Ocean model-based covariates improve a marine fish stock assessment when observations are limited

The productivity of many fish populations is influenced by the environment, but developing environment-linked stock assessments remain challenging and current management of most commercial species assumes that stock productivity is time-invariant. In the Northeast United States, previous studies suggest that the recruitment of Southern New England-Mid Atlantic yellowtail flounder is closely related to the strength of the Cold Pool, a seasonally formed cold water mass on the continental shelf. Here, we developed three new indices that enhance the characterization of Cold Pool interannual variations using bottom temperature from a regional hindcast ocean model and a global ocean data assimilated hindcast. We associated these new indices to yellowtail flounder recruitment in a state–space, age-structured stock assessment framework using the Woods Hole Assessment Model. We demonstrate that incorporating Cold Pool effects on yellowtail flounder recruitment reduces the retrospective patterns and may improve the predictive skill of recruitment and, to a lesser extent, spawning stock biomass. We also show that the performance of the assessment models that incorporated ocean model-based indices is improved compared to the model using only the observation-based index. Instead of relying on limited subsurface observations, using validated ocean model products as environmental covariates in stock assessments may both improve predictions and facilitate operationalization.publishedVersio

Seasonal prediction of bottom temperature on the Northeast U.S. Continental Shelf

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chen, Z., Kwon, Y.-O., Chen, K., Fratantoni, P., Gawarkiewicz, G., Joyce, T. M., Miller, T. J., Nye, J. A., Saba, V. S., & Stock, B. C. Seasonal prediction of bottom temperature on the Northeast U.S. Continental Shelf. Journal of Geophysical Research: Oceans, 126(5), (2021): e2021JC017187, https://doi.org/10.1029/2021JC017187.The Northeast U.S. shelf (NES) is an oceanographically dynamic marine ecosystem and supports some of the most valuable demersal fisheries in the world. A reliable prediction of NES environmental variables, particularly ocean bottom temperature, could lead to a significant improvement in demersal fisheries management. However, the current generation of climate model-based seasonal-to-interannual predictions exhibits limited prediction skill in this continental shelf environment. Here, we have developed a hierarchy of statistical seasonal predictions for NES bottom temperatures using an eddy-resolving ocean reanalysis data set. A simple, damped local persistence prediction model produces significant skill for lead times up to ∼5 months in the Mid-Atlantic Bight and up to ∼10 months in the Gulf of Maine, although the prediction skill varies notably by season. Considering temperature from a nearby or upstream (i.e., more poleward) region as an additional predictor generally improves prediction skill, presumably as a result of advective processes. Large-scale atmospheric and oceanic indices, such as Gulf Stream path indices (GSIs) and the North Atlantic Oscillation Index, are also tested as predictors for NES bottom temperatures. Only the GSI constructed from temperature observed at 200 m depth significantly improves the prediction skill relative to local persistence. However, the prediction skill from this GSI is not larger than that gained using models incorporating nearby or upstream shelf/slope temperatures. Based on these results, a simplified statistical model has been developed, which can be tailored to fisheries management for the NES.This work was supported by NOAA's Climate Program Office's Modeling, Analysis, Predictions, and Projections (MAPP) Program (NA17OAR4310111, NA19OAR4320074), and Climate Program Office's Climate Variability and Predictability (CVP) Program (NA20OAR4310482). We acknowledge our participation in MAPP's Marine Prediction Task Force

Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula

Understanding the mechanisms by which climate variability affects multiple trophic levels in food webs is essential for determining ecosystem responses to climate change. Here we use over two decades of data collected by the Palmer Long Term Ecological Research program (PAL-LTER) to determine how large-scale climate and local physical forcing affect phytoplankton, zooplankton and an apex predator along the West Antarctic Peninsula (WAP). We show that positive anomalies in chlorophyll-a (chl-a) at Palmer Station, occurring every 4-6 years, are constrained by physical processes in the preceding winter/spring and a negative phase of the Southern Annular Mode (SAM). Favorable conditions for phytoplankton included increased winter ice extent and duration, reduced spring/summer winds, and increased water column stability via enhanced salinity-driven density gradients. Years of positive chl-a anomalies are associated with the initiation of a robust krill cohort the following summer, which is evident in Adelie penguin diets, thus demonstrating tight trophic coupling. Projected climate change in this region may have a significant, negative impact on phytoplankton biomass, krill recruitment and upper trophic level predators in this coastal Antarctic ecosystem

Spring bloom dynamics and zooplankton biomass response on the US Northeast Continental Shelf

This paper is not subject to U.S. copyright. The definitive version was published in Continental Shelf Research 102 (2015): 47-61, doi:10.1016/j.csr.2015.04.005.The spring phytoplankton bloom on the US Northeast Continental Shelf is a feature of the ecosystem production cycle that varies annually in timing, spatial extent, and magnitude. To quantify this variability, we analyzed remotely-sensed ocean color data at two spatial scales, one based on ecologically defined sub-units of the ecosystem (production units) and the other on a regular grid (0.5°). Five units were defined: Gulf of Maine East and West, Georges Bank, and Middle Atlantic Bight North and South. The units averaged 47×103 km2 in size. The initiation and termination of the spring bloom were determined using change-point analysis with constraints on what was identified as a bloom based on climatological bloom patterns. A discrete spring bloom was detected in most years over much of the western Gulf of Maine production unit. However, bloom frequency declined in the eastern Gulf of Maine and transitioned to frequencies as low as 50% along the southern flank of the Georges Bank production unit. Detectable spring blooms were episodic in the Middle Atlantic Bight production units. In the western Gulf of Maine, bloom duration was inversely related to bloom start day; thus, early blooms tended to be longer lasting and larger magnitude blooms. We view this as a phenological mismatch between bloom timing and the “top-down” grazing pressure that terminates a bloom. Estimates of secondary production were available from plankton surveys that provided spring indices of zooplankton biovolume. Winter chlorophyll biomass had little effect on spring zooplankton biovolume, whereas spring chlorophyll biomass had mixed effects on biovolume. There was evidence of a “bottom up” response seen on Georges Bank where spring zooplankton biovolume was positively correlated with the concentration of chlorophyll. However, in the western Gulf of Maine, biovolume was uncorrelated with chlorophyll concentration, but was positively correlated with bloom start and negatively correlated with magnitude. This observation is consistent with both a “top-down” mechanism of control of the bloom and a “bottom-up” effect of bloom timing on zooplankton grazing. Our inability to form a consistent model of these relationships across adjacent systems underscores the need for further research

Seasonal Phytoplankton Blooms in the North Atlantic Linked to the Overwintering Strategies of Copepods

The North Atlantic Ocean contains diverse patterns of seasonal phytoplankton blooms with distinct internal dynamics. We analyzed blooms using remotely-sensed chlorophyll a concentration data and change point statistics. The first bloom of the year began during spring at low latitudes and later in summer at higher latitudes. In regions where spring blooms occurred at high frequency (i. e., proportion of years that a bloom was detected), there was a negative correlation between bloom timing and duration, indicating that early blooms last longer. In much of the Northeast Atlantic, bloom development extended over multiple seasons resulting in peak chlorophyll concentrations in summer. Spring bloom start day was found to be positively correlated with a spring phenology index and showed both positive and negative correlations to sea surface temperature and the North Atlantic Oscillation in different regions. Based on the characteristics of spring and summer blooms, the North Atlantic can be classified into two regions: a seasonal bloom region, with a well-defined bloom limited to a single season; and a multi-seasonal bloom region, with blooms extending over multiple seasons. These regions differed in the correlation between bloom start and duration with only the seasonal bloom region showing a significant, negative correlation. We tested the hypothesis that the near-surface springtime distribution of copepods that undergo diapause (Calanus finmarchicus, C. helgolandicus, C. glacialis, and C. hyperboreus) may contribute to the contrast in bloom development between the two regions. Peak near-surface spring abundance of the late stages of these Calanoid copepods was generally associated with areas having a well-defined seasonal bloom, implying a link between bloom shape and their abundance. We suggest that either grazing is a factor in shaping the seasonal bloom or bloom shape determines whether a habitat is conducive to diapause, while recognizing that both factors can re-enforce each other

Seasonal Phytoplankton Blooms in the North Atlantic Linked to the Overwintering Strategies of Copepods

The North Atlantic Ocean contains diverse patterns of seasonal phytoplankton blooms with distinct internal dynamics. We analyzed blooms using remotely-sensed chlorophyll a concentration data and change point statistics. The first bloom of the year began during spring at low latitudes and later in summer at higher latitudes. In regions where spring blooms occurred at high frequency (i. e., proportion of years that a bloom was detected), there was a negative correlation between bloom timing and duration, indicating that early blooms last longer. In much of the Northeast Atlantic, bloom development extended over multiple seasons resulting in peak chlorophyll concentrations in summer. Spring bloom start day was found to be positively correlated with a spring phenology index and showed both positive and negative correlations to sea surface temperature and the North Atlantic Oscillation in different regions. Based on the characteristics of spring and summer blooms, the North Atlantic can be classified into two regions: a seasonal bloom region, with a well-defined bloom limited to a single season; and a multi-seasonal bloom region, with blooms extending over multiple seasons. These regions differed in the correlation between bloom start and duration with only the seasonal bloom region showing a significant, negative correlation. We tested the hypothesis that the near-surface springtime distribution of copepods that undergo diapause (Calanus finmarchicus, C. helgolandicus, C. glacialis, and C. hyperboreus) may contribute to the contrast in bloom development between the two regions. Peak near-surface spring abundance of the late stages of these Calanoid copepods was generally associated with areas having a well-defined seasonal bloom, implying a link between bloom shape and their abundance. We suggest that either grazing is a factor in shaping the seasonal bloom or bloom shape determines whether a habitat is conducive to diapause, while recognizing that both factors can re-enforce each other

Climate Driven Egg and Hatchling Mortality Threatens Survival of Eastern Pacific Leatherback Turtles

Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El Niño Southern Oscillation (ENSO). Drier and warmer conditions associated with El Niño increased egg and hatchling mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly decline in the region over the next 100 years by ∼50–60%, due to warming and drying in northwestern Costa Rica, threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in other areas affected by similar climate changes

Electrical modalities beyond pacing for the treatment of heart failure

In this review, we report on electrical modalities, which do not fit the definition of pacemaker, but increase cardiac performance either by direct application to the heart (e.g., post-extrasystolic potentiation or non-excitatory stimulation) or indirectly through activation of the nervous system (e.g., vagal or sympathetic activation). The physiological background of the possible mechanisms of these electrical modalities and their potential application to treat heart failure are discussed

Mutations in sphingosine-1-phosphate lyase cause nephrosis with ichthyosis and adrenal insufficiency

Steroid-resistant nephrotic syndrome (SRNS) causes 15% of chronic kidney disease cases. A mutation in 1 of over 40 monogenic genes can be detected in approximately 30% of individuals with SRNS whose symptoms manifest before 25 years of age. However, in many patients, the genetic etiology remains unknown. Here, we have performed whole exome sequencing to identify recessive causes of SRNS. In 7 families with SRNS and facultative ichthyosis, adrenal insufficiency, immunodeficiency, and neurological defects, we identified 9 different recessive mutations in SGPL1, which encodes sphingosine-1-phosphate (S1P) lyase. All mutations resulted in reduced or absent SGPL1 protein and/or enzyme activity. Overexpression of cDNA representing SGPL1 mutations resulted in subcellular mislocalization of SGPL1. Furthermore, expression of WT human SGPL1 rescued growth of SGPL1-deficient dpl1. yeast strains, whereas expression of disease-associated variants did not. Immunofluorescence revealed SGPL1 expression in mouse podocytes and mesangial cells. Knockdown of Sgpl1 in rat mesangial cells inhibited cell migration, which was partially rescued by VPC23109, an S1P receptor antagonist. In Drosophila, Sply mutants, which lack SGPL1, displayed a phenotype reminiscent of nephrotic syndrome in nephrocytes. WT Sply, but not the disease-associated variants, rescued this phenotype. Together, these results indicate that SGPL1 mutations cause a syndromic form of SRNS