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We conducted a meta-analysis to summarize current knowledge on the effects of environmental and ecological drivers on the abundance of red snapper (Lutjanus campechanus) within the U.S. Gulf of Mexico. We reviewed 1252 published research articles and extracted or calculated effect sizes for 12 drivers from 82 independent studies within 26 articles that met our inclusion criteria. We used a fixed-effect model to calculate the absolute value of the mean effect size of each driver by age class studied and pooled across age classes to estimate effects on the overall abundance of red snapper. Habitat complexity and intra-specific competition had large effects on overall abundance and juvenile abundance, while habitat type and protection from predators showed medium to large effects on age 0 recruits and juvenile red snapper, and the mean effect of all drivers studied for adult red snapper were small or had no effect on abundance. Our results provide systematic support for the role of density-dependent mechanisms (habitat quality and availability, competition, predation) in shaping the regional abundance of red snapper, particularly during the juvenile stages. Sensitivity analyses indicated that issues with non-independence (e.g. within-article correlation), between-study heterogeneity, and publication bias influenced the magnitude and certainty of effect size estimates in a subset of drivers. Thus, our meta-analytical review also highlights the need for more empirical research on certain drivers (e.g. temperature, hypoxia) to improve our understanding of the factors that shape the regional abundance of red snapper.

Chemical contaminants present in the environment can affect mitochondrial bioenergetics in aquatic organisms and can have substantial effects on individual fitness. As early life stages of fish are particularly vulnerable to environmental contaminants, they are ideal models for examining the relationship between impaired mitochondrial bioenergetics (ATP-dependent respiration, basal oxidative respiration) and apical endpoints such as growth. Here, early life stages of the fathead minnow (Pimephales promelas), an ecologically relevant North American species, were used to investigate the relationship between mitochondrial bioenergetics and growth following perturbation with model mitochondrial toxicants 2,4-dinitrophenol and octylamine. Fathead minnows were exposed to 2,4-dinitrophenol and octylamine at 3 concentrations for 24 h and endpoints related to mitochondrial bioenergetics were measured with the Agilent Seahorse XFe24 Bioanalyzer. In order to link changes in mitochondrial bioenergetics to growth, fathead minnows were exposed to the same chemical contaminants for 7–14 days and growth was measured by measuring total length on a weekly basis. There was a significant correlation between decrease in average length at 14 days and basal respiration (r = 0.997, p = 0.050, n = 3), as well as maximal respiration (r = 0.998, p-value = 0.043, n = 3) for embryos exposed to 2,4 dinitrophenol. For octylamine, ATP production was highly correlated with average length at 7 days (p-value = 0.1) and spare respiratory capacity and average length at 14 days were highly correlated (p-value = 0.1). These data improve understanding of how mitochondrial toxicants impair growth in fish larvae and may be useful for developing an adverse outcome pathway for growth.

Phenols are classified as polar narcotics, which are thought to cause toxicity by non-specific mechanisms, possibly by disrupting membrane structure and function. Here we test three phenolic chemicals, phenol, 2,4-dichlorphenol and pentachlorophenol on embryo development, heartbeat rate and mitochondrial respiration in fathead minnow (Pimephales promelas). While these chemicals have been used on isolated mitochondria, they have not yet been used to verify respiration in intact embryos. Mitochondrial respiration in intact embryos was measured after optimizing the Seahorse XFe24 Extracellular Flux Analyzer. Heartbeat rate and mitochondrial respiration patterns of fathead minnow embryos at different developmental stages were also characterized. Exposures of embryos at developmental stage 20 occurred for 24 h with five concentrations of each phenolic compound ranging from 0.85 to 255 μM for phenol, 0.49 to 147 μM for 2,4-dichlorophenol and 0.3 to 90 μM for pentachlorophenol. Exposure to phenol at the concentrations tested had no effects on development, heartbeat or mitochondrial respiration. However, both 2,4-dichlorophenol and pentachlorophenol showed dose-dependent effects on development, heartbeat rate, and mitochondrial respiration, with the effects occurring at lower concentrations of pentachlorophenol, compared to 2,4-dichlorophenol, highlighting the higher toxicity of the more chlorinated phenols. Both 2,4-dichlorophenol and pentachlorophenol decreased basal mitochondrial respiration of embryos and ATP production. These results indicate that higher chlorinated phenolic chemicals cause developmental toxicity in fathead minnow embryos by decreasing mitochondrial respiration and heartbeat rate.

Estimating the growth of fishes is critical to understanding their life history and conducting fisheries assessments. It is imperative to sufficiently sample each size and age class of fishes to construct models that accurately reflect biological growth patterns, but this may be a challenging endeavor for highly-exploited species in which older fish are rare. Here, we use the Gulf Corvina (Cynoscion othonopterus), a vulnerable marine fish that has been persistently overfished for two decades, as a model species to compare the performance of several growth models. We fit the von Bertalanffy, Gompertz, logistic, Schnute, and Schnute–Richards growth models to length-at-age data by nonlinear least squares regression and used simple indicators to reveal biased data and ensure our results were biologically feasible. We then explored the consequences of selecting a biased growth model with a per-recruit model that estimated female spawning-stock-biomass-per-recruit and yield-per-recruit. Based on statistics alone, we found that the Schnute–Richards model described our data best. However, it was evident that our data were biased by a bimodal distribution of samples and underrepresentation of large, old individuals, and we found the Schnute–Richards model output to be biologically implausible. By simulating an equal distribution of samples across all age classes, we found that sample distribution distinctly influenced model output for all growth models tested. Consequently, we determined that the growth pattern of the Gulf Corvina was best described by the von Bertalanffy growth model, which was the most robust to biased data, comparable across studies, and statistically comparable to the Schnute–Richards model. Growth model selection had important consequences for assessment, as the per-recruit model employing the Schnute–Richards model fit to raw data predicted the stock to be in a much healthier state than per-recruit models employing other growth models. Our results serve as a reminder of the importance of complete sampling of all size and age classes when possible and transparent identification of biased data when complete sampling is not possible.