Suspension feeding by Xestospongia muta was investigated in situ on Conch Reef (24\u00b056\u201959\u201dN; 80\u00b027\u201913\u201dW), Key Largo, Florida in June of 2013. Food availability is known to vary temporally on Conch Reef (e.g. McMurray et al. 2016); therefore, a total of 32 individuals were haphazardly selected for study at 20 m depth over the course of 6 days (5-6 sponges day-1) to quantify feeding rates over a large natural range of food abundances. Individuals spanned a broad range of sizes, however only individuals with a single osculum were included.
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A total of 1 L of both incurrent (ambient) and excurrent seawater was collected from each sponge over a 5 minute sampling interval with paired 100 mL syringes as previously described (McMurray et al. 2016). Following seawater sample collection, the dimensions of each sponge were measured and the morphology of X. muta was approximated as a frustum of a cone to obtain sponge volume estimates (McMurray, Blum & Pawlik 2008). Estimates of sponge pumping rates were derived from the equation Q = 0.02 V1.1 (P < 0.001, R2 = 0.78; McMurray et al. 2014), where Q is the pumping rate (ml s-1) and V is sponge volume (cm3)
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Particulate and dissolved organic carbon (POC and DOC, respectively) in incurrent and excurrent seawater was quantified as previously described (McMurray et al. 2016). Briefly, each sample was filtered through a 100 \u03bcm mesh and subsequently through a pre-combusted GF/F glass fiber filter. In the laboratory, POC on filters was measured using a CE Elantech NC2100 elemental analyzer; DOC in filtrate samples was measured using high temperature catalytic oxidation with a Shimadzu TOC 5050 analyzer. Xestospongia muta hosts symbiotic microbes which may contribute to DOC retention rates (Maldonado, Ribes & van Duyl 2012); therefore carbon flux estimates reported here consider the sponge as a holobiont.
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To assess the effects of sponge feeding on POC and DOC, differences in the concentration of each food type between incurrent and excurrent seawater were analyzed using paired t-tests. For each sponge, POC and DOC consumed were calculated as the difference between the quantities of each food resource in incurrent and excurrent seawater samples. To investigate selective feeding on food resource types, and if relative foraging effort between food resources varied as a function of relative food availability (McMurray et al. 2016), the log10-transformed ratio of POC:DOC consumed was regressed against the log10-transformed ratio of incurrent POC:DOC concentration (van Leeuwen et al. 2013). A one-tailed t-test was used to test if the slope of this regression was greater than a slope of 1 to examine frequency-dependent food consumption.
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Retention efficiency of each food resource was calculated as:
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RE =\u00a0(Cin\u00a0-\u00a0Cex)/Cin x 100
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where RE is the retention efficiency (%), and Cin and Cex are the incurrent and excurrent quantities of each food resource (\u03bcM), respectively. The filtration rate for each food resource was calculated as:\u00a0
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FR = (Cin\u00a0-\u00a0Cex) x Q
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where FR is the filtration rate (\u03bcmol C s-1). Ordinary least squares regression was used to examine how filtration rates for each food resource scaled with sponge size. Filtration rates were standardized by sponge volume to obtain specific filtration rates (\u03bcmol C s-1 L-1). The relationship between specific filtration rate and loge-transformed incurrent food abundance for each food resource was described by ordinary least squares regression.
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These data\u00a0were published in:
\nMcMurray, S.E. 2015. The Dynamics of Sponge Populations and Benthic-pelagic Carbon Flux on Coral Reefs. Ph.D. Dissertation. University of North Carolina Wilmington.
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Analyses were conducted with SAS (version 9.1.3 for Windows; SAS Institute) and SPSS (version 14.0.0 for Windows; SPSS) statistical software.
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BCO-DMO Processing Notes:
\n- added conventional header with dataset name, PI name, version date
\n- modified parameter names to conform with BCO-DMO naming conventions
\n- re-formatted date from m/d/yyyy to yyyy-mm-dd
\n- replaced DOCre (proportion) data with data*100 (percent)