ddi12289-sup-0001-AppendixS1

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Appendix S1 - Detailed methodology
Survey Point Selection
We used a priori stratified, random sampling to select survey points across gradients of variables
previously determined to influence terrapin presence or absence (henceforth occurrence) either
positively (marsh) or negatively (shoreline armouring and crabbing pressure; Roosenburg, 1991;
Rook et al., 2010). Each variable was obtained from spatial data sets provided by the Center for
Coastal Resources Management (CCRM) at the Virginia Institute of Marine Science ( Coastal
Resources Management, 2011) and reclassified into three levels of intensity: none (absent), low
(< median value), and high (> median value). All spatial analyses were conducted in ARCGIS 10.0
(ESRI, 2011). We determined bin width of the three levels of intensity using the equal area in the
Reclassification tool. We then combined the three variables (salt marsh, shoreline armouring,
and crabbing pressure) and three intensities (none, low, and high) into a spatial 3x3x3 matrix of
habitat and disturbance gradients. All variables were assessed within a 270-m neighbourhood
using the “Neighbourhood Statistics” tool. We selected a circular neighbourhood of 270-m
radius to provide a fine-scale, sub-home range (average terrapin home range estimates of 400-m
– 890-m radius; (Spivey 1998; Butler 2002; Harden & Williard, 2012)) assessment of habitat and
human activity variables.
Shoreline armouring (Center for Coastal Resources Management, 2011) was included as
percent of available shoreline within a 270-m neighbourhood that was armored with bulkhead
(i.e., vertical retaining wall made of concrete, steel, wood, or plastic), rip-rap revetment (i.e.,
sloped retaining wall made of loose rock, crushed concrete, or other material), and/or seawall (all
were grouped as “armoured”). The equal area approach provided cutoffs at 0% armoured (none),
1-32% armoured (low), and ≥ 33% armoured (high). We included salt marsh (Center for Coastal
Resources Management, 2011) in relation to beach proximity, as beach is an important nesting
substrate for terrapins (Roosenburg, 1994). Female movements to nesting beaches are typically
<1 km (Sheridan et al., 2010), so we restricted our beach proximity to within 2 km. We coded
salt marsh as either absent, present but no beach within 2 km, or present with beach within 2 km.
Finally, crabbing pressure (Bilkovic et al. 2014) was included using the number of derelict pots
within a 270-m neighbourhood as a proxy for crabbing pressure in an area. The equal area
approach provided cutoffs at 0 pots (none), 1-2 pots (low), and >2 pots (high). We then summed
the three spatial data sets to produce a sampling raster with 27 possible survey habitats ranging
from no armouring, no marsh, and no crabbing pressure to high armouring, marsh with beach,
and high crabbing pressure. A subset of points, spaced at least 270 m apart to ensure
independence were then randomly selected within each of 27 survey habitats to equalize
sampling effort along habitat-disturbance gradients. We selected a different subset of survey
points in 2012 and 2013 to increase sample size and spatial extent.
Site-specific covariates
We reclassifications the South Eastern GAP (SEGAP) land cover classifications and shoreline
armouring. We reclassified all “developed open space” and “low intensity developed” as lowintensity development land cover. We reclassified “row crop” or “pasture/hay” land covers as
agricultural land cover as row crops and hayfields may alternate at different points in time. We
extracted areas classified as “emergent wetland” (reclassified as marsh) from SEGAP
(Biodiversity and Spatial Information Center, 2010) as the essential habitat variable for terrapins.
Survey-specific covariates
We used a portable weather station (Kestrel 2000 Wind Meter) to measure air temperature (°C)
and wind speed (m/s). We also estimated wind with the Beaufort index; we did not sample when
indices were > 5. We recorded glare and precipitation as binary variables (1 or 0), cloud cover as
quintiles (0, 25, 50, 75, or 100%), wave height (cm), and date and start time of the survey.
REFERENCES
Biodiversity and Spatial Information Center (2010) SEGAP. Available at:
http://www.basic.ncsu.edu/segap/ (accessed 18 November 2013).
Bilkovic D.M., Havens K., Stanhope D., & Angstadt K. (2014) Derelict fishing gear in
Chesapeake Bay, Virginia: Spatial patterns and implications for marine fauna. Marine
Pollution Bulletin, 80, 114–123.
Butler J.A. (2002) Population Ecology, Home Range, and Seasonal Movements of the Caolina
Diamondback Terrapin, Malaclemys terrapin centrata, in Northeastern Florida. Final
Report to FFWCC, 1–36.
Center for Coastal Resources Management (2011) Comprehensive Coastal Inventory. Available
at: http://ccrm.vims.edu/gis_data_maps/shoreline_inventories/index.html (accessed 18
November 2013).
ESRI (2011) ArcMap. Environmental Systems Research Institute, Redlands, CA.
Harden L.A. & Williard A.S. (2012) Using spatial and behavioral data to evaluate the seasonal
bycatch risk of diamondback terrapins Malaclemys terrapin in crab pots. Marine Ecology
Progress Series, 467, 207–217.
Rook M.A., Lipcius R.N., Bronner B.M., & Chambers R.M. (2010) Bycatch reduction device
conserves diamondback terrapin without affecting catch of blue crab. Marine Ecology
Progress Series, 409, 171–179.
Roosenburg W.M. (1991) The diamondback terrapin: population dynamics, habitat requirements,
and opportunities for conservation. New perspectives in the Chesapeake system: a
research and management partnership. Proceedings of a conference, 227–234.
Roosenburg W.M. (1994) Nesting habitat requirements of the diamondback terrapin: a
geographic comparison. Wetland Journal, 6, 8–11.
Sheridan C.M., Spotila J.R., Bien W.F., & Avery H.W. (2010) Sex-biased dispersal and natal
philopatry in the diamondback terrapin, Malaclemys terrapin. Molecular Ecology, 19,
5497–5510.
Spivey P.B. (1998) Home range, habitat selection, and diet of the diamondback terrapin
(Malaclemys terrapin) in a North Carolina estuary. Master Thesis, University of
Georgia.
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