High Occupancy of Stream Salamanders Despite High Ranavirus Prevalence in a Southern

High Occupancy of Stream Salamanders Despite High Ranavirus Prevalence in a Southern Appalachians Watershed

APPENDIX

Field Survey Methods -- Starting at the downstream end of a suitable stream reach, we laid out three 2 x 8-m sampling plots per site. The exact starting point of the first plot was randomly chosen from within the first 5 m of the downstream end of the suitable reach. If both sides of the reach had rock-gravel substrate, then we randomly chose which side to survey, with subsequent plots placed on alternate sides of the stream. The second and third plots were placed in the first spots that could be sampled (i.e., places without highly undercut banks or large boulders) that were located upstream and ≥ 15 m from the previous plot. Each plot was placed along the edge of the stream so that it encompassed both bank and inundated microhabitats.

Observers completed two temporary removal passes of each plot, one immediately following the other. Within a plot, observers worked upstream, turning all rocksand other cover objects larger than approximately 5 x 5 cm and using small dipnets to capture salamanders. Captured salamanders of all age classes were placed in individual plastic bags, then set aside in a cool location for the duration of the survey at that site.

Analyses of Occupancy Data -- Because of the small size, cryptic coloration, and semi-fossorial behavior of many amphibians, the probability of detecting a particular species during any given site visit is inevitably less than one, and field surveys must employ methods that account for this imperfect detection (Mazerolle et al., 2007). We estimated site occupancy (Ψ) and detection probability(p) over one season for species that were captured at more than one site, following the methods described by MacKenzie et al. (2006) and using Program PRESENCE (Version 4.2, presence.html, accessed April 11, 2012). The detection probability is the product of the probability that ≥1 individual of a species was available in a plot, given that the site was occupied, and the probability that the species was detected, given that individuals were available for detection in the plot. Occupancy estimation is an approach being employed by national monitoring programs for amphibians, such as the Amphibian Research and Monitoring Initiative in the U.S. (Muths et al., 2005) and the National Amphibian and Reptile Recording Scheme in the U.K. (Sewell et al., 2010), because obtaining reliable estimates of actual population sizes via traditional mark-recapture techniques is typically too labor-intensive to implement at large spatial scales (Mazerolle et al., 2007).

We pooled data from the two passes of each plot and only included detections from the formal survey (i.e., we did not include a few detections of species that were seen at a site, but occurred outside the plot boundaries). We evaluated four models for each species: constant Ψ and constantp; Ψ varying as a function of survey date and constant p; constant Ψand p varying across surveys (i.e., plots); and Ψvarying with survey date and p varying across surveys (Table A1). Estimating abundance of plethodontid salamanders is challenging because a varying proportion of the overall population is present but hidden underground at any particular time (a form of temporary emigration; Bailey et al., 2004). In our sampling design, a significant effect of survey date (DAY, which ranged from day 1-116) would suggest temporal differences in availability for capture over the course of the season (i.e., temporary emigration); true site occupancy was assumed to be constant, because the three plots at a site were surveyed on the same day. We transformed DAY into z-scores prior to analysis to avoid potential problems with model convergence caused by covariates having a large range of values (Donovan and Hines, 2007). By allowingp to vary across surveys (i.e., from the first to the third plot) in two of the candidate models, we accounted for potential differences in detection arising from time of day or systematic variation in observer efficiency over the course of a day.Candidate models were ranked according to Akaike’s Information Criterion adjusted for small sample size (AICc), with the model having the lowest AICc scores considered to be the most supported (Table A1). For each species, we examined the fit of the global model [Ψ(DAY),p(SURVEY)] using the bootstrapping approach recommended by MacKenzie and Bailey (2004; 1,000 parametric bootstraps).

Although the constant model was the top-ranked model for all species, the model that included DAY as a site-specific covariate was equally well-supported (ΔAICc ≤ 2.0) for dwarf black-bellied salamanders and shovel-nosed salamanders (Table A1). However, in both cases, the 95% confidence limits around the coefficient (β) for DAY included zero (D. folkertsi 95% CL:

-0.703 - 1.662; D. marmoratus 95% CL: -1.515 - 0.328), which suggests DAY did not have a statistically significant effect on occupancy.

Chytrid (Bd) Testing -- Skin-swab samples were tested at the Southeastern Cooperative Wildlife Disease Study (SCWDS; Athens, Georgia, USA). Genomic DNA was extracted from each skin swab sample using the DNeasy Blood and Tissue Kit (Qiagen, Inc., Valencia, California, USA) following the manufacturer’s protocol and amplification was conducted with primers Bd1a and Bd2a as described by Annis et al. (2004), except we amplified for 40 cycles. The positive control was Bd DNA obtained from a Georgia amphibian and confirmed to be Bd by multi-locus sequence typing. For the negative controls, we used molecular-grade water extracted with each set of samples and run as an additional PCR sample. Each sample was run in triplicate and a sample was considered positive if Bd was detected in at least two of the replicates.

Toe-clips from the same individual salamanders were tested for Bd at the University of Georgia’s Veterinary Diagnostic and Investigational Laboratory (VDIL; Tifton, Georgia, USA) using real-time qPCR (Boyle et al., 2004; Table A2). The DNA was extracted using a commercially available kit (DNeasy Blood and Tissue Kit, Qiagen, Inc., Valencia, California, USA). For the qPCR assays, we measured the genomic DNA in each sample and standardized the amount of DNA among samples. Positive controls included both cultured Bd and tissue from an amphibian confirmed to be infected by histology. Negative controls included molecular-grade water and tissue from an amphibian that was not infected according to PCR and histology.

Ranavirus (Rv) Testing -- To test the tail-clip samples for Rv,genomic DNA was extracted from the tissues using the DNeasy Blood and Tissue Kit (Qiagen Inc., Valencia, California, USA). Conventional PCR was performed using the protocol and primer sets (MCP4 and MCP5) found in Mao et al. (1996, 1997) and targeting an approximately 450-bp region of the major capsid protein gene (Table A2). The PCR products were resolved via electrophoresis on a 1.0% agarose gel. Each PCR run included two negative controls (water and tissue from a Rv-negative tadpole) and two positive controls (cultured Rv and tissue from a Rv-positive tadpole).For estimating prevalence, we considered the few suspect cases (n = 5) to be negative for Rv. We calculated 95% Clopper-Pearson binomial confidence intervals for prevalence estimates using formulas given in Zar (1999) and the FINV function in Microsoft Excel 2007 to generate two-tailed critical values for the F distribution.

Biosecurity Measures-- In the field, we followed several steps to prevent transmission of pathogens among sites and among individual salamanders. We required personnel to disinfect their footwear upon arrival to and departure from the study area by spraying boots with 1% chlorhexidine solution (Green et al., 2010). We did not require personnel to disinfect gear when moving between sites on the same stream reach; however, before moving to a different stream reach, we sprayed nets and boots thoroughly with 1% chlorhexidine solution and allowed at least 1 minute of contact time. Observers wore disposable gloves while surveying the plots and changed gloves between each site, even when the sites were on the same stream. We tried to minimize handling of captured salamanders by transferring them from the net directly into new, separate plastic bags without touching them, and by identifying them through the bag. When direct handling of salamanders was needed to obtain samples for disease testing, the handler wore a new pair of nitrile gloves for each salamander. Scissors were disinfected with 1% chlorhexidine solution after each use. Plastic bags and gloves were never re-used and were removed from the field sites for proper disposal.

References

Annis SL, Dastoor FP, Ziel H, Daszak P, LongcoreJE (2004) A DNA-based assay identifies Batrachochytrium dendrobatidis in amphibians. Journal of Wildlife Diseases 40:420-428

Bailey LL, SimonsKR, PollockKH (2004) Estimating detection probabilityparameters forPlethodonsalamanders using the robust capture–recapture design. Journal of Wildlife Management 68:1-13

Boyle DG, BoyleDB, OlsenV, MorganJAT, HyattAD (2004) Rapid quantitative detection of chytridiomycosis (Batrachochytrium dendrobatidis) in amphibian samples using real-time Taqman PCR assay. Diseases of Aquatic Organisms 60:141-148

Donovan TM, Hines J(2007) Exercises inoccupancy modeling and estimation. Available: [accessed May 10, 2011]

Green DE, Gray MJ, Miller DL (2010) Disease monitoring and biosecurity. In: Amphibian Ecology and Conservation: A Handbook of Techniques, Dodd CK Jr (editor), New York: Oxford University Press, pp 481-505

MacKenzie DI, BaileyLL (2004) Assessing the fit of site occupancy models. Journal of Agricultural, Biological, and Environmental Statistics 9:300-318

MacKenzie DI, NicholsJD, RoyleJA, PollockK, BaileyLL, HinesJE (2006) Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Burlington: Academic Press

Mao J, Tham TN, Gentry GA, Aubertin A, Chinchar VG (1996) Cloning, sequence analysis, and expression of the major capsid protein of the iridovirus frog virus 3. Virology 216:431-436

Mao J, Hedrick RP, Chinchar VG (1997) Molecular characterization, sequence analysis, and taxonomic position ofnewly isolated fish iridoviruses. Virology 229:212-220

Mazerolle MJ, BaileyLL, KendallWL, RoyleJA, ConverseSJ, NicholsJD (2007) Making great leaps forward: Accounting for detectability in herpetological field studies. Journal of Herpetology 41:672-689

Muths E, JungRE, BaileyLL, AdamsMJ, CornPS, DoddCK, Jr, FellersGM, SadinskiWJ, SchwalbeCR, WallsSC, FisherRN, GallantAL, BattaglinWA, GreenDE (2005) Amphibian Research and MonitoringInitiative (ARMI): A successful start to anational program in the United States. Applied Herpetology 2:355-371

Sewell D, Beebee TJC, GriffithsRA (2010) Optimising biodiversity assessments by volunteers: The application of occupancy modeling to large-scale amphibian surveys. Biological Conservation 143:2102-2110

Zar JH (1999) Biostatistical Analysis, Fourth Edition, Upper Saddle River, New Jersey: Prentice Hall

Table A1.Ranking of candidate occupancy models for six stream salamander species in the Upper Tallulah River watershed based on Akaike’s Information Criterion corrected for small sample size (AICc). ΔAICc = AICc for the given model minus AICc for the best model,wi= Akaike weight, K= number of parameters in the model, and -2L = twice the negative log-likelihood. Estimates of siteoccupancy (Ψ)and detection probability (p) are given for the most supported models (ΔAICc ≤ 2.0). For models that included DAY as a site-specific covariate, we present the estimated occupancy for a “dummy” site having the mean value for DAY.

Models / AICc / ΔAICc / wi / K / -2L / Ψ ± SE / p ± SE
Seal salamander (Desmognathus monticola)
Ψ(.) p(.) / 96.64 / 0.00 / 0.705 / 2 / 92.14 / 0.9767 ± 0.0379 / 0.7584 ± 0.0517
Ψ(DAY) p(.) / 98.97 / 2.33 / 0.219 / 3 / 91.93
Ψ(.) p(SURVEY) / 101.54 / 4.90 / 0.061 / 4 / 91.72
Ψ(DAY) p(SURVEY) / 104.37 / 7.73 / 0.015 / 5 / 91.51
Ocoee salamander (D. ocoee)
Ψ(.) p(.) / 49.12a / 0.00 / 0.723 / 2 / 111.01 / 0.9611 ± 0.1194b / 0.5780 ± 0.0686
Ψ(DAY) p(.) / 51.66a / 2.54 / 0.203 / 3 / 111.00
Ψ(.) p(SURVEY) / 54.06a / 4.94 / 0.061 / 4 / 110.05
Ψ(DAY) p(SURVEY) / 57.09a / 7.97 / 0.013 / 5 / 110.03
Dwarf black-bellied salamander (D. folkertsi)
Ψ(.) p(.) / 109.23 / 0.00 / 0.612 / 2 / 104.73 / 0.7478 ± 0.0972 / 0.6109 ± 0.0746
Ψ(DAY) p(.) / 111.02 / 1.79 / 0.249 / 3 / 103.98 / 0.7565 ± 0.1004 / 0.6118 ± 0.0743
Ψ(.) p(SURVEY) / 112.75 / 3.52 / 0.105 / 4 / 102.93
Ψ(DAY) p(SURVEY) / 115.03 / 5.80 / 0.034 / 5 / 102.17
Shovel-nosed salamander (D. marmoratus)
Ψ(.) p(.) / 89.82 / 0.00 / 0.543 / 2 / 85.32 / 0.5987 ± 0.1245c / 0.7836 ± 0.0627
Ψ(DAY) p(.) / 90.48 / 0.66 / 0.390 / 3 / 83.44 / 0.6026 ± 0.1061d / 0.7829 ± 0.0631
Ψ(.) p(SURVEY) / 94.90 / 5.08 / 0.043 / 4 / 85.08
Ψ(DAY) p(SURVEY) / 96.06 / 6.24 / 0.024 / 5 / 83.20
Models / AICc / ΔAICc / wi / K / -2L / Ψ ± SE / p ± SE
Carolina spring salamander (Gyrinophilus porphyriticus dunni)
Ψ(.) p(.) / 109.82 / 0.00 / 0.639 / 2 / 105.32 / 0.9007 ± 0.1557 / 0.3975 ± 0.0858
Ψ(DAY) p(.) / 112.21 / 2.39 / 0.193 / 3 / 105.17
Ψ(.) p(SURVEY) / 112.92 / 3.10 / 0.136 / 4 / 103.10
Ψ(DAY) p(SURVEY) / 115.79 / 5.97 / 0.032 / 5 / 102.93
Blue Ridge two-lined salamander (Eurycea wilderae)
Ψ(.) p(.) / 113.00 / 0.00 / 0.669 / 2 / 108.50 / 0.8958 ± 0.0761 / 0.6340 ± 0.0661
Ψ(DAY) p(.) / 115.35 / 2.35 / 0.206 / 3 / 108.31
Ψ(.) p(SURVEY) / 116.78 / 3.78 / 0.101 / 4 / 106.96
Ψ(DAY) p(SURVEY) / 119.63 / 6.63 / 0.024 / 5 / 106.77

aValue shown is Quasi-AICc because bootstrapping indicated significant lack of fit for the global model (X2= 8.6765, P = 0.0410)

bStandard error was corrected for overdispersion because ĉ > 1.0 (ĉ = 2.4878; Donovan and Hines, 2007)

cStandard error was corrected for overdispersion because ĉ > 1.0 (ĉ = 1.6927)

dStandard error was corrected for overdispersion because ĉ > 1.0 (ĉ = 1.1423)

Table A2. Summary of pathogen sampling by site and stream, with results of PCR assays for Batrachochytrium dendrobatidis (Bd; qPCR on hind toe) and Ranavirus (Rv; conventional PCR on tail-clip). Species abbreviations: DEFO = Desmognathus folkertsi, DEMA = D. marmoratus, DEMO = D. monticola, DEOC = D. ocoee, DEQU = D. quadramaculatus, EUWI = Eurycea wilderae, GYPO = Gyrinophilus porphyriticus. Life stage: L = larval, P = postmetamorphic.

Site # / Stream / Species / Life stage / No. tested / No. infected with Bd / No. infected with Rv
1 / Deep Gap Branch / DEFO / P / 1 / 0 / 0
3 / Unnamed tributary of Tallulah River / DEMO / P / 1 / 0 / 1
3 / Unnamed tributary of Tallulah River / DEQU / P / 2 / 0 / 0
3 / Unnamed tributary of Tallulah River / GYPO / L / 2 / 0 / 0
4 / Unnamed tributary of Tallulah River / DEMO / P / 1 / 0 / 1
4 / Unnamed tributary of Tallulah River / DEOC / P / 4 / 0 / 3
4 / Unnamed tributary of Tallulah River / DEQU / P / 2 / 0 / 0
7 / Water Spout Branch / DEFO / P / 1 / 0 / 0
7 / Water Spout Branch / DEMA / P / 1 / 0 / 1
7 / Water Spout Branch / DEMO / P / 2 / 0 / 1
7 / Water Spout Branch / DEOC / P / 1 / 0 / 1
7 / Water Spout Branch / DEQU / P / 1 / 0 / 0
8 / Unnamed tributary of Tallulah River / DEFO / P / 3 / 0 / 0
10 / Sassafras Branch / DEMA / P / 2 / 0 / 0
10 / Sassafras Branch / DEMO / P / 2 / 0 / 2
10 / Sassafras Branch / DEQU / P / 1 / 0 / 1
11 / Sassafras Branch / DEMA / P / 2 / 0 / 0
11 / Sassafras Branch / DEMO / P / 1 / 0 / 0
11 / Sassafras Branch / DEQU / P / 2 / 0 / 0
11 / Sassafras Branch / GYPO / L / 1 / 0 / 0
13 / Beech Creek / DEMO / P / 2 / 0 / 0
13 / Beech Creek / DEOC / P / 2 / 0 / 0
13 / Beech Creek / DEQU / P / 1 / 0 / 0
14 / Beech Creek / DEMO / P / 3 / 0 / 2
15 / Burnt Cabin Branch / DEFO / P / 1 / 0 / 0
15 / Burnt Cabin Branch / DEMA / P / 1 / 0 / 1
15 / Burnt Cabin Branch / DEMO / P / 1 / 0 / 0
Site # / Stream / Species / Life stage / No. tested / No. infected with Bd / No. infected with Rv
16 / Unnamed tributary of Fall Branch / DEFO / P / 2 / 0 / 0
16 / Unnamed tributary of Fall Branch / DEMA / P / 2 / 0 / 2
17 / Fall Branch / DEFO / P / 2 / 0 / 1
17 / Fall Branch / DEMA / P / 2 / 0 / 1
17 / Fall Branch / DEOC / P / 2 / 1 / 0
17 / Fall Branch / DEQU / P / 2 / 0 / 0
18 / Unnamed tributary of Tallulah River / DEFO / P / 3 / 0 / 3
18 / Unnamed tributary of Tallulah River / DEOC / P / 2 / 0 / 0
18 / Unnamed tributary of Tallulah River / DEQU / P / 2 / 0 / 0
19 / Denton Creek / DEMA / P / 1 / 0 / 1
19 / Denton Creek / DEMO / P / 1 / 0 / 0
19 / Denton Creek / DEQU / P / 2 / 0 / 0
19 / Denton Creek / EUWI / P / 1 / 0 / 0
19 / Denton Creek / GYPO / L / 2 / 0 / 0
20 / Unnamed tributary of Denton Creek / DEMO / P / 1 / 0 / 0
20 / Unnamed tributary of Denton Creek / DEOC / P / 3 / 0 / 0
20 / Unnamed tributary of Denton Creek / DEQU / P / 1 / 0 / 0
20 / Unnamed tributary of Denton Creek / GYPO / L / 1 / 0 / 0
22 / Mill Creek / DEFO / P / 2 / 0 / 0
22 / Mill Creek / DEMA / P / 2 / 0 / 0
23 / Mill Creek / DEFO / P / 2 / 0 / 0
23 / Mill Creek / DEMA / P / 2 / 0 / 1
23 / Mill Creek / DEMO / P / 2 / 0 / 0
23 / Mill Creek / DEOC / P / 1 / 0 / 0
23 / Mill Creek / DEQU / P / 1 / 1 / 0
25 / Unnamed tributary of Mill Creek / DEMA / P / 1 / 0 / 0
25 / Unnamed tributary of Mill Creek / DEMO / P / 1 / 0 / 1
25 / Unnamed tributary of Mill Creek / DEQU / P / 1 / 0 / 0
26 / Tate Branch / DEMA / P / 3 / 0 / 1
26 / Tate Branch / DEQU / P / 2 / 0 / 1
27 / Tate Branch / DEFO / P / 1 / 0 / 0
27 / Tate Branch / DEMO / P / 2 / 0 / 2
27 / Tate Branch / GYPO / L / 2 / 0 / 0
Total: / 101 / 2 / 28

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