The 2015–2016 El Niño is by some measures one of the strongest on record, comparable to the 1982–1983 and 1997–1998 events that triggered widespread ecosystem change in the northeast Pacific. Here we describe impacts of the 2015–2016 El Niño on the California Current System (CCS) and place them in historical context using a regional ocean model and underwater glider observations. Impacts on the physical state of the CCS are weaker than expected based on tropical sea surface temperature anomalies; temperature and density fields reflect persistence of multiyear anomalies more than El Niño. While we anticipate El Niño‐related impacts on spring/summer 2016 productivity to be similarly weak, their combination with preexisting anomalous conditions likely means continued low phytoplankton biomass. This study highlights the need for regional metrics of El Niño's effects and demonstrates the potential to assess these effects before the upwelling season, when altered ecosystem functioning is most apparent.

Coastal upwelling is responsible for thriving marine ecosystems and fisheries that are disproportionately productive relative to their surface area, particularly in the world's major eastern boundary upwelling systems. Along oceanic eastern boundaries, equatorward wind stress and the Earth's rotation combine to drive a near-surface layer of water offshore, a process called Ekman transport. Similarly, positive wind stress curl drives divergence in the surface Ekman layer and consequently upwelling from below, a process known as Ekman suction. In both cases, displaced water is replaced by upwelling of relatively nutrient-rich water from below, which stimulates the growth of microscopic phytoplankton that form the base of the marine food web. Ekman theory is foundational and underlies the calculation of upwelling indices such as the "Bakun Index" that are ubiquitous in eastern boundary upwelling system studies. While generally valuable first-order descriptions, these indices and their underlying theory provide an incomplete picture of coastal upwelling. Here we review the relevant dynamics and limitations of classical upwelling indices, particularly related to representation of the surface wind stress, the influence of geostrophic currents, and the properties of upwelled water. To address these shortcomings, we present two new upwelling indices for the U.S. West Coast (31-47°N), which are available from 1988 to present. The Coastal Upwelling Transport Index and the Biologically Effective Upwelling Transport Index provide improved estimates of vertical transport and vertical nitrate flux, respectively, by leveraging technological and scientific advances realized since the introduction of the Bakun Index nearly a half century ago. Plain Language Summary The California Current System, running along the North American WestCoast, hosts a rich and diverse marine ecosystem that provides considerable socioeconomic benefit. The process underlying this exceptional biological productivity is wind-driven coastal upwelling, which delivers deep, nutrient-rich water to the sunlit surface layer and stimulates growth of phytoplankton that form the base of the marine food web. Given the ecological importance of upwelling, indices designed to monitor its intensity (e.g., the "Bakun Index") were introduced nearly 50 years ago. While these indices have proved extremely useful, they have a number of limitations as they are derived from relatively coarse resolution atmospheric pressure fields. In particular, uncertainties arise in the estimation of wind stress and from the omission of the influence of ocean circulation. Furthermore, historical indices estimate only the amount of water upwelled, not the nutrient content of that water. Here we present new indices that leverage ocean models, satellite data, and in situ observations to more accurately estimate upwelling strength as well as the amount of nitrate being upwelled. The new indices are publicly available, extend from 1988 to present, and will be valuable for monitoring upwelling in...

No abstract

The abundances of six N₂-fixing cyanobacterial phylotypes were profiled at 22 stations across the tropical Atlantic Ocean during June 2006, and used to model the contribution of the diazotrophs to N₂ fixation. Diazotroph abundances were measured by targeting the nifH gene of Trichodesmium, unicellular groups A, B, C (UCYN-A, UCYN-B and UCYN-C), and diatom-cyanobiont symbioses Hemiaulus-Richelia, Rhizosolenia-Richelia and Chaetoceros-Calothrix. West to east gradients in temperature, salinity and nutrients [NO₃⁻ + NO₂⁻, PO₄³⁻, Si(OH)₄] showed the influence of the Amazon River plume and its effect on the distributions of the diazotrophs. Trichodesmium accounted for more than 93% of all nifH genes detected, dominated the warmer waters of the western Atlantic, and was the only diazotroph detected at the equatorial upwelling station. UCYN-A was the next most abundant (> 5% of all nifH genes) and dominated the cooler waters of the eastern Atlantic near the Cape Verde Islands. UCYN-C was found at a single depth (200 m) of high salinity and low temperature and nutrients, whereas UCYN-B cells were widespread but in very low abundance (6.1 × 10¹ ± 4.6 × 10² gene copies l⁻¹). The diatom-cyanobionts were observed primarily in the western Atlantic within or near the high Si(OH)₄ input of the Amazon River plume. Overall, highest diazotroph abundances were observed at the surface and declined with depth, except for some subsurface peaks in Trichodesmium, UCYN-B and UCYN-A. Modelled contributions of Trichodesmium, UCYN-B and UCYN-A to total N₂ fixation suggested that Trichodesmium had the largest input, except for the potential of UCYN-A at the Cape Verde Islands.

Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered "measured data"), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.