Cyanide fishing is a method employed to capture marine fish alive on coral reefs. They are shipped to markets for human consumption in Southeast Asia, as well as to supply the marine aquarium trade worldwide. Although several techniques can be used to detect cyanide in reef fish, there is still no testing method that can be used to survey the whole supply chain. Most methods for cyanide detection are time-consuming and require the sacrifice of the sampled fish. Thiocyanate anion (SCN−) is a metabolite produced by the main metabolic pathway for cyanide anion (CN−) detoxification. Our study employed an optical fiber (OF) methodology (analytical time <6 min) to detect SCN− in a non-invasive and non-destructive manner. Our OF methodology is able to detect trace levels (>3.16 µg L−1) of SCN− in seawater. Given that marine fish exposed to cyanide excrete SCN− in the urine, elevated levels of SCN− present in the seawater holding live reef fish indicate that the surveyed specimens were likely exposed to cyanide. In our study, captive-bred clownfish (Amphiprion clarkii) pulse exposed for 60 s to either 12.5 or 25 mg L−1 of CN− excreted up to 6.96±0.03 and 9.84±0.03 µg L−1 of SCN−, respectively, during the 28 days following exposure. No detectable levels of SCN− were recorded in the water holding control organisms not exposed to CN−, or in synthetic seawater lacking fish. While further research is necessary, our methodology can allow a rapid detection of SCN− in the holding water and can be used as a screening tool to indicate if live reef fish were collected with cyanide.

Catch per unit effort (CPUE) was computed from fisheries‐independent monitoring data collected from 1996 through 2013 in the lower Peace River and Charlotte Harbor, Florida. Seasonal habitat suitability modeling (HSM) based on delta‐gamma generalized additive models was prepared for eight fish and invertebrate species life stages with affinities for either low or moderate salinities. Using a geographic information system, habitat maps were created from monitoring data for temperature, salinity, dissolved oxygen, depth, and bottom type in the study area. Gear‐corrected CPUEs derived from HSM were applied to corresponding habitat grid cells. Seasonal HSM maps were then created, depicting the spatial distribution and relative abundance for early juvenile, juvenile, and adult life stages. By overlaying Optimum abundance zones from each HSM map onto corresponding salinity grids, the preferred ranges of salinity were found to be similar between seasons for each of six estuarine‐resident species life stages. This implies that each resident species occupies a unique salinity range in the river and estuary, which varies little between seasons. During the summer wet season, the geographic ranges occupied by each resident species life stage expanded in response to increased inflow, while the preferred salinity ranges occupied were similar between seasons. However, this was not the case for the two estuarine‐transient species (Red Drum Sciaenops ocellatus and Spot Leiostomus xanthurus), which tended to utilize different salinity ranges between seasons. Habitat‐based population estimates were prepared for each species life stage by using the predicted CPUE grids used to create the HSM maps. The demonstrated methods support ecosystem‐based fishery management and management of freshwater inflow to tidal rivers.

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In this article, we present an approach based on generalized additive models (GAMs) to predict species’ distributions and abundance in Florida estuaries with habitat suitability modeling. Environmental data gathered by fisheries‐independent monitoring in Tampa Bay from 1998 to 2008 were interpolated to create seasonal habitat maps for temperature, salinity, and dissolved oxygen and annual maps for depth and bottom type. We used delta‐GAM models assuming either zero‐adjusted gamma or beta‐inflated‐at‐zero distributions to predict catch per unit effort (CPUE) from five habitat variables plus gear type for each estuarine species by life stage and season. Bottom type and gear type were treated as categorical predictors with reference parameterization. Three spline‐fitting procedures (the penalized B‐spline, cubic smoothing spline, and restricted cubic spline) were applied to the continuous predictors. Two additive, linear submodels on the log and logistic scales were used to predict CPUEs >0 and CPUEs = 0, respectively, across environmental gradients. The best overall model among those estimated was identified based on the lowest Akaike information criterion. A stepwise routine was used to omit continuous predictors that had little predictive power. The model developed was then applied to interpolated habitat data to predict CPUEs across the estuary using GIS. The statistical models, coupled with the use of GIS, provide a method for predicting spatial distributions and population numbers of estuarine species’ life stages. An example is presented for juvenile pink shrimp Farfantepenaeus duorarum during the summer in Tampa Bay, Florida. Received February 10, 2015; accepted August 11, 2015

Malate dehydrogenase (MDH) electrophoretic mobility patterns were used as a standard against which field methods involving anal fin ray counts (AFCs) and extrinsic gasbladder muscle (EGM) rib passage patterns were compared to separate the beaked redfish species, Sebastes fasciatus and S. mentella. The frequencies of MDH-A phenotypes were determined for 1125 beaked redfish examined from a winter survey in 1983 and 376 from a summer survey in 1984. Allele frequencies were calculated from the MDH-A phenotypic data for the winter survey. The low mobility of the A2 phenotype was characteristic of 90% of S. fasciatus sampled at depths < 320 m in winter and at depths < 250 m in summer. The high-mobility A1 and heterozygotic A1/A2 phenotypes were prevalent in 95% of S. mentella sampled below these depths. The mobility patterns agreed with predominant AFCs ([Formula: see text] for S. fasciatu[Formula: see text] for S. mentella) for all stations in the deep and shallow zones. The MDH mobility patterns showed 93% agreement with EGM patterns for S. fasciatus but only 53% agreement for S. mentella. An overlap of AFCs, of main EGM patterns, and of tendon to vertebrae attachments and the variation from set to set in A1/A2 heterozygotic phenotypes suggest that these species hybridize in the Gulf of St. Lawrence.