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Ecological Archives M080-014-A1
Mari K. Reeves, Peter Jensen, Christine L. Dolph,
Marcel Holyoak, and Kimberly A. Trust. 2010.Multiple stressors and the cause of amphibian
abnormalities.Ecology 80:423440.
Appendix A. Supplemental methodological information for
contaminants sampling, data reduction, and the toxicity experiment.
Contaminants Sampling and Analysis
Two sediment samples were collected from each pond, one for
organic contaminant analysis and one for inorganic contaminant
analysis, using the methods of Csuros (1994). Samples were
homogenates pooled from three random locations in a pond. At each
location, we sampled the top 2030 cm of sediment. Shallow site
samples were collected with hand-held scoops stainless steel for
organics and plastic for inorganics. Deeper sites were sampled with
an Eckman dredge. Organic samples were homogenized in stainless
steel bowls. Inorganic samples were homogenized in Ziploc bags.
Prior to sampling each site, equipment was decontaminated by
washing with Alconox and water, rinsing with deionized water
followed by hexane and then acetone. Inorganic samples were
analyzed at the Trace Element Research Lab (TERL) in College
Station, Texas. Organic samples were analyzed at the Geochemical
and Environmental Research Group (GERG) in College Station,Texas. Sample results were compared to sediment toxicity
thresholds presented in the National Oceanic and Atmospheric
Administration, Screening Quick Reference Tables (Buchman
2008). Water samples were also collected from study ponds in 2004
and 2005 to sample for total inorganic elements using standard field
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collection protocols (Csuros 1994) and inductively coupled plasma/
mass spectrometry at TERL. Sample results were compared to water
quality criteria presented in the National Oceanic and Atmospheric
Administration, Screening Quick Reference Tables (Buchman
2008). The contaminants we measured (metals and chlorinated
organic pollutants) should remain relatively consistent through time,
with the exception of some of the lighter molecular weight aromatic
compounds.
Reducing the complexity of the contaminants data
After screening contaminants data for toxicants above at least one
established toxicity threshold, we used principal components
analyses (PCA) to reduce the dimensionality of contaminants data
separately for organic and inorganic contaminants. These groups
were kept separate because organic and inorganic compounds may
have different environmental sources, different environmental fate
and transport, and different modes of toxicity. If a contaminant was
not detected at a site, half the detection limit for that compound was
used as a substitute.
Inorganic contaminants exceeding at least one toxicity threshold in
water were aluminum, barium, cadmium, copper, iron and
manganese. Elements exceeding at least one threshold in sediment
included arsenic, cadmium, copper, iron, manganese, nickel, and
zinc. Cu was only detected in water from one site, and was therefore
excluded from the PCA. All elements in water and sediment arsenic
were log transformed to improve linearity prior to PCA. Theseelements were then subjected to PCA to result in the inorganic
vectors.
Organic contaminants exceeding at least one toxicity threshold
included phenanthrene (a polycyclic aromatic hydrocarbon or PAH),
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polychlorinated biphenyls (PCBs) and the following organochlorine
pesticides: aldrin, mirex, heptachlor-epoxide,
dichlorodiphenyltrichloroethane (p,p-DDT and metabolites),
lindane (BHC and metabolites), and chlordane (and metabolites
See Appendix B: Table B1 for metabolites detected). For the
pesticides, parent compounds and metabolites were summed prior to
PCA because they were correlated and because this made data
interpretation more straightforward.
For the metals, PCA vector 1 explained 33% of the variance and was
positively correlated (r0.5) with the following elements: Iron,
Manganese, and Nickel in sediment and Aluminum, Barium, Iron,and Manganese, in water. This vector was also negatively correlated
(r -0.5) with sediment Arsenic and Cadmium (for correlations, see
Table A1). PCA vector 2 explained 25% of the variance and was
positively correlated (r 0.5) with Copper, Iron, Nickel, and Zinc in
sediment. The third vector explained an additional 15% of the
variance, but was redundant with the first two vectors and was
therefore not retained for analysis. These PCA vectors were then
used to represent the metals with which they were correlated in theregression analysis.
The organic data required several manipulations before PCA. First,
one site was excluded from the organic PCA (and from all statistical
analyses) because the sample was taken during a forest fire and
concentrations of organic contaminants at this site were
approximately an order of magnitude higher than all other sites,
probably due to mobilization of these compounds by the fire anddeposition in ash (Site KNA60; See Appendix B; Table B3 for data).
Second, several organic contaminants representing a parent
compound (e.g., DDT) and its metabolites (e.g., DDD and DDE)
were quantified and reported separately by the analytical lab. We
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summed these chemicals (parent compounds and metabolites of
DDT, chlordane, and lindane) before the PCA because we believed
they would have similar environmental fate, transport, and relatively
similar toxicological effects. Additionally, this step eased data
interpretation. After these manipulations, we included the following
organic contaminants which were over at least one toxicity threshold
in at least one study site in the PCA: the PAH phenanthrene, total
PCBs, and the organochlorine pesticides aldrin, heptachlor-epoxide,
mirex, lindane (and metabolites benzene hexachloride or BHC),
chlordane (and metabolites), and DDT (and metabolites DDD and
DDE). We performed PCA on these untransformed variables. This
resulted in the four components presented in Table A2. The firstcomponent explained 38% of the variance and was positively
correlated (r0.5) with the following compounds: total PCBs, aldrin,
heptachlor-epoxide, mirex, and chlordane. The second vector
explained an additional 25% of the variance and was positively
correlated (r 0.5) with lindane and DDT and negatively correlated
(r -0.5) with total PCBs (Table A2). The third vector explained an
additional 12% of the variance, but was only correlated with
heptachlor-epoxide, which was also correlated with the first vector,and was therefore not retained for analysis. We therefore retained
the first two PCA vectors to represent organic contaminants in the
statistical analysis.
Site Sediment and Water Exposure Experiment
Sediments were collected from six sites in late April with hand-held
stainless-steel scoops or Eckman dredge. Sediment samples werecomposites of three locations in a pond, homogenized in stainless
steel buckets. Sampling equipment was decontaminated between
sites by washing with Alconox and water, rinsing with DI water,
then rinsing with hexane, then acetone, to remove organic
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contaminants and prevent cross-contamination between sites.
Sediments were sorted to remove predatory invertebrates. On 12
May 2006, we collected six amplecting pairs of wood frogs from
two breeding sites at which abnormalities have consistently been
found and allowed them to oviposit in glass bowls. After
oviposition, adults were released at their breeding sites and extra
eggs were returned to the egg mass cluster. We collected site water
twice per week with certified chemically-clean, 5-gallon cubitainers
(Hedwin Corporation, Baltimore, Maryland, USA). The same
cubitainer was used to collect water from each site at each water
change. Water was changed every 46 days to prevent tadpoles from
fouling the water. Old water was drained with site-dedicated siphonhoses, taking care to not harm the tadpole or disturb the sediment. It
was replaced with temperature-equilibrated site water collected
either that day or the day before. Water changes began after eggs
hatched. Once tadpoles were free-swimming (Gosner (1960) stage
20), they were fed NASCO frog brittle for tadpoleXenopus, ad
libitum at each water change. Four blocks, water baths with 24
bowls each, controlled the temperature of experimental units which
were kept indoors under full-spectrum lighting on a light cyclesimulating field conditions. Temperature was also set to mimic
surface temperatures recorded in the field.
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FIG. A1. Map of Kenai Study Sites (). Heavy black lines are
paved roads. Lighter black lines are gravel roads. Dark gray shading
is KNWR boundary. Light gray shading is designated wilderness.
TABLE A1. Correlations between Metals PCA vectors and elements
that exceeded toxic thresholds in sediment and water.
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TABLE A2. Correlations between Organic PCA vectors and
chemicals that exceeded toxic thresholds in sediment and water.
TABLE A3. Table of pairwise correlations between predictor
variables used to model skeletal and eye abnormalities in wood
frogs.
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LITERATURE CITED
Buchman, M. F. 2008. NOAA Screening Quick Reference Tables.
NOAA OR&R Report 08-1, Seattle, Washington. Office of
Response and Restoration Division, National Oceanic and
Atmospheric Administration, 34 pp.
Csuros, M. 1994. Environmental sampling and analysis for
technicians. CRC Press. Boca Raton, Florida, USA.