For Table and Figure references below, see the document "SquidpopAssay_statistical_analysis.pdf" in the Supplemental Files section.
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Study Site Selection
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We conducted our study across eight discrete seagrass meadows (hereafter referred to as landscapes) located in Back Sound, North Carolina (NC), USA (3442\u2032 N to 3439\u2032 N, 7637\u2032 W to 7631\u2032 W) (Fig. S1). All of our sampled landscapes were composed of a mixture of Back Sound's dominant seagrasses: eelgrass and shoal grass, Halodule wrightii (Ascherson 1868) (Yeager et al. 2016). Landscapes were chosen based upon available aerial imagery in Google Earth Pro as of February 19, 2017, and ground-truthed for changes in seasonal seagrass growth/senescence using summer, 2017, drone photography and ImageJ 1.x (Schneider et al. 2012). No discernable differences in landscape fragmentation states (e.g. total area, number of patches) were found between the two aerial imagery sources. All landscapes were relatively shallow (1-1.5 m depth at high tide), reasonably isolated from other seagrass beds (distance to nearest seagrass meadow = 112 17 m [mean standard error]) and were appropriately sized to encompass short-term (e.g., daily, monthly) movements of common seagrass-associated fauna in this system (Yeager et al. 2016). We identified similarly sized landscapes (25882 6592 m2) available in Back Sound by defining the minimum convex polygon surrounding the seagrass meadow, regardless of the total seagrass cover within the polygon. Among eight candidate landscapes of similar size, we defined four continuous landscapes and four fragmented landscapes based on the number of patches, the perimeter-to-area ratio, and the largest patch's percent cover of the total seagrass area (Table 1). Seagrass fragmentation is often naturally coupled with habitat loss (Wilcove et al. 1986), resulting in the mean seagrass area of our fragmented landscapes being nearly half that of our continuous landscapes (Table 1). Thus, our experiment was designed to examine the effects of fragmentation (i.e., the breaking apart of habitat concomitant with habitat loss) rather than fragmentation per se (i.e., the breaking apart of habitat without habitat loss; sensu Fahrig 2003).
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Squidpop Assays
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Squidpops were also used to measure relative "depredation" across landscapes (acknowledging that a combination of predation and scavenging may account for observed loss patterns). Squidpops are 1-cm 1-cm squares of dried squid mantle tied to 1-cm segments of 12-lbs test monofilament (Duffy et al. 2015). We attached squidpops to 60-cm long, 0.5-cm diameter, fiberglass stakes. Twenty squidpops were deployed (stakes pushed 50 cm into the sediment to prevent squidpop tangling in seagrass or burial in sediment) within each of the eight landscapes per assay date during July and August (July 5, July 13, July 26, August 8, and August 30). Within each landscape, 10 squidpops were haphazardly placed within seagrass edges, defined as 30 cm (a crab tether length) from the seagrass-mudflat interface. The other 10 squidpops were haphazardly placed in seagrass interiors, defined as \u22651 m from the seagrass-mudflat interface. Only patches with a radius of 1 m or larger were used for squidpops classified as 'interior'. However, patches with a radius of <1 m were used for a portion of our 'edge' squidpops. All squidpops were placed at least 1 m apart. A total of 720 squidpops were deployed (Table S1). Squidpop depredation assays did not occur in June due to lack of dried squid availability. During the first two squidpop deployment cycles we checked squidpop status (present, absent/eaten) at 1 h and 24 h. We observed nearly 100% squidpop removal by 24 h, so for the remaining three deployment cycles we performed status checks at 1 h and 2 h.
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Point measurements of water temperature (C) were taken in each landscape at the location and time of all squidpop assays hand-held thermometers (Table S1). We chose temperature as our seasonality proxy (Fig. S2) because several other seasonally affected factors including faunal densities correlate with water temperature variability. Additionally, the measurement of temperature is easy, cheap, reliable, and comparable to previous studies.
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Equipment:
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Dried squid mantel: whole dried squid from Asian food market
\nTether materials:
\nEcoStakes \u2013 tomato plant stakes
\n12-lbs test monofilament fishing line
\nPool noodles \u2013 cut into rounds for tether relocation floats
\nHand-held digital thermometer- LYNCH Waterproof thermometer 39240
\nHand-held refractometer-VEE GEE STX-3 Salinity 0-100%o
\nHand-held Garmin GPSmap 78
Data processing: All data were entered electronically into an Excel spreadsheet.
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BCO-DMO Data Manager Processing Notes:
\n* exported submitted excel file to csv format
\n* added a conventional header with dataset name, PI name, version date
\n* modified parameter names to conform with BCO-DMO naming conventions
\n* date format converted to ISO 8601 standard format yyyy-mm-dd
\n* cells with just a period as a value replaced will no-data values. No-data values in this dataset are displayed as the missing data identifier "nd" for "no data" in the BCO-DMO system.
\n* added ISO_DateTime_ISO_In from local date and time in columns.
\n* commas in comments replaced with semicolons to support csv output