Regional differences in energy allocation of black sea bass (Centropristis striata) along the U.S. Northeast Shelf (36°N to 42°N) and throughout the spawning season

Abstract

Fish reproduction is energetically costly, leading to a suite of energy allocation strategies for maximizing lifetime reproductive potential. Assessing energetic allocation for species that inhabit a wide distributional range can provide insight into different strategies found across individuals and populations. The Northern stock of black sea bass (Centropristis striata) inhabits the U.S. Northeast continental shelf from Cape Hatteras, NC, to the Gulf of Maine, and spawns inshore throughout this distribution from April to October. To assess energy allocation towards spawning, C. striata were collected in four regions across this distribution and throughout their spawning season. By assessing energetic allocation (lipid, energy density and total energy) in muscle, liver and gonad tissues, C. striata were identified as mixed breeders because while they mobilized somatic energy stores towards reproductive development, they also used energy acquired from their diet to sustain reproductive output throughout the spawning season. Unlike male fish, female fish both invested more energy into liver and gonad tissues and exhibited regional differences in energetic values. For both sexes, C. striata in the northern portion of the distribution had lower energetic values both in the somatic stores and towards gonadal development than the fish in the southern portion of the distribution, possibly because of longer migration distance. Overall, the authors found significant spatial variation in energetic constraints that may affect reproductive output and success (recruitment), a relevant result as C. striata are a popular recreational and commercial species throughout this distribution.

Temperature‐ and ration‐dependent winter growth in northern‐stock Black Sea Bass juveniles

“…The front could move further inshore with the increasing frequency of warm core rings (Gawarkiewicz et al 2018;Forsyth et al 2020;Silver et al 2023). Thus, Black Sea Bass offshore winter migrations might progressively become shorter in duration and distance, which would decrease energetic costs and may further fuel the expansion of the northern Black Sea Bass stock (Miller et al 2016;Slesinger et al 2022).…”

“…2020; Slesinger et al. 2021, 2022). While pertinent work on this most northern stock contingent has occurred, we still lack important baseline data for the expanding northern Black Sea Bass stock, especially for early life stages and juveniles.…”

“…The expansion of the northern Black Sea Bass stock has also led to more ecological studies in recent years (La Rosa et al 2020;Wiernicki et al 2020;Secor et al 2021), resulting in added research on the contingent north of the Hudson Canyon (Wuenschel et al 2013;McMahan et al 2020;Slesinger et al 2021Slesinger et al , 2022. While pertinent work on this most northern stock contingent has occurred, we still lack important baseline data for the expanding northern Black Sea Bass stock, especially for early life stages and juveniles.…”

Variation in energy density of northwest Atlantic forage species: Ontogenetic, seasonal, annual, and spatial patterns

“…The solvent used for lipid extraction in PCA can affect the lipids and fats removed (e.g., polar versus nonpolar), thereby affecting overall energy estimates. We chose petroleum ether as the solvent (Dobush et al 1985), and we used the specific energy equivalents recommended by Henken et al (1986), which produce results most comparable to those from bomb calorimetry, as have been used in numerous applications to fish (Morley et al 2012;Schloesser and Fabrizio 2015;Slesinger et al 2022). One distinction between the two methods is that carbohydrates are generally ignored as a negligible fraction of fish and squid when using PCA (i.e., all lipid-free organic matter that is combusted is assumed to be protein).…”

“…In order for bioenergetics models to accurately assess the effects of natural environmental fluctuations and to understand how anthropogenic pressures may impact predator-prey interactions (Bailey and Robison 1986;Pedersen and Hislop 2001;Albo-Puigserver et al 2017), the variation in ED (the currency of such models) must be understood and quantified (Arrhenius and Hansson 1996;Anthony et al 2000;Brownscombe et al 2022). The ED of fishes-and, thus, the energy available to higher trophic levels-can vary in relation to migrations (Pedersen and Hislop 2001;Hedeholm et al 2011;Albo-Puigserver et al 2017), ontogeny (Johnson et al 1999;Wuenschel et al 2006;Morley et al 2007), reproductive state (Craig 1977;Alonso-Fernandez and Saborido-Rey 2012;Slesinger et al 2022), and season (Garvey and Marschall 2003;Albo-Puigserver et al 2017;Forzono et al 2017;Campanini et al 2021). This variation in ED is partially driven by environmental factors (e.g., temperature and primary productivity) at local or regional scales, and the time series of data needed to establish such linkages are usually lacking.…”