ScanFish Optical Plankton Counter (OPC) data from R/V Pelican cruises PE03-NGOMEX, PE04-NGOMEX, PE06-NGOMEX, PE07-NGOMEX, PE09-05, and PE11-06 in the Northern Gulf of Mexico between 2003 and 2010

Dataset: ScanFish OPCAn optical plankton counter (OPC) and CTD mounted to a ScanFish platform were towed and undulated behind the R/V Pelican during cruises PE03-NGOMEX, PE04-NGOMEX, PE06-NGOMEX, PE07-NGOMEX, PE09-05, and PE11-06 in the Northern Gulf of Mexico between 2003 and 2010. CTD and MIDAS data were synchronized and merged with simultaneously collected OPC data and aggregated into 1 second time bins. Bottom depth was obtained from the NOAA NCEI coastal relief model. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/746081NSF Division of Ocean Sciences (NSF OCE) OCE-1043261, NSF Division of Ocean Sciences (NSF OCE) OCE-1043248, NSF Division of Ocean Sciences (NSF OCE) OCE-1043249, National Oceanic and Atmospheric Administration (NOAA) NA06NOS4780148, National Oceanic and Atmospheric Administration (NOAA) NA09NOS4780198, Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (GRP) NAS-GRP-200000641

Mesozooplankton sample data from R/V Pelican cruises PE03-NGOMEX, PE04-NGOMEX, PE06-NGOMEX, PE07-NGOMEX, PE09-05 in the Northern Gulf of Mexico from 2003-2008

Dataset: Pump mesozooplankton samplesCTD casts using a high-capacity, diaphragm pump were conducted during the R/V Pelican cruises PE03-NGOMEX, PE04-NGOMEX, PE06-NGOMEX, PE07-NGOMEX, and PE09-05 in the Northern Gulf of Mexico between 2003 and 2008. Plankton samples were collected from discrete depths during the CTD casts. Subsamples of sample contents were manually counted, identified, and measured in the laboratory. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/746107NSF Division of Ocean Sciences (NSF OCE) OCE-1043261, NSF Division of Ocean Sciences (NSF OCE) OCE-1043248, NSF Division of Ocean Sciences (NSF OCE) OCE-1043249, National Oceanic and Atmospheric Administration (NOAA) NA06NOS4780148, National Oceanic and Atmospheric Administration (NOAA) NA09NOS4780198, Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (GRP) NAS-GRP-200000641

Life in the fast lane: Revisiting the fast growth—High survival paradigm during the early life stages of fishes

Early life survival is critical to successful replenishment of fish populations, and hypotheses developed under the Growth-Survival Paradigm (GSP) have guided investigations of controlling processes. The GSP postulates that recruitment depends on growth and mortality rates during early life stages, as well as their duration, after which the mortality declines substantially. The GSP predicts a shift in the frequency distribution of growth histories with age towards faster growth rates relative to the initial population because slow-growing individuals are subject to high mortality (via starvation and predation). However, mortality data compiled from 387 cases published in 153 studies (1971–2022) showed that the GSP was only supported in 56% of cases. Selection against slow growth occurred in two-thirds of field studies, leaving a non-negligible fraction of cases showing either an absence of or inverse growth-selective survival, suggesting the growth-survival relationship is more complex than currently considered within the GSP framework. Stochastic simulations allowed us to assess the influence of key intrinsic and extrinsic factors on the characteristics of surviving larvae and identify knowledge gaps on the drivers of variability in growth-selective survival. We suggest caution when interpreting patterns of growth selection because changes in variance and autocorrelation of individual growth rates among cohorts can invalidate fundamental GSP assumptions. We argue that breakthroughs in recruitment research require a comprehensive, population-specific characterization of the role of predation and intrinsic factors in driving variability in the distribution and autocorrelation of larval growth rates, and of the life stage corresponding to the endpoint of pre-recruited life. -- Keywords : critical period ; growth-mortality ; individual characteristics ; larval physiology ; predation ; recruitment endpoint

Behavior and Transport of Pelagic Coral Reef Fish Larvae in the Straits of Florida

The supply of coral reef fish larvae from the open ocean to reefs is vital for the persistence of local fish populations. Whether larvae are dispersed over hundreds of km or only few km depends on biophysical interactions between larvae and their environment. Relationships between environmental variables, larval swimming behavior, and larval transport were examined for reef fish larvae in the Florida Straits. In a series of research cruises, the upper 100 m of the water column was sampled with plankton nets fishing at four different depths. Variability in the vertical distributions of most larvae was not consistently related to measured environmental variables. Relative densities of larvae were predictably related to sampling depth in five taxa. In seven taxa, more developed larvae were distributed significantly deeper than less developed larvae, revealing ontogenic vertical migrations. In three taxa, vertical distributions varied significantly between day and night, revealing diel migrations. Since the Florida Current was strongest near the surface, observed vertical distributions and migrations resulted in reduced larval transport relative to surface currents. To identify cues involved in regulating vertical distributions, behavioral experiments were conducted with larvae from four reef fish families. All four groups showed significant responses to pressure cues, swimming up in response to high pressure and down in response to low pressure. In two families there was a significant correlation between capture depth and experimental pressure preference, suggesting that larvae use similar behavior to regulate depth in situ. To study horizontal swimming behavior, late-stage larvae of one species were caught in light-traps and observed by SCUBA divers ~1 km offshore of the Florida Keys barrier reef. All larvae swam remarkably straight, but their swimming directions were distributed randomly. A simulation model was used to generate swimming trajectories of longer duration than could be observed directly. Observed and simulated trajectories indicated that horizontal swimming by larvae with or without an external reference frame was important at spatial scales of several km. Overall, some larvae exercised a strong influence on transport, either by vertical or horizontal swimming. Behaviors varied between species and families, highlighting the need for more species-specific data

A Day in the Life of Fish Larvae: Modeling Foraging and Growth Using Quirks

<div><p>This article introduces “Quirks,” a generic, individual-based model synthesizing over 40 years of empirical and theoretical insights into the foraging behavior and growth physiology of marine fish larvae. In Quirks, different types of larvae are defined by a short list of their biological traits, and all foraging and growth processes (including the effects of key environmental factors) are modeled following one unified set of mechanistic rules. This approach facilitates ecologically meaningful comparisons between different species and environments. We applied Quirks to model young exogenously feeding larvae of four species: 5.5-mm European anchovy (<i>Engraulis encrasicolus</i>), 7-mm Atlantic cod (<i>Gadus morhua</i>), 13-mm Atlantic herring (<i>Clupea harengus</i>), and 7-mm European sprat (<i>Sprattus sprattus</i>). Modeled growth estimates explained the majority of variability among 53 published empirical growth estimates, and displayed very little bias: 0.65%±1.2% d⁻¹ (mean ± standard error). Prey organisms of ∼67% the maximum ingestible prey length were optimal for all larval types, in terms of the expected ingestion per encounter. Nevertheless, the foraging rate integrated over all favorable prey sizes was highest when smaller organisms made up >95% of the prey biomass under the assumption of constant normalized size spectrum slopes. The overall effect of turbulence was consistently negative, because its detrimental influence on prey pursuit success exceeded its beneficial influence on prey encounter rate. Model sensitivity to endogenous traits and exogenous environmental factors was measured and is discussed in depth. Quirks is free software and open source code is provided.</p></div

Quirks model equations.

a<p>“∨” denotes the “max” function operator (e.g., 1 ∨ 2 = 2).</p>b<p>“∧” denotes the “min” function operator (e.g., 1 ∧ 2 = 1).</p>c<p>Based on 0.04 to 2 mm protist plankton and copepods <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-Uye1" target="_blank">[39]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-MendenDeuer1" target="_blank">[42]</a>.</p>d<p>Numerically maximized assuming optimal diet composition.</p>e<p>Primarily based on zooplankton <1 mm <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-Buskey1" target="_blank">[104]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-Titelman1" target="_blank">[105]</a>.</p>f<p>1.62≈55/18 of the universal Kolmogorov constant <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-Kolmogorov1" target="_blank">[44]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098205#pone.0098205-Yeung1" target="_blank">[47]</a>.</p

Ranges (%) of individual parameter perturbations resulting in <10% change in modeled growth potential of North Sea anchovy (<i>Engraulis encrasicolus</i>), cod (<i>Gadus morhua</i>), autumn-spawned herring (<i>Clupea harengus</i>), and sprat (<i>Sprattus sprattus</i>) larvae.

a<p>Perturbations with respect to temperature in °C.</p

Summary statistics quantifying model skill in matching published larval fish growth rates.

<p>Summary statistics quantifying model skill in matching published larval fish growth rates.</p

List of studies used to validate Quirks growth rate estimates.

<p>OIN: otolith increment number, OS: otolith size.</p

Optimal foraging conditions for the indicated sizes of anchovy (<i>Engraulis encrasicolus</i>), cod (<i>Gadus morhua</i>), herring (<i>Clupea harengus</i>), and sprat (<i>Sprattus sprattus</i>) larvae.

<p><i>L</i>: standard length, <i>l</i>: prey length, <i>s</i>: normalized size spectrum slope, <i>ε</i>: Turbulent kinetic energy dissipation rate.</p