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Climate change impacts on the kelp life history cycle Hoos, Jennifer Piper Jorve 2015

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  Climate change impacts on the kelp life history cycle  by  Jennifer Piper Jorve Hoos  B.A., Willamette University 2002 M.Sc., San Jose State University, Moss Landing Marine Laboratories 2008     A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY  in  The Faculty of Graduate and Postdoctoral Studies  (Zoology)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  February 2015  © Jennifer Piper Jorve Hoos 2015  ii  Abstract  Anthropogenic climate change will cause changes to the abundance, distribution, and survival of species in ecosystems worldwide. Kelps are foundation species that form the structure of temperate, marine ecosystems on coastlines worldwide. Kelps support highly productive communities that are ecologically and economically valuable, but are susceptible to the increases in environmental stressors associated with climate change. This susceptibility varies with life history stage, with macroscopic stages less sensitive to environmental stress than microscopic stages. I addressed the effects of climate change on the different life history stages of intertidal kelp from rocky shores on the Pacific coast of North America. I began with two studies on the interactive effects of multiple climate stressors on microscopic stages of kelp. Increasing temperature, CO2, and UV caused mechanical and functional damage to zoospores during their motile phase, and caused further reductions in settlement, germination, and adhesion of the initial sessile phase of the life history cycle. Settlement style was also affected, with decreased time spent looking for suitable attachment locations and microenvironments, and overdispersion of spore settlement distribution, which has been shown to decrease fertilization rates and sporophyte abundance.  In my final research chapter, I describe the effects of increases in frequency of extreme warming events on macroscopic juvenile and adult kelp sporophytes. I also manipulated adult density in situ to determine the stress ameliorating affect of neighbor proximity on both juvenile recruitment and seasonal adult growth along a vertical tidal gradient. Extreme warming treatments reduced recruitment and seasonal growth of adults in the upper shore when adult density was low and environmental stressors were not mitigated by neighboring individuals. All other treatment combinations showed slightly positive effects of warming on recruitment and adult size. I predict that the aforementioned population effects resulting from increases in frequency of extreme warming events will cause an overall reduction in this species’ habitable vertical space in the intertidal zone. The combined impacts of overall reductions in microscopic life history stages with decreasing recruitment and habitable space for the macroscopic life history stage indicate overall reductions in  iii abundance of future populations of intertidal kelp species. iv  Preface  Some of the work included in this dissertation has been submitted for publication to a peer-reviewed scientific journal: Chapters 2 and 3 had very similar experimental laboratory design, which I planned and developed. In Chapter 2 I conducted the collections, performed the laboratory experiments while supervising undergraduate help, analyzed all data, and wrote the manuscript. Chris Harley was the supervisory author on this project and was involved in experimental design and manuscript edits. In Chapter 3 I designed the experiment, conducted the collections, performed the laboratory experiments while supervising undergraduate help, analyzed all data, and wrote the manuscript. Patrick Martone and Chris Harley were the supervisory authors on this project, and were involved in statistical analyses and manuscript edits. In Chapter 4 I designed the experiment, conducted all field work, data analyses, and wrote the manuscript. Chris Harley was the supervisory author on this project and was involved in statistical analyses and manuscript edits.    v  Table of contents   Abstract.......................................................................................................................................... ii	  Preface........................................................................................................................................... iv	  Table of contents ........................................................................................................................... v	  List of tables................................................................................................................................. vii	  List of figures.............................................................................................................................. viii	  Chapter 1	   Introduction.............................................................................................................. 1	  1.1	   Background ......................................................................................................................................1	  1.2	   Dissertation overview ......................................................................................................................8	  Chapter 2	   Multiple interacting climate stressors impact zoospore motility and pre-settlement behaviors ................................................................................................................... 10	  2.1	   Synopsis .........................................................................................................................................10	  2.2	   Introduction....................................................................................................................................11	  2.3	   Methods..........................................................................................................................................14	  2.4	   Results ............................................................................................................................................18	  2.5	   Discussion ......................................................................................................................................26	  Chapter 3	   The interactive effects of temperature, CO2, and UV radiation on kelp zoospore settlement, adhesion, and germination ..................................................................... 32	  3.1	   Synopsis .........................................................................................................................................32	  3.2	   Introduction....................................................................................................................................33	  3.3	   Methods..........................................................................................................................................35	  3.4	   Results ............................................................................................................................................39	  3.5	   Discussion ......................................................................................................................................45	  Chapter 4	   Spatial variation in the sign and magnitude of experimental warming effects on juvenile and adult kelp .............................................................................................. 49	  4.1	   Synopsis .........................................................................................................................................49	  4.2	   Introduction....................................................................................................................................49	  4.3	   Methods..........................................................................................................................................51	  4.4	   Results ............................................................................................................................................56	  4.5	   Discussion ......................................................................................................................................63	  Chapter 5	   Concluding remarks .............................................................................................. 67	  5.1	   Synopsis .........................................................................................................................................67	   vi 5.2	   Temperature and the life history cycle...........................................................................................68	  5.3	   Functional and behavioral changes following UV exposure .........................................................69	  5.4	   Kelp population predictions, and multiple, interacting climate stressors ......................................70	  5.5	   Limitations of methodologies ........................................................................................................71	  5.6	   Suggestions and conclusions..........................................................................................................73	  Bibliography ................................................................................................................................ 76	    vii  List of tables  2.1 Average experimental treatment conditions………………………………………. 18 2.2 Speed swimming style ANOVA table…………………………………………….. 19 2.3 Rate of change of direction over speed swimming style ANOVA table.…………. 21 2.4 Proportion of motile spores ANOVA table……………………………………….. 21 2.5 Proportion of motile spores exhibiting wobbling behavior ANOVA table 23 2.6 Proportion of motile spores exhibiting straight path behavior ANOVA table……. 24 2.7 Proportion of motile spores exhibiting search circle behavior ANOVA table……. 24 2.8 Proportion of motile spores orienting and gyrating ANOVA table………………. 25    3.1 Pre flume proportion of germinated spores ANOVA table……………………….. 40 3.2 Aggregation index (Im) ANOVA table………………............................................. 42 3.3 Post flume retention of settled spores ANCOVA table…………………………… 43 3.4 Post flume retention of germinated spores ANCOVA table…………………….... 45    4.1 Treatment plot tidal heights…………...................................................................... 54 4.2 Average iButton temperatures….............................................................................. 57 4.3 Change in juvenile kelp recruitment ANOVA tables (a, b)………………………. 58 4.4 Average distance of juvenile recruits from plot center…………………………… 60 4.5 Change in average number of blades ANOVA table……………………………... 60 4.6 Change in adult canopy cover ANOVA table…………………………………….. 60 4.7 Average number of Katharina tunicata ANOVA table…………………………... 62 4.8 Change in Katharina tunicata ANOVA table…………………………………….. 62 4.9 Recruitment surface homogeneity MANOVA tables (a, b)………………………. 64  viii  List of figures  1.1 The kelp life history cycle………………………………………………………… 7    2.1 Treatment effects on speed and rate of change of direction swimming styles……. 20 2.2 Treatment effects on spore motility and functionality (a, b)……………………… 22 2.3 UV effects on pre-settlement behaviors…………………………………………... 26    3.1 Temperature, CO2, and UV effects on initial proportions of germinated spores…. 41 3.2 Temperature, CO2, and UV effects on the aggregation index (Im)………………... 42 3.3 Temperature and UV effects on adhesion of settled spores………………………. 44 3.4 Temperature effects on adhesion of germinated spores…………………………... 45    4.1 Daily maximum air temperatures in Port Renfrew in Summer 2010……………... 53 4.2 S. sessilis recruitment variability along a tidal gradient and among treatments…... 59 4.3 Warming and adult density effects on adult S. sessilis……………………………. 61 4.4 Warming and adult density effects on Katharina tunicata abundance…………… 63  1 Chapter 1 Introduction 1.1 Background Anthropogenic climate change is a major threat to present-day organisms, populations, communities, and ecosystems worldwide (Walther et al., 2002; Harley et al., 2006; Parmesan, 2006). Scientists have described the current crisis as the next mass extinction event (Mayhew et al., 2008; Bellard et al., 2012) and a threat to global biodiversity (Halpern et al., 2008). Changes in species abundance, distribution, phenology, and species interactions, as well as local extinctions, have been noted for marine, terrestrial, and freshwater taxa (Parmesan, 2006). Due to ever-rising levels of atmospheric greenhouse gases, these trends are predicted to continue through the end of the century (Bellard et al., 2012). Greenhouse gases reflect heat into and away from the earth’s atmosphere, and changes in greenhouse gas concentrations over time contribute to warming or cooling of the global climate. Since the industrial revolution, continual emissions of greenhouse gases, including carbon dioxide (CO2), methane, and ozone, have increased atmospheric concentrations, some to the highest levels in at least the last 800,000 years (i.e. CO2, IPCC, 2013). Over the last 150 years, global average temperatures have risen 0.85 degrees from 1880-2012 (IPCC, 2013), a rate unprecedented over millennial time scales. Because of climate warming, snow and ice have melted and sea level has risen (IPCC, 2013). A suite of other factors associated with global climate change will likely affect marine climate conditions this century, including decreased surface albedo and oceanic salinity due to snow and ice melt, changes in cloud cover due to ocean warming and therefore solar radiation incident at the ocean’s surface, altered oceanic upwelling and circulation regimes, increasing storm frequencies and extreme warming events, alterations to the deep sea conveyer belt, and ocean acidification (for review, see IPCC, 2013).  The ocean is the single largest sink of excess energy associated with global change, with 30% of anthropogenic emitted carbon dioxide and 90% of excess heat energy stored in the surface ocean. Marine ecosystems have already experienced shifts in their environment, which will continue if greenhouse gas emissions continue unabated (IPCC, 2013). Since its  2 inception, research in the field of ecology has focused on explaining how organisms are affected by their surrounding environment. Interactions between organisms and the physical, chemical, and biological environment dictate their success, distribution, and persistence in space and time. Physiological stressors, such as changes in temperature, ocean chemistry, and the light environment affect organismal performance, which in turn can affect change in growth, reproduction, and survival (Bartsch et al., 2008; Angiletta, 2009; Kroeker et al. 2013). However, change in response to climate conditions is not simply negative or positive, so accurately understanding how future change in physical and chemical conditions in an organisms environment affect performance is important in predicting species persistence and overall ecosystem function.  Ocean acidification may be of particular importance to marine organisms. The term “ocean acidification” describes the changes in the oceanic inorganic carbon system due to increases in atmospheric CO2 concentrations (Doney et al., 2009). Surface oceans are equilibrated with atmospheric concentrations of CO2, and the influx of carbon decreases ocean pH via a series of reactions that balance this carbon input. CO2 reacts with water to form carbonic acid, which eventually dissociates into HCO3- (bicarbonate) molecules and H+ ions. The increase in H+ ions is what decreases oceanic pH. The buffering of pH is achieved by the binding of free H+ ions by CO32- (carbonate) ions. The predominant carbonate-containing material in the ocean is calcium carbonate, which is found in the shells and tests of calcifying marine organisms such as marine phytoplankton (i.e. coccolithophores), molluscs (i.e. mussels), gastropods (i.e. abalone), and echinoderms (i.e. sea urchins). One of the results of ocean acidification is both a decreased quantity of available carbonate for calcifying organisms, and an increase in solubility of calcium carbonate already deposited in the tests and shells of marine organisms. Another result of ocean acidification is the change in the quantity of dissolved carbon species, which can affect marine photosynthesizing and aerobic organisms.  Paleoclimatic data indicate that atmospheric CO2 concentrations have steadily increased from pre-industrial levels of 280 ppm to current levels of 390 ppm (IPCC, 2013), and may reach over 900 ppm by the end of the century (RCP8.5, IPCC, 2013). Oceanic levels of CO2 equilibrate with the atmosphere (Wallace & Holfort, 1996; Frankignouelle & Borges, 2001), with varying degrees of impact on marine organisms. Ocean acidification can cause  3 ecosystem simplification, with decreased variability and functionality among communities (Kroeker et al., 2011). Growth, calcification, survival, development, and abundance are all negatively affected by ocean acidification in a wide variety of organisms, as are early life history stages of some taxonomic groups (e.g. mollusks, echinoderms, see Kroeker et al., 2013). However, some non-calcifying marine algae and seagrasses do not respond negatively to increased oceanic CO2 concentrations, with marginal increases in growth, abundance, and photosynthetic rates (Kroeker et al., 2013).  Rising temperatures can have variable impacts on species performance, but will cause shifts in species distribution and abundance, dependent on their thermal tolerance and ability to adapt (Harley et al., 2006). Average global surface temperatures may increase by up to nearly 5°C by the end of the century under business as usual scenarios (Scenario RCP8.5, IPCC, 2013), but the effects of rising temperature on any given organism will depend on their thermal tolerance. Every individual has a profile of thermal tolerance – the thermal performance curve – that describes performance at any given temperature (Angilletta, 2009). Performance (i.e. growth, photosynthetic rates, metabolic rate) increases with increasing temperature up to a point, the thermal optimum, and then decreases to zero, at which point mortality is ultimately expected if high temperatures continue unabated. Therefore, the effects of climate warming on species performance will depend upon where rising temperatures fall along that species thermal performance curve. To date, marine systems have seen increased rates of species invasions, shifts in latitudinal distribution, changes in community composition and the timing of animal migrations, change in species abundance, and mortality and extinction of structure forming species such as coral due to rising temperatures (Parmesan, 2006; Hoegh-Guldberg & Bruno, 2010). Along with rising average temperature, the frequency of episodic warming events is also predicted to increase (IPCC, 2013), which may push many species already living at the edge of physiological tolerance past their physiological limit (e.g. corals, Parmesan, 2006; mussels, Harley, 2008).  Increases in frequency in extreme weather events encompasses a number of environmental stressors that can impact nearshore marine communities, including increased temperature, but also increased ultraviolet radiation (UV). Recovery of the stratospheric ozone layer that blocks out a large proportion of solar UV radiation will likely occur over the next few decades due to global reductions in anthropogenic emissions of chlorofluorocarbons  4 (CFC’s) following the implementation of the Montreal Protocol (WMO, 2014). However, UV remains an environmental stressor that can have strongly negative impacts on marine organisms (Worrest & Häder, 1989; Coelho et al., 2000). UV intensity will likely be high to extreme during the episodic warming events that may occur with increasing frequency along with decreased cloud cover (IPCC, 2013). The majority of research addressing UV impacts focuses on photosynthesizing marine organisms, but juvenile fish, crab larvae, and shrimp larvae are also susceptible to UV radiation, and have shown decreased reproductive capacity, growth, and survival following UV stress (Worrest & Häder, 1989). However, the influence of UV radiation may become more pronounced at the ecosystem level, as communities and trophic structure shifts to accommodate reductions in biomass of primary producers (Häder et al., 2007). In marine algae, research shows UV radiation can cause photoinhibition and photodamage (Bischof et al., 1998), decreased germination and fertility (Veliz et al., 2006), altered development (Schoenwaelder et al., 2003), DNA damage (Roleda et al., 2006), decreased growth rates (Dring et al., 1996), and restricted depth distribution (Wiencke et al., 2000) in microscopic and macroscopic stages of kelp (Dring et al., 1996). Independently, high levels of UV, ocean acidification, and temperature affect organismal physiology, but when combined, effects of multiple interacting environmental stressors are not always straightforward (Crain et al., 2008).  In general, marine taxa show greater sensitivity to ocean acidification at higher temperatures, with trends toward decreased survival, calcification, growth, and development (Kroeker et al., 2013). However, interactions among climate variables can be additive, synergistic, and antagonistic (Crain et al., 2008). When the isolated effects of 2 or more stressors are the same individually as they are when combined, the effects are deemed additive and the least difficult to predict. When one stressor alters the effects of a second stressor, the responses are termed either synergistic or antagonistic. Synergistic effects occur when the net effects are greater than the sum of their isolated effects, and antagonistic effects occur when the net effects are less than the sum of their isolated effects. The interactive effects of multiple climate stressors may be more apparent in areas where organisms live close to their physiological tolerance, such as the intertidal zone (Connell, 1961; Tomanek & Helmuth, 2002), where small changes in climate can have large impacts on organismal performance (Harley, 2003).  5 Rocky shores have been characterized as one of the harshest environments on the earth (Tomanek & Helmuth, 2002). Life in the intertidal zone is highly stressful as organisms experience both marine and terrestrial stressors. The upper vertical limits in zonation patterns are set by physiological tolerance to environmental stressors, namely temperature and desiccation stress, while lower limits are generally set by biotic factors (Connell, 1961). These zonation patterns reflect a gradient of aerial exposure, as tides recede to expose organisms up to twice daily, with high intertidal organisms exposed for the longest duration. With the ebb and flow of tides also comes a high amount of variability in wave forces, temperature, CO2, salinity, and pH (Tomanek & Helmuth, 2002). As many of these factors are predicted to vary with global climate change, the intertidal zone is a model community to study such changes as the entire community is condensed within small spatial scales and organisms already live at the edge of their physiological limit (Tomanek & Helmuth, 2002). If foundation species (Dayton, 1972) or ecological dominants (Dayton, 1975) in the intertidal zone are particularly vulnerable to climate change, there may be cascading consequences to entire communities.  Kelps (brown algae of the order Laminariales) are ecologically and economically important species found worldwide (Steneck et al., 2002; Graham et al., 2007a), and are both foundation species (Dayton, 1972a) and ecological dominants (Dayton, 1975). There are over 100 species that form kelp forests: large, habitat- and canopy-forming structures in coastal marine ecosystems (Graham et al., 2007b). Some kelps are highly productive and can grow up to 14 cm per day, while others have slower growth rates but are longer lived (Graham et al., 2007b). Kelps support diverse, highly productive communities (Steneck et al., 2002), estimated to contain upwards of 275 species associated with kelp forests in southern California alone (Graham et al., 2007b). The economic value of kelp forests in northern Chile have been estimated at US $40 million (Vásquez et al., 2014), which valuates only a small geographic portion of the global distribution of kelp forests.  Kelps have a biphasic life history cycle that alternates between the macroscopic sporophytes (diploid) and microscopic gametophytes (haploid, Fritsch, 1948, Figure 1.1). Haploid, biflagellate zoospores are produced by meiosis in sporangia, which are densely aggregated in sori on mature sporophytes. Once released, zoospores are motile until they reach the substrate, locate a suitable microenvironment, settle, germinate, and develop into  6 male and female gametophytes (see Graham et al., 2007b for a detailed review of the Laminariales life history cycle). Male gametophytes mature and develop antheridia that release sperm and females mature and develop oogonia, which extrude lamoxirene to attract the male sperm. Once fertilization has occurred, microscopic sporophytes develop directly on top of the female gametophytes, and eventually grow into their macroscopic form. The various stages of the life history cycle have varying levels of susceptibility and sensitivity with regards to physiological stressors associated with global change (e.g. temperature, Fredersdorf et al., 2009). Due to this variability in sensitivity, is it important to consider the effects on all life history stages when considering how a species will fare under future climate conditions as effects at one stage have can population level consequences.    7   Figure 1.1 The kelp life history cycle (drawings by Megan Mach).  Early life history stages of kelp may be more sensitive to the interactive effects of climate change than macroscopic stages (Dring et al., 1996; Coelho et al., 2000) due to their smaller size and still-developing physiological capacity (Henry & Cole, 1982). The majority of research to date on climate impacts on early life history stages of kelp focuses on the independent effects of UV radiation (see Coelho et al., 2000 for a review). This research has demonstrated the clear negative impact of UV radiation on photosynthesis, growth, and survival of microscopic, kelp life history stages (Coelho et al., 2000; Bartsch et al., 2008). However, there have been very few studies on the interactive effects of multiple climate stressors on the kelp life history cycle (but see Müller et al., 2008; Fredersdorf et al., 2009; Gaitán-Espitia et al., 2014), and no fully-factorial 3-factor studies to date. Furthermore, most studies have used subtidal kelps as their study organism, even though intertidal kelps may be Microscopic(Sporophyte(Sporophyte(Microscopic(Gametophytes(Free2Swimming(Zoospores( 8 more susceptible to climate change than their subtidal congeners as intertidal species typically live closer to their physiological limit (Stillman, 2002; Harley et al., 2006). Kelps are ideal organisms to study the impacts of climate change as they are directly affected by changes in ambient and ocean temperature (Davison, 1991; Bruhn & Gerard, 1996), UV radiation (Coelho et al., 2000; Wiencke et al., 2004), and CO2 concentrations (Gaitán-Espitia et al., 2014); all of these processes are predicted to vary over the next years to decades, partly due to anthropogenic activities (IPCC, 2013). To this end, I address the effects of increasing temperature, CO2, and UV radiation predicted to occur with global change on the life history cycle of intertidal kelp. 1.2 Dissertation overview The research in this dissertation uses experimental methods to determine the potential impact of global climate change on the different life history stages of intertidal kelp. Each experiment compares present day (or control) treatments to treatments designed to mimic future levels of environmental stressors known to impact kelp performance. One strength of this dissertation is that it combines laboratory experiments addressing the impact of multiple environmental stressors on microscopic stages, with a field experiment addressing the response of macroscopic stages to environmental stress in a natural setting. Incorporating the effects of climate change on multiple life history stages of intertidal kelps within this dissertation will help expose the variability in sensitivity of microscopic motile zoospores, settled spores, and germinated spores, and macroscopic juvenile and adult sporophytes. In Chapter 2 I simulate end of century levels predicted for temperature, CO2, and UVA intensity, and look at changes in performance of motile kelp zoospores. In addition to quantifying differences in swimming parameters such as speed and overall motility, I also look at behavioral changes known to correlate with the process of settlement, including whether or not zoospores are functional (i.e. motile) or display behaviors indicative of physical or mechanical damage. Specifically, I address the following research question: Do the interactive effects of increasing temperature, CO2 concentration, and UV radiation affect kelp zoospore motility and pre-settlement behaviors?  9 In Chapter 3 I address changes in the rate of progression of the life history cycle, including settlement, germination, and successful adhesion of kelp zoospores. The work in this chapter directly ties into research from the previous chapter, as adhesion, settlement, and germination are the processes directly following the free-swimming stage in the life history cycle. Specifically, I address the following research question: Do the interactive effects of increasing temperature, CO2 concentration, and UV radiation affect kelp settlement, adhesion, and germination? In Chapter 4 I experimentally impose episodic thermal stress on juvenile and adult kelp sporophytes. This field experiment addresses a different component of global climate change than the previous two laboratory experiments, looking at thermal pulses associated with extreme warming events rather than the rise in average temperatures. To ground truth these effects in a natural setting, I also manipulate adult kelp density as a means of determining the effect that neighbor proximity has on stress amelioration (Bruno et al., 2003) to neighboring adults and understory juvenile kelp. The combined stress of reduced adult density and episodic thermal pulses is intended to mimic multiple stressful conditions in a natural setting in the intertidal zone. Specifically, I address the following research question: Do episodic warming events affect seasonal growth in adult sporophytes and recruitment of juvenile sporphytes? Does adult density (neighbor proximity) affect these results? In Chapter 5 I synthesize the work presented in the previous chapters and make general conclusions derived from this research. Avenues of future research arising from questions or limitations raised in the research chapters will be discussed, along with suggestions for the trajectory of experimental ecology focused on global change.   10  Chapter 2 Multiple interacting climate stressors impact zoospore motility and pre-settlement behaviors  2.1 Synopsis Kelps play an integral role in structuring temperate marine coastal communities. Understanding how climate change stressors impact these habitat-forming species’ population dynamics is essential in predicting how community structure will change in the coming century. I investigated the response of a motile microscopic life history stage – the zoospore – to multiple climate factors, using an intertidal species (Egregia menziesii) found along the Pacific coast of North America. Specifically, I looked at how the speed, rate of change of direction, motility, and pre-settlement behaviors of zoospores varied with warming, ocean acidification, and increased ultraviolet radiation (UV). Increased temperature and CO2 reduced zoospore swimming speed, and increasing temperature increased the ratio of rate of change of direction over speed, a measure of angular velocity that dictates the degree of zoospore circular swimming. While temperature and CO2 influence swimming behavior in the water column, UV skewed the distribution of pre-settlement behaviors towards the earliest pre-settlement behavior. More specifically, high UV may have caused zoospores to lose their ability to detect small-scale physical and chemical changes in the microenvironment. The speed and manner in which zoospores find suitable substrate to settle could influence population persistence if negative effects ripple through subsequent life history stages.   11  2.2 Introduction Global climate change is a worldwide concern, causing a suite of cascading effects, including increased temperature, ocean acidification, and decreased cloud cover, which can cause increased solar radiation (including ultraviolet radiation, UV) to the earth’s surface (IPCC, 2013). These climate shifts affect most areas and ecosystems and result in a number of interacting environmental conditions. Temperature and CO2 increases in the atmosphere account for the greatest impact on changing oceanic conditions, causing increased sea surface temperatures and the phenomenon known as ocean acidification, respectively.  Ocean acidification is the concurrent decrease in oceanic pH caused by increases in oceanic carbon concentrations equilibrated from atmospheric CO2 levels. End of century climate models indicate that average surface temperatures could increase by 1.5-5ºC, and CO2 concentrations could more than double, reaching 900 ppm (IPCC, 2013).  Changes in climate can affect growth, reproduction, distribution, and survival of marine species (e.g. Perry et al., 2005; Harley et al., 2006; Edwards & Richardson, 2004; Bartsch et al., 2008; Hoegh-Guldberg & Bruno, 2010; Kroeker et al., 2013). When considering multiple climate stressors acting simultaneously on marine organisms, meta-analyses reveal that effects can be additive, synergistic, or antagonistic depending on the response level (e.g. community, population), trophic level, or stressor pairing (Crain et al., 2008). Additive effects are those whose cumulative impacts equal the sum of their isolated impacts. For example, elevated temperature and CO2 concentrations can impair coral growth and increase coral mortality (Anthony et al., 2011), cause impaired physiological performance in larval sea urchins (Padilla-Gamiño et al., 2013) and decreased germination rates and increased mortality rates in settled kelp spores (Gaitán-Espitia et al., 2014). Synergistic and antagonistic effects are less straightforward, as cumulative impacts do not equal the sum of their isolated impacts. For example, both temperature and ocean acidification can separately impact performance, however the interactive effects may be such that the level of temperature exacerbates the effect of ocean acidification. More specifically, in the jumbo squid, decreased pH caused reductions in metabolic rate and activity levels,  12 which was exacerbated by increased temperature (Rosa & Seibel, 2008). With the addition of a third stressor, interactive effects change significantly (Crain et al., 2008), making multiple stressor manipulations critical to understanding the effects of environmental change. As the general effects of variability in multiple environmental stressors associated with climate change are poorly understood, research targeting integral community members such as structure, foundation, or habitat forming species (e.g. corals and kelps), or keystone species (e.g. beavers, sea otters) may be a beneficial priority, as changes to these species population dynamics, abundance, or persistence can have disproportionate impacts on their associated community. Kelps are integral species in nearshore coastal environments, providing food, shelter, structure, and amelioration of environmental stressors to the understory community (Graham et al., 2007). To date, studies of multiple stressor impacts on kelp indicate that responses are species specific, and habitat specific (Müller et al., 2008), and reveal the disruption of normal ontogenetic progression (e.g. reduced germination rates, see Fredersdorf et al., 2008; Müller et al., 2008; Gaitán-Espitia et al., 2014). However, the magnitude of effect that environmental stress can have on kelps varies with life history stage, with older stages being less sensitive than younger stages (e.g. UV; Dring et al., 1996). Kelps have a multiphasic life history, with macroscopic sporophytes (2N) alternating with microscopic gametophytes (1N). Motile zoospores are released from sporangium on the adult sporophyte and must locate the substratum, find a suitable settlement location, and attach to the substratum. Zoospores are biflagellate, and propel themselves with one longer, anterior “tinsel” flagellum covered with mastigonemes that pulls the zoospore through the water. The “whiplash” posterior flagellum is smooth and beats in the opposite direction to help steer and give another axis of motor control. During daytime hours, zoospores can photosynthesize and do not have to rely on stored energy, which is used while swimming in darkness (Reed, 1999). Timing of release is unknown for many kelp species (except see Dayton, 1973 for information on low tide sporulation in Postelsia palmaeformis, and Amsler & Neushul, 1989a for dawn/dusk sporulation in Nereocystis luetkeana), but zoospores can be released from the parent plant into plankton (long distance dispersal), or may stay close to the bottom at the benthic boundary layer (small scale dispersal, Amsler et al., 1992). In all cases it is important to find the substratum and settle quickly because the nearshore marine  13 environment is highly dynamic (e.g. currents, surge, wave action, tidal regimes) and the majority of kelp zoospores remain motile for less than 24 hours (Wiencke et al., 2000). Although non-motile spores can remain viable for settlement, swimming of zoospores increases the likelihood of settlement (Roleda et al., 2005). Active swimming of zoospores becomes highly important once motile spores have entered the benthic boundary layer, and are actively seeking a suitable settlement location (Amsler et al., 1992). Brown algal zoospores exhibit a number of pre-settlement behaviors before eventually adhering to the substratum: 1) straight path, 2) search circle, 3) orientation, and 4) gyration (Iken et al., 2001). Straight path swimming styles are used for dispersal and movement within the substratum boundary layer. Search circle and orientation behaviors are used to detect changes in the microenvironment: the former is used mostly to detect physical and chemical gradients, and the latter is used to detect physical properties of a surface. Lastly, gyration is the (reversible) initiation of settlement, where the anterior flagellum attaches to the substratum and begins to gyrate. This behavioral progression ultimately leads to settlement, which must be achieved in densities greater than 1/mm2 for the resulting population of gametophytes to achieve successful sexual fertilization (Reed, 1990). Therefore, zoospores that settle in aggregations will have a higher probability of successful sexual fertilization as males and females will be in close proximity to one another (Muth, 2012). A fifth behavior, “wobbling,” is considered indicative of mechanical failure and is not characterized as a pre-settlement behavior (Iken et al., 2001). This behavior could be characteristic of an unfit zoospore, or a physical response to stressful environmental conditions.  Motile kelp zoospores are smaller in diameter than settled spores (which have exuded internal adhesive material), do not have a well-developed cellular wall, and most physiological functions are not yet well developed (Henry & Cole, 1982) making them more susceptible to increases in environmental stressors such as UV (Veliz et al., 2006). Knowing whether stressors interact to affect different components of zoospore motility will provide insight into the potential synergisms of complex global change. In this study, I manipulated temperature, CO2 concentration, and UV-A intensity to determine changes in zoospore motility (percent motile, and swimming speed, and rate of change of direction of motile zoospores), proportion of mechanically damaged spores, and pre-settlement behaviors.  14  2.3 Methods To test the hypothesis that multiple environmental stressors interact to affect kelp zoospore motility, functionality, and pre-settlement behaviors, I designed an experiment with three stress factors. Treatment combinations were a fully factorial implementation of the following: seawater temperature (2 levels, low and high temperature), seawater CO2 concentration (2 levels, ambient and elevated CO2), and UV (with or without UV-A application). The temperature and CO2 treatments represent present day (control) or elevated levels associated with global change, while the UV-A application used mimicked “very high” to “extreme” conditions, as based on the NASA UV Index (http://www.nasa.gov/topics/earth/features/world_avoided.html). For the low (control) temperature treatment, 20 L buckets containing sterilized seawater were immersed into a flowing seawater table set to 15°C. For the high temperature treatment, 20 L buckets were propped on wire racks just above the water level of the flowing seawater tank (ambient air temperatures were set to 21°C). Temperatures were measured for each treatment daily to confirm experimental manipulations. Carbon concentrations were established by bubbling air via mass flow controllers (Sierra Instruments C100L, Monterey, CA, USA). For the ambient treatment (control), ambient air was pumped via air compressors (Gast MOA-P101-AA Vacuum/Air Compressors) and regulated by mass flow controllers into buckets. For the elevated treatment, ambient air was pumped via air compressors and combined with a 5% CO2 gas mixture using mass flow controllers to attain elevated carbon levels (roughly 1000 ppm). CO2 concentrations were verified with a CO2 gas analyzer (Qubit Systems, model S151). pH and salinity were also measured prior to each experimental release (see below) using a pH probe (model RK-59001-70) and a refractometer, respectively. Lastly, experimentally applied UV levels were attained with a portable UV light (UVP LLC, model UVL-26P) set to 12 W/m2, which was verified using a UVX Radiometer. The UV light was propped atop the finger bowls. PAR levels were roughly 40 umol/m2/sec in the incubator where temperature manipulations were maintained and all experimental UV was applied.  15 Egregia menziesii is a perennial macroalga of the order Laminariales (Phaeophyceae, Abbott & Hollenberg 1976). Multiple fronds arise from the holdfast and can reach 5-15 m in length. Found on northeastern Pacific Ocean coastlines in mid-intertidal to shallow subtidal zones, it can form dense and extensive beds. E. menziesii macroscopic adults reproduce year round in southern California, and therefore expose their zoospores to a wide range of thermal conditions. Seawater temperatures in the area of the collection site Rancho Palos Verdes (near Los Angeles, CA) vary from winter means of 13°C to summer means of 21°C (NOAA.gov, Accessed July 2014). Southern California is near the southern latitudinal range limit for this species (in Baja California, Mexico). The northern limit is Alaska, USA. The experimental progression was as follows: we collected kelp (February-March, 2011), prepared reproductive material for release, performed experimental manipulations during the release of zoospores from reproductive material, standardized zoospore density, and then recorded their swimming paths under magnification. First, 10-20 Egregia fronds with reproductive sori were collected, brought back to the lab, and stored in tanks of filtered seawater. In order to prepare the reproductive material for release of zoospores from sporangium, fronds were sterilized in an iodine solution, rinsed with deionized water and sterile seawater, and then stored in a cool, dark refrigerator inside of an opaque garbage bag between seawater-dampened paper towels. This preparation was always performed two days before each experimental trial in order to standardize the duration following collection. After 48 hours in the refrigerator, the sori from a 10 cm portion of a reproductive frond were cut off and placed into a glass finger bowl, and one of the experimental treatments was applied. Finger bowls were filled 2/3 full (roughly 200 mL) with treated seawater, covered with Saran wrap directly touching the water (i.e., no head space) to prevent quick off-gassing of CO2, and kept in an incubator set to maintain constant treatment temperature, with sufficient irradiance for release (roughly 40 umol/m2/sec). A UV lamp was placed directly above the petri dish for treatments with UV-A (UVA level 12 w/m2), which caused minimal shading of PAR from the incubator as it radiated from either side of the UV lamp to treatment water in the petri dish. Reproductive fronds were kept in treatment water for a 30-minute acute exposure, at which time UV treatments were removed (if applicable).  Zoospore concentration measurements were taken every 1-2 minutes using a hemocytometer until solution densities reached 5-10 zoospores/mm2, at which point  16 reproductive fronds were removed. This process spanned 1-30 minutes (following the 30 minute treatment period), with no differences in release time among experimental treatments (3-Factor ANOVA, p>0.30 for all terms, data not shown).  A 10 µL aliquot of newly released E. menziesii zoospores was pipetted into each experimental well slide, covered with a cover slip, and placed on a Olympus IX70 inverted microscope mounted with a NEC model TI23A analog video camera that was converted to digital video via a converter box. One minute videos were taken in a 300 µm (length) by 300 µm (width) viewing field of the zoospores swimming at 1) mid-depth (“center”) where there were no solid surface interactions, and 2) the bottom of the microscope slide on the glass surface. This video process was done 5 total times for each petri dish, which together represented one replicate of each treatment combination. At the beginning of each video, time since initial frond immersion was noted. Ten total videos (5 at the bottom and 5 at the center) from each replicate petri dish from each treatment combination were taken in a single day. Videos were taken on 11 days between February 28 and March 19, 2010. Following the experimental progression, videos were analyzed for differences in swimming characteristics and styles among treatments. Each 1-minute “center” video was then cut into four, 15-second videos using SolveigMM Avi Trimmer software for compatibility with Motion Analysis CellTrak software (see Himes et al., 2011 for further details). All path lengths ≤4 frames were discarded to avoid parallax in spore paths at the edges of the field of view. Swimming speed (pixels/sec) and rate of change of direction (RCD, or absolute value of angular velocity, degrees/sec) were calculated by the CellTrak software. The units for speed were then transformed from pixels to millimeters using the conversion 1120 pixels/mm. Due to the lengthy video processing, results from video 3 (out of the 5 “center” videos taken per petri dish) were used in statistical analyses to standardize the age of zoospores since release when looking at speed (mm/sec) and RCD (degrees/sec) swimming parameters.  All 5 video trials (sub-replicates) were used when analyzing zoospore motility and pre-settlement behaviors. Following Iken et al. (2001), each zoospore in every 1-minute video was binned into one of the following behaviors: non-motile zoospores, short paths (zoospores that swam in and out of the field of view too quickly to characterize their behavior (time periods roughly less than 2 seconds), and then zoospores swimming in  17 straight paths, search circles, orientation, gyration, and wobbling motions. These swimming styles are indicative of zoospore viability and progression towards settlement, except the last behavior (wobbling), which is indicative of mechanical failure. Zoospore counts were transformed to proportion data to standardize the results over all of the video replicates: 1) proportion of motile zoospores out of all zoospores in each video (motile and non-motile), 2) proportion of wobbling (damaged) zoospores out of all motile zoospores in each video, and 3) proportion of straight path, search circle, and combined orientation and gyration behaviors out of all zoospores in each video. Data were analyzed using the statistical program SPSS v. 22. Mixed model ANOVAs were used to test the effects of the blocking factor ‘Date,’ and the fully factorial model of temperature, CO2, and UV on the swimming parameters speed, and the ratio of rate of change of direction (RCD) over speed (RCD/SPD), which is essentially a measure of degrees of turn per distance travelled (Iken et al., 2003). Speed alone was analyzed for comparisons among other studies (and other flagellated, marine organisms) addressing climate stressor impacts, and RCD/SPD was chosen in order ascertain changes in swimming behavior (see Iken et al., 2003). For these two analyses, the α-value was Bonferroni-corrected to α = 0.025, and the blocking factor ‘Date’ was removed from the analysis when p>0.250.  Zoospore viability data were analyzed using mixed model ANOVAs to test the blocking factor ‘date,’ the nested factor ‘date(trial),’ and the fully factorial effects of temperature, CO2 concentration, and UV on the proportion of motile zoospores out of all the motile and non-motile zoospores in each video trial. Lastly, pre-settlement behavior data were analyzed using separate mixed model ANOVAs to test the fully factorial effects of temperature, CO2, and UV, along with the blocking factor ‘date’ and the nested factor ‘date(trial)’ on the following behaviors: proportion of wobbling (damaged) spores of all motile spores, proportion of straight path spores of all motile spores, proportion of search circle spores of total motile spores, and proportion of the combined behaviors of orientation and gyration spores of the total number of motile spores (see Iken et al., 2001). The proportion of orienting and gyrating spores were combined in a single analysis due to issues arising from the large amount of zeros in later stage pre-settlement behavior proportions. For the last 4 behavior analyses, α-values were Bonferroni-corrected to α = 0.013, and the  18 blocking factor ‘date’ and the nested factor ‘trial(date)’ were removed from analyses when p>0.250. 2.4 Results Environmental parameters (temperature, CO2 concentration, pH, and salinity) were successfully altered by the experimental manipulations (Table 2.1). Low (or control) temperature treatments averaged 14.8ºC ± 0.09ºC (mean ± SE), while high temperature (or elevated) data for elevated treatments averaged 20.5ºC ± 0.11ºC. CO2 concentrations for control treatments set to achieve present day levels averaged 357 ppm ± 7.27 with a corresponding pH of 8.06 ± 0.01. CO2 concentrations for elevated conditions averaged 961 ppm ± 29.1 with a corresponding pH of 7.68 ± 0.02. Average salinity for all treatments was 32.6 ± 0.11.   Table 2.1 Average environmental conditions for each desired treatment level (T1=Treatment Level 1 or ambient/control, T2=Treatment 2 or elevated), or the total average for salinity.   T1 T2 Average T1 Average T2 Total Average Temperature (°C) 15 21 14.8 (±0.1) 20.5 (±0.1) n/a CO2 (ppm) 400 1000 356.9 (±7.3) 960.7 (±29.1) n/a pH n/a n/a 8.06 (±0.01) 7.68 (±0.02) n/a Salinity (ppm) n/a n/a n/a n/a 32.6 (±0.7)   Zoospore swimming speed was slower at high temperatures (p<0.001, Table 2.2). The average zoospore swimming speed at low temperatures was 0.18 ± <0.01 mm/sec (SE mean), and 0.15 ± <0.01 mm/sec at high temperatures, a decrease of 0.03 mm/sec between treatments (Figure 2.1a). A kelp zoospore body length is roughly 5 µm, translating to a decrease in swimming speed of roughly 6 body lengths/sec. Secondly, mean zoospore swimming speed was lower with elevated CO2. At ambient CO2 concentrations, zoospore swimming speed was 0.17 ± <0.01 mm/sec and 0.15 ± <0.01 mm/sec at elevated CO2 concentrations, a decrease of 0.02 mm/sec between treatments, which translates to a difference in swimming speed of roughly 4 body lengths/sec (Figure 2.1b). Average swimming speed varied daily (blocking factor, p=0.017, Table 2.2). Lastly, the average  19 RCD/SPD ratio at low temperature was 1199 ± 68.7, and 1658.81 ± 141.1 at high temperature, a difference which was statistically significant (p=0.005, Table 2.3, Figure 2.1c). All other main and interactive effects were non-significant (Tables 2.2, 2.3).  Table 2.2 General Linear Mixed Model: Test on the dependent variable speed with temperature, CO2, and UV as fully factorial fixed factors and date as the random blocking factor. Bonferroni-corrected p-values of 0.025 or less are significant. * Indicates significance.   Sums of Squares DF F P-Value Date 0.013 8 0.001 *0.017 Temperature 0.019 1 30.351 *<0.001 CO2 0.003 1 5.559 *0.022 UV <0.001 1 0.078 0.781 Temperature x CO2 0.002 1 2.734 0.104 Temperature x UV <0.001 1 0.001 0.971 CO2 x UV <0.001 1 0.022 0.883 Temperature x CO2 x UV 0.000 1 0.392 0.534 Error 0.035 56      20 (a)  (b)  (c)  Figure 2.1 (a) Effect of temperature on speed (mm/sec) of motile zoospores. (b) Effect of CO2 concentration on speed (mm/sec) of motile zoospores. (c) Effect of Temperature on the ratio of RCD/SPD of motile zoospores. Error bars are standard error of the mean.   0	  0.05	  0.1	  0.15	  0.2	  15	  C	   21	  C	  Speed	  (mm/sec)	  0	  0.05	  0.1	  0.15	  0.2	  400	  ppm	   1000	  ppm	  Speed	  (mm/sec)	  0	  500	  1000	  1500	  2000	  15	  C	   21	  C	  RCD/Speed	   21  Table 2.3 General Linear Mixed Model: Test on the dependent variable rate of change of direction over speed (RCD/SPD) with temperature, CO2, and UV as fully factorial fixed factors. Bonferroni-corrected p-values of 0.025 or less are significant. * Indicates significance.  RCD/SPD Sums of Squares DF F P-Value Temperature 3803208.27 1 8.537 *0.005 CO2 313183.240 1 0.703 0.405 UV 28162.040 1 0.063 0.802 Temperature x CO2 433514.475 1 0.973 0.328 Temperature x UV 148563.722 1 0.333 0.566 CO2  x UV 154775.643 1 0.347 0.558 Temperature x CO2 x UV 1425431.52 1 3.200 0.078 Error 28510987.1 64     The proportion of motile spores depended on temperature, CO22 concentration, and the interaction between these two factors (Table 2.4). At ambient CO2, the effect of warming was negative but slight (-0.03), whereas warming reduced motility by 0.13 at elevated CO2 (Figure 2.2a). These results suggest that the effects of warming were most detrimental at high CO2 concentrations and, conversely, the effects of ocean acidification were most detrimental in warmer water. The baseline proportion of motile spores varied daily (blocking factor, p<0.001), but all other main and interactive effects were non-significant (Table 2.4).  Table 2.4 Generalized Linear Model: Proportion motile spores (including short paths) of total spores, including non-motile. Omnibus test p < 0.001, Goodness of fit Pearson Chi-square p value 0.021. * Indicates significance.  Wald Chi-Square DF P-Value Date 103.591 10 *<0.001 Temperature 32.235 1 *<0.001 CO2 14.043 1 *<0.001 UV <0.001 1 0.989 Temperature x CO2 14.242 1 *<0.001 Temperature x UV 1.942 1 0.163 CO2 x UV 0.387 1 0.534 Temperature x CO2 x UV 2.145 1 0.143    22 (a)  (b)  Figure 2.2 (a) Interactive effects of temperature × CO2 concentrations on the proportion of (Motile spores)/(Motile + Non-Motile Spores) in each video. (b) Interactive effects of temperature × UV on the proportion of (Wobbling Spores)/(Motile Spores) in each video. Error bars are standard error of the mean.   The mean proportion of wobbling spores depended on temperature, UV, and the interaction between these two factors (Temperature × UV; p<0.001, Table 2.5). At low temperature, the effect of UV on the proportion of wobbling spores was negative but slight (-0.01), whereas UV increased the proportion of wobbling spores by 0.05 with and high temperature (Figure 2.2b). Thus, there were substantially more wobbling zoospores in the 0	  0.1	  0.2	  0.3	  0.4	  0.5	  0.6	  0.7	  400	  ppm	   1000	  ppm	  Motile	  Spores/(Motile	  +	  Non-­Motile	  Spores)	  15	  C	  21	  C	  0	  0.01	  0.02	  0.03	  0.04	  0.05	  0.06	  0.07	  0.08	  15	  C	   21	  C	  Wobbling	  Spores/Motile	  Spores	  No	  UV	  UV	   23 high temperature treatment with UVA treatment. These results suggest that the effects of warming were most detrimental with UV and, conversely, the effects of UV were most detrimental in warmer water. The baseline proportion of motile spores varied daily (blocking factor, p<0.001), but all other main and interactive effects were non-significant (Table 2.5).  Table 2.5 Generalized Linear Model: Proportion of motile spores that exhibit wobbling behavior (indicative of mechanical damage). Omnibus test p < 0.001, Goodness of fit Pearson Chi-square p-value 0.004. Bonferroni-corrected p-values of 0.013 or less are significant. * Indicates significance.   Wald Chi-Square DF P-Value Date 93.860 10 *<0.001 Temperature 11.766 1 *0.001 CO2 2.220 1 0.136 UV 8.001 1 *0.005 Temperature x CO2 4.186 1 0.041 Temperature x UV 20.690 1 *<0.001 CO2 x UV 0.118 1 0.732 Temperature x CO2 x UV 0.658 1 0.380   UV significantly affected the proportion of spores exhibiting straight path behaviors and the combination of spores exhibiting orienting and gyrating behaviors (Tables 2.6 and 2.8, respectively). The proportion of zoospores exhibiting the straight path behavior significantly increased with elevated UV from 0.24 ± 0.01 (without UV; mean ± SE) to 0.29 ± 0.01 (with UV; UV p<0.001, Table 2.6, Figure 2.3a). There were no significant treatment effects on the proportion of zoospores exhibiting the search circle behavior (Table 2.7), however, the proportion of the combination of orientation and gyration zoospores of the total number of motile spores decreased from 0.25 ± 0.01 to 0.20 ± 0.01 with the addition of UV (UV, p<0.001, Table 2.8, Figure 2.3b). On each experimental day (or group of days) the baseline number of zoospores exhibiting each pre-settlement behavior varied (date, p<0.001 for all analyses, Tables 2.6-2.8). All other main effects and higher order interactions were non-significant (Tables 2.6-2.8).   24  Table 2.6 Generalized Linear Model: Proportion of motile spores that exhibit straight path behavior. Omnibus test p < 0.001, Goodness of fit Pearson Chi-square p value 0.027. Bonferroni-corrected p-values of 0.013 or less are significant. * Indicates significance.   Wald Chi-Square DF P-Value Date 128.451 10 *<0.001 Trial(Date) 66.614 44 0.015 Temperature 5.059 1 0.025 CO2 0.389 1 0.533 UV 12.273 1 *<0.001 Temperature x CO2 0.348 1 0.555 Temperature x UV 0.253 1 0.615 CO2 x UV 0.000 1 0.996 Temperature x CO2 x UV 0.015 1 0.903   Table 2.7 Generalized Linear Model: Proportion of motile spores that exhibit search circle behavior. Omnibus test p < 0.001, Goodness of fit Pearson Chi-square p value 0.014. Bonferroni-corrected p-values of 0.013 or less are significant. * Indicates significance.   Wald Chi-Square DF P-Value Date 92.952 10 *<0.001 Temperature 2.494 1 0.114 CO2 0.834 1 0.361 UV 0.210 1 0.647 Temperature x CO2 0.056 1 0.812 Temperature x UV 5.200 1 0.023 CO2 x UV 2.409 1 0.121 Temperature x CO2 x UV 0.077 1 0.782    25  Table 2.8 Generalized Linear Model: Proportion of motile spores that exhibit orientation and gyration behaviors. Omnibus test p < 0.001, Goodness of fit Pearson Chi-square p value 0.019. Bonferroni-corrected p-values of 0.013 or less are significant. * Indicates significance.   Wald Chi-Square DF P-Value Date 82.641 10 *<0.001 Trial(Date) 57.513 44 0.083 Temperature 3.604 1 0.058 CO2 1.235 1 0.266 UV 12.841 1 *<0.001 Temperature x CO2 0.917 1 0.338 Temperature x UV 3.295 1 0.070 CO2 x UV 1.277 1 0.258 Temperature x CO2 x UV 4.628 1 0.032   26  (a)  (b)   Figure 2.3 UV effects on the proportion of (a) (Straight Path Behavior Spores)/(Motile Spores), and (b) (Orienting + Gryating Spores)/(Motile Spores) in each video. Error bars are standard error of the mean. 2.5 Discussion The interactive effects of increasing temperature, CO2, and UV radiation had discernable impacts on kelp zoospore swimming characteristics. I found that motile Egregia zoospores were susceptible to environmental stressors, even though Egregia persist in the intertidal zone; an area characterized by highly fluctuating conditions. The experimental treatments 0	  0.05	  0.1	  0.15	  0.2	  0.25	  0.3	  0.35	  No	  UV	   UV	  Straight	  Path	  Spores/Motile	  Spores	  0	  0.05	  0.1	  0.15	  0.2	  0.25	  0.3	  No	  UV	   UV	  Orienting	  +	  Gyrating	  Spores/Motile	  Spores	   27 representing future average climate conditions are those that marine organisms currently, but infrequently, experience at this location (i.e. high temperature and UV levels during peak summer warming periods of intense sunlight, and fluctuating oceanic carbon concentrations during upwelling conditions). Increased temperature and CO2 concentrations reduced the number of zoospores reaching the substratum by negatively affecting swimming speed and overall motility, while UV radiation appeared to dictate the distribution of pre-settlement behaviors.  Individually, increases in both temperature and CO2 concentrations reduced zoospore swimming speed. Temperature can affect motility via changes in physiological rates and performance, or changes in the viscosity of the fluid medium, as increasing temperature decreases water viscosity. In terms of how this impacts movement, zoospores are operating at very low Reynolds numbers, where viscous forces strongly dominate locomotion. Therefore any reduction in viscosity, e.g., due to warming, would be expected to allow for faster swimming speeds. However, in this study decreasing speed corresponded with increasing temperature, which is counter to what studies on other motile marine microorganisms have indicated (Podolsky & Emlet, 1993). Decreases in speed were therefore likely due to temperature impacts on physiological function rather than due to changes in water viscosity. All organisms have a range of thermal tolerance: performance increases with temperature up to a point, the thermal optimum, and then declines rapidly to zero (i.e. mortality, see Angiletta, 2009 for a review on thermal performance curves). The elevated temperature of 21°C used in this study may have passed the thermal optimum of kelp zoospore motility, which caused swimming speeds to decline. Although there are no data on thermal tolerance of motile E. menziesii zoospores, 21°C is at the upper limit of thermal tolerance for settled E. menziesii gametophytes from Santa Barbara, CA (115 miles north of collection site, Luning & Neushul, 1978). High temperatures could have essentially impaired physiological function if 21°C was above E. menziesii zoospore thermal tolerance. As with temperature, the possible effects of elevated CO2 on zoospore motility could be positive or negative. It is difficult to predict if increasing oceanic carbon concentrations will have positive effects on seaweed performance via increased photosynthetic rates, or negative impacts on physiological function resulting from decreased pH. The mechanisms behind how ocean acidification affects swimming speed in animals are better understood. In  28 marine animals, hypercapnia (increased CO2 in blood) affects acid-base regulation, calcification, and growth, and increased CO2 concentrations can also impact respiration, energy turnover, and metabolism (Pörtner et al., 2004). A reduction of 0.4 pH units caused slower swimming speeds in the sperm of the sea urchin Heliocidaris erythrogramma (Havenhand et al., 2008), but the specific mechanism causing this impairment is unknown. Steelhead (Oncoryhnchus mykiss) sperm were non-motile at low pH, which was attributed to the pH sensitivity of dynein ATPase, the enzyme responsible for driving flagellar motility (Woolsey & Ingermann, 2003). Motility in flagellated marine algal spores, such as zoospores in Laminariales, is also powered by dynein ATPase (Lobban & Harrison, 1994). Therefore, the lower pH found in high CO2 seawater treatments could be the reason for slower swimming speeds (Figure 2.1b) and higher proportions of non-motile spores (Figure 2.2a). If motility in flagellated marine organisms (e.g., protists) and/or ontogenetic stages, such as sperm, larvae, and kelp zoospores, is generally sensitive to decreases in pH, many marine species may be impacted by future oceanic conditions associated with climate change. In non-calcifying marine algae such as E. menziesii, an increase in oceanic carbon concentrations could result in greater photosynthetic rates (and therefore increased growth rates), but this outcome would not directly affect swimming speed. The physiological process of swimming is fueled by energy stored in phosphate bonds (lipids), which can be supplemented by photosynthetic activity in the presence of light (Brzezinski et al., 2003). However, photosynthesis is not essential to create energy for movement, and as increased CO2 concentrations resulted in decreased swimming speeds in E. menziesii, we can gather that decreasing pH (in this case an average decrease of 0.38 pH units) outweighed any positive benefits of increased oceanic carbon concentrations.  The ratio of the swimming parameters rate of change of direction and speed (RCD/SPD) has been used previously to determine the susceptibility of motile brown algal zoospores to environmental stressors (e.g. natural biofouling echinoderm extracts, Iken et al., 2003). Higher RCD/SPD ratios at 21°C indicate that this temperature caused a meaningful change in swimming characteristics; spores swam slower and in tighter circles than spores at lower temperatures. The only swimming behavior significantly affected by increasing temperature was the wobbling behavior, which indicates mechanical damage, and is known to have high RCD/SPD ratios (Iken et al., 2001; 2003). It is unclear whether the flagella or  29 dynein ATPase are adversely affected by high temperature, but this result is most likely another example of thermal optima being exceeded.  Stored energy (lipids) may be required for the process of germination (Brzezinski et al., 1993), and motile zoospores may stop swimming in the water column when reserves reach the critical level needed for this developmental process (Reed et al., 1999). Stressful climate conditions could cause zoospores to deplete their swimming energy more quickly (Fukuhara et al., 2002). Data presented here suggest that this negative impact was seen at the combination of 21°C temperature with 1000 ppm carbon concentration, suggesting that these conditions in combination were stressful to E. menziesii zoospores. Increasing temperature is known to increase metabolic function due to thermal effects on coenzyme Q10, which synthesizes energy and fuels biological function. If increased temperature alone caused motile zoospores to burn through lipid reserves via increased CoQ10 rates, the reduced proportion of motile spores should have been consistent in all high temperature treatments. If increased CO2 concentrations alone reduced motility, as documented in marine invertebrates (Havenhand et al., 2008; Morita et al., 2010), the proportion of motile spores would have been consistent at all high CO2 concentration treatments. In fact, we saw the greatest reduction in motile spores at 21°C with elevated CO2 concentrations (1000 ppm, Figure 2.2a), indicating these effects are not strictly Q10 or ocean acidification effects, but more likely physiological impairment or mechanical damage. As zoospores can swim 24 hours, it is unlikely that they burned through all of their stored energy in the duration of this experiment, as the longest swimming time recorded was less than 1.5 hours. Although I did not record mortality of non-motile spores, Gaitan-Espítia et al. (2014) found that the combination of high temperature with high CO2 concentrations resulted in increased mortality of Macrocystis pyrifera (Laminariales) spores in a pattern similar to our motility results. The mortality effect was attributed to a combination of decreased functionality of cellular repair mechanisms combined with increased vulnerability to environmental stressors due to a lack of a protective outer cell wall. Exposure to stressful conditions can cause alterations in physiological processes, such as changes in the stress response system at high temperatures or impacts on ionic transport at high CO2 concentrations, which may break down when stressors are combined.  30 Environmental stressors could impact three major functions essential for swimming in motile zoospores: respiration, the ability to draw stored energy to fuel flagellar motility, or the mechanical apparatus for flagellar motility. Damage to DNA or cellular ultrastructure, which could affect one or all of the aforementioned processes, can shift the priority of zoospore cellular function from motility to damage repair, which could alter or halt zoospore motility. The impact on zoospore motility was evidenced by the increase in the proportion of mechanically damaged swimming styles of zoospores in high temperature treatments exposed to UV radiation (Figure 2.2b). As UV exposure does not seem to impact respiration of brown algae (Aguilera et al., 1999), UVA exposure must directly impact the apparatus for flagellar motility or the ability to draw energy necessary to fuel flagellar motility. More specifically, UV can damage DNA, proteins, and enzymes (Roleda et al., 2005), all of which can damage the process of flagellar motility.  Following release from parent plants, brown algal zoospores move through an age related progression of pre-settlement behaviors (time of peak proportion after release is noted in parentheses): straight path (10 minutes), search circle (20 minutes), orientation (40 minutes), gyration (60 minutes, Iken et al., 2001). UV application skewed the distribution of pre-settlement behaviors towards early (straight path) and away from late stage (orientating and gyrating) pre-settlement behaviors (Figure 2.3). Zoospores may be spending more time searching for areas shaded from UV, as other flagellated marine organisms have shown increased settlement in locations with reduced or no UVR (Gleason et al., 2006). The increased time spent in the early pre-settlement behavior could delay or halt progression to later stage pre-settlement behaviors if shaded microhabitat isn’t encountered. The methods presented here, modeled after other studies at brown algal zoospore sensory ability (Iken et al., 2001; Iken et al., 2003; Amsler & Neushul, 1989b; 1990; Iken et al., 2001; Iken et al., 2003) may be a useful way to assess changes in swimming behaviors due to environmental stressors (physical and biological) in all brown algae, and possibly all flagellated, motile, algal spores. Variability in space and time can have meaningful impacts on motile spore behavior and function. The significance of the blocking term in all analyses performed in this study indicated that the baseline level of zoospore function was a product of the health of the parent plant, and/or environmental conditions at time of release, on that given day. This effect has  31 been shown in coral larvae as well: larval performance and susceptibility to environmental conditions depended on the day of release from their parent (Cumbo et al., 2013). The slight variations in performance and/or susceptibility among days underscore the importance of incorporating this into experimental practices; release experiments should be performed using a large number of parents. Moreover, the variability in performance and/or susceptibility to environmental conditions highlights the genetic variability in zoospores from a single release event, which will ultimately dictate the organism’s ability to adapt to changing climate conditions.  Temperature plays a major role in determining the latitudinal and vertical tide height distribution of kelps, as well as dictating the timing of reproduction and magnitude of seasonal growth (Graham et al., 2007). High temperature and high CO2 concentrations caused reductions in swimming speeds, and when combined caused greater numbers of non-motile spores. Additionally, high temperature conditions combined with UVA exposure mechanically damaged remaining motile spores. After all of these bottlenecks, the total number of spores successfully arriving at the substrate would be reduced in putative future climate conditions. Although I did not determine the amount of settled zoospores resulting from motility impairments in this experiment, the impairments that I documented suggest that these combinations of stressors may cause reductions in the number of successfully settling spores. Moreover, even if zoospores did successfully attach to the substratum, they may have settled in unsuitable locations due to reductions in the amount of spores searching for suitable microclimate environments. The magnitude of this effect is an important next step in determining ripple effects to progressive ontogenetic stages, and will be considered in the following research chapter. Lastly, the relative resilience of the swimming characteristic RCD/SPD (thought to be a useful response variable in assessing environmental stressor impacts on zoospore motility) to most experimental treatments indicates that exploring straight stress effects may not uncover the full picture of climate impacts on kelp zoospore function, because environmentally-forced changes in behavioral decisions may be just as important as straight impairment via stress.  32  Chapter 3 The interactive effects of temperature, CO2, and UV radiation on kelp zoospore settlement, adhesion, and germination  3.1 Synopsis  Understanding how changes in multiple interacting climate variables affect species performance can help make predictions for the status of future populations, and ultimately their associated communities. This can be complicated in species with multiple life history stages that may have varying degrees of sensitivity to environmental stressors. Kelps have a biphasic, heteromorphic, life history cycle, and are integral species within their community, forming the structure and habitat of communities in the nearshore marine environment. I experimentally tested the effects of increased temperature, CO2 concentrations, and UV exposure on settlement, adhesion, aggregation, and germination of zoospores produced by an intertidal kelp (Egregia menziesii). I found that transition rates from settled to germinated spores were reduced at high temperature, but only in the presence of UV radiation. The interaction of temperature and CO2 affected the aggregation of settled spores, causing overdispersion in experimental treatments relative to the control treatment. Furthermore, high temperatures decreased adhesion of settled and germinated spores subjected to water motion, indicating that high temperatures may affect the synthesis or effectiveness of adhesive material. The non-additive interactive effects of multiple climate stressors on kelp performance in this study highlight the necessity of fully-factorial, multi-factor experiments when making predictions of climate impacts on species performance.   33  3.2 Introduction Climate models indicate that there will be shifts in multiple environmental stressors in the future, such as sea surface warming, ocean acidification, and changes in the light environment (IPCC, 2013). Business as usual scenarios regarding greenhouse gas emissions indicate that atmospheric CO2 concentrations could reach 1000 ppm by the end of the century and cause ocean acidification. Average surface temperatures could increase 5°C in turn causing average ocean temperatures to rise, and decreased cloud cover resulting from dissipation as the ocean warms could allow for more light (including UV) incident to the earth’s surface, and (IPCC, 2013). The rate at which these changes are occurring is unprecedented on decadal and millennial scales (IPCC, 2013), with growing concern for the response of organisms in terrestrial, marine, aquatic, and polar ecosystems to such rapid change (Parmesan, 2006).  Numerous studies on a suite of marine organisms suggest that microscopic life history stages are more vulnerable to environmental stress than later ontogenetic stages (Coelho et al., 2000; Veliz et al., 2006; Muller et al., 2008; Kroeker et al., 2013). Environmental stress tolerance in microscopic stages plays a critical role in determining population dynamics, zonation patterns, and individual- and species-specific survivorship rates (Raffaelli & Hawkins, 1996; Rai & Gaur, 2001). For example, ocean acidification causes reduced development in mollusk and sea urchin early life history stages, and reduced metabolism and survival in mollusk larvae (Kroeker et al., 2013). Furthermore, the gradient in settled spore size seen in different species of arctic kelps corresponds to UV tolerance: smaller sized spores are more susceptible to high UV levels than larger sized spores (Swanson & Druehl, 2000). This susceptibility, in turn, corresponds to the depth distribution of kelp species: larger sized spores are found in shallow waters where UV intensity is greater, and smaller sized spores are found in deeper water where UV intensity is lessened (Swanson & Druehl, 2000). Changes in environmental conditions that result in shifting population structure of habitat-forming species could affect the persistence of entire communities.  34 The impact of change in a single environmental stressor can not only be life history stage specific (Coelho et al., 2000; Veliz et al., 2006), but also species specific, and even habitat specific (Muller et al., 2008). In the case of increasing UV impacts on life history progression of kelp, germination and growth rates decrease with increased UV (Coelho et al., 2000). Additionally, the energetic cost of photoprotection can cause a delay in ontogenic development following UV exposure (Roleda et al., 2009). However, the impact of change in a single environmental stressor is more straightforward to predict than the combined impacts of multiple environmental stressors. Single factor experiments limit inferences to future outcomes of climate change due to the uncertain nature of multiple interacting stressors (Hoffman et al., 2003). Future predictions forecast the simultaneous shifting of multiple climate variables (IPCC, 2013), so including multiple stressors in experimental procedure is necessary in determining interactive effects (Crain et al., 2008). It is therefore important to determine the vulnerability of early ontogenetic, microscopic stages to multiple climate stressors, especially in species such as kelps that have a large impact on their associated community. Kelps (Laminariales, Phaeophyceae) are habitat and structure forming species found in temperate coastal waters and in deep-water habitats of tropical regions (Graham et al., 2007a; Santelices, 2007). Along the Pacific coast of North America, these ecologically and economically important species support highly diverse, multi-trophic, and energy rich communities spanning the intertidal and subtidal zones (Graham et al., 2007b). All kelps have biphasic, heteromorphic life histories that are conspicuously dominated by macroscopic sporophytes, while the rest of the life history cycle is microscopic (Graham et al., 2007b). Zoospores are released from sporangia and must then find the substrate, settle, adhere to the substrate, and germinate. Following germination, spores develop into microscopic male and female gametophytes that must settle within 1 mm of each other for successful sexual fertilization (Reed, 1990). Furthermore, aggregations or clumps of settled spores increase the likelihood of fertilization (Muth, 2012), and protect lower layers of spores from environmental stress (Roleda et al., 2006). The vast majority of research on responses of kelp microscopic life history stages to environmental change has focused solely on UV radiation (see review in Bartsch et al., 2008), with little work on the interactive effects of multiple climate change stressors (but see  35 Hoffman et al., 2003; Muller et al., 2008; Gaitán-Espitia et al., 2014 for 2-factor experiments). Fully-factorial manipulations become logistically difficult with greater than 2 factors (Fredersdorf et al., 2009), making it complicated to understand specifically how kelps will respond to near future conditions. To date, there have been few 3-factor, fully factorial climate change studies on microscopic marine organisms (but see Studer & Poulin, 2013 as an example), and no studies on the interactive effects of climate change on the kelp Egregia menziesii (Turner) a mid-sized, canopy forming kelp found in the shallow subtidal to low intertidal zones along the Pacific coast of North America. This study aimed to determine the interactive effects of multiple shifting climate variables on early life history stages of an intertidal, foundation species. More specifically, this research focused on how temperature, UV, and CO2 interact to affect settlement, germination, aggregation, and adhesion of Egregia zoospores. 3.3 Methods Egregia menziesii (order Laminariales, Phaeophyceae) is a habitat-forming species ranging from Alaska to Baja California Sur (Abbott & Hollenberg 1976). As true of all kelps, it has a heteromorphic life history cycle dominated by the macroscopic sporophyte but dependent on the progression of an individual from a motile zoospore through the remainder of its life history cycle. Once kelp zoospores find a suitable location at the substrate and achieve initial attachment, they reel in their flagella, and external mucilage (a polysaccharide) aids in initial adhesion before cell wall secretion begins that will anchor them to the substrate (Boney, 1981). This process of settlement occurs within 24 hours and is followed shortly by the germination stage, which occurs within 48 hours. Germination is the phase where gametophytes, which are initially sexually indistinct, develop germ tubes that eventually become the vegetative growth of male and female gametophytes. These timelines are important as experiments were initiated after 24 hours post release (see below) in order to determine treatment effects on adhesion, as all zoospores have had sufficient time to anchor themselves to the substrate, and development, as individuals may have germinated within this time duration.  36 To test the hypothesis that multiple environmental stressors interact to affect kelp settlement, germination, aggregation, and adhesion, I designed an experiment with three environmental variables. Treatment combinations included a fully factorial implementation of the following: seawater temperature (low, high), seawater CO2 concentration (ambient, elevated), and UV (with or without UVA application). Temperature treatments were established by immersing 20 L buckets containing seawater into a flowing water table set to 12°C to the height of the water in the bucket for the low temperature treatment (achieved temperatures averaged 10.7°C), or by propping 20 L buckets on wire racks just above the water level of the flowing seawater tank for the high temperature treatment (achieved temperatures averaged 17.5°C). Inorganic carbon concentrations were established by bubbling ambient air via Gast MOA-P101-AA Vacuum/Air Compressors using Sierra Instruments mass flow controllers (C100L, Monterey, CA, USA) directly into buckets for the ambient CO2 treatment (achieved CO2 concentrations averaged 387 ppm).  Ambient air was combined with a 5% CO2 gas mixture using mass flow controllers to attain the elevated CO2 treatment level (achieved CO2 concentrations averaged 1086 ppm).  Lastly, UV levels were established by suspending a 4-foot, 4 bulb strip fixture (Seattle Lighting, Seattle, WA) with 2 bulbs that emitted PAR and 2 additional bulbs that emitted UV radiation (280-400 nm, Phillips UVA F40/350BL, SolArc Systems Inc., Barrie, Ontario, Canada) for the “with UV” treatment. For the “without UV” treatment, 4-foot, 2 bulb strip fixtures (Seattle Lighting, Seattle, WA) were suspended above tanks with 2 bulbs that emitted PAR (F40/T12 Cool White Lights, Philips, Canada). Elevated UV intensity was set to 12 W/m2 (Biologically effective doses are generally those encountered on cloudless summer days, and therefore equivalent to the UV exposure Index level of 11, or extreme exposure, for UVA at sea level, WHO), which was determined using a UVX Radiometer, while ambient light levels were roughly 40-60 µmol photons/m2/sec. On two consecutive days in late July 2012, 100 Egregia menziesii reproductive fronds were collected from the west side of Cattle Point Lighthouse on San Juan Island, WA. Fronds were then transported in a cooler, sterilized in an iodine solution, rinsed with deionized water and sterile seawater, and stored in a cool, dark refrigerator inside of an opaque garbage bag between seawater-dampened paper towels. This process was repeated the following day, after which reproductive material was transported to UBC Vancouver and stored in a refrigerator  37 at 4°C. After 48 hours from the time of collection, the first batch of reproductive fronds was used for experimental trials on August 1, 2012. The second batch of collected reproductive fronds was used for trials on the following day (August 2, 2012); thus, two days elapsed between collection and experimental work in all cases. All experimental replicates at 12°C were performed on the first day (this temperature was randomly chosen to go first), and all experimental replicates at 18°C were performed on the second day. Although temperature was perfectly nested within day, every effort was made to ensure that there were no additional external confounding factors.  For the release, 15-20 cm portions from 20 reproductive E. menziesii fronds were put into a 20 L bucket and filled 1/3 full with treatment water. The fronds were left for roughly 30 minutes until the zoospore concentration in the treatment water reached 5-10 spores per mm2 (determined using a hemocytometer). The treatment water was then poured into cylindrical plastic petri dishes each containing 1 microscope slide. Plastic wrap was fitted to the surface of the treatment water to maintain desired CO2 concentrations, and the lid was fitted tightly to the petri dish and secured with tape. This prevented significant CO2 dissolution from the treatment water over this 24-hour period. The petri dishes were placed into a walk-in incubator set to 12°C on the first day, and 18°C on the second day. The walk-in incubator had lights that were set to a 12:12 hour cycle (12 hours on and 12 hours off) with UVA lights timed to turn on for 4 hours in the middle of the daylight cycle (in order to mimic peak UV hours of 10 am to 2 pm). After 24 hours the petri dishes were removed and placed into incubators that did not have UVA lights. In between the first and second days, the walk-in incubator was then reset to 18°C and the release process was then repeated for the remaining replicates.   To quantify the initial number of settled and germinated spores, 2 petri dishes were removed from the incubator at a time, and the microscope slides were removed and placed under an Olympus BX51WI videoscope fitted with an Olympus DP21 camera. Five photos were taken from randomly selected locations under 40X magnification, and then mounted parallel to water flow in a high speed recirculating water flume (Ecological Mechanics, Rochester NY). The flume was set to 4.5 m/sec and the slides were kept in the flume mount for 1 minute at this speed. The slides were then removed and placed under the microscope,  38 and 5 additional photos were taken from randomly selected locations to quantify the number of settled and germinated spores following hydrodynamic stress. To estimate loss of individuals in the flume, photos were analyzed by counting the number of settled and germinated spores both before and after placing the slides in the flume. Four dependent variables were calculated from these photo data: (1) the pre-flume proportion of germinated spores out of the total number of spores, (2) an aggregation index using pre-flume data to determine patchiness of settlement, and the proportion of (3) settled and (4) germinated spores that remained post-flume. An average for each slide was taken from the 5 photo sub-replicates for each of these 4 dependent variables. The aggregation index (Im, Hurlbert, 1990) was calculated to determine patchiness of settlement using the combined total number of pre-flume settled and germinated spores using the following equation: € Im=s2−mm2−s2Qs+1, where s2 is variance, m is the mean, and Qs is total sample size. Im values less than 1 indicate overdispersed spores, values equal to 1 indicate randomly distributed spores, and values greater than 1 indicate an aggregated distribution of spores.  Data were analyzed in fully factorial multivariate ANOVAs using SPSS (IBM V. 22) statistical software with the treatments of temperature, CO2, and UV as fixed factors, and the aforementioned 4 dependent variables. Data on the pre-flume proportion of germinated spores of the total number of spores were logit transformed (€ log10(y + 0.02)1− (y + 0.02), Warton & Hui, 2011) to conform to equal variance assumptions. Im data did not conform to equal variance assumptions (Levene’s test for equality of error variances, p=0.024), even after transformation. However, because all among group sample sizes were equal and overall sample size was high, this ANOVA test was determined to be robust to slight deviations from the assumption of equal variances (Whitlock & Schluter, 2009). Pre-flume counts of settled and germinated spores were used as covariates in the analyses on post-flume settled and germinated spores. These data were square root transformed to conform to equal variance assumptions.  I expected that the number of spores remaining after exposure to hydrodynamic stress would be related to the number of spores on the slide before placement in the flume; thus, I predicted that the covariate (pre-flume spore counts) should be significant in our analyses.  39 Further, if the climatic variables, alone or in combination, were to influence the number of settled or germinated spores after exposure to the flume, such an effect should emerge as a significant interaction between the variable(s) in question and the covariate. 3.4 Results Pooling across the CO2 treatments, in low temperature treatments, the mean proportion of germinated spores was similar at 0.40 ± 0.04 (SE) without the UV treatment and 0.40 ± 0.05 with the UV treatment (p=0.022, Figure 3.1, Table 3.1). Warming without UV reduced the mean proportion of germinated spores to 0.08 ± 0.01, and warming in combination with UV application further reduced the mean proportion of germinated spores to 0.04 ± 0.01 (Temperature × UV, p=0.022, Figure 3.1, Table 3.1). The significant main effects of temperature were not considered as the interactions term was significant, while all other main effects and higher order interactions were not significant (Table 3.1).  Table 3.1 ANOVA results for the impact of temperature, CO2, and UV on the initial proportion of germinated spores of the total number of spores. Data were logit transformed to conform to equal variance assumptions. * Indicates significance.   Sums of Squares DF F Sig Temperature 5.937 1 76.447 *<0.001 CO2 0.076 1 0.980 0.326 UV 0.395 1 5.086 *0.027 Temperature X CO2 0.130 1 1.673 0.200 Temperature X UV 0.426 1 5.490 *0.022 CO2 X UV 0.037 1 0.481 0.490 Temperature X CO2 X UV 0.266 1 3.424 0.068 Error 15.829 70      40   Figure 3.1 Temperature, CO2, and UV effects on the pre-flume proportion of germinated spores of the total count of pre-flume settled and germinated spores (Temperature x UV, p=0.022). Proportions greater than 1 are due to random sampling (randomly selecting areas without germinated spores initially, and with germinated spores following hydrodynamic stress). Data are presented as the absolute value of (logit) transformed data. Grey bars are treatments without UV, and black bars are treatments with UV. Error bars are standard error.   Patterns of zoospore aggregation depended on the combined influences of temperature and CO2 (Temperature × CO2, p=0.050, Table 3.2), but did not depend on UV. Pooling across UV treatments, at ambient CO2, the aggregation index value was 1.58 ± 0.21 (SE) at low temperature, and 1.18 ± 0.04 at high temperature. At elevated CO2, the aggregation index value was 0.98 ± 0.20 at low temperature, and 1.19 ± 0.11 at high temperature. All other main effects and interaction terms were not significant (Table 3.2).  0	  0.1	  0.2	  0.3	  0.4	  0.5	  0.6	  0.7	  Low	  Temperature,	  Ambient	  CO2	  Low	  Temperature,	  Elevated	  CO2	  High	  Temperature,	  Ambient	  CO2	  High	  Temperature,	  Elevated	  CO2	  Initial	  proportion	  of	  germinated	  spores	  Without	  UV	  With	  UV	   41  Table 3.2 ANOVA results for the impact of temperature, CO2, and UV on the aggregation index (Im). * Indicates significance.  Sums of Squares DF F Sig Temperature 0.191 1 0.408 0.525 CO2 1.722 1 3.668 0.059 UV 1.079 1 2.299 0.134 Temperature X CO2 1.865 1 3.974 *0.050 Temperature X UV 1.505 1 3.207 0.078 CO2 X UV 1.345 1 2.865 0.095 Temperature X CO2 X UV 0.296 1 0.631 0.429 Error 33.798 72      Figure 3.2 Temperature, CO2, and UV effects on Im, the aggregation index (Temperature × CO2, p=0.050). Grey bars are treatments with UV, and black bars are treatments without UV. Error bars are standard error.   The number of settled spores retained following hydrodynamic stress was significantly affected by increased temperature and UV radiation (covariate × Temperature × UV, p=0.045, Table 3.3). The relationships between pre and post flume settled spores were 0	  0.5	  1	  1.5	  2	  2.5	  Low	  Temperature,	  Ambient	  CO2	  Low	  Temperature,	  Elevated	  CO2	  High	  Temperature,	  Ambient	  CO2	  High	  Temperature,	  Elevated	  CO2	  Im	  (Aggregation	  Index)	  Without	  UV	  With	  UV	   42 extremely similar at low temperature (y = 0.661x - 0.259 without UV, and y = 0.581x + 0.192 with UV), indicating roughly 60% retention spores settled following hydrodynamic stress (Figure 3.3). At high temperature, retention was reduced, and more drastically so in the absence of UV, with roughly 22% retention at high temperature without UV (y = 0.221x + 1.154), and 50% retention at high temperature with UV (y = 0.502x + 0.062, Figure 3.3). All other interaction terms including the covariate were not significant (Table 3.3).  Table 3.3 ANCOVA results for the impact of temperature, CO2, and UV on the number of settled spores remaining, dependent on the covariate initial number of settled spores. Data were square root transformed to conform to equal variance assumptions. * Indicates significance of terms including the covariate.   Sums of Squares DF F Sig Temperature 0.127 1 0.850 0.360 CO2 0.029 1 0.193 0.662 UV 0.319 1 2.131 0.149 Temperature X CO2 0.238 1 1.593 0.212 Temperature X UV 1.273 1 8.510 0.005 CO2 X UV 0.241 1 1.609 0.209 Temperature X CO2 X UV 0.148 1 0.986 0.324 Pre-flume Counts 12.669 1 84.663 *<0.001 Pre-flume X Temperature 0.228 1 1.525 0.221 Pre-flume X CO2 0.032 1 0.215 0.644 Pre-flume X UV 0.238 1 1.593 0.212 Pre-flume X Temperature X CO2 0.033 1 0.217 0.643 Pre-flume X Temperature X UV 0.623 1 4.166 *0.045 Pre-flume X CO2 X UV 0.065 1 0.437 0.511 Pre-flume X Temperature X CO2 X UV 0.179 1 1.198 0.278 Error 9.577 64      43  Figure 3.3 Temperature and UV effects on the relationship between initial number of settled spores on number of settled spores remaining (square root transformed, Temperature × UV, p=0.045). Low temperature without UV (solid black line), low temperature with UV (dashed black line), high temperature without UV (solid gray line), and high temperature with UV (dashed gray line).    The number of germinated spores retained following hydrodynamic stress was significantly affected by increased temperature (covariate × Temperature, p=0.007, Table 3.4). At low temperature, 65% of germinated spores were retained following hydrodynamic stress (y = 0.653x + 0.047), while at high temperature retention was reduced, with 37% of germinated spores retained following hydrodynamic stress (y = 0.365x + 0.151, Table 3.4, Figure 3.4).  0 0.5 1 1.5 2 2.5 3 0 1 2 3 4 5 Number of settled spores remaining (square root transformed) Initial number of settled spores (square root transformed) Low Temperature, Without UV Low Temperature, With UV High Temperature, Without UV High Temperature, With UV  44  Table 3.4 ANCOVA results for the impact of temperature, CO2, and UV on the number of germinated spores remaining, dependent on the covariate initial number of germinated spores. Data were square root transformed to conform to equal variance assumptions. * Indicates significance of terms including the covariate.   Sums of Squares DF F Sig Temperature 0.184 1 1.383 0.244 CO2 0.120 1 0.900 0.346 UV 0.223 1 1.674 0.200 Temperature X CO2 0.089 1 0.664 0.418 Temperature X UV 0.011 1 0.082 0.775 CO2 X UV 0.019 1 0.145 0.704 Temperature X CO2 X UV 0.007 1 0.056 0.814 Pre-flume Counts 3.495 1 26.218 *<0.001 Pre-flume X Temperature 1.035 1 7.763 *0.007 Pre-flume X CO2 0.002 1 0.019 0.892 Pre-flume X UV 0.005 1 0.035 0.852 Pre-flume X Temperature X CO2 0.031 1 0.235 0.629 Pre-flume X Temperature X UV 0.158 1 1.184 0.281 Pre-flume X CO2 X UV 0.004 1 0.030 0.864 Pre-flume X Temperature X CO2 X UV 0.033 1 0.245 0.622 Error 8.532 64      Figure 3.4 Temperature effects on the relationship between initial numbers of germinated spores on number of germinated spores remaining (square root transformed, p=0.007). Low temperature (solid black line), and high temperature (solid gray line). 0 0.5 1 1.5 2 2.5 3 0 1 2 3 4 Number of germinated spores remaining (square root transformed) Initial number of germinated spores (square root transformed) Low Temperature High Temperature  45 3.5 Discussion  Environmental change plays a meaningful role in the population dynamics of kelps, because life history transitions are regulated by environmental conditions (Graham et al., 2007b). Kelps undergo a series of life history transitions within a short period of time, including release of spores from parental sporophytes, settlement, germination, and gametogenesis (the differentiation of male and female gametophytes). The timing of life history transitions in most kelp species is synchronized by changes in the environment, therefore shifts in average conditions associated with climate change will likely affect the kelp life history cycle. I investigated the effects of increases in temperature, CO2, and UV radiation associated with climate change and found significant impacts on transition rates of settled to germinated spores, aggregation of spores, and retention of settled and germinated spores following hydrodynamic stress.  In present day conditions, once kelp spores have settled germination quickly follows. In conditions predicted for the end of the century, germination was reduced. Twenty-four hours after initial release, 40% of kelp spores had germinated in the low temperature (present day) treatment, whereas in the high temperature (end of century) treatment less than 8% of spores had germinated (Figure 3.1). Although delays in germination are not detrimental initially, and certainly not after 24 hours, persistence of this delay could eventually impact the number of new recruits to that population if temperatures remain consistently high enough to inhibit germination. Life history transitions are regulated by the number of daylight hours, the magnitude of blue light, and changes in water temperature (Graham et al., 2007b). Elevated average seawater temperature can therefore impact the life history cycle of an organism that is reliant on temperature shifts as a cue to move through different ontogenetic phases.  Combined with elevated temperatures, UV light further reduced germination numbers to 4% (although the overall pattern reflected a strong main effect of temperature and a relatively modest interactive effect between temperature and UV). Germination of zoospores was reduced following UV exposure in Laminaria spp. (Dring et al., 1996), and caused delays in mitosis until DNA and ultrastructural damage was repaired (Buma et al., 1996; Steinhoff et al., 2008). High temperatures combined with UVR decreased germination  46 proportions in the kelp Saccorhiza dermatodea as well (Steinhoff et al., 2011), but results from another study have shown that Arctic Laminaria digitata show enhanced formation of gametes with the addition of UVA at elevated temperatures (high temperature with UVA, Muller et al., 2008).  The combination of elevated temperature and CO2 reduced the aggregation index value of settled spores (Figure 3.2), indicating that spores settle in a less clumped fashion, which could ultimately reduce fertilization and recruitment rates. Settling in aggregations not only increases the likelihood of fertilization (Muth, 2012), but also reduces environmental stressors to lower layers of spores (Roleda et al., 2006). Although warming slightly reduced the negative impacts of elevated CO2 concentrations on the aggregation index, the decreases in pH associated with ocean acidification may be the negative factor contributing to overdispersion in spore settlement. Reductions in pH associated with ocean acidification impaired sensory and homing abilities of fish larvae (Munday et al., 2009), and disrupted the ability of fish to detect olfactory cues and locate suitable adult habitat (Dixson et al., 2010), which were attributed to a disruption in the transfer of chemosensory signals. Little is known about kelp zoospore sensory mechanisms, although there is some indication that spores are chemotactic (Amsler & Neushul, 1989b), and this chemotaxis could also be disrupted by elevated temperature and CO2. Settling zoospores may no longer be able to detect or sense aggregations of conspecifics, or may be directing resources to stress-coping mechanisms rather than sensory mechanisms.  Although kelp zoospores are only single-celled, they have the ability to repair mechanical damage from environmental stressors (Roleda et al., 2006). Directing resources to stress coping mechanisms may also affect a zoospores ability to successfully adhere to the substrate if environmental conditions are not optimal and complete exudation of adhesive material from adhesion vesicles does not occur. Elevated temperatures may have past the threshold of optimal performance of this species (Luning & Neushul, 1978), therefore the exuded mucilage may be less effective at high temperatures, reducing a settled or germinated spores ability to remain attached in areas of high water movement. In this study, proportions of settled and germinated spores were reduced at elevated temperatures (Figures 3.3, 3.4), which intertidal and subtidal species such as E. menziesii would experience frequently in situ under future conditions. Additionally, kelp zoospores that are attempting to adhere to the  47 substrate lack a protective cell wall (Henry & Cole, 1982), which make them vulnerable to external stressors during this transitional phase. Interestingly, UV exposure mediated some of the negative effects of high temperature on the number of settled spores retained following hydrodynamic stress (Figure 3.3). Compared to low temperature treatments, retention rates at high temperatures were 12% without UV and 28% with UV (untransformed data). UV exposure has been shown previously to mediate the negative impacts of increased temperature: productivity and gamete formation was enhanced at elevated temperatures when exposed to UVA in Laminaria digitata, an Arctic kelp (Muller et al., 2008). Overall, retention of settled spores was greatest at high temperatures in low-density situations, but this benefit went away as density increased. The mechanism behind this trend is unclear, and because of the marginal p-value of the covariate × temperature × UV interaction term (p=0.045), this trend should be interpreted with caution. Climate change research is only starting to address the impacts of near future levels of rising environmental stressors, as it is much easier to find significant impacts with large amounts of environmental change. This study addresses increases in temperature, CO2 concentration, and increasing UV radiation intensity using ecologically relevant levels predicted to occur by the end of the century (IPCC, 2013). Although this study used short term exposure in determining future climate impacts on the life cycle of kelps, these laboratory experiments are the best available method to address climate impacts on kelp populations as accurate temperature and CO2 concentration manipulation in the field is not yet possible and kelps do not survive for prolonged periods of time in the laboratory setting.  Temperature appeared to be of over-riding importance during this transitional phase of adhesion through germination, but there were interacting impacts by the addition of CO2 and UV stressors. Increased CO2 partially mediated the negative effects of temperature on overdispersion of settled spores (Figure 3.2), while UV further decreased the initial germination of spores (Figure 3.1). UV also mediated some of the negative effects of temperature on adhesion of settled spores, and showed the greatest retention rates of all the treatments at low densities (Figure 3.3). This highlights the importance of considering multiple stressors in experimental simulations of climate change as combined effects, as in  48 this study, can be non-additive and difficult to predict from the isolated effects of single stressors.  49  Chapter 4 Spatial variation in the sign and magnitude of experimental warming effects on juvenile and adult kelp  4.1 Synopsis  Shifts in temperature associated with climate change can have variable impacts on organisms, and the sign and magnitude of these impacts may depend upon local context. For Saccharina sessilis, a habitat-forming intertidal kelp, the impacts of warming may vary with local density and position in the intertidal zone. To test the effects of warming along an elevation gradient in the intertidal zone, I manipulated S. sessilis densities and experimentally imposed periodic thermal stress in the field across an intertidal gradient. Juvenile S. sessilis recruitment was unimodally related to shore level, peaking near the center of the species’ vertical distribution and falling off at the upper and lower distributional limits. Experimental warming tended to have mildly positive effects on recruitment in most situations, except for upper zone low density plots where episodic warming negatively impacted recruitment. Heat manipulations also had context-specific effects on adult plant growth performance; seasonal increases in blade number and canopy cover were slightly enhanced by warming in high-density plots but greatly reduced by warming in low-density plots. Our results demonstrate that extreme temperature events can affect multiple life history stages and may depend upon both environmental (e.g. intertidal height) and biological (e.g. adult density) context.  4.2 Introduction  Current trends in greenhouse gas emissions may cause average air and sea surface temperatures to continue to rise, with a corresponding increase in the frequency of extreme high temperature events (IPCC, 2013). Although many studies implicitly examine the ecological effects of increasing mean temperatures (see Angilletta, 2009), the greater  50 frequency and severity of extreme events may also have important ecological consequences (Vasseur et al., 2014). In habitats where environmental temperatures already closely approach the limits of organismal tolerance, such as coral reefs (see review in Hughes et al., 2003) and mussel-dominated intertidal shores (Connell, 1972; Harley, 2008), increases in the frequency and severity of high-temperature events may also be important drivers of ecological patterns (e.g. changes in habitable space). Mortality of habitat-forming species such as corals and mussels is of particular ecological significance, because important community-level changes may occur when these ecological dominants are reduced or removed from their respective ecosystem (Harley, 2011).  Macroalgae, like corals and mussels, are important habitat-forming species and can play an important role in regulating community structure (Dayton, 1975). For example, intertidal macroalgae facilitate recruitment by providing shelter (Wieters, 2005), decreasing irradiance to the substrate (Holbrook et al., 1991), and reducing thermal stress (Dayton, 1975; Burnaford, 2004). The stress-ameliorating functions of habitat-forming macroalgae are important to the entire community (Leonard, 2000; Burnaford, 2004), including other life history stages of the habitat-forming species that will eventually grow to replace the existing canopy. Establishing the degree to which these species are vulnerable to climate variability is a high priority for research, because their response could indirectly mediate changes in intertidal diversity. Studies addressing temperature variation in space and time indicate that seaweeds are susceptible to anthropogenic warming. Rising temperatures will likely cause shifts in species distribution and abundance, depending on their thermal tolerance and adaptability (Harley et al., 2012). Increasing ambient temperatures can inhibit photosynthesis and growth, alter sex ratios and reproductive output, and eventually cause mortality in seaweeds (see review in Bartsch et al., 2008). These physiological effects result in recognizable ecological patterns in space and time, with important consequences for algal populations (e.g. Harley, 2003). On the other hand, increasing temperature can also increase growth for subtidal algae (O’Connor, 2009), although relatively few studies have shown such positive effects of warming on intertidal taxa.  Because adult canopies ameliorate environmental stressors to the understory where microscopic stages are found (Bertness et al., 1999), habitat-forming species may play an  51 integral role in buffering stressors on sub-canopy organisms, including other life history stages of conspecifics. Conversely, high densities of large, canopy-forming parent plants may decrease light, available space, and other resources for sub-canopy organisms. This trade-off between adults being facilitators versus competitors to understory individuals, including new recruits, may therefore depend on local environmental conditions (Leonard, 2000; Bruno et al., 2003). I tested the hypothesis that negative population-level effects of extreme thermal events can be mediated/ameliorated by positive, density dependent intraspecific interactions. I predicted that experimentally reduced adult kelp density would exacerbate the negative effects of an extreme thermal event on adult condition (plant size) and kelp recruitment. Conversely, adult size and juvenile recruitment following extreme thermal events should be more similar to unheated treatments when recruits experience natural densities of adult kelps. I further predicted that juvenile sporophytes would recruit in greater numbers closer to the parent plant holdfasts in experimentally warmed areas. Regarding adult kelps, I predicted that simulated warming would have a disproportionately negative impact on adult canopy cover and blade number (a proxy for plant size) in low density plots, because the isolated kelps in these plots may be more susceptible to warming in the absence of stress-ameliorating neighbors. Lastly, I predicted that the response of other species, particularly the chiton Katharina tunicata, would also depend on the combination of adult kelp density and warming, with chitons disproportionately negatively impacted when warming and low kelp density coincided. 4.3 Methods Saccharina sessilis (formerly Hedophyllum sessile, Phaeophyceae, Heterokontophyta, Lane et al., 2006) is a kelp (order Laminariales) that is found on rocky intertidal shores in the low to mid intertidal zone from Alaska to central California (Abbott & Hollenberg, 1976). S. sessilis has a biphasic life history: macroscopic sporophytes persist year round with reproductive sori appearing in the fall and winter months, and microscopic gametophytes developing from released zoospores throughout this period (see review in Bartsch et al.,  52 2008). Juvenile sporophytes begin to appear in late spring, and continue to emerge throughout the summer. This study was conducted at Botany Bay near Port Renfrew, British Columbia, Canada (48° 31.542 N, 124° 26.908 W) from May to September of 2010. Botany Bay is in the Juan de Fuca Provincial Park (BC Parks) on the wave-exposed southwest coast of Vancouver Island. The tidal regime is semi-diurnal, with spring low tides occurring during daylight morning hours in the summer. Mean air temperature in Port Renfew during the summer (May – September) is 13.8°C (climate normals from Environment Canada, National Climate Data and Information Archive). Daily maxima are typically higher; in 2010, summer daily maximum air temperatures were generally between 15 and 20°C with occasional excursions above 30°C (Figure 4.1). Figure 4.1 Daily maximum air temperatures for Port Renfrew, BC, for the summer months of May through September 2010. Arrows indicate the dates during which experimental warming occurred. Data were obtained from Environment Canada, Weather Office, National Climate Data and Information Archive.  I factorially manipulated temperature (heated or un-heated) and S. sessilis adult density (one solitary plant or five plants in an aggregation) in forty 0.32 m2 plots (10 of each treatment combination). Plots were established in early May 2010 by removing all macroscopic S. sessilis individuals except for those forming the plot density treatments (see 05101520253035May Jun Jul Aug Sep OctMaximum air temperature (°C) 53 below). Treatments were established by randomly selecting an area of 100% cover of S. sessilis, then removing all but the treatment number of plants. Pre-experimental canopy cover for all plots was initially 100%, and a similar amount of reproductive source material (and therefore microscopic gametophytes) was assumed for all plots at the beginning of the experiment. Plots were dispersed along a 50 m bench, with tide heights measured for each plot and treatments randomly assigned (Table 4.1). In the low density plots, the centermost individual was selected with a radial clearing of all other S. sessilis plants 50 cm from the outside of the holdfast. In the high-density plots, the five-centermost individuals were selected, with a radial clearing of all other S. sessilis plants 50 cm from the center of the aggregation (therefore all 40 plots were equally sized). Data were also taken in 10 similarly sized, randomly selected plots at the beginning and end of the experimental period to determine the location’s baseline population number of recruits (plants with a single blade < 5 cm), single-bladed juveniles (plants with a single blade > 5 cm), and adults (plants with > 1 blade), and the number of blades on adult plants (a proxy for total plant size).   Table 4.1 Mean tidal heights for all treatment plots, and for treatment plots when split into lower and upper zones. Range and standard error of the mean are also reported.  Zone Mean (m) Range (m) SE Solitary Un-Heated ALL 1.71 1.11 0.11 Solitary Heated ALL 1.76 0.83 0.09 Aggregate Un-Heated ALL 1.78 0.88 0.08 Aggregate Heated ALL 1.81 0.74 0.07 Solitary Un-Heated UPPER 1.97 0.26 0.05 Solitary Heated UPPER 1.97 0.37 0.07 Aggregate Un-Heated UPPER 1.95 0.31 0.06 Aggregate Heated UPPER 1.99 0.40 0.07 Solitary Un-Heated LOWER 1.45 0.84 0.14 Solitary Heated LOWER 1.55 0.46 0.09 Aggregate Un-Heated LOWER 1.60 0.51 0.09 Aggregate Heated LOWER 1.64 0.33 0.07  Temperature manipulations during a single low tide were performed monthly to simulate occasional extreme warming events in June, July, and August. Ten Coleman Procat Portable Catalytic Heaters were suspended upside-down from PVC frames so that the heating element was parallel to and roughly 30 cm above the substratum. The ten heaters were placed above the lower zone heated plots for 60 min, and then moved to the remaining heated plots  54 for 60 min. Because the lower zone plots were heated first, the time between warming and submersion was similar for both lower and upper zone heated plots. Temperatures were not manipulated in control plots. Temperature data during the warming manipulations were collected using iButtons (Dallas Semiconductor) placed on the substratum in the center of the plot, although it should be noted that warming effects would have diminished with distance from the center of the plot (Allison, 2004). For analysis, temperatures within each plot were averaged over the three applications of experimental warming. On the days immediately preceding extreme warming treatments juvenile S. sessilis recruits were counted and the distance of each individual recruit to the center of the plot was determined. The center of the plot was the holdfast for low adult density plots, and the center of the aggregation for high adult density plots. Once distances were determined, the individuals were removed. Abundance of the associated chiton Katharina tunicata was also determined. Treatment effects were assessed on the subsequent sampling trip the following month (i.e. canopy cover impacts by heat treatments completed in July were assessed during the August sampling trip prior to that month’s heat manipulations). To track changes in size and condition of adult plants retained in treatment plots, the number of blades was recorded (a single blade was defined by a continuous separation of material from tip to attachment at the holdfast) and photos were taken to assess changes in canopy cover. Percent cover data for S. sessilis canopy cover was analyzed photographically using ImageJ.  Due to unanticipated non-linearities in juvenile recruitment across the intertidal gradient in this study, plots were further subdivided into lower zone (0.9-1.81m, Canadian Chart Datum) and upper zone (1.82-2.2m). In cases where the slope of a regression line changes at a particular break point, change point regression analysis can be used to test for such a break and estimate the position of the break point, if one indeed exists, and the regression slopes on either side of the break. I applied this type of analysis to the recruitment data in order to separate the data into upper and lower zones and thereby allow data within each zone to conform to the assumptions of ANCOVA, which assumes linear relationships between the covariate (tide height) and the dependent variable (recruitment). The change point regression analysis identified a significant break in the relationship; the position of the break was determined to be 1.81 m. The estimates for the parameters described above, plus or minus the approximated standard error, are: change point position (meters above chart  55 datum) = 1.81 ± 0.05; low shore slope = 335 ± 162; high shore slope = -1487 ± 307. Note that the slope is positive but shallow below the break point (i.e., recruitment increases slightly from very low on the shore up to the break point), but shifts to steep and negative above the break point (i.e., recruitment decreases fairly dramatically as one moves further upshore from the break point). An alternate approach that ensured equal sample sizes among treatment combinations in each zone involved recatagorizing 2 plots within 2 cm of the break point, and yielded similar results. I chose to use the alternate approach to divide our data in order to ensure equal sample sizes and equal variances among treatment groups. This division of the data allowed for the inclusion of a linear covariate (tide height) for each zone. Juvenile recruitment in upper and lower zones was analyzed separately with 2-factor ANCOVAs, with warming and adult density as the main effects and tide height as a covariate. The average distance of each recruit from plot center was analyzed in a similar fashion, with warming and adult density as the main effects and tide height as a covariate. To assess the effects of extreme warming treatments on adult S. sessilis and Katharina population characteristics, I employed two-way factorial ANCOVAs with tide height as a covariate using all 40 plots. When the effect of tide height was trivial (p > 0.25), it was removed from the analyses. The effects of warming and adult density on adult plants were assessed by calculating the relative change in the average number of blades per plant (September data over June data) and the relative change in canopy cover (August percent cover over June percent cover, square root transformed). Katharina responses to experimental treatments were explored for absolute abundance (averaged across months for each plot) and change in abundance (the difference between June and September within each plot).  Homogeneity of recruitment surface (rock, encrusting coralline algae, articulated coralline algae, Mytilus spp.) was determined from photos in order to rule out spatial differences among heat and adult density treatment plots (or other confounding factors) at the beginning of the experiment. Only the topmost, visible layer was included in the determination of percent cover. Using standardized May data (e.g. May % cover rock /(1 - May % cover S. sessilis)), a MANOVA was used with adult density as a fixed factor and tide height as a covariate. In order to meet the assumptions of the analysis (homogeneity of variances), data were logit transformed (log (x/1-x)). All statistical analyses were performed  56 in SPSS Statistics v. 22 (IBM), except for the change point regression analysis, which was performed in JMP v 9.0.2. 4.4 Results In the unmanipulated control plots, the distribution of individuals in each size class bin shifted over the course of the summer. At the beginning of the summer there were 14.3 ± 4.5 (SE) adult individuals with 2.5 ± 1.0 blades per plant in each plot. At the end of the summer, these averages transitioned to 9.5 ± 2.2 adults per plot with 8.4 ± 1.8 blades per adult; therefore, the increase in the number of blades over the course of the summer was 5.9 blades/plant. Recruit numbers transitioned from 79.1 ± 51.1 individuals at the beginning of the summer to 25.4 ± 20.6 at the end of the summer, while juvenile numbers transitioned from 15.8 ± 15.4 individuals to 52.7 ± 31.9 individuals.  On the days on which temperature was experimentally manipulated, there was a significant effect of the heat treatment (p < 0.001) but not adult density on surface temperature (Table 4.2). The grand mean of the daily average iButton temperatures was 13.7 ± 0.3°C (± SE, un-heated plots) and 24.1 ± 0.5°C (heated plots) during the application of the heat treatment, therefore, the magnitude of the warming events averaged 10.4°C. These heating events mimicked rare high temperature events at this field site (Figure 4.1).   Table 4.2 Two-way ANOVA for the dependent variable average iButton temperatures. * Indicates significance.  DF Sums of Squares F Ratio Prob > F Adult Density 1 0.241 0.084 0.773 Warming 1 776.104 271.527 *<0.001 Adult Density x Warming 1 0.553 0.193 0.663 Error 36 102.889      In the lower zone, the number of recruits increased with increasing tidal height (tide height p=0.010, Table 4.3a), In the upper zone, recruitment decreased with increasing tidal height (tide height p=0.001, Figure 4.2a, Table 4.3b), with context-specific effects of warming and adult density on the total number of recruits (adult density x warming, p=0.019, Table 4.3b). Therefore, although periodic warming had no significant effect on recruitment  57 low on the shore (p=0.331, Table 4.3a), the effect of warming was notably negative in upper zone, low density plots, and slightly positive in upper zone, high density plots (Figure 4.2b). There were no effects of warming or adult density on the average distance of juvenile recruits from plot center (Table 4.4).  Table 4.3 Three-way ANCOVA for the dependent variable summer juvenile kelp recruitment in the a) lower zone, and b) upper zone. * Indicates significance. a)  DF Sums of Squares F Ratio Prob > F Adult Density 1 17226.320 0.886 0.362 Warming 1 19489.968 1.002 0.333 Tide Height (covariate) 1 167253.758 8.601 *0.010 Adult Density x Warming 1 138.693 0.007 0.934 Error 15 291694.642       b)  DF Sums of Squares F Ratio Prob > F Adult Density 1 30239.094 1.678 0.215 Warming 1 3925.128 0.218 0.647 Tide Height (covariate) 1 291631.774 16.182 *0.001 Adult Density x Warming 1 125052.902 6.939 *0.019 Error 15 270327.826        58  (a) (b)  Figure 4.2 (a) Variation in juvenile recruitment along the vertical tide height gradient. The line of fit was estimated by a change point regression analysis. The squares represent plots in the lower zone, and the circles represent plots in the upper zone. Open squares/circles represent low adult density plots, while closed squares/circles represent high adult density plots. Gray markers indicate un-heated plots and black markers indicate heated plots. (b) Total number of juvenile recruits in the lower and upper zones (significant term is the upper zone interaction term, adult density × warming, p=0.019) in low and high adult density plots, with and without heat treatment. The gray bars are the un-heated means while the black bars are the heated treatment means. Error bars are standard error.  0 100 200 300 400 500 600 700 800 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 Total number of juvenile recruits Tide height (m, Canadian chart datum) Upper Zone, Low Density, Un-Heated Upper Zone, Low Density, Heated Upper Zone, High Density, Un-Heated Upper Zone, High Density, Heated Lower Zone, Low Density, Un-Heated Lower Zone, Low Density, Heated Lower Zone, High Density, Un-Heated Lower Zone, High Density, Heated 0	  100	  200	  300	  400	  500	  600	  High	  Density	  Low	  Density	  High	  Density	  Low	  Density	  Lower	  Zone	   Upper	  Zone	  Total	  number	  of	  juvenile	  recruits	  Un-­‐Heated	  Heated	   59  Table 4.4 Two-way ANOVA for the dependent variable average distance of juvenile recruits from plot center.   DF Sums of Squares F Ratio Prob > F Adult Density 1 10.852 2.227 0.144 Warming 1 0.096 0.020 0.889 Adult Density x Warming 1 10.643 2.185 0.148 Error 36 175.396       Over the course of the experiment, changes in the number of blades per adult sporophyte and in adult canopy cover were affected by warming in context-specific ways. The number of blades per plant increased in all treatments, but the magnitude of this increase depended on warming and adult density (adult density × warming, p = 0.008; Figure 4.3a, Table 4.5). Warming had little influence on high-density plots, but it limited the seasonal increase in blade number in plots containing only a single adult (Figure 4.3a). The relative change in canopy cover also responded in a context-dependent fashion. In low density plots, heating reduced the seasonal increase in canopy cover, whereas in high density plots, heating resulted in slightly accelerated the increase in canopy cover (adult density × warming, p = 0.002; Figure 4.3b, Table 4.6).  Table 4.5 Two-way ANOVA for the dependent variable relative change in average number of adult blades per plant (September data divided by June data). * Indicates significance.  DF Sums of Squares F Ratio Prob > F Adult Density 1 6.020 5.069 *0.031 Warming 1 3.215 2.707 0.109 Adult Density x Warming 1 9.218 7.761 *0.008 Error 36 42.756       Table 4.6 Two-way ANOVA for the dependent variable relative change in adult canopy cover as the summer progressed (August data over June data, square root transformed). * Indicates significance.  DF Sums of Squares F Ratio Prob > F Adult Density 1 0.075 0.972 0.331 Warming 1 0.300 3.881 0.057 Adult Density x Warming 1 0.906 11.714 *0.002 Error 36 2.783      60  (a)  (b)  Figure 4.3 (a) Relative change in average number of adult blades per plant (September over June data) in solitary and aggregate plots, with and without heat treatments (adult density × warming, p=0.008). (b) Relative change in adult canopy cover over the course of the experiment (August percent cover over June percent cover, square root transformed) in solitary and aggregate plots, with and without heat treatments (adult density × warming, p=0.002). The gray bars are the un-heated means while the black bars are the heated treatment means. Error bars are standard error.  There were no significant effects of adult S. sessilis density or warming on the average number of Katharina per plot when Katharina densities were averaged over the 0	  0.5	  1	  1.5	  2	  2.5	  3	  3.5	  4	  High	  Density	   Low	  Density	  Relative	  change	  in	  average	  number	  of	  blades	  Un-­‐Heated	  Heated	  0	  0.2	  0.4	  0.6	  0.8	  1	  1.2	  1.4	  1.6	  1.8	  2	  High	  Density	   Low	  Density	  Relative	  change	  in	  canopy	  cover	  (square	  root	  transformed)	  Un-­‐Heated	  Heated	   61 course of the experiment (Table 4.7). However, there were treatment-specific patterns in how Katharina densities changed over the course of the experiment, and the interactive effect of adult density × warming on the change in Katharina abundance was significant (p=0.028, Table 4.8, Figure 4.4). Katharina abundance increased in heated, high-density plots, while in all other plots Katharina abundance decreased.  Table 4.7 Two-way ANOVA for the dependent variable average number of Kathrina tunicata.  DF Sums of Squares F Ratio Prob > F Adult Density 1 1.702 0.237 0.629 Warming 1 0.189 0.026 0.872 Adult Density x Warming 1 2.627 0.366 0.549 Error 36 258.569       Table 4.8 Two-way ANOVA for the dependent variable change in average number of Katharina tunicata (September – June count data). * Indicates significance.  DF Sums of Squares F Ratio Prob > F Adult Density 1 28.900 3.128 0.085 Warming 1 12.100 1.310 0.260 Adult Density x Warming 1 48.400 5.239 *0.028 Error 36 9.239       62   Figure 4.4 Change in average number of Katharina tunicata (September – June count data) in low and high adult density plots, with and without heat treatments (adult density × warming, p=0.028). The gray bars are the un-heated means while the black bars are the heated treatment means. Error bars are standard error.  Results from the MANOVA testing for differences in plot recruitment surface (rock, encrusting coralline algae, articulated coralline algae, and Mytilus spp. percent cover) indicated that there were no significant differences of each substratum type among treatment plots (Table 4.9a). There was a significant effect of the covariate tide height on recruitment surface (p=0.010) such that articulated coralline algae and rock percent cover increased slightly from low to high tidal height, while encrusting coralline algae decreased from low to high tidal height (Table 4.9b).  -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Change in Katharina tunicata abundance Un-Heated Heated High Density   Low Density  63  Table 4.9  (a) MANOVA (Wilk’s Lambda) for the dependent variables percent cover of rock, Mytilus spp., encrusting coralline algae, and articulated coralline algae. Logit transformed, standardized data were used to conform to homogeneity of variance assumptions. * Indicates significance.   DF Value F Ratio Prob > F Adult Density 4 0.863 0.870 0.497 Warming 4 0.849 0.981 0.438 Adult Density x Warming 4 0.940 0.348 0.842 Tide Height 4 0.560 4.320 *0.010 Error 32       (b) Effect of the significant MANOVA term tide height on the dependent variables percent cover of rock, Mytilus spp., encrusting coralline algae, and articulated coralline algae. * Indicates significance.  DF Type III SS F Ratio Prob > F Rock 1 0.821 5.606 *0.026 Mytilus spp. 1 <0.001 0.000 0.998 Encrusting Coralline Algae 1 1.442 8.518 *0.007 Articulate Coralline Algae 1 0.373 7.320 *0.012 Error Rock 35 3.662   Error Mytilus spp. 35 6.845   Error Encrusting Coralline Algae 35 4.233   Error Articulate Coralline Algae 35 1.272    4.5 Discussion  Temperature is one of the fundamental drivers of biological rates and processes, and thermal variability has well-known effects on individuals, populations, and communities (Angilletta, 2009; Kordas et al., 2011; Vasseur et al., 2014). However, the effects of high temperatures and other forms of stress can be ameliorated via positive interactions between individuals both within and among species (Scrosati & DeWreede, 1998; Bruno et al., 2003). This suggests that the importance of thermal stress should depend on both the severity of that stress and the ecological context – timing, population density, and community composition - in which the stress is applied. In this study, I found this to be the case for an ecologically important, habitat forming kelp. Experimental warming had important effects on kelp recruitment and growth, but these effects were highly context dependent. The impact of  64 warming depended strongly on the density of adult kelps and, in the case of recruitment, on shore level. The effects of experimental warming on adult sporophytes appear to be a relatively straightforward case of direct stress effects modified by population density. The thermal optimum for growth and fertility in S. sessilis is between 12-20°C (Luning & Neushul, 1978), and this range was exceeded, albeit briefly, when experimental warming was imposed. In general, the effect of warming on seasonal growth tended to be neutral or slightly positive at high densities, where neighbor proximity eased temperature stress, and negative at low densities, where the effects of high environmental stress were not mediated by conspecifics. For example, seasonal growth in the number of blades per plant only increased 150% in heated, low density plots while in all other plots plants grew to over 300% of initial blade density. Higher canopy cover seen in low density un-heated plots was most likely due to an increase in resources (light and space) created by the experimental clearing, which was not seen in low density heated areas where solitary individuals were more vulnerable to thermal stress.  Patterns of S. sessilis recruitment were superficially similar to patterns of adult blade growth. In the upper zone, the effects of warming caused reduced recruitment, but only when adult density was low. Because the upper intertidal limits of seaweeds are typically set by physiological stressors (Connell, 1972; Underwood, 1980; Harley, 2003), and early ontogenetic stages of kelps are particularly vulnerable to such stressors (Bartsch et al., 2008), the reduced number of recruits in the low density, upper zone plots likely reflects greater environmental stressors in this area of reduced canopy cover and longer emersion times. At our field sites, spring tide emersion times in the lower and upper S. sessilis zones were roughly three and five hours, respectively, and kelp near their upper vertical limit may have surpassed a threshold for abiotic stress where the canopy had been experimentally reduced. Furthermore, although I predicted that average distances of juvenile recruits would decrease with the warming treatment to take advantage of the stress ameliorating effects of neighbor proximity and adult canopies, especially when adult density was low, recruitment location was not affected by episodic warming at this level. It is possible that juveniles recruiting to locations absent of a canopy or close neighbor proximity may not have persisted if warming  65 treatments continued, or if resources became limiting, but this was not addressed in the present study. In contrast to low adult density situations, the effects of warming in high adult density plots tended to be slightly positive for recruitment, blade growth, and canopy cover. Although none of these positive effects were significant in univariate tests using high adult density plot data only (data not shown), the unexpected trend was consistent among response variables and warrants some discussion here. Warming is not simply a stressor; it can also have important biological benefits. Although the positive effects of warming on individual growth for ectotherms that are below their thermal optima are well known (Angilletta, 2009), it seems unlikely that such effects would be important here seeing as the experimental warming was only imposed for a few hours in total. However, the brief periods of warming may have served as triggers for specific life history transitions (Page & Kingsbury, 1968). In our case, warming may have triggered the transition from gametophyte to sporophyte (spermatozoid release to oogonium fertilization and sporophyte growth), as initiation of reproduction in seaweeds with heteromorphic life histories can require temperature change (Breeman, 1988). Heat treatments could have boosted rock temperatures, and therefore gametophyte temperatures, up from average water temperatures of 10-12°C (Fisheries & Oceans Canada, 2010), which are below their optimum range for reproduction (Luning & Neushul, 1978). As thermal pulses can result in greater reproduction when compared to constant temperature applications (Page & Kingsbury, 1968), and temperature change is often necessary for reproduction in heteromorphic seaweeds (Breeman, 1988), the thermal pulses achieved in experimentally heated plots (except upper zone, solitary, heated plots) may have triggered a similar reproductive response in S. sessilis, which could be consistent in species with similar life history strategies. Thermal stress can also stimulate branching and growth in some plants; enhanced rhizome and branch production and/or growth following brief periods of high temperature stress have been observed in several terrestrial plants (Pumisutapon et al., 2012 and references therein). Whether or not similar phenomena occur in kelps is unclear. Overall, the extent to which thermal pulses associated with climate variability may affect morphology, growth, reproduction, and other life history transitions in natural populations is an important avenue for future research.   66 In high-density plots, it is also possible that direct negative effects of warming, if any, could have been offset by indirect benefits mediated by the inhibition of competitors or grazers. Our surveys indicated that warming pulses had a significant long term impact on Katharina abundance, with increasing numbers of this grazer at summer’s end in high density, heated plots where a kelp recruitment pulse was noted (Figure 4.4). It appears that tolerable or perhaps even favorable conditions existed in heated, aggregate plots for both S. sessilis and Katharina. Warm conditions may have stimulated primary production (Stromgren, 1977), and the Katharina may have been responding to greater food availability. Furthermore, Katharina is known to facilitate S. sessilis by removal of competitors (Paine, 1984). However, since the increase in Katharina abundance was not seen in all areas where a recruitment pulse was noted, it is unclear whether Katharina played any additional role in indirectly facilitating recruitment of juvenile S. sessilis in my study.  Many habitats feature a mosaic of thermal microclimates, and both gradual warming and extreme temperature events are known to have context-specific effects on a variety of organisms (Weiss et al., 1988; Harley, 2008; Nicole et al., 2011). For intertidal macroalgae, position on the shore and the density of intraspecific facilitators could dictate whether warming has positive, neutral, or negative effects on recruit numbers and individual growth. Periodic heat waves may increase spatial patchiness in upper zone areas as juveniles rely more on higher adult densities, yet juveniles and adults decrease in number and size, respectively.  The occurrence of brief high-temperature events corresponded with neutral or weakly positive responses in a portion of the range, but a possible overall reduction of habitable space. This suggests that, for any given species, the ecological effects of global warming will not be simply “bad” or “good”, but will be a mix of positive and negative impacts – even at the local scale – as dictated by the environmental and biological context. This pattern emerged despite the fact that heat treatments were applied for only one hour, once a month, for three months. As extreme temperature events will most likely occur for the entirety of emersion during daytime low tides, and possibly for multiple, consecutive days, the importance of adult density for stress amelioration may intensify and the effects of local context may become even more pronounced.   67  Chapter 5 Concluding remarks 5.1 Synopsis Anthropogenic climate change has affected polar, terrestrial, marine, and aquatic ecosystems across the globe, with shifts in ecosystem composition, ecosystem function, biodiversity, species interactions, and species abundance, distribution, and survivorship (Walther et al., 2002; Parmesan, 2006; Halpern et al., 2008; Mayhew et al., 2008; Bellard et al., 2012). Reductions in greenhouse gas emissions from a variety of sources could reduce the severity of change expected by the end of the century, but change is inevitable to some degree (IPCC, 2013). Understanding the repercussions of change associated with global climate change should be a priority for species that have pivotal roles within their community, as effects on integral species can have cascading community consequences.  The complex interactions of multiple shifting climate variables hinder the ability of scientists to make broad sweeping conclusions about climate change impacts on species performance (Crain et al., 2008). Therefore, targeting key community members as research priorities to determine such impacts is essential. Kelps are integral community members because they provide food, structure, and protection to a diverse array of algae, invertebrates, fishes, and marine mammals (Graham et al., 2007). However, they have biphasic life history strategies (Fritsch, 1948) that further complicate drawing straightforward conclusions about climate change impacts. The research included in this dissertation helps elucidate how climate change may affect an ecologically important taxon’s growth and life cycle progression. In splitting up the experiments in the manner outlined in my research chapters, the impacts of climate change on each of the following stages were considered: free-swimming zoospores, settling zoospores, settled spores, germinated spores, and juvenile and adult sporophytes. The general trends resulting from the studies performed in this dissertation indicate that very small increases in temperature have widespread effects on kelp performance, both by itself and in combination with additional climate stressors. More  68 specifically, temperature increases impact the progression of the life history cycle, and together with CO2 and UV affect the performance of the individual. In this concluding chapter, I will further describe the impacts of projected levels of climate stressors on the different stages of the kelp life history cycle. Furthermore, I will offer additional thoughts on the surprising, positive, context dependent effects of increasing temperature on juvenile kelp recruitment. I will also discuss the effects of climate on observed behavioral differences of motile and settling spores. Lastly, I will speculate about future population-level implications of climate alterations to the life history cycle, incorporating discussion on multiple climate stressors. Before concluding with suggestions for future research stemming from the results presented here, I will discuss the shortcomings and limitations of the methodologies used in my research chapters, and suggest improvements for future studies.  5.2 Temperature and the life history cycle Increased temperature, CO2, and UV had marked impacts on kelp performance, behavior, and the probability of transitioning through key life stages. Increased temperature caused a series of reductions in the proportion of individuals transitioning through the different life history cycle stages. In Chapter 2 I demonstrated that temperature increases caused reductions in the speed of motile spores, and when combined with increased CO2 or UV caused reductions in the number of motile spores with concurrent increases in the number of mechanically damaged spores. A reduction in the number of ‘healthy’ spores reaching the substrate could result in a winnowing in the number of settling spores. In Chapter 3, temperature increases, as a single stressor and as an interacting stressor, caused overall reductions in the proportion of germinated spores, and further reductions in germinated spores that successfully adhered to the substrate. Several studies on kelp species indicate that temperature plays an integral role in regulating the timing of life history cycle transitions (Graham et al., 2007), and the elevated temperatures may have hindered or halted the process of germination (Steinhoff et al., 2011) as it may have been at their upper thermal tolerance threshold (Luning & Neushul, 1978). Reductions in adhesion rates of settled and germinated spores at elevated temperatures could be due to decreased performance at high temperature, which could have impaired the  69 efficiency of subcellular processes involved in attachment. Furthermore, increased temperature and CO2 caused overdispersion of settling spores when compared to control treatments, which could reduce fertilization rates and ultimately adult sporophyte abundance.   In addition to increasing average temperatures associated with climate warming, extreme or episodic warming events are likely to increase in frequency in the near future (IPCC, 2013). In Chapter 4, experimental thermal pulses mimicking such warming events caused changes in the distribution and recruitment of the intertidal kelp, S. sessilis. The surprising aspect of Chapter 4 was the increase in juvenile recruitment in experimentally warmed areas, except in warmed areas of low adult density high on the shore. Thermal pulses can act as triggers for life history cycle transitions (Page & Kingsbury, 1968), and may have catalyzed an increase in fertilization rates and therefore recruitment numbers, but this hypothesis has yet to be confirmed with experimental evidence. Conversely, recruitment numbers decreased in areas of low adult density high on the shore, where the thermal pulses were most likely too stressful without the proximity of neighbors facilitating stress amelioration (Scrosati & DeWreede, 1998; Bruno et al., 2003). There was a slight trend towards positive effects of temperature on recruitment, but the statistical support for this trend was weak and its biological significance is uncertain. In addition, the overwhelming negative effects of global climate change (Harley et al., 2006; Parmesan 2006; Halpern et al., 2008; Hoegh-Guldberg & Bruno, 2010; Harley et al., 2012; Kroeker et al., 2013) make it difficult to see slight increases in recruitment as a bright side to this global problem. 5.3 Functional and behavioral changes following UV exposure As temperature played a significant role in life history cycle progression in Chapters 2, 3, and 4, UV radiation altered functionality and behavior in microscopic kelps. In Chapter 2, motile zoospores exhibited the swimming behavior characteristic of mechanical damage (“wobbling,” Iken et al., 2001) when UV was experimentally applied. This swimming behavior was an indication that an individual exhibiting this behavior was unfit, and would not transition through pre-settlement behaviors and ultimately adhere to the substrate (Iken et al., 2001). UV can cause ultrastructural damage, and can also damage DNA, proteins, and enzymes (Roleda et al., 2005), all of which can impact flagellar motility. Furthermore, there  70 were increased proportions of zoospores exhibiting early pre-settlement behaviors, and decreased proportions of zoospores exhibiting late stage pre-settlement behaviors in treatments exposed to UV. Zoospores may be spending more time searching for microenvironments shaded from UV (Gleason et al., 2006), and may run out of stored energy used to fuel motility as zoospores deplete stored energy more quickly in stressful environments (Fukuhara et al., 2002). Reduced time spent searching for suitable microenvironments could lead to selection of an unfavorable settlement location if stored energy is low and zoospores settle rather than become immobile in the water column (Reed et al., 1999). Lastly, in Chapter 3, UV radiation exacerbated the negative effects of elevated temperature on life cycle progression, with further reductions in the proportion of germinated spores when UVA was applied. When considering the sum of UV effects on the kelp life history cycle presented in Chapters 2 and 3, increases in UV intensity following decreased cloud cover associated with climate change may have substantial impacts on kelp populations if effects ripple through to the adult sporophyte stage. 5.4 Kelp population predictions, and multiple, interacting climate stressors  It is unclear whether local adaptation in kelp populations will be able to keep up with the rate of change of average seawater temperatures. However, a study on temperature tolerance of Egregia menziesii, the study organism in Chapters 2 and 3, indicated that this species is locally adapted to temperature profiles across latitude (Henkel & Hoffman, 2008). Plasticity and adaptation may not be able to temper the negative effects of increasing temperature in populations with locally adapted temperature profiles (Kelly et al., 2011). Therefore, poleward distributional shifts may occur as species are physiologically stressed near range boundaries (Sorte & Hoffman, 2004) and may be excluded and/or replaced with species that have a larger thermal range and/or a higher thermal optimum (e.g., low latitude species, Harley et al., 2006).  Reductions in the proportions of several life history stages and transitions due to global change (Chapters 2, and 3) could indicate overall reductions in abundance of macroscopic sporophytes. Although I saw increased recruitment of juvenile sporophytes with  71 increasing temperature (Chapter 4), negative effects at one stage may outweigh the positive effects at another stage. Compaction of habitable vertical zonation space is likely as physiological stressors at the upper vertical limit reduce adult size and recruitment numbers, which in turn reduce facilitation in stress amelioration by neighboring individuals. As the field study in Chapter 4 incorporated solely thermal stress, it is unclear how the addition of multiple interacting climate stressors may or may not change this pattern. What is clear is that multiple interacting climate stressors can create variable responses in performance of kelp, including additive, synergistic, and antagonistic outcomes.  This dissertation is novel in that it addressed the effects of three interacting climate stressors on various stages of the kelp life history cycle. The marginally significant effects of the third-order interaction terms throughout chapters 2 and 3 suggests that the number of replicates should be increased in three factor experiments in order to have more power in detecting significant effects, if any. I did find significant temperature × CO2 and temperature × UV interactive effects, and significant main effects, on microscopic life history stages. Although increased CO2 did decrease swimming speed and when combined with increased temperature caused decreased motility of zoospores and affected settlement aggregations, temperature and UV appeared to have the most consistent main and interactive effects on microscopic kelp (see above). 5.5 Limitations of methodologies  A research chapter on temperature, CO2, and UV impacts on the microscopic gametophyte and sporophyte stages was forgone due to a number of limiting factors. First, kelps are methodologically difficult to keep in the lab for extended periods of time because they require water movement. Second, intertidal kelps experience regular emersion in nature, which is difficult to mimic in the lab. Most importantly, keeping intertidal species immersed in treatment water for the duration necessary to reach the microscopic gametophyte and sporophyte life cycle stages would not occur in nature, and therefore outcomes resulting from the previously planned long term laboratory experiment would not necessarily accurately predict the responses of individuals in natural populations. Furthermore, the resources required to achieve a successful, well designed, fully factorial implementation of this forgone  72 study were not available or achievable, and the logistics were not feasible without a large support team. Regardless of this limitation, short-term lab experiments are a value tool in projecting how kelp will perform under future climate conditions. Chapters 2 and 3 were designed to be brief in duration: kelps were completely immersed in experimental treatment water for less than 36 hours in total, as low intertidal species will experience these immersion durations during neap tidal cycles. As the experiments performed in this dissertation were short term in duration, there was no intention to account for an organism’s ability to adapt and evolve to their environmental surroundings. Although short-term acclimation can occur over the course of longer time scales, the transitional processes studied in Chapters 2 and 3 of this dissertation occur over short time scales (less than 24 hours), and acclimation may not be possible during these brief periods. Additionally, changes in environmental stressors associated with climate change are not only expected to change in average conditions, but also in variability (i.e. higher highs and lower lows, with regards to temperature, IPCC, 2013). For example, the temperature pulses applied in the field experiment addressing the impacts on juvenile and adult kelp (Chapter 4) were meant to simulate such episodic warming events, and not the projected rise in average oceanic and air temperatures (IPCC, 2013). Secondly, because different species were used in Chapter 4 than Chapters 2 and 3, I was not able to build a population model to make inferences on the effects of global change on population projections. However, this is an important next step in climate research on structure and habitat-forming species, as changes to their distribution and abundance can impact entire communities (Graham et al., 2007). Modeling shifts in survivorship of the different life history stages of kelp under variable climate scenarios would be a valuable tool for preparing management strategies for economically important ecosystems such as kelp forests.  The field of experimental ecology has made rapid progress on incorporating climate change variables into common practice. As the field of ecology is tasked with understanding how organisms interact and are affected by their environment, the most effective projects are those that can successfully manipulate climate stressors in the field (i.e. Chapter 4 of this dissertation). However, the logistical difficulties of manipulating oceanic CO2 concentrations, for example, make laboratory simulations necessary until further  73 advancements in technology and methodologies occur. Until that time, holistic approaches to ecological questions incorporating climate change, such as looking at complete life history cycle impacts of climate change on performance, are ideal in thoroughly understanding the future state of ecosystems. 5.6 Suggestions and conclusions Intertidal organisms interact and persist in their environment despite constant biotic and abiotic stress. In Chapters 2 and 3 I simulated future climate scenarios in a laboratory setting to determine how multiple interacting stressors impact various processes throughout the microscopic stages of the life history cycle. In Chapter 4 I looked at the transition of microscopic to macroscopic stages, and considered climate impacts on adults as well. The importance of this dissertation, in part, was moving towards the end goal of a complete population model projecting multiple climate impacts on kelp.  One very basic unanswered question whose importance emerged during the progress of this dissertation was the timing of sporulation of both E. menziesii and S. sessilis. In fact, the timing of release of motile zoospores is known for very few kelp species (see Dayton, 1972 for low tide sporulation in the intertidal kelp Postelsia palmaeformis; and Amsler & Neushul, 1989a for dawn/dusk sporulation in the subtidal kelp Nereocystis luetkeana). Knowing reproductive release timing in the field, especially for intertidal kelps, will clarify the environmental conditions under which they are attempting to settle. Of primary importance is when in the tidal cycle spores are released; this is simply because the environmental stressors of settling during low tide are very different than the environmental stressors of settling during high tide. In fact, kelps may ensure reproductive success by synchronizing release with favorable environmental conditions (Kinlan et al., 2003), and avoiding stressful environmental conditions (Amsler & Neushul, 1989a). A second study idea spawned from the work of Chapter 2 would be to look at the overall effects of ocean acidification on motility of flagellated organisms. Because I found reductions in swimming speed of motile zoospores at increased concentrations of CO2, a trend which has also been found in larval stages of marine invertebrates (Morita et al., 2010), I hypothesized that this was due to reductions in pH rather than increases in CO2 as the  74 activation of the enzyme that fuels flagellar motility (dynein ATPase) is pH sensitive (see Woolsey & Ingermann, 2003 for sperm activation in steelhead trout, Oncorhynchus mykiss). If this pattern is conserved across a wide range of taxa, as is highly possible since the enzyme (dynein ATPase) that fuels flagellar motility is most likely the same across taxa (Gibbons, 1988; Lobban & Harrison, 1994; Woolsey & Ingermann, 2003) decreasing pH associated with ocean acidification could have catastrophic effects on sperm, larvae, zoospores, and all other ciliated and flagellated marine organisms. There are several successful ways to track shifts in populations and communities associated with climate change. For community studies, long-term data sets are valuable, but few and far between as continuous funding is difficult to secure. A potential alternative is to mine through historical data to make baseline comparison studies between past and present individual and community characteristics (see Harley, 2011), and I see this as a valuable source of information for climate change scientists developing future studies. For population projections, multi generational studies to look at susceptibility and adaptation of species to climate change stressors will be important in targeting future management priorities. The field of ecology is moving towards a more integrative approach in understanding the functioning of populations and ecosystems (Queirós et al., 2014). This is due largely in part to advancements in technology, as ecologists use experimental data to create population models to project future outcomes of experimental manipulations. By combining empirical and theoretical techniques we can more accurately estimate outcomes resulting from varying degrees global change. Once model parameters are determined, simulations can be run for each of the climate scenarios outlined in the IPCC report (2013), so we will better understand the varying degrees of future impact. Meta-analyses have already taken the first step in incorporating the broad scope of climate change ecology data into synthesis papers (see Kroeker et al., 2013), and the trends of open access and data sharing are the first steps in incorporating climate change research into meta-analyses so that the large amount of research can be distilled into fewer, more highly impactful papers that will reach a larger audience.  Climate change studies on integral community species such as kelp that exhibit multiple life history stages are valuable in gathering a better understanding of realistic impacts on species persistence. By looking at motile (Chapter 2), microscopic (Chapter 3), and macroscopic (Chapter 4) stages of the life history cycle, my research has shown that  75 climate change will have negative impacts on microscopic stages of kelp from the motile stage through the germination stage, and context dependent effects on macroscopic stages depending on neighbor proximity and vertical position on the shore. Although it is possible that we may see increased recruitment numbers with warming, the overall vertical distributional extent may be compacted, which combined with reduced survivorship in microscopic stages could cause an overall decline in kelp populations. 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