Arts, Faculty of
Geography, Department of
DSpace
UBCV
Grishaber, Emily
Master of Science - MSc
University of British Columbia
The rate of environmental change in the Arctic is greater than in any other global biome. Dendrochronological methods have been used in arctic ecosystems to investigate growth changes experienced by woody plants as a result of climate change. Recent and projected future climate warming in the Arctic is expected to increase plant growth potential as arctic ecosystems are heat-limited environments. Recent studies suggest that warmer local temperatures are linked to increases in shrub abundance and growth across the tundra, and that these responses are highly specific to local site conditions and species investigated. Here, we investigated ring-widths from stem/root collars of Dryas integrifolia, a common dwarf evergreen species, collected from three subsites along a moisture gradient at a High Arctic field site, Alexandra Fiord, Ellesmere Island, NU, to determine growth relationships with local environmental variables. We used a passive warming treatment to investigate effects of a 1-3⁰ C increase in growing season temperature over 20 years on the growth of Dryas integrifolia. We determined that temperature was a significant driver of radial growth, demonstrating larger ring width sizes of shrubs grown in the experimental warming treatment compared to plants grown in the control treatment. However, temperature did not appear to be directly correlated to ring width size. Soil moisture was significantly correlated to ring width of plants grown in warmed plots from two of the three investigated subsites at Alexandra Fiord. No other measured environmental variable showed a significant relationship with ring width size. The results from this study suggest that D. integrifolia growth responds to temperature and soil moisture levels; however, the direction and degree of response is highly dependent on local site conditions. These results are consistent with others found from Arctic plant studies, which generally conclude that the effect of environmental change on plant species and communities is variable in time and space. Shrubs are anticipated to proliferate throughout Arctic tundra ecosystems with future warming, and understanding the direct effects of temperature on growth will provide insight as to how we may expect these ecosystems to shift with climate change.
RADIAL GROWTH RESPONSES IN DRYAS INTEGRIFOLIA TO AMBIENT AND EXPERIMENTAL WARMING IN THE HIGH ARCTIC by Emily Grishaber BSc Environmental Biology, Queen’s University, 2019 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Geography) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2023 © Emily Grishaber, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Radial Growth Responses in Dryas integrifolia to Ambient and Experimental Warming in the High Arctic submitted by Emily Grishaber in partial fulfilment of the requirements for the degree of Master of Science in Geography Examining Committee: Greg Henry, Professor Emeritus, Geography, UBC Supervisor Shelly Rayback, Department Chair, Geography and Geosciences, the University of Vermont Supervisory Committee Member Lori Daniels, Professor, Forest and Conservation Sciences, UBC Supervisory Committee Member iii ABSTRACT The rate of environmental change in the Arctic is greater than in any other global biome. Dendrochronological methods have been used in arctic ecosystems to investigate growth changes experienced by woody plants as a result of climate change. Recent and projected future climate warming in the Arctic is expected to increase plant growth potential as arctic ecosystems are heat-limited environments. Recent studies suggest that warmer local temperatures are linked to increases in shrub abundance and growth across the tundra, and that these responses are highly specific to local site conditions and species investigated. Here, we investigated ring-widths from stem/root collars of Dryas integrifolia, a common dwarf evergreen species, collected from three subsites along a moisture gradient at a High Arctic field site, Alexandra Fiord, Ellesmere Island, NU, to determine growth relationships with local environmental variables. We used a passive warming treatment to investigate effects of a 1-3⁰ C increase in growing season temperature over 20 years on the growth of Dryas integrifolia. We determined that temperature was a significant driver of radial growth, demonstrating larger ring width sizes of shrubs grown in the experimental warming treatment compared to plants grown in the control treatment. However, temperature did not appear to be directly correlated to ring width size. Soil moisture was significantly correlated to ring width of plants grown in warmed plots from two of the three investigated subsites at Alexandra Fiord. No other measured environmental variable showed a significant relationship with ring width size. The results from this study suggest that D. integrifolia growth responds to temperature and soil moisture levels; however, the direction and degree of response is highly dependent on local site conditions. These results are consistent with others found from Arctic plant studies, which generally conclude that the effect of environmental change on plant species and communities is variable in time and space. Shrubs are anticipated to proliferate throughout Arctic tundra ecosystems with future warming, and understanding the direct effects of temperature on growth will provide insight as to how we may expect these ecosystems to shift with climate change. iv LAY SUMMARY The global north has been warming at rates much faster than the global average. Alongside this has been a trend of shrubs growing larger, and becoming more abundant across the Arctic. Studies of the growth rings in stems of Arctic shrub species have shown increases in growth with climate warming, although there are variations among places and species. In this study, we investigated the ring growth in a common and wide-spread evergreen Arctic shrub, Dryas integrifolia (white mountain avens, or Malikkaat) grown under both small greenhouse and natural conditions, using the study of plant stem growth rings to determine relationships between growth and environmental variables. Radial growth in D. integrifolia was significantly positively impacted by the greenhouse treatment, and was related to temperature and soil moisture conditions. These relationships were highly variable depending on individual plant and site characteristics at a High Arctic field site. v PREFACE The experimental design and research objectives in this thesis were originally designed by Dr. Greg Henry (UBC). This study contributes to the knowledge base of the International Tundra Experiment (ITEX), an international collaborative network of researchers studying the effects of climate change in Arctic and alpine tundra ecosystems. In the field, I was assisted by Sofie Agger (UBC) in collecting Dryas integrifolia individuals for laboratory work. As recommended by Elise Gallois (University of Edinburgh), Dr. Lori Daniels (UBC), and Dr. Greg Henry, I used Cybis CooRecorder and CDendro software packages to conduct shrub-ring image processing. I was also assisted by Ingrid White, a geography undergraduate student, in shrub-ring image processing (2021). The laboratory methods were adapted from Dr. Lori Daniels PhD dissertation laboratory methods (REF), and statistical code was partially shared by Elise Gallois. The global COVID-19 pandemic inevitably impacted the course of my Master’s program. The field season originally set for three months over the summer in 2020, turned into two weeks during August of 2021. The delay arriving to Alexandra Fiord meant a delay in data collection, as well as a substantial decrease in the amount of data collected. Dr. Greg Henry, Dr. Shelly Rayback (University of Vermont), and Dr. Lori Daniels acted as my thesis committee and provided feedback and advice on my laboratory and statistical methodologies. I was responsible for the writing of the thesis and, with the support of Dr. Greg Henry, conducted all of the analyses included therein. vi TABLE OF CONTENTS ABSTRACT .................................................................................................................................iii LAY SUMMARY..........................................................................................................................iv PREFACE.......................................................................................................................................v TABLE OF CONTENTS ............................................................................................................. vi LIST OF TABLES ..................................................................................................................... viii LIST OF FIGURES ...................................................................................................................... ix LIST OF ABBREVIATIONS .......................................................................................................xi ACKNOWLEDGEMENTS .........................................................................................................xii DEDICATION ............................................................................................................................ xiii 1 INTRODUCTION ....................................................................................................................1 1.1 General ............................................................................................................................1 1.2 Arctic Climate Change ....................................................................................................2 1.3 Plant-environment relationships ......................................................................................3 1.4 Greening and Shrubification ...........................................................................................6 1.5 Dendrochronology ...........................................................................................................8 1.5.1 Shrub dendrochronology ............................................................................................10 1.5.2 Gaps in shrub dendrochronological/dendroecological knowledge ............................12 1.6 Experimental warming treatments in Arctic plant communities ...................................13 1.7 Summary .......................................................................................................................14 2 METHODS AND MATERIALS ...........................................................................................16 2.1 Study Site ......................................................................................................................16 2.2 Dryas integrifolia ...........................................................................................................18 2.3 Experimental Design .....................................................................................................20 2.4 Thin sections ..................................................................................................................22 2.5 Shrub Ring Analysis ......................................................................................................23 2.5.1 Chronology Building ..................................................................................................24 2.6 Data Analysis ................................................................................................................25 2.6.1 Linear Mixed Effects Models .....................................................................................26 2.6.2 Correlation analyses ...................................................................................................26 vii 3 RESULTS… ...........................................................................................................................28 3.1 Radial Growth Chronologies .........................................................................................28 3.2 Linear Mixed Effects Models: chronologies .................................................................30 3.3 Linear Mixed Effects Models: standardized raw ring widths .......................................32 3.4 Variance .........................................................................................................................34 3.5 Correlations with Environmental Variables ..................................................................36 3.6 Air temperature ..............................................................................................................37 3.7 Soil Moisture .................................................................................................................38 3.8 Correlations with climate station data ...........................................................................39 4 DISCUSSION ........................................................................................................................40 4.1 Dendrochronological potential of Dryas integrifolia ....................................................40 4.2 Effect of Treatment on Growth .....................................................................................41 4.3 Environmental Impacts on Growth ...............................................................................46 4.4 Future Work ..................................................................................................................49 5 CONCLUSIONS ....................................................................................................................53 REFERENCES.. ............................................................................................................................55 APPENDIX…… ............................................................................................................................64 viii LIST OF TABLES Table 1. The cover characteristics of the six major plant community types in the coastal valley at Alexandra Fiord (Muc et al., 1989). S-CP-DS: sedge-cushion-plant-dwarf-shrub, DS-CP: dwarf shrub cushion plant, L-CP-DS: lichen-cushion-plant-dwarf-shrub, HERB: herbaceous, DDS-G: deciduous-dwarf-shrub-graminoid, SM: salt marsh……………………………………………...17 Table 2. Soil and vegetation characteristics of the three experimental sites at Alexandra Fiord….18 Table 3. Descriptive statistics for each of the master ring width chronologies for Dryas integrifolia from warming experiments at Alexandra Fiord……………………………………………..……29 Table 4. Effect of experimental warming on ring-width growth in Dryas integrifolia in and across tundra plant communities at Alexandra Fiord. Results are from ANOVA of linear mixed models of standardized chronologies and raw ring width measurements…………………………………33 Table 5. Mean annual ring widths and coefficient of variance from site/treatment chronology for ring-width and raw ring widths………………………………………………………………...…35 Table 6. Previous shrub studies in the context of climate change……………………..………...44 Table S1. Pearson’s correlation of control plot RWI chronologies to camp Climate Tower environmental variable records; including: relative humidity; solar radiation; air temperature……………..……………..65 Table S2. Dryas subsite RWI model iterations and fit statistics…………………….……………………..65 Table S3. Meadow subsite RWI model iterations and fit statistics……….………………………………..65 ix LIST OF FIGURES Figure 1. Map of Alexandra Fiord field site, Ellesmere Island, NU……………………………...17 Figure 2. Global distribution of Dryas integrifolia (left) and Dryas octopetala (right) (from: Royal Botanical Gardens, https://powo.science.kew.org/taxon/urn:lsid:ipni.org:names:33769-1).........19 Figure 3. Cross section from Dryas integrifolia from Alexandra Fiord (left) and cross section of Salix glauca (right; Myers-Smith et al., 2015b) showing the oblong stem shape of D. integrifolia………………………………………………………………………………………..23 Figure 4. Standardized and detrended chronologies by site and treatment: A) Dryas control B) Dryas warmed C) Meadow control D) Meadow warmed E) Willow control F) Willow warmed. The grey line denotes the chronological signal of each year. The red line denotes the smoothing spline. The shaded grey denotes that sample depth of a particular year…………………………...28 Figure 5. Air temperatures in °C through time from within treatment plots (‘o’, orange dashed line) and control plots (‘c’, solid blue line)……………………………………………………….30 Figure 6. Boxplots of ring widths according to site and treatment: (A) Chronology ring width index; (B) Standardized raw ring widths; (C) Chronology ring width index across all sites; (D) Standardized raw ring widths across all sites. Treatments shown as control (blue, c) and warmed (orange, o). Box plots show the median and interquartile range (25-75%). Outliers are shown as individual points………………………………………………………………………………….34 Figure 7. Ring width chronologies through time by site and treatment; blue lines denote ring widths from control plots and dashed orange lines denote ring widths from experimental plots. A) Dryas subsite chronology files; B) Dryas subsite raw ring width files; C) Meadow subsite chronology files; D) Meadow subsite raw ring width files; E) Willow subsite chronology files; F) Willow subsite raw ring width files…………………………………………………………........35 Figure 8. Correlations between ring width indices from control plants at each site: A) Meadow vs Dryas; B) Willow vs Dryas; C) Meadow vs Willow. Red line depicts regression trend line and grey shading represents 95% confidence intervals……………………………………………….37 Figure 9. Ring width index against plot-level mean July air temperature (10 cm) within OTC and control plots. Shading represents 95% confidence intervals…………………………..…….........37 Figure 10. Ring width index against soil moisture (% volume) between warmed and control plots in A) all sites, B) Dryas subsite, C) Meadow subsite, D) Willow subsite. Shading represents 95% confidence intervals……………………………………………………………………………...39 Figure S1. Examples of varying ring width growth and length through time by treatment within two plots taken from the three subsites. A) Dryas plots 1 T and 1 C, B) Dryas plots 2 T and 2 C, (C) Meadow plots 1 T and 1 C, (D) Meadow plots 3 T and 3 C, (E) Willow plots 2 T and 2 C, and (F) Willow plots 4 T and 4 C………………………………………………………………………………………………...…………64 Figure S2. Regressions of Standardized raw ring widths against plot-level mean July air temperature (10 cm) within OTC and control plots. Shading represents 95% confidence intervals………………...……….66 x Figure S3. Regressions of Standardized raw ring widths against soil moisture (% volume) between warmed and control plots in A) all sites, B) Dryas subsite, C) Meadow subsite, D) Willow subsite. Shading represents 95% confidence intervals…………………………………………………………...…………..67 Figure S4. Interaction plots between air temperature and ring width index according to treatment from the Dryas site (left) and the Meadow site (right). Ring widths from treatment chronologies are shown as treat ‘o’ and are purple, ring widths from control chronologies are shown as treat ‘c’ and are blue……………………….…………………………………………………………..68 xi LIST OF ABBREVIATIONS ITEX International Tundra Experiment OTC Open-top Chamber RRW Raw Ring Width RWI Ring Width Index xii ACKNOWLEDGEMENTS Of the past four years completing this thesis, writing these acknowledgements may just be the toughest part yet. It hasn’t exactly been the Master’s program I had imagined before moving to B.C. – I think most people have similar thoughts when remembering the past few years as a global pandemic swept through the world. Nevertheless, I actually managed to make it to this stage; the part where I get to acknowledge all those who helped get me here. Firstly, I’d like to thank the University of British Columbia for opening its doors to this Ontario girl who just thought the Arctic was so neat. I’m proud to say I’m graduating from this school, and from the great Geography Department we have here. Next in line is Dr. Greg Henry (aka Fiord Lord). Thanks to you, I was able to get boots on the ground in the North again – a very special place for boots to be. Thank you for the endless support, laughs, baked oatmeal, and most of all, belief that I could do this project despite all the hurdles and hiccups along the way. I can’t wait to see that magical things you help others unlock at Alexandra Fiord. I’d also like to thank Dr. Shelly Rayback and Dr. Lori Daniels who agreed to be on my committee. You both provided support, energy and insight into my project. I was incredibly grateful to have the opportunity to ‘pick the brains’ of both these excellent researchers. Along this vine, thank you to Elise Gallois for sharing your resources with me, and taking the time out of a schedule I imagine was even busier than my own, to help me understand the way to read shrub-code. Thank you as well to all members of the Tundra Lab, who listened to my research updates, helped me with lab work, offered advice and guidance and were lovely humans to see each week. I am also appreciative of the financial support that I received from the UBC Geography Department, the Weston Family Foundation, NSTP, and NSERC; all of whom made working on research a little less stressful. Thank you as well to PCSP and NSERC for supporting the work done by the Tundra Ecology lab. The last but most certainly not least of the thank-yous go to my friends and family. I could not imagine a better support system throughout these past years. A huge shout-out to the moths – the best friends a girl could have – and to the fourth floor of the library. Thank you to my sister, Natalie, who sat with me through the ups and downs (and side to sides) of this thesis and offered unending support and brain power; I could not have done this without you all. xiii DEDICATION This thesis is dedicated to my sister, who thankfully did her Master’s before I began mine. 1 1 INTRODUCTION 1.1 General Tundra ecosystems have been impacted by the rapidly changing climate, especially in the Arctic. Measured responses include phenological shifts in the seasonal timing of life history events, and community wide responses such as changes to biodiversity, carbon storage, and nutrient cycling (Walsh et al. 2020, Mekonnen et al. 2021, Moon et al. 2021, Previdi et al. 2021). Research in tundra ecosystems has grown over the last few decades to help understand how projected and continued climate change is impacting and will impact northern environments. At local scales, researches have found varying ecosystem responses to environmental variables across Arctic landscapes (Elmendorf et al., 2012a; Myers-Smith et al., 2015a; Ackerman et al., 2017). However, the remote nature of northern work often means that research is site-specific with large areas that are poorly studied and climatic records are temporally limited. As a result, there are often geographical and temporal gaps in environmental and ecological data. There are few long-term records of ecological responses to climate and other drivers; using natural archives of responses in long-lived plants can help provide context for the current changes and responses seen in Arctic ecosystems. It is important to bridge the data gaps of Arctic ecosystems to better link environmental patterns occurring between northern and southern latitudes, to establish benchmarks against which current and future change may be compared, and to quantify variability within a system. Proxy data can help provide historical contexts for environmental change. Dendrochronology, the study of the radial growth of woody plants, is a form of proxy research. The methods are used to investigate growth patterns of woody plants through time, and how they respond to environmental drivers at local and regional scales (Fritts, 1976). 2 Dendrochronology has traditionally been used to study the radial growth of tree species, but has increasingly been applied to shrub species including Arctic shrubs. These methods have revealed various relationships with environmental variables and arctic shrub species such as: correlation of shrub presence to air temperatures; ring width size and stem growth correlations to snow depth, air temperature and soil moisture (Walker et al., 1997; Rayback et al., 2007; Au & Tardif, 2007; Elmendorf et al., 2012a; Myers-Smith et al., 2011; Myers-Smith et al., 2015a; Ackerman et al., 2017; Ackerman et al., 2018). The Arctic shrub species commonly used in dendrochronological studies have included: Cassiope tetragona, Salix spp. and Betula spp. However, not all shrub species are circumpolar, and including more shrub species in dendrochronological research could provide a more holistic sense of responses of tundra plant communities to environmental change over time. Growth patterns of one of the more wide-spread shrub species in the Arctic, Dryas integrifolia, has not been extensively studied. In this thesis, we apply dendrochronological techniques to investigate the growth of Dryas integrifolia in response to experimental and ambient warming from multiple subsites at a High Arctic field site, Alexandra Fiord, NU. 1.2 Arctic Climate Change The Arctic is warming at as much as four times the rate of the global average (Rantanen et al., 2022; IPCC, 2013). The acceleration of Arctic climate change is largely attributed to a phenomenon known as polar amplification (Previdi et al., 2021). The impacts of the rapidly changing climate can be seen in the responses of all Arctic environments, including reductions in sea ice thickness, extent and duration, the timing and duration of snow cover, permafrost thaw, increased drought or increased precipitation, increased emissions of carbon dioxide and methane, and greater shrub cover (Serreze & Hurst, 2000; Chapin et al., 2005; Elmendorf et al. 2012a; 3 Elmendorf et al., 2012b; Beamish et al., 2016). The Arctic response associated with polar amplification, in turn, affects how Arctic systems influence global climate systems (Serreze et al., 2000; Chapin et al., 2005; Beamish et al., 2016). Perhaps the most prominent of these climate change effects, and a major process in polar amplification, is changes to the cryosphere. Sea ice and glaciers are melting at increasing rates, (Carr et al., 2017; Rink et al., 2019) and terrestrial snow cover is decreasing in extent and duration (Sturm et al., 2001). Decreasing snow and ice reduces surface albedo – the reflective capacity of a surface to solar radiation. Surfaces with lower albedo absorb greater amounts of solar radiation; thus, they warm and retain heat which then heats the atmosphere. The reduction of ice and snow in the Arctic reduces albedo and results in a positive feedback loop of increased temperatures leading to exacerbation of warming effects on the environment (Berner et al., 2020; Previdi et al., 2021). Warmer temperatures and the reduction of snow and ice affect tundra plants directly, through increased growth, and indirectly, through changes in nutrient cycling and soil moisture, and also ameliorate habitat conditions to increase opportunities for plant establishment (Molau, 1997; Welker et al., 1997; Bjorkman et al., 2019; Hollister et al. 2023). 1.3 Plant-environment relationships Arctic environments are often limited by low temperatures, extremes in soil moisture content, and low nutrient availability, which are three major environmental controls on plant growth, along with biotic interactions such as competition and herbivory (e.g., Post & Pedersen 2008; Forbes et al., 2010; Macias-Fauria et al., 2012; Tape et al., 2012). Warmer climates in the North have been identified as large drivers of change in plant community dynamics, as temperature limitations on growth are alleviated. Passive warming experiments using open-top plant growth chambers have shown that an increase in the number of snow-free days in the summer can increase 4 the growth potential of Arctic plants by extending the length of the growing season (Molau, 1997; Welker et al., 1997; Bjorkman et al., 2019; Hollister et al. 2023). Further, these studies have shown earlier onset of green-up and flowering dates, increased seed viability, increased plant heights, and altered plant abundance related to higher temperatures (Hudson & Henry, 2010; Klady et al., 2011; Elmendorf et al., 2012b; Panchen & Gorelick, 2015; Bjorkman et al. 2018; Prèvey et al. 2019; Agger & Henry, 2022). However, the effects of warmer temperatures are ultimately determined by local habitat conditions and plant community composition (Elmendorf et al., 2012b). A large portion of the Arctic is classified as polar desert and receives low annual precipitation, usually less than 200 mm (Bliss and Matveyeva 1992; Walker et al. 2005). Mineral soils of polar deserts usually have course texture and drain readily, so soil moisture capacity is low, despite the lack of full vertical drainage imposed by permafrost (Walvoord & Kurylyk, 2016; Jafarov et al., 2018). Non-vascular plants lack the advantage of large rooting systems of vascular plants, and are reliant on surface water content to supply their moisture needs. Increased temperatures can lead to increased rates of surface evaporation, drying out habitats and reducing survivorship for non-vascular plants (Oechel & Sveinbjörnsson, 1978; Tenhunen et al., 1992). Conversely, increased atmospheric temperatures have increased moisture carrying capacity and resulted in greater cloud cover and amounts of precipitation at region scales across the Arctic (IPCC, 2013; McCrystall et al., 2021). Some regions where increased annual precipitation has been observed have also seen increased vegetation cover and rates of evapotranspiration (Zhang et al., 2018). A synthesis of experimental warming studies found that plant type and abundance was often linked to local site conditions, such as ambient temperature, soil moisture, and duration of experimentally applied heat. For instance, although increased temperatures generally saw an 5 increase in shrub abundance for sites that were already warm, evergreen shrubs were specifically correlated with site moisture levels (Elmendorf et al., 2012b). These results highlighted the importance of local site conditions to plant responses to warming. Plant sensitivity to local conditions can make predicting how plant species and communities will respond to continued climate change difficult. The location and composition of vegetation communities across the circumpolar arctic are shifting in response to environmental change. One trend across arctic landscapes is a general increase in shrubs. Deciduous shrubs are expected to have a competitive edge over other plant types, due to traits such as tall branches for better access to light, while shading neighbours, and large rooting systems to better access soil moisture and nutrients (Shaver & Chapin, 1980; Mack et al., 2004; Mekonnen et al., 2021). Deciduous shrubs were expected to initially increase relative to evergreen shrubs due to their greater growth rates which allow them to increase in size more quickly; however, evergreen shrub abundance has been found to increase at the same rate as deciduous shrubs (Hudson & Henry, 2011; Myers-Smith et al., 2011a; Elmendorf et al., 2012a, b; García Criado et al., 2020). By comparison, bryophytes, mosses and lichens have generally decreased in abundance with increased temperatures, especially in warmer regions, likely due to a shading effect of taller vascular plants (Lang et al., 2011; Elmendorf et al., 2012b). However, in the High Arctic, bryophytes have been found to increase in abundance in response to experimental warming (Hudson & Henry 2010). As the local environment influences plant community dynamics, a shift in plant composition and abundance on the landscape also influences the local environment. For instance, increased plant height and cover decreases surface albedo and increases local surface temperatures (Chapin et al., 2005). This is particularly true for shrubs, which are the largest plant growth form 6 beyond treeline in the Arctic and are effective at absorbing incoming solar radiation with large, dark foliage. While surface temperatures may increase, larger canopies shade the soil beneath the plants, and can decrease summer soil temperatures and slow rates of nutrient turnover by soil microbes (Chapin et al., 1983; Ackerman, 2018). Winter soil temperatures, however, may increase through snow-shrub feedbacks. Snow can become trapped in the branches of erect shrubs as it travels by wind across the landscape, which increases local snow depth around the shrub and insulates soils (Sturm et al., 2001; Sturm et al., 2005; Myers-Smith et al., 2011). Plant composition also influences local soil nutrient stores. Deciduous shrubs produce more nutrient-rich leaf litter at greater rates than evergreen shrubs, and influence local nutrient supplies (Arft et al., 1999; Mack et al., 2004; Chapin et al., 2005; Sturm et al., 2005a). As plant-environment relationships shift with climate change, understanding how the larger and potentially more influential plants, such as shrubs, respond will be useful in understanding potential changes to tundra systems. Although plant community dynamics are highly variable across the Arctic, it is predicted that shrubs will generally increase in abundance and non-vascular plants will decrease with continued warming in the tundra (Lang et al., 2011; Elmendorf et al., 2012b). 1.4 Greening and Shrubification The phenomenon known as Arctic ‘greening’ is the increase in vegetation density, cover and height observed in the tundra, which is largely driven by increased temperatures (Forbes et al., 2010; Elmendorf et al., 2012; Edwards & Treitz, 2017; Berner et al., 2020; Myers-Smith et al., 2020; Piao et al., 2020; Berner et al., 2020). Various studies found woody shrubs to be strong contributors to Arctic greening trends, as they are the largest plant-type north of treeline (Elmendorf et al., 2012a; Bjorkman et al., 2018). Shrubification refers to increasing shrub presence on the tundra. Warmer Arctic temperatures have improved growing conditions and allowed shrubs 7 to increase their growth rates, reproductive success, and biomass (Elmendorf et al., 2012a). Shrub abundance on the tundra is largely influenced by temperature, snow cover, permafrost dynamics, soil moisture and nutrients, tundra fires, herbivory, as well as anthropogenic activity (Myers-Smith et al., 2011). Shrubs impact various aspects of local ecosystems, such as plant community composition, soil nutrient cycling, carbon storage and energy exchange (Eugster et al., 2000; Sturm et al., 2001; Liston et al., 2002; Chapin et al., 2005; Sturm, 2005; Wookey et al., 2009; Blok et al., 2010). There are three main mechanisms of shrubification: increased growth potential; infilling; and advancing shrub-line (Myers-Smith et al., 2011). Increased growth potential may include a change of growth form, such as increasing canopy height and branch cover. Infilling occurs when shrub patches become denser by lateral expansion of existing shrubs, and the establishment of new individuals. Advancing shrub-line refers to the expansion of existing shrub ranges beyond historical boundaries, both in latitude into the Arctic and in elevation on alpine slopes (Myers-Smith et al., 2011). Range expansion occurs both from appropriate microhabitat conditions on the landscape, as well as increased reproductive success and establishment (Myers-Smith et al., 2011). Shrubification is not uniform across the Arctic, and the mechanisms, drivers, and effects of shrub increases are heterogenous. However, there is general consensus and extensive evidence of general shrub increases on tundra landscapes (Chapin et al., 1995; Tape et al., 2006; Forbes et al., 2010; Tremblay et al., 2012; Miller & Smith, 2012; Zhang et al., 2013). The direction of Arctic vegetation change is non-uniform and depends on geographical location and local conditions such as weather patterns, fire frequency, surface moisture levels, and plant community composition (Sturm et al., 2001; Blok et al., 2010; Scheffer et al., 2012; Bret-Harte et al., 2013; Nauta et al., 2015; Li et al., 2021). In Subarctic regions, tall deciduous shrubs are the largest contributors to shrubification, 8 whereas in the High Arctic it is dwarf deciduous shrubs (Silapaswan et al. 2001; Tape et al. 2006; Forbes et al. 2010; Elmendorf et al. 2012a). Some research speculates that the most dramatic shrub increases will take place at the upper end of species’ ranges, either at the boundaries of the Subarctic or the High Arctic (Myers-Smith et al., 2015a). A synthesis by Arft et al. (1999) predicted that Subarctic regions will experience the greatest shrub increase due to the height advantage of tall deciduous shrubs, which are able to access more sunlight and shade neighbouring plants. Although the High Arctic regions host dwarf shrub species, range expansion of tall deciduous shrubs with continued warming may see dwarf species outcompeted in the future (Henry & Molau, 1997; Arft et al., 1999). At High Arctic sites, evergreen dwarf shrubs demonstrated greater warming-resistance compared to deciduous shrubs, which responded more readily to temperature increases (Chapin et al., 1996; Henry & Molau, 1997; Hudson & Henry, 2010). Evergreen shrubs are more conservative, slow growing, and often found in nutrient poor soils compared to deciduous shrubs, which have higher growth rates, leaf turnover, nutrient requirements, and photosynthetic rates, and more often grow in nutrient rich soils (Chapin et al., 1996). Therefore, tall deciduous shrubs are predicted to be the largest contributors to tundra shrubification, and evergreen dwarf species may initially decline in abundance with warming Arctic temperatures (Elmendorf et al., 2012b). As the largest form of vegetation beyond treeline, understanding how shrub growth responds to temperature increases would provide useful insights into vegetation-climate relationships and ecosystem processes. 1.5 Dendrochronology Dendrochronology is the study of woody plant annual growth through time. Woody plants in seasonal climates experience distinct productive and unproductive states each year. The productive state is when the plant is actively growing and accumulating cells during the growing 9 season, which generally occurs between May and September in temperate and polar latitudes in the northern hemisphere; the unproductive state is the remainder of the year when the plant is not actively growing, or is dormant (Schweingruber, 1989; Schweingruber et al., 2006). Woody plants accumulate cells in one of the outermost layers of the stem known as the cambium which is known as secondary growth (Schweingruber, 2007). Variation in wood cells formed throughout the growing season and cessation of secondary growth results in annual growth rings. Early in the growing season, the relatively large cells that form have thin walls and appear light in colour, and are typically known as earlywood. Darker-coloured cells result through increasing cell wall thickness and decreasing cell size, marking the end of the growing season, and are known as latewood (Schweingruber et al., 2006). Investigating the annual growth patterns of a woody species and the temporally-associated climate variables characteristic of its environment facilitates the understanding of how climate influences plant growth over long periods of time. Groups or stands of trees, especially of the same species, growing in spatial proximity will generally have similar annual radial growth patterns, if each tree is responding to similar environmental signals and barring effects from inter-tree competition. A common growth pattern averaged across multiple individuals within a stand can be used to generate a master chronology for the site. A detrended chronology is an averaged record of annual growth from a collection of trees (usually of the same species) growing in the same area, with individual growth bias removed (Cook & Kairiukstis, 1990). Master chronologies are useful for accurately cross-dating new trees sampled within an area with a reliable growth record, meaning existing master chronologies may be used to crossdate samples from new trees. Long temporal and spatial records have been developed using multiple tree-ring master chronologies to reconstruct past environmental conditions; from temperature and drought to extreme events such as landslides, fires and insect 10 infestations (Schweingruber, 2007). Historically, dendrochronological studies have been based on the growth rings of trees; however, researchers have been able to apply the same methods to woody shrubs. 1.5.1 Shrub dendrochronology Multiple studies have verified the use of dendrochronology on woody shrub species to investigate past local and regional environmental conditions (i.e., dendroecology) (Rayback & Henry, 2007; Au and Tardif, 2007; Forbes et al., 2010; Myers-Smith et al., 2011; Myers-Smith et al., 2015b; Ropar et al., 2017; Ackerman et al., 2018; Buchwal et al., 2019; Le Moullec et al., 2019; Fontana et al., 2021;). Shrub dendrochronology possesses several advantages for Arctic environmental research – principally its ability to expand the spatial extent where dendrochronological techniques can be applied. Multiple shrub species grow in high latitudes or high alpine environments, vegetation communities beyond the distributional limit of upright trees. The application of dendrochronology on shrubs has allowed the reconstruction of past environments at an annual scale in the tundra ecosystems that previously were outside the geographical scope of the technique. However, the application of dendrochronology to shrubs is not without challenges. Arctic shrubs are small and multi-stemmed, which requires alternative measuring techniques as opposed to traditional tree boring or cutting stem cross-sections. Myers-Smith et al. (2015b) identified three main methods of shrub dendrochronology: 1) stem increments (interior); 2) stem increments (bud scars); and 3) annual growth rings. Stem increments reveal how much a plant has grown in length in a given season through measured distances between 'winter marks' and 'bud scars' which are interior and exterior indicators of growth, respectively, and have been successfully used to create growth chronologies in an Arctic dwarf shrub, Cassiope tetragona (Johnstone & Henry, 1997; Rayback & Henry, 2007; etc.). Rayback and Henry (2007) used bud 11 scars of Cassiope tetragona shrubs from a High Arctic site to generate chronologies ranging from 80-118 years long, and were able to reconstruct a 100-year long July-September temperature record. These records were able to show temperature trends through time, and were comparable to other climate proxies from the same site and region. Rozema et al. (2009) measured various annual growth parameters of High Arctic C. tetragona on Svalbard as a proxy for Arctic summer temperatures, including leaf production, sum of length and weight of individual leaves, stem length increments from leaf scar distances, and distances between wintermarksepta in the stem. Using passive experimental warming, they found that the variation of annual growth was correlated to summer temperatures. More traditional dendrochronological techniques involving the measurement of radial growth can be applied to some shrub species. The cross section of a shrub stem may be analyzed to determine growth patterns over time. The root collar is the transition zone from the roots to the shoots and is the oldest part of the shrub. Portions above or below the collar therefore contain younger plant material, and as such, would contain fewer annual growth rings compared to the collar itself (Myers-Smith et al. 2015b). Studies show that root and shoot growth can be separate, and seemingly disconnected (Ropars et al., 2017). Some evidence suggests that root growth of shrubs is more sensitive to climate than stems, and that climate sensitivity is not consistent throughout the plant (Ropars et al., 2017). The sensitivity of roots to climate variation, paired with the root collar containing the longest record of growth within a plant, makes the root collar the ideal location for shrub dendrochronological investigation. The growth responses of shrubs to environmental conditions can be species and site specific. Lantz et al. (2010) used radial ring widths to determine that green alder (Alnus viridis subsp. fruticosa) growth rates were greater at a more recently burned site in the Mackenzie Delta 12 area than a site that had not been previously burned, highlighting green alder growth patterns and preferences on tundra landscapes. Hollesen et al. (2015) discovered that Betula nana radial growth in western Greenland is linked to warmer winter and spring air temperatures, highlighting the significance of winter warming on plant-climate interactions. Another study involving Betula spp. in western Greenland showed that temperatures and spring time precipitation were drivers of growth (Young et al., 2016). Au and Tardif (2007) were the first to successfully cross date annual growth rings of the wide-spread, dwarf evergreen shrub Dryas integrifolia, and determined that climate signals from the constructed chronology were similar to nearby tree species. They found that secondary growth of D. integrifolia was impacted by October snow fall levels of the previous year and May temperatures of the present year, demonstrating climatic relationships with local conditions. 1.5.2 Gaps in shrub dendrochronological/dendroecological knowledge Recent research indicates that variability in shrub environment-growth relationships across tundra landscapes may depends on species and site conditions. While some research has shown that annual ring growth of some Arctic shrubs positively correlates with above-ground biomass and can be used to reflect past plant production (Le Moullec et al., 2019), other evidence shows that sensitivity to growth in one part of the plant does not reflect growth in all parts (Ropars et al., 2017). As well, there are studies which demonstrate both positive and negative relationships between shrub growth and the same environmental variable, such as summer temperature, at different sites in the Arctic (Hallinger et al., 2010; Rayback et al. 2012; Myers-Smith et al., 2015). There are also contrasting results in Arctic studies with some suggesting variables such as air temperature are the dominant driver of annual growth, whereas other studies conclude that soil moisture is potentially equally significant (Myers-Smith et al. 2015). Hence, most shrub 13 dendrochronological studies have found that shrub-environment relationships are species and site-specific. 1.6 Experimental warming treatments in Arctic plant communities To test the effects of potential climate change on plant species, populations and communities, long-term field experiments have been used. The International Tundra Experiment (ITEX) is a network of researchers conducting similar studies at field sites across the Arctic and in alpine regions, where many sites have long-term passive on-going warming experiments. ITEX was created in 1990 with the objective of providing a platform for standardized measurements of the effects of climate warming on tundra plant species and communities (Henry & Molau, 1997; Henry et al. 2022). The experimental design involves the use of open-top chambers (OTCs) measuring between 0.75 and 1.8 m2. The OTCs are usually made of clear polycarbonate panels, usually inclined at ca. 60 degrees which decrease the wind speed and allow the interior temperature to increase by 1-3⁰ C; essentially simulating projected global warming trends (Marion et al., 1997; Hollister et al. 2023). This design attempts to isolate the direct effects of temperature on the plants within, and minimize effects on other environmental variables such as precipitation, gas exchange or pollination (Jones et al., 1997; Robinson & Henry, 2019). Over twenty years of experimental warming have shown changes to plant phenology, reproduction, growth and community composition (Henry et al. 2022). Results from experimental warming studies using OTCs often depend on region and habitat. For example, a synthesis of ITEX studies showed that after 10 years of experimental warming treatments in the low Arctic, vascular plants grew significantly taller, lichen and moss decreased in abundance, and deciduous shrub cover and graminoids increased (Walker et al., 2006). Some of these results were found after only two growing seasons demonstrating the 14 sensitivity of Arctic plant species to change. This synthesis also found that across ITEX sites, deciduous shrubs were more sensitive to temperature than evergreen shrubs. Hudson and Henry (2011) also found that an evergreen shrub species at Alexandra Fiord in the Canadian High Arctic had no significant response to warming and suggested evergreen species are more stress tolerant, slow growing and conservative, and that these species would therefore be less likely to respond to warming. Contrastingly, a more recent synthesis of ITEX studies by Elmendorf et al. (2012b) determined that evergreen shrub responses to environmental change were as strong as those in deciduous shrubs; however, they did not respond to summer temperatures as strongly as deciduous shrubs. An ITEX synthesis of phenophases in warming experiments found larger effects of experimental warming on reproductive versus vegetative phenophases, as well earlier reproductive phenophases and green up but delayed leaf senescence. The overall effect lengthened the growing season by about 3% (Collins et al., 2021). Similar results have also been found in gradient studies in the High Arctic (Panchen & Gorelick, 2015). The heterogeneity of warming responses by Arctic plants highlights the importance of understanding plant-environment relationships to predict how responses of plant species and communities will shift with continued climate change. 1.7 Summary Understanding how climate warming may influence shrub growth has important implications for how Arctic ecosystems may be impacted by continued warming. To date, few dendrochronological studies have been done in High Arctic regions, and none have been conducted on the abundant High Arctic evergreen shrub, Dryas integrifolia. Applying these techniques to experimentally and ambiently warmed D. integrifolia will provide insight as to how future temperature increases will affect this important tundra plant species. The objective of my research 15 is to use dendrochronological techniques to determine the effects of ambient and experimental climate change at local and regional scales for Dryas integrifolia, and to determine which environmental variables are driving radial growth. This leads to my research questions and hypotheses: • What are the effects of experimental and ambient warming on the radial growth of the common High Arctic shrub, Dryas integrifolia? Hypothesis 1: Due to the growth sensitivity of High Arctic plants to climate, we expect increased growth radial growth of Dryas integrifolia in warmed plots relative to those in control plots. We also expect that with increasing ambient temperatures over the past decades, radial growth will have increased through time. • How well does the growth of Dryas integrifolia reflect local climate? Hypothesis 2: As High Arctic plant growth is typically either temperature and/or moisture limited, we may expect there to be relationships between radial growth of Dryas integrifolia and both temperature and moisture records. 16 2 METHODS AND MATERIALS 2.1 Study Site Alexandra Fiord is a coastal valley on the east coast of Ellesmere Island, NU, Canada (78°53’ N, 75°55’ W). The site is bordered in the north by a fiord, mountains (500-700 m) on two sides, and the Twin Glacier at the southern end of the valley, creating a sheltered polar oasis with enhanced environmental conditions for plant growth relative to the surrounding polar desert (Freedman et al., 1994). Cluster analysis of plant cover data at Alexandra Fiord divided the lowland into six vascular plant community types based on dominant plant types found throughout the area. These plant communities were identified as: sedge-cushion plant – dwarf shrub (S-CP-DS); dwarf shrub – cushion plant (DS-CP); lichen – cushion plant – dwarf shrub (L-CP-DS); herb – dominated (HERB); deciduous dwarf shrub – graminoid (DDS-G); salt marsh (SM) (Muc et al., 1989; Table 1). The soils of the lowland are generally coarse and immature with variable amounts of organic matter and limited vertical drainage and the terrain is mainly comprised of hummocks (Muc, Svoboda & Freedman, 1994). Soil moisture in the lowland is largely what influences the distribution of plant-types, which is variably impacted by snow distribution and melt, glacial run-off, and drainage from rivers and streams (Muc et al., 1989, 1994; Svoboda & Freedman, 1994; Klady et al., 2011). The soils at the site are shallow and young, but comparatively high in organic matter for typical areas of the High Arctic (Muc et al., 1994; Rolph 2003; Beamish, 2013). Despite low levels of annual precipitation, the lack of vertical drainage due to permafrost, the generally flat terrain and low rate of evapotranspiration allows the soils of the lowland to remain moist throughout the growing season (Muc et al., 1994; Labine, 1994; Hudson & Henry, 2010). 17 Figure 1. Location of Alexandra Fiord, Ellesmere Island, NU (from Trefey et al., 2010). Table 1. The cover characteristics of the six major plant community types in the coastal valley at Alexandra Fiord (from Muc et al., 1989): S-CP-DS - sedge-cushion-plant-dwarf-shrub, DS-CP- dwarf shrub cushion plant, L-CP-DS- lichen-cushion-plant-dwarf-shrub, HERB: herbaceous, DDS-G: deciduous-dwarf-shrub-graminoid, SM- salt marsh. S-CP-DS DS-CP L-CP-DS HERB DDS-G SM % of land area 28.4 18.7 37 5.3 3.8 0.1 % plant cover 109 108 73 13 89 16 % lichen cover 12 31 41 1 23 0 18 Table 2. Soil and vegetation characteristics of the three experimental sites at Alexandra Fiord. Site Name Soil Moisture Vegetation Classification* Dominant Plant Species Dryas Mesic Prostrate dwarf-shrub herb tundra DS-CP** Dryas integrifolia, Arctagrostis latifolia Willow Dry-Mesic Prostrate dwarf-shrub herb tundra DDS-G Salix arctica, Dryas integrifolia, Cassiope tetragona Meadow Hydric Hydric sedge, moss, dwarf-shrub wetland S-CP-DS Eriophorum angustifolium, Carex aquatilis stans. Carex membranacea, Dryas integrifolia *Circumpolar Arctic Vegetation Map, Walker et al. (2005). ** Muc et al. (1989) – see Table 1. 2.2 Dryas integrifolia Dryas integrifolia Vahl, a species in the Rosaceae family, also referred to as large-leaf mountain avens or malikkaat, is a mat-forming, prostrate shrub found in Arctic regions of North America (Porsild & Cody 1980; Aiken et al., 2007). D. integrifolia is the dominant species of Dryas in North America, however, D. octopetala is the dominant species in Europe, and they are similar in appearance and ecological relationships (Figure 2). D. integrifolia occurs mainly on 19 gravelly, frost-heaved soils and is one of the most common and widespread flowering plants in the North American Arctic. On the east and west coasts of Greenland, D. integrifolia occurs largely in wet meadows, substrate depressions, tundra slopes, and river terraces in preferably moderately well-drained areas (Porsild & Cody, 1980; Aiken et al., 2003). Dryas produces bisexual white flowers with typically 8 but up to 11 petals and deep nectaries, which serve as a food source for some herbivores, including flies, insect caterpillars, Arctic hare, caribou and muskox (Aiken et al., 2007). D. integrifolia has been shown to require insect pollination for full seed set (Robinson & Henry, 2019). Flowering of D. integrifolia typically occurs in late June-early July and seed dispersal in early August. There is evidence suggesting the reproductive effort of D. integrifolia is partially driven by climate patterns. A particularly cold growing season in 2018 at a High Arctic field site at Alexandra Fiord resulted in near complete reproductive failure of D. integrifolia growing under ambient conditions, with only slightly better success of plants grown in experimentally warmed plots (Panchen et al., 2021). The stems and branches of D. integrifolia have irregular annual growth with a semi-porous ring structure (Schweingruber et al., 2011). Figure 2. Global distribution of Dryas integrifolia (left) and Dryas octopetala (right) (from: Royal Botanical Gardens, https://powo.science.kew.org/taxon/urn:lsid:ipni.org:names:33769-1). 20 2.3 Experimental Design Alexandra Fiord was the first established field site of the International Tundra Experiment (ITEX), a grassroots collection of scientists conducting similar field experiments throughout global Arctic and alpine environments (Henry et al. 2022). In 1992, warming experiments were established in five major plant communities. Three of the experimental subsites (Willow, Dryas, and Meadow) were investigated for this study (Table 2). The Willow subsite has the lowest soil moisture with sandy, dry-mesic soils and is a dwarf-shrub herb tundra, dominated by Salix arctica. The Dryas subsite has mesic soils (Muc et al. 1994), with abundant soil moisture in the year of collection (2021) compared to previous summers, and had flooded twice within the dendrochronological record used here. The dominant species was Dryas integrifolia, although Cassiope tetragona was prominent as well. The Meadow subsite is the wettest among the Alexandra Fiord sites, and supports mainly sedges and mosses with few shrub species (Henry et al., 1990). Climate at the site has been warming by as much as 1ºC per decade (Hill & Henry, 2011). At Alexandra Fiord, plots were chosen to centre on a randomly chosen dominant plant species, and half of the plots were randomly assigned a warming treatment. Plots were warmed by open-top chambers (OTCs) that increase near-surface air temperatures by 1-3 °C compared to control plots (Marion et al., 1997; Bokhorst et al., 2013: Hollister et al., 2023). The OTCs at Alexandra Fiord are constructed with six clear polycarbonate panels sinched together at the edges and lean inward at an angle of 60° (Jones 1996). They enclosed an area of 1.8 m2 with a permanently marked 1 m2 area in the centre. The OTC design was intended to provide a warming effect while minimizing effects on other variables, such as allowing for rain/snowfall, pollinator interaction, and gas exchange. (Henry & Molau, 1997; Hollister et al., 2023). 21 I used air temperature and soil moisture data recorded between 2000-2019. Plot-level temperature measurements represented sites and treatments, as loggers were placed in only select plots within sites. Near-surface air temperature through the growing season was recorded using HOBO loggers (Hobo Pro and Pendant, Onset Computer Corp., Pocaset MA) at 10 cm above the ground. Thermocouples also recorded air temperature at the Willow subsite, and supplemented the temperature data between 2000-2008 at this site before HOBO loggers were installed. For Meadow and Dryas subsites, HOBO data were missing between 2004-2007. Soil moisture was recorded with Hydrosense II soil-water sensors (Campbell Scientific INC., Edmonton, Canada), which were placed 12 cm into the upper soil layer in the north, center and south of each plot, and then averaged per plot. Each of the three subsites (Dryas, Meadow, Willow) contained ten warmed and ten control plots. In August of 2021, a Dryas integrifolia plant was harvested from each plot within these sites, for a total of 30 plants from each treatment across all sites. Plants taken from OTC plots were taken outside of the 1 m2 permanent plot in the centre to limit plot damage. Plants from control plots were taken either from within the plots outside of the 1 m2 marked plot, or close to plot edges for the same reason. Where an abundance of shrubs was available, individuals with the healthiest appearance (i.e., large, leafy, flowers/seed heads) were selected, as it was believed these individuals would provide longer dendrochronological records. Selected shrubs were harvested so that the root collar and several centimetres of root were intact. This allowed for clearer identification of the root collar for thin-sectioning. Each sample was labeled according to site and plot number. Samples were then air-dried before being packed in paper bags for transport to the lab at UBC. 22 2.4 Thin sections To prepare samples for thin sectioning, air dried stems were placed in water for approximately 12 hours to make stems more pliable, and limit potential damage by the microtome blade. For each sample, eight thin-sections measuring 5-6 µm thick were collected using a sliding microtome (GSL1 sliding microtome, Swiss Federal Institute for Forest, Snow and Landscape Research WSL). The area of interest along the stem was the root collar, or root crown, which is the junction between stems and roots, and is the oldest part of the plant (Myers-Smith et al., 2015b). The true root collar is difficult to externally determine, so a best estimate of its location was used. If the region determined to be the collar was damaged or unusable, a section was collected from slightly further (i.e. within millimeters) along the main stem above the collar. Multiple thin-sections are required for within-sample cross-dating to ensure samples are dated as accurately as possible (Myers-Smith et al., 2015b, Kolishchuk, 1990). If thin-sections appeared warped or unclear, the sample was sectioned from a different point along the stem until clear cross-sections were obtained. Thin-sections were stained with Safranin-O 1% aqueous solution to visually enhance ring contrast for counting and measuring. Sections were first submerged in the staining solution for 15 minutes, followed by 5 minutes in a 50% alcohol bath and 10-15 minutes in a 100% alcohol bath to rinse excess stain from the sample. The 100% alcohol bath ranged 10-15 minutes depending on the clarity of the thin-sections after 10 minutes; if ring boundaries remained unclear, the sections would return to the bath for an additional 5 minutes. A small amount of glycerine was added to the alcohol baths to prevent the thin-sections from becoming dehydrated, and a small paintbrush was used to transfer sections between baths. The end result was a pink/red thin section with clear, 23 dark red ring boundaries (Figure 2). After staining, samples were photographed under a dissecting scope with an iPhone XR camera to provide images for ring analysis. 2.5 Shrub Ring Analysis Typical practice in crossdating shrub species uses ring counts from different points around the pith of the cross section (Myers-Smith et al., 2015b), however, the stem growth of Dryas integrifolia is typically oblong and prevents ring counts from many angles around the pith (Figure 3). To accommodate this growth pattern, rings were counted from the point where the distance from the outer bark to the pith was the greatest, ensuring the maximum number of easily discernable rings. Crossdating within an individual involved comparing two separate cross-sections from the same stem of an individual to ensure the ring widths were accurately measured. A similar method was used by Fontana et al. (2021), who employed this style of cross-dating with Dryas octopetala. Figure 3. Cross section from Dryas integrifolia from Alexandra Fiord (left) and cross section of Salix glauca (right; Myers-Smith et al., 2015b) showing the oblong stem shape of D. integrifolia. The dendrochronology programs CooRecorder and CDendro by Cybis (Larsson, 2016; version 8.1. 1) were used for ring measuring and analysis. CooRecorder is a ring counting and measuring software platform. CDendro displays the ring-width time series measured in 24 CooRecorder in order to correlate and compare ring-width time series within a plant and then among individual plants to cross-date series and ensure rings are accurate dates are assigned. Poorly correlated series from the same plant were checked for errors in CooRecorder. Ring widths were compared using normalized ring-width curves as opposed to raw values to assist in cross-dating as normalized ring-width curves remove the low frequency component of ring-width growth which assists in visually crossdating. Individual plants were then cross-dated in a similar way to other plants sampled within the same site and treatment type to identify highly-correlated individuals to be used to build chronologies. When cross-dating tree rings, a Pearson’s correlation coefficient of 0.4 or greater is commonly used (Matalas, 1962); however, given the asymmetry of the stem width growth of Dryas integrifolia I used a threshold correlation coefficient of 0.25. Any sample that could not be accurately crossdated to a standard of a 0.25 correlation coefficient was not included in chronologies. 2.5.1 Chronology Building Accurately cross-dated ring-width files were used to develop site- and treatment-level chronologies using the dplR package in R (Bunn, 2008). Ring widths that have not been detrended are referred to as ‘raw’ ring widths (RRW). The term ‘raw ring widths’ is used when referring to the original ring width files made in CooRecorder/CDendro before detrending and chronology building. Detrending of RRW is a method to accommodate ontogenetic trends (Fritts, 1976; Cook & Kairiūkštis, 1990) to better reflect growth as a response to environmental conditions. There are various detrending methods depending on different limiting factors to growth. Detrending helps to differentiate among potential causes of these limiting growth factors. Dryas integrifolia does not exhibit age/size related trends in ring widths that are common in trees, so detrending was done using a horizontal line to derive departures from the mean ring-width over the life time of each 25 individual plant. Detrended ring width series from individual plants were combined to produce standard and residual chronologies of ring width indices (RWI) for each of the three subsites and type of treatment. Only standard chronologies were used for subsequent analyses. Six chronologies standard were created in total: Dryas control, Dryas warmed; Willow control, Willow warmed; Meadow control, Meadow warmed. Due to the small sample size used in this study and the lack of obvious size- or age-related growth trend in Dryas integrifolia, raw ring width files were also used to investigate relationships with the treatment effect to compare between different analytical scales (i.e. site and treatment level vs plot level). Variability within chronology and raw ring width files was compared using a coefficient of variation, which allows for a comparison between separate data sets which have different means. 2.6 Data Analysis Environmental variables were measured both at the plot level using within-plot sensors, and on an overall site level using climate station data recorded at Alexandra Fiord. Near-surface air temperature and soil moisture data were averaged by month per site and treatment as an averaged representation of monthly conditions. Measurements were most consistently recorded during the summer months while field work was underway, which resulted in some data gaps in records spanning fall, winter and spring. Due to gaps in data collection throughout the calendar year, correlations were done using July records specifically, as July was the most consistently recorded month for environmental variables. As Hobo loggers only became commonly used in the year 2000 among the experimental sites, data analysis used ring width records extending back to only this year. General climate data were recorded by an auto-climate station, known as the camp Climate Tower, located at the base camp at Alexandra Fiord and has been operating since the late 26 1980s. The measured environmental variables include air temperature at two metres above ground, solar radiation, and relative humidity. 2.6.1 Linear Mixed Effects Models Linear mixed effects models were used to determine the effect of the experimental warming treatment on ring widths of Dryas integrifolia at Alexandra Fiord with detrended and raw ring width records. Linear mixed effects models are effective tools when describing an effect on a predictive variable with multiple explanatory and random variables, as is often the case in ecological statistical analysis. The selected models use ring width as the dependent variable, with treatment as the fixed-effects variable of interest, while varying other fixed and random effects unique to each scenario. Mixed effects models were made using the standard chronology files representing a site and treatment scale, as well as using the raw ring width files to include the plot level scale. Models were made using the lme4 package in R (Bates et al., 2015). Models were ranked by Akaike Information Criterion (AIC) which criteria were used to determine model selection. 2.6.2 Correlation analyses Pearson’s correlation analysis was used to investigate relationships between ring width index and environmental variables. Due to the variable nature of the raw ring width datasets, only the detrended chronologies were used for correlation analysis. Raw ring width data are temporally autocorrelated which is a concern for correlation analysis. Where relationships between ring width index and environmental variables were significant according to Pearson’s correlation, linear regressions were done to determine if relationships were causative as well as correlative. Correlations between the climate data and ring widths from control plots were calculated using the package dplR (Bunn et al. 2022). Ring widths from control chronologies did not correlate 27 well (R≤0.3) between the three subsites, and therefore climate data were compared against ring width indices for each subsite independently. Lag correlation analyses between ring width index and environmental variables were also used to determine if conditions in the previous season influenced growth in the current season, as is sometimes the case in dendroecology. Lag correlations were done with a cross-correlation analysis using the ccf function in dplR (Bunn, et al., 2022), which compares two time series together by offsetting one time series by year, thereby showing the degree of correlation between the two data sets at various points in time. 28 3 RESULTS 3.1 Radial Growth Chronologies A total of six chronologies were generated: Drays warmed, Drays control; Meadow warmed, Meadow control; and Willow warmed, Willow control. Only the Dryas control chronologies contained all ten collected D. integrifolia samples. Willow warmed, Willow control, and Dryas warmed chronologies contained nine samples; and Meadow warmed, Meadow control chronologies contained eight samples. Chronologies differed in their interseries correlations according to site and treatment, with the Dryas OTC chronology showing the greatest degree of correlation between plants, and the Willow OTC chronology showing the smallest degree of correlation between plants (Table 3). The longest ring width record (69 years) came from a Dryas subsite control plot, and the youngest plants (10 years) recorded came from a Dryas subsite control plot and Meadow subsite warmed plot. Standardized and detrended chronologies and raw ring width records for each of the three subsites showed no obvious growth trend through time (Figure 4 and Figure 6). Year Year B) Dryas warmed A) Dryas control Year Year D) Meadow warmed C) Meadow control Year Year 29 Figure 4. Standardized and detrended chronologies (RWI) by site and treatment: A) Dryas control B) Dryas warmed C) Meadow control D) Meadow warmed E) Willow control F) Willow warmed. The grey line denotes the chronological signal of each year. The red line denotes the smoothing spline. The shaded grey denotes sample depth of a particular year. Table 3. Descriptive statistics for each of the master ring width chronologies for Dryas integrifolia from warming experiments at Alexandra Fiord. Site/Treatment Chronology length (years) Plots (1 plant/plot) Interseries correlation (sd) Dryas warmed 61 9 0.40 (0.15) Dryas control 69 10 0.21 (0.16) Meadow warmed 19 8 0.34 (0.22) Meadow control 27 8 0.27 (0.16) Willow warmed 32 9 0.18 (0.16) Willow control 51 9 0.32 (0.21) E) Willow control F) Willow warmed Year Year 30 Figure 5. Air temperatures through time from within treatment plots (‘o’, dashed orange line) and control plots (‘c’, solid blue line). Data are from all plots in the three measured subsites. 3.2 Linear Mixed Effects Models: chronologies The site-wide model for the chronology data included ring width index as the dependent variable, with treatment as the class variable fixed effect, and random effects of site and year. Compared with the null model, which excludes fixed effects variables, the full model was a significantly better fit (Chi-square = 9.18; p<0.001). The ANOVA table produced from the full model indicated that treatment is an important driver in ring width size (p=2.48e-3; Table 4). A linear mixed effects model was also used to test for site differences in OTC warming effects. The site comparison model included ring width index as the dependent variable, with site as the fixed effect, and random effects of treatment and year. The ANOVA table produced from the model indicated that site is an important factor in ring width size (p=1.58e-3). Due to the significance of site in ring width size, each site was also investigated separately. Subsites were also investigated individually, as effects of treatment on ring width index varied according to location. A model investigating the effect of location included a fixed effect of subsite and random effects of treatment and year. The full model was not significantly better 31 than the null (Chi-squared= 3.682, p=0.05), however, the ANOVA generated for the model indicated that subsite was an important factor for ring width development (p<0.05). Site level models for Dryas, Willow and Meadow chronologies were unique to each subsite. The model for the Dryas subsite included a significant interaction of treatment and air temperature as the fixed effect variable (p<0.001; Figure 6), and a random effect of year. The interaction between treatment and air temperature indicates that the ring width index relationship with air temperature varies according to treatment. The full model fit the data significantly better than the null model which excluded the fixed effect variable (Chi-square=9.77, p=0.02). The ANOVA output from the full model indicated that treatment was not an important driver for ring width development in this site (p=0.292; Table 4). Model selection justification can be found in Table S2 in the Appendix. The Willow subsite model included treatment as the class variable fixed effect and a random effect of year. The full model was a significantly better fit than the null model, which excludes the fixed effect (Chi-square=7.504; p<0.01). The ANOVA output from the full model indicates that treatment is an important driver in ring width size (p<0.01; Table 4). The Meadow subsite model included fixed effects of treatment, air temperature, and a significant interaction variable between air temperature and treatment based on model fit using AIC and LogLik (p<0.001), with year as the random effect. The full model fits the data significantly better than the null model which excludes fixed effects (Chi-square=29.25, p<0.001). The ANOVA output of the model indicates that treatment and air temperature are important drivers for ring width development at this subsite (p<0.001; p<0.01, respectively). Model selection justification can be found in Table S3 in the Appendix. The significant interaction between air temperature and warming treatment within the Dryas and Meadow subsite models indicated that the effect of treatment on ring width depends on 32 air temperature within treatment (see Appendix Table S2 and Table S3). A regression indicated that air temperature does not significantly influence ring width development in either treatment, although it is an important effect (warmed p=0.08; control p=0.42), and that ring width development may be somewhat influenced by measured air temperature in this instance. A regression analysis of the Meadow subsite air temperature-treatment interaction indicated air temperature significantly impacts ring width size within control plots, explaining 3% of the overall variance (R2= 0.03, p=0.03), however, air temperature did not have a significant relationship with ring width within warmed plots (R2=0.02, p=0.07). 3.3 Linear Mixed Effects Models: standardized raw ring widths The site-wide raw ring width model included fixed effect of treatment and random effects of year, as well as a nested random effect of plots within sites. The full model is a significantly better fit than the null model, which excludes fixed effects (Chi-squared= 11.498, p<0.001). The ANOVA generated for the site-wide model indicated that treatment was an important driver for ring width development (p<0.001, Table 4). A site-wide model investigating the effect of location included a fixed effect of subsite and random effects of plot, treatment and year. The full model was significantly better than the null (Chi-squared= 162.22, p<0.001). The ANOVA generated for the model indicated that subsite was an important factor for ring width development (p<0.001). Within-site models varied according to subsite, and were included as ring width was partially explained by subsite. Each model selection was a significantly better fit than the null models, which exclude fixed effects, and included random effects of plot and year. The Dryas subsite model used log transformed ring width to meet assumptions of normal distribution of 33 residuals with treatment as a class variable fixed effect (Chi-squared= 3713.7, p<0.001). The ANOVA table generated from the full model indicated that treatment was a strong driver of ring width (p<0.001; Table 4). The models for Meadow and Willow subsites also had treatment as a fixed effect, and were significantly better fit than the null models (Chi-squared= 39.406, p<0.001; and Chi-squared=52.443, p<0.001 respectively). The ANOVA generated from the full model indicated treatment was a strong driver of ring width within the Meadow subsite (p<0.001) and the Willow subsite (p<0.001; Table 4). Table 4. Effect of experimental warming on ring-width growth in Dryas integrifolia in tundra plant communities at Alexandra Fiord. Results are from ANOVA of linear mixed models of standardized chronologies and raw ring width measurements. Site Chi-square Treatment effect (p-value) RRW RWI RRW RWI Dryas 3713.7 9.77 2.68e-6 0.278 Meadow 39.406 29.25 3.639e-10 1.764e-06 Willow 52.443 7.504 4.43e-13 0.00625 All Sites 11.498 9.18 6.98e-4 0.00248 * * * * A) RWI within sites B) RRW within sites 34 Figure 6. Boxplots of ring widths according to site and treatment: A) Chronology ring width index; B) Standardized raw ring widths; C) Chronology ring width index across all sites; D) Standardized raw ring widths across all sites. Treatments shown as control (blue, c) and warmed (orange, o). Box plots show the median and interquartile range (25-75%). Outliers are shown as individual points. 3.4 Variance Ring width growth through time was not uniform across or within sites, and was variable in both the chronology and standardized raw ring width data. As expected, RRW datasets had a greater degree of variance within either treatment when compared to the chronology datasets (Table 5). The variability in ring width development through time was evident between sites and among treatments, which showed no clear temporal trend of ring width growth aside from a slight increasing trend from the RRW at the Dryas subsite (Figure 7). However, across sites, Dryas integrifolia from warmed plots generally had larger ring widths than those from control plots (Table 5). There was a similar degree of variance in the raw data sets than the chronology data sets for the Meadow warming treatment (Table 5). The Meadow warming chronology had the greatest average ring width index; however, it also had the largest degree of variance. The greatest variability in ring width chronologies was found in the control plots at the Willow subsite (Table 5). C) RWI across sites D) RRW across sites 35 Table 5. Mean annual ring widths and coefficient of variance from site/treatment chronology for ring-width indices (RWI) and raw ring widths (RRW). Site/treatment Mean annual RWI (µm) (sd) Mean annual RRW (µm) (sd) Coefficient of Variance RWI Coefficient of Variance RRW All sites warmed 0.99 (0.19) 2.69 (0.97) 0.19 0.36 All sites control 0.99 (0.18) 2.34 (1.14) 0.19 0.49 Dryas warmed 0.99 (0.18) 2.16 (0.61) 0.18 0.28 Dryas control 1.00 (0.13) 1.66 (0.79) 0.13 0.48 Meadow warmed 1.03 (0.26) 3.84 (0.92) 0.25 0.24 Meadow control 0.98 (0.19) 2.93 (0.72) 0.19 0.25 Willow warmed 0.98 (0.16) 3.23 (0.78) 0.16 0.24 Willow control 0.98 (2.43) 2.88 (1.28) 0.25 0.44 A) Dryas RWI C) Meadow RWI B) Dryas RRW D) Meadow RRW 36 Figure 7. Ring width chronologies through time by site and treatment; c = control plots, o = warmed. A) Dryas subsite chronology files; B) Dryas subsite raw ring width files; C) Meadow subsite chronology files; D) Meadow subsite raw ring width files; E) Willow subsite chronology files; F) Willow subsite raw ring width files. Records were restricted to the years 2000-2020 to include the maximum number of plants in each category. 3.5 Correlations with Environmental Variables Relationships between environmental variables and ring width were investigated to help determine factors impacting ring width development. Correlations and regressions between environmental variables and ring width were used to identify these relationships. Regression plots for standardized raw ring width records can be found in Appendix Figure S2 and Figure S3. Relationships with environmental data collected from the climate tower were investigated at each subsite independently using ring width datasets from control plots. This was due to variability in correlations of annual ring width records between sites (Figure 8). Only relationships between control data plants and site-wide environmental data sets were investigated as the climate tower records ambient environmental conditions, which are conditions experienced directly by control plots. E) Willow RWI F) Willow RRW 37 (A) Across sites Figure 8. Regression plots between ring width indices from control plants at each site with associated correlation coefficients: A) Meadow vs Dryas; B) Willow vs Dryas; C) Meadow vs Willow. Red line depicts regression trend line and grey shading represents 95% confidence intervals. 3.6 Air temperature There were no significant correlations between ring width index and mean July plot-level air temperature. There were no significant correlations between lagged environmental variables and chronology time series (Figure 9). A) Meadow vs Dryas A) Across sites B) Dryas B) Willow vs Dryas C) Meadow vs Willow 38 Figure 9. Ring width index against plot-level mean July air temperature (10 cm) within OTC and control plots. Shading represents 95% confidence intervals. 3.7 Soil Moisture Ring width index was positively correlated with soil moisture across all sites and treatments (r=0.25, p<0.001; Figure 10). There was a significant correlation between August soil moisture measurements and ring width index (r=0.30, p=0.03), where soil moisture explained 7% of ring width index variance (R2= 0.07, p=0.03). Although there was no significant relationship with soil moisture in neither June nor July, there were positive trends. The site-wide OTC chronology correlated significantly with soil moisture measurements (r=0.33, p<0.01), explaining 6% of ring width variance (R2=0.06, p<0.001). Of the site-specific correlations, a significant correlation between the warmed plot chronology and soil moisture was found at the Meadow subsite (r=0.54, p<0.01), where 27% of the variance in the ring width index was explained by soil moisture (R2=0.27, p<0.01; Figure 10). Although not statistically significant, the experimentally warmed chronology at the Willow subsite also showed a positive trend between ring width and soil moisture (r=0.30, p>0.05; Figure 9). There were no significant relationships between soil moisture and ring width indexes from the Dryas subsite (Figure 10). C) Meadow D) Willow 39 Figure 10. Regressions between ring width index and soil moisture (% volume) in warmed and control plots in A) all sites, B) Dryas subsite, C) Meadow subsite, D) Willow subsite. Shading represents 95% confidence intervals. 3.8 Correlations with climate station data Site level correlation analyses between control chronologies and weather data collected at the Climate Tower did not show any significant relationships (see Appendix Table S1 for correlation results). A) Across sites B) Dryas C) Meadow D) Willow 40 4 DISCUSSION 4.1 Dendrochronological potential of Dryas integrifolia This study shows the potential of Dryas integrifolia for dendrochronological studies and how growth of the species has responded positively to long-term experimental warming. Correlations of annual ring widths between Dryas plants were strong in similar sites and treatments, and chronologies were produced representing growth signals from each of the three sites and two treatments investigated at Alexandra Fiord. The use of chronologies for Dryas species is supported by other research done in subarctic and alpine environments (Au & Tardif, 2007; Fontana et al., 2021). Chronologies are more reliable when a ‘master chronology’ is used as a reference, however, there was no master chronology available for Alexandra Fiord. In a similar study, Au and Tardif (2007) were able to successfully cross-date D. integrifolia ring widths with nearby tree chronology records, which did have an established historical record in Churchill, Manitoba. Master chronologies are chronologies that are deemed to be a highly accurate record of growth ring increments through time, and are useful tools for dating woody plants grown in similar areas which are likely responding to similar environmental signals (Cook and Kairiukstis 1990). The record provided here serves as the first master chronology at a High Arctic site, Alexandra Fiord, based on Dryas integrifolia. There were no obvious temporal trends in the Dryas integrifolia chronologies, however this may be due to the small sample sizes and length of records used in this study. Typical dendrochronology studies using tree species require decades of data before sufficient conclusions can be drawn from these records; therefore, the small sample size and 21-year record for Dryas integrifolia at this site may be too limiting to draw generalized conclusions. Ring widths were 41 comparable within site and treatments through time; however, there was no clear indication of temporal temperature trends on ring width size. Raw ring width chronologies were compared with detrended ring width chronologies to investigate the benefits of reducing individual growth bias ‘noise’ within a dataset. The raw ring widths chronologies showed greater variability compared to the detrended chronologies. This was not surprising given that variability between ring widths is reduced by detrending a chronology to remove individual bias from the collective signal. A comparison was made between analysis with raw ring widths and standardized chronologies to determine the utility of using dendrochronological methods on the ring widths of D. integrifolia. The modelling showed that the treatment effects were similar when using either raw or chronology ring widths, but the reduced variability of the chronologies made them a better fit for some further analyses for dendroecological purposes. However, the raw ring width record showed that responses to treatment were similar across the sites; detrending the record introduced interaction with air temperature in the Dryas and Meadow subsite models which was not present when modelling the raw data. 4.2 Effect of Treatment on Growth Linear mixed effects models indicated that ring width was affected by the warming treatment across all three sites when compiled together. The significant interactions between air temperature and treatment in the Dryas and Meadow subsite models indicates that the influence of air temperature on ring width varies by treatment. Plants in the Dryas subsite were the only ones that did not show an important relationship with treatment. The effect of warming on ring width from the Willow and Meadow subsites indicate that ring growth is sensitive to temperature change. This sensitivity was also seen in Cassiope tetragona at Alexandra Fiord, as well as other shrubs 42 across the Arctic (Rayback & Henry, 2005; Rayback et al., 2011; Gallois 2019). A possible explanation for the lack of response in the Dryas subsite could be due to two flood events in 2001 and 2011(G. Henry, personal communication), which altered typical site conditions. Unlike the Meadow subsite which is consistently wet, introducing a large amount of water to the Dryas subsite would be a dramatic change to environmental conditions, which would have affected the plants. Gallois (2019) also noted the spatial variation in Alexandra Fiord subsites in growth records of C. tetragona, and also suggested the floods at the Dryas subsite could be partially responsible. Further investigation of the growth responses of other species during this period would be helpful in determining if perhaps there was a community-wide response to provide evidence that changes in environment contributed to the difference in Dryas ring response the Dryas subsite. As Dryas plants at the Willow and Meadow subsites both demonstrated an important positive relationship between warming treatment and ring width index, it is plausible that plants in the Dryas subsite might have expressed a similar relationship, had the site conditions been consistent through time. However, the relationship between raw ring widths and treatment showed that there was an effect of experimental warming at Dryas. It would worth investigating further the effects of detrending on small data sets and whether this perhaps masks existing relationships. Evergreen tundra plants tend to have a conservative life history, and therefore are typically less responsive to changes in environmental conditions, such as temperature increases, compared to deciduous shrubs. A meta-analysis of the initial effects of the OTC warming treatment on tundra plants by Arft et al. (1999) found that over the first four-year period, plants initially responded by increasing physical size, but in the following years reduced the amount of growth and increased reproductive efforts. Their explanation included varying internal resource allocation between years of excess in external resources. It is likely that secondary growth of D. integrifolia is benefiting 43 indirectly from temperature increases in warming plots, as warming treatments showed important relationships with ring width growth, however temperature independently did not demonstrate a relationship to ring-with growth. As well, Hudson and Henry (2010) found little change to an evergreen shrub heath community at Alexandra Fiord despite 15 years of experimental warming, implying plant community resiliency to environmental changes. It was speculated that perhaps evergreen species have a resiliency threshold against environmental conditions which must be surpassed before obvious changes to plant behaviour would occur. Despite the reputation of evergreen species being conservative responders to environmental conditions, Dryas integrifolia ring widths showed increased secondary growth in OTCs when compared to control plants. This study suggests soil moisture has a generally positive relationship with ring width size, and could be a variable influenced within OTCs which is part of the treatment effect on ring width size. Soil moisture has previously been found to influence shrub growth and abundance (Walker et al., 2006; Elmendorf et al., 2012a,2012b; Myers-Smith et al., 2015a; Edwards & Treitz, 2017; Ackerman et al., 2018), and is likely demonstrating this relationship at Alexandra Fiord as well. Au and Tardif (2007), however, demonstrated that ring-width records of D. integrifolia correspond to temperatures of the previous season, although they did not test for growth sensitivity. It appears that with continual experimental warming over 30 years, Dryas has been able to take advantage of improved growing conditions within OTCs to grow wider rings, as well as grow taller and increase reproductive effort (c.f. Klady et al., 2011). One meta-analysis of experimental warming sites in Arctic and alpine locations found that shrubs as a whole were more abundant in moist, warm sites, and showed the strongest responses to ambient warming (Elmendorf et al., 2012b). Of the plant types monitored, tall deciduous shrub abundance had the strongest response to warming in warm, moist sites; forbs and graminoids at colder sites; and lichens declined regardless of site or 44 temperature/moisture conditions (Elmendorf et al., 2012b). A summary of shrub studies in the context of climate change can be found in Table 6. Table 6. Previous shrub studies in the context of climate change. Region Shrub change observed Method Reference Alaska Expanding and stable patches of Alnus spp., Salix spp. & Betula spp. Repeat photography Sturm et al., 2001; Tape et al., 2006; Tape et al., 2010 Expansion of alder shrub patches, new shrub cover at the shrubline ecotone Orthophoto comparison, ring widths Dial et al., 2007 Ring growth responded positively to June temperature with diminishing marginal growth in response to increasing temperature Ring widths Ackerman et al., 2018 Western Canadian Arctic Increases in canopy height and cover of Salix pulchra, increases in patch size of Salix richardsonii Repeat photography, vegetation surveys, ring widths Myers-Smith et al., 2011 Increased growth and reproduction of Alnus viridis subsp. fruticosa in tundra fire scars, and retrogressive thaw slumps Ring widths Lantz et al., 2010; Lantz et al., 2009 Eastern Canadian Arctic Increase in Betula glandulosa cover on well-drained non-forested sites Image comparison and ground truthing Ropar & Boudreau, 2011 Stronger climate sensitivity in root collars vs. stems Ring widths Ropars et al., 2017 Central Canadian Arctic Ring width chronologies of D. integrifolia linked to snow levels and air temperatures of previous year ring widths Au & Tardif, 2007 Canadian High Arctic Increase in dwarf evergreen shrubs, and the dwarf willow Salix arctica biomass, point intercept Hudson & Henry, 2009; Hill & Henry, 2011 45 Reconstruction of average summer air temperatures using Cassiope tetragona plant stem increments bud scars Rayback & Henry, 2007 Greenland Stable cover of Salix glauca repeat vegetation type and cover survey Daniëls et al., 2010 Positive relationship between annual growth of Salix dwarf shrub species to summer air temp despite different temperature regimes and shrub growth rates at two sites Ring widths Buchwal et al., 2019 Differences in climate-growth response among Betula and Salix species and sites of contrasting topography ring widths Young et al., 2016 European Arctic Increase in shoot length growth of Cassiope tetragona in response to… leaf production, length and weight of leaves, leaf scar and wintermarksepta Rozema et al., 2009 Growth correlation to summer temperatures Ring widths Forbes et al., 2010 Ring width time series related to above-ground biomass production Ring widths Le Moullec et al., 2019 Shrub expansion into alpine tundra correlated with warm summers and winter snow cover Ring widths Hallinger et al., 2010 The effect of warming is therefore variable between plant types, as well as within types between species, and each response should be considered independently. This is also demonstrated with Dryas integrifolia, as the effect of warming varied between sites. The magnitude of the effect also varied between sites, where plants in the Meadow subsite had the strongest positive response to warming. This variation likely comes from site level differences, such as temperature-moisture relationships and soil conditions, as soil moisture is greatest at Meadow. 46 Interestingly, the warming effect on D. integrifolia ring width growth was strongest at the Meadow subsite, where it is a minor component of the vegetation. Dryas plants are limited to growing on mossy hummocks, as they cannot grow in standing water (BC Ministry of Forests and Range, 2013). As a result, the plants consist of few branches that grow quite tall and thin through the graminoids, as opposed to the multi-branched prostrate mat form found at the Willow and Dryas subsites. The greater ring widths in the Meadow plants could have been due to fewer branches competing for resources within the plants, allowing for more secondary growth in response to the ameliorated conditions in the OTCs. This result is in line with studies that have shown some Arctic shrubs benefit from moist, warm growing conditions (Elmendorf et al., 2012b). The effects of competition should also be considered at the Dryas and Willow subsites where Dryas – and other plant types – are abundant. Habitats where Dryas typically grows are also ideal for other shrubs, such as Salix arctica and Cassiope tetragona, all competing for resources. The high abundance of sedges and their litter at the Meadow subsite can shade Dryas shoots and cause them to be thinner and longer in their search for light; thus, the effects of competition could be investigated further to determine how significantly this influences Dryas secondary growth. 4.3 Environmental Impacts on Growth Although warming influences ring width development in Dryas integrifolia, temperature itself does not appear to be the main driver. In fact, incorporating temperature into the mixed effects models, both site-wide and site specific, to determine the effect of treatment on ring width index actually decreased model fit. As OTC treatment is a warming effect, it was expected that there would have been a relationship between surface air temperature and ring width index. The lack of relationship between ring width and temperature at the sites may be a result of small sample size of both the ring width record, as well as the temperature record in the plots. There was a small 47 negative trend of air temperature on ring width index from warmed plants at the Dryas subsite, and a small positive trend from warmed plants at the Meadow subsite. These were both nonsignificant relationships however, and would require a greater sample size to determine whether the trends are a result of environmental influence, or a result of limited data. Ring widths from the control chronology at Meadow showed a significantly negative relationship with air temperature, and may imply an inhibiting influence of warmer air temperatures on ring width development. OTCs may be causing selective drought conditions due to higher temperatures and lower moisture availability through greater evapotranspiration. However, this would also require further investigation into the relationship between air temperature and D. integrifolia ring width growth. Ring with index had a positive relationship with soil moisture levels from within OTC plots across all three sites, but was only significant at the Meadow subsite, the wettest of the three. It appears that warm and moist conditions have the greatest positive effect on ring with growth for Dryas integrifolia. This result aligns with the finding that evergreen shrub abundance has not responded to experimental warming in OTCs (Molau, 1997; Elmendorf et al., 2012b), however, it is responsive to soil moisture levels (Elmendorf et al., 2012b). It may be that the effects of temperature must be considered in conjunction with soil moisture when considering secondary growth effects of D. integrifolia, supporting the evidence suggesting soil moisture has an important role in evergreen shrub growth in high Arctic environments (Walker et al., 2006). The effect of warming on ring width at Meadow may be due to greater resource allocation to secondary growth as opposed to leaf production. As previously mentioned, Dryas plants at the Meadow subsite are tall with relatively few branches, likely to compete for light against the abundant sedges. As a result, these Dryas plants often lack an abundance of leaves along the stem and instead produce a smaller collection of leaves at the terminus of the stem to maximize exposure of photosynthesizing 48 leaves to sunlight. These morphological, and likely physiological, differences between Dryas plants grown in different habitats could help explain differences in ring width growth responses to experimental warming between sites. A study by Ackermann et al. (2018) investigated ring widths of Salix pulchra in Alaska in soils with varying nutrient and moisture properties. Their study found diminishing ring widths with increasing temperature, implying some other environmental variable must be a limiting factor for growth, such as soil moisture. In our study, only plants from the Meadow subsite demonstrated a subsite-level significant positive relationship between soil moisture and OTC ring width index, while plants in the Willow subsite had a positive trend and those in the Dryas subsite had no relationship. This aligns with the speculation that the flood events at the Dryas subsite have altered typical plant-environment relations to potentially affect growth benefits of site moisture levels. Plants growing at Dryas would be adapted to the mesic soils typically found there. A flood would then have a negative effect on plant growth – for example, by reducing soil oxygen levels. The plants in the OTCs would experience warmer conditions aboveground, but the response was muted because allocation of water and nutrients from the roots was affected by the oxygen poor, wet soils. In addition, soil processes and the microbiome were likely negatively impacted by the flooding events. None of the measured variables from the climate station yielded any significant relationships with radial growth in control plots. This result is unsurprising for this study, as the data showed high variability in growth responses between sites and treatments. Some evidence suggests solar radiation is an important factor (Molau, 1997), especially for evergreen shrubs who rely on solar radiation for cues on when to begin vegetative growth (Parsons et al., 1994; Welker et al., 1997). Although it may have been anticipated that Dryas growth would respond to environmental signals recorded by the climate tower, the limited ring width data and sensitivity to 49 local conditions likely inhibit the expression of potential relationships, similarly to relationships found with the plot level temperature data. The only other study investigating radial growth of Dryas integrifolia, in Churchill, Manitoba, found a positive correlation between secondary growth and snow depth, as well as with growing season length (Au & Tardif, 2007). Although neither snow depth nor growing season length were investigated in this study, it may be that snow depth corresponds to soil moisture amounts, as these relationships have been previously identified in Arctic regions (Wilson et al., 2020; Rixen et al. 2022). However, too much snow can delay the start of the growing season and reduce opportunity for plant growth (Rixen et al., 2022); therefore, the relationship between shrub growth and snow depth should be carefully considered. This may be true for the Willow subsite which typically melts out and is drier than the other sites and ring widths display a positive relationship with soil moisture, however this would not explain the relationship with the Meadow subsite, as it is consistently wet. Season length could not be easily identified with the records available, as there were significant periods of missing climate data, which restricted our analyses to July climate variables. An analysis of Dryas octopetala responses to experimental warming across the Arctic found that warmed plants had increased shoot lengths, greater photosynthesis and green leaf biomass, and accelerated phenological development (Welker et al., 1997). Given the evidence, it seems probable that with continued warming in the high Arctic, Dryas integrifolia will show greater growth. 4.4 Future Work The expanding use of Arctic shrub dendrochronology has provided a resourceful tool for environmental assessments in Arctic ecosystems (Johnstone & Henry, 1997; Rayback & Henry, 2007; Au & Tardif, 2007; Hallinger et al., 2010; Forbes et al., 2010; Rayback et al., 2011; Myers- 50 Smith et al., 2015a; Myers-Smith et al., 2015b; Hollesen et al., 2015; Young et al., 2016; Ackerman et al., 2018; Buntgen et al., 2018; Buchwal et al., 2019; Le Moullec et al., 2019, etc.). Although Dryas integrifolia demonstrated responses to experimental warming and some environmental variables, there are many plant-environment relationships still to be investigated. For instance, understanding seasonal nutrient/growth allocations may provide a more holistic understanding of how Dryas responds to warmer environments. Evidence suggests that some high Arctic plants have ‘boom and bust’ years, where in one year they are more productive relative to the next, in a lagging pattern of productivity (Johnstone and Henry 1997). This is likely due to differences in seasonal nutrient/growth allocation within the plant, and there has yet to be any research investigating relationships between radial growth and these seasonal behaviours, due to the lack of any patterns that fit the hypothesis of alternating allocations between vegetative and reproductive response. As well, Johnstone and Henry (1997) found that in another evergreen dwarf shrub, Cassiope tetragona, more flowers produced in one year coincided with comparatively reduced annual growth in the following year. Long term monitoring of D. integrifolia at Tanquary Fiord, NU, Canada found earlier flowering and fruiting times related to spring/summer temperatures, which had increased during the 20-year study period (Panchen et al., 2015). Secondary growth patterns of Dryas could be partially explained by phenological changes, as was found with Johnstone and Henry (1997) with C. tetragona; however, further research would be required to determine relationships to season length and temperatures. Competition may also affect secondary growth patterns, but has not been explored directly in this study. As mentioned above, it is possible that plant-plant interactions are also influencing annual ring width development in Dryas integrifolia, as competition in Arctic plant communities often dictates the resources available to a plant for growth (Wahren et al., 2005; Elmendorf et al., 2012b). Investigating growth 51 responses of Dryas integrifolia across range distributions would be another avenue of interest. There are several studies demonstrating differential growth patterns of shrubs over space and time (e.g.: Elmendorf et al., 2012b; Myers-Smith et al., 2015; Fontana et al., 2021). Even within Dryas integrifolia, the findings from Au and Tardif (2007) in a Subarctic environment differed from what was found at Alexandra Fiord, and even within among the subsites at Alexandra Fiord, there were varying responses. It is unlikely the responses of Dryas integrifolia at Alexandra Fiord would be universally applicable, and they are likely to be place specific due to nuances in microhabitat conditions, as exhibited through this study. Conducting a similar study spanning the range of Dryas integrifolia would better inform the spatial-scale variability in response to environmental conditions. Relationships between Dryas ring width development and phenology, plant community dynamics, or spatial location may be important in understanding ring width patterns which have not yet been explained by the environmental variables explored in this study. Studies of belowground environments and dynamics are lacking in high Arctic plant communities. Investigation of belowground variables often requires destructive methods, and are therefore not as frequently considered when making ecological assessments. The growth of roots and rhizomes and their responses to environmental factors would be beneficial to investigate in relation to ring width development through time, and in response to environmental warming. The biomass allocation pattern, as expressed standing crop ratio, between above and belowground is typically smaller in tundra plants because of relatively larger investments in roots and rhizomes (Henry et al. 1990). Therefore, it may be illuminating to consider rooting networks of Dryas and other Arctic dwarf shrubs when assessing overall plant growth, particularly with continued environmental warming. 52 The small sample size, limited record for environmental data, and restrictions on plant selection were limiting factors for chronology building in this study. Chronologies increase in reliability and robustness with more plants contributing to the record, and therefore may be more representative of the environments from which the chronologies are made (Cook & Kairiukstis, 1990). Selecting a single plant from plot edges may have missed what might be considered the ‘ideal’ specimen; neither largest nor most vigorous plant, which would be beneficial for ring width assessments, as larger plants sometimes indicate older plants with less noise in the ring width record (Schweingruber et al., 2007), whereas smaller or less vigorous plants may be more likely to have more complex ring width patterns (Schweingruber et al., 2007). Dryas integrifolia also has what may be considered ‘porous’ rings, where ring boundaries can be difficult to discern due to more cells produced within a season which can be mistaken as multiple rings. As well, Dryas integrifolia is comparatively less intuitive to cross date than other shrub species. Dryas is a dwarf Arctic shrub, and the ring development is often not circular around the pith, but oblong from the pith to the outer stem, likely indicating which side of the stem was facing upwards, and which side was on the soil surface. Because of this, cross dating Dryas species sometimes cannot be done (Fontana et al., 2021). 53 5 CONCLUSIONS Ring widths for Dryas integrifolia plants were analyzed from three unique subsites with passive warming experiments at the High Arctic ITEX site, Alexandra Fiord. A total of 30 plants were used to build chronologies for each subsite and treatment. It was hypothesized that ring widths of D. integrifolia between warmed and control plots would differ; it was also hypothesized that ring width size of D. integrifolia would partially depend on local temperature and soil moisture as environmental variables. The results from this study partially supported these hypotheses. Ring widths from warmed chronologies were generally larger than ring widths from control chronologies at the Willow and Meadow subsites, however, plants from the Dryas subsite showed no differentiation between ring width sizes by treatment. Although the treatment effect of OTCs is an increase in near surface air temperatures, temperature as an isolated environmental variable did not significantly influence ring widths of D. integrifolia from any of the three sites. Soil moisture, however, was an important variable in explaining ring width size, and significantly correlated to ring widths of D. integrifolia from both Willow and Meadow; plants from the Dryas subsite did not share this relationship. The lack of relationship between air temperature and ring width was surprising, despite the distinct difference in ring widths in response to a warming treatment, as well as the evidence of other Arctic shrub dendrochronology studies identifying temperature as an important driver for growth (Rayback & Henry, 2007; Au & Tardif, 2007; Hallinger et al., 2010; Ackerman et al., 2018; etc.). Aside from soil moisture, the lack of relationship with other environmental variables suggests there are habitat features, or plant traits, that are influencing ring development of D. integrifolia at Alexandra Fiord, which have not been investigated here. Future dendrochronological work with D. integrifolia should consider further site conditions, such as snow depth (an important feature for ring development according to Au 54 and Tardif (2007), microbial activity and rooting relationships in subsoil environments, as well as phenological effects which may result in a differential allotment of energy within the plant each season. This study supports the use of High Arctic shrubs in dendrochronological research, and provides an opportunity to further our knowledge of plant-environment relationships during a period of continued and amplified climate change conditions in the north. Further investigation into these relationships with Dryas integrifolia may prove useful as an abundant Arctic and alpine shrub for better understanding these relationships. 55 REFERENCES Ackerman, D. (2018). Shrub-induced snowpack variability alters wintertime soil respiration across a simulated tundra landscape. 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Examples of varying ring width growth and length through time by treatment within two plots taken from the three subsites. A) Dryas plots 1 T and 1 C, B) Dryas plots 2 T and 2 C, (C) Meadow plots 1 T and 1 C, (D) Meadow plots 3 T and 3 C, (E) Willow plots 2 T and 2 C, and (F) Willow plots 4 T and 4 C. C) Meadow plot 1 D) Meadow plot 2 A) Dryas plot 1 B) Dryas plot 2 E) Willow plot 1 F) Willow plot 2 65 Table S1. Pearson’s correlation of control plot RWI chronologies to camp Climate Tower environmental variable records; including: relative humidity; solar radiation; air temperature. Site Correlation Coefficient relative humidity solar radiation air temperature Dryas -0.180 0.066 -0.054 Meadow -0.087 -0.121 -0.210 Willow -0.263 0.262 -0.074 Table S2. Dryas subsite RWI model iterations and fit statistics. Model AIC LogLik Chi-squared RWI~treat + (1|year) -322.63 165.31 0.7065 RWI~treat + air temp + (1|year) -320.73 165.37 0.884 RWI~treat + air temp + treat:air temp + (1|year) -328.26 170.13 0.021* RWI~1 + (1|year) -324.49 165.24 NA Table S3. Meadow subsite RWI model iterations and fit statistics. Model AIC LogLik Chi-squared RWI~treat + (1|year) -260.63 134.32 0.002** RWI~treat + air temp + (1|year) -258.84 134.42 0.008** RWI~treat + air temp + treat:air temp + (1|year) -276.49 144.25 1.98e-06*** RWI~1 + (1|year) -253.24 129.62 NA 66 (A) Across sites Figure S2. Regressions of Standardized raw ring widths against plot-level mean July air temperature (10 cm) within OTC and control plots. Shading represents 95% confidence intervals. A) Across sites C) Meadow D) Willow B) Dryas 67 Figure S3. Regressions of Standardized raw ring widths against soil moisture (% volume) between warmed and control plots in A) all sites, B) Dryas subsite, C) Meadow subsite, D) Willow subsite. Shading represents 95% confidence intervals. A) Across sites B) Dryas C) Meadow D) Willow 68 Figure S4. Interaction plots between air temperature and ring width index according to treatment from the Dryas site (left) and the Meadow site (right). Ring widths from treatment chronologies are shown as treat ‘o’ and are purple, ring widths from control chronologies are shown as treat ‘c’ and are blue.
Thesis/Dissertation
eng
Geography
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Henry, Gregory Hugh Ross, 1956-
Radial growth responses in Dryas integrifolia to ambient and experimental warming in the high Arctic
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