Managing habitat for the eastern tiger salamander and other Ambystomid salamander species

Valorie R. Titus, PhDAmerican Public University System

Amphibian Decline

Climate Change

Invasive Species

Pollution

Pet Trade

Disease

Habitat LossAdult A. tigrinum

Management Issues

Habitat Use/Quality

Movement/Buffer Zones

Population genetics

Relocation, Repatriation, Translocation

Typical A. tigrinum breeding pond

Eastern Tiger Salamander

Ambystoma tigrinum

NYS Endangered

Decreasing throughout their range

Many areas on Long Island are in danger of development

Pre-metamorphic A. tigrinum

Current Range

http://www.dec.state.ny.us/website/dfwmr/wildlife/endspec/tisafs.html

Historic Range in N.Y.

Current Range in N.Y.

http://www.dec.state.ny.us/website/dfwmr/wildlife/herp/eatisala.gif

Current Legal ProtectionNew York State Freshwater Wetland Act: 30 m buffer surrounding wetlands

NYS DEC Recommendations: 164 m, no more than 50% upland habitat within 305 m of breeding pond be converted to unusable habitat (based on Semlitsch 1998)

Recent metamorph

Brookhaven National Laboratory, Long Island, N.Y.

Over 5000 acres

22+ confirmed salamander ponds on site

3 Focal Ponds: L1, L3, L7

Tiger Salamander management and monitoring protocols already in place

Movements

Methods

Collected males and females upon emigration from breeding ponds

Collected juveniles upon emigration or just before final metamorphosis

Pre-metamorphic A. tigrinum

ResultsMovements at night during rain event

Some short movements after implant replacement

Avoided open fields, development, planted white pine stands

Adult A. tigrinum outside burrow

Results

Tracked 33 males, 26 females, 47 metamorphs

Predation: Bullfrog, Eastern Hognose Snake, Raccoon, Northern Short-Tailed Shrew, Eastern Ribbon Snake Radiotransmitter with

B. brevicauda tooth marks

ResultsRecovered a greater proportion of implants from males (72.2%, 24 of 33) than females (30%, 8 of 26) (Fisher Exact Probability, P=0.001)

No difference between number of implants recovered (N=25) and lost (N=22) for juveniles

More likely to recover implant from juveniles remaining closer to the breeding pond (Z=2.750, P=0.006) Juvenile A. tigrinum size

differences

ConclusionsPredation may be higher closer to breeding pond

Males may stay closer as a reproductive strategy

Females may move farther to reduce resource competition

Optimal pond conditions during development may influence juvenile dispersal

Traditionally calculated buffer zones may be inadequate for this species

Fails to protect 20% of individuals in this study, however, incorporating a 50 m edge effect, only protects 62%

May encompass unsuitable habitat and reduce availability of good habitat

Pre-metamorphic A. tigrinum

Connectivity

Fragmented landscapes resulting from anthropogenic habitat modification can have a significant impact on dispersal, gene flow, and persistence of wildlife populations

Reduced genetic variation can severely compromise the ability of a population to respond to subsequent environmental change Adult A.

tigrinum

GoalsAssess population genetic diversity of remaining tiger salamander populations

Quantify genetic and landscape connectivity among ponds and populations to identify potential corridors and barriers to migration Adult A.

tigrinum

MethodsCollected samples from 17 breeding sites across Long Island and 9 sites in New Jersey

Collected as many samples as possible (N=2-93) from each site

Genotyped 439 individuals across 12 microsatellite loci

Samples included toe and tail clips and individual eggs from egg masses A. tigrinum egg

mass

Low allelic diversity

Markers not highly polymorphic (1-13 alleles)

Mean numbers of alleles ranged from 1.1 to 3.3 in New York and 1.7 to 2.4 in New Jersey

GENEALEX version 6 (Peakall and Smouse 2006)

Results- Regional Population Structure and Migration

GENEALEX version 6 (Peakall and Smouse 2006)

Results- Regional Population Structure and Migration

Results- Regional Population Structure and Migration

High levels of population differentiation between NY and NJ (average Fst=0.217) (FSTAT Goudet 1995; Weir and Cockerham 1984).

Few individuals were assigned to the pond at which they were sampled with either 80% or 95% confidence, and many of these individuals were assigned to other ponds with high confidence (GENECLASS2; Piry et al. 2004)

Results- Landscape Barriers to Migration

Defined land cover resistance values from Compton et al. (2007) and Greenwald et al. (2009)

Calculated euclidean distance, euclidean resistance, and surface resistance (using CIRCUITSCAPE version 3.3; McRae and Shah 2009);

Correlated these values with Fst using a Mantel test (Rosenburg and Anderson 2011)

Adult A. tigrinum in burrow

Results- Landscape Barriers to MigrationNo relationship between connectivity indices and Fst in either New York (euclidean distance: r = -0.044, p = 0.827; euclidean resistance: r = -0.047, p = 0.812; surface resistance: r = -0.056, p = 0.786) or New Jersey (euclidean distance: r = 0.120, p = 0.388; euclidean resistance: r = 0.183, p = 0.312; surface resistance: r = 0.226, p = 0.246)

No relationship between Euclidean distance and assignment probabilities in NY (R2 = 0.0005, P = 0.791), but significant for NJ (R2 = 0.361, P = 0.00001)

ConclusionsLow allelic diversity; likely from few migrants during Pleistocene (Church et al. 2002)

May make whole population susceptible to collapse in case of catastrophic event

High risk of inbreeding depression if ponds become more isolated from each other

Conclusions3 distinct genetic demes; while evidence of admixture, this is likely due to ancestral polymorphism rather than gene flow between NY and NJ

The second NY deme is centrally located and within 10 m of each other; likely caused by wetland remediation from 2005-2007

Conclusions

Assignment probabilities provide evidence of recent migration between several ponds

Difference between NY and NJ is likely due to distance between ponds

Corridors appear to be present in both NY and NJ, but no relationship between distance/land cover and Fst

ManagementCalculate protection (buffer zones) on a case-by-case basis

Estimate probable dispersal habitat and determine available corridors

Individual breeding ponds can be susceptible to perturbations that may limit migration and dispersal

So What?Global amphibian declines

Desire to know how to properly conserve and manage this and other amphibian species

Disease outbreaks; already confirmed Bd and Ranavirus on site

Can we actively manage this species (e.g. relocation, assisted migration)?

Literature CitedChurch, SA, Kraus JM, Mitchell JC, Church DR, Taylor DR (2002) Evidence for multiple Pleistocene refugia in the postglacial expansion of the eastern tiger salamander, Ambystoma tigrinum tigrinum. Evolution 52:372-383

Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611-2620

Excoffier L, Smouse PE, Quattro, JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data Genetics 131:479-491.

Goudet J (1995) fstat (version 1.2): a computer program to calculate F-statistics. J of Hered 86:485-486

McRae BH, Shah VB (2009) Circuitscape user’s guide. The University of California, Santa Barbara. Available at: http://www.circuitscape.org.

Peakall R, Smouse PE (2006) Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes. 6:288-295.

Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, Estoup A (2004) GENECLASS2: a software for genetic assignment and first-generation migrant detection. J. of Hered. 95:536-539

Pritchard JK, Stephens M and Donnelly P, (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945-959.

Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J Hered 86:248-249.

Rosenburg, NA (2004) distruct: a program for the graphical display of population structure. Molecular Ecology Notes. 4:137-138.

Rosenberg MS, Anderson CD (2011) Passage: Pattern Analysis, Spatial Statistics, and Geographic Exegesis. V.2. Methods in Ecology and Evolution 2:229-232

Schneider S, Roessli D, Excoffier L (2000) Arlequin: A software program for population genetics data analysis (version 2.0). Genetics and Biometry Lab, Department of Anthropology, University of Genevam Switzerland.

Semlitsch, R.D. 1998. Biological delineation of terrestrial buffer zones for pond-breeding salamanders. Conservation Biology 12:1113-1119.

Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molec Ecol Notes 4:535-538

Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358-1370.

Acknowledgements

NYS DEC Project MOU # AM 05513

Brookhaven National Laboratory

NYS DEC

Foundation for Ecological Research in the Northeast (FERN)

Dave Golden and the Endangered and Nongame Species Program of the New Jersey Division of Fish and Wildlife

Upstate Herpetolgical Society

Acknowledgements

Dr. Dale Madison

Dr. Tim Green

Dr. Kelly Zamudio

Al Breisch

Dr. Dan Rosenblatt

Dr. Julian Shepherd

Dr. Richard Andrus

Dr. Matthew Parker

AcknowledgementsThank you to interns and fellow students: Sarah, Chauncey, Wendy, Frank, Jeremy, Jennifer, Esperanza, Stephen, Sarah, Emily, Carmen, Renee, Stephanie, Doris, Rachel, Dane, Katie, Kristine, Susan, Diana, Tyra, Shirin, Lauren, Matt, Miranda, Becky, Mike, Omar, Andy, Nate, Ellie, Jennifer, Miranda, Heather, Bri, Jin Joo, Sarah, Clara, Dave, Rayna, Angie, and Gui