James R. Watson

Taking the chaos out of genetic patchiness: seascape genetics reveals ecological and oceanographic drivers of genetic patterns in three temperate reef species

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.

Isolation by oceanographic distance explains genetic structure for Macrocystis pyrifera in the Santa Barbara Channel.

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.

Identifying critical regions in small-world marine metapopulations

The precarious state of many nearshore marine ecosystems has prompted the use of marine protected areas as a tool for management and conservation. However, there remains substantial debate over their design and, in particular, how to best account for the spatial dynamics of nearshore marine species. Many commercially important nearshore marine species are sedentary as adults, with limited home ranges. It is as larvae that they disperse greater distances, traveling with ocean currents sometimes hundreds of kilometers. As a result, these species exist in spatially complex systems of connected subpopulations. Here, we explicitly account for the mutual dependence of subpopulations and approach protected area design in terms of network robustness. Our goal is to characterize the topology of nearshore metapopulation networks and their response to perturbation, and to identify critical subpopulations whose protection would reduce the risk for stock collapse. We define metapopulation networks using realistic estimates of larval dispersal generated from ocean circulation simulations and spatially explicit metapopulation models, and we then explore their robustness using node-removal simulation experiments. Nearshore metapopulations show small-world network properties, and we identify a set of highly connected hub subpopulations whose removal maximally disrupts the metapopulation network. Protecting these subpopulations reduces the risk for systemic failure and stock collapse. Our focus on catastrophe avoidance provides a unique perspective for spatial marine planning and the design of marine protected areas.

Changing Seascapes, Stochastic Connectivity, and Marine Metapopulation Dynamics

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.

Modeling Social—Ecological Scenarios in Marine Systems

Human activities have substantial impacts on marine ecosystems+ including rapid regime shifts with large consequences for human well-being. We highlight the use of model-based scenarios as a scientific tool for adaptive stewardship in the face of such consequences. The natural sciences have a long history of developing scenarios but rarely with an in-depth understanding of factors influencing human actions. Social scientists have traditionally investigated human behavior, but scholars often argue that behavior is too complex to be represented by broad generalizations useful for models and scenarios. We address this scientific divide with a framework for integrated marine social-ecological scenarios, combining quantitative process-based models from the biogeochemical and ecological disciplines with qualitative studies on governance and social change. The aim is to develop policy-relevant scenarios based on an in-depth empirical understanding from both the natural and the social sciences, thereby contributing to adaptive stewardship of marine social-ecological systems.

The timescales of global surface-ocean connectivity

Planktonic communities are shaped through a balance of local evolutionary adaptation and ecological succession driven in large part by migration. The timescales over which these processes operate are still largely unresolved. Here we use Lagrangian particle tracking and network theory to quantify the timescale over which surface currents connect different regions of the global ocean. We find that the fastest path between two patches—each randomly located anywhere in the surface ocean—is, on average, less than a decade. These results suggest that marine planktonic communities may keep pace with climate change—increasing temperatures, ocean acidification and changes in stratification over decadal timescales—through the advection of resilient types.

Foreign investment in Russia: The case of the oil industry

THE RUSSIAN OIL INDUSTRY is in desperate need of investment. Output has fallen by over 45% since the peak year of 1987, and could fall still further if major financial commitments are not forthcoming. Domestic firms, starved of cash, and often lacking the appropriate technology and expertise, are unlikely, however, to be able to turn the industry around by themselves. Instead they will need to enter into partnerships with Western oil companies, which, attracted by Russias skilled labour force, its relatively low production costs, and, above all, its huge reserves of oil, are ready to make major investments. It is widely accepted that such co-operation could benefit both sides. Projects could generate enough revenue to compensate both the foreign oil companies and their local partners, in the form of profits, and the Russian government, through tax revenues. Increased exports would improve Russias trade balance and make it more able to service its foreign debt; the additional tax receipts would help to balance the state budget, and facilitate macroeconomic stabilisation. Furthermore, Russian equipment suppliers would receive additional orders, employment would be created for Russian workers, and the local economies of the oil-producing regions would benefit generally from large inflows of foreign money. Western energy consumers and governments would gain too, from added insurance against any future tightening of world oil markets and higher world prices. Yet, despite all these benefits, very little investment has actually taken place. By the summer of 1995 no more than

Larval connectivity across temperature gradients, and its potential effect on heat tolerance in coral populations.

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The Spatial Dynamics of Predators and the Benefits and Costs of Sharing Information

Coral reefs are increasingly exposed to elevated temperatures that can cause coral bleaching and high levels of mortality of corals and associated organisms. The temperature threshold for coral bleaching depends on the acclimation and adaptation of corals to the local maximum temperature regime. However, because of larval dispersal, coral populations can receive larvae from corals that are adapted to very different temperature regimes. We combine an offline particle tracking routine with output from a high-resolution physical oceanographic model to investigate whether connectivity of coral larvae between reefs of different thermal regimes could alter the thermal stress threshold of corals. Our results suggest that larval transport between reefs of widely varying temperatures is likely in the Coral Triangle and that accounting for this connectivity may be important in bleaching predictions. This has important implications in conservation planning, because connectivity may allow some reefs to have an inherited heat tolerance that is higher or lower than predicted based on local conditions alone.

Maintaining cooperation in social-ecological systems:

Predators of all kinds, be they lions hunting in the Serengeti or fishermen searching for their catch, display various collective strategies. A common strategy is to share information about the location of prey. However, depending on the spatial characteristics and mobility of predators and prey, information sharing can either improve or hinder individual success. Here, our goal is to investigate the interacting effects of space and information sharing on predation efficiency, represented by the expected rate at which prey are found and consumed. We derive a feeding functional response that accounts for both spatio-temporal heterogeneity and communication, and validate this mathematical analysis with a computational agent-based model. This agent-based model has an explicit yet minimal representation of space, as well as information sharing about the location of prey. The analytical model simplifies predator behavior into a few discrete states and one essential trade-off, between the individual benefit of acquiring information and the cost of creating spatial and temporal correlation between predators. Despite the absence of an explicit spatial dimension in these equations, they quantitatively predict the predator consumption rates measured in the agent-based simulations across the explored parameter space. Together, the mathematical analysis and agent-based simulations identify the conditions for when there is a benefit to sharing information, and also when there is a cost.