ASSESSING THE CHEMICAL AND BIOLOGICAL RECOVERY OF KILLARNEY PROVINCIAL PARK LAKES FROM HISTORICAL ACIDIFICATION
By:
Erin Kiyoko Suenaga
A thesis submitted to the Department of Biology in conformity with the requirements for the degree of Master of Science
Queen’s University
Kingston, Ontario, Canada
July, 2018
Copyright © Erin K. Suenaga, 2018 Abstract
Since the mid 1900s, acidification has impacted water quality and threatened the ecological integrity of thousands of lakes and streams across Eastern North America and Europe.
After the implementation of industrial emission reductions programs in the late 1960s, chemical recovery of historically acid-damaged lakes was observed, but a lag in biological recovery has been partially attributed to changes in multiple environmental variables, such as warming climate, shoreline development, and the introduction and spread of invasive species. To assess the continued recovery of historically acidified lakes, forty-four lakes were sampled for zooplankton and water chemistry in and around Killarney Provincial Park during peak emissions in 1972-73, through the decades after emission reduction programs were implemented in 1990,
2000, 2005, 2011, and 2016. We assessed changes in both univariate and multivariate zooplankton community metrics through time, and evaluated recovery using a reference lake approach that included 8 circumneutral lakes within Killarney Provincial Park and 55 non- acidified lakes in Algonquin Provincial Park. In addition, we assessed the relative importance of local biotic and abiotic variables in shaping recovering zooplankton communities in Killarney and Algonquin Provincial Parks. We found strong evidence for continued chemical and biological recovery in acidified lakes in Killarney Provincial Park. Species richness and diversity increased in acid-recovered lakes to values statistically indistinguishable from those of our reference lakes, and multivariate-based community composition shifted towards a community structure more similar to reference lakes. Several variables were identified as important drivers of zooplankton community structure, including pH and ion concentrations, nutrient concentrations, fish community, water clarity, maximum lake depth, and surface area, with environmental variables accounting for less variation in communities through time. Overall, these results indicated that recovery is still progressing in historically acidified lakes, and unlike
ii similar Canadian Shield communities that did not experience severe acidification, pH and its legacy effects are still acting as primary drivers of zooplankton community structure in Killarney
Provincial Park lakes.
iii
Co-Authorship
This thesis conforms to the Manuscript Format as outlined by the School of Graduate Studies and
Research.
Chapters 1 & 2 of this thesis were edited by Dr. Shelley Arnott. Historical zooplankton and water chemistry data used in this thesis was collected and published by Sprules (1975), Locke and colleagues (1994), Holt and Yan (2003), and Gray and colleagues (2012).
iv Acknowledgements
First and foremost, I would like to thank my supervisor, Shelley Arnott for her seemingly never-ending patience and support throughout my (extended) Master’s project. You provided me with amazing opportunities both here at Queen’s and elsewhere, and for that I will forever be grateful. I appreciate everything you have done for me and attribute my very positive experience with grad school to the support from this wonderful lab! I have so much respect for the work you do and really enjoyed having a strong female mentor in science guiding and supporting me through this experience.
I would also like to thank the members of my committee, Dr. Andrew Paterson and Dr.
Paul Grogan, for providing feedback and suggestions during the last couple of years. I would also like to extend a big thanks to Dr. Lonnie Aarssen who generously agreed to be an examiner for my defence last minute. I am grateful to everyone at the Dorset MOECC who performed all of the water chemistry analysis for my research in a very timely manner. Thank you to the staff at
Killarney Provincial Park who accommodated my research in the summer of 2016 – all of your help and support allowed for a stress- and incident-free field season, which I still think is quite the feat! A very big thanks to my field assistant, Aaron Sneep, for spending two months sampling 47 lakes in Killarney Provincial Park with me - the field season was fun and went
(surprisingly) smoothly thanks to your positive attitude and hard work throughout the summer! I would also like to thank the staff and members of the PEARL lab, DESC, and Algonquin
Provincial Park for helping me collect samples in August 2015 and surviving a microburst. I would also like to thank Dr. Steve Sadro and Dr. Adrianne Smits for their encouragement and support while I worked with them in California.
Thank you to my fellow labmates in the Arnott lab, including Melanie Overhill, Caleb
Yee, James Sinclair, Mike Lavender, Sarah Hasnain, Shakira Azan, Michele Nicholson, and
v Amelia Cox, for their support and company throughout the years. From zooplankton identification, field work prep, statistical analyses, or just chatting over coffee – you were all there to help me out, and I greatly appreciate everything you have all added to my grad school experience!
Finally, thank you to my friends and family for their unconditional support throughout my graduate studies and all of the years before that! To my parents, Shawn and Nancy, thank you for supporting me and always encouraging me to push myself. I would not be where I am today without you, and I become more grateful everyday reflecting on everything you have done for me. I am incredibly lucky to have such an amazing group of people in my life and I look forward to sharing whatever comes next with all of you!
vi Table of Contents Abstract .………………………………………………………………………………………….ii
Co-authorship ……………………………………………………………………………………iv
Acknowledgements .……………………………………………………………………………. v
List of Tables ..…………………………………………………………………………………. ix
List of Figures ………………………………………………………………………………….. x
List of Abbreviations ……………………………………………………………………………xi
Chapter 1: General Introduction …………………………………………………………….. 1 Ecological stressors in freshwater ecosystems …………………………………………. 1 History of Acidification ………………………………………………………………… 2 Recovery of freshwater systems from acidification ……………………………………. 4 Zooplankton as indicators of water quality …………………………………….. 4 Defining and assessing recovery ……………………………………………….. 5 Chemical recovery of acidified lakes ……………………………………………6 Killarney Provincial Park: chemical recovery ………………………………….. 7 Biological recovery of acidified lakes ………………………………………….. 9 Killarney Provincial Park: biological recovery ………………………………….9 Limitations to recovery and factors known to structure zooplankton communities in lakes of the Canadian Shield…………………………………………………………...... 10 Thesis Objectives ……………………………………………………………………….14
Chapter 2: Assessing the chemical and biological recovery of historically acidified lakes in Killarney Provincial Park, 1972-73 to 2016 …………………………………….15 Introduction ……………………………………………………………………………..15 Methods ………………………………………………………………………………...19 Site description …………………………………………………………………19 Sampling design .………………………………………………………………..20 Zooplankton sampling in 2016 .…………………………………………………21 Water chemistry sampling method in 2016 …………………………………….22 Lake categories …………………………………………………………………23
vii Statistical analyses ……………………………………………………………...23 Results …………………………………………………………………………………..29 Chemical recovery of Killarney Provincial Park lakes .………………………….29 Biological recovery of Killarney Provincial Park lakes ………………………...30 Environmental variables shaping zooplankton community structure …………..32 Community comparisons with Algonquin Provincial Park …………………….33 Discussion ……………………………………………………………………………….35 Chemical recovery of Killarney Provincial Park lakes ………………………….35 Biological recovery of Killarney Provincial Park lakes ………………………...38 Factors influencing zooplankton community structure and recovery …………..41 Conclusions …………………………………………………………………………….44
Chapter 3: General Discussion ……………………………………………………………….67
References …………………………………………………………………………………….. 70
Appendix A: Killarney Provincial Park physical lake data …………………………………... 83
Appendix B: Killarney Provincial Park water chemistry data 1972-73 to 2016 ………………. 84
Appendix C: Killarney Provincial Park zooplankton species abundance data 1972-73 to 2016 106
Appendix D: Algonquin Provincial Park physical and chemical lake data 2015 ……………...121
Appendix E: Algonquin Provincial Park zooplankton species abundance data 2015 ……….. 125
Appendix F: Killarney Provincial Park macroinvertebrate data………………………………. 135
Appendix G: Killarney Provincial Park fish data ……………………………………………..137
Appendix H: Killarney & Algonquin PP water chemistry sample comparisons …………….. 145
Appendix I: Killarney & Algonquin PP physical and chemical variable comparisons ……….. 147
Appendix J: Ministry of Environment and Climate Change water chemistry protocols …….. 148
Appendix K: Water quality correlation matrices …………………………………………….. 149
Appendix L: Univariate zooplankton communty metrics dredge tables …………………….. 151
Appendix M: Killarney Provincial Park PCA plots by year ………………………………… 159
viii List of Tables
Chapter 2
Table 2.1. Methodological details for zooplankton sampling in 44 Killarney PP lakes ………. 46
Table 2.2. Scores from first two axes of principal component analysis on measures of water quality of 44 lakes in Killarney PP ……………………………………………….. 47
Table 2.3. Summary of Mann-Kendall trend tests on select water chemistry parameters from the 44 survey lakes in Killarney PP …...……………………………………………… 48
Table 2.4. Zooplankton species abbreviations used for PCA and RDA plotting ………...... 49
Table 2.5. Summary of top models of multiple linear regression analyses on zooplankton community metrics explained by environmental and physical variables ………..50
Table 2.6. Summary of top models of multiple linear regression analyses on changes in zooplankton community metrics explained by changes in water quality ………….51
Table 2.7. Summary of permutation tests from RDA for Killarney PP ………………………..52
ix List of Figures
Figure 1.1. Map of surveyed lakes in Killarney Provincial Park …………………………….. 53
Figure 2.1. Zooplankton species occurrences in Algonquin and Killarney PP ………………. 54
Figure 2.2. Comparison of H+ concentration in 1972-73 and 2016 …………………………. 55
Figure 2.3. Comparison of water chemistry PCA axis 1 scores in 1972-73 and 2016...... 56
Figure 2.4. Principal component analysis biplots on water chemistry data in a) 1972-73 and b) 2016 for 44 lakes in Killarney PP ……………………………………………………………... 57
Figure 2.5. Temporal trends in zooplankton community metrics categorized by changes in water quality …………………………………………………………………………………………..58
Figure 2.6. Comparison of PCA axis 1 scores for zooplankton species composition in 1972-73 and 2016 ………………………………………………………………………………………. 59
Figure 2.7. Principal component analysis biplots on zooplankton species abundance in a) 1972- 73 and b) 2016 ………………………………………………………………………………… 60
Figure 2.8. Comparison of relative abundances of crustacean zooplankton groups in 1972-73 and 2016 ………………………………………………………………………………………..61
Figure 2.9. RDA triplots of zooplankton species abundances constrained by environmental and physical lake variables in a) 1972-73 and b) 2016 ………………...... 62
Figure 2.10. Comparison of univariate zooplankton community metrics between Algonquin PP lakes and Killarney PP lakes …………………………………………………………………...63
Figure 2.11. Comparison of univariate zooplankton community metrics between Algonquin PP lakes and Killarney PP lakes categorized by water quality changes …………………………... 64
Figure 2.12. Principal component analysis biplot of Algonquin and Killarney PP zooplankton species abundances …………………………………………………………………………….. 65
Figure 2.13. RDA triplot of zooplankton species abundances and constraining environmental variables in a) Killarney PP and b) Algonquin PP……………………………………………….66
x List of Abbreviations
[H+] – Hydrogen ion concentration AIC – Akaike’s Information Criterion ANOVA – Analysis of variance Ca – Calcium Cl – Chloride DF – Degrees of Freedom DOC – Dissolved organic carbon Fe – Iron GLM – Generalized linear model GLMM – Generalized linear mixed model MANOVA – Multivariate Analysis of Variance PP – Provincial Park PC1 – Principal component axis 1 PC2 – Principal component axis 2 PCA – Principal components analysis RDA – Redundancy analysis SD – Standard deviation SE – Standard error Secchi – Secchi disk depth
SO4– Sulphate Si – Reactive silicates TKN – Total Kjeldahl Nitrogen TP – Total phosphorus TukeyHSD – Tukey’s Honest Significant Difference VIF – Variance Inflation Factor
xi CHAPTER 1
General Introduction
Ecological stressors in freshwater ecosystems
Understanding how communities respond to a changing environment from both natural and anthropogenic disturbances is an indelible challenge in ecology and will remain a concern as the human population continues to grow. Freshwater ecosystems are some of the most threatened in the world, with biodiversity loss occurring at a faster rate than any terrestrial system (Sala et al.
2000). This loss can be attributed to the increasing number of challenges imposed by multiple environmental and anthropogenic stressors (Dudgeon et al. 2006; Ormorod et al. 2010; Jackson et al. 2016). A stressor, according to Vinebrooke et al. (2004), is “an abiotic or biotic variable that exceeds its range of normal variation, and adversely affects individual physiology or population performance in a statistically significant way”. Over the last several decades, acidification has been a prominent stressor impacting the water quality and threatening the ecological integrity of freshwater ecosystems (Schindler 1988; Stoddard et al. 1999; Driscoll et al. 2001; Keller et al.
2001). As communities continue to recover from this historical disturbance, they are also facing novel challenges associated with climate change, the introduction and spread of invasive species, and shoreline development (Keller 2009; Palmer et al. 2011, 2013). The human-induced degradation of freshwater ecosystems should be of utmost concern for global conservation given the invaluable ecological, financial, and health services that they provide (Dillon et al. 2007).
Increasing efforts to better understand the cumulative and interactive effects of the factors impacting freshwater communities is necessary to ensure the proper management and sustainability of this invaluable resource (Keller 2009; Palmer et al. 2013).
1 History of Acidification
The impacts of anthropogenic acidification have continued to be of interest throughout
North America and Europe since its spotlight in the 1970s and 1980s (Schindler 1988; Driscoll et al. 2001). Acid rain occurs when industrial emissions containing sulphur dioxide and nitrogen oxides are released into the atmosphere and react with the water, oxygen, and other chemicals, to form precipitation with a pH<5. Regions in midwestern and eastern North America, including south central Ontario, Quebec, Vermont, Adirondacks, and Atlantic Canada, as well as regions in
Europe, including Great Britain, Scandinavia, and Germany, all experienced some degree of acid deposition from industrial sulphur emissions produced primarily by mining and smelting complexes (Stoddard et al. 1999). As a result of increased levels of acidity, we observed alterations in community composition (reduced species richness and biomass) and functioning
(lowered primary production, nutrient cycling, and decomposition rates) in terrestrial and aquatic ecosystems, which caused concern for both industries and governments (Beamish and Harvey
1972; Gordon and Gorham, 1963). National and international environmental regulations were implemented, such as the United Nations Economic Commission for Europe’s Convention on
Long-Range Transboundary Air Pollution Sulphur Protocols signed in 1979, to reduce emissions and resulted in widespread declines of acid deposition across the continents (Stoddard et al. 1999;
Skjelkvåle et al. 1998; Driscoll et al. 1998).
In Canada, the discovery of nickel-copper ore in 1883 in Sudbury, Ontario, led to intensive industrial emissions from crude mining and smelting practices (Potvin and Negusanti
1995). Smelters released over 2.5 million tonnes of sulphur dioxide every year during their peak operation in the 1950s and 1960s (Gunn 1996; Snucins et al. 2001) and lakes likely began acidifying as early as the 1920s (Dixit et al. 1992). Neary and colleagues (1990) estimated that
2 over 19 000 lakes in Ontario were acidified to a pH < 6.0 and many of these lakes were considered “critically acidic” with pH levels below 4.5. After several decades of intensive mining activity, it was identified that the sulphur dioxide and nitrogen oxide emissions, along with heavy metal contamination of surrounding terrestrial and aquatic habitats, was causing the decline and, in severe cases, extirpation of many fish, zooplankton, invertebrate, phytoplankton, and shorebird species (Beamish and Harvey 1972; Gorham and Gordon 1963; Schindler 1988).
In an experimentally acidified lake in northwestern Ontario, Schindler and colleagues (1985) observed shifts in the relative abundance of phytoplankton species, decreases in the abundance of fish and crayfish, and the disappearance of acid-sensitive zooplankton species with increased acidity. The observed environmental impacts of acidification prompted the introduction of national legislative action, including the 1991 Canada-US Air Quality Agreement. This led to considerable declines in acid deposition from the Sudbury smelters in Ontario - approximately
90% decrease from peak emissions (Gunn et al. 1995). Some natural chemical recovery of lakes was documented as early as the 1980s (Keller et al. 1986), and studies of the biological recovery of these damaged systems followed (Locke et al. 1994; Arnott et al. 2001; Findlay 2003; Holt and
Yan 2003; Yan et al. 2004; Graham et al. 2007; Gray et al. 2012).
The recovery from acidification in Sudbury is considered a redemption story, and is being used as a model for other regions that are still experiencing high levels of atmospheric industrial pollution, such as China and South America (Larssen et al. 2006). Although the effects of acid deposition in the Sudbury area have been studied extensively over the last 50 years, the continued recovery of this region requires further assessment as these lakes are continually experiencing additional stressors, such as climate change, the spread of invasive species, and calcium decline, that could be acting as barriers to recovery (Gray et al. 2012; Palmer et al. 2013).
3 Recovery of freshwater systems from acidification
Zooplankton as indicators of water quality
In this study, I have used crustacean zooplankton to track ecological changes associated with recovery from acidification in Killarney Provincial Park lakes. Crustacean zooplankton
(Phylum Arthropoda, Subphylum Crustacea) are found in all freshwater systems and have been used as indicators of ecosystem health due to their ability to respond quickly to disturbances and their importance to freshwater food webs (Marmorek and Korman 1993; Korhola and Rautio
2001; Walseng et al. 2003). Zooplankton are split into two classes: Brachiopoda (commonly referred to as cladocerans), and Copepoda. The cladocerans (including the orders Anomopoda,
Ctenopoda, Haplopoda, and Onychopoda) are generally enclosed by a calcium carbonate carapace, are mostly filter feeders, and reproduce primarily by parthenogenesis in favourable conditions (Korhola and Rautio 2001). The copepods consist of three orders, Calanoida,
Cyclopoida, and Harpacticoida, that are generally omnivorous, and reproduce sexually (Covich and Thorp 2001). Zooplankton also produce resting eggs or stages that can remain viable in the lake sediments for many decades, resulting in a stored bank of diversity that can influence community dynamics (Brendonck and De Meester 2003). Zooplankton also provide a critical link between the primary producers (phytoplankton) and higher trophic levels (fish and macroinvertebrates) in freshwater systems (Brooks and Dodson 1965; Hessen et al. 1995).
Zooplankton have short generation times, allowing them to respond quickly to changes to their environment, and certain species are more sensitive to environmental changes, which make them useful indicators of the physicochemical environment (Walseng et al. 2001, 2003).
Crustacean zooplankton have been particularly useful indicators of recovery in lakes surrounding the Sudbury region since pH was known to alter community composition (Keller et
4 al. 2002; Findlay 2003). Daphnia retrocurva, Daphnia mendotae, Epischura lacustris, and
Skistodiaptomus oregonensis are particularly sensitive to acidification, whereas Leptodiaptomus minutus, Bosmina longirostris, and Diaphanosoma birgei dominated acidic North American lakes (Havens et al. 1993; Walseng et al. 2003). For example, Daphnia mendotae populations have been observed to decline rapidly with pH below 6.2, and therefore are rarely found in acid lakes (Keller et al. 1990). Increased acidity in lakes has been shown to impact zooplankton communities both directly and indirectly by impairing reproduction and survival (Brett 1989) and altering biotic interactions (Frost et al. 2006). The sensitivity of zooplankton communities to changes in their environment and their relatively high species richness and abundance conducive to using multivariate statistical analysis (Yan et al. 1996) made them an ideal study system for evaluating the recovery of acidified lakes in Killarney PP within a multiple stressor framework
(Palmer et al. 2013).
Defining and assessing recovery
To assess the recovery of damaged communities, it is important to choose the appropriate benchmarks and metrics to assess. Gray and Arnott (2009) summarized the three main approaches that have been previously used to assess the recovery of freshwater communities from acidification: (1) comparing pre-disturbance and post-disturbance community metrics using historical or paleolimnological data, (2) comparing recovering lakes to reference lakes that are within the same region, but not impacted by the disturbance, or (3) using a temporal sampling approach that allows researchers to examine changes in community metrics through time. Gray and Arnott (2009) suggest that an ideal assessment of recovery would incorporate all three approaches due to their individual limitations. Using pre-disturbance conditions as a benchmark for recovery does not take changes in other environmental factors during that time period into
5 consideration, using reference lakes requires finding lakes that accurately reflect undamaged conditions, and temporal sampling lacks a recovery benchmark. As suggested by Gray and
Arnott (2009), I employ both a temporal and reference lake approach, and refer to published paleolimnological studies (Smol et al. 1998; Keller et al. 2003; Labaj et al. 2015) to assess the continued recovery of lakes in Killarney PP from historical acidification.
The univariate zooplankton community metrics generally used to assess recovery include species richness, species diversity, evenness, and the total and relative abundance of zooplankton species (Gray and Arnott 2009). Species richness and diversity have been shown to be consistently lower in acid-damaged lakes (Yan et al. 1996; Holt and Yan 2003; Gray et al. 2012); therefore, it is expected that species richness and diversity would increase through time as communities recover and become more similar to the reference lake conditions (Marmorek and
Korman 1993). Many studies have also incorporated multivariate analyses using the relative abundance of zooplankton species, such as principal components analysis (PCA) and canonical analysis (CA) (Locke et al. 1994; Keller et al. 2002; Holt and Yan 2003; Yan et al. 2004). When comparing the accuracy of univariate and multivariate metrics for assessing recovery, Yan and colleagues (1996) demonstrated that using relative abundances of species with multivariate methods was the best indicator of recovery, followed by comparisons of species richness and diversity.
Chemical recovery of acidified lakes
Substantial chemical recovery has been observed (i.e., decreased acidity, sulphate, and metal concentration) across lakes in Eastern North America, Scandinavia, and central Europe, as a result of lower rates of acid-deposition with the introduction of emission reductions programs or, in the case of Scandinavia, extensive liming programs (Gunn and Keller 1998; Keller et al.
6 2001; Stoddard et al. 1999; Skjelkvale et al. 2003; Keller et al. 2001). Large-scale liming programs were implemented in Norway and Sweden as a strategy to reverse the effects of acid deposition and protect freshwater systems with important economic and recreational value
(Bengtsson et al. 1990; Olem et al. 1991). Although improvements in water quality were observed after liming, it was deemed a very costly and inefficient method for ensuring long-term recovery of an acid-damaged system (Angeler et al. 2010). Angeler and colleagues (2010) demonstrated that repeated liming events also acted as pulse disturbances that altered community dynamics. Large-scale liming was never considered as a feasible option for Ontario and the northeastern states due to the sheer number of acidified lakes in the regions and the high associated costs; therefore lakes have been recovering naturally (Jeffries et al. 2003). Both assisted and unassisted chemical recovery of historically acidified lakes has resulted in improved water quality across the landscape (Stoddard et al. 1999). In Ontario, we expect lake acidity to continue decreasing, as the standard for sulphur dioxide emissions continues to decrease
(Environmental Protection Act, RSO 1990). Although improvements in water quality have been observed, many lakes have remained acidic (Gray et al. 2012) and altered water quality with continued human development and climate change have become an increasing concern (Keller
2009; Palmer et al. 2011).
Killarney Provincial Park: chemical recovery
Killarney Provincial Park was one of the first regions in Canada where impacts of acid deposition were observed, including documented decreases in lake water pH and declines in fish populations (Beamish and Harvey 1972). Killarney Provincial Park is located on the north shore of the Georgian Bay, approximately 60km southwest of Sudbury, Ontario. The park encompasses over 600 water bodies within 485 km2. The park sits on the southern range of the
7 Canadian Shield, which is characterized by soft-water lakes that are naturally susceptible to low base cation pools due to past glacial activity and underlying geological composition (Debicki
1982). Killarney PP lakes range in their buffering capacity depending on their association with either erosion-resistant orthoquartzite ridges of the LaCloche Mountain range or base cation-rich limestone and sandstone bedrock (Debicki 1982). These differing buffering capacities between lakes led to various levels of acidification across the park.
Many lakes in Killarney PP were severely impacted by the Sudbury emissions, and since then the park has been of interest for studying the recovery of communities due to the availability of historical chemical and biological data (Beamish and Harvey 1972). Unlike lakes in close proximity to the Sudbury smelters, lakes in Killarney PP did not receive large inputs of heavy metal contaminants, such as Cu and Ni (Keller and Pitblado 1986; Labaj et al. 2015). Forty-four lakes in Killarney PP have been monitored intermittently since the years of peak acidification
(1972-73) for water quality and zooplankton community composition (Sprules 1975; Locke et al.
1994; Holt and Yan 2003; Gray et al. 2012; Figure 1.1). The lakes differed in their responses to acidification, where 8 out of the 44 lakes have remained neutral (pH≥6) since the 1970s, 14 lakes have shifted from pH<6 to pH>6 between 1972-73 and 2016, and 22 lakes that have remained acidic (pH<6) since 1973. In 1972-73, 36 out of the 44 survey lakes had pH <6, and, as of 2016, only 26 lakes have pH <6. The benchmark of pH>6 to define chemical recovery has been widely used (Keller et al. 1990; Havens et al. 1993; Holt and Yan 2003; Yan et al. 2004), and was based on research conducted by Havens, Yan, and Keller (1993), who used a combination of laboratory bioassays and field surveys to assess sensitivities of different zooplankton species to increasing levels of acidity. It was determined that the abundances of certain zooplankton species, including
Daphnia mendotae, Daphnia retrocurva, and Skistodiaptomus oregonensis, started to decline in
8 waters with pH below 6. Lakes in Killarney PP were some of the first to show substantial signs of recovery, therefore have been used to further our understanding of the complexities associated with recovering communities in a multiple stressor world (Neary et al. 1990; Keller et al. 2003).
Biological recovery of acidified lakes
The extent of biological recovery in historically acidified lakes varies with region and the community metric used for assessment (Gray and Arnott 2009). In Norway and Sweden, lakes had increased species richness and the abundance of indicator species after the implementation of liming protocols (Walseng et al. 2001; Waervågen and Nilssen 2003). Crustacean zooplankton communities in lakes in the Bohemian Forest in central Europe have not recovered (Nedbalova et al. 2006), whereas full recovery of species richness of littoral cladocerans has been reported for lakes in the Tatra Mountains (Sacherova et al. 2006). In the Sudbury region, evidence for biological recovery was mixed among studies with chemically recovered lakes being similar in community structure to neutral lakes, but univariate metrics showing limited evidence of recovery (Holt and Yan 2003; Gray et al. 2012). Despite improvements in water quality in most acid-damaged lakes to levels tolerated by acid-sensitive species, biological recovery was consistently lagging behind chemical recovery by many years across all regions (Gray and Arnott
2009).
Killarney Provincial Park: biological recovery
Changes in zooplankton community structure in the 44 study lakes in Killarney PP have been monitored since the 1970s (Locke et al. 1994; Holt and Yan 2003; Gray et al. 2012).
Multivariate comparisons of species abundance data by Holt and Yan (2003) showed that lakes that shifted from pH<6 to pH>6 (recovered lakes) between 1972-73 and 2000 had zooplankton communities similar to lakes in the park that had never acidified, but univariate metrics,
9 including species richness, did not show signs of recovery. A more recent assessment of the extent of recovery in Killarney lakes by Gray and colleagues (2012) also showed the return of some acid-sensitive species in recovering lakes, and an overall increase in species richness from the 1970s to 2005. Multivariate analyses of the zooplankton species abundances also demonstrated a shift from 1972-73 and 2005 to a community structure more similar to circumneutral lakes compared to acid lake community structure (Gray et al. 2012). Although there are many changes occurring within Killarney PP lakes over the last several decades, Labaj and colleagues (2015) observed few changes in the sedimentary cladoceran assemblages in
George Lake and Lumsden Lake of Killarney Provincial Park during the period of marked acidification between the 1920s and 1980. Labaj et al. (2015) suggested that pH was not the only variable responsible for structuring cladoceran assemblages in Killarney PP, therefore a return to pre-impact state is unlikely. Evidence for biological recovery in lakes of Killarney PP is incomplete and our understanding of the factors structuring communities is still limited, so my thesis work focussed on assessing whether further recovery has occurred in the last 10 years in the 44 survey lakes.
Limitations to recovery and factors known to shape zooplankton communities on the Canadian
Shield
Communities are shaped by the current and historical, local and regional factors acting across the landscape. Local factors include the abiotic and biotic characteristics of lakes, and the regional factors encompass the dispersal and transfer of species between communities. Dispersal limitation, changes in water quality, and community-level barriers, such as predation and competition, can influence how quickly, and to what extent, communities can recover from damage (Shurin and Allen 2001; Beisner et al. 2006; Gray and Arnott 2009). With freshwater
10 systems constantly being challenged by multiple environmental and anthropogenic stressors, it can be very difficult to assess recovery and predict how communities will respond (Christensen et al. 2006; Palmer et al. 2013; Jackson et al. 2016). As water quality in acid-damaged lakes of the
Canadian Shield continues to change, zooplankton communities face further challenges from depleted base cation pools (i.e., calcium decline), changing nutrient concentrations, climate warming, and the introduction and spread of the invasive macroinvertebrate predator,
Bythotrephes longimanus, as they continue to recovery from historical acidification (Strecker and
Arnott 2008; Yan et al. 2008; Keller et al. 2008; Jeziorski et al. 2008; Palmer et al. 2013; Jackson et al. 2016).
Following acidification and the reduction of sulphur emissions, a decline in base cations in soft-water lakes has become an increasing concern in boreal regions of North America and
Europe (Stoddard et al. 1999; Jeziorski et al. 2008; Keller et al. 2001; Waervågen et al. 2002).
Declining aqueous calcium concentrations in freshwaters is a legacy of years of acidification and timber harvesting that resulted in the leaching of Ca and other cations from surrounding watershed soils (Stoddard et al. 1999). Aqueous Ca depletion is occurring at a much higher rate than can be replenished (Watmough and Aherne, 2008), and this is a concern for many freshwater organisms because they all require varying degrees of Ca for growth and survival. Many species, particularly freshwater crustaceans, are susceptible to declines in aqueous Ca concentrations because they undergo regular moulting cycles of heavily calcified exoskeletons (Jeziorski and
Yan 2006; Cairns and Yan 2009). Laboratory Ca thresholds for survival and reproduction ranged between 0.1-1.5 mg L-1, varying between and within species of Daphnia (Hessen et al. 2000;
Jeziorski and Yan 2006; Ashforth and Yan 2008). In a large-scale study by Jeziorski and colleagues in 2008, it was determined that 35% of the 770 Ontario lakes studied have Ca levels
11 <1.5 mg L-1, and 62% have levels <2.0 mg L-1 causing concern for many biota. Keller and colleagues (2003) revealed that Ca concentrations in several lakes of Killarney PP are well below their inferred pre-industrial levels and have decreased by an average of 43% since the 1970s.
Aqueous Ca concentrations have also been related to zooplankton community composition by inhibiting the occurrence of Ca-rich species, such as Daphnia spp, and reducing the population growth rates of Bosmina spp., and several cyclopoid species, such as Mesocyclops edax (Jeziorski et al. 2015; Azan and Arnott 2018). In contrast, low Ca can promote the occurrence of Ca-poor species, such as Holopedium (Waervågen et al. 2002; Jeziorski et al. 2015). As Ca decline continues, it can interact with other environmental changes such as temperature and nutrient availability (Palmer et al. 2013; Prater et al. 2014), which could impact the rate and extent of crustacean zooplankton community recovery.
The local abiotic and biotic environment of Shield lakes is also being altered by other changing variables, such as increasing levels of dissolved organic carbon (DOC), rising temperatures, and decreasing total phosphorus (TP), that are interacting and influencing zooplankton community structure (Palmer et al. 2013). Decreased sulphur emissions and climate warming have increased levels of DOC, which influence water clarity, UV-B irradiance, and subsequently alter lake thermal structure (Keller et al. 2003; Dixit et al. 2002; Snucins and Gunn
2001). A decreasing trend in TP has also been observed, which reduces food availability for many zooplankton, promoting the success of large-bodied Daphnia that are more efficient grazers
(Wissel et al. 2003; Korosi et al. 2008; Yan et al. 2008). Individually, these changes in water quality are influencing zooplankton communities, but they have also been shown to interact
(Palmer et al. 2013). For instance, phosphorus concentrations have been shown to impact elemental content in Daphnia; therefore combined Ca and P-limitation could alter their survival
12 and growth (Prater et al. 2014). The co-occurrence of increased water temperatures and low aqueous Ca levels negatively impact Daphnia fitness by increasing metabolic energy expenditure, but reduced survivorship has also been observed when food is limited regardless of fluctuations in temperature and Ca levels (in the absence of predation and competition) (Cairns and Yan 2009; Ashforth and Yan 2008). Increased levels of DOC reduced predator vision and increased food supply, which has been shown to benefit larger cladoceran species (Wissel et al.
2003).
Another prominent stressor in inland Ontario lakes is the introduction and spread of the invasive invertebrate predator, Bythotrephes longimanus. The introduction of this invader into lakes in Ontario has been associated with lower total biomass and lower species richness of zooplankton (Boudreau and Yan 2003; Yan et al. 2003; Strecker and Arnott 2005, 2008). The presence of Bythotrephes in a system has been shown to have the largest impacts on small cladocerans, primarily bosminids and daphniids (Azan et al. 2015). This invader has been found in several lakes in Killarney PP, and could be acting as another barrier to recovery from acidification.
There are many stressors acting on freshwater lakes in Eastern North America that are impacting the local abiotic and biotic environment, and potentially impeding the biological recovery of historically acidified lakes in Killarney Provincial Park and the surrounding area. It has become increasingly important to study recovery within a multiple stressor framework as the cumulative and interactive impacts of stressors can play an important role in shaping biological communities on a temporal and spatial scale (Palmer et al. 2013).
13 Thesis Objectives
The overall goal of this thesis was to assess the continued chemical and biological recovery from regional acid deposition of lakes in Killarney Provincial Park within a framework that considers multiple changing environmental factors. As suggested by Gray and Arnott
(2009), we adopted a combined temporal and reference lake approach to assess the recovery of both univariate community metrics (species richness, species diversity, evenness, and total crustacean zooplankton abundance) and multivariate indices of zooplankton species abundances.
We used water quality and zooplankton species data from a survey of 44 lakes in Killarney PP that were sampled in 1972-73, 1990, 2000, 2005, 2011, and 2016. Field surveys have been shown to be a useful tool for studying recovery in a multiple stressor framework because they provide a glimpse of in situ communities that have been structured by current and historical anthropogenic and natural environmental changes (Palmer et al. 2013). Our reference lakes include 8 lakes within Killarney PP that were never acidified to pH<6, along with 55 lakes surveyed in Algonquin Provincial Park. Overall our primary objectives were to:
1. Assess the chemical recovery of historically acid-damaged lakes in Killarney PP
between 1972-73 and 2016.
2. Assess the biological recovery of historically acid-damaged lakes in Killarney PP
between 1972-73 and 2016 using univariate and multivariate techniques.
3. Assess the relative importance of local biotic and abiotic factors in structuring
zooplankton communities in Killarney PP to determine if these factors vary
temporally and between historically disturbed and undisturbed systems.
14 Chapter 2
Assessing the chemical and biological recovery of historically acidified lakes in Killarney
Provincial Park, 1972-73 to 2016
Introduction
Assessing the recovery of aquatic ecosystems from acidification, caused by anthropogenic sulphur dioxide and nitrogen oxide emissions, has been a challenge across North America and
Europe over the last several decades (Schindler 1988; Driscoll et al. 2001; Gunn and Sandøy
2003; Keller et al. 2001, 2003). The crude mining and smelting techniques, used for the extraction of nickel-copper ore in the Sudbury, Ontario, produced one of the largest point sources of sulphur dioxide emissions in the world (Potvin and Negusanti 1995; Snucins et al. 2001). An estimated 19 000 lakes in Ontario were acidified (Neary et al. 1990), starting as early as the
1920s (Dixit et al. 1992). This resulted in large impacts on biota, including decreased species richness and altered community composition of fish, benthic invertebrates, zooplankton, and phytoplankton (Beamish and Harvey 1972; Sprules 1975; Schindler 1988). The observed environmental impacts of acid deposition prompted the introduction of national and international legislative action in the 1980s and 1990s that aimed to reduce sulphur dioxide emissions. The subsequent reduction in acid deposition led to increased pH and alkalinity of acidified waters to varying degrees across the landscape (Stoddard et al. 1999; Skjelkvåle et al. 2001). As a result, lakes that did not go through assisted recovery (i.e., liming) have been undergoing natural recovery since the implementation of emissions reductions programs (Keller et al. 1992; Snucins et al. 2001).
15 Although chemical recovery of historically acidified lakes has been widely recorded in
Eastern North America, Scandinavia, and central Europe (Gunn and Keller 1998; Keller et al.
2001; Stoddard et al. 1999; Skjelkvåle et al. 2003; Keller et al. 2003), evidence for biological recovery has been limited and shown to lag behind improvements in water quality (i.e. increased pH) by many years, suggesting that other factors are also governing biological recovery (Yan et al. 2004; Gray and Arnott 2009; Gray et al. 2012). To date, there has been evidence of shifts towards recovery in phytoplankton (Findlay 2003; Graham et al. 2007), macroinvertebrate
(Griffiths and Keller 1992; Ormerod and Durance 2009; Murphy et al. 2014), and zooplankton communities across Europe, the UK, and North America (reviewed by Gray and Arnott 2009), but studies have shown that recovery is incomplete (Yan et al. 2004; Gray et al. 2012). Given this improved water quality, it has been suggested that the lag in biological recovery of acidified regions may be attributed to several factors, including biological resistance from acid tolerant communities (Yan et al. 1991; Keller and Yan 1998; Arnott et al. 2006), dispersal and colonization barriers (Yan et al. 2003; Gray and Arnott 2011), and multiple environmental stressors occurring simultaneously (Yan et al. 1996; Yan et al. 2004; Keller 2009; Palmer et al.
2013).
Many local and regional factors, including changes in water quality, biotic interactions, and dispersal limitations are known to shape communities in freshwater ecosystems (Shurin and
Allen 2001; Beisner et al. 2006; Palmer et al. 2013). Therefore, all of these factors are expected to influence how quickly, and to what extent, these communities can recover from past disturbances (Gray and Arnott 2012). In Ontario, soft-water Canadian Shield lake communities face challenges from multiple, interacting environmental changes in addition to historical acidification, including decreased base cation concentrations (calcium), reduced food availability
16 with declining total phosphorus (TP) levels, increased levels of dissolved organic carbon (DOC), the spread of the invasive macroinvertebrate predator, Bythotrephes longimanus, and increased water temperatures associated with climate warming (Schindler et al. 1996; Holt and Yan 2003;
Yan et al. 2004; Monteith et al. 2007; Jeziorski et al. 2008; Gray et al. 2012; Palmer et al. 2013).
Therefore, as we study the recovery of Shield lakes from acidification, the influence of simultaneous changes in other local biotic and abiotic environmental variables also need to be taken into consideration.
Crustacean zooplankton have proven to be useful indicators of environmental change and recovery as they respond quickly to disturbances, are critical links between the primary producers and higher trophic levels in freshwater food webs (Marmorek and Korman 1993; Walseng et al.
2003), and their sensitivity to environmental change can be species-specific (Walseng et al.
2003). Past studies have shown that several cladoceran and copepod zooplankton species, including Daphnia mendotae, Daphnia retrocurva, Skistodiaptomus oregonensis, and Epischura lacustris, are particularly sensitive to declines in pH by showing decreased survival, growth, and reproduction in acid conditions (Havens, Yan and Keller 1993; Holt and Yan 2003). Havens and colleagues (1993) determined a threshold of pH≥6 must be attained for the re-establishment of these acid-sensitive species. Low species richness and diversity are associated with highly acidic lakes, with the calanoid copepod, Leptodiaptomus minutus, and small cladoceran bosminids as the dominant community members (Sprules 1975; Holt and Yan 2003; Gray et al. 2012).
Therefore, univariate community metrics such as species richness and diversity have been useful indicators of recovery, alongside multivariate indices using relative species abundances (Yan et al. 1996; Holt and Yan 2003; Gray and Arnott 2009; Gray et al. 2012).
17 Along with taking a multiple stressor framework to study recovery, the benchmark and metric used to define recovery can influence interpretation and conclusions (Gray and Arnott
2009). Previous recovery studies have used comparisons of pre-disturbance and post-disturbance community metrics by experimentally manipulating whole lakes (Schindler et al. 1985) and using paleolimnological reconstructions (Keller et al. 2003; Labaj et al. 2015), compared disturbed lakes with undamaged reference lakes (Holt and Yan 2003), or used a temporal sampling approach that tracks changes in water quality and community structure through time. Gray and
Arnott (2009) suggested using at least two of the three approaches to assess recovery in univariate and multivariate zooplankton community metrics.
For this study, we assessed the chemical and biological recovery from historical acidification in 44 lakes in Killarney Provincial Park (Killarney PP), Ontario, Canada, between
1972-73 and 2016. These lakes have been surveyed for water quality and zooplankton communities beginning in 1972-73 (Sprules 1975) during peak acidification, and continued through 1990 (Locke et al. 1994), 2000 (Holt and Yan 2003), 2005 (Gray et al. 2012), and 2011
(Arnott unpublished data). Results from these studies showed evidence for chemical recovery as early as 1990 after reductions in emissions, but suggested that biological recovery in lakes was not complete. Therefore, our study objectives were to (i) determine if there were changes in acidity and other water quality variables across lakes in Killarney PP since the time of peak emissions in the 1970s to our most recent sampling year in 2016, and (ii) assess if further biological recovery of crustacean zooplankton has occurred using both univariate and multivariate metrics of community composition and comparing historically acid-damaged communities to undamaged reference lake communities both within and outside Killarney PP.
Additionally (iii), we evaluated the relative influence of local biotic and abiotic factors in
18 explaining variation in crustacean zooplankton community composition in Killarney PP and determined if these variables differed in a region that did not experience severe acid deposition.
Methods
Site description
Killarney PP (46.0130°N, 81.4017°W) is located 40-65km southwest from the Sudbury,
Ontario, smelters, and contains over 600 lakes and ponds within its 485km2 area. Low alkalinity, nutrients, and calcium levels are characteristic of many lakes in the park due to their association with the orthoquartzite ridges of the La Cloche Mountain range (Sprules 1975). Extensive mining and smelting activities in the mid-1900s led to the acidification of surrounding lakes to varying degrees, which resulted in large-scale changes in biota, such as decreased species richness and altered community composition (Beamish and Harvey 1972; Sprules 1975). Lakes within the park vary in surface area (ranging 4.6-1088.3 ha), maximum depth (ranging 2.3-55.1 m), elevation (182-294 m) (Table A1; Appendix A), and chemical gradients, such as conductivity
(12.2-73.5 µS cm-1), DOC (0.5-9.1 mg L-1), and TP (0.9-31.8 µg L-1) (Appendix B). Currently, pH in the 44 lakes, included in this study, ranged from 4.56 to 7.02, whereas in 1972-73 pH ranged from as low as 3.8 to 7. Many of the lakes within Killarney PP have highly regulated, recreational activity generally limited to backcountry camping, but several of our study lakes located outside of the park, including Tyson, Charlton, Frood, and La Cloche lakes, are more highly developed with cottages.
Fifty-five lakes in Algonquin Provincial Park (hereby Algonquin PP) were sampled and used as reference lakes to assess the extent of recovery in Killarney PP. Algonquin PP
(45.8372°N, 78.3791°W) is located approximately 200km southeast of Sudbury and encompasses
19 almost 1300 lakes within its 7630km2. Established in 1893, Algonquin PP is the oldest park in
Canada and the third largest park in Ontario. Due to pervasive northwesterly winds, this park
-2 -1 2- experienced 0.75-1.25 gS m y of SO4 deposition in 1983 (Neary and Dillon 1988), but this is
-2 -1 2- low compared to the greater than 20 gS m y of SO4 deposition in lakes in close proximity to the Sudbury smelters (Snucins et al. 2001). Several lakes within the Muskoka, Haliburton, and
Chalk River regions of Ontario that surround Algonquin PP were acidified (Neary et al. 1990), though the 55 lakes included in this study all have pH above 6 as of August 2015.
Sampling design
To assess the chemical and biological recovery of historically acid-damaged lakes, we surveyed 44 soft-water lakes in Killarney PP (46.0130°N, 81.4017°W; Figure 1) in 2016, in accordance to previous studies done in 1972-73, 1990, 2000, 2005, and 2011 (Table 2.1).
Sprules (1975) initially sampled the lakes in 1972 and 1973 when industrial sulphur emissions were at their peak. The same selection of lakes was sampled in each survey, with the exceptions of Evangeline Lake that was not sampled in 2016, Tyson Lake that was not sampled in 1972,
2000, or 2005, and Roque Lake that was excluded in the 2011 survey. These lakes were not included in our analyses.
Zooplankton sampling in 2016
We took vertical zooplankton hauls from the deepest point of the major basin in each lake. The location of maximum depth was determined using a combination of bathymetric maps,
GPS coordinates from previous sampling years, and hand-held depth sounders. A 2m-long, 25cm diameter conical net with 80µm mesh was towed from 2m above the lake bottom up to the surface. For lakes with a maximum depth shallower than 5m, we took horizontal net tows ranging from 10m to 25m. We preserved zooplankton samples in 70% ethanol. Samples were
20 enumerated and identified usually to species level using a Leica MZ12s dissecting microscope.
Subsamples of 3mL, from a standardized 100mL sample volume, were counted until a minimum of 250 individual adult zooplankton were enumerated, ensuring that no single taxon accounted for more than 20% of the total count. If fewer than five species were identified, subsamples were counted until 50 individuals of each species were counted, or until no new species were found in three subsequent subsamples. Juveniles were identified and counted until a total of 50 copepodids and 30 nauplii were counted, but these were not included in the 250 total. The remainder of sample was scanned for rare species. Several taxonomic keys were used to identify cladoceran and copepod species and genera, including Witty (2004), Ward and Wipple (1966),
Smith and Fernando (1978), and Haney et al. (2013). Daphnia pulex and Daphnia pulicaria were pooled following Holt and Yan (2003) and Gray et al. (2012), Bosmina spp. and Eubosmina spp. were pooled (Taylor, Ishikane & Haney 2002; Gray et al. 2012), and Diaphanosoma brachyurum and Diaphanosoma birgei were also pooled as D. birgei to account for taxonomic changes over the record (Kořínek 1981; Gray et al. 2012).
To determine whether lakes were invaded by the predatory macroinvertebrate,
Bythotrephes longimanus, we took a vertical or horizontal net tow from 5 different locations
(including the point of maximum depth) within each lake using a conical net with 400µm mesh and a 35cm diameter. The samples collected from each location were pooled, preserved in minimum 70% ethanol solution, and later scanned under a microscope for the presence of
Bythotrephes (Appendix F). We used data collected by Snucins and Gunn (1998) to determine the presence or absence of 23 different fish species in our 44 lakes (Appendix G). We created a fish community variable used in our multiple linear regression analysis by running a PCA on the fish data, and using the scores from the first PC axis.
21 Water chemistry sampling method in 2015 and 2016
Vertical integrated samples for water chemistry were collected at the point of maximum depth in each lake using a 5 m long, 1.9 cm diameter tube sampler in Killarney PP and a composite sampler in Algonquin PP. No differences in water chemistry measurements were detected between samples taken using the two methods (Appendix H). Water for chemical analysis was filtered through 80µm mesh to remove most zooplankton and stored in a refrigerator for no more than four days. The samples were shipped to the Dorset Environmental Science
Center in Dorset, ON, where pH, DOC, conductivity, ion concentrations, and nutrient concentrations were analyzed for each lake sample according to Ontario Ministry of the
Environment and Climate Change protocols (Appendix J). pH was defined as the negative logarithm of hydrogen ions, conductivity was defined as the reciprocal of the water’s electrical resistance, cations (including calcium, magnesium, sodium, and potassium) were measured using an automated atomic absorption method, and anions (chloride and sulphate) were separated through ion chromatography and then converted into their acid forms to estimate concentrations using conductivity. DOC was determined by adding the sample to an automated colourimetric system where the inorganic carbon was removed through acidification and nitrogen flushing, and the sample was subsequently oxidized and converted into carbon dioxide and measured by looking at the loss of absorbance with an AAII Colourimeter. Total phosphorus was determined by measuring orthophospate in digested samples using ascorbic acid as a reducing agent and total nitrogen was measured by pyrolitically oxidizing the water sample and using a chemiluminescence detector, and this nitrogen signal was quantified using a calibration curve of known nitrate standards. Maximum depth, surface area, and elevation were the selected physical characteristics of the 99 lakes included in this study. Physical variables for Killarney PP were taken from Shead (2007) and from Rampone (unpublished data) for Algonquin PP.
22
Lake categories
To assess the chemical and biological recovery of Killarney PP lakes from historical acidification, we divided our lakes into three categories according to water quality improvement since 1972-73 (based on changes in pH). The three categories are as follows:
Acid lakes (n=22): lakes that had pH<6 in 1972-73 and remained pH <6 in each subsequent sampling year including 2016. This also includes three lakes that had a pH of <6 in 1972-73, then rose to a pH>6 in the 2000 or 2005 sampling year, then returned to pH<6 in the 2011 or
2016 sampling year.
Recovered lakes (n=14): lakes that had pH<6 in 1972-73, then rose to pH>6 as of the 1990 survey or later.
Circumneutral lakes (n=8): lakes that had pH>6 since 1972-73 and remained pH>6 in each subsequent sampling year including 2016. These lakes were used as a reference for assessing the recovery of water chemistry and zooplankton communities from historical acidification in our recovered and acid lake categories.
Statistical analyses
All statistical analyses were performed in R version 3.3.1 (2016-06-21) using packages ‘vegan’ v.2.4-2 (Oksanen et al. 2013), ‘MuMIn’ v.1.15.6, ‘lme4’ v.1.1-12, and ‘Kendall’ v.2.2 with
α=0.05.
Chemical recovery
We took a temporal and reference lake approach to assess chemical recovery in acid- damaged lakes (Gray and Arnott 2009). We compared changes in hydrogen ion concentrations
23 ([H+]) between 1972-73 and 2016 in the 44 study lakes using a paired t-test. To describe the variation of the three lake groups (acid, neutral, and recovered) with water quality (pH, Si,
Secchi, and SO4), we used principal components analysis (PCA) as our ordination technique after conducting a preliminary indirect gradient analysis using detrended correspondence analysis
(DCA) with the function decorana {vegan} in R. The gradient lengths for the first two axes of
1972-73 were 1.1 and 0.7, respectively, 1.7 and 0.9 in 2016, and 1.02 and 0.86 for our analysis combining data from all six survey years. Gradient lengths <2 suggest linear relations along the gradient, which is appropriate for PCA (Lepš and Šmilauer, 2003). Significant shifts in water quality were detected using non-parametric multivariate ANOVAs (Anderson 2001) with the function adonis{vegan} containing the matrix of center-scaled water chemistry variables and the
44 lakes.
Additionally, we assessed temporal trends in water quality variables, including pH, conductivity, Ca, TP, DOC, Cl, SO4, Na, Si, and secchi depth, using Mann-Kendall trend tests for each lake with the MannKendall {kendall} function in R. We determined whether there were significant (p<0.1) positive or negative trends for each of our water quality variables for each of the 44 lakes between 1972-73 and 2016 or 2000 and 2016 depending on the data available.
Biological recovery
Similar to Gray et al. (2012) and Holt and Yan (2003), we assessed biological recovery in both univariate, including species richness, diversity, evenness, and total abundance, and multivariate zooplankton community metrics in the 44 lakes of Killarney PP. All community metrics were calculated using adult species abundances; juveniles were not included in analyses.
Zooplankton samples taken in 2011 were excluded from analysis due to unreliable species
24 identifications. Species richness was defined as the number of species counted in a sample, and has been a reliable index used to assess impacts of acidification (Marmorek and Korman 1993;
Yan et al. 1996). We used corrected Shannon-Wiener index of entropy with a correction suggested by Jost (2006) to calculate species diversity. We calculated species evenness as Evar as recommended by Smith and Wilson (1996). Evar uses the variance of abundances to ensure that the index is not dependent on species richness. Evenness ranges from 0 to 1, with values closer to 1 indicating maximum evenness. The total abundance of crustacean zooplankton was defined as the number of adult zooplankton per liter of sampled lake water.
To determine if species richness, Shannon-Weiner diversity, evenness, and total abundance changed between sampling years, we used linear mixed effect models with sampling year and lake category (acid, recovered, neutral) as categorical fixed effects and individual lake as the random effect using the lmer {lme4} function. We assessed the assumptions of homoscedasticity and normality for the full models by looking at histograms of residuals, plots of residual vs. fitted values, and normal quantile plots. Total abundance of crustacean zooplankton data and species evenness data were log (x + 1) transformed to improve normality and homogeneity of variances. If given a significant interaction term in our model, we used an
ANOVA and post-hoc Tukey’s Honest Significant Difference (Tukey HSD) test to determine if differences in community metrics between our different lake categories within each sampling year were significantly different (p<0.05). We also used paired t-tests to see if means of community metrics between 1972-73 and 2016 were significantly different.
We used PCAs on Hellinger-transformed zooplankton abundance data (Borcard et al.
1992) to describe the structure of zooplankton communities in the 44 Killarney PP lakes in 1972-
73, 2016, and all six survey years pooled. The scores from the first PCA axis, describing the
25 most variation in zooplankton community composition across all sampling years, for 1972-73 and 2016 were plotted to observe shifts in community structure. Changes in PCA axis 1 scores between each subsequent sampling year can be found in Figure M1 in Appendix M. To determine if there was significant change in zooplankton community composition through time, we used the lake categories as partitions to assess dissimilarities in the acid, recovered, and neutral groups using non-parametric MANOVAs as described above within our first (1972-73) and last (2016) sampling years, with Benjamini-Hochberg False Discovery Rate corrected p- values for multiple comparisons.
Environmental variables shaping zooplankton community structure
To assess the importance of morphometric and environmental variables in explaining variation in zooplankton univariate community metrics, we conducted multiple linear regressions using the community metrics as response variables and center-scaled physical and chemical indices as the predictor variables. Separate regressions were run on each of our four community metrics in each of our survey years, 1972-73, 1990, 2000, 2005, and 2016. To minimize the number of predictor variables and reduce collinearity in our analyses for the 2000, 2005, and
2016 sampling years, we used the scores from the axes with the highest ion and nutrient loadings from PC analysis on mean-centered water chemistry variables. The first PC axis in 2000, 2005, and 2016 was strongly associated with ion concentrations, and were included as predictor variables in the models. We also defined a nutrient variable using the scores from the second PC axis in 2016 and the third PC axis in 2000 and 2005, as nutrient concentrations (TP, TKN, DOC, and Fe) had the highest loadings on these axes. Presence/absence data for Bythotrephes was also used as a predictor variable, as well as a fish variable represented as the score from a PCA on fish presence/absence data collected by Snucins and Gunn (1998). The top models explaining each
26 community metric response variable were determined using Akaike’s information criterion (AIC) with the function dredge {MuMIn} (Barton, 2016). All models with a delta AICc <2 were considered as plausible models and summarized in Table 2.5. Species richness had a non-normal distribution; therefore a generalized linear model (GLM) with a Poisson distribution was used for each sampling year. Species evenness and total abundance distributions were right skewed; therefore a log (x +1) transformation was applied. We assessed the assumptions of homoscedasticity and normality for the full models by looking at the residual vs. fitted values, the normal quantile-quantile, scale-location, and residuals vs. leverage plots.
To determine the relative importance of environmental variables in explaining changes in the univariate measures of community structure between 1972-73 and 2016, we conducted multiple linear regression analysis. We used the differences in species richness, diversity, evenness, and total abundance in zooplankton communities, calculated by subtracting 1972-73 values from 2016 values, as our response variables, and differences in the pH, Si, SO4, and secchi depth as our predictor variables. Assumptions of normality and homoscedasticity were assessed as described above. To avoid multicollinearity in the models, the variance inflation factors
(VIFs) were calculated using the function vif {car}. All VIFs were <4, therefore all predictor variables were kept in the models. Top models were selected for each community metric using
AICs, as described above.
We described environmentally-constrained variation in zooplankton community composition in the 1972-73 and 2016 sampling years with redundancy analysis (RDA) using the rda {vegan} function. Hellinger-transformed species abundance data was used as the response variable and a matrix of center-scaled morphological and environmental variables as the explanatory variables. VIFs were assessed to ensure no collinearity between explanatory
27 variables. We determined the significance of each constraining variable on community composition using an ANOVA-like permutation test on the RDA for 1972-73 and 2016 using the function anova.cca {vegan} (Legendre and Legendre 1998).
Algonquin Provincial Park lakes as a reference for recovery
To further assess the recovery of Killarney PP lake communities from historical acidification, we compared the univariate zooplankton community metrics in our three Killarney
PP lake categories in 2016 to the same metrics from 55 undamaged lakes in Algonquin PP sampled in 2015. Algonquin PP is used as a reference system for recovery as it is also located on the Canadian Shield, possesses similar zooplankton communities consisting of the same six most common species occurring in each park, including: Mesocyclops edax, Diaphanosoma birgei,
Bosmina spp, Holopedium glacialis, Diacyclops thomasi, and Leptodiaptomus minutus (Figure
2.1). Comparisons of morphometric and water quality metrics between parks are plotted in
Appendix I. Algonquin PP lakes did experience some effects from acidification during the mid-
70s (Hadley et al. 2015), but levels of acid deposition were much lower than in Killarney PP
(Neary and Dillon 1988).
To assess recovery of Killarney PP communities using Algonquin PP community metrics as the benchmark for recovery, we compared means of each metric using ANOVAs and post-hoc
Tukey HSD tests. We also assessed differences in community structure between parks using
PCA on Hellinger-transformed species abundance data from Killarney PP lakes, 2016, and
Algonquin PP lakes, 2015. Non-parametric MANOVAS, as described above, were used to determine differences in zooplankton community composition between Algonquin PP and the
28 neutral and recovered lake groups of Killarney PP, with Benjamini-Hochberg False Discovery
Rate corrected p-values for multiple comparisons for non-Tukey HSD post-hoc analyses.
To compare environmental variables structuring zooplankton communities in each park,
RDAs on individual parks using maximum lake depth, surface area, pH, SO4, TP, and Cl as the constraining environmental variables. Constraining variables were chosen because they have been previously shown to influence zooplankton communities in Shield lakes (Yan et al. 2008;
Gray et al. 2012; Palmer et al. 2013), and VIFs <4. We determined the significant explanatory variables on community structure in each park using the ANOVA-like permutation test on RDA.
Results
Chemical recovery of Killarney Provincial Park
We found strong evidence for pH recovery in acid-damaged lakes in Killarney PP.
Hydrogen ion concentration decreased in 95% of sampled lakes, and we saw the greatest changes in the acid lakes (Figure 2.2). In 1972-73, 22 out of the 44 survey lakes were critically acidic
(pH<5), but this decreased to only 7 lakes in 2016. The mean pH of the 44 survey lakes has increased significantly from 4.63 to 5.36 between 1972-73 and 2016 (Paired t-test: T=4.70,
DF=43, P<0.001). We observed an overall increase in pH, including 14 lakes that shifted from an acidic (pH<6) to recovered (pH>6) state, though three of these lakes that had recovered in earlier sampling years experienced a reversal to pH<6 in 2016; Boundary, Terry, and Johnnie lakes.
A shift in water quality between 1972-73 and 2016 was revealed in all but two of the surveyed lakes, Shingwak and Little Superior, in our PCA using water chemistry data from all six survey years (Figure 2.3). The greatest improvements in water quality occurred in the recovered
29 lakes group, as evidenced by a shift from low PCA axis 1 scores in 1972-73, to higher PC 1 scores in 2016, which accounts for 41.4% of the variation in lakes. High PC 1 scores are typical of circumneutral lakes and are characterized by circumneutral pH, low sulphate, low silica, high
TP, and shallower secchi depths (Table 2.2). Together, the first two axes of the PCA explain
68% of the variation among Killarney PP lakes. By 2016, recovered lakes were statistically indistinguishable from circumneutral lakes (non-parametric MANOVA: Fmodel1,20= 2.86,
P=0.27; Figure 2.4a, Table 2.2), whereas in 1972-73, these two groups were significantly different from each other (non-parametric MANOVA: Fmodel1,20=3.71, P=0.005); Figure 2.4b,
Table 2.2).
Along with improvements in water quality with regards to acidity, we also detected general increasing temporal trends in DOC, and decreasing trends in conductivity, calcium, chloride, sulphate, sodium, and silica (Table 2.3). Trends were deemed significant if P<0.1, given that each Mann-Kendall trend test had low power with only had 4 to 6 data points.
Biological recovery of Killarney Provincial Park
Along with improvements in water quality, we also found evidence for biological recovery with changes in univariate and multivariate metrics of zooplankton community structure in historically acid-damaged lakes in Killarney PP. Changes in species richness (GLMM, interaction vs no interaction ΔAICc = 6) and Shannon-Weiner diversity (GLMM, interaction vs no interaction ΔAICc > 7) differed between lake groups through time. Species richness in individual lakes ranges from 1 to 15 species in 1972-73, and from 2-15 in 2016. Mean species richness increased from 6.2 (±0.60 SE) to 8.4 (±0.49 SE) between 1972-73 and 2016 (Paired t- test: T=-5.44, DF=43, P<0.001; Figure 2.5a). Acid lakes had consistently lower species richness
30 compared to recovered and circumneutral lakes (ANOVA, F2,41=20.96, P<0.001). Mean species richness in recovered lakes increased from 7.7 (±0.90 SE) in 1972-73 to 9.5 (±0.77 SE) in 2016
(Paired t-test: T=2.62, DF=43, P=0.02), and in 2016 species richness in recovered lakes did not differ from circumneutral lakes (Tukey HSD, P=0.39). Species diversity (corrected Shannon-
Weiner diversity) ranged from 1 to 8 in 1972-73 and from 1 to 10 in 2016 (Figure 2.5b). Mean species diversity increased from 3.1 (±0.32 SE) in 1972-73 to 5.6 (±0.40 SE) in 2016 (Paired t- test, T=-7.17, DF=43, P<0.001). In acid lakes, species diversity was consistently low between
1972-73 and 2005 (highest mean of 2.4±0.35 SE in 2000), but increased to 4.85 (±0.54 SE) in
2016. Species diversity did not differ between circumneutral and recovered lake categories in either 1972-73 or 2016 (Tukey HSD, P>0.05).
In contrast, changes in species evenness and total crustacean zooplankton abundance did not differ between lake categories through time (GLMM, interaction vs no interaction ΔAICc
<2). Species evenness was variable through time in all lake categories (Figure 2.5c). Overall, there was a significant decline in species evenness between 1972-73 and 2016 (Paired t-test,
T=4.44, DF=43, P<0.001). Total abundance of crustacean zooplankton also varied greatly across years in all lake categories (Figure 2.5d). Mean total abundance was lower in acid lakes across all sampling years, though differences were not significant between the lakes categories
(ANOVA, F2,41=1.14, P=0.33).
Additionally, there was a shift towards recovery in zooplankton community composition between 1972-73 and 2016 (Figure 2.6). The first and second PCA axes explained 25% of the total variation in zooplankton species composition in Killarney lakes. Acid lake communities had high PC1 scores and were dominated by the acid-tolerant Leptodiaptomus minutus, whereas circumneutral lakes were characterized by lower PC1 scores and dominated by a more diverse
31 community consisting of Mesocyclops edax, Diaphanasoma birgei, Daphnia retrocurva,
Tropocyclops extensus, and Epischura lacustris (Figure 2.6, 2.7). The majority of lakes experienced a negative shift in PC1 score through time towards zooplankton assemblages more similar to those in circumneutral lakes (Figure 2.5e). Community composition in recovered and circumneutral lakes was significantly different in 1972-73 (non-parametric MANOVA,
Fmodel=3.71, P=0.002; Figure 2.7a), but did not differ in 2016 (non-parametric MANOVA,
Fmodel=0.80, P=0.56; Figure 2.7b).
In the majority of the 44 lakes in Killarney PP, we observed increases in the relative abundance of Daphnia spp, Bosmina spp, Holopedium glacialis, large cladocerans (which included Daphnia spp, Sida crystillina, Holopedium, Diaphanosoma birgei, and Latona setifera) and cyclopoid species (including Mesocyclops edax, Diacylcops thomasi, Tropocyclops extensus,
Cyclops scutifer, and Cyclops vernalis) between the 1972-73 and 2016 sampling years, but decreased relative abundance of calanoid and cyclopoid copepods was detected (Figure 2.8).
Environmental variables shaping zooplankton community structure
The influence of pH and ion concentrations on zooplankton community structure was ubiquitous across all sampling years (Table 2.5). Physical characteristics of the lakes, including maximum depth, elevation, and surface area, and biological variables, the presence/absence of
Bythotrephes and fish species, were also important explanatory variables for species richness, diversity, evenness, and total abundance and temporal changes in these community metrics in the
44 Killarney PP lakes. The nutrient variable was included as an important predictor variable for all community metrics in the 2005 and 2016 sampling years. The amount of variation in species richness explained by the physical and environmental variables included in the top models
32 decrease from 76% in 1972-73 to 49% in 2016. A similar pattern was detected for species diversity where 64% of the variation was explained in 1972-73, but only 23% was explained in
2016.
Regression analyses demonstrated that changes in univariate zooplankton community metrics between 1972-73 and 2016 most likely occurred with changes in acidity, water clarity and nutrient levels (Table 2.6). Our predictor variables explained between 8 and 22% of variation in our community metrics, indicating that other factors not included in the models, such as dispersal and biotic interactions may also be influencing changes in zooplankton community assemblages as was found in regression models above.
The importance of the constraining variables on zooplankton community composition changed through time: the first three axes of our RDA accounted for 38.6% of the variation in community structure in 1972-73 (Figure 2.9a) and only 25.5% in 2016 (Figure 2.9b). In 1972-73, pH (ANOVA, F=8.78, P=0.001), sulphate concentration (ANOVA, F=2.11, P=0.02), depth
(ANOVA, F=2.81, P=0.01), area (ANOVA, F=7.44, P=0.001), and elevation (ANOVA, F=4.19,
P=0.001) explained significant variation of zooplankton species composition. In 2016 pH
(ANOVA, F=3.43, p=0.001), depth (ANOVA, F=3.09, p=0.001), and secchi depth (ANOVA,
F=4.90, p=0.001) were the constraining variables explaining significant variation in community composition (Table 2.7).
Community comparisons with Algonquin Provincial Park
Zooplankton communities in lakes of Killarney PP generally had lower species richness
(Two-sample t-test: T=7.71, DF=72.9, P<0.001; Figure 2.10a), diversity (T=3.24, DF=81,
P=0.002; Figure 2.10b), and evenness (T=4.17, DF=72.9, P<0.001; Figure 2.10c) compared to
33 lakes in Algonquin PP. However, total abundance of zooplankton was similar between the two regions (T=-1.31, DF=69.6, P=0.2; Figure 2.10d).
To further assess biological recovery, we compared community metrics in Algonquin lakes to community metrics of our three lake groups categorized by water quality in Killarney
PP: acid, recovered, and circumneutral. No difference in species richness in Algonquin lakes and
Killarney PP circumneutral lakes was detected (Tukey HSD, P=0.26), but species richness was significantly lower in recovered (Tukey HSD, P<0.001) and acid lakes (Tukey HSD, P<0.001)
(Figure 2.11a). Species diversity (Figure 2.11b) and species evenness (Figure 2.11c) were significantly lower in Killarney PP acid lakes (Tukey HSD, P<0.001) relative to Algonquin PP lakes. No difference in total abundance of crustacean zooplankton was observed between lakes in Algonquin PP and Killarney PP (Figure 2.11d).
Zooplankton community composition in circumneutral Killarney PP lakes was similar to that of lakes in Algonquin PP (non-parametric MANOVA, Fmodel1,64=1.98, P=0.25; Figure
2.12), but zooplankton community structure of recovered Killarney PP lakes differed significantly (non-parametric MANOVA, Fmodel1,64=4.57, P=0.002) and also from acidic lakes
(non-parametric MANOVA, Fmodel1,64=6.07, P=0.0004). The importance of constraining variables on zooplankton community structure between the two parks differed. Killarney PP community composition was significantly explained by lake depth (ANOVA, F=2.93, P=0.001), area (ANOVA, F=2.74, P=0.01), and pH (ANOVA, F=4.59, P=0.001) with the first three significant RDA axes explaining 22% of variation, in comparison to Algonquin PP community composition where the only significant explanatory variable was lake depth (ANOVA, F=2.96,
P=0.001) and the first three significant RDA axes only explained 12% of variation in zooplankton community structure.
34 Discussion
Chemical recovery of Killarney Provincial Park lakes
We detected changes in water chemistry and shifts in zooplankton community structure in historically acidified lakes in Killarney Provincial Park that are consistent with recovery from acidification. Our survey of 44 lakes in Killarney Provincial Park revealed a shift in the historically acid-damaged lakes to a chemical state more typical of circumneutral lakes between
1972-73 and 2016 (Figure 2.6). Over the past four decades, the number of severely acidified
(pH<5) lakes decreased from 23 to 7, with the majority of these changes occurring between 1972-
73 and 1990, following the implementation of emission reductions programs. These findings are consistent with those from other lakes in Ontario where decreases in acidity and changes in other water quality parameters have been recorded (Yan et al. 2008; Keller et al. 2003; Keller 2009;
Palmer et al. 2011).
Although we observed an increase in pH in all but two of our survey lakes
(Delamorandiere and Helen lakes), 24 out of 44 lakes still have pH<6 as of 2016. The benchmark of pH≥6 has been widely used to define the state of recovery (Keller et al. 1990;
Havens et al. 1993; Holt and Yan 2003; Yan et al. 2004). Despite adequate water quality being one of the main factors promoting biological recovery (Kurek et al. 2011), using pH 6 as the standard for designating recovery may not be applicable to all lakes. According to paleolimnological reconstructions of past environmental conditions, several of our study lakes that had pH<6 as of 2016 have returned to their diatom-inferred pre-industrial pH levels (Smol et al. 1998; Keller et al. 2003). For example, the pH of Ruth Roy Lake increased from 4.5 in 1972-
73 to 5.1 in 2016, exceeding its diatom-inferred pre-industrial pH of 4.9 (Smol et al. 1998).
Similarly, Acid and Terry lakes both had diatom-inferred pre-industrial pH of 5.6 (Smol et al.
35 1998), and the measured pH increased from 4.8 and 4.2, respectively, in 1972-73, to pH 5.6 in
2016. This suggests that some acid lakes should be expected to remain acidic, as this was their pre-industrial state. Therefore, if the data is available, background, pre-acidification conditions should be taken into consideration when assessing recovery (Gray and Arnott 2009; Vrba et al.
2003). Given the lack of pre-industrial reference conditions for the majority of our lakes, we used both reference lakes and changes in acidity levels between peak acidification years (1972-
73) and our most recent survey (2016) to assess the chemical recovery.
Despite improved water quality with increased pH through time and several lakes being fully recovered to pre-industrial conditions or to pH>6, there are still many lakes that have not chemically recovered. Some of our 2016 survey lakes, including Nellie, OSA, Clearsilver, and
David lakes continued to have pH values well below their diatom-inferred pre-industry levels
(Smol et al. 1998; Keller et al. 2003). The recovery of pH in a lake is influenced by water retention times, the size and location of the watershed (Arnott et al. 2003), the rate of weathering and erosion altering alkalinity of the water (Arnott et al. 2001), and the rate of anthropogenic inputs (Gorham et al. 1986). Nellie Lake has a diatom-inferred pre-industrial pH of ~6 (Keller et al. 2003), but had a low pH of 4.65 in 2016, which may be attributed to it being a large headwater lake within a relatively small watershed that is located on the erosion-resistant orthoquartzite ridge of the La Cloche mountains. Unfortunately, we did not possess diatom-inferred conditions for all of the 44 study lakes sampled in Killarney PP, but this study reinforced the need for consistent, long-term monitoring data for the assessment of recovery and supported the need for collaborative efforts to better understand both past and present changes in these systems for a complete recovery story.
36 While increasing pH in lakes has been a central goal of emission reduction programs, we observed other changes in water chemistry associated with other environmental changes across the landscape. We detected decreasing temporal trends in conductivity and ion concentrations, including Ca, Na, Cl, and increasing temporal trends in DOC in several lakes. Although, these observed trends in water quality variables were not statistically significant for the majority of lakes (p>0.05), this could be due to low power associated with only 4 to 6 sample years. The trends in Killarney PP are consistent with those detected in soft-water lakes across the Canadian
Shield (Palmer et al. 2011). Decreasing levels of base cation concentrations, namely calcium, have become an increasing concern over the last few decades as they decline towards thresholds of ecologically important species (Keller et al. 2001; Jeziorski et al. 2008). Years of acid deposition and timber growth and harvesting practices in Ontario have promoted the depletion of exchangeable ion pools in catchment soils that were already relatively low due to the weather- resistant bedrock that makes up the Canadian Shield (Watmough and Dillon 2003). Consistent with regional trends, increased DOC was observed between 1972-73 and 2016. Mean TP concentrations decreased from 12.59 µg L-1 in 2000 to 5.38 µg L-1 in 2016, and mean DOC concentration increased from 2.43 mg L-1in 2000 to 3.41 mgL-1 in 2016 across the 44 Killarney
PP lakes. Increases in DOC have been attributed to higher temperatures promoted by climate warming (Keller et al. 2008; Stoddard et al. 2003; Skjelkvale et al. 2005) and reductions in acid deposition (Monteith et al. 2007). Although an increasing trend in DOC was observed, according to paleolimnological reconstructions of pre-industrial environmental conditions, some lakes still have DOC levels below their diatom-inferred conditions (Keller et al. 2003). For example, Nellie and Low lakes have inferred DOC concentrations of ~1.9 mg L-1and ~7.5 mg L-1 (Keller et al.
2003), respectively, but the measured DOC concentrations in 2016 were 0.5 mgL-1and 2.9 mg L-
1. Conversely, Bell, Johnnie, and Carlyle lakes have DOC concentrations that exceed their
37 diatom-inferred levels (Keller et al. 2003). High levels of DOC in lakes have been shown to alter thermal structure and UV-B penetration into the water column, which can influence biotic interactions in lakes (Schindler et al. 1996; Williamson et al. 1999; Keller et al. 2003, 2008). In contrast to regional trends, many lakes in Killarney PP demonstrated decreasing trends in Cl and
Na ions presumably from leaching promoted by historical acid deposition and the limited development in the surrounding area. Many lakes across the USA and Canada are experiencing high inputs of Cl and Na ions from road salt application (Dugan et al. 2017),
Overall, many changes in water quality are occurring simultaneously as pH increased with reductions in emissions in Killarney PP, including legacies from historical acid deposition, climate warming, and other anthropogenic activities. The persistence of acidification-related issues observed in many lakes across Ontario, after the significant reduction of acid deposition from industrial emissions, are caused by the depletion of ions in surrounding soils from acidification, drought events promoting pulse exports of SO4 and Al, and climate-mediated biogeochemical processes (Watmough et al. 2016). The enduring impacts of historical acidification, along with the multiple other regional stressors, suggest that a return to pre-impact state is generally unlikely and recovery targets should reflect these changes (Palmer et al. 2011).
Historical and current, local and regional abiotic factors are known to influence to freshwater community composition, and understanding these changes and their associated interactions will be required for proper management and conservation of these systems.
Biological recovery of lakes in Killarney Provincial Park lakes
Temporal changes in both our univariate and multivariate indices of zooplankton community structure demonstrated that zooplankton communities in Killarney PP are recovering.
38 Evidence for recovery was found with increases in species richness and diversity across most of the lakes included in our survey and shifts in zooplankton community composition of acid- damaged lakes towards a composition more similar to reference lakes in Killarney PP and
Algonquin PP. Similar to Gray and colleagues’ (2012) findings, species evenness and total zooplankton abundance did not change with water quality improvements through time.
Zooplankton community composition also supported recovery, with recovered lake communities shifting from a state significantly different from circumneutral lake communities in 1972-73 to the two groups being indistinguishable in 2016. Although most of the lakes shifted from higher
PCA axis 1 scores to lower scores associated with circumneutral lakes through time, community structure in two of the neutral lakes, LaCloche and Bodina, became more similar to acid communities. LaCloche Lake was invaded by Bythotrephes longimanus, which has been shown to alter zooplankton biomass and diversity (Yan et al. 2002; Strecker & Arnott, 2005). Bell,
Carlyle, George, Johnnie, and Kakakise lakes have all recovered from pH<6 to pH>6, but have also all been invaded by Bythotrephes, which is reflected in their PCA axis scores being more similar to those of acid lakes compared to uninvaded recovered lakes (Figure 2.6). Bythotrephes preys on daphniids and bosminids, which are also sensitive to low pH and low Ca concentrations
(Azan et al. 2015), which makes it difficult to disentangle the effects of these individual stressors using field surveys. Bodina Lake is a very shallow, eutrophic lake. The observed shift towards a community structure more similar to acid lakes that occurred between the 1970s and 2016 resulted in a shift from an acid-sensitive copepod dominated community (including Tropocyclops extensus, Skistodiaptomus oregonensis, and Mesocyclops edax) to a Bosmina spp dominated community, but the reason for this shift is unknown as Bodina Lake has not been invaded by
Bythotrephes. Despite these few exceptions, temporal changes in zooplankton communities
39 generally reflected recovery as pH increased, with shifts towards community structure more similar to circumneutral lakes.
Along with increases in species richness and diversity in historically acidified Killarney
PP lakes, we also observed shifts in the relative abundance of zooplankton species and groups
(Figure 2.8). We found a decline in the relative abundance of copepods between 1972-73 and
2016, and an increase in the relative abundance of daphniids, bosminids, cyclopoid copepods, and large cladoceran zooplankton in the majority of the sampled lakes. Calanoid copepods, particularly Leptodiaptomus minutus, dominated acid lakes in Killarney PP in 1972-73 (Sprules
1975), as it has a high tolerance to acidity (Havens et al. 1993; Walseng et al. 2003). Daphniids, including Daphnia mendotae and Daphnia retrocurva, and the calanoid copepod,
Skistodiaptomus oregonensis, are acid-sensitive species (Havens et al. 1993); therefore, with increased pH in lakes after emission reductions, we observed an increase in the relative abundance of these groups.
In contrast, when using Algonquin PP zooplankton communities as our reference for recovery, we observed a significant difference in zooplankton community composition between recovered lakes in Killarney PP and undamaged lakes in Algonquin PP. This suggested that biological recovery might not be as complete in historically acid-damaged lakes in Killarney PP as originally documented, as these recovered communities are different from undamaged systems. All univariate community metrics, with the exception of total abundance, were significantly lower in Killarney PP lakes relative to Algonquin PP lakes, but when we compared only circumneutral lakes in Killarney PP to lakes in Algonquin PP, community structure was indistinguishable. Given the similarities in zooplankton species found in both parks, these results contradicted our previous support for biological recovery. Further investigation into using
40 Algonquin PP as a reference system for other areas on the Canadian Shield is required, but the lakes have demonstrated that the extent of recovery of acid-damaged lakes in Killarney PP as of
2016 was limited, and that acid-related variables are still prominent factors shaping communities in the park.
Factors influencing zooplankton community structure and recovery
With the improvement of acidity levels in our 44 study lakes in Killarney PP, pH was still one of the most important factors explaining variation in zooplankton community structure across all sampling years. Our study revealed that other variables, along with pH, are structuring communities. Ion concentrations, nutrient concentrations, lake morphometry (maximum depth and surface area), fish community, and the presence of the invasive macroinvertebrate predator,
Bythotrephes, were also important in explaining variation in crustacean zooplankton species richness, diversity, evenness, and abundance in the 44 lakes. Given the multiple changing environmental variables shaping zooplankton communities in Killarney PP, we need to focus on managing overall water quality improvement, not just pH, to sustain diverse, healthy communities.
Altough there is evidence that changes in ion concentration (e.g., Ca, Cl) and nutrients can shape zooplankton community composition (Vanni 1987; Yan et al. 2008; Palmer et al. 2013) we were not able to tease apart the individual effects of different ion or nutrient concentrations on zooplankton community metrics due to multicollinearity between many of these variables (see
Appendix K for correlation matrices). Calcium concentration is highly correlated with pH level in lakes (Pearson’s correlation coefficient, r=0.71, p<0.001), as Ca decline is a legacy effect of historical acid deposition. It was expected that aqueous Ca concentrations would be an important
41 variable in structuring zooplankton communities because many species, including Daphnia spp., some Bosmina spp., and some cyclopoids, including Mesocyclops edax, are susceptible to low Ca
(Azan and Arnott 2018). Daphniids require relatively high levels of aqueous Ca to undergo regular moult cycles of heavily calcified carapaces and to produce predator-defense structures for protection (Riessen et al. 2012; Cairns and Yan 2009). The impacts of Ca decline on zooplankton community structure in Killarney PP lakes might be masked by the pervasive influence of pH and acid-related variables in this study, but could also be contributing to the observed lag in biological recovery.
The presence or absence of predators, including fish communities and Bythorephes, were also found to be important variables explaining zooplankton community structure in recovering lakes and have been previously shown to impact zooplankton community structure (Lynch 1979;
Vanni 1988; Yan et al. 2001; Valois et al. 2010; Louette and De Meester 2007). Acid lakes that contained fish tended to be dominated by yellow perch, and Valois and colleagues (2010) found that these fish limited the survival of zooplankton, particularly Daphnia mendotae. Yan and colleagues (2004) also suggested that local factors, including predation by yellow perch, were preventing the recovery of cladoceran compared to copepod zooplankton, as cladocerans are generally more susceptible to both vertebrate and invertebrate predation (Yan et al. 2001;
Boudreau and Yan 2003). Lakes where fish were absent or had low diversity, had relatively high abundances of Chaoborus spp, including Clearsilver, Little Mountain, and Lumsden lakes
(Appendix F). High predation by Chaoborus favours zooplankton communities consisting of large-bodied species and small rotifers (Lynch 1979; Hanazato and Yasuno 1989). Chaoborus have also been observed to survive in pH≤3.5 (Havas and Likens 1985), therefore zooplankton species that are not adapted to high invertebrate predation may have a difficult time re-
42 establishing in this acid-structured lakes. Despite evading predation by macroinvertebrates, large-bodied zooplankton species, particularly the cladocerans, are more susceptible to Ca decline and fish predation, therefore these contasting responses to different stressors could be inhibiting recovery of zooplankton communities. Additionally, the introduction of the invasive macroinvertebrate predator, Bythotrephes longimanus, has been shown to decrease species richness, especially of cladocerans, in lakes of the Canadian Shield (Yan et al. 2002; Strecker and
Arnott 2005). The current community of predators may be impeding the re-establishment and survival of zooplankton through biological resistance as recovery progresses in acid-damaged lakes.
We also found that lake morphometry, including maximum depth and surface area, were important factors in structuring zooplankton communities in Killarney PP and Algonquin
PP. In general, large, deep lakes supported more diverse communities (Figure 2.13). Although this was not considered in our analyses, Gray and Arnott (2011) demonstrated that spatial variables that influence dispersal also contribute to zooplankton community structure, although explained less variation than did local environmental variables. The return and recovery of acid- sensitive species into a community depended on their presence and availability in the diapausing egg bank and the size of the watershed and number of stream connections within a lake (Gray and
Arnott 2011). Knapp and Sarnelle (2008) showed that depth is positively related to egg bank size in lakes, suggesting that larger lakes have larger banks of eggs available to aid in recovery.
Overland dispersal has also been demonstrated, but occurs at much slower rates (Gray and Arnott
2011). Although dispersal is known to contribute to zooplankton community structure in boreal lakes, the local and regional biotic and abiotic variables are shown to be the driving factors in this area (Labaj et al. 2015; Yan et al. 2004; Kurek et al. 2011).
43
Assessing the recovery of communities from disturbances is complicated by the impacts of multiple stressors acting simultaneously (Palmer et al. 2013) and requires a benchmark for recovery that encompasses this complexity. Using a temporal and reference lake approach, we demonstrated that further chemical and biological recovery of acidified lakes in Killarney PP has occurred, but recovery is not complete. Increased species richness and diversity, along with a shift in zooplankton community composition, showed evidence for recovery, although recovered lakes in Killarney PP are still distinguished from undamaged lakes in Algonquin PP. Continued monitoring for water chemistry and zooplankton communities will be necessary to tease apart the individual and interactive effects of changing water quality. Field surveys are useful tools for observing the impacts of multiple stressors in natural environments, but lend themselves more to correlative versus causative trends, especially with multiple collinear variables (Palmer et al.
2013). Using single point sample zooplankton surveys have also been shown to miss upwards of
50% of species in a lake (Arnott et al. 1998), which we attempted to control for by sampling at similar times of the year, but taking multiple samples at different times of the year would provide a more complete picture of the lake community. Killarney PP and the greater Sudbury, ON, region have provided an excellent resource for understanding and managing communities recovering from severe acid-deposition. The insights gained from this research that can be applied to developing regions that are still experiencing relatively high levels of emissions, such as China and South America (Larssen et al. 2006), or regions recovering from other point disturbances while being altered by multiple environmental and anthropogenic disturbances.
Conclusions
This study evaluated the continued chemical and biological recovery of crustacean zooplankton communities in 44 historically acidified lakes in Killarney PP. Although we provide
44 evidence for both chemical and biological recovery of historically acidified lakes within
Killarney PP, zooplankton communities in acid-damaged lakes have not recovered to a state similar to the reference lakes that did not experience this disturbance. The lagged recovery of zooplankton communities was explained primarily by factors related to acidity, but ion concentrations, nutrient concentrations, predation pressure, and lake morphometry also contributed to the variation in species richness, diversity, evenness, and total abundance of crustacean zooplankton. Given the multiple environmental and anthropogenic stressors continuing to impact freshwater systems on the Canadian Shield, it is becoming increasingly important to approach ecological questions from multiple stressor perspectives. Understanding pre-impact conditions, and assigning realistic recovery goals that encompass current changes occurring within a system is important for assessing the complex nature of recovery.
45
Table 2.1. Methodological details for zooplankton sampling in 44 Killarney Provincial Park lakes.
Year Survey months Net diameter Mesh size of Reference (cm) net (µm) 1972-73 July-September 30, 25 75, 100 Sprules, 1975 1990 August 25 76 Locke et al., 1994 2000 July-August 12.5 80 Holt and Yan, 2003 2005 July-August 25 80 Shead, 2007; Gray et al., 2012 2011 July-August 25 80 Arnott unpublished data 2016 July-August 25 80 Suenaga
46 Table 2.2. Scores from principal component analysis on measures of water quality from 44 lakes in Killarney Provincial Park. The first two score columns summarize results from a pooled analysis using water quality data from both 1972-73 and 2016 survey years, and the subsequent columns describe the loadings of the first two principal component axes on individual year analyses. SO4 = sulphate concentration, Si = silica, TP = total phosphorus, Secchi = secchi disc depth.
PC1 Score PC2 Score 1972 PC1 1972 PC2 2016 PC1 2016 PC2 Variable (41.4%) (26.5%) (31.2%) (23.6%) (42.5%) (28.5%)
pH 2.327 -0.627 1.544 -0.311 -1.597 -0.296
SO4 -1.531 -1.487 0.135 1.393 1.087 0.908
Si -0.984 -2.123 0.367 1.310 0.316 1.307
TP - - - - -1.041 0.577
Secchi -2.057 1.414 -1.562 0.121 1.148 -1.109
47 Table 2.3. Summary of trends in water quality measures from 44 lakes in Killarney Provincial Park from 1972-73 until 2016 using Mann-Kendall trend tests. Shaded rows represent trends determined using data from six survey years (1972-73, 1990, 2000, 2005, 2011, and 2016), and non-shaded rows represent trends determine using data from 2000 onward. Trends were significant if p<0.1, and the direction of positive ( ), negative ( ), or no trends were determined based on the tau value sign (+/−).
1972-73 1990 2000 2005 2011 2016 No. of lakes
Parameter Abbrev Units 0 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD pH − − 8 36 0 5.06 0.78 5.77 0.83 5.93 0.9 7.95 0.89 5.93 0.73 5.8 0.65 Conductivity − µS/cm 26 18 21.84 12.1 - - 29.18 10.13 27.57 12.33 22.77 12.71 21.99 12.32 Calcium Ca µg/L 31 13 - - - - 1.92 1.21 1.9 1.44 1.89 1.5 1.82 1.49 Total Phosphorus TP mg/L 1 42 1 - - - - 12.59 7.58 5.33 3.7 6.92 4.46 5.38 5.08 Dissolved Org. C DOC mg/L 7 37 - - - - 2.43 1.84 2.73 2.17 4.13 2.75 3.41 1.98 Chloride Cl mg/L 35 9 - - - - 0.56 0.57 0.7 1.03 0.61 0.99 0.48 0.86
Sulphate SO4 mg/L 40 4 9.64 4.46 - - 6.42 1.38 6.64 1.15 5.11 1.07 4.26 0.9 Sodium Na mg/L 25 17 - - - - 0.82 0.44 0.8 0.6 0.82 0.65 0.81 0.63 Silica Si mg/L 44 1.69 0.87 - - 0.45 0.34 0.6 0.39 0.62 0.33 0.83 0.45 Secchi Secchi m 34 10 8.29 4 7.95 6.31 7.68 5.46 8.93 6.37 6.5 4.17 7.69 5.45
48 Table 2.4. Abbreviations used in PCA and RDA plots for zooplankton species identified in lakes across Killarney Provincial Park and Algonquin Provincial Park.
Species Abbreviation Alonella excisa A.exci Acanthocyclops vernalis A.vern Bosmina spp. Bos.sp Ceriodaphnia lacustris C.lac Cyclops scutifer C.scut Chydorus sphaericus C.sph Cyclops strenuus C.stren Ceriodaphnia spp. Cd.sp Daphnia ambigua D.amb Diaphanosoma birgei D.birg Daphnia catawba D.cat Daphnia dentifera D.dent Daphnia dubia D.dub Daphnia longiremus D.long Daphnia mendotae D.mend Daphnia pulex/pulicaria D.pul Daphnia retrocurva D.ret Diacyclops thomasi D.thom Epischura lacustris E.lac Eucyclops serrulatus E.ser Holopedium glacialis H.glac Limnocalanus macrurus L.mac Leptodiaptomus minutus L.min Latona setifera L.set Leptodiaptomus sicilis L.sic Mesocyclops edax M.edax Ophryoxus gracilis O.grac Polyphemus pendiculus P.ped Senecella calanoides S.cal Sida crystillina S.crys Skistodiaptomus oregonensis S.oreg Skistodiaptomus reighardi S.reig Tropocyclops extensus T.ext
49 Table 2.5. Summary of multiple linear regression models on zooplankton community metrics explained by environmental and physical variables across 5 sampling years spanning 44 years from 44 lakes in Killarney Provincial Park. The first two PCA axes on water chemistry variables are used as predictor variables in the models: A1 consisting of ions (calcium, and A2 consisting of nutrients. Table cells are shaded according to the number of top models (AICc<2) based on Akaiki’s information criterion (AIC), darker colours representing the inclusion of the variable in more top models. Data for fish and Bythotrephes was not available in the first two survey years, and no nutrient data was available in 1990. Secchi disc depth was removed as a predictor variable in 2016 due to a high variance inflation factor. NS represents models that were not significant.
76-100% 51-75% 26-50%
1-25%
0% Not included
50
Table 2.6. Summary of multiple linear regression models on changes in zooplankton community metrics explained by changes in environmental variables between 1972-73 and 2016 from 44 lakes in Killarney Provincial Park. Shading of cells corresponds to the percentage of top models the variable is included in, based on delta AICc of <2. Secchi = secchi disc depth, Si= reactive silicate, SO4=sulphate concentration.
R2 of full Community metric Δ pH Δ Secchi Δ Si Δ SO4 DF AICc ΔAICc Weight model 2.681 1.357 4 204.8 0 0.396 Δ Species Richness 2.498 1.481 -0.0999 5 205.8 0.95 0.246 0.219 2.496 -0.0881 1.441 5 206.6 1.82 0.159
2.018 -0.1593 1.022 5 194.2 0 0.286 Δ Species Diversity 2.354 0.870 6 194.7 0.53 0.219 0.208 2.058 4 195.8 1.62 0.128
-0.041 3 14.3 0 0.305 Δ Evenness (Evar) -0.045 0.085 4 14.7 0.39 0.252 0.198 -0.046 0.008 4 16.0 1.75 0.127
-15.57 -2.558 4 426.4 0 0.152 Δ Total Abundance -2.203 3 426.5 0.11 0.144 0.082 1.566 -2.742 4 427.6 1.21 0.083 -13.63 1.111 -2.897 5 428.3 1.89 0.059
76-100%
51-75%
26-50%
0-25%
51 Table 2.7. Summary of permutation test results on redundancy analysis for constraining environmental and physical variables on zooplankton community structure across 5 sampling years on 44 lakes in Killarney Provincial Park. Shaded cells represent variables not included in the analysis. Only values from statistically significant constraints are shown. Secch = secchi disk depth, SO4 = sulphate concentration, TP = total phosphorus.
% % variation variation Year Depth Area Elevation Secchi pH SO4 TP explained explained by RDA by RDA axis 1 axis 2 1972 F=2.69 F=7.12 F=4.02 F=8.41 F=2.03 24.9 8.0 p=0.012 p=0.001 p=0.001 p=0.001 p=0.04
1990 F= 4.23 F=3.89 F=2.47 F=3.89 15.8 7.8 p=0.001 p=0.001 p=0.009 p=0.001 2000 F=2.72 F=2.91 F=3.98 F=2.53 15.0 4.9 p=0.001 p=0.002 p=0.001 p=0.004 2005 F=2.32 F=3.73 F=3.73 F=2.13 F=3.38 F=2.73 16.3 7.5 p=0.009 p=0.002 p=0.001 p=0.015 p=0.001 p=0.006 2016 F=3.09 F=4.90 F=3.43 13.6 6.6 p=0.001 p=0.001 p=0.001
52 Figure 1.1. Map of Killarney Provincial Park, Ontario, Canada, with lakes shaded by water quality categories. Lakes shaded in red represent acid lakes (pH<6 since 1972-73), blue represents lakes that have shifted from pH<6 in 1972-73 to pH>6 as of 1990 or later, and green represents lakes that have had pH>6 since 1972-73.
Acid lakes Recovered lakes Neutral lakes (pH<6 since 1972-73) (pH<6 to pH>6 between (pH>6 since 1972-73) 1972-73 and 2016)
53 Algonquin PP
Killarney PP
Figure 2.1. Zooplankton species occurrence in 55 lakes in Algonquin Provincial Park (2015) represented by grey bars and 44 lakes in Killarney Provincial Park (2016) represented by black bars. Species that occurred in less than 20% of sampled lakes in both parks are not included.
54
Acid Recovered Neutral
Figure 2.2. Comparison of hydrogen ion (H+) concentration in 1972-73 to 2016 in 44 lakes in Killarney Provincial Park sorted into three groups corresponding to water quality improvements. Acid = lakes with pH<6, Neutral=lakes with pH>6, Recovered= lakes that changed from pH<6 to pH>6 between 1972 and 2016. Red lines on histograms represent mean H+ concentration equal to pH 6.
55 acid neutral recovered
0.4
e
r
o
c
S
0.2
1
A
C
P 0.0
6
1
0 2 −0.2
−0.4 −0.6 −0.4 −0.2 0.0 1972 PCA 1 Score
Figure 2.3. Comparison of Principal Component Axis 1 (explaining 41.4% of variation) water chemistry scores between 1972-73 and 2016 in 44 lakes in Killarney Provincial Park, categorized by water quality changes (red circles represent acid lakes that have had a pH<6 since 1972-73, green squares represent circumneutral lakes that have had a pH>6 since 1972-72, and blue diamonds represent lakes that have from pH<6 to pH>6 between the years of 1990 and 2016). The dashed line is the 1:1, indicating no change in PCA 1 score between years. Axis loading scores are provided in Table 2.2.
56 acid neutral recovered
0.50 a) 1972-73
e
r 0.25 o c
S
1 0.00 A C
P
6 −0.25 1
0 2 −0.50
−0.6 −0.4 −0.2 0.0 1972 PCA 1 Score
b) 2016
Figure 2.4. Principal component analysis on water quality measurements (blue arrows) in 44 lakes in Killarney Provincial Park in a) 1972-73 and b) 2016. Lakes are categorized into three groups based on water quality improvements: acid (pH<6 since 1972-73), recovered (pH recovered from < 6 to > 6 after 1972-73 and before 2016), and circumneutral (pH >6 since 1972- 73). TP = Total phosphorus, SO4 = sulphate concentration, Si= Reactive silicate concentration, Secchi = Secchi disc depth.
57 10.0
s
y
t
s 6
i
e
s
r
n
e
h
v
i
c
i
d
r
7.5
s
s
e
e
i
i
c 4
c
e
e
p
p
S S 5.0
2
1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 Year Year
0.5 50
)
L
/
s
# s 40
0.4 (
e
e
n
c
n
n
e
v a 30
e
d
n
s
0.3 u
e
i
b
c
a
e l 20
p
a
t
S
o 0.2 T 10
1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 Year Year
acid neutral recovered 0.50 0.2 Figure 2.5. Mean zooplankton a) species richness, b) species diversity, c) species
s
e evenness, d) total abundance of crustacean
r
e
o
r c 0.25 zooplankton, and e) principal components
s
0.0 o
1 analysis axis 1 scores (explaining 16.1% of c
s
i
S variation in community composition) over five
x
a
1 sampling years of 44 lakes in Killarney
A 0.00 C −0.2 Provincial Park categorized by water quality
A P improvements: acid (n=22) = lakes with pH<6, C
P recovered (n=14) = lakes that shifted from pH<6
6 to pH>6 between 1972 and 2016, and −0.4 −0.25 1970 1980 1990 20001 2010 circumneutral (n=8) = lakes with pH>6. Error Year 0
2 bars represent standard error.
−0.50 58 −0.6 −0.4 −0.2 0.0 1972 PCA 1 Score acid neutral recovered
L.MIN *
D. BIRG M. EDAX
e
r 0.25 S. OREG
o D. RET c D. MEND
S
E. LAC
1
*
A 0.00
C * *
P
Bodina * *
6 LaCloche 1 * * 0 −0.25 *
2
−0.4 −0.2 0.0 0.2 1972 PCA 1 Score
Figure 2.6. Comparison of Principal Component Axis 1 (16.1%) species scores between 1972- 73 and 2016 in 44 lakes in Killarney Provincial Park, categorized by water quality changes (red circles represent acid lakes that have had a pH<6 since 1972-73, green squares represent circumneutral lakes that have had a pH>6 since 1972-73, and blue diamonds represent lakes that have increased from pH<6 to pH>6 between the years of 1972-73 and 2016). The dashed line is the 1:1, indicating no change in PCA 1 score between years. Asterisks (*) represent lakes that have been invaded by Bythotrephes longimanus based on surveys conducted in 2008 and circled asterisks represent lakes in the 2016 survey where Bythotrephes was observed. Green arrows and species abbreviations represent zooplankton species with highest loadings on PCA 1 associated with circumneutral lakes, and the red arrow with species abbreviation represents the zooplankton species with highest loading on PCA 1 associated with acid lakes.
59 acid neutral recovered 0.50 a) 1972-73
e
r 0.25
o
c
S
1 0.00
A
C
P
6 −0.25 1
0
2
−0.50
−0.6 −0.4 −0.2 0.0 1972 PCA 1 Score
b) 2016
Figure 2.7. Principal component analysis of zooplankton species abundances in 44 lakes in Killarney Provincial Park in a) 1972-73 and b) 2016, categorized into three groups based on water quality improvements: acid (pH<6 since 1972-73), recovered (pH recovered from < 6 to > 6 after 1972-73 and before 2016), and circumneutral (pH >6 since 1972-73). Red arrows represent species, but species with short arrows were removed to reduce crowding. Species abbreviations can be found in Table 2.4.
60 acid neutral recovered
0.50
e
r 0.25 o c
S
1 0.00 A C
P
6 −0.25 1
0 2 −0.50
−0.6 −0.4 −0.2 0.0 1972 PCA 1 Score
Figure 2.8. Comparisons of the relative abundances of a) Daphnia spp, b) Bosmina spp, c) Holopedium glacialis, d) large cladocerans (including Daphnia spp, Holopedium, S. crystillina), e) copepod species, and f) cyclopoid species between 1972-73 and 2016.
61 acid neutral recovered 0.50 a) 1972-73
e r 0.25
o c
S
1 0.00 A C
P
6 −0.25
1
0 2
−0.50 −0.6 −0.4 −0.2 0.0 1972 PCA 1 Score b) 2016
Figure 2.9. Redundancy analysis on zooplankton species abundances and environmental and physical constraints in a) 1972-73 and b) 2016 for 44 lakes in Killarney Provincial Park. Environmental and physical variables are represented by the blue arrows, and species are abbreviated in red according to Table 1. Bolded variables represent significant (p<0.05) explanatory variables of zooplankton community structure based on permutation tests of redundancy analysis. Species with short arrows were removed to lessen crowding. TP= Total Phosphorus, Depth = maximum depth, Secchi = Secchi disc depth.
62
Figure 2.10. Comparison of univariate zooplankton community metrics, including a) species richness, b) species diversity, c) species evenness, and d) total abundance of crustacean zooplankton, in 55 lakes in Algonquin Provincial Park (light grey) and 44 lakes in Killarney Provincial Park (dark grey). Asterisks indicate results of a two-sampled t-test comparing mean community metrics in each park.
63
Figure 2.11. Comparison of univariate zooplankton community metrics from lakes in Algonquin Provincial Park (n=55), and lakes in Killarney Provincial Park categorized by water quality improvements: acid (pH<6 since 1972-73), recovered (pH recovered from < 6 to > 6 after 1972- 73 and before 2016), and circumneutral (pH >6 since 1972-73). The letters indicate significant results from Tukey post-hoc tests (p<0.05).
64
0.8
0.4
0
−0.4
−0.8
−0.4 −0.2 0 0.2 0.4 0.6 0.8
Algonquin PP lakes
Killarney PP neutral
Killarney PP recovered
Killarney PP acid
Figure 2.12. Principal components analysis on zooplankton species abundances in 55 lakes in Algonquin Provincial Park and 44 lakes in Killarney Provincial Park categorized by lake water quality improvements: grey points represent lakes in Algonquin PP, red points represent acid lakes in Killarney PP, blue points represent recovered lakes in Killarney PP, and green points represent neutral lakes in Killarney PP. Species abbreviation are listed in Table 2.4. Species with short arrows were removed to lessen crowding.
65
a)
b)
Figure 2.13. Redundancy analysis plots of zooplankton species abundances and environmental and physical constraints in a) Killarney Provincial Park (n=44) and b) Algonquin Provincial Park (n=55). Environmental and physical variables are represented by the blue arrows, and species are abbreviated in red according to Table 1. Bolded variables represent significant (p<0.05) explanatory variables of zooplankton community structure based on permutation tests of redundancy analysis. Species with short arrows were removed to lessen crowding. Depth = maximum depth, Secchi = Secchi disc depth, SO4= sulphate concentration, TP= total phosphorus.
66
CHAPTER 3
General Discussion
Understanding and evaluating the recovery of freshwater ecosystems from historical acidification has been of interest for many years in North America and Europe (Driscoll et al.
2001). Lakes in Killarney Provincial Park have been a useful resource for understanding community responses to changes in acid deposition as 44 lakes have been sampled intermittently over the last half-century starting in peak acidification (1972) through to decades after emission reductions in 2016 (Sprules 1975; Locke et al. 1994; Holt and Yan 2003; Gray et al. 2012).
Lakes in Killarney PP experienced varying degrees of acid deposition resulting from the sulphur dioxide and nitrogen oxide emissions released by the Sudbury smelters located 40-60km away.
The acidification of freshwater lakes and streams in the park resulted in widespread damage to biota, including reduced species richness and altered community composition of phytoplankton, zooplankton, macroinvertebrate, and fish populations (Beamish and Harvey 1972; Sprules 1975;
Griffiths and Keller 1992). After the implementation of national and international legislation for emission reduction controls, decreased acidity was observed with increased pH and lower sulphate concentrations in lakes (Keller and Pitblado 1986; Stoddard et al. 1999; Gunn and Keller
1998, Keller et al. 2001). Despite documented chemical recovery of lakes in Killarney Provincial
Park, a delay in biological recovery was observed (Gray et al. 2009; Gray et al. 2012; Valois et al. 2010). This observed lag has been attributed to changes in the local environment, including calcium decline and altered nutrient and DOC concentrations (Palmer et al. 2013), biological resistance from acid-structured communities (Valois et al. 2010), and factors limiting dispersal
(Yan et al. 2001; Gray et al. 2011). Given the multiple environmental and anthropogenic historical and current changes occurring across lakes of the Canadian Shield (Palmer et al. 2011),
67 the need to study recovery within a multiple stressor context has been encouraged (Yan et al.
1996; Keller 2009; Palmer et al. 2013).
The objectives of this study were to assess the chemical and biological recovery of acidified lakes in Killarney Provincial Park and evaluate the relative importance of local abiotic and biotic variables in structuring recovering zooplankton communities. We used large-scale, replicated lake surveys of Killarney PP to examine changes in water quality and zooplankton community structure between years of peak acidification and decades after the implementation of emission reductions programs. We provided continued evidence of both chemical and biological recovery of acidified lakes of Killarney PP, but found that biological recovery was not complete when using undamaged lakes of Algonquin PP as a reference system. Zooplankton communities in lakes of Killarney PP have continued to be shaped by acidification-related variables from
1972-73 to 2016, but the relative importance of other variables, including nutrient concentrations and biotic interactions, have become more prominent in more recent sampling years (2000 onwards).
The continued monitoring of the 44 lakes in Killarney PP allowed us to observe further changes in the ecologically important zooplankton communities with changes in water quality.
Understanding how communities respond to disturbances in their environment within a multiple stressor context will become increasingly important as the human population continues to grow and develop. The effects of acidification, climate change, invasive species, and development are international issues, and are of particular concern for freshwater ecosystems that are disproportionately impacted my multiple stressors (Sala et al. 2000). Large-scale field surveys have been useful for providing accurate depictions of natural environments (Palmer et al. 2013), but more controlled laboratory and field experiments will be needed to tease apart the effects of
68 stressor interactions on community composition. Overall, we have demonstrated that human- induced changes of the biotic and abiotic environment can influence community structure and the extent to which historically damaged communities are able to recover.
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82
APPENDIX A: Killarney Provincial Park Lake Survey, Physical Variables
Table A.1. Select physical variables of 44 lakes in Killarney Provincial Park, Ontario, and their water quality status as of the 2016 sampling year (acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972-73). Depth is the maximum lake depth, area is the lake surface area.
Lake Status Depth (m) Area (ha) Elevation (m) Acid acid 30.1 17.7 272 AY Jackson recovered 9.9 6.1 197 Bell recovered 26.1 281.3 223 Bodina neutral 2.8 30.3 210 Boundary acid 8.4 74.1 223 Carlyle recovered 14.2 166.9 218 Charlton neutral 17.9 218.9 200 Clearsilver acid 13.5 23.9 222 David acid 25 325.8 243 deLamorandiere acid 7 5.3 294 Fish recovered 7.6 90.7 212 Freeland acid 2.3 32.2 191 Frood recovered 18.4 191.8 196 Gail acid 16.4 16.6 252 Gem neutral 19.7 14.2 214 George recovered 39.1 147.9 185 Great Mountain acid 38.9 191.6 224 Helen neutral 42.2 68.2 185 Howry neutral 27.6 101.9 201 Ishmael neutral 19.5 65.4 182 Johnnie acid 34.3 395.5 200 Kakakise recovered 25.7 118.9 190 Killarney acid 55.1 357.2 199 LaCloche neutral 35.1 1088.3 192 Little Mountain acid 25.2 20 232 Little Sheguindah recovered 2.6 5 184 Little Superior acid 38.9 12.1 276 Logboom acid 6 6 220 Low neutral 28.8 28.6 182 Lumsden acid 22.6 21.5 213 Muriel acid 13.4 22.6 194 Nellie acid 49.7 238.3 267 Norway acid 35 59.6 198 OSA acid 39.9 291.4 205 Partridge recovered 17.7 9.2 203 Proulx acid 28.9 10.5 257 RuthRoy acid 18.5 46.1 217 Shingwak acid 21.4 4.6 282 Solomon acid 5 5.2 292 Terry acid 8.1 10.1 212 ThreenarrowsEast recovered 54.6 947.9 197 ThreenarrowsNorth recovered 36.3 947.9 197 Turbid acid 9.3 14.8 217 Whiskeyjack acid 42.5 13.8 276 83 APPENDIX B: Killarney Provincial Park Lake survey: water chemistry variables 1972-73 to 2016
Table B.1. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Sprules (1975). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972-73. Secchi = secchi disk depth, TP = total phosphorus, SO4 = sulphate, Si= reactive silicates.
Secchi TP SO4 Si Lake Status pH (m) (µg/L) (mg/L) (mg/L) Acid acid 2.4 4.8 0.8 12.1 1.63 AY Jackson recovered 6.9 5 0.06 10 1.08 Bell recovered 6.9 5.2 0.11 12 1.95 Bodina neutral 2.4 6.3 0.15 11 0.95 Boundary acid 9.5 4.2 0.21 6 1.35 Carlyle recovered 7.6 5 0.5 8 2.9 Charlton neutral 5.1 6.2 0.09 3 1.35 Clearsilver acid 10.8 4.3 0.15 5 1.83 David acid 12.9 4.6 0.15 12 1.63 deLamorandiere acid 4.3 5 0.35 12.5 1.5 Fish recovered 5.7 5.7 0.08 5 1.51 Freeland acid 1.8 4.2 0.12 16 0.85 Frood recovered 6.3 5.9 0.15 14 0.9 Gail acid 10.2 3.8 0.03 5 0.21 Gem neutral 5 6.1 0.08 8 0.87 George recovered 9 4.9 0.19 13 2.5 Great Mountain acid 8.6 4.4 0.11 10 0.65 Helen neutral 6 7 0.05 6 1.36 Howry neutral 6 6 0.09 5 1.48 Ishmael neutral 5.1 6.4 0.03 8 0.92 Johnnie acid 9.3 5.1 0.05 15 2.2 Kakakise recovered 10.1 5.6 0.04 22 3.3 Killarney acid 11.3 4.7 0.04 12 1.57 LaCloche neutral 2.5 6 0.13 4 2.2 Little Mountain acid 14.8 4.4 0.08 6 1.98 Little Sheguindah recovered 2.4 5 0.17 7 2.33 Little Superior acid 12.3 4.5 0.05 6 0.53 Logboom acid 5.5 5.3 0.09 18 1.73 Low neutral 7.3 7 0.06 9 1.5 Lumsden acid 8 4.4 0.21 8 3.3 Muriel acid 7.1 4.8 0.12 13 1.65 Nellie acid 20.9 4.1 0.15 7 0.94 Norway acid 12.5 4.7 0.15 14 2.95 OSA acid 13.2 4.8 0.15 7.5 1.02
84 Secchi TP SO4 Si Lake Status pH (m) (µg/L) (mg/L) (mg/L) Partridge recovered 12.4 5.2 0.12 18 2.18 Proulx acid 13.1 4.6 1 7 1.85 RuthRoy acid 12.8 4.5 0.05 8 0.93 Shingwak acid 10.3 4.6 0.9 2 0.8 Solomon acid 4.3 5 0.37 10 1.65 Terry acid 8 4.2 0.24 6 2.12 Threenarrows East recovered 6.4 5.2 0.12 7 4 Threenarrows North recovered 6.4 5.2 0.12 7 4 Turbid acid 7.3 4.6 0.13 17 1.15 Whiskeyjack acid 14 4.2 0.13 12 1.24
85
Table B.2. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Locke and colleagues (1994). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972-73. Secchi = secchi disk depth.
Lake Status Secchi (m) pH Acid acid 8 5.15 AY Jackson recovered 5.5 6.25 Bell recovered 4.7 6.08 Bodina neutral 2.5 6.95 Boundary acid 9 5.25 Carlyle recovered 4 6.65 Charlton neutral 5 6.55 Clearsilver acid 12 4.85 David acid 6.5 4.9 deLamorandiere acid 5 5.1 Fish recovered 4.5 6.25 Freeland acid 6 6.05 Frood recovered 5.5 7 Gail acid 12 4.6 Gem neutral 4 6.6 George recovered 6 6.35 Great Mountain acid 7 5.15 Helen neutral 6 7 Howry neutral 4 6.85 Ishmael neutral 6 6.95 Johnnie acid / 5.32 Kakakise recovered 5.5 6.5 Killarney acid 23 5.6 LaCloche neutral 3 7 Little Mountain acid 3 4.85 Little Sheguindah recovered 2 6.1 Little Superior acid 18 4.35 Logboom acid 3 5.3 Low neutral 7 7.15 Lumsden acid 6.5 5.25 Muriel acid 10.5 5.95 Nellie acid 34 4.55 Norway acid 15 5.1 OSA acid 21 5.15 Partridge recovered 10 5.05 Proulx acid 7 4.65
86 Lake Status Secchi (m) pH RuthRoy acid 15 5.1 Shingwak acid 9 4.85 Solomon acid 3.5 6.05 Terry acid 2.5 5.9 Threenarrows East recovered 4.17 6.54 Threenarrows North recovered 4.17 6.54 Turbid acid 6 5.65 Whiskeyjack acid 6 4.75
87
Table B.3. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Holt and Yan (2003). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972- 73. Secchi = secchi disk depth, TP= total phosphorus, DOC = dissolved organic carbon, Cl= chloride, SO4=sulphate, Na=sodium, K=potassium, Si= reactive silicates, TKN=total Kjeldahl nitrogen, Al=aluminum, Fe=iron, Cu=copper, Zn=zinc, Ni=nickel, Mg=magnesium, DIC=dissolved inorganic carbon, Pb=lead, Mn=manganese.
Secchi Conductivity TP DOC Ca Cl SO4 Na K Lake Status pH (m) (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Acid acid 7.85 5.28 21 4 0.9 1.1 0.4 5.5 0.52 0.23 AY Jackson recovered 6.25 6.25 25 12 3.4 1.55 0.6 5 0.86 0.39 Bell recovered 3.5 6.39 27 6 4.2 1.9 0.4 6 0.84 0.41 Bodina neutral 1.8 7.18 41 24 9.2 3.35 0.4 5 1.3 0.41 Boundary acid 6.7 6.12 21 16 2.3 1.3 0.4 6 0.62 0.34 Carlyle recovered 4.25 6.43 27 8 3.2 1.8 0.6 6.5 0.94 0.36 Charlton neutral 4.1 7.2 63 12 3.6 5 3.8 10.5 3.02 0.61 Clearsilver acid 5.85 4.92 22 16 0.9 1 0.4 6.5 0.54 0.26 David acid 7.1 5.2 21 8 1.3 1.2 0.4 5.5 0.54 0.28 deLamorandiere acid 4.3 5.27 20 4 2.9 1 0.4 5 0.58 0.23 Fish recovered 3.65 6.68 24 12 3.4 1.65 0.4 4.5 0.84 0.36 Freeland acid 2.125 6.42 27 32 2.8 1.75 0.6 6.5 0.98 0.39 Frood recovered 4.5 6.9 38 16 3.2 2.8 1.6 7 1.42 0.38 Gail acid 16.4 4.6 24 4 0.1 0.7 0.2 6.5 0.38 0.13 Gem neutral 4.85 6.78 28 12 4.3 2.3 0.4 5 0.88 0.4 George recovered 6.4 6.44 25 8 1.8 1.75 0.4 6.5 0.74 0.33 Great Mountain acid 8.1 5.86 21 12 2.1 1.35 0.4 6.5 0.66 0.29 Helen neutral 5.7 7.06 30 12 3.2 2.4 0.4 6 0.84 0.37 Howry neutral 6 6.8 30 18 4 2.5 0.4 5.5 0.86 0.4 Ishmael neutral 4.55 7.06 33 6 3.4 2.6 0.4 6 0.9 0.41 Johnnie acid 3.4 6.12 26 10 3.1 1.65 0.4 7 0.76 0.37 Kakakise recovered 4.625 6.75 30 8 2.9 2.15 0.8 5.5 0.84 0.36 Killarney acid 10.25 5.27 25 2 0.4 1.45 0.4 7 0.62 0.3
88 Secchi Conductivity TP DOC Ca Cl SO4 Na K Lake Status pH (m) (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) LaCloche neutral 3.6 7.23 45 16 4.6 3.75 1.4 6.5 1.52 0.58 Little Mountain acid 13.35 5.15 24 4 0.2 1.4 0.4 7.5 0.58 0.27 Little Sheguindah recovered 2.6 6.8 30 24 4.3 1.65 0.4 5 1.16 0.73 Little Superior acid 19.65 4.33 39 4 0.2 0.9 0.4 9.5 0.34 0.21 Logboom acid 3.35 6.35 26 22 3.9 1.9 0.4 6 0.84 0.41 Low neutral 7.4 7.67 71 8 3.1 7.85 1.4 8 1.46 0.59 Lumsden acid 6.55 5.52 21 12 1 1.3 0.4 5 0.52 0.2 Muriel acid 9.1 5.94 26 12 1.2 2 0.4 7.5 0.72 0.27 Nellie acid 22.65 4.63 33 28 0.3 1.4 0.4 5 0.52 0.22 Norway acid 9.55 5.35 24 8 1 1.55 0.4 9 0.66 0.3 OSA acid 13.5 4.93 30 16 0.3 1.95 0.4 5 0.66 0.28 Partridge recovered 8 6 27 6 1.9 2 0.4 5 0.76 0.31 Proulx acid 19.05 4.54 36 36 0.2 1.35 0.4 9.5 0.5 0.25 RuthRoy acid 8.25 4.75 26 16 0.4 1.1 0.4 5.5 0.56 0.19 Shingwak acid 20.35 4.71 27 10 0.2 1.15 0.2 7 0.44 0.24 Solomon acid 1.6 5.36 20 16 2.8 1.2 0.4 6 0.64 0.24 Terry acid 4.25 5.92 22 10 5.7 1.4 0.4 6.5 0.82 0.35 Threenarrows E recovered 4.9 6.34 26 12 2.9 1.8 0.4 6 0.82 0.37 Threenarrows N recovered 4.9 6.34 26 12 2.9 1.8 0.4 6 0.82 0.37 Turbid acid 4.3 5.46 25 16 3.2 1.45 0.4 7.5 0.92 0.37 Whiskeyjack acid 18.8 4.6 31 4 0.1 1.15 0.4 8.5 0.44 0.22
89 Table B.3. continued
Si TKN Al Mg DIC Lake Fe (µg/L) Zn (µg/L) Ni (µg/L) (mg/L) (µg/L) (µg/L) (mg/L) (mg/L) Acid 0.76 0.12 98.3 15.5 15.7 4.68 0.42 0.2 AY Jackson 0.2 0.36 26.5 44.1 17.3 2.98 0.66 0.6 Bell 0.56 0.22 35.2 67.6 6.16 7.04 0.72 0.4 Bodina 0.84 0.76 18.1 54.6 1.95 2.18 1.34 2 Boundary 0.02 0.24 11 25.3 2.61 2.51 0.52 0.2 Carlyle 0.6 0.22 18.3 74.7 6.22 3.97 0.72 0.2 Charlton 0.18 0.24 10.4 30.4 1.57 6.84 1.58 2 Clearsilver 0.68 0.1 125 29.1 13.2 10.5 0.4 0.2 David 0.24 0.12 49 48.7 8.6 8.9 0.42 0.2 deLamorandiere 0.24 0.28 85.1 35.6 11.9 4.23 0.455 0.2 Fish 0.24 0.24 9.96 37.4 0.593 1.67 0.64 0.2 Freeland 0.44 0.32 124 65.4 7.03 2.78 0.7 0.6 Frood 0.16 0.24 17 39.5 0.848 2.51 1.02 1.2 Gail 0.08 0.12 209 57.5 13.6 11.7 0.239 0.2 Gem 0.28 0.28 22.7 53.5 2.99 3.39 0.74 1.2 George 0.42 0.16 7.98 7.46 5.91 2.61 0.7 0.2 Great Mountain 0.26 0.16 19.4 45.9 4.32 3.68 0.5 0.2 Helen 0.76 0.2 8.93 6.3 2.08 1.11 0.94 1 Howry 0.6 0.22 16.4 18.5 2.3 2.87 0.875 0.8 Ishmael 0.48 0.2 4.77 13.3 0.73 2.03 1.05 0.8 Johnnie 0.82 0.2 31.4 29.1 7.56 6.16 0.64 0.2 Kakakise 0.08 0.2 8.39 7.26 2.18 1.39 0.82 0.4 Killarney 1.08 0.08 103 10.3 13.9 7.66 0.54 0.2 LaCloche 0.32 0.28 8.78 25.5 0.789 0.906 1.52 2.6 Little Mountain 0.88 0.08 94.9 23.5 11.6 10.3 0.42 0.2 Little Sheguindah 0.28 0.4 152 50.6 5.06 1.53 1.08 1.2 Little Superior 0.08 0.04 557 64.8 22.6 12.8 0.3 0.2
90 Si TKN Al Mg DIC Lake Fe (µg/L) Zn (µg/L) Ni (µg/L) (mg/L) (µg/L) (µg/L) (mg/L) (mg/L) Logboom 0.48 0.28 43.4 83.5 5.59 5.83 0.7 0.6 Low 0.52 0.16 6.11 3.6 1.22 0.209 2.1 5.6 Lumsden 1.04 0.1 69.7 30.9 14.9 4.59 0.48 0.4 Muriel 0.22 0.16 18.2 16.7 7.63 2.63 0.62 0.2 Nellie 0.2 0.06 427 29.7 19.7 10.5 0.42 0.6 Norway 1.1 0.1 78 10.2 12.9 8.31 0.58 1 OSA 0.08 0.06 122 8.8 16.2 7.24 0.6 0.8 Partridge 0.16 0.2 30.6 17.1 9.26 4.46 0.7 1 Proulx 0.12 0.08 481 32.9 22.7 12.5 0.48 0.2 RuthRoy 0.48 0.08 265 34.2 17 13.1 0.4 0.6 Shingwak 0.12 0.08 254 35.2 20.6 9.54 0.36 0.2 Solomon 0.32 0.28 86.6 43.5 9.79 3.48 0.42 0.2 Terry 0.92 0.34 119 289 9.65 6.59 0.58 0.8 Threenarrows E 1.16 0.2 17.2 9.91 6.05 4.3 0.82 0.4 Threenarrows N 1.16 0.2 17.2 9.91 6.05 4.3 0.82 0.4 Turbid 0.14 0.28 84.1 137 9.99 8.09 0.62 0.2 Whiskeyjack 0.08 0.08 415 24.9 19.9 13.2 0.38 0.2
91 Table B.3. continued
Pb Anions Cations Lake Mn (µg/L) (µg/L) (meq/L) (meq/L) Acid -1.01 0.167 0.118 118 AY Jackson 0.794 0.182 0.181 21.1 Bell 1.94 0.21 0.203 37 Bodina 1.84 0.351 0.353 25.9 Boundary -0.0623 0.183 0.145 6.34 Carlyle -1.49 0.218 0.201 71.5 Charlton 4.03 0.553 0.525 28 Clearsilver 2.51 0.173 0.114 128 David -0.444 0.157 0.125 73.2 deLamorandiere 1.65 0.15 0.12 77.4 Fish 6.22 0.207 0.183 18.1 Freeland 4.13 0.238 0.198 13.3 Frood 5.75 0.321 0.294 18.4 Gail 4.22 0.157 0.0765 92 Gem -5.49 0.235 0.222 18.8 George 4.22 0.201 0.186 26 Great Mountain 6.98 0.185 0.146 52.1 Helen -0.347 0.279 0.243 3.69 Howry 4.22 0.254 0.237 23.1 Ishmael 2.13 0.3 0.261 16.7 Johnnie -0.443 0.214 0.18 50.3 Kakakise 3.84 0.238 0.221 16.2 Killarney -1.2 0.194 0.154 110 LaCloche 0.509 0.427 0.394 12.6 Little Mountain 2.32 0.199 0.139 249 Little Sheguindah 0.508 0.246 0.24 10.5 Little Superior 4.79 0.218 0.0909 139
92 Anions Cations Lake Pb (µg/L) Mn (µg/L) (meq/L) (meq/L) Logboom 1.27 0.201 0.201 22.5 Low 2.89 0.686 0.643 1.92 Lumsden -4.35 0.156 0.132 88.8 Muriel 0.224 0.21 0.19 33.5 Nellie 4.32 0.147 0.134 187 Norway -3.01 0.236 0.16 56.6 OSA -0.919 0.156 0.183 119 Partridge 3.27 0.164 0.201 30.1 Proulx 1.27 0.23 0.136 123 RuthRoy -0.253 0.149 0.12 78 Shingwak -0.348 0.177 0.114 125 Solomon 1.94 0.175 0.132 39.8 Terry 1.93 0.202 0.165 73.7 Threenarrows E 1.27 0.207 0.197 24.5 Threenarrows N 1.27 0.207 0.197 24.5 Turbid 0.315 0.209 0.175 23.1 Whiskeyjack -4.63 0.209 0.116 441
Pb concentrations are reported with uncertainty resulting in negative numbers, which arised from inter-element and background corrections that were applied. The method detection limit for Pb concentration using the MET3474 scan is 0.05 and the zero value (W) was 0.01 µg/L as determined by the Ontario Ministry of Environment.
93 Table B.4. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Shead (2007) and Gray et al. (2012). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972-73. Secchi = secchi disk depth, TP= total phosphorus, DOC = dissolved organic carbon, Cl= chloride, SO4=sulphate, Na=sodium, K=potassium, Si=reactive silicates, TKN=total Kjeldahl nitrogen, Al=aluminum, Fe=iron, Cu=copper, Zn=zinc, Ni=nickel, Mg=magnesium, DIC=dissolved inorganic carbon, Pb=lead, Mn=manganese.
Conductivity TP DOC Ca Cl SO4 Lake Status Secchi (m) pH (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) Acid acid 8.5 5.3 18.3 2.6 1.6 1.1 0.35 5.55 AY Jackson recovered 8.3 6.3 19.8 6.1 3.3 1.4 0.34 6.55 Bell recovered 3.6 6.6 25.5 5.1 5.8 1.8 0.56 6.75 Bodina neutral 1.8 6.9 NA 19.4 10 3.2 0.43 6.4 Boundary acid 8 6 19.5 4.2 1.4 1.1 0.33 5.35 Carlyle recovered 3.6 6.4 22.6 10.2 3.6 1.6 0.55 6.5 Charlton neutral 4.6 7.3 62.2 6 4.3 5 4.76 9.5 Clearsilver acid 11.2 5.2 18.7 1.8 0.9 0.7 0.26 5.55 David acid 4.9 5.5 17.5 3.1 1.5 1.1 0.56 5.3 deLamorandiere acid 7.6 5.1 NA 5.3 1.4 1 0.22 5.8 Fish recovered 3.8 6.5 25.7 6.1 4.4 1.9 1.17 5.6 Freeland acid 2.4 5.7 21.6 7.2 3.4 1.6 0.08 6.8 Frood recovered 4.4 7.3 61.4 11.2 4.4 4.9 4.87 9.45 Gail acid 15.5 4.6 20.8 2.8 0.5 0.6 0.29 5.35 Gem neutral 3.5 6.8 27.3 8.1 5.2 2.5 0.47 5.35 George recovered 8 6.6 24.9 3.5 1.9 1.8 0.44 6.7 Great Mountain acid 7.1 6 20.1 12.9 2.6 1.4 0.33 5.95 Helen neutral 6.6 7.1 26.8 3.6 3.4 2.6 0.31 6.25 Howry neutral 4.5 6.9 28.8 7.2 4.8 2.7 0.48 5.85 Ishmael neutral 6.8 7 29.2 4.8 4 2.8 0.33 6.05 Johnnie acid 4.3 6.2 23.6 4.5 3.5 1.7 0.37 6.8 Kakakise recovered 6.9 6.8 32.2 2.6 3 2.4 0.63 6.65 Killarney acid 13.6 5.4 23.6 2.5 0.5 1.4 0.31 7.2
94 Conductivity TP DOC Ca Cl SO4 Lake Status Secchi (m) pH (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) LaCloche neutral 3.8 7.3 42.8 7.3 5.5 3.4 1.52 5.95 Little Mountain acid 15.3 5.2 22.8 1.8 0.1 1.3 0.33 6.7 Little Sheguindah recovered 2.5 7 20.2 9.2 5.2 1.4 0.15 3.9 Little Superior acid 18.5 4.4 NA 2 0.1 0.7 0.4 8.6 Logboom acid 1.4 6.1 25.1 11.3 5 1.8 0.36 6.6 Low neutral 6.8 7.8 68 6.6 3.3 8.8 1.49 7.8 Lumsden acid 9 5.6 17.4 3.3 1.2 1.1 0.3 5.45 Muriel acid 9.8 5.8 NA 3.1 0.9 1.8 0.41 7.6 Nellie acid 21.6 4.7 30.7 1.2 0.3 1.3 0.46 8.2 Norway acid 8.5 5.7 21.6 1.7 1 1.3 0.53 6.85 OSA acid 20 5.1 28 2.6 0.2 1.7 0.41 7.85 Partridge recovered 10 6.2 25 2.6 2 1.8 0.34 7.85 Proulx acid 22 4.7 NA 2.4 0.1 1.1 0.34 8.45 RuthRoy acid 13.7 5.1 22.1 2.4 0.1 1 0.32 6.35 Shingwak acid 22.1 4.8 NA 2 0.1 0.9 0.27 6.5 Solomon acid 3.6 5 NA 8.9 2 1.1 0.25 6.35 Terry acid 4.8 5.8 20.6 8.8 4.5 1.4 0.27 5.6 Threenarrows E recovered 6.1 6.3 NA 4.2 3.4 1.8 0.34 6.55 Threenarrows N recovered 6.1 6.3 NA 5.3 3.6 1.8 0.35 6.8 Turbid acid 5.4 5.4 23.5 5.8 6 1.3 3.04 6.8 Whiskeyjack acid 28 4.6 27.2 1.3 0.2 0.4 0.29 8.1
95
Table B.4. continued
K Na Si TKN Al Fe Zn Cu Ni Mg DIC Pb Lake (mg/L (mg/L) (mg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (mg/L) (mg/L) (µg/L) ) Acid 0.46 0.21 0.96 0.11 112 49 14.8 0.6 5.2 0.42 0.2 -1.01 AY Jackson 0.72 0.32 0.28 0.27 16.6 9 3.5 1.1 2.1 0.66 0.6 0.794 Bell 0.92 0.53 0.66 0.43 40 25.4 10.5 2.1 5.9 0.72 0.4 1.94 Bodina 1.12 0.42 0.02 0.16 19.4 49.8 2.3 1.3 1.8 1.34 2 1.84 Boundary 0.47 0.35 0.34 0.17 21.4 42 6.7 1 4.4 0.52 0.2 -0.0623 Carlyle 0.89 0.33 1.14 0.27 33.1 24.6 8.9 1.8 3.5 0.72 0.2 -1.49 Charlton 3.27 0.56 0.4 0.27 13 19.8 0.7 2.1 3.5 1.58 2 4.03 Clearsilver 0.4 0.24 0.78 0.09 138 55.6 24.5 1.1 9.9 0.4 0.2 2.51 David 0.49 0.53 0.62 0.16 42.7 24.8 7.5 1.7 6.4 0.42 0.2 -0.444 deLamorandiere 0.46 0.22 0.06 0.21 72.6 86.1 12.7 1.2 4.4 0.455 0.2 1.65 Fish 0.79 1.49 0.68 0.19 16.9 30.2 3.4 1.9 3 0.64 0.2 6.22 Freeland 0.51 0.17 0.02 0.24 35.2 90.8 6.9 0.7 3.7 0.7 0.6 4.13 Frood 3.31 0.57 0.36 0.26 12.5 18.1 0.9 3.1 4.8 1.02 1.2 5.75 Gail 0.33 1.14 0.2 0.25 268 42.1 14.3 1.5 10 0.239 0.2 4.22 Gem 0.85 0.45 0.68 0.3 28.6 48.9 1.8 1.5 3.6 0.74 1.2 -5.49 George 0.68 0.33 1.02 0.15 21.6 11.3 7.4 1.1 3.2 0.7 0.2 4.22 Great Mountain 0.64 0.28 0.66 0.26 23.6 14.5 4.9 1 3.6 0.5 0.2 6.98 Helen 0.8 0.38 1.14 0.18 20.2 15 0.7 0.8 1.7 0.94 1 -0.347 Howry 0.9 0.43 0.94 0.59 32 20.1 2.6 1.6 4.3 0.875 0.8 4.22 Ishmael 0.85 0.41 0.8 0.25 12.5 14.3 0.7 0.6 1.7 1.05 0.8 2.13 Johnnie 0.75 0.38 0.58 0.12 62.3 40.9 9.7 2.5 7 0.64 0.2 -0.443 Kakakise 0.8 0.33 0.6 0.39 9.2 8.3 1.5 1 1.7 0.82 0.4 3.84 Killarney 0.59 0.29 1.1 0.09 101 21.4 27.4 2.2 7.2 0.54 0.2 -1.2 LaCloche 1.47 0.5 0.52 0.27 9.8 16.5 0.9 1.2 1.8 1.52 2.6 0.509 Little Mountain 0.54 0.26 1.04 0.37 135 27.2 11.9 1 9.9 0.42 0.2 2.32
96 K Na Si TKN Al Fe Zn Cu Ni Mg DIC Pb Lake (mg/L (mg/L) (mg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (mg/L) (mg/L) (µg/L) ) Little Sheguindah 0.75 0.11 0.46 0.36 30.4 27.4 2.8 1.2 0.5 1.08 1.2 0.508 Little Superior 0.3 0.21 0.14 0.1 544 67.7 23.3 3.5 11.8 0.3 0.2 4.79 Logboom 0.78 0.41 0.56 0.47 50.9 187 12 2.9 6.9 0.7 0.6 1.27 Low 1.38 0.59 0.44 0.2 9.7 6.6 0 1 0.7 2.1 5.6 2.89 Lumsden 0.49 0.21 1.1 0.14 85.2 46.1 13.3 0.3 3.7 0.48 0.4 -4.35 Muriel 0.64 0.29 0.14 0.15 45.9 23.4 11.1 1.1 5.3 0.62 0.2 0.224 Nellie 0.47 0.25 0.36 0.08 412 29 19.5 2.1 8.6 0.42 0.6 4.32 Norway 0.69 0.34 1.24 0.18 62.6 17.3 11.8 1.3 6.8 0.58 1 -3.01 OSA 0.6 0.29 0.02 0.06 116 10.2 19.7 1.3 5.3 0.6 0.8 -0.919 Partridge 0.69 0.32 0.42 0.18 28.8 4.4 8.9 1.2 5.1 0.7 1 3.27 Proulx 0.46 0.3 0.36 0.14 434 28.5 20.6 2.6 11.3 0.48 0.2 1.27 RuthRoy 0.47 0.19 0.5 0.07 166 29.1 19.7 1.2 11.2 0.4 0.6 -0.253 Shingwak 0.4 0.21 0.8 0.09 238 24.3 19.7 1.5 8.4 0.36 0.2 -0.348 Solomon 0.63 0.3 0.02 0.31 82.8 98.3 13 0.5 4.3 0.42 0.2 1.94 Terry 0.68 0.27 0.78 0.31 122 167 9.4 1 4.9 0.58 0.8 1.93 Threenarrows E 0.78 0.38 1.42 0.11 19.9 12.5 3.8 1.1 3.7 0.82 0.4 1.27 Threenarrows N 0.78 0.38 1.42 0.21 20.5 15.2 4.8 1.3 3.4 0.82 0.4 1.27 Turbid 0.81 4.07 0.34 0.36 111 76.9 13.9 2.3 12.8 0.62 0.2 0.315 Whiskeyjack 0.41 0.23 0.16 0.09 367 29.3 17.8 3.8 11.1 0.38 0.2 -4.63
Pb concentrations are reported with uncertainty resulting in negative numbers, which arised from inter-element and background corrections that were applied. The method detection limit for Pb concentration using the MET3474 scan is 0.05 and the zero value (W) was 0.01 µg/L as determined by the Ontario Ministry of Environment.
97 Table B.5. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Arnott (unpublished data). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972-73. Secchi = secchi disk depth, TP= total phosphorus, DOC = dissolved organic carbon, Cl= chloride, SO4=sulphate, Na=sodium, K=potassium, Si=reactive silicates, TKN=total Kjeldahl nitrogen, Al=aluminum, Fe=iron, Cu=copper, Zn=zinc, Ni=nickel, Mg=magnesium, DIC=dissolved inorganic carbon, Pb=lead, Mn=manganese. Secchi Conductivi TP DOC Ca Cl SO4 Lake Status pH (m) ty (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) Acid acid 7.1 5.14 12.8 4 2.3 1.08 0.25 4.2 AY Jackson recovered 6.9 6.14 17.4 6.1 3.8 1.44 0.29 4.8 Bell recovered 3 6.3 20.6 5.1 5.8 1.82 0.35 5.15 Bodina neutral 2.7 NA 31.4 11 9.4 3.34 0.3 3.65 Boundary acid 6.35 6.07 13.8 5.2 3.3 1.18 0.22 4.95 Carlyle recovered 3.3 6.13 20.6 6.6 4.8 1.64 0.59 4.95 Charlton neutral 4.1 7.12 61.4 9.1 4.5 5.22 4.79 7.95 Clearsilver acid 4.6 5.43 13 3.8 2.3 1.08 0.24 4.25 David acid 8.6 5.73 13.2 2.6 2.3 1.08 0.26 4.1 deLamorandiere acid 6.3 5.01 17 8.5 11 0.94 0.63 4.15 Fish recovered 3.05 6.31 18 7 4.5 1.64 0.31 4.3 Freeland acid 2.7 5.75 18.2 7.4 2.8 1.48 0.31 5.4 Frood recovered 4.2 7.02 61.4 8.6 5.9 5.16 5.08 7.85 Gail acid 13.35 5.15 14.4 1.6 0.5 0.64 0.22 4.3 Gem neutral 2.9 6.72 23.4 8.8 7.1 2.6 0.27 3.85 George recovered 3.33 6.4 20.8 6.2 3.5 1.66 0.68 5.5 Great Mountain acid 6.65 5.9 15.2 3.8 3 1.3 0.3 4.5 Helen neutral 4.3 6.68 26 5.4 5.4 2.48 0.4 5 Howry neutral 3.45 6.7 22.6 5.4 5.3 2.4 0.33 4.25 Ishmael neutral 5.2 6.79 26.4 3.7 5.4 2.62 0.36 5 Johnnie acid 4.5 6.21 18.4 5.4 4.2 1.52 0.32 5 Kakakise recovered 5.1 6.53 24.4 12.8 3.5 2.12 0.66 5.6 Killarney acid 9.25 5.23 17.4 2.5 1.2 1.36 0.31 5.65 LaCloche neutral 4.2 6.99 38.2 5 7.1 3.76 1.4 4.6
98 Secchi Conductivity TP DOC Ca Cl SO4 Lake Status pH (m) (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) Little Mountain acid 12.75 5.18 17.2 4.3 0.6 1.3 0.31 5.8 Little Sheguindah recovered 2.25 6.62 21.2 11.9 5.1 1.64 0.23 3.85 Little Superior acid 16.8 4.45 28.8 25 0.5 0.76 0.28 6.95 Logboom acid 3.3 5.97 20 7.8 5.3 1.76 0.64 4.5 Low neutral 6.3 7.08 72.2 3 6.8 9.14 1.61 6.9 Lumsden acid 3.5 5.56 12 7.6 2.8 0.94 0.26 3.9 Muriel acid 7.5 5.9 18.6 3.6 1.7 1.56 0.39 5.8 Nellie acid 12.9 4.77 23 4.7 12.9 1.2 0.4 6.25 Norway acid 9 5.75 16.8 3.6 2.4 1.32 0.36 5.25 OSA acid NA 5.12 20.2 1.6 0.6 1.6 0.38 6.3 Partridge recovered 8.7 6.06 20 4.7 3.1 1.74 0.32 6.2 Proulx acid 11.8 NA 24.2 NA 2.6 1.08 0.34 NA RuthRoy acid 13.25 5.24 14.4 2.3 1.2 0.94 0.34 4.65 Shingwak acid 11.5 4.93 18.2 12.2 0.8 1 0.26 5.35 Solomon acid 3.6 5.4 13.6 8.8 4.2 0.88 0.19 4.05 Terry acid 1.7 6.02 18.4 17.2 7.9 1.52 0.3 4.1 Threenarrows E recovered 4.35 NA 19.8 11.3 4.2 1.66 0.32 5.15 Threenarrows N recovered 3.9 NA 17.8 5.4 4.7 1.52 0.29 4.6 Turbid acid 4.5 5.35 18 7.3 4.8 1.28 0.26 5.45 Whiskeyjack acid 17.4 4.7 21.4 3.6 0.7 0.94 0.3 6.4
99 Table B.5. continued
TKN Mg DIC Lake Na (mg/L) K (mg/L) Si (mg/L) (µg/L) (mg/L) (mg/L) Acid 0.45 0.155 1.08 199 0.355 0.6 AY Jackson 0.725 0.295 0.28 319 0.615 0.42 Bell 0.795 0.34 0.68 292 0.645 0.48 Bodina 1.01 0.39 0.24 506 1.16 1.88 Boundary 0.505 0.27 0.6 236 0.435 0.46 Carlyle 0.965 0.315 1.04 308 0.625 0.48 Charlton 3.52 0.585 0.56 325 1.56 1.98 Clearsilver 0.475 0.225 1.1 220 0.34 0.42 David 0.515 0.23 0.24 162 0.365 0.54 deLamorandiere 0.785 0.31 0.32 523 0.355 0.5 Fish 0.75 0.31 0.72 250 0.565 0.46 Freeland 0.63 0.245 0.28 266 0.565 0.48 Frood 3.62 0.6 0.56 312 1.53 1.96 Gail 0.345 0.105 0.52 95 0.185 0.5 Gem 0.785 0.335 0.1 380 0.72 0.78 George 0.865 0.355 0.8 311 0.62 0.5 Great Mountain 0.62 0.28 0.36 195 0.475 0.36 Helen 0.83 0.335 1.36 331 0.915 1.02 Howry 0.805 0.37 0.8 284 0.69 0.48 Ishmael 0.835 0.94 0.64 252 0.94 0.92 Johnnie 0.72 0.305 0.76 234 0.545 0.48 Kakakise 0.78 0.315 0.68 303 0.735 0.44 Killarney 0.59 0.26 1.08 116 0.455 0.5 LaCloche 1.5 0.495 0.56 348 1.37 1.6 Little Mountain 0.545 0.265 0.88 119 0.385 0.48 Little Sheguindah 0.9 0.405 0.44 307 0.87 0.24 Little Superior 0.305 0.19 0.08 69 0.25 0.52
100 TKN Mg DIC Lake Na (mg/L) K (mg/L) Si (mg/L) (µg/L) (mg/L) (mg/L) Logboom 0.775 0.36 0.66 339 0.635 1.04 Low 1.46 0.6 0.44 263 2.18 5.12 Lumsden 0.445 0.165 1.1 257 0.365 0.46 Muriel 0.625 0.245 0.48 167 0.5 0.48 Nellie 0.495 0.26 0.44 81 0.355 0.4 Norway 0.62 0.28 1.2 192 0.475 0.52 OSA 0.605 0.25 0.22 84 0.49 0.5 Partridge 0.685 0.29 0.28 223 0.6 0.56 Proulx 0.485 0.23 NA 93 0.38 1.24 RuthRoy 0.49 0.19 1 167 0.31 0.46 Shingwak 0.43 0.225 0.4 106 0.32 0.42 Solomon 0.505 0.14 0.16 304 0.34 0.5 Terry 0.795 0.29 0.88 473 0.575 0.44 Threenarrows E 0.75 0.32 1.3 246 0.665 0.46 Threenarrows N 0.705 0.3 1.36 306 0.57 0.42 Turbid 0.75 0.335 0.8 285 0.51 0.44 Whiskeyjack 0.41 0.2 0.24 86 0.345 0.52
101 Table B.6. Select water chemistry variables from 44 lakes sampled in Killarney Provincial Park by Suenaga (2016). Lake status categories include acid: pH<6 since 1972-73, recovered: shifted from pH<6 in 1972-73 to pH>6 as of 2016, neutral: pH>6 since 1972- 73. Secchi = secchi disk depth, TP= total phosphorus, DOC = dissolved organic carbon, Cl= chloride, SO4=sulphate, Na=sodium, K=potassium, Si=silicate, TKN=total Kjeldahl nitrogen, Al=aluminum, Fe=iron, Cu=copper, Zn=zinc, Ni=nickel, Mg=magnesium, DIC=dissolved inorganic carbon, Pb=lead, Mn=manganese.
Secchi Conductivity TP DOC Ca Cl SO4 Lake Status pH (m) (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) Acid acid 7.85 5.59 12.9 3.1 2.5 1.1 0.29 3.25 AY Jackson recovered 6.25 6.03 17.4 4.9 3.1 1.36 0.22 4 Bell recovered 3.5 6.07 20.1 4 5.3 1.76 0.25 4.3 Bodina neutral 1.8 6.63 30.8 16.5 9.1 3.2 0.28 3.1 Boundary acid 6.7 5.64 14.3 3.5 2.9 1.24 0.15 3.6 Carlyle recovered 4.25 6.05 20.7 3.7 4.7 1.52 0.81 4.1 Charlton neutral 4.1 6.85 56.9 6 4.6 4.66 4.06 6.25 Clearsilver acid 5.85 5.28 13.5 3.6 2.5 0.94 0.18 3.6 David acid 7.1 5.55 13.5 3.7 3.5 1.06 0.25 3.3 deLamorandiere acid 4.3 4.99 14.8 9.8 3.4 1.02 0.14 4.05 Fish recovered 3.65 6.23 18.3 5.9 3.4 1.72 0.29 3.6 Freeland acid 2.125 5.71 17.3 7.9 3.8 1.46 0.11 4.65 Frood recovered 4.5 6.86 58.8 5.5 4.9 5.8 4.4 6.45 Gail acid 16.4 4.77 13.6 4.4 0.5 0.6 0.21 3.45 Gem neutral 4.85 6.34 20.3 9.4 4 2.02 0.26 3.75 George recovered 6.4 6.06 18.9 2.5 2.2 1.54 0.37 4.45 Great Mountain acid 8.1 5.84 15.8 3.4 3 1.32 0.27 3.9 Helen neutral 5.7 6.55 26.4 3.7 3.7 2.48 0.27 4.65 Howry neutral 6 6.47 22.7 5.9 4.9 2.36 0.32 3.95 Ishmael neutral 4.55 6.46 26.3 4 4 2.54 0.3 4.4 Johnnie acid 3.4 5.89 17.9 4.7 4.7 1.46 0.26 4.1 Kakakise recovered 4.625 6.3 22.5 2.9 3.3 2.04 0.49 4.5 Killarney acid 10.25 5.85 17.25 1.6 2.4 1.32 0.27 4.5 LaCloche neutral 3.6 6.73 34.8 8.2 5.9 3.28 1.01 3.05
102 Table B.6. continued
Secchi Conductivity TP DOC Ca Cl SO4 Lake Status pH (m) (µS/cm) (µg/L) (mg/L) (mg/L) (mg/L) (mg/L) Little Mountain acid 13.35 5.25 16.2 1.9 0.6 1.32 0.24 4.8 Little Sheguindah recovered 2.6 6.4 21.5 9.7 5.1 1.74 0.14 3 Little Superior acid 19.65 4.56 25.3 2 0.5 0.7 0.23 5.85 Logboom acid 3.35 5.99 21.1 11.3 5.7 1.72 0.28 3.8 Low neutral 7.4 7.02 73.5 3.2 2.9 9 1.38 5.85 Lumsden acid 6.55 5.45 12.2 3.2 2.6 1.2 0.19 2.75 Muriel acid 9.1 5.89 18.3 3.5 2 1.44 0.31 5.1 Nellie acid 22.65 4.65 21.1 0.9 0.5 1.12 0.35 5.2 Norway acid 9.55 5.88 17.1 3 2.7 1.24 0.23 4.45 OSA acid 13.5 5.7 18.4 2 1.2 1.46 0.31 4.8 Partridge recovered 8 6.1 19.1 4.3 2.8 1.46 0.21 4.55 Proulx acid 19.05 4.68 22.2 1.5 0.5 1 0.22 5.75 RuthRoy acid 8.25 5.08 13.2 3.5 1.8 0.78 0.23 3.6 Shingwak acid 20.35 4.91 16.5 1.6 0.5 0.86 0.19 4.3 Solomon acid 1.6 5.15 12.8 31.8 8.3 0.78 0.21 2.4 Terry acid 4.25 5.62 16.8 6.5 4.8 1.28 0.16 4.05 Threenarrows E recovered 5.4 6.09 18.9 4.3 4.4 1.54 0.26 4.25 Threenarrows N recovered 4.9 6.03 19.5 4.1 5.5 1.52 0.26 4.2 Turbid acid 4.3 5.32 17.9 7.5 4.7 1.14 0.18 4.6 Whiskeyjack acid 18.8 4.79 20.4 2.2 0.5 0.84 0.23 5.2
103 Table B.6. continued Na K Si TKN Al Fe Zn Cu Ni Mg DIC Pb Anions Cations Lake (mg/L) (mg/L) (mg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (mg/L) (mg/L) (µg/L) (meq/L) (meq/L) Acid 0.435 0.185 1.22 194 67.2 40 11.8 1 3.3 0.32 0.46 0.1 0.0873 0.106 AY Jackson 0.735 0.24 0.48 266 40.6 30 4 1.1 2.7 0.59 0.68 0.1 0.122 0.155 Bell 0.785 0.36 1.24 299 61.6 40 4.3 2.2 6 0.598 0.64 0.1 0.134 0.181 Bodina 1.05 0.455 0.36 688 24.3 100 2.3 1.3 2 1.09 2.18 0.3 0.234 0.312 Boundary 0.5 0.205 0.64 270 16.2 40 6.1 1.3 1.8 0.428 0.52 0.2 0.095 0.124 Carlyle 1.09 0.32 1.48 259 49.3 50 6.1 1.6 3.5 0.6 0.66 0.1 0.138 0.181 Charlton 3.37 0.55 0.48 286 13.4 30 2.8 2.5 4.7 1.38 2.74 0 0.463 0.508 Clearsilver 0.485 0.155 1.52 181 87.4 70 13.8 1.7 7 0.318 0.48 0.2 0.0897 0.0988 David 0.51 0.23 0.5 216 22.2 0 8.4 2 3.1 0.362 0.42 0.1 0.0797 0.111 deLamorandiere 0.445 0.165 0.4 333 129 180 16.8 1.2 4 0.376 0.58 0.4 0.0906 0.108 Fish 0.825 0.315 0.82 250 9.7 80 2.7 1.1 1.8 0.596 0.96 0.1 0.136 0.179 Freeland 0.475 0.17 0.04 332 29.7 100 3.2 0.9 1.9 0.536 0.68 0.1 0.118 0.143 Frood 3.52 0.555 0.56 276 12.1 20 3.2 2.7 4.8 1.38 2.8 0.1 0.474 0.572 Gail 0.39 0.115 0.28 122 142 40 13.8 1.1 6.9 0.188 0.36 0.5 0.0785 0.0685 Gem 0.815 0.3 0.48 293 21.1 20 3.6 1 2.6 0.646 1.12 0.1 0.148 0.198 George 0.675 0.3 1.12 190 29.6 20 5.3 1 2.7 0.556 0.62 0 0.135 0.16 Great Mountain 0.7 0.29 0.52 205 13.5 0 3.6 1 2.5 0.504 0.52 0.1 0.106 0.147 Helen 0.835 0.355 1.66 258 25.4 10 4.2 1 1.8 0.862 1.44 0 0.219 0.241 Howry 0.9 0.415 1 314 28.6 0 5.1 1.7 2.8 0.716 1.12 0.1 0.184 0.228 Ishmael 0.845 0.345 1 229 17.6 10 3.9 1 1.5 0.89 1.46 0.1 0.199 0.245 Johnnie 0.69 0.325 1.26 277 72.1 60 5.4 2.5 5.8 0.522 0.5 0.2 0.108 0.155 Kakakise 0.74 0.31 1.02 207 17.1 20 2.6 1.2 2.1 0.692 0.98 0 0.165 0.2 Killarney 0.615 0.27 1.28 167 42.8 20 8.3 1 3.7 0.442 0.48 0.1 0.122 0.137 LaCloche 1.39 0.455 0.92 309 24.2 40 3 1.2 1.1 1.2 2.26 0 0.258 0.336 Little Mountain 0.615 0.22 1.12 101 46.2 10 9.2 0.6 6.5 0.398 0.42 0.1 0.114 0.134 Little Sheguindah 0.855 0.33 0.6 306 39.7 60 2.2 1.9 0.9 0.92 1.52 0.2 0.163 0.209 Little Superior 0.3 0.17 0.04 94 410 40 23.1 3.1 8.6 0.24 0.36 1.8 0.135 0.0739
104 Table B.6. continued
Na K Si TKN Al Fe Zn Cu Ni Mg DIC Pb Anions Cations Lake (mg/L) (mg/L) (mg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (µg/L) (mg/L) (mg/L) (µg/L) (meq/L) (meq/L) Logboom 0.775 0.32 1.08 332 73.2 390 6.3 2.3 6.8 0.618 1.94 0.5 0.148 0.18 Low 1.46 0.61 0.56 217 11.6 10 2.2 1 1 2.09 6.12 0 0.663 0.701 Lumsden 0.43 0.19 1.24 162 54.8 40 9.8 0.9 2.8 0.348 0.44 0.1 0.076 0.113 Muriel 0.635 0.24 0.62 172 29 10 7.7 1 2.1 0.482 0.56 0.1 0.134 0.147 Nellie 0.51 0.26 0.76 79 203 20 17.4 1.2 6.4 0.342 0.32 0.5 0.129 0.116 Norway 0.575 0.25 1.62 166 57.8 40 9.1 1.1 4.5 0.456 0.5 0.1 0.111 0.132 OSA 0.61 0.255 0.32 128 18.2 0 7 0.7 2 0.46 0.48 0.1 0.122 0.144 Partridge 0.65 0.27 0.56 216 40.8 20 7.1 1.4 3.1 0.542 0.64 0.1 0.124 0.153 Proulx 0.455 0.175 0.4 84 231 20 17.8 1.5 7.7 0.368 0.36 1 0.133 0.106 RuthRoy 0.455 0.125 1.32 163 119 30 11.1 1.3 7.4 0.288 0.46 0.1 0.0815 0.0865 Shingwak 0.41 0.155 0.52 105 134 20 15.3 1.1 6.4 0.292 0.38 0.7 0.0992 0.0901 Solomon 0.455 0.26 0.02 870 276 1240 5.1 1.4 2.7 0.278 1.38 1 0.057 0.101 Terry 0.66 0.22 1.16 266 148 110 8.5 1.7 5.4 0.492 0.6 0.3 0.107 0.139 Threenarrows E 0.755 0.3 1.52 254 39.8 30 7.2 1.3 3.2 0.606 0.74 0.1 0.131 0.17 Threenarrows N 0.74 0.315 1.52 246 42.2 30 7.5 1.3 3.3 0.618 0.78 0.1 0.131 0.167 Turbid 0.71 0.265 0.72 265 118 150 10.3 1.7 8.8 0.474 0.5 0.2 0.101 0.134 Whiskeyjack 0.4 0.185 0.52 122 241 30 14.6 1.5 8.6 0.306 0.36 0.4 0.126 0.0919
Pb concentrations are reported with uncertainty resulting in negative numbers, which arised from inter-element and background corrections that were applied. The method detection limit for Pb concentration using the MET3474 scan is 0.05 and the zero value (W) was 0.01 µg/L as determined by the Ontario Ministry of Environment.
105 APPENDIX C: Killarney Provincial Park zooplankton species abundance data (num./L) from 1972-73 to 2016.
Table C.1. Abundances of zooplankton species that occur in >5% of lakes in Killarney Provincial Park in a 44 lake survey in 1972-73 (Sprules 1975), 1990 (Locke et al. 1994), 2000 (Holt and Yan 2003), 2005 (Shead 2007; Gray et al. 2012), and Suenaga (2016). Species with abundance of 0.00 represent abundances <0.005.
Acid AY Jackson Bell Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.00 Bosmina sp. 0.00 4.28 0.11 0.11 1.96 0.56 3.13 0.35 1.82 6.19 0.84 Ceriodaphnia sp. 0.01 Chydorus sphaericus 0.04 0.01 0.00 Cyclops scutifer 0.37 0.10 Cyclops vernalis 0.42 Daphnia catawba 0.03 0.22 0.56 0.02 Daphnia mendotae 0.08 0.02 Daphnia longiremis 0.09 0.06 0.10 Letpodiaptomus minutus 3.08 3.44 2.25 0.55 1.44 7.64 2.18 1.91 2.17 3.90 7.56 3.74 0.10 1.89 1.08 Skistodiaptomus oregonensis 0.67 0.33 0.21 Daphnia pulex/pulicaria 0.02 0.07 0.01 Daphnia retrocurva 0.19 0.03 0.01 0.04 Daphnia ambigua 0.31 0.04 5.08 0.12 0.18 0.01 0.18 0.03 Diacyclops thomasi 0.27 2.32 0.59 3.99 6.11 0.02 5.93 0.08 1.06 2.95 0.30 1.16 4.40 4.70 Diaphanosoma birgei 0.92 5.47 0.21 0.07 0.55 4.87 1.87 0.52 1.55 Skistodiaptomus reighardi 0.15 0.01 Epischura lacustris 0.01 0.07 Holopedium glacialis 0.03 11.61 0.71 4.87 2.04 1.95 1.47 1.49 1.66 1.57 0.65 Mesocylops edax 0.02 0.03 0.07 0.74 1.08 0.22 0.73 1.09 Ophryoxus gracilis Polyphemus pediculus 0.01 0.01 0.18 Tropocyclops extensus 0.04 0.37 0.87 0.18 0.43 0.10 1.05 0.06 Acroperus harpae
106
Bodina Boundary Carlyle Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.02 0.03 Bosmina sp. 12.06 0.21 11.59 51.81 5.30 37.82 4.90 34.81 4.07 29.23 2.07 7.83 7.61 1.26 Ceriodaphnia sp. 8.04 1.28 0.23 0.58 3.94 Chydorus sphaericus Cyclops scutifer Cyclops vernalis Daphnia catawba 0.55 0.04 Daphnia mendotae 0.91 0.00 Daphnia longiremis 0.05 0.04 Letpodiaptomus minutus 0.04 0.37 71.03 17.01 5.42 23.13 6.68 74.54 3.33 4.70 2.73 0.38 Skistodiaptomus oregonensis 0.23 0.97 0.17 0.52 Daphnia pulex/pulicaria 0.01 0.02 9.54 0.03 Daphnia retrocurva 10.72 0.36 41.65 0.20 2.09 0.25 Daphnia ambigua 1.46 0.10 0.17 0.05 Diacyclops thomasi 18.54 0.05 2.92 1.22 9.65 Diaphanosoma birgei 8.04 3.63 9.73 2.31 0.03 8.74 4.94 9.62 29.23 2.37 4.35 0.66 Skistodiaptomus reighardi 30.82 0.05 1.36 0.52 0.01 Epischura lacustris 1.34 0.03 0.06 Holopedium glacialis 1.34 0.11 3.60 15.90 1.38 1.92 11.03 0.82 8.77 0.63 2.78 11.37 1.21 Mesocylops edax 21.44 0.09 0.23 1.15 3.18 0.50 3.67 0.76 1.67 1.46 0.27 0.70 0.28 0.94 Ophryoxus gracilis 0.03 Polyphemus pediculus 0.17 0.38 0.03 0.02 Tropocyclops extensus 42.87 3.67 16.52 30.97 0.80 0.87 0.13 Acroperus harpae 0.02
107 Charlton Clearsilver David Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.01 0.09 0.01 Bosmina sp. 2.67 2.25 17.25 5.15 2.99 0.05 0.02 0.00 1.21 0.21 0.34 3.40 1.91 Ceriodaphnia sp. 0.02 0.00 Chydorus sphaericus 0.08 0.05 0.03 0.05 0.24 0.02 Cyclops scutifer Cyclops vernalis Daphnia catawba 0.14 0.39 Daphnia mendotae 0.84 1.44 3.33 0.66 0.00 Daphnia longiremis 1.21 13.66 12.66 1.15 0.08 Letpodiaptomus minutus 6.07 1.68 1.44 1.14 1.04 4.79 4.35 1.70 0.03 0.31 14.15 1.02 3.96 2.96 0.58 Skistodiaptomus oregonensis 2.43 9.30 0.72 2.29 0.23 0.04 0.13 Daphnia pulex/pulicaria 2.52 0.61 0.05 Daphnia retrocurva 1.46 6.48 0.72 2.33 0.07 0.07 Daphnia ambigua 0.67 0.02 0.00 Diacyclops thomasi 0.97 4.67 8.87 2.76 0.00 0.33 Diaphanosoma birgei 3.16 5.49 1.80 14.31 1.79 0.02 0.04 0.00 0.64 0.33 Skistodiaptomus reighardi Epischura lacustris 0.24 0.30 0.52 Holopedium glacialis 0.97 0.57 0.29 0.38 0.02 0.05 2.83 1.43 8.16 1.55 0.29 Mesocylops edax 4.61 4.27 0.36 0.57 1.61 0.01 0.04 0.13 1.85 1.06 Ophryoxus gracilis 0.01 Polyphemus pediculus 0.00 0.00 0.05 0.20 0.01 Tropocyclops extensus 0.73 0.46 0.36 0.16 0.07 0.09 Acroperus harpae 0.01
108 DeLamorandiere Fish Freeland Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.02 0.01 0.63 Bosmina sp. 0.69 0.62 0.06 2.00 1.25 0.36 0.91 1.88 6.32 12.81 9.32 20.95 0.75 2.92 Ceriodaphnia sp. Chydorus sphaericus 0.04 0.02 Cyclops scutifer Cyclops vernalis Daphnia catawba Daphnia mendotae 0.31 0.11 Daphnia longiremis Letpodiaptomus minutus 5.76 9.07 24.72 18.67 18.67 16.19 1.42 0.45 0.01 0.54 0.85 0.76 0.31 Skistodiaptomus oregonensis 2.18 5.05 2.27 0.01 0.04 0.11 1.80 Daphnia pulex/pulicaria Daphnia retrocurva 0.31 0.43 9.07 0.11 Daphnia ambigua 0.31 1.36 Diacyclops thomasi 0.01 0.11 Diaphanosoma birgei 15.76 0.05 0.30 7.78 5.80 20.41 0.10 3.67 0.13 0.03 3.48 0.08 Skistodiaptomus reighardi 0.18 Epischura lacustris 0.25 0.04 0.11 Holopedium glacialis 0.08 0.04 0.31 0.45 0.25 0.05 0.13 Mesocylops edax 0.87 1.55 0.12 8.69 2.18 0.46 11.34 0.01 1.15 0.20 0.54 0.03 0.07 Ophryoxus gracilis 0.03 0.06 Polyphemus pediculus 0.02 0.13 0.06 0.07 Tropocyclops extensus 1.87 0.02 5.90 0.40 1.18 0.20 0.33 7.53 1.00 Acroperus harpae
109 Frood Gail Gem Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.00 Bosmina sp. 1.52 2.85 8.16 2.95 0.31 9.01 0.22 4.01 0.27 8.96 8.74 0.27 Ceriodaphnia sp. 0.15 Chydorus sphaericus 0.36 0.01 0.01 Cyclops scutifer Cyclops vernalis 0.04 0.67 Daphnia catawba Daphnia mendotae 0.15 0.60 1.07 2.26 0.07 1.56 0.80 2.14 0.34 0.69 Daphnia longiremis 1.21 0.08 8.23 11.88 4.18 0.13 4.28 1.86 1.15 Letpodiaptomus minutus 5.31 1.15 4.65 8.40 2.19 30.16 16.13 14.32 11.75 3.73 3.35 2.40 0.49 3.14 1.03 Skistodiaptomus oregonensis 0.46 1.00 0.72 3.63 0.52 0.22 0.93 0.16 0.15 Daphnia pulex/pulicaria Daphnia retrocurva 0.61 2.15 2.50 0.75 1.00 0.16 Daphnia ambigua 0.15 0.36 0.08 0.22 0.04 Diacyclops thomasi 1.21 0.70 4.29 2.50 2.48 7.14 0.22 3.95 4.93 1.17 Diaphanosoma birgei 1.67 2.90 2.50 5.45 0.28 0.00 0.00 3.79 3.49 1.15 3.59 2.09 Skistodiaptomus reighardi 0.02 Epischura lacustris 0.13 0.37 0.22 0.02 0.45 0.03 Holopedium glacialis 1.21 1.00 1.43 1.95 0.01 0.03 0.45 0.24 0.82 0.45 0.81 Mesocylops edax 1.37 2.90 5.01 1.59 1.74 1.56 0.98 1.65 0.22 0.55 Ophryoxus gracilis 0.00 Polyphemus pediculus 0.19 0.01 Tropocyclops extensus 0.15 0.70 0.72 0.45 0.33 0.22 0.04 0.33 1.34 0.17 Acroperus harpae 0.00
110 George Great Mountain Helen Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. Bosmina sp. 1.85 1.46 12.60 4.25 1.78 1.18 9.28 3.50 4.57 0.44 2.15 0.27 2.17 Ceriodaphnia sp. Chydorus sphaericus 0.01 0.04 0.08 0.06 0.00 Cyclops scutifer Cyclops vernalis Daphnia catawba 0.21 Daphnia mendotae 0.24 0.01 0.41 0.69 2.62 2.24 0.23 Daphnia longiremis Letpodiaptomus minutus 7.93 1.20 6.76 2.89 1.83 14.18 1.92 0.41 2.05 0.74 1.23 0.36 0.57 2.42 0.70 Skistodiaptomus oregonensis 0.41 0.14 0.46 0.09 0.03 Daphnia pulex/pulicaria Daphnia retrocurva Daphnia ambigua 1.84 0.06 0.16 Diacyclops thomasi 0.24 24.89 3.45 3.63 0.34 0.07 4.15 2.39 1.23 5.33 0.13 3.65 2.69 0.50 Diaphanosoma birgei 1.50 2.81 0.02 0.28 0.01 0.41 0.58 4.10 Skistodiaptomus reighardi 0.00 0.08 Epischura lacustris 0.05 0.10 0.11 0.11 0.18 0.12 Holopedium glacialis 3.44 0.67 1.23 0.24 0.00 0.51 1.15 0.73 0.85 0.65 0.20 0.11 0.34 0.63 0.20 Mesocylops edax 0.38 0.16 0.06 0.68 0.15 0.08 0.06 0.06 0.10 0.03 0.34 0.09 0.09 Ophryoxus gracilis Polyphemus pediculus 0.13 0.01 Tropocyclops extensus 0.02 0.10 0.03 0.27 Acroperus harpae
111 Howry Ishmael Johnnie Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. Bosmina sp. 1.57 0.37 5.05 5.51 1.06 2.84 4.55 3.82 5.35 2.68 0.87 0.26 0.47 4.05 1.24 Ceriodaphnia sp. Chydorus sphaericus Cyclops scutifer 0.20 Cyclops vernalis 0.04 Daphnia catawba 0.13 0.19 0.15 0.00 0.09 Daphnia mendotae 0.74 0.83 0.71 0.80 0.95 0.26 6.90 0.13 0.40 0.09 0.03 Daphnia longiremis 0.08 1.25 0.97 0.68 0.36 0.13 0.33 0.27 0.00 0.01 0.03 Letpodiaptomus minutus 2.23 0.11 0.18 2.21 0.22 5.16 1.24 0.64 4.84 0.52 11.07 2.73 2.88 2.56 0.49 Skistodiaptomus oregonensis 0.08 0.32 0.18 0.69 0.13 0.26 0.18 0.25 0.15 Daphnia pulex/pulicaria Daphnia retrocurva 0.05 0.77 0.13 0.51 Daphnia ambigua 0.03 0.03 0.06 0.02 Diacyclops thomasi 2.31 0.64 3.62 2.34 0.34 15.23 0.60 3.95 3.31 6.95 0.15 0.01 1.62 1.16 1.54 Diaphanosoma birgei 0.66 0.59 1.77 5.93 0.54 0.52 0.39 0.89 6.62 1.62 0.15 1.60 0.60 0.52 Skistodiaptomus reighardi 0.09 0.00 Epischura lacustris 0.01 0.26 1.10 0.13 3.31 0.12 0.11 0.05 Holopedium glacialis 0.50 0.18 0.26 0.28 0.24 0.26 0.36 0.13 1.78 0.48 2.33 0.38 1.24 0.58 0.11 Mesocylops edax 0.08 0.26 0.35 0.69 0.34 0.77 0.46 0.51 3.05 0.21 0.15 0.31 0.26 0.28 Ophryoxus gracilis Polyphemus pediculus 0.00 Tropocyclops extensus 0.02 0.03 0.18 0.25 0.11 0.07 0.05 0.06 Acroperus harpae
112 Kakakise Killarney LaCloche Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.01 0.21 Bosmina sp. 0.89 1.17 10.88 2.12 1.29 4.89 1.22 1.05 1.13 2.77 1.12 1.08 3.19 2.16 Ceriodaphnia sp. 0.16 Chydorus sphaericus 0.00 0.16 Cyclops scutifer Cyclops vernalis 0.16 Daphnia catawba 0.10 0.03 0.28 Daphnia mendotae 0.19 1.00 0.97 1.50 0.28 0.26 0.26 0.05 Daphnia longiremis 0.28 0.07 0.14 Letpodiaptomus minutus 5.20 0.35 0.57 3.25 3.14 10.46 0.27 0.21 1.27 0.78 1.39 1.31 0.23 5.07 0.33 Skistodiaptomus oregonensis 0.55 0.21 0.23 0.44 0.54 Daphnia pulex/pulicaria Daphnia retrocurva 0.83 0.16 0.11 Daphnia ambigua 0.02 0.19 0.06 0.06 0.16 0.00 0.00 0.00 Diacyclops thomasi 8.32 0.48 2.28 5.20 12.85 0.33 4.44 0.26 1.54 0.78 Diaphanosoma birgei 0.37 0.19 0.81 0.64 0.01 1.94 0.96 0.77 Skistodiaptomus reighardi Epischura lacustris 0.19 0.49 0.11 0.28 0.10 0.11 0.04 Holopedium glacialis 0.15 1.39 0.24 0.02 0.80 2.01 0.24 0.10 0.28 0.16 0.41 0.21 Mesocylops edax 0.30 0.16 0.24 0.32 0.28 0.02 0.02 0.00 0.01 11.09 0.21 0.03 0.11 0.03 Ophryoxus gracilis 0.05 Polyphemus pediculus 0.15 0.12 Tropocyclops extensus 0.01 4.71 0.27 0.08 1.87 0.06 Acroperus harpae
113 Little Mountain Little Sheguindah Little Superior Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.07 Bosmina sp. 3.37 0.00 0.52 0.01 6.69 28.80 59.08 10.47 30.52 0.01 0.00 0.00 Ceriodaphnia sp. 0.04 1.46 0.50 0.65 Chydorus sphaericus 0.00 0.01 0.00 0.49 0.01 0.01 Cyclops scutifer Cyclops vernalis Daphnia catawba Daphnia mendotae 0.49 0.01 Daphnia longiremis 0.01 Letpodiaptomus minutus 30.31 0.02 0.62 6.77 1.20 0.18 1.46 0.06 9.44 2.24 0.78 6.24 2.93 Skistodiaptomus oregonensis 0.01 0.98 2.27 0.01 Daphnia pulex/pulicaria Daphnia retrocurva Daphnia ambigua Diacyclops thomasi 0.00 0.01 Diaphanosoma birgei 0.00 0.00 13.38 7.73 59.78 0.12 7.57 0.01 0.04 Skistodiaptomus reighardi 7.94 0.04 0.98 0.06 Epischura lacustris Holopedium glacialis 0.00 7.94 0.53 7.47 0.01 Mesocylops edax 5.85 0.04 2.93 1.66 0.00 Ophryoxus gracilis Polyphemus pediculus 0.01 0.00 Tropocyclops extensus 3.56 3.26 5.36 Acroperus harpae
114 Logboom Low Lumsden Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.01 0.06 Bosmina sp. 9.85 4.57 26.67 71.65 72.24 0.23 0.26 0.96 8.08 1.07 12.48 0.03 0.01 Ceriodaphnia sp. 0.11 0.10 1.43 5.32 Chydorus sphaericus 0.00 Cyclops scutifer Cyclops vernalis 0.02 Daphnia catawba 0.94 0.01 Daphnia mendotae 0.24 0.46 1.19 5.12 0.73 0.56 Daphnia longiremis 0.00 Letpodiaptomus minutus 1.14 0.01 0.11 14.16 0.45 1.60 11.75 0.46 17.47 1.87 0.71 1.39 0.92 Skistodiaptomus oregonensis 0.01 0.12 1.27 1.16 0.09 0.02 0.03 Daphnia pulex/pulicaria 0.06 Daphnia retrocurva 0.07 0.14 Daphnia ambigua 0.11 0.01 0.01 Diacyclops thomasi 0.11 0.24 9.25 6.96 0.23 4.80 24.60 5.03 0.31 0.03 0.20 0.46 0.89 Diaphanosoma birgei 0.11 0.10 2.86 0.05 10.70 0.23 0.09 0.96 0.05 0.07 Skistodiaptomus reighardi 0.01 2.62 0.03 Epischura lacustris 0.23 0.09 Holopedium glacialis 0.11 7.14 0.15 0.06 0.23 0.02 1.60 0.37 0.53 0.31 0.02 0.36 Mesocylops edax 0.11 1.67 0.06 0.17 0.23 0.23 0.96 0.21 0.01 Ophryoxus gracilis 0.01 Polyphemus pediculus 0.11 0.02 0.31 Tropocyclops extensus 0.90 1.43 0.43 2.12 Acroperus harpae
115 Muriel Nellie Norway Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.06 Bosmina sp. 1.54 3.09 5.22 7.98 2.65 0.02 0.00 1.85 5.63 19.48 3.13 Ceriodaphnia sp. Chydorus sphaericus 0.02 0.01 0.04 0.05 Cyclops scutifer Cyclops vernalis 0.01 Daphnia catawba Daphnia mendotae 0.05 0.00 0.00 Daphnia longiremis Letpodiaptomus minutus 41.17 0.91 2.82 6.79 1.11 44.30 0.52 6.82 3.48 0.92 7.67 0.44 1.38 0.66 0.96 Skistodiaptomus oregonensis 0.14 Daphnia pulex/pulicaria 1.03 1.64 0.14 0.03 0.01 Daphnia retrocurva Daphnia ambigua 0.02 0.05 Diacyclops thomasi 0.02 Diaphanosoma birgei 0.12 4.92 0.08 0.00 0.19 0.16 0.23 0.03 Skistodiaptomus reighardi 0.07 0.00 0.05 Epischura lacustris 0.00 Holopedium glacialis 8.75 8.61 9.59 3.06 4.75 0.02 0.00 0.28 0.27 Mesocylops edax 0.51 0.30 3.67 1.53 0.17 0.02 0.00 0.26 0.11 0.01 0.32 Ophryoxus gracilis 0.00 Polyphemus pediculus 0.51 0.45 0.00 0.00 0.01 Tropocyclops extensus 0.02 0.03 0.04 Acroperus harpae
116 O.S.A. Partridge Proulx Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 5.55 Bosmina sp. 5.52 0.75 1.63 0.10 0.98 0.04 8.42 4.24 2.00 0.00 0.62 Ceriodaphnia sp. Chydorus sphaericus 0.03 0.00 0.01 0.04 0.00 0.00 Cyclops scutifer Cyclops vernalis Daphnia catawba 0.00 Daphnia mendotae 0.01 Daphnia longiremis Letpodiaptomus minutus 30.15 0.40 0.16 2.43 1.02 26.45 1.41 1.88 16.46 18.67 16.30 1.37 0.24 3.39 3.33 Skistodiaptomus oregonensis Daphnia pulex/pulicaria 1.58 Daphnia retrocurva Daphnia ambigua 0.00 0.08 0.00 0.10 Diacyclops thomasi 0.18 1.10 0.09 Diaphanosoma birgei 0.00 1.75 0.30 Skistodiaptomus reighardi 0.00 0.42 Epischura lacustris Holopedium glacialis 1.47 0.39 6.00 0.70 0.10 0.28 1.64 0.54 2.34 Mesocylops edax 0.00 8.69 0.00 Ophryoxus gracilis 0.03 0.01 Polyphemus pediculus 0.05 0.00 0.28 0.02 0.00 Tropocyclops extensus Acroperus harpae
117 Ruth Roy Shingwak Solomon Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.00 0.00 0.07 Bosmina sp. 0.08 0.06 0.14 0.03 0.24 0.53 0.03 3.67 Ceriodaphnia sp. 0.00 Chydorus sphaericus 0.01 0.01 0.00 0.00 0.07 0.02 0.00 Cyclops scutifer Cyclops vernalis 0.01 Daphnia catawba 0.00 Daphnia mendotae 0.00 0.13 Daphnia longiremis Letpodiaptomus minutus 26.84 0.86 1.83 1.42 0.40 2.74 14.40 1.00 9.62 3.04 10.18 28.27 8.69 55.31 5.03 Skistodiaptomus oregonensis 0.07 Daphnia pulex/pulicaria Daphnia retrocurva 0.09 Daphnia ambigua Diacyclops thomasi 0.08 0.01 Diaphanosoma birgei 0.00 0.03 0.21 0.01 0.00 0.13 0.03 Skistodiaptomus reighardi 0.01 Epischura lacustris 0.04 Holopedium glacialis 1.41 0.01 0.66 0.00 0.10 Mesocylops edax 0.00 0.00 0.00 0.01 0.01 0.01 Ophryoxus gracilis 0.00 Polyphemus pediculus 0.28 0.00 0.00 0.01 0.01 Tropocyclops extensus 0.00 Acroperus harpae 0.00
118 Terry Three Narrows East Three Narrows North Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. 0.03 Bosmina sp. 0.55 1.78 12.64 9.59 4.81 1.24 0.46 2.24 1.20 0.21 1.24 0.46 2.24 1.20 0.29 Ceriodaphnia sp. 0.00 0.00 Chydorus sphaericus 0.00 0.00 Cyclops scutifer 0.14 0.02 0.14 0.05 Cyclops vernalis 0.30 0.30 Daphnia catawba 0.18 0.87 0.27 0.03 0.04 0.27 0.03 0.34 Daphnia mendotae 0.01 0.96 0.35 2.55 0.31 0.40 0.96 0.35 2.55 0.31 0.25 Daphnia longiremis 0.04 0.03 0.03 Letpodiaptomus minutus 10.63 3.11 0.87 23.03 9.11 6.73 1.35 2.65 2.70 0.15 6.73 1.35 2.65 2.70 0.57 Skistodiaptomus oregonensis 0.04 0.89 0.63 0.04 0.89 0.63 Daphnia pulex/pulicaria Daphnia retrocurva 0.14 0.31 0.10 0.05 0.01 0.14 0.31 0.10 0.05 Daphnia ambigua 1.42 2.17 0.33 0.27 0.02 0.12 0.04 0.27 0.02 0.12 0.04 Diacyclops thomasi 2.57 6.09 0.71 9.05 1.24 0.10 1.04 2.60 1.73 1.24 0.10 1.04 2.60 1.85 Diaphanosoma birgei 0.18 0.36 12.61 9.94 8.77 0.96 0.29 1.96 1.70 0.63 0.96 0.29 1.96 1.70 0.59 Skistodiaptomus reighardi 0.20 0.00 0.00 Epischura lacustris 0.03 0.01 0.40 0.00 0.03 0.01 0.40 0.07 Holopedium glacialis 4.03 4.00 12.18 9.23 8.15 1.10 0.09 0.27 0.50 0.45 1.10 0.09 0.27 0.50 0.94 Mesocylops edax 0.55 0.53 0.43 1.07 1.56 0.55 0.07 0.66 1.80 0.09 0.55 0.07 0.66 1.80 0.21 Ophryoxus gracilis Polyphemus pediculus 0.14 0.14 Tropocyclops extensus 1.78 16.09 1.07 0.61 0.14 0.20 0.14 0.20 Acroperus harpae
119 Turbid Whiskeyjack Zooplankton species 1972-73 1990 2000 2005 2016 1972-73 1990 2000 2005 2016 Alona sp. Bosmina sp. 1.20 0.19 5.40 1.40 4.46 0.00 0.00 Ceriodaphnia sp. 0.05 7.74 Chydorus sphaericus 0.00 0.00 Cyclops scutifer 0.30 Cyclops vernalis Daphnia catawba Daphnia mendotae Daphnia longiremis 0.30 Letpodiaptomus minutus 15.22 7.27 2.98 13.86 2.67 4.42 0.04 1.48 2.71 Skistodiaptomus oregonensis Daphnia pulex/pulicaria 8.81 Daphnia retrocurva 0.30 Daphnia ambigua 0.30 0.03 Diacyclops thomasi Diaphanosoma birgei 3.20 23.81 18.12 13.00 0.03 Skistodiaptomus reighardi 0.19 Epischura lacustris Holopedium glacialis 15.22 8.24 15.78 13.20 14.26 Mesocylops edax 0.30 1.62 Ophryoxus gracilis Polyphemus pediculus 0.10 0.23 0.04 Tropocyclops extensus 0.23 2.20 Acroperus harpae
120 APPENDIX D: Algonquin Provincial Park 2015 chemistry and physical data
Table D.1. Select physical and chemical variables of 55 lakes in Algonquin Provincial Park. Lake water was sampled using a composite sampler lowered twice the secchi depth of the lake during August, 2015. Secchi = Secchi disc depth, TP= average total phosphorus, DOC=dissolved organic carbon, Ca= calcium, Cl= chloride, SO4= sulphate, Na= sodium, K= potassium, Si= reactive silicate, TKN= Total Kjeldahl Nitrogen, Al=Aluminum, Fe=Iron.
Depth Area Elevation Secchi pH Conductivity TP DOC Ca Lake (m) (m) (m) (m) (µS/cm) (µg/L) (mg/L) (mg/L) Big Trout 31.7 1547.62 4.25 6.75 21.8 4.7 5.3 1.88 0.2 Biggar 27 372.46 2.95 6.86 24.5 6.2 6.7 2.24 0.19 Birchcliff 7.8 86.42 1.7 6.77 25.7 10.2 7.1 2.28 0.16 Bonita 4.7 55.39 3.45 6.66 20.8 5.5 4.6 1.58 0.8 Brule 21 85.47 3.1 6.44 14.5 5.2 6.1 1.18 0.14 Burnt Island 33 984.04 4.65 6.69 20.3 4.2 4.3 1.8 0.2 Burnt Root 19.5 1201.16 2.85 6.66 21.1 5.5 5.9 1.78 0.19 Cache 34.1 289.09 6 6.78 34.7 4 4.7 1.94 3.73 Canoe 40.4 366.37 3.25 6.61 18.2 5.5 4.7 1.5 0.3 Catfish 19 527.14 2.2 6.75 22.3 6 5.7 1.9 0.17 Cauchon 41 231.39 3.7 6.91 24.7 5.1 4.8 2.36 0.18 Cedar 34 2520.3 2.9 6.94 26.7 5 5.8 2.52 0.18 Clydegale 10.5 316.1 2.5 6.86 24.1 7.2 6.4 2.26 0.2 Dickson 13 1000.79 1.8 7.17 34.7 10.2 4.7 2.98 0.27 Farncomb 15 63.3 3.4 6.94 30.1 4.9 5.2 2.38 0.2 Galeairy 20.5 1026.53 4.8 6.84 27.9 6 5.3 2.14 1.64 Gibson 19 169.05 2.5 6.72 19.2 7.6 5.3 1.58 0.17 Grand 42 749.57 4.6 7.2 41.9 6.5 5.8 3.96 0.35 Harry 21 109.51 1.9 6.74 19.4 5 5.7 1.66 0.2 Hogan 29.2 1279.35 2.8 6.99 30.7 6.6 5.5 2.7 0.22 Joe 23.6 139.07 3.35 6.56 18.6 3.9 5.1 1.56 0.19 Kioshkokwi 39 1070.1 3.7 6.88 25 7.5 4.9 2.24 0.24 LaMuir 40 745.22 4.75 6.93 28.8 4.8 4.7 2.5 0.22
121 Laveille 40 2524.01 2.5 6.98 31.8 4.6 5 2.62 0.25 Little Cauchon 49 545.72 3.2 6.82 33.9 5.7 5.7 2.22 2.99 Little Crooked 8 314.7 4.4 6.96 30.3 4.8 4.2 2.92 0.19 Little Dickson 22 257.74 4.4 6.86 35.3 11.2 7.7 3.12 0.25 Little Joe 8.5 92.76 4.5 6.92 29.8 5.5 5.8 2.38 0.25 Louisa 60 119.71 3.15 6.73 21.9 5.6 5 2.04 0.2 Manitou 34 49.85 3.95 6.52 17.5 3.4 3.7 1.42 0.2 McCraney 61 1377.49 2.75 6.88 25.3 6.6 4.9 2.28 0.23 McIntosh 28 391.25 6.1 6.41 14.6 3.1 3.4 1.1 0.18 McKaskill 19.4 332.9 2.5 6.34 15.7 6 5.6 1.28 0.18 Merchant 28.5 285.13 5.55 7.23 41.6 3.7 2.6 3.52 0.24 Mink 46.7 452.05 4 6.94 27.4 4.8 3.8 2.26 0.24 Mouse 6 227.15 3 6.83 24.3 5.6 6.5 2.16 0.19 North Branch 12 131.43 1.55 6.65 21.9 7.4 7.6 1.96 0.18 North Tea 30 48.96 4.9 7.3 50.3 4.6 4.3 4.98 0.31 Opeongo 41 1468.68 3.15 6.91 26.3 7 4.9 2.4 0.28 Philip 15 5911.15 4.35 7.05 30.7 4.8 4.8 2.42 1.25 Radiant 31 178.63 3.3 7.01 32.7 6 5.8 2.76 0.21 Rain 21 635.81 3.6 7 28.9 4.6 5.3 2.72 0.18 Ralph Bice 45 166.64 4.4 6.5 15.3 4.5 3.8 1.16 0.15 Rence 7 468.29 7.7 6.68 17.6 3.1 2.4 1.42 0.19 Rock 24.1 91.3 1.5 6.66 18.9 6.8 6.4 1.74 0.17 RoseBarry 17 513.2 5.8 6.68 27.2 4.5 5.4 2.02 1.46 Shirley 27 202.85 2.8 6.71 17.1 6.2 4.4 1.36 0.16 Smoke 47 499.93 2.95 6.84 25 4.8 6 2.04 0.21 Source 39.5 659.12 4.65 6.81 28.6 3.3 3.7 1.8 2.27 Tea 14 265.7 6.9 6.71 22.1 4.4 4.4 1.76 0.61 Tim 21 149.14 2.95 6.72 24.6 4.6 4.4 1.7 1.61 Two Rivers 39 185.44 3.9 6.51 13.6 4.7 4 1.08 0.16 Waterclear 19 51.43 2.5 6.96 28.4 4.5 4.9 2.56 0.21 Welcome 22 254.89 5.2 6.77 20 3.5 4.6 1.72 0.18 Whitefish 25.2 220.39 4.5 6.73 34.3 5.2 5.9 2.22 3.16
122
Cl SO4 Na K Si TKN Al Fe Lake (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (µg/L) (µg/L) (µg/L) Big Trout 3.5 3.5 0.775 0.37 1.16 167 24.6 40 Biggar 3.15 3.15 0.885 0.425 1.46 303 40.3 120 Birchcliff 3.4 3.4 0.93 0.405 1.12 370 25 230 Bonita 2.9 2.9 1.09 0.31 0.92 243 28.7 130 Brule 2.3 2.3 0.575 0.295 0.72 276 70.7 110 Burnt Island 3.6 3.6 0.785 0.29 0.72 208 16.1 20 Burnt Root 3.35 3.35 0.83 0.385 0.96 276 30.4 80 Cache 3.3 3.3 3 0.36 1.24 215 15.5 50 Canoe 2.85 2.85 0.78 0.285 0.84 231 31.1 100 Catfish 3.35 3.35 0.805 0.37 1.08 281 20.6 90 Cauchon 2.9 2.9 0.925 0.38 1.8 296 21.1 20 Cedar 3.5 3.5 0.885 0.44 1.76 259 32.3 80 Clydegale 3.2 3.2 0.905 0.385 0.66 319 28.1 180 Dickson 4.5 4.5 1.17 0.59 0.8 373 11.3 70 Farncomb 4.1 4.1 1.18 0.425 2 260 9 40 Galeairy 3.25 3.25 1.71 0.395 1.52 272 24.6 90 Gibson 2.8 2.8 0.6 0.31 0.38 267 12.6 70 Grand 3.95 3.95 1.41 0.625 2.36 281 7.3 50 Harry 2.9 2.9 0.7 0.375 1.42 310 36.9 60 Hogan 4.4 4.4 0.985 0.5 1.18 248 13 30 Joe 3.1 3.1 0.75 0.23 0.52 241 20.6 70 Kioshkokwi 3.35 3.35 0.885 0.47 1.6 241 16.7 30 LaMuir 4.65 4.65 0.865 0.49 0.64 221 13.7 20 Laveille 4.85 4.85 1.17 0.565 1.2 244 9.7 20 Little Cauchon 3.55 3.55 2.61 0.355 1.68 262 36.5 140 Little Crooked 3.65 3.65 0.89 0.51 1.8 220 14 20 Little Dickson 4.4 4.4 1.14 0.675 1.92 326 11.6 120 Little Joe 4.2 4.2 1.04 0.46 1.22 253 8.4 30
123 Louisa 3.6 3.6 0.82 0.225 0.6 247 16.7 130 Manitou 3.3 3.3 0.64 0.335 1.04 243 24.6 10 McCraney 3.4 3.4 0.875 0.46 1.76 248 17.4 30 McIntosh 2.6 2.6 0.56 0.285 1.12 186 23.2 50 McKaskill 2.75 2.75 0.58 0.265 0.78 254 33.3 50 Merchant 4.25 4.25 1.26 0.735 4.24 167 2.6 20 Mink 4.4 4.4 0.815 0.43 0.16 234 4.3 10 Mouse 3.15 3.15 0.91 0.485 2.06 295 39.6 50 North Branch 2.95 2.95 0.835 0.465 1.92 314 57.8 170 North Tea 4.75 4.75 1.31 0.84 3.76 198 2.2 80 Opeongo 3.35 3.35 0.88 0.48 2.44 256 13.6 40 Philip 4.15 4.15 1.49 0.475 0.76 236 16.1 30 Radiant 4.2 4.2 1.1 0.535 1.46 278 14 60 Rain 3.55 3.55 0.905 0.465 2 241 27.3 70 Ralph Bice 2.65 2.65 0.645 0.315 1.24 229 20.7 60 Rence 3.4 3.4 0.595 0.335 0.6 161 8.9 10 Rock 2.5 2.5 0.655 0.325 0.84 332 43.7 260 RoseBarry 3.4 3.4 1.68 0.38 1.4 275 28.3 100 Shirley 2.5 2.5 0.62 0.335 0.56 246 14.2 60 Smoke 3.7 3.7 0.935 0.48 2.1 262 24.1 80 Source 3.35 3.35 1.98 0.36 0.96 232 12.8 10 Tea 3.45 3.45 0.995 0.34 1.3 265 16.7 20 Tim 3.1 3.1 1.61 0.325 1 231 20 80 Two Rivers 2.1 2.1 0.48 0.32 0.36 234 14.1 50 Waterclear 3.5 3.5 0.95 0.55 0.58 280 7.9 10 Welcome 3.1 3.1 0.725 0.38 1.4 256 17.7 40 Whitefish 3.6 3.6 2.78 0.355 1.74 276 38 160
124 APPENDIX E: Algonquin Provincial Park zooplankton species abundances from samples taken in 2015.
Table E.1. Crustacean zooplankton species abundances from 55 lakes in Algonquin Provincial Park sampled in 2015.
Big Burnt Burnt Lake Biggar Birchcliff Bonita Brule Cache Canoe Catfish Cauchon Cedar Clydegale Trout Island Root Daphnia mendotae 0.03 0.42 0.62 0.61 0.08 0.75 0.04 1.04 0.23 0.40 Daphnia retrocurva 0.29 4.04 0.32 0.23 0.09 0.09 0.05 0.08 1.87 Daphnia dubia 0.29 0.05 0.43 0.81 0.23 2.28 0.02 Daphnia dentifera 0.03 0.14 0.23 0.01 Daphnia catawba 0.03 Daphnia longiremis 0.02 0.63 0.50 0.04 0.35 0.29 0.24 Daphnia pulicaria 0.02 Daphnia ambigua 0.03 0.16 Holopedium glacialis 0.16 0.23 0.55 22.89 0.41 0.47 0.19 0.12 0.15 0.58 0.11 0.27 4.57 Diaphanosoma birgei 0.43 0.64 2.93 7.54 0.13 0.91 1.55 0.22 0.16 0.30 0.87 3.29 3.71 Bosmina spp 0.76 1.37 0.66 24.90 0.14 0.92 0.93 0.15 0.68 1.18 0.67 1.27 3.79 Polyphemus pendiculus 0.02 0.25 0.01 0.04 0.05 0.04 Sida crystillina Chydorus sphaericus 0.07 Simocephalus serrulatus Simocephalus vetulus Ceriodaphnia lacustrus 0.37 Latona setifera Alonella excisa 0.12 Ophryoxus gracilis Latona setifera Diacyclops thomasi 0.39 0.15 1.32 3.26 0.70 0.54 0.94 0.88 0.43 0.03 0.12 Mesocyclops edax 0.52 0.68 1.91 5.45 0.61 0.34 0.89 0.18 0.18 0.38 0.71 1.08 1.10
125
Tropocyclops extensus 7.49 4.53 0.21 0.50 0.08 0.31 0.15 0.33 2.08 Cyclops scutifer 0.25 0.03 0.01 Cyclops strenuus 0.02 Eucyclops serrulatus 0.23 Acanthocyclops vernalis 0.03 Skistodiaptomus oregonensis 0.09 0.11 0.43 0.08 0.01 0.81 0.32 0.31 0.24 0.20 Skistodiaptomus reighardi 0.12 Leptodiaptomus minutus 0.08 2.34 0.75 0.15 0.12 0.36 0.03 0.03 0.15 0.20 Epischura lacustris 0.06 0.10 0.40 0.00 0.03 0.07 0.02 Leptodiaptomus sicilis 0.05 0.23 Senecella calanoides 0.18 Limnocalanus macrunus Calanoid copepodid 2.81 4.73 0.59 4.86 3.82 2.30 0.85 2.20 3.20 1.32 2.54 5.54 6.07 Cyclopoid copepodid 0.22 0.43 10.89 7.54 0.63 0.56 0.50 0.51 0.21 0.48 0.89 0.65 2.57
126
Table E.1. continued
Lake Dickson Farncomb Galeairy Gibson Grand Harry Hogan Joe Kioshkokwi LaMuir Laveille Daphnia mendotae 0.58 0.84 0.40 0.05 0.54 0.03 0.37 0.08 0.11 Daphnia retrocurva 1.46 0.43 0.28 0.04 0.41 0.02 Daphnia dubia 0.04 20.37 0.31 2.42 0.19 0.32 Daphnia dentifera 0.04 0.04 0.12 0.05 Daphnia catawba 0.81 Daphnia longiremis 0.25 5.33 0.01 0.61 2.22 0.31 0.05 0.07 Daphnia pulicaria Daphnia ambigua 0.08 Holopedium glacialis 16.45 0.37 0.08 0.22 0.13 0.06 1.35 0.27 0.01 Diaphanosoma birgei 5.31 4.60 0.31 5.75 0.95 0.04 1.12 0.54 0.96 0.41 Bosmina spp 1.32 0.52 1.13 1.05 0.32 1.12 1.01 0.28 0.54 Polyphemus pendiculus 0.02 0.04 0.01 Sida crystillina 1.25 0.03 0.01 0.01 0.02 Chydorus sphaericus 1.94 0.03 0.03 0.16 0.01 0.39 Simocephalus serrulatus 0.03 Simocephalus vetulus Ceriodaphnia lacustrus 0.12 Latona setifera Alonella excisa Ophryoxus gracilis 0.04 Latona setifera Diacyclops thomasi 5.06 0.52 0.03 0.24 0.42 2.29 1.35 1.63 0.38 1.97 0.42 Mesocyclops edax 1.09 13.32 0.00 0.87 0.31 0.27 0.55 0.54 0.32 0.20 Tropocyclops extensus 3.34 0.11 0.55 0.35 0.17 0.12 0.04 Cyclops scutifer 0.08 3.87 0.41 0.01
127
Cyclops strenuus 0.02 Eucyclops serrulatus Acanthocyclops vernalis Skistodiaptomus oregonensis 0.23 1.57 0.08 0.61 0.23 0.01 0.20 0.24 0.06 0.06 Skistodiaptomus reighardi 0.02 Leptodiaptomus minutus 0.21 4.60 0.04 1.32 0.03 0.14 0.09 0.04 0.09 0.19 Epischura lacustris 2.19 0.03 0.01 0.04 0.03 0.04 Leptodiaptomus sicilis 0.39 0.10 Senecella calanoides Limnocalanus macrunus 0.45 Calanoid copepodid 0.06 65.29 0.79 9.51 0.44 1.84 4.42 4.75 1.50 3.16 0.27 Cyclopoid copepodid 4.44 3.45 0.18 0.77 1.68 0.30 0.41 0.25 0.44 0.30 0.29
128
Table E.1. continued
Little Little Little Little Lake Louisa Manitou McCraney McIntosh McKaskill Merchant Cauchon Crooked Dickson Joe Daphnia mendotae 0.72 0.22 0.03 0.28 0.48 0.10 0.42 0.45 0.04 Daphnia retrocurva 2.41 0.29 0.69 0.23 Daphnia dubia 0.07 0.85 0.32 0.34 1.68 0.16 Daphnia dentifera 0.24 0.07 0.08 0.06 Daphnia catawba 0.06 0.04 0.21 Daphnia longiremis 1.02 0.02 0.47 0.32 0.57 1.78 0.04 Daphnia pulicaria 0.15 0.17 Daphnia ambigua Holopedium glacialis 0.04 0.06 0.58 13.82 0.02 0.37 0.11 0.19 0.49 0.08 Diaphanosoma birgei 0.74 1.41 1.26 0.40 0.31 0.06 0.16 0.52 1.09 0.19 Bosmina spp 0.48 0.03 1.60 0.33 0.26 0.06 0.14 0.76 0.18 0.67 Polyphemus pendiculus 0.02 0.03 Sida crystillina 0.02 0.01 Chydorus sphaericus 0.04 0.29 0.04 Simocephalus serrulatus Simocephalus vetulus Ceriodaphnia lacustrus 0.01 Latona setifera Alonella excisa Ophryoxus gracilis Latona setifera Diacyclops thomasi 0.52 0.06 1.29 0.08 0.90 1.46 0.45 1.59 2.38 2.56 Mesocyclops edax 0.62 3.40 0.81 0.73 0.22 0.52 0.20 0.30 0.25 0.10 Tropocyclops extensus 0.14 1.13 0.49 0.11 0.02 0.04 0.39 0.33 Cyclops scutifer 0.14 0.34 0.22 0.10
129
Little Little Little Little Lake Louisa Manitou McCraney McIntosh McKaskill Merchant Cauchon Crooked Dickson Joe
Cyclops strenuus Eucyclops serrulatus Acanthocyclops vernalis 2.38 Skistodiaptomus oregonensis 0.31 0.46 0.14 0.02 0.05 0.01 0.06 0.35 Skistodiaptomus reighardi Leptodiaptomus minutus 0.05 0.06 1.34 0.30 0.05 0.04 0.10 1.54 0.92 0.45 Epischura lacustris 0.06 0.28 0.19 0.06 0.02 0.02 0.06 Leptodiaptomus sicilis 0.15 0.06 0.12 Senecella calanoides 0.35 Limnocalanus macrunus Calanoid copepodid 3.11 7.92 4.35 1.12 4.77 6.28 1.50 5.20 7.10 4.25 Cyclopoid copepodid 0.94 2.89 5.53 0.13 0.29 0.74 0.62 0.35 0.37 0.24
130
Table E.1. continued
North North Ralph Lake Mouse Opeongo Philip Radiant Rain Rence Rock RoseBarry Branch Tea Bice Daphnia mendotae 1.08 0.05 0.01 0.14 1.15 0.52 2.82 0.12 0.48 Daphnia retrocurva 3.51 0.28 0.23 0.01 0.03 0.12 0.60 Daphnia dubia 0.01 0.19 0.34 0.41 0.60 0.09 Daphnia dentifera 0.07 0.02 0.80 0.05 Daphnia catawba 0.67 0.02 6.59 Daphnia longiremis 0.14 0.24 0.01 0.43 0.08 0.26 Daphnia pulicaria 0.19 0.04 Daphnia ambigua Holopedium glacialis 1.41 0.08 0.13 0.61 0.13 0.02 1.93 0.01 0.02 0.28 0.03 Diaphanosoma birgei 3.06 0.12 0.89 1.65 0.17 0.68 0.21 0.33 0.06 1.43 Bosmina spp 19.69 0.14 2.23 0.10 0.12 1.55 0.28 0.74 1.49 Polyphemus pendiculus 0.02 0.01 0.02 0.09 Sida crystillina 0.02 0.19 0.07 Chydorus sphaericus 0.00 0.38 0.71 Simocephalus serrulatus Simocephalus vetulus Ceriodaphnia lacustrus Latona setifera Alonella excisa Ophryoxus gracilis Latona setifera 0.05 Diacyclops thomasi 0.17 0.29 0.71 0.29 1.17 0.66 0.77 0.16 Mesocyclops edax 3.62 0.42 0.47 1.03 0.73 0.75 0.23 1.47 1.01 1.70 Tropocyclops extensus 0.31 0.00 0.91 0.12 0.02 1.04 0.15 Cyclops scutifer 0.53 0.02 0.12 0.43
131
North North Ralph Lake Mouse Opeongo Philip Radiant Rain Rence Rock RoseBarry Branch Tea Bice
Cyclops strenuus Eucyclops serrulatus Acanthocyclops vernalis 0.06 Skistodiaptomus oregonensis 2.55 0.20 0.05 0.02 0.22 0.10 0.05 0.99 0.08 0.12 Skistodiaptomus reighardi 0.34 0.05 0.33 0.06 0.10 0.26 Leptodiaptomus minutus 0.96 0.19 0.10 0.47 0.09 0.20 0.17 0.29 0.15 Epischura lacustris 0.04 0.03 0.04 0.12 0.08 0.02 0.02 Leptodiaptomus sicilis 0.05 Senecella calanoides 0.15 Limnocalanus macrunus Calanoid copepodid 1.41 1.70 6.88 2.18 3.34 1.87 3.50 3.15 5.91 2.46 11.63 Cyclopoid copepodid 2.04 0.25 0.13 0.54 0.67 1.17 0.19 1.16 1.58 1.06 0.77
132
Table E.1. continued
Two Lake Shirley Smoke Source Tea Tim Waterclear Welcome Whitefish Rivers Daphnia mendotae 1.13 0.51 0.28 0.03 0.13 2.52 0.37 0.39 Daphnia retrocurva 0.03 0.16 Daphnia dubia 0.10 0.21 0.13 0.12 0.11 Daphnia dentifera 0.20 0.08 0.28 0.11 0.16 0.35 0.16 Daphnia catawba 0.08 0.49 Daphnia longiremis 0.46 0.09 0.33 1.79 0.17 0.18 0.18 Daphnia pulicaria 0.01 0.05 Daphnia ambigua 0.01 Holopedium glacialis 0.29 0.12 0.45 0.17 0.46 0.10 0.06 0.21 Diaphanosoma birgei 0.95 0.41 0.48 2.04 0.68 0.43 1.42 0.15 Bosmina spp 1.48 0.51 1.22 2.04 0.72 0.50 0.50 0.15 0.47 Polyphemus pendiculus 0.03 Sida crystillina Chydorus sphaericus 0.04 0.06 0.15 Simocephalus serrulatus Simocephalus vetulus Ceriodaphnia lacustrus 0.59 Latona setifera Alonella excisa Ophryoxus gracilis Latona setifera Diacyclops thomasi 0.30 1.27 1.42 0.23 1.84 0.38 11.50 0.88 0.38 Mesocyclops edax 1.01 0.17 0.84 1.41 0.26 0.67 0.60 0.44 0.66 Tropocyclops extensus 0.94 0.31 1.56 0.21 0.50 0.09 0.28 Cyclops scutifer 0.05 0.09 2.36
133
Two Lake Shirley Smoke Source Tea Tim Waterclear Welcome Whitefish Rivers
Cyclops strenuus Eucyclops serrulatus Acanthocyclops vernalis 0.03 Skistodiaptomus oregonensis 0.03 0.14 0.14 0.04 0.06 0.03 0.32 Skistodiaptomus reighardi 0.03 0.10 Leptodiaptomus minutus 0.04 0.07 0.03 0.06 0.31 0.02 0.92 0.03 Epischura lacustris 0.02 0.02 0.03 0.04 0.01 0.05 Leptodiaptomus sicilis 0.01 Senecella calanoides Limnocalanus macrunus Calanoid copepodid 3.88 1.24 3.15 10.41 0.24 1.43 7.83 2.60 2.20 Cyclopoid copepodid 1.17 0.71 0.64 1.05 0.30 0.29 3.56 0.27 0.60
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APPENDIX F: Killarney Provincial Park macroinvertebrate abundances
Table F.1. Abundance (#/L) of Chaoborus, the invasive Bythotrephes longimanus, and Leptodora kinditii from 44 lakes in Killarney Provincial Park sampled in 2016.
Lake Chaoborus species Bythotrephes longimanus Leptodora kinditii Acid 0.000562875 0 0 AY Jackson 0 0 0 Bell 0.000987525 0 0.0022572 Bodina 0 0 0 Boundary 0.013208798 0 0.006604399 Carlyle 0.000841126 0.002523379 0.001261689 Charlton 0 0 0.002547411 Clearsilver 0.034995059 0 0 David 0.001074209 0 0.002148419 Delamorandiere 0.003900723 0 0.008915939 Fish 0.000969124 0 0.010660361 Freeland 0.001783188 0 0.007132751 Frood 0.000995082 0 0.000597049 Gail 0.001418445 0 0.00324216 Gem 0.00053927 0 0 George 0 0 0.001055141 Great Mountain 0.007854517 0 0.000849137 Helen 0 0 0.001578042 Howry 0.002726949 0 0.001778445 Ishmael 0 0 0.002315828 Johnnie 0.000114896 0.000114896 0.001148961 Kakakise 0 0 0.002206916 Killarney 0 0 0 LaCloche 0 0.007686154 0 Little mountain 0.075303536 0 0.002409713 Little Sheguindah 0.001671738 0 0.001671738 Little Superior 0 0 0.001180919 Logboom 0 0 0.003566375 Low 0 0.000371497 0.00198132 Lumsden 0.075303536 0 0 Muriel 0.000227447 0 0.003639159 Nellie 0 0 0 Norway 0.034117112 0 0.001819579 OSA 0 0 0.00198132 Partridge 0.00200974 0 0 Proulx 0 0 0.001959547
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Lake Chaoborus species Bythotrephes longimanus Leptodora kinditii Roque 0.119409893 0 0 RuthRoy 0.087069713 0 0.002786231 Shingwak 0.002492943 0 0 Solomon 0.000742995 0 0.005943959 Terry 0.052752637 0 0 Threenarrows E 9.60769E-05 0 0.001537231 Threenarrows N 0 0 0 Turbid 0.009858971 0 0.006858414 Tyson 0.001149873 0 0.000884518 Whiskeyjack 0.000104158 0 0.001666531
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APPENDIX G: Killarney Provincial Park fish presence/absence data and PCA
Table G.1. Presence (1) and absence (0) of freshwater fish species from 44 surveyed lakes in Killarney Provincial Park. Data from Snucins and Gunn, 1998.
BS CM BNM BT BB FHM GS BLU (brook (central CIS LAKE (bluntnose (brook (brown (fathead (golden (bluegill) stickle- mudminno (cisco) minnow) trout) bullhead) minnow) shiner) backs) w) Acid 0 0 0 0 0 0 0 0 0 AY Jackson 0 0 0 0 0 0 0 0 0 Bell 0 0 0 0 1 0 1 0 1 Bodina 0 1 0 0 0 0 0 0 1 Boundary 0 0 0 0 0 0 0 0 1 Carlyle 0 0 0 0 1 0 1 0 1 Charlton 0 0 0 0 0 0 0 0 0 Clearsilver 0 0 0 0 0 0 0 0 0 David 0 0 0 0 0 0 0 0 0 deLamorandiere 0 0 0 0 0 0 0 0 0 Fish 1 0 0 0 0 0 0 0 0 Freeland 0 0 1 0 1 1 0 1 1 Frood 0 0 0 0 0 0 0 0 0 Gail 0 0 0 0 0 0 0 0 0 Gem 0 1 0 0 1 0 1 0 0 George 0 1 1 0 1 0 1 0 0 Great Mountain 0 0 0 0 0 0 1 0 0 Helen 1 1 0 0 0 0 1 0 0 Howry 1 0 0 0 1 0 1 0 0 Ishmael 1 1 0 0 0 0 1 0 0
137
Johnnie 0 0 0 0 1 0 1 0 1 Kakakise 0 1 0 0 0 1 1 1 1 Killarney 0 0 0 0 1 1 0 0 0 LaCloche 0 0 0 0 0 0 0 0 0 Little Mountain 0 0 0 0 0 0 0 0 0 Little Sheguindah 0 0 0 0 1 0 0 0 1 Little Superior 0 0 0 0 0 0 0 0 0 Logboom 0 0 0 0 0 0 0 0 1 Low 1 1 0 0 0 0 1 0 0 Lumsden 0 0 0 0 0 0 0 0 0 Muriel 0 0 0 0 1 0 0 0 0 Nellie 0 0 0 0 0 0 0 0 0 Norway 0 0 0 0 0 1 0 0 0 OSA 0 0 0 0 0 0 0 0 0 Partridge 0 0 0 0 0 0 0 0 0 Proulx 0 0 0 0 0 0 0 0 0 Ruthroy 0 0 0 0 0 0 0 0 0 Shingwak 0 0 0 0 0 0 0 0 0 Solomon 0 0 0 0 0 0 0 0 0 Terry 0 0 0 0 1 0 0 0 0 Threenarrows North 1 1 0 0 0 0 1 0 0 Threenarrows East 1 1 0 0 0 0 1 0 0 Turbid 1 0 0 1 0 0 0 0 0 Whiskeyjack 0 0 0 0 0 0 0 0 0
138
Table G.1. continued NRD ID JD LT LW LMB NP PUM RB (northern LAKE (Iowa (johnny (lake (lake (largemouth (northern (pumpkin- (rock redbelly darter) darter) trout) whitefish) bass) pike) seed) bass) dace) Acid 0 0 0 0 0 0 0 1 1 AY Jackson 0 0 0 0 0 0 0 0 0 Bell 0 0 1 1 1 1 0 1 1 Bodina 1 0 0 0 0 0 1 1 1 Boundary 0 0 0 0 0 0 0 1 0 Carlyle 0 0 0 0 0 1 0 1 1 Charlton 0 0 0 0 0 0 0 0 0 Clearsilver 0 0 0 0 0 0 0 0 0 David 0 0 0 0 0 0 0 0 0 deLamorandiere 0 0 0 0 0 0 0 0 0 Fish 0 0 0 0 1 0 0 1 1 Freeland 0 0 0 0 0 1 1 1 0 Frood 0 0 0 0 0 0 0 0 0 Gail 0 0 0 0 0 0 0 0 0 Gem 0 1 0 0 0 1 0 1 1 George 0 0 1 1 0 1 0 1 1 Great Mountain 0 0 1 0 1 0 0 1 0 Helen 1 0 1 0 0 0 0 1 1 Howry 0 0 0 0 0 1 0 1 1 Ishmael 0 0 1 0 0 1 0 1 1 Johnnie 0 0 1 1 0 1 0 1 1 Kakakise 1 0 1 0 0 1 0 1 1 Killarney 0 0 0 0 0 0 0 1 0 LaCloche 0 0 0 0 0 0 0 0 0
139
Little Mountain 0 0 0 0 0 0 0 0 0 Little Sheguindah 0 0 0 0 0 0 0 1 1 Little Superior 0 0 0 0 0 0 0 0 0 Logboom 0 0 0 0 0 1 0 1 0 Low 1 1 1 0 0 0 0 1 1 Lumsden 0 0 0 0 0 0 0 0 0 Muriel 0 0 0 0 0 0 0 1 0 Nellie 0 0 0 0 0 0 0 0 0 Norway 0 0 0 0 0 0 0 0 0 OSA 0 0 0 0 0 0 0 0 0 Partridge 0 0 0 0 0 0 0 0 0 Proulx 0 0 0 0 0 0 0 0 0 Ruthroy 0 0 0 0 0 0 0 0 0 Shingwak 0 0 0 0 0 0 0 0 0 Solomon 0 0 0 0 0 0 0 0 0 Terry 0 0 0 0 0 0 0 1 0 Threenarrows Nort 0 0 1 0 0 1 0 1 1 Threenarrows East 0 0 1 0 0 1 0 1 1 Turbid 0 0 0 0 0 0 0 1 0 Whiskeyjack 0 0 0 0 0 0 0 0 0
140
Table G.1. continued
SMB WS YP SS (slimy WAL LAKE (smallmouth (white (yellow sculpin) (walleye) bass) sucker) perch) Acid 0 1 0 0 1 AY Jackson 0 1 0 0 0 Bell 0 1 0 1 1 Bodina 0 0 0 0 1 Boundary 0 0 0 0 1 Carlyle 0 1 0 1 1 Charlton 0 0 0 0 0 Clearsilver 0 0 0 0 0 David 0 0 0 0 1 deLamorandiere 0 0 0 0 0 Fish 0 0 0 0 1 Freeland 0 0 0 1 1 Frood 0 0 0 0 0 Gail 0 0 0 0 0 Gem 0 1 0 1 1 George 0 0 0 1 1 Great Mountain 0 0 0 0 0 Helen 1 1 0 0 1 Howry 1 1 0 0 1 Ishmael 0 1 0 0 1 Johnnie 0 1 0 1 1 Kakakise 0 1 0 0 1 Killarney 0 0 0 0 1 LaCloche 0 0 0 0 0
141
Little Mountain 0 0 0 0 0 Little Sheguindah 0 0 0 1 1 Little Superior 0 0 0 0 0 Logboom 0 0 0 1 1 Low 0 1 0 0 0 Lumsden 0 0 0 0 0 Muriel 0 0 0 0 1 Nellie 0 0 0 0 0 Norway 0 0 0 0 1 OSA 0 0 0 0 0 Partridge 0 0 0 0 1 Proulx 0 0 0 0 0 Ruthroy 0 0 0 0 0 Shingwak 0 0 0 0 0 Solomon 0 0 0 0 0 Terry 0 0 0 0 1 Threenarrows North 0 1 1 0 1 Threenarrows East 0 1 1 0 1 Turbid 0 0 0 0 1 Whiskeyjack 0 0 0 0 0
142
acid neutral recovered
0.50
e r 0.25
o
c
S
1
0.00
A
C
P
6 −0.25 1
0
2
−0.50
−0.6 −0.4 −0.2 0.0
Figure G.1. Principal components analysis of fish presence/absence data collected1972 by Snucins PCA and Gunn, 1 Score 1998, from 44 lakes in Killarney Provincial Park, Ontario, categorized into three groups based on water quality improvements: acid (pH<6 since 1972-73), recovered (pH recovered from < 6 to > 6 after 1972-73 and before 2016), and circumneutral (pH >6 since 1972-73). Species abbreviations can be found in Table G.1.
143
Table G.2. Principal component analysis axis 1 and 2 scores for fish presence absence data collected by Snucins and Gunn, 1998, for 44 lakes in Killarney Provincial Park, Ontario.
PC1 PC2 FISH SPECIES (29.1%) (15.4%) Bluegill 0.992980725 1.93477424 Bluntnose minnow 1.511408153 1.128143367 Brook sticklebacks 0.6218327 1.742224793 Brook trout 0.122870345 0.271012187 Brown bullhead 1.036802259 1.595618637 Central mudminnow 0.300090829 1.361474444 Cisco 1.886733029 0.818935142 Fathead minnow 0.63175799 1.456446419 Golden shiner 0.959552542 1.798614956 IIowa darter 0.84034565 0.742915854 Johnny darter 0.624611997 0.715764402 Lake trout 1.623310397 0.876503106 Lake whitefish 1.002444702 0.943634013 Largemouth bass 0.343373054 0.028229637 Northern pike 1.764721578 0.626444207 Northern redbelly dace 0.338072593 1.458337563 Pumpkinseed 1.764368204 0.258052282 Rock bass 1.886730282 0.595619184 Slimy sculpin 0.600374071 0.963002899 Smallmouth bass 1.634930936 1.053166736 Walleye 0.721521305 1.163436268 White sucker 1.155885817 1.843341013 Yellow perch 1.444280083 0.666856325
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APPENDIX H: Water sample chemistry measurement comparisons
Water samples for chemistry analysis were collected using two different methods between Killarney Provincial Park (n=44) and Algonquin Provincial Park (n=55). In Killarney PP, the end of a 5-meter, 1.9cm diameter tube sampler was lowered into the water column, raised, and the collected water was filtered through an 80µm mesh. The composite sampler hauled twice the measured secchi depth of the lake, allowing water to be collected equally as it was lowered through the water water, and collected water was filtered through 80µm mesh. To assess whether these two methods resulted in comparable measurements, we collected water samples using both methods in 9 lakes in Killarney PP. These samples were shipped to the Ministry of Environment and Climate Change in Dorset, Ontario, for analysis after being refrigerated for no more than 4 days. I performed two sample t-tests comparing the values measured from water samples taken from the tube sampler and composite sampler. As summarized in Table_, we detected no difference in measurements between the two water-sampling methods (p>0.05); therefore we were able to use Algonquin Provincial Park lakes as a reference system in our study.
Table H.1. Results from two-sample t-tests comparing water chemistry measurements taken using a tube sampler and a composite sampler in 9 lakes in Killarney Provincial Park in 2016.
Variable t df p-value pH -0.08 15.99 0.94 Calcium -0.02 16.00 0.99 DOC -0.70 15.10 0.49 TP -0.03 15.81 0.98 TKN -0.57 15.90 0.58 Gran Alkalinity -0.99 8.00 0.35 DIC -0.43 15.69 0.67 Chloride 0.03 15.98 0.98 Conductivity -0.09 15.94 0.93 Iron 0.21 16.00 0.83 Magnesium -0.08 15.97 0.93 Potassium -0.15 15.94 0.88 Sodium -0.04 15.99 0.97 Reactive silicate -0.01 15.91 0.99 Sulphate -0.14 14.90 0.89
145
pH Calcium (mg/L) DOC (mg/L) 0 5 . 2 . . 2 5 6 6 0 8 . . . 1 4 5 5 4 2 . . . 2 5 1 5.4 5.6 5.8 6.0 6.2 1.2 1.4 1.6 1.8 2.0 3 4 5 6 7
Total Phosphorus (µg/L) Sulphate (mg/L) Total Kjeldahl Nitrogen (µg/L) 6 0 . 2 4 7 3 4 . 4 0 6 5 2 2 . 4 0 3 0 0 . 2 4 3 4 5 6 7 4.0 4.2 4.4 4.6 200 250 300
Chloride (mg/L) Iron (µg/L) Potassium (mg/L) 8 . 5 0 3 0 . 2 0 1 5 . 0 0 5 6 2 . 2 0 . 0 0 2 0.2 0.4 0.6 0.8 20 60 100 140 0.25 0.30 0.35
Conductivity (µS/cm) Sodium (mg/L) Aluminum (µg/L) 1 3 . 2 1 0 2 1 1 2 9 . 0 9 0 1 6 7 . 7 0 0 1 2 17 19 21 23 0.7 0.8 0.9 1.0 1.1 50 100 150
Silicate (mg/L) Figure H.1. Comparison of water quality measurements analyzed following the Ministry of Environment and 4 .
1 Climate Change protocols taken using a 5m, 1.9cm diameter, composite tube sampler (Y axis), and a 0 . 1 composite sampler (X axis) dropped to twice the secchi
6 depth of lakes, from 9 lakes in Killarney Provincial Park, . 0 Ontario. Each point represents one lake, and the dashed 0.4 0.8 1.2 line is the 1:1.
146
APPENDIX I. Comparison of Algonquin Provincial Park and Killarney Provincial Park physical and chemical lake measurements 0 6 0 0 ) 0 ) 5 ) m 0
( 0
0 m ( 4 m 0 n
( 1 o h i t t a 0 p a e 0 0 r e v 0 0 0 e A 2 6 D l 2 E 0 0 0 0 2 Algonquin Killarney Algonquin Killarney Algonquin Killarney 0 8 2 ) ) 5 L . / m 5 6 g 6 ( 1
i m H h (
p c 0 4 c 5 C 1 . e 5 O S D 2 5 5 . 4 Algonquin Killarney Algonquin Killarney Algonquin Killarney ) L ) / 0 g m 7 ) µ c 8 / ( L
5 / S s 2 g µ u ( r 0 6 m ( 5 o y
t h i 5 m v p 1 i 4 u t s i c 0 o c l u 3 h a d p 2
5 n l C o a t 0 0 C o 1 T Algonquin Killarney Algonquin Killarney Algonquin Killarney 0 5 . 0 3 2 ) 4 ) 1 L L / / ) g 5 g 0 L . 3 / 0 m 2 m g ( 8 (
µ e (
m 2 d 5 i n . 0 u r i 1 o 0 o r d l 4 I o 1 h S C 5 . 0 0 0 Algonquin Killarney Algonquin Killarney Algonquin Killarney
Figure I.1. Comparison of lake morphometry and chemistry between 55 lakes in Algonquin Provincial Park and 44 lakes in Killarney Provincial Park.
147
APPENDIX J: Water chemistry protocols used in the analyses of water samples. For more information contact the Ministry of Environment and Climate Change Laboratory Services Branch in Rexdale, Ontario. DOC = Dissolved organic carbon, Ca = Calcium, Mg = Magnesium, Na = Sodium, K = potassium, TP = total phosphorus, Cl = Chloride, SO4 = Sulphate, TKN = Total Kjeldahl Nitrogen, Al = Aluminum, Cu = Copper, Fe= Iron, Ni = Nickel, Zn = Zinc.
Parameter Protocol Report Report Code pH and alkalinity The determination of pH and alkalinity in lakes, streams, groundwater DOCSI-E3042 and precipitation samples.
DOC and Silica The determination of molybdate reactive silicates and dissolved DOT-E3422 organic carbon in water and precipitation by colourimetry.
Ca, Mg, Na, and K The determination of cations in precambrian shield waters by Atomic DOFLAME-E3249 Absorption Spectrophotometry (AAS)
TP The determination of total phosphorus in water by colourimetry DOP-E3036
Cl and SO4 The determination of chloride and sulphate in surface water and wet DOIC-E3147 deposition samples by automated Ion Chromatography (IC).
TKN The determination of Total Kjeldahl Nitrogen in surface water and DTKN-E3424 precipitation by colourimetry
Conductivity The determination of conductivity in water and precipitation by DOCOND-E3024 potentiometry
Al, Cu, Fe, Ni, Zn The determination of metals in surface water by inductively coupled MET-E3386 plasma – Atomic Emissions Sepectroscopy (ICP-AES) using ultrasonic neubulization.
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APPENDIX K: Correlation matrices for chemical and physical data for Killarney and Algonquin Provincial Parks.
Table K.1. Pearson’s correlation values between select physical and chemical variables from 44 lakes in Killarney Provincial Park. Shaded cells represent significant correlations (p<0.05).
Depth Secchi Area Elev. Bytho Fish Al Ca DOC Cl Cond Cu Fe Pb Mg Ni TKN pH K Si SO4 TP Depth 0.44 0.54 -0.34 -0.34 -0.44 0.36 0.33 -0.49
Secchi 0.44 0.47 -0.61 0.56 -0.82 0.52 -0.39 0.5 -0.65 -0.67 -0.43 0.4 -0.5
Area 0.54 0.3 0.3 0.32 0.36
Elevation 0.47 -0.77 0.72 -0.44 -0.35 0.36 0.63 -0.57 0.45 -0.76 -0.55 -0.34
Bytho 0.33 0.35 0.33 0.31 0.36
Fish -0.46 -0.53 0.41 -0.43 0.38 -0.37 0.33 -0.36 0.55 0.39 0.39
Al 0.56 0.72 -0.64 -0.4 0.3 0.38 0.9 -0.48 0.64 -0.77 -0.47 -0.32
Ca -0.44 0.33 0.39 -0.4 0.67 0.95 -0.31 0.96 -0.34 0.71 0.86 0.42
DOC -0.34 -0.82 0.3 0.53 0.46 0.41 -0.35 0.87 0.58 0.55 -0.39 0.73
Cl 0.67 0.79 0.42 0.64 0.47 0.66 0.54
Cond. -0.35 0.31 0.95 0.79 0.92 0.6 0.84 0.59
Cu 0.3 0.42 0.36 0.46
Fe -0.34 0.36 0.38 0.46 0.38 0.74 -0.37 0.87
Pb 0.52 0.63 -0.52 0.9 -0.31 0.36 0.38 -0.38 0.49 -0.64 -0.37 -0.47
Mg -0.39 -0.57 0.35 0.54 -0.48 0.96 0.41 0.64 0.92 -0.38 -0.42 0.82 0.92 0.33
Ni 0.5 0.45 -0.45 0.64 -0.34 -0.35 0.46 0.49 -0.42 -0.33 -0.64 -0.37 0.31
TKN -0.44 -0.65 0.87 0.74 -0.33 0.32 0.33 -0.44 0.94 pH -0.67 -0.76 0.33 0.79 -0.77 0.71 0.58 0.47 0.6 -0.64 0.82 -0.64 0.32 0.85
K -0.43 0.32 -0.55 0.31 0.61 -0.47 0.86 0.55 0.66 0.84 -0.37 0.92 -0.37 0.33 0.85 0.3
Si 0.36 0.36 -0.34 0.36 -0.32 -0.47 -0.33
SO4 0.33 0.4 0.42 -0.39 0.54 0.59 -0.37 0.33 0.31 -0.44 0.3 -0.47
TP -0.49 -0.5 0.73 0.87 0.94 -0.33 -0.47
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Table K.2. Pearson’s correlation values between select physical and chemical variables from 55 lakes in Algonquin Provincial Park. Shaded cells represent significant correlations (p<0.05).
Ca Cl DOC DIC K Mg Na Si SO4 Fe TKN TP Cond pH Al Mn Secchi Area Depth Ca 0.85 0.90 0.95 0.68 0.76 0.92 0.90 -0.43 Cl 0.94 0.32 0.28 DOC 0.85 0.81 0.83 0.70 0.59 0.76 0.77 -0.45 DIC 0.64 0.74 0.64 0.54 0.45 -0.58 K 0.90 0.81 0.92 0.69 0.72 0.82 0.84 -0.41 Mg 0.95 0.83 0.92 0.66 0.81 0.89 0.88 -0.49 Na 0.94 0.28 0.60 0.28 Si 0.68 0.70 0.69 0.66 0.34 0.64 0.55 SO4 0.76 0.59 0.72 0.81 0.28 0.34 -0.28 0.78 0.77 -0.56 0.32 Fe 0.64 -0.28 0.58 0.50 0.58 0.63 -0.45 TKN 0.74 0.58 0.73 0.37 0.57 -0.63 TP 0.64 0.50 0.73 0.64 -0.54 Cond 0.92 0.32 0.76 0.82 0.89 0.60 0.64 0.78 0.86 -0.43 pH 0.90 0.77 0.84 0.88 0.28 0.55 0.77 0.86 -0.53 0.29 Al -0.43 -0.45 0.54 -0.41 -0.49 -0.56 0.58 0.37 -0.43 -0.53 -0.37 Mn 0.45 0.63 0.57 0.64 -0.31 -0.43 Secchi 0.28 -0.58 -0.45 -0.63 -0.54 -0.37 -0.31 Area 0.32 0.29 Depth -0.43
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APPENDIX L. Dredge tables of top models for multiple regression analysis on zooplankton community metrics
SPECIES RICHNESS
Table L.1. Top models from multiple regression analysis on species richness in 1972-73.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -2.688 0.009 -0.084 -0.021 2.812 NA 6.000 -88.824 191.919 0.000 0.499 -0.486 0.008 -0.061 -0.022 2.508 -0.130 7.000 -88.053 193.217 1.298 0.261 -9.337 0.009 -0.090 NA 3.201 NA 5.000 -90.899 193.377 1.458 0.241
Table L.2. Top models from multiple regression analysis on species richness in 1990.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight 0.375 0.000 NA NA 0.290 NA 3 -99.058 204.732 0.000 0.442 0.224 NA NA NA 0.327 NA 2 -101.014 206.328 1.595 0.199 -0.324 0.000 NA 0.002 0.337 NA 4 -98.711 206.474 1.742 0.185 0.130 0.000 NA NA 0.322 0.008 4 -98.775 206.603 1.871 0.174
Table L.3. Top models from multiple regression analysis on species richness in 2000.
(Intercept) A1c00 A3c00 Area Bytho Depth Elevation fish.pca Secchi df logLik AICc delta weight 4.126 NA NA NA NA NA -0.008 NA -0.076 3 -91.368 189.336 0.000 0.451 3.931 NA NA 0.0003 NA NA -0.007 NA -0.075 4 -90.380 189.785 0.449 0.360 3.929 NA NA NA NA 0.004 -0.007 NA -0.086 4 -91.021 191.067 1.731 0.190
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Table L.4. Top models from multiple regression analysis on species richness in 2005.
(Intercept) A1c05 A3c05 Area Bytho Depth Elevation Fish.pca df logLik AICc delta weight 1.934 0.386 NA NA NA NA NA NA 2 -76.489 157.353 0.000 0.329 1.885 0.353 NA 0.0003 NA NA NA NA 3 -75.737 158.247 0.894 0.211 1.931 0.396 -0.230 NA NA NA NA NA 3 -75.816 158.405 1.053 0.195 1.874 0.358 -0.269 0.0004 NA NA NA NA 4 -74.862 159.056 1.704 0.140 1.931 0.368 NA NA NA NA NA 0.096 3 -76.258 159.290 1.937 0.125
Table L.5. Top models from multiple regression analysis on species richness in 2016.
(Intercept) A1c16 A2c16 Area Bytho Depth Elevation fish.pca df logLik AICc delta weight 3.354 -0.241 NA NA NA NA -0.006 NA 3 -101.733 210.066 0.000 0.296 3.172 -0.237 NA 0.0003 NA NA -0.005 NA 4 -100.664 210.353 0.287 0.256 3.373 -0.258 0.182 NA NA NA -0.006 NA 4 -101.000 211.025 0.959 0.183 3.198 -0.253 0.173 0.0003 NA NA -0.005 NA 5 -100.015 211.609 1.543 0.137 3.286 -0.213 NA 0.0004 NA -0.005 -0.005 NA 5 -100.077 211.733 1.667 0.128
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SPECIES DIVERSITY
Table L.6. Top models from multiple regression analysis on Shannon-Weiner diversity in 1972-73.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -4.302 0.004 -0.049 NA 1.561 NA 5.000 -72.665 156.909 0.000 0.483 -1.228 0.004 -0.046 -0.010 1.382 NA 6.000 -71.673 157.617 0.708 0.339 -3.291 0.004 -0.038 NA 1.420 -0.061 6.000 -72.313 158.897 1.988 0.179
Table L.7. Top models from multiple regression analysis on Shannon-Weiner diversity in 1990.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -7.847 0.003 NA NA 1.925 NA 4 -67.884 144.821 0.000 0.555 -8.865 0.002 0.022 NA 2.031 NA 5 -66.819 145.260 0.439 0.445
Table L.8. Top models from multiple regression analysis on Shannon-Weiner diversity in 2000.
(Intercept) A1c00 A3c00 Area Bytho Depth Elevation fish.pca Secchi df logLik AICc delta weight 4.102 -1.041 NA 0.002 NA NA NA + -0.095 7 -71.079 159.270 0.000 0.242 3.994 -1.204 NA 0.003 NA -0.033 NA + NA 7 -71.313 159.737 0.468 0.192 3.366 -1.565 NA 0.002 NA NA NA + NA 6 -72.971 160.213 0.943 0.151 8.334 NA NA 0.003 NA -0.049 -0.018 + NA 7 -71.768 160.647 1.377 0.122 6.502 -0.842 NA 0.003 NA -0.036 -0.011 + NA 8 -70.409 160.933 1.663 0.105 4.539 NA NA 0.002 NA NA NA + -0.154 6 -73.421 161.113 1.843 0.096 7.183 NA NA 0.002 NA NA -0.013 + -0.127 7 -72.050 161.212 1.942 0.092
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Table L.9. Top models from multiple regression analysis on Shannon-Weiner diversity in 2005.
(Intercept) A1c05 A3c05 Area Bytho Depth Elevation Fish.pca Secchi df logLik AICc delta weight 3.540 2.483 NA NA NA NA NA NA NA 3 -60.307 127.388 0.000 0.528 3.379 2.386 NA 0.001 NA NA NA NA NA 4 -59.801 128.935 1.547 0.244 3.530 2.327 NA NA NA NA NA 0.504 NA 4 -59.865 129.063 1.676 0.228
Table L.10. Top models from multiple regression analysis on Shannon-Weiner diversity in 2016.
(Intercept) A1c16 A2c16 Area Bytho Depth Elevation fish.pca df logLik AICc delta weight 12.430 NA NA 0.004 NA NA -0.034 NA 4 -92.198 193.422 0.000 0.722 11.150 -0.580 NA 0.004 NA NA -0.028 NA 5 -91.876 195.331 1.909 0.278
SPECIES EVENNESS
Table L.11. Top models from multiple regression analysis on species evenness (Evar) in 1972-73.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -1.095 NA NA NA NA NA 2.000 -39.239 82.771 0.000 0.723 -1.188 NA 0.004 NA NA NA 3.000 -39.045 84.690 1.919 0.277
Table L.12. Top models from multiple regression analysis on species evenness (Evar) in 1990.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -3.621 NA NA NA 0.325 NA 3 -39.953 86.521 0.000 0.507 -3.874 NA 0.007 NA 0.339 NA 4 -39.283 87.619 1.098 0.293 -4.300 -0.001 0.013 NA 0.404 NA 5 -38.377 88.376 1.855 0.200
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Table L.13. Top models from multiple regression analysis on species evenness (Evar) in 2000.
(Intercept) A1c00 A3c00 Area Bytho Depth Elevation fish.pca Secchi df logLik AICc delta weight -0.367 -0.160 NA NA NA NA 0.003 NA NA 4 5.955 -2.884 0.000 0.201 -0.498 -0.182 -0.209 NA NA NA 0.004 NA NA 5 7.166 -2.754 0.130 0.188 -0.435 -0.141 NA NA 0.116 NA 0.004 NA NA 5 6.838 -2.097 0.787 0.135 -0.508 -0.191 NA NA NA 0.003 0.004 NA NA 5 6.698 -1.816 1.067 0.118 -0.134 NA NA NA 0.145 NA 0.002 NA NA 4 5.227 -1.428 1.455 0.097 0.355 NA NA NA NA NA NA NA NA 2 2.814 -1.336 1.548 0.093 0.006 NA NA NA NA NA 0.002 NA NA 3 3.913 -1.226 1.657 0.088 -0.529 -0.164 -0.175 NA 0.088 NA 0.004 NA NA 6 7.667 -1.063 1.820 0.081
Table L.14. Top models from multiple regression analysis on species evenness (Evar) in 2005.
(Intercept) Area Bytho Depth Elevation A1c05 A3c05 Fish.pca Secchi df logLik AICc delta weight 0.235 NA NA NA NA 0.130 NA NA NA 3 15.944 -25.088 0.000 0.163 0.839 NA NA NA -0.003 NA NA NA NA 3 15.870 -24.940 0.148 0.151 0.236 NA NA NA NA 0.129 0.108 NA NA 4 16.792 -24.205 0.884 0.105 0.334 NA NA NA NA NA 0.180 NA -0.012 4 16.788 -24.196 0.892 0.104 0.321 NA NA -0.004 NA 0.104 0.185 NA NA 5 18.161 -24.178 0.910 0.103 0.603 NA NA NA -0.002 0.082 NA NA NA 4 16.682 -23.986 1.103 0.094 0.977 NA NA NA -0.003 NA NA -0.069 NA 4 16.466 -23.552 1.537 0.076 0.254 0.000 NA NA NA 0.140 NA NA NA 4 16.460 -23.541 1.547 0.075 0.846 NA NA -0.002 -0.003 NA NA NA NA 4 16.316 -23.253 1.836 0.065 0.365 NA NA NA NA NA 0.202 -0.084 -0.015 5 17.667 -23.191 1.897 0.063
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Table L.15. Top models from multiple regression analysis on species evenness (Evar) in 2016.
(Intercept) A1c16 A2c16 Area Bytho Depth Elevation fish.pca df logLik AICc delta weight 0.359 NA NA NA NA -0.012 -0.009 + 6 -31.789 77.849 0.000 0.152 0.680 NA NA NA NA NA -0.011 NA 3 -35.730 78.060 0.212 0.137 0.145 NA NA 0.001 NA -0.016 -0.008 + 7 -30.648 78.407 0.558 0.115 0.454 NA NA NA -0.286 -0.011 -0.009 + 7 -30.910 78.931 1.082 0.089 0.595 NA NA 0.001 NA -0.012 -0.010 NA 5 -33.792 79.163 1.314 0.079 0.850 NA NA NA NA -0.007 -0.011 NA 4 -35.078 79.181 1.332 0.078 0.153 NA NA NA NA NA -0.009 + 5 -33.810 79.199 1.351 0.078 0.722 NA 0.239 NA NA NA -0.012 NA 4 -35.161 79.349 1.500 0.072 0.236 NA NA 0.001 -0.300 -0.015 -0.008 + 8 -29.623 79.361 1.512 0.072 0.293 NA NA NA -0.348 NA -0.009 + 6 -32.582 79.434 1.585 0.069 0.287 -0.173 NA NA NA NA -0.010 NA 4 -35.356 79.737 1.888 0.059
TOTAL CRUSTACEAN ABUNDANCE
Table L.16. Top models from multiple regression analysis on total crustacean abundance in 1972-73.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight 5.513 0.001 -0.041 -0.012 NA 0.100 6.000 -46.157 106.584 0.000 0.587 5.841 NA -0.029 -0.013 NA 0.076 5.000 -47.855 107.289 0.705 0.413
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Table L.17. Top models from multiple regression analysis on total crustacean abundance in 1990.
(Intercept) Area Depth Elevation pH Secchi df logLik AICc delta weight -1.330 0.002 -0.076 NA 0.681 0.080 6 -65.170 144.673 0.000 0.343 -2.069 NA -0.058 NA 0.796 0.065 5 -66.790 145.201 0.528 0.263 -0.537 NA -0.045 NA 0.569 NA 4 -68.183 145.418 0.744 0.236 0.282 0.001 -0.057 NA 0.443 NA 5 -67.307 146.236 1.563 0.157
Table L.18. Top models from multiple regression analysis on total crustacean abundance in 2000.
(Intercept) A1c00 A3c00 Area Bytho Depth Elevation fish.pca Secchi df logLik AICc delta weight 35.586 -12.451 45.386 -0.019 NA NA NA NA -1.506 6 -187.166 388.603 0.000 0.104 34.066 -16.532 34.228 NA NA -0.570 NA NA NA 5 -188.546 388.672 0.069 0.100 32.488 -10.499 50.315 NA NA NA NA NA -1.488 5 -188.701 388.980 0.378 0.086 37.498 NA 50.808 NA NA NA NA NA -2.141 4 -189.987 389.000 0.397 0.085 95.661 NA 38.774 NA NA -0.689 -0.269 NA NA 5 -188.837 389.252 0.650 0.075 68.492 -10.594 38.034 NA NA -0.593 -0.155 NA NA 6 -187.598 389.465 0.863 0.067 37.378 -14.632 41.560 -0.019 -9.833 NA NA NA -1.516 7 -186.240 389.591 0.989 0.063 40.758 NA 46.896 -0.016 NA NA NA NA -2.253 5 -189.023 389.626 1.023 0.062 74.559 NA 50.571 -0.019 NA NA -0.170 NA -1.754 6 -187.682 389.634 1.032 0.062 64.858 NA 54.481 NA NA NA -0.140 NA -1.710 5 -189.096 389.771 1.168 0.058 34.430 -12.818 46.210 NA -10.234 NA NA NA -1.499 6 -187.764 389.798 1.196 0.057 36.665 -11.868 40.005 NA NA -0.376 NA NA -0.914 6 -187.830 389.930 1.327 0.053 79.695 NA 43.646 NA NA -0.443 -0.187 NA -0.990 6 -187.976 390.222 1.620 0.046 34.624 -18.487 32.148 NA -7.461 -0.535 NA NA NA 6 -188.061 390.392 1.790 0.042 41.252 NA 42.847 NA NA -0.292 NA NA -1.761 5 -189.482 390.543 1.941 0.039
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Table L.19. Top models from multiple regression analysis on total crustacean abundance in 2005.
(Intercept) Area Bytho Depth Elevation nA1c05 nA3c05 Fish.pca Secchi df logLik AICc delta weight 2.806 NA NA NA NA 1.107 -0.961 NA NA 4 -42.282 93.942 0.000 0.363 2.811 NA NA NA NA 1.098 NA NA NA 3 -44.291 95.382 1.439 0.177 2.918 -0.001 NA NA NA 1.170 -0.881 NA NA 5 -41.682 95.507 1.564 0.166 2.891 NA -0.363 NA NA 1.178 -0.829 NA NA 5 -41.775 95.692 1.749 0.152 2.935 NA -0.533 NA NA 1.204 NA NA NA 4 -43.223 95.826 1.883 0.142
Table L.20 Top models from multiple regression analysis on total crustacean abundance in 2016.
(Intercept) Area Bytho Depth Elevation nA1c16 nA2c16 fish.pca df logLik AICc delta weight 3.138 NA NA -0.049 NA -0.686 NA NA 4 -52.374 113.801 0.000 0.520 3.022 NA NA -0.044 NA -0.705 0.421 NA 5 -51.753 115.127 1.326 0.268 3.171 NA NA -0.050 NA -0.559 NA + 6 -50.628 115.590 1.789 0.212
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APPENDIX M: PCA plots of PC 1 scores on Hellinger-transformed crustacean zooplankton abundances in 44 lakes in Killarney Provincial Park sampled in 1972-73, 1990, 2000, 2005, and 2016
acid neutral recovered
a) b)
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e e 0.2
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Figure M.1. Principal component analysis axis 1 scores on zooplankton species abundance data from 44 lakes in Killarney Provincial Park, categorized by water quality improvements, between a) 1972-73 and 1990, b) 1990 and 2000, c) 2005 and 2000, and d) 2016 and 2005. The dashed line represents 1:1.
159