Integration of technologies for understanding the functional relationship between reef habitat and fish growth and production

Functional linkage between reef habitat quality and fish growth and production has remained elusive. Most current research is focused on correlative relationships between a general habitat type and presence/absence of a species, an index of species abundance, or species diversity. Such descriptive information largely ignores how reef attributes regulate reef fish abundance (density-dependent habitat selection), trophic interactions, and physiological performance (growth and condition). To determine the functional relationship between habitat quality, fish abundance, trophic interactions, and physiological performance, we are using an experimental reef system in the northeastern Gulf of Mexico where we apply advanced sensor and biochemical technologies. Our study site controls for reef attributes (size, cavity space, and reef mosaics) and focuses on the processes that regulate gag grouper (Mycteroperca microlepis) abundance, behavior and performance (growth and condition), and the availability of their pelagic prey. We combine mobile and fixed-active (fisheries) acoustics, passive acoustics, video cameras, and advanced biochemical techniques. Fisheries acoustics quantifies the abundance of pelagic prey fishes associated with the reefs and their behavior. Passive acoustics and video allow direct observation of gag and prey fish behavior and the acoustic environment, and provide a direct visual for the interpretation of fixed fisheries acoustics measurements. New application of biochemical techniques, such as Electron Transport System (ETS) assay, allow the in situ measurement of metabolic expenditure of gag and relates this back to reef attributes, gag behavior, and prey fish availability. Here, we provide an overview of our integrated technological approach for understanding and quantifying the functional relationship between reef habitat quality and one element of production – gag grouper growth on shallow coastal reefs

Fishing Gear Modifications to Reduce Elasmobranch Mortality in Pelagic and Bottom Longline Fisheries Off Northeast Brazil

One of the biggest challenges of fisheries research is reducing the bycatch of unwanted species. The incidental fishing mortality of species with low reproductive rates, such as elasmobranchs (sharks, skates, and rays), is recognized as a key threat for their populations. In the present study, gear modifications related to the type of hook and position of the hook in the water column were tested to examine their effects on catch rates and mortality of elasmobranch species in both pelagic and coastal environments. Comparisons between circle (size 18/0, 0° offset) and J-style (size 9/0, 10° offset) hooks demonstrated that the circle hooks have a greater efficiency in reducing the mortality of most species caught, both in pelagic and coastal longline fisheries. Internal lodging of the hook was significantly less frequent for the individuals caught with circle hooks, which likely contributed to their higher survival rate at haulback. Additionally, circle hooks also increased the CPUE of elasmobranchs caught in the pelagic longline fishery, which was particularly evident for Carcharhinus falciformis and Prionace glauca. The position of the hook in the water column exhibited a strong influence on the species caught in the coastal bottom longline fishery. Suspending hooks in the middle of the water column reduced the bycatch of common demersal species, such as Carcharhinus acronotus, Ginglymostoma cirratum, and Dasyatis americana, while increasing the CPUE of potentially aggressive species, such as Galeocerdo cuvier and Carcharhinus leucas. The interaction of the type of hook utilized with its position in the water column appears to be an essential factor in the optimization of longline selectivity and minimization of bycatch mortality

Effects of Variable Flows on Water Chemistry Gradients and Fish Communities at the Hillsborough River, Florida

Abstract.-We evaluated the effects of variable flows on water chemistry and fish communities to recommend biologically based minimum flows that protect low-salinity zones for freshwater-oligohaline (FO) fishes below the Hillsborough River Dam, Tampa, Florida. We plotted the distributions of hypoxic (dissolved oxygen [DO] 4 mg/L) and meso-and polyhaline (salinity . 5%) habitats and evaluated changes in species richness and spatial distributions of FO fishes on five sampling dates from Octobe

Salinity Preference in Hatchery-Reared Juvenile Red Drum

Juvenile red drum (Sciaenops ocellatus), reared in either 15- or 30-ppt salinity seawater, were tested to determine whether they develop preference for the salinity of the water in which they were cultured. In a two-choice test, large- and small-sized juvenile red drum chose the raceway that matched the seawater in which they were cultured over the other salinity. Additional large and small fish reared in either 15- or 30-ppt salinity water were also tested following a 4-h acclimation period that simulated the duration of transport time from the hatchery to a release site. These fish also showed preference for their original culture salinity. This observed salinity preference in juvenile red drum has implications with respect to movement or residency of hatchery-reared juvenile red drum out-planted into natural coastal systems

Sampling commercial fisheries

Commercial fisheries involve the harvest and sale of a variety of wild fishes, crustaceans, mollusks, echinoderms, and other aquatic species (e.g., kelps) for a variety of uses, including food for human consumption, pet food, bait, and fish meal products. These fisheries play a vital role in the economies of many countries and provide essential nutrition for billions of people worldwide (FAO 2010). Commercial fisheries are sampled to monitor the quantity of fish caught, seasonal closures, minimum sizes, the presence of toxins, and catches of protected species. However, the most important reasons for sampling commercial fisheries are to determine if fished stocks are at sustainable abundances and if they are being harvested at sustainable levels. Basic data collected from commercial fisheries to monitor stock status include the number or weight of individuals caught, fishing effort, and biological characteristics of the catch. For some species, commercial catch data are the only data available for managing fisheries and are therefore used as indices of abundance or in simple models to monitor trends over time. In many instances, catch data are supplemented by data on the age or length of individuals so that more complex models can be used to assess stock status. For other stocks, multiple commercial fisheries using different gears, recreational or recreational-for-hire fisheries, or fisheries-independent data may exist; in such cases, commercial fisheries data are used in conjunction with these other data sources in a formal and complex process called a stock assessment (section 20.7). Because sampling of commercial fisheries is an integral part of stock assessment, it is critical that the data are collected in a scientifically valid manner

Reproductive biology of yellowfin tuna (Thunnus albacares) in the northcentral U.S. Gulf of Mexico

The reproductive biology of yellowfin tuna (Thunnus albacares) was investigated from fish collected throughout 2000–2017 in the northcentral U.S. Gulf of Mexico (GOM; n = 1135 females, 776 males), predominately from recreational anglers fishing off the Mississippi River (93 %). Histological evidence, along with mean gonadosomatic index (GSI) values, showed that peak spawning occurred from May to August, with the highest mean GSI value for both sexes observed in May (females, 1.52 %; males, 0.57 %). During the reproductive season, the amount of active spermatogenesis in spawning capable males varied monthly as observed by the progression of germinal epithelium (GE) subphases (i.e., early-GE, mid-GE, late-GE), with the mid-GE subphase observed most frequently throughout the peak spawning season. The upper and lower 95 % confidence intervals among length at 50 % maturity (L50) estimates had the largest degree of separation between the physiological (cortical alveoli, L50 =1002 ± 7.18 mm CFL) and functional maturity thresholds (primary or secondary vitellogenesis; L50 =1071 ± 4.89 mm CFL), indicating that the physiological maturity threshold should be used with caution as it may underestimate L50. Using the postovulatory follicle (POF) method, the minimum spawning interval was estimated during peak spawning months for all functionally mature females at 2.10 days, with a minimum of 17.30 % daily spawning. Batch fecundity estimates for 24 females was linearly related to size and ranged from 37,956–6.2 million eggs per batch. These data allow for U.S. GOM reproductive parameter estimates to be incorporated, for the first time, into future Atlantic yellowfin tuna stock assessments done by the International Commission for the Conservation of Atlantic Tunas.[Display omitted]•Peak spawning occurred from May-August in the northcentral Gulf of Mexico.•Under the functional maturity threshold, L50 and L95 were 1071 and 1200 ± mm CFL, respectively.•The spawning interval for all mature females in the population is estimated as 2.1 days; 17.3% were daily spawners.•Batch fecundity estimates for 24 females ranged from 37,956–6.2 million eggs per batch

Reproductive Biology of Yellowfin Tuna (\u3ci\u3eThunnus albacares\u3c/i\u3e) In the Northcentral U.S. Gulf of Mexico

The reproductive biology of yellowfin tuna (Thunnus albacares) was investigated from fish collected throughout 2000–2017 in the northcentral U.S. Gulf of Mexico (GOM; n = 1135 females, 776 males), predominately from recreational anglers fishing off the Mississippi River (93 %). Histological evidence, along with mean gonadosomatic index (GSI) values, showed that peak spawning occurred from May to August, with the highest mean GSI value for both sexes observed in May (females, 1.52 %; males, 0.57 %). During the reproductive season, the amount of active spermatogenesis in spawning capable males varied monthly as observed by the progression of germinal epithelium (GE) subphases (i.e., early-GE, mid-GE, late-GE), with the mid-GE subphase observed most frequently throughout the peak spawning season. The upper and lower 95 % confidence intervals among length at 50 % maturity (L50) estimates had the largest degree of separation between the physiological (cortical alveoli, L50 =1002 ± 7.18 mm CFL) and functional maturity thresholds (primary or secondary vitellogenesis; L50 =1071 ± 4.89 mm CFL), indicating that the physiological maturity threshold should be used with caution as it may underestimate L50. Using the postovulatory follicle (POF) method, the minimum spawning interval was estimated during peak spawning months for all functionally mature females at 2.10 days, with a minimum of 17.30 % daily spawning. Batch fecundity estimates for 24 females was linearly related to size and ranged from 37,956–6.2 million eggs per batch. These data allow for U.S. GOM reproductive parameter estimates to be incorporated, for the first time, into future Atlantic yellowfin tuna stock assessments done by the International Commission for the Conservation of Atlantic Tunas

Catch rates and size composition of blue sharks (

Distribution and relative abundance of blue sharks (Prionace glauca) in the southwestern Atlantic Ocean was modeled based on catch-per-unit-effort (CPUE) per 1000 hooks and length frequencies of blue sharks caught by the Brazilian pelagic tuna longline fleet. As a measure of relative abundance, CPUE of blue sharks caught in 58 238 fishing sets by the Brazilian pelagic tuna longline fleet (national and chartered), from 1978 to 2009, was standardized by a Generalized Linear Model (GLM) using three different approaches: i) a negative binomial error structure (log link); ii) the traditional delta lognormal model; and iii) the Tweedie distribution, recently proposed to adjust models with a high proportion of zeros. A cluster analysis using the K-means method was used to identify target species and incorporate it as a factor into the GLM. Cluster analysis grouped the data into six different fishing clusters according to the percentage of target species. Target factor (cluster) was the most important factor explaining the variance in all three CPUE models. The Tweedie model showed a relatively better fit compared to the other models. Blue shark nominal and standardized CPUE showed a relatively stable trend from 1978 to 1995. From 1995 onwards, however, there was an increasing trend in the standardized CPUE, up to a maximum value in 2008. In general, nominal CPUE and standardized CPUE tracked well up until 2000, after which standardized CPUE’s values were at a noticeably lower level than nominal CPUE. Length frequency data were analyzed for 11 932 blue sharks measured as part of the Brazilian onboard observer program operating on the pelagic tuna longline fleet between 2006 and 2008, with sizes ranging from 91 to 224 cm fork length. Overall, blue shark size data showed clear spatial and seasonal distributions for males and females in the southwestern Atlantic Ocean, with juveniles predominantly concentrated in the most southerly latitudes

Appendix A. Procedures for using the fitted linear model to predict mean gag abundances.

Procedures for using the fitted linear model to predict mean gag abundances