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. 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