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163 results for “temporal variability”
Data from: Temporal variability in snow accumulation and density at Summit Camp, Greenland ice sheet
<p>A 3-year record of weekly snow water equivalent (SWE) accumulation at Summit Camp, central Greenland ice sheet, obtained by direct sampling, is presented. While the overall SWE accumulation of 24.2 cm w.e. a<sup>−1</sup> matches long-term ice core estimates, variability increases at shorter timescales. Half of the annual SWE accumulation occurs during a few large events, with the average accumulation rate decreasing 35% between the first and second halves of the record coinciding with exceptional anticyclonic conditions in the spring and summer of 2019. No seasonality in accumulation is detected. Rather, local accumulation rates appear to be significantly impacted by wind redistribution that obscures temporal patterns in snowfall. Surface snow density is consistent, on average, with previously measured values but does not correlate with near surface temperature or wind speed. Two surface mass balance reanalysis models significantly underestimate accumulation rates at Summit Camp. This is concerning because such models are often used to estimate ice-sheet mass loss.</p>
Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations
<p>This dataset contains the NPOCE (http://npoce.org.cn) data used in the following submission for Journal of Geophysical Research: Oceans:</p> <p>Hu, S., J. Sprintall, C. Guan, B. Sun, F. Wang, G. Yang, F. Jia, J. Wang, D. Hu, and F. Chai (2018), Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations, Journal of Geophysical Research: Oceans.</p> <p>Variables in this dataset are eddy kinetic energy (EKE) observed by the NPOCE moorings, longitudes, latitudes, depths and dates.</p> <p> </p> <p> </p>
Code and Data for "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.
<p>This repository contains the code and data for the study of "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.</p> <p>Specifically, this repository contains the following items: </p> <p>(1) The codes needed for assessing the representation and prediction skills of Random Forest (RF) and Convolutional Neural Network (CNN) models. </p> <p>(2) Original and normalized data to run these codes.</p> <p>(3) Code here is built on early work from our laboratory (Guan et al., 2022; Zhang et al., 2023), though great modifications have been made tailored to our scientific question.</p> <div>[1] Guan, W., Chen, R., Zhang, H., Yang, Y., & Wei, H. (2022). Seasonal surface eddy mixing in the Kuroshio Extension: Estimation and machine learning prediction. Journal of Geophysical Research: Oceans, 127 (3), e2021JC017967.</div> <div>[2] Zhang, G., Chen, R., Li, X., Li, L., Wei, H., & Guan, W. (2023). Temporal variability of global surface eddy diffusivities: Estimates and machine learning prediction. Journal of Physical Oceanography, 53 (7), 1711–1730.</div>
Data from: Habitat connectivity and in-stream vegetation control temporal variability of benthic invertebrate communities
One of the key challenges to understanding patterns of β diversity is to disentangle deterministic patterns from stochastic ones. Stochastic processes may mask the influence of deterministic factors on community dynamics, hindering identification of the mechanisms causing variation in community composition. We studied temporal β diversity (among-year dissimilarity) of macroinvertebrate communities in near-pristine boreal streams across 14 years. To assess whether the observed β diversity deviates from that expected by chance, and to identify processes (deterministic vs. stochastic) through which different explanatory factors affect community variability, we used a null model approach. We observed that at the majority of sites temporal β diversity was low indicating high community stability. When stochastic variation was unaccounted for, connectivity was the only variable explaining temporal β diversity, with weakly connected sites exhibiting higher community variability through time. After accounting for stochastic effects, connectivity lost importance, suggesting that it was related to temporal β diversity via random colonization processes. Instead, β diversity was best explained by in-stream vegetation, community variability decreasing with increasing bryophyte cover. These results highlight the potential of stochastic factors to dampen the influence of deterministic processes, affecting our ability to understand and predict changes in biological communities through time.
Data from: The ghost of introduction past: spatial and temporal variability in the genetic diversity of invasive smallmouth bass
Understanding the demographic history of introduced populations is essential for unravelling their invasive potential and adaptability to a novel environment. To this end, levels of genetic diversity within the native and invasive range of a species are often compared. Most studies, however, focus solely on contemporary samples, relying heavily on the premise that the historic population structure within the native range has been maintained over time. Here, we assess this assumption by conducting a three-way comparison of the genetic diversity of native (historic and contemporary) and invasive (contemporary) smallmouth bass (Micropterus dolomieu) populations. Analyses of a total of 572 M. dolomieu samples, representing the contemporary invasive South African range, contemporary and historical native USA range (dating back to the 1930s when these fish were first introduced into South Africa), revealed that the historical native range had higher genetic diversity levels when compared to both contemporary native and invasive ranges. These results suggest that both contemporary populations experienced a recent genetic bottleneck. Furthermore, the invasive range displayed significant population structure, whereas both historical and contemporary native USA populations revealed higher levels of admixture. Comparison of contemporary and historical samples showed both a historic introduction of M. dolomieu, as well as a more recent introduction, thereby demonstrating that undocumented introductions of this species have occurred. Although multiple introductions might have contributed to the high levels of genetic diversity in the invaded range, we discuss alternative factors that may have been responsible for the elevated levels of genetic diversity and highlight the importance of incorporating historic specimens into demographic analyses.
Data from: Long-lived marine species may be resilient to environmental variability through a temporal portfolio effect
<p>Maintenance of a portfolio of adaptive alleles may provide resilience of populations to natural environmental variability. We used Pacific ocean perch (POP; Sebastes alutus) to test for the maintenance of adaptive variation across overlapping generations. POP are a long-lived species characterized by widespread larval dispersal in their first year and a longevity of over 100 years. In order to understand how early marine dispersal affects POP survival and population structure, we used Restriction Site Associated DNA sequencing (RADseq) to obtain 11,146 single-nucleotide polymorphisms (SNPs) from 401 young-of-the-year (YOY) POP collected during surveys conducted in 2014 (19 stations) and 2015 (4 stations) in the eastern Gulf of Alaska. Population clustering analysis showed that the POP samples represented four distinct ancestral populations mixed throughout the sampling area. Based on prior work on larval dispersal of POP, these larvae are most likely from distinct parturition locations that are mixing during their pelagic dispersal life stage. Latent factor mixed models revealed that POP larvae face significant selection during their first year at sea, which were specific to the year of their birth. Thus each adult cohort's genetic composition is heavily influenced by the environmental conditions experienced during their first year at sea. Long-lived species relying on broadcast spawning strategies may therefore be uniquely resilient to environmental variability by maintaining a portfolio of cohort-specific adaptive genotypes, and age truncation due to overfishing of older cohorts may have detrimental effect on the population viability.</p>
Temporal variability of microparticles under the Seattle Aquarium, WA: Documenting the global Covid‐19 pandemic
<p>Anthropogenic debris including microparticles (MP; <5mm) are ubiquitous in marine environments. The Salish Sea experiences seasonal fluctuations in precipitation, river discharge, sewage overflow events, and tourism– all variables previously thought to have an impact on MP transport and concentrations. Our goals are two-fold: 1) Describe long-term MP contamination data including concentration, type, and size and 2) Determine if seasonal MP concentrations are dependent on environmental or tourism variables in Elliott Bay, Salish Sea. We sampled 100 L of seawater at depth (~9 m) at the Seattle Aquarium approximately every two weeks 2019 – 2020 and used an oil extraction protocol to separate MP. We found MP concentrations ranged from 0 – 0.64 particles L⁻¹ and fibers were the most common type observed. Microparticle concentration exhibited a breakpoint on April 10, 2020, where estimated slope and associated MP concentration significantly declined. Further, when considering both environmental as well as tourism variables, temporal MP concentration was best described by a mixed-effects model with tourism as the fixed effect and the person counting MP as the random effect. While monitoring efforts presented here set out to identify effects of seasonality and interannual differences in MP concentrations, it instead captured an effect of decreased tourism due to the global Covid-19 pandemic. Long-term monitoring is critical to establish temporal MP concentrations and to help researchers understand if there are certain events, both seasonal and sporadic (e.g. rain events, tourism, or global pandemics), when the marine environment is more at risk from anthropogenic pollution.</p>
Spatial and temporal drivers of in situ fluorescence quantum yield variability in the Southern Ocean
<p>The datasets in this repository are part of the manuscript entitled "Spatial and temporal drivers of in situ fluorescence quantum yield variability in the Southern Ocean".</p>
Data from: Temporal variability in the environmental and geographic predictors of spatial-recruitment in nearshore rockfishes
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Data from: Accounting for the effects of biological variability and temporal autocorrelation in assessing the preservation of species abundance
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Data from: Submerged macrophytes affect the temporal variability of aquatic ecosystems
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Data from: The ghost of introduction past: spatial and temporal variability in the genetic diversity of invasive smallmouth bass
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Data from: Spatial and temporal variability in propagule limitation of California native grasses
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Data from: Temporal variability and cooperative breeding: testing the bet-hedging hypothesis in the acorn woodpecker
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Data from: Foraging strategies of generalist and specialist Old World nectar bats in response to temporally variable floral resources
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Temporal variability is key to modelling the climatic niche
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Data from: Temporally variable multivariate sexual selection on sexually dimorphic traits in a wild insect population
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Data from: Exploring the temporal variability of a food web using long-term biomonitoring data
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Data from: Long-lived marine species may be resilient to environmental variability through a temporal portfolio effect
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Data from: High temporal variability in the occurrence of consumer–resource interactions in ecological networks
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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.