Aquatic Sciences (2018) 80:40
https://doi.org/10.1007/s00027-018-0591-2
Aquatic Sciences
RESEARCH ARTICLE
Breeding eider ducks strongly influence subarctic coastal pond
chemistry
Matthew P. Duda1
H. Grant Gilchrist3
· Kathryn E. Hargan2,5 · Neal Michelutti1 · Linda E. Kimpe2 · Nik Clyde3
· Mark L. Mallory4 · Jules M. Blais2 · John P. Smol1
·
Received: 17 April 2018 / Accepted: 13 August 2018
© Springer Nature Switzerland AG 2018
Abstract
Arctic freshwater ponds are typically pristine and oligotrophic, however seabird biovectors can markedly alter water quality
via enrichment with marine-derived nutrients and bioaccumulated metals. These ornithogenic inputs can be the dominant
factor structuring aquatic biota and the surrounding island flora. Here, we measured a suite of limnological water chemistry
variables and sediment geochemistry from 21 freshwater ponds influenced by Common Eiders (Somateria mollissima) in
Hudson Strait, near the northern communities of Cape Dorset (Nunavut) and Ivujivik (Quebec). Nest counts and sedimentary δ15N values were used as proxies of bird abundance. Nutrient-rich guano from the nesting eiders visibly promoted the
growth of catchment vegetation. Elevated metal (Al, Cd, Zn), metalloid (Se), and nutrient concentrations (N, P) in the water
of eider-affected sites were recorded (Sign test; p = 0.004), but the proximity of many sites to the coast meant that variables related to ocean spray (conductivity, Na+, Mg2+, Cl−, Sr) confounded the effects of birds on pond water chemistry. In
contrast, sediment geochemistry appeared to more clearly characterize sites according to the level of eider activity in their
catchments by tracking Pb, Cd, N, and P sedimentary concentrations (Sign test; p = 0.02). These results have direct implications for reconstructing historical eider population trends using sediment archives, which is necessary to inform effective
conservation management strategies.
Keywords Ornitholimnology · Biovector · Common Eider · Arctic · Nutrients · Metals
Introduction
Electronic supplementary material The online version of this
article (https://doi.org/10.1007/s00027-018-0591-2) contains
supplementary material, which is available to authorized users.
* Matthew P. Duda
mattpduda@gmail.com
1
Paleoecological Environmental Assessment and Research
Lab (PEARL), Department of Biology, Queen’s University,
Kingston, ON K7L 3N6, Canada
2
Department of Biology, University of Ottawa, 30 Marie
Currie Pvt., Ottawa, ON K1N 6N5, Canada
3
Wildlife Research Division, Science and Technology
Branch, Environment and Climate Change Canada, Ottawa,
ON K1S 5B6, Canada
4
Department of Biology, Acadia University, 33 Westwood
Ave., Wolfville, NS B4P 2R6, Canada
5
Present Address: Keck Sciences Department, Claremont
McKenna College, 925 N. Mills Ave., Claremont, CA 91711,
USA
The study of Arctic lakes and ponds is logistically challenging, yet limnological research at high latitudes remains
active primarily due to the sensitivity of Arctic freshwaters
to global change (Smol and Douglas 2007; Rühland et al.
2008; Kaufman 2009; Smol 2016). One emerging field of
study, ornitholimnology (Hurlbert and Chang 1983), investigates the influence of bird colonies on freshwater systems.
Seabirds are potent biovectors, meaning they are capable of
transporting and focusing nutrients (and contaminants) from
their marine feeding grounds to their terrestrial nesting sites
largely via their nutrient-rich feces and other deposits, eggshells and carcasses (Bildstein et al. 1992; Blais et al. 2007).
In naturally oligotrophic Arctic regions, the nutrients and
contaminants transported by biovectors greatly modifies the
recipient terrestrial and aquatic ecosystems. For example,
Blais et al. (2005) describe a 25-fold enrichment of total Hg
and a 60-fold enrichment dichlorodiphenyltrichloroethane
(DDT) to the environment derived from a Northern Fulmar
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M. P. Duda et al.
Page 2 of 16
(Fulmarus glacialis) colony in Cape Vera, Nunavut. Seabirds are one of the most prolific biovectors on the planet,
with breeding seabirds producing and concentrating an estimated global excrement input onto land of 591 Gg N/y and
99 Gg P/y (Otero et al. 2018) and a total global input from
all seabirds of 3800 Gg N/y and 631 Gg P/y (Otero et al.
2018). The total seabird input of N and P is comparable
to estimates of the total nutrient input inland from the sea
via global fisheries (N = 3700 Gg/y, Maranger et al. 2008,
P = 320 Gg/y; Mackenzie et al. 1993). The effect of N and
P loading cannot be understated as avian guano is a driving
factor in shaping many biological communities, including
floral (Zwolicki et al. 2013; Otero et al. 2015) and faunal
(Sánchez-Piñero and Polis 2000; Zhu et al. 2015) assemblages. Because seabirds markedly alter the nutrient composition of the water chemistry and sediment geochemistry
of their environment (Evenset et al. 2004; Blais et al. 2005;
Keatley et al. 2009), paleolimnology can be used to infer
population presence (Stewart et al. 2015), trends (Luoto
et al. 2014), and dynamics through time (Keatley et al.
2011). By determining the historical population dynamics
of a species, more effective conservation strategies can be
implemented to sustain extant populations.
Common Eiders (Somateria mollissima) are the largest
duck in the Northern Hemisphere, inhabiting coastal marine
Arctic and subarctic environments (Goudie et al. 2000).
Most Common Eiders in the Arctic are migratory, although
some may reside year-round and principally feed on molluscs and crustaceans (Goudie et al. 2000). Eiders nest in
colonies, reusing previously built nests (Goudie et al. 2000).
Once eggs are laid, female eiders spend > 99% of their time
on the nest (Mallory et al. 2015), presumably to provide
warmth and to prevent egg predation. However, eiders must
drink freshwater, therefore it is advantageous to build nests
near inland ponds to minimize time away from the nest (Fast
2006). Due to their gregarious nature, as well as the proximity of their nests to freshwaters, Common Eiders are ideal
study organisms in ornitholimnological investigations.
Here, we focus on the Northern Common Eider (S. m.
borealis; hereafter eider), a subspecies that breeds along
the coastline of the eastern Canadian Archipelago and winters along southwest Greenland through Newfoundland and
Labrador (Mosbech et al. 2006; Steenweg et al. 2017). This
subspecies prefers to build its nests on small, exposed, lowlying flat islands with small amounts of cover (Schmutz
et al. 1983; Goudie et al. 2000). Many of these islands support small, freshwater ponds, which were the targets for
our investigation. However, given the proximity of marine
waters to the ponds and nest sites, we expected that ocean
spray variables (conductivity, major ions and Sr, a trace
metal highly associated with ocean spray) may confound
variables related to eider influence, therefore we determined
if other elements in the sediments more effectively track
13
eider presence. Annual eider inputs to the same islands and
nesting sites, including guano, eggshells, moulted feathers and carcasses, continually fertilize the soil around their
nests with nutrients and potentially metals and other contaminants, which inadvertently also fertilizes the nearby
pond catchment, water, and sediments (Mallory et al. 2006;
Brimble et al. 2009a; Keatley et al. 2009; Mallory 2015;
Clyde 2016).
To quantify the influence of eider presence on the subarctic islands, we measured limnological water chemistry and
sediment geochemistry of 21 ponds on islands in Hudson
Strait influenced to varying degrees by eiders. The amount
of eider activity in the catchments was estimated by direct
counts of the active nests on each island and by using stable
isotopes of nitrogen (δ15N) in surface sediments, a wellestablished proxy for tracking marine nutrients in freshwaters (Minagawa and Wada 1984; Kelly 2000; Michelutti
et al. 2009). Additionally, the guano of eiders was analyzed
to determine the direct elemental inputs and isotopic signature. Principal component analysis (PCA) was used to
graphically visualize the main patterns of variation in the
study sites in relation to the water chemistry variables and
sediment geochemistry. We hypothesized that eiders act as
biovectors and ecological engineers (like dovekies Alle alle,
González-Bergonzoni et al. 2017) and that their breeding
activity alters the terrestrial and freshwater habitats. Consequently, we predicted that ornithogenic markers (e.g., δ15N,
Pb, Zn, P) would be enriched in water and/or sediment samples of the high influence ponds compared to low influence
sites. This study is the first ornitholimnological investigation
in the remote Hudson Strait region and has direct implications towards reconstructing long-term eider population
dynamics using sediment records from the ponds.
Study area and site selection
Cape Dorset (Nunavut, Canada) and Ivujivik (Quebec, Canada) are remote communities in the westerly arm of Hudson
Strait (Fig. 1). Both areas have several nearby small uninhabited islands on which eiders nest. The two study regions
exhibit similar geography and topography, both categorized
as the Meta Incognita ecoregion (Sanborn-Barrie et al. 2008).
The area is characterized by continuous permafrost and rugged bedrock, with minor amounts of colluvial soils (3vGeomatics Inc. 2011). Natural vegetation is dwarfed due to high
winds, frigid temperatures and poor soils (Ricketts et al. 1999).
Sampling locations were given unofficial names by the monitoring program at Environment Canada and Climate Change
(ECCC). Sites A036 to A136 were ponds near Cape Dorset,
and sites D003 to D022 were ponds near Ivujivik (Fig. 1).
Sampling locations were the main pond of each island, and
islands were selected on the basis of previous eider colony
Breeding eider ducks strongly influence subarctic coastal pond chemistry
Page 3 of 16
40
Fig. 1 Map showing the locations of the study ponds. Gull
and ocean spray reference ponds
are represented by black stars;
low influence ponds (active
nests ≤ 10; δ15N ≤ 6‰) are
represented by open circles;
moderate influence ponds
(δ15N < 10‰) are represented
by grey circles; high influence
ponds (δ15N > 10‰) are represented by black triangles
surveys, attempting to encompass a range of eider abundance
(Clyde 2016). Site D018 was a nearly abandoned eider colony
with few remaining eiders, taken over by a large number of
gulls, outnumbering the number of eider nests of the other
sampled islands. Large Arctic gulls occupy high trophic levels and are opportunistic feeders that consume a variety of
foods, including fish, eggs and carrion (Mallory and Braune
2012). Since site D018 had a larger population of the gulls
than eiders (which occupy lower trophic levels), site D018
was expected to have higher concentrations of metals (Portnoy
1990; Michelutti et al. 2009). Site D019 was particularly close
to the ocean and received large amounts of ocean spray, and
therefore was expected to have higher levels of aqueous marine
ions, such as Na+, Mg2+, Cl−, as well as Sr compared to the
study sites located farther inland (Côté et al. 2010; ChaguéGoff 2010; Hargan et al. 2017). Certain physical characteristics of the sample islands were measured post-hoc, including
surface area using Google Earth ©2018 and distance to shore,
which was measured from the centre of the pond to the nearest
shoreline, accurate to 10 m (Government of Canada 2016).
Materials and methods
Sample collection
Ivujivik surface sediments and water chemistry samples
were collected from nine island ponds between July 25–30,
2014, and Cape Dorset samples were collected from 12
island ponds between July 17–25, 2015. Approximately 1 L
of surface water (< 1 m depth) and a single sediment core
were collected from each pond, and sampling occurred once
per pond. For metal analysis, approximately 300 mL of water
was filtered using Sartorius© 47 mm polycarbonate filters
with 0.4 µm pore size and kept in the dark at 4 °C until
analysis. For chlorophyll-a determination, 47 mm Whatman© glass microfibre filters were pre-ashed at 450 °C for
12 h, then 500 mL of water was filtered. The filters were
transferred to Petri dishes, wrapped in aluminum foil, and
then stored frozen in the dark until sent to National Laboratory for Environmental Testing (NLET; Burlington, ON).
Upon return to the lab, the water filtered for metal analysis
was acidified to a pH < 2 and all water samples were sent
to NLET to be analyzed for major ions, nutrients, and trace
metals using standard procedures (Environment Canada
Manual of Analytical Methods 1994a, b). Specific conductivity and pH measurements were taken on-site using a
calibrated YSI meter (Xylem, USA), and Hanna® handheld
pH meter (USA), respectively. Temperature and pH were
not collected in 2015 due to meter malfunction and therefore omitted from analyses (see Supplementary Table S1).
Concurrently, sediment cores were retrieved using a highresolution push corer (Glew and Smol 2016) and sectioned
onsite at 0.5 cm intervals using a Glew (1989) extruder. Only
the surface 0.5 cm interval, representing the most recent
conditions, was used in sedimentary geochemistry and δ15N
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40
M. P. Duda et al.
Page 4 of 16
analyses. Eider guano samples were collected from eiders
that defecated while being handled by ornithologists and
analyzed independently.
Elemental analysis
Samples were prepared following standard methodologies
(SGS Canada Inc. 2014). Briefly, freeze-dried sediment and
guano samples from two eiders were pulverized in an agate
bowl and then subjected to an aqua regia digestion to extract
the environmentally relevant metals while preserving the
silicate matrix. Inductively coupled plasma mass spectrometry was used to analyze 30 elements of the sediment and
guano: Al, As, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Li,
Mg, Mn, Mo, Na, Ni, P, Pb, Sb, Se, Sn, Sr, Ti, Tl, U, V, Y,
and Zn. Quality assurance and control were ensured by running certified reference material, internal standards, blanks,
and duplicates after every batch of 20 samples. Analyses
were carried out by SGS Canada in Lakefield, Ontario, with
results certified by the Canadian Association for Laboratory
Accreditation Inc. (CALA).
δ15N stable isotopes
Nitrogen elemental and isotopic analyses of all samples were
performed at the G.G. Hatch Stable Isotope Laboratory at
the University of Ottawa, Ottawa, ON. For elemental %N
analysis, sediment samples and standards were analyzed
using a Vario EL III Elemental Analyzer (Elementar, Germany) following methods described in Brazeau et al. (2013).
Sediment amounts needed for the δ15N isotopic analyses
were determined based on the results of the elemental analysis and weighed accordingly into tin capsules with two parts
tungsten trioxide (WO3). The isotopic composition of nitrogen was determined by the analysis of N2, produced by combustion on a Vario EL III Elemental Analyzer (Elementar,
Germany) followed by “trap and purge” separation and online analysis by continuous-flow with a DeltaPlus XP Plus
Advantage Isotope Ratio Mass Spectrometer coupled with a
ConFlo II (Thermo, Germany). Our δ15N data were reported
using delta (δ) notation in parts per thousand (‰) enrichments or depletions relative to common standards. Isotope
data were normalized using previously calibrated internal
standards, and analytical precision was ± 0.2% (Pella 1990).
Quantifying eider influence
To evaluate the influence of eiders on each pond, we used
the number of occupied nests on the island, as well as δ15N
values from the surface sediments of each site. Prior to fieldwork, the number of nests on each island were determined
from unpublished field surveys conducted by ECCC and
were used to approximate the number of eiders inhabiting
13
the island (Clyde 2016). Due to the inconsistency of survey
years, ranging from 1997 to 2012, the possibility of eiders
abandoning their nests between years, and the opportunity of
migratory birds utilizing the islands as stopovers, sedimentary δ15N was used in conjunction with nest counts. Sedimentary δ15N has been shown repeatedly to be elevated in
soils and sediments receiving marine-derived nitrogen, and
a faithful indicator of seabird inputs (Mizutani et al. 1986;
Blais et al. 2005; Brimble et al. 2009a). δ15N is enriched
by approximately 3.4‰ per trophic level (Minagawa and
Wada 1984), and therefore molluscivorous eiders introduce
elevated levels of δ15N via their guano to the otherwise low
δ15N freshwater environment (Michelutti et al. 2010). Further, due to biological processes, ocean water has a higher
natural abundance of δ15N than terrigenous or freshwater
habitats (Montoya 2007), therefore ocean spray will elevate
pond δ15N.
Based on the above qualifiers of active nest counts and
δ15N, sites were divided into five categories: low, moderate
and high influence, gull reference and ocean spray reference.
Low influence sites had few active nests (≤ 10 per island)
and low δ15N (≤ 6‰). All other sites were split into moderate or high influence ponds, dependant on whether they
were higher or lower than δ15N = 10‰, the average level
of eider guano (Clyde 2016). Based on this categorization,
increasing number of nests was generally related to increasing δ15N. The main exception was A038 that was categorized as high influence (active eider nests = 7, δ15N = 12.3),
which may have elevated δ15N due to migratory gull and/
or goose populations, evidenced by droppings around the
catchment of the pond. This highlights the importance of
using an independent ornithological measurement, such as
δ15N, to confirm nest or bird counts. As explained earlier,
the gull and ocean spray reference sites, D018 and D019,
were determined to qualify the effects of ornithological and
ocean spray influence.
Statistical techniques
Principal component analysis (PCA) was used to summarize the relationship of study sites to measured environmental variables. Water chemistry variables that had
> 10% below the detection limit (DL) were removed.
Otherwise, if < 10% of measured variables fell below
DL, they were approximated using DL of variable/square
root(2) (Hornung and Reed 1990). Variables that were
right skewed were normalized with a log(x + 1) transformation. Parameters were then tested for normality with
a Shapiro–Wilk test (α = 0.05) (Shapiro and Wilk 1965),
and nonparametric variables were eliminated. Redundant
variables were identified with a Pearson correlation matrix
(p ≤ 0.05) with Bonferroni-adjusted probabilities using
SPSS (see Supplementary Tables S2, S3) (IBM SPSS
Breeding eider ducks strongly influence subarctic coastal pond chemistry
Statistics for Windows, Version 19, 2010). A PCA of the
correlated variables was used to determine a single variable that explained the largest amount of variation along
the primary axis to represent the group. All ordination
analyses were performed in Canoco, version 5.0 (ter Braak
and Šmilauer 2012). A sign test is a nonparametric analysis that was used to determine if ornithological tracers (i.e.
Al, As, Cd, Pb, Se, Zn, P, TN-F) were elevated in high
influence ponds compared to low influence ponds. This
test is well suited for small datasets to determine if the
difference in medians is zero (Conover 1999).
Page 5 of 16
40
Statistical limitations
There were statistical limitations in this study due to the
difficulty of locating and sampling islands with ponds with
varying degrees of eider presence. This, compounded with
finding sites that had similar geology and pond morphology,
resulted in a limited sample size of 21 ponds, with a narrow
range of eider populations. For this reason, there were too
few samples to normalize several variables for PCA. However, of the removed variables, Cl−, K+, Mg2+, Na+ are all
major ions correlated to conductivity, which was represented
on the water PCA. Additionally, the removed ornithogenic
markers (As, Cd, TP-UF) were represented by other bird
influence markers, including Pb and chlorophyll-a.
Data treatment
Water chemistry ordination
Results and discussion
Arsenic, Cd, Cl −, K +, Mg 2+, Na + and total phosphorus
unfiltered (TP-UF) were eliminated from the ordinal analysis due to skewness from a normal unimodal distribution.
Other than dissolved inorganic carbon (DIC), Cu and Pb,
all variables were normalized with a log(x + 1) transformation. Conductivity, major ions (Ca2+, SO42−) and Sr were
correlated (see Supplementary Table S2) and represented
by conductivity, which explained the largest amount of
variation. Calcium and SO42− are major ions that contribute to conductivity, and Sr is a trace metal highly associated with ocean spray (Chen et al. 1997; Wang and Zhai
2008; Chagué-Goff 2010). To constrict ordination results
to reflect only the distribution of eider sites relative to
water chemistry and sediment geochemistry, the gull and
ocean spray reference ponds, D018 and D019, were plotted passively.
Guano and physical characteristics
Sediment geochemistry ordination
Six sedimentary variables (As, Bi, Li, Sb, Se, Sn) were
removed due to a large amount of below detection values.
All variables other than Cd and Pb were normalized with
a log(x + 1) transformation, however Be, Ca2+, Mg2+, Mo,
Na+, Th and U were eliminated from further analysis due
to skewness. Trace metals, including Al, Ba, Co, Cr, Cu,
Fe, Ni, Ti and V, were all correlated (see Supplementary
Table S3), and therefore grouped using Al, which explained
the largest amount of variation. Similarly, Cd and Zn were
also correlated due to their binary relationship (Tang et al.
2014) and represented by Zn. Zinc has stable geochemistry
in sediments (Boyle 2001) and has been correlated with seabird inputs (Brimble et al. 2009b; Foster et al. 2011). Similar
to the water ordination, the gull and ocean spray reference
ponds, D018 and D019, were plotted passively.
Given the proximity of the study ponds to each other and
their similar morphometries (Table 1), variability related
to site-specific differences such as geology, climate, and
atmospheric deposition was minimal. Thus, the main factor
influencing pond chemistries was presumed to be the varying abundances of eiders at each site. As has been shown
previously, seabird guano fertilizes and modifies freshwater
ponds and their catchments (Mallory et al. 2006; Brimble
et al. 2009a; Côté et al. 2010). Guano is high in P, constituting 0.9–17% of excrement total mass (Otero et al. 2015).
The guano samples analyzed from two eiders had P concentrations of 980 ± 170 µg/g (Table 2), which likely fertilized
the catchment because sites that had high eider abundance
also had visibly more catchment vegetation compared to
the catchments of unaffected sites, which were bare rock
(Fig. 2). Eiders prefer to build their nests in vegetation, using
plant material and their down feathers to insulate their eggs
and avoid harsh conditions (Goudie et al. 2000). This likely
forms a mutualistic feedback loop, in which eiders return
to vegetated areas, which they ultimately fertilized, and
continue to support plant material via nutrient-rich waste
products.
Ornithogenic elements analyzed in the guano, including
Al, Cd, Pb and Se, were more elevated in the water and
sediment chemistry of high influence ponds relative to low
influence ponds (Tables 3, 4), emphasizing the pronounced
ornitholimnological effect of eiders. Eiders bioaccumulate
trace metals due to their preference to feed on molluscs
and benthic crustaceans, which are typically enriched in
Al, Cd, Pb and Zn (Szefer et al. 2006) or their propensity
to acquire Pb from hunting activities (Hicklin and Barrow
2004; Falk et al. 2006; Johansen et al. 2006). In eiders, elements bioaccumulate due to persistence and their inability
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M. P. Duda et al.
Page 6 of 16
Table 1 Locations and physical variables of the 21-pond set, as well as the number of active Common Eider nests on each island in the most
recent survey year, with corresponding surface sedimentary δ15N
Pond
Official island name
Latitude (N)
Longitude (W)
Gull ref.
Ocean
spray ref.
Low
D018
D019
N/A
N/A
62°19′50″
62°20′17″
78°09′16″
78°09′30″
70
30
0.027
0.034
21 (2012)
11 (2012)
23.0
10.6
A036
D007
A045
A054
A056
A114
D003
D004
D012
D022
A038
A044
A083
A085
A108
A135
A136
D013
D016
Neta Islands
North Skerries
Tunitjuak Island
Putaguk Island
Qasigijjat
Salunnaqtuuq
North Skerries
North Skerries
South Skerries
North Skerries
Neta Islands
Simikutak
Tatsiumajukallak
Inugiavvik
Qalirusilik
Qujjautaq
N/A
South Skerries
Île Pikiulik
64°15′12″
62°26′43″
64°17′08″
64°19′04″
64°16′59″
64°16′06″
62°25′52″
62°26′37″
62°23′01″
62°26′37″
64°14′51″
64°17′52″
64°19′20″
64°17′32″
64°20′23″
64°03′44″
64°05′07″
62°22′56″
62°19′20″
76°18′21″
78°08′08″
75°46′56″
75°45′17″
75°44′25″
74°11′20″
78°10′17″
78°09′02″
78°11′06″
78°09′02″
76°13′45″
75°47′14″
74°40′01″
74°38′56″
74°22′33″
73°31′56″
73°30′44″
78°11′32″
78°10′33″
250
50
110
100
190
170
130
110
70
110
50
80
60
180
130
170
60
50
60
0.54
0.040
1.2
0.096
0.28
0.39
0.24
0.19
0.11
0.068
0.010
0.078
0.037
0.17
0.15
0.25
0.12
0.058
0.054
10 (1997)
8 (2012)
15 (2012)
243 (2012)
434 (2012)
197 (2012)
228 (2012)
212 (2012)
230 (2012)
101 (2012)
7 (2011)
141 (2012)
259 (2010)
225 (2010)
234 (2010)
127 (2012)
444 (2012)
74 (2012)
367 (2012)
5.42
3.08
7.14
8.65
6.30
9.64
7.72
7.68
9.04
9.82
12.3
12.2
11.6
11.6
12.2
10.4
13.6
10.6
10.3
Mod.
High
Table 2 Concentration and
standard deviation (SD) of
relevant elements in Common
Eider (n = 2) guano
Element
Concentration (µg/g
dry weight ± SD)
As
Ca
Cd
Cu
P
Pb
Se
Sr
Zn
2.15 ± 1.20
175 ± 7
0.17 ± 0.021
5.15 ± 0.49
980 ± 170
1.05 ± 0.07
1.35 ± 0.071
770 ± 85
11.5 ± 0.7
to biodegrade (Cardwell et al. 2013). The elevated elements
are released back to the ecosystem through guano, eggshells
and carcasses.
Pond water chemistry
Elevated major ions and ornithogenic elements were
recorded in the water of the eider-affected sites. In our
21-pond dataset, the gull colony reference pond, D018,
had the highest measured metals of ornithogenic influence,
13
Distance to
shore (m)
Island surface
area (km2)
δ15N (‰)
Influence
Nests (year)
as also described by Brimble et al. (2009b), including: As
(8.45 µg/L), Cd (0.199 µg/L), Se (1.6 µg/L) and Zn (17 µg/L)
(Table 3). Additionally, D018 had the highest concentrations of variables linked to eutrophication, and thus eider
and/or gull influence, including: chlorophyll-a (429 µg/L),
TP-F (3800 µg/L) and TP-UF (7100 µg/L) (Table 3). In
our dataset, the ocean spray reference pond, D019, had the
highest concentrations of major ions including: conductivity (13,000 µS/cm), Ca2+ (133 mg/L), K+ (116 mg/L),
Mg2+ (357 mg/L), Na+ (3350 mg/L) and SO42− (862 mg/L)
(Table 3). Moreover, D019 had the highest Sr (3180 µg/L),
which is strongly associated with ocean spray (Chen et al.
1997; Wang and Zhai 2008; Chagué-Goff 2010).
The ornithogenic bioaccumulated elements were elevated in the water of the high eider-influence ponds compared to low influence ponds. Examples of such metals
and metalloids include Al (low influence 28.2 ± 11.8 µg/L,
high influence 93.8 ± 70.7 µg/L), Cd (low influence
0.031 ± 0.031 µg/L, high influence 0.047 ± 0.032 µg/L),
Se (low influence 0.19 ± 0.16 µg/L, high influence
0.23 ± 0.19 µg/L) and Zn (low influence 1.7 ± 0.57 µg/L,
high influence 2.7 ± 1.1 µg/L). Though comparisons of
individual elements were not statistically significant due to
a limited sample size, mean values of all eight identified
Breeding eider ducks strongly influence subarctic coastal pond chemistry
Page 7 of 16
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Fig. 2 On the left is an image of a low-influence pond, A036, with minimal vegetation, and on the right, is a high-influence pond, D016, with
lush vegetation
ornithogenic tracers (Al, As, Cd, Pb, Se, Zn, P, TN-F; Mallory et al. 2004; Michelutti et al. 2010) were greater in the
waters of the moderate and high influence ponds compared
to low influence (Sign test; p = 0.004). Some of these elements were highlighted by Brimble et al. (2009b) as ornithogenic metals of concern, and potentially toxic. However,
at the time of measurement, the elements were below the
chronic level of concern in freshwater as per the Water
Quality Guidelines for the Protection of Aquatic Life set
by the Canadian Council of Ministers of the Environment
(CCME 1999) (Cd 0.09 µg/L; Se 1 µg/L; Zn 30 µg/L). Further, these metals are considered guano-derived, and would
not normally be elevated in pristine, unaffected ponds (Roberts et al. 2017), additionally supporting the marked influence of eiders on their environment.
Similar to metals, nutrients were elevated in eider-affected
sites relative to control ponds (Table 3). As expected, measured phosphorus in the water was high, similar to other
Arctic seabird studies (e.g. Keatley et al. 2009; Côté et al.
2010). In a 2001 study of nutrients in the Canadian Arctic Archipelago, the mean TP-UF of unimpacted lakes was
12 ± 18 µg/L (Hamilton et al. 2001). Although the low influence ponds had a mean TP-UF of 102 ± 1.4 µg/L, the high
influence sites recorded a mean value four times greater at
416 ± 408 µg/L. The elevated P concentration in the low
influence sites indicates that there is likely an additional
source of phosphorus. Although the control sites currently
do not have a large eider population, it is possible that seasonal migratory geese or gull populations land at the islands
for short stopovers, evidenced by geese droppings across the
islands. Geese are known to release a substantial amount of
P in the Arctic via their feces (Mariash et al. 2018), from
which the detectable reintroduction can last several decades
(Søndergaard et al. 2003). Additionally, high δ15N sites with
few eider nests (e.g. A038) support the possibility of transient bird populations.
Total filtered nitrogen (TN-F) was also measured to
determine the amount of organic N in the water, which
has been shown to increase due to biovectors (Marion et al. 1994; Zwolicki et al. 2013). We measured a
TN-F of 1.61 ± 1.06 mg/L in the low influence ponds
and 3.98 ± 7.52 mg/L in high influence ponds (Table 3).
Nitrogen, along with P, is associated with the growth and
abundance of algal communities (Smith 1982) and can
be linked to elevated chlorophyll-a concentrations in the
eider ponds (low influence 19.3 ± 1.13 µg/L; high influence
22.0 ± 25.8 µg/L). The elevated TN-F in the eider affected
ponds further highlights the ability of eiders to shape their
environment.
In the Arctic, it is difficult to find control ponds with no
bird influence because suitable habitat is limited, therefore
every island is likely occupied and influenced by some bird
presence during either migration or breeding seasons. Even
sites with few active eider nests (e.g. A036, A038, D007)
had higher P and δ15N than would be expected if there were
no birds present (Brimble et al. 2009a). This highlights the
importance of independent proxies, such as δ15N, to corroborate nest or bird counts. Without controls, biogenic
enrichment factors (Brimble et al. 2009b) to quantify the
enrichment of affected sites due to guano subsidies were not
developed. This limitation made comparisons between high
and low influence sites statistically imperfect.
The PCA axes 1 and 2 explained 48.4% of the total variation with eigenvalues of λ1 = 0.294, and λ2 = 0.190 (Fig. 3).
Axis 1 was strongly characterized by a Pb and dissolved
organic carbon (DOC) gradient, which we consider to track
the influence of eiders. As seen in other studies, eiders commonly have elevated Pb in their liver (Mallory et al. 2004),
13
40
Lake
CHL-a
(µg/L)
DIC (mg/L) DOC
(mg/L)
TN (mg/L)
TP-F
(µg/L)
TP-UF
(µg/L)
Cond. (µS/
cm)
Ca2+
(mg/L)
K+ (mg/L)
Mg2+
(mg/L)
Na+ (mg/L) SO42−
(mg/L)
Gull ref.
Ocean
spray
ref.
Low
D018
D019
429
8.00
14.8
10.1
47.1
14.2
7.90
1.17
3800
30
7100
93.0
1066
13,000
14.0
133
16.7
116
13.0
357
177
3350
52.5
862
A036
D007
Mean ± SD
Moderate A045
A054
A056
A114
D003
D004
D012
D022
Mean ± SD
High
A038
A044
A083
A085
A108
A135
A136
D013
D016
Mean ± SD
18.5
20.1
19.3 ± 1.13
6.00
0.100
0.100
4.20
128
25.3
166
3.50
41.7 ± 66.3
10.6
76.5
47.9
3.60
3.10
33.8
14.2
7.20
1.20
22.0 ± 25.8
8.60
10.2
9.40 ± 1.10
10.7
20.8
14.3
4.00
3.50
12.0
18.0
20.6
12.9 ± 6.80
13.3
4.90
8.20
9.30
9.90
9.20
9.60
10.6
26.6
11.3 ± 6.10
10.2
19.8
15.0 ± 6.8
11.9
15.4
8.80
14.0
18.8
20.8
35.6
16.3
17.7 ± 8.20
10.7
14.6
7.40
17.9
13.5
14.8
14.7
21.6
40.2
17.3 ± 9.50
0.867
2.36
1.61 ± 1.06
2.64
1.54
0.865
0.817
1.04
1.71
3.61
1.89
1.76 ± 0.962
1.69
1.04
0.838
1.46
1.39
1.38
1.44
2.57
24.0
3.98 ± 7.52
65
34
50 ± 22
38
79
47
180
41
66
88
170
89 ± 57
350
69
40
510
230
71
49
52
1300
290 ± 401
101
103
102 ± 1.40
75.0
102
65.0
230
249
549
1260
283
352 ± 399
397
294
130
594
308
304
161
126
1430
416 ± 408
172
5000
2590 ± 3410
292
438
324
75.0
325
650
1270
346
465 ± 363
342
112
1490
157
332
117
198
414
750
435 ± 445
8.95
46.0
28.0 ± 26.0
13.6
40.1
19.9
2.12
7.35
20.4
42.8
24.8
21.4 ± 14.4
12.5
5.33
17.7
12.1
9.21
10.1
12.1
27.2
32.0
15.4 ± 8.80
2.14
39.1
20.6 ± 26.1
2.70
3.37
4.16
0.53
2.09
4.96
9.83
2.47
3.76 ± 2.79
2.21
1.67
9.08
0.94
2.50
0.51
0.84
3.66
5.80
3.02 ± 2.81
2.36
112
57.2 ± 77.5
4.44
5.46
4.54
1.31
4.34
7.59
19.8
5.95
6.68 ± 5.59
6.04
1.62
25.0
2.18
5.64
1.70
3.70
6.34
8.85
6.79 ± 7.26
17.3
1060
539 ± 737
34.2
37.5
33.8
10.6
52.7
89.9
223
45.4
65.9 ± 67.3
43.2
12.2
209
16.8
43.6
12.0
17.5
60.3
85.9
55.6 ± 62.8
5.80
328
167 ± 228
17.0
40.5
17.5
2.60
16.2
31.0
44.3
13.4
22.8 ± 14.3
10.5
2.20
54.6
3.70
13.4
4.00
12.9
21.9
31.3
17.2 ± 16.9
Influence
Lake
Al (µg/L)
As (µg/L)
Cd (µg/L)
Cr (µg/L)
Cu (µg/L)
Fe (µg/L)
Pb (µg/L)
Se (µg/L)
SiO2
(mg/L)
Sr (µg/L)
V (µg/L)
Zn (µg/L)
Gull ref.
Ocean
spray
ref.
Low
D018
D019
52.3
28.6
8.45
1.72
0.199
0.041
0.34
0.42
5.22
2.31
196
76.7
0.165
0.047
1.6
0.34
1.6
0.38
189
3180
3.3
2.0
17
1.7
0.24
2.02
1.13 ± 1.26
0.009
0.22
0.053
0.15
0.031 ± 0.031 0.19 ± 0.05
A036
36.5
D007
19.8
Mean ± SD 28.2 ± 11.8
9.34
91.3
6.32
114
7.83 ± 2.14 103 ± 16.1
0.171
0.07
0.39
27.5
0.68
0.083
0.30
0.72
833
1.3
0.127 ± 0.062 0.19 ± 0.16 0.56 ± 0.23 430.3 ± 570.0 0.99 ±
0.44
1.3
2.1
1.7 ± 0.57
M. P. Duda et al.
Influence
Page 8 of 16
13
Table 3 Water variables of the 21-pond set
Influence
Lake
Moderate A045
A054
A056
A114
D003
D004
D012
D022
Mean ± SD
A038
High
A044
A083
A085
A108
A135
A136
D013
D016
Mean ± SD
Al (µg/L)
As (µg/L)
Cd (µg/L)
Cr (µg/L)
Cu (µg/L)
Fe (µg/L)
Pb (µg/L)
Se (µg/L)
SiO2
(mg/L)
Sr (µg/L)
V (µg/L)
Zn (µg/L)
46.8
121
14.4
154
125
167
73.2
48.8
93.8 ± 55.6
22.1
148
56.8
103
93.4
249
27.3
49.6
94.7
93.8 ± 70.7
0.66
1.35
3.91
0.32
0.47
1.45
3.15
0.79
1.51 ± 1.32
0.79
0.36
0.71
0.62
0.88
0.78
0.44
1.02
4.34
1.10 ± 1.23
0.048
0.075
0.006
0.022
0.024
0.078
0.039
0.037
0.041 ± 0.025
0.049
0.123
0.046
0.021
0.050
0.032
0.011
0.038
0.056
0.047 ± 0.032
0.29
0.88
0.10
0.23
0.29
0.64
0.34
0.18
0.37 ± 0.26
0.10
0.36
0.18
0.25
0.44
0.19
0.47
0.35
0.31
0.29 ± 0.12
5.14
5.19
6.91
3.39
4.83
6.19
0.91
4.96
4.69 ± 1.84
1.25
6.25
3.64
1.52
12.4
2.75
5.33
2.79
3.53
4.38 ± 3.41
203
547
60.6
375
210
463
668
111
330 ± 218
271
90.2
154
257
363
295
1370
275
1130
467 ± 455
0.303
0.130
0.043
0.129
0.262
0.371
0.410
0.167
0.227 ± 0.130
0.467
0.140
0.129
0.195
0.402
0.201
0.026
0.601
0.263
0.269 ± 0.185
0.10
0.17
0.08
0.10
0.23
0.36
0.35
0.24
0.20 ± 0.11
0.14
0.20
0.16
0.16
0.20
0.10
0.10
0.38
0.62
0.23 ± 0.19
0.84
0.35
0.31
0.06
1.5
2.0
1.3
2.0
1.1 ± 0.77
0.81
0.91
0.05
0.02
1.7
0.53
0.14
0.13
2.2
0.72 ± 0.78
75.3
216
97.1
17.4
52.4
128
312
113
126 ± 95.2
89.9
40.6
229
87.5
82.1
78.1
75.5
171
215
119 ± 68
1.3
1.3
0.74
1.2
1.0
7.8
7.1
0.95
2.7 ± 2.9
0.71
1.1
0.88
1.3
1.8
2.1
0.57
6.2
9.8
2.7 ± 3.2
1.1
3.4
0.5
4.1
4.3
4.3
2.8
3.4
3.0 ± 1.5
1.6
5.2
3.0
1.9
3.1
2.6
1.5
2.1
3.1
2.7 ± 1.1
Breeding eider ducks strongly influence subarctic coastal pond chemistry
Table 3 (continued)
Chlorophyll-a is expressed as CHL-a; dissolved inorganic carbon is expressed as DIC; dissolved organic carbon is expressed as DOC; total nitrogen filtered is expressed as TN-F; total phosphorus is expressed as TP, and is either filtered, -F, or unfiltered, -UF; conductivity is expressed as Cond. Mean and standard deviation are calculated with the gull and ocean spray reference ponds
omitted
Page 9 of 16
40
13
40
Lake
Ca2+ (mg/g) K+ (mg/g) Mg2+ (mg/g) Na+ (mg/g) P (mg/g)
Al (µg/g)
As (µg/g) Ba (µg/g)
Be (µg/g)
Cd (µg/g)
Co (µg/g)
Cr (µg/g) Cu (µg/g)
Gull ref.
Ocean
spray
ref.
Low
D018
D019
56
34
6.7
2.7
6.3
4.7
16
14
16
0.98
1400
1800
6.9
0.9
37
37
0.03
0.03
0.86
0.09
2.8
3.2
7.2
16
10
5.7
A036
D007
Mean ± SD
A045
A054
A056
A114
D003
D004
D012
D022
Mean ± SD
A038
A044
A083
A085
A108
A135
A136
D013
D016
Mean ± SD
15
11
13 ± 2.8
8.5
16
16
8.3
29
16
14
60
21 ± 17
11
16
39
12
8
10
13
18
12
15 ± 9.3
3.8
11
7.4 ± 5.1
4.5
3.4
3.8
1.3
2.7
4.8
3.8
4.6
3.6 ± 1.2
5.2
2.1
1.5
3.1
2.9
2.0
2.9
5.4
2.0
3.0 ± 1.4
3.1
26
15 ± 16
3.8
3.3
4.6
2.2
4.4
5.9
3.0
5.7
4.1 ± 1.3
3.3
9.6
2.8
1.6
4.0
1.5
2.6
5.0
2.3
3.6 ± 2.5
2.6
98
51 ± 67
0.75
0.76
0.97
0.59
1.7
1.3
2.3
1.2
1.2 ± 0.57
2.9
0.61
1.6
0.37
1.2
0.29
2.0
2.3
0.96
1.4 ± 0.91
3.7
0.26
2.0 ± 2.4
5.6
4.3
3.0
2.7
2.4
4.2
4.8
4.7
4.0 ± 1.1
7.0
3.3
0.98
4.5
2.0
4.2
5.6
5.3
3.1
4.0 ± 1.9
1700
530
1100 ± 830
2600
2300
3500
3700
4000
3600
710
3100
2900 ± 110
1100
14,000
1900
690
2400
1100
2100
3300
1600
3100 ± 4200
< 0.5
3.0
1.7 ± 1.7
1.3
1.6
19
0.8
1.0
2.2
5.7
3.0
4.3 ± 6.1
0.8
< 0.5
< 0.5
0.7
< 0.5
2.0
1.6
2.7
2.8
1.3 ± 1.0
34
27
31 ± 4.9
78
150
400
62
45
94
18
89
120 ± 120
9.0
38
38
9.2
53
7.5
36
47
24
29 ± 17
0.05
< 0.02
0.03 ± 0.02
0.13
0.05
0.26
0.16
0.11
0.06
0.03
0.11
0.11 ± 0.07
0.04
0.40
0.05
0.03
0.03
0.04
0.15
0.09
< 0.02
0.09 ± 0.12
0.72
0.04
0.38 ± 0.48
0.66
2.5
1.5
4.1
2.2
1.0
1.6
1.4
1.9 ± 1.1
1.8
2.9
0.28
3.3
0.44
3.4
2.4
0.84
2.9
2.0 ± 1.2
2.3
1.4
1.9 ± 0.63
5.1
8.7
22
10
3.8
4.9
1.8
3.5
7.5 ± 6.5
0.90
13
2.2
1.4
5.3
1.7
4.6
3.2
3.7
4.0 ± 3.7
15
3.6
9.3 ± 8.1
26
21
80
25
17
22
12
18
28 ± 22
5.9
62
14
7.7
24
7.4
30
12
9.0
19 ± 18
240
4.4
120 ± 170
83
91
280
130
74
66
20
49
99 ± 80
13
100
6.1
25
46
45
180
16
45
53 ± 55
Influence
Lake
Fe (mg/g)
Li (µg/g)
Mo (µg/g)
Ni (µg/g)
Pb (µg/g) Se (µg/g)
Sr (µg/g)
Ti (µg/g)
Th (µg/g)
U (µg/g)
V (µg/g)
Y (µg/g)
Zn (µg/g)
Gull ref.
Ocean
spray
ref.
Low
D018
D019
5.9
17
3
4
0.4
0.8
7.2
5.9
1.4
0.88
3.2
0.7
310
190
270
400
0.02
0.05
0.42
0.25
12
48
2.3
5.9
81
20
3
5
4±1
2
0.3
1±1
13
5.3
9.2 ± 5.4
12
0.60
6.3 ± 8.1
1.4
< 0.7
0.95 ± 0.49
53
190
120 ± 97
180
150
170 ± 21
0.17
11
< 0.02
0.12
0.10 ± 0.11 5.6 ± 7.7
13
4.0
8.5 ± 6.4
4.1
0.54
2.3 ± 2.5
55
10
33 ± 32
Moderate
High
A036
4.7
D007
1.4
Mean ± SD 3.1 ± 2.3
M. P. Duda et al.
Influence
Page 10 of 16
13
Table 4 Sedimentary variables of the 21-pond set
Influence
Lake
Fe (mg/g)
Li (µg/g)
Mo (µg/g)
Ni (µg/g)
Pb (µg/g) Se (µg/g)
Sr (µg/g)
Ti (µg/g)
Th (µg/g)
U (µg/g)
V (µg/g)
Y (µg/g)
Zn (µg/g)
Moderate
A045
A054
A056
A114
D003
D004
D012
D022
Mean ± SD
A038
A044
A083
A085
A108
A135
A136
D013
D016
Mean ± SD
8.7
9.3
12
8.1
9
13
5.8
9.2
9.4 ± 2.2
4.3
17
8.7
3.1
16
2.5
31
13
4.3
11 ± 9.3
6
8
28
3
4
5
<2
6
7.8 ± 8.4
3
35
5
<2
4
<2
<2
4
<2
7 ± 11
0.8
0.3
1
1
0.3
0.3
< 0.1
0.3
0.5 ± 0.4
0.4
0.2
0.6
0.4
0.4
0.4
0.5
0.6
0.4
0.4 ± 0.1
40
86
250
56
54
15
8.2
13
65 ± 79
3.2
29
5.9
8.7
15
20
48
6
11
16 ± 14
12
2.4
10
16
12
5.1
5.0
4.1
8.3 ± 4.8
9.2
7.3
1.2
4
3.4
2.8
3.8
10
2.6
4.9 ± 3.1
49
93
170
160
150
84
90
230
130 ± 59
85
130
250
92
49
62
92
88
76
102 ± 60
480
320
1230
260
360
680
130
470
490 ± 340
180
840
360
64
630
93
150
550
300
350 ± 270
0.11
0.13
0.3
0.07
0.09
0.12
0.04
0.1
0.12 ± 0.08
0.05
0.11
0.07
0.04
0.09
< 0.02
0.07
0.08
0.05
0.06 ± 0.03
0.9
0.21
1.9
2.3
3.8
1.1
0.21
0.66
1.4 ± 1.2
1.0
0.53
0.35
0.39
0.61
3.0
0.60
0.73
0.39
0.84 ± 0.83
18
14
51
23
12
25
13
19
22 ± 13
6.0
105
16
4.0
33
5.0
19
31
13
26 ± 32
3
1.3
3.4
15
7.9
5.9
1.3
5.4
5.4 ± 4.5
1.5
4.7
7.2
1.2
5.1
2.5
4.8
6.0
1.7
3.9 ± 2.2
53
70
120
330
130
68
75
72
110 ± 91
62
140
26
120
44
120
130
70
150
96 ± 46
High
1.3
1.5
2.8
5.3
3.5
2.4
2.9
3.2
2.9 ± 1.3
1.3
2.1
< 0.7
2.3
< 0.7
< 0.7
2.5
2.4
3.2
1.8 ± 0.93
Breeding eider ducks strongly influence subarctic coastal pond chemistry
Table 4 (continued)
Mean and standard deviation are calculated with the gull colony, D018, and ocean spray pond, D019, omitted. Bismuth and Sb were below detection for all sites and therefore omitted
Page 11 of 16
40
13
40
M. P. Duda et al.
Page 12 of 16
which is attributed to shot birds that survive and ingested
lead shot leftover from hunting (Flint and Grand 1997;
Franson et al. 2000; Grand et al. 2002). Additionally, eiders
are molluscivorous, feeding on mussels and other benthic
crustaceans (Goudie et al. 2000). Since molluscs are filter
feeders, they concentrate Pb from the sediments (Szefer et al.
2006), which may be a minor contributor to Pb elevation in
eiders, despite the inability of Pb to biomagnify (Cardwell
et al. 2013) and evidence for biominification (Jenkins 1980).
As the Pb is not metabolized, it is eventually excreted into
the catchments of the study ponds (Michelutti et al. 2010).
In alkaline waters (pH > 7.5), like the water in this study,
Pb complexes to form the insoluble PbCO3, which is very
stable and persistent in sediments (Long and Angino 1977).
Dissolved organic carbon in water is largely related to vegetation (Neff and Hooper 2002), and thus aqueous DOC
would be largely allochthonous in origin. There are also
autochthonous sources of DOC via aquatic algal cell death
and senescence, grazing, viral lysis and extracellular release
(Bertilsson and Jones 2003). The study ponds had high productivity as evidenced by the elevated chlorophyll-a concentration compared to other Canadian Archipelago ponds
(mean = 0.55 µg/L; Hamilton et al. 2001). Therefore, DOC
in the highly influenced eider ponds will be elevated likely
due to allochthonous eider guano fertilization and enhanced
growth of mosses, as well as autotrophic algae. Importantly,
increased DOC may influence the aquatic biota composition by limiting primary production (Carpenter et al. 1998),
affecting both epilimnetic (Hanson et al. 2003) and hypolimnetic respiration (Houser et al. 2003) and increasing metal
Fig. 3 Principal components analysis (PCA) of the 21-pond set. On
the left is a PCA of water variables; on the right is a PCA of sedimentary variables. Gull and ocean spray reference ponds are represented by black stars; low influence ponds (active nests ≤ 10;
δ15N ≤ 6‰) are represented by open circles; moderate influence
13
toxicity (Evans et al. 2005). The secondary axis was characterized by a gradient of conductivity, which is explained
primarily by ocean spray. Ocean spray can strongly influence
the water chemistry of nearshore Arctic ponds (Rühland and
Smol 1998; Michelutti et al. 2002; Antoniades et al. 2003).
Sediment geochemistry
The sediment geochemistry of the study ponds also tracked
the effects of eiders. The gull pond reference site, D018,
had the highest measured P (16 mg/g) and As (6.9 µg/g),
both of which are elements associated with high bird influence (Bildstein et al. 1992; Brimble et al. 2009b). Ocean
spray variables that were elevated in the water chemistry
(Ca2+, Mg2+, Na+ and SO42−) were not increased in the
sedimentary geochemistry of the ocean spray reference
pond, D019. Most ions (Mg 2+, Na +, SO 42−) are likely
elevated in the sediment due to the underlying geology
as opposed to water chemistry and allochthonous sources
(Lent 1994), indicating that the effects of ocean spray on
tracking biovectors in water do not translate to the sediments. Calcium in sediments may be elevated from guano
and uneaten mussel shells (Öst and Kilpi 1998; Ebert et al.
2013). Potentially toxic trace metals and elements known
to bioaccumulate in seabirds (Braune et al. 1999; Brimble et al. 2009b) were elevated in high influence relative
to the low influence sites, including Al (low influence
110 ± 830 µg/g; high influence 3100 ± 4200 µg/g), Cd (low
influence 0.38 ± 0.48 µg/g; high influence 2.0 ± 1.2 µg/g),
Se (low inf luence 1.1 ± 0.49 µg/g; high inf luence
ponds (δ15N < 10‰) are represented by grey circles; high influence
ponds (δ15N > 10‰) are represented by black triangles. Dissolved
organic carbon is expressed as DOC; dissolved inorganic carbon is
expressed as DIC; chlorophyll-a is expressed as CHL-a
Breeding eider ducks strongly influence subarctic coastal pond chemistry
1.8 ± 0.93 µg/g), and Zn (low influence 33 ± 32 µg/g; high
influence 96 ± 46 µg/g) (Table 4). As with the water chemistry, these comparisons were not statistically significant
for each element due to low sample sizes. However mean
values of all ornithogenic tracers (Al, As, Cd, Pb, Se, Zn,
P) were higher in sediments of high and moderate influence
ponds relative to low influence ponds (Sign test; p = 0.02).
Additionally, many of these elements (As, Cd, Se, Zn, P)
are considered guano-derived and would not normally be
found elevated in the environment (Roberts et al. 2017).
As with the water chemistry, sedimentary metals were far
below the probable effect level of concern in sediment set
by the CCME (1999). Given that eiders occupy a relatively
low trophic level, feeding on filter-feeding molluscs, there
is minor metal accumulations compared to other Arctic
marine birds. Our results are consistent with earlier work
describing species-specific differences in the effect of
Arctic avian biovectors, dependent on their trophic position (Michelutti et al. 2010). Considering the increased
concentrations of ornithogenic tracers in high influence
sites compared to low influence sites, and the high metal
concentrations in the guano, we conclude that sediment
geochemistry is tracking the ornithogenic inputs.
Elemental phosphorus was also elevated in the sediment of the ponds highly affected by eiders (low influence
2.0 ± 2.4 mg/g; high influence 4.0 ± 1.9 mg/g). Phosphorus
in seabird guano constitutes 0.9–17% of total excrement
mass (Otero et al. 2015). Following this trend, we measured
high P in eider guano, which no doubt contributes to the
long-term eutrophication and fertilization of the island and
ponds (see Fig. 2).
Axes 1 and 2 of the PCA explained 51.6% of the total
variation with eigenvalues λ 1 = 0.311, and λ 2 = 0.205
(Fig. 3). The first axis was characterized by a combination
of eider influence (K+) and ocean spray (Sr). Potassium is
both bioenriched in sediments due to birds (Brimble et al.
2009a), as well as a major ion in ocean water. The secondary
axis showed a strong gradient of Sr, which is associated with
sea spray (Chen et al. 1997; Wang and Zhai 2008; ChaguéGoff 2010). Importantly, ornithogenic variables oriented
together, including δ15N, Pb, Zn and P (Fig. 3). This reflects
the elevated δ15N and metal concentrations typical of seabird
guano. As discussed above in “Pond water chemistry”, Pb
would be expected to be elevated due to hunting and in part
prey preference. Zinc is an essential element that has the
potential to be toxic in waterfowl (Beyer et al. 2004) and may
be elevated in eiders (Burger and Gochfeld 2008; Lovvorn
et al. 2013; Mallory et al. 2014). Zinc is a robust ornithogenic tracer due to its stability in sediments (Boyle 2001)
and strong independent correlation to seabird inputs (Brimble et al. 2009b; Foster et al. 2011). Finally, P, as described
above, was oriented with other ornithogenic variables. This
Page 13 of 16
40
is due to the high P concentrations in eider guano, washing
into the pond from the nest.
Conclusions
Our study characterized the water chemistry and sediment
geochemistry of 21 ponds influenced by eiders inhabiting
Hudson Strait and demonstrated a pronounced ornitholimnological influence of the eiders. Proxies of ornithogenic
influence, including Pb, bioaccumulated high-trophic metals
(Al, Cd, Zn), metalloid (Se), and nutrient concentrations (N,
P), were all higher in ponds with larger eider abundances
than ponds with few or no eiders, consistent with earlier
studies on the influence of various bird species on pond
chemistry (Brimble et al. 2009a, b; Michelutti et al. 2009;
González-Bergonzoni et al. 2017; Roberts et al. 2017). Consequently, these ornithogenic variables support the hypothesis that eiders act as ecological engineers and biovectors,
thus having the potential to structure the biota of the islands,
as was reflected in much greater chlorophyll-a levels. Also,
we determined that sediment geochemistry appears to better
record ornithogenic variables than water chemistry because
it tracks major ornithogenic proxies, including δ15N, Pb, Zn,
and P. Since sedimentary geochemistry appears to faithfully
track ornithogenic enrichment, this research provides additional evidence that downcore paleolimnological analyses
are key tools for garnering insights into the timing of seabird
arrival, colony growth and possible extirpation; information
critical for conservation management. These data are key
in understanding population and colony dynamics in areas
for which data are typically sparse or logistically difficult
to acquire.
Acknowledgements Thank you to Michael Janssen and Jake RussellMercier (Wildlife Research Division, ECCC) for logistical support.
Thank you to the Aiviq Hunters and Trappers Organizations’ and
Ivujivik Hunters and Trappers Association for their support in our
research. We especially thank Xiaowa Wang for her careful attention to
the water samples. This research was funded by Environment and Climate Change Canada, the W. Garfield Weston Foundation, the Natural
Sciences and Engineering Research Council of Canada (NSERC), the
Pew Charitable Trusts, the Nunavut General Monitoring Plan (NGMP),
and ArcticNet Network Centres of Excellence Canada. Finally, thank
you to two anonymous reviewers for their very helpful feedback and
comments.
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