0.73,

respectively (20 year average from 1983 to 2003; Breton 2006a). MSI has lower

resighting rates due to the larger number of birds compared with other islands in the

metapopulation. The number of islands visited by an individual from age one to

recruitment age, "IV", was recorded based on resightings from all islands.

Breeding success, "BS", was determined for monitored burrows on MSI as the

mean number of young fledged per egg laid per year. Burrows were not included if the

35

fate of the egg or chick was unknown. Chicks reaching 35d and not subsequently found

dead were treated as fledged.

Food

The type and amount of prey fed to chicks was determined by conducting three-

hour “feeding watches” throughout the chick-rearing period (n = 568 feeding watches

from 1997 to 2013). Three sample plots were monitored each year and items carried in

from the sea by adults were identified by researchers concealed by blinds. Hourly amount

(by mass) for each three-hour stint was determined for common prey types based on the

length of each item in relation to the length of the bill multiplied by mass per length.

Mass per length was determined by length/mass regressions from collected samples

(A.W. Diamond, unpublished data).

As a clear division can be made, food items were categorised as "good" or "poor"

based on fat content of collected samples. My measure of good food, "GF", included

metamorphosed (or non-larval) fish species (herring, hake, and sandlance), while poor

food (or "junk-food", Romano et al. 2006) included invertebrates, butterfish, and larval

fish.

Statistical Analyses

All analyses were conducted in R v. 3.1.2 (R Core Team 2014). Response

variables natal recruitment and survival were recorded as binomial variables (1 =

recruited to MSI, 0 = dispersed, N=898; and 1 = detected at recruitment age, 0 = was not

detected at recruitment age, N=3,143, respectively) and was modeled using a generalised

linear model (family = binomial, link function = logit) approach. I tested fit of the global

36

(fully additive) model with the logit, probit, and cloglog link functions. Fit was best using

the logit link function and so this was applied to all nested models. Response was

modeled as a function of time (year), five parameters relating to conditions during an

individual's hatch year (body condition (unique to individual), fledge date (unique to

individual), mean breeding success, mean proportion of good food delivered by adults; all

continuous variables), and one parameter relating to behaviour between hatch year and

recruitment (number of islands visited; a categorical variable unique to individual; Table

3-1). In addition, three biologically relevant interaction terms were included: condition

index × proportion of × good food delivered, condition index × fledge date, and fledge

date × proportion of × good food delivered.

Ideally, I would have also included several parameters relating to the juvenile

period (the time between fledging and recruitment). However, detailed data were not

available on conditions at colonies other than MSI during the study period.

Parameters were centered and scaled around a mean of zero and standard

deviation of one. Competing models were compared using Akaike's Information Criterion

(AIC). Weighted averages (weighted by AICc weights) were calculated for parameter

estimates using models with ΔAICc less than four, and are reported with their standard

error and significance (H0: slope = 0, alpha = 0.05). I employed the 'shrinkage' method of

calculating model averaged estimates (Burnham and Anderson 2002) in order to reduce

model selection bias. The shrinkage correction provides more conservative variance

estimates by including a zero parameter estimate in models where the parameter being

estimated is not present (as opposed to dropping the model) resulting in more

conservative variance estimates.

37

In order to avoid difficulties in interpreting models, I tested for collinearity of

predictors using a correlation matrix. Correlation coefficients were 0.50 or less for all

predictors indicating no strong collinearity. In addition, changing the order of predictors

in the models had no effect on results.

I assessed model fit by visual inspection of modeled relationships created with R

package visreg (Breheny and Burchett 2013). Visually, I assessed model fit as "good" if

there was no obvious pattern in the residuals, no clear changes in variance or obvious

outliers.

Results

I detected no strong collinearity between predictors (all correlation coefficients ≤

0.50; Figure 3-3). Visual inspection of regression plots on the logit scale showed

reasonable model fit, with some evidence of skewness for good food and number of

islands visited. However, the skewness was mild and logistic regression is robust to

variation in distribution of the predictors.

Of the 28% of banded individuals that were detected at recruitment age, 86%

(84.4% - 88.9%, 95% CI) recruited to MSI, their natal colony. Values ranged from 75%

of the 2001 cohort to 94% of the 1998 cohort (Table 3-3). There was not strong support

for any single model in the analysis, with many models having essentially equal support.

The top supported models (ΔAICc < 4) collectively included all predictors (Table 3-4).

Number of islands visited appeared in all top models.

The number of islands visited had a negative effect on the probability of natal

recruitment (Table 3-5). A juvenile puffin that visits two islands before recruitment age is

38

89% (83% - 92%, 95% CI) less likely to recruit to MSI than one that visited only one

island. The relationship between recruitment and number of islands visited at the five

island level (n = 2) was not significant with confidence intervals incorporating the

possibility of no effect (Figure 3-4, Figure 3-5). However, removing these data points did

not change the results qualitatively.

The single top model (ΔAICc < 4) in the survival model set included the

predictors good food and year (Table 3-6). For each unit increase in good food, puffins

are 48% (32% - 66%, 95% CI; Table 3-7, Figure 3-6) more likely to be detected at

recruitment age while for each unit increase in year, puffins are 18% (7% - 31%, 95% CI;

Table 3-7, Figure 3-6) more likely be detected. These relationships are depicted visually

in Figure 3-6.

Discussion

In contrast to my predictions but similar to other auks (Lloyd 1979, Hedgren

1981, Harris et al. 1992), I found that hatch year conditions for chicks on the natal colony

did not have a strong effect on the probability of natal recruitment in puffins. While hatch

year parameters were present in models with ΔAICc < 4, support for the effects was not

strong, as the effect sizes bounded zero (on the log-odds scale) for all parameters.

The number of islands visited (a parameter relating to the juvenile period) was the

only parameter with a statistically significant effect on natal recruitment in my models.

Intuitively, this is not a surprising result; the more islands a bird visits, the more likely

they are to settle on one of them, rather than their natal island. What is surprising is that

39

this has not yet been reported for puffins. Likely, this is due to a lack of resighting effort

and subsequent data.

One possible reason for the support of hatch year parameters in the models is that,

instead of affecting recruitment rates, they may have an effect on the number of islands

visited. However, in a preliminary look at simple correlations between predictors I

detected no strong correlations between islands visited and any other predictor. A path

analysis could provide better insight into these relationships and allow for a deeper

understanding of how each contribute to the probability of natal recruitment. Another

plausible explanation is that these predictors are actually affecting the survival process,

rather than the natal recruitment process. The survival models provided some evidence to

suggest that the effect of food may be attributable to the carryover affect of survival in

the recruitment models.

Based on these results I suggest that either (a) destination colony may be more

important than colony of origin in the natal recruitment/dispersal process for puffins;

and/or (b) conditions experienced by puffins during the juvenile phase may be more

important than those experienced during hatch year in the natal recruitment process.

Although several studies have reported that the location an individual breeds depends on

factors relating to the destination colony such as colony size (Breton et al. 2006a,

Coulson and Coulson 2008) and density (Gauthier et al. 2010), to my knowledge no

previous study has reported an effect of the extent of prospecting (number of islands

visited) on natal recruitment probability in seabirds. This novel finding is the direct result

of ongoing examination of long-term data and collaborations between researchers on all

islands in the region's puffin metapopulation. Without resighting taking place on all

40

possible breeding islands and data sharing, these results would not have been possible.

This is an important finding, as it suggests that conditions on potential breeding islands

during the prospecting period, rather than conditions on the natal colony during the hatch

year, play an important role in the process of natal recruitment and dispersal for puffins.

A worthwhile future endeavor would be to study the effect of conditions at potential

breeding islands during the prospecting period on natal recruitment probability. Such a

study should yield interesting results and is within the scope of current research being

conducted on the islands by ALAR and others.

My findings highlight the importance of long-term studies of seabirds at the

metapopulation level. Studies of seabirds that focus on a single colony treated as a closed

population ignore two major characteristics of metapopulation dynamics: movement and

dispersal. Puffins in the GOM/BOF are a good example of a metapopulation with discrete

local breeding populations (colonies) where movement between colonies is common and

mitigates the effects of stochasticity at the local level. Modeling population parameters

using data from a single colony in isolation would surely be inaccurate.

41

Table 3-1. Count of number of birds that were detected (survived) by number of

islands visited. The proportion of birds that survived increases as more islands are

visited.

Number of

Islands VisitedSurvived Did Not Survive

1 685 2087

2 151 136

3 53 20

4 7 1

5 2 0

42

Table 3-2. List and description of parameters included in statistical models

describing natal recruitment at Machias Seal Island during 1997 – 2014.

Parameter Code Units Description

Natal Recruitment RE0 = Dispersed

1 = RecruitedRecruited to/Dispersed from MSI

Return Rate (Survival) SU0 = Did not Survive

1 = SurvivedSurvived/Did Not Survive to Recruitment Age

Condition Index CI g/mm fledge mass (g) / fledge wing chord (mm)

Fledge Date FD days fledge date as the number of days since 1 May

Breeding Success BSchicks fledged per

egg laidmean breeding success in an individual's hatch year

Good Food GF g/hourmean hourly amount of herring, hake, and sandlance delivered

to sample plots in an individual's hatch year

Islands Visited IV number of Islandsnumber of islands visited by an individual between fledging and

recruitment

Year YR Year an individual's hatch year

43

Table 3-3. Yearly means from 1997 - 2006 for parameters included in natal

recruitment models.

YearNatal

Recruitment

Condition

Index

Fledge

Date

Number of

Islands

Visited

Breeding

Success

Proportion of

Good Food

1997 0.89 2.14 89.06 1.16 0.61 1.00

1998 0.94 2.17 87.69 1.08 0.65 0.99

1999 0.89 2.11 90.87 1.38 0.60 1.00

2000 0.79 1.91 98.28 1.40 0.48 0.97

2001 0.75 2.16 93.25 1.46 0.71 1.00

2002 0.92 2.02 92.21 1.23 0.59 0.88

2003 0.89 2.15 94.01 1.42 0.67 0.97

2004 0.87 1.87 105.48 1.30 0.76 0.60

2005 0.82 1.97 103.37 1.33 0.82 0.61

2006 0.84 2.07 96.59 1.30 0.35 0.85

44

Table 3-4. Summary of results from generalised linear models with binomial

response recruited to MSI (natal recruitment). Models were compared using Akaike's

Information Criterion (AICc). Number of parameters in the model (K), AICc, ΔAICc

(difference between AICc of current and top model), AICc weight (a measure of support

for each model; values sum to 1) and cumulative AICc weight are reported. Parameters as

in Table 3-1. AICc was 598.27 for the top model.

Model K ΔAICc AICc Wt. Model K ΔAICc AICc Wt.

IV 5 0.00 0.17 IV_GFCI_FD 9 6.48 0.01IV_FDGF 8 1.03 0.10 IV_BS_GFCI 9 6.63 0.01

IV_BS_FDGF 9 1.24 0.09 Null 1 109.97 0.00FD_IV 6 1.30 0.09 FD 2 110.03 0.00IV_GF 6 1.72 0.07 YR 2 110.72 0.00CI_IV 6 1.76 0.07 FDGF 4 110.75 0.00IV_BS 6 1.99 0.06 CIFD 4 111.57 0.00IV_YR 6 2.00 0.06 CI 2 111.66 0.00

IV_FDGF_CI 9 2.84 0.04 FD_YR 3 111.70 0.00IV_YR_FD 7 3.30 0.03 GF 2 111.84 0.00IV_GF_FD 7 3.31 0.03 FD_GF 3 111.88 0.00IV_GF_CI 7 3.58 0.03 BS 2 111.97 0.00IV_GF_BS 7 3.61 0.03 FD_BS 3 112.04 0.00IV_GF_YR 7 3.67 0.03 CI_FD 3 112.04 0.00IV_CIFD 8 3.70 0.03 GF_YR 3 112.45 0.00

CI_YR 3 112.54 0.00

BS_YR 3 112.69 0.00

IV_GFCI 8 4.62 0.02 CI_GF 3 113.61 0.00

IV_GF_BS_FD 8 5.22 0.01 CI_BS 3 113.65 0.00

IV_BS_CIFD 9 5.56 0.01 BS_GF 3 113.86 0.00

IV_CIFD_GF 9 5.73 0.01 CIGF 4 114.77 0.00

CI_FD_IV_BS_GF_YR

_CIFD_CIGF_FDGF13 3.99 0.02

45

Table 3-5. Model averaged estimates of parameter effects (with shrinkage).

Weighted averages of odds ratios for parameters present in top natal recruitment models

(ΔAICc < 4). IV3, IV4 and IV5 = three, four and five islands visited respectively, SYR =

year banded (scaled and centred), SGF = good food (grams per hour; scaled and centred),

SFD = fledge date (days since 1 May; scaled and centred).

Parameter Estimate LCL UCL Pr(>|z|)

(Intercept) 14.84 10.44 21.09 0.00

IV2 0.11 0.07 0.17 0.00

IV3 0.07 0.03 0.16 0.00

IV4 0.04 0.00 0.45 0.01

IV5 0.07 0.00 1.11 0.06

SFD 0.95 0.77 1.17 0.61

SGF 0.94 0.65 1.33 0.71

SFD:SGF 1.09 0.79 1.49 0.60

SBS 1.02 0.88 1.18 0.78

SCI 1.01 0.90 1.14 0.83

SYR 1.00 0.89 1.11 0.98

SCI:SFD 1.01 0.94 1.08 0.85

SCI:SGF 1.01 0.91 1.12 0.89

46

Table 3-6. Summary of results from generalised linear models with binomial

response detected at recruitment age (1), or not detected at recruitment age (0); a

measure of apparent survival. Models were compared using Akaike's Information

Criterion (AICc). AICc, ΔAICc (difference between AICc of current and top models),

AICc weight (a measure of support for each model; values sum to 1). K = number of

parameters.

Model K ΔAICc AICc Wt.

GF_YR 3 0.00 0.87CI_FD_BS_GF_YR_CIFD_CIGF_FDGF 9 6.19 0.04

CIFD_GF 5 7.17 0.02GF 2 7.92 0.02

CI_GF 3 9.24 0.01FD_GF 3 9.30 0.01CIGF 4 9.32 0.01

BS_GF 3 9.57 0.01GFCI_FD 5 10.04 0.01

FDGF 4 10.79 0.00FDGF_CI 5 10.86 0.00BS_GFCI 5 11.16 0.00BS_FDGF 5 12.71 0.00BS_CIFD 5 28.11 0.00

CIFD 4 31.97 0.00

CI_BS 3 35.04 0.00

FD_BS 3 36.04 0.00

BS_YR 3 36.93 0.00

BS 2 39.09 0.00

FD 2 40.71 0.00

CI_FD 3 40.88 0.00

CI_YR 3 41.37 0.00

FD_YR 3 41.86 0.00

CI 2 42.10 0.00

YR 2 44.29 0.00

Null 1 46.44 0.00

47

Table 3-7. Estimates of parameter effects (with shrinkage) for the only supported

survival model (ΔAICc < 4). Estimates are odd ratios. SYR = year banded (scaled and

centred), SGF = good food (grams per hour; scaled and centred).

Parameter Estimate LCL UCL Pr(>|z|)

(Intercept) 0.39 0.36 0.42 2.00E-16

SGF 1.48 1.32 1.66 4.03E-11

SYR 1.18 1.07 1.31 1.59E-03

48

Figure 3-1. The cumulative percentage of puffins tagged as chicks that recruited to

Machias Seal Island per year from ages 5 - 7 for each year cohort form 1997 to 2006.

Recruitment by cohort ranges from 0.12 of the 2004 cohort, to 0.46 of the 2001 cohort. N

= 3,143. Lines are terminated at age 7 so that early cohorts (which have had more time to

recruit) are not over-represented; overall, 96% of birds that recruit, have done so by age 7

(Figure 2). Note that these proportions incorporate individuals that were not seen at

recruitment age as well as those that dispersed to other islands, and as such the values are

lower than "natal recruitment" in the modeling results where only individuals that were

known to have recruited or dispersed are included.

49

Figure 3-2. Resightings of banded puffins showing the proportion of all resighted

birds that were observed at a given age. Most (96%) puffins that are resighted are seen

by age 7. N = 898.

50

Figure 3-3. Correlation matrix for predictors. Correlation coefficients for predictors

included in the model set. Size and colour of circles indicates strength and direction of

the relationship, respectively and corresponds to the numbers on the bottom left portion

of the figure. Parameters as in Table 3-2.

51

Figure 3-4. Relationships between the probability of natal recruitment to Machias

Seal Island and the number of islands visisted. Shading represents 95% confidence

limits. "Rugs" on the top and bottom represent the actual data where points on the top rug

are observations with positive residuals and those on the bottom are observations with

negative residuals.

52

Figure 3-5. Model averaged effect sizes (with 95% confidence intervals) of

predictors for natal recruitment models. Parameter from models in Table 3-4 with

ΔAICc < 4 were used for averaging based on AICc weights. Effect size was calculated

for each parameter with all others held at their mean. IV2, IV3, IV4, and IV5 = two,

three, four and five islands visited respectively, SFD = fledge date (days since 1 May;

scaled and centred), SGF = good food (grams per hour; scaled and centred), SFD:SGF =

interaction between fledge date and good food, SBS = breeding success (chicks fledged

per egg laid; scaled and centred), SCI = condition index (mass at fledge/wing chord at

fledge; scaled and centred), SYR = year banded (scaled and centred), SCI:SFD =

interaction between condition index and fledge date.

53

Figure 3-6. Relationship between the probability of survival and variables present in

top models from Table 3-5 (ΔAICc < 4). Shading represents 95% confidence limits.

"Rugs" on the top and bottom of each graph represent the actual data where points on the

top rug are observations with positive residuals and those on the bottom are observations

with negative residuals. Jitter was applied to better visualise density of the data points.

54

Figure 3-7. Model averaged effect sizes (with 95% confidence intervals) of

predictors for survival models. Parameter from models in Table 3-5 with ΔAICc < 4

were used for averaging based on AICc weights. Effect size was calculated for each

parameter with all others held at their mean. SGF = good food (grams per hour; scaled

and centred), SYR = year banded (scaled and centred).

55

Chapter 4 : Synthesis

My thesis explores the significance of declines in fledging parameters of Atlantic

puffins on MSI over the past three decades. Three parameters, in particular, have all

shown weakly declining trends with time over this period: physical condition (mass/wing

chord); quality of food; and timing of fledging. Similar trends (for condition, food, and

timing of breeding) that were observed in puffins breeding on the Isle of May in Scotland

during a comparable time period were accompanied by a decline in breeding success

(Wanless et al. 2009, Harris and Wanless 2011). I expected to see a similar decline in

breeding success (number of young fledged per egg hatched) in puffins on MSI.

Surprisingly, I found a slight increase over time. However, differences in breeding

success from year to year are much greater than any long-term trend. Puffins in

Newfoundland and Labrador have demonstrated resilience to considerable changes in

food conditions (Baillie 2001), and the same may be true of puffins in the Gulf of Maine.

Young puffins appear to be able to fledge the nest even in years when conditions are not

ideal; one mechanism identified is the preferential allocation of growth to aspects of

development that are the most important for survival, such as head and wing development

(Oyan and Anker-Nilssen 1996, Morrison et al. 2009). A striking decline in breeding

success was observed, however, during a year (2013) when body condition was the worst

(lowest mean mass/wing chord) in the 33 years of observation and the fledge date was the

latest (15 days later than the mean) over that same 33 year period. This is consistent with

a limit to the ability of puffins to overcome poor conditions; the existence of such a limit

is supported by patterns of declining puffin populations that are currently being observed

at the Isle of May and elsewhere in Europe (BirdLife International 2015).

56

The declining trends in fledging condition might be expected to produce

corresponding negative patterns in natal recruitment, especially for a population existing

on the far southern boundary of the species' range. However, I observed only weak (i.e.,

not statistically significant) effects of hatch-year parameters on the probability of natal

recruitment five years later. The degree to which an individual prospected for breeding

sites during the sub-adult life stage (ages 1-4) was the only parameter included in my

models showing a detectable effect on probability of natal recruitment. To my

knowledge, this is a novel result, and provides rare insight that may not have been

apparent had I not been able to control for survival in my analysis. This leads me to

speculate that conditions on destination colonies during the prospecting period may be

more important than conditions at the natal colony when young puffins are deciding

where to breed. Further insight into the natal recruitment process may be gained by

investigating the effect of conditions on destination islands during the prospecting period

on the probability of natal recruitment.

After observing the weak effects of fledging parameters that appeared in the top

models for the recruitment analysis, I suspected that these parameters may contribute

more to the survival process than to natal recruitment. Although I controlled for survival

in this analysis by excluding those that did not survive to breeding age, the process of

survival is still inherent in recruitment. To explore this hypothesis, I conducted an

analysis with survival to breeding age as the response variable. Results of that analysis

confirmed my suspicion, at least partially, with food and year having significant effects

on survival to breeding age. Interpretation of these results is complicated by difficulty in

controlling for recruitment in a survival analysis and, to a lesser degree, the reverse,

57

controlling for survival in a recruitment analysis. The latter difficulty was controlled by

excluding individuals that did not survive to recruitment age. However, contrary to a

study on tufted puffins (Morrison et al. 2009) reporting better survival for birds that

fledged heavier and with longer wings I found no effect of fledge condition on survival.

Natal philopatry of puffins on MSI is very strong with an average of 86% of

survivors from each cohort (1997-2006) returning to MSI (their natal island) to breed.

This is high in comparison to other islands in the metapopulation (ranging from 42% -

75%, Breton et al. 2006a), and other reports for puffins (6.5% - 30.1%, Harris and

Wanless 2011). The proportion that settle on MSI declines with increased prospecting

during the juvenile stage. The reason that some young prospect more than others is

unclear and does not appear to be linked to conditions during their hatch year.

Ideally, natal recruitment in any study would be determined by using data directly

related to breeding status (such as presence of a brood patch, capture within a breeding

burrow, etc.). In the absence of such data, movement patterns of juveniles can be used to

confirm that puffins on MSI, similar to puffins elsewhere (Petersen 1976, Breton et al.

2006a, Harris and Wanless 2011), begin breeding around the age of five years (Breton et

al. 2005). This approach to assigning breeding status is useful when data directly relating

to breeding status are unavailable, and should be considered by those without access to

such data.

In science we seek to gain an understanding of a particular system by observing

patterns and then determining the underlying processes responsible for the observed

patterns. Certainly, the scale at which any process should be studied is an important

consideration. Organisms respond to heterogeneity at multiple spatial and temporal

58

levels, and deciding at what scale to measure this heterogeneity is essential to obtaining

reliable insight into a particular process (Fahrig 1992, Levin 1992). For puffins (and

seabirds in general), the importance of studying dispersal and recruitment at the

metapopulation scale cannot be overemphasized. In terms of the spatial scale considered

for such studies, data from as many locations as possible within the metapopulation are

essential in obtaining reliable recruitment rates, as death and dispersal cannot be

separated in the absence of such data. This process takes many years, especially in long-

lived species, so data must also be collected over a large time scale. Such large-scale data

sets are understandably rare. Data from the Gulf of Maine puffin metapopulation are a

fortunate exception and have allowed for investigations into many aspects of puffin

ecology, including recruitment and dispersal, at an appropriate scale. My study in

particular has provided valuable insight into the nature of natal recruitment in puffins and

should ideally lead to further research into conditions faced during the juvenile period

between fledging and recruitment.

59

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Curriculum Vitae

Candidate’s full name: Susan Erin Whidden

Universities attended (with dates and degrees obtained):

University of New Brunswick, 2005 B.Sc. Biology

University of New Brunswick, 2016 M.Sc. Biology

Publications:

Whidden, S. E., C. T. Williams, A. R. Breton and C. L. Buck. 2007. Effects of

transmitters on the reproductive success of Tufted Puffins. Journal of Field Ornithology,

78(2), 206-212.

Conference Presentations and Posters:

Whidden, S. Erin, and A. W. Diamond. Patterns of Natal Recruitment in the Atlantic

Puffin (Fratercula arctica). Presentation given to the Gulf of Maine Seabird Working

Group (GOMSWG) spring meeting, 2012. Bangor, Maine.

Whidden, S. Erin, Cory T. Williams, Andre R. Breton and C. Loren Buck. Effects of

Radiotransmitters on Tufted Puffin (Fratercula cirrhata) Reproductive Success. Poster

Presented at Pacific Seabird Group annual meeting, 2006. Girdwood, Alaska.

Whidden, S. Erin, Cory T. Williams, Andre R. Breton and C. Loren Buck. Effects of

Radiotransmitters on Tufted Puffin (Fratercula cirrhata) Reproductive Success. Poster

Presented at Seabird Group annual meeting 2006. Aberdeen, Scotland.