University of South Florida St. Petersburg

Abstract Accurate estimation of post-release survival is fundamental to fisheries stock assessment and effective management. Conventional tag-return studies and acoustic telemetry are commonly used to estimate this probability, yet each approach has limitations when applied independently. Using gag ( Mycteroperca microlepis ) as a case study, we integrated data from a large-scale conventional tagging program and an acoustic telemetry experiment within a discrete-time statistical modeling framework that links relative recapture risk with telemetry-derived fate. This approach enabled estimation of post-release survival across a broad gradient of capture depths representative of recreational fishing conditions. Estimated survival was high in shallow waters (≈97%) but declined with increasing capture depth, consistent with depth-related barotrauma. Applying model predictions to depth distributions from the recreational fishery yielded annual and monthly post-release survival probabilities. Annual estimates were consistent with values assumed in recent stock assessments, while monthly values highlighted seasonal patterns potentially relevant for management. This integrated framework advances post-release survival estimation by combining the extensive sample sizes and environmental coverage characteristic of conventional tagging data with the direct fate observations provided by acoustic telemetry, and offers a transferable approach for other highly targeted fisheries.

This study challenges widely held metabolic theory, which suggests that whole-animal metabolic rates increase with temperature because of its universal effects on the kinetics of the underlying biochemical reactions. Here, we show that metabolic rates across flatfish species are largely invariant from poles to the equator, which points to an explanation for interspecific thermal sensitivity based on ecology and evolution rather than thermodynamic constraints. The explanation proposed here is that warm water provides a thermodynamic opportunity, not a mandate, for metabolic rate escalation when required for predator-prey interactions. Flatfish do not require metabolic escalation because of their reliance on camouflage that mitigates the greater predation intensity in tropical waters. These findings have strong implications for models attempting to diagnose the response of organisms to climate change and for macroecological patterns more generally.

Phytoplankton blooms, defined as a periods of high biomass, are key indicators of climate-driven ocean responses. Shifts in their timing and magnitude can substantially alter the marine ecosystem, yet the environmental regimes governing bloom development remain poorly constrained. We analyzed long-term environmental data (2003-2023) from the Central Yellow Sea (CYS) to decode the drivers of the spring phytoplankton bloom (SPB), which is defined into four developmental stages based on changes in chlorophyll-a (Chl-a). A machine-learning decision tree (DT) was employed to identify specific quantitative critical thresholds associated with each phase. Results show that the SPB initial stage represented low-light intensity in early-April. The peak stage was determined by strong-light intensity; thus, the Chl-a increased rapidly in mid-April. The decline stage corresponded to a high sea surface temperature (SST[Formula: see text]14.40 °C) in May, while the termination stage indicated no SPB occurrence after late-May due to very-high SST ([Formula: see text]17.27 °C). We classified four SPB types from phenology and discussed the unique environmental characteristics of each type. SPB peak timing is set by the coupled physical oceanic structure (SST-mixing-light), whereas atmospheric inputs modulate bloom magnitude. The study provides a consistent baseline and a physically interpretable phenology-threshold approach for integrated interpretation of timing and conditions.

Abstract. When coastal and river floods occur concurrently or in close succession, they can cause a compound flood with significantly higher impacts. While our understanding of compound flooding has improved over the past decade, no studies to date have assessed the spatial correlation of compound flooding. To address this gap, we develop a framework that captures dependence between coastal total water level and river discharge across a set of locations along the US coastline. Using 41 years of observed data from 41 station combinations, we stochastically model 10 000 years of spatially-joint events of extreme sea level and river discharge based on their dependence structure and cooccurrence rate. We define potential compound flooding as events in which both drivers exceed their respective 99th percentile thresholds. Results based on our simulated large event set show that the US West coast shows high spatial correlation of potential compound flooding. Among all three coasts, the West coast has the highest frequency of widespread potential compound flooding, with around 50 % of compound events arising at multiple locations simultaneously. We identify two clusters with mutually high joint occurrence rates of simultaneous compound events on this coast, namely (1) Charleston – Crescent City – North Spit, and (2) Santa Monica – Los Angeles – La Jolla. Widespread compound events are less frequent on the East coast where approximately 30 % of potential compound flooding may affect multiple locations. Moderate spatial dependence is observed in the central region and weaker spatial dependence for the remaining locations on this coast. In contrast, the Gulf coast shows the weakest spatial correlation, where over 82 % of compound events only affect single locations. Our findings highlight the importance of accounting for spatial dependence in compound flood assessments. Our large set of stochastic spatially-joint events can be used as boundary conditions for the hydrologic-hydraulic models to simulate the surface inundation and further assess risks of compound flooding in low-lying coastal and estuarine areas.

Abstract. Nickel (Ni) is an essential micronutrient for marine microorganisms, being involved in enzymes controlling the nitrogen cycle and metabolic responses to oxidative stress. In this study, we examine the covariation between the abundance of Ni-related enzymes and Ni isotope fractionation. To do so, dissolved Ni concentrations and isotope compositions are presented together with metagenomics on samples from the Antarctic Circumnavigation Expedition. Overall, results reveal lower Ni concentrations and higher δ60Ni values in surface waters north of the Sub-Antarctic Front compared to southerly stations. One exception is seen near the high-latitude Mertz Glacier, where the systematics between Ni and δ60Ni better resemble those of low-latitude stations. Relative abundances of urease and Ni-SOD in metagenomes are found to correlate with δ60Ni, potentially suggesting preferential biological uptake of Ni by the organisms using these enzymes. We find a particularly high abundance of urease in diatoms and alphaproteobacteria near the Mertz Glacier, matching the surprisingly high δ60Ni. We thus hypothesise that urea could serve as a nitrogen source for microbial organisms in the late stage of polynya diatom blooms, perhaps causing the observed Ni drawdown and isotope fractionation. This study represents an initial exploration of the influence of biological processes on Ni and δ60Ni distributions. It constitutes a first step towards the further analyses (e.g., culture experiments and metatranscriptomics) needed to determine which exact processes lead to the δ60Ni biogeochemical divide observed between low-latitude and high-latitude waters.

Abstract. A new series of mascons are made from GRACE and GRACE-FO data, specifically designed for use by oceanographers interested in studying variations in ocean mass transport and circulation. This series has pre-removed those changes in ocean mass distribution caused by barystatic gravity, rotation, and deformation (GRD) signals, as well as the non-oceanographic signals caused by four major oceanic earthquakes, neither of which impact circulation. Subtle changes in the processing and regularization schemes also help reduce the visibility of instrument/orbital errors in the ocean signal, particularly in the arctic and near the sites of the removed earthquakes. The primary benefit of this data set is increased ease of use for researchers interested in ocean dynamics, as the product is designed to be used "off the shelf" with no additional corrections required, even by those less familiar with GRACE data usage. The complete dataset is available at https://doi.org/10.18738/T8/3VUPEW (Pie et al., 2025).