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Locally enhanced biological production and increased carbon export are persistent features at oceanic density fronts. Studies often assume biological properties are uniform along fronts or hypothesize that along‐ and across‐front gradients reflect physical‐biological processes occurring in the front. However, the residence times of waters in fronts are often shorter than biological response times. Thus, an alternate—often untested—hypothesis is that observed biological patchiness originates upstream of a front. To test these two hypotheses, we explore an eddy‐associated front in the California Current System sampled during two surveys, separated by 3 weeks. Patches of high phytoplankton biomass were found at the northern ends of both surveys, and phytoplankton biomass decreased along the front. While these patches occurred in similar locations, it was unclear whether the same patch was sampled twice, or whether the two patches were different. Using an advection‐reaction framework combined with field and satellite data, we found that variations in along‐front gradients in dissolved oxygen, particle biovolume, and salinity support the conclusion that the two phytoplankton patches were different. They were only coincidentally sampled in similar locations. Backward‐ and forward‐in‐time tracking of water parcels showed that these phytoplankton patches had distinct origins, associated with specific, strong coastal upwelling pulses upstream of the front. Phytoplankton grew in these recently upwelled waters as they advected into and along the frontal system. By considering both local and upstream physical‐biological forcings, this approach enables better characterizations of critical physical and biogeochemical processes that occur at fronts across spatial and temporal scales.

The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO₂) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO₂beyond direct measurements requires the use of paleoproxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. In this study, we critically evaluated, categorized, and integrated available proxies to create a high-fidelity and transparently constructed atmospheric CO₂record spanning the past 66 million years. This newly constructed record provides clearer evidence for higher Earth system sensitivity in the past and for the role of CO₂thresholds in biological and cryosphere evolution.

In the California Current System, cross‐shore transport of upwelled, nutrient‐rich waters from the coastal margin to the open ocean can occur within intermittent, submesoscale‐to‐mesoscale features such as filaments. Time‐varying spatial gradients within filaments affect net cross‐shore fluxes of physical, biological, and chemical tracers but require high‐resolution measurements to accurately estimate. In June 2017, theCalifornia Current EcosystemLong Term Ecological Research program process cruise (P1706) conducted repeat sections by an autonomousSprayglider and a towed SeaSoar to investigate the role of one such coastal upwelling feature, the Morro Bay filament, which was characterized by enhanced cross‐filament gradients (both physical and biological) and an along‐filament jet. Within the jet, speeds were up to 0.78 m/s and the offshore transport was 1.5 Sverdrups (3.8 Sverdrups) in the upper 100 m (500 m). A climatological data product from the sustained California Underwater Glider Network provided necessary information for water mass differentiation. The analysis revealed that the cold, salty side of the filament carried recently upwelled California Undercurrent water and corresponded to higher chlorophyll‐afluorescence than the warm, fresh side, which carried California Current water. Thus, there was a convergence of heterogeneous water masses within the core of the filament’s offshore‐flowing jet. These water masses have different geographic origins and thermohaline characteristics, which has implications for filament‐related cross‐shore fluxes and submesoscale‐to‐mesoscale biological community structure gradients.

The potential influences of turbulence on planktonic processes such as nutrient uptake, grazing, predation, infection, and mating have been explored in hundreds of laboratory and theoretical studies. However, the turbulence levels used may not represent those experienced by oceanic plankton, bringing into question their relevance for understanding planktonic dynamics in the ocean. Here, we take a data‐centric approach to understand the turbulence climate experienced by plankton in the ocean, analyzing over one million turbulence measurements acquired in the open ocean. Median dissipation rates in the upper 100 m were < 10⁻⁸ W kg⁻¹, with 99% of the observations < 10⁻⁶ W kg⁻¹. Below mixed layers, the median dissipation rate was ~ 10⁻¹⁰ W kg⁻¹, with 99% of the observations < 10⁻⁷ W kg⁻¹. Even in strongly mixing layers the median dissipation rates rarely reached 10⁻⁵ W kg⁻¹, decreasing by orders of magnitude over 10 m or less in depth. Furthermore, episodes of intense turbulence were transient, transitioning to background levels within 10 min or less. We define three turbulence conditions in the ocean: weak (< 10⁻⁸ W kg⁻¹), moderate (10⁻⁸–10⁻⁶ W kg⁻¹), and strong (> 10⁻⁶ W kg⁻¹). Even the strongest of these is much weaker than those used in most laboratory experiments. The most frequent turbulence levels found in this study are weak enough for most plankton—including small protists—to outswim them, and to allow chemical plumes and trails to persist for tens of minutes. Our analyses underscore the primary importance of planktonic behavior in driving individual interactions.

In recent years, harmful algal blooms (HABs) have increased in their severity and extent in many parts of the world and pose serious threats to local aquaculture, fisheries, and public health. In many cases, the mechanisms triggering and regulating HAB events remain poorly understood. Using underwater microscopy and Residual Neural Network (ResNet‐18) to taxonomically classify imaged organisms, we developed a daily abundance record of four potentially harmful algae (Akashiwo sanguinea,Chattonellaspp.,Dinophysisspp., andLingulodinium polyedra) and major grazer groups (ciliates, copepod nauplii, and copepods) from August 2017 to November 2020 at Scripps Institution of Oceanography pier, a coastal location in the Southern California Bight. Random Forest algorithms were used to identify the optimal combination of environmental and ecological variables that produced the most accurate abundance predictions for each taxon. We developed models with high prediction accuracy forA. sanguinea(),Chattonellaspp. (), andL. polyedra(), whereas models forDinophysisspp. showed lower prediction accuracy (). Offshore nutricline depth and indices describing climate variability, including El Niño Southern Oscillation, Pacific Decadal Oscillation, and North Pacific Gyre Oscillation, that influence regional‐scale ocean circulation patterns and environmental conditions, were key predictor variables for these HAB taxa. These metrics of regional‐scale processes were generally better predictors of HAB taxa abundances at this coastal location than the in situ environmental measurements. Ciliate abundance was an important predictor ofChattonellaandDinophysisspp., but not ofA. sanguineaandL. polyedra. Our findings indicate that combining regional and local environmental factors with microzooplankton populations dynamics can improve real‐time HAB abundance forecasts.

A variety of proxies have been developed to reconstruct paleo‐CO₂from fossil leaves. These proxies rely on some combination of stomatal morphology, leafδ¹³C, and leaf gas exchange. A common conceptual framework for evaluating these proxies is lacking, which has hampered efforts for inter‐comparison. Here we develop such a framework, based on the underlying physics and biochemistry. From this conceptual framework, we find that the more extensively parameterised proxies, such as the optimisation model, are likely to be the most robust. The simpler proxies, such as the stomatal ratio model, tend to under‐predict CO₂, especially in warm (>15^°C) and moist (>50%humidity) environments. This identification of a structural under‐prediction may help to explain the common observation that the simpler proxies often produce estimates of paleo‐CO₂that are lower than those from the more complex proxies and other, non‐leaf‐based CO₂proxies. The use of extensively parameterised models is not always possible, depending on the preservation state of the fossils and the state of knowledge about the fossil's nearest living relative. With this caveat in mind, our analysis highlights the value of using the most complex leaf‐based model as possible.