CAFA Publications

Author(s): Kang, D., and E.N. Curchitser

Project PI: Curchister
DOI: https://doi.org/10.1175/JPO-D-14-0200.1

A detailed energetics analysis of the Gulf Stream (GS) and associated eddies is performed using a highresolution multidecadal regional ocean model simulation. The energy equations for the time-mean and timevarying flows are derived as a theoretical framework for the analysis. The eddy–mean flow energy components and their conversions show complex spatial distributions. In the along-coast region, the cross-stream and cross-bump variations are seen in the eddy–mean flow energy conversions, whereas in the off-coast region, a mixed positive–negative conversion pattern is observed. The local variations of the eddy–mean flow interaction are influenced by the varying bottom topography. When considering the domain-averaged energetics, the eddy–mean flow interaction shows significant along-stream variability. Upstream of Cape Hatteras, the energy is mainly transferred from the mean flow to the eddy field through barotropic and baroclinic instabilities. Upon separating from the coast, the GS becomes highly unstable and both energy conversions intensify. When the GS flows into the off-coast region, an inverse conversion from the eddy field to the mean flow dominates the power transfer. For the entire GS region, the mean current is intrinsically unstable and transfers 28.26 GW of kinetic energy and 26.80 GW of available potential energy to the eddy field. The mesoscale eddy kinetic energy is generated by mixed barotropic and baroclinic instabilities, contributing 28.26 and 9.15 GW, respectively. Beyond directly supplying the barotropic pathway, mean kinetic energy also provides 11.55 GW of power to mean available potential energy and subsequently facilitates the baroclinic instability pathway.

Author(s): Kang, D., E.N. Curchitser and A. Rosati

Project PI: Curchister
DOI: https://doi.org/10.1175/JPO-D-15-0235.1

The seasonal variability of the mean kinetic energy (MKE) and eddy kinetic energy (EKE) of the Gulf Stream (GS) is examined using high-resolution regional ocean model simulations. A set of three numerical experiments with different surface wind and buoyancy forcing is analyzed to investigate the mechanisms governing the seasonal cycle of upper ocean energetics. In the GS along-coast region, MKE has a significant seasonal cycle that peaks in summer, while EKE has two comparable peaks in May and September near the surface; the May peak decays rapidly with depth. In the off-coast region, MKE has a weak seasonal cycle that peaks in summer, while EKE has a dominant peak in May and a secondary peak in September near the surface. The May peak also decays with depth leaving the September peak as the only seasonal signal below 100 m. An analysis of the three numerical experiments suggests that the seasonal variability in the local wind forcing significantly impacts the September peak of the along-coast EKE through a local-flow barotropic instability process. Alternatively, the seasonal buoyancy forcing primarily impacts the flow baroclinic instability and is consequently related to the May peak of the upper ocean EKE in both regions. The analysis results indicate that the seasonal cycle of the along-coast MKE is influenced by both local energy generation by wind and the advection of energy from upstream regions. Finally, the MKE cycle and the September peak of EKE in the off-coast region are mainly affected by advection of energy from remote regions, giving rise to correlations with the seasonal cycle of remote winds.

Author(s): Gray SA, SB Scyphers

Project PI: Scyphers
DOI: https://doi.org/10.1016/B978-0-12-805375-1.00022-2

Including stakeholders in environmental monitoring and research has been an increasingly recognized necessity for understanding the complex nature of marine social–ecological systems (SES). Stakeholder engagement and participation is often an essential ingredient for successful conservation and management. As a result, new inclusive approaches to scientific research have emerged under a broad umbrella often referred to as “citizen science.” These are collaborative research efforts that include stakeholders in the scientific process and strive to in various ways (1) decrease uncertainty of the dynamics of marine SES through collaborative data collection; (2) harness the expertise and knowledge of stakeholders that rely on marine resources to better understand these systems; and (3) provide a venue for more inclusive forms of resource and ecosystem management decision-making. Although the literature on citizen science shows that it is a popular way to collaboratively understand and collaboratively make decisions about natural resources, to date there is little information about how citizen science can specifically support social–ecological research and participatory decision-making in marine systems. In this chapter, we provide an overview of how participatory approaches to citizen science have been applied in marine research. Further, we theorize about the role that emerging online technologies may play in the future for collaborative science, decision-making, and marine policy.

Author(s): Muhling, Barbara, et al.

Project PI: Jacox
DOI: https://calcofi.org/publications/calcofireports/v60/Vol60-Muhling.pdf

Juvenile north Pacific albacore (Thunnus alalunga) forage in the California Current System (CCS), supporting fisheries between Baja California and British Columbia. Within the CCS, their distribution, abundance, and foraging behaviors are strongly variable interannually. Here, we use catch logbook data and trawl survey records to investigate how juvenile albacore in the CCS use their oceanographic environment, and how their distributions overlap with the habitats of four key forage species. We show that northern anchovy (Engraulis mordax) and hake (Merluccius productus) habitat is associated with productive coastal waters found more inshore of core juvenile albacore habitat, whereas Pacific sardine (Sardinops sagax) and boreal clubhook squid (Onychoteuthis borealijaponica) habitat overlaps more consistently with that of albacore. Our results can improve understanding of how albacore movements relate to foraging strategies, and why preyswitching behavior occurs. This has relevance for the development of ecosystem models for the CCS, and for the eventual implementation of ecosystem-based fishery management.

Author(s): Kang, Dujuan, and Enrique N. Curchitser

Project PI: Curchister
DOI: http://https://doi.org/10.1175/JPO-D-17-0063.1

The seasonal cycles of the mean kinetic energy (MKE) and eddy kinetic energy (EKE) are compared in an idealized flow as well as in a realistic simulation of the Gulf Stream (GS) region based on three commonly used definitions: orthogonal, nonorthogonal, and moving-average filtered decompositions of the kinetic energy (KE). It is shown that only the orthogonal KE decomposition can define the physically consistent MKE and EKE that precisely represents the KEs of the mean flow and eddies, respectively. The nonorthogonal KE decomposition gives rise to a residual term that contributes to the seasonal variability of the eddies, and therefore the obtained EKE is not precisely defined. The residual term is shown to exhibit more significant seasonal variability than EKE in both idealized and realistic GS flows. Neglecting its influence leads to an inaccurate evaluation of the seasonal variability of both the eddies and the total flow. The decomposition using a moving-average filter also results in a nonnegligible residual term in both idealized and realistic GS flows. This type of definition does not ensure conservation of the total KE, even if taking into account the residual term. Moreover, it is shown that the annual cycles of the three types of EKEs or MKEs have different phases and amplitudes. The local differences of the EKE cycles are very prominent in the GS off-coast domain; however, because of the spatial inhomogeneity, the area-mean differences may not be significant.

Author(s): Miller, T., C. M. Jones, C. Hanson, S. Heppell, O. Jensen, P. Livingston, K. Lorenzen, K. Mills, W. F. Patterson, P. J. Sullivan, and R. Wong.

Project PI: Mills
DOI: https://doi.org/10.1002/fsh.10179

Author(s): Bell, R. J., Wood, A., Hare, J., Richardson, D., Manderson, J., & Miller, T.

Project PI: Collie
DOI: https://doi.org/10.1139/cjfas-2017-0085

Decadal-scale climate variability and change can cause trends in oceanographic conditions that impact demographic rates. Rebuilding scenarios, therefore, developed assuming constant demographic rates may not be realistic. Winter flounder (Pseudopleuronectes americanus) is an important commercial and recreational species that has declined in the southern portion of its range despite reduced exploitation. Laboratory and mesocosm studies suggest that stock productivity is reduced under warmer conditions and that rebuilding to historical levels may not be possible. Our goal was to examine the rebuilding potential of winter flounder in the face of regional warming. We integrated winter temperature into a population model to estimate environmentally driven stock–recruitment parameters and projected the stock into the future under different climate and fishing scenarios. The inclusion of winter temperature had minor impacts on the estimates of current abundance, but provided greater understanding of the drivers of recruitment. Projections that included the environment suggest that rebuilding the stock to historical levels is unlikely. The integration of both fishing and the environment has the potential to provide more realistic expectations of future stock status.

Author(s): Brodie, S., M. G. Jacox, S. J. Bograd, H. Welch, H. Dewar, K. L. Scales, S. M. Maxwell, D. K. Briscoe, C. A. Edwards, L. B. Crowder, R. L. Lewison, E. L. Hazen

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2018.00219

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks Isurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997–2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (<100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models.

Author(s): E.L. Hazen, K.L. Scales, S.M. Maxwell, D. Briscoe, H. Welch, S.J. Bograd, H. Bailey, S.R. Benson, T. Eguchi, H. Dewar, S. Kohin, D.P. Costa, L.B. Crowder, R.L. Lewison

Project PI: Jacox
DOI: 10.1126/sciadv.aar3001

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.

Author(s): D. Politikos, E.N. Curchitser, K.A. Rose, D.M. Checkley, J. Fiechter

Project PI: Jacox
DOI: https://doi.org/10.1111/fog.12381

Recruitment varies substantially in small pelagic fish populations. Understanding of the mechanisms linking environment to recruitment is essential for the effective management of fisheries resources. In this study, we used a fully coupled end-to-end ecosystem model to study the effect of climate variability on sardine recruitment in the California Current System during 1965–2006. Ocean variability was represented by ROMS hydrodynamic and NEMURO biogeochemical models, and sardine population dynamics was simulated through a full life cycle individual-based model. Model analysis was designed to elucidate how changes in abiotic and biotic conditions may impact the spawning habitats, early life stage survival, and ultimately recruitment of sardine. Our findings revealed the importance of spatial processes to shape early life stages dynamics. Shifts in spawning habitats were dictated by the spatial variations in temperature and the behavioral movement of adults. Additionally, the spatial match of eggs with warmer temperatures and larvae with their prey influenced their survival. The northward shifts in spawning locations and the accomplishment of good recruitment in warmer years agreed with existing knowledge. Egg production and survival during egg and yolk-sac larval stages were key factors to drive the long-term variations in recruitment. Finally, our analysis provided a quantitative assessment of climate impact on year-to-year variation in sardine recruitment by integrating multiple hypotheses.