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Hydrologic and vegetative removal of Cryptosporidium parvum, Giardia lamblia, and 1
Toxoplasma gondii surrogate microspheres in coastal wetlands 2
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Running Title: Hydrologic and vegetative removal of protozoa in coastal wetlands. 4
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Jennifer N. Hogan1, Miles E. Daniels2, Fred G. Watson2, Stori C. Oates3, Melissa A. Miller3, 6
Patricia A. Conrad1, Karen Shapiro1, Dane Hardin4, Clare Dominik4, Ann Melli1, David A. 7
Jessup3, Woutrina A. Miller1* 8
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1Department of Pathology, Microbiology & Immunology, School of Veterinary Medicine, 10
University of California, Davis, One Shields Avenue, Davis, California, 95616, USA; 2Division 11
of Science and Environmental Policy, California State University, Monterey Bay, 100 Campus 12
Center, Seaside, California, USA 93955; 3Marine Wildlife Veterinary Care and Research Center, 13
California Department of Fish and Game, 1451 Shaffer Road, Santa Cruz, California, 95060 14
USA; 4Applied Marine Sciences and Central Coast Long-term Environmental Assessment 15
Network, P.O. Box 8346, Santa Cruz, California, 95061, USA 16
*Corresponding Author. Tel: +1 530 219 1369; fax: +1 530 752 3349; [email protected] 17
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Copyright © 2013, American Society for Microbiology. All Rights Reserved.Appl. Environ. Microbiol. doi:10.1128/AEM.03251-12 AEM Accepts, published online ahead of print on 11 January 2013
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ABSTRACT 20
Constructed wetland systems are used to reduce pollutants and pathogens in wastewater effluent, 21
but comparatively little is known about pathogen transport through natural wetland habitats. 22
Fecal protozoans including Cryptosporidium parvum, Giardia lamblia, and Toxoplasma gondii 23
are waterborne pathogens of humans and animals, which are carried by surface waters from land-24
based sources into coastal waters. This study evaluated key factors of coastal wetlands for the 25
reduction of protozoal parasites in surface waters using settling column and re-circulating 26
mesocosm tank experiments. Settling column experiments evaluated the effects of salinity, 27
temperature, and water type (“pure” versus “environmental”) on the vertical settling velocities of 28
C. parvum, G. lamblia, and T. gondii surrogates, with salinity and water type found to 29
significantly affect settling of the parasites. The mesocosm tank experiments evaluated the 30
effects of salinity, flow rate, and vegetation parameters on parasite and surrogate counts, with 31
increased salinity and presence of vegetation found to be significant factors for removal of 32
parasites in a unidirectional transport wetland system. Overall, this study highlights the 33
importance of water type, salinity, and vegetation parameters on pathogen transport within 34
wetland systems, with implications for wetland management, restoration efforts, and coastal 35
water quality. 36
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Keywords 38
Cryptosporidium, Giardia, salinity, Toxoplasma, transport, vegetation, wetlands 39
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INTRODUCTION 41
Natural and constructed wetlands have the capacity for waterborne pollutant and pathogen 42
reduction and removal. Construction of wetlands near dairies, farms, and wastewater treatment 43
facilities may help reduce pollutant loads entering adjacent surface waters (10, 12, 26). Few 44
published studies have focused on the efficacy of naturally occurring coastal wetlands to filter 45
polluted water (26, 30). As a conduit for microbial transport from land to sea, natural wetlands 46
may have an ameliorating effect on concentrations of potential pathogens including 47
Cryptosporidium parvum, Giardia lamblia (syn. G. intestinalis and G. duodenalis), and 48
Toxoplasma gondii, reducing pathogen contamination in downstream waters that may be used 49
for recreation, drinking water, food harvest, and wildlife habitat (18). 50
Waterborne protozoa including C. parvum, G. lamblia, and T. gondii are important 51
human and animal pathogens in coastal ecosystems (6, 19). The environmentally resistant oocyst 52
and cyst stages of C. parvum and G. lamblia, respectively, facilitate parasite survival, rendering 53
them potentially infectious to susceptible hosts as they are transported through waterways 54
(35).The presence of these protozoal parasites in surface waters that are used for human 55
recreation, drinking, or food harvest is of significant public health interest, because infectious 56
doses are relatively low. Both C. parvum and G. lamblia are transmitted through fecal-oral routes 57
and can cause severe gastrointestinal illness (7, 9, 27). Toxoplasma gondii oocysts are shed in the 58
feces of cats, the only known definitive host of the parasite; humans and other warm-blooded 59
animals are intermediate hosts (4). Toxoplasma gondii can adversely affect the fetus if a pregnant 60
woman acquires the parasite, and immunocompromised individuals may suffer severe, even 61
fatal, infections (23). Toxoplasma gondii can also infect and cause disease in marine mammals, 62
including the threatened California sea otter (Enhydra lutris nereis) that ranges along the 63
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California coast. Otters may become infected following exposure to oocysts that are transported 64
from land-to-sea through contaminated freshwater runoff (14, 19). 65
Previous studies have examined parasite transport through surface waters to identify 66
hydrologic factors that result in protozoal reduction. For example, C. parvum counts were 67
reduced more quickly in water flumes containing sediment when compared to those without (29), 68
which is consistent with results from studies examining the vertical settling velocity of C. 69
parvum and G. lamblia (2, 28). Wetland vegetation has also been demonstrated to reduce water 70
pollution and prevent pathogen run-off near dairies through application of various vegetation 71
types and configurations in constructed wetlands (1, 3, 11). For example, in a study of natural 72
estuarine wetlands, vegetation-lined waterways significantly reduced transport of T. gondii 73
surrogates, when compared with non-vegetated mud flats (30). 74
Our aim was to establish a more robust model of estuarine wetland ecology and its role in 75
removing waterborne pathogens of public health significance. Our objectives were to: 1) 76
compare the effects of physical factors (salinity, temperature, and water type) on the vertical 77
settling velocities of C. parvum, G. lamblia, and T. gondii surrogates; and 2) compare the effects 78
of hydrologic factors (salinity and flow rate) and vegetation (presence, species, and 79
configuration) on removal of these parasites from environmental surface water using wetland 80
mesocosm tanks. 81
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MATERIALS AND METHODS 83
Source of protozoa and surrogates. Heat inactivated C. parvum oocysts and G. lamblia 84
cysts were obtained from the Wisconsin State Laboratory of Hygiene (Madison, WI) and 85
Waterborne Inc. (New Orleans, LA), respectively. Oocysts and cysts were obtained no more than 86
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one week prior to use for both settling column and mesocosm tank studies. Dragon Green (DG) 87
microspheres (Product No. FC07F/5493, Bangs Laboratories, Inc., Fishers, IN) and Glacial Blue 88
(GB) microspheres (Product No. PC06N/8319, Bangs Laboratories, Inc., Fishers IN) have been 89
previously evaluated as surrogate particles for T. gondii oocysts based on their surface properties 90
(31). 91
Settling column experiments. To investigate the effects of hydrologic factors on settling 92
velocities, experiments were conducted in vertical settling columns (Figure 1). Each settling 93
column held 1 L of water with sampling ports at 10cm (T) and 30cm (B) from the top of the 94
water column. Protozoan and microsphere counts at the two ports over time were used to assess 95
differences in settling velocities for the various water conditions that were evaluated. Eight 96
treatment conditions in a complete blocked design were evaluated in triplicate to measure the 97
effects of water type, salinity level, and water temperature on settling velocity of parasites and 98
microspheres. Two water types were evaluated: reverse osmosis purified distilled water from a 99
Milli-Q® water system (“pure”) and environmental water collected from Tembladero Slough 100
near Castroville, CA (“environmental”). Two salinity levels were evaluated to parameterize the 101
variability in salinity levels in coastal wetlands from freshwater to marine influence: “low 102
salinity” at baseline saline levels (0 ppt in Milli-Q® water and 0.1 ppt in environmental water) 103
and “high salinity” at 30 ppt, which was achieved through the addition of salt (Coralife Scientific 104
Grade Marine Salt®, Franklin, WI).Two water temperatures, 4°C and 27°C, were also evaluated 105
for each water type and salinity level to assess the effect of water temperature on protozoan and 106
microsphere settling properties. 107
Immediately prior to each experiment, 1x106 each of C. parvum oocysts, G. lamblia 108
cysts, and T. gondii oocyst surrogates (DG and GB) were mixed together into a 1 L container of 109
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water and homogenized by shaking. Once mixed, water was poured into the settling column and 110
subsamples were taken at 0, 5, 15, 30, 60, and 90 min, and 2, 4, 8, 24, and 48 hrs. At each sample 111
point, 1 mL of water was removed from the column using an 18 gauge needle and 100 µL was 112
expressed onto a microscope slide and air-dried. Slides were stained with direct fluorescent 113
antibody (DFA) for oocyst and cyst identification using Aqua-Glo™ G/C Direct (Waterborne, 114
Inc., New Orleans, LA, USA) and parasites were enumerated under epifluorescent illumination 115
using FITC and DAPI emission filter sets. Particles with apple-green fluorescence in an oval or 116
spherical shape (3-7 μm in diameter) with bright, highlighted edges under FITC and light blue 117
internal staining with a green rim or up to four distinct, sky-blue nuclei under DAPI were 118
classified as C. parvum oocysts. Particles with apple-green fluorescence in a round to oval shape 119
(6-15 μm in diameter) with bright, highlighted edges under FITC and light blue internal staining 120
with a green rim or up to four distinct, sky-blue nuclei under DAPI were classified as G. lamblia 121
cysts. Surrogates were enumerated using epifluorescent microscopy as previously described (32). 122
Settling velocities were calculated by linear regression using the equation derived by Dai 123
and Boll (2006): 124
ln
where N0 is the number of parasites or microspheres enumerated from a single port at time 0, Nt 125
is the number of parasites or microspheres enumerated at time t, H is the height (mm) from the 126
top of the water column to the sampling port, and vs is the settling velocity expressed as mm/hr. 127
These settling velocities were converted to µm/sec. Any settling velocities estimated using 128
regression to be below zero were truncated to 0 µm/sec, and were classified as NS, “no settling”. 129
Regression on Ordered Statistics (ROS) analysis was used to determine mean settling velocity 130
and the 95% Confidence Interval for each experimental condition by adjusting for the truncated 131
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values (34). Given the non-normal distribution of residual errors observed around the predicted 132
mean with a linear regression model, the non-parametric Kruskall-Wallis test was used to 133
evaluate if there were differences between any of the treatment groups or combinations. 134
Wetland mesocosm release experiments. To investigate the effect of wetland factors 135
(salinity, flow rate, and vegetation) on reduction of particle numbers, experiments were 136
completed in re-circulating wetland mesocosm tanks (Figure 2A). Three tanks were used in this 137
study, and each was a closed system measuring 3 m by 0.5 m. A depth of one cm of 138
commercially available Monterey Beach silica sand was used on the bottom of the tank as 139
substrate. Water for the tanks was obtained from Tembladero Slough in Castroville, CA. Each 140
tank was filled with 450 L of water to achieve a depth of 30 cm. Ten treatment conditions were 141
compared: non-vegetated tanks at high and low salinity, California bulrush (Schoenoplectus 142
californicus) at low salinity in two configurations, and slough sedge (Carex obnupta) at low 143
salinity. Each of these conditions was tested at fast and slow water flow rates. The inflow 144
velocity of water was manipulated to compare flow rates of 0.1 cm/sec (slow) and 1 cm/sec 145
(fast), which approximate water flow rates observed in regional natural and reconstructed coastal 146
wetlands (30). 147
In non-vegetated tanks, salinity was increased from baseline (0.1 ppt; low) to 30 ppt (high) 148
through addition of Coralife Scientific Grade Marine Salt® to the tank. For experimental 149
conditions requiring vegetation, wild California bulrush and slough sedge were transplanted from 150
Molera Constructed Wetland near Castroville, CA and placed in tanks at 150 cm from the water 151
inflow and between the two sampling locations. Both species of California bulrush and slough 152
sedge were placed such that water would flow through stalks emerging from a 15cm wide piece 153
of rhizome. This was stabilized by gravel at the base of the rhizome and rootstock as well as 154
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through securing the top of the stalks with twine. Furthermore, vegetation was placed in either 155
of two configurations across the width of the tank: buffer or channel. The buffer configuration 156
consisted of stands of bulrush being placed across the width of the tanks (Figure 2B). The root 157
and substrate mass reached a height of 15 cm, and plant stalks continued past the top of the 158
water. The channel configuration was similar to the buffer configuration, but an opening 25 cm 159
wide was left between two stands of bulrush (Figure 2C). For slough sedge, only the buffer 160
configuration was used. Three tank replicates were evaluated for each combination of salinity, 161
flow rate, and vegetation. 162
At the beginning of each experiment, aliquots of 4.5x106 each of C. parvum, G. lamblia, 163
and DG T. gondii surrogates were homogenized into a 5 mL volume of phosphate buffered saline 164
(PBS). Prior to particle injection, baseline water samples were taken to determine prevalence of 165
naturally occurring C. parvum or G. lamblia. Particles were then injected as a bolus at a depth of 166
10 cm and a distance of 10 cm from the inflow. Fifty mL samples were collected downstream at 167
a 15 cm depth at two locations: 76 cm and 226 cm from the inflow, at post-injection times of 1, 168
5, 10, 15, 30, 60, 90 min, and 2, 4, 6, 24, 48, and 72 hr. Water quality data, including pH, 169
temperature, salinity, conductivity, turbidity, and dissolved oxygen, were also collected for each 170
tank once at the start of the experiment. 171
After collection, samples were centrifuged at 1000 g for 15 min and the upper 45 mL of 172
supernatant was discarded. The remaining pellet was stored at 4º C and processed within 48 hr. 173
Cryptosporidium parvum and G. lamblia were concentrated using immunomagnetic separation 174
(IMS) with a half dose of magnetic beads (20) (Dynabeads® Invitrogen Life Sciences, Carlsbad, 175
CA, USA) and visualized using DFA (Easy Stain™, BTF Bio, Pittsburgh, PA, USA) as 176
described above. Results were expressed as the (oo)cyst count per 50 mL of water and were not 177
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adjusted for assay percent recovery. Supernatant from the IMS process was directly filtered 178
through a 5µm pore size membrane filter and T. gondii surrogates trapped on the filter surface 179
were enumerated under epifluorescence microscopy (32). 180
To estimate the time for water to fully circulate within the tank and allow complete 181
dispersion, concurrent tracer experiments were conducted for each treatment condition. Using a 182
single bolus injection of sodium bromide (NaBr), the salt reached equilibrium in each tank after 183
15 min, so samples taken at 15 min or earlier were excluded from subsequent analyses in order to 184
focus on post-dispersion parasite counts. 185
Mesocosm tank experimental data were analyzed using longitudinal negative binomial 186
(NB) regression models to determine associations between cyst counts and key factors including 187
sample location, flow rate, salinity, vegetation presence, vegetation species (bulrush versus 188
sedge), configuration of bulrush (buffer versus channel), and time post-particle injection. The 189
models were fitted using generalized estimating equations (GEE) because this approach 190
inherently allows for temporal autocorrelation, which we expected to be present in our data by 191
virtue of repeated sampling of each tank; a first-order autoregressive correlation structure was 192
specified in the GEE formulation after an initial examination of the covariance structures (15). 193
Negative binomial variance was specified in the models because the descriptive statistics 194
revealed that the mean counts for all three parasites were over-dispersed, with the variances far 195
exceeding the means. A logarithmic link function was employed in order to assure that modeled 196
mean counts were non-negative, as is typical for negative binomial regressions (36). Predictors 197
were included for each variable assessed in the study, including time post-particle injection. The 198
importance of each predictor was inferred from its incident rate ratio ( IRR), which in turn was 199
calculated by exponentiation of the estimated parameter value corresponding to that predictor 200
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(25).The effect of individual covariates was modeled first, and those determined to be significant 201
were then used to build models with multiple covariates. Quasi-likelihood under the 202
Independence model Criterion (QIC) values were used to determine model fit. Statistical 203
analyses were conducted using SAS software, Version 9.2 (SAS Institute Inc., Cary, NC, USA, 204
PROC GENMOD, with options REPEATED, CORR=AR(1), and DIST=NEGBIN), and p<0.05 205
was considered statistically significant. 206
207
RESULTS 208
Settling column experiments. A total of eight conditions (evaluating water type, 209
temperature, and salinity) were examined in settling column experiments, each run in triplicate, 210
and 48 individual settling velocities were determined, which included one for each condition per 211
replicate and sampling port. The overall mean settling velocities (± standard error) were 0.44 212
(±0.13) µm/sec for C. parvum, 0.84 (±0.16) µm/sec for G. lamblia, and 1.05 (±0.19) µm/sec and 213
1.14 (±0.19) µm/sec for DG and GB T. gondii surrogates, respectively. No statistical difference 214
in settling velocities was observed between the top and the bottom ports within a single column, 215
so data from both ports was pooled for subsequent analysis. 216
Settling velocity means and standard errors for C. parvum, G. lamblia, and both T. gondii 217
surrogates stratified by water type and salinity are shown in Table 1. No direct comparisons were 218
made between C. parvum, G. lamblia, and T. gondii surrogates due to potential variation in 219
percent recovery across assays. When the settling velocities were compared across individual 220
predictor variables of water type, salinity, and temperature, the DG surrogates’ settling velocities 221
were significantly different between the pure and environmental water matrices (Kruskall-Wallis 222
p <0.05). When these predictor variables were examined in combination, significant differences 223
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were found for the settling velocities of both C. parvum and G. lamblia: in pure water, increased 224
salinity led to faster settling; however, in environmental water, increased salinity led to slower 225
settling (Kruskall-Wallis p <0.05, for both parasites). No significant differences were found 226
between settling velocities at high and low temperatures. 227
Wetland mesocosm release experiments. Based on the significant effect of salinity on 228
the settling velocities of protozoa in the settling column experiments, salinity was also examined 229
in the subsequent mesocosm release experiments using environmental waters. With the NB 230
regression model evaluating the effects of individual predictors (Table 2), the C. parvum oocyst 231
concentration ratio for the effect of salinity was 1.33 (p <0.05), indicating that the IRR of oocysts 232
per 50 mL was 1.33-fold higher in the higher saline water compared to the concentration of 233
oocysts in lower salinity water. No significant difference was observed between slow and fast 234
flow rates for either parasite or T. gondii surrogate counts with the NB model (Table 2). There 235
was no significant difference between sampling locations or flow rates in the non-vegetated 236
system in the NB analyses. 237
Both California bulrush and slough sedge significantly enhanced removal of G. lamblia 238
and T. gondii surrogates from the surface water in the wetland mesocosm tanks, compared to 239
experimental replicates where no vegetation was used. Figure 3 shows the mean parasite count 240
changes over time for C. parvum, G. lamblia, and T. gondii surrogates in surface water from the 241
vegetated and non-vegetated tanks. To illustrate the effect that individual variables had on 242
parasite and surrogate counts, Table 2 shows the IRRs for individual vegetation parameters. For 243
the T. gondii surrogate counts, the presence of any vegetation (regardless of species or 244
configuration) was significant (OR = 0.51; p <0.05), indicating that fewer surrogates were 245
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recovered from the water column of mesocosm tanks with vegetation, when compared to 246
mesocosm tanks without vegetation. 247
Individual vegetated conditions also showed significant trends in parasite or surrogate 248
recovery, as shown in Table 2. Recovery of T. gondii surrogates from all three vegetated 249
conditions was significantly lower than recovery counts from the non-vegetated replicates, with 250
IRRs of less than 1 (p <0.01). The effect of vegetation species and California bulrush 251
configuration comparisons varied between the parasites and surrogates (Table 2). When 252
comparing buffer and channel configurations of California bulrush, a significant effect on 253
recovery counts occurred for T. gondii surrogates only, with an IRR of 0.75 (p <0.001), 254
indicating that the buffer strip configuration removed more surrogates than the channel 255
configuration. Conversely, there was no difference in effect of channel or buffer configurations 256
of California bulrush on counts of either C. parvum or G. lamblia. When comparing vegetation 257
species in a buffer configuration, significant differences were noted for both G. lamblia and T. 258
gondii surrogates (p <0.001) with IRRs of 0.45 and 0.7, respectively, which suggests that 259
wetland mesocosm tanks containing bulrush removed more parasites than those containing 260
sedge. 261
Evaluation of the combined effect of the hydrologic and vegetation parameters on the rate 262
of removal in the mesocosm tanks further emphasizes the role of vegetation in removing G. 263
lamblia and T. gondii surrogates from surface water. Using longitudinal NB multiple regression 264
analysis (Table 3), parameters significant to the final model included the effects of either 265
vegetation type when compared to absent vegetation, plus the effect of increasing salinity for C. 266
parvum and G. lamblia. For C. parvum, both bulrush in the channel configuration and slough 267
sedge had significant effects on parasite counts, with IRRs of 1.5 and 1.6, respectively (p <0.01), 268
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as compared to absent vegetation. The inclusion of salinity was also significant with an IRR of 269
1.8 (p <0.0001), indicating that at increased salinity more C. parvum oocysts were retained in 270
surface water than at lower salinity. For G. lamblia, bulrush in the buffer configuration was 271
significant with an IRR of 0.56 (p <0.05), indicating that when California bulrush is present, 272
fewer cysts were recovered. For T. gondii surrogates, all three vegetation conditions had IRRs of 273
less than 1 (p<0.05), indicating that when vegetation is present, fewer surrogates are recovered. 274
In summary, addition of vegetation significantly enhanced removal of G. lamblia cysts and T. 275
gondii surrogates, while decreased water salinity enhanced removal of C. parvum oocysts in 276
wetland mesocosm tanks. 277
278
DISCUSSION 279
Wetlands reduce the concentration of numerous water pollutants and pathogens in effluent 280
waters, but the mechanisms responsible for pathogen removal vary by wetland and pathogen (8, 281
26). This study aimed to better characterize the physical and hydrological conditions that 282
enhance removal of Cryptosporidium, Giardia, and Toxoplasma in fecal pathogen-polluted 283
surface water that enters coastal wetlands. We determined that salinity, water type, and 284
vegetation type and configuration are key factors for reduction of suspended protozoal parasites 285
in water. Although field investigations in the Tembladero Slough wetland system have also been 286
conducted to evaluate its role in pathogen transport (8), experimental laboratory approaches in 287
simulated natural wetlands conditions utilized during this study enabled examination of key 288
factors not easily controlled in the field setting. 289
At low salinity, faster settling of all four particles (C. parvum oocysts, G. lamblia cysts, 290
DG and GB T. gondii surrogates) was observed in environmental water as compared to pure 291
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water, a finding that is consistent with previous studies (17, 28). Higher salinity correlated with 292
faster settling of Cryptosporidium oocysts and Giardia cysts in pure water, but higher salinity 293
correlated with slower settling of Giardia cysts in environmental water. This latter observation 294
was surprising in light of recent findings that increased numbers of T. gondii oocysts and 295
surrogate microspheres were recovered from settled aggregates in environmental waters with 296
increased concentrations of salt (33). The effect of salinity on aggregation and subsequent 297
particle settling may be countered by increased buoyancy of particles when suspended in higher 298
density aquatic solutions. In addition, the experimental setup described here was conducted on 299
spiked parasites and surrogates added directly to settling columns, without incubation or rolling 300
conditions that enhance formation of aggregates (33). Thus, the apparent impact of salinity on 301
pathogen settling may be confounded by experimental methodology, altered surface properties of 302
the organism, and/or interactions between the protozoa and suspended sediments (5), perhaps 303
due to the use of heat-inactivated protozoa which may have altered surface properties compared 304
to live protozoa. 305
Previous studies aiming to quantify the settling velocities of C. parvum and G. lamblia in 306
pure and environmental waters at low salinity have demonstrated a wide range of results (2, 17, 307
28). Our study showed that salinity has a significant effect on the vertical settling of 308
Cryptosporidium, Giardia and Toxoplasma surrogates and that water type also contributes 309
significantly to variation in settling properties, thus accounting for the wide range of results in 310
prior studies. The impact of environmental water salinity on parasite transport was further 311
evaluated in the mesocosm tank studies. For Giardia and T. gondii surrogates in the settling 312
columns, increased salinity in environmental water correlated with slower settling velocities, and 313
in the mesocosm tanks increased salinity correlated with slower removal of Cryptosporidium. 314
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The impact of salinity is relevant for coastal wetlands, which are greatly affected by tidal 315
influence. 316
Beyond the interaction of water type and salinity affecting the settling of protozoa, the 317
presence or absence of vegetation was also shown to be a critical factor in protozoal removal. 318
Wetlands can reduce microbial pollutant loads through several processes, including adsorption, 319
sedimentation, and vegetative uptake (10, 11, 13). When vegetation was included in the 320
experimental wetland mesocosm tanks, Giardia and T. gondii surrogate counts were significantly 321
lower in the surface water as compared with mesocosm tanks without vegetation, suggesting that 322
the presence of vegetation can reduce the concentrations of parasites that remain suspended in 323
surface waters. 324
The utility of vegetation for microbial removal has been demonstrated in prior studies, 325
which have shown that vegetated buffer strips can effectively remove microbial pathogens from 326
contaminated run-off (1, 21, 22, 37). However, different aquatic plants may vary in their ability 327
to remove parasites due to distinct surface properties, unique biofilms, and differential effects on 328
water flow and drag (16, 24). Therefore, plant selection is an important consideration for 329
wetlands managers in understanding how to best restore degraded wetlands or conserve existing 330
ones (18, 30, 38). This study compared California bulrush, a dense, reed-like plant, to slough 331
sedge, a more grass-like plant. Both are found in California coastal wetlands and are commonly 332
used in landscape restoration. The presence of bulrush was more likely to reduce parasite counts 333
for both Giardia and T. gondii surrogates; however no difference was seen between the two 334
vegetation treatment groups for Cryptosporidium. A further consideration for wetlands managers 335
is how to best integrate vegetation into the landscape, as this can also affect the flow and drag of 336
water (24). Interestingly, the channel and buffer configurations of California bulrush in the 337
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mesocosm tanks showed no significant difference in removal of Cryptosporidium or Giardia, 338
despite the presence of a 15 cm gap between stands of bulrush in the channel configuration. 339
Although wider gaps still need to be studied, our results support the use of either configuration in 340
restoration efforts, particularly if the waterway is narrow. 341
In coastal habitats where land-to-sea transport of parasites such as Cryptosporidium, 342
Giardia, and Toxoplasma is of concern for the commercial and sport harvest of invertebrates for 343
human consumption, recreational water use, and marine wildlife health, the comparatively low-344
cost water purification services provided by wetlands should not be discounted. The ability of 345
wetland habitats to reduce outflow of parasites and other fecal pathogens to receiving coastal 346
waters could play a key role in preserving or restoring adequate water quality that will promote 347
human and wildlife health. Salinity and the presence of vegetation play an important role in 348
moderating wetlands’ capacity to remove parasites through adsorption, sedimentation, and 349
uptake (13). Because much of the coastal wetlands in the United States have been degraded, 350
there are numerous efforts currently underway to restore these habitats; the inclusion of 351
vegetation within wetland restoration projects will not only promote healthier ecosystems, but 352
will also enhance parasite removal from surface waters. 353
354
ACKNOWLEDGEMENTS 355
This project was made possible by: the California Sea Grant Program (Grant 356
NA08OAR4170669), the Central Coast Long-term Environmental Assessment Network 357
(CCLEAN) (Grant 06-076-553) from the California State Water Board to the City of 358
Watsonville; the National Science Foundation (NSF) Ecology of Infectious Disease Grant 359
Program (Grant OCE-1065990), and the University of California, Davis Center for Food Animal 360
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Health. Support was also provided by the California Department of Fish and Game Marine 361
Wildlife Veterinary Care and Research Center (MWVCRC), Santa Cruz, CA. We would like to 362
thank Andrea Packham as well as the MWVCRC staff and volunteers for their assistance and 363
inspiration. 364
365
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Table 1: Settling velocities (µm/sec) as measured in settling column experiments utilizing 469
Cryptosporidium parvum oocysts, Giardia lamblia cysts, and Toxoplasma gondii surrogate 470
microspheres (DG-Dragon Green; GB-Glacial Blue), stratified by water type and relative salinity 471
472
Cryptosporidium Giardia
DG surrogates for
T. gondii
GB surrogates
for T. gondii Water Type Salinity (ppt) n Mean SE Mean SE Mean SE Mean SE
Pure Low (0) 6 0.08 0.04 0.14 0.04 0.42 0.13 0.84 0.26 Pure High (30) 6 0.93 0.44 1.04 0.14 0.84 0.50 0.81 0.51
Environmental Low (0) 6 0.86 0.28 1.48 0.49 1.82 0.48 1.95 0.48 Environmental High (30) 6 NS 0.79 0.29 1.11 0.30 1.15 0.23 NS=No Settling 473
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Table 2: Effect of individual hydrologic or vegetation parameters on counts of Cryptosporidium 474
parvum oocysts, Giardia lamblia cysts, and Dragon Green (DG) Toxoplasma gondii surrogate 475
microspheres in wetland mesocosm tanks using longitudinal negative binomial regression. 476
477 Cryptosporidium Giardia T. gondii surrogates
Predictor n IRR p IRR p IRR pSalinity-Low 480 1 1 1 Salinity-High 120 1.33 0.0167* 0.79 0.3377 1.30 0.3422 Flow-Slow 300 1 1 1 Flow-Fast 300 1.02 0.8796 1.12 0.5475 1.19 0.4052 Tank Location 1 300 1 1 1 Tank Location 2 300 0.99 0.8384 1.00 0.988 1.04 0.2221 Time since injection (continuous) 600 0.97 <0.0001* 0.97 <0.0001* 0.97 <0.0001*
Vegetation absent 240 1 1 1 Vegetation present 360 1.04 0.7114 0.97 0.9147 0.51 <0.0001* Vegetation Absent (reference) 240 1 1 1 Bulrush Buffer 120 0.92 0.5737 0.66 0.0729 0.41 <0.0001* Bulrush Channel 120 1.05 0.7271 0.82 0.3809 0.54 0.0006* Sedge Buffer 120 1.14 0.3366 1.46 0.1003 0.59 0.0026* Bulrush Configuration Channel (reference) 120 1 1 1 Buffer 120 0.88 0.4504 0.81 0.3775 0.75 0.0006* Vegetation Species Sedge (reference) 120 1 1 1 Bulrush 120 0.81 0.1225 0.45 <0.0001* 0.70 <0.0001**Effect of factor is significant with p<0.05 478 IRR = incident rate ratio = eβ 479 n = number of water samples included in analysis for factor, 480
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481 Table 3: Effect of multiple hydrologic and vegetation parameters on counts of Cryptosporidium 482
parvum oocysts, Giardia lamblia cysts, and Dragon Green (DG) Toxoplasma gondii surrogate 483
microspheres in wetland mesocosm tanks using longitudinal negative binomial regression. 484
485 Cryptosporidium Giardia T. gondii surrogates
Predictor n IRR p IRR p IRR p Salinity-Low (reference) 480 1 1 1 Salinity-High 120 1.8 <0.0001* 0.69 0.2922 0.77 0.3427 Vegetation Absent (reference) 240 1 1 1 Bulrush Buffer 120 1.3 0.1381 0.56 0.0167* 0.36 <0.0001* Bulrush Channel 120 1.5 0.0075* 0.69 0.1445 0.48 0.0033* Sedge Buffer 120 1.6 <0.0001* 1.23 0.3045 0.52 0.0079* *Effect of factor is significant with p<0.05 486 IRR = incident rate ratio = eβ 487 n = number of water samples included in analysis for factor 488 489
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490 Figure Captions 491
492
Figure 1: Schematic diagram of an experimental settling column where T is top sampling port 493
and B is bottom sampling port. 494
495
Figure 2: Schematic diagrams of an experimental wetland mesocosm tank where 1 and 2 indicate 496
sampling locations, and “inj” indicates the injection point for Cryptosporidium parvum, Giardia 497
lamblia and DG Toxoplasma gondii surrogates. (A) Entire mesocosm tank with water flow 498
directionality; (B) Mesocosm tank view from above with vegetation (v) in buffer strip 499
configuration; (C) Mesocosm tank view from above with vegetation (v) in channel configuration. 500
501
Figure 3: Concentrations of Cryptosporidium parvum, Giardia lamblia, and Dragon Green 502
Toxoplasma gondii surrogates per 50 mL volume of surface water in mesocosm tanks plotted 503
over time. Three replicates of each wetland condition were tested to evaluate the effect of 504
vegetation presence and species on removal of parasites from water column. (A) 505
Cryptosporidium, (B) Giardia, and (C) Toxoplasma surrogates. 506
507
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