Limnology and Paleolimnology of Adjacent High Arctic Lakes with an Emphasis on Terrestrial-Aquatic Linkages

Limnology and paleolimnology of adjacent High Arctic lakes with an emphasis

on terrestrial-aquatic linkages: Cape Bounty, Melville Island, Nunavut

Kailey Amanda Stewart

A thesis submitted to the Department of Geography in conformity with the

requirements for the degree of Doctor of Philosophy

Queen’s University, Kingston, Ontario, Canada

October, 2011

Abstract

Our knowledge of how Arctic freshwater ecosystems will respond to continued climate change and variability is fundamentally limited by logistical difficulties of such remote research, resulting in relatively sparse long-term baseline data on these systems.

This research applies a unique paired-watershed approach (i.e., two similar, adjacent lakes and catchments) to help address these limitations, which provided an opportunity to identify how broad-scale factors are filtered or modified by site-specific characteristics.

My first main objective was to document the seasonal hydrochemical variability of runoff and influences on lake chemistry. Both lakes appear to be relatively insensitive to seasonal hydroclimatic variability, largely because periods of high discharge were also characterized by lower concentrations of dissolved and particulate matter, but also because of the relatively long lake water turnover time that suggests the effects of climatic and environmental changes would be felt later in these systems than in lakes and ponds with smaller lake volumes.

My second objective was to investigate spatial and temporal trends in the lake diatom communities in order to refine subsequent paleoenvironmental reconstructions.

A critical aspect of this objective was testing how faithfully the whole lake diatom community was represented in deep lake surface sediments where sediment cores are routinely collected. Most differences between the two lakes were largely accounted for with microenvironmental conditions associated with the specific sampling location.

Also, both lakes exhibited a degree of disconnection between littoral benthic and

profundal zones that manifested as an under-representation of the bentic community in deep lake surface sediments, with implications for paleoenvironmental interpretations.

Finally, I present a multi-proxy record of environmental conditions in adjacent lakes spanning the period from pre-industrial times. Biogeochemical records reflected major changes in lake primary productivity and terrestrial organic matter accumulation beginning prior to 1950 in both lakes, pointing to profound environmental changes that culminated with the establishment of an appreciable diatom community in both lakes in the 1980s. Differences in the timing of changes between the two lakes point to differing threshold capacities to external forcings, and suggest that East Lake’s response to post- industrial climate change is advanced compared to West Lake.

Co-Authorship

This thesis is presented in manuscript style conforming to the style outlined by the School of Graduate Studies and Research. Each chapter contains its own literature cited, and is presented in the format of the journal to which it was submitted, when applicable. My supervisor, Scott Lamoureux, is a co-author on all chapters. In addition,

Brent Paulter, Myrna Simpson, and Jaclyn Cockburn are co-authors on chapter 4, due to their contributing roles in laboratory access, training and research support (BP, MS), and development of the final varve chronologies (JC).

All field work was developed, coordinated and carried out by me, with assistance by others as indicated in the acknowledgement section of each chapter. All laboratory and data analysis was conducted by me, with the exception of specialized analyses including 210Pb dating (MyCore Scientific Inc.), water chemistry analysis (National Water

Research Institute), C/N (Guelph Analytical Unit), chlorophyll-a determinations (Paul

Hamilton, Canadian Museum of Nature), and inferred chlorophyll-a determinations

(Elizabeth Kjikjerkovska, Queen’s University). I developed the methodology, drafted all figures, and was solely responsible for writing each of the manuscripts.

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Acknowledgements

My sincerest appreciation goes out to my supervisor, Scott Lamoureux, for his continuous support, encouragement, mentorship, patience, and probably most important, his inspiration and enthusiasm, which undoubtably carried me through the more challenging parts of this process. All in all, you are a fantastic supervisor! I am also incredibly greatful to Scott for giving me the opportunity to study and visit the Arctic – an amazing, awe-inspiring place in so many ways – a gift I will always treasure.

I am extremely grateful to my husband, Matthew, for being by my side throughout this seemingly endless process. I started my PhD many years ago (before we were married and had two lovely children and another one due tomorrow!), and I cannot begin to imagine how much time he has spent encouraging me along this journey. His faith in my ability to accomplish my PhD was a great source of strength during times when I sincerely questioned whether or not I could. He assured me that as long as I was making progress, no matter how small at times, eventually I would finish.

Thank you for being right! Thank you also to my children, Nora and Wyatt, for keeping me grounded and reminding me daily of what truly matters.

Thank you also to my extended academic family that collectively guided me through this process, including committee members John Smol, Roland Hall, Paul Treitz,

Paul Grogan, Melissa Lafrenière, and past and current EVEX lab members, especially

Jaclyn Cockburn, Jessica Tomkins, and Kasey Kathan. A special thank you to Myrna

Simpson and Brent Paulter (University of Toronto, Scarborough), for their generosity of time and laboratory assistance, and especially to Sarah Finkelstein (University of

Toronto) for adopting me into her lab and being a great mentor and friend. I cannot forget the good times and help had by colleages and assistants in the field: Jaclyn

Cockburn, Jake Wall, David Atkinson, Dana Macdonald, Freyja Forsyth, Beth Wells, Liam

Colgan and Andrew Forbes. I would also like to express my appreciation to the staff and many faculty members in the Department of Geoography at Queen’s University who were a constant source of positive energy.

Finally, a sincere appreciation goes out to all of my friends and family for their genuine interest in my research, for riding through the highs and lows with me and, finally, for celebrating this achievement along side me!

Statement of Originality

I hereby certify that all of the work described within this thesis is the original work of the author. Any published (or unpublished) ideas and/or techniques contributed by others are fully acknowledged in accordance with standard referencing practices.

Kailey A. Stewart

October, 2011

Table of Contents

Abstract ...... i Co-Authorship ...... iii Acknowledgements ...... iv Statement of Originality ...... vi Table of contents ...... vii List of Appendices ...... x List of Tables ...... xi List of Figures ...... xii

Chapter 1: Introduction...... 1 Arctic environmental change...... 1 Assessing variability and sensitivity: High Arctic limnology and seasonality...... 2 Diatoms: key indicators in Arctic lacustrine systems ...... 3 Gaining perspective: multi-proxy paleolimnological reconstructions ...... 6 Justification of field site: a paired watershed approach ...... 9 Thesis hypothesis and research questions ...... 10 References ...... 12

Chapter 2: Connections between river runoff and limnological conditions in adjacent High Arctic lakes: Cape Bounty, Melville Island, Nunavut ...... 20 Abstract ...... 21 Introduction ...... 22 Materials and methods ...... 24 Site description ...... 24 Sample collection ...... 25 Results ...... 27 Seasonal hydroclimatic variability ...... 27 Hydrochemistry ...... 28 Ions and metals ...... 29 Major nutrients...... 30 Aquatic productivity...... 31 Discussion ...... 32 Regional controls on limnology ...... 32 Allochthonous and autochthonous sources of particulate nutrients...... 35 Controls on aquatic productivity ...... 36 The influence of river runoff on lake water chemistry ...... 38

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Melt intensity and lake water chemistry ...... 40 Conclusions ...... 42 Acknowledgements ...... 44 References ...... 45 Figures ...... 50 Tables ...... 57

Chapter 3: Seasonal and microhabitat influences on diatom assemblages and their representation in sediment traps and surface sediments from adjacent High Arctic lakes: Cape Bounty, Melville Island, Nunavut...... 62 Abstract ...... 63 Introduction ...... 64 Site Description ...... 67 Materials and Methods ...... 69 Sample collection ...... 69 Diatom processing and microscopy ...... 71 Numerical analyses ...... 72 Results ...... 74 Hydrochemistry ...... 74 Diatom flora ...... 75 Discussion ...... 81 Similarity of diatom floras ...... 81 Site-specific differences ...... 84 Species-environment relationships...... 86 Implications for paleoenvironmental reconstructions ...... 87 Conclusion ...... 90 Acknowledgements ...... 92 References ...... 93 Tables ...... 100 Figures ...... 105

Chapter 4: A paired-lake comparison of recent aquatic and terrestrial dynamics recorded in varved sediments from adjacent High Arctic lakes: Cape Bounty, Melville Island, Canada...... 119 Abstract ...... 120 Introduction ...... 122 Study site ...... 125

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Methods ...... 126 Coring and chronology ...... 126 Diatom preparation and enumeration ...... 127 Spectrally inferred Chl-a and C/N ratios ...... 128 Solvent extracted organic matter ...... 129 Results ...... 130 Chronology ...... 130 Diatoms ...... 131 Sediment accumulation and Chl-a fluxes ...... 133 Lipid geochemistry ...... 134 OM degradation ...... 136 Bulk element and lipid biomarkers ...... 138 Instrumental and proxy climate records ...... 141 Discussion ...... 143 Appearance of diatoms in the late- 20th century ...... 143 Littoral-profundal disconnection ...... 146 Asynchronous ecological thresholds ...... 147 Influence of sedimentation rates...... 149 Between-lake differences in aquatic-terrestrial linkages ...... 150 Biomarkers of changes in aquatic and terrestrial vegetation ...... 156 Conclusion ...... 160 Acknowledgements ...... 162 References ...... 163 Tables ...... 173 Figures ...... 176

Chapter 5: Summary and Conclusions ...... 185 Implications and future directions...... 192

Appendices ...... 196

List of Appendices

Appendix 1: Table of water chemistry samples - nutrients ...... 197

Appendix 2: Table of water chemistry samples - ions and metals ...... 199

Appendix 3: Environmental variable correlation matrix ...... 200

Appendix 4: Seasonal diatom abundances per sample from West Lake ...... 202

Appendix 5: Seasonal diatom abundances per sample from East Lake ...... 204

Appendix 6: Abundances of diatoms from West and East Lake diatom core samples ...... 206

Appendix 7: List of all diatom taxa identified in the Cape Bounty Lakes ...... 207

Appendix 8: Photomicrographs of common diatom species ...... 209

Appendix 9: 210Pb and 137Cs concentration data ...... 211

Appendix 10: Inferred chlorophyll a concentrations and profiles ...... 212

Appendix 11: Organic matter extract yields and lipid concentations ...... 214

Appendix 12: Concentrations of individual lipid compounds from West Lake...... 215

Appendix 13: Concentrations of individual lipid compounds from East Lake ...... 216

Appendix 14: Detailed methods of solvent extractions and GC-MS analyses ...... 218

Appendix 15: Comparison of regional climate station data ...... 219

List of Tables

Chapter 2

Table 2. 1 Physical and chemical attributes of the Cape Bounty lakes (2003-4)...... 57 Table 2. 2 A summary of key differences between the two years studied...... 58 Table 2. 3 Summary of 2003 and 2004 water chemistry results for Cape Bounty...... 59 Table 2. 4 Replacement times and dissolved nitrogen and phosphorus stocks…… ...... 61

Chapter 3

Table 3. 1 Major physical and chemical attributes of the Cape Bounty lakes………….……..100 Table 3. 2 Summary statistics for ordinations………………………………………………………….……..101 Table 3. 3 Ordination codes and abundance of common West Lake species ………….……..102 Table 3. 4 Ordination codes and abundances of common East Lake species…………….……103 Table 3. 5 Matrix of t-test levels of significance between sample type diversities…….…..104

Chapter 4

Table 4. 1 Major physical and chemical attributes of the Cape Bounty lakes...... 173 Table 4. 2 Relative abundance data of common species...... 174 Table 4. 3 Climate station and varve thickness correlations...... 175

List of Figures

Chapter 2

Figure 2. 1 Location of the Cape Bounty field site on Melville Island...... 50 Figure 2. 2 Seasonal stream flow and meteorological data ...... 51 Figure 2. 3 Seasonal trends of specific conductance ...... 52 Figure 2. 4 Seasonal trends of major ions ...... 53 Figure 2. 5 Seasonal distribution of nitrogen species ...... 54 Figure 2. 6 Seasonal trends of major nutrients and Chl-a ...... 55 Figure 2. 7 Seasonal trends of river discharge and nutrient fluxes and lake nutrient and Chl-a concentrations...... 56

Chapter 3

Figure 3. 1 Study site ...... 105 Figure 3. 2 Seasonal profiles of select chemical variables ...... 106 Figure 3. 3 Temporal changes in Shannon diversity in each microhabitat...... 107 Figure 3. 4 Seasonal abundances of all common diatoms...... 108 Figure 3. 5 DCA bi-plots of species and samples...... 110 Figure 3. 6 DCA ordination graphs of samples classified by sample type and bi-plot of species and samples...... 112 Figure 3. 7 DCA tri-plots of species and samples, unconstrained to habitat ...... 114 Figure 3. 8 CCA bi-plots of species and primary environmental variables...... 116 Figure 3. 9 Relative abundances of select taxa across sample types...... 118

Chapter 4

Figure 4. 1 Study site...... 176 Figure 4. 2 Radioisotopic and varve chronologies...... 177 Figure 4. 3 Stratigraphy of common diatoms, concentration profiles of valves, valve fragments and chrysophyte cysts, inferred Chl-a fluxes and sedimentation rates...... 179 Figure 4.4 Total extract yields and concentrations of the dominant aliphatic and cyclic lipids in sediment extracts ...... 181 Figure 4. 5 Indicators of degradation and diagenesis of lipid fractions...... 182 Figure 4. 6 Proxy indicators of past terrestrial and aquatic organic matter dynamics ...... 183 Figure 4. 7 Composite of climate and proxy climate records...... 184

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Chapter 1: Introduction

Arctic environmental change

Due to positive feedbacks primarily associated with melting snow and ice cover, warming in the Arctic is amplified and accelerated relative to the rest of the planet, and this trend is likely to continue (Zweirs et al., 2002; ACIA, 2005; White et al., 2007). An important knowledge gap remains around how high latitude freshwater ecosystems will respond to continued climate trends (ACIA, 2005). Freshwater lakes, rivers, ponds and wetlands are a ubiquitous feature of the Arctic landscape and are an important component of global climate and biogeochemical cycles, as well as being critical to human activity and subsistence for many Northern communities (White et al., 2007).

Though it is not certain how Arctic freshwater ecosystems will respond to continued climate change, a vast amount of evidence pertaining to Arctic hydrologic change is accruing, and will no doubt impact downstream lake and pond ecosystems.

Evidence includes, but is not restricted to, changes in permafrost and active layer temperature and depth (Frauenfeld et al., 2004), glacial thickness and extent (Abdalati et al., 2004; Burgess and Sharp, 2004), the areal extent of lakes, ponds and wetlands

(Smol and Douglas, 2007; Walter et al., 2006; Smith et al., 2005a), precipitation and winter snow cover (Serreze et al., 2002; Peterson et al., 2006), and the timing of snowmelt and subsequent discharge patterns (McClelland et al., 2006; Déry and Wood,

2005). Though the relationships between Arctic hydrological change and aquatic ecosystem integrity are not fully understood, it is clear that Arctic freshwater ecosystems are also exhibiting profound ecological changes that are directionally

consistent with overall warming (ACIA, 2005; Quinlan et al., 2005; Smol et al., 2005;

Muller et al., 2006; Antoniades et al., 2007; Michelutti et al., 2010).

Assessing variability and sensitivity: High Arctic limnology and seasonality

Arctic aquatic ecosystems are subjected to extreme changes in hydroclimatic conditions over the course of a year. The long, cold winter is interrupted by a relatively short growing season characterized by an intense runoff fuelled by rapid melting of the winter snowpack. Once this snowpack is exhausted, runoff recedes quickly to baseflow conditions punctuated by infrequent and generally low magnitude rainfall events

(groundwater contributions are negligible due to permafrost). Such extreme changes in runoff and associated particulate and dissolved constituents hold implications for downstream aquatic ecosystems, particularly those characterized by low productivity and oligotrophic conditions where contributions from the terrestrial environment are relatively large.

Despite large strides in reporting baseline physical and chemical limnology from lakes and ponds throughout the circumpolar Arctic in recent years (e.g., Douglas and

Smol, 1994; Pienitz et al., 1997; Hamilton et al., 2001; Michelutti et al., 2002a;

Antoniades et al., 2003; Lim et al., 2005; Keatley et al., 2007), logistical constraints continue to limit our understanding of seasonal variability in these systems (Forsström et al., 2007). Yet, the range of conditions Arctic aquatic ecosystems are subjected to over the course of a year suggests that seasonal variability may be instrumental in

understanding how they might respond to continued or even accelerated hydroclimatic change in the future.

Diatoms: key indicators in Arctic lacustrine systems

In addition to a better understanding of how ecosystems respond to short term changes, anticipating freshwater ecosystem responses to continued climate change requires an understanding of how these systems have responded to variability in the past. Developing a long-term perspective is critical to assessing ecosystem sensitivity and, in the absence of historical data, efforts must be made to reconstruct past conditions (Smol and Douglas, 2007). One approach that is widely employed in Arctic paleolimnology focuses on the fossil remains of diatoms, a class of algae obtained from undisturbed lake sediment cores. Diatoms often form a major component of the relatively simple Arctic freshwater ecosystems and, as such, can be used as a proxy indicator of overall aquatic conditions.

Diatoms have become a vital indicator of past and present conditions in Arctic lakes and ponds owing to the fact that many taxa have specific ecological requirements and their siliceous cell walls generally remain well preserved and are easily identified to the species level even in very old lake sediments (Smol and Stoermer, 2010).

Furthermore, the wealth of knowledge amassed in recent decades on Arctic lake and pond diatoms and their relationships to environmental variables including pH, salinity, conductivity, nutrient status, temperature, ice-cover and substrate availability is impressive (Smol, 1983; 1988; Battarbee et al., 2001; Lim et al., 2001; Michelutti et al,

2003; Smol et al., 2005; Fritz, 2008; Soininen and Weckström, 2009), and presents an excellent opportunity for direct comparison with other sites and to make inferences based on documented Arctic autecologies. For example, diatoms have been instrumental in identifying post-industrial circumpolar changes to Arctic aquatic ecosystems and the specific nature of these changes is consistent with climate warming and associated impacts on lake and pond ice-cover and thermal regimes (Smol et al.,

2005). In addition, associations between environmental variables and diatom species assemblages have been successfully used to infer past environmental conditions through the use of transfer functions (e.g., Antoniades et al., 2005), which distil modern limnological conditions across numerous lakes or ponds down to a single predictive variable (Birks, 1998).

Despite the overall success of diatoms as proxy indicators of past conditions, marked shifts in modern day assemblages of Arctic lakes and ponds, most likely in response to rapid environmental change, may produce future assemblages bearing little resemblance to past communities, rendering transfer functions unfeasible. In addition, the logistical constraints of sampling remote Arctic locations limit our understanding of not only seasonal changes, but microhabitat structure and development and other unmeasured variables and multi-variable interactions that may be critical to understanding how diatoms will respond to future environmental conditions (Sayer et al., 2010). The fact that many taxa are cosmopolitan, and yet very different taxa can inhabit closely situated sites that appear to be very similar (e.g., Keatley et al., 2008) also warrants a greater focus on intensively studying single systems on seasonal and inter-

annual scales to compliment the more common single-point analysis of numerous sites spanning a broad geographic range, so that a more holistic understanding of species- environment relationships and distributions may be achieved.

Though less common, single-site investigations focussed on seasonal and inter- annual timescales are increasing and important new insights are being revealed (e.g.,

Lotter and Bigler, 2000; Rautio et al., 2000; Köster and Pienitz, 2006; Kirilova et al., 2008;

Sanchez-Castillo et al., 2008; Sayer et al., 2010; Woodbridge and Roberts, 2010). Of paleolimnological significance in particular are how faithfully modern lake diatom communities translate to deep lake sediments. For example, Woodbridge and Roberts

(2010) observed that large but infrequent mono-specific algal blooms overwhelmed bulk sediment samples, having the potential to skew paleoenvironmental reconstructions based on typical multi-year aggregate samples. Perhaps of equal importance, however, is the fact that an opportunity to refine the reconstruction with valuable information about species ecologies and seasonal dynamics would have been missed without the initial seasonal investigation.

In addition to seasonal dynamics, taphonomic and other processes that bias the sedimentary record must be considered. Hitherto, this issue has been largely restricted to taphonomic processes in marine (e.g., Zielinski and Gersonde, 1997) and deep lake systems (e.g., Ryves et al., 2003), and few lake studies have complimented the analysis of surface sediment assemblages with that of the modern lake flora to assess the completeness of the sedimentary record (e.g., Woodbridge and Roberts, 2010; Ryves et al., 2009). Moreover, increased abundance of diatom valves in recent sediments of

several Arctic lakes has warranted careful consideration of the possibility of dissolution in explaining such fundamental changes (Doubleday et al., 1995; Perren et al., 2003;

Antoniades et al., 2007).

Gaining perspective: multi-proxy paleolimnological reconstructions

In addition to the limited temporal extent of diatom communities in some Arctic lakes, diatoms only represent a single component of aquatic ecosystems and may not respond as immediately to changing environmental conditions as other ecological components (Antoniades et al., 2007), though they have demonstrated a rapid response to major limnological changes in other systems (e.g., Douglas and Smol, 2000; Michelutti et al., 2002b). Hence, their usefulness may be limited by their chronological extent or their relative sensitivity to environmental changes compared to other ecosystem components, thus advocating for complimenting diatom-based investigations with other proxy indicators. For example, the combination of diatom and algal pigment analyses in lake sediments has augmented our understanding of recent changes in Arctic lake primary productivity and the role of diatom productivity. In a Baffin Island lake, simultaneous increases in biogenic silica (BSiO2) and chlorophyll-a (Chl-a) concentrations in recent sediments indicated the important contribution of siliceous algae to primary productivity in this system (Michelutti et al., 2005), whereas asynchronous changes in diatom assemblages and algal pigment extractions in recent sediments from Lake Hazen,

Ellesmere Island suggested additional algal components were responding to ameliorated climatic conditions in advance of the diatom community (Antoniades et al., 2007).

Additional opportunities to develop robust records of paleolimnological conditions involve molecular-level analysis of sedimentary organic matter. Organic matter geochemistry can be used to compliment aquatic proxies by offering information on specific sources and diagenetic alteration of both aquatic and terrigenous contributions to the sedimentary record, thereby offering a more complete picture of paleoenvironmental conditions (Meyers and Ishiwatari, 1993). For example, molecular level organic matter proxies including bulk elemental ratios of total organic carbon: total nitrogen (C/N) and insoluble plant lipids tend to retain their source signatures in lake sediments, making them valuable indicators of past aquatic and terrestrial dynamics

(Meyers and Ishiwatari, 1993; Meyers, 1994). In addition, certain components of the lipid fraction of organic matter can be traced to the parent material (i.e., organic biomarkers), generating opportunities to infer past terrestrial and aquatic community and organism contributions from their molecular representation in lake sediments (e.g.,

Cranwell, 1973; Rieley et al., 1991; Bourbonniere and Meyers, 1996; Volkman et al.,

1998; Ficken et al., 2000). However, lipid analyses in Arctic settings has been largely restricted to marine and terrestrial environments (Yunker et al., 1995; Vonk et al., 2008,

Zech et al., 2010), and lacustrine-based studies are extremely rare (Routh et al., 2007,

Paulter et al., 2010), and it seems have yet to be conducted on High Arctic lake sediment sequences.

Nevertheless, assessing the molecular composition of organic matter is well suited to Arctic lake studies due to relatively limited microbial activity that results in a comparatively intact organic matter record compared to warmer and generally more

productive systems of lower latitudes (Kuder and Kruge, 1998). This is especially relevant to Arctic lacustrine systems characterized by low autochthonous productivity

(Karlsson et al., 2005) but surrounded by large stocks of terrestrial soil organic matter due to low rates of decomposition (Jahn et al., 2010). The fact that the terrestrial environment is likely more immediately sensitive to changes in prevailing climate and hydrological conditions compared to the more buffered lake ecosystem provides an opportunity to investigate the influence of changes in terrestrial inputs and hydrology on downstream ecosystems, thereby elucidating relationships between climate and hydrological change and aquatic ecosystem response. Moreover, despite the fact that

Arctic terrestrial-aquatic linkages have tended to be relatively simple due to the presence of permafrost and associated limits on subsurface flow, continued or accelerated degradation of permafrost is likely to have major implications for terrestrial and downstream aquatic ecosystems (Smith et al., 2005b, Hinzman et al., 2005; Walsh,

2005).

Justification of field site: a paired watershed approach

This research is focussed on two adjoining catchments (unofficially named West and East; 75°55’N, 109°35’W) near Cape Bounty, adjacent to Viscount Melville Sound on

Melville Island, in the Canadian High Arctic. This site was chosen because of the unique opportunity presented by neighbouring systems with similar physiographic features, characterized by the same vegetation, underlain by the same geology and subjected to the same climate conditions (see Chapters 2-4 for detailed site descriptions). Controlling for broad-scale influences such as geology and climate presents a rare opportunity to identify the relative influence of site-specific factors governing aquatic dynamics.

In addition to the advantages of using a paired watershed, the Cape Bounty field site is home to a range of ongoing research interests collectively concerned with improving understanding of the linkages between climate, hydrology, biogeochemical cycling and aquatic and terrestrial ecosystem processes. An international community of scientists and students are cultivating an inter-disciplinary body of literature focussed on the Cape Bounty Arctic Watershed Observatory (CBAWO), with a collective interest in better anticipating the implications of continued climate change on the High Arctic

(Lamoureux, 2011). Research at CBAWO began in 2003, making it the most comprehensive and continuous High Arctic monitoring and research station in existence.

Thesis hypothesis and research questions

The central hypothesis of this thesis is that the degree of coherency between two closely situated and physiographically similar lakes can be used to improve understanding of the sensitivity and possible future trajectories of Arctic aquatic ecosystems to hydroclimatic variability and change.

Fundamental to this hypothesis is a more comprehensive understanding of present ecosystem dynamics, which can then be used to refine paleoenvironmental interpretations and gain a longer term perspective on environmental variability and ecosystem response. As such, chapters 2 and 3 are focussed on the contemporary physio-chemical environment and diatom communities of each lake, and chapter 4 focuses on combining insights gained through modern day observations with the fossil diatom record and other independent proxy indicators from both aquatic and terrestrial sources to elucidate past ecosystem sensitivities and dynamics in order to better anticipate their future trajectories. An inherent objective of chapter 4 is to test the potential to make inferences of past terrestrial and aquatic dynamics based on the extractable lipid fraction contained in the sedimentary record, something that has yet to be explored in a High Arctic lake setting. The specific research questions of each of the three primary research chapters are as follows:

Chapter 2:

What are the limnological responses to intra- and inter-annual hydro-chemical

variability and what accounts for differences between the two systems?

Chapter 3:

What evidence is there of spatial and temporal variability within the lake diatom

assemblages and can these be related to physio-chemical variables and or

habitat specificity?

To what extent do the diatom communities differ between the lakes, and can

these differences be explained?

How faithfully does the modern diatom assemblage translate to deep lake

sediments where sediment cores are normally collected?

Chapter 4:

What does the fossil diatom record suggest about aquatic conditions spanning

from pre-industrial revolution times to the present?

Do climate records and independent proxy indicators including sedimentation

rates, C/N ratios, inferred-Chl-a, and terrestrial and aquatic lipids corroborate

these findings and do they provide further insight into past environmental

conditions?

What are the fundamental differences in long term responses between the two

lake systems and what does this suggest about possible future trajectories of

these and similar systems?

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Chapter 2:

Connections between river runoff and limnological conditions in adjacent High Arctic lakes: Cape Bounty, Melville Island, Nunavut

Kailey Stewart and Scott Lamoureux

Citation: Stewart, K.A., and Lamoureux, S.F. 2011. Connections between river runoff and limnological conditions in adjacent High Arctic lakes: Cape Bounty, Melville

Island, Nunavut. Arctic 64: 169–182.

Abstract

Hydrological and hydrochemical monitoring of paired watersheds in the High

Arctic was conducted in 2003-2004 to investigate the influence of seasonal runoff on lake water chemistry and productivity. Despite similar limnological conditions overall between the two lakes, marked differences in aquatic productivity were attributed to watershed and basin morphology and resultant influences on lake-ice deterioration and growing season length. A switch from allochthonous to autochthonous sources of carbon late in the season reflected the simultaneous decline in river runoff and increase in aquatic productivity as the growing season progressed. However, low air temperatures and protracted snowmelt and ponding in the deeply incised channel of one river in 2003 led to greater solute accumulation in runoff that was discernable in seasonal hydrochemical profiles of that lake, even though runoff was greater in 2004.

Notwithstanding, calculated nutrient fluxes were greater during the higher flow year

(2004), but mixing was impeded due to underflow conditions in the lakes. Despite these differences, connections between river and lake water chemistry appeared weak even with marked seasonal changes in the volume of runoff. Our results highlight the inter- connection between site-specific features and hydroclimatic factors like snowmelt and lake-ice conditions in influencing limnological conditions and suggest that similar systems may respond differently to the same hydroclimatic conditions.

Introduction

Knowledge about the potential impacts of climate change on northern freshwaters is insufficient, despite the fact that the Arctic is warming faster than anywhere else (White et al., 2007; ACIA, 2005). In particular, the sensitivity of Arctic aquatic ecosystems to changing hydroclimatic conditions is uncertain, and makes anticipating the response of these systems to continued climate change difficult. In spite of this, evidence of changing hydrologic conditions with direct implications for northern aquatic ecosystems is mounting, and includes changes in permafrost and active layer temperature and depth (Frauenfeld et al., 2004), glacial thickness and extent (Abdalati et al., 2004; Burgess and Sharp, 2004), the areal extent of lakes, ponds and wetlands

(Smol and Douglas, 2007; Walter et al., 2006; Smith et al., 2005), precipitation and winter snowcover (Serreze et al., 2002; Peterson et al., 2006), the timing of snowmelt and subsequent discharge patterns (McClelland et al., 2006; Déry and Wood, 2005), and changes to aquatic algal and invertebrate assemblages (Smol et al., 2005). Such changes, particularly in combination, are likely to fundamentally change water quality and alter the structure and function of Arctic aquatic ecosystems.

Although long term monitoring of Arctic freshwaters are generally lacking, recent efforts to document baseline physical and chemical limnology across the Canadian Arctic have been significant, particularly for small lakes and ponds (e.g., Douglas and Smol,

1994; Keatley et al., 2007). However, our understanding of seasonal changes in limnology and hydrochemistry of Arctic lakes remains limited (Forsström et al., 2007),

and may be key to understanding how aquatic ecosystems are likely to respond to future hydroclimatic change.

The importance of intra- and inter-annual changes in limnology may be especially relevant to high latitude systems, where extreme seasonality subjects aquatic ecosystems to a wide range of hydroclimate conditions over a relatively short growing season. The Arctic hydrological cycle is characterized by an intense spring runoff period caused by rapid melting of winter snowpack. In summer, typically low precipitation and reduced hydrologic connectivity due to greater soil storage mean that the bulk of runoff occurs during a brief spring freshet. Changes in catchment hydrology and the subsequent delivery of nutrients and other constituents to lake basins could impact aquatic ecosystems significantly, particularly in systems characterized by low productivity and oligotrophic conditions.

The purpose of this paper is to help address the aforementioned insufficiencies by i) documenting the physical and chemical limnology of two relatively large lakes and their major sources of inflow in the Canadian High Arctic; ii) identifying the influence of site specific factors and the range of hydrochemical responses generated by the same hydroclimatic conditions through comparison of two physiographically similar and adjacent catchments, and iii) assessing the limnological response to intra- and inter- annual hydroclimatic variability to help shed light on the sensitivity of High Arctic lake ecosystems to future hydroclimatic scenarios.

Materials and methods

Site description

Cape Bounty is situated on the south-central coast of Melville Island, in the

Canadian High Arctic (74°55' N, 109°35' W; Fig. 2.1). Bedrock geology consists of weathered Palaeozoic sand- and siltstones overlain by Holocene marine and glacial sediments (Hodgson et al., 1984). The study site lies in the area of continuous permafrost, with a maximum summer active (thawed) layer of <1 m. The catchments are composed of low relief (<120 m a.s.l.) hills with sparse vegetation cover characterized by dwarf-shrub tundra. Wet sedge meadow consisting primarily of bryophytes, cotton grass and sedges is found in moist low lying areas (Atkinson and Treitz, 2007).

Climate conditions consist of long, cold winters and short growing seasons with limited precipitation. Mean annual precipitation (1971-2000) at Mould Bay, Prince

Patrick Island (Fig. 2.1), approximately 200 km west of Melville Island, is 111 mm

(Meteorological Service of Canada, 2002), and falls predominantly as snow (October-

May). At Cape Bounty, snow surveys indicated a snow water equivalence of 43 mm and

82 mm for the West catchment in 2003 and 2004, respectively, and 20 mm and 41 mm in East catchment in 2003 and 2004, respectively (Cockburn and Lamoureux, 2008a).

The greater snowpack in the West catchment is attributed to the steeper gradient and consequently deeper gullies and channels where drifting snow disproportionately collects (Cockburn and Lamoureux, 2008a; McDonald and Lamoureux, 2009). Summer precipitation at Cape Bounty is limited to occasional low-intensity events, typically <10 mm∙day-1. At Mould Bay, mean daily temperatures range from –34°C in February, to 4°C

in July (Meteorological Service of Canada, 2002). At Cape Bounty, mean July air temperature was 4°C in 2003 and 2.5°C in 2004.

The study site consists of two adjacent and physiographically similar watersheds, unofficially named West and East (Fig. 2.1; Table 2.1). The West catchment is smaller and has a slightly steeper gradient with deeper channels and greater vegetative coverage (Atkinson and Treitz, 2007) than the East catchment. Both have tributaries that feed a principal stream flowing into the north end of the lakes. While the lakes are morphologically quite similar, East Lake is shallower than West Lake and has a greater surface area, resulting in a higher surface area to volume ratio (Table 2.1).

Sample collection

Water samples were systematically collected from the river gauging stations and moats of both lakes (Fig. 2.1) approximately every 5-6 days from snowmelt in late-June to early August in 2003 and 2004. Lake water samples were collected from moats rather than more centrally to capture conditions representing the most productive part of the lake. Moat widths increased through the season as lake ice diminished, from approximately 3 m to over 20 m by the end of the sampling period, but samples were consistently collected from 30 cm below the surface in approximately 1.5 m of water.

River samples were collected at or just below the water surface, dependent on stream depth. Samples were immediately partitioned and filtered following standard procedures outlined by Environment Canada (1994). Measurements of temperature, pH and conductivity were made in the field with an Orion 290A pH meter and YSI 30M EC meter, respectively (note that EC measurements are not available for 2003 due to

instrumentation problems). Analysis of major and minor ions (Ca2+, Mg2+, Na+, K+, Cl-,

SO42-), and trace metals (Ag, Al, As, B, Ba, Be, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, P, Pb, S, Sb,

Se, Si, Sn, Sr, Ti, Tl, U, V, Zn) were conducted by the Analytical Services Unit (ASU),

Queen’s University, Kingston, Ontario. Nutrient analyses conducted by the National

- Water Research Institute (NWRI) in Burlington, Ontario, included nitrate-nitrite (NO3

- - +NO2 ), nitrite (NO2 ), ammonia (NH3), total Kjeldahl nitrogen (TKN), total dissolved nitrogen (TN-F), particulate organic nitrogen (PON), soluble reactive phosphorus (SRP), total dissolved phosphorus (TP-F), total phosphorus (TP), particulate organic carbon

(POC), dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC). Analysis for chlorophyll-a (Chl-a; uncorrected) was conducted at the Canadian Museum of

Nature, Gatineau, Quebec. Subsequent calculations based on water chemistry results included dissolved organic nitrogen (DON) = TKN - NH3, dissolved inorganic nitrogen

(DIN) = NO3NO2 + NH3, total nitrogen (TN) = PN + NO3NO2 + TKN, and ratios of TN:TP (mg l-1), TN:TP (molar ratios), POC:PON (mg l-l) and POC:Chla (mg l-1).

Lake profiles of electrical conductivity were conducted on samples drawn at 1.5 m depth intervals from approximately the middle of the ice pan of both lakes using a

Kemmerer sampler and methods described above. Throughout the 2003 and 2004 hydrologic season, stream flow characteristics (e.g., discharge and water temperature) were monitored for both rivers and three meteorological stations recorded weather conditions (e.g., air temperature, precipitation; see Cockburn and Lamoureux (2008a) for hydrological and meteorological details).

Results

Seasonal hydroclimatic variability

Hydrographs for both seasons show the characteristic nival Arctic pattern, where the majority of runoff occurs at the beginning of the season with the onset of snowmelt, and rapid recession as the snowpack is exhausted. In 2003, initial flow and peak discharge occurred on June 19 and June 27 in East River and on June 25 and June 30 in

West River, with baseflow conditions being met in both rivers by the second week in July

(Fig. 2.2). In 2004, peak discharge occurred on June 25 and June 28 in both rivers, and receded to baseflow conditions by mid-July (Fig. 2.2). Maximum discharge was higher in both rivers in 2004, particularly in East River (1.8 m3 s-1 versus 0.9 m3 s-1 in 2003) compared to West River (1.6 m3 s-1 versus 1.2 m3 s-1 in 2003). Summer precipitation was limited to several low-intensity rainfall events that produced moderate discharge responses during both years (Fig. 2.2).

East River exhibited lower water temperatures than West River in both study years, but both rivers demonstrated a gradual increase to maximum values mid-season

(Fig. 2.2). The maximum water temperature recorded in 2003 was 5.3 °C for East River and 12.1 °C for West River. In 2004, the maximum recorded water temperatures were

7.1 °C and 10.0 °C for East and West Rivers, respectively. Note that the recording period for East River is shorter than for West, but likely still captures the maximum temperature period, as observed in the West River data. Air temperatures recorded at meteorological stations in both catchments indicate a seasonal maximum of 12.4 °C in

2003 and 7.3 °C in 2004, while mean daily July air temperatures were 4.0 °C and 2.5 °C

for 2003 and 2004, respectively. Air temperatures correlate well with data from the closest Meteorological Service of Canada stations at Rea Point, Nunavut to the east, and

Mould Bay, NWT to the northwest (Cockburn and Lamoureux, 2008a). Refer to Table 2.2 for a summary of some of the key climatic and limnological differences between the two study years.

Prior to the melt season, both lakes had ice covers in excess of 2 m thick. Open water moats formed with the onset of the melt season in both years, and a satellite image taken in late-August 2003 revealed that East Lake was completely ice-free whereas West Lake remained ~30% ice covered, despite a thicker initial ice-pan on East

Lake (2.3 m versus 2.0 m). Field observations from 2004 suggest a similar pattern of faster ice deterioration and ice-free conditions on East Lake.

Hydrochemistry

Since few records of seasonal hydrochemical variability in Arctic lakes exist, a comprehensive suite of measured variables is presented in Table 2.3. Both lakes and rivers were circum-neutral during the study period, with pH values ranging from 6.4 - 7.9 and a mean of 7.4 (Table 2.3). River and lake values in each catchment were similar, and there was little evidence of seasonal variability in pH, but mean values were higher in both lakes and rivers in 2004 compared to 2003. Electrical conductivity was higher in the lakes (mean = 45 μS cm-1, n = 14) than the rivers (mean = 27 μS cm-1, n = 14) and both

East River and Lake were higher than West River and Lake, respectively (Table 2.3). A seasonal pattern of high EC in early- to mid-July, followed by a sharp decline and then

gradual increase is apparent in both lakes, whereas river profiles are less variable, tending toward higher values as the season progresses (Fig. 2.3). Water column profiles of electrical conductivity taken in the middle of the lakes (Fig. 2.1) in early July were stable, with mean values of 55.7 μS cm-1 (SD = 2.4 μS cm-1) and 75.7 μS cm-1 (SD = 1.4 μS cm-1) for West and East Lakes, respectively (Fig. 2.3).

Ions and metals

In order of importance, mean concentrations of major cations and anions,

+ 2+ 2+ + - 2- respectively, were Na >Ca >Mg >K and Cl >DIC>SO4 (Table 2.3). Ions were marginally more concentrated in the lakes than the rivers, with the exception of DIC in the East catchment in 2003 (Table 2.3). Inter-annual variability was limited, with the

- 2- exception of higher mean lake Cl and SO4 concentrations in 2004 compared to 2003

(Table 2.3). River solute concentrations are not available for the peak discharge period in

2003, but 2004 concentrations were stable despite marked changes in river discharge

(Fig. 2.4). Of the 27 trace (dissolved) metals analyzed, those below detection levels

(0.005 mg l-1) in the majority of samples are not reported, leaving a subset of Al, Ba, Cu,

Fe, Mn, Sr, and Zn (Table 2.3). All values were within the range for Canadian surface waters (McNeely et al., 1979), and were relatively stable both intra- and inter-annually

(Table 2.3).

Major nutrients

Nutrient data indicate generally higher concentrations in West Lake compared to

East Lake. Conversely, East River was more nutrient-rich than West River, and overall higher concentrations were found in the rivers compared to the lakes (Table 2.3). With respect to nitrogen, TKN (a measure of reduced forms of nitrogen, principally ammonia and amino forms of organic nitrogen) was most abundant, followed by PON, NO3NO2, and NH3 (Table 2.3). Higher concentrations of NO3NO2 in West Lake compared to East

Lake were not reflected in the river data, where concentrations in East River exceeded those in West River. In 2003, high early season PON concentrations in West River coincide with the peak flow period, and lake concentrations also appear to be elevated during this time (Fig. 2.5). A similar early season increase in East River PON is not apparent, where sampling was initiated more than two weeks after peak flow.

However, sampling in East Lake in 2003 did capture the peak runoff period and PON concentrations remained stable during this period.

Seasonal profiles of nitrogen species reveal higher N concentrations (especially

PON) in both rivers that coincided with the peak discharge period. However, there is no evidence of this pattern in the corresponding lake profiles (Fig. 2.5). In both years DIN, which includes the most readily assimilated nitrogen forms (ammonia and nitrate) necessary for periphytic and macrophytic growth, are higher in West Lake than in East

Lake or either river (Table 2.3). Overall, a general trend toward declining TN-F concentrations throughout the season is apparent in the lake profiles of both years (Fig.

2.6a). No data are available for the peak discharge period in 2003, but 2004 TN-F

concentrations increased during the peak discharge period before tapering off through the remainder of the season for both rivers (Fig. 2.6a).

The majority of phosphorus was in particulate form, with higher concentrations in the river compared to lake samples (Table 2.3). Since most particulate phosphorus is unavailable for biological activity, SRP and dissolved P (TP-F) are more relevant when considering nutrient availability (EMAN-North 2005; Hamilton et al. 2001). The majority of SRP concentrations were at or below the detection level of 0.002 mg l-1. The mean

TP-F concentration was 0.009 mg l-1 and differed only marginally between sites.

However, both lakes and rivers had higher means in 2003 than 2004. Seasonal profiles are inconsistent, and except for West Lake in 2003, do not appear to be influenced by river discharge (Fig. 2.6b). Overall, concentrations span a range similar to a suite of 46 ponds and lakes sampled elsewhere on Melville Island (Keatley et al., 2007).

The most abundant carbon fraction for both rivers and lakes was DIC (mean = 3.2 mg l-1), followed by DOC (mean = 1.6 mg l-1) and POC (mean = 0.77 mg l-1; Table 2.3).

Mean DIC and DOC concentrations in the lakes and their respective rivers were similar for both years, whereas POC was consistently higher in the rivers relative to the lakes.

Carbon fractions are generally highest in early season, with greater seasonal variability in 2003 compared to 2004 (Fig. 2.6c, d).

Aquatic productivity

Lake Chl-a concentrations ranged from 0.48 to 1.91 μg l-1 (mean=1.12 μg l-1), and were substantially higher in East Lake (mean = 1.9 μg l-1) compared to West Lake (mean

= 1.0 μg l-1). Chl-a levels were also higher for both lakes in 2004 (mean = 1.8 μg l-1) compared to 2003 (mean = 1.1 μg l-1). In all cases, there is a gradual increase in lake Chl- a concentrations during the season, and all seasonal trends except West Lake in 2004 appear to be declining by the end of the sampling period (Fig. 2.6e). River Chl-a has been omitted due to the high error associated with the abundance of detrital matter in river runoff.

Nutrient ratios were calculated to provide insight into the potential controls on aquatic productivity. Mass ratios of TN:TP > 17 suggest the system may be P limited, whereas ratios <14 suggest N is the limiting nutrient (Downing and McCauley, 1992).

Ratios of TN:TP for Cape Bounty ranged from 6 to 55, with a mean of 19 (Table 2.3). For

Cape Bounty, 34% of samples suggested productivity would be limited by P but the greatest proportion of samples (39%) fell between 14 and 17, suggesting both P and N are in limited supply in these systems. When TN:TP molar ratios are considered

(Guildford and Hecky, 2000), over 70% of samples were either N or P limited, with a further 20% suggesting P limitation (<20 = N limited, 20-50 = either N or P limited, >50 =

P limited; Table 2.3).

Discussion

Regional controls on limnology

Chemical analyses of the lakes indicate generally similar limnological conditions.

Compared to many Arctic regions, the Cape Bounty lakes are less alkaline due to the absence of carbonate bedrock that predominates through much of the region. In

addition, conductivity measurements indicate that the Cape Bounty lakes are dilute

(mean = 37 µS∙cm-1) compared to data from elsewhere in the region (e.g., Antoniades et al., 2003a; Hamilton et al., 2001; Lim et al., 2001), including 46 shallow lakes and ponds from Melville Island (Keatley et al., 2007). This is likely due to the combined effect of relatively large catchments that drain more sparsely vegetated upland areas and rapid runoff of dilute snowmelt that limits contact time with potential solutes (Schindler et al.,

1974a; Lim et al., 2001). Relatively sparse catchment vegetation is also suggested by low

DOC values (Pienitz et al., 1997), which are considerably lower at Cape Bounty (1.6 mg l-

1) than the mean for small lakes and ponds across Melville Island (5.45 mg l-1; Keatley et al., 2007) and on other islands in the Canadian Arctic Archipelago (Lim et al., 2005;

Antoniades et al., 2003a; Hamilton et al., 2001; Lim et al., 2001). In addition, lower DOC values are often reported for larger and/or more sparsely vegetated areas (Keatley et al.,

2007; Michelutti et al., 2002a; Antoniades et al., 2003b; Lim and Douglas, 2003; Lim et al., 2001). A significantly higher DOC value (10.4 mg l-1) obtained from a pond situated on a more densely vegetated plateau between the lakes (unpublished data, Fig. 2.1), further supports this conclusion. Low dissolved organic carbon concentrations at Cape

Bounty suggest an increased susceptibility to UV-B penetration (Pienitz and Vincent,

2000) than is typically found in Arctic lakes and ponds (Lim and Douglas, 2003; Hamilton et al., 2001; Antoniades et al., 2003b; Michelutti et al., 2002a), although there are exceptions associated with sparsely vegetated catchments and/or deeper basins where

DOC is more dilute (Lim et al., 2005; Lim et al., 2001; Keatley et al., 2007).

The prominence of Cl- and Na+ in lakes and ponds across Melville Island (Keatley et al., 2007) extends to Cape Bounty, and may reflect the proximity of sites to the coast and the resulting influence of sea spray (Wetzel, 2001). Alternatively, the Cape Bounty watersheds contain widespread ground ice, and late summer melt of the ice has mobilized water with high solute levels (Lafrenière and Lamoureux, unpublished data) which could be derived from the widespread marine sediments below c. 100 m above sea level.

While larger Arctic lake systems tend to be more nutrient limited and have reduced productivity when compared to smaller aquatic systems (Hamilton et al., 2001), this is not exclusively the case at Cape Bounty. For example, the mean TKN (generally the most abundant biologically available nitrogen species) concentration in the Cape

Bounty lakes was lower (0.171 mg l-1) than found in small lakes and ponds surveyed across Melville Island, Banks Island, Bathurst Island and elsewhere in the eastern Arctic

Archipelago (Hamilton et al., 2001; Lim et al., 2001; Lim et al., 2005; Keatley et al., 2007), but higher than mean values from small lakes and ponds from Victoria Island, Ellef

Rignes Island, and Devon Island (Michelutti et al., 2002a; Antoniades et al., 2003b; Lim and Douglas, 2003). Phosphorus is more difficult to compare due to extremely low soluble concentrations and susceptibility to contamination, but mean total dissolved phosphorus concentrations (9.25 μg l-1) in the Cape Bounty lakes were comparable to smaller lakes and ponds from Melville Island (Keatley et al., 2007) and Victoria Island

(Michelutti et al., 2002), but above mean concentrations from other Arctic island sites

(e.g., Hamilton et al., 2001; Lim et al., 2001; Antoniades et al., 2003a; Lim and Douglas,

2003; Lim et al., 2005).

Allochthonous and autochthonous sources of particulate nutrients

Particulate nutrient concentrations, as indicated in PN, POC and TP fractions, were within the range of reported Arctic sites, but more likely reflect the greater potential for transport associated with a high energy spring runoff than smaller systems where autochthonous productivity plays a larger role. This is also suggested by higher particulate concentrations in the river compared to the lake samples. In addition,

POC:Chl-a ratios (mean = 555) suggest a predominantly allochthonous carbon source

(i.e., >100; Eppley et al., 1977), with the exception of the last sample in East and West

Lake in 2004 (i.e., the only samples with ratios <100). A higher proportion of allochthonous organic carbon is commonly found in Arctic freshwater systems with low aquatic productivity (e.g., Hamilton et al., 2001; Lim et al., 2001; Keatley et al., 2007).

The shift to a predominantly autochthonous carbon source at the end of the 2004 sampling period is attributed to minimal runoff inputs and increased lake productivity with diminished ice cover. Generally lower ratios of POC:Chl-a in East Lake compared to

West Lake might be a response to the earlier deterioration of lake ice and larger littoral zone in East Lake, resulting in more of the most productive area of the lake being exposed sooner. The late season change to predominantly autochthonous carbon is not apparent in the 2003 samples, but sampling concluded approximately one week earlier

and ice-cover persisted longer than in 2004. However, a trend is apparent toward lower

POC:Chl-a ratios through the 2003 season.

Controls on aquatic productivity

Calculated TN:TP ratios did not conclusively point to either N or P as limiting, and suggest that an increase in one or the other would not be sufficient to boost productivity. The relatively high TN:TP ratios at Cape Bounty are common in oligotrophic systems and reflect the nutrient sources of undisturbed watersheds, which export more

N than P (Downing and McCauley, 1992). Poor correlations between N or P and Chl-a in lakes and ponds across the High Arctic are common and point to factors other than nutrient limitation as controls on primary productivity (e.g., Lim et al., 2001; Antoniades et al., 2003a; Keatley et al., 2007). A surprisingly muted diatom response to major nutrient enrichment due to sewage inputs in Meretta Lake strongly suggested that physical factors including prolonged lake ice cover were ultimately controlling productivity (Douglas and Smol, 2000; Michelutti et al., 2002b). At Cape Bounty, higher nutrient concentrations and lower Chl-a levels in West Lake compared to East Lake suggest likewise. Although parallel increases in Chl-a and air temperature further suggest temperature may be controlling productivity, Chl-a concentrations were higher in 2004 when mean air and water temperatures for the sampling period (2.3 °C and 1.9

°C, respectively) were lower compared to 2003 (4.1 °C and 2.5 °C, respectively). Hence, we propose that greater inflow and consequently earlier ice break-up in 2004 advanced and prolonged the lake growing season resulting in greater aquatic productivity. In

addition, greater turbulence due to higher discharge likewise produced a more favourable environment for planktonic productivity.

Chl-a levels from East Lake were almost twice those of West Lake in both years.

Field observations indicate the presence of a late lying snowbank that drains through a densely vegetated slope on the north shore of East Lake, and more frequent observations of fish along this shore area provide anecdotal support that East Lake is more productive. Despite this, nutrient concentrations are higher in West Lake which may be attributed to a more vegetated West catchment (Atkinson and Treitz, 2007) and associated potential for greater nutrient transport. However, this explanation is not supported by our data, which indicate higher nutrient concentrations in East River than

West River. Instead, higher Chl-a levels and lower nutrient concentrations in East Lake suggest nutrients were more readily sequestered for primary production than in West

Lake (Wetzel, 2001). This is further supported by higher levels of DIN, the most readily assimilated forms of nitrogen (NO3+NO2 + NH3), in West Lake in both years.

Basin morphology might account for the difference in lake productivity, as East

Lake is slightly shallower and has a greater surface area than West Lake. As a result, water temperatures are higher and the littoral zone notably broader than in West Lake.

In addition, East Lake experienced greater inflow and earlier lake-ice deterioration and break-up, thus gaining pelagic habitat sooner and for longer each growing season than

West Lake. Hence, the hypothesis that higher discharge and earlier ice break-up in 2004 resulted in greater primary productivity (Chl-a) than in 2003 is further supported by the fact that productivity was higher in East Lake compared to West Lake in both years.

Our observations support the strong influence of lake ice on Arctic aquatic productivity proposed by Brylinski and Mann (1973) and advanced by Smol (1983).

Climate amelioration and associated changes in the length of the growing season are considered the primary cause of recent changes in algal and invertebrate assemblages across the circumpolar Arctic (Smol et al., 2005). Aquatic ecosystem changes associated with other factors, such as elevated atmospheric nitrogen deposition, have also been attributed to a synergistic effect with warmer climatic conditions (Wolfe et al., 2006).

However, distinct responses to nutrient enrichment without apparent changes in ice cover have also been observed (e.g., Schindler et al., 1974a; Douglas et al., 2004), suggesting that productivity is limited but not exclusively controlled by lake ice conditions.

The influence of river runoff on lake water chemistry

An influx of dilute runoff during the peak flow period did not dilute the lake water, which was more solute rich than the rivers. The gradual increase in river solute concentrations through the 2004 season, despite a decline in discharge, revealed an inverse relationship commonly observed in Arctic catchments (e.g., Stewart et al., 2005).

This implies the spring freshet is not an important mechanism for solute delivery.

However, gradual increases in solute concentrations over the season were offset by higher spring discharge, and resulted in the highest flux rates of solutes occurring early in the season. In other systems, the limited impact of inflow on lake solute concentrations has been attributed to dilute runoff not readily mixing with denser

solute-rich lake water below, instead travelling over or just under the lake ice and eventually lost as outflow (Schindler et al., 1974b; Bergmann and Welch, 1985). At Cape

Bounty, density differences likewise inhibited mixing, but in this case high spring discharge and suspended sediment concentrations generate underflow conditions

(Cockburn and Lamoureux, 2008b). The impact of subsequent increases in solute concentrations in runoff as the melt season progressed were mitigated by a decline in discharge (i.e., reduced solute fluxes), thus minimizing the impact of increased mixing on lake concentrations as the lake ice disappeared.

The dilute nature of snowmelt captured in the 2004 seasonal trend of electrical conductivity in river runoff was likewise not reflected in the lake water chemistry.

Whereas seasonal trends in ion concentrations were more subtle and gradual, lake specific conductance indicated a distinct early season peak. The subsequent melting of dilute lake ice and influx of dilute runoff might account for the sharp decline in lake conductivities mid-season. A trend toward higher conductivities late in the season likely reflected greater exposure to melting channels and slopes, combined with mixing and loss to outflow of dilute lake ice. The absence of higher conductivity water at depth than at the surface in the lake profiles may be the result of profiles having been collected early in the season while the lakes were still largely ice-covered.

Nutrient flux calculations for 2004 demonstrate a strong seasonal pattern that paralleled discharge, but as was the case with ions and electrical conductivity, fluxes were not reflected in lake concentration changes (Fig. 2.7). In addition, seasonal changes in river particulates (PON, POC, TP) did not translate to the lakes. These findings were

consistent with the relatively large existing stocks of nutrients in the lakes compared to seasonal river influxes. However, we know that allochthonous contributions were the primary source of organic carbon to the lakes, and evidence of the hydrologic inflows can be seen in nutrient trends from 2003, particularly for West Lake (Fig. 2.6).

Melt intensity and lake water chemistry

The apparent connection with river runoff in 2003 and disconnection in 2004 may be in response to the damming and ponding of snowmelt which delayed streamflow in

West River in 2003. Flow began almost one week later in West River compared to East

River in 2003 due to lower melt temperatures which resulted in greater ponding behind snow dams in the more deeply incised channel of West River (Cockburn and Lamoureux,

2008a). In contrast, higher melt temperatures in 2004 produced a rapid melt that initiated stream flow without significant ponding, thus overriding differences in channel morphology. As a result, the timing of initial stream flow, peak discharge, and return to baseflow conditions were similar in East and West River in 2004.

Slower melting and subsequent ponding due to low melting temperatures in

2003 increased the contact time with solutes while maintaining hydrological connectivity over a greater proportion of the catchment for longer, thus producing a more solute-rich runoff. The important role of melt intensity is also evident in higher particulate nutrient (POC, PON) concentrations in West River and Lake samples in 2003 compared to 2004, and stable particulate nutrient concentrations in the East catchment samples between the two years, despite notably higher discharge in 2004.

The differential response in lake water chemistry between the two years suggests that melt intensity is an important mechanism for the delivery of nutrients to the basin.

Nevertheless, calculated turnover rates of water and nutrients demonstrate a strong sensitivity to annual discharge, whereby replacement times based on 2003 data are approximately twice as long as with 2004 data (Table 2.4). Hence, slower melt and ponding in the channel had a discernable impact on the surface water chemistry, but overall nutrient fluxes were higher with increased discharge, albeit as underflows and not immediately available in the photic zone. As such, the implications of hydroclimatic change for the aquatic ecosystems may be different over different timescales.

Evidence suggests that the character of spring runoff has changed in recent decades (Déry and Wood, 2005; Serreze et al., 2002). Advances in the timing of stream flow may be accompanied by a less intense melt due to lower early season melt temperatures, resulting in greater nutrient fluxes. Conversely, higher temperatures and a more rapid melt may lead to a fragmented snowpack, thus diminishing the spatial extent and connectivity of runoff, and reduce the potential for nutrient transport. These hydrological factors will be balanced against a greater availability of nutrients due to enhanced terrestrial productivity and a deeper active layer, changes in soil storage, and enhanced snow ablation and melt season evapotranspiration. Opposing trends in nutrient delivery, suspended sediment concentrations and lake turbidity hold additional implications for the lake ecosystem through changes in allochthonous nutrient contributions, lake mixing and nutrient resuspension, and light regimes and UVB exposure.

Conclusions

Both East and West Lake are relatively dilute and have low nutrient concentrations due to the combined effects of the majority of runoff occurring while the ground is still frozen, and the relatively short growing season and lake-ice cover, which limit nutrient recycling and productivity. Differences between the Cape Bounty lakes and other Arctic sites are largely explained by geological setting and basin and catchment morphology.

Though similar, important differences between the two systems exist and may lead to a differential response to changing hydroclimatic conditions. The influence of channel morphology on the timing and intensity of runoff appears to be dependent on melt conditions. Whereas a less intense melt season in 2003 resulted in more melt water ponding in the deeper channels of West River and a delay in spring runoff compared to

East River, a more intense melt in 2004 initiated stream flow rapidly and produced very similar discharge patterns in both catchments. In addition, slower melt conditions and subsequent ponding in 2003 (which increased nutrient accumulation in stream water) had a discernable impact on seasonal lake nutrient trends, particularly in West Lake.

Despite this, overall nutrient fluxes were higher in 2004 when discharge was greater, but underflow conditions prevented immediate mixing with surface waters. Hence, the importance of melt conditions and site specific controls (i.e., channel morphology) relative to discharge, differ in the two basins over the short and long term, with uncertain implications for the aquatic ecosystem.

Differences in basin morphology dictated the timing of ice break-up and revealed the greater potential for primary productivity in East Lake. A longer ice-free season may elevate the importance of nutrient availability, and shift greater productivity to West

Lake. Furthermore, a trend toward earlier, more protracted melt seasons that result in greater channel ponding might further enhance productivity in West Lake compared to

East Lake.

Acknowledgements

We are grateful for the financial support of a NSERC PGS-D scholarship and

Northern Studies Training Programme (NSTP) funding to KAS, and NSERC Discovery and

ArcticNet NCE grants to SFL. We gratefully acknowledge the logistical support provided by the Polar Continental Shelf Project (PCSP publication # 04709). We are grateful to

Paul Hamilton at the Canadian Museum of Nature for conducting chlorophyll analysis.

We would also like to thank Greg McQuat for providing lake volume and surface area data. Field assistance by J. Cockburn, D. MacDonald, E. Wells, G. Hambley, D. Atkinson,

F. Forsythe and J. Wall is sincerely appreciated.

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Figures

Figure 2. 1 Location of the Cape Bounty field site on Melville Island in the western Canadian Arctic Archipelago (inset). The location of Environment Canada meteorological stations at Mould Bay on Prince Patrick Island, and Rea Point on Melville Island are also indicated. The main map shows the delineation of the two catchments and locations where meteorological, river and lake data were collected (see legend).

Figure 2. 2 Seasonal stream flow (discharge and temperature) and meteorological data for West and East Rivers in 2003 and 2004. Note that East Lake 2003 hourly discharge prior to June 29th has been omitted due to the initial location of the stilling well, but manual rating curves indicated peak discharge occurred on June 27 (asterisk).

Figure 2. 3 Seasonal trends of specific conductance for West and East River and Lake for 2004. Asterisks indicate when depth profiles of specific conductivity (inset) were collected for East and West Lake (July 3 and 4, respectively).

Figure 2. 4 Seasonal trends of major ions for West and East Lake in 2003 and 2004, and West and East River in 2004. Solid lines in river profiles represent discharge (Q).

Figure 2. 5 Seasonal distribution of nitrogen species in East and West Lake and River for 2003 (upper panels) and 2004 (lower panels). Note the scale is different for East River in 2004. Solid line plots represent river discharge (Q).

Figure 2. 6 Seasonal trends of major nutrients and Chl-a in lakes and rivers during the 2003 (left panels) and 2004 (right panels) seasons. Note that river Chl-a measurements are not included due to abundant particulate mineral and organic matter on filters during high flow periods that precluded accurate Chl-a measurements.

Figure 2. 7 Seasonal trends of river discharge and nutrient fluxes (a) and lake nutrient and Chl-a concentrations (b) for 2004. TN-F and TP-F nutrient fluxes were calculated with mean daily Q. Note that TP-F concentrations in panel a) were multiplied by a factor of 10 for the purpose of figure clarity.

Tables

Table 2. 1 Physical and chemical attributes of the Cape Bounty lakes (2003-4).

West Lake East Lake Catchment area (km2) 8 11.6 Lake area (km2) 1.4 1.6 Lake volume (m3) 2140 2090 Surface area/volume .065 .076 Maximum depth (m) 35 32 Mean depth (m) 15.3 13.1 Mean water temp (°C) 1.1 2.7 Littoral zone (km2)* .32 .44 Mean TN-F (mg l-1) .26 .17 Mean TP-F (mg l-1) .011 .008 Mean Chl-a (µg l-1) 1.0 1.85 Mean pH 7.3 7.3 Conductivity (µS cm-1) 38 52 Ice off Persistent Mid-August ice-pan

*Littoral zone is defined as the surface area corresponding to a lake depth of 5 m or less (i.e., area of the 0-5 m bathymetric contour interval).

Table 2. 2 A summary of key differences between the two years studied. Plus signs (+) indicate the year in which the variable is greater.

2003 2004 Mean June air temperature* - + Mean July air temperature + - Snow water equivalence - + Snowmelt rate - + Maximum discharge - + Total runoff - + River solute concentrations + - Nutrient fluxes - + Mean river temperature + - Mean lake Chl-a - + Mean lake TN-F + - Mean lake TP-F + - Mean lake DOC + - *represents snow melt period

6.500

1.700

3.155

3.700

2.900

3.386

4.100

2.800

3.357

3.800

1.900

2.486

3.300

1.700

2.386

4.200

3.300

3.713

6.500

2.900

4.300

4.100

2.600

3.013

3.600

2.000

2.633

DIC

4.200

0.800

1.604

1.700

1.100

1.343

2.700

1.100

1.771

2.300

1.100

1.386

2.200

1.400

1.700

2.500

1.000

1.688

3.200

0.800

1.533

4.200

1.000

1.775

2.000

1.200

1.583

DOC

4.300

0.152

0.766

0.620

0.228

0.518

2.230

0.464

1.208

0.784

0.152

0.358

1.520

0.296

0.764

0.680

0.352

0.479

1.700

0.632

0.960

2.500

0.264

0.739

4.300

0.336

1.237

POC

, unless otherwise not otherwise ,unless

0.057

0.001

0.027

0.028

0.014

0.022

0.039

0.002

0.028

0.031

0.001

0.021

0.057

0.004

0.031

0.035

0.015

0.027

0.037

0.024

0.030

0.045

0.028

0.035

0.031

0.028

0.029

0.019

0.004

0.009

0.011

0.008

0.010

0.005

0.007

0.010

0.005

0.009

0.008

0.005

0.007

0.019

0.009

0.013

0.012

0.005

0.008

0.010

0.008

0.009

0.008

0.004

0.006

0.805

0.056

0.315

0.234

0.056

0.192

0.532

0.281

0.370

0.341

0.079

0.261

0.805

0.291

0.438

0.164

0.001

0.012

0.003

0.001

0.009

0.001

0.003

0.004

0.001

0.002

0.164

0.001

0.041

0.119

0.001

0.026

0.006

0.003

0.004

0.015

0.002

0.006

0.002

0.004

0.387

0.003

0.071

0.018

0.006

0.014

0.065

0.004

0.041

0.039

0.003

0.022

0.268

0.026

0.076

0.126

0.027

0.060

0.260

0.054

0.167

0.387

0.046

0.166

0.249

0.053

0.147

0.038

0.001

0.007

0.009

0.001

0.005

0.038

0.001

0.011

0.024

0.001

0.009

0.010

0.001

0.006

0.010

0.002

0.007

0.002

0.015

0.003

0.007

0.002

0.096

0.002

0.035

0.048

0.029

0.037

0.053

0.011

0.036

0.043

0.028

0.032

0.096

0.002

0.036

0.046

0.014

0.033

0.047

0.033

0.038

0.062

0.022

0.034

0.035

0.029

0.033

0.323

0.004

0.071

0.043

0.004

0.032

0.113

0.014

0.073

0.076

0.008

0.046

0.178

0.047

0.085

0.092

0.028

0.050

0.144

0.042

0.102

0.323

0.037

0.121

0.141

0.056

0.097

6.77

1.34

3.40

5.89

4.49

5.47

2.65

1.61

2.01

4.33

2.74

3.98

2.31

1.34

1.58

6.77

4.12

5.85

2.73

1.39

2.06

4.49

2.21

3.73

1.57

1.37

1.45

2.94

0.65

1.60

2.25

1.70

2.07

2.09

1.22

1.56

1.52

0.98

1.41

1.17

0.73

0.95

2.54

2.23

2.35

2.94

1.17

1.86

2.00

1.50

1.67

1.33

0.65

0.96

1.003

0.278

0.577

0.931

0.565

0.717

0.714

0.404

0.533

0.659

0.486

0.583

0.451

0.293

0.359

0.827

0.633

0.733

1.003

0.417

0.654

0.924

0.462

0.653

0.339

0.278

0.316

4.31

0.89

2.17

3.11

2.11

2.64

2.70

1.30

2.04

2.10

1.04

1.75

2.17

1.00

1.42

4.31

2.86

3.39

4.29

1.68

2.71

2.34

2.06

2.18

2.25

0.89

1.45

4.16

0.31

2.31

4.16

3.26

3.77

2.75

2.00

2.23

4.09

2.28

3.21

2.75

1.88

2.25

3.88

0.33

1.05

1.77

0.33

1.02

3.40

0.31

1.89

1.60

0.91

1.22

9.74

1.01

4.16

9.74

6.74

8.52

3.15

2.00

2.45

9.50

4.30

6.72

2.68

1.73

2.02

8.18

1.35

2.75

3.10

2.10

2.51

7.34

1.01

3.48

1.85

1.15

1.41

-1

83.7

20.6

35.9

83.7

31.8

52.1

31.7

23.3

29.1

56.6

23.8

38.0

34.9

20.6

24.5

EC EC

7.9

6.4

7.4

7.7

6.6

7.4

7.9

7.3

7.5

7.4

7.9

6.4

7.3

7.5

7.2

7.3

7.6

7.3

7.5

6.8

7.1

7.5

7.1

7.3

Summary of 2003 and 2004 water chemistry results for Cape Bounty. All units are mgl are All units Bounty. Cape for results water chemistry and2004 2003 of Summary

Table 2. Table

2003 West2003 R.

max

min

mean

All

max

min

mean

2004 East2004 L.

max

min

mean

2004 East2004 R.

max

min

mean

2004 West2004 L.

max

min

mean

2004 West2004 R.

max

min

mean

2003 East2003 L.

max

min

mean

2003 East2003 R.

max

min

mean

2003 West2003 L.

max

min mean

555

272

221

769

373

821

184

418

285

5086

1208

POC:Chla

POC:PON

121

mol

TN/TP TN/TP

TN:TP

-1

1.91

0.48

1.12

3.02

1.74

2.38

1.86

0.48

1.15

1.91

0.58

1.32

1.42

0.49

0.85

ug l ug

Chl-a Chl-a

0.074

0.005

0.021

0.015

0.005

0.008

0.047

0.018

0.032

0.017

0.006

0.011

0.074

0.013

0.034

0.022

0.011

0.014

0.053

0.019

0.029

0.060

0.011

0.022

0.039

0.021

0.028

0.030

0.002

0.009

0.007

0.004

0.005

0.014

0.003

0.006

0.015

0.002

0.008

0.015

0.003

0.009

0.013

0.009

0.011

0.017

0.009

0.012

0.030

0.009

0.013

0.008

0.010

TP-F

0.007

0.000

0.001

0.007

0.000

0.002

0.004

0.000

0.001

0.000

0.004

0.000

0.001

0.002

0.000

0.001

0.000

0.002

0.000

SRP

0.670

0.000

0.230

0.263

0.169

0.225

0.650

0.267

0.430

0.360

0.228

0.296

0.531

0.186

0.318

0.262

0.158

0.219

0.498

0.327

0.387

0.670

0.224

0.357

0.545

0.174

0.313

0.392

0.012

0.081

0.068

0.020

0.050

0.221

0.056

0.146

0.072

0.012

0.032

0.192

0.040

0.083

0.056

0.024

0.042

0.224

0.048

0.124

0.224

0.016

0.062

0.392

0.032

0.129

PON

0.368

0.005

0.169

0.105

0.151

0.368

0.127

0.234

0.209

0.005

0.117

0.295

0.005

0.176

0.189

0.107

0.156

0.300

0.122

0.196

0.294

0.110

0.166

0.191

0.109

0.158

DON

0.280

0.003

0.057

0.035

0.005

0.022

0.173

0.012

0.049

0.129

0.044

0.100

0.080

0.006

0.039

0.043

0.003

0.021

0.092

0.038

0.067

0.280

0.040

0.128

0.061

0.003

0.025

DIN

0.446

0.110

0.220

0.179

0.110

0.152

0.366

0.144

0.242

0.280

0.182

0.231

0.301

0.121

0.203

0.214

0.139

0.180

0.378

0.188

0.267

0.446

0.223

0.296

0.252

0.153

0.186

TN-F

0.414

0.110

0.191

0.177

0.110

0.158

0.414

0.127

0.246

0.216

0.115

0.171

0.313

0.140

0.210

0.204

0.115

0.170

0.334

0.156

0.221

0.309

0.121

0.184

0.246

0.134

0.178

TKN

0.055

0.005

0.018

0.014

0.005

0.009

0.046

0.016

0.027

0.013

0.005

0.009

0.029

0.006

0.017

0.020

0.008

0.016

0.046

0.010

0.025

0.039

0.005

0.018

0.055

0.007

0.024

0.009

0.001

0.002

0.008

0.001

0.003

0.001

0.002

0.003

0.001

0.002

0.003

0.001

0.002

0.003

0.001

0.002

0.005

0.002

0.004

0.009

0.001

0.004

0.003

0.001

0.002

0.241

0.005

0.054

0.035

0.018

0.023

0.157

0.012

0.044

0.117

0.038

0.094

0.061

0.020

0.034

0.024

0.005

0.010

0.077

0.009

0.042

0.241

0.019

0.110

0.019

0.005

0.010

Continued

3. 3.

max

min

mean

All

max

min

mean

2004 East2004 L.

max

min

mean

2004 East2004 R.

max

min

mean

2004 West2004 L.

max

min

mean

2004 West2004 R.

max

min

mean

2003 East2003 L.

max

min

mean

2003 East2003 R.

max

min

mean

2003 West2003 L.

max

min

mean

2003 West2003 R. Table Table

Table 2. 4 Replacement time for lake water and dissolved nitrogen and phosphorus stocks. Calculations were based on 2003 and 2004 mean fluxes of water and nutrients from the principal streams relative to measured lake volume and nutrient concentrations.

West Lake East Lake

2003 2004 2003 2004

Lake water (yrs) 38.6 22.4 28.0 16.7

TN-F (yrs) 61.5 25.5 18.9 10.5

TP-F (yrs) 50.2 19.9 25.7 13.9

Chapter 3:

Seasonal and microhabitat influences on diatom assemblages and their representation in sediment traps and surface sediments from adjacent High Arctic lakes: Cape Bounty, Melville Island, Nunavut.

Kailey Stewart and Scott Lamoureux

Submitted to Hydrobiologia.

Abstract

The spatial (i.e., microhabitat) and temporal (i.e., seasonal) characteristics of diatom assemblages in adjacent High Arctic lakes were studied intensively June-August

2004. These baseline data are intended to improve understanding of modern diatom community dynamics, as well to inform paleoenvironmental reconstructions. Diatoms were collected approximately weekly through the melt season from each principal benthic substrate (moss/macrophyte, rock scrapes, littoral sediment), plankton, and sediment traps, and were compared to the uppermost 0.5 cm of a surface core obtained from the deepest part of the lake where sediment cores are routinely collected. Water samples were collected concurrently with diatom samples to investigate species- environment relationships. The two study lakes share approximately half of their common taxa, the most abundant overall in both lakes being small Cyclotella species.

Results of detrended correspondence analysis (DCA) indicate that the largest gradient in species turnover existed between benthic and planktonic communities in both lakes, and that sediment trap and the surface core top samples most closely resemble the planktonic assemblage, with an additional contribution from the lotic environment. Our results suggest a degree of disconnection between the benthos and deep lake sediments that manifests as an under-representation of benthic taxa in deep lake surface sediments. These findings are particularly relevant in the context of interpreting the paleoenvironmental record and assessing ecosystem sensitivity to continued climate change.

Introduction

Despite intensifying research efforts devoted to Arctic environmental change, a need remains for detailed understanding of how Arctic aquatic ecosystems respond to environmental variability and change. One approach is to use proxy indicators to reconstruct past environmental conditions and ecosystem responses. Diatoms, a class of siliceous algae that are ubiquitous in freshwater environments, have proved successful as indicators of limnological conditions owing to the fact that many taxa have specific ecological requirements (Smol & Stoermer, 2010). In lake and pond sediments, diatoms are generally well preserved and relatively easy to identify to the species level.

Therefore, fossil diatom analysis is suitable to reconstruct environmental conditions in areas where monitoring data cover short time periods or are unavailable. Developing long term records of environmental conditions and ecosystem dynamics is crucial for anticipating how aquatic ecosystems might respond to continuing environmental change, and diatoms in particular have been instrumental in recording post-industrial circumpolar changes to Arctic aquatic ecosystems (Smol et al., 2005).

In recent years, a vast amount of information on species occurrence and associated limnological conditions across environmental gradients has been collected and a number of key controls including pH, salinity, conductivity, nutrient status, temperature, ice-cover and substrate availability have been identified (Battarbee et al.,

2001, and references therein, Lim et al., 2001; Michelutti et al, 2003; Smol et al., 2005;

Fritz, 2008; Soininen & Weckström, 2009; Smol & Stoermer, 2010). Associations between these environmental controls and diatom species have been used to infer past

environmental conditions through the use of multivariate analyses, such as transfer functions, which distil modern limnological conditions across numerous lakes or ponds down to a single predictive variable (Birks, 1998). However, marked shifts in modern day assemblages of Arctic lakes and ponds, likely in response to rapid environmental change, may produce assemblages bearing little resemblance to past communities, i.e. non- analogue species, rendering transfer functions unfeasible. In addition, this method does not consider the role of seasonal changes, microhabitat structure and other unmeasured variables and multi-variable interactions (Sayer et al., 2010). Furthermore, the fact that many diatom taxa are cosmopolitan, and at the same time completely different taxa can be found in closely situated lakes bearing strong physico-chemical resemblance (e.g.,

Keatley et al., 2008), suggests that regional lake datasets should be complimented with more intensive single-system based research, in order to more fully understand species- environment relationships and ecology.

In response to such limitations, single-site investigations focussed on seasonal and inter-annual timescales are increasing in frequency with important new insights being revealed (e.g., Lotter & Bigler, 2000; Rautio et al., 2000; Köster & Pienitz, 2006;

Kirilova et al., 2008; Sanchez-Castillo et al., 2008; Sayer et al., 2010; Woodbridge &

Roberts, 2010). For example, how sporadic single-species algal blooms can distort paleoenvironmental interpretations based on the analysis of bulk (i.e., multi-year) sediment samples (Woodbridge & Roberts, 2010). However, more information is needed, particularly from the High Arctic where environmental change is accelerated

(ACIA, 2005), and from lakes, which are relatively unstudied compared to the more common pond setting.

Until recently, consideration of taphonomic processes and how prevailing diatom communities translate to bottom sediments has been largely restricted to marine (e.g.,

Zielinski and Gersonde, 1997) and deep lake systems (e.g., Ryves et al., 2003). Few lake studies have considered the extent to which the sediment record is an accurate representation of the diatom community corresponding to that time (Ryves et al., 2009;

Woodbridge & Roberts, 2010). One way to do this is by deploying sediment traps into the lake water column to see how the modern lake community is integrated into the sedimentary record over discrete time intervals (Battarbee et al., 2001). Some recent studies that employed sediment traps underscore the value of this approach and the risk of bias in interpretations of integrated sediment samples when seasonal and depositional processes are not considered (Koster & Pienitz, 2006; Woodbridge &

Roberts, 2010).

The purpose of this study was to assess the modern ecological controls on the diatom communities of two adjacent High Arctic lakes by examining spatial (i.e., between microhabitats and between lakes) and temporal (i.e., seasonal) patterns in the assemblages, so that subsequent paleoenvironmental reconstructions may be refined.

Specifically, we aimed to i) gain insight into site-specific controls on the diatom assemblages; ii) identify any species or groups of species that demonstrate clear microhabitat preferences or seasonal patterns in abundance; iii) identify species- environment relationships; and iv) determine how the lake diatom community is

represented in material deposited in the deepest part of the lake, where sediment cores are routinely collected. We address these aims in the context of adjacent paired High

Arctic lakes that exhibit similar limnological conditions. A paired watershed approach holds the advantage of controlling for broad scale physical (e.g., climate, geology) and biotic (e.g., dispersal) influences, thus generating an opportunity to discern site-specific environmental controls.

Site Description

The study site consists of adjacent (~ 1 km apart) lakes (unofficially named West and East Lake) in separate catchments located near Cape Bounty on south-central

Melville Island (74°54’N, 109°35’W), in the Canadian Arctic Archipelago (Fig. 3.1). The major physical and chemical characteristics of the two lakes are summarized in Table

3.1. Despite some differences, the two lakes are similarly sized, relatively deep, circumneutral, oligotrophic, and both are situated close to the coastline (Fig. 3.1). See

Stewart & Lamoureux (2011; Chapter 2), for detailed limnological data for the Cape

Bounty lakes and their major sources of inflow.

Surrounding the lakes, the landscape is characterized by low-relief plateaus and hills with a maximum elevation of 125 m above sea level. Surface vegetation typical of polar desert tundra (bryophytes, sedges and grasses) is sparse throughout the catchments and primarily restricted to plateaus and low lying areas directly adjacent to the lakes. Surface geology consist of Late Glacial and Holocene glacial and marine

sediments overlying Devonian sandstone and siltstone bedrock that has similar exposure in both catchments (Hodgson et al., 1984).

Cape Bounty is located in the zone of continuous permafrost, and has a typical maximum active layer thickness of approximately 50 cm. Meteorological Service of

Canada (2002) records from Mould Bay, Prince Patrick Island (approximately 200 km west of Cape Bounty) indicate a mean daily temperature (1971-2000) ranging from -34

°C in February to 4 °C in July. At Cape Bounty, mean daily July temperatures were 4 °C in

2003 and 2.5 °C in 2004. Mean annual precipitation at Mould Bay is 111 mm, the majority of which occurs as snow. Snow is significantly redistributed into depressions and channels, particularly the deeply incised channels of the West catchment, due to frequent high winds (Cockburn & Lamoureux, 2008a). The melt season is confined to

June – August, and the majority of runoff occurs during a brief, intense period of snow melt in late June and early July. By late July, flow is restricted primarily to infrequent low intensity rain events (<10 mm/day), as permafrost essentially precludes subsurface flow. Prior to the melt season, ice-cover on both lakes is in excess of 2 m thick. Open water moats form with the onset of the melt season, and by the end of the 2004 June -

August field season East Lake was completely ice-free, whereas West Lake remained

~30% ice-covered.

Materials and Methods

Sample collection

In an effort to capture the whole-lake diatom community, littoral samples collected from moss/macrophytes (M), rock scrapes (R) and littoral sediment (S) substrates, as well as plankton (P) samples and mid-lake sediment trap (T) samples were collected at approximately one-week intervals during the majority of the melt season from late June to early August 2004, for a total of 34 samples from each lake (Fig. 3.1).

As ice likely began to re-form in late August, several weeks of open water conditions are not accounted for in the current dataset, due to logistical constraints. Additionally, as a result of rapidly fluctuating lake water levels, a complete absence of moss or macrophytes around the collection area of West Lake on August 6 precluded this sample from being collected, and unsafe ice conditions on East Lake precluded an August 6 sediment trap sample from being collected. Moss, rock and sediment samples were collected from approximately a 3 m2 area below the water surface at the lake margin and consisted of either three submerged moss/macrophyte specimens (approximately 5 cm long), three rocks (approximately 10-20 cm in diameter) brushed with a toothbrush, or three samples of littoral sediment (approximately 2 g each), all of which were deposited into 20 ml scintillation vials. Plankton samples were collected approximately 3 m from the shoreline at a depth of 30 cm in 1 L Nalgene bottles, and through several steps of settling overnight and decanting, were transferred to 20 ml scintillation vials.

Sediment traps spanning sampling dates (June 23 - August 6) were collected on the same day as the benthic and planktonic samples. Sediment trap samples were

collected by suspending 50 ml centrifuge tubes attached to the mouth of an inverted 2 L plastic bottle funnel with the base removed to provide an opening for the sediment to collect (Cockburn & Lamoureux, 2008b) approximately 0.5 m from the bottom of the lake in the deepest part of the basin (Fig. 3.1). Weights suspended below the trap kept the trap in place and vertical. All samples were subsequently topped with filtered water and several drops of Lugol’s solution were added as a preservative.

A surface sediment sample (0-0.5 cm depth) representing recent (approximately

5 years) depositional conditions was obtained from a short gravity sediment core collected with an Aquatic Research Instruments corer from the sediment trap location prior to the 2005 (West Lake) and 2007 (East Lake) melt seasons. The cores were immediately stabilized by removal of surface water and the use of hydrophilic floral foam at the sediment surface to absorb water. Cores were stored vertically for seven days, further dewatered, and transported to the laboratory in the vertical position.

To investigate the relationships between the diatom community and physical and chemical limnological conditions, lake-water samples were collected in 1L Nalgene bottles that were pre-cleaned and then rinsed three times with lake water immediately before sample collection. Samples were collected concurrent with the littoral and planktonic diatom samples and filtered and partitioned upon return to camp following standard Environment Canada (1994) procedures. Full details of hydrochemical methods are presented in Stewart and Lamoureux (2011; Chapter 2). Briefly, temperature, pH and conductivity were measured in situ with an Orion 290A pH meter and YSI 30M EC meter,

2+ 2+ + + - 2- respectively. Major and minor ions (Ca , Mg , Na , K , Cl , SO4 ), and trace metals (Ag,

Al, As, B, Ba, Be, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, P, Pb, S, Sb, Se, Si, Sn, Sr, Ti, Tl, U, V, Zn) were analyzed by the Analytical Services Unit (ASU), Queen’s University, Kingston,

- - - Ontario. Nutrient analyses included nitrate-nitrite (NO3 +NO2 ), nitrite (NO2 ), ammonia

(NH3), total Kjeldahl nitrogen (TKN), total dissolved nitrogen (TN-F), particulate organic nitrogen (PON), soluble reactive phosphorus (SRP), total dissolved phosphorus (TP-F), total phosphorus (TP), particulate organic carbon (POC), dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC), and was conducted by the National Water

Research Institute (NWRI) in Burlington, Ontario. Analysis for chlorophyll-a (Chl-a; uncorrected for phaeophytin) was conducted at the Canadian Museum of Nature,

Gatineau, Quebec.

Diatom processing and microscopy

Due to the difficult task of establishing absolute numbers of cells/valves in substrate samples (particularly rock scrapes and macrophyte samples) only relative abundance data were calculated. For diatom analysis (following Wilson et al., 1996), approximately 5 ml of each of the benthic, planktonic and sediment trap samples, and approximately 0.3 g of dry sediment from the surface sediment core, were placed in a 50 ml centrifuge tube and digested overnight with 15 ml of 50:50 molar ratio of sulphuric and nitric acids. To ensure complete digestion of organic matter, samples were then heated in a water bath for a minimum of two hours at approximately 90 °C. Samples were centrifuged and rinsed repeatedly in distilled water until a neutral pH was obtained. Samples were topped to 20 ml with deionised water and several dilutions

were dispersed onto coverslips and left to dry overnight. Dried samples were mounted onto microscope slides using Zrax, a mounting medium with a high refractive index suitable for observing diatoms under light microscopy. A Zeiss Axio Imager A1 microscope with differential interference contrast (DIC) optics was used to identify and count diatom valves. A minimum of two transects, corresponding to 400-800 total valves, were counted for each sample. Reference material for taxanomic identification included Fallu et al. (2000), Krammer & Lange-Bertalot (2004, 2007), and Antoniades et al. (2008).

Numerical analyses

Microhabitat diversity (i.e., richness and occurrence) and seasonal changes in species diversity in each microhabitat was assessed using Shannon’s Index (Krebs, 1999).

To investigate the influences of microhabitat and other environmental factors on the diatom assemblages of the two lakes, detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) using the program CANOCO 4.5 (ter Braak &

Šmilauer, 2002) were employed. A DCA of species and samples indicates a first axis gradient length of 3.74 SD for West Lake and 2.83 SD for East Lake, revealing a relatively high degree of species turnover within each lake (Table 3.2). These gradient lengths suggest unimodal (e.g., Canonical Correspondence Analysis) rather than linear (e.g.,

Principal Components Analysis) methods are appropriate (Jongman et al., 1995) for investigating species-environment relationships. A Monte Carlo permutations procedure

was used to investigate the statistical significance of the effects of the environmental variables.

Prior to statistical analyses, diatom taxa were pre-screened and only taxa with relative abundances of 1% or greater in at least one microhabitat (macrophyte/moss, rock, littoral sediment, plankton, sediment trap, surface sediment) per lake were retained for the analyses. In West Lake, 42 out of 192 taxa met the criteria, and accounted for an average of 77% of the total assemblage (Table 3.3), and in East Lake

180 taxa were reduced to 37, accounting for approximately 70% of all counted valves

(Table 3.4). Diatom relative abundances were square-root transformed with rare species down-weighted. Environmental variables were transformed prior to statistical analysis using either log(x+1) (DOC, DIC, Chl-a, O2, pH, EC, CaCO3, Cl, SO4, Ca, K, Mg, Na, mean river water temperature, mean air temperature) or log(10x+1) (SiO2, Al, Ba, Cr, Cu,

Fe, Mn, Sr, Zn, Ni, NO2NO3, NH3, TKN, TN-F, DIN, DON, PON, TN, SRP, TP-F, TP, mean discharge). In order to reduce the overall number of environmental variables to as few as could best describe the variability in the data, a Pearson Product Moment correlation matrix was constructed to identify significantly (p<0.05, one tailed test of significance) correlated variables and reduce the number to a subset of representative variables.

Based on a sample size of n=7 and p<0.05, variables were deemed highly correlated if r≥

0.87. A CCA with forward selection was performed and variables with the highest

Variance Inflation Factors (VIFs) were systematically eliminated until all VIFs were less than five, and so that no more than n-1 (i.e., 6) variables remained (i.e., fewer than the number of samples collected). This resulted in the variables TP-F, DOC, POC, SiO2, and

EC for West Lake, and TN-F, DIC, DOC, SiO2, pH, EC for East Lake. Monte Carlo permutations were used to assess the significance of the explanatory power of each remaining variable.

Results

Hydrochemistry

The following is a brief overview of conditions at Cape Bounty during the Jun -

Aug 2004 field season. See Stewart and Lamoureux (2011) for a detailed analysis of hydrochemical conditions during the 2003 and 2004 seasons. Seasonal profiles of selected biologically important chemical variables are depicted in Figure 3.2. Despite extreme changes in runoff through the sampling period, most limnological variables remain relatively stable in both lakes. Both lakes have a mean pH of 7.4, although East

Lake demonstrates more seasonal variability than West Lake. Measurements of electrical conductivity were higher in East Lake (mean=52 µS cm-1) than in West Lake

(mean=38 µS cm-1), but both lakes followed a similar seasonal trend. In order of importance, mean concentrations of major cations and anions, respectively, were

+ 2+ 2+ + - 2- Na >Ca >Mg >K and Cl >DIC>SO4 . Metals above the instrumental detection limit included Al, Ba, Cu, Fe, Mn, Sr, and Zn, all of which were within the range for Canadian surface waters (McNeely et al., 1979), and were stable throughout the season.

With respect to lake nutrient conditions, TKN (a measure of reduced forms of nitrogen, principally ammonia and amino forms of organic nitrogen) was most abundant,

- - followed by PON, NO3 +NO2 , and NH3. DIN (which includes ammonia and nitrate, the

most readily assimilated forms of nitrogen for periphytic and macrophytic growth) was higher in West Lake than in East Lake. The majority of phosphorus was in particulate form and therefore largely unavailable for diatom growth. SRP concentrations were at or below the detection level of 0.002 mg l-1. Mean seasonal concentrations of TP-F were slightly higher in West Lake (0.008 mg l-1) than East Lake (0.005 mg l-1), and are within the range reported from numerous ponds and lakes located elsewhere on Melville Island

(Keatley et al., 2007). Low mean DIC concentrations (2.5 mg l-1 in West Lake, 3.4 mg l-1 in

East Lake) reflect the lack of carbonate bedrock and the poor buffering capacity of these lakes. Mean DOC fractions were similarly low, even by Arctic standards, in both lakes

(1.4 mg l-1 in West Lake and 1.3 mg l-1 in East Lake), indicative of the sparse catchment vegetation and low productivity of these deep, polar systems with relatively small photic zones compared to smaller lakes and ponds. Mean seasonal Chl-a concentrations in East

Lake (2.38 μg l-1) were roughly double those of West Lake (1.15 μg l-1), but both lakes exhibited a gradual rise through the sampling period with evidence of a decline in Chl-a in East Lake in the final sample collected (Aug 6).

Diatom flora

A similar number of taxa were recorded in West Lake (192) and East Lake (180) contemporaneous samples, including 137 species (24 of which are considered common taxa: >1% abundance) represented in both lakes and 235 species identified in total. No taxa dominate either of the contemporary lake assemblages, although Cyclotella psuedostelligera reached almost 50% in plankton samples from West Lake and Cyclotella

rossii reached over 40% in plankton samples from East Lake (Tables 3.3, 3.4). However, in the surface core samples C. pseudostelligera had a relative abundance of 66% in West

Lake and C. rossii represented over 50% of the assemblage in East Lake (Tables 3.3, 3.4).

Shannon Diversity is similar in West Lake (2.8) compared to East Lake (2.7), and in both cases is higher than the sediment core sample (2.1 and 2.2 for West and East Lake, respectively). In both lakes the highest diversity was recorded in littoral sediment samples and the lowest diversity in plankton samples (Tables 3.3, 3.4). A series of t-tests conducted on the seasonal datasets indicate significantly different diversities occur between rock and plankton and littoral sediment and plankton communities in West

Lake, and between plankton and all littoral samples (M, R, S), and between sediment trap and moss, littoral sediment and plankton sampes in East Lake (Table 3.5). Temporal changes in species diversity within the major sample types demonstrate no consistent trends between the two lakes over the sampling period (Fig. 3.3).

Seasonal profiles of the common species provide a picture of temporal trends and microhabitat preferences among taxa (Fig. 3.4a, b). In the West Lake samples,

Diatoma tenuis, Diadesmis gallica and Diatoma contenta are well represented in the littoral (M, R, S) substrates compared to the plankton or trap samples. Conversely, C. psuedostelligera and C. rossii demonstrate much higher abundances in the plankton and trap samples compared to the littoral environment, as do Sellaphora pupula and

Hannaea arcus, to a lesser extent. The remainder of common species appears to be more closely linked to the littoral environment, with the possible exception of

Achnanthidium minutissimum, which is represented in all sample types. Though difficult

to discern unequivocally given the small dataset and shortness of the growing season, some taxa do appear to exhibit seasonal trends. For example, D. tenuis and D. contenta are most abundant at the beginning of the sampling period, whereas D. gallica and

Fragilaria capucina var. capucina are more competitive mid-season, and Nitzschia perminutum and A. minutissimum demonstrate their greatest abundances later in the season.

Seasonal profiles of common species from East Lake indicate a similarly clear relationship between C. pseudostelligera, C. rossii and the planktonic and trap environments, as do Nitzschia acicularis and Fragilaria capucina var. gracilis, albeit at lower abundances. Fragilaria tenera is more closely associated with the littoral environment, and appears to be more competitive later in the season. Conversely,

Pinnularia obscura is most abundant in the moss samples early in the season. Another notable feature of the East Lake seasonal profile is the greater abundance of Achnanthes daonensis and Gomphonema parvulum var. micropus in rock scrape samples. Finally, a number of small taxa from the Achnanthes sensu lato genus appear to be most closely aligned with the sediment samples, including Achnanthes helveticum, Achnanthes rupestris, Psammothidium chlidanos, Psammothidium marginulatum and Rossithidium petersenii.

Possible affinities between diatom species and microhabitats were further explored with DCA. The percent variance explained by the first ordinal axis was 35% and

34.2% for West and East Lakes, respectively. In a bi-plot of species and samples from

West Lake, the first axis is characterized by diatom species C. psuedostelligera, C. rossii

and Achnanthes nitidiformis to the far right (high on axis 1), and taxa including Hanzschia amphioxys, Muelleria gibbula and D. gallica to the far left (Fig. 3.5a) (low on axis 1).

Similarly, the East Lake bi-plot places C. pseudostelligera and C. rossii to the far right, as well as N. acicularis, and F. capucina var. gracilis, and Navicula bjoernensis, P. obscura,

Pinnularia subrostrata and Eunotia arcus occupy the far left of the ordination space (Fig.

3.5b). A comparison with the seasonal and microhabitat distributions of these taxa suggest the first axis represents a microhabitat gradient, with littoral species to the left and planktonic species to the right. A notable vertical spread in species scores is also apparent in the bi-plots of both lakes. Axis 2 explains approximately 10% of the variability in species data in both datasets, and is characterized by Pinnularia interupta,

D. gallica and A. rupestris toward the top, and Pinnularia krammeri Psammothidium kryophilum, and Cymbella lapponica toward the bottom for West Lake, and F. tenera, D. tenuis and C. lapponica toward the top, and G.parvulum var. micropus and A. daonensis toward the bottom of the axis for East Lake. Seasonal trends among these taxa suggest that this axis represents a temporal gradient.

A combined lake DCA with envelopes (i.e., polygons) encompassing each of the sample types from each lake more clearly demonstrates a first ordinal axis gradient representing microhabitat for both lakes, with benthic assemblages to the left and planktonic and trap assemblages to the right, while the second axis represents a broader site gradient separating West from East Lake assemblages (Fig. 3.6a). For clarity, species are shown in a separate bi-plot (Fig. 3.6b). In both lakes sediment trap and core samples are closely aligned with plankton samples and there is a clear separation between

benthic and planktonic habitats (Fig. 3.6a). Overlap between the earliest plankton sample (JN28) and littoral samples in the West Lake ordination coincides with the period of maximum discharge, and is most likely a reflection of turbulent conditions and possible resuspension of littoral valves and transport from the lotic environments by underflows (Cockburn & Lamoureux, 2008b). This effect is not apparent in our East Lake dataset, most likely due to the greater distance between stream outlet and sampling site. DCCA tri-plots constrained to microhabitat support the claim that the strongest gradient in species composition relates to microhabitat over the time frame investigated

(Fig. 3.7a, b).

Multivariate statistics were used to explore whether any of the measured environmental variables could significantly explain seasonal variability within the diatom community (Fig. 3.8a, b). Results of a CCA indicate that no variables were significant (α=

0.05) in explaining the variability of species data within the datasets. This is likely due to the small environmental gradients among measured variables from each of the lakes.

Very low inertia values (i.e., variance in the dataset; West Lake = 0.280, East Lake =

0.238) attest to the low variability in both lake datasets. As a result, the power of CCA to explain variation in the dataset with respect to environmental variables is limited. In addition, the relatively high species turnover (indicated by DCA first axis gradient lengths; Table 3.2) suggest factors other than those measured exert a greater influence on the diatom communities through the growing season.

We hypothesized that sediment trap samples should represent an integration of the whole lake diatom community and should be most closely aligned with the sediment

core samples. In West Lake, C. pseudostelligera and C. rossii make up approximately 11% and 4% respectively of the moss, rock, sediment and plankton communities combined, whereas trap samples demonstrate abundances of 34% and 17% and core samples demonstrate abundances of 66% and 14%, respectively (Table 3.3). In East Lake, these same taxa represent 3% and 30% of benthic/planktonic communities, 22% and 26% of the trap assemblage and 28% and 51% of the core assemblage (Table 3.4). In both lakes the most dominant taxa exhibit a relative abundance in the core samples that is twice that of the trap samples, and in both cases abundances are more closely aligned with the plankton samples (Fig. 3.9). In addition to the most abundant Cyclotella taxa, West

Lake species including D. tenuis, D. contenta and D. gallica are under-represented in trap samples and the surface core sample and, to a lesser extent, H. arcus, A. nititdiformis and S. pupula are over-represented in trap samples, though not in the surface core sample (Table 3.3, Fig. 3.9a). In East Lake, A. daonensis, A. helveticum, F. tenera, P. marginulata and P. obscura are under-represented in the trap and core samples, whereas N. acicularis is over-represented in trap samples, but not in the core sample

(Table 3.4, Fig. 3.9b). Finally, in East Lake Fragilaria capucina var. gracilis is over- represented in the core sample compared to any of the lake or sediment trap samples

(Table 3.4).

Discussion

Similarity of diatom floras

The close proximity and similarity of West and East Lake is reflected in the distinct resemblance of the two diatom assemblages. Diversity is roughly the same in both lakes, and approximately 50% of common taxa are shared by both lakes. Not surprisingly, littoral sediment samples from both lakes presented the greatest species diversity, as this substrate is both a microhabitat and an accumulation zone for dead cells from other microhabitats. It is also not surprising that moss and sediment samples have more species in common than rock and sediment samples, since the growth and movement of plants would dictate a less stable environment for diatom colonization

(Cetin, 2008, and references therein).

Results of DCAs indicate that the greatest pattern of variation in species composition in both lakes relates to spatial (i.e., benthic versus planktonic habitats) and then temporal (i.e., seasonal succession) factors over the three month time period investigated. As would be expected, there is a high degree of overlap among littoral habitats, attributed to both a lack of habitat specificity, and to the greater potential for cell contamination within a small spatial area. While limited, there does appear to be temporal structure in the datasets of both lakes. DCA axis 2 represents approximately

10% of the variation in species data in each of the lake datasets, but comparison of the seasonal changes suggests that axis two represents a temporal gradient. However, for both lakes the vast majority of species cluster close to the first axis, suggesting temporal patterns in abundances are limited compared to spatial patterns.

A clear seasonal pattern in species diversity is also not apparent. One exception is the littoral sediment samples, which demonstrate an overall seasonal increase in diversity that most likely represents a combination of the development of the existing community and the seasonal accumulation of dead cells from other substrates.

However, typically species diversity is expected to increase through the season as growing communities enhance the dimensionality of existing substrates (Douglas &

Smol, 2010). However, prolonged ice cover (a perennial ice pan in the case of West

Lake) and oligotrophy may have tempered the seasonal progression toward more complex diatom communities. The extent of oligotrophy has been associated with slower colonization and development of benthic communities in English lakes (King et al., 2006), and a greater number of stages of algal succession were observed in more eutrophic systems in a series of Swiss peri-alpine lakes (Anneville et al., 2004). Also, productivity under such extreme environmental conditions may have been insufficient to exert an influence on nutrient concentrations, which has the potential to drive cyclical patterns in species abundances (Kilham et al., 1996).

In both lake assemblages the most abundant taxa overall were small Cyclotella species, though these were primarily confined to sediment trap and plankton samples.

Typically, planktonic species play a minor role in High Arctic freshwater systems, attributed to the shallowness of many systems with insufficient vertical space to support planktonic communities, and prolonged ice-cover which limits light penetration in the pelagic zone compared to littoral areas (Smol, 1988; Michelutti et al., 2007). In the Cape

Bounty Lakes neither of these issues appears to be a factor, where both lakes support

strong planktonic communities despite samples having been collected in the shallow moat area, and considering the prolonged ice-cover (including a perennial ice-pan in

West Lake). Cyclotella species also dominate the surface sediment assemblage of another lake on Melville Island (Keatley et al., 2008), and are common in High Arctic lake sediments in Greenland (Cremer & Wagner, 2004).

The planktonic dominance in the Cape Bounty lakes is consistent with mounting observations across the circum-polar Arctic of expanding planktonic communities most likely in response to enhanced thermal stratification and/or reduced length of ice-cover

(Sorvari & Korhola, 1998; Sorvari et al., 2002; Rühland et al., 2003; Rühland & Smol,

2005; Rühland et al., 2008; Adams & Finkelstein, 2010), although not all occurrences of small Cyclotella species in Arctic lakes are recent (Cremer & Wagner, 2004). However, the presence of small Cyclotella species in a West Lake sediment core is confined to within the last half century (Kirk et al., 2011; Stewart and Lamoureux, in preparation).

However, the fact that both Cyclotella species appear to be represented in across littoral microhabitats suggests that conditions favourable for Cyclotella were not necessarily limited to the pelagic environment. Their competitiveness in the benthic environment is in agreement with other reports of tychoplanktonic Cyclotella in the Arctic, though in these cases specifically associated with either rock (Lim et al., 2001) or moss substrates

(Michelutti et al., 2003).

Site-specific differences

Notable differences between the two lake assemblages existed and appeared to be strongly influenced by immediate conditions at the sampling sites. In particular, the closer proximity of the sampling location relative to the river outlet in West Lake likely subjected the littoral environment to conditions more closely aligned with the lotic environment. For example, A. minutissimum and H. arcus, both common in West Lake littoral samples, are associated with lotic environments elsewhere (Ludlum et al., 1996;

Beyens & Van de Vijver, 2000; Antoniades & Douglas, 2002; Stewart et al., 2005), but were not common in East Lake. However, both species are present in the East Lake assemblage, and demonstrate their highest abundances in sediment trap samples, suggesting they achieve greater success outside the sampling location, such as the stream or delta areas, or are washed in from elsewhere in the catchment. In the case of

West Lake, proximity to the stream may mean a greater potential for accumulating transported cells, or that conditions in this location were similar enough to the stream environment to support analogous communities.

The West Lake assemblage was also characterized by species competitive in a range of niches, possibly reflecting the more dynamic local environment of this sampling site. Characteristic littoral species from West Lake included D. tenuis, D. gallica and D. contenta, which demonstrated similar abundances in all littoral habitats, suggesting these species are habitat generalists. D. tenuis, D. contenta and D. gallica were all common in High Arctic stream assemblages (Antoniades et al., 2009), and D. tenuis and

D. contenta have been noted as common in pond and small lake systems elsewhere in

the Arctic (Lim et al., 2007), including Melville Island (Keatley et al., 2008). The more generalist autecology of these species might explain why, although they were more abundant in West Lake, they were also competitive in East Lake. That said, F. tenera, which was most abundant in moss and rock samples from East Lake and was virtually absent from West Lake samples, has also been identified as a common species in High

Arctic stream assemblage (Antoniades et al., 2009), though its strong presence among both the plankton and benthos of other High Arctic lakes (Cremer & Wagner, 2004) and across all sample types in East Lake, suggests this species can succeed in various microhabitats.

Relative to the more dynamic environment in West Lake, the East Lake littoral community is suggestive of more stable conditions. For example, there appeared to be more temporal structure among the East Lake assemblage (e.g., F. tenera, P. obscura, G. micropus var. parvulum, A. daonensis), suggesting a degree of algal succession that may have been facilitated by greater stability of substrates not replicated in West Lake. In particular, abundances of G. parvulum var. micropus and A. daonensis on East Lake rock substrates demonstrate a distinctly seasonal pattern unparalleled in West Lake. G. parvulum is known to be an early colonizer that adheres directly to surfaces, as are short-stalked Achnanthidium species (Hoagland et al., 1982; King et al., 2006), and we would expect evidence of succession to be more likely on stone surfaces, given their greater stability compared to either sediment or moss. Generally, algal succession is impeded by disturbance (King et al., 2006), and in West Lake conditions associated with being closer to the stream outlet, and perhaps confined by a more proximal ice pan,

would likely introduce a level of disturbance related to sedimentation, resuspension, and water transparency not found at the East Lake sampling site.

Other notable taxa from East Lake littoral sediments are suggestive of fluctuating water levels. For example, P. obscura, which is abundant in early season moss samples, was a common species in High Arctic stream assemblages (Antoniades et al., 2009) though in East Lake the sampling location is far from the primary inflowing stream.

However, P. obsura is also associated with terrestrial mosses from northeast Greenland

(Van Kerckvoorde et al., 2000), suggesting it may be competitive under fluctuating water levels, such as along stream banks and lake margins. Transitional areas subjected to fluctuating water levels may also explain the success of P. marginulatum in East Lake, a recognized aerophilic taxa, including in the High Arctic (Michellutti et al., 2007). The more extensive littoral shelf of the East Lake basin in the location where samples were collected dictates that any change in water level would impact a larger spatial area compared to West Lake, and thus would be more likely to favour species adapted to changing water levels than the West Lake site.

Species-environment relationships

Though diatoms are known to be sensitive to changing water chemistry, including pH, nutrient concentrations, salinity and ice-cover (Battarbee et al., 2001; Smol et al.,

2005; Smol & Stoermer, 2010), it appears that conditions within the Cape Bounty lakes did not change sufficiently during the season to be a major control on the diatom communities. Aquatic environmental data from 2003 is similarly stable throughout the

open water season (Stewart & Lamoureux, 2011). The absence of a relationship between seasonal diatom dynamics and environmental conditions is not unique to Cape

Bounty (Soinenen & Eloatra, 2004; Duncan & Blinn, 1989) and even regional studies of suites of lakes from the High Arctic report water chemistries lacking enough variability to be the principal control on diatom species compositions (Michelutti et al., 2007).

However, it is also possible that the influence of environmental variability is simply undetectable under the current sampling design and that relationships may be evident at finer or broader temporal and spatial resolutions (Soinenen & Eloantra, 2004).

Alternatively, species-environment relationships may be obscured by different pore- water chemistry and resultant influences on the littoral sediment community (King et al.,

2006). Nevertheless, it is likely that additional factors are controlling species dynamics, and that relatively minor changes in chemical conditions may have been overwhelmed by more extreme fluctuations, such as the extent and duration of ice cover and light penetration (e.g., Lotter & Bigler, 2000) in controlling diatom populations.

Implications for paleoenvironmental reconstructions

In the Cape Bounty lakes, trap and sediment core samples are not a true representation of the whole lake diatom communities. The over-representation of

Cyclotella species, which are most abundant in plankton samples, reflects the more direct depositional path between plankton and lake bottom, despite the fact that plankton samples were collected in the lake moat in close proximity to the littoral samples. Higher abundances of Cyclotella species in the core samples compared to the

trap samples suggests they are either more dominant during the interval represented by the sediment, or that continued expansion of the planktonic environment and community as the lake ice retracted and, in the case of East Lake, disappeared, after the sampling season had resulted in greater overall abundances in the core samples. The apparent over-representation of planktonic taxa is accompanied by an under- representation of key benthic species in trap and core samples (e.g., D. tenuis, D. gallica and D. contenta in West Lake, A. daonensis, A. helvetica, P. marginulatum, F. tenera and

P. obscura in East Lake), suggestive of a less efficient pathway between the littoral environment and the lake bottom.

Taxa from the sediment traps that do not appear to be strongly connected with the plankton or benthos (e.g., H. arcus, A. nitidiformis, S. pupula in West Lake, and N. acicularis in East Lake) may represent alternative depositional pathways, such as from the delta or stream environment, or elsewhere in the catchment. S. pupula is a recognized taxon from the region (Bouchard et al., 2004) and not uncommon in the epipelon of lotic environments (Mann & Droop, 1996). H. arcus has also been associated with lotic assemblages elsewhere in the Arctic, as have small Achnanthes taxa, though we are not aware of any reports of A. nitidiformis specifically (Ludlum et al., 1996;

Antoniades & Douglas, 2002; Stewart et al., 2005). It is not surprising that small

Achnanthes species might be competitive in lotic environments, owing to the mucilage stocks or prostrate manner in which they adhere to substrates (Soininen & Eloatra,

2004). N. acicularis has been associated with river delta areas and more recently has transitioned to form a major component of the Lake Baikal (Siberia) plankton, a change

which has been attributed to anthropogenic forcings (Bondarenko, 1999). However, all of these species are absent or demonstrate very low abundances in the sediment core samples, suggesting their representation in 2004 sediment trap samples reflected sporadic blooms that did not translate to the aggregate sediment samples and/or were diluted by late season productivity. Similarly, the over-representation of Fragilaria capucina var. gracilis in the East Lake core sample compared to any of the lake or sediment trap samples may mean the growth of this taxon was either suppressed during the 2004 season or is successful later in the growing season after sampling had concluded (Table 3.4).

Overall, the under-representation of distinctly benthic taxa in sediment trap samples suggests a degree of disconnection between the littoral and deep basin environments. It is unlikely that the under-representation of these species is attributed to dissolution, given the contribution of lotic taxa and the greater distance associated with their deposition at the lake bottom. Though in smaller systems with no significant source of inflow sediment samples can offer a reliable integration of lake habitats (e.g.,

Michelutti et al., 2003), clearly larger more complex systems necessitate a more comprehensive understanding of depositional processes.

The contribution of apparently lotic taxa to the sediment traps suggests that river discharge is an important depositional mechanism for diatom valves, and that the sedimentary record may reflect an integration of species from the broader catchment.

While the traps are not an absolute reflection of the sedimentary environment, analysis of the uppermost 0.5 cm of sediment (~5 years) from cores collected from the deepest

parts of West and East Lake reflect a community dominated by the same Cyclotella species, and more closely resembles the 2004 trap communities than either the benthic or plankton communities. Woodbridge & Roberts (2010) observed disproportionate plankton taxa relative to benthic taxa in sediment traps resulting from short lived planktonic blooms occurring only in certain years. They caution that such high magnitude but infrequent events could overwhelm aggregated sediment samples and mislead paleoenvironmental interpretations. Similarly, Hausman & Pienitz (2009) observed disproportionate abundances of benthic species in sediment traps from boreal lakes that they attributed to sediment resuspension. In the case of Cape Bounty, it appears that the delivery of valves from the various microhabitats is a function of both the transport potential (i.e., movement of water) and life strategies (i.e., freely motile or adherent) of individual species. As a result, we predict an apparent over-representation of planktonic taxa in the longer sedimentary record, especially those with an affinity for lotic environments, and an under-representation of species that attach to benthic substrates and are more competitive under calm water conditions.

Conclusion

The goal of this study was to document the contemporaneous diatom community; identify relationships between species or groups of species and spatial, temporal, and environmental variables; and assess how surface sediments integrate the modern diatom flora and represent the whole lake community. The two lake communities were dominated by small Cyclotella species and shared the majority of

common taxa, attesting to their common climatic, geological, and morphological setting.

However, notable differences between the two assemblages shed light on the importance of specific sampling locations and the spatial variability of environmental conditions within a single site. Variation in species composition within each lake was greatest between microhabitats (i.e., spatially rather than temporally), particularly between benthic and planktonic assemblages. Sediment trap and surface core assemblages are over-represented by planktonic and lotic taxa, suggestive of a relatively low efficiency of valve delivery from the littoral zone. Collectively, these results generate the potential to refine interpretations of past environmental conditions based on fossil diatom assemblages and advocate for the importance of understanding modern existing diatom communities and microhabitats at seasonal and sub-seasonal scales. Our findings suggest that subsequent paleoenvironmental reconstructions based on fossil diatoms might be best suited to questions related to catchment hydrology (i.e., the contribution of lotic taxa) and lake ice conditions (i.e., the contribution of planktonic taxa).

Acknowledgements

This work was supported by a National Science and Engineering Research Council of Canada (NSERC) Discovery Grant to SFL, and a NSERC PGS-D Scholarship, Northern

Scientific Training Program (NSTP) Award, Queen’s Graduate Award, and McDonald-

Sinclair Travelling Scholarship to KAS. We would also like to thank the Polar Continental

Shelf Program (PCSP/PPCP contribution # 011-15), Natural Resources Canada for logistical support in conducting field research. We gratefully acknowledge field assistance by D. Atkinson, J. Wall, G. Hambley, A. Forbes, J. Cockburn, D. Macdonald, E.

Wells and F. Forsythe.

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Tables

Table 3. 1 A comparison of major physical and chemical attributes of the Cape Bounty lakes during the 2004 season. After Stewart and Lamoureux (2011).

West Lake East Lake Max. depth (m) 35 32 Surface area (km2) 1.4 1.6 Lake volume (m3) 21400 20900 Catchment area (km2) 8.0 11.6 Residence time (yrs) 22.4 16.7 pH 7.4 7.4 Conductivity (µS s-1) 38 52 Mean TN-F (mg l-1) .23 .15 Mean TP-F (mg l-1) .008 .005 Mean Chl-a (µg l-1) 1.15 2.38 DOC (mg l-1) 1.4 1.3 Ice-off Persistent Mid-August ice-pan 1

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Table 3. 2 Summary statistics for ordinations. DCAs were performed on samples and species for each lake and a combined lake dataset. DCCAs constrained to microhabitat were performed on the individual lake datasets. CCAs were performed for each lake on species data constrained to measured environmental variables.

West Lake East Lake Both lakes Ordination axis 1 2 1 2 1 2 DCA Eigenvalues (λ) 0.688 0.139 0.343 0.129 0.319 0.168 Length of gradient 3.74 1.9 2.83 1.58 2.67 1.57 % variance spp. 35.0 7.1 34.2 12.8 24.4 12.8 DCCA Eigenvalues (λ) 0.341 0.075 0.343 0.129 (microhabitat) Length of gradient 2.6 1.72 2.83 1.59 % variance spp. env. 73.4 6.8 75.9 0.02 CCA Eigenvalues (λ) 0.101 0.054 0.102 0.059 (env. variables) % variance spp. 35.9 19.3 42.9 24.9 % variance spp. Env. 40.8 21.9 42.9 24.9

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Table 3. 3 Ordination variable code and abundance of common (>1% per sample type) diatoms in West Lake. Taxa in bold are common to both lake datasets. Headings represent percent abundance of taxa in M=moss/macrophyte, R=rock scrapes, S=littoral sediment, P=plankton, L=combined lake microhabitats (M, R, S and P), T=sediment traps, and C= surface sediment (0- 0.5 cm) from a lake core.

Code West Lake - Taxon and authority M% R% S% P% L% T% C% Ach daon Achnanthes daonensis Lange-Bertalot 0 0.1 0.0 0.0 0.0 0.5 2.8 Ach niti Achnanthes nitidiformis Lange-Bertalot 0.0 0.1 0.15 0.4 0.1 1.6 0.0 Ach rupo Achnanthes rupestoides Hohn 0.4 0.8 3.0 0.3 0.8 0.1 0.0 Ach rupi Achnanthes rupestris Krasske 0.0 0.7 1.2 0.0 0.3 0.1 0.0 Ach minu Achnanthidium minutissimum (Kützing) Czarnecki 1.5 2.5 0.8 1.1 1.1 2.1 2.9 Aul ambi Aulacoseira ambigua (Grunow ex Van Heurck) Simonsen 0.0 0.1 0.1 0.5 0.2 0.9 1.0 Cal aero Caloneis aerophila Bock 0.8 1.4 2.0 0.2 0.8 0.1 0.0 Cyc pseu Cyclotella pseudostelligera Hustedt 3.9 3.3 0.9 45.9 11.2 33.6 66.2 Cyc ross Cyclotella rossii Håkansson 1.2 2.1 1.0 16.2 4.2 17.0 13.5 Cym lapp Cymbella lapponica Grunow ex Cleve 0.9 1.1 2.1 0.2 0.8 0.0 0.0 Dia brek Diadesmis brekkaensis (Krasske) D.G. Mann 0.0 0.9 1.3 0.2 0.5 0.2 0.0 Dia cont Diadesmis contenta (Grunow ex Van Heurck) D.G. Mann 7.8 8.5 7.3 1.3 4.6 1.1 0.8 Dia gall Diadesmis gallica W. Smith 9.1 8.2 8.0 0.0 4.6 0.3 0.6 Dia tenu Diatoma tenuis C. Agardh 18.4 11.2 5.2 2.3 6.8 1.6 1.9 Dip oblo Diploneis oblongella (Nägeli) Cleve-Euler 0.1 0.1 0.0 0.0 0.0 0.2 1.0 Enc sile Encyonema silesiacum (Bleisch) D.G. Mann 0.3 0.4 1.3 0.2 0.4 0.0 0.2 Enc vent Encyonema ventricosum (C. Agardh) Grunow 1.1 0.3 1.4 0.1 0.5 0.0 0.0 Eun prae Eunotia praerupta Ehrenberg 0.5 1.1 1.9 0.0 0.6 0.2 0.0 Fra capu Fragilaria capucina var. capucina Desmazières 3.9 3.1 1.1 0.2 1.5 0.5 0.0 Gom parv Gomphonema parvulum var. micropus (Kützing) Cleve 0.1 1.8 0.7 0.0 0.5 0.3 0.0 Han arcu Hannaea arcus (Ehrenberg) R.M. Patrick 1.3 0.6 0.3 0.2 0.4 1.9 0.0 Han amph Hantzschia amphioxys (Ehrenberg) Grunow 0.2 0.3 1.0 0.0 0.3 0.0 0.0 Lut muti Luticola mutica (Kützing) D.G. Mann 0.2 0.4 1.2 0.0 0.3 0.2 0.0 Mue gibb Muelleria gibbula (Cleve) S. A. Spaulding & E. F. Stoermer 0.4 0.5 1.3 0.0 0.4 0.1 0.0 Nav berg Navicula bergerii Krasske 2.4 1.6 2.2 0.6 1.2 0.4 0.0 Nav cinc Navicula cincta (Ehrenberg) Kutzing 1.0 1.4 3.1 0.2 1.0 0.2 0.0 Nav cryp Navicula cryptocephala Kützing 2.2 1.5 3.6 0.6 1.4 0.3 0.3 Nit alpi Nitzschia alpina Hustedt 1.3 0.8 1.6 0.3 0.7 0.1 0.0 Nit lacu Nitzschia lacunarum Hustedt 1.7 1.4 1.7 0.2 0.9 0.4 0.0 Nit pale Nitzschia palea (Kützing) W. Smith 0.7 1.2 1.3 0.4 0.7 0.9 0.6 Nit perm Nitzschia perminutum (Grunow) M. Peragallo 6.1 3.2 3.2 1.0 2.5 0.5 1.0 Pin balf Pinnularia balfouriana Grunow ex Cleve 0.5 0.9 1.1 0.2 0.5 0.2 0.2 Pin inte Pinnularia intermedia (Lagerstedt) Cleve 0.3 0.9 3.9 0.1 0.9 0.1 0.0 Pin kram Pinnularia krammeri Metzeltin 1.3 0.4 0.5 0.1 0.4 0.0 0.0 Pin obsc Pinnularia obscura Krasske 4.3 2.1 2.0 0.4 1.6 0.2 0.0 Psa chli Psammothidium chlidanos (Hohn & Hellerman) Lange-Bertalot 2.2 2.8 2.0 0.6 1.4 0.5 0.0 Psa kryo Psammothidium kryophilum (Petersen) Reichardt 3.9 1.2 0.8 0.1 1.1 0.1 0.0 Psa marg Psammothidium marginulatum (Grunow) Bukhtiyarova & 2.8 1.5 2.6 0.7 1.4 0.3 0.6 Ros pete RossithidiumRound petersenii (Hustedt) Bukhtiyarova & Round 2.3 2.4 2.5 0.4 1.4 0.3 0.8 Sel pupu Sellaphora pupula (Kützing) Mereschkovsky 0.2 0.5 0.3 0.4 0.3 2.0 0.2 Sta ance Stauroneis anceps Ehrenberg 2.0 1.0 2.2 0.1 1.0 0.2 0.0 Sta lund Stauroneis lundii Hustedt 0.0 0.3 1.3 0.2 0.3 0.1 0.0 Proportion of all valves counted in that sample type (%) 87 74 79 75 79 68 91.8

Shannon's Index 2.8 3.2 3.3 1.8 2.8 2.4 2.1

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Table 3. 4 Ordination codes and abundances of common (>1% per sample type) diatoms in East Lake. Taxa in bold are common in both lake datasets. Headings represent percent abundance of taxa in M=moss/macrophyte, R=rock scrapes, S=littoral sediment, P=plankton, L=combined lake microhabitat samples (M, R, S and P),T=sediment traps, and C= surface sediment (0-0.5 cm) from a lake core.

Code East Lake - Taxon and Authority M% R% S% P% L% T% C% Ach daon Achnanthes daonensis Lange-Bertalot 0.0 24.8 0.2 0.0 4.7 0.0 0.2% Ach helv Achnanthes helvetica (Hustedt) Lange-Bertalot 5.6 2.0 8.5 0.1 3.8 0.2 0.0 Ach rupe Achnanthes rupestris Krasske 1.3 1.8 4.2 0.3 1.7 0.0 0.0 Ach sacc Achanthes saccula J.R. Carter 0.0 0.0 0.0 0.0 0.0 0.1 2.2 Ano vitr Anomoeoneis vitrea (Grunow) R. Ross 0.1 0.1 0.0 0.2 0.1 0.47 1.0 Cal aero Caloneis aerophila Bock 1.1 0.4 0.6 0.0 0.5 0.1 0.0 Cyc pseu Cyclotella pseudostelligera Hustedt 1.7 3.3 1.0 5.0 3.3 22.4 27.6 Cyc ross Cyclotella rossii Håkansson 4.8 9.7 3.8 40.7 19.9 25.6 50.8 Cym lapp Cymbella lapponica Grunow ex Cleve 0.8 0.2 1.4 0.0 0.6 0.1 0.0 Dia brek Diadesmis brekkaensis (Krasske) D.G. Mann 2.4 0.8 1.7 0.2 1.2 0.0 0.0 Dia cont Diadesmis contenta (Grunow ex Van Heurck) D.G. Mann 2.2 1.1 2.6 0.3 1.5 1.1 0.0 Dia gall Diadesmis gallica W. Smith 2.1 1.2 4.8 0.2 1.9 0.4 0.0 Dia tenu Diatoma tenuis C. Agardh 1.4 1.1 0.3 0.1 0.7 0.9 0.8 Dip oblo Diploneis oblongella (Nägeli) Cleve-Euler 0.0 0.1 0.0 0.3 0.1 0.7 1.0 Eun arcu Eunotia arcus Ehrenberg 1.4 0.2 1.5 0.0 0.7 0.0 0.0 Eun prae Eunotia praerupta Ehrenberg 1.6 0.2 0.8 0.0 0.7 0.1 0.0 Fra capu Fragilaria capucina var. capucina Desmazières 2.2 2.7 0.6 0.1 1.3 0.1 0.0 Fra grac Fragilaria capucina var. gracilis (Oestrup) Hustedt 0.0 0.1 0.0 0.6 0.3 1.5 8.1 Fra tene Fragilaria tenera (W. Smith) Lange-Bertalot 15.6 12.4 3.3 3.7 9.0 2.3 0.4 Gom parv Gomphonema parvulum var. micropus (Kützing) Cleve 0.5 5.8 0.1 0.1 1.3 0.3 0.4 Nav berg Navicula bergerii Krasske 1.3 0.8 1.2 0.1 0.8 0.3 0.0 Nav bjoe Navicula bjoernoeyaensis Metzeltin, Witkowski & Lange-Bertalot 0.3 0.0 2.0 0.0 0.5 0.0 0.0 Nav pseu Navicula pseudotenelloides Krasske 0.9 1.5 0.8 0.2 0.8 0.6 0.0 Nit acic Nitzschia acicularis (Kützing) W. Smith 0.1 0.4 0.0 1.2 0.6 4.6 0.0 Nit alpi Nitzschia alpina Hustedt 0.5 1.3 1.3 0.2 0.7 0.5 0.0 Nit lacu Nitzschia lacunarum Hustedt 0.9 0.7 2.0 0.0 0.8 0.2 0.0 Nit pale Nitzschia palea (Kützing) W. Smith 0.5 0.3 1.2 0.0 0.5 0.6 0.0 Nit perm Nitzschia perminutum (Grunow) M. Peragallo 3.0 0.9 4.3 0.5 2.1 0.3 2.8 Pin subr Pinnularia subrostrata (A. Cleve) Cleve-Euler 1.5 0.2 2.3 0.0 1.0 0.0 0.0 Pin kram Pinnularia krammeri Metzeltin 1.1 0.2 0.4 0.1 0.5 0.1 0.0 Pin micr Pinnularia microstauron (Ehrenberg) Cleve 1.5 0.5 0.8 0.0 0.7 0.1 0.0 Pin obsc Pinnularia obscura Krasske 6.2 0.2 1.6 0.0 2.2 0.0 0.0 Psa chli Psammothidium chlidanos (Hohn & Hellerman) Lange-Bertalot 2.2 1.5 3.0 0.2 1.6 0.4 0.0 Psa marg Psammothidium marginulatum (Grunow) Bukhtiyarova & 7.0 3.2 9.6 0.7 4.9 0.5 0.0 Ros pete RossithidiumRound petersenii (Hustedt) Bukhtiyarova & Round 0.7 0.2 1.3 0.2 0.6 0.2 0.0 Sta ance Stauroneis anceps Ehrenberg 1.4 0.4 1.8 0.1 0.9 0.2 0.0 Sta lundi Stauroneis lundii Hustedt 1.8 0.4 4.5 0.0 1.6 0.0 0.0 Proportion of total assemblage (%) 76 80 74 55 74 64 95.3 Shannon's Index 3.3 2.6 3.3 1.6 2.7 2.3 2.2 1

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Table 3. 5 Matrix of t-test levels of significance (P<0.005; two-tailed) between sample type diversities. Note that West Lake occupies the lower left and East Lake occupies the upper right portion of the table.

Moss Rock Litt. sed. Plankton Sed. trap

East Moss 0.023 0.439 <0.005 <0.005 Rock 0.109 <0.005 <0.005 0.23

Lake Lake

Sediment 0.131 0.496 <0.005 <0.005

Plankton 0.045 <0.005 <0.005 <0.005

West Trap 0.348 0.012 0.023 0.143

104

Figures

Figure 3. 1 Main map features West and East Lakes and their respective catchments (solid lines) near Cape Bounty, Nunavut. Top map is a close-up of the area of interest in the inset map, indicating the location of Cape Bounty and Melville Island in the Canadian Arctic Archipelago.

105

Figure 3. 2 Seasonal profiles of select chemical variables from West Lake (left) and East Lake (right) in 2004. After Stewart and Lamoureux (2011).

106

4 a) West Lake 3.5

3 JN28

2.5 JY5 2 JY9 1.5 JY16 1 JY22 0.5 JY30

Shannon Diversity Index Diversity Shannon 0 AU6 Moss Rock Sediment Plankton Sediment trap

4 b) East Lake 3.5 JN28 3 JY3 2.5 JY9 2 JY16 1.5 JY22 1

Shannon Diversity Index Diversity Shannon JY30 0.5 AU6 0 Moss Rock Sediment Plankton Sediment trap

Figure 3. 3 Temporal changes in Shannon diversity in each sampled microhabitat for a) West Lake and b) East Lake.

107

a) West Lake

108

Figure 3. 4 Seasonal abundances of all common diatoms (>1% per microhabitat) from a) West Lake and b) East Lake. Taxa are presented left to right in groups according to which sample they demonstrated the greatest abundance in.

108

b) East Lake

109

a) West Lake

3 Enc vent Cym lapp Nav cryp

Pin kram Enc sile Nitz per Nitz alp Sta ance Psa marg Psa chli Psa kryo Nitz pale Han amph Nitz lacu Dip oblo

Nav cinc Ros pete Ach minu Cyc ross Pin obsc Pin balf Sta lund Cyc pseu Nav berg Aul ambi Ach niti Pin inte Mue gibb

Axis 2 Axis Lut muti Ach daon Cal aero Sel pupu

Eun prae Ach rupr Frag capu Dia gall Ach rupo

Gom parv Han arcu Dia tenu Dia brek

Dia cont

SPECIES SAMPLES -2 M R S P T C

-1 Axis 1 4

Figure 3. 5 DCA bi-plots of species and samples from a) West Lake and b) East Lake. Legend codes refer to sample type as follows: M=moss/macrophyte, R=rock scrapes, S=littoral sediment, P=plankton, T=sediment traps, C= uppermost 0.5 cm of sediment core collected at the deepest part of lake.

110

b) East Lake

4 Fra tene

Cym lapp Pin micr Ano vitr Nit lacu Dia tenu Sta ance Nitz per Nit pale Eun prae Dia gall Eun arcu Dip oblo Pin subr Cal aero Nav bjoe Dia brek Dia cont Ach sacc Psa marg Fra capu Cyc ross Fra grac Axis 2 Axis Pin obsc Nav berg Cyc pseu Ach helv Psa chli Sta lund Nit acic Ach rupe Ros pete Nav pseu Pin kram Nit alpi

Gom parv

Ach daon

-2 SPECIES SAMPLES M R S P T C -3 5 Axis 1

111

Axis 2 Axis

SAMPLES -0.5 WM WR WS WP WT WC EM ER ES EP ET EC

-0.5 3.0 Axis 1

Figure 3. 6 DCA ordination graphs of (a) samples classified by sample type, and (b) bi-plot of species and samples, representing both lake datasets. Codes denote lake (W=West Lake or E=East Lake) and sample type (M=moss/macrophyte, R=rock scrapes, S=littoral sediment, P=plankton, T=sediment traps, C= uppermost 0.5 cm of sediment core collected at the deepest part of lake).

112

Ach helv Ach daon

Fra tene Pin subr Nit acic

Fra grac Ach rupr Sta lund Ano vitr Nav bjoe Psa marg Gom parv Eun arcu Nit alpi Pin micr Dia brek Nav pseu Cyc ross Pin inte Pin kram Dip oblo Ach rupo Dia gall Cym lapp Nav berg Sta ance Nit perm Cal aero Fra capu Psa chli Eun prae Nit pale Ros pete Lut muti Nit lacu Cyc pseu Ach sacc Pin obsc Dia cont Ach niti Enc vent Nav cryp

Sel pupu Mue gibb Enc sile

Nav cinc Dia tenu Ach minu Psa kryo Pin balf

Han arcu

Han amph Aul ambi Ax

-3 is 1

-2 Axis 1 4

113

a) West Lake

Dia brek

Pin inte

Ach rupr Sta lund Ach rupo Dia gall microhabitat Lut muti Gom parv Ach daon Cal aero Eun prae Dia cont Pin balf Ach niti Aul ambi Han amph Sel pupu Frag capu Han arcu Nav cinc Mue gibb Cyc pseu Nav berg Nitz pale Cyc ross Nitz lacu Ros pete Ach minu Pin obsc Nitz alpi Enc sile Dia tenu Dip oblo Psa chli Psa marg Sta ance Nav cryp Nitz per Cym lapp

Pin kram Enc vent

Psa kryo SPECIES SAMPLES -3 WM WR WS WP WT WC

-2 6 Axis 1

Figure 3. 7 DCCA tri-plots of species and samples, constrained to habitat for a) West Lake and b) East Lake.

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b) East Lake

4 Fra tene

Cym lapp Pin micr Ano vitr Nit lacu Dia tenu Sta ance Nitz per Nit pale Dia gall Eun arcu Eun prae Dip oblo Pin subr Cal aero Nav bjoe Dia brek Dia cont Fra capu Ach sacc Psa marg Cyc ross Axis 2 Axis Pin obsc Nav berg Fra grac Psa chli Cyc pseu microhabitat Sta lund Ach helv Ach rupe Ros pete Nav pseu Nit acic Pin kram Nit alpi

Gom parv SPECIES

SAMPLES Ach daon EM ER ES EP ET EC -2 -4 6 Axis 1

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a) West Lake

1.0

Cyc ross

Enc sile Nit pale Ach niti Eun arcu Sel pupu Ach minu EC Cym lapp Eun prae Gom parv Nav pseu Cyc pseuFra capu Mue gibb Han amph Psa chli Dia tenu Nit lacu Pin micr Pin inte Nav cryp Pin balf Nav bjoe Lut muti Dia brek Han arcu Nit perm Nit alpi DOC Sta ance Ach rupo Dia cont Ros pete Dia gall Nav cinc Cal aero Nav berg Sta lund Pin obsc Psa marg Pin subr Ach rupi Enc vent Psa kryo Pin kram TP-F Nit acic Ach helv

POC

SiO2

Fra tene

SPECIES ENV. VARIABLES

-1.5

-0.8 Axis 1 1.0

Figure 3. 8 CCA bi-plots of species (stars) and primary environmental variables (arrows) for a) West Lake, and b) East Lake.

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b) East Lake

1.0

Enc vent Psa kryo

Enc sile Nit pale pH Dia tenu Fra grac Fra capu Pin obsc Nav bjoe Cym lapp Sta ance Psa chli DOC Nav berg Nav pseu Eun arcu Nit perm Nit alpi Nit acic Ach niti Sel pupu Fra tene Nav cryp Pin micr Nav cinc Psa marg Dia cont Pin balf Lut muti Ach helv Sta lund SiO Pin kram 2 Dia gall Pin inte Ach rupi Cyc pseuDia brek Cal aero Cyc ross Ros pete Pin subr Eun prae Ach minu Han arcu TN-F Mue gibb Ach rupo

EC DIC Gom parv

SPECIES

-1.0 Ach daon ENV. VARIABLES

-1.0 Axis 1 1.5

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Figure 3. 9 Relative abundance of select taxa from a) West Lake and b) East Lake among sample types. Benthos refers to percent abundance of each taxon in all moss/macrophyte, rock scrape and littoral sediment samples.

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Chapter 4:

A paired-lake comparison of recent aquatic and terrestrial dynamics recorded in varved sediments from adjacent High Arctic lakes: Cape Bounty, Melville Island, Canada.

Kailey Stewart, Scott Lamoureux, Brent Paulter, Myrna Simpson and Jaclyn Cockburn

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Abstract

Fossil diatom records from annually-laminated sediments of two closely situated and otherwise similar lakes in the High Arctic were analysed to investigate the recent

(250-300 year) ecological histories of the lakes and to better understand the range of ecological responses generated by the same broad environmental conditions (i.e., climate, geology). Diatoms occur only in the uppermost centimetres of both sedimentary records and the similar nature of the assemblages, combined with the later onset of diatom productivity in West Lake (1980s) compared to East Lake (1960s), suggest that these systems filter regional climatic signals individually. To elucidate this discrepancy and shed light on site-specific controls on lake ecology, a number of other proxy indicators were analyzed from the lake sediments, including varve thickness measurements, atomic C/N ratios, spectrally-inferred Chl-a concentrations and solvent- extractable lipids.

Collectively, these indicators suggest a closer connection between West Lake and catchment hydrology, which manifests through higher terrestrially-derived organic matter accumulation in response to increased winter precipitation. In contrast, East

Lake is more productive as a consequence of being slightly shallower, warmer, and losing its ice cover sooner and more completely each year, resulting in an organic matter record more strongly imprinted with internal dynamics of aquatic productivity, with a less coherent connection to catchment hydrology. Our results suggest that both lakes have undergone recent changes consistent with 20th century climate warming and that the later onset of diatom productivity in West Lake is related to its greater depth and

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longer ice cover that delays response to synoptic climate trends. Collectively, our results also suggest that even seemingly small differences between lacustrine systems can manifest as distinct differences in sedimentary archives, and that while West Lake presents a clearer picture of hydroclimatic trends, as climate continues to warm and aquatic productivity expands, this relationship is likely to become less obvious.

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Introduction

Due to feedbacks associated with extensive snow and ice cover, the Arctic environment is predicted to experience the greatest warming (Zwiers, 2002). Evidence is mounting of circumpolar changes in aquatic ecosystems, most notably among diatom communities, attributed to climate change and associated impacts on ice cover, thermal regimes and nutrient dynamics, beginning in the mid-19th century (ACIA, 2005; Smol et al., 2005). However, diatoms only represent a single component of aquatic ecosystems, and sometimes do not respond as immediately to changing environmental conditions as other algal components (Antoniades et al., 2007). In addition, there are reports of diatoms only appearing recently in appreciable numbers in some Arctic lake sediments

(e.g., Doubleday et al., 1995; Perren et al., 2003; Antoniades et al., 2007), which confines the chronological extent of this proxy in these systems.

Employing a multi-proxy approach can help resolve these limitations and strengthen paleoenvironmental interpretations overall. Expanding paleolimnological applications of rapid analysis techniques (e.g., Near Infrared Spectrometry (NIR), Visible

NIR, and Visible Reflectance Spectroscropy (VRS)), offer new insight to past aquatic conditions with non-destructive consequences to sediment samples (Wolfe et al., 2006).

For example, inferred chlorophyll-a (Chl-a) concentrations derived from the spectral properties of lake sediments point to pronounced increases in photosynthetic productivity in Arctic lakes that coincide with the period of industrial climate warming

(Michelutti et al., 2005; Antoniades et al., 2007).

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Organic matter (OM) geochemistry may be used to compliment aquatic microfossils and indicators of aquatic productivity by offering information on specific sources and diagenetic alteration of both aquatic and terrigenous contributions to the sedimentary record, thereby offering a more complete picture of paleoenvironmental conditions (Meyers and Ishiwatari, 1993). Moreover, the combination of generally low lake productivity (Karlsson et al., 2005) and large stock of terrestrial soil OM in the Arctic

(Jahn et al., 2010), the inherent connection of the terrestrial and aquatic systems via the seasonal runoff from snowmelt, and the more immediate response of the terrestrial environment to climate change compared to aquatic environments, all favour investigating terrestrial organic matter sources and signals in Arctic lake sediments.

Furthermore, continued or accelerated degradation of permafrost hold important implications for terrestrial and downstream aquatic ecosystems (Smith et al., 2005a,

2005b; Hinzman et al., 2005; Walsh et al., 2005).

Bulk elemental ratios of total organic carbon: total nitrogen (C/N) tend to retain their source signature in lake sediments, making them widely applied indicators of past terrestrial and aquatic organic matter contributions (Meyers and Ishiwatari, 1993;

Meyers, 1994). Plant lipids hold the same advantage, and the analysis of solvent- extractable lipid compounds from lake sediments generates an opportunity to trace individual molecules to their plant source (i.e., organic biomarkers). Lipid analyses have been used to infer past changes in a variety of terrestrial plant communities and aquatic microorganisms in lake sediments (e.g., Cranwell, 1973; Rieley et al., 1991;

Bourbonniere and Meyers, 1996; Volkman et al., 1998; Ficken et al., 2000), though their

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application in high latitude lake settings remains extremely limited (e.g., Routh et al.,

2007). However, a recent investigation of lipid compounds in littoral sediments from the current study site indicated the presence of terrestrial biomarkers (Paulter et al., 2010), suggesting an opportunity exists to incorporate these indicators into paleoenvironmental reconstructions.

Our multi-proxy paired-watershed study combines these techniques to investigate the recent (~250-300 yr) history of aquatic ecosystem dynamics in two closely situated and otherwise very similar (i.e., limnology, geology, morphology) lakes on Melville Island, in the Canadian High Arctic, an environmentally sensitive region where relatively little long term limnological data exists. A paired-watershed approach offers the opportunity to discern broad-scale forcing mechanisms (i.e., climate) from site-specific influences, providing an opportunity to assess how similar systems respond differently to the same over-arching conditions. In addition, annually laminated sediments in both lakes presented an opportunity to identify the precise timing of any changes and directly compare the two records. Thus, the objectives of this study are to i) contribute baseline data on pre- and post-industrial Arctic diatom assemblages and trends; ii) assess the extent to which similar lakes respond differently to the same external forcings; and iii) explore the potential to identify organic biomarkers of both aquatic and terrestrial origin and develop a more comprehensive picture of recent terrestrial-aquatic dynamics and possible future trajectories.

This research forms an important contribution to the growing body of research focussed on the Cape Bounty Arctic Watershed Observatory (CBAWO), which aims to

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improve understanding of the linkages between climate, hydrology, biogeochemical cycling and ecosystem processes in the High Arctic.

Study site

The study site consists of two closely situated lakes and physiographically similar lakes (unofficially named West and East Lake) inland of Cape Bounty, adjacent to

Viscount Melville Sound on south-central Melville Island (75°55’N, 109°35’W; Fig. 4.1).

West Lake is slightly deeper (Zmax=35 m) than East Lake (Zmax=32 m), with a smaller surface area (1.4 km2 vs. 1.6 km2) but greater overall water volume than East Lake (21

400 m3 versus 20 900 m3), resulting in a smaller surface area to volume ratio than for

East Lake. The West catchment is smaller with a slightly steeper gradient and deeper channels than the East catchment. Overall, vegetation in the West catchment is more continuous, though both are characterized by dwarf-shrub tundra bryophytes, cotton grass and sedges covering low-lying moist areas (Atkinson and Treitz, 2007). Both catchments have tributaries that feed a principal stream flowing into the lakes from the north (Fig. 4.1). The catchments are characterized by low relief hills (<120 m) and plateaus of Holocene marine and glacial sediments underlain by weathered Palaeozoic sandstones and siltstones (Hodgson et al., 1984) in the zone of continuous permafrost, with a summer maximum active layer of <1m.

Climate at Cape Bounty consists of long, cold winters and short growing seasons with low annual precipitation. At Mould Bay, Prince Patrick Island (Fig. 4.1), approximately 200 km west of Melville Island, mean daily temperatures (1971-2000)

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range from –34°C in February, to 4°C in July, and mean annual precipitation is 111 mm, the majority of which falls as snow (i.e., September-May; Meteorological Service of

Canada, 2002). Snow surveys conducted at Cape Bounty, 2003-2005 indicated greater snowpack in the West Catchment, attributed to the steeper gradient and associated deeper gullies and channels where drifting snow disproportionately collects (Cockburn and Lamoureux, 2008a; McDonald and Lamoureux, 2009).

Methods

Coring and chronology

Data presented here are based on sedimentary records obtained from gravity cores (Boyle, 1995) retrieved from the deepest areas in West Lake in 2005 (core 05WL7;

30 cm long) and in East Lake in 2007 (core 07EL01; 40 cm long). Except in cases where other cores were used for chronological constraint, all reference to sedimentary records from West and East Lake refer to these two cores. The varve chronology was determined from thin sections prepared from overlapping 7 cm slabs spanning the length of the core, which were embedded in epoxy resin and mounted to microscope slides before being ground down to <1mm thick (Lamoureux, 1994). Thin section slides were subsequently scanned at 2400 dpi using a slide scanner and examined at high magnification (~3500x) in the graphics program CorelDRAW 13. Repeating couplets of coarse material overlain by narrow laminae consisting of fine particles occurred throughout both cores and were consistent with the pattern of seasonal sediment delivery in Arctic nival catchments, as well as hydrological monitoring observations

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carried out at Cape Bounty between 2003-2005 (Cockburn and Lamoureux, 2008a;

Cuven et al., 2010). Subsequent radioisotopic dating confirmed that these couplets represented annual units of deposition (i.e., varves).

Dating with profiles of 210Pb and 137Cs was performed on 0.5 cm depth increments contained within the upper 20 cm of each core. Radionuclide activity levels were determined with alpha spectroscropy by MyCore Scientific Inc. (Deep River, ON).

Age-depth modelling was applied to the unsupported (i.e., above existing background levels) 210Pb activity using the Constant Rate of Supply (CRS) method (Appleby and

Oldfield, 1978). Dating for 137Cs is based on the first appearance and peak concentrations of the radionuclide in sediments, which correspond to calendar years

~1954 and 1963, respectively, representing the introduction and peak of nuclear weapons testing.

Diatom preparation and enumeration

For each 0.5 cm depth interval, approximately 0.3 g of homogenized dry sediment from the surface sediment core were placed in a 50 ml centrifuge tube and digested overnight with 15 ml of 50:50 molar ratio of sulphuric and nitric acid. Samples were then heated in a water bath for a minimum of two hours at approximately 90 °C to ensure complete digestion of organic matter. Samples were centrifuged and rinsed repeatedly in distilled water until a neutral pH was obtained. Samples were topped to

20 ml and several dilutions were dispersed onto cover slips and left to dry overnight.

Dried samples were mounted onto microscope slides using Zrax, a mounting medium

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with a high refractive index suitable for observing diatoms under light microscopy. A

Zeiss Axio Imager A1 microscope with differential interference contrast (DIC) optics was used to identify and count diatom valves. A minimum of 400 diatom valves were counted per sample, and included up to six complete transects. Samples that rendered fewer than 400 valves after six complete transects were included in valve concentration data but omitted from relative abundance calculations. Reference material for taxanomic identification included Fallu et al. (2000), Krammer & Lange-Bertalot (2004,

2007), and Antoniades et al. (2008).

Spectrally inferred Chl-a and C/N ratios

The value of spectrally-inferred chlorophyll-a pigments is founded in the highly consistent absorption spectra of algal pigments and post-depositional degradation products (Rundquist et al., 1996; Das et al., 2005; Wolfe et al., 2006; Michelutti et al.,

2010). Measurements of spectrally-inferred Chl-a were made on samples corresponding to 1 cm depth intervals spanning both cores. Samples were freeze-dried, lightly ground and sieved, and analyzed on a Rapid Content Analyser FOSS NIRSystems, Model 6500 interfaced with Vision® software. Samples were run for a minimum of 1 minute and blanks were run every few samples for more than one minute each. Errors were less than 1% based on systematic duplicate runs conducted on every 5th or 6th sample.

Inferred Chl-a concentrations are expressed as flux rates (mg g-1 a-1), to account for changes in sedimentation rates that could skew temporal trends in productivity.

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To obtain C/N ratios, measurements of organic carbon and total nitrogen were established at 0.5 cm (West Lake) or 1 cm (East Lake) intervals spanning the cores. To remove carbonates, samples were digested with hydrochloric acid for 24 hours and rinsed repeatedly with distilled water to eliminate the acid. Samples were freeze dried and ground and measurements were obtained on a Leco CNS 2000 analyser with errors of 3.3% for carbon and 7.0% for nitrogen.

Solvent extracted organic matter

To further investigate changes in organic matter sources in recent sediments, lipid compounds were extracted from the sediment cores using organic solvents, and quantified using gas chromatography-mass spectrometry (GC-MS). Given the novelty of this analysis on High Arctic lake sediments, and to ensure we had sufficient organic matter per sample for a reliable analysis, we initially sampled and freeze-dried a portion of the West Lake core in 2 cm depth intervals to obtain final dry weights of approximately 20 g per sample. In our subsequent sampling of the East Lake core, 1 cm intervals were freeze-dried and sub-sampled for approximately 5 g of dry sediment per sample. As a result, the East Lake record portrays greater chronological resolution than the West Lake core.

Solvent extractions followed the methods of Otto and Simpson (2005) and

Paulter et al. (2010). Briefly, sediment samples were sequentially extracted in methanol, methanol:dichloromethane (1:1 v/v), and then dichloromethane. The extracts were filtered and then blown dry under a stream of nitrogen. Extract yields were determined

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by weighing the dried residue. GC-MS analysis was performed with an Agilent model

6890N chromatograph coupled to an Agilent model 5973N quadrupole mass selective detector. Data was processed with Agilent Chemstation G1701DA software.

Compounds were identified through comparison of mass spectra to Wiley MS library data, comparison with standards, and with published data.

Results

Chronology

Due to the brief but intense snowmelt period, sediment delivery to the lakes at

Cape Bounty is characterized by a short period of coarse sediment accumulation followed by the settling of finer particles, which gives the sedimentary record a distinct annual structure (Cockburn and Lamoureux, 2008b). The measuring and counting of these annual laminations (i.e., varves) in thin sections permitted the development of an annual chronology corroborated with isotopic dating methods (Fig. 4.2a, b). The 30 cm sediment core from West Lake captures the period 1671-2002 AD, and the 40 cm core obtained from East Lake spans the period of 1755-2006 AD. These results indicate higher mean sedimentation rates in East Lake (1.6 mm yr-1) than in West Lake (0.91 mm yr-1) for the period of these records, partly attributed to the closer proximity of the coring location to the river outlet in East Lake (Fig. 4.1).

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Diatoms

The West Lake sedimentary diatom assemblage consisted of 94 taxa, 10 of which demonstrated abundances ≥2% and accounted for 72-89% of all valves counted (Table

4.2). The West Lake flora was dominated by centric taxa of the genus Cyclotella, including C. pseudostelligera and C. rossii, and Aulacoseira ambigua. Note that C. rossii is labelled as a complex, due to gradations in the physical appearance of valves more characteristic of C. comensis and C. ocellata, with distinctly C. rossii valves being the most abundant. Other common taxa were from the Achnanthes sensu lato genus

(Achnanthidium minutissimum, Achnanthes daonensis, Psammothidium chlidanos), with smaller contributions from Diadesmis gallica, Diadesmis contenta, Fragilaria capucina var. capucina, and Nitzschia perminutum. The East Lake flora was even more clearly defined by Cyclotella species of C. rossii complex and C. pseudostelligera, with minor contributions from the genus Achnanthes (A. laevis, A. laterostrata, A. saccula) and

Fragilaria (F. capucina var. gracilis, F. tenera), as well as from Diadesmis gallica,

Diploneis oblongella, Nitzschia perminutum, Navicula cincta, and Stauroneis smithii. Of the 111 taxa identified in the East Lake core samples, 14 demonstrated abundances ≥2% in any one sample, accounting for 76-93% of all valves counted (Table 4.2).

Stratigraphic profiles of diatom taxa and valve concentrations indicate that significant diatom productivity since approximately the mid-18th century is limited to the most recent decades in both lakes (Fig. 4.3a, b). In West Lake, diatom productivity appears to be limited to the period since the early to mid-1980s (2.5-3.0 cm), and

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maximum diatom concentrations occurred in the mid- to late 1990s (1.0-1.5 cm). In East

Lake, productivity increased sufficiently for taxonomic counting for a brief period in the mid- to late 1960s (5-5.5 cm), and then again spanning from the late 1980s (1.5 cm) until the present, with peak valve concentrations occurring in the mid- to late 1990s (0.5-1.0 cm). The brief appearance of diatoms in the East Lake core in the 1960’s (5-5.5 cm sample) ends with the onset of higher than average sedimentation rates lasting until approximately the mid-1970s. Valve concentrations increase again above 2 cm (1984), and are abundant enough to be counted in the upper 1.5 cm of sediment, corresponding to the late-1980s to onward. Though of short duration, the West Lake stratigraphy appears to reflect a change in the assemblage from a dominance of A. ambigua circa

1980-1990 to a dominance of C. pseudostelligera in post-1990 sediments. With the exception of the Cyclotella species, all other common taxa (primarily benthic, with the exception of Aulacoseira) demonstrate a decline toward the most recent sediments as

Cyclotella species overwhelm the assemblage. No obvious trend is apparent in the East

Lake stratigraphy, though Cyclotella species clearly dominate the recent assemblage, as in West Lake. Stratigraphic profiles of diatom fragment and chrysophycean cyst concentrations reveal very similar patterns to valve concentrations in both lake records

(Fig. 4.3a, b). Diatom and cyst concentrations increase substantially at approximately 1.5 cm depth in both cores.

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Sediment accumulation and Chl-a fluxes

Sedimentation rates in both lakes are characterized by periodic high sedimentation events spanning the records (Fig. 4.3a, b). Despite higher overall mean sedimentation rates in East Lake compared to West Lake over the course of the records, mean sedimentation rates have declined in East Lake in recent decades whereas West

Lake sedimentation rates have increased (e.g., from 1.6 mm y-1 to 1.2 mm y-1 post-1950 in East Lake, and from 0.91 mm y-1 to 1.0 mm y-1 post-1950 in West Lake). Inferred Chl- a concentrations and derivative products (collectively referred to as inferred Chl-a in this study), normalized to sedimentation rates to account for the diluting effect of periods of higher sedimentation rates, provides a picture of Chl-a fluxes into the lake sediments.

Mean Chl-a fluxes are extremely low in both lakes, at 0.53 µg g-1 a-1 in West Lake and

0.89 µg g-1 a-1 in East Lake, attesting to the extreme oligotrophy in these deep High

Arctic lakes. Both lake records depict prolonged periods of low Chl-a fluxes, followed by a period of consistently above mean concentrations occurring in the post 1940’s period in West Lake (0.78 µg g-1 a-1 versus 0.34 µg g-1 a-1 pre-1940s) and in the post-1920s period in East Lake (1.3 µg g-1 a-1 versus 0.59 µg g-1 a-1 pre-1920s; Fig 4.3a, b). Despite the extremely low concentration of inferred Chl-a, consistency with the timing of changes in other proxy indicators (C/N ratios, lipid concentrations) suggest trends in Chl- a represent accurate trends in aquatic productivity.

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Lipid geochemistry

Free lipids (i.e., extractable with an organic solvent) were analyzed from both lake cores to investigate the recent paleolimnological record of organic matter (OM) contributions and sources. Extracts were primarily composed of long-chained (Cn>20) aliphatic lipids (n-alkanes, n-alkanols and n-alkanoic acids) and cyclic lipids (steroids and terpenoids), with small contributions of carbohydrates (e.g., glucose, mannose). Extract yields and concentrations of the major lipids were consistently higher in East Lake than in West Lake (Fig. 4.4). Total extract yields normalized to percent organic carbon (OC) ranged from 12-62 mg g-1 OC for West Lake and 29-872 mg g-1 OC for East Lake.

Concentrations of the major lipid groups were lowest among the n-alkanes and highest among n-alkanols. Major sterols and derivatives included β-sitosterol, campesterol, stigmasterol, cholesterol, stigmastanol and stigmastenol. Terpenoids included friedelin and hopene, and the terpenoid α-amyrin, a biomarker for angiosperms (Hernes and

Hedges 2004), was only detected in the West Lake sediment core.

Extract yield profiles differ markedly between the two lake records, with West

Lake demonstrating peak concentrations circa 1816 followed by a gradual decline toward the present, with a subtle increase in concentrations apparent since the 1960s

(Fig. 4.4a). East Lake yields are higher and more variable in the upper half of the record, corresponding to the post-1950s period, though a more subtle trend toward increased concentrations is apparent since the beginning of the 20th century (Fig. 4.4b). Trends in

West Lake extract yields are roughly reflected in n-alkane, n-alkanoic acid and n-alkanol profiles in West Lake, but these same lipid fractions do not reflect the high and more

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variable total extract concentrations in the upper portion of the East Lake core, possibly indicating increased importance of bound (i.e., not solvent-extractable) compounds in the OM fraction (Fig. 4.4). The non-extractable compounds are most likely comprised primarily of lignins derived from the non-woody tissues of vascular plants, as these formed a larger portion of the OM content in littoral samples from East Lake, which were subjected to both solvent-extraction and copper-oxidization techniques, as presented in an earlier study (Paulter et al., 2010).

Stratigraphic profiles of lipid classes indicate lower concentrations toward the present compared to deeper sediments in both lakes (Fig. 4.4a, b). The decline in West

Lake can be isolated to a period between 10 and 8 cm, corresponding to the 1920s-

1940s, with relatively stable concentrations before and after this point, though there is indication of an increase in the uppermost sample that is consistent with total extract yields (Fig. 4.4a). Compound concentrations in East Lake are approximately double that of West Lake, demonstrate greater variability, and are less coherent than in West Lake, but reflect an overall decline in all lipids spanning the length of the record to the present

(Fig. 4b). The trends in aliphatic lipids are similarly reflected in total steroid (β-sitosterol, campesterol, stigmasterol, cholesterol, stigmastanol, cholestanol) concentrations in both lakes, though both lakes exhibit an overall trend of higher concentrations in recent sediments, commencing in the 1950s in West Lake and the 1980s in East Lake, with an additional isolated peak in the East Lake record corresponding to the 1920s (Fig. 4.4a, b).

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OM degradation

Measures were employed to evaluate source versus diagenetic changes in down- core concentrations (Fig. 4.5). Carbon Preference Indices (CPI) provide an indication of diagenetic losses based on the fact that n- alkanes preferentially retain odd chain length homologues and n-alkanol and n-alkanoic acids preferentially retain even chain length homologues (Bray and Evans, 1961; Meyers and Ishiwatari, 1993). Ratios of less than 2 are generally considered highly degraded (Tuo and Li, 2005). All CPI values for both lakes were above 2, with the exception of the 4 cm sample in West Lake and the 11 cm sample in East Lake, indicating lipid material is generally in the early stages of degradation (Fig. 4.5a, b). CPI values of n-alkanes, which are more resistant to degradation than n-alkanols and n-alkanoic acids (Otto and Simpson, 2005), demonstrate limited variability and mean values of 2.4 in West Lake and 4.2 in East Lake, suggesting a relatively high degree of preservation in these systems. This is further supported by the fact that the relationship between n-alkane CPI values and degradation is less clear in aquatic environments due to weaker odd or even preference of bacteria and aquatic algae, thereby resulting in lower CPI values than that of terrestrial OM

(Cranwell et al., 1987). More generally, OM degradation is likely to be limited in these records, owing to the fact that the sediments are relatively young and the climate is cold with prolonged periods of darkness, especially under the ice-cover, thereby inhibiting microbial activity and subsequent diagenesis of OM (Kuder and Kruge, 1998). The sharp rise in n-alkanoic acid CPI values above 3 cm (post-1976) is attributed to higher

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concentrations of unsaturated C18 molecules (i.e., iso-alkanoic acids; C18:1, C18:2) relative to deeper sediments (Fig. 4.5b).

In addition to odd or even Cn predominance, molecules with greater than 20 carbon atoms (i.e., high molecular weight; HMW) tend to be more resistant to degradation than those with fewer than 20 carbon atoms (low molecular weight; LMW) and, therefore, the ratio of HMW: LMW provides an additional indication of relative degradation (Meyers and Ishiwatari, 1993). West Lake ratios increase somewhat in the latter half of the record, but this more likely reflects changes in the contribution of long chain homologues, as ratios strongly mirror this contribution (Fig. 4.5a).

Long-chain homologues do not so clearly overwhelm the East Lake record, and

HMW:LMW ratios are less consistent (Fig. 4.5b). The n-alkanoic acid profile depicts a variable but overall decline in long-chain relative to short chain contributions. Due to the labile nature of these lipids, it is more likely that the decline in ratios toward the present represents a source change. This is supported by the punctuated increases in the LMW fraction at 7 cm (1950) and 2 cm (1984) caused by an increase in unsaturated C18- alkanoic acids, which are even more susceptible to degradation than their saturated homologues (Otto and Simpson, 2005). However, ratios of unsaturated:saturated n- alkanoic acids provide a clearer picture of this increased susceptibility, and suggest that preservation is greater in West Lake compared to East Lake (2.1 versus 1.6), though ratios are more stable in East Lake over the course of the record (Fig. 4.6). Both n- alkane and n-alkanol ratios peak at roughly 4 cm (1972) before declining in the uppermost portion of the core (post-1970s), suggesting higher followed by lower rates

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of degradation in recent decades or, more likely, an increase flux of HMW-enriched OM

(i.e., terrestrial) followed by an increase in LMW-enriched OM (i.e., aquatic) in recent sediments.

Bulk element and lipid biomarkers

A number of proxies were used to investigate differences in sources and concentrations of OM (Fig. 4.6). Atomic C/N ratios, an indication of terrestrial versus aquatic derived organic carbon whereby ratios >20 indicate predominantly terrestrial sources of organic carbon and ratios 4-10 are characteristic of algal productivity

(Meyers, 1994), demonstrate increased and more variable influxes of terrestrial OM in

West Lake (10.5-22.5) since the 1930s, despite relatively stable bulk organic carbon contributions (Fig. 4.6a). In East Lake, C/N ratios are lower and less variable (8-10.5), and

OC concentrations are higher than in West Lake (mean of 1.4% versus 1.1% for West

Lake). Minimum C/N values for East Lake values occur in the uppermost 2 cm, corresponding to the period of peak diatom concentrations since the mid-1980s (Fig.

4.6b).

In addition to offering information on selective degradation of certain OM fractions, as discussed in the previous section, ratios of higher to lower chain lengths

(HMW:LMW) can provide information on the relative contribution of terrestrial and aquatic sources of OM (Vonk et al., 2008). Aquatic plants and bacteria tend to be characterized by higher contributions of LMW n-alkanes, n-alkanols and n-iso-alkanoic acids, whereas terrestrial vegetation is more abundant in HMW homologues (Bianchi,

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1995; Weete, 1976; Harwood and Russell, 1984; Otto and Simpson, 2005). This characteristic division is particularly useful in n-alkane fractions, which are relatively resistant to degradation compared to the more labile n-alkanoic acid and n-alkanol aliphatic fractions, and has led to the development of a terrigenous aquatic ratio n- alkane proxy (TAR=∑C27+C29+C31/∑C17+C19+C21; Bourbonniere and Meyers, 1996). Mean n-alkane TAR values are 4.0 (1.5-7.4) for West Lake and 7.8 (4.4-14.6) for East Lake, indicating higher overall terrestrial contributions in East Lake, especially between 2-5 cm

(1969-1984) that correspond with a period of high sedimentation rates and increased

C/N ratios, relative to the uppermost 2 cm (Fig. 4.5). Generally higher concentrations of

HMW lipid molecules in East Lake compared to West Lake sediments also suggests a strong terrestrial contribution, though the lipid record also demonstrates aquatic sources, most obvious in the LMW n-alkanoic acid record punctuated by increased pulses of unsaturated C18-alkanoic acids in West Lake, and especially in East Lake (Fig.

4.5).

Carbon number distributions (i.e., Cn predominance) also shed light on the dominant source of OM in the sedimentary record (Fig. 4.6). Series distributions of n- alkanols for West and East Lakes indicate a Cn predominance of C26. The most abundant n- alkanoic acids are C24 in both lakes, with departures to unsaturated C18 molecules in the upper portion of both records. The C27-alkane maxima observed in West Lake is not as distinct in East Lake, which depicts a variable but decreasing trend from C31 predominance in older sediments to predominantly C27 through the middle of the core,

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and an increase in the C23 molecule in the most recent sediments (Fig. 4.6b). Both lake n- alkane records indicate C31 maxima in the oldest sediments.

Ratios of odd C n-alkanes can be used to help differentiate sources of OM derived from aquatic plants (i.e., emergent versus submergent macrophytes), terrestrial plants and Sphagnum (Ficken et al., 2000; Nott et al., 2000; Vonk et al., 2008). This proxy is based on the fact that submergent macrophytes and Sphagnum species produce higher concentrations of C23 and C25-alkanes, whereas emergent and terrestrial vascular vegetation are more abundant in long-chain (C29 and C31) n-alkanes. Since many

Sphagnum species also contain appreciable amounts of C31-alkanes, the following ratios were calculated to investigate contributions of submergent macrophytes and to differentiate terrestrial vascular plants from non-vascular Sphagnum species (Nott et al.,

2000; Vonk et al., 2008):

Paq = C23+C25/C23+C25+C29+C31

Paq Sphagnum = C23/C23+C29

Paq ratios of 0.09, 0.25 and 0.69 are associated with dominant contributions of terrestrial plants, emergent macrophytes and submergent macrophytes, respectively, and values between these represent a mixture of sources (Ficken et al, 2000). Mean ratios of Paq for West and East Lake were 0.54 and 0.53, respectively. Ratios of

PaqSphagnum bear a striking resemblance to Paq, with mean values of 0.5 for West Lake and 0.55 for East Lake. Average ratios for five Sphagnum species calculated by Nott et al. (2000) were 0.63. Profiles of Paq indicate a subtle decline in West Lake since the late

1930s, with below mean values since the early 1960s, whereas East Lake is relatively

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stable, though there is evidence of a positive departure in the uppermost 2 cm (post-

1984) (Fig. 4.6).

Instrumental and proxy climate records

Meteorological data and climate reconstructions provide a broader environmental context from which to investigate ecological and organic matter changes in the Cape Bounty lake sediment records. A correlation analysis of climate records from the three closest meteorological stations (Rea Point, Melville Island, 100 km NE; Mould

Bay, Prince Patrick Island, 320 km NW; and Resolute Bay, Cornwallis Island, 420 km W;

Environment Canada, 2007; see Fig. 4.1 for locations) was conducted on seasonal and annual temperature and precipitation data spanning the lengths of the records in order to determine the most representative conditions at Cape Bounty. Significant (p<0.005) positive correlations were found between all three stations for summer (June, July,

August), winter (September, October, November, December, January, February, March,

April, May) and annual mean temperatures, whereas precipitation data produced weak correlations (Table 4.3).

Records indicate consistently above mean winter temperatures since the early

1990s, encompassing the recent period of peak diatom concentrations (Fig. 4.7a).

Temperature data recorded at Cape Bounty (2003-2010) appear to follow the station data but temperatures are notably higher in the period since the station data has been available; however, it is likely that the Cape Bounty data overestimated summer temperatures during this time since data collection did not always span the entire period

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of June 1st to August 31st (i.e., data collection initiated after June 1st and/or ended prior to August 31st in some years; Fig. 4.6a). In addition, it is likely that the proximity to the coast of Rea Point and Mould Bay stations introduces a moderating effect that is less pronounced at the Cape Bounty meteorological station, located 6 km inland.

Mass balance data from the ice cap on western Melville Island corroborate ameliorated climate conditions since the early 1990s, and demonstrate an overall decline spanning the length of the record, though the record is not continuous (Dave

Burgess, pers. comm., 2008; Fig. 4.6a). There are no other records of ice caps and glaciers in the western archipelago, but data from the eastern islands indicate a clear negative mass balance since the 1960s that has become even more pronounced since the mid-1980s (Boon et al., 2010), and an overall negative mass balance in recent decades has risen sharply since 2004 for the Arctic in general (Gardner et al., 2011).

Correlations were also conducted between temperature and precipitation data and West and East Lake varve thickness measurements (Table 4.3). The highest correlation occurred between West Lake varve thickness measurements and winter precipitation at Rea point (r=0.63, p<0.01). The East Lake varve series was most significantly correlated with annual precipitation at Rea Point (r=0.55, p<0.05). The

West Lake record suggests that winter precipitation has increased since the 1750s; however, declining sedimentation rates in East Lake imply lower mean annual precipitation spanning the length of the record (Fig. 4.6b).

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Discussion

Appearance of diatoms in the late- 20th century

The general absence of diatoms prior to the 1980s in West Lake and the 1960s in

East Lake suggests these lakes have experienced environmental changes unprecedented in at least the last ~250-300 years. Though the almost complete lack of valves in deeper sediments may be the result of dissolution, if this were the case we would have expected the concentration of fragments to show an earlier increase and subsequent decline concomitant with increased whole valve concentrations. In addition, the fragments observed were commonly of larger pennate taxa (Pinnularia, Eunotia) not associated with recent sediments or modern day assemblages of either lakes (Stewart and Lamoureux, submitted; Chapter 3), but appear to be similar to taxa observed in sediments from a pond situated between the two lakes and in saturated areas surrounding the lakes. Furthermore, an occassional pristine lotic diatom specimen was observed in the deep lake sediments, attesting to the potential for allochthonous diatom inputs and preservation. Finally, current chemical conditions in the lakes, including abundant dissolved silica, low salinity and alkalinity, neutral pH, and that the lakes are not exceptionally shallow or deep, are not typically associated with diatom dissolution

(Table 4.1; Wetzel, 2001). As such, we believe that the few fragments and whole diatom valves observed in deeper sediments did not originate from within the lakes, but rather were washed in during seasonal runoff, and that the recent development of diatom communities in the two lakes signify braoder environmental changes.

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Compositional changes in the assemblages of West and East Lake, notably the increase in Cyclotella pseudostelligera in both lakes, accompanied by a decrease in

Aulacoseira ambigua in West Lake, are consistent with changes observed in other Arctic lakes and ponds that are increasingly being recognized as a unified response to external forcings (e.g., Rhüland et al., 2008). For example, in the High Arctic Perren et al. (2003) report a shift from an initially Fragilaroid assemblage in the early 20th century to an assemblage dominated by planktonic taxa including Cyclotella bodanica taxa in pre-1997 sediments. Paul et al. (2010) noted an expansion of small Cyclotella species and concurrent decline in Aulacoseira lirata in the uppermost sediments of a Low Arctic lake, and Adams and Finkelstein (2010) report small Cyclotella species appearing around 1965 in lakes on Melville Peninsula, in the Middle Arctic. Expanding Cyclotella communities are also being reported in high latitude European lakes (e.g., Bigler and Hall, 2003).

Aulacoseira taxa, initially competitive under expanding open water conditions, may become less competitive than small Cyclotella taxa under conditions of greater thermal stability and increased competition, due to its relatively heavy frustules with high silica demands and requiring greater turbulence to remain suspended in the photic zone

(Rhüland and Smol, 2005; Rhüland et al., 2008). Though it is unclear why West Lake would support Aulacoseira but not East Lake, the success of Cyclotella elsewhere in the

Arctic is attributed to the expansion of the planktonic environment in response to a decrease in the extent and duration of ice cover resulting from climate warming (Perren et al., 2003; Smol et al., 2005; Adams and Finkelstein, 2010; Paul et al., 2010). In addition, recent synchronous changes observed across multiple algal groups favours

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broad scale environmental change rather than internal algal interactions as a more likely explanation (Antoniades et al., 2007).

More generally, the recent emergence of diatom communities in the Cape

Bounty lake sediment records are consistent with mounting evidence of circum-polar changes in aquatic ecosystems attributed to climate change and associated impacts on ice cover, thermal regimes and nutrient dynamics since the mid-19th century (Smol et al.,

2005). Though most reports indicate earlier shifts in diatom species than at Cape

Bounty, these studies are largely focused on small, shallow pond systems. However, reports of recently emerging or expanding diatom communities that coincide with the onset of appreciable diatom concentrations in the Cape Bounty lakes are also being observed in larger systems. For example, Doubleday et al. (1995) noted an almost complete lack of diatom valves in pre-1950 sediments in Lower Dumbell Lake, northern

Ellesmere Island, and Perren et al. (2003) reported the onset of significant diatom production in Sawtooth Lake, central Ellesmere Island, commencing in the 1920s after being absent from the remainder of the 2500 year record. Studies with longer diatom records have also reported major changes in composition and productivity coinciding with the latter half of the 20th century. Antoniades et al. (2005) reported modest increases in the number of species observed in post-1920 sediments, followed by a sharp increase beginning in the 1990s in a small lake on Ellesmere Island, and Gajewski et al. (1997) reported significant increases in diatom productivity during the 20th century, with major increases in the 1920s and 1950s, in a lake on Devon Island. Finally, major shifts in diatom communities commencing in the late 1980s were also observed in

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relatively deep lakes in the High Arctic (Michelutti et al., 2003) and Middle Arctic

(Stewart and Lamoureux, 2005). The comparatively late onset of diatom changes in lake records like those at Cape Bounty compared to smaller and more frequently reported pond records is suggestive of differing thresholds related to ice-cover and thermal storage capacities (Michelutti et al., 2003; Stewart and Lamoureux, 2005; Antoniades et al., 2005), although this is difficult to establish due to the inherently coarse chronological resolution of small pond records with low sedimentation rates.

Littoral-profundal disconnection

Despite the consistency with other Arctic records, the abundance of apparently planktonic taxa relative to benthic species in the Cape Bounty lakes is counter-intuitive to what would be expected from these relatively large deep lakes characterized by a short ice-free season (East Lake) or near-perennial ice-pan (West Lake), which should favour benthic production in the littoral zone (Douglas and Smol, 1999). However, the lack of diatoms below the uppermost sediment only indicates that conditions were unfavourable for a planktonic community to develop. Analysis of the contemporary assemblages and comparison to surface sediments and sediment traps indicate a degree of disconnection between the benthic environment and deep lake (i.e., profundal) valve deposition that results in an under-representation of benthic taxa compared to planktonic and lotic species in the sedimentary record of both lakes (Stewart and

Lamoureux, submitted; Chapter 3). Moreover, this disconnection appears to be greater in East Lake, as significantly higher valve concentrations in West Lake sediments

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suggests a stronger connection with the littoral environment. Studies elsewhere employing sediment traps to investigate the contribution of diatoms to the sedimentary record have also reported a disparity between the actual living community and relative contributions to the sedimentary record and the potential to misinterpret the fossil record (Köster and Pienitz, 2006; Woodbridge and Roberts, 2010).

Given the littoral-profundal disconnection, changes in the sedimentary record are likely to provide only a partial picture of recent diatom dynamics, and diatom productivity may have existed prior to the recent accumulation of valves in the sedimentary record. Given that the benthic community is under-represented but not altogether unrepresented in recent sediments, the absence of valves below the uppermost sediments may signify an even greater disconnect with the littoral environment, or low but not entirely non-existent benthic diatom productivity, prior to the late 20th century. If conditions were unfavourable for planktonic diatoms to grow, this may have manifested as an overall lack of diatoms in deep lake sediments.

Regardless, the recent expansion of a diatom community in these adjacent lakes signifies a profound change in conditions in both lakes that is consistent with an external forcing mechanism, and lends support to the hypothesis that deeper, more northerly lakes exhibit higher ecological thresholds to climate change.

Asynchronous ecological thresholds

Further to the ecological threshold hypothesis, we would expect climate changes that promote open water conditions and favour planktonic growth to be recorded

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earlier in East Lake, which is shallower, warmer and consistently loses its ice cover earlier and more completely than West Lake (Smol and Douglas, 2007). In light of this, the initial appearance of diatoms in the mid-1960s in East Lake most likely represented the introduction of diatoms in this system, despite the subsequent interruption and reappearance in the late 1980s. In addition to differences in timing, the similar character of the observed changes in both lakes support the hypothesis of an external forcing mechanism rather than internal lake dynamics such as species interactions or grazing pressures. In addition, differences in the timing of biochemical changes in Chl-a, C/N ratios and lipid fractions reflect an earlier onset of ecological changes occurring in East

Lake compared to West Lake. Fluxes of Chl-a indicate higher and more variable deposition commencing in the early 1920s in East Lake, and between the early 1930s and 1950s in West Lake. West Lake atomic C/N ratios also demonstrate more variable and generally higher values beginning in the late 1930s. The fact that Chl-a fluxes in both lakes increase before the initiation of diatom productivity suggests that diatoms may exhibit a delayed response to environmental changes compared to other algal groups. Changes in algal pigments in a shallow lake on Ward Hunt Island in the High

Arctic preceded the onset of diatom productivity, affirming that changes in limnological conditions can predate changes recorded in the fossil diatom record (Antoniades et al.,

2007). Nevertheless, these results collectively point to a lower ecological threshold to external climate forcing in East Lake.

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Influence of sedimentation rates

The first appearance and subsequent interruption of the East Lake diatom record may be related to changes in sedimentation rates. A large increase in sedimentation rates in the 1960s due to sub-aqueous slumping may have entrained diatom valves from shallower locations, a hypothesis supported by the specific content of the assemblage

(e.g. A. laevis, C. rossii , D. oblongella, N. cincta,N. perminutum, S. smithii) and their associated benthic and/or lotic affinities (Stoermer, 1978; Potopova, 1996; Soininen et al., 2004; Garcia et al., 2008; Antoniades et al., 2009), as well as the relative disconnection between the benthic environment and accumulation in deep lake sediments. Alternatively, diatom production could have been halted by this change in sedimentation due to a sudden change in chemical or physical (i.e., turbidity and light penetration) factors, or sufficiently diluted by high sedimentation rates associated with turbid river inflow. The re-establishment of diatoms in East Lake (early 1990s) may be the result of high sedimentation rates continuing into the 1980s. Regardless, the fact that diatoms are absent throughout the earlier sedimentary record, despite major changes in sedimentation rates, suggest that diatom production only initiated in East

Lake in the latter part of the 20th century, further suggestive of major ecological changes in recent sediments.

The possible influence of sedimentation rates on diatom concentrations is further supported by other proxies demonstrating departures coinciding with major depositional events. For example, atomic C/N ratios become higher and more variable

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coinciding with a major depositional event in West Lake in the 1930s and 1940s. Since increases in C/N ratios are associated with greater terrestrial inputs, it is not surprising that C/N ratios would co-vary with sedimentation rates. In addition, West Lake Chl-a fluxes demonstrate higher and more variable rates coinciding with a prolonged period of higher than usual sedimentation rates in the latter half of the 20th century and East Lake inferred Chl-a also appears to mimic sediment accumulation rates.

Between-lake differences in aquatic-terrestrial linkages

Based on correlations between West and East Lake varve series and precipitation data from Rea Point, the closest meteorological station, varve thicknesses from West

Lake suggest that winter precipitation has increased since the 1750s. Agreement between winter precipitation and West Lake varve thicknesses are consistent with findings from a previous study conducted on hydrometeorological controls on sediment delivery to the Cape Bounty lakes, which indicated winter precipitation (snow water equivalence) as the dominant control on suspended sediment yields (Cockburn and

Lamoureux, 2008a). The influence of winter snow accumulation and subsequent runoff at Cape Bounty extends to sediment delivery and nutrient fluxes to the lake, with implications for lake productivity (Cockburn and Lamoureux, 2008a, b; Stewart and

Lamoureux, 2011). The relationship between West Lake varve thickness and winter precipitation is more generally supported by evidence of increased river discharge in the circumpolar region in response to higher temperatures and positive precipitation anomalies associated with the North Atlantic Oscillation (NAO; Peterson et al., 2006),

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though there is also support for declining runoff and dryer overall conditions in lakes and ponds (due to enhanced evaporation) in the Canadian Arctic (Forbes and

Lamoureux, 2005; Smol and Douglas, 2007). Regional climate records indicate increasing temperatures (particularly during the winter months) and precipitation since at least the 1990s, though precipitation records are discontinuous and station records are less coherent.

Given the steeper gradient and deeper channels of the West Lake catchment and the colder lake conditions and more prolonged ice cover (Table 4.1), it is plausible that

West Lake is more strongly influenced by winter snowpack accumulation than East Lake.

This is supported by seasonal hydrochemical data indicating a closer connection between river and lake nutrient conditions in West Lake under rapid melt conditions due to ice obstruction and ponding in the more deeply incised channels of West River, despite higher overall discharge into East Lake (Cockburn and Lamoureux, 2008a;

Stewart et al., 2011). In addition, extensive field measurements (2003-10) demonstrate greater sediment availability in the West Lake catchment, at least in recent years, likely due to permafrost degradation and a deepening active layer that manifest in greater mobilization of surface soils in the steeper West Lake catchment (Lamoureux and

Lafrenière, 2009).

Declining sedimentation rates in East Lake imply lower mean annual precipitation spanning the length of the record, which is inconsistent with regional climate trends.

This points to the complex relationship between climate and sedimentation rates, a product of the nature and abundance of available sediment (e.g., active layer depth,

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vegetation coverage and character) and the efficiency of sediment transport (e.g., channel characteristics, slope angle, runoff) (Cockburn and Lamoureux, 2008a, b). As such, sedimentation rates express a combination of direct and indirect climatic influences that can manifest as either increases or decreases in sedimentation rates and can change over time. For example, higher precipitation rates could manifest as lower sedimentation rates in East Lake if a deepening active layer resulted in disproportionately greater soil water storage. Nevertheless, the decline in sedimentation rates in East Lake indicates a reduction in the availability or delivery of sediment associated with the snowmelt period and a more complex relationship between runoff efficiency, sediment availability, and deposition. This may also explain lower concentrations of diatom valves in East Lake compared to West Lake, despite being a more productive system. The more complex nature of the East Lake catchment is echoed in C/N ratios, inferred Chl-a fluxes and lipid geochemistry, which all suggest a greater influence of internal rather than external dynamics.

Key differences in bulk elemental, pigment and lipid geochemistry shed additional light on how broad scale climatic influences are filtered by site-specific factors. Increasing C/N ratios in West Lake in post-1930s sediments, indicative of higher terrestrial organic inputs (Meyers, 1994), coincide with increased sedimentation rates and Chl-a fluxes, suggesting the sedimentary Chl-a record may reflect changes in the terrestrial environment or the delivery of terrestrial organic matter to the lake.

However, it is more likely that higher Chl-a concentrations are indicative of increased aquatic productivity, though not enough to shift the C/N imprint, given that land-derived

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pigments rarely survive transport from the terrestrial environment (Meyers and

Ishiwatari, 1993). This suggests that the West Lake OM record reflects coincident changes in both terrestrial inputs and aquatic productivity. In the uppermost sediments, corresponding to the post-1980s period, below mean C/N ratios and high Chl-a fluxes coincide with relatively muted sedimentation rates, suggestive of increased aquatic contributions during this time, though terrestrial contributions appear to remain dominant (C/N>10).

By contrast, lower C/N ratios in East Lake suggest higher autochthonous productivity and less overall variability, perhaps reflecting a more buffered response to external dynamics and changes in terrestrial inputs. This is consistent with findings of a clearer relationship between West Lake sedimentation rates and regional climatic trends. However, a recent period of low sedimentation rates beginning in the 1980s correspond with the lowest C/N ratios and a decline in Chl-a fluxes, possibly reflecting reduced delivery of terrestrial inputs to West Lake during this time. The generally muted response in the East Lake C/N record coincides with increasing and more variable

Chl-a fluxes since the 1920s, suggesting photosynthetic productivity increases are primarily driven by aquatic productivity in this system. This is supported by 2003 and

2004 water chemistry analyses indicating significantly higher concentrations of water column Chl-a in East Lake compared to West Lake (Stewart and Lamoureux, 2011).

Nevertheless, sedimentary solvent extracts are dominated by HMW lipids and reflect the important contribution of terrestrial OM in both West and East Lakes. Long- chain n-alkanes, n-alkanoic acids and n-alkanols are major components of the

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epicuticular waxes of higher plants (Eglinton and Hamilton, 1967; Otto and Simpson,

2005). In addition, the predominance of high even Cn molecules (n-alkanols and n- alkanoic acids) and high odd Cn molecules (n-alkanes), as indicated in CPI values, are typical of higher plant origin (Hedges and Prahl, 1993). Conversely, short-chain (

Russell, 1984). In particular, short-chain unsaturated n-alkanoic acids are major components of freshwater algae (Cranwell, 1987). However, the preferential degradation of aquatic plant lipid relative to terrestrial sources, likely due to their relative “freshness”, inflates the importance of terrestrial lipids in the lake sedimentary record (Meyers and Ishiwatari, 1993) despite limited evidence of OM degradation in these lakes, suggesting algal and bacterial contributions from the aquatic environment are likely to have been greater than the data indicates. This might explain the complete absence of the C17-alkane, a known algal biomarker, in both lakes (Kawamura et al.,

1987).

It is likely that preferential degradation of algal lipids is more pronounced in East

Lake compared to West Lake, since long-chain lipids characteristic of vascular land plants overwhelm their short-chain homologues in the sedimentary record, despite low atomic

C/N ratios indicating a predominantly aquatic OM contribution. This apparent contradiction is not unexpected (e.g., Goossens et al., 1989), and warrants careful interpretation of down-core changes in OM sources as relative rather than absolute.

The subtle trend toward higher n-alkane TAR in East Lake spanning the record until approximately 1972 suggests increasing terrestrial inputs until this time, but algal

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productivity also may have been dampened by an increase in microbial and benthic reworking as a consequence of warmer water temperatures and greater lake productivity (Kuder and Krude, 1998). The exclusive occurrence of the short-chain C19- alkane in deeper sediments of East Lake compared to throughout the West Lake record lends support to this hypothesis. In addition, the decline in East Lake sedimentation rates and consequent slower burial of the more volatile lipid fractions may have resulted in increasing diagenetic losses toward the present (Meyers and Ishiwatari, 1993). The presence of bottom water anoxia in West Lake, at least in recent years (Lewis et al., in press), likely also contributes to a more intact OM record (Meyers and Ishiwatari, 1993).

Thus, trends in West Lake HMW homologues and HMW:LMW ratios throughout the latter half of the record agree with our interpretation of a stronger terrestrial OM signal in West Lake sediments.

Despite the potential exaggeration of terrestrial OM due to the effect of selective preservation of terrestrial plant lipids and selective degradation of aquatic flora, a distinct period of enhanced aquatic productivity has occurred in East Lake in the last several decades. The n alkane TAR values signify an increase in aquatic OM contributions in post-1972 sediments, as do trends toward lower HMW:LMW in n- alkanol and n-alkanoic fractions. The greater susceptibility of n-alkanoic acids to microbial degradation compared to n-alkanols and n-alkanes, particularly the short- chain unsaturated homologues characteristic of freshwater algae (Cranwell, 1987; Otto and Simpson, 2005), lends further support to our hypothesis of a recent increase in aquatic productivity in East Lake, as do lower C/N ratios. The pronounced increase in

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Chl-a flux prior to this suggests a trend toward increased aquatic productivity likely started earlier, but higher sedimentation rates and, consequently, higher terrestrial inputs may have dampened the effect of higher aquatic productivity on n-alkane TAR values and C/N ratios during this time.

Biomarkers of changes in aquatic and terrestrial vegetation

The detected sterols campesterol, β-sitosterol and stigmasterol are most abundant in higher plants (Bianchi et al., 1995; Harwood and Russell, 1984), but can also be produced by freshwater phytoplankton (Volkman, 1986). Concentrations of cholesterol were plotted separately because they are mainly derived from animals, fungi, algae and emergent plants (Weete, 1976; Harwood and Russell, 1984; Meyers and

Ishiwatari, 1993). The absence of ergosterol, a known biomarker for fungi (Weete,

1976), the sparseness of wildlife in this High Arctic desert biome, and the general absence of emergent macrophytes in West and East Lake suggest that cholesterol is primarily of algal origin in this environment.

The sterol record in West Lake suggests that trends in the concentration of terrestrial inputs are similarly expressed in algal contributions, lending further support to our earlier claim of simultaneous increases in aquatic productivity and terrestrial OM contributions. In East Lake, the decline in total steroid concentrations toward the present, despite gradually increasing cholesterol concentrations, also supports our earlier claim of reduced importance of terrestrial inputs relative to aquatic algae in this system. The recent increase near the surface of the core corresponds to the upper 2 cm

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and coincides with the recent increase in diatom productivity since the mid-1980s, lending further support to the notion that cholesterol is primarily algal in this system.

The fact that cyclic lipids (sterols) do not degrade as quickly as aliphatic lipids (Otto and

Simpson, 2005), and that measures of OM degradation indicate relatively unaltered OM overall, suggest that trends in sterol contributions accurately reflect past contributions.

Carbon number predominance can provide insight on specific OM sources. In addition, changes in carbon distribution patterns can signify either relative changes in

OM source inputs, or overall changes in catchment or aquatic OM sources. Cn maxima in all aliphatic lipids in West Lake and in n-alkanoic acid and n-alkanol fractions in East Lake suggest stable catchment vegetation spanning the record. The most abundant n-alkanoic acids are C24 in both lakes, with departures to unsaturated C18 molecules in the upper portion of both records. Ratios of unsaturated to saturated C18-alkanoic acids offer an indication of the contribution of algae, since algae are enriched in unsaturated acids

(e.g., C18:1 and C18:2; Cranwell, 1987; Fig. 4.6). Hence, departures in Cn predominance to unsaturated acids and the concomitant increase in unsaturated:saturated C18 ratios in the 1960s in West Lake and the 1950s and 1980s in East Lake likely reflect periods of enhanced algal productivity, though significantly higher concentrations of unsaturated

C18 molecules suggest relatively greater increases in algal productivity in East Lake.

Both n-alkane records indicate a C31 maximum in the oldest sediments, which have been previously associated with grasses as the dominant catchment vegetation

(Cranwell, 1973; Otto and Simpson, 2005). Above this, a consistent C27 predominance in

West Lake indicates stable terrestrial OM sources. Greater efficiency of the West Lake

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catchment in delivery of terrigenous OM is also evident in the absence of α-amyrin, a known angiosperm biomarker (Bianchi, 1995; Otto and Simpson, 2005), in the East Lake record, despite angiosperms (e.g., Carex species) being a dominant component of the terrestrial vegetation in both catchments (Atkinson and Trietz, 2007). While C27-alkane predominance has been associated with deciduous forest cover (Meyers and Ishiwatari,

1993), isotopic C analysis of sediments and individual leaves in an English lake catchment indicated C25-29-alkanes were specifically associated with willow trees (Rieley et al.,

1991). Arctic willow is a common species in the Cape Bounty watersheds, and the greater vegetative coverage in the West Lake catchment, combined with a stronger terrestrial signal in the sedimentary OM record, may be contributing to the steady dominance of the C27-alkane in West Lake sediments, though it is impossible to assign a specific source to the dominant C27-alkane without comparing series distributions in sediments to species samples. Series distribution of n-alkanes in East Lake is comparatively more variable, suggesting changes in OM source materials consistent with greater autochthonous contributions. A trend toward lower Cmax is characterized by the appearance of C25 and C23 maximums toward the surface of the core. Whereas long chain alkanes (C27+)are associated with terrestrial plants, short and mid chain n-alkanes

(i.e., ≤C25) serve as biomarkers for lacustrine-derived OM (Ficken et al., 2000; Zech et al.

2010).

Ratios of odd C n-alkanes (e.g., Paq and PaqSphagnum) shed light on the relative contributions of aquatic macrophytes, algae and terrestrial vegetation (Ficken et al.,

2000; Nott et al., 2000; 2006; Vonk et al., 2008). Similar mean Paq values for both lakes

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suggest primarily macrophytic source of sedimentary OM. However, ratios of

PaqSphagnum bear a striking resemblance to Paq, indicating ratios from Cape Bounty are most closely aligned with submerged macrophytes and Sphagnum. Since macrophytes, submerged or otherwise, are sparse in both lakes, the strong terrestrial OM signal likely reflects the predominance of bryophytes such as Sphagnum in both catchments

(Atkinson and Treitz, 2007). Despite similar mean values, profiles of Paq from the two lakes diverge in the upper part of the record, with West Lake values demonstrating a subtle decline since the 1940s, potentially indicating lower contributions of non-vascular plants and/or higher contributions of vascular plant OM. In contrast, East Lake reflects a more stable contribution of non-vascular OM, though the contribution appears to increase in post-1984 sediments.

Overall, specific biomarkers in both lakes appear to reflect the existing catchment vegetation which is dominated by grasses and non-vascular plants (e.g.,

Sphagnum). Greater contributions of bryophytes in East Lake in recent decades may reflect conditions on an adjacent saturated slope comprised primarily of non-vascular plants, which is continually fed by a late-lying snow bank that drains through the slope and into the north shore of the lake, thereby supplementing stream channel inputs.

West Lake lacks this distinct marginal feature, and runoff is primarily channelled by the main stream outlet from throughout the catchment, including upland areas dominated by vascular plant species.

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Conclusion

Despite similar water chemisty, morphological characteristics, geological and climatological conditions, differences between West and East Lake paleoecological records indicate that external forcings are filtered by different connections with the surrounding terrestrial environment and internal lake dynamics. The earlier onset of diatom productivity in East Lake compared to West Lake is likely a function of a shallower basin that is warmer and loses its ice cover sooner, resulting in an earlier and more pronounced response to climate warming trends. The nature and timing of the recent appearance of diatoms is consistent with numerous other high latitude studies, which strongly suggest recent climate warming and associated impacts on limnological conditions are driving these changes. Early response in the East Lake diatom community compared to West Lake is likewise represented in even earlier changes in other paleoenvironmental indicators, including inferred Chl-a, C/N ratios and source-specific organic molecules, collectively suggesting a lower overall threshold to environmental change beginning circa the 1920s in East Lake and the 1940s in West Lake. The fact that

Chl-a, C/N ratios and lipid biomarkers reflect environmental changes occurring prior to the onset of diatom productivity suggests that the appearance of diatoms signifies the crossing of an important ecological threshold in recent decades.

Sedimentary records from West and East Lake demonstrate differences in the contributions of aquatic and terrestrial organic matter that can be explained by differing autochthonous productivities and terrestrial connections. Higher overall C/N ratios in

West Lake reflect the larger relative contribution of terrestrial OM and indicate

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increasing terrestrial OM contributions since the 1940s that coincide with higher sedimentation rates associated with increased winter snowfall and, possibly, greater sediment availability due to a deepening active layer. In contrast, East lake OM reflects a predominantly aquatic source that appears relatively insensitive to changes in sedimentation rates. Atomic C/N are consistently low throughout the record, with a decrease to the lowest C/N ratios in the upper 2 cm, reflecting an increase in algal productivity that is consistent with the emerging diatom community. The recent development of a West Lake diatom community can likewise be seen in lower C/N ratios in the uppermost sediments, indicating that aquatic productivity in this system is also increasing, but is still exceeded by terrestrial OM contributions.

Solvent-extractable lipid compounds corroborate the stronger connection between West Lake and the terrestrial environment, and point to enhanced aquatic productivity as the dominant influence on the East Lake OM record. Whereas both lakes exhibit greater abundances of terrestrially-derived aliphatic and cyclic lipids, conditions in East Lake (i.e., higher aquatic productivity) likely favour greater microbial activity and enhanced degradation of the more susceptible aquatic lipid fraction compared to West

Lake, thereby reducing the importance of aquatic contributions in the sedimentary record. Moreover, trends in the least susceptible lipid fractions (n-alkanes, HMW aliphatic lipids, steroids) and specific biomarkers of aquatic microorganisms (e.g., LMW n-alkanes, iso-alkanoic acids) indicate enhanced aquatic productivity over the last century.

161

Acknowledgements

This work was supported by a National Science and Engineering Research Council of Canada (NSERC) Discovery Grant to SFL, and a NSERC PGS-D Scholarship, Northern

Scientific Training Program (NSTP) Award, Queen’s Graduate Award, and McDonald-

Sinclair Travelling Scholarship to KAS. We would also like to thank the Polar Continental

Shelf Program, Natural Resources Canada for logistical support in conducting field research. We gratefully acknowledge field assistance by D. Atkinson, J. Wall, G.

Hambley, A. Forbes, J. Cockburn, D. Macdonald, E. Wells and F. Forsythe. We are especially grateful to S. Finkelstein and E. Kjikjerkovska for laboratory accommodation and assistance. This is PCSP/PPCP contribution #011-15.

162

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Tables

Table 4. 1 Major physical and chemical attributes of the Cape Bounty lakes.

Attribute West Lake East Lake Max. depth (m) 35 32 Surface area (km2) 1.4 1.6 Lake volume (m3) 21 400 21 900 Catchment area (km2) 8.0 11.6 Based on 2003-2004 seasons: Mean turnover rate (yrs) 22.4 16.7 Max. discharge (m3 s-1) 1.57 1.76 Mean mid-July surface water temp (°C) 1.1 2.7 Mean pH 7.4 7.4 Mean conductivity (µS s-1) 38 52 Mean TN- F 0.26 0.17 Mean TP-F (mg l-1) 0.011 0.008 Mean Chl-a 1.0 1.85 Mean DOC (mg l-1) 1.4 1.3 Ice-off (2003-2010) Mid-July to Early July to persistent mid-August ice-pan

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Table 4. 2 Relative abundance data of common (≥2%) species and authorities from West Lake and East Lake sediment core samples.

Species and authority Mean (%) Min (%) Max (%) West Lake Achnanthes daonensis Lange-Bertalot 4.7 2.8 7.5 Achnanthidium minutissimum (Kützing) Czarnecki 7.5 2.9 11.7 Aulacoseira ambigua (Grunow) O. Müller 17.3 0.7 39.3 Cyclotella pseudostelligera Hustedt 35.4 11.9 66.2 Cyclotella rossii Håkannson 12.5 5.5 22.3 Diadesmis contenta (Grunow ex Van Heurck) D.G. Mann 1.2 0.0 3.3 Diadesmis gallica W. Smith 1.2 0.0 3.1 Fragilaria capucina var. capucina Desmazières 1.3 0.0 2.9 Nitzschia perminutum (Grunow) M. Peragallo 1.2 0.5 2.2 Psammothidium chlidanos (Hohn & Hellerman) Lange-Bertalot 0.7 0.0 2.3 Proportion of all valves counted 83 72 89

East Lake Achnanthes laevis Østrup 0.9 0.0 3.6 Achnanthes laterostrata Hustedt 1.1 0.0 2.6 Achnanthes saccula J.R. Carter 0.9 0.0 2.2 Cyclotella pseudostelligera Hustedt 14.0 0.0 27.6 Cyclotella rossii Håkannson 56.4 44.3 68.0 Diadesmis gallica W. Smith 0.6 0.0 2.5 Diploneis oblongella (Nägeli) Cleve-Euler 1.5 1.0 2.2 Fragilaria capucina var. gracilis (Østrup) Hustedt 4.1 0.0 8.1 Fragilaria tenera (W. Smith) Lange-Bertalot 1.2 0.0 2.2 Navicula cincta (Ehrenberg) Ralfs 1.0 0.0 3.2 Nitzschia perminutum (Grunow) M. Peragallo 1.8 0.8 2.8 Stauroneis smithii Grunow 0.7 0.0 2.9 Proportion of all valves counted 76 93 84

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Table 4. 3. Mean annual, mean summer and mean winter Pearson Product Moment correlation coefficients (r) for the three weather stations most proximal to the study site: Mould Bay, Prince Patrick Island (MB; 1948-2007), Rea Point, Melville Island (RP; 1969-2007), and Resolute Bay, Cornwallis Island (RB; 1948-2007) and for West Lake and East Lake varve thickness records. See Fig. 4.1 for station locations. Correlations at significance levels of p<.05 are indicated in bold, and number of samples and significance level are in parentheses (n, p<). Summer includes those months when mean minimum monthly temperature >0 °C (i.e., June, July, August) and winter includes months in which mean maximum monthly temperature is <0°C (i.e., September, October, November, December, January, February, March, April, May).

West Lake East Lake RP RB varves varves Temperature Annual MB .76 (20, 0.0001) .83 (57, 0.0001) -.11 (52, 0.5) -.11 (57, 0.5) RP .77 (20, 0.0001) -.58 (16, 0.05) -.24 (20, 0.5) RB -.15 (54, 0.5) -.18 (59, 1.0) Summer MB .79 (21, 0.001) .76 (58, 0.001) .06 (53, 1.0) -.01 (59, 1.0) RP .78 (21, 0.001) -.52 (17, 0.05) .13 (21, 1.0) RB -.04 (54, 1.0) -.02 (59, 1.0) Winter MB .85 (20, 0.001) .78 (57, 0.001) -.04 (52, 1.0) -.25 (57, 1.0) RP .89 (20, 0.001) -.18 (16, 1.0) -.29 (20, 0.5) RB -.10 (54, 0.5) -.28 (59, 0.05) Precipitation Annual MB .58 (16, 0.05) .37 (52, 0.01) .03(48, 1.0) -.13(52, 0.5) RP .00 (16, 1.0) .00 (16, 1.0) .55 (16, 0.05) RB .03 (48, 1.0) -.13 (52, 0.5) Summer MB .54 (17, 0.05) .40 (53, 0.005) -.05 (49, 1.0) -.10 (53, 0.5) RP .26 (17, 0.5) -.08 (17, 1.0) .17(17, 1.0) RB -.15 (54, 0.5) -.05 (59, 1.0) Winter MB .15 (16, 1.0) .30 (52, 0.05) .08 (48, 1.0) .00 (52, 1.0) RP .34 (16, 1.0) .63 (16, 0.01) .394 (16, 1.0) RB -.02 (54, 1.0) -.06 (59, 1.0)

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Figures

Figure 4. 1 Study site indicating the location of East and West Lakes near Cape Bounty, Melville Island, in the Canadian High Arctic (top panel), indicating the location where sediment cores were retrieved. Meteorological and hydrologic data collection sites are also indicated. The locations of regional climate stations referred to in the text are indicated in the top panel.

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Figure 4. 2 a) Chronology for West Lake based on cumulative varve thickness measurements corroborated with 137Cs and 210Pb isotopic dating methods. Inset depicts concentrations of 137Cs with depth, indicating the initial rise and peak concentration of 137Cs corresponding to the approximately 1954 and 1963, respectively. The 210Pb dates are based on a CRS age model applied to the excess 210Pb inventory (far right panel). b) The East Lake chronology is based on cumulative varve thickness measurements from core 07EL01, corroborated with cumulative varve thickness measurements and 137Cs dating profiles from core 05EL11. Inset depicts 137Cs concentrations with depth, representing the depth at which nuclear weapons testing began (~1954) and peaked (1963).

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178

a) West Lake

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Figure 4. 3 Stratigraphy of common diatoms (≥2% in one or more sample depths), concentration profiles of valves, valve fragments and chrysophyte cysts, inferred Chl-a fluxes and sedimentation rates for a) West Lake and b) East Lake. Chronologies at the far left and right are based on varve counts.

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b) East Lake

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Year (AD) Year

Figure 4. 4 Total extract yields and concentrations of the dominant aliphatic (n-alkane, n-alkanol, n-alknanoic acids) and cyclic (sterols and derivatives) lipids in sediment extracts from a) West Lake and b) East Lake. All concentrations are normalized to % organic carbon. Steroids detected include β-sitosterol, campesterol, stigmasterol, cholesterol, stigmastanol and cholestanol. Chronology of sequences is based on varve years corresponding to each 0.5 cm depth interval.

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Figure 4.5 Indicators of degradation and diagenesis of lipid fractions for a) West Lake and b) East Lake, including carbon preference indices (CPI) and concentrations and ratios of high molecular weight (HMW; long-chain) and low molecular weight (LMW; short-chain) homologues of n- alkanes, n-alkanols and n-alkanoic acids. CPI n-alkane = ∑odd Cn/∑even Cn; CPI n-alkanol and n- akanoic acid = ∑even Cn/∑odd Cn. HMW:LMW n-alkane ratios also serve as a proxy for terrestrial and aquatic OM inputs, and therefore follow the equation for terrigenous-aquatic inputs (TAR = (C27+C29+C31)/(C17+19+C21)) presented by Bourbonniere and Meyers ( 1996). Ratios for n-alkanols and n-alkanoic acids are based strictly on the number of carbon atoms (i.e. greater than or less than 20). Shading corresponds to CPI values indicative of significant degradation (i.e., ≤2).

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Figure 4. 6 Proxy indicators of past terrestrial and aquatic organic matter dynamics for a)West Lake and b) East Lake, including Corganic/Ntotal (C/N), total organic carbon (%OC), and Cn predominance (i.e., Cmax) profiles of the major aliphatic lipid classes. Odd Cn-alkane ratios of Paq =(C23+C25)/(C23+C25+C27+C29) and Paq Sphagnum=C23/(C23+C29) serve as a proxy to separate terrestrial from macrophytic plant contributions (Nott et al., 2000; Ficken et al., 2000).

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Figure 4. 7 Composite of climate and proxy records including a) temperature records from Mould Bay, Prince Patrick Island, Rea Point, Melville Island, Resolute Bay, Cornwallis Island, and Cape Bounty, Melville Island (refer to figure 4.1 for station locations) and changes in mass balance of the Melville Ice Cap. Note that summer refers to the months when mean maximum monthly temperatures are greater than zero (June, July and August), and winter includes the months in which mean maximum monthly temperature is less than zero (September, October, November, December, January, February, March, April and May), and b) longer record of varve thickness measurements and associated calendar year for East Lake and West Lake. Shading illustrates the timing of the initial development of diatom communities and peak valve concentrations in each lake. 184

Chapter 5: Summary and Conclusions

Similarities between West Lake and East Lake highlight the importance of proximity and otherwise similar settings (e.g., climate, geology, vegetation) in shaping both present and past limnological conditions. Both lakes were relatively dilute and had low nutrient concentrations due to the combined effect of the majority of runoff occurring while the ground was still frozen, and the relatively short growing season and lake-ice cover, which limit nutrient recycling and productivity. Limnological conditions at

Cape Bounty generally agreed with those of other Arctic freshwater systems, and differences were largely explained by geological setting and basin and catchment morphology.

Both contemporaneous lake diatom assemblages were dominated by small

Cyclotella species (C. pseudostelligera and C. rossii). The recent emergence of Cyclotella species in the sedimentary record of both lakes is consistent with numerous other observations of recently expanding planktonic communities in high latitude freshwater systems, collectively suggestive of ameliorated climate conditions and associated effects on lake thermal and ice-cover regimes. Species diversity was roughly the same in the two lakes, and the majority of common species were found in both lakes. In addition, the diatom assemblages were also characterized by numerous benthic and lotic species not uncommon in other Arctic sites, suggesting a degree of coherency between the two lakes and with Arctic freshwater systems in general.

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Variation in species composition within each lake was greatest between microhabitats (spatially rather than temporally), particularly between benthic and planktonic assemblages, most likely reflecting the short growing season and limited potential for seasonal succession. In addition, sediment trap and deep lake surface sediments revealed an assemblage most closely resembling the planktonic assemblage, with limited benthic inputs, revealing a degree of disconnection between the littoral zone and deep lake sediments. As a result, information about the benthic community is limited in the sedimentary record. This holds implications for interpreting past diatom communities, whereby an absence of valves may not mean a complete lack of a diatom community, but rather the absence of a planktonic community and a more limited benthic community. These findings create an opportunity to refine interpretations of past environmental conditions based on fossil diatom assemblages and advocate for the importance of understanding existing diatom communities at seasonal and sub-seasonal scales. As such, subsequent environmental reconstructions based on the fossil diatom record from West and East Lake might be best suited to questions related to catchment hydrology (i.e., the contribution of lotic taxa) and lake ice conditions (i.e., the contribution of planktonic taxa).

In addition to limnological and diatom records, both lake sediments contain organic matter contributions dominated by terrestrial inputs, reflecting the oligotrophic and low productivity status common to lakes subjected to prolonged periods of cold and dark. However, both lakes also indicated an increase in productivity in the early 20th century unprecedented since at least 1671 in West Lake and 1755 in East Lake (i.e.,

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beginning of the presented records), suggestive of recent changes in limnological conditions consistent with an external forcing mechanism such as climate warming or related influences on the quality or quantity of runoff. In both lakes, C/N ratios demonstrate a notable decline in the uppermost samples that corresponded to the emergence of the diatom communities, suggesting diatom productivity had a discernable impact on organic matter accumulation in both systems. The more recent appearance of diatoms in the sedimentary records corresponding to the latter half of the 20th century demonstrates the crossing of an important new ecological threshold in both of these lakes, not unlike in other Arctic systems.

Despite broad similarities, differences between the two systems provided the greatest insight and were paramount to interpreting and understanding limnological and paleolimnological records at Cape Bounty. In particular, differences in water chemistry and hydroclimatic variability (Chapter 2), differences in contemporaneous diatom communities and representation in sediment trap and surface sediments (Chapter 3), and differences in hydroclimatic and sediment delivery connections and biotic contributions in the sediment core record (Chapter 4) were elucidated by the paired- watershed approach applied in this study.

Differences in the response of the two lakes to seasonal hydroclimatic conditions were largely dictated by their specific morphologies. West Lake is slightly deeper than

East Lake, with a smaller surface area but greater overall water volume than East Lake, resulting in a smaller surface area to volume ratio. This has implications for lake temperature, the extent and duration of the ice-free period, the areal extent of

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planktonic and littoral zones, and overall primary productivity. In particular, differences in basin morphology likely contributed to the earlier ice break-up in East Lake, thereby generating conditions favourable for greater primary productivity, despite the fact that

West Lake had higher nutrient concentrations. This result suggests that an earlier or more protracted ice-off period in West Lake could elevate the importance of nutrient availability in this system, and result in greater primary productivity in West Lake, possibly even surpassing that of East Lake. Furthermore, the fact that nutrient concentrations in runoff were enhanced relative to East Lake in 2003 due to a slower melt season and, consequently, greater channel ponding and nutrient sequestration in that catchment, suggests that a trend toward earlier, more protracted melt seasons could further enhance productivity in West Lake compared to East Lake.

Differences in channel morphology account for the above disparity in stream nutrient concentrations in 2003, which also resulted in a discernable seasonal pattern in lake nutrient concentrations in West Lake that was not duplicated in East Lake. West

Lake’s catchment is smaller but more steeply graded with deeper and more frequent channels than East Lake’s catchment, resulting in greater winter precipitation accumulation and potential for ice and snow damming. However, this pattern was not replicated in 2004, and indicated that the relative influence of channel morphology on the timing and intensity of runoff appeared to be dependent on melt conditions.

Whereas a less intense melt season in 2003 resulted in more melt water ponding in the deeper channels of West River and delayed the spring freshet compared to East River, more intense melting in 2004 initiated stream flow quickly and generated very similar

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discharge patterns in both rivers. Despite higher nutrient concentrations in West River in

2003, overall nutrient fluxes were greater in 2004 due to higher overall discharge.

However, underflow conditions prevented immediate mixing with surface waters.

Hence, the importance of melt conditions and site specific controls (channel morphology) relative to discharge, differ in the two basins over the short (seasonal) and long term (lake water residency).

Differences in the diatom communities point to the spatial heterogeneity and micro-spatial controls operating within each system. The closer proximity of seasonal diatom sample collection to the main stream outlet in West Lake compared to East Lake most likely contributed to a community exhibiting less seasonal structure and microhabitat preference. Instead, the West Lake contemporaneous diatom assemblage was characterized by species that appear to be highly competitive (i.e., cosmopolitan taxa like Diatoma tenuis and Diadesmis contenta), demonstrated less habitat specificity, and were more likely to be associated with lotic and deltaic environments elsewhere

(e.g., Fragilaria capucina). In contrast, there was inherently more structure in the East

Lake assemblage, including evidence of seasonal succession and microhabitat preferences; for example the peak abundances of Pinnularia obscura and Fragilaria tenera in early and late season samples, and the dominance of Achnanthes daonensis and Gomphonema parvulum var. micropus in mid-season rock scrape samples. In addition, the more gradual slope at the East Lake collection site most likely resulted lake-level fluctuations being more pronounced, thus explaining the higher proportion of aerophilic taxa (e.g., Psammothidium marginulatum) at this site.

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Differences between West and East Lake paleoecological records indicate that external forcings are filtered by different connections with the surrounding terrestrial environment and internal lake dynamics. The earlier onset of diatom productivity in

East Lake compared to West Lake is likely a function of a shallower basin that is warmer and loses its ice cover sooner (and is ice free for longer each season), resulting in an earlier and more pronounced response to climate warming trends. These findings are consistent with other high latitude studies that generally point to an earlier onset of major compositional changes in species assemblages in small systems (ponds), and a later onset of changes or sudden appearance of diatoms in deeper and often more northerly lakes, though this is difficult to establish due to the inherently low sedimentation rates and resultant coarse chronological resolution of many pond records.

Advanced response in the East Lake diatom community compared to West Lake is likewise represented in even earlier changes in other paleoenvironmental indicators, including inferred Chl-a, C/N ratios and terrestrial and aquatic lipids, collectively suggesting a lower overall threshold to environmental change beginning circa the 1920s in East Lake and in the 1940s in West Lake. The fact that Chl-a, C/N ratios and lipid biomarkers reflect environmental changes occurring prior to the onset of diatom productivity adds credence to the claim that the appearance of diatoms signifies the crossing of an important ecological threshold in recent decades.

Sedimentary records from West and East Lake demonstrate differences in the contributions of aquatic and terrestrial organic matter that can be explained by differing

190

autochthonous productivities and terrestrial connections. Atomic C/N ratios indicated predominantly terrestrial organic matter sources in West Lake, particularly since the

1940s, that coincided with increased winter precipitation and, possibly, greater sediment availability associated with a deepening active layer and greater mobility of surface soils in this steeper catchment. In contrast, the organic matter record in East

Lake reflected a predominantly aquatic source that did not appear to respond to major changes in sedimentation rates. In addition, despite a decline in C/N ratios in West Lake that corresponded to the recent onset of diatom production, ratios still indicated a predominantly terrestrial source of organic matter, in contrast to the distinctly aquatic organic matter contributions in the most recent sediment from East Lake.

Solvent-extractable lipid compounds also suggest that a stronger connection between West Lake and the terrestrial environment exists. Organic matter in both lakes was dominated by terrestrial inputs; however, aquatic sources tend to be more susceptible to degradation that terrestrial inputs, thereby exaggerating the importance of terrestrial contributions. This effect was likely more pronounced in East Lake where greater overall productivity would disproportionately favour microbial and benthic reworking of organic matter compared to West Lake. Moreover, trends in the least susceptible lipid fractions (n-alkanes, long-chain aliphatic lipids and steroids) and specific biomarkers of aquatic microorganisms (e.g., short-chain n-alkanes, iso-alkanoic acids) indicated enhanced aquatic productivity over the last century that is more pronounced in East Lake.

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Collectively, results suggest that while East Lake appears to be less connected to the terrestrial environment than West Lake, it is more likely that the unique site attributes of East Lake resulted in an earlier response to climate warming, expressed primarily through greater primary productivity and more complex terrestrial-aquatic relationships. Thus, under a continued climate warming scenario, it is likely that productivity in West Lake will also continue to increase, and a more complex system will likewise emerge. A more densely vegetated and steeper West Lake catchment and greater nutrient inputs into West Lake in the contemporary environment suggest that productivity in West Lake has the potential to surpass that of East Lake if current climate trends continue. However, the recent emergence of diatom communities signifies that an important new ecological threshold has been crossed in both systems.

Implications and future directions

Seasonal lake water chemistry is influenced in different years according to the interplay between melt season conditions (snowpack, melt intensity) and catchment characteristics (i.e., channel morphology), with potential implications for short-lived aquatic biota (e.g., diatoms) over short time scales. Over longer time scales (e.g., lake water residency time) stream flow influences on lake water chemistry are more closely linked to discharge, suggesting that the resiliency of aquatic ecosystems insofar as the hydrochemical environment is concerned is likely to be on the order of lake water turnover times. Hence, the implications for the lake ecosystem will be different over the short and long term and research questions aimed at better understanding the

192

relationship between catchment hydrology and hydrochemical conditions in the lake should be tailored accordingly.

The identity of microspatial controls on the diatom assemblages (i.e., environmental conditions at the specific sampling locations) suggests that efforts to characterize the whole system diatom community should focus on more than one sampling location. For example, efforts to capture the littoral environment favour the collection of samples from a wider perimeter of the lake. In addition, refining methods to capture the stream assemblage despite significant turbidity would further elucidate where diatoms in trap samples and the deep lake sedimentary environment are originating. Furthermore, sediment trap studies might benefit from an additional trap suspended at an intermediate depth in the water column to shed light on relative contributions of settling diatoms and those transferred laterally via underflows, as well as establishing whether or not there is sufficient light for diatoms to grow under the ice surface. Finally, a more accurate understanding of the relative influence of lake water chemistry on seasonal diatom dynamics would benefit from efforts to capture hydrochemical conditions from the immediate environment (e.g., pore water chemistry and water samples that included the microhabitat being collected) rather than from the water column more generally. This would also shed light on the conventional approach of linking diatom assemblages to point samples of water chemistry (e.g., for the purposes of constructing transfer functions).

Further refining interpretations of the sedimentary diatom environment would also have benefited from more extensive sampling of diatom micro-habitats. In

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particular, further constraint on where Cyclotella cells were originating would improve understanding of the controls on this taxa, including their response to changes in the physical environment, such as lake-ice cover. For example, establishing whether or not

Cyclotella grow on or simply accumulate in littoral benthic and/or lotic environments would reveal whether their representation in lake sediments reflects the extent of the planktonic zone exclusively. In addition, multiple sampling locations would better illuminate the connection between the littoral region and deep profundal zone and whether the coherence between these two regions is spatially variable. This could be used to direct future sampling strategies so that the modern community is captured most efficiently.

The unusual setting of a paired-watershed permitted great insight into the influences of site-specific and broad-scale controls. The relative importance of these influences is dependent on the hypothesis being tested. Questions aimed at better understanding aquatic ecology and the nature of species-environment relationships, or how the terrestrial and aquatic environments are linked, would benefit from data collection strategies carried out at fine spatial and temporal scales (e.g., seasonal and inter-annual). However, a general coherence between the two lake sedimentary records with respect to ecological indicators over the last several centuries attests to the influence of longer-term trends ultimately controlled by climate, and suggests that lakes can present a discernable unified response to changes occurring at the regional scale, despite differences in how this information is filtered by internal and external conditions of individual lakes.

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The recent significant mobilization of surface sediment in the steeper West Lake catchment as a result of permafrost degradation provides an exceptional opportunity to continue exploring the relative influences of external and internal controls on the two lakes. A major influx of nutrient and organic matter rich sediment into West Lake has the potential to emulate possible future conditions of increased nutrient loadings on lakes, similar to that of lower latitude lakes, without major changes in ice cover. The response of West Lake to this enrichment, while controlling for ice-cover, would provide unique insight into the lake size-ecological threshold hypothesis. In addition, record high temperatures at Cape Bounty since 2007, combined with the added influx of terrigenous materials, may mean that the hypothesis that West Lake has greater potential for productivity than East Lake can be tested immediately.

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Appendices

196

Appendix 1. Individual sample water chemistry data - nutrients. Units are mg l-1. mean TN/TP TN/TP

Yr and site Date NO 3NO2 NO 2 NH3 TKN TN-F DIN DON PON TN SRP TP-F TP TN:TP mean mol mol 03 West R. July 6 0.019 0.002 0.025 0.134 0.153 0.044 0.109 0.392 0.545 0.0002 0.011 0.039 14 31 July 12 0.0025 0.002 0.016 0.196 0.197 0.016 0.18 0.08 0.279 0.0001 0.008 0.026 11 24 July 17 0.005 0.001 0.015 0.167 0.172 0.02 0.152 0.112 0.284 0.0002 0.010 0.027 10 23 July 22 0.0025 0.002 0.007 0.183 0.177 0.007 0.176 0.08 0.266 0.0001 0.013 0.023 11 25 July 27 0.006 0.001 0.055 0.246 0.252 0.061 0.191 0.08 0.332 0.0002 0.010 0.029 12 25 July 31 0.0025 0.003 <0.005 0.139 0.163 0.003 0.139 0.032 0.174 0.0002 0.010 0.021 8 11 18 24 03 West L. June 15 0.241 0.003 0.039 0.169 0.41 0.28 0.13 0.072 0.482 0.0003 0.011 0.026 19 41 June 26 0.137 0.004 0.015 0.309 0.446 0.152 0.294 0.224 0.670 0.0023 0.030 0.060 11 25 July 6 0.129 0.004 0.032 0.147 0.276 0.161 0.115 0.016 0.292 0.0002 0.011 0.018 17 37 July 12 0.108 0.001 0.012 0.135 0.223 0.12 0.123 0.048 0.291 0.0001 0.009 0.011 26 56 July 17 0.11 0.009 0.01 0.182 0.292 0.12 0.172 0.024 0.316 0.0002 0.010 0.013 24 53 July 22 0.051 0.003 0.005 0.179 0.243 0.056 0.174 0.032 0.262 0.0001 0.010 0.015 18 39 July 27 0.019 0.004 0.021 0.232 0.251 0.04 0.211 0.064 0.315 0.0002 0.010 0.018 17 38 July 31 0.087 0.005 0.011 0.121 0.225 0.098 0.11 0.016 0.224 0.0002 0.012 0.011 20 19 45 42 03 East R. July 7 0.034 0.003 0.046 0.256 0.29 0.08 0.21 0.096 0.386 0.0002 0.014 0.022 18 39 July 12 0.009 0.002 0.034 0.156 0.191 0.043 0.122 0.224 0.389 0.0001 0.010 0.053 7 16 July 17 0.044 0.003 0.034 0.334 0.378 0.078 0.3 0.12 0.498 0.0003 0.017 0.027 19 41 July 22 0.028 0.005 0.01 0.156 0.188 0.038 0.146 0.168 0.352 0.0002 0.010 0.030 12 26 July 27 0.077 0.004 0.015 0.243 0.32 0.092 0.228 0.048 0.368 0.0002 0.009 0.022 17 38 July 31 0.057 0.004 0.013 0.182 0.235 0.07 0.169 0.088 0.327 0.0005 0.012 0.019 17 15 39 33 03 East L. June 17 0.008 0.002 0.02 0.168 0.176 0.028 0.148 0.04 0.216 0.0018 0.011 0.011 19 42 June 24 0.024 0.003 0.019 0.19 0.214 0.043 0.171 0.048 0.262 0.0002 0.009 0.022 12 27 July 7 0.009 0.001 0.018 0.186 0.195 0.027 0.168 0.032 0.227 0.0002 0.009 0.015 15 33 July 12 0.0025 0.001 0.014 0.165 0.16 0.014 0.151 0.056 0.224 0.0001 0.011 0.011 20 43 July 17 0.005 0.001 0.015 0.204 0.209 0.02 0.189 0.048 0.257 0.0002 0.012 0.016 16 35 July 22 0.0025 0.003 <0.005 0.155 0.166 0.003 0.155 0.024 0.182 0.0001 0.011 0.011 17 37 July 27 0.006 0.001 0.018 0.173 0.179 0.024 0.155 0.048 0.227 0.0002 0.010 0.014 16 35 July 31 0.0025 0.002 0.008 0.115 0.139 0.008 0.107 0.04 0.158 0.0005 0.013 0.013 12 16 27 35 04 West R. June 28 0.061 0.001 0.019 0.228 0.228 0.08 0.209 0.072 0.361 0.0001 0.003 0.014 27 59 July 5 0.026 0.001 0.018 0.313 0.301 0.044 0.295 0.056 0.395 0.0004 0.009 0.067 6 13 July 9 0.04 0.003 0.029 0.299 0.287 0.069 0.27 0.192 0.531 0.0002 0.006 0.074 7 16 July 16 0.02 <0.001 0.022 0.206 0.191 0.042 0.184 0.056 0.282 0.0036 0.010 1.04* July 22 0.024 0.001 <0.005 0.14 0.121 0.024 0.005 0.12 0.284 0.0001 0.005 0.023 12 27 July 30 0.0025 0.002 0.006 0.14 0.138 0.006 0.134 0.048 0.191 0.0028 0.012 0.014 14 31 August 6 0.0025 0.002 0.006 0.143 0.158 0.006 0.137 0.04 0.186 0.0023 0.015 0.013 14 13 32 30 04 West L. June 28 0.038 0.003 0.006 0.208 0.182 0.044 0.202 0.032 0.278 0.0003 0.004 0.273* July 5 0.116 0.001 0.007 0.216 0.28 0.123 0.209 0.028 0.360 0.0007 0.006 0.013 28 63 July 9 0.116 0.002 0.013 0.168 0.233 0.129 0.155 0.032 0.316 0.0001 0.006 0.007 44 97 July 16 0.099 0.001 <0.005 0.178 0.248 0.1 0.005 0.024 0.301 0.142* 0.015 0.013 24 52 July 22 0.117 <0.001 <0.005 0.163 0.243 0.117 0.005 0.072 0.352 0.0002 0.014 2.69* July 30 0.089 0.001 0.005 0.115 0.21 0.094 0.11 0.024 0.228 0.0007 0.007 0.017 13 30 August 6 0.08 0.001 0.012 0.146 0.224 0.092 0.134 0.012 0.238 0.0003 0.002 0.006 41 30 91 66 04 East R. June 28 0.022 0.002 <0.005 0.337 0.28 0.022 0.337 0.116 0.475 0.0009 0.004 0.041 12 26 July 3 0.015 0.002 0.046 0.414 0.366 0.061 0.368 0.221 0.650 0.0349* 0.088 0.314* July 9 0.157 0.003 0.016 0.271 0.344 0.173 0.255 0.192 0.620 0.0001 0.003 0.108* July 16 0.027 0.001 <0.005 0.22 0.193 0.027 0.22 0.112 0.359 0.0001 0.006 0.494* July 22 0.028 0.001 <0.005 0.144 0.157 0.028 0.144 0.168 0.340 0.0004 0.004 0.022 16 35 July 30 0.012 0.002 <0.005 0.127 0.144 0.012 0.127 0.16 0.299 0.0001 0.007 0.047 6 14 August 6 0.0025 0.001 0.018 0.208 0.21 0.018 0.19 0.056 0.267 0.004 0.014 0.018 15 12 33 27 04 East L. June 28 0.021 0.001 0.012 0.168 0.154 0.033 0.156 0.044 0.233 0.0001 0.004 0.006 38 83 July 3 0.018 0.001 0.014 0.177 0.169 0.032 0.163 0.068 0.263 0.0013 0.005 0.006 48 106 July 9 0.019 0.003 <0.005 0.169 0.138 0.019 0.169 0.064 0.252 0.0001 0.004 0.005 55 121 July 16 0.035 0.008 <0.005 0.15 0.155 0.035 0.15 0.052 0.237 0.0001 0.017 0.007 33 73 July 22 0.021 <0.001 0.006 0.169 0.179 0.027 0.163 0.048 0.238 0.0018 0.004 0.015 16 35 July 30 0.0025 0.001 0.005 0.11 0.11 0.005 0.105 0.056 0.169 0.193* 0.007 0.010 17 37 August 6 0.0025 0.001 0.007 0.16 0.161 0.005 0.153 0.02 0.183 0.0071 0.005 0.008 22 32 49 72 mean 0.044 0.002 0.018 0.191 0.220 0.057 0.169 0.081 0.316 0.001 0.011 0.021 18.804 42 SD 0.050 0.002 0.012 0.063 0.073 0.053 0.070 0.071 0.119 0.001 0.011 0.016 10.584 23 min 0.003 0.001 0.005 0.110 0.110 0.003 0.005 0.012 0.158 0.000 0.002 0.005 5.931 13 max 0.241 0.009 0.055 0.414 0.446 0.280 0.368 0.392 0.670 0.007 0.088 0.074 54.783 121 * indicates questionable results bold values denote the number that is half w ay betw een zero and the detection limit.

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Appendix 1, continued. Individual sample water chemistry data.

-1 -1 Yr and site Date DIC DOC POC Chla (ug l ) POC:PON POC:Chla SiO2 O2 pH EC (uS s ) CaCo3 03 West R. July 6 2.0 1.4 4.300 1.51 11 2853 7.1 July 12 2.2 1.5 0.672 0.64 8 1053 7.3 July 17 2.5 1.6 0.824 0.46 7 1794 9.6 7.5 7.6 July 22 2.6 1.2 0.624 0.63 8 984 11.1 7.3 8.8 July 27 3.6 2.0 0.664 0.59 8 1135 8.8 7.2 8.4 July 31 2.9 1.8 0.336 0.34 11 1000 11.5 7.5 10.4 03 West L. June 15 2.8 1.3 1.340 0.57 19 2345 7.0 14.8 June 26 4.1 4.2 2.500 0.49 11 5086 1.1 6.8 9.6 July 6 2.7 1.1 0.264 0.71 17 373 11.4 7.0 5.6 July 12 2.6 1.0 0.448 1.17 9 383 10.5 7.1 7.2 July 17 3.2 1.7 0.272 0.91 11 299 9.5 7.2 8.8 July 22 2.8 1.1 0.280 0.98 9 285 7.0 7.0 9.6 July 27 3.2 2.4 0.520 1.42 8 367 9.5 7.5 8.8 July 31 2.7 1.4 0.288 0.55 18 527 10.9 7.2 10.4 03 East R. July 7 3.2 1.3 0.704 0.38 7 1835 7.3 July 12 2.9 1.0 1.700 2.02* 8 * 7.3 July 17 3.4 0.8 0.896 0.73 7 1221 10.3 7.5 11.2 July 22 3.8 1.1 1.190 0.62 7 1931 12.7 7.4 13.2 July 27 6.5 3.2 0.640 0.74 13 869 10.6 7.5 12.4 July 31 6.0 1.8 0.632 1.16* 7 * 8.6 7.6 24.4 03 East L. June 17 3.3 1.1 0.480 0.58 12 821 7.5 6.4 June 24 4.2 2.5 0.456 0.76 10 598 1.3 7.3 10.0 July 7 3.8 2.3 0.440 1.43 14 308 11.4 7.2 11.2 July 12 3.5 1.7 0.536 1.49 10 359 11.1 7.3 11.4 July 17 3.9 2.2 0.472 1.32 10 359 10.8 7.3 11.6 July 22 3.6 1.5 0.352 1.91 15 184 11.0 7.4 12.4 July 27 3.8 1.2 0.680 1.58 14 429 11.5 7.3 16.4 July 31 3.6 1.0 0.416 1.46 10 286 10.2 7.5 19.2 04 West R. June 28 2.5 2.2 0.820 1.06 11 771 0.468 12.0 7.5 25.3 4.8 July 5 3.3 1.7 0.568 2.28* 10 * 0.805 11.0 7.5 23.7 4.0 July 9 2.3 1.7 1.520 0.76 8 2010 0.291 10.0 7.8 20.6 8.8 July 16 1.9 1.4 0.616 0.53 11 1170 0.318 13.0 7.3 22.0 4.8 July 22 1.7 1.5 1.130 0.73 9 1553 0.436 11.3 7.9 21.3 4.4 July 30 2.3 1.4 0.400 0.56 8 717 0.343 13.0 6.4 23.9 7.2 August 6 2.7 2.0 0.296 0.65 7 453 0.406 3.5 7.0 34.9 6.8 04 West L. June 28 1.9 2.3 0.368 0.48 12 769 0.276 9.9 7.5 25.3 4.8 July 5 3.8 1.2 0.240 0.90 9 267 0.341 12.0 7.4 56.6 3.2 July 9 2.5 1.2 0.364 0.90 11 406 0.277 11.0 7.5 54.4 7.6 July 16 2.5 1.5 0.320 1.16 13 276 0.274 9.5 7.4 32.8 4.0 July 22 2.3 1.3 0.784 1.25 11 625 0.323 14.0 7.4 27.0 4.4 July 30 2.3 1.1 0.280 1.53 12 183 0.259 7.2 7.5 23.8 6.0 August 6 2.1 1.1 0.152 1.86 13 82 0.079 12.9 7.5 46.3 8.4 04 East R. June 28 2.8 2.7 1.030 0.62 9 1661 0.525 13.5 7.6 29.5 4.4 July 3 3.2 2.4 2.230 4.94* 10 * 0.532 12.0 7.9 23.3 5.2 July 9 3.2 2.0 1.510 0.63 8 2404 0.318 13.7 7.5 27.3 4.0 July 16 3.2 1.6 0.984 0.31 9 3212 0.335 8.6 7.5 30.4 6.0 July 22 3.2 1.5 1.240 4.98* 7 * 0.306 11.7 7.4 31.7 6.0 July 30 3.8 1.1 1.000 1.75* 6 * 0.281 11.3 7.3 29.7 5.2 August 6 4.1 1.1 0.464 0.45 8 1036 0.295 10.8 7.7 31.6 7.2 04 East L. June 28 2.9 1.5 0.448 1.74 10 258 0.188 11.5 7.7 48.0 4.4 July 3 3.5 1.4 0.508 2.17 7 235 0.056 10.4 7.6 62.3 7.2 July 9 3.5 1.2 0.608 2.24 10 272 0.203 11.9 7.7 67.7 8.4 July 16 3.5 1.3 0.620 2.43 12 255 0.233 10.0 6.6 83.7 7.2 July 22 3.5 1.2 0.608 2.64 13 230 0.234 7.7 7.6 31.8 4.0 July 30 3.7 1.7 0.608 3.02 11 201 0.204 7.6 7.2 34.2 12.4 August 6 3.1 1.1 0.228 2.44 11 93 0.227 4.5 7.4 36.8 4.4 mean 3.2 1.6 0.766 1.100 10.288 936.392 0.315 10.1 7.4 35.9 8.4 SD 0.9 0.6 0.678 0.672 2.710 967.806 0.146 2.8 0.3 15.9 4.2 min 1.7 0.8 0.152 0.306 6.250 81.819 0.056 1.1 6.4 20.6 3.2 max 6.5 4.2 4.300 3.022 18.611 5085.795 0.805 14.0 7.9 83.7 24.4

198

Appendix 2. Individual sample water chemistry data – ions and metals (mg l-1).

Cl SO4 Ca K Mg Na Al Ba Cr Cu Fe Mn Pb Sr Zn Ni 2003 West R. July 6 1.85 0.91 0.89 0.331 0.65 1.42 0.094 0.035 0.0014 0.002 0.138 0.005 0.001 0.004 0.030 0.0006 July 17 1.15 1.14 1.23 0.278 0.89 1.37 0.056 0.029 0.0009 0.002 0.053 0.002 0.000 0.005 0.028 0.0004 July 27 1.23 1.60 2.25 0.339 1.33 1.57 0.141 0.035 0.0017 0.002 0.249 0.006 0.000 0.008 0.031 0.0009 2003 West L. June 15 1.04 0.36 2.33 0.553 1.64 4.47 0.057 0.024 0.0149 0.015 0.097 0.004 0.002 0.010 0.039 0.0016 June 26 5.18 3.40 2.34 0.924 2.00 3.02 0.323 0.062 0.0014 0.008 0.387 0.015 0.002 0.009 0.045 0.0016 July 6 1.01 0.31 2.06 0.677 1.60 4.44 0.067 0.022 0.0016 0.003 0.135 0.005 0.001 0.009 0.028 0.0008 July 17 7.34 3.37 2.09 0.652 1.61 4.49 0.037 0.032 0.0011 0.005 0.046 0.002 0.001 0.009 0.033 0.0007 July 27 2.84 2.00 2.06 0.462 1.50 2.21 0.123 0.033 0.0013 0.004 0.164 0.004 0.001 0.008 0.029 0.0011 2003 East R. July 7 2.33 0.96 1.68 1.003 1.17 1.39 0.119 0.035 0.0012 0.002 0.187 0.005 0.000 0.005 0.037 0.0006 July 17 2.10 1.77 2.16 0.417 1.48 2.07 0.042 0.033 0.0010 0.002 0.054 0.003 0.000 0.007 0.024 0.0003 July 27 3.10 0.33 4.29 0.543 2.94 2.73 0.144 0.047 0.0010 0.002 0.260 0.006 0.001 0.012 0.028 0.0008 2003 East L. June 17 1.35 0.34 4.31 0.691 2.35 5.95 0.054 0.035 0.0014 0.008 0.027 0.002 0.001 0.019 0.033 0.0009 June 24 8.18 3.88 2.86 0.633 2.23 4.12 0.044 0.014 0.0008 0.009 0.072 0.004 0.001 0.009 0.015 0.0009 July 7 1.42 0.35 3.11 0.727 2.38 6.23 0.035 0.046 0.0011 0.010 0.042 0.119 0.003 0.011 0.020 0.0008 July 17 1.38 0.33 3.38 0.787 2.26 6.16 0.028 0.031 0.0013 0.005 0.032 0.001 0.001 0.014 0.034 0.0011 July 27 1.40 0.34 3.27 0.827 2.54 6.77 0.092 0.039 0.0009 0.002 0.126 0.003 0.001 0.011 0.035 0.0007 2004 West R. June 28 2.68 2.34 1.18 0.451 0.96 1.65 0.066 0.002 0.0006 0.001 0.049 0.001 0.001 0.006 0.004 0.0013 July 5 117.89* 2.75 1.38 46.439* 1.00 2.31 0.178 0.096 0.0194 0.003 0.268 0.164 0.000 0.008 0.057 0.0013 July 9 2.04 2.12 1.14 0.399 0.87 1.41 0.088 0.024 0.0006 0.008 0.056 0.008 0.000 0.006 0.034 0.0006 July 16 1.73 2.05 1.59 0.301 0.88 1.35 0.047 0.030 0.0000 0.008 0.026 0.003 0.000 0.006 0.032 0.0006 July 22 1.88 1.88 1.00 0.293 0.73 1.34 0.071 0.034 0.0000 0.008 0.033 0.002 0.000 0.005 0.035 0.0006 July 30 1.92 2.23 2.17 0.341 1.09 1.49 0.074 0.031 0.0000 0.010 0.047 0.110 0.001 0.008 0.024 0.0006 August 6 1.90 2.35 1.52 0.371 1.17 1.53 0.071 0.034 0.0006 0.003 0.056 0.001 0.000 0.008 0.033 0.0006 2004 West L. June 28 4.30 2.28 1.04 0.486 0.98 2.74 0.011 0.028 0.0000 0.001 0.003 0.001 0.000 0.005 0.001 0.0006 July 5 6.82 3.39 1.87 0.659 1.52 4.33 0.062 0.031 0.0006 0.002 0.019 0.001 0.000 0.010 0.021 0.0006 July 9 6.53 3.21 1.83 0.568 1.47 4.19 0.063 0.034 0.0006 0.012 0.039 0.002 0.000 0.010 0.031 0.0006 July 16 6.69 3.16 2.10 0.553 1.48 4.01 0.076 0.028 0.0006 0.010 0.034 0.003 0.000 0.010 0.021 0.0006 July 22 6.62 3.18 1.81 0.553 1.46 4.06 0.056 0.043 0.0006 0.024 0.027 0.004 0.000 0.009 0.022 0.0006 July 30 9.50 4.09 1.89 0.624 1.47 4.27 0.045 0.034 0.0000 0.013 0.021 0.001 0.000 0.010 0.028 0.0013 August 6 6.59 3.14 1.73 0.634 1.48 4.30 0.008 0.028 0.0000 0.001 0.009 0.001 0.000 0.009 0.026 0.0006 2004 East R. June 28 2.61 2.22 1.50 0.714 1.32 1.91 0.014 0.011 0.0000 0.001 0.004 0.001 0.000 0.005 0.002 0.0006 July 3 2.51 2.05 1.30 0.560 1.22 2.04 0.076 0.038 0.0006 0.038 0.061 0.009 0.001 0.006 0.039 0.0006 July 9 2.00 2.00 1.93 0.544 1.47 1.61 0.098 0.033 0.0006 0.014 0.065 0.002 0.000 0.007 0.026 0.0006 July 16 2.16 2.17 2.12 0.404 1.44 1.82 0.063 0.053 0.0006 0.007 0.033 0.006 0.000 0.008 0.036 0.0006 July 22 2.10 2.00 2.04 0.434 1.54 1.81 0.056 0.045 0.0006 0.008 0.037 0.003 0.000 0.008 0.035 0.0006 July 30 2.64 2.39 2.68 0.501 1.81 2.19 0.113 0.031 0.0006 0.010 0.023 0.002 0.000 0.009 0.028 0.0006 August 6 3.15 2.75 2.70 0.571 2.09 2.65 0.094 0.044 0.0006 0.001 0.064 0.003 0.000 0.010 0.033 0.0006 2004 East L. June 28 7.17 3.39 2.11 0.565 1.70 4.49 0.043 0.048 0.0006 0.001 0.017 0.001 0.000 0.008 0.024 0.0006 July 3 8.48 3.70 2.41 0.931 2.00 5.52 0.004 0.034 0.0000 0.002 0.006 0.001 0.000 0.009 0.014 0.0013 July 9 9.28 4.02 2.82 0.658 2.11 5.44 0.038 0.034 0.0000 0.005 0.013 0.001 0.000 0.011 0.019 0.0006 July 16 9.74 4.16 2.81 0.714 2.25 5.89 0.036 0.041 0.0000 0.004 0.018 0.001 0.000 0.011 0.019 0.0006 July 22 9.31 3.98 2.69 0.721 2.14 5.76 0.043 0.043 0.0006 0.009 0.017 0.003 0.000 0.011 0.028 0.0006 July 30 6.74 3.26 3.11 0.724 2.19 5.71 0.031 0.031 0.0000 0.009 0.013 0.001 0.000 0.011 0.026 0.0006 August 6 8.92 3.90 2.54 0.708 2.06 5.47 0.031 0.029 0.0000 0.001 0.013 0.001 0.000 0.011 0.027 0.0006

mean 4.37 2.39 2.22 0.597 1.65 3.54 0.069 0.035 0.0014 0.007 0.066 0.012 0.000 0.009 0.027 0.0008 SD 2.93 1.20 0.79 0.18 0.53 1.74 0.054 0.014 0.0035 0.007 0.084 0.033 0.001 0.003 0.010 0.0003 min 1.01 0.31 1.00 0.293 0.73 1.34 0.004 0.002 0.0000 0.001 0.003 0.001 0.000 0.005 0.001 0.0003 max 9.74 4.16 4.31 1.003 2.94 6.77 0.323 0.096 0.0194 0.038 0.387 0.164 0.003 0.019 0.057 0.0016 * questionable result; not factored into summary statistics.

199

Appendix 3. Environmental variable Pearson Product Moment correlation matrix.

NO3NO2 NO2 NH3 TKN TN-F DIN DON PON TN SRP TP-F TP DIC DOC POC Chla SiO2 O2

NO3NO2 0.67 -0.11 0.46 0.44 0.91 0.53 0.41 0.79 -0.86 0.51 -0.17 0.02 -0.15 0.53 -0.41 -0.02 0.68

NO2 -0.70 -0.57 -0.07 -0.04 0.38 0.07 0.17 0.24 -0.39 0.92 -0.30 0.22 -0.14 0.33 0.01 0.26 0.31

NH3 0.00 0.23 0.40 0.38 0.30 0.19 0.01 0.22 0.07 -0.45 -0.19 -0.46 0.27 -0.32 -0.56 -0.74 0.10 TKN -0.14 0.44 -0.06 0.83 0.58 0.98 -0.01 0.79 -0.13 -0.29 -0.27 -0.44 -0.63 -0.21 -0.70 -0.33 0.27 TN-F 0.86 -0.69 -0.07 0.24 0.57 0.80 -0.23 0.58 0.32 -0.09 0.16 -0.35 -0.63 -0.26 -0.40 -0.21 -0.07 DIN 0.99 -0.66 0.15 -0.15 0.84 0.57 0.43 0.85 -0.84 0.28 -0.20 -0.13 0.00 0.43 -0.59 -0.32 0.71 DON 0.12 0.05 -0.58 0.72 0.38 0.03 0.00 0.80 -0.30 -0.19 -0.27 -0.36 -0.72 -0.13 -0.63 -0.19 0.28 PON 0.29 0.04 -0.49 0.15 0.13 0.21 0.54 0.56 -0.82 0.09 -0.26 0.63 0.43 0.85 -0.01 -0.51 0.80

East Lake TN 0.53 -0.04 -0.22 0.68 0.66 0.49 0.77 0.64 -0.86 0.01 -0.34 0.00 -0.27 0.40 -0.59 -0.44 0.73 SRP 0.10 -0.24 -0.46 0.11 0.25 0.03 0.47 -0.18 0.06 -0.24 0.27 -0.30 -0.66 -0.88 0.39 0.15 -0.96 TP-F 0.44 -0.38 -0.79 0.01 0.38 0.31 0.66 0.58 0.45 0.65 -0.13 0.28 0.05 0.27 0.20 0.20 0.11 TP 0.00 0.08 -0.51 0.10 -0.10 -0.08 0.50 0.91 0.41 -0.22 0.46 0.25 -0.05 0.12 0.63 0.43 -0.50

DIC 0.64 -0.43 -0.01 0.40 0.86 0.64 0.24 -0.02 0.61 0.05 0.10 -0.29 0.19 0.68 0.74 -0.11 0.10 DOC -0.77 0.80 -0.31 0.58 -0.57 -0.81 0.47 0.14 0.06 0.16 0.03 0.28 -0.41 0.40 0.08 -0.26 0.33 POC 0.21 0.14 -0.54 0.10 -0.01 0.11 0.55 0.96 0.55 -0.02 0.66 0.87 -0.16 0.26 0.21 -0.03 0.69 Chl-a 0.38 -0.81 0.08 -0.78 0.22 0.39 -0.47 -0.24 -0.46 0.05 0.05 -0.14 -0.09 -0.78 -0.30 0.32 -0.53

SiO2 0.30 0.13 -0.54 0.44 0.30 0.22 0.56 0.63 0.72 0.08 0.53 0.35 0.48 0.24 0.64 -0.61 -0.33

O2 0.30 -0.13 0.22 0.39 0.43 0.33 0.43 0.39 0.57 -0.24 0.00 0.45 0.17 -0.12 0.22 0.05 -0.11

pH -0.77 0.55 0.47 -0.26 -0.83 -0.70 -0.58 -0.59 -0.81 -0.14 -0.64 -0.37 -0.72 0.33 -0.47 -0.01 -0.67 -0.34 Lake EC 0.47 -0.16 0.71 0.33 0.61 0.57 -0.05 -0.34 0.35 -0.11 -0.37 -0.50 0.61 -0.44 -0.46 0.03 -0.15 0.47

CaCo3 -0.14 0.12 0.73 -0.61 -0.44 -0.03 -0.76 -0.37 -0.64 -0.34 -0.55 -0.28 -0.56 -0.32 -0.33 0.43 -0.75 -0.03

West Cl 0.61 -0.78 -0.08 -0.74 0.37 0.59 -0.50 -0.13 -0.25 0.03 0.19 -0.28 0.30 -0.84 -0.17 0.72 -0.03 -0.36

SO4 0.67 -0.78 -0.04 -0.67 0.45 0.66 -0.47 -0.12 -0.16 -0.01 0.16 -0.30 0.41 -0.87 -0.17 0.67 0.03 -0.31 Ca 0.87 -0.87 -0.10 -0.38 0.76 0.85 -0.03 -0.05 0.17 0.41 0.48 -0.26 0.51 -0.80 -0.07 0.63 0.05 0.00 K 0.53 -0.74 0.30 -0.32 0.58 0.58 -0.46 -0.40 -0.11 -0.21 -0.27 -0.47 0.61 -0.85 -0.58 0.63 -0.25 0.06 Mg 0.89 -0.88 0.10 -0.40 0.78 0.90 -0.16 -0.07 0.15 0.17 0.27 -0.26 0.54 -0.93 -0.16 0.70 -0.08 0.16 Na 0.85 -0.87 0.19 -0.47 0.72 0.88 -0.28 -0.12 0.07 0.04 0.14 -0.29 0.52 -0.97 -0.22 0.74 -0.14 0.15 Al 0.79 -0.42 -0.36 0.08 0.70 0.73 0.39 0.33 0.60 0.47 0.71 -0.02 0.62 -0.33 0.37 -0.04 0.68 -0.09 Ba 0.57 -0.27 -0.28 -0.28 0.23 0.52 0.14 0.86 0.43 -0.32 0.48 0.71 0.05 -0.34 0.80 0.15 0.45 0.29 Cr 0.78 -0.28 -0.19 0.41 0.79 0.73 0.65 0.48 0.88 0.35 0.62 0.17 0.62 -0.20 0.45 -0.18 0.61 0.40 Cu 0.54 -0.31 -0.46 -0.39 0.17 0.46 0.21 0.78 0.31 0.07 0.73 0.62 -0.10 -0.26 0.82 0.21 0.42 0.06 Fe 0.80 -0.35 -0.08 -0.16 0.54 0.77 0.17 0.28 0.42 0.41 0.61 -0.05 0.33 -0.44 0.36 0.12 0.40 -0.04 Mn 0.50 -0.32 -0.57 -0.12 0.30 0.40 0.56 0.74 0.45 0.40 0.90 0.64 -0.09 -0.08 0.80 0.15 0.37 0.25 Sr 0.90 -0.85 0.08 -0.43 0.75 0.90 -0.18 -0.08 0.14 0.22 0.31 -0.30 0.54 -0.91 -0.13 0.66 -0.01 0.05 Zn 0.80 -0.71 0.30 -0.62 0.52 0.84 -0.43 -0.12 -0.06 0.02 0.11 -0.31 0.30 -0.94 -0.16 0.72 -0.19 0.02 Ni -0.04 -0.24 -0.19 -0.75 -0.30 -0.06 -0.67 -0.18 -0.60 -0.16 -0.06 -0.21 -0.12 -0.32 -0.14 0.37 0.00 -0.78 Q -0.14 0.57 0.19 0.80 0.10 -0.11 0.29 -0.09 0.47 -0.05 -0.25 -0.28 0.47 0.45 -0.09 -0.86 0.51 -0.04 Tw 0.39 -0.62 -0.09 -0.91 0.03 0.37 -0.44 -0.02 -0.45 0.18 0.32 -0.02 -0.29 -0.64 0.04 0.84 -0.35 -0.24 Ta 0.65 -0.50 0.60 -0.56 0.38 0.74 -0.63 -0.26 -0.15 -0.25 -0.25 -0.44 0.29 -0.91 -0.33 0.61 -0.30 0.04 bold =p< .005 ital= p<.01 one-tailed, n=7

200

Appendix 3, continued. Environmental variable correlation matrix.

pH EC CaCo3 Cl SO4 Ca K Mg Na Al Ba Cr Cu Fe Mn Sr Zn Ni Q Tw Ta

NO3NO2 -0.27 0.70 -0.19 0.51 0.52 -0.19 -0.07 -0.01 0.00 0.15 0.72 0.26 -0.13 0.41 0.24 -0.15 -0.51 0.06 0.27 0.66 -0.45

NO2 -0.81 0.77 0.24 0.50 0.56 0.31 -0.07 0.45 0.36 0.15 0.14 -0.38 -0.12 0.41 0.01 0.41 -0.42 -0.20 -0.15 0.58 -0.02

NH3 0.54 -0.13 -0.34 -0.41 -0.48 -0.80 0.30 -0.74 -0.57 -0.56 0.21 0.31 -0.51 -0.51 -0.42 -0.83 -0.23 0.68 0.68 -0.82 -0.59 TKN 0.54 0.31 -0.68 0.55 0.51 -0.68 0.07 -0.43 -0.32 -0.14 0.40 0.33 -0.54 -0.09 0.29 -0.54 -0.38 0.36 0.53 -0.69 -0.30 TN-F 0.26 0.07 -0.83 0.61 0.55 -0.58 0.23 -0.22 -0.05 -0.14 0.42 0.42 -0.37 0.05 0.52 -0.33 -0.15 0.32 0.17 0.15 -0.56 DIN -0.02 0.58 -0.31 0.30 0.28 -0.48 0.05 -0.30 -0.22 -0.07 0.79 0.41 -0.26 0.19 0.09 -0.47 -0.57 0.33 0.53 -0.07 -0.72 DON 0.44 0.39 -0.63 0.69 0.66 -0.54 0.01 -0.29 -0.21 -0.03 0.38 0.26 -0.47 0.01 0.39 -0.39 -0.38 0.24 0.43 -0.26 -0.19 PON 0.00 0.48 0.61 -0.05 -0.07 0.24 0.36 0.16 0.17 -0.35 0.11 -0.15 0.31 -0.35 -0.20 -0.02 -0.66 0.46 0.52 -0.26 0.63 TN 0.26 0.63 -0.23 0.50 0.47 -0.39 0.18 -0.21 -0.13 -0.20 0.53 0.23 -0.26 -0.08 0.18 -0.40 -0.70 0.45 0.66 -0.41 -0.21 SRP 0.09 -0.61 -0.48 0.12 0.08 -0.02 0.15 0.11 0.16 -0.11 -0.65 -0.22 -0.24 -0.19 0.15 0.24 0.51 -0.07 -0.49 0.11 -0.08 TP-F -0.95 0.59 0.29 0.33 0.37 0.35 0.09 0.51 0.46 0.01 0.05 -0.41 -0.05 0.34 -0.07 0.46 -0.32 -0.12 -0.27 0.56 -0.16 TP -0.05 -0.75 -0.27 0.01 0.00 0.31 0.01 0.35 0.40 0.34 0.12 0.47 0.72 0.36 0.71 0.37 0.72 -0.33 -0.71 0.59 -0.10 DIC -0.39 0.10 0.71 0.16 0.15 0.84 0.55 0.82 0.83 -0.28 -0.40 -0.46 0.71 -0.27 0.17 0.71 -0.23 0.19 -0.24 0.57 0.68 DOC -0.14 -0.09 0.58 -0.86 -0.85 0.08 0.00 -0.20 -0.23 -0.16 0.08 0.03 0.24 -0.16 -0.65 -0.21 -0.04 0.14 0.23 -0.74 -0.14 POC -0.23 0.31 0.50 0.01 0.03 0.45 0.08 0.34 0.30 0.09 0.33 0.09 0.62 0.14 0.13 0.22 -0.30 0.02 0.09 0.88 0.65 Chl-a -0.45 -0.43 0.46 0.02 0.02 0.88 0.31 0.84 0.82 0.02 -0.55 -0.36 0.77 -0.02 0.32 0.87 0.40 -0.22 -0.77 0.85 0.50 East Lake

SiO2 -0.31 -0.28 -0.17 0.15 0.23 0.37 -0.73 0.27 0.10 0.91 0.14 0.22 0.36 0.85 0.49 0.46 0.72 -0.98 -0.79 0.69 0.12

O2 0.10 0.66 0.26 -0.04 -0.03 -0.19 -0.11 -0.28 -0.32 -0.03 0.53 0.16 -0.07 0.01 -0.27 -0.41 -0.65 0.23 0.69 -0.61 -0.07 pH -0.36 -0.39 -0.19 -0.24 -0.53 -0.09 -0.63 -0.57 -0.05 0.11 0.46 -0.14 -0.33 0.06 -0.63 0.10 0.22 0.48 -0.64 0.05

EC -0.18 0.26 0.42 0.44 -0.06 0.12 0.06 0.03 -0.24 0.14 -0.41 -0.45 -0.06 -0.30 -0.05 -0.86 0.28 0.49 -0.01 0.01

CaCo3 0.69 0.15 -0.33 -0.30 0.69 0.26 0.47 0.38 -0.29 -0.52 -0.67 0.37 -0.37 -0.50 0.45 -0.32 0.12 0.03 -0.03 0.68 Cl -0.30 0.00 0.13 0.99 0.13 0.21 0.46 0.49 0.03 0.02 -0.16 -0.10 0.17 0.65 0.37 -0.28 0.01 -0.17 0.83 0.12

SO4 -0.37 0.10 0.09 0.99 0.16 0.13 0.47 0.49 0.11 0.03 -0.17 -0.09 0.24 0.64 0.41 -0.25 -0.08 -0.22 0.86 0.14 Ca -0.57 0.32 -0.06 0.79 0.81 0.17 0.90 0.80 0.11 -0.53 -0.52 0.74 0.05 0.22 0.93 0.15 -0.31 -0.63 0.81 0.74 K -0.28 0.52 0.09 0.71 0.76 0.61 0.39 0.57 -0.90 -0.46 -0.47 0.02 -0.77 -0.07 0.19 -0.52 0.84 0.20 -0.06 0.11 Mg -0.54 0.47 0.07 0.79 0.82 0.96 0.76 0.97 -0.04 -0.49 -0.55 0.58 0.02 0.40 0.97 0.01 -0.14 -0.64 0.82 0.56

Na -0.47 0.48 0.16 0.82 0.85 0.91 0.83 0.99 -0.21 -0.48 -0.52 0.54 -0.11 0.43 0.89 -0.06 0.06 -0.56 0.75 0.46 Al -0.76 0.18 -0.47 0.44 0.49 0.73 0.14 0.59 0.49 0.45 0.51 0.31 0.91 0.45 0.13 0.66 -0.95 -0.52 0.46 -0.02 Ba -0.59 -0.21 -0.07 0.33 0.34 0.29 -0.02 0.32 0.31 0.42 0.82 -0.06 0.61 0.24 -0.54 0.01 -0.18 0.24 0.05 -0.79 Cr -0.81 0.42 -0.48 0.06 0.13 0.55 0.02 0.48 0.38 0.85 0.43 0.14 0.51 0.41 -0.54 0.44 -0.26 0.04 -0.05 -0.59

Cu -0.51 -0.39 -0.07 0.38 0.36 0.42 -0.18 0.34 0.29 0.56 0.90 0.46 0.20 0.47 0.59 0.43 -0.33 -0.55 0.73 0.49 West Lake West Fe -0.52 0.23 -0.04 0.45 0.48 0.75 0.07 0.63 0.56 0.89 0.48 0.77 0.65 0.46 0.14 0.51 -0.84 -0.52 0.61 -0.30 Mn -0.57 -0.31 -0.25 0.14 0.11 0.42 -0.32 0.29 0.19 0.58 0.70 0.61 0.88 0.64 0.38 0.40 -0.35 -0.55 0.78 0.06 Sr -0.53 0.43 0.07 0.82 0.85 0.98 0.72 0.99 0.97 0.66 0.32 0.50 0.37 0.71 0.31 0.20 -0.35 -0.77 0.88 0.61 Zn -0.28 0.41 0.39 0.82 0.84 0.86 0.67 0.92 0.94 0.47 0.36 0.31 0.39 0.66 0.23 0.94 -0.72 -0.73 0.36 -0.03 Ni 0.16 -0.49 0.17 0.72 0.67 0.18 0.31 0.15 0.21 0.03 0.14 -0.47 0.20 0.01 -0.16 0.21 0.30 0.69 -0.54 -0.13 Q -0.07 0.41 -0.40 -0.50 -0.41 -0.35 -0.19 -0.38 -0.39 0.16 -0.35 0.28 -0.47 -0.04 -0.42 -0.33 -0.43 -0.36 -0.96 -0.21 Tw 0.01 -0.26 0.46 0.76 0.69 0.63 0.29 0.60 0.61 0.20 0.37 -0.08 0.57 0.44 0.43 0.62 0.73 0.54 -0.86 0.18 Ta -0.08 0.56 0.56 0.71 0.74 0.65 0.72 0.79 0.85 0.25 0.23 0.14 0.15 0.47 -0.09 0.79 0.93 0.29 -0.26 0.55

201

Appendix 4. Relative abundances (%) of common (≥2%) taxa in West Lake moss and rock samples. Moss Rock

West Lake common taxa taxa # Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Mean Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 mean Achnanthes nitidiformis Lange-Bertalot 1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.00 0.00 0.00 0.00 0.48 0.39 0.00 0.14 Achnanthes rupestoides Hohn 2 0.0 0.5 0.0 1.6 0.0 0.0 0.4 0.00 0.41 2.16 0.00 1.08 0.97 0.65 0.84 Achnanthes rupestris Krasske 3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00 2.03 0.29 0.19 1.44 0.58 0.00 0.67 Achnanthidium minutissimum ( Kützing) Czarnecki 4 1.3 1.6 2.8 0.7 1.2 1.5 1.5 4.91 1.62 1.73 1.17 1.44 0.00 7.00 2.54 Caloneis aerophila Bock 5 0.0 0.6 1.8 0.5 0.6 1.2 0.8 0.00 5.27 2.01 2.34 0.48 0.78 0.00 1.44 Cyclotella pseudostelligera Hustedt 6 1.1 0.3 1.1 13.8 2.7 1.8 3.9 2.16 1.22 3.31 6.24 5.04 0.78 3.09 3.29 Cyclotella rossii Håkansson 7 1.8 0.6 0.4 3.8 0.6 0.9 1.2 2.36 0.41 1.01 1.36 4.80 0.58 2.93 2.13 Cymbella lapponica Grunow ex Cleve 8 3.1 0.0 0.0 0.8 0.1 2.1 0.9 3.93 0.41 1.29 0.58 0.96 0.19 0.65 1.13 Diadesmis brekkaensis ( Krasske) D.G. Mann 9 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.00 0.00 1.15 1.95 1.44 1.56 0.00 0.91 Diadesmis contenta (Grunow ex Van Heurck) D.G. Mann 10 0.0 13.9 7.9 16.5 3.0 2.4 7.8 0.98 18.26 9.64 16.57 9.24 5.07 0.81 8.51 Diadesmis gallica W. Smith 11 0.9 4.8 51.4 0.0 3.6 0.0 9.1 0.39 1.01 22.30 26.51 5.40 0.00 0.00 8.23 Diatoma tenuis C. Agardh 12 35.0 27.6 1.5 22.0 2.1 24.9 18.4 10.41 22.92 4.75 0.97 8.16 14.23 19.71 11.18 Encyonema silesiacum ( Bleisch) D.G. Mann 13 1.1 0.0 0.0 0.3 0.3 0.2 0.3 0.39 0.00 0.58 0.39 0.36 0.39 0.81 0.43 Encyonema ventricosum (C. Agardh) Grunow 14 1.1 0.0 0.2 0.3 3.6 1.5 1.1 2.16 0.00 0.00 0.00 0.36 0.00 0.00 0.34 Eunotia praerupta Ehrenberg 15 0.7 0.2 0.6 0.5 0.6 0.5 0.5 0.59 0.41 1.01 3.12 1.44 0.00 0.98 1.10 Fragilaria capucina v ar. capucina Desmazières 16 0.9 2.9 1.3 9.3 3.9 2.9 3.9 1.38 0.00 3.02 5.65 4.56 1.56 4.23 3.09 Gomphonema parvulum var. micropus ( Kützing) Cleve 17 0.0 0.0 0.4 0.1 0.0 0.3 0.1 1.38 0.00 0.58 0.39 1.08 6.24 3.58 1.82 Hannaea arcus ( Ehrenberg) R.M. Patrick 18 0.2 1.3 0.0 4.1 0.9 0.3 1.3 0.20 2.23 0.43 0.19 0.84 0.19 0.00 0.58

2 Hantzschia amphioxys ( Ehrenberg) Grunow 19 0.0 0.3 0.2 0.3 0.1 0.0 0.2 0.20 0.41 0.43 0.19 0.36 0.39 0.00 0.29

2 Luticola mutica (Kützing) D.G. Mann 20 0.0 0.0 0.4 0.5 0.0 0.0 0.2 0.00 1.22 1.01 0.00 0.60 0.00 0.00 0.43 Muelleria gibbula (Cleve) S. A. Spaulding & E. F. Stoermer 21 0.4 1.6 0.0 0.0 0.0 0.6 0.4 0.00 1.83 0.29 0.78 0.00 0.39 0.33 0.46 Navicula bergerii Krasske 22 4.4 2.1 0.7 0.5 5.1 2.0 2.4 1.18 1.62 1.15 0.39 3.60 1.17 0.81 1.56 Navicula cincta (Ehrenberg) Kutzing 23 0.2 1.6 0.6 0.9 1.9 0.6 1.0 2.16 3.45 0.43 0.97 1.44 0.39 1.14 1.37 Navicula cryptocephala Kützing 24 4.2 0.3 1.1 0.7 4.3 3.3 2.2 2.55 0.20 1.15 0.97 1.32 1.36 2.77 1.49 Nitzschia alpina Hustedt 25 0.0 0.3 0.9 0.0 4.0 2.0 1.3 1.57 0.00 1.58 0.78 0.96 0.00 0.33 0.79 Nitzschia lacunarum Hustedt 26 0.4 1.9 1.7 0.3 2.8 3.0 1.7 1.57 1.01 1.29 0.39 1.56 2.14 1.63 1.39 Nitzschia palea (Kützing) W. Smith 27 0.7 0.3 0.2 0.8 0.3 1.7 0.7 1.18 0.00 0.72 0.97 2.04 0.97 1.79 1.18 Nitzschia perminutum (Grunow) M. Peragallo 28 12.3 0.3 0.6 0.9 10.9 12.5 6.1 11.79 0.61 1.15 2.14 2.28 3.70 2.44 3.24 Pinnularia balfouriana Grunow ex Cleve 29 0.0 0.3 0.0 0.9 1.3 0.0 0.5 0.79 0.20 1.58 0.58 2.04 0.19 0.16 0.91 Pinnularia intermedia (Lagerstedt) Cleve 30 0.0 0.0 1.1 0.7 0.0 0.0 0.3 0.00 1.62 2.01 2.34 0.36 0.00 0.00 0.89 Pinnularia krammeri Metzeltin 31 0.9 0.6 0.2 0.1 4.2 1.7 1.3 0.79 1.42 0.29 0.00 0.24 0.00 0.00 0.36 Pinnularia obscura Krasske 32 2.9 4.1 7.7 1.4 7.0 3.2 4.3 2.36 6.69 3.02 1.75 0.60 0.78 0.65 2.11 Psammothidium chlidanos ( Hohn & Hellerman) Lange-Bertalot 33 2.4 1.6 0.7 1.2 3.9 3.2 2.2 5.89 1.01 1.58 0.58 4.08 1.95 4.07 2.83 Psammothidium kryophilum (Petersen) Reichardt 34 2.9 11.3 2.0 0.0 4.8 2.7 3.9 6.48 2.23 0.43 0.00 0.24 0.00 0.00 1.18 Psammothidium marginulatum (Grunow) Bukhtiyarova & Round 35 4.0 4.6 0.7 1.2 4.8 1.5 2.8 4.72 3.65 0.72 0.78 0.48 1.17 0.00 1.46 Rossithidium petersenii (Hustedt) Bukhtiyarova & Round 36 4.4 2.2 0.0 1.9 3.6 2.0 2.3 3.54 1.22 2.45 0.97 3.96 2.73 1.14 2.40 Sellaphora pupula (Kützing) Mereschkovsky 37 0.7 0.0 0.0 0.8 0.0 0.0 0.2 0.59 1.62 0.29 0.19 0.24 0.39 0.33 0.48 Stauroneis anceps Ehrenberg 38 1.5 1.9 1.5 0.1 1.2 5.9 2.0 3.54 0.61 0.86 0.58 0.48 0.39 0.81 0.98 Stauroneis lundii Hustedt 39 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00 0.41 1.01 0.00 0.36 0.00 0.00 0.29 Proportion of total sample 89.4 89.8 89.4 88.1 83.2 85.9 87.2 82.1 87.2 78.7 83.0 75.9 51.7 62.9 74.4 *mean for sample type 199

Appendix 4, continued. Relative abundances of common taxa in West Lake littoral sediment, plankton and sediment trap samples. Sediment Plankton Sediment trap

taxa # Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 mean Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 mean Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 mean 1 0.00 0.00 0.00 0.00 0.18 0.20 0.00 0.05 0.00 1.16 0.59 0.16 0.32 0.14 0.57 0.44 2.36 2.74 1.27 1.10 0.33 0.64 2.58 1.57 2 0.80 7.85 2.62 0.00 2.34 6.07 1.72 2.99 1.55 0.00 0.30 0.00 0.81 0.00 0.00 0.33 0.25 0.00 0.00 0.22 0.00 0.00 0.00 0.08 3 0.40 1.09 1.50 0.96 3.60 0.00 0.76 1.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.68 0.28 0.00 0.00 0.00 0.00 0.12 4 0.40 0.00 1.12 0.00 0.72 2.63 1.15 0.82 1.16 0.00 1.34 0.95 0.65 2.44 1.43 1.15 3.23 3.08 1.13 2.52 0.00 0.38 3.75 2.07 5 0.40 2.37 5.98 1.43 2.16 1.21 0.38 2.01 1.94 0.00 0.00 0.00 0.00 0.00 0.00 0.22 0.00 0.34 0.71 0.00 0.00 0.00 0.00 0.14 6 0.20 0.73 0.00 0.00 1.80 2.83 0.76 0.87 15.50 55.80 51.26 46.10 48.79 52.58 44.19 45.93 31.18 24.32 34.94 46.32 19.40 28.48 42.89 33.57 7 0.20 0.00 1.50 0.00 1.26 1.42 2.68 0.98 6.20 15.94 19.32 21.78 13.41 14.76 19.94 16.23 20.12 11.47 8.77 11.64 28.60 27.20 12.79 17.05 8 7.80 0.73 2.99 0.00 0.00 0.20 3.63 2.09 1.55 0.29 0.00 0.00 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9 0.20 3.47 0.00 0.96 0.54 3.04 1.34 1.35 0.97 0.00 0.00 0.00 0.00 0.14 0.14 0.15 0.25 0.51 0.28 0.22 0.00 0.00 0.13 0.19 10 4.60 18.25 9.53 4.78 6.29 4.86 2.49 7.29 3.68 0.29 1.49 0.32 2.91 0.57 0.72 1.33 0.25 2.57 1.70 1.32 1.34 0.38 0.65 1.10 11 0.40 9.49 4.49 35.67 0.00 0.00 0.00 7.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.68 1.13 0.22 0.33 0.00 0.26 0.35 12 4.40 16.06 3.18 0.00 2.52 5.26 5.35 5.15 6.78 0.00 0.30 0.32 2.42 4.58 2.30 2.26 0.25 3.08 5.66 2.09 0.33 0.26 0.00 1.61 13 0.80 0.00 4.30 0.16 0.54 0.40 3.25 1.32 0.39 0.00 0.00 0.00 0.48 0.29 0.00 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.02 14 3.40 0.36 2.24 0.00 2.88 0.81 0.19 1.37 0.97 0.00 0.00 0.00 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.04 15 0.00 0.73 0.00 9.55 0.36 0.61 0.38 1.88 0.39 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.37 0.00 0.42 0.11 0.00 0.00 0.26 0.17 16 0.40 0.91 0.75 0.16 1.44 1.62 2.87 1.14 0.58 0.29 0.00 0.00 0.48 0.29 0.00 0.22 0.75 1.03 0.85 0.66 0.00 0.00 0.52 0.54 17 0.00 1.09 0.00 0.00 1.08 2.02 0.76 0.69 0.39 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 1.54 0.57 0.22 0.00 0.00 0.00 0.29 18 0.20 0.18 0.37 0.00 0.54 1.01 0.00 0.32 0.39 0.00 0.00 0.00 0.48 0.00 0.29 0.15 4.10 4.11 2.83 1.43 0.00 0.00 0.90 1.88 19 0.20 0.18 2.80 3.18 0.00 0.00 0.38 1.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.28 0.00 0.00 0.00 0.00 0.04 20 20 0.00 0.00 1.12 5.10 1.26 0.00 0.38 1.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.57 0.11 0.33 0.00 0.00 0.15

3 21 1.00 1.64 2.62 2.55 0.00 0.40 0.76 1.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.68 0.00 0.00 0.00 0.00 0.00 0.08 22 1.20 6.02 0.75 0.00 3.78 1.82 1.72 2.17 3.10 0.87 0.00 0.00 0.81 0.00 0.00 0.60 0.00 0.68 1.13 0.88 0.00 0.00 0.00 0.39 23 1.00 2.01 4.30 0.00 11.87 0.61 1.72 3.09 0.58 0.29 0.00 0.00 0.16 0.29 0.00 0.18 0.12 0.68 0.85 0.00 0.00 0.00 0.00 0.21 24 10.60 0.00 7.66 0.32 3.24 1.42 2.68 3.57 3.68 0.00 0.00 0.32 0.65 0.29 0.00 0.60 0.25 0.68 0.85 0.22 0.00 0.00 0.00 0.27 25 3.00 0.00 0.00 0.48 3.06 2.43 2.87 1.64 0.58 0.00 0.00 0.48 0.97 0.00 0.00 0.27 0.25 0.17 0.00 0.00 0.00 0.00 0.00 0.06 26 1.80 2.19 3.55 0.32 1.62 1.42 1.15 1.69 1.74 0.00 0.00 0.00 0.00 0.14 0.00 0.22 0.00 1.20 1.13 0.22 0.00 0.38 0.13 0.41 27 1.00 0.00 0.37 0.00 0.90 0.40 7.07 1.35 0.78 0.43 0.30 0.00 0.81 0.29 0.29 0.40 0.37 1.71 0.71 0.99 1.17 0.64 0.78 0.87 28 11.20 0.36 2.24 0.00 2.88 5.47 1.72 3.22 6.40 0.29 0.15 0.16 1.13 0.14 0.14 1.02 0.00 0.86 0.00 0.33 1.51 0.26 1.03 0.52 29 0.00 0.00 0.00 0.00 0.18 5.47 2.49 1.08 0.97 0.14 0.00 0.16 0.16 0.29 0.00 0.22 0.12 0.34 0.57 0.22 0.33 0.00 0.00 0.21 30 0.00 2.92 5.23 14.49 1.44 1.01 0.19 3.94 0.39 0.00 0.00 0.00 0.16 0.00 0.29 0.11 0.00 0.51 0.00 0.00 0.00 0.51 0.00 0.14 31 1.80 0.36 0.93 0.00 0.00 0.20 0.38 0.50 0.39 0.00 0.00 0.00 0.16 0.00 0.00 0.07 0.00 0.17 0.14 0.00 0.00 0.00 0.00 0.04 32 2.60 2.92 3.18 1.11 2.70 1.01 0.19 1.96 1.55 0.00 0.45 0.00 0.48 0.29 0.00 0.35 0.25 0.00 0.85 0.00 0.00 0.00 0.00 0.15 33 3.80 0.18 0.75 0.00 0.36 5.26 4.40 1.98 2.13 0.00 0.00 0.48 0.97 0.57 0.29 0.57 0.12 0.68 1.41 0.99 0.00 0.00 0.00 0.46 34 5.20 0.55 0.00 0.00 0.18 0.00 0.00 0.79 0.78 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.28 0.00 0.17 0.00 0.00 0.06 35 7.60 1.82 1.12 0.96 5.22 1.42 0.38 2.59 4.84 0.58 0.00 0.00 0.32 0.00 0.00 0.69 0.12 1.03 0.57 0.33 0.00 0.00 0.39 0.33 36 2.60 0.73 0.37 0.16 8.99 2.23 2.68 2.51 1.36 0.00 0.45 0.16 0.81 0.00 0.14 0.38 0.00 0.00 0.85 0.22 0.67 0.13 0.13 0.27 37 0.00 0.18 0.00 0.00 0.36 1.42 0.57 0.34 0.39 0.43 0.00 0.00 0.48 0.72 0.57 0.38 1.99 2.57 1.84 2.85 1.17 0.26 2.97 1.98 38 6.00 2.01 3.36 0.16 1.80 1.01 1.72 2.22 0.58 0.00 0.00 0.00 0.00 0.29 0.00 0.11 0.25 0.86 0.00 0.22 0.50 0.00 0.00 0.23 39 0.00 1.28 1.87 3.66 0.72 0.81 0.00 1.27 0.39 0.00 0.00 0.00 1.13 0.00 0.00 0.20 0.00 0.00 0.14 0.22 0.00 0.00 0.00 0.06 85.2 88.7 82.8 86.1 78.8 68.0 61.2 79.0 73.1 76.8 75.9 71.4 80.0 79.1 71.3 75.4 67.0 69.2 72.7 76.1 56.2 59.5 70.3 67.7 200

Appendix 5. Relative abundances (%) of common taxa in East Lake moss and rock samples.

Moss Rock East Lake common taxa taxa # Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 Achnanthes daonensis Lange-Bertalot 1 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00 13.79 27.57 65.53 35.08 0.80 0.00 Achnanthes helvetica (Hustedt) Lange-Bertalot 2 5.11 6.46 6.85 6.19 3.17 3.93 7.25 3.60 5.07 6.54 1.02 1.66 3.38 0.00 Achnanthes rupestris Krasske 3 0.53 2.58 0.57 1.73 2.05 1.31 0.30 9.01 5.21 1.40 0.85 0.13 4.98 0.50 Caloneis aerophila Bock 4 0.35 1.45 1.86 1.15 2.23 0.00 1.04 0.00 0.47 0.93 0.00 0.26 0.96 0.33 Cyclotella pseudostelligera Hustedt 5 1.23 2.75 0.00 2.30 1.12 1.96 2.51 3.60 3.44 3.27 1.02 4.34 5.31 2.16 Cyclotella rossii Håkansson 6 3.52 7.11 1.57 7.48 1.86 7.59 3.70 15.32 9.99 4.67 3.58 12.50 14.63 7.65 Cymbella lapponica Grunow ex Cleve 7 0.18 0.32 0.29 1.44 0.93 1.18 0.89 0.00 0.00 0.00 0.00 0.38 0.00 0.67 Diadesmis brekkaensis (Krasske) D.G. Mann 8 1.58 2.26 7.86 1.01 1.49 1.70 0.30 7.21 3.60 0.00 0.00 0.51 0.80 0.83 Diadesmis contenta (Grunow ex Van Heurck) D.G. Mann 9 4.75 2.42 1.57 1.15 2.98 1.96 1.04 4.50 3.19 1.87 0.00 1.02 0.96 1.33 Diadesmis gallica W. Smith 10 2.11 1.29 1.43 1.73 4.10 2.36 1.78 3.60 2.04 0.47 0.00 0.38 2.73 1.50 Diatoma tenuis C. Agardh 11 0.35 0.81 0.14 0.58 1.12 1.70 4.88 0.00 0.70 1.40 0.17 0.00 0.32 4.16 Eunotia arcus Ehrenberg 12 2.82 1.45 3.14 0.00 0.19 0.79 1.33 0.90 0.45 0.00 0.00 0.13 0.32 0.17 Eunotia praerupta Ehrenberg 13 1.23 1.29 5.43 0.29 2.23 0.79 0.00 0.00 0.00 0.00 0.00 0.51 0.16 0.33 Fragilaria capucina var. capucina Desmazières 14 1.06 0.97 0.57 2.16 4.66 1.18 5.33 0.90 4.19 7.48 0.17 1.40 1.45 6.82 Fragilaria capucina var. gracilis (Oestrup) Hustedt 15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.26 0.16 0.00 20 Fragilaria tenera (W. Smith) Lange-Bertalot 16 0.53 3.07 1.00 29.21 17.88 20.55 33.43 0.00 0.23 0.47 0.17 8.29 15.59 32.95 4 Gomphonema parvulum var. micropus (Kützing) Cleve 17 0.00 0.48 0.29 0.43 0.37 0.26 1.33 0.00 7.71 15.42 13.65 6.25 0.64 0.67

Navicula bergerii Krasske 18 0.18 0.65 1.29 1.29 0.37 4.32 0.00 3.60 2.27 0.93 0.34 0.00 1.45 0.83 Navicula bjoernoeyaensis Metzeltin, Witkowski & Lange-Bertalot 19 0.00 0.32 0.71 0.58 0.00 0.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Navicula pseudotenelloides Krasske 20 0.88 1.29 0.86 0.29 0.74 1.57 0.59 1.80 2.30 2.80 0.68 0.51 3.86 0.50 Nitzschia acicularis (Kützing) W. Smith 21 0.00 0.00 0.00 0.86 0.00 0.00 0.00 3.60 1.80 0.00 0.34 0.13 0.16 0.50 Nitzschia alpina Hustedt 22 0.88 0.32 0.29 0.29 0.74 0.65 0.74 5.41 3.64 1.87 0.68 0.51 2.73 0.33 Nitzschia lacunarum Hustedt 23 1.06 1.29 1.43 0.14 0.00 0.65 1.92 0.00 0.00 0.00 0.17 0.38 1.77 0.67 Nitzschia palea (Kützing) W. Smith 24 0.00 0.00 0.00 0.29 0.37 1.57 1.04 0.00 0.00 0.00 0.17 0.38 0.64 0.00 Nitzschia perminutum (Grunow) M. Peragallo 25 0.53 2.10 3.57 1.15 0.93 8.90 2.22 0.00 0.70 1.40 0.00 0.77 0.48 2.16 Pinnularia subrostrata (A. Cleve) Cleve-Euler 26 1.23 3.55 1.71 1.44 3.35 0.00 0.00 0.00 0.00 0.00 0.00 0.38 0.48 0.00 Pinnularia krammeri Metzeltin 27 3.35 0.81 1.57 0.72 0.74 0.65 0.00 1.80 1.13 0.47 0.00 0.51 0.00 0.00 Pinnularia microstauron (Ehrenberg) Cleve 28 1.76 0.97 0.29 1.15 3.72 2.36 0.89 0.00 0.00 0.00 0.00 0.26 1.93 0.33 Pinnularia obscura Krasske 29 32.39 5.33 5.00 0.00 4.84 0.79 0.00 0.90 0.68 0.47 0.00 0.00 0.00 0.67 Psammothidium chlidanos (Hohn & Hellerman) Lange-Bertalot 30 4.23 2.75 6.71 0.58 0.56 0.92 0.00 0.00 1.17 2.34 0.85 0.77 0.16 4.66 Psammothidium marginulatum (Grunow) Bukhtiyarova & Round 31 7.04 8.08 11.29 8.78 6.52 2.75 5.03 9.01 5.44 1.87 1.71 2.81 3.22 4.66 Rossithidium petersenii (Hustedt) Bukhtiyarova & Round 32 0.53 1.62 1.00 0.86 0.19 0.00 1.04 0.00 0.23 0.47 0.51 0.38 0.00 0.00 Stauroneis anceps Ehrenberg 33 1.23 1.62 0.71 1.58 0.19 2.23 1.63 0.00 0.00 0.00 0.17 0.77 0.48 0.17 Stauroneis lundii Hustedt 34 0.70 1.13 2.57 2.01 5.21 1.18 0.44 8.11 4.52 0.93 0.17 0.00 0.16 0.00 Proportion of total sample % 81.3 66.6 71.7 78.8 74.9 76.3 80.6 82.9 84.0 85.0 92.0 81.6 70.7 75.5

201

Appendix 5, continued. Relative abundances of common taxa in East Lake littoral sediment, plankton and sediment trap samples. Sediment Plankton Sediment trap taxa # Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 Au 6 Jn 28 Jy 5 Jy 9 Jy 16 Jy 22 Jy30 1 0.00 0.00 0.00 0.00 0.73 0.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 15.95 10.69 2.53 15.17 8.44 0.00 3.26 0.00 0.00 0.00 0.00 0.60 0.00 0.00 0.24 0.00 0.00 0.37 0.46 0.00 3 1.95 8.28 6.33 2.65 6.97 6.56 0.65 0.44 0.33 0.21 0.25 0.50 0.49 0.00 0.00 0.00 0.00 0.00 0.31 0.00 4 0.00 0.34 3.80 0.53 0.73 0.77 0.81 0.00 0.00 0.00 0.08 0.10 0.00 0.00 0.00 0.11 0.00 0.49 0.00 0.00 5 0.00 0.69 0.00 0.71 1.10 1.93 1.30 9.06 8.30 7.54 4.64 2.50 3.41 3.29 18.31 11.34 13.81 15.89 48.70 33.19 6 0.00 3.10 1.27 4.23 4.22 5.79 5.37 37.35 38.15 38.96 44.94 39.02 41.58 41.13 29.13 30.24 27.62 31.28 9.19 22.08 7 0.00 2.76 2.53 0.71 0.37 1.54 3.42 0.00 0.00 0.00 0.00 0.30 0.00 0.00 0.00 0.00 0.28 0.25 0.31 0.00 8 3.89 1.72 0.00 2.29 2.39 0.00 0.33 0.11 0.06 0.00 0.00 0.90 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 9 3.50 3.45 2.53 2.47 3.12 2.51 0.98 0.99 0.71 0.42 0.00 0.60 0.00 0.00 0.00 1.95 2.65 0.99 0.77 0.29 10 1.95 2.41 3.80 11.46 4.04 6.56 1.63 0.22 0.11 0.00 0.33 0.40 0.00 0.00 0.24 1.49 0.14 0.00 0.15 0.14 11 0.00 0.00 0.00 0.35 0.00 0.58 0.65 0.00 0.00 0.00 0.00 0.30 0.00 0.11 0.00 1.72 0.70 0.25 2.91 0.29 12 1.17 2.41 0.00 1.23 2.75 0.77 1.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13 0.78 1.03 1.27 0.53 2.20 0.19 0.16 0.00 0.00 0.00 0.00 0.00 0.19 0.00 0.00 0.00 0.28 0.00 0.00 0.29 14 0.00 0.69 0.00 0.71 0.18 0.77 1.14 0.55 0.28 0.00 0.00 0.00 0.00 0.11 0.48 0.00 0.00 0.00 0.31 0.00 15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.10 2.01 1.91 0.00 0.00 0.00 0.00 0.00 2.86 1.67 2.59 0.61 1.30

20 16 0.00 0.34 0.00 1.23 1.47 3.47 11.07 0.66 1.98 3.29 1.24 5.89 5.06 6.16 0.48 4.12 4.88 1.97 0.00 2.31

17 0.00 0.00 0.00 0.35 0.00 0.39 0.00 0.00 0.11 0.21 0.00 0.00 0.10 0.21 0.00 0.80 0.00 0.00 0.46 0.29 18 0.00 0.69 2.53 1.59 0.73 0.77 2.93 0.00 0.21 0.42 0.17 0.20 0.00 0.00 0.00 0.00 1.39 0.25 0.00 0.00 19 9.92 1.38 0.00 0.35 1.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20 0.00 0.69 0.00 0.00 0.00 3.67 0.81 0.55 0.38 0.21 0.17 0.10 0.19 0.21 0.00 1.49 0.28 0.99 0.31 0.29 21 0.00 0.34 0.00 0.00 0.00 0.00 0.00 1.88 1.79 1.70 0.75 0.20 1.17 1.91 9.63 0.92 5.86 4.93 0.61 5.05 22 0.00 0.69 0.00 2.12 2.20 1.16 1.47 0.33 0.22 0.11 0.17 0.00 0.49 0.00 1.07 0.80 0.56 0.25 0.15 0.00 23 7.20 0.00 0.00 0.35 0.73 2.90 0.98 0.00 0.05 0.11 0.00 0.10 0.00 0.00 0.00 0.23 0.00 0.49 0.00 0.29 24 0.39 0.34 0.00 0.53 0.37 0.97 4.07 0.22 0.11 0.00 0.00 0.00 0.10 0.00 0.24 0.46 0.56 1.23 0.31 0.58 25 0.19 2.41 1.27 5.29 5.14 6.56 5.54 0.88 0.65 0.42 0.25 1.00 0.00 0.43 0.24 0.00 0.28 0.00 0.00 1.30 26 4.67 3.45 8.86 1.76 0.92 2.70 0.33 0.00 0.11 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 27 0.00 1.38 0.00 0.00 1.10 0.58 0.16 0.00 0.00 0.00 0.08 0.30 0.00 0.21 0.00 0.00 0.56 0.00 0.00 0.29 28 0.58 2.41 5.06 0.18 0.73 1.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.61 0.00 29 5.84 0.69 0.00 0.18 1.83 1.16 0.16 0.33 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 30 0.78 4.48 7.59 3.17 0.55 5.41 3.42 0.22 0.11 0.00 0.17 0.50 0.10 0.21 0.48 0.00 0.00 0.00 0.77 1.30 31 10.12 12.07 11.39 8.64 17.25 4.05 6.68 1.33 1.09 0.85 0.25 0.80 0.10 0.96 0.24 0.80 0.28 0.49 0.31 0.87 32 0.19 1.72 3.80 0.88 2.94 1.54 0.65 0.77 0.60 0.42 0.00 0.20 0.00 0.00 0.24 0.23 0.14 0.00 0.31 0.00 33 0.58 1.72 2.53 1.94 1.10 1.54 3.42 0.11 0.06 0.00 0.00 0.20 0.00 0.11 0.24 0.23 0.14 0.00 0.61 0.00 34 8.75 2.76 16.46 5.47 2.02 2.90 3.09 0.00 0.00 0.00 0.00 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.15 0.00 78.4 75.2 83.5 77.1 77.4 69.3 65.6 58.1 57.6 57.0 53.5 54.9 53.0 55.0 61.2 59.8 62.1 62.7 68.9 70.1 202

Appendix 6. Relative abundances (%) of common (≥2%) diatom species in a) West Lake and b) East Lake sediment cores.

West Lake Depth interval (cm) Taxon 0-0.5 0.5-1 1-1.5 1.5-2 2-2.5 2.5-3 mean min max Chrysophyte cysts 8.8 4.8 8.2 9.0 13.9 15.8 10.1 4.8 15.8 Achnanthes chlidanos 0.0 0.0 0.7 0.5 0.7 2.3 0.7 0.0 2.3 Achnanthes daonensis 2.8 3.1 5.4 7.5 4.9 4.8 4.7 2.8 7.5 Achnanthes minutissimum 2.9 7.6 5.1 8.3 11.7 9.6 7.5 2.9 11.7 Aulacoseira ambigua 1.0 0.7 9.0 34.7 39.3 19.0 17.3 0.7 39.3 Cyclotella rossii 13.5 11.3 22.3 8.1 5.5 14.2 12.5 5.5 22.3 Cyclotella pseudostelligera 66.2 61.2 44.7 13.9 14.6 11.9 35.4 11.9 66.2 Diadesmis gallica 0.6 0.7 0.0 1.0 1.7 3.1 1.2 0.0 3.1 Fragilaria capucina var capucina 0.0 0.4 0.7 1.3 2.9 2.3 1.3 0.0 2.9 Navicula contenta 0.8 0.5 0.0 2.3 0.3 3.3 1.2 0.0 3.3 Nitzschia perminuta 1.0 0.7 0.9 0.5 2.2 1.7 1.2 0.5 2.2 total 88.8 86.2 88.8 78.1 83.7 72.0 83.0 72.0 88.8

East Lake Depth interval (cm) Taxon 0-0.5 0.5-1.0 1.0-1.5 5-5.5 mean min max Cysts 9.58 10.25 14.08 21.38 13.83 9.58 21.38 Achnanthes laevis 0.00 0.00 0.00 3.60 0.90 0.00 3.60 Achnanthes laterostrata 0.59 1.30 2.62 0.00 1.13 0.00 2.62 Achnanthes saccula 2.17 1.04 0.37 0.00 0.89 0.00 2.17 Cyclotella rossii 50.79 44.34 68.04 62.23 56.35 44.34 68.04 Cyclotella pseudostelligera 27.56 25.49 2.80 0.00 13.96 0.00 27.56 Diadesmis gallica 0.00 2.47 0.00 0.00 0.62 0.00 2.47 Diploneis oblongella 0.98 1.56 1.12 2.16 1.45 0.98 2.16 Fragilaria cap gracilis 8.07 6.63 1.50 0.00 4.05 0.00 8.07 Fragilaria tenera 0.39 1.95 2.24 0.00 1.15 0.00 2.24 Navicula cincta 0.00 0.65 0.00 3.24 0.97 0.00 3.24 Nitzschia perminuta 2.8 2.0 0.7 1.8 1.81 0.75 2.76 Stauroneis smithii 0.00 0.00 0.00 2.88 0.72 0.00 2.88 Total abundance 93.30 87.39 79.44 75.90 84.01 75.90 93.30

206

Appendix 7. List of identified diatom species and varieties from the Cape Bounty lakes.

Achnanthes altaica C. bacillum Frustulia rhomboides var. A. broenlundensis C. molaris crassinerva A. coarctata C. silicula Geissleria similis A. daonensis Cavinula cocconeiformis G. bereasuberica A. didyma Cocconeis placentula G. decussis A. distincta Cyclotella atomus Gomphonema angustum A. flexella C. ocellata G. parvulum var. micropus A. bioretti C. bodanica Hannaea arcus A. helveticum C. comensis H. cyclopum A. holstii C. pseudostelligera Hanzschia amphioxys A. impexiformis C. rossii Luticola mutica A. kriegerii C. stelligera L. mutica var. ventricosa A. laevis Cymbopleura Meridion circulare A. lanceolata stauroneiformis Muelleria gibbula A. laterostrata Denticula Navicula angustum A. levanderi Dia. oblogella N. bacillum A. nitidiformis Dia. tenuis N. bergerii A. nodosa Diadesmis gallica N. brekkaensis A. pusilla var.gallica N. capitata A. reimeri D. gallica var. laevissima N. cincta A. rupestoides D. gallica var. perpusilla N. contenta A. rupestris Diatoma monoliformis N. costulata A. saccula Diploneis oculata N. cryptocephala A. stolida D. parma N. cryptotenella A. subatomoides Eunotia arcus N. decussis Achnanthidium E. bilunaris N. digitulus minutissimum E. exigua N. diluviana Amphora inariensis E. lapponica N. egregia Anomoneis vitrea E. praerupta N. elginensis var. Aulacoseira ambigua E. pseudopectinalis elginensis Cymbella amphicephala E.intermedia N. festiva C. angustata Encyonema fogedii N. gerloffii C. arctica E. latens N. gregaria C. cesatii E. silesiacum N. halophila C. cuspidata E. ventricosum N. ignota var. palustris C. cuspitosa Fragilaria capucina var. N. impexa C. ehrenbergerii cf capucina N. ingrata C. hybrida var. lanceolata F. capucina var. gracilis N. jaggii C. incerta F. capucina var. N. kriegerii C. lapponica vaucheriae N. maceria C. neocistula F. construens N. minima C. reinhardtii F. gracilis N. miniscula C. sinuata F. pinnata N. miniscula var. muralis C. turgidula F. tenera N. minisculoides C. tynnii F. ulna N. monoculata Caloneis aerophila N. palaearctica

207

N. phyllepta N. tubicola N. pseudotenelloides Pinnularia balfouriana N. ryncocephala P. divergentissima var. sub N. schmassmannii P. diversa var. minor N. similis P. intermedia N. slesvicensis P. lundii N. subadnata P. subrostrata N. sublucidula P. borealis N. subminiscula P. borealis cf N. submodesta P. brandelii N. subtillissima P. bulacostae N. tripunctata P. cuneola N. var.iostriata P. diversa N. weinziettii P. humilis N.krasskei P. interrupta Neidiopsis carterii P. krammeri Neidiopsis levanderi P. lagerstedtii Neidium affine var. P. microstauron longiceps P. obscura N. ampliatum P. schimanski N. bisulcatum P. schimanski cf N. carterii P. viridis N. decoratum Psammothidium chlidanos N. decoratum var. bergii P. kryophilum N. minutissimum P. marginulatum N. wolfii P. ventralis Nitzschia alpina Rossithidium petersenii N. angustiforaminata Sellaphora pupula N. bryophila S. pupula var. aquaductae N. clausii Stauroneis anceps N. commutata S. anceps var. siberica N. debilis S. borrichii N. dissipata S. laterostrata N. draveillensis S. lundii N. epithemoides S. phoeniciteron N. fonticola S. sagitta N. lacunarum S. smithii N. ovalis Stephanodiscus niagarae N. palea Surirella dubravicensis N. perminuta S. minuta N. pura Tabellaria flocculosa N. tripunctata

208

Appendix 8. Photomicrographs of common (≥2%) taxa from West and East lakes. Bold denote taxa common to both lakes.

209

Appendix 8, continued. Photomicrographs of common taxa (≥2%) from East and West lakes.

210

Appendix 9. Radioisotopic dating including a) West Lake 137Cs concentrations, b) West Lake 210Pb concentrations, and c) East Lake 137Cs concentrations.

West Lake 7 137Cs concentrations b) sample depth interval (cm) dpm/g 1 0.0-0.5 0.12 West Lake 7 210Pb concentrations 2 0.5-1.0 0.37 3 1.0-1.5 0.92 sample top (cm) bottom Bq/g age 4 1.5-2.0 1.09 1 0 1 0.091398 2002 5 2.0-2.5 0.83 2 1 2 0.061882 1989 6 2.5-3.0 0.19 7 3.0-3.5 0.18 3 2 3 0 Turbidity Flow 8 3.5-4.0 0.63 0 3 5 0 Turbidity Flow 9 4.0-4.5 1.74 4 5 6 0 1973 10 4.5-5.0 4.28 5 6 7 0 1969 11 5.0-5.5 1.18 0 7 9 0 Turbidity Flow 12 5.5-6.0 0.81 6 9 10 0 Turbidity Flow 13 6.0-6.5 0.57 7 10 11 0.028786 1964 14 6.5-7.0 0.22 8 11 12 0.017794 1950 15 7.0-7.5 0.14 0 12 13 0.013813 1937 16 7.5-8.0 0.23 9 13 14 0.009832 1922 17 8.0-8.5 1.87 18 8.5-9.0 0.10 0 14 16 0.00557 19 9.0-9.5 0.01 10 16 17 0.001308 Background 20 9.5-10.0 - 0.01 11 25 26 Background 21 10.0-10.5 0.04 12 26 27 Background

East Lake 11 137Cs Sample 137Cs (dpm/g) CBEL11 0-0.5 0.451971807 CBEL11 0.5-1.0 0.733621512 CBEL 11 1.0-1.5 1.138186251 CBEL 11 1.5-2.0 1.560187117 CBEL 11 2.0-2.5 1.333436415 CBEL 11 2.5-3.0 1.053537973 CBEL 11 3.0-3.5 2.477819621 CBEL 11 3.5-4.0 5.30997885 CBEL 11 4.0-4.5 5.915651388 CBEL 11 4.5-5.0 3.254356719 CBEL 11 5.0-5.5 0.583474273 CBEL 11 5.5-6.0 0.200665297 CBEL 11 6.0-6.5 0.016017305 CBEL 11 6.5-7.0 -0.000639728 CBEL 11 7.0-7.5 0.256633639 CBEL 11 7.5-8.0 -0.001727628 CBEL 11 8.0-8.5 0.066363895 CBEL 11 8.5-9.0 0.142067866 CBEL 11 9.0-9.5 0.1892628 CBEL 11 9.5-10.0 -0.117661891

211

Appendix 10. West Lake Chl-a (and derivatives) concentrations and profile.

Interval Chl-a (mg g-1 bottom (cm) dry mass) 0.5 0.0016 West Lake Chl-a 1.0 0.0034 0.0120 1.5 0.0034 0.0100 2.0 0.0030 2.5 0.0025 0.0080 3.0 0.0023 0.0060 3.5 0.0029 0.0040

4.0 0.0028 mass) dry (mg/g a - 0.0026 4.5 Chl 0.0020 5.0 0.0034 5.5 0.0016 0.0000 6.0 0.0024 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 6.5 0.0021 Depth (cm) 7.0 0.0020 7.5 0.0020 8.0 0.0023 8.5 0.0025 9.0 0.0022 9.5 0.0028 10.0 0.0024

11.0 0.0021 12.0 0.0028 13.0 0.0026 14.0 0.0035 15.0 0.0026 16.0 0.0032 17.0 0.0027 18.0 0.0027 19.0 0.0027 20.0 0.0026 21.0 0.0021 22.0 0.0026 23.0 0.0022 24.0 0.0021 25.0 0.0020 26.0 0.0020 27.0 0.0027 28.0 0.0027 29.0 0.0024 30.0 0.0021

212

Appendix 10, continued. East Lake Chl-a (and derivatives) concentrations and depth profile.

Interval top Chl-a+ (mg g-1 dry mass) 0 0.0054 0.5 0.0051 Chl-a concentrations 1.0 0.0058 0.012 1.5 0.0072 2.0 0.0030 0.01 2.5 0.0031 0.008 3.0 0.0022 3.5 0.0032 0.006 4.0 0.0020 4.5 0.0020 0.004 5.0 0.0060 5.5 0.0069 0.002 6.0 0.0063 0

6.5 0.0036 Concentration (mg g/g dry weight) dry g/g (mg Concentration 7.0 0.0039 0 10 20 30 40 Depth (cm) 7.5 0.0051 8.0 0.0024 8.5 0.0039 9.0 0.0064 9.5 0.0056 10.0 0.0020 11.0 0.0105 12.0 0.0025 13.0 0.0042 14.0 0.0041 15.0 0.0036 16.0 0.0035 17.0 0.0030 18.0 0.0059 19.0 0.0045 20.0 0.0051 21.0 0.0025 22.0 0.0033 23.0 0.0032 24.0 0.0013 25.0 0.0034 26.0 0.0028 27.0 0.0022 28.0 0.0023 29.0 0.0019 30.0 0.0020 31.0 0.0021 32.0 0.0020 33.0 0.0021 34.0 0.0044 35.0 0.0024 36.0 0.0032 37.0 0.0041 38.0 0.0042 39.0 0.0031 40.0 0.0022

213

Appendix 11. Organic solvent extract yield masses for a) West Lake and b) East Lake, and c) concentration ranges (in µg g-1 OC) of major lipid groups for West and East Lake.

a) West Lake

Depth interval Weight (g) % Carbon gC/gSed sample mass (g) mass of extract (g) mg/g sed mg/g OC 0-2 0.601 1.078 0.01078 20.1 0.0071 0.353234 32.76752 2-4 0.603 0.9364 0.009364 20 0.0034 0.17 18.15463 4-6 0.6013 0.9256 0.009256 20 0.0036 0.18 19.44685 6-8 0.603 0.8417 0.008417 20 0.002 0.1 11.88072 8-10 0.6027 0.958 0.00958 20 0.0026 0.13 13.56994 10-12 0.6019 1.018 0.01018 20 0.0046 0.23 22.59332 12-14 0.6014 1.003 0.01003 20 0.0046 0.23 22.93121 14-16 0.6005 1.031 0.01031 20 0.0065 0.325 31.52279 16-18 0.6029 1.031 0.01031 20 0.0128 0.64 62.07565 18-20 0.6029 1.045 0.01045 20 0.016 0.8 76.55502 20-21 0.6003 1.04 0.0104 20 0.008 0.4 38.46154

b) East Lake

Depth Org C (% dry) sample mass vial mass vial + extract mass mass of extract (g) mg/g sed mg/g OC 0 1.4 5.5 2.3324 2.3732 0.0408 7.418181818 529.87013 1 1.35 5.8 2.3099 2.3522 0.0423 7.293103448 540.22989 2 1.04 5.9 2.3365 2.39 0.0535 9.06779661 871.90352 3 1.16 5 2.3557 2.3615 0.0058 1.16 100 4 0.916 4.9 2.3794 2.3807 0.0013 0.265306122 28.96355 5 1.34 5.3 2.2938 2.3091 0.0153 2.886792453 215.43227 6 1.28 5 2.3987 2.4002 0.0015 0.3 23.4375 7 1.35 4.8 2.2893 2.345 0.0557 11.60416667 859.5679 8 1.3 5.2 2.3907 2.3931 0.0024 0.461538462 35.502959 9 1.39 3.8 2.3988 2.4059 0.0071 1.868421053 134.41878 10 1.39 5.1 2.3226 2.3388 0.0162 3.176470588 228.52306 11 1.56 3.8 2.415 2.4254 0.0104 2.736842105 175.4386 12 1.41 4.9 2.3959 2.4023 0.0064 1.306122449 92.632798 13 1.47 5.3 2.3738 2.3845 0.0107 2.018867925 137.33795 14 1.48 5.3 2.3365 2.3389 0.0024 0.452830189 30.596634 15 1.45 5.5 2.3197 2.324 0.0043 0.781818182 53.918495 16 1.42 5.7 2.3042 2.3069 0.0027 0.473684211 33.358043 17 1.59 5.4 2.3848 2.3893 0.0045 0.833333333 52.410901 18 1.57 5.3 2.3655 2.3698 0.0043 0.811320755 51.676481 19 1.62 5.2 2.3029 2.3073 0.0044 0.846153846 52.231719

West Lake East Lake n-Alkanes 572-1176 434-1604 n-Alkanols 2143-4474 2972-10590 n-alkanoic acids 748-2868 746-9479 Steroids 1423-2743 2517-4922 Terpenoids 1799-3517 3117-7371

214

Appendix 12. Extract compounds and concentrations (ug g-1 OC) for West Lake.

Depth interval (cm) Lipid group Compound 0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20 20-21 n-Alkanes ane18 31.41 0.00 0.00 0.00 0.00 0.00 0.00 31.34 0.00 0.00 39.88 ane19 23.53 28.53 28.20 35.13 43.45 28.09 30.37 0.00 26.73 17.23 0.00 ane20 27.28 23.64 43.74 69.05 44.48 76.50 29.67 25.89 26.53 20.92 30.60 ane21 63.29 68.18 59.47 61.84 68.50 74.85 69.28 57.39 54.35 51.77 48.07 ane22 56.64 64.43 70.97 61.88 43.73 71.63 60.67 51.28 46.41 44.68 43.55 ane23 103.63 86.06 93.81 81.75 77.23 128.96 118.48 98.35 122.85 127.09 101.15 ane24 50.90 55.49 50.88 43.34 41.11 58.81 52.18 33.25 47.85 49.29 47.04 ane25 118.09 103.90 99.79 88.04 77.27 147.59 129.68 90.06 101.61 106.00 102.67 ane26 42.16 39.32 40.75 19.59 10.85 42.78 40.49 30.68 25.38 29.93 32.50 ane27 172.83 120.88 139.34 128.30 85.97 174.34 158.74 109.02 120.86 111.75 118.19 ane28 52.63 37.43 52.94 ane29 142.18 109.70 113.25 78.77 45.49 141.59 115.62 86.26 106.56 91.00 118.65 ane31 127.40 93.71 97.18 39.96 33.77 114.74 95.07 65.72 38.77 77.32 120.46 ane32 107.16 49.60 76.49 0.00 0.00 116.12 108.06 69.97 55.72 49.73 80.64 Sum total 1119.11 880.87 966.82 707.66 571.84 1176.02 1008.30 749.22 773.63 776.70 883.42

n-Alkanols anol15 0.00 0.00 0.00 0.00 0.00 23.74 23.27 24.42 16.62 20.34 18.92 anol 16:1 19.94 0.00 27.83 0.00 0.00 30.12 16.87 0.00 0.00 0.00 0.00 anol16 27.83 0.00 24.98 25.57 37.58 27.93 25.29 0.00 0.00 20.15 24.39 anol18 29.20 47.13 43.03 39.86 25.38 35.27 27.66 28.45 27.82 35.26 27.91 anol20 92.31 85.08 78.85 73.15 71.29 136.50 132.25 141.54 142.85 182.97 159.34 anol21 35.01 27.65 27.33 28.10 33.91 68.58 65.94 59.06 59.91 75.74 58.18 anol22 583.41 571.11 574.60 590.50 626.77 744.34 711.00 620.18 609.38 716.46 558.14 anol23 125.53 69.98 77.88 74.66 66.62 131.25 129.14 121.99 118.97 150.91 132.57 anol24 586.80 375.51 381.97 422.30 348.73 678.18 585.38 560.67 575.92 665.73 617.25 anol25 138.79 60.07 69.08 65.81 52.41 117.98 105.20 100.83 103.41 139.61 120.76 anol26 1140.14 593.52 602.18 721.12 514.46 1264.93 1142.81 799.32 836.79 864.65 881.40 anol27 142.06 47.97 66.37 68.64 43.14 150.77 115.44 63.41 70.21 101.08 113.71 anol28 550.32 256.41 276.92 298.63 243.52 781.79 639.98 336.81 335.55 372.71 496.39 anol30 225.86 99.61 158.87 126.05 79.28 282.76 255.45 214.11 191.13 143.38 256.91 Sum total 3697.22 2234.05 2409.87 2534.38 2143.09 4474.14 3975.66 3070.79 3088.55 3488.98 3465.87

n-Alkanoic acids fa12 0.00 12.08 4.39 31.60 25.57 25.29 43.83 35.81 39.48 0.00 46.30 (fatty acids) fa14 61.98 49.07 62.29 42.72 30.60 59.03 41.39 33.71 20.01 20.22 34.34 fa15 20.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fa16 171.94 110.05 167.47 117.79 103.15 117.24 111.96 134.71 106.65 145.12 205.22 fa18 63.75 43.99 79.88 52.77 50.09 52.95 52.09 75.00 64.44 60.97 99.73 fa18:1 79.64 103.91 383.02 65.95 89.08 119.54 36.45 75.21 30.97 21.73 218.97 fa18:2 16.14 45.75 116.36 23.75 19.46 43.35 0.00 33.38 0.00 0.00 57.37 fa20 43.56 39.91 34.26 32.00 34.96 51.99 57.44 74.10 65.30 72.51 86.08 fa21 30.49 18.81 32.67 31.78 27.42 35.37 36.50 46.89 37.46 24.90 38.18 fa22 163.90 133.10 134.23 124.85 83.36 211.44 206.81 265.29 272.34 150.55 305.84 fa22 O-hydroxy 122.26 65.78 94.95 39.00 35.86 78.63 73.09 110.42 103.80 0.00 160.26 fa23 79.09 54.07 55.45 49.31 41.01 103.90 89.12 113.35 120.06 40.69 112.58 fa24 268.25 225.17 200.36 209.67 133.50 364.57 301.13 476.33 466.16 161.82 633.87 fa25 72.66 40.84 47.68 30.05 23.87 78.68 56.30 88.98 80.68 0.00 106.82 fa26 175.80 146.18 155.82 144.01 73.97 256.11 153.40 289.31 270.45 0.00 441.79 fa28 303.85 117.99 158.05 333.99 66.78 302.51 200.92 205.34 166.86 49.62 320.66 sum all 1673.42 1206.72 1726.90 1329.26 838.67 1900.61 1460.43 2057.82 1844.67 748.13 2868.03

steroids campesterol 311.69 242.31 273.16 234.72 168.16 324.21 299.46 267.34 255.97 288.01 274.82 cholestanol 227.24 214.03 313.33 169.53 171.66 349.85 326.30 333.84 292.62 68.14 390.06 cholesterol 200.86 112.25 178.15 60.41 74.22 123.51 101.71 66.08 55.64 77.62 105.04 sitosterol 1072.15 802.95 757.17 636.94 555.61 1007.25 984.58 988.74 976.94 998.62 946.84 stigmastanol 406.58 308.32 387.98 324.55 326.33 673.82 642.09 619.61 596.06 477.98 561.66 stigmasterol 252.91 153.87 192.54 138.35 127.27 264.00 252.88 208.99 178.04 157.12 188.82 Sum total 2471.44 1833.73 2102.33 1564.50 1423.25 2742.64 2607.03 2484.60 2355.27 2067.49 2467.24

Terpinoids friedelin 91.52 79.85 87.35 82.05 69.85 142.44 112.20 96.66 72.54 38.61 51.31 hopene 135.57 51.08 89.99 33.38 73.41 101.07 49.97 61.76 9.23 69.82 82.23 a-amyrin 78.19 29.61 61.81 46.44 26.82 104.07 84.57 60.10 50.54 42.74 62.19 2829.29 2028.27 2401.80 1765.73 1629.04 3169.17 2923.03 2763.87 2553.55 2281.88 2744.61 Sum total 3134.56 2188.82 2640.95 1927.60 1799.12 3516.74 3169.77 2982.39 2685.85 2433.06 2940.35

carbohydrates #1 42.45 20.73 23.56 24.02 29.92 30.15 26.06 27.09 19.99 19.61 17.73 #2 23.92 47.87 19.36 58.00 27.41 37.33 26.05 20.01 20.52 20.13 40.36 #3 17.07 31.54 38.93 54.75 49.55 78.49 31.33 35.23 35.89 35.20 48.95 # galactose 30.98 61.11 30.87 0.00 41.00 31.47 63.68 46.27 56.29 55.22 18.87 # glucose 68.38 37.62 37.13 0.00 0.00 33.62 20.24 1.52 12.12 11.89 22.65 # mannose 40.31 0.00 0.00 0.00 0.00 78.81 39.80 45.25 26.20 25.70 63.44 #4 19.28 0.00 0.00 0.00 0.00 0.00 24.44 0.00 0.00 0.00 0.00 #glucose 84.65 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 #lactose 16.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 #trehalose 618.88 35.13 57.56 34.99 85.15 139.30 131.18 53.06 59.15 0.00 40.60 #succrose 144.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

215

Appendix 13. Extract compounds and concentrations for East Lake for depths 0-10 cm. Concentrations are in µg g-1 OC. Depth (cm) Lipid group Compound 0 1 2 3 4 5 6 7 8 9 n-Alkanoic acids fa12 13.09 82.28 311.03 39.19 0.00 46.08 76.81 220.35 140.70 0.00 fa13 5.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fa14 35.09 55.06 58.99 0.00 29.13 12.64 24.88 59.61 0.00 48.63 fa15 0.00 14.94 13.49 0.00 0.00 0.00 0.00 0.00 0.00 fa16 115.95 195.90 367.75 175.70 175.85 127.74 139.65 503.46 227.47 210.67 fa17 7.14 0.00 0.00 0.00 0.00 0.00 0.00 52.42 0.00 21.26 fa18 77.67 149.17 426.05 189.83 132.52 122.02 142.66 660.76 230.71 133.05 fa 18:1 44.19 113.51 506.46 195.16 0.00 0.00 194.57 808.90 239.69 57.35 fa 18:2 36.77 123.82 818.00 164.21 0.00 87.07 165.50 577.07 359.28 57.35 fa19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15.95 0.00 0.00 fa20 0.00 33.71 46.34 38.35 74.84 25.40 38.80 86.64 72.84 118.66 fa21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 42.68 45.72 70.79 fa22 47.10 138.53 169.50 155.95 335.78 137.94 179.62 384.55 323.99 618.33 fa23 0.00 48.37 63.84 64.81 155.88 56.94 72.26 139.87 156.53 329.79 fa24 146.07 361.87 311.07 312.97 667.31 332.68 366.39 682.68 623.88 1329.02 fa25 24.81 30.32 0.00 99.19 103.40 34.14 51.87 110.83 110.90 224.81 fa26 192.64 371.51 203.68 224.88 485.17 193.59 270.67 468.39 454.81 961.65 fa27 0.00 0.00 78.10 96.08 83.56 106.41 81.33 144.67 182.14 226.33 fa28 0.00 293.10 204.54 180.74 424.86 178.93 279.24 334.48 333.82 969.40 fa29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fa30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 241.67 103.75 197.25 sum total 746.03 2012.08 3578.83 1937.06 2668.28 1461.59 2084.26 5534.95 3606.21 5574.35

n-Alkanols alkanol13 9.08 12.65 4.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol14 12.25 9.98 0.00 0.00 0.00 4.49 0.00 12.70 0.00 0.00 alkanol15 0.00 0.00 27.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol16 216.79 14.43 23.49 0.00 0.00 10.01 11.84 18.30 0.00 24.82 alkanol17 0.00 109.95 17.76 0.00 0.00 10.28 0.00 195.23 87.36 130.88 alkanol18 0.00 43.19 41.70 0.00 38.20 0.00 0.00 38.51 0.00 51.32 alkanol19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol20 79.32 107.37 123.08 112.55 188.54 97.97 116.80 199.01 173.08 300.17 alkanol21 37.84 64.68 54.48 49.05 78.98 60.17 49.79 82.54 74.54 130.46 alkanol22 425.06 324.82 610.06 574.22 872.57 520.35 528.05 790.13 753.80 1172.42 alkanol23 71.01 155.66 118.30 111.95 176.99 145.90 113.16 176.00 156.11 276.76 alkanol24 426.39 637.43 765.82 772.59 1152.82 763.25 698.98 965.56 845.13 1482.54 alkanol25 98.01 153.44 124.85 122.22 176.14 126.02 116.76 184.54 154.17 282.17 alkanol26 606.13 1138.19 1592.49 1479.56 2228.66 1137.92 1276.63 1855.25 1507.42 3117.13 alkanol27 0.00 0.00 131.47 139.08 179.19 95.98 94.36 138.26 121.86 302.52 alkanol28 1205.80 812.20 905.24 991.79 1870.04 0.00 598.19 898.05 744.31 3052.49 alkanol29 49.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol30 0.00 194.41 116.68 127.51 240.67 0.00 252.47 158.97 143.93 266.53 alkanol31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sum total 3237.47 3778.42 4657.51 4480.52 7202.79 2972.34 3857.02 5713.05 4761.71 10590.22

n-Alkanes alkane19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12.04 alkane20 0.00 11.54 10.35 0.00 0.00 10.57 8.90 15.05 25.28 22.62 alkane21 24.03 41.78 32.29 27.08 30.29 32.57 32.76 46.51 42.55 74.21 alkane22 28.30 45.79 31.99 32.11 35.19 39.90 32.12 47.62 42.91 66.45 alkane23 83.29 153.26 81.44 89.26 113.83 99.20 89.40 119.08 107.56 176.54 alkane24 27.12 52.71 28.33 37.23 43.51 25.45 43.20 61.71 47.14 64.66 alkane25 84.60 119.53 93.14 97.81 137.31 71.46 101.20 137.58 115.95 156.47 alkane26 21.93 11.77 15.50 15.44 17.56 25.07 11.84 23.94 13.25 25.39 alkane27 85.27 104.20 128.57 115.91 165.35 83.49 114.51 157.57 113.11 251.62 alkane28 0.00 6.59 35.76 33.12 61.69 33.77 33.71 45.86 28.63 65.67 alkane29 39.34 41.96 90.85 94.97 138.37 61.49 94.53 119.67 97.98 88.56 alkane31 39.82 69.11 85.97 90.50 139.14 59.21 107.54 90.70 97.45 152.60 sum total 433.70 658.25 634.18 633.44 882.25 542.18 669.71 865.29 731.80 1156.82

n-alkanals alkanal20 39.01 76.05 0.00 0.00 0.00 0.00 28.01 45.63 38.39 64.56

Steroids cholesterol 406.03 2176.94 369.39 1702.89 1805.45 1288.58 1572.06 2071.76 141.24 891.93 sitosterol 1400.81 646.77 232.78 387.83 639.91 412.13 370.26 476.10 488.74 650.25 campesterol 348.66 812.01 1997.85 588.24 852.91 468.37 416.85 259.63 403.56 200.16 stigmasterol 431.78 515.10 377.99 370.60 518.89 348.03 510.17 369.39 1629.39 1929.83 sum total 2587.29 4150.82 2978.01 3049.55 3817.16 2517.11 2869.34 3176.88 2662.93 3672.17

Terpenoids a-Amyrin 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Friedelin 0.00 98.66 126.99 115.35 174.88 88.60 87.50 137.73 135.42 158.27 Hopene 127.60 220.94 127.94 171.81 116.89 206.12 0.00 168.34 143.88 262.75 sum total 3117.23 5190.58 4067.61 3876.05 4759.82 3287.15 3416.16 4830.28 3720.10 5668.45

Carbohydrates #galactose 29.05 45.41 53.34 52.00 70.18 0.00 41.14 52.50 42.41 62.36 trehalose 0.00 75.33 47.83 304.05 65.07 99.97 37.77 61.84 67.33 102.39 #1 0.00 79.05 175.47 0.00 647.41 0.00 288.47 294.60 65.68 88.76 #2 0.00 255.46 0.00 0.00 0.00 0.00 0.00 0.00 243.04 458.90 sum total 29.05 455.25 276.64 356.05 782.65 99.97 367.38 408.95 418.46 712.41

216

Appendix 13, continued. Compounds and concentrations of lipids from East Lake for depths 10- 20 cm.

Lipid group Compound 10 11 12 13 14 15 16 17 18 19 n-Alkanoic acids fa12 0.00 0.00 0.00 71.36 0.00 0.00 0.00 21.43 33.10 0.00 fa13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fa14 0.00 68.65 0.00 49.81 63.40 52.08 0.00 50.37 67.02 57.47 fa15 0.00 26.27 0.00 0.00 0.00 0.00 0.00 31.16 0.00 0.00 fa16 176.88 237.61 186.79 283.79 202.42 196.06 207.99 253.89 292.83 296.87 fa17 0.00 17.30 0.00 0.00 70.20 0.00 0.00 0.00 64.72 58.38 fa18 115.28 127.15 131.58 290.14 142.53 136.68 187.90 194.02 225.37 263.93 fa 18:1 85.53 144.37 68.35 235.62 363.26 213.25 159.71 86.41 155.56 208.95 fa 18:2 85.53 79.66 0.00 283.58 28.96 0.00 68.10 48.38 60.90 98.31 fa19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fa20 130.21 162.02 109.02 128.92 114.62 127.46 192.01 268.96 283.92 251.83 fa21 71.76 77.57 50.22 58.55 54.99 62.67 79.09 137.78 129.25 121.76 fa22 624.12 790.45 503.72 512.52 513.71 535.02 871.54 1155.41 1174.24 1040.80 fa23 286.78 403.69 222.37 240.86 168.75 211.85 395.47 559.95 590.38 529.18 fa24 1150.85 1624.71 972.98 993.12 706.23 906.14 1584.34 2176.98 2235.39 1953.95 fa25 215.96 2478.29 189.13 198.70 106.78 178.03 246.36 402.67 391.06 381.60 fa26 963.49 257.39 730.63 761.30 396.67 630.64 1171.26 1749.50 1875.60 1673.99 fa27 217.35 1391.67 230.43 240.74 0.00 278.40 114.50 308.97 307.82 363.79 fa28 606.89 239.41 674.76 501.91 321.67 605.41 594.81 0.00 1166.57 1230.66 fa29 0.00 416.61 0.00 91.16 0.00 0.00 0.00 1054.28 0.00 0.00 fa30 225.29 254.44 299.81 288.33 0.00 266.28 198.14 374.30 425.60 413.87 sum total 4955.92 8797.25 4369.78 5230.44 3254.20 4399.98 6071.20 8874.47 9479.34 8945.35

n-Alkanols alkanol13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.36 0.00 alkanol14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 alkanol16 0.00 24.82 0.00 24.01 0.00 0.00 0.00 0.00 30.05 0.00 alkanol17 78.64 119.15 82.09 74.10 0.00 67.38 0.00 52.86 118.90 92.83 alkanol18 52.64 65.72 47.21 47.77 45.96 55.31 38.54 48.32 71.37 56.52 alkanol19 0.00 0.00 0.00 16.55 0.00 0.00 0.00 0.00 0.00 0.00 alkanol20 302.07 323.64 280.30 301.48 363.25 355.93 342.84 475.22 443.98 450.13 alkanol21 110.23 137.84 126.46 130.32 144.60 150.03 107.51 185.04 176.09 186.47 alkanol22 1062.84 1284.04 1246.91 1258.82 1582.32 2126.30 1419.32 2245.33 2042.83 1550.16 alkanol23 183.39 308.03 257.06 244.51 254.42 279.87 193.42 310.35 332.08 356.87 alkanol24 1200.38 1442.74 1308.02 1290.47 1248.24 1479.09 1372.57 1790.39 1810.72 1663.45 alkanol25 197.02 245.71 258.00 251.97 214.13 265.35 173.30 321.58 292.55 352.86 alkanol26 1899.27 110.12 2306.63 2392.02 1944.14 2447.65 1980.07 2716.59 2861.60 2750.10 alkanol27 134.25 455.99 227.48 207.42 144.71 233.89 0.00 0.00 0.00 0.00 alkanol28 897.83 218.58 1099.97 1252.78 909.65 1077.48 1071.78 1491.65 1622.75 1775.50 alkanol29 0.00 200.19 0.00 140.73 0.00 0.00 0.00 0.00 0.00 0.00 alkanol30 382.23 3246.87 511.54 326.37 288.64 452.38 366.48 606.55 636.44 664.29 alkanol31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sum total 6500.79 8183.45 7751.68 7959.30 7140.07 8990.65 7065.83 10243.87 10443.73 9899.18

n-Alkanes alkane19 0.00 18.28 0.00 9.83 0.00 0.00 0.00 20.53 27.62 23.61 alkane20 0.00 20.91 25.60 22.71 0.00 21.25 0.00 24.87 29.40 26.31 alkane21 44.47 66.66 69.95 74.68 71.08 84.94 48.77 92.64 99.60 87.04 alkane22 44.47 70.13 64.36 71.69 59.57 69.85 53.21 73.27 84.70 83.38 alkane23 102.80 187.56 171.00 167.57 128.94 151.02 112.32 187.82 208.60 217.15 alkane24 31.75 84.81 55.70 66.58 42.72 76.12 70.17 71.57 72.29 77.46 alkane25 114.97 200.95 178.12 197.30 133.62 155.54 139.88 190.09 206.16 200.36 alkane26 32.76 13.80 33.10 86.24 22.94 37.26 36.08 44.94 70.12 49.42 alkane27 113.22 277.34 189.34 218.62 128.43 185.92 182.80 226.28 244.45 222.06 alkane28 44.62 88.97 77.97 95.06 41.17 59.51 57.43 76.98 73.88 78.36 alkane29 132.08 176.44 168.88 156.51 66.37 166.11 52.62 216.35 208.70 217.66 alkane31 158.48 250.53 216.74 230.52 75.82 212.20 134.47 239.02 278.68 252.36 sum total 819.62 1456.38 1250.76 1397.32 770.67 1219.73 887.76 1464.34 1604.20 1535.17

n-alkanals alkanal20 0.00 114.64 40.64 62.22 54.17 64.33 0.00 72.39 117.95 110.11

Steroids cholesterol 1146.93 489.98 844.64 844.16 801.83 822.54 908.47 1301.83 1336.42 1279.95 sitosterol 676.63 571.71 788.76 753.29 619.84 735.87 527.01 910.76 891.75 970.32 campesterol 186.76 1032.95 235.67 230.79 223.69 178.80 68.60 177.16 198.77 265.90 stigmasterol 2037.69 1284.92 2236.06 2290.97 1968.43 1878.48 2063.95 2531.76 2486.60 2399.75 sum total 4048.01 3379.57 4105.12 4119.21 3613.78 3615.69 3568.02 4921.52 4913.55 4915.92

Terpenoids a-Amyrin 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Friedelin 156.76 311.01 155.71 118.36 127.68 123.72 208.20 151.77 147.02 240.81 Hopene 232.27 149.36 305.73 276.58 131.57 299.37 98.64 298.73 294.09 353.99 sum total 5524.88 3959.58 5890.67 4156.53 4781.00 5106.65 4827.11 7067.49 7032.88 7371.13

Carbohydrates #galactose 82.78 113.64 52.97 77.31 58.40 48.23 44.26 64.89 45.38 59.76 trehalose 72.93 62.34 74.62 65.71 28.87 39.94 36.74 52.57 166.59 45.44 #1 404.46 413.75 59.41 44.76 84.49 140.67 241.77 36.28 62.33 892.89 #2 0.00 0.00 378.56 212.29 0.00 0.00 0.00 504.95 1317.60 0.00 sum total 560.17 589.73 565.57 400.07 171.77 228.85 322.77 658.69 1591.90 998.08 217

Appendix 14. Detailed methods of organic solvent extractions and Gas chromatography-Mass spectrometry (GC-MS) of West and East Lake core samples.

Solvent extractions followed the methods of Otto and Simpson (2005) and Paulter et al.

(2010). Sediment samples were sequentially extracted by sonification for 15 minutes with 40 ml methanol, methanol:dichloromethane (1:1 v/v), and finally dichloromethane. The extracts were filtered through glass fibre filters (Whatman GF-A) and concentrated by rotary evaporation before being transferred to 2 ml glass vials and blown dry under a stream of N2. Extract yields were determined by weighing the dried residue. Samples were stored at -20 °C. Prior to GC-MS, solvents were redissolved in 500 µl of methanol:dichloromethane (1:1 v/v) and 50 µl aliquots of solvent were transferred to a second 2 ml glass vial. These subsamples were then blown dry under a stream of N2 and converted to trimethlysilyl (TMS) derivatives by reaction with 90 µl

N,O-bis-(trimethylsilyl)trifluoracetamide (BSTFA) and 10 µl anhydrous pyridine at 70 °C for 3 hours. After cooling 500 µl hexane was added to dilute the samples.

GC-MS analysis was performed with an Agilent model 6890N chromatograph coupled to an Agilent model 5973N quadrupole mass selective detector. Separation was achieved on a HP-

5MS fused silica capillary column with He as the carrier gas. Operating conditions consisted of

65 °C for 2 minutes and 300 °C for 20 minutes before 1 µl samples were injected in splitless mode with an injector port temperature of 280 °C using an Agilent 7683 autosampler. The spectrometer was operated in the electron ionization mode (EI) at 70 eV and scanned from 50-

650 m/z. Data was processed with Agilent Chemstation G1701DA software. Compounds were identified through comparison of mass spectra to Wiley MS library data, comparison with standards, and with published data. The external quantification standards were used as follows: tetracosane for n-alkanes, mBHA for n-alkanoic acids, n-alkanols and carbohydrates, and mERG for steroid fractions. 218

Appendix 15. Visual comparison of climate station data for Mould Bay, Prince Patrick Island, Rea Point, Melville Island, and Resolute Bay, Cornwallis Island, spanning the instrumental records. Data represent summer (Tmax>0 °C; June, July, August) , winter (Tmax<0 °C; September, October, November, December, January, February, March, April, May) and annual trends in temperature and precipitation.

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