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2018

Linking Physiology, Temperature, And Recruitment: A Classic Linking Physiology, Temperature, And Recruitment: A Classic

Competitive Story Rewritten By Climate Competitive Story Rewritten By Climate

Maeve Kerrigan Snyder University of South Carolina

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LINKING PHYSIOLOGY, TEMPERATURE, AND RECRUITMENT: A CLASSIC COMPETITIVE STORY REWRITTEN BY CLIMATE

by

Maeve Kerrigan Snyder

Bachelor of Science Coastal Carolina University, 2014 �

Submitted in Partial Fulfillment of the Requirements �

For the Degree of Master of Science in

Biological Sciences

College of Arts and Sciences

University of South Carolina�

2018

Accepted by:

Thomas J. Hilbish, Director of Thesis

David S. Wethey, Reader

Jesus Pineda, Reader

Cheryl L. Addy, Vice Provost and Dean of the Graduate School

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© Copyright by Maeve Kerrigan Snyder, 2018 All Rights Reserved

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ACKNOWLEDGEMENTS

I would like to extend my sincere and deep gratitude first and foremost to Dr.

Jerry Hilbish, without whose encouragement, patience, and mentorship, this work would

not have been possible. Through opportunities and confidence in my ability, Dr. Hilbish

has enabled me to grow and improve as a researcher and an individual. I am also

appreciative to Dr. David Wethey and Dr. Jesus Pineda for their guidance, input, and

inspiration. Amy Zyck, Jesse Turner, Sophia Sudak, and Cameron Good contributed

enormously to this work as research and field assistants. I am additionally grateful to

Rachel Steward, Mike Bramson, Rhiannon Rognstad, and Sam Crickenberger for their

contributions and advice. Special thanks to my friends and family for their loving

support. This work was funded by NASA (NNX11AP77G) and NSF (OCE 1129401)

grants to DSW and TJH and a Magellan Voyager Grant from the University of South

Carolina Office of Undergraduate Research to JMT.

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ABSTRACT

Climatic changes have the potential to alter population and community dynamics,

ultimately influencing the biogeographic distributions of species. For many organisms,

reproduction is physiologically tied to temperature. We tested the hypothesis that a

physiological mechanism for reproductive failure in the acorn barnacle, Semibalanus

balanoides, would result in predictable patterns of larval recruitment over broad

geographic scales. Recruitment density was predicted to be dependent on the duration of

permissive temperatures (< 10oC). for successful reproduction in adult populations of S.

balanoides. We found that temperature was a reliable predictive variable for recruitment

densities throughout our study region. Post-recruitment processes were also considered,

specifically the competition between Semibalanus balanoides and Chthamalus montagui,

described in Joseph Connell’s 1961 experiment. The competitive hierarchy outlined in

this experiment is not consistently observed throughout the range overlap of the two

species. Growth and mortality were found to differ dependent on species and latitude,

indicating that climate mediates this classic ecological system. Our results provide useful

knowledge for refining models of biogeographic shifts. A consistent failure of larval

supply and a breakdown of competitive advantage could accelerate the pace of predicted

range contraction for S. balanoides. Further investigation of how environmental variables

interact with physiology and ecological processes is necessary for accurate predictions of

climate change effects.

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ................................................................................................... iii

ABSTRACT ............................................................................................................................ iv

LIST OF TABLES.................................................................................................................. vi

LIST OF FIGURES ............................................................................................................... vii

LIST OF ABBREVIATIONS .............................................................................................. viii

CHAPTER 1: PREDICTING RECRUITMENT SUCCESS FROM A TEMPERATURE – BASED PHYSIOLOGICAL MECHANISM ACROSS A BROAD LATITUDINAL RANGE .....................................................................................................................................1

1.1 INTRODUCTION .................................................................................................2

1.2 METHODS.............................................................................................................9

1.3 RESULTS ............................................................................................................ 15

1.4 DISCUSSION ..................................................................................................... 19

CHAPTER 2: REVISITNG CONNELL: A CLASSIC COMPETITIVE SYSTEM LINKED TO CLIMATE ....................................................................................................... 38

2.1 INTRODUCTION .............................................................................................. 39

2.2 METHODS.......................................................................................................... 44

2.3 RESULTS ............................................................................................................ 49

2.4 DISCUSSION ..................................................................................................... 51

LITERATURE CITED ......................................................................................................... 66

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LIST OF TABLES

Table 1.1 Sampling period by region for 2015 and 2016. .................................................. 27

Table 1.2 Summary statistics of salinity time series for all sites ........................................ 28

Table 2.1 Subquadrats and corresponding experimental treatments .................................. 60

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LIST OF FIGURES

Figure 1.1 Study region and sites (in blue) on the west coast of the United Kingdom ..... 29 Figure 1.2 Time series of hourly air temperature, daily sea surface temperature, and composite air and SST for both study years ........................................................................ 30 Figure 1.3 Relationship between low tide CFSR air temperature and iButton temperature at Whitsand Bay ..................................................................................................................... 31 Figure 1.4 Figure 4. Relationship between combined SST and adjusted - air temperature and iButton temperature at Whitsand Bay ........................................................................... 32 Figure 1.5 Cumulative days below 10oC using composite air and sea surface temperature across the latitudinal gradient of the study sites for both sample years ............................. 33 Figure 1.6 Number of days below 10oC using composite air and sea surface temperature during the embryonic brooding period using composite temperature vs. recruitment density of S. balanoides at all sites ....................................................................................... 34 Figure 1.7 Early juvenile mortality of Semibalanus balanoides. Recruitment density sampled in May 2016 vs. recruitment density in June 2016 ............................................... 35 Figure 1.8 Log – transformed chlorophyll a concentration vs. recruitment density ......... 36 Figure 1.9 Averaged daily salinity data vs. recruitment density at each site ..................... 37

Figure 2.1 Experimental groupings for measurements of mortality and growth rate ....... 61 Figure 2.2 Average proportional cover of SB and CM across sites. Sites 1 – 18 are southwest England. Sites 18 – 23 are Wales. Sites 23 – 28 are Scotland .......................... 62

Figure 2.3 Percent cover analysis of simulated SB recruitment failure ............................. 63 Figure 2.4 Mortality (mean ± standard error) of SB and CM across latitude in isolation and interspecific groupings ................................................................................................... 64 Figure 2.5 Growth rate (mean ± standard error) of SB and CM across latitude in isolation and interspecific groupings ................................................................................................... 65

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LIST OF ABBREVIATIONS

CM .......................................................................................................... Chthamalus montagui

SB ....................................................................................................... Semibalanus balanoides

SST ....................................................................................................Sea Surface Temperature

UK ...................................................................................................................United Kingdom

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CHAPTER 1

PREDICTING RECRUITMENT SUCCESS FROM A TEMPERATURE – BASED

PHYSIOLOGICAL MECHANISM ACROSS A BROAD LATITUDINAL RANGE1

1 Maeve K. Snyder, David S. Wethey, Rhiannon L. Rognstad, Jesse M. Turner, Thomas J. Hilbish. Submitted to Marine Ecology Progress Series, 10/2/17.

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1.1 INTRODUCTION

Warming sea surface temperatures as a result of anthropogenic climate change

have the potential to cause dramatic shifts in the distributions, dynamics, and community

structures of intertidal organisms (Southward et al. 1995, Hawkins et al. 2008, Wethey et

al. 2011). Furthermore, a major goal of ecology is to understand the drivers that limit

biogeographic distributions. Numerous models have attempted to forecast future species

distributions using current distribution patterns and IPCC (Intergovernmental Panel on

Climate Change) future climate scenarios. This is of particular interest due to the

potential consequences of range migrations, contractions, and expansions, but the

specifics of these changes remain unclear for the populations of many organisms

(Helmuth et al. 2006, Burrows et al. 2014).

Increasingly, research has emphasized the need to consider physiological and

ecological mechanisms when predicting the effects of climate change on organisms and

ecosystems (Woodin et al. 2013, Rapacciuolo et al. 2014, Deutsch et al. 2015). Since

reproduction and larval survival are often sensitive stages in the life history of many

organisms (Thorson 1950, Pechenik 1999), information about how these stages are

affected by environmental variables may prove to be useful for improving ecological

forecasting models. A mechanistic understanding of how temperature interacts with

reproductive physiology and early life history could be a powerful predictor of climate

change effects on biological systems. In this thesis, the role of climate was investigated

for two processes of ecological influence and theoretical importance in rocky intertidal

systems – recruitment and competition. Research in this area will improve understanding

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of population and community structure and will give insight into how a changing climate

may alter interactions and distributions.

Rocky intertidal ecosystems are frequently used for field-based experiments and

have contributed disproportionately to the development of theory in population and

community ecology (Connell 1961, Paine 1966, Dayton 1971). These habitats are suited

to experimental studies of ecology in a number of ways. They experience steep gradients

of environmental conditions and can provide researchers with easy access during low

tides. The rocky intertidal is also home to many sessile or, if mobile, slow-moving

organisms that can easily be marked, tracked, and manipulated in experimental

treatments. (Menge & Branch 2001). The fauna of rocky intertidal habitats in the United

Kingdom (UK) have been model organisms for many such studies of ecology.

Furthermore, the extensive climatic and biogeographic records maintained in the UK help

with the construction of correlational patterns between climate and biogeographic trends.

The United Kingdom is a region of biogeographic overlap and allows the

coexistence of several southern and northern species (Crisp & Southward 1958, Herbert

2003). Populations of sessile invertebrates, particularly barnacles, found in the rocky

intertidal system of the UK therefore provided a model system to investigate the

questions addressed in this thesis. Barnacles are marine crustaceans found worldwide as

members of subtidal, intertidal, and fouling communities. Adult barnacles live in calcium

carbonate shells that are permanently cemented to a substrate. They are able to disperse

and colonize new locations through a planktonic early life history stage (Thorson 1950).

Semibalanus balanoides is a cold-water species occurring throughout the UK but

reaching a southern range limit in southwest England. S. balanoides and other barnacles

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reproduce with internal fertilization followed by an embryonic brooding period, in which

developing embryos are held within the shell cavity of adult individuals until they

develop into larvae that are competent to be released into the water column as

zooplankton. Chthamalus montagui is a warm water species found throughout the

western coast of Britain and further south in Europe (Barnes 1957, Crisp & Southward

1958). S. balanoides and C. montagui have staggered recruitment seasons: S. balanoides

fertilizes gametes in late Autumn, broods embryos during the winter months, releases

larvae into the plankton in late winter/early spring, and recruit to the shoreline in April –

June (Crisp & Clegg 1960, Crickenberger & Wethey 2017) C. montagui follows this

same procession with the timing offset so that they commonly recruit in late summer –

early fall (Jenkins 2005). Hereafter, Semibalanus balanoides will be referred to as SB and

Chthamalus montagui as CM.

Climate effects on populations have been observed in a multitude of species and

ecosystems, but rocky intertidal may be especially sensitive to these changes due to their

combined exposure to aquatic and terrestrial stresses (Mieszkowska et al. 2006; Helmuth

et al. 2006, Hawkins et al. 2008). Species may manifest climate change effects in a

multitude of ways. For example, phenological shifts are changes in the timing of periodic

life cycle events, such as blooming, migrations, or reproductive events (Memmott et al.

2007, Schlüter et al. 2010). Organisms may also respond to changing climate through

range shifts, genetic shifts, or community shifts (Root et al. 2003). Many intertidal

species in southwest England have changed in abundance since the 1980s (Crisp &

Southward 1958, Herbert et al. 2003, Mieszkowska et al. 2006). Warm water species

(e.g., Chthamalid barnacles, Patella depressa and B. perforatus) have increased while

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cold-water species have decreased in abundance (e.g., SB and Patella vulgata)

(Mieszkowska et al. 2006, Southward 1991, Southward et al. 1995, Helmuth et al. 2006).

However, these changes in abundance could be attributed to a variety of mechanisms and

ecological processes.

To link the influence of climate on ecology, an important focus is physiological

processes that are sensitive to temperature (Woodin et al. 2013). It has been increasingly

recognized that physiology is a vital consideration in biogeographic forecasting. Many

studies of forecasted distribution changes are correlational in nature. The merit of

collecting data on physiological relationships lies in the ability to mechanistically justify

biogeographic models (Woodin et al. 2013, Rapacciuolo et al. 2014). However, the

complexity of relating physiological constraints to large-scale consequences remains a

challenge. Physiological limits may scale up to population level effects in a number of

ways – some acutely fatal, others weaker but persistent. Some organisms are limited by

thermal maxima (Jansen et al. 2007), however physiological stresses may also depend on

the length, frequency, and magnitude of exposure to stressful levels of an environmental

variable, not to mention the state, age, and genetics of the organism (Lima & Wethey

2012, Crickenberger & Wethey 2017). A further complication is that many

environmental conditions act concurrently. Intertidal organisms are often thought to be

more resistant to extremes due to the large fluctuations in their habitat. However,

depending on the organism, it is possible populations may be more sensitive to changes

because they are already near their physiological limits (Findlay et al. 2009). Since

barnacles are immobile following settlement, they are susceptible to even short-term

periods of acutely unfavorable conditions of the environment. Determining the most

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important manner that climate influences organisms, whether it is the magnitude,

duration, or frequency of climatic events, whether it is temperature extremes (maxima or

minima), and the manner of physiological effect that is elicited remains an intricate

challenge to ecologists.

Since reproduction and larval survival are often sensitive stages in the life history

of many organisms, information about how these stages are affected by environmental

variables may prove to be useful for improving ecological forecasting models (Thorson

1950). A mechanistic understanding of how temperature interacts with reproductive

physiology and early life history could be a powerful predictor of climate change effects

on biological systems. Most sessile marine organisms rely on a larval planktonic stage for

dispersal and population connectivity. This life history strategy necessitates that larvae

successfully recruit from a planktonic larval stage into the adult population. Studying the

dynamics surrounding recruitment is crucial to understanding the ecology of such

organisms (Thorson 1950, Strathmann 1993, Nathan 2001). Recruitment is affected by

conditions at global, regional, and local spatial scales (Menge & Sutherland 1987,

Svensson et al. 2006). Recruitment has been described as “setting the stage” on which

post-settlement processes, such as competition and predation, play out (Menge 2000,

Underwood & Keough 2001).

Connecting physiology to biogeography can be approached by working

backwards to find a mechanistic explanation for an observed pattern of range shift or by

applying a known physiological limit to test hypotheses about whether it can cause large-

scale patterns. Using the latter approach, we designed an experiment to empirically test

the physiological model’s predicted effects on broad-scale patterns of recruitment in the

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barnacle Semibalanus balanoides. SB is a boreo-artic species and its reproduction is

physiologically linked to temperature (Southward & Crisp 1954, Crisp 1964, Rognstad &

Hilbish 2014). It broods embryos within its shell during the winter months and this

process is inhibited if sea surface temperature (SST) exceeds 10oC during brooding

(Rognstad & Hilbish 2014). In the United Kingdom, larval release occurs in the months

of March and April; recruitment primarily occurs during May and June (Barnes 1962,

Hawkins & Hartnoll 1982, Kendall et al. 1985). Populations of SB occur throughout the

northeast Atlantic, including the west coast of the United Kingdom. However, the species

reaches its southern range limit in several locations throughout Europe, including

southwest England. In this region, populations of SB are transient and have been shown

to fluctuate with yearly temperature trends (Southward & Crisp 1954, Rognstad et al.

2014). Range extension occurs with high-density recruitment levels following cold

winters where temperature was permissive to reproduction (below 10oC) for greater than

6 weeks (Rognstad et al. 2014). Recruitment is weak or fails after warmer winters.

Here, we specifically test the hypothesis that broad geographic variation in winter

air and sea surface temperatures creates regional variation in larval recruitment that can

be predicted by the cold-temperature threshold model of Rognstad et al. (2014). We

predict that high recruitment will occur in regions where winter temperatures are

sufficiently cold (below 10oC) for greater than six weeks and recruitment will be weak in

warmer regions that do not meet this threshold. However, it is well known that

recruitment is the compilation of complex processes and, consequently, success in

surviving the multiple population bottlenecks during larval development and planktonic

dispersal may obscure any effect of brooding-stage temperature (Pineda et al. 2009,

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Crickenberger & Wethey 2017). We test the hypothesis that recruitment can be predicted

from winter temperatures in SB on the west coast of the United Kingdom, despite this

complexity. The English Channel has already experienced notable climatic warming and

several corresponding changes in its marine communities (Southward et al. 1995, Lima &

Wethey 2012). Understanding the drivers underlying the reproduction and recruitment of

SB will provide insight into the likelihood of their persistence in the current extent of

their range. It will also shed light onto the question of how other marine organisms that

are physiologically linked to temperature may respond to a warming ocean.

Since scientists can make predictions about what is expected to happen

biologically as a result of climate change, it is possible to generate null models and test

hypotheses about whether observed patterns of biological change are probabilistically

explained by climate change (Root et al. 2003, Parmesan & Yohe 2003). Climate change

may have a synergistic effect of modification on these sites since an additional source of

variation in the outcome of density manipulations is differences in recruitment between

sites and between years (Sutherland 1978). The English Channel has already experienced

notable climatic warming and several corresponding changes in its marine communities

(Southward et al. 1995, Lima & Wethey 2012). Understanding the drivers underlying the

reproduction and recruitment of SB will provide insight into the likelihood of their

persistence in the current extent of their range. It will also shed light onto the question of

how other marine organisms that are physiologically linked to temperature may respond

to a warming ocean.

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1.2 METHODS

Data Collection

Recruitment was sampled at 30 intertidal sites along the west coast of the United

Kingdom (Figure 1.1). Sites were spaced at approximately 50 km intervals, based on

estimated dispersal distance for barnacle larvae (Southward 1967, Rognstad et al. 2014).

Five quadrats (7.5cm x 7.5 cm) were established at the mid-tidal level in 2014 and 2015

at each site. The quadrats were scraped completely free of barnacles during May to June

of 2014 (following settlement), which allowed the measurement of de novo recruitment

in subsequent years. Each quadrat was photographed using an Olympus TG-4 digital

camera. Sampling occurred during spring (May to June) 2015 and spring (May to July)

2016 (Table 1.1). In 2016, all sites were sampled twice (once in May and once in June).

Because it was logistically impossible to sample all sites at the same time, we compared

photographs taken in May 2016 to those from June 2016 to address two questions: 1) Did

appreciable recruitment occur following the earliest sampling events? 2) Does early

juvenile mortality obscure the pattern of recruitment?

Image Analysis

The density of new recruits was analyzed using the open source software Image J

(Abramoff et al. 2004). New recruits were identified and quantified from scrapes that

were created the year prior (after the end of Semibalanus balanoides recruitment for that

year). The edge of the square quadrat frame was used to calibrate the ImageJ

measurement tool. To eliminate edge effects, an area of 30.25 cm2 was delineated in the

center of each quadrat, and this area was analyzed for recruitment density. Density was

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measured in all five quadrats for each site, each year. All newly recruited barnacles were

identified based on plate number and shape as described by Drévès (2001). Individuals of

S. balanoides could be confidently differentiated from other common intertidal species in

the region, including Chthamalus stellatus, C. montagui, and Austrominius (=Elminius)

modestus (Southward 1976).

Temperature Analysis

NOAA Optimum Interpolation ¼ Degree Daily Sea Surface Temperature

Analysis data (Reynolds et al. 2009) were obtained from the NOAA National Climatic

Data Center (https://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-

interpolation/access/) These data were available from each field sample site at a 25 km

spatial scale. Climate Forecast System Reanalysis (CFSR) hourly 23km gridded 2m air

temperature data (Saha et al. 2011) were obtained from the NCAR National Centers for

Environmental Prediction (https://rda.ucar.edu/datasets/ds094.1/). Temperature data were

then imported into RStudio (Version 1.1.414) and a script was developed to identify the

closest marine pixel to each sample site and extract the temperature data for each

location. This method was justified based on Lima & Wethey 2012 (their supplemental

materials), which showed that the nearest pixel to intertidal sites and SST measured

onshore are highly correlated. We considered other temperature metrics, such as

cumulative degree days and temperature maxima. The various representations of

temperature all showed a similar trend across latitude, and it is not likely a different

metric would have altered our results. While temperature extremes are often important

from a biological standpoint, we found that at no time during the embryonic brooding

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period did any site meet or exceed 18 – 20oC for air or SST, which is lethal to developing

embryos (Crisp 1959b). Figure 1.2 presents time series data for air, SST, and composite

temperature data at three sites (representative of regions within the latitudinal gradient).

Since SB is an intertidal species, a composite of hourly air temperature and daily

SST data was created to accurately reflect the temperatures experienced by barnacles at

each site. The composite temperature was assembled using SST data during high tide

periods (>3 m tide height, the mid – tide level of quadrats) and air temperature during

low tide periods (<3 m tide height). Tide predictions were estimated with XTide (Flater

2005). To assess how accurately remotely sensed data reflected the body temperatures of

individuals of SB, SST and air temperature were compared to previously recorded

iButton temperature data. iButtons were cemented to rock surfaces among clusters of SB

at a site in southwest England (Whitsand Bay) from November 1 to January 31 of 2012 –

2013 and remotely sensed data were obtained for the same period. iButtons were wrapped

in Parafilm and embedded in marine epoxy (Z-Spar A-788 Splash Zone Epoxy, Carboline

Co, St. Louis, MO USA) to improve water-resistance and mimic rock reflectivity (Jones

et al., 2012). Marine epoxy also attached the iButtons to rock surfaces. Temperature

readings were recorded by iButtons every two hours during this period. iButton and

barnacle body temperatures are expected to conform closely to the surface temperature of

the rock to which they are attached. We found a close correlation between iButton and

SST while the iButton was submerged. However, during emersion remotely sensed air

temperature was typically colder, and often much colder, than were the temperatures of

the iButtons (Slope = 0.30604; R2 = 0.4222, F1,403 = 294.5, p < 0.0001, Figure1.3). This

discrepancy was greater for colder temperatures and the two measures of temperature

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converged (y = 0.30604 * x + 8.1509, Figure S1). We used the regression between

iButton and air temperature to predict the body temperature of barnacles during emersion.

These data were then combined with the remotely sensed SST during immersion to

estimate a composite daily temperature that a barnacle is expected to experience. The

composite daily temperature was closely correlated to the average daily temperature of

the iButton temperature loggers (Slope = 0.7982; R2 = 0.3763, F 1,698 = 421, p <0.0001). We

used this approach to estimate composite daily body temperatures for SB during the

brooding periods in 2015 and 2016 (see Figure 1.4).

Embryonic brooding period was estimated from recorded dates of fertilization,

development rate, and larval release in previous literature. Timing of fertilization of SB

varies latitudinally, and interacts with temperature, but is generally consistent within sites

and regions (Crisp & Clegg 1960, Crickenberger & Wethey 2017). Within a site, tide

level is the best predictor of fertilization timing, which is a controlled variable in this

study (Crisp 1959a). Barnacles at sites in southwest England have been observed to

fertilize later than in colder regions, and additionally have increased rates of development

(Crisp 1959b). The embryonic brooding period was estimated to be November 1 –

February 28 for sites in Wales and Scotland (Crisp & Clegg 1960, Kendall et al. 1985,

Barnes 1962). Due to the delayed timing of fertilization and increased rate of

development for SB in southwest England, brooding period was estimated to be

November 30 – February 28 for this region (Crisp 1959a, Crisp 1959b, Crisp & Clegg

1960). From the composite of hourly air temperature and daily SST, a daily average was

calculated for each day in the brooding period. The cumulative number of averaged days

that each site spent below 10oC during the brooding period was recorded from these data.

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As per Rognstad et al. (2014), sites were then assigned to 1 of 3 categories for the

duration of permissive temperature for reproduction (below 10°C): (1) greater than 6

weeks (> 6) (2) 4 to 6 weeks (4 - 6) (3) less than 4 weeks (< 4). These categories of

temperature duration were chosen based on observed patterns of temperature influencing

reproductive physiology of SB described in Rognstad et al. (2014). Recruitment densities

were designated as “very low” (< 1 individual cm-2), “low” (1-5 individuals cm-2), and

“high” (> 5 individuals cm-2). Density categories were determined based on recruitment

levels that were observed during years with comparatively long or short durations of

permissive winter temperature. These patterns were observed and described for southwest

England in Rognstad et al. 2014. We predicted that sites corresponding to category 1

would receive high levels of SB recruitment; sites corresponding to category 2 would

receive low recruitment; and sites corresponding to category 3 would receive very low

recruitment

Chlorophyll a Analysis

We additionally investigated whether food supply for larvae could be a stronger

predictor of recruitment at local scales, as predicted by phytoplankton mismatch

hypothesis (Cushing 1990). We hypothesized that low phytoplankton abundance during

the planktonic larval period might explain recruitment failure at sites where the

occurrence of cold winter temperature predicted high recruitment. Inadequate food

supply could result in high mortality during the planktonic stage and uncouple high larval

supply from recruitment at a local scale. Gimenez et al. 2017 found that nutritional

reserves for SB vary spatially and may influence recruitment and early post- settlement

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survival. This suggests that food availability during the planktonic stage may be

consequential even following settlement. We tested this hypothesis using remotely sensed

chlorophyll a concentration as a proxy for food supply of barnacle nauplii. Chlorophyll a

data were obtained from the European Union Copernicus Marine Environment

Monitoring Service (http://marine.copernicus.eu/) and were chosen by locating the

monitoring pixel that was closest to each sample site. For 2015, averaged the mean

chlorophyll a concentration across sites to obtain a single value representing during the

planktonic period (estimated to be between March 1 – May 1 as per Southward & Crisp

1954 and Barnes 1962).

Salinity Analysis

Salinity was another environmental variable that was investigated as a potential

influence on recruitment, particularly at more estuarine sites in the study region. We

hypothesized that at sites that experienced low salinities during the settlement period

(corresponding to an influx of freshwater following large precipitation events), we would

find depressed levels of recruitment. We tested this hypothesis using 2015 daily salinity

data from the European Union Copernicus Marine Environment Monitoring Service

(http://marine.copernicus.eu/). Salinity data were averaged across the embryonic

brooding period for all sites. Time series of salinity during the brooding period were also

visualized to check for extreme minima and concluded the averaged salinity data

accurately represented the salinity across time (Table 1.2). Salinity data were imported

into RStudio (Version 1.1.414) and a script was developed to identify the closest marine

pixel to each sample site.

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Statistical Analysis

Mean recruitment density was obtained from each site by averaging the density

measurements from the five quadrats at each site. A simple linear regression was used to

compare the relationship between cumulative cold days (number of days < 10oC) and

recruitment density (individuals per cm-2 ) against a null hypothesis of constant

recruitment across cumulative cold days. A G-test of independence was used to analyze

the relationship between the categories of cumulative cold days (< 4, 4 - 6, > 6 weeks)

and the predicted category of recruitment density (“very low”, “low”, “high”). For early

juvenile mortality, the trend in density reduction between May and June was fit to a non-

linear model using the Michaelis-Menten equation (y = (b1 * x) / (x * b2))) with b1 = 10

and b2 = 20, based on the visually estimated Vmax and Km of the data. Simple linear

regression was used to test additional hypotheses about variables that may affect

recruitment – chlorophyll a concentration and salinity.

1.3 RESULTS

Recruitment and Brooding Period Temperature

Figure 1.2 presents air and sea surface temperature time series data for the

brooding periods in 2015 and 2016. Remotely sensed air temperature was considerably

more variable and colder than SST. Composite temperatures, which combined SST and

adjusted air temperature, during the periods of immersion and emersion, respectively,

were much less variable than remotely sensed air temperature and were much more

similar to SST. Composite temperatures were used to estimate the number of days below

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10oC experienced by barnacles at each sample site. There was a strong relationship

between days below 10oC and latitude during both 2015 and 2016 (Figure 1.5). Barnacles

at sites in Southwest England frequently experienced fewer than four weeks below 10oC

while sites in Scotland all experienced 6 - weeks or longer below 10oC.

A significant, positive linear relationship was found between cumulative cold

days and recruitment density (R2 = 0.4013, F1,52 = 34.86, p < 0.0001, Figure 1.6). A G-test

of independence revealed a significant effect for the duration of permissively cold

temperature on recruitment density levels (G = 22.744, df = 4, p = 0.00014). At the broad

spatial scale, there was an overall latitudinal gradient of recruitment density based on

duration of permissive temperatures. The majority of sites in southwest England (<51oN

latitude) experienced <4 weeks of permissively cold temperatures (< 10oC) in both years

(Figure 1.5). Comparatively, 2016 was a warmer year than 2015, and all southwest sites

were predicted to have “very low” recruitment, having experienced less than 4 weeks of

permissively cold temperatures. In 2016, some sites were in the predicted ranges for

“low” recruitment. Recruitment densities at these sites were found to be either “low” (<

5 individuals cm-2) or “very low” (< 1 individual cm-2) for all sites in both years. Two sites

in southwest England received virtually no recruitment despite being permissively cold

for nearly six weeks in 2015 (Figure 1.6). There was no apparent relationship between the

cumulative time categories (4 -6 weeks vs. < 4 weeks) in regard to whether recruitment

was “low” or “very low.” However, none of these sites experienced “high” recruitment

densities of SB (>5 individuals cm-2) (Figure 1.6).

Sites in Wales were highly variable in the duration of permissive brooding

temperatures (Figure 1.5). As in southwest England, 2016 was found to be a warmer year

‘ 17

than 2015 in this region. All sites in Scotland experienced well over six weeks of

permissively cold temperatures both years. Recruitment densities in Wales and Scotland

showed a greater range compared to southwest England, with some sites receiving

virtually no recruitment, up to nearly 25 individuals per cm2 (Figure 1.6). While most

sites in Wales and Scotland met the prediction of “high” recruitment based on duration of

permissive temperatures, four sites were found to have “low” recruitment despite

experiencing well over six weeks of permissive temperatures. Recruitment at two sites in

Wales was predicted to be “very low” due to the short duration of permissive

temperatures, but “high” densities were observed (Figure 1.6).

Early juvenile Mortality

In 2016, we asked whether appreciable recruitment occurred at sample sites late

in the recruitment season (April – June). We also investigated if early juvenile mortality

modified populations over the recruitment season. We found a density – dependent

relationship between early and late recruitment season recruitment density (Figure 1.7).

For sites with high initial recruitment, density-dependent mortality resulted in reductions

in density between the May and June sampling periods. Some sites with initial

recruitment densities >40 individuals cm-2 had density reductions of over 50% (Figure

1.7). At sites in southwest England, however, recruitment densities during May were

typically <5 individuals cm-2 and very similar densities were observed in June, indicating

that there was neither significant mortality or additional recruitment between the two

samples (Figure 1.7). Across all sample sites there were very few that had greater

densities in June compared to May, and the increased densities were never greater than 2

‘ 18

- 3 individuals cm-2 at any site. This indicates that the vast majority of settlement was

complete by the time of initial sampling in May.

Chlorophyll a

There was no apparent relationship between chlorophyll a concentration and

recruitment of SB (R2 = 0.016, F1,24 = 0.385, p = 0.541, Figure 1.8). Indeed, the site with

the highest level of phytoplankton was Great Cumbrae in 2015 which experienced nearly

complete recruitment failure that same year (Figure 1.8). It should be recognized that

food quality may be more important than abundance, and that chlorophyll a may be

uninformative about the quality or type of phytoplankton available for consumption

(Toupoint et al. 2012). Regardless, at present we could not attribute variation in

recruitment to food availability while barnacle nauplii were developing in the plankton.

Salinity

There was no significant relationship between salinity and recruitment of SB (R2 =

0.1182, F1, 24 = 3.216, p = 0.086, Figure 1.9). The majority of sites experienced fully

marine salinity (~35 ppt) throughout the brooding period. Two sites, Great Cumbrae

(GC) and St. Bees (SB) (Figure 1.9) were known to be more estuarine in location. These

sites also had the lowest minima recorded during the planktonic period (Table 1.2). These

sites did show decreased average salinity as well as lower recruitment but there was no

overall relationship present between recruitment and salinity. Ullapool experienced a low

minimum and average salinity as well, but had the highest observed recruitment density.

‘ 19

1.4 DISCUSSION

Recruitment in benthic marine species with planktonic larval dispersal is typically

erratic in both time and space. Pineda et al. (2009) argued that survival between various

stages of larval development may be so variable that recruitment may be effectively

uncoupled from success at any given stage of development. It may, therefore, be

exceptionally difficult to predict large-scale geographic patterns of recruitment. Within

the region of southwest England, Rognstad et al. (2014) demonstrated that annual

variation in winter sea surface temperatures (SST) could be used to predict larval

recruitment of the cold-water barnacle Semibalanus balanoides. At sites where composite

winter temperatures were sufficiently cold for > 6 weeks, there was high recruitment of

SB that was not observed at sites where this cold threshold was not met. These results are

consistent with the findings that warm temperatures above 10oC inhibit embryonic

development in SB (Barnes 1957, Crisp & Clegg 1960, Crisp & Patel 1969, Rognstad &

Hilbish 2014). In this study we found that the same physiological model used by

Rognstad et al. (2014) to predict annual variation in recruitment of SB at their southern

range margin can also be used to predict large-scale patterns of SB recruitment.

As predicted from the physiological model, larval recruitment was “low” or “very

low” (<5 cm-2) at over 90% of sites where temperature was not sufficiently cold for more

than four weeks (Figure 1.6). Winter temperatures were warmer in 2016 than in 2015,

especially in Southwest England (latitudes <51oN), and larval recruitment was

correspondingly lower (~1 cm-2). Across all sample locations, there was a significant

correlation between larval recruitment and the number of days < 10oC (R2 = 0.4013, F1,52 =

34.86, p < 0.0001, Figure 1.6). This explains a large portion of the variation across

‘ 20

latitude but is not the sole source of variation. Latitude was closely related to variation in

recruitment (R2 = 0.7061, F 1,52 = 125, p = 1.93e-15). However, winter temperature and

latitude are related measures (Figure 1.5). Based on a known temperature mechanism for

reproduction, we observed a broad geographic pattern of recruitment for populations of

SB in the United Kingdom.

An interesting test of these results would be the response of SB recruitment to a

severe cold winter. There is observational evidence to support that cold winter seasons

result in increased recruitment of SB, which is likely driven by the physiological

mechanism described here (Crisp 1964, Rognstad et al. 2014). Incorporation of effects

from extreme brooding period temperatures into this temperature response model would

improve the mechanistic basis for use in climate and biogeographic forecasting (Wethey

2011, Thompson et al. 2013). In this study we assumed that the 10oC threshold for high

reproductive output was the same for all populations of SB across the species range.

Assessing geographic variability in this temperature threshold may be important for

improving biogeographic forecasts. Explorations of microclimate effects, especially

during low tide, will be a worthwhile direction for research to further investigate the

ability of this physiological method to drive recruitment.

Our results indicate that larval recruitment was highly correlated with predicted

input into the larval pool as a result of successful brooding of embryos. This seems at

odds with the hypothesis of Pineda et al. (2009) that recruitment may be unpredictable

given the potential for success at one stage of the recruitment process to be decoupled

from success at other stages. However, Pineda et al. (2009) also suggests that variation in

recruitment will depend most strongly upon that stage of the life cycle with the greatest

‘ 21

temporal and spatial variation in survival. In this case, we suggest that successful

brooding of embryos may be the most variable stage, and therefore plays the greatest role

in determining variation in recruitment across a large spatial scale. In Southwest England,

winter temperatures were too warm to permit high larval output by brooding adults,

causing widespread and consistent recruitment failure. In contrast, winter temperatures in

Scotland were consistently permissive to successful larval brooding and yet there was

variation in recruitment among sites and between years. For SB, we suggest modifying

the Pineda model to include this threshold effect for embryonic brooding success. If

larval supply is predicted to be high, it remains possible for recruitment to fail at later

stages of development. However, when larval production is precluded by warm winter

temperatures, the model should reflect that it is very unlikely that success later in

development could compensate for this failure to ultimately yield high recruitment. This

revised model treats larval supply as the determinant for recruitment potential, with high

larval supply as a prerequisite to high recruitment. As our results show, at warm locations

there is low variation in recruitment indicating little evidence of rebounding from low

input into the larval pool. At cold locations, while recruitment was generally high as

predicted, it was nonetheless possible for recruitment to fail.

Early juvenile mortality is another process with the ability to uncouple

recruitment from larval success in the plankton (Pineda et al. 2009). Since density-

dependent mortality of recruited juveniles is strongest shortly after recruitment for SB

(Jenkins et al. 2008), we wanted to assess whether appreciable settlement occurred

following sampling in May and whether density dependent mortality was strong enough

to obscure early patterns of recruitment. We found little evidence for additional

‘ 22

recruitment following the May sampling. There was a decline in abundance of new

recruits in the first few weeks post-settlement, the magnitude of which was strongly

dependent upon initial density (Figure 1.7). The greatest reductions in density occurred at

sites where initial settlement was greatest and, in some cases, declined by as much as

50% (Figure 1.7). These results are consistent with the results of Jenkins et al. 2000,

which showed a density dependent reduction in density in southwest England and Wales

(their Figure 1.7). For years with permissive temperature in southwest England, higher

densities of recruits may result in density dependent effects that are typically present at

higher latitudes. Following rapid growth of new recruits, crushing and crowding are

likely sources of mortality, but we did not test the specific causes of density reduction.

Even with density reductions, sites with higher density early in the recruitment period

still had the greatest densities of SB at the end of the recruitment period. The pattern of

recruitment observed in May samples was retained – sites that received high recruitment

remained as such and vice versa.

While there was a strong broad-scale pattern in recruitment related to brooding

temperature there were nonetheless sites that received very low recruitment despite the

fact that the physiological model predicted high requirement (e.g. St. Bees, Borth, Great

Cumbrae). We investigated three possible explanations for why low recruitment was

observed despite the prediction that recruitment would be high. One possible explanation

may be that there was a mismatch between larval release and the availability of suitable

food in the plankton, which may result in recruitment failure (Barnes 1962, Cushing

1990). Prior attempts to apply the phytoplankton mismatch hypothesis to recruitment data

have shown mixed results (Thackeray 2012). Scrosati & Ellrich (2016) found that a

‘ 23

combination of temperature and remotely sensed chlorophyll a explained 51% of the

variability in a 12-year record of recruitment data for SB in Nova Scotia. Leslie et al.

(2005) found no connection between primary production (also measured by chlorophyll

a) and recruitment of Balanus glandula. However, there was a relationship between

primary production and larval production. This would be another potential mechanism by

which primary production could limit recruitment to investigate in future analyses. Our

cursory investigation into the potential explanatory power of phytoplankton mismatch for

SB recruitment in our sample region yielded no support for this hypothesis (Figure 1.8).

However, models predicting the success of early life history stages for SB found that

phytoplankton mismatch is more likely for populations in the western English Channel

(Crickenberger & Wethey 2017).

There is a plethora of other possibilities that may explain variability in

recruitment level when high recruitment is predicted (e.g. predation, transport, etc.). Our

results, however, suggest a specific hypothesis. We observed that anomalously low

densities of Semibalanus balanoides co-occur with elevated abundance of the invasive

barnacle Austrominius modestus (pers. obs.). A. modestus is known to be tolerant of more

estuarine conditions than many barnacle species native to the United Kingdom, especially

SB (Lawson et al. 2004, Gallagher et al. 2016). This observation suggests that several

sites, especially St. Bees, Great Cumbrae and Borth, may be intermittently inundated by

water from nearby estuarine sources. However, it is unlikely that salinity ever fell low

enough to directly kill the larvae or newly settled recruits of SB. During the settlement

period, the lowest minima (Table 1.2) were likely insufficient to kill or even greatly

impair the motion SB larvae (Barnes 1953, Bhatnagar & Crisp 1965, Rosenberg 1972).

‘ 24

While we did not find a significant relationship between daily salinity data averaged

across the recruitment period, two sites (Great Cumbrae and St. Bees) that were noted for

having anomalously low recruitment were found to have lower salinity. It is possible that

SB may be physically excluded from these sites located near estuaries when freshwater

discharge is high. Estuarine water, carrying larvae of A. modestus, may displace marine

water (carrying larvae of SB). Boundaries between water masses, such as an

estuarine/marine front can influence dispersal and recruitment of marine organisms; the

role of fronts was not tested but may have been another driver of recruitment outcomes

(Woodson et al. 2012). Testing this hypothesis would require high-resolution sampling of

plankton communities and salinity levels along a transect of the proposed

estuarine/marine front.

For species with limited dispersal ability, shifting zones of physiological tolerance

may lead to complete extermination (Pearson & Dawson 2003, Araújo & Guisan 2006).

The majority of SB populations in the southwest are dependent on colonization from sites

east of a headland called Start Point in the English Channel, where SST is typically

colder. The lifespan of SB is three years (Southward & Crisp 1954, Wethey 1985).

Several successive years of non-permissive winter temperatures could result in the

extirpation of SB from much of its range in Devon and Cornwall (Gilg & Hilbish 2003,

Rognstad et al. 2014). SB has already been predicted to become locally extinct in

southwest England by 2050 (Poloczanska et al. 2008). Moreover, continued warming will

have negative consequences to populations of SB on the western coast of the United

Kingdom. Wethey et al. 2011 found that SST permissive to SB during the brooding

season might significantly contract northward over the next century. Based on their

‘ 25

analysis, it seems likely that winter temperatures that favor high brooding success will no

longer occur in southwest England by 2100.

Sites in southwest England had high levels of open space available to recruiting

Semibalanus balanoides. However, recruitment densities at these sites were low in the

years of our study, and the majority of space in sample quadrats remained open. At sites

with little open space, SB often smothers other barnacles. This does not seem to affect

community composition at southern sites where recruitment of SB on adult barnacles or

mussels was rarely observed. Competition is an important ecological process for shaping

community structure in the rocky intertidal; the competitive hierarchy between SB and

CM is a classic illustration of the realized and fundamental niche (Connell 1961). If

population smothering is an important mechanism of interspecific competition for SB,

poleward movement of warm temperatures inhospitable to reproduction may lead to

progressively thinning larval at a retreating range edge. Loss of a density driven

competitive mechanism may make SB more vulnerable to competition for space with

other intertidal organisms and accelerate their disappearance at southern range limits.

Climate change has the potential to dramatically re-structure ecosystems, which

could result in negative consequences for biodiversity (Pereira et al. 2010). Furthermore,

range expansions and contractions can drastically alter community functioning. A shift

from a rocky intertidal zone dominated by SB to one dominated by CM has implications

for biodiversity and trophic effects. The body structure of SB is more rugose, which may

promote the recruitment of other intertidal species, such as algae and mussels. SB is also

a preferred prey species for several intertidal predators, such as dogwhelks (Nucella spp.)

(Crothers 1985, Burrows & Hughes 1991).

‘ 26

Our study highlights the importance of considering climate change effects on the

organismal level. Physiological thresholds that play a disproportionately large role in

determining species distribution may amplify the effect of small changes in temperature.

Looking at the community or ecosystem level may lead to broad assumptions that are

invalidated by the specific biology of the organisms in question. It is particularly

important to examine the larval stages of organisms because they are usually more

sensitive than adults, occupy very different environments than adults, and are necessary

for dispersal and population connectivity (Byrne 2011, 2012). Anthropogenic effects such

as climate change are often measured in terms of effects on adult populations (Thomas et

al. 2004), but it will be equally important for conservation scientists and managers to

consider factors of population persistence such as fecundity, recruitment, and

connectivity. Understanding the dynamics of these processes will be vital to the

conservation of all species that have a life history that couples planktonic and sessile

stages (Hughes et al. 2000). Overall, we find a need to increasingly incorporate natural

history and physiology into models forecasting distribution shifts as a result of climate

change. Understanding the interplay of complex physical and ecological processes will

allow conservation managers to predict and plan for changing biological communities.

‘ 27

Figures

Table 1.1 Sampling period by region for 2015 and 2016 (All dates are presented as Month/Day/Year).

Region Sampling Period Southwest England 5/16/2015 - 6/19/15 Wales 6/28/15 - 7/2/15 Scotland 7/3/15 - 7/13/15 Scotland 5/6/2016 - 5/10/16 Wales 5/11/16 - 5/16/16 Southwest England 5/17/2016 - 6/9/16 Wales 6/20/2016 - 6/22/16 Scotland 6/24/2016 - 6/27/16

‘ 28

Table 1.2 Summary statistics of salinity times series for all sites (All data are measured in ppt). Site Min Max Mean StD Ullapool 28.40 32.85 31.57 0.97 Glenbrittle 33.40 33.96 33.69 0.13 Great Cumbrae 25.89 32.34 29.94 1.63 St. Bees 30.76 32.14 31.43 0.33 Porth Trecastell 34.32 34.55 34.44 0.06 Borth 32.88 33.32 33.04 0.12 St. David's Head 34.43 34.58 34.51 0.03 Manorbier 32.72 33.72 33.27 0.22 Port Quin 34.53 34.90 34.76 0.09 Trevaunance 35.11 35.16 35.14 0.01 Portreath 35.08 35.17 35.15 0.01 Cape Cornwall 35.13 35.17 35.15 0.01 Michael's Mount 35.13 35.18 35.16 0.01 Poldhu 35.14 35.17 35.16 0.01 Kennick Sands 35.12 35.16 35.14 0.01 Maenporth 35.08 35.12 35.10 0.01 Hemmick Beach 35.02 35.10 35.06 0.02 Pendower 34.87 35.07 34.99 0.05 Whitsand Bay 34.78 35.01 34.90 0.07 Mothecomb 34.94 35.05 35.00 0.03 Maidencombe 34.82 34.98 34.92 0.04 Porthmeor NA NA NA NA Lansallos NA NA NA NA Wembury NA NA NA NA Hope Cove NA NA NA NA Dartmouth NA NA NA NA

‘ 29

Figure 1.1 Study region and sites on the west coast of the United Kingdom. Inset box: Sites in southwest England (Devon and Cornwall). The cities of Plymouth and Exeter are shown for reference. Designated sites are: GB = Glenbrittle, GC = Great Cumbrae, SB = St. Bees, PT = Porth Trecastell, BT = Borth, MB = Manorbier, WB = Whitsand Bay, MC = Maidencombe. SP designates the Start Point headland.

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‘ 31

Figure 1.3 Relationship between low tide CFSR air temperature and iButton temperature at Whitsand Bay. Red, solid line is line of best fit. Dashed, black line is a 1:1 line. Red line represents a line of best fit (Slope = 0.30604; R2 = 0.4222, F1,403 = 294.5, p < 0.0001). Dashed, black line is a 1:1 line.

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‘ 32

Figure 1.4 Relationship between combined SST and adjusted - air temperature and iButton temperature at Whitsand Bay. Red line represents line of best fit (Slope = 0.7982; R2 = 0.3763, F1, 698 = 421, p <0.0001). Dashed, black line is a 1:1 line.

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‘ 33

Figure 1.5 Cumulative days below 10oC using composite air and sea surface temperature across the latitudinal gradient of the study sites for both sample years. Red, dashed lines indicate the breaks between Category 1 (<four weeks), Category 2 (four to six weeks), and Category 3 (>six weeks).

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Figure 1.6 Number of days below 10oC using composite air and sea surface temperature during the embryonic brooding period using composite temperature vs. recruitment density of S. balanoides at all sites (mean ± standard error). Red, dashed lines indicate the breaks between Category 1 (<four weeks), Category 2 (four to six weeks), and Category 3 (>six weeks). A = St. Bees, B = Borth, C = Great Cumbrae (R2 = 0.4013, F 1,52 = 34.86, p < 0.0001).

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Figure 1.7 Early juvenile mortality of Semibalanus balanoides. Recruitment density sampled in May 2016 vs. recruitment density in June 2016. The Michaelis-Menten curve is shown with a red line and a 1:1 line is shown for comparison with a black, dashed line. Each data point is color-coded by latitude of the sample site.

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Figure 1.8 Log – transformed chlorophyll a concentration vs. recruitment density at each site (R2 = 0.016, F1,24 = 0.385, p = 0.541). GC = Great Cumbrae.

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CHAPTER 2:

REVISITING CONNELL: A CLASSIC COMPETITIVE SYSTEM LINKED TO

CLIMATE2

2 Maeve K. Snyder, David S. Wethey, Thomas J. Hilbish. To be submitted.

39

2.1 INTRODUCTION

Competition is a driving force of community structure across ecosystems (Connell

1961a, Dayton 1971, Menge 1976, Connell 1978). Competitive interactions are especially

well known in intertidal areas because organisms in these systems often occur in high

densities and are sessile or slow moving. For this reason, studies carried out in the

intertidal have had a large role in shaping theory around ecology and biodiversity at

several levels of organization. As previously shown, a physiological for recruitment

success is a useful predictor of population dynamics across a latitudinal gradient.

However, the degree to which patterns of recruitment are later modified is an important

consideration for forecasting population persistence and biogeographic changes. Post-

recruitment processes are highly consequential at the community and ecosystem level

(Findlay et al. 2010). Competition may be the most important determinant of community

structure in harsh environments, such as the intertidal, where abiotic conditions limit the

influence of predators (Menge & Sutherland 1987). Following the definition of Birch

1957, competition occurs when animals (of the same or of different species) utilize a

common resource, which is limited. Or if the resources are not in short supply, animals

seeking the resource nevertheless harm one another in the process (Birch 1957).

Barnacles have been tractable model organisms for several ecological questions

due to their sessile adult stage, small size, dense populations, and intertidal habitat

(Connell 1961, Wethey 1983, Leslie 2005, Jenkins et al. 2008). My thesis re-examines a

classic experimental demonstration of the potential for competition to restructure

communities, Joseph Connell’s 1961 study, “The Influence of Interspecific Competition

and Other Factors on the Distribution of the Barnacle, Chthamalus Stellatus”. In this

40

highly influential paper (as of November 2017: 2,057 citations on Google Scholar and

1,317 citations on Web of Science), Connell describes patterns of recruitment and

competition in two barnacles, Semibalanus balanoides and Chthamalus montagui, at an

intertidal site on the Isle of Great Cumbrae in the Firth of Clyde, Scotland. Connell 1961

demonstrated that both species of barnacles were able to settle through the intertidal zone.

However, through interference competition for space, SB was superior in smothering,

crushing, and undercutting CM and eventually eliminated this species from the mid-

intertidal. In the high intertidal, SB is unable to withstand the physical stress of

desiccation. Its absence creates a refuge for CM resulting in distinct bands of species

zonation in the mid- and high intertidal. The results of this study led to the development

of the fundamental and realized niche concept.

A limitation of Connell 1961, however, is that it represented a single geographic

snapshot of the latitudinal range across which these two species co-exist. Therefore, the

potential for latitudinally varying environmental factors to mediate this interaction was

not considered. Connell 1978 recorded an instance of marine sessile organisms reversing

competitive rankings and remarked, “climates do change gradually, which probably

results in changes in the competitive hierarchy” (p. 1309, Connell 1978). It has been

observed that the intensity of competitive interactions is mediated by physical conditions

that affect the dominant competitor (Wethey 1984). It is therefore important to

characterize the geographic range where a certain interaction can exert influence in a

community, as well as understanding the forces that determine its effect. Based on

observations of population abundances and percent cover in southwest England (within

the mid-intertidal zone where CM is expected to cede space to SB), we investigated the

41

possibility of competitive breakdown. Near its range limit in southwest England, we

hypothesize that the competitive advantage of SB is neutralized or even reversed.

In a similar experiment, Gordon & Knights 2017 examined differences in

mortality and growth rate in individual adult barnacles at two sites near Plymouth,

England. Their results indicated that initial size was an important predictor of competitive

outcome, and suggests that scope-for-growth is an important consideration when using

growth rate as a metric of competitive outcomes (Gordon & Knights 2017). My

experiment expanded this analysis by examining growth and mortality at more sites,

across a latitudinal range, and, importantly, in newly recruited barnacles. We expected

that the majority of consequential interference competition would occur during the

recruitment period, when the greatest amount of growth is occurring.

Investigating the interplay of climate and competition necessitates carrying out

studies across environmental gradients. Patterns of competition need to be repeatedly

investigated under a variety of conditions to fully understand the drivers and

consequences of struggling for limited resources. Connell himself recognized the

importance of repeated studies of field experiments of competition: “Probably the most

direct way to decide how the occurrence or strength of competition varies is to repeat the

field experiment on the same species at a different time or place.” (Connell 1983).

Temporal and spatial variability in competition could have important consequences for

biogeography and ecosystem functioning, and it is problematic to generalize

geographically limited studies of competition across the full extent of a species

distribution. Interspecific competition may not take place at all times or in all locations

between two co-occurring species (Menge 1976). Determining the variables that govern

42

competitive interactions allows for predictions of population and community dynamics.

One of the most tractable approaches to such questions is to search for correlations in

competitive outcomes and environmental conditions.

To identify interspecific competition, there needs to be a significant, reciprocal

response of Species A to a change in density of Species B (Connell 1983). If reducing

density of SB in southwest England did not lead to a change in CM, then we would

conclude that competition is not occurring there. Investigation of competitive interactions

requires researchers to identify the limiting resource for a population as well as a

mechanism for differential capability in exploiting the resource (Underwood 1978).

Wiens 1977 discusses a number of limitations and challenges associated with field

experiments of competition theory. In particular, it is rarely established that the resource

in question is the only or most important limiting factor and that observed differences

between species are related directly or solely to the limiting resource. For intertidal

ecosystems, it is well-established that organisms are predominantly constrained by the

same limiting resource, space (Underwood 1978) Competition may occur through a wide

variety of mechanisms. The means of competition between SB and CM most likely

include one or more of the following descriptions (modified from Schoener 1983):

1) Consumptive competition - some quantity of the limiting resource is consumed or

used up by an individual, prohibiting its use by other individuals.

2) Preemptive competition - space is passively occupied by an organism, causing

other individuals to be unable to occupy that space before it is cleared. This style

of competition occurs most frequently in sessile organisms, like barnacles.

43

3) Overgrowth competition – this is the method of competition described in Connell

1961. It occurs when an individual or individuals grow over, crush, or smother

another individual, which may deprive it of some necessary resource (e.g. light,

food, etc.) or may directly injure or kill the organism.

In order to investigate the ability of temperature to mediate competitive outcomes

across a latitudinal gradient, it was necessary to consider all three potential mechanisms

of competition as potentially consequential for community structure patterns. Therefore,

for our investigation of competitive breakdown at the southern range limit of SB, we

proposed the following mechanistic hypotheses:

1. Differential growth rate due to temperature: At colder latitudes, SB grows faster

and can overgrow or crush neighbouring CM (Connell 1961). It is possible that at

more southern latitudes these rates of growth are reversed and CM can out-grow

and competitively displace SB.

2. Competitive swamping: Reproduction is temperature-dependent in SB (Rognstad

& Hilbish 2014, Rognstad et al. 2014) and larval output is greater in northern

locations than in the south (Snyder et al. in prep.). SB may smother CM with

newly settled larvae (Connell 1961). We observed that smothering is common in

the north but rare in the south. At warmer temperatures in the south SB may not

be able to produce enough larvae to smother CM. Deprived of this mechanism of

competition, SB may no longer be able to out-compete CM at southern locations.

44

3. Space pre-emption: It is possible that if they grow to a sufficient size, adult CM

cannot be displaced by juvenile SB. As a consequence of the latitudinal

differences in reproductive output CM may recruit to open sites more rapidly and

have more time to grow into adults at southern latitudes than in the north.

4. Non-competitive population turnover: It is possible that competition does not play

a significant role in the dominance of CM at southern locations. Both species may

be continuously removed by predation or some other disturbance and CM

eventually occupies open space through its greater reproductive output over SB.

Despite this complexity, it is important to consider mediating effects of climate on

drivers of community structure. If the relationship described in Connell 1961, a textbook

ecological principle, is modified by climatic variables, it suggests that climate disruptions

may be more extensive and difficult to predict than our current approaches can manage.

Refining our knowledge of ecology with climate effects will help improve resilience of

human society, especially industries that rely on natural resources, through improving

decision-making capabilities and promoting a conceptual understanding of organisms as

part of connected systems.

2.2 METHODS

Basis of Competitive Breakdown

To establish a quantitative basis for the observation that competitive exclusion of

CM in the mid-intertidal does not occur in southwest England, a percent cover analysis of

45

the control subquadrats was conducted across the latitudinal gradient (approximately 51

to 58 degrees North) using photos from spring 2015. Percent cover was estimated using

the open source software Image J (Abramoff et al. 2004). The edge of the square quadrat

frame was used to calibrate the ImageJ measurement tool. A grid of dots was placed over

the image of the control subquadrat. Spacing of dots was determined by measuring the

largest barnacle within the control (approximated by eye). The width of this barnacle was

used to set the spacing, so that no barnacle could have two dots fall on it. Each dot was

then assigned to one of the following categories: 1) Open Space 2) SB 3) CM 4) Other

(A. modestus, mussel, algae, etc.)

Experimental Design and Treatments

Five quadrats per site were established at the mid-intertidal level (the same

quadrats used to analyze recruitment densities). The mid-intertidal level is known for

having the strongest influence of interspecific competition (Menge 1976). Experimental

treatments were applied within subquadrat areas of each quadrat (Table …X) Scrapes

were created to allow de novo measurement of recruitment densities, as well as for

controlling pre-emptive settlement of certain species. This is an important consideration

since competitive ability may be size and age specific, rather than species specific

(Connell 1978). Since SB recruits in spring and CM recruits in fall, the timing of a

scrape determines which species will have first access to the cleared space and allows the

testing of the space pre-emption hypothesis as a mechanism of competition. Selective

removal of SB, simulating a year in which SB failed to recruit across all latitudes, also

tested this hypothesis. In this treatment, SB were thinned by using a needle to selectively

46

kill individuals (all individuals present were killed, but some may have re-colonized in

the period following the treatment, hence thinned). The shells of barnacles that are dead

will usually persist on a rock surface for a few days, but will eventually be removed

through wave action or the growth of adjacent barnacles (pers. obs.). Controls were

established concurrently to experimental treatments when quadrats were created so that

they experienced the same environmental conditions as experimental treatments. Controls

were never manipulated in any way.

Percent Cover Analysis of Simulated Recruitment Failure

With the same methods used to analyze percent cover in the control subquadrat,

an analysis of subquadrats 2 and 3 was conducted using photographs from spring 2016.

This analysis served as a preliminary investigation into patterns of space occupation

when CM is reprieved of competition with SB for 1.5 years. In this investigation,

subquadrat 2 served as a control for comparison against the experimental removal of SB

in subquadrat 3.

Image Analysis for Growth Rate and Mortality

Images were analyzed using the open source software Image J (Abramoff et al.

2004). The edge of the square quadrat frame was used to calibrate the ImageJ

measurement tool. The metrics of mortality and growth rate were measured over a one-

year period, from 2015 to 2016. Measurements were taken from barnacles in subquadrats

2 and 3. Since both of these subquadrats were scraped in spring of 2014, C. montagui

settled preemptively into these spaces in fall of 2014. SB then settled in spring of 2015.

47

Therefore, measurements collected in spring 2015 represent 0.5-year-old individuals of

CM and newly recruited SB.

Barnacles were sorted into nine groupings based on growing in situations of

isolation, intraspecific competition, and interspecific competition, at the level of the

individual (Figure 2.1). Since groupings were encountered based on recruitment into the

cleared spaces, not all groupings were present in all quadrats or all sites. A power

analysis was conducted, which showed that approximately 26 individual barnacles

needed to be sampled per quadrat. While this was not possible at every site, there were

sufficient populations across regions to analyze samples from the entire latitudinal range.

Therefore, barnacles were identified and measured from photographs taken at four sites

in spring 2015. The same quadrats were then analyzed from photographs in spring 2016.

If an individual barnacle could not be re-located, it would be marked as deceased. When

a barnacle could be found, opercular length was measured to obtain estimates of growth

rate. All newly recruited barnacles were identified based on plate number and shape as

described by Drévès (2001). Individuals of S. balanoides could be confidently

differentiated from other common intertidal species in the region, including Chthamalus

stellatus, C. montagui, and Austrominius (=Elminius) modestus (Southward 1976).

Competition is often studied in field experiments by changing the densities of

competitors and measuring their response (Connell 1983, Gordon & Knights 2017).

Response may be measured in a number of ways. This analysis examined both growth

rate and mortality. These two response variables were selected to be useful in comparing

across latitude (since temperature varies at this scale) and to test the hypotheses of

competitive mechanism. Mortality was measured in two ways: 1) Change in density over

48

time 2) Individuals were assigned a binary code (0 for dead or 1 for alive) and proportion

of surviving individuals was measured from one year to the next. Barnacles were

identified as dead by the absence of opercular plates. Mortality is a useful measure of

ultimate trends, which are consequential for community structure. Growth rate allowed

the testing of the differential growth rate hypothesis as a mechanism of competition.

Growth rate was measured using opercular length (Wethey 1983, Jenkins et al. 2008,

Gordon & Knights 2017). This measurement is better than basal plate length, which is

highly plastic in response to the rock and other organisms it is in contact with. Opercular

growth rate was measured as initial length – final length.

Statistical Analysis

The results to be presented are preliminary patterns across latitude and will be

expanded with subsequent analysis of all available data. To ensure sufficient statistical

power for these preliminary analyses, all interspecific groupings (5, 6, and 7) and all

intraspecific groupings (3, 4, 8, and 9) were categorized together, forming three

groupings: “alone”, “interspecific”, and “intraspecific.” Data were collected at two sites

in southwest England, one site in Wales, and one site in Scotland. Mortality data were

analyzed with a binomial generalized linear model (GLM). Growth rate was analyzed

with a linear model and ANOVA.

49

2.3 RESULTS

Basis of Competitive Breakdown

We found that in the control subquadrat, there is considerable variation in

proportional occupancy of mid-intertidal space across latitudes (figure 2.2) Percent cover

data show that both species are present throughout the entire sample region (although not

at all sites sampled). Looking at the transition in dominance between SB and CM

specifically (figure 2.2) shows that CM never outnumbers SB in reciprocal densities of

the sort that occur in Scotland - including the Isle of Great Cumbrae, the research site for

Connell 1961. The transition to mid-intertidal dominance seems to occur around site 18,

which corresponds to the transition between southwest England and Wales. In southwest

England, SB fails to competitively exclude CM and they occur in relatively equal

proportions.

Percent Cover Analysis of Simulated Recruitment Failure

The results of a year of simulated SB recruitment failure showed little difference

in the percent cover of the two experimental treatments (with and without SB). Across

latitude, the average proportional cover of each site is roughly the same regardless of

whether SB was allowed to recruit into cleared space or not (figure 2.3).

Mortality

There was enormous variability in the mortality of barnacles growing in isolation,

across latitudes (figure 2.4). Still, at lower latitudes CM has far higher survivorship

(almost all CM individuals survived) than SB (~25% of individuals survive) from 2015 –

50

2016. Survivorship of CM decreases with latitude while survivorship of SB appears to

increase, but with high variability for both species. Confidence intervals for both species

overlap indicating that the data do not support the likelihood of a difference between

mortality of SB and CM growing at high latitudes.

For SB and CM growing in interspecific groupings, patterns of mortality were

more distinct. CM again had higher survivorship and declining survivorship with latitude.

Although it is hard to draw conclusions about patterns with such broad confidence

intervals, averaged mortality at high latitudes was higher for CM in interspecific growing

in interspecific treatments as opposed to isolated individuals, indicating a negative

consequence for CM growing in contact with SB. One of the reasons for the wide

confidence intervals for individuals in isolation is that there is little open space at

northern latitudes and there was a smaller sample size for isolated individuals. In contrast

to SB individuals growing in isolation, SB growing in interspecific treatments showed

decreasing mortality with increasing latitude.

Growth Rate

For barnacles growing in both isolation and interspecific competition treatments,

SB has a much higher growth rate than CM (Figure 2.5). There was no effect of latitude

on growth rate of SB growing in isolation, which stayed constant at ~0.13 cm per year.

For interspecific treatments, however, SB had a lower growth rate overall, with rate

increasing with latitude. SB growth rate seems to be inhibited by interspecific

competition, but is recovered to its isolation level growth rates at the northernmost

latitudes of our study region. Growth rate of CM showed a negative relationship with

51

latitude in both isolation and interspecific competitions. There was no effect of

competitive grouping on CM growth rate.

2.4 DISCUSSION

The results of the percent cover analysis of control subquadrats supported the

personal observations of competitive breakdown across latitude. In the mid intertidal

zone where the expectation based on a known competitive hierarchy would have been the

exclusion of CM, we quantitatively demonstrated SB exists in relatively equal

proportions with CM in southwest England. Although a percent cover analysis is not a

rigorous way to investigate mechanisms of competition, our result suggests that space

preemption is not an influential mechanism relative to competition outcomes, at least for

CM, which is the species that received a preemption advantage in this experiment. While

not identical, there is no apparent shift in the overall pattern between treatments. Wiens

(1977) has proposed that competition might occur only when resources are scarce. I.e. in

southwest England competition is a non-issue. I can test this hypothesis by considering

competition at the level of the individual. However, it appears that at the population scale

it is effectively true that competition is not occurring due to an excess of space.

Comparing the percent cover results of the simulated recruitment failure

treatments to percent cover of control subquadrats shows an interesting pattern. It appears

that in southwest England, SB will eventually come to occupy more space than initially

suggested by the recruitment failure analyses, which are based on patterns of recruitment.

Recruitment lays out patterns of space occupation that are later modified with growth and

competition. It is unclear from this data to what extent growth and competition are

52

important in this shift, but it does show that occupation of space for SB is not reduced

following recruitment.

Declining survivorship of CM with increasing latitude supports the expectation

that SB should come to dominate the mid-intertidal at these latitudes. Furthermore, it

shows that densities of CM at northern latitudes is not the result of patterns of

recruitment. Some mechanism (environmental or biotic interaction) is resulting in greater

mortality in these locations. In southwest England, this mechanism seems to be lost

resulting in near 100% survivorship. This is consistent with the findings of Hyder et al.

2001.

SB survivorship declines with latitude in interspecific groupings. This result is

most likely misleading, in that it seems to indicate that SB are losers in competitive

contests with CM. This result is almost certainly an artifact of the fact that recruitment

supplies sites at northern latitudes with far more SB larvae than can ultimately grow to

occupy the available space, resulting in intense intraspecific competition and density

dependent mortality (figure 2.4). SB still comes to occupy the majority of space in the

mid-intertidal at higher latitudes (figure 2.2), so it remains to be seen if part of this

pattern is a mechanism of competition that varies with latitude.

Furthermore, SB survivorship is far lower in southwest England when growing in

isolation compared to interspecific treatments. This was a somewhat surprising result,

since we expected that having ample space for growth would be advantageous across

latitude. However, it may be that in southwest England, the stresses of environmental

variables may outweigh negative consequences of growing in interspecific competitive

groupings. There may be a positive effect of being in a competitive grouping in

53

southwest England, through creating a moist microclimate that shelters SB from a known

cause of mortality – desiccation. This has been observed in populations of SB in North

America (Bertness 1989).

SB had a higher growth rate regardless of competitive grouping. Part of this result

may be that we compared photographs from spring 2015 to spring 2016, the recruitment

season for SB. Therefore, CM may have had a lower scope-for-growth than SB. This

could be remedied by examining photographs from fall 2015 to spring 2016 to see if

newly recruited CM have a comparable growth rate in the early months following

recruitment. CM showed no effect of competitive grouping on growth rate. SB, however,

had a depressed growth rate in interspecific competition, that was at its lowest in

southwest England. This supports our hypothesis of differential growth rate across

latitude. SB is growing slowest in the region where it has been observed to lose its ability

to competitive exclude CM. There is no effect of latitude for SB growing in isolation,

however.

The possibility of non-competitive population turnover as an explanation for our

observations of patterns of abundance, presents a confounding factor in testing other

hypotheses of competitive mechanisms. Although these are numerous, we hypothesize

that two of the most important variables acting on these species were predation and

desiccation. In the UK, a main predator of barnacle populations in the intertidal is

Nucella lapillus, known as dog-whelks. Dog-whelks are direct developing gastropods that

are known to prey on a variety of species, but preferentially consume S. balanoides and

mussels (Mytilus edulis) (Crothers 1985). Predation has been proposed as the single most

important determinant of biodiversity and community structure in several ecosystems.

54

The relative importance of competition and predation at different trophic levels to

determining community structure remains a tug of war in ecological theory (Paine 1971,

Menge & Sutherland 1976).

Because barnacles occupy a relatively intermediate trophic level, predation and

competition may play a relatively equal role in structuring their communities (Menge &

Sutherland 1976). It should also be noted that when environmental conditions are severe

enough, intertidal communities may be released from biological stresses from mobile

predators and competitors, and become composed entirely of organisms capable of

withstanding mechanical stresses (Menge & Sutherland 1987). The relative influence of

competition, predation, and physical stress shifts with several variables that may

characterize any one site. An experiment was carried out to provide proof of concept and

preliminary data to investigate effects of predation and desiccation. Overall, this

experiment represents only a limited view of how these factors affect populations of SB

and CM because the intensity of predation and desiccation certainly vary across our

entire study region. Furthermore, these two effects (predation and desiccation) are likely

to have a significant interaction. For example, Menge & Sutherland 1976 found that

shaded sites in their experiment of had increased predation of SB by Thais snails, most

likely due to the mobile predators seeking moist refuges during low tide. An alternative

hypothesis about the influence of predators is presented in Paine 1971 – in which

predators preferentially prey on a dominant competitor. This would seem to be the case

for our system where Nucella preferentially consumes SB over CM. However, there is no

evidence that they are the preferred prey because they are the dominant competitor and

not some other aspect of their biology. Understanding the interplay between competition

55

and predation will be important for making predictions about how these communities will

respond to climate change. Ecological processes rarely act in isolation and it is prudent to

avoid testing hypotheses that assume only one variable is responsible for an observation

(Quinn & Dunham 1983, Connell 1983).

Recruitment may have played a role in creating these patterns of competition. The

magnitude of recruitment is known to be influential on other ecological processes that

influence community structure – environmental conditions, predation, and competition

(Menge & Sutherland 1987, Hyder et al. 2001, Svensson et al. 2006). For example, we

have observed that barnacles may or may not recruit in sufficient densities to create a

moist microclimate through the complex topography of their shells, and suffer

desiccation mortality as a consequence. Furthermore, higher recruitment densities may

create a foraging landscape that benefits mobile predators, such as Nucella spp. It has

been suggested that competition may only be an important driver of community structure

when populations are near their carrying capacity (Menge & Sutherland 1976,

Underwood & Keough 2001). Low recruitment densities at warmer sites, due to a

physiological mechanism for embryo brooding, may therefore interfere with the

possibility for recruitment-dependent mechanisms of competition to act in ways that are

consequential to community structure. In that scenario, SB may be at a greater

disadvantage at its range limit in southwest England population predictions based on

thermal tolerances of adults or embryos may suggest.

There are, however, a number of ecological processes that have not been

controlled in our experiments and may be exerting meaningful influence. Disturbances

are known to play a role in structuring intertidal communities (Dayton 1971, Connell

56

1978, Menge & Sutherland 1987) and may interrupt competition and preserve diversity.

While we have made no observations to suggest this is the case, we have not measured

variability in disturbances across our sites, we are confident this does not explain our

results. Many varieties of disturbance (especially mechanical removal by waves and

rocks) would be expected to affect SB and CM equally. Additionally, our study has

focused on temperature as an environmental stressor, but such stressors do not occur in

isolation. An additional variable that was of interest when considering multiple stressors

that act on this competition system was ocean acidification. Findlay et al. 2010 discusses

findings that indicate ocean acidification could negatively affect population dynamics of

SB at its southern range limit and accelerate local extinction in this region. The interplay

of these effects with competitive outcomes would be an interesting avenue for further

research.

It is also important to consider evolutionary processes across a species range.

Organisms typically occur at reduced densities at range edges compared to within the

core of a range (Weiss-Lehman et al. 2017). Therefore, selection pressures may favor

traits that confer an advantage in these different density environments. Differing selective

forces (challenging environmental variables, decreased probability of finding a mate,

different foraging landscape) at range edges may force trait trade-offs that lower

competitive ability (Weiss-Lehman et al. 2017). Ecological processes at range limits may

prove difficult to study because of the stochastic evolutionary processes that act on these

populations. The majority of studies of eco-evolutionary feedbacks have focused on

expanding range edges, neglecting empirical studies of these effects at contracting edges

(Bridle & Vine 2006, Burton et al. 2010, Hargreaves & Eckert 2014, Fronhofer &

57

Altermatt 2015). Continuing work on this aspect of biogeography will be important for

future studies but is not addressed in this experiment.

Measuring the influence of interspecific competition in determining distribution,

abundance, and resource use of species in communities is a challenge due to the number

of other factors that can play a role, such as symbioses, abiotic factors, disturbances, etc.

One limitation of our experimental approach is that we were only able to manipulate

densities below the levels in which they were naturally occurring in the sample sites.

However, the densities we encountered during the time period of the experiments was not

reflective of the full range of population densities that have been known to occur at these

locations. Another uncontrolled variable in our experiment was how sheltered vs. high

energy shorelines affect predation, competition, and ultimately community structure

(Menge & Sutherland 1987). We have not measured the degree of mechanical stress

occurring across sample sites.

As it has been noted before in other systems (Connell 1983, Woodin et al. 2013),

it is limiting to measure ecological processes in only one point in space and time. More to

the point, it is misleading to draw general conclusions about community dynamics from

any such case study of competition. This reassessment of Connell 1961 prompts the

question of how many foundational concepts of ecology are less widely applicable than

thought, due to interplay with physical characteristics with biotic interactions. Climate

variability and frequency and amplitude of extreme events are important aspects of

climate change (Thompson et al. 2013). This result further muddies the waters of

predicting how species and ecosystems may respond to rapid environmental change as a

result of climate change. However, it is likely that predictions founded on assumptions

58

that the interactions within ecosystems (competition or otherwise) will remain stable

through rapid environmental changes, are inaccurate. There is a need for increased study

of ecological interactions across physical and latitudinal gradients and how

environmental variables interact with trait – mediated effects (Woodin et al. 2013).

Competition is a crucial ecological consideration in this regard because it has been

implicated in the creation or maintenance of biodiversity (Pianka 1966, Menge &

Sutherland 1976, Underwood 1978, Connell 1978, Lubchenco 1978, Underwood 1978).

Through competition, the rocky intertidal of the UK is highly structured and allows the

coexistence of SB and CM. Changes in competitive hierarchies due to climate could flip

community dynamics from coexistence to competitive exclusion, leading to local

extinctions.

Overall, our results suggest an accelerated pace of range contraction for SB.

Through an interaction modification (Wootton 1993), SB has lost the competitive edge

that promotes its presence in the mid-intertidal at colder latitudes. Range contraction of

boreal species is likely to be a consistent pattern in marine environments. For industries

that depend on natural resources, it is crucial to be able to predict where organisms will

occur in the future. Besides helping society predict and adapt to changes in the

distributions of commercially important species, building models to incorporate climate-

mediated processes such as recruitment and competition will lead breakthroughs in

understanding of evolution and ecology. Applying paleoclimate data may provide

insights into ecological processes throughout geologic time and shed light on

evolutionary history. Furthermore, these results reinforce the complexity of ecological

processes and the need to conduct experiments across a range of spatial and temporal

59

scales. Ecologists should be circumspect in the broad application of ecological theory,

such as outlined in Connell’s iconic 1961 experiment, particularly in the face of changing

climate

Climate envelope models have been a standard approach to forecasting

biogeographic responses to climate change (Pearson & Dawson 2004, Araújo & Guisan

2006, Helmuth et al. 2006, Poloczanska et al. 2008, Woodin et al. 2013). However, they

have several limitations, such as a failure to consider physiologically sensitive stages

across the life span of an organism, dispersal abilities, direct- and in-direct effects of

species interactions, and the mediating effects of physical conditions on those

interactions. Failing to incorporate details of natural history and organismal biology often

limits the broad scale predictive power of ecological theory (Tewksbury et al. 2014).

Models that include mechanistic predictors incorporating physiologically sensitive life

history stages and trait-mediated ecological processes are likely to improve forecasting of

biogeographic response to climate change (Wethey et al. 2011, Wethey & Woodin 2008).

60

Table 2.1 Subquadrats and corresponding experimental treatments.

Subquadrat Number Treatment

1 Control. Unmanipulated.

2 Scraped spring 2014. All species recolonize.

3 Scraped spring 2014. S. balanoides selectively removed to simulate a year of recruitment failure.

4 Scraped spring 2015. All species recolonize.

5 Scraped fall 2015. All species recolonize.

6 Scraped spring 2016. All species recolonize.

Figure 2.1 Experimental groupings for measurements of mortality and growth rate.

61

62

Figure 2.2 Average proportional cover of SB and CM across sites. Sites 1 – 18 are southwest England. Sites 18 – 23 are Wales. Sites 23 – 28 are Scotland.

Figure 2.3 Percent cover analysis of simulated SB recruitment failure.

63

Figure 2.4 Mortality (mean ± standard error) of SB and CM across latitude in isolation and interspecific groupings. Shown with 95% confidence intervals.

SpeciesChthamalusSemibalanus

50.0 52.5 55.0 57.5 60.0

0.25

0.50

0.75

1.00

Latitude

Perc

ent S

urvi

val

SpeciesChthamalusSemibalanus

50.0 52.5 55.0 57.5 60.0

0.25

0.50

0.75

1.00

Latitude

Perc

ent S

urvi

val

SpeCS

Alone Interspecific

64

Figure 2.5 Growth rate (mean ± standard error) of SB and CM across latitude in isolation and interspecific groupings. Shown with 95% confidence intervals.

SpeciesChthamalusSemibalanus

Alone Interspecific

50.0 52.5 55.0 57.5 60.00.00

0.05

0.10

0.15

Latitude

Gro

wth

Rat

e (c

m p

er y

ear)

SpeciesChthamalusSemibalanus

50.0 52.5 55.0 57.5 60.00.00

0.05

0.10

0.15

Latitude

Gro

wth

Rat

e (c

m p

er y

ear)

SpecieChthSem

65

66

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