CAFA Publications

Author(s): Muhling, B. A., Brodie, S., Smith, J. A., Tommasi, D., Gaitan, C. F., Hazen, E. L., ... & Brodeur, R. D.

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2020.00589

Spatial distributions of marine fauna are determined by complex interactions between environmental conditions and animal behaviors. As climate change leads to warmer, more acidic, and less oxygenated oceans, species are shifting away from their historical distribution ranges, and these trends are expected to continue into the future. Correlative Species Distribution Models (SDMs) can be used to project future habitat extent for marine species, with many different statistical methods available. However, it is vital to assess how different statistical methods behave under novel environmental conditions before using these models for management advice, and to consider whether future projections based on these techniques are biologically reasonable. In this study, we built SDMs for adults and larvae of two ecologically important pelagic fishes in the California Current System (CCS): Pacific sardine (Sardinops sagax) and northern anchovy (Engraulis mordax). We used five different SDM methods, ranging from simple [thermal niche model (TNM)] to complex (artificial neural networks). Our results show that some SDMs trained on data collected between 2003 and 2013 lost substantial predictive skill when applied to observations from more recent years, when ocean temperatures associated with a marine heatwave were outside the range of historical measurements. This decrease in skill was particularly apparent for adult sardine, which showed non-stationary relationships between catch locations and sea surface temperature (SST) through time. While sardine adults and larvae shifted their distributions markedly during the marine heatwave, anchovy largely maintained their historical spatiotemporal distributions. Our results suggest that correlative relationships between species and their environment can become unreliable during anomalous conditions. Understanding the underlying physiology of marine species is therefore essential for the construction of SDMs that are robust to rapidly changing environments. Developing distribution models that offer skillful predictions into the future for species such as sardine and anchovy, which are migratory and include separate sub-stocks, may be particularly challenging.

Author(s): Evans, N, Schroeder, ID, Pozo Buil, M, Jacox, MG, Bograd, SJ

Project PI: Jacox
DOI: https://doi.org/10.1029/2020GL089274

A confluence of subarctic, tropical, and subtropical water masses feed the California Current System (CCS), supporting a highly productive ecosystem and wide array of marine ecosystem services. Long-term declines in oxygen have been observed in this region, causing habitat compression and other ecosystem consequences. Here we quantify the water masses and processes causing deoxygenation in the subsurface CCS from 1993–2018, and we find that deoxygenation was caused both by changes in the advection of source waters and increased remineralization in the source waters. The historical deoxygenation trend can be attributed primarily (81%) to the Northern Equatorial Pacific Intermediate Water, the deep Pacific Equatorial Water mass transported in the California Undercurrent. We also find that advection and remineralization share nearly equal contributions to deoxygenation. This improved understanding of the mechanisms affecting the aerobic habitat of the CCS will inform projections of ecological impacts and mitigation of future deoxygenation.

Author(s): J. Schmidt, S. Bograd, H. Arrizabalaga, et al.

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2019.00550

Advances in ocean observing technologies and modeling provide the capacity to revolutionize the management of living marine resources. While traditional fisheries management approaches like single-species stock assessments are still common, a global effort is underway to adopt ecosystem-based fisheries management (EBFM) approaches. These approaches consider changes in the physical environment and interactions between ecosystem elements, including human uses, holistically. For example, integrated ecosystem assessments aim to synthesize a suite of observations (physical, biological, socioeconomic) and modeling platforms [ocean circulation models, ecological models, short-term forecasts, management strategy evaluations (MSEs)] to assess the current status and recent and future trends of ecosystem components. This information provides guidance for better management strategies. A common thread in EBFM approaches is the need for high-quality observations of ocean conditions, at scales that resolve critical physical-biological processes and are timely for management needs. Here we explore options for a future observing system that meets the needs of EBFM by (i) identifying observing needs for different user groups, (ii) reviewing relevant datasets and existing technologies, (iii) showcasing regional case studies, and (iv) recommending observational approaches required to implement EBFM. We recommend linking ocean observing within the context of Global Ocean Observing System (GOOS) and other regional ocean observing efforts with fisheries observations, new forecasting methods, and capacity development, in a comprehensive ocean observing framework.

Author(s): Capotondi, A, MG Jacox, et al

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2019.00623

Many coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.

Author(s): Dussin, R, EN Curchitser, CA Stock, N Van Ooostende

Project PI: Jacox
DOI: https://doi.org/10.1016/j.dsr2.2019.05.013

Recent observations have revealed significant fluctuations in near-shore hypoxia in the California Current Ecosystem (CCE). These fluctuations have been linked to changes in the biogeochemical properties (e.g. oxygen and nutrient contents) of the oceanic source waters of the California Current upwelling, and projections suggest the potential for decreased oxygen and increased nutrients in the source water under climate change. We examine both the separate and combined influences of these projected changes through a sequence of perturbation experiments using a regional coupled ocean dynamics/biogeochemistry (BGC) model of the CCE. The direct effect of a projected 5% decline in source water oxygen is to expand the hypoxic area by 12.5% in winter to 22.5% in summer. This exceeds the impact of a +0.5% nitrate enrichment of source waters, which expands the hypoxic area by 6.5% to 12% via stimulation of nearshore Net Primary Productivity (NPP), increased organic matter export, and subsequent enhanced remineralization and dissolved oxygen (DO) consumption at depth. The combined effect of these perturbations consistently surpasses the sum of the individual impacts, leading to 20% to 32% more hypoxic area. The combined biogeochemical impact greatly exceeds the response resulting from a 10% strengthening in upwelling-favorable winds (+1% in hypoxic area) or the decreased oxygen solubility associated with a 2◦C ocean warming (+3%). These results emphasize the importance of improved constraints on dynamic biogeochemical changes projected along the boundaries of shelf ecosystems. While such changes are often viewed as secondary impacts of climate change relative to local warming or stratification changes, they may prove dominant drivers of coastal ecosystem change.

Author(s): Hazen, EL, et al

Project PI: Jacox
DOI: https://doi.org/10.1002/fee.2125

The rapid pace of environmental change in the Anthropocene necessitates the development of a new suite of tools for measuring ecosystem dynamics. Sentinel species can provide insight into ecosystem function, identify hidden risks to human health, and predict future change. As sentinels, marine apex (top) predators offer a unique perspective into ocean processes, given that they can move across ocean basins and amplify trophic information across multiple spatiotemporal scales. Because use of the terms “ecosystem sentinel” and “climate sentinel” has proliferated in the scientific literature, there is a need to identify the properties that make marine predators effective sentinels. We provide a clear definition of the term “sentinel”, review the attributes of species identified as sentinels, and describe how a suite of such sentinels could strengthen our understanding and management of marine ecosystems. We contend that the use of marine predators as ecosystem sentinels will enable rapid response and adaptation to ecosystem variability and change.

Author(s): Nishikawa, H, EN Curchitser, J Fiechter, KA Rose, K Hedstrom

Project PI: Jacox
DOI: https://doi.org/10.1186/s40645-019-0257-2

The influence of the well-known 1976–1977 regime shift on the Northern anchovy (Engraulis mordax) and the Pacific sardine (Sardinops caeruleus) populations in the California Current System (CCS) is investigated using a climate-to-fishery model. This model consists of four coupled submodels (regional ocean circulation model; Eulerian nutrient-phytoplankton-zooplankton-detritus model; individual-based full life cycle anchovy and sardine model; agent-based fishery model). Analysis of a historical simulation (1958–1990) showed that survival fraction of age-0 anchovy was lower just after 1977, while survival fraction of age-0 sardine was relatively unaffected by the regime shift. The age-0 survival of both species was influenced by the growth in the larval stage. Simulated zooplankton densities in the historical simulation shifted from high to low in 1976–1977 in the CCS, with the shift being most drastic in winter in the coastal area. The model also shows that anchovy larvae feed extensively from winter to early spring in the coastal area, while sardine larvae were mainly distributed in the offshore area. The differential seasonal and spatial responses of zooplankton in the simulation caused anchovy survival to be more sensitive than sardine to the 1976–1977 regime shift. The model-generated zooplankton shift was a result of reduced phytoplankton production due to lowered nutrient concentrations after 1977 due to the weakening of both the coastal upwelling and mixed layer shoaling, which reduced the vertical nutrient flux from the bottom layer to the surface layer.

Author(s): Smith, J.A., Tommasi, D., Sweeney, J., Brodie, S., Welch, H., Hazen, E.L., Muhling, B., Stohs, S.M. and Jacox, M.G.

Project PI: Jacox
DOI: https://doi.org/10.1111/1365-2664.13565

Time-area closures are an important tool for reducing fisheries bycatch, but their effectiveness and economic impact can be influenced by the changes in species distributions. For fisheries targeting highly mobile species, the economic impact of a closure may by highly dynamic, depending on the current suitability of the closed area for the target species.We present an analysis to quantify the fine-scale economic impact of time-area closures: the ‘lost economic opportunity’, which is the percentage of total potential profit for an entire fishing season that occurs within and during a time-area closure. Our analysis integrates a spatially explicit and environment-informed catch model with a utility model that quantifies fishing revenues and costs, and thus incorporates a dynamic target species distribution in the estimated economic impact of a closure. We demonstrate this approach by evaluating the economic impact of the Loggerhead Conservation Area (LCA) on California's drift gillnet swordfish Xiphias gladius fishery.The lost economic opportunity due to the LCA time-area closure ranged from 0% to 6% per season, with variation due to port location and trip duration, as well as inter-annual changes in swordfish distribution. This increased by 40%–90% when a seasonally varying swordfish price was considered. There was a clear signal in economic impact associated with a shift from warm to cool conditions in the California Current following the 1998 El Niño, with increased lost economic opportunity from 1999. This signal was due to higher swordfish catch inside the LCA during the cool phase, associated with increased water column mixing, and due to higher catches outside the LCA in the warmer phase, associated with increased sea-surface temperature.Synthesis and applications. We found small economic impact from a fishery closure, but with meaningful inter-annual variation due to environmental change and the dynamic distribution of a target species. Our approach could be used to help determine the timing of closures, simulate impacts of proposed closures and, more generally, assess some economic consequences of climate-induced shifts in species’ ranges.

Author(s): Welch, H, S Brodie, MG Jacox, SJ Bograd, EL Hazen

Project PI: Jacox
DOI: https://doi.org/10.1111/cobi.13417

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers.

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.