Orientation Behavior in Fish Larvae: A Missing Piece to Hjort\u27s Critical Period Hypothesis

Larval reef fish possess considerable swimming and sensory abilities, which could enable navigation towards settlement habitat from the open ocean. Due to their small size and relatively low survival, tagging individual larvae is not a viable option, but numerical modeling studies have proven useful for understanding the role of orientation throughout ontogeny. Here we combined the theoretical framework of the biased correlated random walk model with a very high resolution three-dimensional coupled biophysical model to investigate the role of orientation behavior in fish larvae. Virtual larvae of the bicolor damselfish (Stegastes partitus) were released daily during their peak spawning period from two locations in the Florida Keys Reef Tract, a region of complex eddy fields bounded by the strong Florida Current. The larvae began orientation behavior either before or during flexion, and only larvae that were within a given maximum detection distance from the reef were allowed to orient. They were subjected to ontogenetic vertical migration, increased their swimming speed during ontogeny, and settled on reefs within a flexible window of 24 to 32 days of pelagic duration. Early orientation, as well as a large maximum detection distance, increased settlement, implying that the early use of large-scale cues increases survival. Orientation behavior also increased the number of larvae that settled near their home reef, providing evidence that orientation is a mechanism driving self-recruitment. This study demonstrates that despite the low swimming abilities of the earliest larval stages, orientation during this critical period would have remarkable demographic consequences

Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean

Pelagic organisms' movement and motion of buoyant particles are driven by processes operating across multiple, spatial and temporal scales. We developed a probabilistic, multi-scale model, the Connectivity Modeling System (CMS), to gain a mechanistic understanding of dispersion and migration processes in the ocean. The model couples offline a new nested-grid technique to a stochastic Lagrangian framework where individual variability is introduced by drawing particles' attributes at random from specified probability distributions of traits. This allows 1) to track seamlessly a large number of both actively swimming and inertial particles over multiple, independent ocean model domains and 2) to generate ensemble forecasts or hindcasts of the particles' three dimensional trajectories, dispersal kernels, and transition probability matrices used for connectivity estimates. In addition, CMS provides Lagrangian descriptions of oceanic phenomena (advection, dispersion, retention) and can be used in a broad range of oceanographic applications, from the fate of pollutants to the pathways of water masses in the global ocean. Here we describe the CMS modular system where particle behavior can be augmented with specific features, and a parallel module implementation simplifies data management and CPU intensive computations associated with solving for the tracking of millions of active particles. Some novel features include on-the-fly data access of operational hydrodynamic models, individual particle variability and inertial motion, and multi-nesting capabilities to optimize resolution. We demonstrate the performance of the interpolation algorithm by testing accuracy in tracing the flow stream lines in both time and space and the efficacy of probabilistic modeling in evaluating the bio-physical coupling against empirical data. Finally, following recommended practices for the development of community models, we provide an open source code with a series of coupled standalone, optional modules detailed in a user's guide. ► CMS simulates the transport and fate of living and non-living particles in the ocean. ► CMS has extensive applications to fisheries, ocean climate, and oil spill studies. ► CMS is a community-based open-source system with flexible data source and format. ► CMS offers a multi-nested approach for optimization of circulation model resolution. ► CMS provides adaptive treatments of the land boundary to avoid artificial grounding

Surface Evolution of the Deepwater Horizon Oil Spill Patch: Combined Effects of Circulation and Wind-Induced Drift

Following the Deepwater Horizon blowout, major concerns were raised about the probability that the Loop Current would entrain oil at the surface of the Gulf of Mexico toward South Florida. However, such a scenario did not materialize. Results from a modeling approach suggest that the prevailing winds, through the drift they induced at the ocean surface, played a major role in pushing the oil toward the coasts along the northern Gulf, and, in synergy with the Loop Current evolution, prevented the oil from reaching the Florida Straits. This implies that both oceanic currents and surface wind-induced drift must be taken into account for the successful forecasting of the trajectories and landfall of oil particles, even in energetic environments such as the Gulf of Mexico. Consequently, the time range of these predictions is limited to the weather forecasting range, in addition to the range set up by ocean forecasting capabilities

Surface Evolution of the Deepwater Horizon Oil Spill Patch: Combined Effects of Circulation and Wind-Induced Drift

Following the Deepwater Horizon blowout, major concerns were raised about the probability that the Loop Current would entrain oil at the surface of the Gulf of Mexico toward South Florida. However, such a scenario did not materialize. Results from a modeling approach suggest that the prevailing winds, through the drift they induced at the ocean surface, played a major role in pushing the oil toward the coasts along the northern Gulf, and, in synergy with the Loop Current evolution, prevented the oil from reaching the Florida Straits. This implies that both oceanic currents and surface wind-induced drift must be taken into account for the successful forecasting of the trajectories and landfall of oil particles, even in energetic environments such as the Gulf of Mexico. Consequently, the time range of these predictions is limited to the weather forecasting range, in addition to the range set up by ocean forecasting capabilities

Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and Synthetic Dispersants on the Subsea Oil Transport

During the Deepwater Horizon incident, crude oil flowed into the Gulf of Mexico from 1522 m underwater. In an effort to prevent the oil from rising to the surface, synthetic dispersants were applied at the wellhead. However, uncertainties in the formation of oil droplets and difficulties in measuring their size in the water column, complicated further assessment of the potential effect of the dispersant on the subsea-to-surface oil partition. We adapted a coupled hydrodynamic and stochastic buoyant particle-tracking model to the transport and fate of hydrocarbon fractions and simulated the far-field transport of the oil from the intrusion depth. The evaluated model represented a baseline for numerical experiments where we varied the distributions of particle sizes and thus oil mass. The experiments allowed to quantify the relative effects of chemical dispersion, vertical currents, and inertial buoyancy motion on oil rise velocities. We present a plausible model scenario, where some oil is trapped at depth through shear emulsification due to the particular conditions of the Macondo blowout. Assuming effective mixing of the synthetic dispersants at the wellhead, the model indicates that the submerged oil mass is shifted deeper, decreasing only marginally the amount of oil surfacing. In this scenario, the oil rises slowly to the surface or stays immersed. This suggests that other mechanisms may have contributed to the rapid surfacing of oil–gas mixture observed initially. The study also reveals local topographic and hydrodynamic processes that influence the oil transport in eddies and multiple layers. This numerical approach provides novel insights on oil transport mechanisms from deep blowouts and on gauging the subsea use of synthetic dispersant in mitigating coastal damage

Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and Synthetic Dispersants on the Subsea Oil Transport

During the Deepwater Horizon incident, crude oil flowed into the Gulf of Mexico from 1522 m underwater. In an effort to prevent the oil from rising to the surface, synthetic dispersants were applied at the wellhead. However, uncertainties in the formation of oil droplets and difficulties in measuring their size in the water column, complicated further assessment of the potential effect of the dispersant on the subsea-to-surface oil partition. We adapted a coupled hydrodynamic and stochastic buoyant particle-tracking model to the transport and fate of hydrocarbon fractions and simulated the far-field transport of the oil from the intrusion depth. The evaluated model represented a baseline for numerical experiments where we varied the distributions of particle sizes and thus oil mass. The experiments allowed to quantify the relative effects of chemical dispersion, vertical currents, and inertial buoyancy motion on oil rise velocities. We present a plausible model scenario, where some oil is trapped at depth through shear emulsification due to the particular conditions of the Macondo blowout. Assuming effective mixing of the synthetic dispersants at the wellhead, the model indicates that the submerged oil mass is shifted deeper, decreasing only marginally the amount of oil surfacing. In this scenario, the oil rises slowly to the surface or stays immersed. This suggests that other mechanisms may have contributed to the rapid surfacing of oil-gas mixture observed initially. The study also reveals local topographic and hydrodynamic processes that influence the oil transport in eddies and multiple layers. This numerical approach provides novel insights on oil transport mechanisms from deep blowouts and on gauging the subsea use of synthetic dispersant in mitigating coastal damage