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84 results for “seasonal variability”
Figure 3 in Seasonal and Interannual Variability of the Barents Sea Temperature
Figure 3. Fields of changes in the average monthly temperature of the Barents Sea (°C over 10 years) at depths of 5 meters (above) and 105 meters (below) calculated from the linear trends of its monthly average anomalies for 1948 - 2016.
Figure 9 in Seasonal and Interannual Variability of the Barents Sea Temperature
Figure 9. Interannual variability of the North Atlantic Oscillation Index (red) and monthly average temperature anomalies of the Barents Sea (blue) at a depth of 5 meters for the period 1948-2016 after applying the Butterworth bandpass filter from 7 to 10 years (above), and the cross-correlation picture of their material transformations without filtering (below). Preliminary removal of linear trends, centering and normalization of the series to their standard deviations were performed.
Figure 2 in Seasonal and Interannual Variability of the Barents Sea Temperature
Figure 2. Fields of average temperature of the Barents Sea at depths of 5 meters (above) and 105 meters (below) for 1948-2016.
Figure 6 in Seasonal and Interannual Variability of the Barents Sea Temperature
Figure 6. Energy spectra (blue) of the monthly average temperature anomalies of the Barents Sea at depths of 5 meters (above) and 105 meters (below) for 1948-2016. A confidence level from 5% (black line at the bottom) to 95% (black line at the top) and a spectrum of red noise (red line between them) were drown. The preliminary normalization of the series to their standard deviations was made.
Figure 1 in Seasonal and Interannual Variability of the Barents Sea Temperature
Figure 1. Series of monthly average temperature anomalies for the Barents Sea at depths of 5, 55, 105, 154 and 222 meters for the period 1948-2016 after applying the 2-year low-frequency Butterworth filter.
FIG. 8. — Auksiivik 174X Feature 567, a in To freeze or to dry: Seasonal variability in caribou processing and storage in the barrenlands of Northern Canada
FIG. 8. — Auksiivik 174X Feature 567, a marrow cracking area. Note anvil and hammer stones near centre of photo.
Seasonal and episodic runup variability on a Caribbean reef-lined beach
<p>This dataset contains data extracted from two cross-shore profiles used in the study. The dataset includes the date of observations, daily total water level (dTWL) for each profile, and the elevation of the vegetation limit for profile 1. The file consists of eight columns arranged in the following order: year, month, day, hour, dTWL for profile 1 (in meters), dTWL for profile 2 (in meters), vegetation limit elevation for profile 1 (in meters), and vegetation limit elevation for profile 2 (in meters).</p>
Code, scripts and data for: Seasonality and competition select for variable germination behavior in perennials
<p class="MsoNoSpacing"><span>The occurrence of within-population variation in germination behavior and associated traits such as seed size has long fascinated evolutionary ecologists. In annuals, unpredictable environments are known to select for bet-hedging strategies causing variation in dormancy duration and germination strategies. Variation in germination timing and associated traits is also commonly observed in perennials and often tracks gradients of environmental predictability. Although bet-hedging is thought to occur less frequently in long-lived organisms, these observations suggest a role of bet-hedging strategies in perennials occupying unpredictable environments. We use complementary analytical and evolutionary simulation models of within-individual variation in germination behavior in seasonal environments to show how bet-hedging interacts with fluctuating selection, life-history traits, and competitive asymmetries among germination strategies. We reveal substantial scope for bet-hedging to produce variation in germination behavior in long-lived plants, when "false starts" to the growing season results in either competitive advantages or increased mortality risk for alternative germination strategies. Additionally, we find that lowering adult survival may, in contrast to classic bet-hedging theory, result in less spreading of germination by decreasing density-dependent competition. These models extend insights from bet-hedging theory to perennials and explore how competitive communities may be affected by ongoing changes in climate and seasonality patterns.</span></p>
Data and code from: Western larch regeneration more sensitive to wildfire-related factors than seasonal climate variability
Open the record for dataset details and reuse information.
Code, scripts and data for: Seasonality and competition select for variable germination behavior in perennials
Open the record for dataset details and reuse information.
Seasonal Variability of Mercury's Sodium Exosphere Deduced from MESSENGER Data and Numerical Simulation
<p>This is the dataset used in "Suzuki et al. (2020). Seasonal variability of Mercury's sodium exosphere deduced from MESSENGER data and numerical simulation. <em>Journal of Geophysical Research: Planets</em>, 125, e2020JE006472. doi:10.1029/2020JE006472".</p>
A seasonal analysis of sea spray aerosol variability across the Southern Ocean
<p>This dataset includes filter based aerosol observations of atmospheric sodium concentration from the Southern Ocean marine boundary layer in summer (2018/19), winter (2019) and spring (2019). Environmental data such as sea surface temperature and wind speed are also included.</p>
Data from: Seasonal variability drives differences in the structure of the calanoid copepod community in two contrasting regions of the Gulf of Mexico
<p>Calanoid copepods (CC) are key contributors to the biological carbon pump and pelagic trophic dynamics. The deep-water regions of Perdido and the Bay of Campeche in the western and southern Gulf of Mexico (GM), respectively, differ in hydrography and productivity, leading to potential differences in copepod biomass and community structure. Zooplankton (0-200 m) were collected from the shelf edge to the deep-water region during the winter and summer autumn 2016. Calanoids contributed 38-60% of total zooplankton biomass and 55-70% of overall copepod abundance. The Bay of Campeche had the highest total zooplankton biovolume (287±120 ml 1000 m<sup>-3</sup>) and total mean copepod abundance (CC and non-calanoids ~146,000 ind. 1000 m<sup>-3</sup>) during summer-autumn, likely resulting from cross-shelf nutrient transport fueling local productivity. Adult females dominated calanoid numerical abundance (43-50%), thus suggesting a high reproductive potential. Cluster analysis showed differences between seasons (~40% dissimilarity) but not regions. Environmental conditions explained 22% of the variability in community composition; the winter assemblage was significantly related to oxygen concentrations, whereas the summer-autumn community was related to warmer conditions and higher integrated chlorophyll-<em>a</em> concentrations. The CC community responded to seasonal changes more than regionally related hydrographic differences, with likely implications for organic matter cycling and export.</p>
The Seasonal Variability in the Semidiurnal Internal Tide; A Comparison between Sea Surface Height and Energetics
<p>This dataset contains data from global HYCOM simulations with realistic atmospheric and tidal forcings. The horizontal resolution is 8 km. Data is stored as netcdf4 classic.</p>
Recent natural variability in global warming weakened phenological mismatch and selection on seasonal timing in great tits (Parus major)
<p></p><p> Climate change has led to phenological shifts in many species, but with large variation in magnitude among species and trophic levels. The poster child example of the resulting phenological mismatches between the phenology of predators and their prey is the great tit (Parus major), where this mismatch led to directional selection for earlier seasonal breeding. Natural climate variability can obscure the impacts of climate change over certain periods, weakening phenological mismatching and selection. Here, we show that selection on seasonal timing indeed weakened significantly over the past two decades as increases in late spring temperatures have slowed down. Consequently, there has been no further advancement in the date of peak caterpillar food abundance, while great tit phenology has continued to advance, thereby weakening the phenological mismatch. We thus show that the relationships between temperature, phenologies of prey and predator, and selection on predator phenology are robust, also in times of a slowdown of warming. Using projected temperatures from a large ensemble of climate simulations that take natural climate variability into account, we show that prey phenology is again projected to advance faster than great tit phenology in the coming decades, and therefore that long-term global warming will intensify phenological mismatches. </p><p></p>
Evaluating the Arabian Sea as a regional source of atmospheric CO2: seasonal variability and drivers
<p>The netCDF file included here corresponds to datasets used in the Biogeosciences paper entitled "Evaluating the Arabian Sea as a regional source of atmospheric CO2: seasonal variability and drivers" by Alain de Verneil, Zouhair Lachkar, Shafer Smith, and Marina Levy</p> <p>The data included here comprises of model output used in the paper to generate figures in the main manuscript. Many of the figures also contain data from publicly available sources, which is detailed in the "Data availability" section at the end of the paper.</p> <p>The data are in standard netCDF file format, readily readable using netCDF tools (i.e. netCDF4 package in Python, ncread function in Matlab, etc.).</p> <p>Variables names, dimensions, and units are described in the metadata within the netCDF file.</p> <p>Questions regarding this dataset and how it can be used to reproduce the results in the article can be forwarded to Alain de Verneil through email at ajd11@nyu.edu</p>
Data underlying the figures "Diabatic Upwelling in the Tropical Pacific: Seasonal and subseasonal variability"
<p>Data for the figures in the paper Diabatic Upwelling in the Tropical Pacific: Seasonal and subseasonal variability </p>
Surface dust coverages on rock targets in Gale crater: Influence of seasonal wind variability, elevation and proximity to aeolian sand fields.
<p>The following dataset accompanies the paper submission to AGU - JGR: Planets for the paper titled: "</p> <p><span>Surface dust coverages on rock targets in Gale crater: Influence of seasonal wind variability, elevation and proximity to aeolian sand fields."</span></p>
Surface Height Displacements and Time-Variable Gravity From Changes in the Seasonal Polar Cap on Mars
<p>This repository is the location at which the data created for Wagner et al. 2024 is located. Info about specific files is included in the README.</p>
Dataset for Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea
<p>Uto Atmospheric and Marine Research Station<br>Finnish Meteorological Institute and Finnish Environment Institute</p> <p>Data Jan 2017 - Dec 2021</p> <p> </p> <p>Data used in:<br>Honkanen, M., Aurela, M., Hatakka, J., Haraguchi, L., <br>Kielosto, S., Mäkelä, T., Seppälä, J., Siiriä, S.-M., <br>Stenbäck, K., Tuovinen, J.-P., Ylöstalo, P., and Laakso, L.: <br>Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea, <br>EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-628, 2024.</p> <p> </p> <p>This research has been supported by the Research Council of Finland project SEASINK (Evolving carbon sinks and sources in coastal<br>seas – will ecosystem response temper or aggravate climate change? project nos. 317297 and 317298), and the JERICO-NEXT and JERICO-S3 projects which have received funding from the European Union Horizon 2020 Research and Innovation Program under grant agreement nos. 654410 and 871153, respectively.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.