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Zooplankton community composition across a range of productivity regimes in coastal British Columbia Mahara, Natalie 2018

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  ZOOPLANKTON COMMUNITY COMPOSITION ACROSS A RANGE OF PRODUCTIVITY REGIMES IN COASTAL BRITISH COLUMBIA by  Natalie Mahara  B.Sc., The University of British Columbia, 2015  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Oceanography)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   May 2018  © Natalie Mahara, 2018  ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled:  ZOOPLANKTON COMMUNITY COMPOSITION ACROSS A RANGE OF PRODUCTIVITY REGIMES IN COASTAL BRITISH COLUMBIA  submitted by Natalie Mahara in partial fulfillment of the requirements for the degree of Master of Science in Oceanography  Examining Committee: Evgeny Pakhomov, Earth and Ocean Sciences Supervisor  Brian Hunt, Institute for the Oceans and Fisheries Supervisory Committee Member  William Cheung, Institute for the Oceans and Fisheries Additional Examiner   Additional Supervisory Committee Members: Christopher Harley, Zoology Supervisory Committee Member     iii  Abstract Coastal British Columbia is composed of deep channels and shallow sills intricately woven around a collection of small islands, creating complex oceanographic conditions. Consequently, seasonal production varies up to several orders of magnitude throughout the region, with some regions undergoing large annual phytoplankton blooms, while others have permanently low phytoplankton biomass. The region from the northern Strait of Georgia (SoG) to Johnstone Strait (JS) has been vastly understudied from the perspective of zooplankton despite its importance to many higher trophic levels. The objectives of this study were to: a) describe the annual seasonal cycle of zooplankton in the northern SoG over the course of two years and examine how communities differed, and b) examine the spatial patterns in zooplankton community composition and abundance from the northern SoG to JS, a region spanning seasonally productive / stratified areas (northern SoG, eastern Discovery Islands (DI)) as well as permanently high-nutrient, low-chlorophyll (HNLC) regions (JS, western DI). There was a strong signal of intra-annual seasonality in zooplankton community dynamics in the northern SoG, separating into distinct winter, early spring, and summer – fall assemblages. Despite a six week difference in spring bloom timing between years, peak zooplankton abundance occurred within the same calendar week during both years and community composition was similar between years, indicating that there is likely resilience within the zooplankton seasonal cycle to short scale interannual changes in environmental conditions. Our spatial analysis indicated that the northern SoG, DI, and JS each had distinct zooplankton communities with key species and densities separating regions. We detected minimal overlap in the JS zooplankton community with the DI and northern SoG, indicating that while DI zooplankton are likely sourced from the SoG, JS zooplankton likely originate from Queen Charlotte Sound. The DI were comprised of both productive and HNLC regions, yet zooplankton abundance was highest in the mixed western DI channels. Intense tidal mixing in the DI likely supplies nutrients to stratified surface waters in the eastern DI, which in turn supply zooplankton to the western DI with low in-situ production. These results provide insight into how feeding conditions for higher trophic levels may vary throughout the region.   iv  Lay Summary Zooplankton are small animals in the water column that consume organic matter and cannot swim against strong currents. They are a very important link in marine food webs, acting as a source of food for many animals including fish, seabirds, and whales. Zooplankton and phytoplankton (their primary food source) are influenced by factors such as temperature, salinity, and ocean currents. The British Columbia coast is an important region for many different plants and animals. This is the first study to look at zooplankton species composition from the northern Strait of Georgia to Johnstone Strait, which covers a wide range of environmental conditions. We determined which species dominate across the region and how zooplankton communities may be connected to each other. Since some zooplankton species are better food quality than others, it is important to know which species are in each region and how zooplankton communities may shift with climate change.    v  Preface This thesis represents original, unpublished, independent work written by Natalie Mahara. The research questions in this thesis were created in collaboration with Evgeny Pakhomov and Brian Hunt. This work is part of the Hakai Institute Ocean Observing Program, with aims to “provide fundamental, year-round, long-term physical, chemical, and biological measurements of ocean conditions on the British Columbia coast”. Field sampling was conducted by members of the Quadra Island Ocean Monitoring program and the Salmon Coast Field Station. Laboratory analysis was conducted by Natalie Mahara and taxonomists from the Institute of Ocean Sciences in Sidney, British Columbia.  Analysis of data for this thesis was conducted by Natalie Mahara.   vi  Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Abbreviations ................................................................................................................. xiv Acknowledgements ......................................................................................................................xv Dedication .................................................................................................................................. xvii Chapter 1: Introduction ............................................................................................................... 1 1.1 Oceanography of coastal British Columba: Strait of Georgia to Johnstone Strait ..... 2 1.1.1 Strait of Georgia ...................................................................................................... 2 1.1.2 Discovery Islands .................................................................................................... 4 1.1.3 Johnstone Strait ....................................................................................................... 4 1.2 Purpose of this study ................................................................................................... 5 Chapter 2: Seasonal zooplankton development in a semi-enclosed basin: two years with different spring bloom timing ...................................................................................................... 6 2.1 Introduction ................................................................................................................. 6 2.2 Methods....................................................................................................................... 9 2.2.1 Field sampling ......................................................................................................... 9 2.2.2 Zooplankton taxonomic analysis .......................................................................... 10 2.2.3 Statistical analysis ................................................................................................. 10 vii  2.3 Results ....................................................................................................................... 12 2.3.1 Physical environment ............................................................................................ 12 2.3.2 Macronutrient concentrations ............................................................................... 12 2.3.3 Chlorophyll-a biomass .......................................................................................... 13 2.3.4 Zooplankton .......................................................................................................... 13 2.4 Discussion ................................................................................................................. 17 2.4.1 Comparing environmental conditions between years ........................................... 17 2.4.2 Robust seasonal succession in zooplankton communities despite species-level interannual variation ......................................................................................................... 18 2.4.3 Key zooplankton species: separating seasons ....................................................... 22 2.4.4 Implications for higher trophic levels ................................................................... 24 2.4.5 Limitations ............................................................................................................ 25 2.5 Conclusions ............................................................................................................... 26 2.6 Tables ........................................................................................................................ 27 2.7 Figures....................................................................................................................... 28 Chapter 3: Habitat mosaics and small-scale connectivity drive zooplankton composition and production in complex coastal environments ................................................................... 38 3.1 Introduction ............................................................................................................... 38 3.2 Methods..................................................................................................................... 41 3.2.1 Field sampling ....................................................................................................... 41 3.2.2 Zooplankton taxonomic analysis .......................................................................... 42 3.2.3 Statistical analysis ................................................................................................. 42 3.3 Results ....................................................................................................................... 43 viii  3.3.1 Physical environment ............................................................................................ 43 3.3.2 Macronutrient concentration ................................................................................. 44 3.3.3 Chlorophyll-a biomass .......................................................................................... 44 3.3.4 Zooplankton .......................................................................................................... 45 3.4 Discussion ................................................................................................................. 48 3.4.1 Persistent high-nutrient, low-chlorophyll regions in complex coastal regions ..... 48 3.4.2 Regional differences in zooplankton seasonality: a combination of in-situ production and advection .................................................................................................. 49 3.4.3 Broader implications ............................................................................................. 51 3.4.4 Limitations ............................................................................................................ 52 3.5 Conclusions ............................................................................................................... 54 3.6 Tables ........................................................................................................................ 55 3.7 Figures....................................................................................................................... 56 Chapter 4: Conclusions .............................................................................................................. 66 4.1 Strong zooplankton community succession in the northern Strait of Georgia ......... 66 4.2 Zooplankton communities in connected coastal environments ................................ 67 4.3 Consequences for outmigrating juvenile sockeye salmon ........................................ 67 4.4 Future directions ....................................................................................................... 68 References .....................................................................................................................................70 Appendix .......................................................................................................................................79 Sampling methodology ................................................................................................. 79 Strait of Georgia, additional data .................................................................................. 81 Strait of Georgia to Johnstone Strait, additional data ................................................... 85 ix  List of Tables Table 2.1 Summary of environmental conditions comparing 2015 and 2016 in the northern Strait of Georgia. ........................................................................................................................ 27 Table 3.1. Summary of environmental conditions comparing 2015 and 2016 at four core stations from the northern Strait of Georgia (QU39), the Discovery Islands (QU29, QU33), and Johnstone Strait (JS2). ...................................................................................................... 55  x  List of Figures Figure 2.1. Map of the northern Strait of Georgia showing the location of sampling stations, QU39 and QU24 ( ). The inset is a map of coastal British Columbia, including the entire Strait of Georgia and the northern portion indicated by the black box. ............................ 28 Figure 2.2. Temperature (°C) and salinity (psu) profiles in the northern Strait of Georgia from January 2015 to December 2016. Note the change of depth scale. .................................. 29 Figure 2.3. Mean monthly temperature and salinity in the northern Strait of Georgia from January 2015 to December 2016. Error bars represent the standard deviation from the mean. ................................................................................................................................. 30 Figure 2.4. Nitrate, phosphate, and silicate profiles in the northern Strait of Georgia from January 2015 to December 2016. Note the change of depth scale. Grey dots indicate depth and days of discrete bottle sampling. ....................................................................................... 31 Figure 2.5. Chlorophyll-a concentration in the northern Strait of Georgia from January 2015 to December 2016. Grey dots indicate depth and days of discrete bottle sampling. ............ 32 Figure 2.6. Integrated chlorophyll-a concentrations (mg m-2) over the top 30 m in the northern Strait of Georgia from January 2015 to December 2016. ................................................. 32 Figure 2.7. Total abundance (individuals m-3) and biomass (mg dry weight m-3) in the northern Strait of Georgia from January 2015 to December 2016. Vertical dashed lines indicate the start of the spring bloom. .................................................................................................. 33 Figure 2.8. Abundance (individuals m-3 and biomass (mg dry weight m-3) of major zooplankton taxa in the northern Strait of Georgia from January 2015 to December 2016. Abundance and biomass are presented on a log10 scale. Vertical dashed lines indicate the start of the spring bloom. .................................................................................................................... 34 xi  Figure 2.9. Abundance (individuals m-3) of copepod species abundant in this study and/or frequently reported in studies in the northeast Pacific in the northern Strait of Georgia from January 2015 to December 2016. ............................................................................. 35 Figure 2.10. Dendrogram of cluster analysis of zooplankton samples using the average-linkage clustering method. Similarity levels were determined using the Bray-Curtis dissimilarity index applied to log10(x+1) transformed abundance data. Three primary clusters and three secondary clusters were identified. ................................................................................... 36 Figure 2.11. NMDS plot of zooplankton species composition in the northern Strait of Georgia for samples collected in 2015 and 2016 (2D stress = 0.16). Similarity was based on the Bray-Curtis dissimilarity metric, applied to log10(x+1) transformed abundance data . a) Ellipses around the clusters indicate the standard deviation based on sample-group clusters; b) arrow indicates the environmental variable that explains the most variation in the community data. ................................................................................................................ 36 Figure 2.12. Results of indicator species analysis for zooplankton species abundance data in the northern Strait of Georgia. Indicator values were calculated at each level of separation in the cluster analysis. Only species that have an indicator value of > 25 were included. ... 37 Figure 3.1. Map of the northern Strait of Georgia to Johnstone Strait including the Discovery Islands, showing the location of sampling stations ( ).  The inset is a map of coastal British Columbia. .............................................................................................................. 56 Figure 3.2. Temperature and salinity over the top 30 m of the water column at four core stations from April 2015 to July 2016............................................................................................ 57 xii  Figure 3.3. Temperature – salinity diagrams for all stations from the northern Strait of Georgia through the Discovery Islands and into Johnstone Strait from April 2015 to July 2016. Surface depths range from 0 to 2 m and bottom depths range from 145 m to 360 m. ..... 58 Figure 3.4. Macronutrient (NO3- + NO2, PO4, SiO2) concentrations over the top 30 m of the water column at four core stations from April 2015 to July 2016. ................................... 59 Figure 3.5. Chlorophyll-a concentrations (μg L-1) at four core sampling stations in the Discovery Islands and Johnstone Strait region from April 2015 to July 2016. Grey dots indicate depth and days of discrete bottle sampling. ...................................................................... 60 Figure 3.6. Integrated chlorophyll-a (mg m-2; 0-30 m) at four core sampling stations in the Discovery Islands and Johnstone Strait region from April 2015 to July 2016. ................ 60 Figure 3.7. Total abundance of zooplankton (log10 (number of individuals m-3) at four core sampling stations in 2015 (top) and 2016 (bottom) from April to July. ........................... 61 Figure 3.8. Total biomass of zooplankton (log10 (mg DW m-3) at four core sampling stations in 2015 (top) and 2016 (bottom) from April to July. ............................................................ 61 Figure 3.9. Dendrogram of cluster analysis comparing zooplankton community composition across the northern Strait of Georgia, Discovery Islands and Johnstone Strait region from April to May of 2015 and 2016. Zooplankton abundance data were log10(x+1) transformed and a Bray-Curtis dissimilarity index was used for the average-linkage clustering method. ............................................................................................................. 62 Figure 3.10. Results of indicator species analysis for zooplankton species abundance data across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016. Indicator values were calculated at each level of separation in the cluster analysis. Only species that have an indicator value of > 25 were included. ............................................. 63 xiii  Figure 3.11. NMDS plot of zooplankton species composition across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016 based on a Bray-Curtis dissimilarity ordination (2D stress = 0.19). Ellipses around the clusters indicate the standard deviation based on sample-group clusters and arrows indicate the combination of environmental variables that explains the most variation in the community data. ....... 64 Figure 3.12. Abundances (individuals m-2) of select copepod species across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016. ...................... 65  xiv  List of Abbreviations DI    Discovery Islands DW   Dry weight HNLC   High-nutrient, low-chlorophyll JS   Johnstone Strait SoG   Strait of Georgia Southern SoG  Southern & Central Strait of Georgia (South of Texada Island)   xv  Acknowledgements This project was financially supported by the Natural Sciences and Engineering Research Council, the Tula Foundation, and Mitacs. A huge thank you to my supervisor, Dr. Evgeny Pakhomov, for welcoming me into the exciting world of zoops while I was in my undergraduate degree and letting me stick around for this long… The care and thoughtfulness that you put into your students as well as your work is inspiring, and I hope to carry many of the valuable lessons you have taught us with me for the rest of my career. I aspire to one day know as much about zooplankton as you do. I would also like to thank Dr. Brian Hunt for all of your guidance and feedback with this project – I know how much time and effort you have given to make this thesis as good as possible, and I truly appreciate it. Thank you for being such a fantastic de facto co-supervisor. Thank you to Dr. Christopher Harley for bringing a fresh perspective and good questions to committee meetings. I’m sorry that you never got that puppet show that I promised you.   To my labmates – you’re certainly more than mere “labmates” to me. I am so blessed to be part of such a special group of people who are all uniquely intelligent, hilarious, and welcoming human beings. You’ve made my Masters such a wonderful experience and I cannot thank you enough for everything. A HUGE thank you to Yulia for spending so much time with me in my eternal quest to defeat R. There is little chance I could have completed this without you, and there is a high chance that everything would have been done in Excel. Thank you Joanne for getting my feet wet with zooplankton taxonomy – even though it was a steep learning curve, it was one of the best things I’ve done and I’m grateful for your patience in those early months of microscopy (and also you make adorable kiddos). Sam, thank you for sending me photos of zooplankton from salmon stomachs to let me know how good I have it with my undigested samples… and also for being such a positive light in my life. Vanessa, thank you for sharing my love of crab megalops – it takes a special kind of person to think they are adorable, which is one reason that I know you’re particularly great. Yuliya, thank you for being an unbelievable baker and frequently sharing your treats with us, ultimately making lab meetings the best part of the week. Thank you to past grad students, post docs, and undergrads for contributing to such a great environment. Finally, a massive thank you to the best work wife that xvi  a girl could ask for. Lian, your appreciation for denim and black coffee almost matches my appreciation for you – thanks for all the good times (and edits).   Thank you to my family not only tolerating my incessant chatter about zooplankton and the oceans, but for supporting me throughout all of my education so far. Mom & Dad, thank you for making it so easy to think the world of you both. You are the best role models and friends that a gal could ask for, and I’m grateful for you every day. Liam and Nana, thank you both for showing up to family dinners every week or two so I can be updated and proud of you for your football/academic and lawn bowling achievements, respectively. Thomas, thank you for being such an amazing friend and partner – especially by keeping my iron levels sufficient by cooking for me all the time, and for relieving me at my stressiest by adventuring with me and making me laugh. A special shout out to the teams on Quadra Island and at Salmon Coast Field Station for doing the field work that gave me such a fun project to work on. Thank you to my “dream team” on Quadra – Kate, Katie, Leo, & Rebecca – for so many of my favourite memories that I will always treasure. To my cohort at the Institute of the Oceans and Fisheries (aka my “fish friends”) – your friendship and insane knowledge of everything under the sun is impressive and inspiring. Thank you for all the laughs.  Lastly, thank you to the zooplankton, you underappreciated group of critters. You have taken me to so many beautiful places and introduced me to so many amazing people. Without you, charismatic microfauna, who knows where I would be?   xvii             To my parents. 1  Chapter 1: Introduction Zooplankton are a critical link in marine food webs, transferring energy from primary producers to higher trophic levels. The word ‘zooplankton’ is derived from the Greek words ‘zoon’, meaning ‘animal’, and ‘planktos’, meaning ‘wanderer’ or ‘drifter’, so by definition zooplankton are heterotrophs that cannot swim again currents. Zooplankton are poikilothermic, with their physiological processes being highly sensitive to temperature (Mauchline, 1998). Most zooplankton species have generation times of less than one year (Hays et al., 2005). These characteristics make zooplankton particularly vulnerable to changes in ocean temperature and circulation.  Zooplankton exhibit substantial taxonomic, functional, and energetic variability. Zooplankton feed on a wide array of organic matter and their diets can be herbivorous, carnivorous, omnivorous, detritivorous, or some combination (Lee et al., 2006). Consequently, there is considerable variation in the intra- and interspecific differences in the energetic value of zooplankton over spatial and temporal scales (El-Sabaawi et al. 2009; El-Sabaawi et al. 2010; Bevan 2015; Miller et al. 2017). Since zooplankton are a food source to many higher level consumers including other zooplankton, fish, seabirds, and cetaceans, it is imperative to study zooplankton community dynamics and how they may shift with climate change.  Temperate coastal oceans are typically characterized by a spring phytoplankton bloom followed by a prolonged period of high primary production during the summer (Harrison et al., 1983; Wiltshire et al., 2008; Tommasi et al., 2013). This increase in phytoplankton biomass cues an increase in zooplankton reproduction and growth (Harrison et al., 1983; Tommasi et al., 2013). In temperate coastal regions the spring bloom is typically followed within a few weeks by a significant increase in zooplankton biomass and a shift in the composition of zooplankton communities (Harrison et al. 1983). The period of high phytoplankton production is critical in determining the development and growth of certain species that time their migration to surface waters to coincide with the period of maximum phytoplankton biomass (e.g., Neocalanus plumchrus; Sastri and Dower, 2009). Consequently, important life stages of some higher trophic levels align with peak zooplankton biomass to maximize growth and survival rates (e.g., Oncorhynchus nerka; see summary in Cushing, 1990). 2    1.1 Oceanography of coastal British Columba: Strait of Georgia to Johnstone Strait Coastal British Columbia has a complex coastline with many channels and inlets. There is an inherent range of mixing and productivity regimes in the nearshore environment. The Strait of Georgia (SoG), Discovery Islands (DI), and Johnstone Strait (JS) region is a dynamic and intricate portion of the southern British Columbia coastline. The region includes some of the most seasonally productive waters in North America (Jackson et al., 2015), waters that remain in a “permanent winter state” with low primary productivity year-round due to turbulent mixing (McKinnell et al., 2014; Thomson, 1976), and waters that experience some of the strongest tidal currents in the world (Lin et al., 2011; Chandler et al., 2017a). The physical environment throughout the SoG / DI / JS region has been relatively well documented because of its complex bathymetry and intense tidal interactions (Waldichuk, 1957; Thomson, 1976; Thomson, 1981; Pawlowicz et al., 2007; Foreman et al., 2012; Chandler et al., 2017a). A brief overview of the oceanography of each of these regions is discussed below.  1.1.1 Strait of Georgia The SoG is a large (220 km mean length, 33 km average width) semi-enclosed basin between mainland British Columbia and Vancouver Island, Canada (Waldichuk, 1957). The average depth of the SoG is 155 m, reaching a maximum depth of 420 m in the central portion of the strait (Waldichuk, 1957). The SoG is subject to strong and positive estuarine circulation, frequently exchanging water with the Pacific Ocean (Waldichuck, 1957; Pawlowicz et al., 2007). Most exchange with the shelf occurs through Juan de Fuca Strait. Deep water is typically renewed in the SoG every summer, while intermediate water (50-200 m) is continually renewed, and surface waters (< 50 m) have a residence time of a few days to a few months depending on the season (Pawlowicz et al., 2007). Consequently, the SoG has many oceanic physical water characteristics despite its semi-enclosed and coastal location. A defining characteristic of the SoG is the Fraser River freshet, which typically occurs during early summer. This annual phenomenon drains a watershed of approximately 217,000 km2 into the SoG and reaches peak outflow rates of approximately 104 m3 s-1 around mid-June (Waldichuk, 1957; Thomson, 1981; 3  Morrison et al., 2002). This massive flux of freshwater and sediments results in stratified and turbid surface waters (1-10 m) at the mouth of the Fraser River. Phytoplankton biomass remains relatively low within the plume, and maximum values for chlorophyll-a in the southern SoG occur at some distance outside the central Fraser River plume (Waldichuk, 1957; Parsons et al., 1969; Pawlowicz, 2001). During the spring bloom phytoplankton biomass can increase 20-fold compared to the average winter biomass on the time scale of a few days (Harrison et al. 1983).  The northern SoG basin is separated from the southern SoG basin by a relatively shallow (~100 m) sill near the southern end of Texada Island (Waldichuk, 1957). This sill limits the interaction of deep bottom water between the northern SoG and the southern SoG, and the northern basin is, on average, shallower than the southern basin (Waldichuk, 1957). Deep water renewal in the northern basin is mostly from convective overturning during abnormally cold winters or the slow northward movement of deep water from the southern SoG (Thomson, 1981). The positive estuarine circulation that characterizes the SoG influences the southern basin more intensely than the northern basin, and the Fraser River plume has less direct influence on the northern basin (Waldichuck, 1957). The northern SoG has a smaller salinity range than the southern SoG and minimum surface salinity is observed in late July and early August, with surface temperatures peaking in early August (Waldichuk, 1957; Thomson, 1981). Although the central and northern portions of the SoG are more stable than the tidally mixed southern SoG, the northwest component of the SoG interacts with the tidally mixed Discovery Passage (Thomson, 1981). Due to nutrient inputs from these tidally mixed frontal regions, the northern SoG can have higher chlorophyll-a values than central portions of the Strait (Parsons et al., 1980; Harrison et al., 1983). Although the SoG south of Texada Island (including the central and southern SoG, hereafter referred to as the southern SoG) has been relatively well studied, the northern SoG remains largely undescribed in terms of general oceanography and zooplankton community composition. Most comprehensive oceanographic studies have been conducted in the southern portions of the SoG, as urban expansion is concentrated along these areas (e.g., see reviews by Harrison et al., 1983; LeBlond, 1983). Decades of zooplankton research in the southern SoG has resulted in studies describing the life history of important species, energetic content of select species, seasonal succession in communities, as well as long-term changes in community composition (e.g., Fulton, 1973; Gardner, 1982; Harrison et al., 1983; El-Sabaawi et al., 2009; 4  El-Sabaawi et al., 2010; Mackas et al., 2013). However, comparatively few in-situ measurements have been taken from the northern SoG.   1.1.2 Discovery Islands  The DI are a complex network of islands that connect the SoG to JS through an array of deep channels and inlets with various shallow sills. Due to the interaction of tides from the north (Queen Charlotte Strait) and the south (Juan de Fuca Strait), some of the strongest tidal forces are observed in the DI, with surface currents reaching 7.8 m s-1 in Discovery Passage (Lin et al., 2011; Chandler et al., 2017a). Particles in the water can move more than 14 km in one direction until the tide changes, when the water will reverse direction. The average depth in the Discovery Islands is 173 m, with maximum depths of 700 m in Bute Inlet and Homfray Channel (Foreman et al., 2012). The eastern DI are warmer, fresher, and more stratified than the vertically mixed western DI during spring and summer (Thomson, 1981; Chandler et al., 2017a). The largest freshwater input to the DI is due to river discharge and snowmelt and is mainly sourced from the Homathko River at the head of Bute Inlet, reaching peak discharges of over 600 m3 s-1 in July (Chandler et al., 2017a). Models and past observations have indicated that the surface estuarine flow is largely northward, with fast surface currents having the potential to transport particles from the DI to JS within 2.5 days (Thomson, 1976; Foreman et al., 2015). The DI are an important component of the migration/travel routes of adult and juvenile Fraser River salmon, cetaceans, and commercial boat traffic (Groot and Clark, 1987; Chandler et al., 2017a). In 2015-2016, 18 Atlantic salmon farms held valid aquaculture licenses in the DI (Chandler et al., 2017a), urging the importance of understanding baseline biology in this region, which is largely absent from existing literature. 1.1.3 Johnstone Strait Johnstone Strait is a 110 km channel connecting the DI to Queen Charlotte Strait along the northeastern side of Vancouver Island. Thomson (1976) published a detailed report covering the physical oceanography of the region, primarily focusing on the tidal currents and circulation throughout the strait. The vast majority of water enters JS from the north, originating from Queen Charlotte Strait, and is eventually circulated through JS and returned north through Queen 5  Charlotte Strait (Khangaonkar et al., 2017). In the western basin of JS, maximum depths are over 450 m, meeting Broughton Strait to the west at a shallow (68 m) sill. The eastern JS basin is comparatively more shallow and narrow. As in the DI, tidal currents in JS are very strong and can exceed 6 m s-1 (Thomson, 1976). The water column in JS is typically very well mixed, with a small annual range of salinity (30-32 psu) and temperature (varying between 0.45-0.55°C across all depths) (Thomson, 1976). However, the surface layer is slightly warmer and fresher than deeper layers, indicating estuarine circulation in JS from freshwater runoff in the surrounding area (Thomson, 1976, Thomson and Huggett, 1980; Khangaonkar et al., 2017). Due to the strong tidal mixing in JS, primary production is low year-round (Thomson, 1976; McKinnell et al., 2014). Similar to the DI, JS is an important channel for salmon migration, cetacean populations, and commercial boat traffic (Groot and Clark, 1987; Chandler et al., 2017a).  1.2 Purpose of this study Despite considerable literature on the physical characteristics of the region and its importance to many higher trophic levels, studies of the northern SoG to JS have largely neglected zooplankton. Aside from a few sampling events in Bute Inlet (Lee, 1974; Gardner, 1982) and bulk biomass measurements from a few channels from the northern SoG to the British Columbia central coast (Price et al., 2013; McKinnell et al., 2014). The purpose of this dissertation is to determine the spatial and temporal differences in zooplankton communities from the northern SoG to JS over the course of two years. We aim to provide the first in-depth description of seasonal zooplankton dynamics across a range of mixing and productivity regimes in coastal British Columbia. The main objectives of this thesis were to a) describe the mesozooplankton community in the northern SoG over two years, including a description of environmental conditions that influence zooplankton phenology and a detailed examination of the seasonal patterns in zooplankton abundance and composition, and b) complete a spatial analysis of zooplankton communities and their environments in a region comprised of productive and non-productive channels in a connected and complex environment. To our knowledge, this is the first attempt in creating a high-resolution baseline for zooplankton communities in the region.   6  Chapter 2: Seasonal zooplankton development in a semi-enclosed basin: two years with different spring bloom timing 2.1  Introduction Zooplankton play a critical functional role in marine environments. They link primary producers to higher trophic levels, are key in the biogeochemical cycles of carbon and nutrients, and are indicators of water quality and large-scale environmental changes (Morales, 1999; Mackas and Galbraith, 2002; Beaugrand et al., 2003; Webber et al., 2005; Li et al., 2013). In temperate coastal regions zooplankton communities often vary significantly across spatial scales ranging from meters to ocean basins and temporal scales ranging from days to decades (Gardner, 1982; Kiørboe and Nielsen, 1994; Mackas et al., 2007a). Since zooplankton are rarely commercially fished, generally have short generation times (typically a few weeks to a year; Hays et al., 2005), and are directly influenced by local physical factors (e.g., temperature, currents), their community dynamics can provide us with information about how an ecosystem may respond to changing environmental conditions (Batten et al., 2018).   In mid-latitude coastal regions, primary production can vary by over an order of magnitude throughout the year (Harrison et al., 1983; Cloern and Jassby, 2008). Chlorophyll-a concentrations are typically low (< 1 μg L-1) during winter months when vertical mixing is high and photoperiod is low (Cushing, 1959; Harrison et al., 1983; Parsons, 1979). After unproductive winters, northern coastal margins usually experience a warming of surface waters and a spring bloom where chlorophyll-a concentrations rapidly increase to > 10 μg L-1 in response to increased light availability, decreased vertical mixing, and replete nutrient conditions in surface waters (Cushing, 1959; Harrison et al., 1983). After the initial bloom, phytoplankton become limited by either nutrient concentration or zooplankton grazing as the season progresses, with subsequent erratic and smaller blooms attributed to pulses of nutrient input to surface waters (Cushing, 1959; Stockner et al., 1979). The spring bloom is typically followed within a few weeks by a significant increase in zooplankton biomass and a shift in the composition of zooplankton communities (Harrison et al. 1983).  In the northeast Pacific, community composition, phenology and abundance of zooplankton vary with both small-scale regional processes (e.g., upwelling and downwelling 7  dynamics, chlorophyll-a concentrations; Ware and Thomson, 2005) and large-scale climate indices such as the Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI) (Hare and Mantua, 2000; Hallett et al., 2004; Mackas et al., 2007a; Keister et al., 2011; Li et al., 2013) Shifts in zooplankton phenology have the potential to negatively affect higher-level consumers that time migrations or important life stages with the window of maximum zooplankton biomass (see Cushing, 1990 for an updated summary). The timing of zooplankton reproduction and growth are largely influenced by temperature and food availability (Ban, 1994; Batten and Mackas, 2009). In mid-latitude enclosed seas variability in both seasonal temperature and the timing of the spring bloom are high (Cloern and Jassby, 2008; Mackas et al., 2012; Allen and Wolfe, 2013). Consequently, zooplankton in such environments must be suited to survive in physiological and feeding conditions that often vary independently from one another and exhibit considerable interannual variability. Batten et al. (2018) found a positive relationship between zooplankton biomass, temperature, and diatom abundance on the Alaskan shelf from 2000-2013, but did not find the same relationship during the anomalous warming events of 2014 and 2015. The authors suggested that such large-scale anomalous warming events could alter lower trophic levels and impact higher-level consumers. In the northeast Pacific, Mackas et al. (1998) described changes in Necoalanus plumchrus phenology from the 1960s until the 1990s. Changes in the timing of N. plumchrus ontogenetic migration were positively correlated with sea surface temperature (Mackas et al., 1998), but no such correlation with annual peak chlorophyll has been described (Mackas et al., 2012). Atkinson et al. (2015) argue that while the match-mismatch hypothesis may apply to highly seasonal and pulsed systems, shifts in zooplankton phenology have been simplified in many marine systems with more factors contributing to predator-prey mismatches. Although temperature and spring bloom timing may be important to zooplankton in some marine ecosystems, populations in regions with strong seasonality may be somewhat resilient to interannual fluctuations in environmental conditions.  The Strait of Georgia (SoG) is a large semi-enclosed basin between mainland British Columbia and Vancouver Island (Figure 2.1). The SoG has some of the most seasonally productive surface waters in the northeast Pacific, and a large spring bloom is observed each year (Harrison et al., 1983; Ware and Thomson, 2005; Jackson et al., 2015). Although the SoG south of Texada Island (including the central and southern SoG, hereafter referred to as the southern 8  SoG) has been relatively well studied, the northern SoG remains largely undescribed in terms of general oceanography and zooplankton community composition. Studies in the northern SoG have addressed questions about the physical properties of the water column, or phytoplankton and microzooplankton communities over relatively short temporal or vertical scales (Stephens et al., 1969; Stockner et al., 1979; Thomson, 1981; Haigh and Taylor, 1990; Haigh and Taylor, 1991). The physical water properties directly influence the distribution of zooplankton in the water column, and zooplankton typically feed on phytoplankton and microplankton, making these existing studies valuable in the context of understanding zooplankton dynamics in the region. However, since zooplankton are the primary link to higher trophic levels, it is essential to describe these communities and understand how they may respond to environmental changes. The northern SoG is of particular importance as it constitutes an area of considerable aquaculture activity and important migration routes and habitats for various commercially and ecologically important species including herring, Pacific salmon, and various marine mammal populations (Groot and Margolis, 1991; Hay and McCarter, 1997; Williams and Thomas, 2007).   The northern SoG is an important yet largely undescribed part of the SoG, and we expect its physical and biological components to function differently from the southern SoG. Since zooplankton communities can vary on relatively small spatial scales, it is important to understand how assemblages may differ across a large seasonally productive and semi-enclosed basin. The main aim of this study is to describe the entire mesozooplankton community in the northern SoG and determine how the environment influences community succession and interannual variability. Specifically, the objectives of this study are to: a) investigate the response of zooplankton phenology to the oceanographic properties of the northern Strait of Georgia and b) determine the seasonal patterns of zooplankton biomass, abundance, and community composition in two years with very different spring bloom timing.    9   2.2 Methods 2.2.1  Field sampling Sampling in the northern SoG was conducted from January 2015 to December 2016 by the Hakai Institute Ocean Observing Program. Sampling was conducted every 7-14 days between April and September and monthly between October and March. The majority of sampling was conducted at station QU39; however, in 2015 samples from January to mid-March were collected from the nearby station QU24 (Figure 2.1). Station coordinates and additional information can be found in the appendix (Table A1).  Zooplankton vertical tows were performed using a 2 m or 3 m length bongo net with a mouth diameter of 0.5 m and a mesh size of 250 μm. Nets were deployed to 5 m above bottom depth (240 m at QU24 and 265 m at QU39) and retrieved at 1 m s-1. Each net was equipped with a General Oceanics mechanical flowmeter that was used to estimate volume filtered during each tow. After each vertical tow the net was rinsed down and the sample from one cod end was preserved in a 5% buffered formaldehyde-seawater solution. The sample from the other cod end was used for complementary analyses.  Environmental variables were collected at the same time as zooplankton tows during almost all events, and at a higher frequency (approximately weekly) than zooplankton tows. CTD (Conductivity, Temperature, Depth) probes were deployed to 5 m above bottom depth at a speed of 1 m s-1. CTD measurements were obtained using either an RBR maestro or a SeaBird 19plus V2. CTD data were subsequently processed and then binned in 1 m increments. Temperature and salinity data from 30 to 100 m were combined in subsequent sections as this depth range is important for many zooplankton undergoing diel vertical migrations (Ohman et al., 1983; Bollens et al., 1992; Osgood and Frost, 1994). Niskin bottles were used to collect water samples at discrete depths in the water column (0, 5, 10, 30, 50, 100, and 5 m above the bottom). During some sampling events water was collected at additional depths (Table A2).  Water samples were analyzed for nutrient concentrations (NO2 + NO3-, PO4-3, and SiO2) and bulk and/or size fractioned Chlorophyll-a. Chlorophyll-a samples were filtered onto GF/F filters immediately on collection and later extracted using 90% acetone and fluorescence was measured on a Trilogy© Laboratory Fluorometer (Holm-Hansen and Riemann, 1978). 10   2.2.2 Zooplankton taxonomic analysis  In the lab, samples were transferred from the formalin solution and rinsed thoroughly with tap water. Whole samples were initially processed by identifying and counting all organisms > 10 mm in length. Whole samples were then processed for individuals between 5-10 mm in length; if there were >> 300 individuals in the 5-10 mm size range in a sample, the sample was split using a box plankton splitter and one half was processed in full and the other half was examined to ensure the sub-sample was representative of the entire sample. Samples were then subsampled using the box plankton splitter until approximately 300-400 individuals < 5 mm remained. All individuals in the subsample were identified to the lowest taxonomic level possible (Figure A1). Density was calculated by dividing the count data by the proportion of the sample processed and then dividing the total count by the volume filtered as measured by the flowmeter. Biomass was calculated using conversions of zooplankton species and stage data to mg dry weight (DW) (Moira Galbraith, unpublished data).  2.2.3 Statistical analysis  Multivariate analyses were performed in R using the statistical packages vegan and clustsig (Whitaker and Christman, 2014; Oksanen et al., 2016; R Core Team, 2018). Zooplankton abundances were log10(x+1) transformed to reduce the weighting of highly abundant species. A q-type cluster analysis (normal analysis, where samples are sorted into groups with similar biotic compositions) was performed on the log-transformed data based on the Bray-Curtis similarity matrix and average-linkage clustering (Field et al., 1982). A simprof test was conducted (α = 0.01) to determine statistical significance between clusters. All taxa present in > 5 % of samples were included for the q-type analysis (Peterson and Keister, 2003). Copepods were separated into species for stages > C4 and genus if < C4, and stage categories of C1-C3, C4-C5, and C6. Fish were categorized as either “Fish larvae” or “Fish egg”. All other taxa were grouped to the lowest taxonomic level possible.  Non-metric multidimensional scaling (NMDS) was executed using the same similarity matrix as the cluster analysis procedure (Oksanen et al., 2016). The procedure was performed with both two- and three-dimensional scaling to observe goodness of fit (stress). To identify the 11  environmental variables that best correlated with sample similarities based on species abundance, a version of Clarke and Ainsworth’s (1993) BIOENV analysis was conducted (Oksanen et al., 2016). Variables tested include 5 m measurements of nitrate, phosphate, silicate, chlorophyll-a concentration, temperature, and salinity, surface temperature and salinity, bottom (~265 m) temperature and salinity, temperature and salinity stratification indices (i.e., surface measurement – bottom measurement), as well as integrated chlorophyll-a concentration over the top 30 m of the water column. Two samples (2016-06-08 and 2016-10-05) were eliminated from this analysis due to missing environmental data. To test the resemblance matrix correlation for statistical significance, a Mantel test based on Spearman’s rank correlation coefficient (ρ) was performed (Legendre and Legendre, 2012).   An indicator value (IndVal) analysis was conducted to identify taxa that were characteristic of sample groupings identified by the cluster analysis (Dufrene and Legendre, 1997). A species’ indicator value is a combination of group specificity and group fidelity. For each species i in each group j, Aij is the mean abundance of species i in the samples of group j compared to all groups in the study and Bij is the relative frequency of occurrence of species i in the sites of group j, as follows:   where IndVal is the indicator value for species i in group j. Aij is maximized when species i is present only in group j and Bij is maximized when species i is present in all samples in group j. An IndVal of ≥ 25 was selected as the minimum point for indicator species for this study, as this indicates that a species was present in ≥ 50 % of samples in a group and its relative abundance within that group was ≥ 50 %.   12   2.3 Results 2.3.1  Physical environment Temperature and salinity profiles indicated a strong seasonal cycle in the northern SoG. Shallow waters (< 10 m) showed the most intra- and interannual variation, with temperatures ranging from 7°C to 18°C and salinities ranging from 26 to 29 psu (Figure 2.2, 2.3, A3; Table A3). Water temperatures at 5 m were 7.4-8.9°C during winter (December to February) and averaged ~14°C (ranging from 13-14.5°C) during summer (June to September) of each year. In 2015 surface waters began warming in January, whereas in 2016 surface waters began warming in February (Figure 2.3). There was considerable interannual variation in the salinity of water at 5 m, with the average salinity in winter of 2016 being ~1.5 psu saltier than winter 2015, (28.7 psu and 27.0 psu, respectively). Although the average salinity in 5 m waters during the summers of 2015 and 2016 was similar (27.8 psu and 27.4 psu, respectfully), June and July were fresher by ~1 psu in 2016, and overall 2016 was more variable (Figure 2.3). November and December salinities at 5 m were 2-3 psu fresher in 2016 than in 2015.  Seasonal and interannual variability was less extreme in the water column below 10 m. Waters from 30 to 100 m showed some intra-annual differences, with waters increasing slightly in temperature (8.9°C to 9.7°C) and salinity (29.3 psu to 29.8 psu) from minima in winter to maxima in late summer. Deep water (> 100 m) varied minimally seasonally and between years. Water at 100 m was warmer than bottom water (> 200 m) in winter 2015 but colder than bottom water in winter 2016, and bottom water was slightly fresher in winter of 2016 (Figure 2.3). Water > 200 m was approximately 0.7°C warmer and 0.5 psu saltier in the winter of 2016 compared to winter 2015 (10.0°C/30.4 psu and 9.3°C/29.9 psu, respectively) (Figure 2.2, 2.3). 2.3.2 Macronutrient concentrations The strong seasonality observed in the temperature and salinity plots of the northern SoG was mirrored by macronutrient profiles (Figure 2.4). Macronutrient concentrations were high at depth year-round and high in surface waters during winter months. Intense nutrient drawdown was observed in surface concentrations of nitrate, phosphate, and silicate commencing in spring. Redfield ratios indicated that nitrate was typically the limiting macronutrient, aside from a few 13  occasions when either phosphate or silicate was limiting (Figure A4). During 2015 nutrients in surface waters were low from late February until early September, while in 2016 surface water nutrients were low from early April until early September (Figure 2.4). Nitrate and silicate concentrations at depths > 150 m were slightly higher in 2015 compared to 2016.  2.3.3 Chlorophyll-a biomass In 2015 and 2016 there is a sharp increase in chlorophyll-a in early spring each year. Notably, the timing of the spring bloom was very different between years, with the bloom initiating in late-February in 2015 and early April in 2016 (Figure 2.5; Table 2.1). We defined the start of the spring bloom as the date when concentrations of chlorophyll-a were > 5 μg L- (Gower et al., 2013). Phytoplankton concentrations remained relatively high from late February until early May in 2015 with an additional small bloom in late August. Contrastingly, in 2016 chlorophyll-a concentrations were high from early April until late May and again from mid-June until the end of September. In addition to the difference in temporal extent of the bloom, there was also a stark difference in the vertical extent of the bloom between years, with the 2015 bloom being concentrated in the top 10-15 m of the water column and the 2016 bloom effects being observed down to 20-30 m.  Integrated chlorophyll-a over the top 30 m also differed between years. Chlorophyll-a was highest from March until May in 2015 compared to April until September in 2016. Maximum chlorophyll-a in the top 30 m was higher in 2016 compared to 2015 (Figure 2.6; Table 2.1). 2.3.4 Zooplankton Zooplankton abundance and biomass showed a strong seasonal cycle (Figure 2.7). For the purposes of this analysis, “high” zooplankton abundances are defined as > 5x the minimum average winter abundance (i.e., > 500 ind.m-3). Generally, zooplankton abundance was lowest (100-200 ind.m-3) during winter and highest (> 1500 ind.m-3) during the spring and summer months. Each year there was an increase in zooplankton abundance in spring. In 2015 this increase started in mid-March while in 2016 it started in early April. Maximum abundance was observed on May 11 and May 18 in 2015 and 2016, respectively. The zooplankton blooms between years had comparable maximum values aside from the brief increase in zooplankton 14  abundance and biomass during May 2016, which was attributed to a bloom of the marine cladoceran Evadne spp. The patterns in zooplankton biomass mirrored the trends seen in the abundance data, with biomass minima (11.5-13 mg DW m-3) in winter and maxima (100-110 mg DW m-3) in spring and summer. Although there was considerable intra-seasonal variation in biomass, both years had similar maximum values, with biomass peaking from May-June during both years and remaining high until September-October. Notably, the period of “high” zooplankton abundance and biomass lasted for the same amount of time (seven and a half months) each year; however, in 2015 this period was from March until mid-October, and in 2016 it was shifted to April until mid-November.   The relative dominance of major taxa varied considerably in terms of both abundance and biomass during both years (Figure 2.8, Figure A5). Small copepods numerically dominated zooplankton communities for the vast majority of the year, typically accounting for > 50 % of the total abundance (ranging from 30-95 %). Meroplankton (organisms spending a portion of their life cycle as plankton; primarily decapods, barnacles, bivalves, and gastropods in this study) increased in abundance during the spring (March - May) and were more numerically dominant in 2016 compared to 2015, with maximum abundances of 490 ind.m-3 and 130 ind.m-3, respectively. “Other zooplankton” (primarily ostracods, cladocerans, fish eggs, euphausiids eggs and juvenile stages, polychaetes, and chaetognaths) were numerically most important during spring and summer (March - August). Euphausiid eggs and juvenile stages drove the highest observed abundances of “other zooplankton” during March to June of 2015, May 2016 (in addition to Evadne spp.) and August 2016. Larvaceans reached maximum abundances in March 2015 and February-April 2016, accounting for up to 16 % of the total zooplankton. Amphipods, euphausiids, copepods > 2.5 mm, and gelatinous zooplankton were present in zooplankton communities for most of the year but were never numerically dominant (i.e., total abundances accounted for < 10 % of total zooplankton abundance).  The taxa that contributed most to biomass differed substantially from those contributing to abundance (Figure 2.8). In particular, small copepods generally constituted < 50 % of the total biomass, ranging from 13-68 %. “Other zooplankton”, Copepods > 2.5 mm, gelatinous zooplankton, and euphausiids each contributed up to 30-40 % of the total biomass. Meroplankton and amphipods each accounted for up to 27 % of the total biomass. Zooplankton biomass in 15  winter (November - February) 2016 had a greater contribution of large copepods and gelatinous zooplankton compared to late winter 2015.  The meroplankton bloom in 2016 made a larger contribution to biomass in 2016, accounting for up to 27 % of the total biomass in 2016 and < 10 % in 2015.   Copepod species with high abundance in this study and/or frequently reported in studies in the northeast Pacific are presented in Figure 2.9. Some species, including Calanus marshallae, Acartia longiremis, Neocalanus plumchrus, Oithona similis, Pseudocalanus minutus, and Pseudocalanus newmani, were relatively more abundant in 2015 than 2016. Notably, overwintering N. plumchrus were observed in much higher abundances in January 2015 compared to January 2016. Other species, such as Calanus pacificus, Centropages abdominalis, Corycaeus anglicus, Eucalanus bungii, Paracalanus indicus, Paracalanus parvus, and Pseudocalanus moultoni were relatively more abundant in 2016 than 2015. In general, larger copepods were never observed in very high abundances (e.g., Eucalanus bungii, Neocalanus plumchrus) and the highest abundances were observed in smaller copepods (e.g., Oithona spp., Paracalanus spp., Pseudocalanus spp., and Calanus pacificus). Acartia hudsonica and Paracalanus parvus were both observed on rare occasions in 2015 and more frequently during summer 2016.   Cluster analysis of zooplankton abundance data identified three distinct sample clusters at approximately the 60 % level of dissimilarity (Figure 2.10). These clusters comprised winter samples (Cluster 1; 10 samples), early spring (Cluster 2; 4 samples), and summer-fall (Cluster 3; 24 samples). At 50 % similarity, samples could be further split into October-early February (Cluster 1A; 8 samples), late February (Cluster 1B; 2 samples), early spring (Cluster 2; 4 samples), late spring (Cluster 3A; 6 samples), summer-fall (Cluster 3B; 15 samples), and 2 outliers (Cluster 3C; late June 2015 and mid-August 2016).  Little interannual variability was evident, with seasonal zooplankton communities being remarkably similar between years.   The NMDS ordination of zooplankton assemblages in both two- and three-dimensional ordinations (stress = 0.16 and 0.10, respectively) supported the strong seasonal variation evident in the cluster analysis. Only the two-dimensional ordination is discussed here. Three distinct clusters were observed in the NMDS: winter, early spring, and summer-fall (Figure 2.11). The BIOENV analysis and Mantel tests identified a significant correlation (ρ = 0.41, p = 0.001) 16  between nitrate concentration at 5 m and zooplankton community dissimilarity (Figure 2.11; other combinations of environmental variables can be found in Table A4). The arrow points to the direction of most rapid change in nitrate at 5 m and separated summer-fall samples from winter samples (Figure 2.11).   At the highest level of clustering, the winter cluster (Cluster 1) had two indicator species: adult Neocalanus plumchrus and early copepodite Canadacia columbiae (Figure 2.12). Typhoscolex muelleri was identified as separating late February from the rest of winter samples (i.e., Cluster 1A and 1B). There were many indicator species for the early spring cluster (Cluster 2), including meroplankton taxa (e.g., fish eggs, fish larvae, barnacle larvae, echinoderm larvae, bryozoan larvae, Galatheidae sp., and Pandalopsis dispar), euphausiids eggs, adult Candacia columbiae, Centropages abdominalis, Pseudocalanus moultoni, and appendicularians. The summer-fall cluster (Cluster 3) had indicators including Tomopteris pacifica, gelatinous zooplankton (Aegina citrea, Nanomia bijuga, siphonophore gas floats), copepods (Corycaeus anglicus, late stage Eucalanus bungii, Paracalanus indicans, Metridia pacifica, Microcalanus pygmaeus, Calanus pacificus, and Oithona atlantica), as well as Euphausia pacifica, Themisto pacifica, and Cyphocaris challengeri. The late spring cluster 3A was characterized by the copepods Centropages abdominalis and adult Acartia longiremis, as well as Clytia gregarium, Chaetopterus sp., juvenile Tomopteris sp., cladocerans, and Limacina helicina. The summer-fall cluster 3B was characterized by adult Aetideus divergens, Tomopteris septentrionalis, and late-stage Calanus pacificus. There were no indicator species for the cluster 3C outlier.  17   2.4 Discussion This study provides insights into the interannual and seasonal zooplankton community dynamics in the northern SoG. We detected a strong seasonal cycle and a lack of interannual variability in zooplankton community structure despite a six-week difference in the timing of the spring bloom between years. Zooplankton abundance, biomass, taxonomic composition, and indicator species data all support this robust zooplankton successional pattern in the northern SoG. The grouping of zooplankton communities based on season has been illustrated in other seasonally productive regions along the northeast Pacific coast from Alaska to Oregon (Harrison et al., 1983; Mackas, 1992; Keister and Peterson, 2003; McKinstry and Campbell, 2017). 2.4.1  Comparing environmental conditions between years Coastal waters in the north Pacific were under the influence of two separate climatic anomalies during the course of this study: the warm water mass that developed during the 2013-2014 winter in the northeast Pacific Ocean (termed ‘the Blob’) and the El Niño event that developed in 2015-2016 (Chandler et al., 2017b). The effects of these events on the northeast Pacific coast were observed from late 2014 into 2016 as warmer surface waters (down to 100 m depth), warmer winter conditions along the coast, and the detection of new zooplankton species assemblages (Bond et al., 2015; Peterson et al., 2017). The potential effects of these two climatic events on the zooplankton communities in the SoG are discussed in Section 2.4.2.  Temperature and salinity data for surface waters (0-30 m) in the northern SoG in 2015 and 2016 were within historical ranges since observations began in 1932 (Figure A2; Chandler et al., 2017a). However, 2015 was particularly close to the warmer and fresher extremes observed in the northern SoG, with February and March temperatures more than 1°C warmer than average and salinities 1 psu below historic averages (Chandler et al., 2017a). Notably, the southern SoG was 2°C warmer and with lower salinity in 2015 compared to the previous 15 years, and this trend of warmer than normal waters persisted into the spring of 2016 (Chandler et al., 2016; Chandler et al., 2017a). The increased surface temperatures and decreased salinity anomalies observed in the both the northern and southern SoG can be attributed to the Blob and El Niño events. Deep water was also likely affected by these large-scale events, indicated by the warmer 18  temperatures and lower nitrate and silicate concentrations observed during winter 2016. It is possible that the warmer winter in the northern SoG restricted exchange with the cold bottom water from the southern SoG. Despite relatively small interannual differences in the physical properties of the water, these changes may influence zooplankton species that overwinter at depth and already live close to their physiological limits (Mackas et al., 2012).    The spring bloom in the northern SoG was observed six weeks earlier in 2015 than 2016. Although this was not outside the documented range of interannual variability in the southern SoG (Collins et al., 2009; Allen and Wolfe, 2013), six weeks constitutes a considerable difference in bloom timing between two years. In the southern SoG the spring bloom was detected approximately a month later than in the northern SoG bloom in 2015 and at nearly the same time in 2016 (Allen and Latornell, 2015; Allen et al., 2017). Although the spring bloom in the southern SoG typically occurs between March and April (Allen and Wolfe, 2013), due to the complex nature of bloom initiation there is a great deal of variation in temperate coastal waters and, although rarer outside of March to September, peak phytoplankton biomass can occur during any time of year (Cloern and Jassby, 2008). Early spring blooms in temperate coastal systems can be due to changes in wind speed and cloud fraction during winter (Collins et al., 2009; Allen and Wolfe, 2013), surface water temperature (Hunter-Cevera et al., 2016), or freshwater input (Sugimoto and Tadokoro, 1997). Weather conditions across British Columbia were warmer than normal during the winter of 2014-2015 and consequently river outflow was higher than normal during spring 2015 and lower than normal during the summer (Anslow et al., 2016). Increased stratification from decreased mixing and increased temperatures likely induced the early bloom observed in the northern SoG in 2015. While conditions were still relatively warm in 2016, a higher frequency of wind events and storms, leading to increased mixing, likely delayed the spring bloom onset (Allen et al., 2016). 2.4.2 Robust seasonal succession in zooplankton communities despite species-level interannual variation Although the timing of the spring bloom can influence zooplankton community composition and succession (Tommasi et al., 2013), we observed little evidence of interannual community compositional shifts during the course of this study. However, distinct seasonal changes in taxonomic composition occurred. Divisions between winter, early spring, and summer-fall 19  marked the annual successional pattern observed in the zooplankton of the northern SoG in 2015 and 2016.  The spring bloom has been described as the start of zooplankton production in temperate coastal waters (Kiørboe and Nielsen, 1994), which was reflected in our data by the increase in total zooplankton abundance and biomass shortly after each spring bloom. However, the shift from winter to early spring zooplankton communities in the northern SoG did not appear to be influenced by the timing of the spring bloom, but instead occurred during mid-late March in both years. Other studies in the North Pacific have documented shifts in zooplankton phenology linked to changes in the spring bloom timing. In Rivers Inlet, British Columbia, an early spring bloom in 2006 compared to 2007 was associated with a higher recruitment of some zooplankton juvenile stages and an overall higher zooplankton community biomass, resulting in a different summer assemblage that would not occur with a late spring bloom (Tomassi et al., 2013). A possible mismatch of timing with peak phytoplankton biomass and the large calanoid copepod Neocalanus spp. has been proposed to explain the decline of their respective populations during certain years in the SoG (Sastri and Dower, 2009) as well as in Oyashio, Japan (Chiba et al., 2008) (See Section 2.4.3).   Seasonal cues for zooplankton to quickly reproduce or migrate to surface waters after winter dormancy can vary between taxonomic groups. Particularly for large copepods in temperate marine waters (e.g., Neocalanus plumchrus, Eucalanus bungii), phenology is strongly dependent on temperature (Batten and Mackas, 2009). It is possible that in 2015 the spring bloom occurred before waters were warm enough to initiate zooplankton reproduction. This could explain the lack of variability in zooplankton biomass and abundance between the two years, aside from the notably higher abundance peak in 2016, which we largely attributed to a bloom of Evadne spp. Marine cladocerans can overwinter as resting eggs and quickly grow and reproduce when environmental conditions are appropriate (Onbé, 1985). As these blooms can be relatively short-lived, it is possible either that in 2015 we missed the cladoceran peak or the magnitude of the bloom was smaller, perhaps due to unfavorable conditions. Although the period of high zooplankton abundance lasted for approximately seven and a half months in both years and the peak abundance timing was very similar, the window of high abundance commenced two weeks later in 2016 than in 2015, possibly due to the delayed spring bloom. In 2016 zooplankton 20  density remained relatively high until November whereas in 2015 zooplankton abundance decreased in October. This shift in timing of maximum zooplankton abundance could directly affect higher-level consumers and will be discussed in further detail below. A study investigating phytoplankton-zooplankton coupling in the central SoG from the mid-1960s until the 1990s determined that despite substantial variation in the timing of the spring bloom, peak zooplankton biomass between years remained relatively fixed, with maximum zooplankton biomass occurring on May 6 (± 10 days) (Bornhold, 2000). These patterns align with our observations in the northern SoG, reporting similar zooplankton dynamics despite years with very different spring bloom timing. Bornhold (2000) also reported that years with tight coupling between phytoplankton and zooplankton peak biomass did not necessarily result in higher zooplankton biomass. The consistency in peak zooplankton timing may indicate a level of resilience to shifting bloom timing in the SoG system.  Changes in zooplankton communities in the SoG have been linked more strongly to decadal oscillations than interannual variability (Li et al., 2000; Mackas et al., 2013). Therefore, it is likely that on the time scale of this study interannual community composition and succession is less variable than the strong seasonality observed in the northern SoG.  Despite a distinct successional pattern in the overall zooplankton community composition in the northern SoG, we detected several intra-specific differences between years. In addition to the euphausiids spawning events in May of both years, we observed a second increase in larval krill in August 2016. Euphausiid spawning events have been linked closely to pulses of high phytoplankton production in Saanich Inlet (Heath, 1977), and historically two major spawning events were detected in the waters off southwestern Vancouver Island – one in May-June and one in August-September (Mackas, 1992). The second spawning event observed in 2016 was likely due to the second large phytoplankton bloom we observed in the northern SoG in mid-late August, suggesting that in years with multiple phytoplankton blooms euphausiids in the northern SoG undergo several spawning events. Most of the copepod species that had higher abundances in 2016 compared to 2015 (C. pacificus, C. anglicus, and Paracalanus spp.) have been associated with warmer water masses in the north Pacific (Peterson and Keister, 2003; Batten and Walne, 2011; Keister et al., 2011). The species that were relatively more abundant in 2015 21  (A. longiremis, C. marshallae, and Pseudocalanus spp.) are considered to be cold-water species (Peterson and Keister, 2003; Batten and Walne, 2011; Keister et al., 2011).  As previously mentioned, 2015 and 2016 were two years under the influence of large-scale climate features: the Blob and El Niño, respectively. Although both events influenced coastal British Columbia by increasing temperature and decreasing salinity in surface waters, the Blob and the El Niño likely impacted zooplankton communities in the SoG differently. The Blob warm water anomaly originated in the Gulf of Alaska due to a strongly positive sea level pressure (Bond et al., 2015), whereas the El Nino event was due to weakened trade winds in the equatorial Pacific (Rasmusson and Wallace, 1983). Batten et al. (2018) found a shift towards smaller copepods in the Gulf of Alaska associated with the Blob and El Nino events. Without a longer time series including non-anomalous years in the northern SoG, it is difficult to determine whether average copepod size was below the long term average. However, zooplankton community composition in the SoG has been closely linked to changes in the Southern Oscillation Index, so the El Nino event that developed in 2015 likely had an influence on species composition differences in the SoG. Since most water in the SoG enters the strait through Juan de Fuca Strait, there may have been a delay or reduced magnitude in the effects on the zooplankton community in the northern SoG since intermediate (50-200 m) water can take months to move north through the SoG (Pawlowicz et al., 2007).  The existing time series for zooplankton community composition in the SoG allows us to track long-term changes in the ecosystem. Interannual changes in the zooplankton assemblages in the SoG have been linked most closely to large-scale climate fluctuations (Li et al., 2000; Li et al., 2013), and the variations in the zooplankton communities in the SoG reflect these fluctuations in combination with the more local factors that can directly influence plankton communities. All species observed during this study are similar to historical datasets from the southern SoG (e.g., Harrison et al., 1983; Mackas et al., 2012) and those documented in the northeast Pacific, aside from the southern-origin copepods often observed in the waters off Oregon to the west coast of Vancouver Island (Mackas, 1992; Peterson and Keister, 2003; Keister et al., 2011). However, the relative dominance of key species has changed compared to historical records (Harrison et al., 1983). Allen and Wolfe (2013) determined that although the timing of the spring bloom in the SoG has not shifted to be earlier or later, the variability 22  between years has increased since the 1990s. An ecosystem with spring bloom timing that is more variable may select for species that are able to tolerate sporadic pulses of productivity. In addition, this will select against species with life history stages that require an overlap with the time of highest phytoplankton production such as Neocalanus plumchrus. Long-term sampling programs in the North Atlantic have detected the northward movement of calanoid copepods due to increasing temperatures (Beaugrand et al., 2009). As such, it is important to continue monitoring the SoG so that future changes can be detected.  Although the overall zooplankton community did not appear to respond to the different phytoplankton dynamics in 2015 and 2016, clearly there are still interannual differences in taxa-specific levels that can likely be attributed to a combination of local and regional factors.  2.4.3 Key zooplankton species: separating seasons Our comprehensive dataset allows us to differentiate the drivers of seasonal succession and regional differences on a species-level. The winter community was characterized by low zooplankton abundance and biomass. The community was best indicated by adult Neocalanus plumchrus, a large herbivorous calanoid copepod that overwinters and reproduces at depth. Overwintering N. plumchrus abundances were lower than those historically reported in the southern SoG from 1967 to 2006 (Fulton, 1973; El-Sabaawi et al., 2009). However, it is difficult to determine whether this was due to inherent differences between the northern and central SoG or an overall decline in N. plumchrus in the SoG observed over the last few decades (El-Sabaawi et al., 2009).  Our data suggest that this species has the ability to overwinter in the comparatively shallower northern SoG, whereas previously N. plumchrus has only been reported to overwinter in the deepest parts of the central SoG basin (~ 400 m) or in deep adjoining inlets (Fulton, 1973; Gardner, 1977; Harrison et al., 1983). Unlike winter 2015, we did not observe adult N. plumchrus overwintering at depth in winter 2016. However, we detected juveniles in spring of 2016, suggesting that transport from nearby resident populations following winters with poor recruitment in the northern SoG may be important in maintaining N. plumchrus populations in the northern basin (described at nearby locations by Gardner, 1977).  Early spring had a high abundance of meroplankton species, which has been observed in other mid to high latitude coastal regions (McKinstry and Campbell, 2017). Meroplankton larval stage abundance has been positively linked to sea surface temperature (Kirby et al., 2008). 23  Surface water temperatures may have initiated meroplankton reproduction, explaining the increase in abundance that was independent from the spring bloom timing in 2015 and 2016. The detection of higher abundances of fish eggs, larval fish, and euphausiids larval stages commencing in early spring aligns with historical reports from the SoG (Harrison et al., 1983).  Early spring was also characterized by the high abundance of several calanoid copepods, including Candacia columbiae, Centropages abdominalis, and Pseudocalanus spp. In previous studies in the northeast Pacific Pseudocalanus spp. has been an indicator of late spring-fall zooplankton communities when their abundances are maximum (e.g., P. minutus in Harrison et al., 1983; P. mimus in Keister and Peterson, 2003; Pseudocalanus spp. in Tommasi et al., 2013 and McKinstry and Campbell, 2017). Our study determined that P. moultoni and P. newmani were indicators of the early spring zooplankton assemblage, despite their peak abundances occurring in late summer during both years. This was likely due to an increase in their contribution to the overall zooplankton abundance in early spring. The summer-fall community was indicated by a combination of polychaetes, cnidarians, amphipods, cladocerans, and various copepods including Corycaeus anglicus, Eucalanus bungii, and Paracalanus spp. Polychaetes, cnidarians, and amphipods are all carnivorous, mostly feeding on small crustacean zooplankton. It is reasonable to assume that the increase in their respective populations was a response to the increased biomass of smaller zooplankton taxa in early spring. An increase in carnivorous zooplankton in late spring-fall has been observed in other coastal temperate environments (Mackas, 1992; Sastri and Dower, 2009; Mackas et al., 2013; Tommasi, 2013). Corycaeus anglicus and Paracalanus spp. are copepods that have been associated with warm water / summer zooplankton assemblages in the north Pacific (Keister and Peterson, 2003; Batten and Walne, 2011; Yoshiki et al., 2015). Our data showed that these two species thrived in warm surface waters during the summer months in the northern SoG. Eucalanus bungii are large copepods that overwinter at depths > 150 m (Krause and Lewis, 1979). High abundances of C3-C5 copepodite stages of E. bungii have been observed in surface waters of the northeast Pacific from April until July, before overwintering in deep water as C5 copepodites until the next spring (Krause and Lewis, 1979; Miller et al., 1984). The key species that separate seasons in the zooplankton community in the northern SoG likely reflect changes in environmental tolerances (i.e., temperature limits), food availability, and life history strategies.  24  2.4.4 Implications for higher trophic levels The robustness of the zooplankton successional dynamics in the northern SoG could benefit higher trophic levels that time important life history events to overlap with maximum zooplankton abundance. Despite a large difference in spring bloom timing between years, maximum zooplankton abundance in the northern SoG was observed within the same week in both years and very similar community development was observed. This lack of interannual variability provides some degree of stability for higher trophic levels that depend on encountering conditions of high zooplankton biomass.  Sockeye salmon are an ecologically, economically, and culturally important species in British Columbia. Fraser River Sockeye smolts enter the SoG from April to May and feed on zooplankton during their outmigration to the Gulf of Alaska (Groot and Cooke, 1987). Price et al. (2013) reported peak outmigration of Fraser River Sockeye Salmon through the northern SoG over the first 2 weeks in June from 2007 to 2011. During the course of this study juvenile Sockeye reached the northern SoG on May 12 and peaked during the first two weeks of June in 2015 and 2016 (Johnson et al., 2018). Healey (2011) suggested that climate change might shift the timing of outmigration by juvenile Fraser River salmon to be earlier, resulting in a mismatch with maximum zooplankton abundance. Outmigrating smolts encountered conditions of high zooplankton biomass in 2015 and 2016, reaching the northern SoG during the week of highest zooplankton biomass of both years. However, if zooplankton communities in the northern SoG exhibit resiliency to phenological changes despite changing environmental conditions, the likelihood of a mismatch between peak zooplankton abundance and salmon outmigration may increase in future years.  Although the period of high biomass was the same duration during both years, the window of high zooplankton occurred one month later in 2016. This shift in the period of “high biomass” could directly impact higher-level consumers. Pacific herring spawn in the SoG every spring and remain in the Strait for approximately one year, feeding on zooplankton and subsequently acting as an important food source to higher trophic levels or to commercial fisheries. Years with a mismatch between the zooplanktivorous seabird Cassin’s aucklet (Ptychoramphus aleuticus) and its prey Neocalanus cristatus in British Columbia have been linked to lower breeding success (Hipfner, 2008). Baleen whales feed directly on forage fish and 25  euphausiids in coastal British Columbia and can be directly or indirectly influenced by changes in zooplankton community composition and abundance. Additional data are needed to understand how the shift in the period of high zooplankton biomass would affect higher-level consumers in 2015 and 2016. 2.4.5 Limitations The years analyzed in this study represent two anomalous years in terms of oceanographic conditions, including the Blob in 2015 and El Niño in 2016. This makes drawing conclusions about the zooplankton community in the northern SoG difficult as no true baseline exists in the region for comparison. However, when comparing surface temperatures from this study to historical records, we confirmed that the years in this study are within historical ranges but warmer than average conditions in the northern SoG. Additionally, species composition is similar to that reported from the southern SoG.   Zooplankton are notoriously heterogeneously distributed through the water column, both vertically and horizontally. The full water column zooplankton tows analyzed in this study did not give us information on how zooplankton were distributed vertically in the water column. However, they provided us with integrated community changes, and were more comparable with existing literature that largely reports on full water column tows. Zooplankton often gather along fronts and other oceanographic features, adding to their so-called “patchiness” horizontally in the water column.  26   2.5 Conclusions This study was the first comprehensive analysis of seasonal and interannual zooplankton community dynamics in the northern SoG. The strong intra-annual seasonality observed in the water properties was reflected in the separation of distinct zooplankton communities during winter, early spring, and summer-fall. Despite the six-week difference in spring bloom timing in 2015 and 2016 in the northern SoG, zooplankton seasonal development was remarkably similar between years and peak abundance was observed within the same week in mid-May. The effects of several large phytoplankton blooms in 2016 did not alter zooplankton species composition between years, but was reflected by the occurrence of multiple euphausiid spawning events in 2016 compared to the single spawning event we observed in 2015. Copepod species that have been associated with warm-water assemblages in the North Pacific were more abundant in 2016 than 2015, likely as a result of the El Niño event that developed in late 2015. Similar to the southern SoG, our data support that zooplankton dynamics in the northern SoG are largely determined by large-scale climate events, with minor influences from local environmental factors. Although this study presents data from two anomalous years in terms of oceanographic conditions, 2015 and 2016 were within the historical range of water temperatures and therefore were likely representative of the seasonal and interannual variations we would expect to see in zooplankton communities in the northern SoG. Continued monitoring in the area will allow us to determine if the two years represent anomalies in terms of oceanographic conditions and community composition, or if they are representative of the northern SoG through time.         2.6 Tables Table 2.1 Summary of environmental conditions comparing 2015 and 2016 in the northern Strait of Georgia.   2015 2016 Environmental  parameters  Date  (Julian Date) Value Depth Date  (Julian Date) Value Depth Max temperature   June 22  (173) 18.1oC Surface July 20  (202) 17.9oC Surface Min temperature   Jan 6  (6) 7.0oC Surface Jan 4  (4) 7.2oC Surface Max salinity   Jan 21  (21) 30.80 psu Bottom Nov 28  (333) 31.00 psu Bottom Min salinity   Oct 27  (300) 22.16 psu Surface June 29  (181) 24.07 psu Surface Spring bloom initiation  ([Chl-a] > 5 μg L-1)  Feb 24  (55) 13.2 μg L-1 Surface Apr 1   (92) 8.8 μg L-1 Surface Max chl-a   Feb 24  (55) 13.2 μg L-1 5 m Aug 22  (235) 19.1 μg L-1 0 m Max integrated chl-a   Mar 13  (72) 181.8 μg L-1 0 – 30 m May 9  (130) 213.5 μg L-1 0 – 30 m Max zooplankton abundance  May 11  (131) 1381.4 ind.m-3 0 – 250 m May 18  (139) 3345.2 ind.m-3 0 – 250 m Approximate time of high zooplankton abundance (> 500 ind.m-3) Mar 1 – Oct 15 (60 – 288) > 500 ind.m-3 0 – 250 m Apr 1 – Nov 15 (92 – 320) > 500 ind.m-3 0 – 250 m   2.7 Figures   Figure 2.1. Map of the northern Strait of Georgia showing the location of sampling stations, QU39 and QU24 ( ). The inset is a map of coastal British Columbia, including the entire Strait of Georgia and the northern portion indicated by the black box.      Figure 2.2. Temperature (°C) and salinity (psu) profiles in the northern Strait of Georgia from January 2015 to December 2016. Note the change of depth scale.   30  81012141618Dec JanFebMarAprMay JunJulAugSep OctNovDec JanFebMarAprMay JunJulAugSep OctNovDec JanTemperature (°C) Depth (m)510305010020025026283032Dec JanFebMarAprMay JunJulAugSep OctNovDec JanFebMarAprMay JunJulAugSep OctNovDec JanSalinity (psu)Depth (m)5103050100200250 Figure 2.3. Mean monthly temperature and salinity in the northern Strait of Georgia from January 2015 to December 2016. Error bars represent the standard deviation from the mean.    2015                                                           2016 31   Figure 2.4. Nitrate, phosphate, and silicate profiles in the northern Strait of Georgia from January 2015 to December 2016. Note the change of depth scale. Grey dots indicate depth and days of discrete bottle sampling.    Figure 2.5. Chlorophyll-a concentration in the northern Strait of Georgia from January 2015 to December 2016. Grey dots indicate depth and days of discrete bottle sampling.    Figure 2.6. Integrated chlorophyll-a concentrations (mg m-2) over the top 30 m in the northern Strait of Georgia from January 2015 to December 2016.   33   Figure 2.7. Total abundance (individuals m-3) and biomass (mg dry weight m-3) in the northern Strait of Georgia from January 2015 to December 2016. Vertical dashed lines indicate the start of the spring bloom.  34   Figure 2.8. Abundance (individuals m-3 and biomass (mg dry weight m-3) of major zooplankton taxa in the northern Strait of Georgia from January 2015 to December 2016. Abundance and biomass are presented on a log10 scale. Vertical dashed lines indicate the start of the spring bloom.   35    Figure 2.9. Abundance (individuals m-3) of copepod species abundant in this study and/or frequently reported in studies in the northeast Pacific in the northern Strait of Georgia from January 2015 to December 2016.                 36     Figure 2.10. Dendrogram of cluster analysis of zooplankton samples using the average-linkage clustering method. Similarity levels were determined using the Bray-Curtis dissimilarity index applied to log10(x+1) transformed abundance data. Three primary clusters and three secondary clusters were identified.    Figure 2.11. NMDS plot of zooplankton species composition in the northern Strait of Georgia for samples collected in 2015 and 2016 (2D stress = 0.16). Similarity was based on the Bray-Curtis dissimilarity metric, applied to log10(x+1) transformed abundance data . a) Ellipses around the clusters indicate the standard deviation based on sample-group clusters; b) arrow indicates the environmental variable that explains the most variation in the community data. 37       Figure 2.12. Results of indicator species analysis for zooplankton species abundance data in the northern Strait of Georgia. Indicator values were calculated at each level of separation in the cluster analysis. Only species that have an indicator value of > 25 were included.  Chapter 3: Habitat mosaics and small-scale connectivity drive zooplankton composition and production in complex coastal environments 3.1 Introduction In seasonally productive coastal environments, intense vertical mixing during winter limits phytoplankton growth (Harrison et al., 1983; Wiltshire et al., 2008). Light limiting conditions are lifted when waters begin to stratify in spring and phytoplankton spend more time in the euphotic zone (Cushing, 1959; Harrison et al., 1983; Wiltshire et al., 2008). However, in areas where turbulent mixing does not cease in spring, nearshore waters are permanently mixed and light availability to phytoplankton remains low throughout the year (Thomson, 1976; Masson and Peña, 2009; McKinnell et al., 2014). Insufficient time in the euphotic zone can result in low phytoplankton biomass despite high macronutrient concentrations in surface waters. This phenomenon of high-nutrient, low-chlorophyll (HNLC) regions has been well documented and is typically a consequence of iron limitation or grazing and primarily occurs in offshore waters (e.g., Cullen, 1991; Miller et al., 1991; Boyd et al., 1996; Boyd et al., 2000; Lam and Bishop, 2008). Since phytoplankton constitute the base of the food web, their biomass levels impact their grazers, which are primarily zooplankton. Intensified mixing regimes that lower primary production compared to seasonally productive and stratified regions could influence zooplankton communities through changes in overall biomass, life history strategies, or species assemblages.   Localized mixing due to wind or tidally induced events may also significantly increase total zooplankton densities in mixed surface waters compared with the nearby stable water column (St. John et al., 1992; Sabatini et al., 2004). These increases have been attributed to the mixing and reallocation of nearby zooplankton aggregations as opposed to increased in-situ production in the mixed waters (St. John et al., 1992; Sabatini et al., 2004). A redistribution of the zooplankton maximum would likely increase the opportunities that higher-level consumers have to prey on zooplankton. Permanent mixing regime with low internal production may primarily rely on nearby productive regions to continually supply zooplankton biomass, i.e., allochthonous inputs. Concomitantly, coastal HNLC regions characterized by high tidal mixing likely act as a source of macronutrients to nearby stratified and productive waters. There are various global examples of coastal marine environments that are permanently well mixed, 39  including areas of Alaska (Etherington et al., 2007), British Columbia (Thomson, 1976; Perry et al., 1983; Masson and Peña, 2009), the United Kingdom (Pingree, 1978; Wafar et al., 1983), and Argentina (Sabatini et al., 2004). However, very few of these studies have addressed the question of how turbulent mixing conditions affect zooplankton dynamics.  Remarkably little research has been conducted on HNLC environments aside from the offshore and archetypal iron-limited HNLC region. Studies tend to focus on offshore waters and largely concentrate on how micronutrient addition might influence carbon export to deep waters (e.g., Le Borgne and Rodier, 1997; Boyd et al., 2000; Boyd et al., 2004; Hamme et al., 2004; Korb and Whitehouse, 2004). The paucity of HNLC studies in nearshore regions limits our understanding of how zooplankton production may be distributed across a range of productivity regimes as well as what species can thrive in an unproductive ecosystem existing within a larger seasonally productive region. Steele and Henderson (1992) modeled nitrate, phytoplankton, and zooplankton dynamics in productive and non-productive (i.e., HNLC) regions. They found that zooplankton populations in HNLC regions showed a small degree of seasonality in overall biomass, and that the observed changes were much smaller than those in regions with a large spring bloom (Steele and Henderson, 1992). The surface waters off British Columbia become iron limited west of the continental shelf and consequently, primary production remains relatively low offshore for most of the year (Boyd et al., 2004). Goldblatt et al. (1999) surveyed mesozooplankton during spring and summer from the west coast of Vancouver Island, British Columbia to HNLC waters in the northeast Pacific and found that maximum zooplankton biomass occurred in May and June. Despite a decrease in biomass from spring to summer, total abundance remained similar from May until August as the mesozooplankton community transitioned from large-bodied copepods in spring to smaller zooplankton in summer (Goldblatt et al., 1999). Coastal zooplankton biomass remained high into August and had a higher proportion of small to medium copepods and euphausiids compared to the offshore iron-limited HNLC stations (Goldblatt et al., 1999). However, ecosystem dynamics in large open water HNLC environments and localized light-limited HNLC regions may not be comparable, as the intensity of small-scale variability is much greater in nearshore regions compared with the open ocean (Longhurst, 1981). The impacts of mixing-driven coastal HNLC conditions on zooplankton and higher trophic levels remain to be investigated.  40  Coastal British Columbia presents a mosaic of productivity regimes. These encompass some of the most seasonally productive marine waters in North America (Harrison et al., 1983; Jackson et al., 2015), as well as regions remaining in a state of “permanent winter” with low chlorophyll-a despite high nutrients in surface waters year-round due to strong tidal mixing (Masson and Peña, 2009; McKinnell et al., 2014; Murray et al., 2015). Examples of two such extremes are found within a few hundred kilometers in the waters from the northern Strait of Georgia (SoG) to Johnstone Strait (JS) between Vancouver Island and mainland British Columbia (Figure 3.1). The SoG is a large semi-enclosed basin where most water exchange with the Pacific Ocean occurs through the Juan de Fuca Strait to the south, with minor influences through the northern connection with JS (Pawlowicz et al., 2007). The SoG undergoes extreme seasonal variability in surface waters and is characterized by a large phytoplankton bloom each spring with chlorophyll-a concentrations > 15 μg L-1 (Waldichuk, 1957; Harrison et al., 1983). Johnstone Strait is a 110 km long channel along the northeastern side of Vancouver Island and is characterized by intense tidal mixing and a cold and weakly stratified water column, resulting in low phytoplankton biomass year-round (Thomson, 1976). The Discovery Islands (DI) region connects the northern SoG to JS and is comprised of many narrow channels and fjords. Due to the interaction of tides from the north (Queen Charlotte Strait) and the south (Juan de Fuca Strait), the DI have some of the strongest tidal currents in the world, with currents up to 7.8 m s-1 in Discovery Passage (Lin et al., 2011; Chandler et al., 2017a).  This study aims to investigate the zooplankton composition in seasonally productive regions and permanently HNLC regions. The SoG, DI, and JS will be used as case studies to determine how zooplankton communities interact in a complex and dynamic coastal system with strong tidal influence. We predict that zooplankton distribution will be mostly influenced by the circulation patterns in the region, and areas with the strongest exchange of waters due to tidal mixing will have more similar zooplankton communities. We expect zooplankton communities in HNLC regions to have lower overall densities due to lower phytoplankton biomass, and be comprised of species that can survive in cold waters with low food availability. Past research in the region indicates that most water exchange in the SoG with the Pacific Ocean occurs through Juan de Fuca Strait (i.e., < 10 % through JS; Pawlowicz et al., 2007). Therefore, if water 41  exchange is limited between parts of the SoG / DI / JS, we expect to see regional differences in zooplankton community composition. 3.2 Methods 3.2.1  Field sampling Sampling was conducted the northern SoG, DI, and JS from April 2015 to July 2016. Samples from the northern SoG and the DI were collected by the Hakai Institute Ocean Observing Program (referred to in the methods collectively as SoG / DI), and samples from JS were collected by the Salmon Coast Field Station. A total of eight stations in the SoG / DI and four stations in JS were sampled during this study for zooplankton and environmental properties (Figure 3.1). Station QU33 was replaced with station QU43 in May 2016 and station JS2 was moved to station JS12 in April 2016 (Figure 3.1). Station coordinates and additional information can be found in the appendix (Table A1).  Zooplankton vertical tows were performed using a 2 m or 3 m length bongo net with a mouth diameter of 0.5 m and a mesh size of 250 μm. Nets were deployed to 5 m above bottom depth (April 2015 to May 2016) or to a maximum depth of 300 m (post-May 2016) at each station and retrieved at 1 m s-1. Each net was equipped with a General Oceanics mechanical flowmeter that was used to estimate volume filtered during each tow. After each vertical tow the net was rinsed down and the sample from one cod end was preserved in a 5 % buffered formalin-seawater solution. The sample from the other cod end was used for complementary analyses.  In the SoG / DI environmental data were collected every 7-14 days from April to August and monthly from September to March. In JS, environmental data were collected every 5-10 days from April to July and one station was sampled until late September 2015, when sampling in JS stopped until the following April. Environmental variables were collected at the same time as most zooplankton tows, and at a higher frequency (approximately weekly) than zooplankton tows in the SoG / DI in 2015, and for stations QU29, QU39, and QU43 in 2016. CTD (Conductivity, Temperature, Depth) probes were deployed to 5 m above bottom depth at a speed of 1 m s-1. SoG / DI CTD measurements were obtained using either an RBR maestro or a SeaBird 19plus V2. Johnstone Strait CTD measurements were obtained using an RBR concerto. CTD data were processed and then binned in 1 m increments. Niskin bottles were used to collect 42  water samples at discrete depths in the water column (0, 5, 10, 30, 5 m above the bottom). At some stations water was collected at additional depths (Table A2). Water samples were analyzed for nutrient concentrations (NO2 + NO3-, PO4-3, and SiO2) and bulk and/or size fractioned Chlorophyll-a. Chlorophyll-a samples were filtered onto GF/F filters immediately on collection and later extracted using 90 % acetone and fluorescence was measured on a Trilogy© Laboratory Fluorometer (Holm-Hansen and Riemann, 1978). 3.2.2 Zooplankton taxonomic analysis In the lab, zooplankton samples were transferred from the formalin solution and rinsed thoroughly with tap water. Samples were initially processed by identifying all organisms > 10 mm in length. Whole samples were then processed for individuals between 5-10 mm in length. If there were obviously >> 300 individuals in the 5-10 mm size range in a sample, the sample was split using a box plankton splitter and one half was processed in full and the other half was examined to ensure the sub-sample was representative of the entire sample. Samples were then subsampled using the box plankton splitter until approximately 300-400 individuals < 5 mm remained. All individuals in the subsample were identified to the lowest taxonomic level possible (Figure A1). Density was calculated by dividing the count data by the proportion of the sample processed and then dividing the total count by the volume filtered as measured by the flowmeter. Biomass was calculated using conversions of zooplankton species and stage data to mg dry weight (DW; Moira Galbraith, unpublished data).  3.2.3 Statistical analysis Multivariate analyses were performed in R using the statistical packages vegan and clustsig (Whitaker and Christman, 2014; Oksanen et al., 2016; R Core Team, 2018). Zooplankton abundances were log10(x+1) transformed to reduce the weighting of highly abundant species. A q-type analysis (normal analysis, where samples are sorted into groups according to zooplankton compositions) was performed on the log-transformed data based on the Bray-Curtis similarity matrix and average-linkage clustering (Field et al., 1982). A simprof test was conducted (α = 0.01) to determine statistical significance between clusters. All taxa present in > 5 % of samples were included for the q-type analysis (Peterson and Keister, 2003). Copepods were separated into species (or genus for Microcalanus spp., Paracalanus spp., Pseudocalanus spp.) if 43  > C4, genus if < C4, and stage categories of C1-C3, C4-C5, and C6. Fish were categorized as either “Fish larvae” or “Fish egg”. All other taxa were grouped to the lowest taxonomic level possible (Figure A1).  3.3 Results 3.3.1  Physical environment We observed a large range in the water properties across sampling stations from April 2015 to July 2016. Temperature and salinity in surface waters had a much larger range in the northern Strait of Georgia (SoG; QU39) and in the eastern Discovery Islands outside the mouth of Bute Inlet (eastern DI; QU33/43) compared to surface waters in the western Discovery Islands in Okisollo Channel (western DI) (QU29) or Johnstone Strait (JS) (JS2/12) (Figure 3.2; Table 3.1). The northern SoG and eastern DI will hereafter be referred to as (seasonally) stratified areas and JS and western DI will be referred to as mixed areas. Only environmental data for the four main sampling stations (QU39, QU29, QU33/43, and JS2/12) are discussed here. Additional data can be found in the appendix (Figure A7). Temperature varied over the study region with the warmest sea surface temperatures in stratified areas (17.1-18.1°C) and never higher than 13.3°C in mixed areas (11.3°C in JS and 13.3°C in western DI) (Table 3.1). The warm surface waters that developed over spring and summer in stratified stations appeared to penetrate deeper in the water column in the northern SoG than eastern DI (down to 20-30 m vs. 10-15 m, respectively; Figure 3.2). The lowest temperatures in surface waters were observed during December/January. Sampling was not conducted in JS from October to April, and the earliest environmental data were from mid-April. In stratified areas the minimum temperature in surface waters ranged from 6.5 to 8.2°C, whereas mixed area surface water minima were always above 8.2°C (8.9°C in JS and 8.2°C in eastern DI). The seasonal range of surface temperatures was much larger (> 10°C) in stratified waters than in mixed waters (never > 5°C).   Surface water salinity was more variable and generally lower in stratified areas compared to mixed areas (Figure 3.2). Surface salinity in the northern SoG was lowest during June / July (25.5 psu) and highest (29 psu) during December / January. Eastern DI had the freshest surface 44  waters observed in this study, with minimum values of approximately 18 psu in June / July and surface salinities of 26-27 psu in winter. Western DI had relatively high surface salinities throughout the year typically ranging from 28 to 29 psu. Johnstone Strait had distinctly higher salinity surface waters than any other stations, ranging from 30-31 psu throughout the year.   Temperature-Salinity plots showed that JS had characteristics distinct from the water in the northern SoG and DI (Figure 3.3). Generally, there was a much smaller range in temperature and salinity in JS than in any other region, and waters were persistently cold and salty. The northern SoG and eastern DI had similar water properties, and western DI appeared to be a mixed intermediate of surface and deep northern SoG / DI waters. There appeared to be some overlap of temperature and salinity properties in surface waters between western DI and southern JS (JS3), but when looking at the top 30 m of the water column averaged, it is clear that JS waters were different than other regions looked at in this study. 3.3.2 Macronutrient concentration Surface concentrations of nitrate, phosphate, and silicate were all decreased to limiting concentrations (< 2 μM for nitrate; Eppley et al., 1969; Mackas and Harrison, 1997) in stratified stations for most of the spring and summer months (Figure 3.4). Nutrient depletion was more intense in the northern SoG compared to eastern DI. Strong nutrient depletion was observed at depths > 30 m in the northern SoG, whereas most nutrient draw down was observed in the top 10 m in eastern DI. The mixed stations had slightly lower macronutrient concentrations in spring/summer compared to winter, but concentrations were always non-limiting (i.e., >> 2 μM for nitrate). All stations indicated high nutrient concentrations in surface waters during winter. Phosphate and nitrate were higher in winter surface waters in the northern SoG, eastern DI, and in western DI compared to JS. Concentrations of silicate were > 10 μM lower in JS surface waters during winter compared to other stations.    3.3.3 Chlorophyll-a biomass Seasonally stratified stations had intense and prolonged phytoplankton blooms during spring in both 2015 and 2016, whereas mixed stations had smaller and more episodic increases in chlorophyll-a in spring and summer (Figure 3.5). In the stratified stations we observed large blooms of chlorophyll-a with concentrations > 10 μg L-1. In the northern SoG the 2015 spring 45  bloom was observed in late February, which precedes the time series for this study (refer to Chapter 2; Table 3.1). This was six weeks earlier than 2016, however, zooplankton communities were not substantially influenced by the difference in spring bloom timing between years, and the difference in bloom timing between years is not expected to have influenced the results of the spatial analysis. Chlorophyll-a concentrations from February and March indicated that the bloom did not start until late-April 2015 in eastern DI and other stratified DI stations (data not shown for earlier months). In 2016 the northern SoG bloom was detected in early April, whereas in eastern DI it was observed in mid-April. Conversely, the mixed stations showed no evidence of large phytoplankton blooms during either year. In mid-April 2015 we observed elevated concentrations of chlorophyll-a in western DI, however, for most of the year concentrations remained between 0-1 μg L-1. JS similarly had very low chlorophyll-a concentrations for most of the year, with relatively higher concentrations in the top few meters in June 2015 and a short and shallow bloom in May 2016. Notably, concentrations in the mixed stations almost were rarely > 5 μg L-1.    Integrated chlorophyll-a over the top 30 m of the water column supported that there was higher phytoplankton biomass in the seasonally stratified stations compared to the mixed stations during spring and summer (Figure 3.6). These data indicated peak concentrations between 150-200 μg m-2 of chlorophyll-a over the top 30 m in stratified stations, whereas concentrations were typically < 50 μg m-2 at mixed stations (aside from 12-May 2015 in JS and 28-April 2015 in western DI). The highest integrated chlorophyll-a was observed in Hoskyn Channel at QU9 where integrated chlorophyll-a over the top 30 m was > 250 μg m-2 (Figure A8). 3.3.4 Zooplankton Total zooplankton abundance and biomass varied across the different regions in terms of both the timing and magnitude of maximum values (Figure 3.7; Figure 3.8; Table 3.1, Figure A11). Maximum zooplankton abundance across regions monitored in this study was consistently observed in western DI (QU29), with peak abundances observed in late April 2015 and late May 2016 (6512 and 9699 ind. m-3, respectively). Maximum zooplankton abundance in eastern DI (QU33) was detected in late April 2015 and late May 2016 and had the lowest overall abundances (1124 and 1696 ind. m-3) observed in this study. The peak in northern SoG (QU39) zooplankton abundance was observed in mid-May in 2015 and in 2016, with higher abundances 46  in 2016 (1381 and 3245 ind. m-3, respectively). Maximum zooplankton abundance in JS was observed at the end of June in 2015 and 2016 (1532 and 1963 ind. m-3, respectively). Data from the northern SoG and the DI stations suggest these regions have a zooplankton bloom each year where abundance is highest at some point in spring. Contrastingly, JS abundance in early spring was very low and abundance increased as spring and summer progressed.   Similar regional differences were reflected by zooplankton biomass patterns across the region (Figure 3.8; Table 3.1). The highest biomass observed in this study was in western DI, and biomass peaked at the same time as maximum abundance during both years (258.2 and 355.3 mg DW m-3 in 2015 and 2016, respectively). In eastern DI, peak zooplankton biomass was observed more than a month after peak abundance (57.4 mg DW m-3 on 26-June 2015 and 63.7 mg DW m-3 on 4-July 2016). In the northern SoG maximum biomass was observed on the same date as maximum abundance in 2015 and approximately six weeks after maximum abundance in 2016 (103.5 mg m-3 in 2015 and 210.3 mg DW m-3 on 29-June 2016). In JS, peak biomass was detected four days earlier than peak abundance in 2015 and at the same time in 2016 (60.3 and 78.4 mg DW m-3, respectively).  Cluster analysis of log-transformed zooplankton abundance identified two distinct clusters that separated out at approximately 48 % dissimilarity (Figure 3.9, Figure A9). One branch (Cluster 1; 11 samples) contained most of the samples from the northern SoG and the other (Cluster 2; 109 samples) contained the remaining northern SoG samples as well as all of the DI and JS samples. The next set of sub-clusters separated out at approximately 42 % dissimilarity, further separating the DI / JS cluster into distinct DI (and northern SoG) (Cluster 2A; 52 samples) and JS (Cluster 2B; 57 samples) clusters. A third set of sub-clusters identified three additional groupings at approximately 41 % dissimilarity, including the early spring zooplankton communities from 2015 in the DI (Cluster 2A1; 10 samples), an outlier in the northern SoG (Cluster 1A; 1 sample), and two outliers in JS (Cluster 2B1; 2 samples).  To identify the species that were characteristic of each cluster, an indicator species analysis was done at each of the three levels of clustering (Figure 3.10). At the highest level of clustering, the northern SoG cluster (Cluster 1) had 37 taxa identified as indicator species. This included various polychaetes, large copepods, euphausiids, ostracods, cnidarians, amphipods, small copepods, as well as other taxa. The DI / JS cluster (Cluster 2) was indicated by 12 47  different taxa, largely comprised of meroplankton. At the level separating the DI from JS zooplankton communities, the DI cluster (Cluster 2A) was distinguished by 11 taxa, mostly cnidarians and small copepods. Good indicator species for JS (Cluster 2B) included three copepods and the decapod Fabia subquadrata. The JS outlier (Cluster 2B1) was due to a combination of low abundance and the presence of the decapod Pasiphaea pacifica. The DI early spring 2015 community (Cluster 2A1) was indicated by meroplankton, the copepod Centropages abdominalis, and chaetognaths. The northern SoG outlier (Cluster 1A) had indicator taxa including Merluccius productus juveniles, various decapods, copepods, and larvaceans. The remaining northern SoG samples in cluster 1B were indicated by the polychaete Typhloscolex muelleri. No indicator species were identified for the lowest level of clustering for the remaining DI (Cluster 2A2) or JS (Cluster 2B2) samples.  The NMDS ordination of spring/summer zooplankton assemblages supported the spatial differences in the northern SoG / DI / JS region in both two and three dimensions (2D stress = 0.19, 3D stress = 0.15; Figure 3.11). Only the two-dimensional ordination is discussed here. The BIOENV analysis and Mantel tests identified a significant correlation (ρ = 0.55, p = 0.001) between a combination of temperature stratification index, sea surface temperature, and integrated chlorophyll-a with the zooplankton community dissimilarity.  Other combinations of environmental variables can be found in table A6. The arrows in Figure 3.11 point to the direction of the most rapid change in those environmental variables in this dataset.   Species of copepods that were abundant in this study and/or have been frequently reported in the literature for the region are presented in Figure 3.12. The abundance of each species is separated by each region (northern SoG, DI, and JS), month, and year. The mean is presented (±s.d. if sufficient samples were collected). Obvious regional differences include the higher abundance of Eucalanus bungii, Metridia pacifica, and Oithona spp. in the northern SoG during 2015 and 2016. In JS, Pseudocalanus spp. was significantly more abundant than the other regions, with abundances > 3 x higher than other stations in June and July. The abundance of several copepod species were lower in JS compared to the northern SoG and the DI (including Centropages abdominalis, Eucalanus bungii, Oithona spp., and Paracalanus spp.). Generally, in the DI species abundances were intermediate of the densities of the northern SoG and JS aside from the higher concentration of Corycaeus anglicus in June and July.   48 3.4 Discussion The spatial and temporal variability in coastal British Columbia marine waters provides a unique opportunity to examine zooplankton communities across a gradient of mixing and productivity regimes. Vertically mixed channels (e.g., JS and western DI) had low chlorophyll-a concentrations despite high macronutrient concentrations in surface waters throughout the spring and summer. In contrast, stratified areas (e.g., northern SoG and eastern DI) where surface waters were warmer and fresher in spring and summer had a large spring bloom where chlorophyll-a concentrations were >> 5 μg L-1.  During the period of highest zooplankton biomass in the North Pacific (March to July; Harrison et al., 1983; Mackas and Tsuda, 1999) we identified distinct zooplankton communities associated with these respective regions. This difference was consistent between years. Although the northern SoG, DI, and JS are close in physical proximity (all occurring within ~ 200 km), zooplankton communities were all remarkably distinct, with regional differences in species composition, dominant species, and seasonal patterns in abundance and biomass. Despite observing HNLC conditions in JS and the western DI, key zooplankton species and seasonal dynamics were very different between the two mixed systems. Below we discuss the small-scale regional differences in zooplankton communities in a complex coastal environment.  3.4.1  Persistent high-nutrient, low-chlorophyll regions in complex coastal regions To our knowledge, this is the first study to investigate the consequences of persistent turbulent mixing-induced HNLC conditions on zooplankton communities in nearshore environments. Johnstone Strait and the DI (particularly western DI) are both heavily influenced by tidal mixing (Thomson, 1976; Chandler et al., 2017a; Figure A6), and the resulting turbulence likely limits phytoplankton productivity via light limitation. At mixed water column locations surface waters never stabilize long enough for phytoplankton to take advantage of available nutrients in the euphotic zone. Although the top few meters in JS were slightly warmer and fresher than deeper waters, surface waters were advected out of JS into Queen Charlotte Strait due to strong estuarine circulation (Thomson and Huggett, 1980) and fast surface currents (maximum currents > 6 m s-1, average currents > 20 cm s-1; Thomson, 1976). This circulation pattern likely advected any possible in-situ primary production out of JS into Queen Charlotte Strait within approximately 24 hours (Thomson, 1976), likely playing a key role in the low chlorophyll-a   49 concentrations observed. The Juan de Fuca Strait at the southern end of the SoG exhibits similar permanently mixed conditions with low phytoplankton standing stock despite high nitrate concentrations (> 20 μM) throughout the year (Lewis, 1978; Masson and Peña, 2009).  In complex coastal channels and inlets the interaction between HNLC and stratified waters may increase overall productivity in the environment. In this study, we observed the highest chlorophyll-a values in the channel between the stratified SoG and the mixed western DI in Hoskyn Channel (QU9; Figure A8). Pingree (1978) observed that phytoplankton biomass was low on either side of a front separating tidally mixed waters and stratified waters - the mixed side was limited by light, whereas the stratified side is limited by nutrients. However, phytoplankton biomass was very high at the frontal zone where nutrients were supplied to the stratified waters (Pingree, 1978). Perry et al. (1983) observed a similar phenomenon in Hecate Strait, British Columbia, where the highest chlorophyll-a concentrations were observed at a front between tidally mixed waters and nearby stratified water. Sabatini et al. (2004) determined that vertical mixing on the southern portion of the Patagonian shelf limits primary and secondary production, but enhances production in nearby stratified waters. We expect that JS acts as a source of nutrients to stratified surface waters in Queen Charlotte Strait and Queen Charlotte Sound, which would similarly enhance primary production.  3.4.2 Regional differences in zooplankton seasonality: a combination of in-situ production and advection We observed a spring bloom in the northern SoG and parts of the DI, where chlorophyll-a concentration peaked on between late February to early April in the northern SoG (February 24, 2015 and April 1, 2016) and between late April to early May in the eastern DI (April 29, 2015 and May 3, 2016). Zooplankton abundance (and often biomass) peaked shortly after. Notably, in the western DI phytoplankton biomass remained low throughout the spring and summer but zooplankton abundance and biomass were the highest among all regions surveyed, with similar peak timing to other stations in the DI. Despite low chlorophyll-a concentrations in JS, zooplankton abundance increased through the duration of the summer and had the second highest abundance of the stations monitored (after western DI) after June in 2015 and 2016.  In the northern SoG and the DI we observed a strong successional pattern of zooplankton species during the spring/summer of both years. Barnacles, juvenile euphausiids, Pseudocalanus   50 spp., and Centropages abdominalis dominated abundance in April and May, shifting to adult euphausiids, Eucalanus bungii, and Metridia pacifica in June, and to Disconchoecia elegans and warm water copepods such as Paracalanus spp. and Corycaeus anglicus in July. The species detected and successional pattern of zooplankton communities we observed in this study are similar to past reports from the southern SoG (e.g., Harrison et al., 1983; Mackas et al., 2013). The northern SoG is a highly productive marine environment and zooplankton populations are likely sustained by a combination of permanent breeding populations in the northern SoG and advection from the southern SoG (Chapter 2). However, the DI had a higher density of meroplankton (particularly barnacles, bivalves, and gastropods) and fewer large (> 2 mm) zooplankton (aside from cnidarians) than the northern SoG. The higher abundance of meroplankton in the DI may be attributed to the numerous shallow sills and narrow channels that provide more surface area for benthic invertebrates with planktonic larval stages. The strong tidal currents in the DI can move water more than 14 km between ebb and flow cycles (Chandler et al., 2017a), and thus may transport zooplankton between channels with every tidal change. Although the cluster analysis indicated that the DI zooplankton communities were more similar to those in JS than to the northern SoG, the same analysis using presence/absence data instead of density data revealed that the northern SoG and DI are more similar to each other than to JS (Figure A10). This provides strong evidence for the zooplankton in the DI being sourced from the SoG, further supported by the physical oceanography data. Differences in community composition between the northern SoG and DI were largely driven by differences in the density of similar taxa.   Our study reported high densities of Acartia longiremis, Calanus marshallae, and Pseudocalanus spp. in JS compared to the northern SoG and DI after May during each year. These are all Boreal shelf species that have been reported in high abundance in Queen Charlotte Sound (Mackas and Galbraith, 2002). This indicates that zooplankton in JS are likely sourced from Queen Charlotte Sound through Queen Charlotte Strait and are upwelled over the sill at the northwest end of JS. Unlike the northern SoG and DI, Pseudocalanus spp. numerically dominated the zooplankton community in JS, reaching peak densities of 1460 ind.m-3 in July. Without zooplankton composition data from Queen Charlotte Sound, it is difficult to determine if high densities of Pseudocalanus spp. reflect high abundances in Queen Charlotte Sound, or if they indicate some other mechanism driving high abundances in JS. In Saanich Inlet, British   51 Columbia Pseudocalanus minutus has been documented to successfully grow and even reproduce in cold surface waters during winter by grazing on flagellates (Koeller et al., 1979). Therefore, it is possible that Pseudocalanus spp. feed and grow in JS despite persistent winter-like conditions through the spring and summer. Peterson et al. (1978) found that many boreal shelf zooplankton species have diel and/or ontogenetic migration strategies that help in population maintenance and retention in an advective coastal shelf system. Although Oregon is influenced by coastal upwelling and not strong tidal mixing as in JS, it is possible that Pseudocalanus spp. may utilize similar strategies to retain themselves in JS if conditions are suitable for growth. Species that may not be well adapted are likely advected back out of JS or potentially preyed on by higher trophic levels if turbulent mixing transports them to surface waters.  Densities of Pseudocalanus spp. were higher in this study in JS than past reports in Queen Charlotte Sound in 2000 and 2001 where abundances were highest in June (Mackas and Galbraith, 2002). Mackas et al. (2007b) reported that Pseudocalanus spp. is one of the most abundant copepods in Hecate Strait throughout spring and fall, so it is likely that there is considerable interannual variability in Queen Charlotte Sound zooplankton communities.   3.4.3 Broader implications Despite the global prevalence of tidally mixed nearshore environments, very little work has been done to address how these regions impact zooplankton distribution and species composition. The link between coastal HNLC regions and stratified productive regions may be important in increasing productivity locally, which may in turn enhance fisheries production. The waters north of Queen Charlotte Sound are hypothesized to be very important to groundfish populations due to the enhanced productivity from tidally mixed fronts (Perry et al., 1983). Furthermore, Owen (1981) summarized research identifying the association of various fish aggregations along oceanographic fronts. Sabatini et al. (2004) described a physical front where well mixed waters interacted with stratified waters as a “zooplankton hot spot” that may be important for local fish populations as good nursery or spawning grounds.  Changes in circulation patterns or temperature could impact not only the well-mixed systems, but also the nearby productive systems. Along the central to northern coast of BC, the southern copepod species have shown a long-term upward trend in abundance, which could shift the zooplankton community from predominantly cold water species (e.g., Calanus marshallae,   52 Pseudocalanus spp.) to warm water species (e.g., Paracalanus parvus, Ctenocalanus vanus) (Cummins and Haigh, 2010). Warm water species are typically less energetically favourable for higher trophic levels to consume due to their lower lipid content (Peterson and Schwing, 2003; Mackas et al., 2007a). Calanoid copepods in the North Atlantic have been reported to be shifting northward as temperatures increase (Beaugrand et al., 2009). The introduction of difference species assemblages to source waters would directly impact species composition in HNLC regions if most zooplankton production is advected in, and the new introduced species may not be able to tolerate the turbulent and mixed environment. 3.4.4 Limitations Our two years of data collection were both during years of anomalous ocean conditions, including “the Blob” in 2015 and El Niño in 2016. Although El Niño is part of the natural climate cycle in the Pacific Ocean, it is the warmer aperiodic phase of the El Niño-Southern Oscillation. This makes drawing conclusions about the zooplankton community throughout the northern SoG / DI / JS difficult, as no other baseline for zooplankton exists in the region. However, these scenarios act as a good example of how warming due to climate change may influence zooplankton populations and are thus important to study. Additionally, the species described in this study have all been previously described from nearby coastal environments indicating that the species present are likely representative of typical zooplankton communities in the region. It will be interesting to compare zooplankton communities across the region during “normal” and “cold” years.   Samples from the northern SoG (station QU39) were analyzed at the Institute of Ocean Sciences by zooplankton taxonomists at Fisheries and Oceans Canada. Combining datasets analyzed by various people are expected to introduce some differences in taxonomy. However, there was still overlap in the cluster analysis with the northern SoG station and other nearby stations, indicating that analysis was comparable. Due to time constraints, some copepods could not be identified down to the species level due to similarities in morphology (e.g., Pseudocalanus spp., Paracalanus spp.). Despite grouping some species to the genus level, we were still able to show strong interregional differences.   53   Our mesh size (250 μm) does not allow us to collect the smaller stage classes of many of the copepod species, which may have provided stronger evidence for in-situ vs. advected production of zooplankton within each region.    54  3.5 Conclusions This study is the first study to explicitly compare zooplankton communities across a gradient of productivity regimes in coastal British Columbia. The physical, chemical, and biological environments were very different between the northern Strait of Georgia (SoG), Discovery Islands (DI), and Johnstone Strait (JS). After the onset of water column stratification in spring of each year in the northern SoG and eastern DI, a large spring bloom developed with chlorophyll-a concentrations > 10 μg L-1 and subsequent nutrient depletion in surface waters during most of the summer. Conversely, in JS and western DI the water column never vertically stratified and remained well-mixed through spring and summer. These conditions resulted in high-nutrient, low-chlorophyll (HNLC) conditions where phytoplankton biomass remained low despite replete surface nutrient concentrations. Although regions were characterized as either productive / stratified or low-chlorophyll / mixed, zooplankton communities did not follow this characterization, rather grouping into distinct northern SoG, DI, and JS communities. Zooplankton species composition in the northern SoG and the DI were very similar, indicating that zooplankton in the DI were likely sourced from the SoG. However, differences in relative species densities between regions drove the differences observed in overall zooplankton communities. We detected very little interaction between the northern SoG / DI and JS from the physical water column profiles and zooplankton communities, suggesting that JS might have even less influence on the SoG than previously described (Thomson, 1976). Although we observed maximum zooplankton abundance shortly after the spring bloom in the northern SoG (aside from the anomalous early spring bloom in 2015) and the DI, in JS zooplankton abundance steadily increased from April until July. We suggest that strong tidal mixing in the DI and JS may enhance phytoplankton production in nearby stratified regions via increased nutrient input to surface waters.    55 3.6 Tables Table 3.1. Summary of environmental conditions comparing 2015 and 2016 at four core stations from the northern Strait of Georgia (QU39), the Discovery Islands (QU29, QU33), and Johnstone Strait (JS2). 2015 JS2 QU29 QU33 QU39 Max chl-a (value, date) 5.3 μg L-,  24-June 4.2 μg L-,  28-April 9.5 μg L-,  29-April 7.0 μg L-,  14-April* Max integrated chl-a (value, date) 82.1 μg,  12-May 108.8 μg,  28-April 188.4 μg,  29-April 166.3 μg,  1-May Max zoopl abundance (value, date) 1532 ind. m-3,  24-June 6512 ind. m-3,  28-April 1124 ind. m-3,  29-April 1381 ind. m-3,  11-May Max zoopl biomass (value, date) 60.3 mg DW m-3, 20-June  258.2 mg DW m-3, 28-April 57.4 mg DW m-3, 26-June 103.5 mg DW m-3, 11-May Max surface temperature (value, date) 11.25 °C, 30-June 12.54 °C,  25-June 17.50 °C,  26-June 18.09 °C,  22-June      2016 JS2 QU29 QU33 QU39 Max chl-a (value, date) 2.4 μg L-,  17-May 1.9 μg L-,  1-July 11.6 μg L-, 3-May  18.4 μg L-, 11-July Max integrated chl-a (value, date) 41.0 μg,  17-May 44.1 μg 1-July 151.1 μg, 3-May 213.5 μg, 9-May* Max zoopl abundance (value, date) 1963 ind. m-3,  29-June 8688 ind. m-3,  20-May 1686 ind. m-3, 21-May 3345 ind. m-3,  18-May Max zoopl biomass (value, date) 78.4 mg DW m-3,  29-June 355.3 mg DW m-3,  20-May 63.7 mg DW m-3, 4-July 210.3 mg DW m-3,  29-June Max surface temperature (value, date) 10.96 °C,  19-July 13.29 °C,  9-July 17.10 °C,  4-July 17.89 °C,  20-July  * in 2015 in the northern Strait of Georgia the spring bloom started before the scope of this study at the end of February where chlorophyll-a concentrations were up to 13 μg L-1 . Maximum integrated chlorophyll-a in 2016 was observed on May 13 with 181.8 μg over the top 30 m.   56 3.7 Figures                                        Figure 3.1. Map of the northern Strait of Georgia to Johnstone Strait including the Discovery Islands, showing the location of sampling stations ( ).  The inset is a map of coastal British Columbia.              57   Figure 3.2. Temperature and salinity over the top 30 m of the water column at four core stations from April 2015 to July 2016.   58  Figure 3.3. Temperature – salinity diagrams for all stations from the northern Strait of Georgia through the Discovery Islands and into Johnstone Strait from April 2015 to July 2016. Surface depths range from 0 to 2 m and bottom depths range from 145 m to 360 m.            59  Figure 3.4. Macronutrient (NO3- + NO2, PO4, SiO2) concentrations over the top 30 m of the water column at four core stations from April 2015 to July 2016.    60  Figure 3.5. Chlorophyll-a concentrations (μg L-1) at four core sampling stations in the Discovery Islands and Johnstone Strait region from April 2015 to July 2016. Grey dots indicate depth and days of discrete bottle sampling.   Figure 3.6. Integrated chlorophyll-a (mg m-2; 0-30 m) at four core sampling stations in the Discovery Islands and Johnstone Strait region from April 2015 to July 2016.    61  Figure 3.7. Total abundance of zooplankton (log10 (number of individuals m-3) at four core sampling stations in 2015 (top) and 2016 (bottom) from April to July.     Figure 3.8. Total biomass of zooplankton (log10 (mg DW m-3) at four core sampling stations in 2015 (top) and 2016 (bottom) from April to July.    62    Figure 3.9. Dendrogram of cluster analysis comparing zooplankton community composition across the northern Strait of Georgia, Discovery Islands and Johnstone Strait region from April to May of 2015 and 2016. Zooplankton abundance data were log10(x+1) transformed and a Bray-Curtis dissimilarity index was used for the average-linkage clustering method.    63                                 Figure 3.10. Results of indicator species analysis for zooplankton species abundance data across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016. Indicator values were calculated at each level of separation in the cluster analysis. Only species that have an indicator value of > 25 were included.  Hippolytidae (67)Cirripedia (66)Acartia longiremis (65)Cancer spp. (64)Oikopleura dioica (64)Gastropod veliger (62)Calanus spp. juv. (58)Copepod nauplii (58)Pseudocalanus spp. (57)Evadne spp. (57)Pagarus spp. (55)Crangonidae (43)Tomopteris pacifica (89)Eucalanus bungii (84)Oithona atlantica (83)Euphausia pacifica (82)Alacia minor (81)Tomopteris septentrionalis (79)Paraeuchaeta elongata (77)Cyphocaris challengeri (77)Disconchoecia elegans (74)Thysanoessa longipes (72)Clione limacina (68)Aegina citrea (67)Chiridius gracilis (67)Scolecithricella minor (67)Aglantha digitale (65)Nanomia bijuga (65)Oithona similis (63)Limacina helicina (62)Triconia borealis (61)Siphonophore gas float (60)Calanus pacificus (59)Dimophyes arctica (56)Metridia pacifica (56)Scina borealis (56)Neocalanus plumchrus (55)Littorina sp. eggs (53)Primno abyssalis (52)Munida quadrispina (47)Tomopteris spp. juv. (42)Polynoidae (40)Paraeuchaeta spp. juv. (38)Heterorhabdus tanneri (37)Gaetanus simplex (36)Spionidae (32)Fish eggs (28)Scaphocalanus echinatus (27)Sebastes spp. (27)Tortanus discaudatus (75) Fabia subquadrata (58)Aetideus divergens (44)Calanus marshallae (42)Aequorea victoria (57)Proboscidactyla flavicirrata (49)Muggiae atlantica (48)Bivalvia (48)Oithona spp. juv. (40)Microcalanus spp. (40)Corycaeus anglicus (40)Acartia hudsonica (39)Podon spp. (36)Nematocelis difficilis (33)Holothuroidea (27)Merluccius productus (91)Neotrypaea spp. (91)Gaetanus minutus (88)Caridea spp. (86)Aetideus spp. juv. (71)Candacia columbiae (59)Oikopleura labradorensis (44)Typhloscolex      muelleri (30)Polychaete trochophore (67)Centropages spp. juv. (65)Bryozoa (51)Centropages abdominalis (43)Parasagitta elegans (37)Pasiphaea     pacifica (76)QU39 Outlier QU39 (most)DI 2015 early springDI JS3 outliers (early 2015)JS1 22A 2B1A 1B 2A1 2A2 2B1 2B2  64  Integrated chl−a (0−30 m)Surface temp.Temp. stratification−1.0−0.50.00.51.0−1.0 −0.5 0.0 0.5 1.0NMDS1, Bray−Curtis Beta−deviationNMDS2, Bray−Curtis Beta−deviationStationJS1JS2JS3QU17QU29QU33QU39QU9ClusterNorthern SoGDIJS Figure 3.11. NMDS plot of zooplankton species composition across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016 based on a Bray-Curtis dissimilarity ordination (2D stress = 0.19). Ellipses around the clusters indicate the standard deviation based on sample-group clusters and arrows indicate the combination of environmental variables that explains the most variation in the community data.  65  Figure 3.12. Abundances (individuals m-2) of select copepod species across the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016.  66  Chapter 4: Conclusions This is the first study to investigate the spatial and temporal patterns of zooplankton communities in the northern Strait of Georgia (SoG), Discovery Islands (DI), and Johnstone Strait (JS) region in coastal British Columbia. This dissertation was motivated by a lack of zooplankton data for the region, despite its importance to many higher trophic levels. That, along with the complex oceanographic conditions resulting in a range of productivity and mixing regimes, inspired this research to address the regional and seasonal patterns that exist in the zooplankton communities. Since changes in zooplankton communities have been linked to changes in large-scale environmental changes in the north Pacific (Li et al., 2013; Mackas et al., 2013), it is critical to create a baseline in important areas for vulnerable, higher trophic level species feeding on them, (e.g., juvenile sockeye salmon).  4.1 Strong zooplankton community succession in the northern Strait of Georgia Despite decades of research in the southern basin of the SoG, zooplankton communities from the northern basin remained largely undescribed until now. A six week difference in spring bloom timing between years appeared to have minimal influence on zooplankton communities in the northern SoG, as we detected three distinct zooplankton assemblages that formed independent of the timing of the spring bloom each year: winter, early spring, and summer-fall. Each seasonal community was characterized by indicator species, and annual zooplankton abundance peaked within the same week of the calendar year. Although there were species-level differences between years, we believe that the system as a whole retains a degree of interannual resilience to buffer against unpredictable or variable environmental changes that may occur on short time scales. Since the northern SoG is connected to the southern basin and nearby inlets and channels, if a population of zooplankton is unsuccessful in overwintering for whatever reason (e.g., Neocalanus plumchrus during the winter of 2015-2016), the northern basin populations can be supplemented by adjacent regions. Though the overall zooplankton assemblage remained relatively robust between years, the years varied in terms of cold water species and warm water species dominance. Since there is an inherent energetic difference between warm and cold water copepods due to life history strategies (Lee et al., 2006), slight shifts to community composition  67  between years could have consequences for higher trophic levels that depend on zooplankton for food (Section 4.3). 4.2 Zooplankton communities in connected coastal environments Despite regional differences in chlorophyll-a biomass spanning an order of magnitude, zooplankton communities in the northern SoG / DI / JS region were separated more strongly by region rather than season or productivity. We believe that zooplankton in JS are sourced from Queen Charlotte Sound, whereas zooplankton in the DI are sourced from the SoG. This study suggests that JS and the DI (via Discovery Passage) may interact less than previously described by Thomson (1976) or more recent models (e.g., Foreman et al., 2012; Khangaonkar et al., 2017), which suggest frequent exchange between the two channels, albeit relatively small in quantity. Our results indicate that JS and the DI are largely unique water masses, so changes occurring in the SoG / DI due to exchange with the Pacific Ocean through Juan de Fuca Strait may differ from changes in JS through Queen Charlotte Sound. We explored the interactions between tidally mixed waters with low in-situ production and stratified waters that are productive but typically become nutrient limited in summer months. We found that in the western DI, despite permanent HNLC conditions, zooplankton abundance and biomass were consistently the highest across all stations sampled. The high community similarity throughout the DI regardless of chlorophyll-a concentration indicated that tidal mixing likely redistributed zooplankton from productive channels to tidally mixed channels, resulting in higher zooplankton densities in regions expected to have low in-situ production.    4.3 Consequences for outmigrating juvenile sockeye salmon Sockeye salmon (Oncorhynchus nerka) are a species of particular interest in British Columbia, holding considerable ecological, economic, and cultural importance. The Fraser River is the largest producer of wild salmon in Canada (Cooke et al. 2004), with the vast majority of sockeye smolts exiting freshwater during April to May each year (Hartt and Dell, 1986), funneling through the SoG / DI / JS to the Gulf of Alaska. The early marine migration has been hypothesized as an important factor in determining overall abundance, and marine survival of juvenile salmon is dependent on their early marine growth (Ricker 1976; Beamish et al. 2004; Farley et al. 2007). Salmonids are classified as opportunistic feeders, consuming prey within a  68  certain visible size range (Everest and Chapman 1972; Brodeur et al. 2003). Thus, differences in zooplankton species assemblage or density along the migration route of the early marine portion of their life could have a very significant impact on sockeye salmon survival.  McKinnell et al. (2014) hypothesized that JS was food limiting for outmigrating juvenile smolts, which would leave juvenile sockeye in poor condition every year after exiting JS. We detected different zooplankton conditions across the migration route, with the northern SoG and DI having a distinct window of maximum zooplankton abundance at some point in spring (in April or May in 2015 and 2016), and JS showing a pattern of increasing abundance with time over the season. This indicates that a mismatch in sockeye migration and zooplankton peak abundance timing in the northern SoG and DI may influence salmon survival (match-mismatch hypothesis; see updated summary in Cushing, 1990), whereas in JS the highest food conditions always occur later in the sockeye migration season. The western DI consistently had the highest zooplankton abundance and biomass, which may offer the best feeding conditions for salmon migrating through the DI. Although JS abundance increased over the season, biomass stayed relatively constant and was largely comprised of the copepod Pseudocalanus spp., which is one of the primary prey species of chum salmon in Nemuro Strait (Seki et al., 2006). Intense water column mixing could potentially distribute prey species more evenly vertically in the water column, increasing visual predation on energetically favourable species in surface waters. 4.4 Future directions Since our two years of sampling were conducted during two anomalously warm years (due to the Blob and El Niño) and this is the first study to report detailed species composition for the region, it is not possible to confirm if the zooplankton communities we described in this study are representative of “normal” or “cold” years. Continued monitoring of the region is necessary to understand how zooplankton communities may shift with large-scale climate indices and if zooplankton in the northern SoG, DI, and JS follow the same patterns with these indices as do those in the southern SoG (Li et al., 2013). Climate change is predicted to increase the frequency and intensity of large-scale climate variations (Di Lorenzo et al., 2008), causing a shift in dominating zooplankton species (i.e., “warm” versus “cold” copepods; Peterson et al., 2017), with serious implications for food quality. By linking these changes with fish production, we can  69  predict how commercially valuable fisheries may be influenced by shifts in zooplankton communities expected with climate change.   70  References Allen, S.E., Latornell, D.J. 2015. Spring phytoplankton bloom in the Strait of Georgia, 2015 and 2015. In: Chandler, P.C., King, S.A., Perry, R.I. (Eds.). State of the physical, biological and selected fishery resources of Pacific Canadian marine ecosystems in 2014. Can. Tech. Rep. Fish. Aquat. Sci. 3131: 151-156. Allen, S.E., Olson, E., Latornell, D.J, Pawlowicz, R. 2017. Timing of the spring phytoplankton bloom in the Strait of Georgia, 2016. In: Chandler, P.C., King, S.A., and Boldt, J. (Eds). State of the physical, biological and selected fishery resources of Pacific Canadian marine systems in 2016. Can. Tech. Rep. Fish. Aquat. Sci. 3225. Allen, S.E., Wolfe, M.A. 2013. Hindcast of the timing of the spring phytoplankton bloom in the Strait of Georgia, 1968-2010. Prog. Oceanogr. 115: 6-13. doi: 10.1015/j.pocean.2013.05.026 Anslow, F.S., Schnorbus, M., Campbell, D. 2016. British Columbia hydroclimatological conditions, 2015. In: Chandler, P.C., King, S.A., and Perry, R.I. (Eds.). State of the physical, biological and selected fishery resources in Pacific Canadian marine ecosystems in 2015. Can. Tech. Rep. Fish. Aquat. Sci. 3179.  Atkinson, A., Harmer, R.A., Widdicombe, C.E., McEvoy, A.J., Smyth, T.J., Cummings, D.G., Somerfield, P.J., Maud, J.L., McConville, M. 2015. Questioning the role of phenology shifts and trophic mismatching in a planktonic food web. Prog. Oceanogr. 137: 498-512. doi: 10.1016/j.pocean.2015.04.023 Ban, S. 1994. Effect of temperature and food concentration on post-embryonic development, egg production and adult body size of calanoid copepod Eurytemora affinis. J. Plankton Res. 16: 721-735. Batten, S.D., Raitsos, D.E., Danielson, S., Hopcroft, R., Coyle, K., McQuatters-Gollop, A. 2018. Interannual variability in lower trophic levels on the Alaskan Shelf. Deep Sea Res. II. 147: 58-68. Batten, S.D., Mackas, D.L. 2009. Shortened duration of the annual Neocalanus plumchrus biomass peak in the Northeast Pacific. Mar. Ecol. Prog. Ser. 393: 189-198. doi: 10.3354/meps08044 Batten, S.D., Walne, A.W. 2011. Variability in northwards extension of warm water copepods in the NE Pacific. J. Plankton Res. 33: 1643-1653. doi: 10.1093/plankt/fbr065 Beamish, R.J., Mahnken, C., Neville, C.M. 2004. Evidence that reduced early marine growth is associated with lower marine survival of Coho salmon. Trans. Am. Fish. Soc. 133: 26-33. Beaugrand, G., Brander, K,M,, Alistair, L.J., Souissi, S., Reid, P.C. 2003. Plankton effect on cod recruitment in the North Sea. Nature, 426(6967): 661-664. Beaugrand, G., Luxzac, C., Edwards, M. 2009. Rapid biogeographical plankton shifts in the North Atlantic Ocean. Global Change Biol. 15: 1790-1803. doi: 10.1111/j.1365-2486.2009.01848.x Bevan, D. 2015. Spatiotemporal variability in fatty acid profiles of the copepod Calanus marshallae off the west coast of Vancouver Island. M.Sc. thesis, The University of Victoria, Victoria, B.C.  Bollens, S., Frost, B., 1989. Predator-induced diel vertical migration in a planktonic copepod. J. Plankton Res. 11: 1047-1065. Bond, N.A., Cronin, M.F., Freeland, H., Mantua, N. 2015. Causes and impacts of the 2014 warm  71  anomaly in the NE Pacific. Geophys. Res. Lett. 42: 3414-3420. doi: 10.1002/2015GL063306  Bornhold, E.A. 2000. Interannual and interdecadal patterns in timing and abundance of phytoplankton and zooplankton in the central strait of Georgia, BC with special reference to Neocalanus plumchrus. M.Sc. thesis, The University of British Columbia, Vancouver, B.C. Boyd, P.W., Muggli, D.L., Varela, D.E., Goldblatt, R.H., Chretien, R., Orians, K.J., Harrison, P.J. 1999. In vitro iron enrichment experiments in the NE subarctic Pacific. Mar. Ecol. Prog. Ser. 136: 179-193. Boyd, P.W. 2004. Ironing out algal issues in the Southern Ocean. Science. 304(5669): 396-397. Boyd, P.W., Watson, A.J., Law, C.S., Abraham, E.R., Trull, T., Murdoch, R., Bakker, D.C.E., Bowie, A.R., Buesseler, K.O., Chang, H., Charette, M., Croot, P., Downing, K., Frew, R., Gall, M., Hadfield, M., Hall, J., Harvey, M., Jameson, G., LaRoche, J., Liddicoat, M., Ling, R., Maldonado, M.T., McKay, R.M., Nodder, S., Pickmere, S., Pridmore, R., Rintoul, S., Safi, K., Sutton, P., Strzepek, R., Tanneberger, K., Turner, S., Waite, A., Zeldis, J. 2000. A mesoscale phytoplankton bloom in the polar Southern Ocean stimulated by iron fertilization. Nature. 407(6805): 695-702. Brodeur, R.D., Myers, K.W., Heele, J.H. 2003. Research conducted by the United States on the early life history of Pacific salmon. N. Pac. Fish. Comm. Bull. 3: 89-131. Chandler, P.C., Foreman, M.G.G., Ouellet M., Mimeault C., Wade J. 2017a. Oceanographic and environmental conditions in the Discovery Islands, British Columbia. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/071. Chandler, P.C., King, S.A., Boldt, J. 2017b. Temperature and salinity observations in the Strait of Georgia and Juan de Fuca Strait in 2016. State of the physical, biological and selected fishery resources of Pacific Canadian marine ecosystems in 2016. Can. Tech. Rep. Fish. Aquat. Sci. 3225: 243 + vi p. Chandler, P.C., King, S.A., Perry, R.I. 2016. State of the physical, biological and selected fishery resources of Pacific Canadian marine ecosystems in 2015. Can. Tech. Rep. Fish. Aquat. Sci. 3179: viii + 230 p. Chiba, S., Aita, M.N., Tadokoro, K., Saino, T., Sugisaki, H., Nakata, K. 2008. From climate regime shifts to lower trophic level phenology: synthesis of recent progress in retrospective studies of the western North Pacific. Prog. Oceanogr. 77: 112-126. Clarke, K.R., Ainsworth, M. 1993. A method of linking multivariate community structure to environmental variables. Mar. Ecol. Prog. Ser. 92: 205-219.  Cloern, J.E., Jassby, A.D. 2008. Complex seasonal patterns of primary producers at the land-sea interface. Ecol. Lett. 11: 1294-1303. doi: 10.000/j.1461-0248.2008.01244.x Collins, A.K., Allen, S.E., Pawlowicz, R. 2009. The role of wind in determining the timing of the spring bloom in the Strait of Georgia. Can. J. Fish. Aquat. Sci. 66: 1597-1616. doi: 10.1139/F09-071 Cooke, S.J., Hinch, S.G., Farrell, A.P., Lapointe, M.F., Jones, S.R., Macdonald, J.S., Patterson, D.A., Healey, M.C., Van Der Kraak, G. 2004. Abnormal migration timing and high en route mortality of sockeye salmon in the Fraser River, British Columbia. Fisheries. 29(2): 22-33. doi: 10.1577/1548-8446(2004)29[22:AMTAHE]2.0.CO;2. Cullen, J.J. 1991. Hypotheses to explain high-nutrient conditions in the open sea. Limnol. Oceanogr. 36(8): 1578-1599.  72  Cummins, P. and Haigh, R. 2010. Ecosystem Status and Trends Report for North Coast and Hecate Strait ecozone. DFO Can. Sci. Advis. Sec. Res. Doc. 2010/045. vi + 61 p. Cushing, D.H. 1959. The seasonal variation in oceanic production as a problem in population dynamics. J. Cons. Cons. Perm. Int. Explor. Mer. 24: 455-464. Cushing, D.H. 1990. Plankton production and year-class strength in fish populations: an update of the match/mismatch hypothesis. Adv. Mar. Biol. 26: 491-496. Di Lorenzo, E., Schneider, N., Cobb, K.M., Franks, P.J.S., Chhak, K., Miller, A.J., McWilliams, J.C., Bograb, S.J., Arango, H., Curchitser, E., Powell, T.M., Rivière, P. 2008. North Pacific Gyre Oscillation links ocean climate and ecosystem change. Geophys. Res. Lett. 35: L08607. doi: 10.1029/2007GL032838 Dufrêne, M., Legendre, P. 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monograph. 67(3): 345-366. El-Sabaawi, R., Dower, J.D., Kainz, M., Mazumder, A. 2009. Interannual variability in fatty acid composition of the copepod Neocalanus plumchrus in the Strait of Georgia, British Columbia. Mar. Ecol. Prog. Ser. 382: 151-161. doi: 10.3354/meps07915 El-Sabaawi, R.W., Sastri, A.R., Dower, J.R., Mazumder, A. 2010. Deciphering the seasonal cycle of copepod trophic dynamics in the Strait of Georgia, Canada, using stable isotopes and fatty acids. Estuaries Coast. 33: 738-752. doi: 10.1007/s12237-009-9263-8. Eppley, R.W., Rogers, J.N., McCarthy, J.J. 1969. Half-saturation constants for uptake of nitrate and ammonium by marine phytoplankton. Limnol. Oceanogr. 14(6): 912-920. Etherington, L.L., Hooge, P.N., Hooge, E.R., Hill, D.F. 2007. Oceanography of Glacier Bay, Alaska: Implications for biological patterns in a glacial fjord estuary. Estuaries and Coasts. 30(6): 927-944. Everest, F.H., Chapman, D.W. 1972. Habitat selection and spatial interaction by juvenile Chinook Salmon and steelhead trout in two Idaho streams. J. Fish. Res. Board Can. 29: 91-100. Farley, E.V., Murphy, J.M., Adkinson, M., Eisner, L. 2007. Juvenile Sockeye Salmon distribution, size, condition and diet during years with warm and cool spring sea temperatures along the eastern Bering Sea shelf. J. Fish Biol. 71: 1145-1158.  Field, J.G., Clarke, K.R., Warwick, R.M. 1982. A practical strategy for analysing multispecies distribution patters. Mar. Ecol. Prog. Ser. 8: 37-52. Foreman, M.G.G., Guo, M., Garver, K.A., Stucchi, D., Chandler, P., Wan, D., Morrison, J., Tuele, D. 2015. Modelling infectious hematopoietic necrosis virus dispersion from marine salmon farms in the Discovery Islands, British Columbia, Canada. PLoS ONE. 10(6): e0130951.  Foreman, M.G.G, Stucchi, D.J., Garver, K.A., Tuele, D., Isaac, J., Grime, T., Guo, M., Morrison, J. 2012. A circulation model for the Discovery Islands, British Columbia. Atmos.-Ocean. 50(3): 301-306. doi: 10.1080/07055900.2012.686900 Fulton, J. 1973. Some aspects of the life history of Calanus plumchrus in the Strait of Georgia. J. Fish. Res. Board Can., 30(6): 811-815. Gardner, G.A. 1982. Patterns in the distribution and abundance of selected zooplankton species from the coast of British Columbia. Biol. Oceanogr. 1(3): 255-270. Gardner, G.A., 1977. Analysis of zooplankton population fluctuations in the Strait of Georgia, British Columbia. J. Fish. Res. Board Can. 34: 1196-1206. Goldblatt, R.H., Mackas, D.L., Lewis, A.G. 1999. Mesozooplankton community characteristics  73  in the NE subarctic Pacific. Deep Sea Res. II. 46: 2619-2644. Groot, C., Cooke, K. 1987. Are the migrations of juvenile and adult Fraser River sockeye salmon (Oncorhynchus nerka) in nearshore waters related? In Sockeye salmon (Oncorhynchus nerka) population biology and future management. Eds. Smith, H.D., Margolis, L., Wood, C.C. Can. Spec. Publ. Fish. Aquat. Sci. 96: 53-60. Groot, C., Margolis, L. 1991. Pacific salmon life histories. University of British Columbia Press, Vancouver. Gower, J., King, S., Statham, S., Fox, R., Young, E. 2013. The Malaspina Dragon: A newly-discovered pattern of the early spring bloom in the Strait of Georgia, British Columbia, Canada. Prog. Oceanogr. 115: 181-188. doi: 10.1016/j.pocean.2013.05.024 Haigh, R., Taylor, F.J.R. 1990. The distribution of potentially harmful phytoplankton species in the northern Strait of Georgia, British Columbia. Can. J. Fish. Aquat. Sciences. 47: 2339-2350. Haigh, R., Taylor, F.J.R. 1991. Mosaicism of microplankton communities in the northern Strait of Georgia, British Columbia. Mar. Biol. 110: 301-314. Hallett, T., Coulson, T., Pilkington, J., Clutton-Brock, T., Pemberton, J., Grenfell, B. 2004. Why large-scale climate indices seem to predict ecological processes better than local weather. Nature. 430: 71-145. Hamme, R.C., Webley, P.W., Crawford, W.R., Whitney, F.A., DeGrandper, M.D., Emerson, S.R., Eriksen, C.C., Giesbrecht, K.E., Gower, J.F.R., Kavanaughm, M.T., Peña, M.A., Sabine, C.L., Batten, S.D., Coogan, L.A., Grundle, D.S., Lockwood, D. 2010. Volcanic ash fuels anomalous plankton bloom in subarctic northeast Pacific. Geophys. Res. Lett. 37: L19604. doi: 10.1029/2010GL044629 Hare, S.R., Mantua, N.J. 2000. Empirical evidence for North Pacific regime shifts in 1977 and 1989. Prog. Oceanogr. 47: 103-145. Hartt, A.C., Dell, M.B. 1986. Early oceanic migrations and growth of juvenile Pacific salmon and steelhead trout. Int. N. Pac. Fish. Comm. Bull. 46. Harrison, P.J., Fulton, D.J., Taylor, R.J.R., Parsons, T.R. 1983. Review of the biological oceanography of the Strait of Georgia: pelagic environment. Can. J. Fish. Aquat. Sci. 40: 1064-1094. Hay, D.E., McCarter, P.B. 1997. Larval distribution, abundance, and stock structure of British Columbia herring. J. Fish Biol. 51(Supplement A): 155-175. Hays, G.C., Richardson, A.J., Robinson, C. 2005. Climate change and plankton. Trends Ecol. Evol. 20: 337-344. Healey, M. 2011. The cumulative impacts of climate change on Fraser River sockeye salmon (Oncorhynchus nerka) and implications for management. Can. J. Fish. Aquat. Sci. 68: 718-737. Heath, W.A. 1977. The ecology and harvesting of euphausiids in the Strait of Georgia. Ph.D. thesis, University of British Columbia, Vancouver, B.C. 187 p. Hipfner, J.M. 2008. Matches and mismatches: ocean climate, prey phenology and breeding success in a zooplanktivorous seabird. Mar. Ecol. Prog. Ser. 368: 295-304. Holm-Hansen, O., and Riemann, B. 1978. Chlorophyll a determination: improvements in methodology. Oikos, 30(3): 438-447. Hunter-Cevera, K.R., Neubert, M.G., Olson, R.J., Solow, A.R., Shalapyonok, A., Sosik, H.M. 2016. Physiological and ecological drivers of early spring blooms of a coastal  74  phytoplankter. Science. 354(6310): 326-329. doi: 10.1126/science.aaf8536 Jackson, J. M., R. E. Thomson,
L. N. Brown, P. G. Willis, and G. A. Borstad (2015), Satellite chlorophyll off the British Columbia Coast, 1997–2010, J. Geophys. Res. Oceans, 120, 4709– 4728, doi:10.1002/2014JC010496  Johnson, B.T., Gan, J.C.L., Janusson, C.V., Hunt, B.V.P. 2018. Juvenile salmon migration dynamics in the Discovery Islands and Johnstone Strait; 2015-2017. NPAFC Doc. 1790. 10 pp. Hakai Institute, Institute for the Oceans and Fisheries and Department of the Earth, Ocean and Atmospheric Sciences, University of British Columbia (Available at http://www.npafc.org) Keister, J.E., Di Lorenzo, E., Morgan, C.A., Combes, V., Peterson, W.T. 2011. Zooplankton species composition is linked to ocean transport in the Northern California Current. Global Change Biol. 17: 2498-2511. doi: 10.1111/j.1365-2486.2010.02383.x Keister, J.E., Peterson, W.T. 2003. Interannual variability in copepod community composition at a coastal station in the northern California Current: a multivariate approach. Deep Sea Res. II. 50: 2499-2517. Khangaonkar, T., Long, W., Xu, W. 2017. Assessment of circulation and inter-basin transport in the Salish Sea including Johnstone Strait and Discovery Islands pathways. Ocean. Model. 109: 11-32. Kiøboe, T., Nielsen, T.G., 1994. Regulation of zooplankton biomass and production in a temperate, coastal ecosystem. I. Copepods. Limnol. Oceanogr. 39(3): 493-507.  Kirby, R.R., Beaugrand, G., Lindley, J.A. 2008. Climate-induced effects on the meroplankton and the benthic-pelagic ecology of the North Sea. Limnol. Oceanogr. 53(5): 1805-1815.  Koeller, P.A., Barwell-Clarke, J.E., Whitney, F., Takahasi, M. 1979. Winter condition of marine plankton populations in Saanich Inlet, B.C., Canada. III. Meso-zooplankton. J. Exp. Mar. Biol. Ecol. 37: 161-174. Korb, R.E., Whitehouse, M. 2004. Contrasting primary production regimes around South Georgia, Southern Ocean: large blooms versus high nutrient, low chlorophyll waters. Deep Sea Res. I. 51: 721-738. doi: 10.1019/j.dsr.2004.02.006 Krause, E.P., Lewis, A.G. 1979. Ontogenetic migration and the distribution of Eucalanus bungii (Copepoda; Calanoida) in British Columbia inlets. Can. J. Zool. 57: 2211-2222. Lam, P.J., Bishop, J.K.B. 2008. The continental margin is a key source of iron to the HNLC North Pacific Ocean. Geophys. Res. Lett. 35(7). doi:10.1029/2008GL033294 Le Borgne, R., Rodier, M. 1997. Net zooplankton and the biological pump: a comparison between the oligotrophic and mesotrophic equatorial Pacific. Deep Sea Res. II. 9-10: 2003-2023. Lee, R.F. 1974. Lipids of zooplankton from Bute Inlet, British Columbia. J. Fish. Res. Board Can. 31: 1577-1582. Lee, R.F., Hagen, W., Kattner, G. 2006. Lipid storage in marine zooplankton. Mar. Ecol. Prog. Ser. 307: 273-306. LeBlond, P.H. 1983. The Strait of Georgia: functional anatomy of a coastal sea. Can. J. Fish. Aquat. Sci. 40: 1033-1063. Legendre, P., Legendre, L.F.J. 2012. 3rd ed. Numerical Ecology. Elsevier, Amsterdam, The Netherlands, 599-604.  Lewis, A.G. 1978. Concentrations of nutrients and chlorophyll on a cross-channel transect in Juan de Fuca Strait, British Columbia. J. Fish. Res. Board Can. 35: 305-314.  75  Li, M., Gargett, A., Denman, K. 2000. What determines seasonal and interannual variability of phytoplankton and zooplankton in strongly estuarine systems? Application of the semi-enclosed estuary of Strait of Georgia and Juan de Fuca Strait. Estuar. Coast. Shelf Sci. 50: 467-488. Li, L., Mackas, D.L., Hunt, B.P.V., Schweigert, J., Pakhomov, E.A., Perry, R.I., Galbraith, M., Pitcher, T.J. 2013. Zooplankton communities in the Strait of Georgia, British Columbia, track large-scale climate forcing over the Pacific Ocean. Prog. Oceanogr. 115: 90-102.  Lin, Y., Jiang, J., Fissel, D.B., Foreman, M.G., Willis, P.G. 2011. Application of a finite-volume coastal ocean model in studying strong tidal currents in Discovery Passage, British Columbia, Canada. Estuar. Coast. Model. 1: 99-117. Longhurst, A.R. 1981. Significance of spatial variability. In Analysis of marine ecosystems, Ed. Longhurst, A.R. New York: Academic Press, 415-441. Mackas, D.L. 1992. Seasonal cycle of zooplankton off southwestern British Columbia: 1979-89. Can. J. Fish. Aquat. Sci. 49: 903-921. Mackas, D.L., Batten, S., Trudel, M. 2007a. Effects on zooplankton of a warmer ocean: Recent evidence from the Northeast Pacific. Prog. Oceanogr. 75: 223-252. Mackas, D.L., Galbraith, M.D. 2002. Zooplankton distribution and dynamics in a North Pacific eddy of coastal origin: I. Transport and loss of continental margin species. J. Oceanogr. 58: 725-738. Mackas, D.L., Galbraith, M., Faust, D., Masson, D., Young, K., Shaw, W., Romaine, S., Trudel, M., Dower, J., Campbell, R., Sastri, A., Bornhold Pechter, E.A., Pakhomov, E.A., El-Sabaawi, R. 2013. Zooplankton time series from the Strait of Georgia: Results from year-round sampling at deep water locations, 1990-2010. Prog. Oceanogr. 115: 129-159. Mackas, D.L., Goldblatt, R., Lewis, A.G. 1998. Interdecadal variation in developmental timing of Neocalanus plumchrus populations at OSP in the subarctic North Pacific. Can. J. Fish. Aquat. Sci. 55: 1878-1893. Mackas, D.L., Greve, W., Edwards, M., Chiba, S., Tadokoro, K., Eloire, D., Mazzocchi, M.G., Batten, S., Richardson, A.J., Johnson, C., Head, E., Conversi, A., Peluso, T. 2012. Changing zooplankton seasonality in a changing ocean: Comparing time series of zooplankton phenology. Prog. Oceanogr. 97-100: 31-62. doi: 10.1016/j.pocean.2011.11.005 Mackas, D.L., Harrison, P.J. 1997. Nitrogenous nutrient sources and sinks in the Juan de Fuca Strait/Strait of Georgia/Puget Sound estuarine system: assessing the potential for eutrophication. Estuar. Coast. Shelf Sci. 44: 1-21. Mackas, D.L., Tsuda, A. 1999. Mesozooplankton in the eastern and western subarctic Pacific: community structure, seasonal life histories, and interannual variability. Prog. Oceanogr. 43: 335-363. Mackas, D., Peña, A., Johannessen, D., Birch, R., Borg, K., and Fissel, D. 2007b. Appendix D: Plankton. In Ecosystem overview: Pacific North Coast Integrated Management Area (PNCIMA). Edited by Lucas, B.G. Verrin, S., and Brown, R. Can. Tech. Rep. Fish. Aquat. Sci. 2667: iv + 33 p. Masson, D., Peña, A. 2009. Chlorophyll distribution in a temperate estuary: The Strait of Georgia and Juan de Fuca Strait. Estuar. Coast. Shelf Sci. 82: 19-28. doi: 10.1016/j.ecss.12.022 Mauchline, J. 1998. The biology of calanoid copepods. Advances in Marine Biology. 33: 1-710.  76  McKinnell, S., Curchitser, E., Groot, K., Kaeriyama, M., Trudel, M. 2014. Oceanic and atmospheric extremes motivate a new hypothesis for variable marine survival of Fraser River sockeye salmon. Fish. Oceanogr. 23(4): 322-341. doi: 10.111/fog.12063 McKinstry, C.A.E., Campbell, R.W. 2017. Seasonal variation of zooplankton abundance and community structure in Prince William Sound, Alaska, 2009-2016. Deep Sea Res. II. 147: 69-78. doi: 10.1016/j.dsr2.2017.08.016 Miller, C.B., Frost, B.W., Batchelder, H.P., Clemons, M.J., Conway, R.E. 1984. Life histories of large, grazing copepods in a subarctic ocean gyre: Neocalanus plumchrus, Neocalanus cristatus, and Eucalanus bungii in the Northeast Pacific. Prog. Oceanogr. 13(2): 201-243. Miller, C.B., Frost, B.W., Wheeler, P.A., Landry, M.R., Welschmeyer, N., Powell, T.M. 1991. Ecological dynamics in the subarctic Pacific, a possibly iron-limited ecosystem. Limnol. Oceanogr. 36(8): 1600-1615. Miller, J.A., Peterson, W.T., Copeman, L.A., Du, X., Morgan, C.A., Litz, M.N.C. 2017. Temporal variation in the biochemical ecology of lower trophic levels in the Northern California Current. Prog. Oceanogr. 155: 1-12.  Morales, C.E. 1999. Carbon and nitrogen fluxes in the oceans: the contribution by zooplankton migrants to active transport in the North Atlantic during the Joint Global Ocean Flux Study. J Plankton Res. 21(9): 1799-1808. Morrison, J., Quick, M.C., Foreman, M.G.G. 2002. Climate change in the Fraser River watershed: flow and temperature projections. J. Hydrol. 263: 230-244. Murray, J.W., Roberts, E., Howard, E., O’Donnell, M., Bantam, C., Carrington, E., Foy, M., Paul, B., Fay, A. An inland sea high nitrate-low chlorophyll (HNLC) region with naturally high pCO2. Limnol. Oceanogr. 60: 957-966. doi: 10.1002/lno.10062 Ohman, M.D., Frost, B.W., Cohen, E.B. 1983. Reverse diel vertical migration: an escape from invertebrate predators. Science. 220: 1404-1407. Oksanen, J., Blanchet, F.G., Fiendly, M., Kindt, R., Legendre, P. McGlinn, D., Minchin, P.R., O’Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Szoecs, E., Wagner, H. 2016. vegan: Community Ecology Package. R package version 2.4-1. http://CRAN.R-project.org/package=vegan Onbé, T. 1985. Seasonal fluctuations in the abundance of populations of marine cladocerans and their resting eggs in the Inland Sea of Japan. Mar. Biol. 87: 83-88. Osgood, K.E., Frost, B.W. 1994. Ontogenetic diel vertical migration behaviors of the marine planktonic copepods Calanus pacificus and Metridia lucens. Mar. Ecol. Prog. Ser. 104: 13-25. Owen, R.W. 1981. Fronts and eddies in the sea: mechanisms, interactions and biological effects. In Analysis of Marine Ecosystems, Ed. Longhurst, A.R. Academic Press: New York; 197-231. Parsons, T.R. 1979. The Strait of Georgia program. In Marine Production mechanisms. Ed. Dunbar, M.J. Cambridge University Press, Cambridge, p. 133-149. Parsons, T.R., LeBrasseur, R.J., Fulton, J.D., Kennedy, O.D. 1969. Production studies in the Strait of Georgia. Part II. Secondary production under the Fraser River plume, February to May, 1967. J Exp. Mar. Biol. Ecol. 3: 39-50. Pawlowicz, R. 2001. A tracer method for determining transport in two-layer systems, applied to the Strait of Georgia/Haro Strait/ Juan de Fuca Strait estuarine system. Estuar. Coastal Shelf Sci. 51: 491-503.  77  Pawlowicz, R. Riche, O., Halverson, M. 2007. The circulation and residence time of the Strait of Georgia using a simple mixing-box approach. Atmos.-Ocean. 45(4): 173-193. doi: 10.3137/ao.45401 Perry, R.I., Dilke, B.R., Parsons, T.R. 1983. Tidal mixing and summer plankton distributions in Hecates Strait, British Columbia. Can. J. Fish. Aquat. Sci. 40: 871-887. Peterson, W.T., Fisher, J.L., Strub, P.T., Du, X., Risien, C., Peterson, J., Shaw, C.T. 2017. The pelagic ecosystem in the Northern California Current off Oregon during the 2014-2016 warm anomalies within the context within the context of the past 20 years. J. Geophys. Res. Oceans. 122: 7267-7290. doi: 10.1002/2017JC012952 Peterson, W.T., Keister, J.E. 2003. Interannual variability in copepod community composition in a coastal station in the northern California Current: a multivariate approach. Deep Sea Res. II. 50: 2499-2517. Peterson, W.T., Miller, C.B., Hutchinson, A. 1978. Zonation and maintenance of copepod populations in the Oregon upwelling zone. Deep Sea Res. 26A: 467-494. Peterson, W.T., Schwing, F.B. 2003. A new climate regime in Northeast Pacific ecosystems. Geophys. Res. Lett. 30(17): 1896. doi: 10.1029/2003GL017528 Pingree, R.D. 1978. Mixing and stabilization of phytoplankton distributions on the northwest European continental shelf. In Spatial Pattern in Plankton Communities, Ed. Steele, J.H. Boston, MA: Springer US, 181-220. Price, M.H.H., Glickman, B.W., Reynolds, J.D. 2013. Prey selectivity of Fraser River Sockeye salmon during early marine migration in British Columbia. Trans. Am. Fish. Soc. 142(4): 1126-1133. R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R- project.org/. Rasmusson, E.M., Wallace, J.M. Meteorological aspects of the El Niño/Southern Oscillation. Science. 222(4629): 1195-1202. doi: 10.1126/science.222.4629.1195 Ricker, W.E. 1976. Review of the rate of growth and mortality of Pacific salmon in salt water, and non-catch mortality caused by fishing. J. Fish. Res. Board Can. 33: 1483-1524. Sabatini, M., Reta, R., Matano, R. 2004. Circulation and zooplankton biomass distribution over the southern Patagonian shelf during late summer. Cont. Shelf Res. 24: 1359-1373. Sastri, A.R., Dower, J.F. 2009. Interannual variability in chitobiase-based production rates of the crustacean zooplankton community in the Strait of Georgia. Mar. Ecol. Prog. Ser. 388: 147-157. doi: 10.3354/meps08111 Seki, J., Saito, T., Shimizu, I. 2006. Temporal changes of vertical distribution of zooplankton communities during spring and early summer in the Nemuro Strait coastal waters off Shibetsu, esastern Hokkaido. Bull. Natl. Salmon Resour. Center. 7: 37-46. St. John, M.A., Harrison, P.J., Parsons, T.R. 1992. Tidal wake-mixing: localized effects on primary production and zooplankton distributions in the Strait of Georgia, British Columbia. J. Exp. Mar. Biol. Ecol. 164: 261-274. Steele, J.H., Henderson, E.W. 1992. The role of predation in plankton models. J Plankton Res. 14(1): 157-172. Stephens, K.J., Fulton, J.D., Kennedy, O.D. 1969. Summary of biological observations in the Strait of Georgia, 1965-1968. Fish. Res. Board Can. Tech. Rep. 110: 11 p. Stockner, J.G., Cliff, D.D., Shortreed, K.R.S. 1979. Phytoplankton ecology of the Strait of Georgia, British Columbia. J. Fish. Res. Board. Can. 36: 657-666.  78  Sugimoto, T., Tadokoro, K. 1997. Interannual-interdecadal variations in zooplankton biomass, chlorophyll concentration and physical environment in the subarctic Pacific and Bering Sea. Fisheries Oceanography. 6(2): 74-93. Thomson, R.E. 1976. Tidal currents and estuarine-type circulation in Johnstone Strait, British Columbia. J. Fish. Res. Board Can. 33: 2242-2264. Thomson, R. E., 1981. Oceanography of the British Columbia Coast, Can. Spec. Publ. Fish. Aquat. Sci., 56, 291 pp., Canada communication group, Ottawa. Thomson, R.E., Huggett, W.S. 1980. M2 baroclinic tides in Johnstone Strait, British Columbia. J. Phys. Oceanogr. 10: 1509-1539.  Tommasi, D.A.G., Routledge, R.D., Hunt, B.V.P., Pakhomov, E.A. 2013. The seasonal development of the zooplankton community in a British Columbia (Canada) fjord during two years with different spring bloom timing. Mar. Biol. Res. 9(2): 129-144. doi: 10.1080/17451000.2012.708044 Wafar, M.V.M., Le Corre, P., Birrien, J.L. 1982. Nutrients and primary production in permanently well-mixed temperate coastal waters. Estuar. Coast. Shelf Sci. 17: 431-446. Waldichuk M., 1957. Physical oceanography of the Strait of Georgia, British Columbia. J. Fish. Res. Bd. Can. 14(3), 321-486. Ware, D.M., Thomson, R.E. 2005. Bottom-up ecosystem trophic dynamics determine fish production in the Northeast Pacific. Science, 308: 1280-1284. Williams, R., Thomas, L. 2007. Distribution and abundance of marine mammals in the coastal waters of British Columbia, Canada. J. Cetacean Res. Manage. 9(1): 15-28. Wiltshire, K.H., Malzahn, A.M., Wirtz, K., Greve, W. Janisch, S., Mangelsdorf, P., Manly, B.F.J., Boersma, M. 2008. Reslience of North Sea phytoplankton spring bloom dynamics: an analysis of long-term data at Helgoland Roads. Limnol. Oceanogr., 53(4): 1294-1302. Webber, M., Edwards-Myers, E., Campbell, C., Webber, D. 2005. Phytoplankton and zooplankton as indicators of water quality in Discovery Bay, Jamaica. Hydrobiologia 545(1): 177-193. Whitaker, D., Christman, M. 2014. clustsig: Significant Cluster Analysis. R package version 1.1. http://CRAN.R-project.org/package=clustsig Yoshiki, T.M., Chiba, S., Sasaki, Y., Sugisaki, H., Ichikawa, T., Batten, S. 2015. Northerly shift of warm-water copepods in the western subarctic North Pacific: Continuous Plankton Recorder samples (2001-2013). Fish. Oceanogr. 24(5): 414-429.   79  Appendix Sampling methodology Table A1. List of sampling stations, their respective coordinates, the bottom depth (in metres) of each station, and the time frame for which it was repeatedly sampled for the duration of this study. Stations beginning with ‘JS’ indicate the station was sampled by the Salmon Coast Field Station and stations beginning with ‘QU’ indicate the station was sampled by the Quadra Ecological Observatory. Station Latitude Longitude Bottom depth (m) Time frame sampled  JS1 50.6204 -126.7647 145 2015, 2016 JS2 50.5480 -126.6960 345 2015 JS12 50.5110 -126.5960 360 2016 JS3 50.5010 -126.3380 305 2015 QU17 50.1200 -125.1300 170 2015, 2016 QU29 50.2536 -125.1885 135 2015, 2016 QU33 50.3151 -125.0890 350 2015 – April 2016 QU43 50.3392 -125.1176 500 after April 2016 QU39 50.0307 -125.0992 265 mid-March 2015, 2016 QU24 50.0300 -125.0800 240 January – mid-March 2015 QU5 50.1183 -125.2122 70 2015, 2016 QU9 50.1804 -125.1371 130 2015, 2016  Table A2. Niskin sampling depths (in metres from surface) for each station and year. A ‘1’ indicates that depth was sampled, whereas a ‘0’ indicates no sampling at that depth.   Station Year Niskin Depth (m) 0 5 10 20 30 40 50 75 100 150 200 300 450 5 ab* JS1 2015 1 1 1 0 1 0 1 0 1 0 0 0 0 1 JS1 2016 1 1 1 0 1 0 1 0 1 0 0 0 0 1 JS2 2015 1 1 1 0 1 0 1 0 1 0 0 0 0 1 JS12 2016 1 1 1 0 1 0 1 0 1 0 0 0 0 1 JS3 2015 1 1 1 0 1 0 1 0 1 0 0 0 0 1 QU17 2015 1 1 1 0 1 0 0 0 0 0 0 0 0 1 QU17 2016 0 0 0 0 0 0 0 0 0 0 0 0 0 0 QU29 2015 1 1 1 0 1 0 0 0 1 0 0 0 0 1 QU29 2016 1 1 1 1 1 1 1 1 1 0 0 0 0 1 QU33 2015 1 1 1 0 1 0 0 0 1 0 0 0 0 1 QU43 2016 1 1 1 1 1 1 1 1 1 1 0 1 1 1 QU39 2015 1 1 1 0 1 0 1 0 1 0 0 0 0 1 QU39 2016 1 1 1 1 1 1 1 1 1 1 1 0 0 1 QU24 2015 1 1 1 0 1 0 0 0 1+ 0 0 0 0 1+ QU5 2015 1 1 1 0 1 0 0 0 0 0 0 0 0 1 QU5 2016 0 0 0 0 0 0 0 0 0 0 0 0 0 0 QU9 2015 1 1 1 0 1 0 0 0 0 0 0 0 0 1 QU9 2016 0 0 0 0 0 0 0 0 0 0 0 0 0 0 *ab indicates ‘above bottom depth’ + indicates inconsistent sampling of these depths  80  AnnelidaArthropodaBryozoaChaetognathaChordataCnidariaCtenophoraEchinodermataMolluscaPhoronoidaNemerteaSpp. or family LarvaeTrochophores, juvenilesSpp.LarvaceansFish larvaeSpp.Spp. or familySiphonophoraScyphozoaHydrozoaSpp. Gas floatsSpp.If <1mm, juvenile medusaIf >1mm, spp. or genusGenusClass, larvaeBivalviaCephalopodaGastropodaSpp. (L. helicina, C. limacina)VeligerLarvaeSpp.PilidiumLarvaeBranchiopodaInsectaMalacostracaMaxillopodaOstracoda Spp.Spp.OrderIsopodaEuphausiaMysidaDecapodaCumaceaAmphipodaCirripediaCopepodaStageCalanoidaCyclopoidaHarpacticoidaMonstrilloidaPoecilostomat.If >C4, stage & spp.If C1-C3, stage & genus<C6 or >C6; & spp.>C6 or <C6<C6 or >C6; & spp.<C6 or >C6; & spp.If <5mm, stage & family If 5-10mm, stage & spp.If >10mm, stage & spp. & sexIf zoea, genusIf megalops, spp. or genusFamily (Crangonidae, Hippolytidae, Majidae)If >5mm, sex & spp. or genus (Jassa, Orchomenella, Stillipes) Caprellidae Figure A1. Level of taxonomic identification done in this study.   81  Strait of Georgia, additional data Table A3. Temperature (°C, 0-30 m) and salinity (psu, 0-30 m) in the northern Strait of Georgia for 2015 and 2016.  2015 2016 Month Temp (± sd)  Salinity (± sd) Temp (± sd) Salinity (± sd)  January 7.78 (± 0.20) 27.57 (± 0.09) 7.93 (± 0.48) 28.78 (± 0.22) February 8.50 (± 0.21) 27.66 (± 0.30) 7.98 (± 0.05) 28.04 (± 0.37) March 9.08 (± 0.28) 27.98 (± 0.13) 8.75 (± 0.35) 27.51 (± 0.40) April 9.73 (± 0.17) 27.93 (± 0.55) 10.19 (± 0.51) 27.87 (± 0.21) May 11.62 (± 0.94) 28.13 (± 0.16) 11.15 (± 1.01) 28.41 (± 0.42) June 11.86 (± 1.36) 28.41 (± 0.54) 12.08 (± 0.55) 27.85 (± 0.32) July 12.12 (± 1.20) 28.48 (± 0.30) 13.04 (± 1.97) 27.78 (± 0.949) August 11.97 (± 1.48) 28.66 (± 0.17) 11.52 (± 0.97) 28.77 (± 0.29) September 12.84 (± 1.48) 28.50 (± 0.40) 12.90 (± 1.01) 28.65 (± 0.20) October 11.03 (± 0.72) 28.61 (± 0.24) 11.34 (± 0.17) 28.84 (± 0.05) November 10.01 (± 0.81) 28.92 (± 0.13) 10.18 (± 0.63) 27.03 (± 0.93) December 9.12 (± 0.26) 28.92 (± 0.32) 9.24 (± 0.01) 27.04 (± 0.50)      Table A4. Best combination of environmental variables with the zooplankton communities in the northern SoG from January 2015 to December 2016 with similarity score. Rank Combination of environmental variables Similarity score  1 NO3_5m 0.301 2 int_chla 0.188 3 int_chla + temp_5m + salin_5m + temp_surf + salin_surf + salin_deep + salin_strat 0.184 4 int_chla + temp_5m + salin_5m + salin_surf + salin_deep + temp_strat + salin_strat  0.175 5 SiO2_5m + Chla_5m + temp_5m + salin_5m + temp_surf + salin_surf + salin_deep + temp_strat 0.167 6 int_chla + temp_5m + salin_5m + temp_surf + salin_deep 0.161 7 NO3_5m + PO4_5m + Chla_5m + temp_5m + temp_surf + salin_deep + temp_strat 0.159 8 PO4_5m + SiO2_5m + Chla_5m + int_chla + temp_5m + salin_5m + temp_surf + salin_surf + salin_strat 0.157 9 PO4_5m + Chla_5m + temp_5m + salin_5m + temp_surf + salin_surf + temp_strat 0.157 10 NO3_5m + PO4_5m + Chla_5m + int_chla + salin_surf 0.156  82   Figure A2. Mean monthly temperature and salinity from 0-30 m in the northern Strait of Georgia. Blue dots indicate the long-term average (±sd) since 1932 (Chandler et al., 2017a). Black line indicates the full historical range of measurements collected in the area (Chandler et al., 2017a). Red and green dots represent observed measurements (±sd) in 2015 and 2016, respectively.   83   Figure A3. Temperature – salinity diagram of the northern Strait of Georgia from January 2015 to December 2016. From top right clockwise: all data collected, top 30 m, bottom depth, surface depth.  02040600 1 2 3 4Phosphate [uM]Nitrate [uM]02040600 20 40 60 80Silicate [uM]Nitrate [uM]0204060800 1 2 3 4Phosphate [uM]Silicate [uM] Figure A4. Macronutrient ratios in the northern Strait of Georgia from January 2015 to December 2016. Red line indicates the Redfield Ratio relationship (16 N : 15 Si : 1 P).    84   Figure A5. Abundances (individuals m-3) of select non-copepod species in the northern Strait of Georgia from January 2015 to December 2016.   85  Strait of Georgia to Johnstone Strait, additional data Table A5. Best combination of environmental variables with the zooplankton communities in the northern SoG, DI, and JS regions from April 2015 to July 2016 with similarity score.   Rank Combination of environmental variables Similarity score  1 int_chla + temp_surf + temp_strat 0.120 2 Chla_5m + salin_5m + salin_surf + temp_deep + salin_deep + temp_strat + salin_strat 0.115 3 NO3_5m + PO4_5m + SiO2_5m + Chla_5m + salin_5m + temp_surf + salin_surf + salin_deep + temp_strat + salin_strat 0.107 4 SiO2_5m + Chla_5m + salin_5m + temp_surf + salin_surf + salin_deep + salin_strat 0.103 5 NO3_5m + PO4_5m + SiO2_5m + temp_strat + salin_strat 0.100 6 PO4_5m + salin_5m + temp_surf + salin_surf + salin_deep + salin_strat 0.098 7 7                                        NO3_5m + PO4_5m + SiO2_5m + Chla_5m + salin_5m + salin_surf + salin_deep 0.096 8 SiO2_5m + salin_deep + salin_strat 0.094 9 NO3_5m + Chla_5m + salin_surf + temp_deep + salin_deep + temp_strat + salin_strat 0.094 10 temp_5m + salin_5m + salin_surf + temp_deep + salin_deep + salin_strat 0.090     86   Figure A6. Mean monthly temperature (°C) and salinity (psu) (±sd) from 0-30 m across the northern Strait of Georgia to Johnstone Strait, reproduced from Chandler et al., 2017a.       87   Figure A7. Full water column profiles of temperature and salinity for four core stations from March 2015 – July 2016. 88    Figure A8. Integrated chlorophyll-a at all stations in the Discovery Islands and Johnstone Strait region from April 2015 to July 2016.    89  QU39_20160629QU39_20160427QU39_20160508QU39_20160608QU39_20160619QU39_20160710QU39_20150616QU39_20150511QU39_20150527QU39_20150415QU39_20150622QU33_20150429QU29_20150428QU9_20150428QU17_20150415QU5_20150415QU9_20150515QU9_20150525QU29_20150416QU9_20150416QU29_20160529QU9_20160529QU5_20150622QU29_20160520QU5_20160518QU5_20150511QU5_20150527QU5_20160629QU29_20160610QU29_20160619QU29_20160701QU5_20150616QU17_20160629QU5_20160608QU17_20160608QU9_20160619QU29_20150608QU29_20150515QU29_20150525QU29_20150625QU9_20150608QU9_20150625QU17_20150616QU17_20150511QU33_20150421QU33_20160611QU33_20160704QU33_20160503QU33_20160521QU17_20150527QU17_20150622QU33_20150514QU33_20150528QU33_20150610QU33_20150626QU9_20160508QU29_20160429QU29_20160508QU39_20160529QU17_20160518QU39_20160518QU5_20160427QU17_20160427QU33_20160419JS3_20150417JS3_20150429JS1_20160423JS2_20150520JS1_20160418JS2_20160421JS2_20160428JS1_20150515JS1_20150502JS2_20150503JS2_20150512JS2_20160510JS1_20160430JS1_20160503JS1_20160509JS1_20160605JS1_20160522JS1_20160519JS2_20160528JS1_20160515JS1_20160531JS1_20150623JS1_20160618JS1_20160627JS1_20150526JS3_20150608JS3_20150518JS3_20150523JS3_20150603JS1_20150507JS3_20150513JS3_20150622JS2_20160616JS3_20150615JS2_20160626JS2_20160704JS1_20160703JS2_20160629JS1_20160613JS2_20160621JS2_20150613JS1_20150616JS2_20160609JS2_20150527JS1_20150609JS2_20150620JS2_20150607JS2_20150624JS2_20160612JS2_20160602JS2_20160514JS2_20160517JS1_20150519JS1_20150606JS1_20160623JS2_201505160.00.10.20.30.40.5Bray−Curtis DissimilarityFigure A9. Dendrogram of cluster analysis comparing zooplankton community composition in the Discovery Islands and Johnstone Strait region from April to May of 2015 and 2016. Zooplankton abundance data were log10(x+1) transformed and a Bray-Curtis dissimilarity index was used for the average-linkage clustering method.  90   Figure A10. Dendrogram of cluster analysis comparing zooplankton community composition in the Discovery Islands and Johnstone Strait region from April to July of 2015 and 2016. Zooplankton abundance data were transformed into a presence/absence matrix and a Sorensen dissimilarity index was used for the average-linkage clustering method. Three primary clusters and two secondary clusters appear.  91   Figure A11. Total abundance of zooplankton (number of individuals *105 m-2) at each station in 2015 (black circles) and 2016 (white squares) from April to July. Station JS3 was only sampled in 2015.    

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