Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Solar irradiance dictates settlement timing and intensity of marine mussels.

ABSTRACT: Identifying the environmental factors driving larval settlement processes is crucial to understand the population dynamics of marine invertebrates. This work aims to go a step ahead and predict larval presence and intensity. For this purpose we consider the influence of solar irradiance, wind regime and continental runoff on the settlement processes. For the first time, we conducted a 5-years weekly monitoring of Mytilus galloprovincialis settlement on artificial suspended substrates, which allowed us to search for interannual variability in the settlement patterns. Comparison between the seasonal pattern of larval settlement and solar irradiance, as well as the well-known effect of solar irradiance on water temperature and food availability, suggest that solar irradiance indirectly influences the settlement process, and support the use of this meteorological variable to predict settlement occurrence. Our results show that solar irradiance allows predicting the beginning and end of the settlement cycle a month in advance: Particularly we have observed that solar irradiance during late winter indirectly drives the timing and intensity of the settlement onset, Finally, a functional generalise additive model, which considers the influence of solar irradiance and continental runoff on the settlement process, provides an accurate prediction of settlement intensity a fortnight in advance.

SUBMITTER: Fuentes-Santos I

PROVIDER: S-EPMC4935941 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Placing limits on long-term variations in quiet-Sun irradiance and their contribution to total solar irradiance and solar radiative forcing of climate.

Project description:Recent reconstructions of total solar irradiance (TSI) postulate that quiet-Sun variations could give significant changes to the solar power input to Earth's climate (radiative climate forcings of 0.7-1.1 W m-2 over 1700-2019) arising from changes in quiet-Sun magnetic fields that have not, as yet, been observed. Reconstructions without such changes yield solar forcings that are smaller by a factor of more than 10. We study the quiet-Sun TSI since 1995 for three reasons: (i) this interval shows rapid decay in average solar activity following the grand solar maximum in 1985 (such that activity in 2019 was broadly equivalent to that in 1900); (ii) there is improved consensus between TSI observations; and (iii) it contains the first modelling of TSI that is independent of the observations. Our analysis shows that the most likely upward drift in quiet-Sun radiative forcing since 1700 is between +0.07 and -0.13 W m-2. Hence, we cannot yet discriminate between the quiet-Sun TSI being enhanced or reduced during the Maunder and Dalton sunspot minima, although there is a growing consensus from the combinations of models and observations that it was slightly enhanced. We present reconstructions that add quiet-Sun TSI and its uncertainty to models that reconstruct the effects of sunspots and faculae.

| S-EPMC7428030 | biostudies-literature

Girasol, a sky imaging and global solar irradiance dataset.

Project description:The energy available in a microgrid that is powered by solar energy is tightly related to the weather conditions at the moment of generation. A very short-term forecast of solar irradiance provides the microgrid with the capability of automatically controlling the dispatch of energy. We propose a dataset to forecast Global Solar Irradiance (GSI) using a data acquisition system (DAQ) that simultaneously records sky imaging and GSI measurements, with the objective of extracting features from clouds and use them to forecast the power produced by a Photovoltaic (PV) system. The DAQ system is nicknamed the Girasol Machine (Girasol means Sunflower in Spanish). The sky imaging system consists of a longwave infrared (IR) camera and a visible (VI) light camera with a fisheye lens attached to it. The cameras are installed inside a weatherproof enclosure that it is mounted on a solar tracker. The tracker updates its pan and tilt every second using a solar position algorithm to maintain the Sun in the center of the IR and VI images. A pyranometer is situated on a horizontal mount next to the DAQ system to measure GSI. The dataset, composed of IR images, VI images, GSI measurements, and the Sun's positions, has been tagged with timestamps.

| S-EPMC7988281 | biostudies-literature

Validation of trophic and anthropic underwater noise as settlement trigger in blue mussels.

Project description:Like the majority of benthic invertebrates, the blue mussel Mytilus edulis has a bentho-pelagic cycle with its larval settlement being a complex phenomenon involving numerous factors. Among these factors, underwater noise and pelagic trophic conditions have been weakly studied in previous researches. Under laboratory conditions, we tested the hypothesis that picoplankton assimilation by the pediveliger blue mussel larvae acts as a food cue that interacts with anthropic underwater sound to stimulate settlement. We used (13)C-labeling microalgae to validate the assimilation of different picoplankton species in the tissues of pediveliger larvae. Our results clearly confirm our hypothesis with a significant synergic effect of these two factors. However, only the picoeukaryotes strains assimilated by larvae stimulated the settlement, whereas the non-ingested picocyanobacteria did not. Similar positive responses were observed with underwater sound characterized by low frequency vessel noises. The combination of both factors (trophic and vessel noise) drastically increased the mussel settlement by an order of 4 compared to the control (without picoplankton and noise). Settlement levels ranged from 16.5 to 67% in 67?h.

| S-EPMC5028714 | biostudies-other

The total solar irradiance during the recent solar minimum period measured by SOHO/VIRGO.

Project description:Various space missions have measured the total solar irradiance (TSI) since 1978. Among them the experiments Precision Monitoring of Solar Variability (PREMOS) on the PICARD satellite (2010-2014) and the Variability of Irradiance and Gravity Oscillations (VIRGO) on the mission Solar and Heliospheric Observatory, which started in 1996 and is still operational. Like most TSI experiments, they employ a dual-channel approach with different exposure rates to track and correct the inevitable degradation of their radiometers. Until now, the process of degradation correction has been mostly a manual process based on assumed knowledge of the sensor hardware. Here we present a new data-driven process to assess and correct instrument degradation using a machine-learning and data fusion algorithm, that does not require deep knowledge of the sensor hardware. We apply the algorithm to the TSI records of PREMOS and VIRGO and compare the results to the previously published results. The data fusion part of the algorithm can also be used to combine data from different instruments and missions into a composite time series. Based on the fusion of the degradation-corrected VIRGO/PMO6 and VIRGO/DIARAD time series, we find no significant change (i.e [Formula: see text] W/m[Formula: see text]) between the TSI levels during the two most recent solar minima in 2008/09 and 2019/20. The new algorithm can be applied to any TSI experiment that employs a multi-channel philosophy for degradation tracking. It does not require deep technical knowledge of the individual radiometers.

| S-EPMC8035225 | biostudies-literature

Pollutants bioavailability and toxicological risk from NSAIDs to marine mussels

Project description:Pharmaceutical compounds are emerging contaminants in aquatic environment due to their massive use (human and veterinary medicines, agriculture and aquaculture) and a limited removal by waste water treatment plants (WWTPs). In this work, a representative determination of ecotoxicological potential of two different NSAIDs compounds was studied in the sensitive bioindicator marine organism M. Galloprovincialis. Mussels were exposed, under regulated laboratory conditions, to Ketoprofen (KET) and Nimesulide (NIM), dosed alone at the realistic environmental concentration of 0.5µg/L for 14 days. Gene expression analyses of Mytilus galloprovincialis exposed to KET and NIM have been performed through a DNA microarray platform.

2016-02-22 | GSE66990 | GEO

Pollutants bioavailability and toxicological risk from microplastics to marine mussels

Project description:Microplastics represent a growing environmental concern for the oceans due to their potential capability to adsorb different classes of pollutants, thus representing a still unexplored source of exposure for aquatic organisms. In this study polystyrene (PS) microplastics were characterized for their capability to adsorb pyrene (PYR) as model compound for polycyclic aromatic hydrocarbons, and transfer this chemical to filter feeding mussels Mytilus galloprovincialis. Gene expression analyses of Mytilus galloprovincialis exposed to polystyrene (PS) microplastics and to polystyrene contaminated with pyrene (PS-PYR) have been performed trough a DNA microarray platform.

2014-12-27 | GSE57460 | GEO

Interdependent photo- and chemosensory systems regulate larval settlement in a marine sponge

Project description:Marine pelagic larvae from throughout the animal kingdom use a hierarchy of environmental cues to identify a suitable benthic habitat on which to settle and metamorphose into the reproductive phase of the life cycle. The majority of larvae are induced to settle by biochemical cues and many species have long been known to preferentially settle in the dark. Combined, these data suggest that larval responses to light and biochemical cues may be linked, but this is yet to be explored at the molecular level. Here, we track vertical position of larvae of the sponge Amphimedon queenslandica to show that they descend to the benthos at twilight, by which time they are competent to respond to biochemical cues, consistent with them naturally settling in the dark. We then conduct larval settlement assays under three different light regimes (natural day-night, constant dark or constant light), and use transcriptomics on individual larvae to identify candidate molecular pathways underlying the different settlement responses that we observe. We find that constant light prevents larval settlement in response to biochemical cues, likely via actively repressing chemostransduction; this is consistent with the sustained upregulation of a photosensory cryptochrome and two putative inactivators of G-protein signalling in the constant light only. We hypothesise that photo- and chemosensory systems may be hierarchically integrated into ontogeny to regulate larval settlement via nitric oxide (NO) and cyclic guanosine monophosphate (cGMP) signalling in this sponge that belongs to one of the earliest branching of the extant animal lineages.

2019-10-09 | GSE130274 | GEO

The impacts of thermal heterogeneity across microhabitats on post-settlement selection of intertidal mussels.

Project description:Rapid genetic selection is critical for allowing natural populations to adapt to different thermal environments such as those that occur across intertidal microhabitats with high degrees of thermal heterogeneity. To address the question of how thermal regimes influence selection and adaptation in the intertidal black mussel Mytilisepta virgata, we continuously recorded environmental temperatures in both tidal pools and emergent rock microhabitats and then assessed genetic differentiation, gene expression patterns, RNA editing level, and cardiac performance. Our results showed that the subpopulations in the tidal pool and on emergent rocks had different genetic structures and exhibited different physiological and molecular responses to high-temperature stress. These results indicate that environmental heterogeneity across microhabitats is important for driving genetic differentiation and shed light on the importance of post-settlement selection for adaptively modifying the genetic composition and thermal responses of these intertidal mussels.

| S-EPMC10682278 | biostudies-literature

Intra-hour irradiance forecasting techniques for solar power integration: a review.

Project description:The ever-growing installation of solar power systems imposes severe challenges on the operations of local and regional power grids due to the inherent intermittency and variability of ground-level solar irradiance. In recent decades, solar forecasting methodologies for intra-hour, intra-day and day-ahead energy markets have been extensively explored as cost-effective technologies to mitigate the negative effects on the power grids caused by solar power instability. In this work, the progress in intra-hour solar forecasting methodologies are comprehensively reviewed and concisely summarized. The theories behind the forecasting methodologies and how these theories are applied in various forecasting models are presented. The reviewed mathematical tools include regressive methods, stochastic learning methods, deep learning methods, and genetic algorithm. The reviewed forecasting methodologies include data-driven methods, local-sensing methods, hybrid forecasting methods, and application orientated methods that generate probabilistic forecasts and spatial forecasts. Furthermore, suggestions to accelerate the development of future intra-hour forecasting methods are provided.

| S-EPMC8531863 | biostudies-literature

A deep learning virtual instrument for monitoring extreme UV solar spectral irradiance.

Project description:Measurements of the extreme ultraviolet (EUV) solar spectral irradiance (SSI) are essential for understanding drivers of space weather effects, such as radio blackouts, and aerodynamic drag on satellites during periods of enhanced solar activity. In this paper, we show how to learn a mapping from EUV narrowband images to spectral irradiance measurements using data from NASA's Solar Dynamics Observatory obtained between 2010 to 2014. We describe a protocol and baselines for measuring the performance of models. Our best performing machine learning (ML) model based on convolutional neural networks (CNNs) outperforms other ML models, and a differential emission measure (DEM) based approach, yielding average relative errors of under 4.6% (maximum error over emission lines) and more typically 1.6% (median). We also provide evidence that the proposed method is solving this mapping in a way that makes physical sense and by paying attention to magnetic structures known to drive EUV SSI variability.

| S-EPMC6774717 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data