Many nearshore fish and invertebrate populations are overexploited even when apparently coherent management structures are in place. One potential cause of mismanagement may be a poor understanding and accounting of stochasticity, particularly for stock recruitment. Many of the fishes and invertebrates that comprise nearshore fisheries are relatively sedentary as adults but have an obligate larval pelagic stage that is dispersed by ocean currents. Here, we demonstrate that larval connectivity is inherently an intermittent and heterogeneous process on annual time scales. This stochasticity arises from the advection of pelagic larvae by chaotic coastal circulations. This result departs from typical assumptions where larvae simply diffuse from one site to another or where complex connectivity patterns are created by transport within spatially complicated environments. We derive a statistical model for the expected variability in larval settlement patterns and demonstrate how larval connectivity varies as a function of different biological and physical processes. The stochastic nature of larval connectivity creates an unavoidable uncertainty in the assessment of fish recruitment and the resulting forecasts of sustainable yields.coastal oceanography ͉ fisheries ͉ marine ecology N earshore ecosystems host a wide variety of marine organisms and are among the most productive environments on Earth. Yet many species harvested from these ecosystems are overfished (1-3), a problem that is especially acute for those invertebrates and fishes with a relatively sedentary adult life stage. One potential cause of overfishing is mismanagement because of a poor understanding and accounting of stochasticity in these systems (4,5). Stochasticity caused by climate variations has long been known to influence the dynamics of ocean ecosystems and the fisheries they support (6). Climate variation affects rates of fecundity and recruitment by altering water temperature, coastal circulation patterns, or the availability of spawning grounds (7,8); such effects can be understood and, given sufficient data, may be predictable. Here, we introduce a mechanism that generates stochasticity in spatial and temporal patterns of larval transport on annual time scales. This stochasticity is inherently unpredictable because of the chaotic nature of coastal circulations and the relatively short larval time scales.Many harvested fish and invertebrates from nearshore ecosystems have a life cycle that includes a pelagic larval stage that can last up to months and a localized benthic adult stage (9, 10). These relatively sedentary adults release hundreds to millions of larvae that are advected and dispersed by ocean currents as they develop competency to settle (9-13). Spawning releases can occur continuously over months or in a few short events. Biotic factors, such as active swimming and vertical migration, also contribute to movement patterns (12,14,15). A small fraction of the larvae settle at suitable sites, and an even smaller fraction recruit to adult...

Marine species frequently show weak and/or complex genetic structuring that is commonly dismissed as 'chaotic' genetic patchiness and ecologically uninformative. Here, using three datasets that individually feature weak chaotic patchiness, we demonstrate that combining inferences across species and incorporating environmental data can greatly improve the predictive value of marine population genetics studies on small spatial scales. Significant correlations in genetic patterns of microsatellite markers among three species, kelp bass Paralabrax clathratus, Kellet's whelk Kelletia kelletii and California spiny lobster Panulirus interruptus, in the Southern California Bight suggest that slight differences in diversity and pairwise differentiation across sampling sites are not simply noise or chaotic patchiness, but are ecologically meaningful. To test whether interspecies correlations potentially result from shared environmental drivers of genetic patterns, we assembled data on kelp bed size, sea surface temperature and estimates of site-to-site migration probability derived from a high resolution multi-year ocean circulation model. These data served as predictor variables in linear models of genetic diversity and linear mixed models of genetic differentiation that were assessed with information-theoretic model selection. Kelp was the most informative predictor of genetics for all three species, but ocean circulation also played a minor role for kelp bass. The shared patterns suggest a single spatial marine management strategy may effectively protect genetic diversity of multiple species. This study demonstrates the power of environmental and ecological data to shed light on weak genetic patterns and highlights the need for future focus on a mechanistic understanding of the links between oceanography, ecology and genetic structure.

[1] The quantification of coastal connectivity is important for a wide range of real-world applications ranging from assessment of pollutant risk to nearshore fisheries management. For these purposes, coastal connectivity can be defined as the probability that water parcels from one location have advected to another site over a given time interval. Here we demonstrate how to quantify connectivity using Lagrangian probability-density functions (PDFs) based on numerical solutions of the coastal circulation of the Southern California Bight (SCB). Ensemble mean dispersal patterns from a single release site show strong dependencies on particle-release location, season, and year, reflecting annual and interannual circulation patterns in the SCB. Mean connectivity patterns are heterogeneous for the advection time of 30 days or less, due to local circulation patterns, and they become more homogeneous for longer advection times. However, connectivity patterns for a single realization are highly variable because of intrinsic eddy-driven transport and synoptic wind-forcing variability. In the long term, mainland sites are good sources while both Northern and Southern Channel Islands are poor sources, although they receive substantial fluxes of water parcels from the mainland. The predicted connectivity gives useful information to ecological and other applications for the SCB (e.g., designing marine protected areas and predicting the impact of a pollution event) and demonstrates how high-resolution numerical solutions of coastal ocean circulations can be used to quantify nearshore connectivity.

Populations of many nearshore marine species are connected through the dispersal of their larvae. In this paper, larval connectivity patterns in the Southern California Bight are explored using 2 quantities: potential and realized larval connectivity. Potential connectivity is defined as the probability of larval transport from a source to a destination location and is quantified using Lagrangian particle simulations. Realized connectivity is the product of potential connectivity with larval production and can be used to estimate larval settlement patterns. Potential and realized connectivity patterns are quantified for kelp bass Paralabrax clathratus, kelp rockfish Sebastes atrovirens, and red abalone Haliotis rufescens, 3 species with a range of larval dispersal characteristics. Connectivity patterns were found to be both heterogeneous, with locations having different source and destination strengths, and asymmetric, with directionality in larval transport. Both potential and realized connectivity were strongly influenced by the length and timing of the spawning season as well as planktonic larval duration. For kelp bass and kelp rockfish, a strong correspondence was found between realized and potential destination locations, suggesting that circulation processes have a dominant role in shaping the spatial distribution of these 2 species. Strong temporal variability in realized larval connectivity was observed on seasonal and inter-annual time scales (particularly between El Niño and La Niña conditions). These results provide novel information for use in marine fisheries and conservation management.

Hydrothermal vent fields in the western Pacific Ocean are mostly distributed along spreading centers in submarine basins behind convergent plate boundaries. Larval dispersal resulting from deep-ocean circulations is one of the major factors influencing gene flow, diversity, and distributions of vent animals. By combining a biophysical model and deep-profiling float experiments, we quantify potential larval dispersal of vent species via ocean circulation in the western Pacific Ocean. We demonstrate that vent fields within back-arc basins could be well connected without particular directionality, whereas basin-to-basin dispersal is expected to occur infrequently, once in tens to hundreds of thousands of years, with clear dispersal barriers and directionality associated with ocean currents. The southwest Pacific vent complex, spanning more than 4,000 km, may be connected by the South Equatorial Current for species with a longer-than-average larval development time. Depending on larval dispersal depth, a strong western boundary current, the Kuroshio Current, could bridge vent fields from the Okinawa Trough to the Izu-Bonin Arc, which are 1,200 km apart. Outcomes of this study should help marine ecologists estimate gene flow among vent populations and design optimal marine conservation plans to protect one of the most unusual ecosystems on Earth.

The probability of dispersal from one habitat patch to another is a key quantity in our efforts to understand and predict the dynamics of natural populations. Unfortunately, an often overlooked property of this potential connectivity is that it may change with time. In the marine realm, transient landscape features, such as mesoscale eddies and alongshore jets, produce potential connectivity that is highly variable in time. We assess the impact of this temporal variability by comparing simulations of nearshore metapopulation dynamics when potential connectivity is constant through time (i.e., when it is deterministic) and when it varies in time (i.e., when it is stochastic). We use mathematical analysis to reach general conclusions and realistic biophysical modeling to determine the actual magnitude of these changes for a specific system: nearshore marine species in the Southern California Bight. We find that in general the temporal variability of potential connectivity affects two important quantities: metapopulation growth rates when the species is rare and equilibrium abundances. Our biophysical models reveal that stochastic outcomes are almost always lower than their deterministic counterparts, sometimes by up to 40%. This has implications for how we use spatial information, such as connectivity, to manage nearshore (and other) systems.

Ocean currents are expected to be the predominant environmental factor influencing the dispersal of planktonic larvae or spores; yet, their characterization as predictors of marine connectivity has been hindered by a lack of understanding of how best to use oceanographic data. We used a high-resolution oceanographic model output and Lagrangian particle simulations to derive oceanographic distances (hereafter called transport times) between sites studied for Macrocystis pyrifera genetic differentiation. We build upon the classical isolation-by-distance regression model by asking how much additional variability in genetic differentiation is explained when adding transport time as predictor. We explored the extent to which gene flow is dependent upon seasonal changes in ocean circulation. Because oceanographic transport between two sites is inherently asymmetric, we also compare the explanatory power of models using the minimum or the mean transport times. Finally, we compare the direction of connectivity as estimated by the oceanographic model and genetic assignment tests. We show that the minimum transport time had higher explanatory power than the mean transport time, revealing the importance of considering asymmetry in ocean currents when modelling gene flow. Genetic assignment tests were much less effective in determining asymmetry in gene flow. Summer-derived transport times, in particular for the month of June, which had the strongest current speed, greatest asymmetry and highest spore production, resulted in the best-fit model explaining twice the variability in genetic differentiation relative to models that use geographic distance or habitat continuity. The best overall model also included habitat continuity and explained 65% of the variation in genetic differentiation among sites.

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