Fast and Pervasive Transcriptomic Resilience and Acclimation of Extremely Heat-Tolerant Coral Holobionts from the Northern Red Sea

Corals from the northern Red Sea and Gulf of Aqaba exhibit extreme thermal tolerance. To examine the underlying gene expression dynamics, we exposed Stylophora pistillata from the Gulf of Aqaba to short-term (hours) and long-term (weeks) heat stress with peak seawater temperatures ranging from their maximum monthly mean of 27 °C (baseline) to 29.5 °C, 32 °C, and 34.5 °C. Corals were sampled at the end of the heat stress as well as after a recovery period at baseline temperature. Changes in coral host and symbiotic algal gene expression were determined via RNA-sequencing (RNA-Seq). Shifts in coral microbiome composition were detected by complementary DNA (cDNA)-based 16S ribosomal RNA (rRNA) gene sequencing. In all experiments up to 32 °C, RNA-Seq revealed fast and pervasive changes in gene expression, primarily in the coral host, followed by a return to baseline gene expression for the majority of coral (\u3e94%) and algal (\u3e71%) genes during recovery. At 34.5 °C, large differences in gene expression were observed with minimal recovery, high coral mortality, and a microbiome dominated by opportunistic bacteria (including Vibrio species), indicating that a lethal temperature threshold had been crossed. Our results show that the S. pistillata holobiont can mount a rapid and pervasive gene expression response contingent on the amplitude and duration of the thermal stress. We propose that the transcriptomic resilience and transcriptomic acclimation observed are key to the extraordinary thermal tolerance of this holobiont and, by inference, of other northern Red Sea coral holobionts, up to seawater temperatures of at least 32 °C, that is, 5 °C above their current maximum monthly mean

Empirically Derived Thermal Thresholds of Four Coral Species Along the Red Sea Using a Portable and Standardized Experimental Approach

Global warming is causing an unprecedented loss of species and habitats worldwide. This is particularly apparent for tropical coral reefs, with an increasing number of reefs experiencing mass bleaching and mortality on an annual basis. As such, there is a growing need for a standardized experimental approach to rapidly assess the thermal limits of corals and predict the survival of coral species across reefs and regions. Using a portable experimental system, the Coral Bleaching Automated Stress System (CBASS), we conducted standardized 18 h acute thermal stress assays to quantitively determine the upper thermal limits of four coral species across the length of the Red Sea coastline, from the Gulf of Aqaba (GoA) to Djibouti (~ 2100 km). We measured dark-acclimated photosynthetic efficiency (Fv/Fm), algal symbiont density, chlorophyll a, and visual bleaching intensity following heat stress. Fv/Fm was the most precise response variable assessed, advancing the Fv/Fm effective dose 50 (ED50, i.e., the temperature at which 50% of the initial Fv/Fm is measured) as an empirically derived proxy for thermal tolerance. ED50 thermal thresholds from the central/southern Red Sea and Djibouti populations were consistently higher for Acropora hemprichii, Pocillopora verrucosa, and Stylophora pistillata (0.1–1.8 °C above GoA corals, respectively), in line with prevailing warmer maximum monthly means (MMMs), though were lower than GoA corals relative to site MMMs (1.5–3.0 °C). P. verrucosa had the lowest thresholds overall. Despite coming from the hottest site, thresholds were lowest for Porites lobata in the southern Red Sea, suggesting long-term physiological damage or ongoing recovery from a severe, prior bleaching event. Altogether, the CBASS resolved historical, taxonomic, and possibly recent environmental drivers of variation in coral thermal thresholds, highlighting the potential for a standardized, short-term thermal assay as a universal approach for assessing ecological and evolutionary variation in the upper thermal limits of corals

What is the correct cost functional for variational data assimilation?

Variational approaches to data assimilation, and weakly constrained four dimensional variation (WC-4DVar) in particular, are important in the geosciences but also in other communities (often under different names). The cost functions and the resulting optimal trajectories may have a probabilistic interpretation, for instance by linking data assimilation with maximum aposteriori (MAP) estimation. This is possible in particular if the unknown trajectory is modelled as the solution of a stochastic differential equation (SDE), as is increasingly the case in weather forecasting and climate modelling. In this situation, the MAP estimator (or “most probable path” of the SDE) is obtained by minimising the Onsager–Machlup functional. Although this fact is well known, there seems to be some confusion in the literature, with the energy (or “least squares”) functional sometimes been claimed to yield the most probable path. The first aim of this paper is to address this confusion and show that the energy functional does not, in general, provide the most probable path. The second aim is to discuss the implications in practice. Although the mentioned results pertain to stochastic models in continuous time, they do have consequences in practice where SDE’s are approximated by discrete time schemes. It turns out that using an approximation to the SDE and calculating its most probable path does not necessarily yield a good approximation to the most probable path of the SDE proper. This suggest that even in discrete time, a version of the Onsager–Machlup functional should be used, rather than the energy functional, at least if the solution is to be interpreted as a MAP estimator

The Coral Bleaching Automated Stress System (CBASS): A low‐cost, portable system for standardized empirical assessments of coral thermal limits

Ocean warming is increasingly affecting marine ecosystems across the globe. Reef-building corals are particularly affected by warming, with mass bleaching events increasing in frequency and leading to widespread coral mortality. Yet, some corals can resist or recover from bleaching better than others. Such variability in thermal resilience could be critical to reef persistence; however, the scientific community lacks standardized diagnostic approaches to rapidly and comparatively assess coral thermal vulnerability prior to bleaching events. We present the Coral Bleaching Automated Stress System (CBASS) as a low-cost, open-source, field-portable experimental system for rapid empirical assessment of coral thermal thresholds using standardized temperature stress profiles and diagnostics. The CBASS consists of four or eight flow-through experimental aquaria with independent water masses, lighting, and individual automated temperature controls capable of delivering custom modulating thermal profiles. The CBASS is used to conduct daily thermal stress exposures that typically include 3-h temperature ramps to multiple target temperatures, a 3-h hold period at the target temperatures, and a 1-h ramp back down to ambient temperature, followed by an overnight recovery period. This mimics shallow water temperature profiles observed in coral reefs and prompts a rapid acute heat stress response that can serve as a diagnostic tool to identify putative thermotolerant corals for in-depth assessments of adaptation mechanisms, targeted conservation, and possible use in restoration efforts. The CBASS is deployable within hours and can assay up to 40 coral fragments/aquaria/day, enabling high-throughput, rapid determination of thermal thresholds for individual genotypes, populations, species, and sites using a standardized experimental framework

The Coral Bleaching Automated Stress System (CBASS): A Low-Cost, Portable System for Standardized Empirical Assessments of Coral Thermal Limits

Ocean warming is increasingly affecting marine ecosystems across the globe. Reef-building corals are particularly affected by warming, with mass bleaching events increasing in frequency and leading to widespread coral mortality. Yet, some corals can resist or recover from bleaching better than others. Such variability in thermal resilience could be critical to reef persistence; however, the scientific community lacks standardized diagnostic approaches to rapidly and comparatively assess coral thermal vulnerability prior to bleaching events. We present the Coral Bleaching Automated Stress System (CBASS) as a low-cost, open-source, field-portable experimental system for rapid empirical assessment of coral thermal thresholds using standardized temperature stress profiles and diagnostics. The CBASS consists of four or eight flow-through experimental aquaria with independent water masses, lighting, and individual automated temperature controls capable of delivering custom modulating thermal profiles. The CBASS is used to conduct daily thermal stress exposures that typically include 3-h temperature ramps to multiple target temperatures, a 3-h hold period at the target temperatures, and a 1-h ramp back down to ambient temperature, followed by an overnight recovery period. This mimics shallow water temperature profiles observed in coral reefs and prompts a rapid acute heat stress response that can serve as a diagnostic tool to identify putative thermotolerant corals for in-depth assessments of adaptation mechanisms, targeted conservation, and possible use in restoration efforts. The CBASS is deployable within hours and can assay up to 40 coral fragments/aquaria/day, enabling high-throughput, rapid determination of thermal thresholds for individual genotypes, populations, species, and sites using a standardized experimental framework

An international initiative of predicting the Sars-Cov-2 pandemic using ensemble data assimilation

This work demonstrates the efficiency of using iterative ensemble smoothers to estimate the parameters of an SEIR model. We have extended a standard SEIR model with age-classes and compartments of sick, hospitalized, and dead. The data conditioned on are the daily numbers of accumulated deaths and the number of hospitalized. Also, it is possible to condition the model on the number of cases obtained from testing. We start from a wide prior distribution for the model parameters; then, the ensemble conditioning leads to a posterior ensemble of estimated parameters yielding model predictions in close agreement with the observations. The updated ensemble of model simulations has predictive capabilities and include uncertainty estimates. In particular, we estimate the effective reproductive number as a function of time, and we can assess the impact of different intervention measures. By starting from the updated set of model parameters, we can make accurate short-term predictions of the epidemic development assuming knowledge of the future effective reproductive number. Also, the model system allows for the computation of long-term scenarios of the epidemic under different assumptions. We have applied the model system on data sets from several countries, i.e., the four European countries Norway, England, The Netherlands, and France; the province of Quebec in Canada; the South American countries Argentina and Brazil; and the four US states Alabama, North Carolina, California, and New York. These countries and states all have vastly different developments of the epidemic, and we could accurately model the SARS-CoV-2 outbreak in all of them. We realize that more complex models, e.g., with regional compartments, may be desirable, and we suggest that the approach used here should be applicable also for these models

The seasonal nitrogen cycle in Wilkinson Basin, Gulf of Maine, as estimated by 1-D biological model optimization

Author Posting. © Elsevier B.V., 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 78 (2009): 77-93, doi:10.1016/j.jmarsys.2009.04.001.The objective of this study was to fit a simple ecosystem model to climatological nitrogen cycle data in the Gulf of Maine, in order to calibrate the biological model for use in future 3-D modelling studies. First depth-dependent monthly climatologies of nitrate, ammonium, chlorophyll, zooplankton, detritus and primary production data from Wilkinson Basin, Gulf of Maine, were created. A 6-box nitrogen-based ecosystem model was objectively fitted to the data through parameter optimization. Optimization was based on weighted least squares with model-data misfits nondi- mensionalized by assigned uncertainties in the monthly climatological estimates. These uncertainties were estimated as the standard deviations of the raw data from the 6-meter and monthly bin averages. On average the model fits the monthly means almost within their assigned uncertainties. Several statistics are examined to assess model-data misfit. Pattern statistics such as the correlation coefficient lack practical significance when data errors are large relative to the signal, as in this application. Thus Taylor diagrams were not found to be useful. The RMSE and model bias normalized by the data error were found to be the most useful skill metrics as they indicate whether the model fits the data within its estimated error. The optimal simulated nitrogen cycle budgets are presented, as an estimate of the seasonal nitrogen cycle in Wilkinson Basin, and discussed in context of the available data.Wilkinson Basin has spring and fall phytoplankton blooms, and strong summer stratification with a deep chlorophyll maximum near 21 m, just above the nitracline. The mean euphotic zone depth is estimated to be 25 m, relatively constant with season. The model estimates annual primary production as 176 g C m−2 yr−1, annual new production as 71 g C m−2 yr−1 and sinking PON fluxes of 9.7 and 4.7 g N m−2 yr−1 at 24 and 198 m respectively. Areas for improvement in the biological model, the model optimization method, and significant data gaps are identified.This work was supported by ONR, NSF, and NOAA grant to Dennis McGillicuddy

Repurposing NGO data for better research outcomes: A scoping review of the use and secondary analysis of NGO data in health policy and systems research

Background Non-government organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas including the evaluation of health policy and programmes. Methods A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytic approach provided a comprehensive overview and descriptive analyses of the studies which: 1) used data produced or collected by or about NGOs; 2) performed secondary analysis of the NGO data (beyond use of an NGO report as a supporting reference); 3) used NGO-collected clinical data. Results Of the 156 studies which performed secondary analysis of NGO-produced or collected data, 64% (n=100) used NGO-produced reports (e.g. to critique NGO activities and as a contextual reference) and 8% (n=13) analysed NGO-collected clinical data.. Of the studies, 55% investigated service delivery research topics, with 48% undertaken in developing countries and 17% in both developing and developed. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), with some limitations such as inconsistencies and missing data. Conclusion We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics, such as conflict-affected areas. NGO–academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. Their use could enable relevant and timely research in the areas of health policy, programme evaluation and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries

Hepatic transcriptional responses in Atlantic salmon (Salmo salar) exposed to gamma radiation and depleted uranium singly and in combination

acceptedVersio