Impact of Historical Logging and Hydroelectric Development on an Upland River System, Nova Scotia, Canada: a Paleolimnological Perspective

IMPACT OF HISTORICAL LOGGING AND HYDROELECTRIC DEVELOPMENT ON AN UPLAND RIVER SYSTEM, NOVA SCOTIA, CANADA: A PALEOLIMNOLOGICAL PERSPECTIVE

JOHN ADAM DOUGLAS GODFREY

Thesis Submitted in partial fulfillment of the requirements for The Degree of Master of Science (Biology)

Acadia University Spring Convocation 2019

I, J. Adam D. Godfrey, grant permission to the University Librarian at Acadia University to archive, preserve, reproduce, loan, or distribute copies of my thesis in microform, paper, or electronic formats on a non-profit basis. I undertake to submit my thesis, through my University, to Library and Archives Canada and to allow them to archive, preserve, reproduce, convert into any format, and to make available in print or online to the public for non-profit purposes. I, however, retain the copyright in my thesis.

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TABLE OF CONTENTS List of tables……………………………………………………………….. vii List of figures……………………………………………………………… viii List of acronyms and abbreviations……………………………………… ix List of units………………………………………………………………… x List of chemical symbols………………………………………………….. xi Acknowledgments…………………………………………………………. xii Abstract……………………………………………………………………. xiv Chapter 1: Introduction 1 1.1 Problem statement…………………………………………………………. 1 1.2 Background…………………………………………………………………. 2 1.2.1 Impact of logging on lakes and rivers…………………………... 4 1.2.2 Historical logging practices in Nova Scotia: An overview…... 6 1.2.3 Impact of damming on fluvial lakes and rivers………………... 8 1.3 Use of paleolimnological proxies………………………………………… 10 1.3.1 Radiocarbon and radiolead dating……………………………… 10 1.3.2 Organic matter content…………………………………….……… 11 1.3.3 Oxidation-reduction reactions…………………………………… 14 1.3.4 Sediment physical properties…………………………………….. 15 1.3.5 Trace elements……………………………………………………... 18 1.4 Site description……………………………………………………………... 19 1.4.1 Disturbance history………………………………………….…….. 22 1.4.2 Climate, geology, glacial history, forest composition, and soils………………………………………………………………….. 24 1.5 Knowledge gaps…………………………………………………….………. 26 1.6 Thesis objectives……………………………………………………………. 26 1.7 Caveat………………………………………………………………………... 27 Chapter 2: Impacts of logging and damming on an upland river system: A paleolimnological perspective 28 2.1 Problem statement………………………………………………………….. 28 2.2 Introduction…………………………………………………………………. 28

2.2.1 Disturbance history………………………………………….…….. 29 2.2.2 Impact of logging on lakes and rivers: Paleolimnology perspectives……………………………………………………….… 31 2.2.3 Knowledge gaps……………………………………………………. 33 2.3 Methods……………………………………………………………………… 33 2.3.1 Bathymetric and sub-bottom profiling…………………..……… 34 2.3.2 Water quality data collection…………………………………….. 35 2.3.3 Sediment core collection and processing………………………. 36 2.3.4 Bulk geochemical analysis……………………………………….. 37 2.3.5 Other sediment analyses………………………………………….. 38 2.3.6 Radiometric dating………………………………………………… 39 2.3.7 Quality control……………………………………………………... 39 2.4 Results……………………………………………………………………….. 42 2.4.1 Modern water characterization………………………………….. 42 2.4.2 Bathymetry and sub-bottom profile……………………………... 43 2.4.3 Stratigraphy………………………………………………………… 43 2.4.4 Age-depth…………………………………………………………… 45 2.4.5 Bulk geochemistry and environmental paleoproxy results…… 46 2.4.6 Data correlations………………………………………………….. 50 2.5 Discussion………………………………………………………………...…. 50 2.5.1 Chronological reconciliation…………………………………….. 50 2.5.2 The effect of historical logging and damming on the modern aquatic environment………………………………………………. 54 2.5.2.1 Particle size and clastic fraction……………………… 54 2.5.2.2 Organic matter and stable isotopes………………….. 55 2.5.2.3 Redox……………………………………………………… 56 2.6 Conclusions………………………………………………………………….. 57

Chapter 3: Legacy of anthropogenic disturbance on an upland fluvial lake: Focus on metal sequestration, toxicity, and bioavailability 59 3.1 Problem statement…………………………………………………………………... 59 3.2 Introduction…………………………………………………………………..……... 59 3.2.1 Aquatic metal contaminants in Nova Scotia……………………………. 61 3.2.1.1 Arsenic…………….……………………………………………… 61 3.2.1.2 Aluminum………………………………………………………… 63 3.2.1.3 Mercury…………………………………………………………... 63 3.2.1.4 Other metals……………………………………………………... 64 3.2.1.5 Metals as proxies………………………………………………... 66 3.2.2 Impact of logging and damming on metals in the aquatic environment…………………………………………………………………. 67 3.2.2.1 Logging and metals……………………………………………... 67 3.2.2.2 Damming and metals…………………………………………… 70 3.2.3 Knowledge gap……………………………………………………………… 71 3.3 Methods………………………………………………………………………………. 71 3.4 Results………………………………………………………………………………… 72 3.4.1 Data quality…………………………………………………………………. 72 3.4.2 Proxy data…………………………………………………………………… 73 3.4.3 Metal and particle size data correlations……………………………….. 77 3.4.4 Correlations between metals and bulk geochemistry and environmental paleoproxy data from Chapter 2……………………….. 79 3.5 Discussion……………………………………………………………………………. 80 3.5.1 Redox-sensitive and associated metals…………….………………….… 81 3.5.2 Strontium…………………………………………………………………….. 84 3.5.3 Copper……………………………………………………………………….. 87 3.5.4 Lead………………………………………………………………………….. 87 3.6 Conclusions…………………………………………………………………………... 88 Chapter 4: Thesis conclusions 90 Chapter 5: References 94

LIST OF TABLES Table 2.1 Quality control results for bulk geochemistry and %water analyses on core DS3………………………...………...……………………… 40 Table 2.2 Average concentrations of elements in laboratory standards and percentage reproducibility error………………..……………………. 41 Table 2.3 Quality control for paleoenvironmental analyses δ13C, δ15N, %C, %N, and C/N as provided by SINLab………….……………………. 42 Table 2.4 Mean bulk geochemistry concentrations and paleoproxy values for Deep Stillwater, core DS3, segregated by sediment zone………...…. 49 Table 2.5 Pearson correlation coefficients for strong and moderate correlations of bulk geochemical and environmental paleoproxy data……..…….. 51 Table 3.1 Quality control for bulk geochemical analysis of metals on core DS3 73 Table 3.2 Mean metal concentrations and particle size percentages for Deep Stillwater, core DS3, segregated by sediment zone…….…………… 78 Table 3.3 Pearson correlation coefficients for strong and moderate correlations of sediment metal data……………………………………...………... 79 Table 3.4 Pearson correlation coefficients for strong and moderate correlations of metals with paleoenvironmental reconstruction data from Chapter 2……………………………………………………………………… 82

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LIST OF FIGURES Figure 1.1 [Top] Map of the Canadian Maritimes denoting the study site of Deep Stillwater, NS. [Bottom] Topographic map of Deep Stillwater and area...... 21 Figure 1.2 The Forks River before-and-after the installation of five hydroelectric and spillover dams……………………..……………... 23 Figure 2.1 Lake water physiochemical data for Deep Stillwater ...…………….. 30 Figure 2.2 Bathymetry and sub-bottom profiles for Deep Stillwater….………... 35 Figure 2.3 Photo of stratigraphic profile of frozen and split core DS2 alongside graphic representation of sedimentary data derived from extruded and geochemically analyzed core DS3……………………………… 44 Figure 2.4 Age-depth results for Deep Stillwater core DS3..…………………… 46 Figure 2.5 Bulk geochemistry and environmental paleoproxy trendlines for Deep Stillwater core DS3……………………………..……………... 48 Figure 2.6 Chronological reconstruction of environmental change at Deep Stillwater based on the sediment record……………………………... 53 Figure 3.1 Depth and stratigraphic profile, radioisotope dates, particle size distribution and metal element trendlines for Deep Stillwater core DS3…………………………………………………………………... 74 Figure 3.2 Examination of the Sr trendline for Deep Stillwater compared to historic disturbance events…………………………………………... 86

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LIST OF ACRONYMS AND ABBREVIATIONS AQM aquatic moss standard NS Nova Scotia ca. circa OM organic matter CLE conserved lithogenic ORP oxidation-reduction potential element PSD particle size distribution CMS corn meal standard SAR sediment accumulation rate CRS constant rate of supply SINLab Stable Isotopes in Nature DO dissolved oxygen laboratory DS1/2/3 Deep Stillwater (core) SPL Spirulina standard 1/2/3 spp. species (pl.)

EPS ephedra plant standard SRB sulphate-reducing bacteria GPS Global Positioning System WBAR West Branch of the Avon KNP Kejimkujik National Park River LOD limit of detection XRF X-ray fluorescence LOI loss on ignition spectrometry MDN marine-derived nutrients Z1/1a/2/2a/3 (sediment) zone 1/1a/2/2a/3 n/a not applicable

LIST OF UNITS α alpha km kilometers AD anno Domini L liters β beta m meters BCE before the common era m3 meters cubed BP years before the present (1950) Ma million years ago Bq becquerels masl meters above sea level oC degrees Celsius um micrometers cal BP calibrated years before the mg milligrams present mm millimeters cm centimeters n the size of a statistical sample g grams ppm parts per million h hour(s) r Pearson correlation coefficient ha hectares yr year(s) kHz kilohertz

LIST OF CHEMICAL SYMBOLS Ag silver Mo molybdenum Al aluminum N nitrogen As arsenic 14N 7-neutron stable isotope of nitrogen AsIII trivalent arsenic 15N 8-neutron stable isotope of nitrogen AsV pentavalent arsenic δ15N notation for nitrogen isotope Ba barium fractionation Bi bismuth Nb niobium C carbon Nd neodymium 12C 6-neutron stable isotope of carbon Ni nickel 13C 7-neutron stable isotope of carbon P phosphorus 14C 8-neutron radioisotope of carbon; Pb lead radiocarbon 210Pb 128-neutron radioisotope of lead; δ13C notation for carbon isotope radiolead fractionation Pr praseodymium Ca calcium Rb rubidium Cd cadmium S sulphur Ce cesium Sb antimony Cl chlorine Se selenium Co cobalt Sn tin

CO2 carbon dioxide Sr strontium Cr chromium Th thorium Cu copper Ti titanium Fe iron U uranium Fe2+ divalent iron V vanadium Fe3+ trivalent iron W tungsten Hg mercury Y yttrium K potassium Zn zinc La lanthanum Zr zirconium MeHg methylmercury C/N, Cr/V, proportional ratios of select Mn manganese Cu/Ni, Fe/Mn, elements Sr/Ca

ACKNOWLEDGMENTS

Thank you to Arthur and Sandra Irving, and the Arthur L. Irving Family Foundation, not only for providing financial assistance for this research, but also for your constant interest and encouragement throughout. I feel immensely privileged to have garnered your support and to have been counted amongst the inaugural Arthur L. Irving Family

Foundation scholars.

Thank you to my supervisor Mark Mallory. Although we crossed paths infrequently, you have remained fully supportive of my efforts and quick to provide guidance when asked. You’ve always had my back; I can’t begin to express how that foundation has gotten me through some tough moments; thank you.

Thank you to David MacInnes for drawing attention to the need for this research and your trove of historical and first-hand knowledge that helped frame the narrative of this work.

Thank you to Dewey Dunnington, without whom I would probably still be floundering in data collection. Your assistance in the field, in the lab, and beyond has been immensely valuable.

Thank you to Chris White and the Nova Scotia Department of Natural Resources for providing the XRF upon which so much of this research hinged; truly appreciated!

A wholly inadequate thank you to my supervisor Ian Spooner. I could truly write an entire page in gratitude, Ian. You have been such a patient, guiding, rudder for me, for

(too many) years now. Without dissolving into exaltation, I will just say thank you for educating me – academically, socially, and mentally. I am now changed for the better in so many ways.

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Lastly, thank you to my family for sticking with me as I dove back into post- secondary waters. To Kelly, Eliza, and AJ, especially thank you for embarking on this journey with me and to Gus, thanks for showing up mid-thesis and disrupting the status quo. Love you all.

- Adam

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ABSTRACT

In Atlantic Canada, historical logging practices and watershed development for hydroelectric power generation has significantly altered flow dynamics, stream and sediment biogeochemistry, and seasonal discharge in forested upland rivers. In this study, the paleolimnological method was used to determine the immediate and legacy impacts of these practices on sedimentation rate, particle size, organic fraction, and bulk geochemistry, on a fluvial lake along the West Branch of the Avon River, Nova Scotia.

Sediment cores were obtained in May of 2015 and either extruded and sliced on- site or frozen and split to reveal comparative stratigraphy. Extruded sediment was analyzed by XRF, particle size analysis, and loss on ignition. Chronological constraints

(210Pb and 14C) and stable isotope (13C and 15N) data were obtained by outside laboratories. Quantitative data were analyzed in conjunction with historical records and local ecological accounts to create a chronology of disturbance in the area.

This research determined that: [1] fluvial lake sediments can provide an effective archive of watershed disturbance when coupled with historical records; [2] historical logging produced significant short-term unconformities in the sediment record, increased allochthonous contaminant load, and altered redox chemistry; [3] damming decreased the clastic fraction and particle size of sediment, reduced system energy and dissolved oxygen, altered redox conditions, and initiated biological regime shifts; [4] concentrations of all metals, except lead, decreased post-damming, despite increased adsorbsion and complexation characteristics of the system, indicating a significant loss of geogenic input due to watershed reduction; and [5] the sedimentary strontium record seems to reflect logging and damming disruptions in anadromous fish visitation.

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Chapter 1: Introduction

1.1 Problem statement

This thesis was undertaken to explore two research themes. It is an attempt to use a sediment archive in an upland fluvial lake to understand how historical logging and damming developments have affected sedimentation and influenced metal distribution in fluvial environments. This research was also designed to provide a detailed and time stratigraphic perspective on the impact of anthropogenic activity on watersheds in forested upland environments. It will provide insight into the effects and impacts of environmental changes on river dynamics, sedimentation and erosion, and the mobility and bioavailability of chemicals in the watershed, as well as how adverse impacts can be mitigated in the future. This research took place on the West Branch of the Avon River

(WBAR) in southwestern Nova Scotia (NS), a watershed subjected to extensive historical logging and hydroelectric development. A sedimentary archive of environmental change was obtained from Deep Stillwater (informal name), a small (1.3 ha) and relatively deep

(12 m) fluvial lake along the WBAR.

Most studies of environmental change in upland watersheds in Maritime Canada have focused on the impacts of mineral resource development and the bioavailability and mobility of contaminants such as arsenic (As) and lead (Pb) (Corriveau et al., 2008;

Natural Resources Canada, 2012; Wang and Mulligan, 2006; Wong et al., 1999). Recent research in Kejimkujik National Park (KNP) in southwestern NS has focused on the source of methylmercury (MeHg), a toxic contaminant that has been linked to reproductive distress in loons (Burgess et al., 1998). Though some pathways and sources have been recognized, the influence of historical logging on contaminants is not well

1 known and is complicated by the size of the watersheds involved and the complexity of the environment. Like KNP, the WBAR, traditionally known as the Forks River, was chosen for this study as it too has a long history of logging and damming that has been well documented. No significant mining activity has taken place within the WBAR watershed, however, enabling a study more focused on the impact of historical logging and hydroelectric development. It is also typical of a moderate relief, glaciated upland watershed that has developed on largely crystalline bedrock where a relatively uncomplicated and consistent geological setting reduces the complexity of integrating geogenic influences into the interpretation of the chemical and sedimentological data.

1.2 Background

In Maritime Canada and the northeastern United States, many forested lake and river systems have been negatively impacted by historical forestry practices (Higgins, 2011;

Keenan and Kimmins, 1993; Wynn, 2015). Logging can adversely affect water quality and chemistry, and thus the ecological state of lakes and rivers, through nutrient loading, sudden influx and decomposition of dissolved organic matter, addition of metals and other toxins, and increased erosion, sedimentation, and destruction of benthic habitat

(Binkley and Brown, 1993; Bragée et al., 2013). Watercourse alteration such as channel widening, temporary dams, and bed scouring or compaction, often accompanied logging and has a demonstrated significant deleterious effect on water quality (Sedell and

Luchessa, 1981; Sedell et al., 1991).

In addition to logging, emplacement of dams for hydroelectricity generation also significantly degrades fluvial biotic and abiotic processes (Freeman et al., 2003; Kairo et

2 al., 2011; Wildi, 2010). Through reservoir creation, headwater removal or reduction, channel redirection, or flow regime shifts, damming alters watercourses both upstream and downstream of the construction site (Hall et al., 2012; Santucci Jr. et al., 2005).

Water quality, sediment transport, geochemical cycling, and species’ movement, are all affected by the reduction or loss of river connectivity (Hall et al., 2012; Limburg and

Waldman, 2009; Santucci Jr. et al., 2005).

Logging and damming occur world-wide but are especially common in eastern

North America, where topographic relief, reduced arable land, diverse forest structure and nearby markets combine to elevate the economic potential of forestry and hydroelectric generation both at present and historically (Thompson et al., 2013). Nova

Scotia is representative of much of Appalachia, and its forested and glaciated physiography facilitates the transportability of this study to much of eastern North

America, northern Europe, and Scandinavia. Understanding the environmental legacy of historical logging and damming practices is essential to decoupling relic from modern impacts and informing current and future watercourse management practices. The paleolimnological method of using biotic and abiotic proxies to understand environmental change through time is well suited to assessing watershed scale impact, however, applying the method in a fluvial setting can be challenging, as sediment archives are rare, especially in upland watersheds where rivers are often shallow and dominantly erosional. Nonetheless, the gradient of youthful, upland, low order rivers is often controlled by bedrock sills and the depth of the river may be influenced by glacial scour and its relationship with varying bedrock lithology, especially in a setting where non-erosional, cold-based ice or thin ice-marginal conditions existed. In this setting,

3 relatively deep fluvial lakes (also referred to as stillwaters) can develop and may preserve a sedimentological archive of environmental change upstream of the site.

1.2.1 Impact of logging on lakes and rivers

In traditional logging, the large quantity of log-drive timber typically damaged stream- banks and resulted in the mobilisation of large amounts of organic debris, some of which settled to the bottom of rivers and fluvial lakes (Williamson, 1970). The subsequent degradation of the logging debris can result in the development of anoxic conditions in environments where it accumulates and, in extreme cases, can cause oxygen deficiencies to long reaches of a river system (Williamson, 1970). The degradation of large amounts of organic material requires significant dissolved oxygen (DO), which is normally available in most river systems (Campbell and Doeg, 1989). A sudden or sustained reduction in DO can be lethal to resident organisms or create an impassable barrier to fish passage. Nutrients, metals, and airborne toxins (e.g. polycyclic aromatic hydrocarbons) sequestered in logging debris can be released into the water column upon decomposition of organic matter (OM) (Binkley and Brown, 1993; Bragée et al., 2013; Cheng et al.,

2007; Unterbrunner et al., 2007). These chemicals can then become sequestered in either accumulating sediment or the porewater that surrounds it. As well, consumption of the

OM can result in bioaccumulation of these substances. Nutrient loading associated with the decomposition of the debris can lead to a change in the trophic status of the water body and increase the bioavailability of these chemicals. Additionally, increased erosion often accompanies a reduction in forest cover, exacerbating OM load during runoff, while also increasing clastic input to the system.

A few studies have used the paleolimnological method to investigate the impact of logging on the environment. Turkia et al. (1998) determined that select forest harvesting practices could lead to eutrophication in small forest lakes. Forestry-induced soil disturbance, after clear-cutting played a major role in watercourse impact. Watmough et al. (2003) found that forest harvesting can have a significant impact on water chemistry, which was more apparent as exchangeable base cation concentrations declined and acid inputs were no longer buffered. They outlined the importance of the watershed- scale study of soil and bedrock chemistry, and the resultant chemistry of groundwater, on the chemical impact of logging. Laird and Cumming (2001) and Räsänen et al. (2007) investigated the impact of forest harvesting on lakes in a paleolimnological study using diatoms and macrofossils, respectively, as the primary proxies for impact. The changes were subtle in both impacted and reference lakes and the researchers inferred that abiotic proxies may be more sensitive to tracking the effects of logging.

However, Scully et al. (2000) determined that logging can have significant effects on the physical structure and autotrophic community in small temperate lakes. They used fossil carotenoids and chlorophylls to produce a 200-year record of environmental change. Biological responses to forest harvest included elimination of deep-water populations of anaerobic photosynthetic bacteria and reduced abundance of metalimnetic chrysophytes. Photosynthetic bacteria remained absent for over 100 years, while sediment laminae and chrysophytes were noted to have returned only when logging activity began to decline around 1970 (Scully et al., 2000). In contrast, populations of epilimnetic phytoplankton (cyanobacteria, chlorophytes, and cryptophytes) were unaffected by logging. Analysis of sediment profiles did not reveal evidence of

5 eutrophication or of increased flux of OM following watershed disturbance. Scully et al.

(2000) noted that such century-long disturbance may be common in small, stratified boreal lakes.

There are few studies of the impact of logging on river water chemistry and whether logging practices, especially those in the late 19th century in eastern North

America, resulted in significant flux of OM (primarily bark) and consequently metals into fluvial sediment (Chrzan et al., 2010; Dickinson and Lepp, 1997; Lepp, 1996; Parzych et al., 2017; Pulford and Watson, 2003). Studies of the impact of forest succession after logging are not particularly common but do indicate that sustained impacts are greater if there is not a wide protective zone around the lakes, as was the case in historical logging in NS (Räsänen et al., 2007). Dunnington et al. (2017) used a paleolimnological approach in the Cumberland Marsh Region in Eastern Canada to construct a record of metal deposition in lakebed sediments and found that aquatic sediment concentrations of some metals and isotopes fluctuated substantially in response to changes in vegetation cover influenced by precipitation and fire activity. Koinig et al. (2003) used a paleolimnological record of sediment geochemistry and changes in sediment mineralogy, grain-size, pollen, and macrofossils from a lake in Switzerland to infer that changes in vegetation associated with human activities are the controlling factor for variations in the geochemical composition of the lakebed sediment.

1.2.2 Historical logging practices in Nova Scotia: An overview

In all studies that examine the environmental impact of logging, an independent record of the nature and timing of logging activity within the watershed is required (Räsänen et al.,

2007). In NS, historical logging was essentially a winter occupation, starting immediately after the first snowfall (Wynn, 2015). Low-wage labour was abundant during winter and it was easier to harvest trees when the sap was not running, as well as move them across the snow instead of bare ground. Cutting typically began at the water’s edge, as this timber was the cheapest and easiest to move by river to the mill. Cutting density declined inland, as the cost of moving the cut timber through the forest to the watercourse being used for the log drive increased. After the timber was cut, the logs were made square, as square logs were easier to transport; the slash (unused bark and wood) was left in the forest, or sometimes, beside or in the water body that would serve as the transport corridor (Wynn, 2015). The bark of logs was stripped off manually with a debarking spud, like an adze (Food and Agriculture Organization of the United Nations, 1986; Food and Agriculture Organization of the United Nations Forest Products Division, 1990). A snow road was used to haul logs to riverbanks by oxen or horses. With the spring thaw, the timber drive began. The logs were floated down streams during the spring melt.

Where necessary, a temporary log drive dam was constructed to create sufficient water pressure to move the logs downstream. When enough water was contained, the dam was breached, and the logs were moved downstream in the resulting flood (Sedell and Duvall,

1985; Wohl, 2001; Young et al., 1994). It was not uncommon to have three or more drive dams on a river to facilitate moving the logs to the mill. When more open water was reached, or where falls and rapids could be bypassed by timber slides, logs and timber were assembled into rafts to continue downstream to mills or to river-mouth booms, from which they were shipped abroad.

From the 1700’s to 1950’s, white pine (Pinus glauca) was the major harvest species, although smaller quantities of spruce (Picea spp.), birch (Betula spp.), oak

(Quercus spp.), elm (Ulmus spp.), ash (Oleaceae spp.), basswood (Tilia spp.), butternut

(Juglans spp.), and cedar (Thuja spp.) were also cut. White pine has since diminished in harvest value, with spruce and hemlock (Conium spp.) now the primary harvest species of NS forestry (Defebaugh, 1906; Wynn, 2015). By 1850, lumbering had moved into more remote areas and the clearing of boulder-strewn streams (to transport the timber via the water) became necessary.

1.2.3 Impact of damming on fluvial lakes and rivers

Many environmental effects of dams are immediate and obvious, such as restricting fish movement, sediment diversion or sequestration, and changes to flow regime. However, numerous other effects are more gradual or subtle, such as changes in nutrient cycling, flood dynamics, and benthic assemblages (Nilsson and Berggren, 2000; Ward and

Stanford, 1995).

Watercourse alteration from damming redirects sediment transport, causing siltation at the dam site, and loss of sediment resources to downstream locations (Nilsson and Berggren, 2000). Dogra (1986) found that a dam across the Maujira River in India lost 60% of its storage capacity over 43 years due to siltation behind the dam.

Interruptions in flow also alter erosion and sediment patterns below the dam.

Biodiversity patterns along regulated rivers are characterized by major declines at riverine sites immediately downstream from dams, followed by relatively rapid increases concomitant with the recovery of environmental conditions (Ward, 1997). Stream

8 regulation alters virtually all environmental variables downstream. The sub-lethal effects of modified flow and temperature regimes are paramount in structuring biotic communities below many dams throughout the world (Dudgeon, 1992; Petts, 1984;

Walker, 1985; Ward, 1982).

The impoundment of water and subsequent changes to flow velocity and natural flow regimes have a demonstrated potential to negatively affect the diversity and abundance of stream invertebrates that provide important trophic resources in river networks (Käiro et al., 2011). Altered flow regimes disrupt the transport of coarse and fine particulate OM on which many invertebrates feed (Marchant and Hehir, 2002; Takao et al., 2008).

Northington and Webster (2017) experimentally manipulated stream connectivity to examine how altered water availability affected leaf litter decomposition. They found that flow manipulation led to changes in OM accumulation, as well as microbial and macroinvertebrate colonization. Even minor disruptions at key times of the year had community- and ecosystem-level influences on decomposition. Ryder et al. (2015) artificially reduced flow velocity on the Chamkharchu River in Bhutan and found no effect on macroinvertebrate diversity and richness downstream, but instead a shift in community composition, most notably a reduction in abundance of flow-dependent invertebrate taxa.

Riparian communities are affected upstream as water levels rise, but also downstream as flow regime is altered and often reduced (Nilsson and Berggren, 2000).

River regulation changes that eliminate or reduce the negative effects of floods alter the species composition of riparian forests to that of forest types more characteristic of

9 unflooded upland areas (Décamps et al., 1988). Many upland species are normally excluded from growing in and near free-flowing river channels because of intolerance to sedimentation, erosion, submersion, physical damage, and low soil fertility (Johnson,

1994). Riparian pioneer species, on the other hand, are adapted to or need such processes; they have easily dispersed seeds, rapid germination, and rapid root and height growth

(Johnson, 1994). Lack of regeneration leads the succession toward older, less productive states, which also affects wildlife negatively (Nilsson and Dynesius, 1994).

Even if floods remain, changes in their timing may be sufficient to cause environmental change. Atwell (1970) found that delayed flooding would negatively affect reproduction and feeding patterns of many animal species. Animals breeding adjacent to water suffer from destruction of eggs and larvae. Amphibians and birds are particularly affected (Dudgeon, 2000).

1.3 Use of paleolimnological proxies

A broad suite of biogeochemical proxies can be used to characterize both sedimentary processes and sediment deposition conditions in lake sediment. Multiproxy analyses allow for holistic environmental reconstruction and identification of environmental disturbances and their effects (Michelutti and Smol, 2013).

1.3.1 Radiocarbon and radiolead dating

Carbon (C) dating uses the predictable radioactive decay of the unstable C isotope carbon-14 (14C or radiocarbon), to establish the age at which an organism died, at which point the organism ceases to absorb 14C from the environment and the 14C retained in the

10 organism’s tissue begins to decay to nitrogen-14 (14N). Results are expressed in 14C years, which can be converted to calendar years before present using an appropriate calibration curve (Cohen, 2003; Reimer et al., 2013). Calendar years before present (cal

BP) are presented as years before 1950. Radiocarbon decay can accurately predict tissue age back 26,000 cal BP, or less accurately to 43,500 cal BP.

Radiolead (210Pb) enters lakes and rivers via atmospheric deposition then adsorbs to particulate matter and is deposited as sediment. The subsequent decay of 210Pb can be used to date recent sediment (< 150 yr). Sediment accumulation rate (SAR) can also be modelled from 210Pb measurements, assuming that 210Pb delivery to sediment has been constant through time (Constant Rate of Supply (CRS) model) or assuming surficial 210Pb concentrations have been constant through time (Constant Initial Concentration model).

1.3.2 Organic matter content

Lake sediments can be classified as: [1] clastic, comprised mostly of eroded rock fragments, [2] chemical, comprised mostly of chemical precipitates, or [3] organic, comprised of the remains of dead plants and animals (Mackereth, 1966; Smol, 2008;

Menzel et al., 2013; Mitsch and Gosselink, 2015). Organic matter is an important source of nutrients and energy, and a compartment for cation exchange, with the potential to sequester or source contaminants and trace metals (Lin et al., 2011; Meyers and Teranes,

2001; Ravichandran, 2004). Organic matter content in lakes is driven strongly by nutrient loading, primary production, decomposition rates, and surface water flows (Shaffer and

Ernst, 1999; Smol, 2008).

Carbon and nitrogen (N) are major constituents of OM that can be analyzed to assess composition (e.g. algal or macrophytic) and provenance (e.g. terrestrial or aquatic), and thus infer environmental conditions both in the lake itself and also the source watershed (Mackie et al., 2005; Mackie et al., 2007; Shaffer and Ernst, 1999; Torres et al., 2012).

Algae and aquatic plants are mainly composed of N-rich lipids and proteins, whereas terrestrial and vascular plants are mainly composed of C-rich lignin and cellulose (Meyers and Teranes, 2001; Talbot, 2001). Thus, the proportion of total C (%C) in sediments over the proportion of total N (%N), called the carbon-nitrogen ratio (C/N), is used to infer the proportion of autochthonous (aquatic-derived) primary productivity versus allochthonous (land-derived) (Meyers and Teranes, 2001; Schaller et al., 2013).

Ratios between 4 and 10 indicate autochthonous productivity, whereas C/N ˃20 indicate allochthonous productivity, and ratios between 10 and 20 indicate a combination of autochthonous and allochthonous productivity (Meyers and Lallier-Verges, 1999; Meyers and Teranes, 2001; Talbot, 2001). These C/N values can be used to infer shifts in aquatic versus terrestrial OM contributions to sediment, due to changes in lake morphology, watershed topography, climate and land use ( Brenner et al., 2006; Meyers and Lallier-

Verges, 1999).

Stable isotopes (non-radioactive atoms with differing amounts of neutrons than their parent atom) of C can further refine analyses of OM provenance in the aquatic system (Finlay and Kendall, 2007; Torres et al., 2012). Photosynthesizing organisms discriminate to various degrees against heavier carbon-13 (13C) isotopes in lake water,

12 and preferentially assimilate carbon-12 (12C) isotopes in low- to moderately-productive environments (Cohen, 2003; Ortiz et al., 2004; Wolfe et al., 2001).

Isotopes are measured relative to standard materials with known isotope ratios, and expressed in parts per thousand deviation from the standard (Finlay and Kendall,

2007; Meyers and Teranes, 2001). Carbon isotope fractionation (i.e. the ratio of the heavier 13C to the lighter 12C isotope) is expressed with the following delta notation

(Brenner et al., 1999; Dunnington, 2015; Meyers and Teranes, 2001):

13 13 12 13 12 δ C = Csample/ Csample)/( Cstandard/ Cstandard)

Carbon isotopic composition is reflected in sedimentary OM and can be used to differentiate past photosynthesizing organisms, particularly those with different photosynthetic pathways. Differences in δ13C values are most prominent between C3 and

C4 pathway terrestrial plants, as C4 plants (typically found in warm and dry conditions) are more efficient at processing carbon dioxide (CO2) (Finlay and Kendall, 2007; Meyers and Lallier-Verges, 1998).

Additionally, under highly productive conditions in an aquatic environment, 12C may deplete from the imminent water column and force algae to intake inorganic 13C to compensate. Plants may rely on a heavier C source, such as bicarbonate, and sedimentation of such OM is reflected in the sediment record as more positive δ13C values (Brenner et al., 1999; Meyers and Lallier-Verges, 1998; Meyers and Teranes,

2001; Wolfe et al., 2001). Thus, higher values of δ13C can indicate predominantly autochthonous organic input and/or higher aquatic productivity, whereas more negative values of δ13C can indicate predominantly allochthonous input and lower productivity

(Brenner et al., 1999; Wolfe et al., 2001).

Like C, stable isotopes of N can also be used to infer productivity and OM provenance (Finlay and Kendall, 2007; Meyers, 2003). Nitrogen isotope fractionation

(δ15N) has the same delta notation as C isotope fractionation, using 15N and 14N instead of

13C and 12C respectively.

Organisms assimilate N for primary production and preferentially uptake lighter

14N from the inorganic N pool when demand for N is low, discriminating against heavier

15N (Finlay and Kendall, 2007; Talbot, 2001). Higher δ15N values in OM may infer a depletion of the 14N isotope, due to elevated productivity or changes in N-cycling

(Dunnington, 2015; Talbot, 2001). Furthermore, N isotopic composition is distinguishable between primary producers that assimilate dissolved inorganic N, such as algae, and those that assimilate atmospheric-derived N2, such as land plants and cyanobacteria (Meyers, 2003).

Additional proxy analyses are required when interpreting C and N data because of the complexities associated with OM interactions, decomposition, cycling, and provenance, that can be influenced by hydrology, temperatures, and microbial activity, and can affect proxy measurements (Brenner et al., 1999; Talbot, 2001).

1.3.3 Oxidation-reduction reactions

Major and trace element cycling, sorption, mobility, bioavailability, and toxicity are all affected by oxidation-reduction (redox) reactions (Grundl et al., 2011), which occur by the exchange of electrons between chemical species. A chemical is said to be oxidized when it donates electrons to an oxidant, which accepts electrons and is thereby reduced.

Likewise, a chemical can be reduced by accepting electrons from a reducing agent, or

14 reductant, that is thereby oxidized. Abiotic processes are more efficient under reducing conditions, including adsorption of metal cations to organic or mineral substrates, organometallic complexation, and the formation of sulphides and oxyhydroxides

(Tribovillard et al., 2006).

All metals can be oxidized in water to form positively charged cations. Transition metals can achieve multiple oxidations states, as in the case of iron (Fe) which can be oxidized to Fe2+ or Fe3+ in water. Characteristics of metals (adsorption, solubility, complexation, etc.) change with oxidation state (Schaller et al., 1997). In lakes, temporal and spatial redox gradients induce internal cycling of metals and can lead to focusing at deeper parts of the basin (Davison, 1993; Schaller et al., 1997).

Examination of element ratios, such as Fe and manganese (Mn), that have differing susceptibility to redox reactions, can infer paleoredox conditions in lakes.

However, redox reactions are complex and need to be considered in accordance with other paleoproxy indicators.

1.3.4 Sediment physical properties

Lake sediments exhibit physical properties that are a product of processes occurring at a range of temporal and spatial scales. Even for a single lake, the network is likely to be temporally dynamic, as the various component systems evolve (Hodder and Gilbert,

2013).

Remote sensing techniques have been successfully used to assess site specifics, such as sediment depth, distribution, and bathymetry, for selecting coring sites that are likely to provide a complete sedimentary record (Gilbert, 2003). This method commonly

15 relies on the generation of acoustic waves that penetrate the sediment, paired with detection of any reflected waves generated at the sediment–water interface and at boundaries within the sediment, such as bedrock or other impenetrable surfaces.

Repeated soundings can generate a longitudinal sub-bottom profile of the basin, allowing for visualization of sediment deposits and inference of depositional processes. Acoustic impedance is a function of the density of the media and therefore related to water and

OM content, porosity, and particle size (Hodder and Gilbert, 2013).

Sediment focusing has been attributed to the action of turbidity currents (Francus et al., 2008; Ludlam et al., 1996), slope instability (Pickrill and Irwin, 1983), the depth of overlying water (Blais and Kalff, 1995), and modification of sediment dispersal patterns by wind (Girardclos et al., 2003). Thus, portions of the lake basin may undergo differing sedimentation patterns and record variable paleoenvironmental signals.

Visual analysis of core stratigraphy is useful in guiding interpretation of subsequent analyses, describing compositional variability, and identifying unconformities

(Hodder and Gilbert, 2013). Schnurrenburger et al. (2003) presented a lake sediment classification scheme based on differentiation of the freshly exposed sediment surface into discrete lithologic units, described by colour, sediment structure, thickness, inclination, bedding planes, presences of macroscopic fossils, and degree of coring disturbance.

Clastic particle size distribution (PSD) influences fundamental sediment physical properties, such as surface area, shear strength, bulk density, porosity, and water content

(Hodder and Gilbert, 2013). It is integral to understanding sedimentary processes, provenance, and paleoenvironmental conditions in the watershed (Last, 2001). Particles

16 are divided into clay- (< 2 μm in diameter), silt- (2 to 63 μm in diameter), sand- (63 to

2000 μm in diameter), and gravel-sized (> 2000 μm in diameter) (Miller, 1987; Smol,

2008). Several approaches can be used to determine PSD, including older hydrometric methods, geochemical techniques, and laser counters (Last, 2001; Miller, 1987).

Lakes are typically dominated by a background of silt and clay particles, punctuated by event layers with markedly different particle distribution. Events interpreted from PSD in sedimentary records include turbidity currents (Gilbert et al.,

2006), mass movements (Vogel et al., 2010), hurricanes (Donnelly and Woodruff, 2007), ice rafting (Vogel et al., 2010), and avalanches (Vasskog et al., 2011). An increased frequency of larger-sized particles would suggest a high-energy environment, such as a river flow (Smol, 2008).

Clay-sized particulates are also of interest due to their negative charge and propensity for immobilizing flocculated OM, pollutants, and metal cations (Dube et al.,

2001). The content of heavy metals in lacustrine sediments has been shown to decrease from clay-sized to sand-sized as surface area decreases (Martincic et al., 1990;

Masslenikova et al. 2012; Salomons and Förstner, 1984). However, this is not always so when other factors, such as OM content or accumulation conditions, have a more pronounced effect on metal adsorption to particles (Masslenikova et al., 2012; Singh et al., 1999; Tessier et al., 1982).

Water occupies the void space between sediment particles and water content typically declines with depth, as deeper sediment has been subject to longer periods of mass-based dewatering from overlying layers (Hodder and Gilbert, 2013). Thus, water content is often used as a proxy for compaction (Håkanson and Jansson, 1983;

Menounos, 1997). The portion of the sedimentary record near the sediment–water interface may be more liquid than solid (Glew et al., 2001), and water content can be very high in this layer. A variety of factors, including particle size, OM content, and dry sediment density, influence the water content of lacustrine sediments.

1.3.5 Trace elements

Trace elements in aquatic sediments are frequently used in paleolimnological studies to infer past and present environmental conditions and events, such as bank and watershed erosion, redox conditions, PSD, and anthropogenic effects (Cohen, 2003; Jeffers and

Willis, 2016; Mackereth, 1966). Concentrations of trace elements in lake water are often much lower than expected based on solubility calculations and water supply, due to adsorption onto clastic or organic particulates and subsequent sedimentation (Davidson,

2005; Drever, 1997). However, lacustrine sediments typically maintain reducing conditions that slow decomposition and favour adsorption of redox sensitive elements such as Fe and Mn (Gambrell et al., 1991; Howler, 1972). Aeration of sediments increases redox potential and alters water acidity (pH), such that mobility of contaminants can increase (Davidson, 2005). Thus, lake bed sediments may act as a sink for trace elements, or as a source when disturbed.

Potassium (K), rubidium (Rb), and titanium (Ti) are known mineral byproducts of erosion and are frequently bound to clay particulates. This can be used to infer elevated allochthonous sedimentation, such as from bank erosion or tidal or riverine influx, and/or reduced autochthonous sedimentation (Cohen, 2003; Jeffers and Willis, 2016; Mackereth,

1966).

Trace metals occur in low concentrations in lake sediment and are of interest as indicators of anthropogenic activity and/or sources of biological toxicity (Cohen, 2003;

Covelli, 1999). Zinc (Zn), copper (Cu), Pb, vanadium (V), chromium (Cr), mercury (Hg), and As have all been used to reconstruct anthropogenic activity. Regional industrial activity has often been investigated using Pb (and sometimes V) in sediment (Camarero et al., 1998; Charles et al., 1990; Koinig et al., 2003; Laperriere et al., 2007; Renberg et al., 1994). The phasing out of leaded gasoline has produced a characteristic Pb-curve in sediment records.

Metal deposition also occurs due to clastic sedimentation from watershed erosion, if the watershed contains the appropriate geology. Many studies (Brunschon et al., 2010;

Guyard et al., 2007; Misiuk, 2014; Shotyk et al., 2005) normalize metal concentrations to geochemically unreactive conserved lithogenic elements (CLE), such as Ti or Rb, to separate erosional and anthropogenic input. These methods assume a lithogenic component to metal deposition, which is not always valid. If a metal concentration shows no correlation with clastic deposition, normalization to a conserved element is unnecessary (Dunnington, 2015).

1.4 Site description

Fluvial lakes are defined as water bodies formed along a river course as a result of excavation by running water or flooding due to sediment accumulation (Bengtsson et al.,

2012); they also commonly form where river tributaries meet. Because of the strong fluvial influence, fluvial lakes often expand during the wet season; however, if the water budget is balanced, the form of fluvial lakes becomes relatively steady. In the low order

19 tributaries and upland watersheds of the southern upland of NS, fluvial lakes are common, are often called stillwaters, are usually < 5 m deep, and often form where there has been preferential glacial scour associated with local faults or a concentration of jointing in crystalline bedrock.

Deep Stillwater is a small (1.3 ha), fluvial, dystrophic lake, located along the

WBAR in NS (Figure 1.1). The WBAR has a maximum elevation of 175 masl at the

Forks River Dam. It is turbid (1.7 m average secchi depth), achieves weak seasonal thermal stratification, and has a maximum flushing rate of approximately 0.22 days. The epilimnion becomes depleted in DO early in the summer and water temperature increases rapidly as air temperatures rise. The site was chosen for this study as it was known as the deepest (~12 m depth at David’s Pool) fluvial lake along the WBAR and therefore it was reasoned that it had the greatest potential to contain a lakebed sedimentary record of environmental change.

Deep Stillwater is dystrophic due to high concentrations of humic substances and organic acids leached from peaty soils (Joint Nature Conservation Committee, 2007).

Relative to other lake types, dystrophic lakes have low pH, low light penetration, and often low essential plant nutrients. Furthermore, due to high DOM input, dystrophic lakes can have low DO concentrations, as oxygen is consumed in DOM decomposition.

Historical accounts describe pH as low as 4.3 in the 1980s at Deep Stillwater (D.

MacInnes, personal communication, April 21, 2015); however, more recent water quality measurements indicate summer pH of between 6 and 7, although spring and fall are typically periods of lower pH and the WBAR may still experience seasonal acidic conditions.

Figure 1.1. [Top] Map of the Canadian Maritimes denoting the study site of Deep Stillwater, NS. [Bottom] Topographic map of Deep Stillwater and area.

1.4.1 Disturbance history

The watershed of the WBAR was extensively logged by clear-cutting from 1900 until the

1950s, as far as Dean Chapter and Methals Lakes (Figure 1.2), including Deep Stillwater; logging in the watershed continues to present (D. MacInnes, personal communication,

April 21, 2015). Much of the timber processing in the early 20th century was done on site

(Wynn, 2015), before the logs were transported downstream to Benjamin’s Mill (Figure

1.2).

The intensive nature of the logging and the use of the WBAR to move the logs to

Benjamin’s Mill likely resulted in extensive river bank and forest floor erosion and some alteration of the waterway (Parker, 2012). Significant terrestrial OM input from forest floor and bankside erosion was also likely at this point, as water levels and discharge fluctuated substantially due to periodic damming as part of the log drive process.

In 1928, completion of a spillover dam between the WBAR and Black River created Black River Lake (Figure 1.2), and effectively removed the WBAR from its headwaters. The installation of the Forks River Dam reduced river discharge and the velocity of the WBAR. Water from Black River Lake occasionally overtops the dam in spring, typically in May, but otherwise the upper WBAR, where Deep Stillwater is located, is fed only by surface runoff and wetland storage at Duncan’s Meadow (Figure

1.1). The original timbered dam constructed in 1928 was replaced in 1944 with the current earth fill structure. Residents who have hunting camps along the WBAR noted a significant decline in brook trout (Salvelinus fontinalis) since the initial construction of the dam (D. MacInnes, personal communication, April 21, 2015).

Figure 1.2. The Forks River (a.k.a. the West Branch of the Avon River) before-and- after the installation of five hydroelectric and spillover dams. Recreated from Bishop (1994).

1.4.2 Climate, geology, glacial history, forest composition, and soils

The climate of the region is characterized by a mean annual temperature of 6.6 oC, with mean summer and winter temperatures of 17.4 and -4.4 oC, respectively. The region receives an annual precipitation of ca. 1441 mm. The site is located within the Acadia

Forest region, characterized by red spruce (Picea rubens), balsam fir (Abies balsamea), yellow birch (Betula alleghaniensis) and sugar maple (Acer saccharum). Black spruce

(Picea mariana), white and grey birch (Betula papyrifera and Betula populifolia, respectively), red oak (Quercus rubra), white elm (Ulmus americana), black ash

(Fraxinus nigra), beech (Fagus grandifolia), red maple (Acer rubrum), trembling aspen

(Populus tremuloides), and balsam poplar (Populus balsamifera) are also widely distributed. The site contains mixed forests, with hardwood on hilltops and slopes and softwood in wet areas. Barrens and bogs are common in the watershed, with some mixed and hardwood stands to the northwest (Agriculture and Agri-Food Canada and

Environment Canada, 1999).

The geology of the WBAR and Deep Stillwater is relatively uncomplicated. The site and much of the surrounding area is underlain by biotite monzogranite within the

South Mountain batholith (ca. 381-370 Ma), a peraluminous granitoid suite that underlies approximately half of southern NS (MacDonald, 2001; MacDonald et al., 1992;

McKenzie and Clarke, 1975; Reynolds et al., 1987). The batholith intruded the Lower

Paleozoic metasedimentary rocks of the Goldenville, Halifax, and Rockville Notch

Groups (MacDonald, 2001; White, 2010a, 2010b; White 2012a). This resistant rock provides generally waterlogged ground with an irregular pattern of drainage.

An outlier of the Horton Group (Horton Bluff Formation) is located downstream of the study site and consists of carboniferous sandstone, siltstone, and shale with minor coal measures; calcite cement is common in the coarser units (Martel and Gibling, 1996).

The calcite cement and coal measures locally influence groundwater and surface water chemistry, but as these sediments are located approximately 2 km downstream of the

Deep Stillwater site, they do not directly influence the chemistry of either surface water or ground water at the study site.

The glacial history of southwestern NS is complex. The study site was ice- covered from the Early to Late Wisconsinan time, ca. 75,000 – 14,600 before present

(BP) (Stea and Grant, 1982). By 16,700 BP, the ice cover began to thin and ice margins retreated northwards; by 14,000 BP, the study site was likely ice free, although a local ice cap may have persisted southwest of the study site until about 11,000 BP (Stea and Mott,

1998). The site is located near to a late glacial (Scotian) ice divide, and as such till cover tends to be thin, with bedrock located within 1 m of the surface. Bedrock exposure is moderate to poor but, where present, is glacially sculpted, and roche moutonnée and associated lee side plucking features are common. The provenance of the till is local, consistent throughout the WBAR watershed, and almost entirely composed of the underlying granitic bedrock.

Soil development at the site is poor and belongs to the Gibraltar catena (Cann et al., 1965). It is a very stony, pale brown, sandy loam derived principally from granite- sourced till. The hilly terrain has good surface drainage, with numerous poorly-drained depressions. Pockets of swampy land surround Deep Stillwater and are continually water saturated.

1.5 Knowledge gaps

Very little is known about the impact of damming and logging on sedimentation rates, sediment composition, and metal fate in upland drainage systems. Studies from

Kejimkujik Lake in KNP, focusing on bioaccumulation and biomagnification of Hg in a variety of species, note that watershed impact associated with logging, and watercourse alteration and changes in sedimentation associated with damming, likely influence metal accumulation in lake and river sediment; however, the processes are unclear. Baseline data on changes in sediment composition and metal sequestration associated with natural fluvial processes and environmental change is also not well established, especially for higher order, upland watersheds.

1.6 Thesis objectives

The main objectives of this study were:

1) To use the paleolimnological method to assess the watershed scale environmental

impact of historical logging and damming.

2) To test the effectiveness of using lakebed sedimentary archives in forested upland

fluvial environments.

3) To determine how historical logging and damming activity impact sediment

chemistry, particularly metals in the environment and the potential for metal

mobility and bioavailability.

1.7 Caveat

There is some redundancy in content between chapters, particularly in background material and methodology, as chapters 2 and 3 were written such that they could be modified into papers with minimal alteration.

Chapter 2: Impacts of logging and damming on an upland river system: A paleolimnological perspective

2.1 Problem statement

Upland river systems through time have been significantly degraded by anthropogenic activity (Binkley and Brown, 1993; Bragée et al., 2013; Laird and Cumming, 2001;

Turkia et al., 1998). Quantifications of these impacts are often subjective and rely upon historical accounts of processes such as erosion, stream bank denudation, stream course alteration, and other physical and biological changes resulting from disturbance. The types of activity often referenced with respect to significant deleterious impacts to rural river systems are damming and logging. The WBAR is an upland river that has been extensively logged and dammed over the past 100 years. In this chapter, I will use a variety of techniques to better understand how damming and logging on the WBAR have impacted fluvial processes. In particular, sediment cores obtained from a fluvial lake on the WBAR will be used to determine how river discharge and sediment dynamics have been influenced by the 100-year record of river alteration and watershed exploitation.

This research will provide perspective on the impacts of logging and damming on ecosystems in upland river systems, particularly the potential impacts on anadromous and freshwater fish.

2.2 Introduction

Deep Stillwater is classified as a fluvial lake. For most of the year, it is slightly acidic and turbid (1.7 m secchi depth). Weak thermal stratification is apparent, as spring and fall

28 temperatures average 9-12 oC throughout the water column, whereas summer temperatures range from 20 oC at the surface to 8 oC at the bottom (Figure 2.1). During spring, DO increases in the normally anoxic system; however, increased oxygenation is less evident in the fall months.

2.2.1 Disturbance history

The entirety of the WBAR, as far as Dean Chapter Lake and Methals Lake (Figure 1.2), and including Deep Stillwater, was extensively clear-cut from 1900 to 1910 (D.

MacInnes, personal communication, April 21, 2015). Much of the timber processing was done on site, before transporting the logs downstream to Benjamin’s Mill (Figure 1.2).

This process would likely have resulted in increased watershed erosion and alteration of the waterway, as well as significant OM input.

In 1928, completion of a spillover dam between the Forks and Black Rivers created Black River Lake (Figure 1.2), and effectively removed the Forks River from its headwaters. The Forks River Dam reduced river discharge and the velocity of the Forks

River, now known as the WBAR. Runoff from Black River Lake typically overtops the dam each spring, usually in May, but otherwise the upper WBAR, where Deep Stillwater is located, is fed only by runoff and a spring located at Duncan’s Meadow (Figure 1.1).

The original timbered dam was replaced in 1944 with the current earth fill structure.

Before logging began, large runs of salmon were common on the Forks River

(Smith, 1965). Isaacman and Beazley (2005) described a significant decline in anadromous fish species following damming and disjunction from the river’s headwaters.

Bleakney (1994) believed acid rain deposition may have led to the rapid decline in many

Dissolved Oxygen pH Temperature 0

Depth (m) Depth 6

0 2 4 6 6 7 8 10 15 20 -1 mg * L oC May August October

Figure 2.1. Lake water physiochemical data for Deep Stillwater, 2015. species, fish included. Consultation with area residents suggested that trout fishing on the

WBAR declined significantly in the 1960s (D. MacInnes, personal communication, April

21, 2015). In the late 1960s, smallmouth bass (Micropterus dolomieu) were introduced to

Black River Lake and may have entered the WBAR during spring dam overflow events

(Bleakney, 1994).

Since the 1980s, residents have monitored water quality on the WBAR. The pH has risen from 4 to near neutral in the past three decades. In 1996, the Windsor causeway across the Avon River was briefly opened for maintenance, and numerous salmonids were identified along the WBAR. D. MacInnes (2015) caught numerous trout one day in

May 2012, but otherwise had not caught trout in the WBAR around Deep Stillwater.

Though fish numbers and diversity increase downstream of the Forks River Dam, no salmonids regularly travel beyond the Horton Meadow Brook tributary (Figure 1.1) (D.

MacInnes, personal communication, April 21, 2015). The only anadromous species that are still known to occupy the WBAR are blueback herring (Alosa aestivalis) and alewives

(Alosa pseudoharengus), collectively known locally as gaspereau (Isaacman and Beazley,

2005).

2.2.2 Impact of logging on lakes and rivers: Paleolimnological perspectives

The quantity of log-drive timber produced by historical logging damaged stream-bank habitats and left behind large amounts of organic debris, which settled to the bottom of rivers and fluvial lakes. This practice often resulted in anoxic conditions in the benthic environment and, in extreme cases, could cause DO deficiencies to the entire ecosystem.

The degradation of organic material requires oxygen normally available to other biota

(Campbell and Doeg, 1989) and a sudden reduction in DO can be lethal to resident organisms or create an impassable barrier to fish passage. Furthermore, excess nutrients would be released into the aquatic system as the OM decomposed (Binkley and Brown,

1993; Bragée et al., 2013), potentially leading to eutrophication. As well, increased erosion would accompany a reduction in forest cover, exacerbating OM load during runoff while also increasing clastic input to the system.

Turkia et al. (1998) used the paleolimnological method to study historic diatom assemblages and determined that select timber harvesting practices could lead to eutrophication in small forest lakes. Forestry-induced soil disturbance, after clear-cutting,

31 resulted in declining DO, which in turn resulted in sedimentary phosphorous (P) release.

However, Turkia et al. (1998) only found evidence for forestry-induced eutrophication in one of five studied lakes, while results from their other sites were inconclusive. Likewise,

Laird and Cumming (2001) and Räsänen et al. (2007) investigated the impact of forest harvesting on lakes in a paleolimnological study using diatoms and macrofossils, respectively, as the primary proxies for change. The changes were subtle in both impacted and reference lakes and the researchers inferred that abiotic proxies may be more sensitive to tracking the effects of logging.

In contrast, Scully et al. (2000) determined that logging can have significant effects on the physical structure and autotrophic community in small temperate lakes.

They used fossil carotenoids and chlorophylls to produce a 200-year record of environmental change. Biological responses to forest harvest included elimination of deep-water populations of anaerobic photosynthetic bacteria and reduced abundance of metalimnetic chrysophytes. Photosynthetic bacteria remained absent for over 100 years, while sediment laminae and chrysophytes were noted to have returned only since around

1970. In contrast, populations of epilimnetic phytoplankton (cyanobacteria, chlorophytes, and cryptophytes) were unaffected by the clear-cut. Analysis of sediment profiles did not reveal evidence of eutrophication or of increased flux of OM following watershed disturbance. They noted that such century-long disturbance may be common in small, stratified boreal lakes.

According to Watmough et al. (2003), forest harvesting can have a significant impact on water chemistry, which becomes more apparent as exchangeable base cation pools decline and acid inputs can no longer be buffered into the lake. They outlined the

32 importance of watershed soil and bedrock, and the resultant chemistry of groundwater, on the chemical impact of logging.

2.2.3 Knowledge gaps

The impacts of early 20th century logging practices and historic headwater removal on watershed dynamics and lake water quality is not well addressed in the available literature. Also, sediment archives from fluvial systems are difficult to obtain and are understandably nearly absent from the literature. However, the substantial changes that have occurred over the last century in the WBAR watershed strongly suggest that there has been significant impact that may be recorded in sediment archives. This study addresses these knowledge gaps by examining the bulk geochemistry of a paleolimnological archive from Deep Stillwater to better understand how logging and damming affect natural processes in upland watersheds.

2.3 Methods

To model fluvial lake evolution through time, lake sediment cores were obtained, from which a proxy model of past environments was constructed. Cores were split, sub- sampled for geochemical and paleoproxy analyses, and analyzed at Acadia University.

The modelling of the physical and chemical characteristics of upland fluvial lakes that have been impacted by logging and damming practices, and the change in proxies over time that these impacts have influenced, will allow for the reconstruction of both historic and pre-historic physical and environmental change that has occurred in the watershed. Specific proxies will be used to determine watercourse impact over time. An

33 understanding of the resilience of a system to environmental change, its natural evolutionary trajectory and the overprint of anthropogenic effects is essential to effectively manage the resource with respect to future environmental change

(anthropogenic or natural) scenarios.

Furthermore, historical change, and its effect on water and habitat quality, will be investigated through archival research, interviews with stakeholders and residents, and field research. The present state of the system will be calibrated by comparing paleolimnological proxies from undisturbed sediment samples and correlating them with historical findings.

2.3.1 Bathymetric and sub-bottom profiling

Soundings across Deep Stillwater were recorded before coring in May – June 2015 to construct a bathymetric profile of the lake (Figure 2.2). The point-depth measurements were generated by depth sounder (50 kHz Global Positioning System (GPS) synchronized SyQwest echo sounder with sub-bottom capability) and locations recorded by GPS. Points were collected in a pattern across the lake until a sufficient data set was generated with which to profile the entirety of the basin (Figure 2.2). Data points were plotted using Hypach bathymetric modeling software. Basin shape is important in understanding sediment deposition, and combined with sub-bottom profiling of sediment thickness, provides the most likely location to retrieve a complete sediment record.

Figure 2.2. Bathymetry (top left) and sub-bottom profiles for Deep Stillwater. Sub- bottom transects are described on the bathymetry image. The star denotes coring location beneath a back eddy and area of greatest sediment accumulation.

2.3.2 Water quality data collection

Modern water quality was determined using an YSI 650 multi-parameter display system multi-probe display logger. The multi-probe measured pH, temperature, DO, and

35 oxidation-reduction potential (ORP), all important parameters when analyzing water quality. Instrumental water quality data was collected from the surface and down through the water column, in 1 m intervals.

2.3.3 Sediment core collection and processing

Three sediment cores (DS1, DS2, DS3) were collected from Deep Stillwater in May of

2015 (Fig 2.2) using a Glew Gravity Corer (Glew, 1991) following procedures developed by Reasoner (1993). Core barrels measured 60 cm in length with a 6.5 cm inner diameter.

Coring location was chosen based on bathymetry and sub-bottom profiling to obtain representative sediment samples of the fluvial lake (Fig 2.2). The deepest part of the basin was inappropriate for sampling due to the accumulation of coarse woody debris, presumably logs, and so coring was conducted nearby at 10 m depth, where sediment retrieval was possible (Fig 2.2).

All the cores were measured and photographed before processing. Core DS3 was extruded and sliced at 0.5 cm intervals, on site, using a Glew portable extrusion device

(Glew 1988; Glew et al., 2001), immediately after sampling. Sediment slices were extruded into individual Ziploc bags for transport back to Acadia University.

The remaining cores (DS1 and DS2) were decanted and sealed with bentonite clay for later analysis. Core DS2 was visually the most like the extruded core (DS3) and was frozen and split lengthwise to reveal stratigraphy that could be compared to the data collected from DS3. Core DS1 was also frozen and stored.

Extruded 0.5 cm samples of core DS3 were homogenized by hand within 24 h of field sampling. Homogenized samples were sub-sampled in duplicate, with a stainless-

36 steel spatula, and dried in crucibles at 105 oC for 8 h. Every fifth sample was sub-sampled in triplicate to ensure sample homogeneity. Crucibles were weighed before and after drying to calculate water content and sediment density, to provide physical context for later data interpretation and as a requirement for 210Pb-dating. Dried samples were stored in sterile individual vials (pill bottles) until further analysis.

2.3.4 Bulk geochemical analysis

Concentrations of individual elements, or suites of elements, can be useful for reconstructing paleoenvironments and disturbances. Analysis of cation concentrations in core sediment was accomplished using x-ray fluorescence spectrometry (XRF), which measures X-rays emitted by atoms when exposed to certain quantities of energy. Atoms that have absorbed an amount of energy greater than the binding energy of inner shell electrons eject those electrons from the atom, causing outer shell electrons to transition to the vacated inner shells, resulting in a loss of energy which is released as X-ray photons

(Markowicz, 2002). Atoms of different elements have unique electron transitions, with different binding energies, and thus an element can be identified by measuring the energy intensities released in this process. This is advantageous in being rapid, non-destructive, and of high resolution (Koinig et al., 2003; Kylander et al., 2011).

Geochemical data was obtained from the extruded core samples using an

Olympus X-5000 portable desktop XRF. Concentrations were obtained for 37 elements: antimony (Sb), As, barium (Ba), bismuth (Bi), cadmium (Cd), calcium (Ca), cesium (Ce), chlorine (Cl), Cr, cobalt (Co), Cu, Fe, lanthanum (La), Pb, Mn, Hg, molybdenum (Mo), neodymium (Nd), nickel (Ni), niobium (Nb), P, K, praseodymium (Pr), Rb, selenium

(Se), silver (Ag), strontium (Sr), sulphur (S), thorium (Th), tin (Sn), Ti, tungsten (W), uranium (U), V, yttrium (Y), Zn, and zirconium (Zr). Of these, 19 had a reasonable number (>50%) of samples with concentrations above the limit of detection (LOD) for the XRF (As, Ba, Ca, Cl, Cr, Cu, Fe, Pb, Mn, K, Rb, Sr, S, Ti, U, V, Y, Zn, Zr).

2.3.5 Other sediment analyses

Several other methods of sediment analysis employed were loss on ignition (LOI), PSD,

Total Carbon, Total Nitrogen and stable isotopes (δ15N, δ13C). These analytical methods are both expensive and destructive and so had to be chosen carefully. Loss on ignition, a percent by-weight approximation of OM in sediment, was performed for 24 h at 500 oC in the kiln at Acadia University. Starting at 1.0 cm depth, a sub-sample of every other sediment slice (1.0 cm resolution) from core DS3 was subjected to LOI. Particle size distribution was obtained via the pipette method (Miller, 1987) at the Environmental

Biogeochemistry Lab in the K.C. Irving Environmental Science Centre at Acadia

University. As with LOI, a sub-sample of every other sediment slice (1.0 cm resolution), starting at 1.5 cm depth, was subjected to PSD.

Percent values of C and N, and stable isotopes (δ13C, δ15N), are proxies for paleoproductivity and OM composition and provenance in freshwater ecosystems. Sub- samples were collected every 1.0 cm, from 1.5 cm depth to 16.5 cm depth, after which the following depths were sub-sampled: 18.5, 21.5, 24.5, 27.5 (cm). Stable isotope analysis was conducted at the Stable Isotopes in Nature Laboratory (SINLab) at the

University of New Brunswick.

2.3.6 Radiometric dating

Core chronology was constrained via 14C and 210Pb dating. Three 14C dates were established from wood samples extracted from 9.5 cm, 15.0 cm, and 29.5 cm depths within core DS3. The 14C dates were determined by the A.E. Lalonde Accelerator Mass

Spectrometry Laboratory. Analysis of 210Pb for the entire extruded core was performed by Université d’Ottawa. Radiometric dating was supplemented and supported by analysis of disturbance history within the watershed, via literature review and compiling local knowledge accounts.

2.3.7 Quality Control

For bulk geochemistry and water content (% water), each slice of sediment was pseudo- replicated twice before analysis, with every fifth sample (beginning at 1.5 cm depth) being pseudo-replicated in triplicate. In this case, pseudo-replication refers to the separate analysis of two portions from each homogenized sample. Elemental and % water data points are mean concentrations between pseudo-replicates at each depth with error bars based on standard error of the averaged means. In addition to triplicate pseudo- replication, every fifth bulk geochemistry sample was analyzed three times, without removal from the XRF, to establish analytical error. Percentage analytical error is presented in Table 2.1.

Two laboratory standards (CAN174 and CAN277) that were analysed in previous

XRF studies (Dunnington 2011; Englehardt 2013; Misiuk 2014; Tymstra 2013; White

2012b) were analyzed at the beginning of each day of analysis and after every twenty samples, for determination of reproducibility of results (Table 2.2). The average

Analytical Mean Method Blank

Error (%) Concentration (ppm)

Fe 0.49 ± 0.31 341.1 ± 128.2

K 1.27 ± 0.62 -

Mn 1.16 ± 0.82 25.9 ± 3.4

Rb 2.12 ± 1.57 -

Ti 1.29 ± 0.93 47.7 ± 8.6

%water 0.76 ± 0.97 n/a

Table 2.1. Quality control results for bulk geochemistry and %water analyses on core DS3.

reproducibility error of lab standards was ±11.2%. Alongside the standards, seven method blank vials were analyzed on the XRF. Only Fe, Mn, and Ti were detected on the blank runs; mean concentrations of these elements in blanks can be found in Table 2.1.

Three method blanks were analyzed alongside the 29 PSD samples, none of which measured any sand-, silt-, or clay-sized particles. One sample (15.5 cm depth) was analyzed in triplicate, with a standard deviation of ±1.5% for clay-sized, ±3.1% for silt- sized, and ±2.1% for sand-sized particles.

SINLab analyzed four working standards (AQM, CMS, EPS, SPL) and two standards (acetanilide, peach leaf) during Total C, Total N, and stable isotope analyses

(SINLab 2016). These results are compiled in Table 2.3.

Of the 19 elements with suitable XRF concentrations for further analysis, five presented analytical challenges that prevented such, and were removed from the data set.

Barium, Cl, and S had wide error bars and thus could not be considered accurate.

lab standard CAN174 lab standard CAN277

Element concentration error concentration error

(ppm) (%) (ppm) (%) arsenic (As) 34.9 15.8 34.5 8.6 chromium (Cr) 54.0 17.6 71.0 11.1 copper (Cu) 30.7 21.7 37.3 11.5 iron (Fe) 23134.9 12.8 30727.3 7.0 lead (Pb) < LOD n/a < LOD n/a manganese (Mn) 501.7 9.2 636.0 6.6 potassium (K) 7152.6 9.6 23434.0 8.0 rubidium (Rb) 61.7 8.1 129.2 6.1 strontium (Sr) 85.7 10.9 121.7 6.5 titanium (Ti) 1729.1 8.6 4541.7 7.5 uranium (U) 23.4 20.1 44.3 9.4 vanadium (V) 51.7 8.9 83.6 9.2 yttrium (Y) 80.7 9.5 54.0 5.0 zinc (Zn) 131.3 12.2 166.7 33.3

Table 2.2. Average concentrations (n = 7) of elements in laboratory standards and percentage reproducibility error (standard deviation). Both lab standards were below the XRF LOD for Pb.

δ13C δ15N %C %N C / N acetanilide (n=9) ± 0.19% ± 11.54%* ± 1.16% ± 1.51% ± 1.13% peach leaf (n=3) ± 0.29% ± 6.97%* ± 0.74% ± 4.73%* ± 5.39%

AQM (n=6) ± 0.12% ± 2.47% ± 2.77% ± 3.20%* ± 2.67%

CMS (n=6) ± 1.57% ± 3.76% ± 1.54% ± 1.89% ± 3.00%

EPS (n=6) ± 0.28% ± 51.74%* ± 1.97% ± 2.57%* ± 3.19%

SPL (n=6) ± 0.50% ± 2.30% ± 1.64% ± 2.45% ± 2.05%

Table 2.3. Quality control for paleoenvironmental analyses δ13C, δ15N, %C, %N, and C/N as provided by SINLab (2016). Error was derived from the standard deviation of average values for each of the measured standards. Numbers marked with an * should be interpreted with caution, as they were derived from averaged values that were much lower than other values within the same standard or measured parameter and thus may not be indicative of the accuracy of the analytical process.

Zirconium is sometimes used as a CLE but can be subject to the nugget effect

(Simmonds, 2009; C. Stanley, personal communication, November 10, 2017), and was removed from consideration due to the high sand content of the Deep Stillwater cores

(see Results). Calcium displayed no variability and was therefore unnecessary to include in the context of this study.

2.4 Results

2.4.1 Modern water characterization

The temperature profile data for Deep Stillwater indicated a stratified summer profile,

42 with a thermocline from 0.5 to 6.5 m depth. Temperatures in August ranged from 8.2 oC at the bottom to 21.3 oC at the surface. The DO profile indicated the water column was anoxic throughout the summer and fall seasons, except for a sharp increase in DO concentration in the summer epilimnion. Spring DO concentrations were uniform throughout the water column and much higher than other months. Secchi depth was measured at 1.75 m in spring; however, this most likely is a factor of water colour and turbidity, rather than eutrophication.

2.4.2 Bathymetry and sub-bottom profile

High-resolution bathymetric data revealed that Deep Stillwater has a single basin nearly

12 m deep. The approximate volume of Deep Stillwater is 79000 m3. Sub-bottom basin analysis revealed consistently strong reflectors, indicating a hard substrate likely created by sediment scour and/or debris build-up. Attempts to obtain sediment cores from the

deepest portion of the basin were unsuccessful. However, sediment accumulation was greatest below a back eddy just to the northeast of the basin’s deepest point, and it was from this area that sediment cores were collected for analysis.

2.4.3 Stratigraphy

Cores DS2 and DS3 were sampled very close together and were of similar length. DS3 was extruded and subjected to geochemical analyses, while DS2 was sealed with bentonite clay, frozen, and sliced to observe stratigraphy. Figure 2.3 shows the two cores beside each other, as a photo (DS2) and as a graphic representation of the data collected

(DS3). Large woody debris, at least one sand lens, and gravel-size (>2000 um) grains can

Figure 2.3. Photo of stratigraphic profile of frozen and split core DS2 alongside graphic representation of sedimentary data derived from extruded and geochemically analyzed core DS3. Zone descriptors can be found in section 2.4.5 of this chapter.

be seen embedded in DS2 (Figure 2.3). Also, the sediment in DS2 darkens from brown to near black towards the surface (Figure 2.3), indicating a possible shift to more organic- rich, less clastic, sediment.

2.4.4 Age-depth

Terrestrial OM was found throughout core DS3. Three pieces were selected for 14C dating; from the bottom of the core, at 29.5 cm, and from the two visible sand lenses at

9.5 cm and 15.0 cm. Radiocarbon dating of this material resulted in ages of 1521 ± 40 cal

BP (9.5 cm), 1975 ± 65 cal BP (15.0 cm), and 9719 ± 147 cal BP (29.5 cm).

Background 210Pb activity was reached at a depth of 10.5 cm, above which ages and sedimentation rates were calculated according the CRS model (Figure 2.4) (Appleby and Oldfield 1983). Sediment accumulation increased towards the top of the core (Figure

2.4). The sharp decrease in 210Pb age at 10.0 cm is coincident with the uppermost sand lens visible in the stratigraphic profile and may be indicative of an erosion event.

However, this event is not believed to be a turbidity inflow, as that would result in much lower 210Pb results (J. Cornett, personal communication, March 18, 2016).

The uppermost 14C date at 9.5 cm, is incompatible with the established 210Pb age- depth curve (Figure 2.4). This is likely the result of the dated material being inherited carbon transported from the watershed during the erosion event, which deposited the sandy sediment at this depth, or sediment scoured away during the erosive event to reveal previously buried carbon. As the second 14C date at 15.0 cm was also located at the base of a sand lens, it is likely be subject to similar conditions. The lowermost 14C date at 29.5 cm does not coincide with a sand lens, nor does the sedimentary record show any

Figure 2.4. Age-depth results for Deep Stillwater core DS3. Sediment accumulation rate (SAR) was calculated using the CRS model by J. Cornett at Université d’Ottawa. indication of disturbance at that layer, so the date of the sample is likely consistent with the age of the surrounding sediment. Given the presumed unreliability of the 14C dates, a

SAR for the entire core was not extrapolated from the combined 14C and 210Pb data.

2.4.5 Bulk geochemistry and environmental paleoproxy results

Geochemical results are discussed by zone and summarized in Figure 2.5 and Table 2.4.

Zone boundaries were abrupt, occurring over 1 cm or less of sediment.

Zone 1 (Z1) begins at the bottom of DS3 (30.5 cm) and continues to 18 cm depth

(Figure 2.5). It is characterized by high, stable concentrations of Ti, Rb, and K, an approximately 3:1 sand to silt ratio, and the highest values for δ15N and δ13C in the core

(Table 2.4). Zone 1 also displayed the highest zonal Fe/Mn. This zone is evident in the 46 stratigraphic profile as a thick layer of homogeneous brown sediment, with bits of woody terrestrial matter throughout.

Zone 1a (Z1a) (23.5 – 22.0 cm) represents a change to coarser sediment relative to background values defined by Z1, with increases in Ti, K, Rb, and %sand (Table 2.4).

The %water trendline indicates a slight increase; however, this was not evident statistically. No change in δ15N, δ13C, %C, %N, or %OM was apparent in Z1a. This zone was not visibly apparent in the stratigraphic profile.

Zone 2 (Z2) begins at 18 cm up to 9.5 cm depth (Figure 2.5). It is defined by the lowest values for %water, %silt, %C, %N, and %OM (Table 2.4). Zone 2 has the highest concentration of Rb and the highest value for %sand and C/N (Table 2.4). This zone is evident in the stratigraphic profile as two bands of lighter-coloured, visibly sandy, sediment.

Zone 2a (Z2a) lies within Z2 between 14.0 cm and 11.0 cm depth (Figure 2.5). It is evident in the stratigraphic profile as a heterogenous layer of silty, brown, sediment and organic-rich black sediment. It differs from background values defined by Z2 with higher %water, %silt, %C, %N and %OM (Table 2.4). Concentrations of Ti and K in this zone are approximately half of those in Z2, with Rb also lower (Table 2.4). Fe/Mn appears lower than the baseline values established by Z2; however, the data are erratic.

Zone 3 (Z3) begins at 9.5 cm depth and rises to the top of the core at 0.0 cm

(Figure 2.5). It is characterized by the lowest concentrations of Ti, Rb, and K, as well as the lowest results for δ15N and Fe/Mn, in the entire core (Table 2.4). This is the only sediment zone where %silt is higher than %sand. Water content, %C, %N, and %OM

Figure 2.5. Bulk geochemistry and environmental paleoproxy trendlines for Deep Stillwater core DS3. Sediment zones are divided by dotted lines with sub-zones highlighted in grey.

Mean (n)

Zone 1 Zone 1a Zone 2 Zone 2a Zone 3

30.5 - 18.0 cm* 23.5 - 22.0 cm 18.0 - 9.5 cm* 14.0 - 11.0 cm 9.5 - 0.0 cm silt (%) 25.5 ± 5.1 (11) 15.3 (1) 13.1 ± 3.2 (6) 23.2 ± 5.4 (3) 51.0 ± 8.6 (8) sand (%) 71.3 ± 5.2 (11) 83.2 (1) 85.1 ± 3.6 (6) 74.3 ± 5.5 (3) 44.9 ± 7.8 (8)

Cr/V 0.91 ± 0.08 (22) 0.87 ± 0.03 (3) 0.63 ± 0.18 (11) 0.54 ± 0.08 (6) 0.58 ± 0.09 (17)

Fe/Mn 46.3 ± 2.2 (22) 44.7 ± 2.0 (3) 42.6 ± 2.6 (11) 37.1 ± 2.4 (6) 36.6 ± 3.3 (17)

Ti (ppm) 2599 ± 188 (22) 2755 ± 169 (3) 2182 ± 486 (11) 1396 ± 102 (6) 1079 ± 125 (17)

K (ppm) 10447 ± 1024 (22) 12435 ± 1387 (3) 11824 ± 2136 (11) 6038 ± 661 (6) 3367 ± 471 (17)

Rb (ppm) 88.5 ± 10.7 (22) 103.0 ± 11.0 (3) 111.3 ± 8.4 (11) 79.8 ± 5.3 (6) 51.9 ± 7.0 (17) water (%) 83.5 ± 2.0 (22) 81.0 ± 1.8 (3) 75.9 ± 3.7 (11) 85.5 ± 1.1 (6) 92.2 ± 1.3 (17)

OM (%) 27.2 ± 4.6 (11) 23.6 ± 0.7 (2) 16.8 ± 2.6 (5) 36.3 ± 3.8 (3) 51.6 ± 5.4 (9)

δ13C (‰) -28.5 ± 0.4 (4) n/a -29.0 ± 0.2 (8) -28.7 ± 0.1 (3) -29.0 ± 0.1 (8)

δ15N (‰) 1.7 ± 0.4 (4) n/a 0.7 ± 0.3 (8) 0.8 ± 0.2 (3) 0.5 ± 0.1 (8)

C (%) 12.1 ± 3.0 (4) n/a 7.1 ± 2.3 (5) 16.5 ± 0.9 (3) 26.4 ± 1.7 (8)

N (%) 0.7 ± 0.2 (4) n/a 0.4 ± 0.1 (5) 0.9 ± 0.1 (3) 1.7 ± 0.1 (8)

C/N 16.4 ± 0.5 (4) n/a 16.7 ± 1.5 (5) 17.9 ± 1.5 (3) 15.9 ± 0.2 (8)

* less associated sub-zone sediment

Table 2.4. Mean bulk geochemistry concentrations and paleoproxy values for Deep Stillwater, core DS3, segregated by sediment zone. Error (expressed as ±) was derived from the standard error of averaged means at each depth. No measurements of δ13C, δ15N, %C, or %N were recorded for the narrow Z1a sediment. were also higher in Z3 than any other sediment zone (Table 2.4). Zone 3 was evident in the stratigraphic profile as a homogeneous, loose, black, sediment layer.

2.4.6 Data correlations

Pearson correlation coefficients (r) were determined for all environmental proxies and compiled in Table 2.5. Only coefficients with a p-value of < 0.05 were considered. A correlation was considered strong if r > 0.7 or r < -0.7 and moderate if 0.5 < r < 0.7 or -

0.7 < r < -0.5.

Most environmental proxies correlated strongly or moderately with each other, excepting C/N which correlated with no other proxy; δ13C, which only correlated with

δ15N; and δ15N, which also correlated with Ti, Ba, and Fe/Mn. The minerogenic proxies

Ti, Rb, K, and Ba correlated positively with each other, as well as with %sand and

Fe/Mn, and negatively with %water, %silt, and %OM.

Correlating PSD or stable isotope data with %OM was not possible due to perfectly off-setting datasets given that only every other slice was analyzed for the destructive analyses.

2.5 Discussion

2.5.1 Chronological reconciliation

Before logging and damming influence could be analyzed, the sediment record must be chronologically reconciled. The base of the DS3 sediment core has a time stratigraphic constraint of 11107 ± 502 cal BP based on 14C dating. As this date is well before any known anthropogenic disturbance, the sediment it belongs to, Z1, is considered that deposited by the pre-disturbance environment or the natural run of the WBAR before logging or damming.

sand Ti Rb K water OM δ13C δ15N

(%) Cr/V Fe/Mn (ppm) (ppm) (ppm) (%) (%) (‰) (‰) C (%) N (%) C/N silt (%) -0.995 - -0.608 -0.649 -0.907 -0.814 0.890 n/a - - 0.919 0.936 - sand (%) - 0.602 0.649 0.921 0.819 -0.904 n/a - - -0.930 -0.945 -

Cr/V 0.715 0.727 - - - - 0.643 0.717 - - -

Fe/Mn 0.832 0.647 0.746 -0.574 -0.621 - 0.525 -0.779 -0.768 -

Ti (ppm) 0.753 0.913 -0.683 -0.801 - 0.709 -0.795 -0.791 -

Rb 0.916 -0.949 -0.948 - - -0.968 -0.969 -

(ppm)

K (ppm) -0.892 -0.942 - - -0.916 -0.912 -

%water 0.947 - - 0.939 0.936 -

OM (%) n/a n/a n/a n/a n/a

δ13C (‰) 0.743 - - -

δ15N (‰) - - -

C (%) 0.995 -

N (%) -

Table 2.5. Pearson correlation coefficients (r) for strong (r > 0.7 or r < -0.7) and moderate (0.5 < r < 0.7 or -0.7 < r < -0.5) correlations of bulk geochemical and environmental paleoproxy data. Only correlations with a P-value of < 0.05 were considered. Entries of ‘-’ indicate weak or no correlation between parameters and entries of ‘n/a’ indicate an inability to correlate parameters due to perfectly off-setting data points.

Two sandy deposits overlay Z1, at 14.0-18.0 cm depth and 9.5-11.0 cm depth.

They have similar clastic, organic, particle size, water content, and Fe/Mn response, and are collectively referred to as Z2. The deeper sandy layer had a 14C date of 1962 ± 156 cal BP, and the more recent sand event was 14C-dated as 1429 ± 96 cal BP. Z2a, located

51 between the two sand layers, had similar C/N, δ13C, and δ15N values to bounding sediment in Z2; however, Z2a displayed a sharp decline in clastic content, decreasing

Fe/Mn and % sand particle size, and increased water content, %OM, %C, and %N.

The 210Pb dating trend is not compatible with the uppermost 14C date. The 210Pb date at 9.5 cm depth is ~1943, with another date at 10.0 cm depth of ~1906. Both sand deposition events are likely associated with logging and channel/bank scour, and the 14C dates are derived from inherited material. Early 20th century logging practices often included the construction of splash dams which temporarily impounded the river before being burst to allow a deluge of water and conveyance of timber to flow to downstream mills. These rapid increases in river stage and local discharge were erosive, and likely led to sediment scouring along the riverbed and a loss of a significant amount of the upper portion of Z1 sediment (Figure 2.6). Erosion from the impoundment release, and terrestrial logging activities, resulted in a large amount of sediment entering the system; however, high discharge resulted in the deposition of coarse clastic sediment within the deep portion of the basin (David’s Pool). Therefore, the material that provided the two uppermost 14C dates was either inherited from an unknown location or was exposed by local downcutting during the scour event.

Additionally, Z2 and Z2a show an increase in C/N, indicating an influx of terrestrial OM to the system which would be expected during logging activity in the watershed. The clastic content is lower in Z2a, relative to Z1, likely due to an increase in

OM, not a decrease in clastic input. Overall, the sedimentation rate for Z2, if coincident with logging from ~1900-1910, was elevated as ~8.5 cm of sediment accumulated over approximately 10 years, a sedimentation rate that is conservative, as it does not account

Figure 2.6. Chronological reconstruction of environmental change at Deep Stillwater based on the sediment record. for unconformities due to scour events.

It is difficult to differentiate the timing of the end of logging with the emplacement of the dam in 1928. Z3 begins at 9.5 cm depth and continues to the top of the core. This zone displays a shift in PSD and likely indicates a siltier or less energetic system, in accordance with the loss of headwaters. Organic matter content increased as clastic content decreased; however, the %OM was not accompanied by an increase in

δ13C or δ15N as it was in Z2. Likewise, C/N decreased from Z2 levels, indicating a reduction in terrestrial organic input. An increase in %OM, if not attributed to logging, may have resulted from an increase in algae and aquatic plant productivity in a less energetic system.

Thus, Z1, which is basally constrained at 11107 cal BP, would have accumulated to an indeterminate thickness before a major scour event (logging), which in turn would produce an unconformity, erroneously constraining the top of Z1 (and the processes responsible for its deposition) at approximately 1890-1900 AD (from historical logging records). Z2 sedimentation occurred in conjunction with logging activity and contains inherited wood from watershed disturbance. The chronological constraint for Z2 is ~1928

AD, coincident with the first Forks River Dam emplacement. The upper sand layer of Z2 is likely derived from the combined disturbance caused by logging activity and the emplacement of the dam.

2.5.2 The effect of historical logging and damming on the modern aquatic environment

2.5.2.1 Particle size and clastic fraction

Particle size increased temporarily during logging events; however, overall the reduction in energy after the emplacement of the Forks River dam has led to finer grained sedimentation. As particle size is represented as a percentage, it is not clear if this change is due to a decrease in sand-sized grains, an increase in silt-sized grains, or both.

Smaller particle size increases the surface area of sediment particles, reducing porewater space and providing increased binding sites for trace elements, pollutants, and

OM. In this way, sedimentation in Deep Stillwater now has greater potential for the sequestration of metals and pollutants, but also makes such hazards more readily bioavailable for lacustrine benthos.

A reduction in system energy will result in increased sedimentation, as more particles can settle, and increase turbidity, as eroded particles are not flushed rapidly from

Deep Stillwater. This would have resulted in a reduction in sunlight penetration into the water. Furthermore, reduced energy also implies a reduction in DO, particularly at depth.

Low DO leads to benthic anaerobic bacterial respiration and subsequent increases in dissolved CO2 (Lee and Hoadley, 1967). Dissolved CO2 decreases the pH of water through the formation of carbonic acid. Changes in pH at the sediment-water interface can affect solubility, sorption, and redox processes (Delfino and Lee, 1971).

The CLE all correlate positively with the %sand-sized data and negatively with

%OM. Their overall reduction post-disturbance, coupled with the increase in %OM post- disturbance, indicate a change to a more organic-rich sediment.

Thus, the sediment at Deep Stillwater, post-disturbance, has a greater organic fraction, with a greater percentage of silt-sized particulates.

2.5.2.2 Organic matter and stable isotopes

An increase in the C/N in Z2 reflects increased allochthonous OM input to Deep

Stillwater, which is consistent with an interpretation that this zone was deposited during the period of logging. However, %OM only increases in Z2a, perhaps being overwhelmed fractionally by the increase in sand-sized clastics during the Z2 scour events.

Overall, %OM nearly doubled post-disturbance, yet, the C/N value remained constant. As flow along the WBAR decreased, algal production in Deep Stillwater would increase, thereby lowering C/N. However, flow reduction would also allow for the

55 anchorage of more macrophytic plants surrounding Deep Stillwater, which have a higher

C concentration than algae, thereby balancing out the C/N.

%N and %C both correlated strongly positive with %OM, which is expected; however, δ13C and δ15N did not. Bacterial activity is usually the cause of decreases in

δ13C and δ15N, in conjunction with increases in %C and %N, respectively. Mineralization of sinking particles by anaerobic heterotrophic bacteria, due to increasing anoxia, has been found to reduce δ13C sedimentation (Gaiser et al., 2009; Hollander and Smith, 2001;

Kankaala et al., 2006; Lehmann et al., 2002).

Sedimentary δ15N can be depleted in eutrophic or hypereutrophic systems due to cyanobacterial N-fixation (Fogel and Cifuentes, 1993; Gu et al. 1996; Rosenmeier et al.

2004). Deep Stillwater is classified as a dystrophic lake; however, its trophic status likely shifted more toward eutrophia with the reduction in flow and consequent increase in OM deposition. Many factors can influence δ15N and δ13C sedimentation and further study is needed to fully understand the influence of logging and damming on OM in Deep

Stillwater.

2.5.2.3 Redox

Oxidation-reduction (redox) reactions are integral to major and trace element cycling, mobility, and bioavailability (Grundl et al., 2011). The ratio of Fe to Mn (Fe/Mn) is a simple means of inferring paleoredox conditions in lakes. The two elements are chemically similar; however, Mn dissolves more readily under reducing conditions, and an increase in Fe/Mn is expected at the onset of reducing conditions (Davison, 1993;

Engstrom and Wright, 1984; Mackereth, 1966). In Deep Stillwater, this would imply that

56 sediment became more oxidizing post-disturbance (Figure 2.5). However, Fe and Mn cycling is complex and can be affected by oxidation or mixing events (Schaller et al.,

1997), DOM provenance (Franz et al., 2006; Young and King, 1989), and DOM quantity and DO (Koinig et al., 2003).

In addition to Fe/Mn, the Cr to V ratio (Cr/V) can also serve as a paleoindicator of redox conditions as a function of hydroxyl scavenging dynamics (Schaller et al., 1997).

In oxidizing waters Cr and V both form oxoanions (chromate and vanadate, respectively).

Compared to chromate, vanadate more readily forms surface complexes with Fe- hydroxides, thereby decreasing the Cr/V of sediment. Under anoxic, reducing, conditions,

V forms the stable vanadyl cation which hydrolyses at pH 8 (Baes and Mesmer, 1976).

Chromium, however, is readily reduced to Cr (III) in anoxic waters and has a strong affinity for surface complexation with hydroxyl groups (Richard and Bourg, 1991), thereby increasing the Cr/V ratio.

In Deep Stillwater, the Cr/V trendline supports that of Fe/Mn (Fig. 2.5) and indicates that the system is more oxidizing pre-disturbance. The more oxidizing environment was onset by logging activity, and either reinforced or maintained by the emplacement of the dam, given that there was no return to the more reducing, pre- disturbance redox conditions.

2.6 Conclusions

1) Historical logging practices temporarily increased erosion and system energy, leading

to larger particle size deposition and scouring of bottom sediment, with resultant

unconformities in the sediment record.

2) Additionally, the faster flow associated with splash dam demolition (Z2) can bring

inherited C into fluvial lakes, complicating radiocarbon dating of sediment. We

recommend special attention to 14C analysis from fluvial lakes, with considerations

for system history and preferably in conjunction with other sediment dating

techniques.

3) Logging also increased allochthonous OM input to Deep Stillwater, and coupled with

the changes in energy, likely led to disruption of the biological community.

4) Damming significantly lowered the energy of the WBAR and Deep Stillwater,

allowing for finer-grain particle deposition. Furthermore, the slower-moving water

allowed for an ecological regime shift, with more algal and macrophytic colonization

than there was pre-disturbance. It is likely that Deep Stillwater underwent a period of

eutrophia after the Forks River Dam was constructed, as the water slowed, reducing

DO, and algal and macrophytic productivity increased. This may have been

compounded by the decomposition of allochthonous OM left over from previous

logging.

5) Coincident with logging, the aquatic system became more oxidizing. This persisted

past the time of damming, and it is unclear whether both logging and damming led to

a more oxidizing environment, or if the latter served to reinforce the redox

disturbance of the former. This would have been a significant alteration to the

biogeochemical structure of Deep Stillwater, with cascading effects throughout the

ecosystem.

Chapter 3: Legacy of anthropogenic disturbance on an upland fluvial lake: Focus on metal sequestration, toxicity, and bioavailability.

3.1 Problem statement

Logging and damming practices alter fluvial lake environments in the short- and long- term. Aquatic pollutants, such as metals, can be significantly impacted by environmental changes such as bank side erosion, nutrient influx, and flushing rate, which affect PSD, redox, pH, and DO. Additionally, increased erosion and allochthonous OM input can influence metal concentrations in water and sediment. This chapter will address the legacy of historic logging and damming practices on modern fluvial lake sediments, which is of concern when investigating ecosystem changes and developing future best management practices.

3.2 Introduction

Aquatic metal concentrations are a growing concern, as they are infinitely persistent, and insusceptible to degradation processes in the environment (Allan and Nriagu, 1993;

Campbell et al., 2006). High metal concentrations do occur naturally; however, human activity such as agriculture, effluent discharge, river channel management, urbanization, hydropower generation, and industry can also lead to problematic water and sediment metal concentrations in sensitive environments (Chon et al., 2010; Domingos et al., 2015;

Ferrier and Jenkins, 2010).

Dependent upon conditions, metal species can be transformed into more- or less- toxic forms or substitute for essential elements, such as Zn or Ca, and disturb biological

59 functions (Chon et al, 2012; Domingos et al., 2015; Horváth et al., 2013; Walker et al.,

2006). Metal concentrations have been found to alter key microbial community compositions and disrupt geochemical cycling of N and S (Kandeler et al., 1996; Kang et al., 2013; Ni et al, 2016). Metal toxicity also affects microbial community resiliency and the ability for an ecosystem to rebound after disturbance (Allison and Martiny, 2008;

Feris et al., 2004; Griffiths and Philippot, 2013; Shade et al., 2011). Ni et al. (2016) found that β-diversity (i.e. composition of species) but not α-diversity (i.e. diversity of species) in freshwater microbial communities was significantly affected by heavy metal concentrations.

Sediments are considered the greatest repositories of metals in aquatic ecosystems

(Demirak et al., 2006; Maceda-Veiga et al., 2012; Ricart et al., 2010). Roig et al. (2016) found that concentrations of metals in river waters were low or undetectable; however, metals such as Hg, As, Cr, Zn, Ni, and Cu reached concerning concentrations in the underlying sediment. Freshwater sediments may act as a sink for metals that adhere to buried organic (e.g. humic substances), inorganic (e.g. clays, Fe-oxides), or engineered

(e.g. nanoparticles) particles, or are dissolved in porewater (Alvares-Guerra et al., 2007;

Domingos et al., 2015; Horváth et al., 2013; Keller et al., 2013; Sparks, 2005). However, entrapped soluble metals can be resuspended if disturbed (Baudo and Muntau, 1990;

Burton and Johnston, 2010; Burton Jr., 2002; Crane, 2003; Nemati et al., 2011; SedNet,

2004) either naturally (e.g. wind, bioturbation, flood events) or anthropogenically (e.g. dredging, boating, channel management). Resuspended particles can react with chemicals in the water, sunlight, or available DO, and release metals back into the water column and surficial sediments, increasing bioavailability (Audry et al., 2004; Crane, 2003; SedNet,

2004; Simpson et al., 1998). In this way, even older sediments, which may have historically accumulated high concentrations of metals due to poor management practices, can still be exposed to overlying waters and damage modern ecosystems (Chon et al., 2010).

3.2.1 Aquatic metal contaminants in Nova Scotia

3.2.1.1 Arsenic

Arsenic, a bioaccumulative toxic metalloid, is classified as a human carcinogen that causes skin, bladder, kidney, and lung cancer (World Health Organization, 2004). It is a common element in the upper crust and was widely used in agricultural pesticide application in the first half of the 20th century (Shaller et al., 1997). Although As can exist in four oxidation states and twenty species, in the environment it is primarily inorganic arsenate (AsV) or arsenite (AsIII), two of the more toxic forms (Rodie et al.,

1995; Wang and Mulligan, 2006; Wang et al., 2014); AsIII is approximately 10 times more toxic and mobile than AsV (Wang and Mulligan, 2006).

Arsenic is considered the most prevalent naturally occurring groundwater contaminant in NS (Nova Scotia Department of Fisheries and Aquaculture, 2010).

Bedrock geology is the most important control on well water As concentrations

(Bottomley, 1984; Dummer et al., 2015), although four coal-burning power plants also emit As aerially and in on-site tailings and waste-rock repositories (Environment Canada,

2014; Nova Scotia Power, 2015). Arsenopyrite contained in the Meguma Terrane, particularly the metamorphic rocks of the Goldenville and Halifax groups, as well as the

61 granitoid South Mountain Batholith, is the main contributor of geological As in NS

(Chappells et al., 2015; Kickbush, 2015; Nova Scotia Department of Natural Resources,

2016).

Although anthropogenic sources exist, the majority of As is sequestered in rocks, and it becomes bioavailable when mobilized via erosion processes (Rodie et al., 1995;

Wang and Mulligan, 2006). Free As, or As bound to suspended particulates, is easily assimilated and bioaccumulated by organisms (Dale and Freedman, 1982; United States

Environmental Protection Agency, 2003). Competing ions, such as P, redox, and pH can also affect As bioavailability in aquatic systems (Wang and Mulligan, 2006). AsIII dominates in anoxic waters, while AsV is more prominent under oxic conditions

(Kickbush, 2015; Rahman et al., 2014). Arsenic can undergo biomethylation and becomes particularly toxic once methylated, breaking down deoxyribonucleic acid in affected organisms (Wang and Mulligan, 2006)

Arsenic bioaccumulation in fish can lead to behavioural changes, hormonal and metabolic disruption, and mortality (Shah et al., 2009; Sopinka et al., 2010). Freshwater fish typically express higher As concentrations in their tissues due to their proximity to atmospheric deposition and direct geological and anthropogenic inputs (Bowden, 2014).

However, anadromous alewife (Alosa pseudoharangus) and blueback herring (Alosa aestivalis), collectively and commonly referred to as gaspereau, migrating into NS lakes, have been found to have significantly elevated As concentrations compared to resident fish species (Kickbush, 2015). Kickbush (2015) suggested that gaspereau may have greater bioaccumulation or storage capacity for As then other freshwater fish species.

3.2.1.2 Aluminum

Aluminum (Al) ionizes readily in low-pH waters and becomes toxic to aquatic life

(MacLeod, 2016; Poléo, 1997). Aquatic plants are typically more tolerant of high Al concentrations than animals (British Columbia Ministry of Environment, 1987; Sparling and Lowe, 1996), with salmonids being a particularly vulnerable fish species (Spry and

Wiener, 1991). Aluminum toxicity in fish resolves as iono- and osmoregulatory dysfunction, as well as acute respiratory impediment (Lewis et al., 1990).

Acid deposition from industrial emissions in the latter half of the 20th century led to widespread, chronic, freshwater acidification across the northwestern United States, eastern Canada, Europe, and Scandinavia (Likens et al., 1972; Norwegian Institute for

Water Research 1997). Efforts to curb emissions in Europe and North America have caused freshwater acidity to stabilize and fish stocks have rebounded; however, in NS, high levels of dissolved organic carbon in dystrophic lakes and rivers have exacerbated acidification concerns and prevented rehabilitation of fish stocks (Dennis and Clair, 2012;

Fisheries and Oceans Canada, 2013). Low pH environments underlain by granites, such as the South Mountain batholith, experience increased mobilization of Al (Driscoll and

Schecher, 1990).

Across NS, freshwater ionic Al concentrations have exceeded the toxic threshold for Atlantic salmon (Salmo salar), and perhaps to other aquatic species, posing a threat to species diversity in NS ecosystems (MacLeod, 2016).

3.2.1.3 Mercury

Mercury volatilizes into the atmosphere from natural (e.g. soil outgassing, vulcanism,

63 evaporation) and anthropogenic sources (e.g. fossil fuel consumption, gold ore processing). It then enters aquatic systems through wet or dry deposition and becomes bioavailable (Berg et al., 2003; Wania and Mackay, 1996). Methylmercury, a biomagnifying, bioaccumulative neurotoxin, is formed in anoxic waters through the metabolic action of sulphate-reducing bacteria (SRB) (Compeau and Bartha, 1985; Nova

Scotia Department of Fisheries and Aquaculture, 2010). Because of its propensity for biomagnification, high trophic status organisms, such as piscivorous fish, birds, and mammals, are at the highest risk of Hg poisoning (Burgess et al. 2005; Evers et al. 1998;

Nova Scotia Department of Fisheries and Aquaculture, 2010; Wiener et al 2003).

Highly vegetated or high productivity environments, with ample OM decomposition, tend toward anoxia, prevalent SRB activity, and increased risked of

MeHg contamination (King et al., 2002; Klepac-Ceraj et al., 2004). Like many contaminants, Hg and MeHg readily bind to organic and inorganic particulates and can be sequestered in sediment, both increasing sedimentary concentrations of Hg, but also potentially decreasing bioavailability (Lin et al., 2011; Sizmur et al., 2015).

3.2.1.4 Other metals

Mercury, As, and Al are among the most concerning and studied metals in aquatic environments; however, other heavy metals, such as Cr, Cu, Pb, Ni, and Zn, can also be hazardous in aquatic systems (Shuhaimi-Othman et al., 2015). Copper, Ni, and Zn, along with Fe and Mn, are all trace metals necessary for metabolic reactions in organisms.

However, all metals, essential or non-essential, become toxic in high concentrations or when subjected to specific environmental conditions (Depledge et al., 1994).

Different organisms have varied sensitivities to metals due to natural biological variations from genetic make-up to individual condition. Many studies have found that

Cu is the most toxic heavy metal for fish (Gomes et al., 2009; Khangarot, 1981;

Shuhaimi-Othman et al., 2015), macroinvertebrates (Jindal and Verma, 1999), and marine gastropod larvae (Gorski and Nugegoda, 2006). However, other studies on biologically similar organisms have found Cd to be more toxic than Cu (Borgmann et al.,

1993; Keppler and Ringwood, 2002; Khan and Nugegoda, 2007; Shuhaimi-Othman et al., 2011a, 2011b, 2011c). This indicates that different organisms have varied sensitivities to metals. In most of these studies, Mn was the least toxic metal studied.

Environmental conditions and individual species response are integral to understanding aquatic metal toxicity. Wilde et al. (2006) found that lowering pH increased the toxicity of Cu and Zn to freshwater algae. However, despite increased solubility and bioavailability in acidic conditions, some metals decrease in toxicity. For example, Schubauer-Berigan et al. (1993), studying minnows and two species of macroinvertebrates, found that Cd and Ni were less toxic below pH 6.3, and increased in toxicity with increased alkalinity. In this study, Zn followed the same trend, contrary to

Schubauer-Berigan et al. (1993) indicating metal toxicity is species-dependent, regardless of pH. Acid conditions also increase the toxicity of Pb to fish (Grosell et al., 2006).

Oxidation-reduction potential, the propensity for compounds in solution to gain or lose electrons, can also strongly influence metal speciation and toxicity. In pH neutral and alkaline environments, Cr, Cu, Mn, and Fe react with water to produce low solubility oxide and hydroxide precipitants (Magalhães et al., 2015). Furthermore, in oxidizing

(electron gaining) conditions, Fe- and Mn-oxide strongly adsorb other metals such as Cu,

Pb, Ni, and Cr, sequestering them in sediment; however, this adsorption is reversible under reducing (electron releasing) conditions (Cornell and Schwertmann, 2006;

Invertsen et al, 2013; Matagi et al. 1998; Taillefert et al, 2000). Shaw et al. (1990) postulated that Cu fate in sediment may be affected more by biological activity and redox potential, however. Some metals, such as Zn, are not redox sensitive and do not change oxidation state due to ORP fluctuations (Magalhães et al., 2015).

Higher water hardness is typically associated with lower metal toxicity (Saglam et al., 2013), as Ca and Mg ions compete with metal ions for binding sites on tissues

(Kozlova et al., 2009). Some studies have shown that water hardness has more of an effect on acute, rather than chronic, toxicity for Zn in fish and invertebrates (De

Schamphelaere et al., 2005) and Cu in invertebrates as well (De Schamphelaere and

Janssen, 2004). Calcium, in high concentrations, may have more of a protective effect than Mg, as many metals compete for binding sites with Ca ligands (De Schamphelaere and Janssen, 2004; Niyogi and Wood, 2004).

Lastly, organic ions, in the form of humic and fluvic acids (Reeve, 2002), occur naturally in NS dystrophic water bodies, and actively bind free metal cations, decreasing their bioavailability (Rocha et al., 2000; Sánchez-Marín et al., 2007). Organic matter- metal complexes are less toxic than free metals, due to their higher molecular weights and reduced ability to penetrate biological membranes (Richards et al. 1999).

3.2.1.5 Metals as proxies

Redox-sensitive metals tend to be less soluble under reducing conditions, resulting in enrichments in oxygen-depleted sediment layers (Tribovillard et al., 2006). This makes U

66 and V, and to a lesser extent, Cr, useful as paleoredox proxies. Redox-sensitive elements

Ni, Cu, and Zn are mainly delivered to sediment in association with OM deposition and may be retained as the OM decays (Tribovillard et al., 2006). Nickel and Cu are particularly good proxies for organic C sinking flux, a measure of paleoproductivity.

Yuan et al. (2014) measured Cu/Ni values in three basins of Lake Erie and discovered that increases in Cu/Ni coincided with two massive algal blooms in the 1960s and 2000s, and that eutrophication may have begun as early as 1880, associated with forest clearing.

They supported their findings with stable isotope analysis.

Strontium, a non-essential metal, exists in much higher (100-fold) concentrations in seawater than freshwater (Bagenal et al. 1973; Campana, 1999; Courtemanche et al,

2005; Ingram and Sloan 1992; Rosenthal et al. 1970). It has a similar ionic radius to Ca and readily incorporates into growing bony fish tissue (i.e. otoliths, scales) A well- established relationship between otolith (fish inner ear bone) Sr/Ca and salinity allows for the study of migratory behaviour and habitat use in fish (Bagenal et al. 1973; Chang et al., 2004; Halden et al. 1995; Moreau and Barbeau 1979; Secor et al., 1995; Tzeng,

1996). Campbell et al. (1997) used otolith Sr concentrations to differentiate between anadromous and resident populations of arctic char (Salvelinus alpinus). Variations in freshwater sediment Sr concentrations may serve as a proxy for anadromous species presence. This is important, not just for biodiversity, but also for understanding the role of marine derived nutrients (MDN), such as P, N, and C, to freshwater systems.

3.2.2 Impact of logging and damming on metals in the aquatic environment

3.2.2.1 Logging and metals

Historical logging led to greatly increased allochthonous OM input to aquatic systems.

On land, trees were felled, delimbed, and often scaled (bark removed). Much of this slash

(woody debris generated during logging) ended up in nearby water bodies during removal of timber, or during rain events where overland flow was unimpeded by removed trees.

This sudden influx of OM greatly increases aquatic nutrient load, fueling algal eutrophication, and alters in-stream ORP, pH, and DO (Schaller et al., 1997; Yuan et al.,

2014). Anoxia from the decomposition of OM leads to strong complexation between Fe- oxides metals such as Cr and V, and their subsequent sequestration from the water column (Belzile and Tessier, 1990; De Vitre et al., 1994; Dzomback and Morel, 1990;

Schaller et al., 1997; Sigg et al, 1987).

Allochthonous, arboreal OM can also introduce heavy metals to aquatic systems.

Trees intake a suite of nutritional macro-components aerially and through root systems, but also require adequate quantities of micro-components, most of which are heavy metals (Parzych et al., 2017). Coniferous trees typically accumulate metals in higher concentrations than leafy species (Chrzan et al., 2010). Metals can bioaccumulate in trees, even when soil concentrations are low, and are compartmentalized preferentially in different tissues.

Wood and bark are important sinks for biologically available metals (Lepp, 1996;

Pulford and Watson, 2003). Metal concentrations in bark and wood are typically lower

68 than root tissue; however, the biomass fraction represents a much more significant proportion of total metal in the tree (Dickinson and Lepp, 1997).

Compartmentalization of heavy metals in tree tissues is strongly species dependent (Pulford and Watson, 2003; Rykowska and Wasiak, 2009). Of bark sampled from six studied pine species, Pinus armandii (Armand pine) bark accumulated the most

Mn, Fe, Cu, and Cd; Pinus sylvestris (Scots pine) the most Ni; and Pinus mugo (mountain pine) the most Cu (Rykowska and Wasiak, 2009). In needles, Parzych et al. (2017) reported that Mn accumulation was highest in Pinus banksiana (Jack pine), Fe and Cu in

Pinus wallachiana (Himalayan pine), Ni in P. sylvestris, Zn in Pinus nigra (Corsican pine), and Cd in P. armandii.

Pyatt (1997), studying P. nigra grown on untreated and sewage sludge-treated stands, found that Cu concentrations in needles were 100-fold that of concentrations in uncontaminated soil, and Cu in stems was 20-fold higher than in untreated soil. Likewise,

Zn concentrations were 6-fold higher in both stems and needles of trees grown on untreated soil. However, in needles of trees grown on sludge-treated soils, Cu accumulation was 180-fold higher than soil concentration, and Zn 25-fold, while stem concentrations remained constant with untreated trees, suggesting preferential compartmentalization of Cu and Zn in P. nigra needles (Pyatt, 1997)

Several studies have concluded that Pb is not actively accumulated by Alnus spp.

(alder), Betula spp. (birch) or Pinus spp. (pine) (Butkus and Baltrenaite, 2007; Henning et al., 2000; Korentejar, 1991;). If grown in contaminated soil, however, Pb has been shown to accumulate in stems of Platanus spp. (sycamore) (Turner and Dickinson, 1993) and

Salix spp. (willow) (Hasselgren, 1999) trees.

3.2.2.2 Damming and metals

The emplacement of a spillover dam greatly reduces flow and watershed area. Flow reduction results in increased colonization of aquatic plants and algae, coupled with reduced oxygen dissolution, and consequent reduced water column and benthic DO concentrations. Furthermore, flushing rate for the system is also reduced, and authigenic metal toxins are retained in the system for greater periods. Additionally, watershed area reduction can reduce sediment input, both quantity and diversity.

Loss of habitat due to changing environmental conditions or inaccessibility of upstream environments, as in the case of spawning anadromous fish, also significantly alters ecosystem dynamics. Gaspereau are anadromous fish native to NS that undertake annual spawning migrations numbering in the thousands of fish per river. During spawning, gaspereau release significant biomass into freshwater systems in the form of spawn, waste, and corpses, due to their often-high spawning mortality rate (O’Neil,

1980). This contributes a substantial amount of MDN to freshwater environments

(Durbin et al., 1979; Garman and Macko, 1998; MacAvoy et al., 2009; Walters et al.,

2009; West et al., 2010), increasing aquatic (Bilby et al., 1996; Gross et al., 1998;

Naiman et al., 2002; Wipfli et al., 2003) and terrestrial productivity (Ben-David et al.,

1998; Drake and Naiman, 2007; Naiman et al., 2002). Marine-derived metals, such as Sr, are deposited along with MDN and can serve as an indicator of anadromous migrations.

Fish like gaspereau that can no longer access key spawning grounds die off, and soon no populations return to dam-impacted waters.

3.2.3 Knowledge gap

Most studies on the effects of logging on metals in the aquatic environment focus on modern, or near-modern, forestry practices, and many choose to sample water rather than sediment. Missing from the literature are the impacts of historic logging practices on heavy metal concentrations in sediment, a known paleoenvironmental archive, at the time of disturbance, and the legacy those practices have on modern metal concentrations in affected systems.

Additionally, while much research has been conducted on the downstream effects of hydroelectric dams on metals, almost no literature exists on the downstream effects of spillover dams, which often completely sever rivers from their headwaters.

Furthermore, no studies that I know of investigate the combined effect of logging and damming on metals in the environment at the same site, either at a single point in time or over the span of years. This study aims to use a paleolimnological archive from

Deep Stillwater to understand how logging and damming alter metals in the environment in upland watersheds.

3.3 Methods

See Chapter 2

Data is discussed in this chapter for the following analyzed metals and metalloids: As, Cr,

Cu, Fe, Mn, Pb, Sr, U, V, Y, and Zn. The following metals were previously discussed in

Chapter 2: K, Ti, and Rb. The following metals were analyzed for, but either had >50% of the results returned as

Mo, Nd, Ni, Pr, Se, Ag, Th, Sn, and W. Mercury is known to be difficult to measure by

XRF and is better analyzed by using thermal degradation – gold amalgamation atomic absorbance spectroscopy, as outlined in United States Environmental Protection Agency

Method 7473 (2007); however, this method is destructive and was not attempted in favour of other paleoenvironmental analyses. Lastly, the following metals returned a result on the XRF, but either did not change in concentration through time, regardless of disturbance, or were inconclusive due to large spreads in the data (error): Ba, Ca, Nb, and

Zr.

3.4 Results

3.4.1 Data Quality

Duplicate XRF pseudo-replications were performed for each sediment slice. Every fifth slice was pseudo-replicated in triplicate. Plotted XRF data points are mean concentrations between pseudo-replicates at each depth, with error bars based on standard error of the averaged means.

In addition to triplicate pseudo-replication, every fifth sample was analyzed three times without removal from the XRF, to establish analytical error. Base analytical error was calculated as the average of all the standard deviations for each triplicate group of

XRF concentrations. Percentage analytical error is presented in Table 3.1. Chromium and

U had the highest mean analytical error, at 11.8% and 10.6% respectively.

Method blanks were analyzed on the XRF after every ten sediment samples. Only

As, Fe, Mn, and Ti were detected on the blank runs (Table 3.1).

Analytical Mean Method Blank

Error (%) Concentration (ppm)

As 5.64 ± 1.61 17.6 ± 2.7

Cr 11.84 ± 7.10 -

Cu 9.60 ± 8.57 -

Fe 0.49 ± 0.31 341.1 ± 128.2

Mn 1.16 ± 0.82 25.9 ± 3.4

Pb 6.98 ± 5.33 -

Sr 3.13 ± 1.86 -

U 10.60 ± 7.94 -

V 5.82 ± 3.91 -

Y 7.54 ± 7.95 -

Zn 2.91 ± 2.85 -

Table 3.1 Quality control for bulk geochemical analysis of metals on core DS3.

3.4.2 Proxy Data

Geochemical results are discussed by zone and summarized in Figure 3.1. The zones presented in this chapter are consistent with those in Chapter 2.

Zone 1 begins at the bottom of DS3 (30.5 cm) and rises to a depth of 18 cm. It is characterized by the highest concentrations of As, Fe, Mn, Zn, U, Y, Cr, and V in the entire core, as well as the highest zonal Fe/Mn and an approximately 3:1 sand to silt ratio.

Also notable is that all Pb measurements for this zone, save one, were below the LOD.

This zone is evident in the stratigraphic profile as a thick layer of homogeneous brown sediment, with bits of woody terrestrial matter throughout.

Figure 3.1 Depth and stratigraphic profile, radioisotope dates, particle size distribution and metal element trendlines for Deep Stillwater core DS3. Sediment was divided into zones and delineated with dotted lines. Highlighted areas denote sub-zones of interest.

Zone 1a (23.5 – 22.0 cm) represents a change to coarser sediment relative to background values defined by Z1, with an increase in %sand and consequent decrease in

%silt. Concentrations of As, Zn, U, and Y all decreased relative to Z1. This zone was not visibly apparent in the stratigraphic profile.

Zone 2 begins at 18 cm up to 9.5 cm depth. With metals, this zone is more difficult to reconcile, as delineated by the paleoenvironmental parameters established in

Chapter 2. Iron and Mn abruptly decrease in concentration at the zone boundary, as do

Fe/Mn and Zn, although not as sharply. Arsenic does not show any immediate change until it too decreases sharply at 15.5 cm. Uranium, Y, Cr, and V also decrease, but the trend is more gradual, a continuation of that seen at the top of Z1. Lead concentrations are still low, as in Z1, but are more frequently recorded above LOD. Copper peaked sharply at the bottom of Z2 over 1.5 cm of sediment, before decreasing back to Z1 concentrations. Arsenic, Fe, Mn, Zn, U, Y, Cr, and V all remain low at the top of Z2 and do not regain the same concentration as the lower part of the zone. The highest %sand and lowest %silt measurements occur in this zone. The zone is evident in the stratigraphic profile as two bands of lighter-coloured, visibly sandy, sediment.

Zone 2a lies within Z2 between 14.0 cm and 11.0 cm depth. It is evident in the stratigraphic profile as a heterogenous layer of silty, brown, sediment and organic-rich black sediment. Iron and Mn abruptly decrease in concentration again, before stabilizing at a lower concentration. Fe/Mn appears lower than the baseline values established by Z2; however, the data is erratic. Strontium, which increased steadily through Z1 and Z1a, decreases abruptly at the lower zonal boundary, but immediately begins increasing in

75 concentration again. Copper peaks over 0.5 cm before restabilizing. Arsenic, Zn, U, Y,

Cr, and V all stabilize at low concentrations.

Zone 3 begins at 9.5 cm depth and rises to the top of the core at 0.0 cm. This is the only sediment zone where %silt is higher than %sand. No change was observed in Fe and Mn concentrations from those in Z2, except for at the top of the sediment column where the reduced sediment is more prone to oxidation-reduction reactions. As both Fe and Mn increase across the top ~3 cm of sediment, conditions at the sediment-water interface at the time of sampling were likely oxidizing. Fe/Mn is lowest in this zone; however, it does not decrease significantly from Z2 levels until 6.5 cm depth and above.

Unlike the other redox-sensitive elements, As increases at the lower Z3 boundary before decreasing, like Fe/Mn, at 6.5 cm and then increasing toward the top of the core, similar to Fe and Mn.

Zone 3 concentrations of Pb are the highest for the entire core, increasing sharply at the lower zone boundary before stabilizing from 8.5 cm to 6.0 cm and then decreasing to the top of the core. The 6.0 cm decrease corresponds with a reduction in leaded gasoline consumption beginning in 1973.

Strontium increased immediately at the Z3 lower boundary to the highest Sr concentration in the entire core. However, it then decreased just as suddenly to low concentrations, comparable to those found at the bottom of Z1. From 8.0 cm to the top of the core, Sr appears to again be increasing steadily, but not at the same rate as in previous zones.

Concentrations of Cu, Zn, U, Y, V, and Cr did not change from those observed in

Z2. Zone 3 was evident in the stratigraphic profile as a homogeneous, loose, black, sediment layer.

Mean concentrations for all metals and PSD are summarized by zone in Table 3.2.

3.4.3 Metal and particle size data correlations

Pearson correlation coefficients (r) were determined for all metal proxies and compiled in

Table 3.3. Only coefficients with a p-value of < 0.05 were considered. A correlation was considered strong if r > 0.7 or r < -0.7 and moderate if 0.5 < r < 0.7 or -0.7 < r < -0.5.

Particle size did not seem to be much of a determinant for metal concentration.

Lead was the only metal that correlated strongly with particle size (positively with %silt and negatively with %sand) and Sr the only other metal correlation (moderately negative with %silt and moderately positive with %sand).

Strong positive correlations existed between all of Fe, As, Mn, Zn, U, Y, Cr, and

V. Conversely, none of these metals correlated with either Sr or Cu. Fe/Mn correlated strongly positive with Fe, Mn, Zn, Cr, and V and moderately positive with U and Y.

There was no correlation between Fe/Mn and As.

Lead did not correlate strongly with any elemental data; however, it did correlate moderately positive with As and moderately negative with Fe, Sr, Cr, and V. Lead was the only metal or particle size parameter to correlate with Sr (moderately negative).

Copper did not correlate with any metal or particle size parameter.

Mean (n)

Zone 1 Zone 1a Zone 2 Zone 2a Zone 3

30.5 - 18.0 cm* 23.5 - 22.0 cm 18.0 - 9.5 cm* 14.0 - 11.0 cm 9.5 - 0.0 cm silt (%) 25.5 ± 5.1 (11) 15.3 (1) 16.5 ± 6.3 (6) 23.2 ± 5.4 (3) 51.0 ± 8.6 (8) sand (%) 71.3 ± 5.2 (11) 83.2 (1) 81.5 ± 6.7 (6) 74.3 ± 5.5 (3) 44.9 ± 7.8 (8)

Pb (ppm) 4.7 ± 0.4 (22) 4.6 ± 0.4 (3) 6.4 ± 3.1 (11) 5.4 ± 1.4 (6) 27.3 ± 3.0 (17)

As (ppm) 36.7 ± 5.8 (22) 24.5 ± 3.1 (3) 16.9 ± 6.4 (11) 14.2 ± 2.5 (6) 25.5 ± 4.5 (17)

Fe (ppm) 24809 ± 1349 (22) 23154 ± 1351 (3) 13218 ± 4094 (11) 9820 ± 616 (6) 10290 ± 2008 (17)

Mn (ppm) 536.8 ± 40.0 (22) 517.2 ± 7.3 (3) 322.0 ± 79.4 (11) 265.1 ± 9.4 (6) 282.1 ± 55.4 (17)

Fe/Mn 46.3 ± 2.2 (22) 44.8 ± 2.0 (3) 40.6 ± 3.5 (11) 37.1 ± 2.4 (6) 36.6 ± 3.3

Zn (ppm) 428.1 ± 80.2 (22) 311.8 ± 57.8 (3) 169.6 ± 115.9 (11) 107.8 ± 52.6 (6) 121.6 ± 33.6 (17)

Cu (ppm) 50.0 ± 41.4 (22) 28.5 ± 5.8 (3) 36.8 ± 40.4 (11) 21.2 ± 11.1 (6) 24.9 ± 8.6 (17)

Sr (ppm) 95.5 ± 11.8 (22) 97.7 ± 3.8 (3) 112.5 ± 10.2 (11) 104.1 ± 5.4 (6) 97.4 ± 9.4 (17)

U (ppm) 136.9 ± 41.7 (22) 92.8 ± 10.6 (3) 30.5 ± 14.1 (11) 26.5 ± 1.4 (6) 38.8 ± 4.2 (17)

Y (ppm) 127.3 ± 31.0 (22) 95.3 ± 9.9 (3) 38.6 ± 12.7 (11) 33.9 ± 6.5 (6) 28.5 ± 13.1 (17)

Cr (ppm) 59.8 ± 8.9 (22) 54.7 ± 2.1 (3) 22.4 ± 10.2 (11) 15.4 ± 2.3 (6) 14.6 ± 2.6 (17)

V (ppm) 65.2 ± 5.8 (22) 62.8 ± 2.3 (3) 36.3 ± 8.4 (11) 28.3 ± 2.1 (6) 25.9 ± 4.0 (17)

* less associated sub-zone sediment

Table 3.2. Mean metal concentrations and particle size percentages for Deep Stillwater, core DS3, segregated by sediment zone. Error (expressed as ±) was derived from the standard error of averaged means at each depth.

(%) (%) (ppm)

silt sand Pb As Fe Mn Fe/Mn Zn Cu Sr U Y Cr sand -1.00

Pb 0.91 -0.91

As - - 0.63

Fe - - -0.53 0.72

Mn - - - 0.74 0.98

Fe/Mn -0.61 0.60 - - 0.84 0.72

Zn - - - 0.71 0.86 0.84 0.72

Cu ------

Sr -0.53 0.55 -0.62 ------

U - - - 0.86 0.84 0.84 0.61 0.76 - -

Y - - - 0.77 0.88 0.88 0.68 0.79 - - 0.97

Cr - - -0.52 0.76 0.96 0.95 0.76 0.87 - - 0.92 0.95

V - - -0.68 0.71 0.97 0.96 0.79 0.85 - - 0.87 0.91 0.98

Table 3.3. Pearson correlation coefficients (r) for strong (r > 0.7 or r < -0.7) and moderate (0.5 < r < 0.7 or -0.7 < r < -0.5) correlations of sediment metal data. Entries of ‘-’ indicate weak or no correlation between parameters.

3.4.4 Correlations between metals and bulk geochemistry and environmental paleoproxy data from Chapter 2

Lead was the only metal to correlate strongly (positive) with %water. The only other

%water correlation with a metal was Sr, which correlated moderately negatively.

The environmental proxies associated with clastic material (Ti, Rb, and K) all correlated strongly negative with Pb. Besides with Pb, Rb only correlated with Sr

(moderately positive). Titanium correlated strongly positive with Fe, Mn, Zn, Y, Cr, and

V and had a moderately positive correlation with U, and was the only clastic-associated element to correlate with U. Potassium correlated strongly positive with Fe and V, and moderately positive with Mn, Zn, Y, and Cr. There were no correlations between the clastic fraction elements with either As or Cu.

Strontium was the only metal element not to show any correlation with δ15N. Iron,

Mn, Zn, U, Y, Cr, and V correlated strongly positive, and As and Cu correlated moderately positive, with δ15N. This was the only correlation between Cu and a paleoenvironmental parameter. Lead correlated strongly negative with δ15N. There was no correlation between Pb and δ13C; however, the C stable isotope correlated strongly positive with U, Y, and Cr, and moderately positive with As, Fe, Mn, Zn, and V.

%C, %N, and %OM all correlated strongly positive with Pb and moderately negative with Fe and V. %C and %N also correlated moderately negative with Sr, while

%OM correlated moderately negative with Zn. C/N only displayed one correlation, moderately negative with Pb.

Like Fe/Mn, Cr/V correlated strongly positive with Fe, Zn, Cr, and V. The correlations between Cr/V and Mn, U, and Y were also positive and stronger than the correlations between Fe/Mn and those elements. Additionally, Cr/V displayed a strong positive correlation with As where Fe/Mn had no correlation with As data.

3.5 Discussion

As outlined in Chapter 2, Z1 sediment was likely deposited prior to anthropogenic disturbance, with Z1a (coarser sediment, increased Ti, K, Rb, lower %water) indicating a natural scour event, such as a large storm or flood (Figure 2.5). The 10-yr period of

80 logging, ~1900-1910, is represented by Z2 and Z2a (Figure 2.5). The sediment in Z2 was deposited during two scour events, both likely from splash dam activity, and Z2a represented a period between log drives. The volume of water required for these scour events was generated by head build-up behind temporary dams. Z3 contains modern,

‘post-disturbance’, sediment, deposited after the emplacement of the Forks River spillover dam in 1928.

3.5.1 Redox-sensitive and associated metals

All of the observed redox-sensitive metals (Fe, Mn, Zn, and As), as well as U, Y, Cr, and

V, decrease across Z2, indicating that logging activity may have significantly reduced sedimentary concentrations of these metals. The %OM trendline runs counter to the trendlines for these metals (Figure 2.5), suggesting that OM input may be diluting the concentrations of geogenic elements; however, only Fe, Zn, and V correlated negatively with %OM (Table 3.4).

While the redox-sensitive and associated metals decreased in conjunction with the logging-associated scour event (Z2), only As, Zn, U, and Y decreased during the natural scour event (Z1a). This may indicate that As, Zn, U, and Y, are associated with silt-size particles. Iron, Mn, Cr, and V did not decrease or increase, and may be more associated with clay-sized particles. However, there was no correlation between As, Zn, U, and Y with %silt, nor between Fe, Mn, Cr, and V with %clay, suggesting that concentrations of these elements may not be dependent on sediment particle size, particularly in disturbed environments.

Fe/Mn and Cr/V are both considered to be indicators of paleo redox trends

(Davison, 1993; Engstrom and Wright, 1984; Mackereth, 1966; Schaller et al., 1997).

(ppm)

Pb As Fe Mn Zn Cu Sr U Y Cr V

Cr/V - 0.74 0.87 0.86 0.84 - - 0.86 0.88 0.94 0.86

Ti (ppm) -0.81 - 0.91 0.88 0.74 - - 0.63 0.74 0.84 0.90

Rb (ppm) -0.87 - - - - - 0.61 - - - -

K (ppm) -0.82 - 0.71 0.67 0.56 - - - 0.51 0.63 0.72 water (%) 0.81 ------0.58 - - - -

OM (%) 0.86 - -0.54 - -0.54 ------0.58

δ13C (‰) - 0.51 0.58 0.58 0.67 - - 0.78 0.76 0.71 0.64

δ15N (‰) -0.76 0.51 0.83 0.83 0.78 0.50 - 0.88 0.90 0.91 0.89

C (%) 0.85 - -0.53 - - - -0.67 - - - -0.61

N (%) 0.89 - -0.52 - - - -0.65 - - - -0.60

C/N -0.56 ------

Table 3.4. Pearson correlation coefficients (r) for strong (r > 0.7 or r < -0.7) and moderate (0.5 < r < 0.7 or -0.7 < r < -0.5) correlations of metals with paleoenvironmental reconstruction data from Chapter 2. Entries of ‘-’ indicate weak or no correlation between parameters.

Both decrease at or across the lower half of Z2, which may indicate that the disruption associated with logging had an immediate oxidizing effect on Deep Stillwater. Fe, Mn, and As trend upward at the top of the sediment core. This ionic diffusion gradient, as described by Klinkhammer et al. (1982), occurs when metals reduce into solution in deeper, anoxic sediments, and precipitate in upper, oxic layers. Based on the Fe/Mn and

Cr/V data, damming did not have an immediate effect on ORP; however, the system became significantly more oxidizing at ~5 cm depth.

Oxidation-reduction reactions in the environment are complex, especially so at sediment-water boundaries in lake and marine systems (Pufahl, 2010). It can be difficult to ascertain the specific effects of certain events or sedimentary components (Khalid et al., 1978). Much depends upon the presence of sulphides, oxides, and hydroxides in the system. For instance, under reducing conditions, many metals (Fe, Pb, Cd, Cu, Ni, Zn) form highly insoluble metal sulphides (Kosolapov et al., 2004; Krauskopf, 1956;

Sobolewski, 1999; Stumm and Morgan, 1981), thereby sequestering those metals in sediment. However, under oxidizing conditions, the oxidation of sulphide to sulphate releases these metals into the water, increasing their bioavailability (Engler and Patrick

Jr., 1975; Gardiner, 1974). Contrary to this, Fe- and Mn-oxides and hydroxides adsorb and co-precipitate trace metals (Zn, Cu, Cr(III), As) under oxidizing conditions (Brooks et al., 1968; Bartlett and Kimble, 1976; Dreiss, 1986; Jenne, 1968; Otte et al., 1989;

Schroeder and Lee, 1975; Smedley and Kinniburgh, 2002; St-Cyr and Campbell, 1996;

Stumm and Morgan, 1981) and these bound metals can desorb into the aqueous state under reducing conditions (Korte, 1991; Korte and Fernando, 1991).

Furthermore, the presence of organics greatly modifies the effects of sulphides, oxides, and hydroxides on trace metal solubility (Gambrell, 1994; Morel et al., 1973).

Organic compounds, under anaerobic conditions, can lower the oxidation state of some metals (Mn, Fe, Co, Ni), increasing their solubility by several orders of magnitude (Stone and Morgan, 1987). Sulphide analysis was beyond the purview of this study but could be used to better understand the effect of logging and damming on Deep Stillwater sedimentary metal concentrations.

With the decreased flushing rate and increased productivity (see Chapter 2) at

Deep Stillwater, a shift to more oxidizing conditions was unexpected. Local accounts of the fluvial lake in summer describe a near-stagnant water body, which strongly suggests a reducing aquatic environment. The onset of lacustrine conditions (stratification and minimal flushing) may be aiding in the retention of DO in the deep parts of the basin and maintaining a more oxidizing environment. Also, groundwater through-flow may have more of an influence on the system when the flushing rate is reduced, resulting in cooler and more oxygenated hypolimnetic water. Another hypothesis is that Deep Stillwater may have become shallower post-disturbance, allowing for greater diffusion of DO from surface waters to sediment.

3.5.2 Strontium

The Sr trendline is dissimilar to all other measured parameters and may reflect prehistoric and historic anadromous fish residency in the WBAR.

Strontium commonly occurs in marine environments at concentrations 100 times higher than freshwater. It is not known to be an essential element to fish, and therefore its concentration in fish (or any other organism) is likely a reflection of the environment of residency. As such, the high Sr values in Deep Stillwater are likely not associated with a specific freshwater species bioconcentrating available Sr in the watershed. Strontium is also not an element associated with the local bedrock or overlying unconsolidated sediment (Boner et al., 1989; Moore et al., 2009). For these reasons, Sr concentrations in lake sediment may have the potential to be an indicator of the transfer of marine OM into freshwater environments. Most paleolimnological records in southwestern NS contain some Sr. Background Sr concentrations in Halifax, NS, lake sediments are estimated at

84 about 90 ppm (D. Dunnington, unpublished data, March 14, 2018). The Deep Stillwater record indicates an increase beyond this level at about 24 cm depth in the core, coincident with tidal expansion in the Bay of Fundy and the possible removal of a barrier limiting saltwater in the Minas Basin (Figure 3.2; Shaw et al. 2010).

Shaw et al. (2010) analyzed a suite of 148 radiocarbon dates from around the

Minas Basin and hypothesized that the Minas Basin and Avon River may have been isolated from the Bay of Fundy until a catastrophic marine incursion ca. 3400 BP. This might explain the increasing Sr trend from Z3 into Z2, as anadromous species would have been able to better utilize the watershed after 3400 BP. This research was supported by the Mi’kmaq, First Nations, legend of Glooscap, recounted in Shaw et al. (2010) as follows:

One day, Glooscap decided that he wanted to take a bath. He ordered Beaver to build a dam across the mouth of the bay to hold the ocean water so that there would be lots of water for his bath. Beaver did as Glooscap asked and the bath was made but Whale was unhappy because now the water did not flow as before. "Why has the water stopped?” Whale cried. Glooscap hearing him and not wanting Whale to be upset, told Beaver to break the dam and release the water. Beaver liked the dam he had made so he was slow to begin taking it apart. Whale became impatient because he wanted the water as it was before and he started using his great tail to break the dam apart. This caused the water to flow back and forth with such force that it continues so until this day.

Shaw et al. (2010) argued that the actions of Whale could be ascribed to a major storm-surge event ca. 3400 BP, leading to the bursting of a gravel barrier across the mouth of the Avon River, and subsequent massive tidal incursion. Although we did not

Figure 3.2. Examination of the Sr trendline for Deep Stillwater compared to historic disturbance events.

obtain a 14C date around this time, the increasing Sr trendline at approximately 24 cm depth appears to support the Glooscap legend and the findings of Shaw et al. (2010).

Strontium levels stay consistently high (above 90 ppm) from 24 cm – 9 cm depth in the core, a time span until the construction of a causeway at the mouth of the Avon

River. The sharp decrease at Z2a, during the period of low energy between the two logging scour events (Z2), may indicate a short-term barrier to fish passage up the river, likely the emplacement of temporary, head-building, splash dams.

The decrease at Z3 may also be associated with the construction of the Forks

River dam in addition to the installation of the causeway across the mouth of the Avon

River at Windsor, effectively blocking fish passage upriver. Water flow through the narrow gates in the causeway is typically well above the maximum swim speed of

86 gaspereau; however, up to thirty minutes of lower velocity flow occurs, sufficient to keep a small population of gaspereau in the Avon River (Daborn and Brylinksky, 2004).

According to reports, historic runs of gaspereau up the WBAR, before the causeway’s construction, were much greater in number (Kolstee, 2003).

3.5.3 Copper

Only trace amounts of Cu are present in the bedrock and till around Deep Stillwater

(Boner et al., 1989; Moore et al., 2009), and the two peaks in Cu concentration in Z2 and

Z2a are likely derived from OM input. Copper is an essential nutrient for plants that has been shown to bioaccumulate in coniferous trees; thus, the increased Cu concentration is most likely associated with allochthonous OM derived from logging activity.

Copper fate in sediment is poorly understood and can be influenced by redox,

DO, and biological activity (Diks and Allen, 1983; Shaw et al., 1990), limiting the interpretation of Cu trends in lake sediment. Sedimentary Cu can be mobilized under oxidizing conditions and released into the water column (Brown, 1999; Engler and

Patrick Jr.,1975; Gardiner,1974); however, Cu complexation with Fe- and Mn-oxides under oxidizing conditions causes it to be precipitated and sequestered (Bartlett and

Kimble, 1976; Brooks et al., 1968; Dreiss, 1986; Jenne, 1968; Otte et al., 1989;

Schroeder and Lee, 1975; Smedley and Kinniburgh, 2002; St-Cyr and Campbell, 1996;

Stumm and Morgan, 1981).

3.5.4 Lead

Like Cu, only trace amounts of Pb are present in the bedrock and soils around Deep

Stillwater (Boner et al., 1989; Moore et al., 2009). The increase in sedimentary Pb can be

87 attributed to atmospheric deposition from the introduction and subsequent phasing-out of leaded gasoline (Dunnington 2011; Gallagher et al. 2004). Evidence for atmospheric Pb contribution can be obscured by wastewater input (Laperriere et al., 2007) or industrial processes (Couillard et al. 2007; Merilainen et al. 2001; Salonen et al. 2006) in a watershed; however, these processes did not occur at Deep Stillwater. This apparent evidence of continuous sedimentation from ~1900 onwards indicates that Deep Stillwater likely experienced very low flushing rates, similar to lakes.

3.6 Conclusions

1) Damming had a significant effect on system energy, reducing particle size of

sediment, which allows for increased adsorbsion of metals to clastic particles (see

Chapter 1). Additionally, the increased OM content of Deep Stillwater, post-

damming, also increases metal retention in sediment, due to complexation with

precipitated OM. Coupled with the lower flushing rate, post damming, the retention

and sequestration of metals in Deep Stillwater sediment should be higher than pre-

disturbance. However, except for Pb, all metals decreased post-disturbance. It is

likely that the loss of geogenic input from the larger watershed after dam

emplacement had a significant effect on metal input to the system, and despite the

increased ability of Deep Stillwater for metal retention, geogenic metal input is so

reduced as to lead to lower sedimentary metal concentrations.

2) The redox regime in Deep Stillwater has shifted to a more oxidizing environment.

The implications for this are unclear and would require investigation of sedimentary

sulphides and hydroxides to better understand. Given that almost all metal

concentrations in sediment decreased post-disturbance, and the conditions are now

more oxidizing, it might imply that those metals were bound to sulphides and released

into the water column with the onset of oxidizing conditions. This is speculative,

however, without data on sulphide concentrations in sediment.

3) Sedimentary Sr concentrations are a potential indicator of anadromous fish

occupation of a system. It is unclear how well this technique would perform in

regions with geogenic sources of Sr or with different species of anadromous fishes,

but in this case, with the high biomass input of gaspereau into the freshwater system,

Sr in sediment appears to be an indicator of fish presence. This is particularly useful

for studying past fish migrations, as the more common methods of otolith or scale

analysis are only applicable to modern populations. Understanding the disturbance

history of the system is also integral to interpreting the sedimentary Sr record.

4) The characteristic Pb curve obtained supports the hypothesis that, with a reduction in

watershed size and flow associated with hydroelectric development, Deep Stillwater

is behaving as a lake and experiences low flushing rates.

5) Logging slash introduced to the system appears to cause temporary spikes in Cu

concentrations.

4.0 Thesis conclusions

1) Fluvial lakes can be effective sediment archives:

• The establishment of a Pb-curve at the top of the core is characteristic of lake

sediments in the industrialized world and indicates that a fluvial lake, such as

Deep Stillwater, can act as an effective archive of lake sediment and

environmental change, much as a more typical lake would.

• Understanding the disturbance history of fluvial lakes is of great importance when

analyzing the sediment record. Sediment geochemical and proxy analysis would

likely not have been sufficient to tell the story of Deep Stillwater, but was highly

complementary to local knowledge, historical records, and First Nations accounts

and legends.

• Caution is advised when interpreting radiocarbon dates obtained from fluvial lake

sediments, particularly in systems that have experienced watershed-level

disturbance, such as extensive logging. Inherited C from heavy floods, erosion, or

anthropogenic activity complicates sediment chronology and could lead to

incorrect analyses.

2) Impact of historical logging:

• The build-up of head behind temporary splash dams, and the consequent violent

removal of those structures, significantly altered elemental concentrations,

particle size, and system energy, leading to a scouring of the lake-bed and

unconformities in the sediment record. Anadromous visitation to Deep Stillwater

and upper parts of the watershed was also likely disrupted by logging practices.

• Widespread disturbance of the WBAR watershed led to the introduction of

inherited C to Deep Stillwater, complicating radiocarbon dating.

• The influx of allochthonous OM to Deep Stillwater, in the form of logging slash,

shifted the carbon-nitrogen balance in the system. Decomposition of

allochthonous OM and a sudden influx of nutrients likely led to a period of

eutrophia in Deep Stillwater, with the potential for anoxia. Furthermore, metals

such as Cu, and other contaminants sequestered in trees, would have been

introduced to the aquatic system and if not incorporated into sediment, perhaps

made bioavailable.

• The oxidation-reduction potential of Deep Stillwater also shifted during logging,

becoming more oxidizing. This would have cascading implications for

bioregulatory processes in the ecosystem, as well as biogeochemical dynamics

and element speciation and subsequent toxicity and bioavailability.

3) Impact of damming and watershed reduction:

• Sediment structure became more organic, with less clastic particles, and particle-

size overall became smaller, more silt-sized, because of the emplacement of the

Forks River Dam. Additionally, separation from the greater watershed reduced

sedimentary clastic provenance to only the nearby bedrock and till.

• Damming either further oxidized Deep Stillwater or reinforced the increasingly

oxidative state of the system after logging.

• Not only did %OM increase post-damming, but the types of organics were also

altered. Both %C and %N both increased after damming, likely from increased

algal and macrophytic primary productivity. Higher levels of bacterial activity in

Deep Stillwater are the likely cause of reduced δ13C and δ15N, despite the higher

concentrations of C and N. Bacterial activity could be promoted by the lower flow

rate and possibly higher temperature of Deep Stillwater, as well as the increased

nutrient input, and possibly changes to the redox regime.

• The sharp decrease in Sr, along with local knowledge of fishing along the WBAR,

point to a sudden loss of anadromous species after damming.

4) Reduction in anadromous visitation:

• Sedimentary Sr seems to be an effective proxy for the presence of anadromous

fishes in Deep Stillwater, particularly with gaspereau, which provide a high

biomass contribution to lakes and rivers.

• Loss of anadromous species would also result in the loss of MDN typically

deposited at Deep Stillwater.

5) Caveats and application to management:

• The redox and nutrient changes to Deep Stillwater have likely resulted in an entire

ecosystem shift. Certainly, local accounts of changes to the fishery would support

this. With the Forks River spillover dam emplaced, there is likely no way to return

Deep Stillwater to its former ecological state.

• Metals appear to have mostly decreased in concentration at Deep Stillwater, but

this may not be as beneficial as it seems. Changes in redox conditions, particle-

size, DO, and OM all have significant impacts on metal bioavailability and

toxicity in aquatic environments. An investigation of metals that includes

elemental speciation, sulphides, oxides, and hydroxides would better inform on

the threat of metals to wildlife, and potentially humans, at Deep Stillwater.

• Further paleolimnological studies on fluvial lakes would benefit from a more

comprehensive suite of 14C analyses to better understand the role of inherited C

and sediment scour in these systems.

• Fe/Mn and Cr/V redox proxies indicate a more oxidizing environment post-

disturbance, which was unexpected at Deep Stillwater due to the lower flushing

rate and increased productivity. Other factors such as groundwater input, depth, or

the onset of stratification may play a vital role in redox dynamics of fluvial lakes.

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