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11,506 results for “Dynamics”
Dissolved organic carbon dynamics in an urban desert stream ecosystem in central Arizona-Phoenix: site locations
Variation in stream chemistry is a function of the strength of terrestrial-aquatic linkages, the extent to which surface and groundwater exchanges, and the rate of instream biotic processes. The importance of these variables may fluctuate as a function of climate regime, catchment geomorphology, or level of human impact. A mechanistic understanding of the influence of each of these variables on ecosystem functioning will increase understanding of the role of streams in global nutrient and carbon cycles. Of particular interest is dissolved organic carbon (DOC), an important source of carbon and energy for microbial processes. Respiration by heterotrophic bacterial communities has recently been linked to the quality (ability of microbes to utilize C source) of the DOC pool in streams. DOC not only influences stream nutrient supply, but also the transport of contaminants and the attenuation of UV radiation. This dissertation focused on DOC delivery to two arid-land stream ecosystems, one native desert (Sycamore Creek, AZ), and one urban (Phoenix, AZ). The overall objectives of this work were to (1) document patterns in DOC quantity and chemical composition in response to flooding and groundwater exchange, (2) generate and test hypotheses explaining variation in DOC quantity and quality and (3) relate this variation to microbial activity. In the native desert stream ecosystem, the climate regime influenced seasonal variation in the quantity and quality of DOC inputs, with higher complexity and higher concentrations of DOC in summer monsoonal runoff. In contrast, human alteration of geomorphology and hydrologic flowpaths in the Phoenix metropolitan area significantly influenced streamwater chemistry in comparison to low-impact streams in the Sonoran Desert. In the city, mechanisms of nutrient retention and transformation were often shifted from dominance by biotic to abiotic ones, severely dampening the influence of climate regime and substituting instead the maintenance
Litter Decomposition and Nitrogen Dynamics: Effects of Nitrogen Fertilization on Litter and Soil Decomposition
The influence of inorganic nitrogen (N) inputs on decomposition is poorly understood. Some prior studies suggest that N may reduce the decomposition of substrates with high concentrations of lignin via inhibitory effects on the activity of lignin-degrading enzymes, although such inhibition has not always been demonstrated. The purpose of E145 was to study the effects of nitrogen (N) addition on decomposition of seven substrates ranging in initial lignin concentrations (from 7.4 - 25.6%) over five years in eight different grassland and forest sites in central Minnesota.
Soil organic matter responses to nutrient enrichment in the Nutrient Network:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Soil nutrient analysis:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Dynamics of wood recruitment in streams of the northeastern US
A space-for-time analysis was used to quantify large wood loading to 28 streams in the northeastern US with a range of in-stream and riparian forest characteristics in order to better inform stream restoration and stream management efforts. We documented the current volume and frequency of occurrence of large wood in streams with riparian forests varying in their stage of stand development as well as stream size and gradient. This data set includes wood, stream and riparian forest metrics collected between 2003 and 2007. Linear models relating stream wood characteristics to stream geomorphic and forest characteristics were compared and results can be found in: Warren, D. R., C. E. Kraft, W. S. Keeton, J. S. Nunery and G. E. Likens. 2009. Dynamics of wood recruitment in streams of the northeastern US. Forest Ecology and Management 258(5):804-81 https://doi.org/10.1016/j.foreco.2009.05.020 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
VIIRS/NPP Land Cover Dynamics Yearly L3 Global 500m SIN Grid V001
The VNP22Q2 Version 1 data product was decommissioned on July 31, 2025. Users are encouraged to use the [VNP22Q2](https://doi.org/10.5067/VIIRS/VNP22Q2.002) Version 2 data product.The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics data product provides global land surface phenology (GLSP) metrics at yearly intervals. The VNP22Q2 data product is derived from time series of the two-band Enhanced Vegetation Index (EVI2) calculated from VIIRS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR). Vegetation phenology metrics at 500 meter spatial resolution are identified for up to two detected growing cycles per year.Provided in each VNP22Q2 product are 19 Science Dataset (SDS) layers. The product contains six phenological transition dates: onset of greenness increase, onset of greenness maximum, onset of greenness decrease, onset of greenness minimum, dates of mid-greenup, and senescence phases. The product also includes the growing season length. The greenness related metrics consist of EVI2 onset of greenness increase, EVI2 onset of greenness maximum, EVI2 growing season, rate of greenness increase and rate of greenness decrease. The confidence of phenology detection is provided as greenness agreement growing season, proportion of good quality (PGQ) growing season, PGQ onset greenness increase, PGQ onset greenness maximum, PGQ onset greenness decrease, and PGQ onset greenness minimum. The final layer is quality control specifying the overall quality of the product. A low-resolution browse image showing greenup is also available when viewing each VNP22Q2 granule. Important information is provided in Sections 5 of the User Guide when comparing VNP22Q2 with the MCD12Q2 data product.Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS).
VIIRS/NPP Land Cover Dynamics Yearly L3 Global 0.05 Deg CMG V001
The VNP22C2 Version 1 data product was decommissioned on July 31, 2025. Users are encouraged to use the [VNP22C2](https://doi.org/10.5067/VIIRS/VNP22C2.002) Version 2 data product.The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics data product provides global land surface phenology (GLSP) metrics at yearly intervals. The VNP22C2 data product is derived from time series of the two-band Enhanced Vegetation Index (EVI2) calculated from VIIRS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR). Vegetation phenology metrics at 0.05 degree (~5,600 meters) spatial resolution are identified for up to two detected growing cycles per year. Provided in each VNP22C2 product are 19 Science Dataset (SDS) layers. The product contains six phenological transition dates: onset of greenness increase, onset of greenness maximum, onset of greenness decrease, onset of greenness minimum, dates of mid-greenup, and senescence phases. The product also includes the growing season length. The greenness related metrics consist of EVI2 onset of greenness increase, EVI2 onset of greenness maximum, EVI2 growing season, rate of greenness increase and rate of greenness decrease. The confidence of phenology detection is provided as greenness agreement growing season, proportion of good quality (PGQ) growing season, PGQ onset greenness increase, PGQ onset greenness maximum, PGQ onset greenness decrease, and PGQ onset greenness minimum. The final layer is quality control specifying the overall quality of the product. A low-resolution browse image showing greenup is also available when viewing each VNP22C2 granule. Important information is provided in Section 5 of the User Guide when comparing VNP22C2 with the MCD12C2 data product.Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS).
Data for "Coherent phonon dynamics in spatially-separated graphene mechanical resonators"
<p>Data for "Coherent phonon dynamics in spatially-separated graphene mechanical resonators"</p>
Research data supporting "Remote magnetic nanoparticle manipulation enables the dynamic patterning of cardiac tissues"
<p>Research data supporting the publication:</p> <p>Zwi-Dantsis et al., 2020, Advanced Materials, DOI: 10.1002/adma.201904598.</p>
Role of black carbon in the formation of primary organic aerosols: Insights from molecular dynamics simulations: Supplementary Materials
<p>This zip file contains supplements for the article entitled "Role of black carbon in the formation of primary organic aerosols: Insights from molecular dynamics simulations" authored by Zhou et al. including three different sets of data as follows:</p> <p>data: Data files that contain optimized atomistic configurations of organic molecules adsorbed on nanoparticles are provided. These .xyz files contain the atomic coordinates of the adsorbed organic molecules. The first line in each file contains the total number of atoms, the second line comprises three integers corresponding to the number of molecules, number of atoms in each molecule and number of atoms in the nanoparticle, and each subsequent line contains the atomic species and the three Cartesian coordinates (in Angstrom) for an atom. Please see the PDF in the directory for instructions.</p> <p>code: Sets of Lammps simulation input scripts.</p> <p>video: Supplements demonstrating the formation process of molecular clusters of these simulations.</p>
Data and model scripts for "Non-structural carbohydrate dynamics associated with antecedent stem water potential and air temperature in a dominant desert shrub"
<p>Model code and data as used in the first revision submitted to Plant, Cell and Environment, Feb. 2020. </p> <p>Models are coded in JAGS or OpenBUGS and run in R. Three related models are presented:</p> <p>1) "mod_allometry.R" and "jags_allometry.R" run the aboveground biomass allometry model described in Methods S1, utilizing stem and leaf mass data ("data_allometry.Rdata") and the associated initial values ("inits_allometry.Rdata")</p> <p>2) "mod_predawn.R" and "bugs_predawn.R" run the gap-filling model described in Methods S2, utilizing predawn water potential data ("data_predawn.Rdata") and the associated initial values ("inits_predawn.Rdata")</p> <p>3) "mod_NSC.R" and "bugs_NSC.R" run the NSC model described in the main text of the manuscript, utilizing NSC and covariate data ("data_NSC.Rdata") and the associated initial values ("inits_NSC.Rdata")</p>
Dataset for: Molecular Dynamics study of the Recognition of the Nucleic Acid Aptamer to ATP
<p>Files with the initial aptamer structures (wt and three mutant forms) and their complexes with ATP after docking, used in the MD simulations, along with MD simulation trajectories and meta-eABF simulations, are included as tarballs (.tar.gz). </p> <p>Mutant structures were generated using PyMol, ATP docking performed using AutoDock Vina, and MD simulations based on NAMD software and Charmm36 and CGenFF force fields. </p> <p> </p>
CoPhy: Counterfactual Learning of Physical Dynamics (Benchmark Dataset)
<p> </p> <p>Benchmark website: https://projet.liris.cnrs.fr/cophy/</p> <p>Understanding causes and effects in mechanical systems is an essential component of reasoning in the physical world. This work poses a new problem of counterfactual learning of object mechanics from visual input. We develop the COPHY benchmark to assess the capacity of the state-of-the-art models for causal physical reasoning in a synthetic 3D environment. Having observed a mechanical experiment that involves, for example, a falling tower of blocks, a set of bouncing balls or colliding objects, we require to learn to predict how its outcome is affected by an arbitrary intervention on its initial conditions, such as displacing one of the objects in the scene.</p> <p>The main objective for the creation of our benchmark is (a) to focus specifically on evaluating capabilities of state of the art models for performing counterfactual reasoning, (b) to be unbiased in terms of distributions of parameters to be estimated and balanced with respect to possible outcomes, and (c) to have sufficient variety in terms of scenarios<br> and latent physical characteristics of the scene that are not visually observed and therefore can act<br> as confounders.</p> <p>If you use this benchmark, you need to cite the following paper:</p> <p>Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, Christian Wolf. COPHY: Counterfactual Learning of Physical Dynamics. pre-print arXiv:1909.12000, 2019.</p>
Dataset and software for "Time-resolved imaging of three-dimensional nanoscale magnetization dynamics"
<p>Dataset and software for "Time-resolved imaging of three-dimensional nanoscale magnetization dynamics", Donnelly, C., Finizio, S., Gliga, S. <em>et al.</em> Time-resolved imaging of three-dimensional nanoscale magnetization dynamics. <em>Nat. Nanotechnol.</em> (2020). https://doi.org/10.1038/s41565-020-0649-x</p>
DATA of 'Quantification of seasonal and diurnal dynamics of subglacial channels using seismic observations on an Alpine Glacier.' from Nanni et al. 2020,
<p>This dataset belongs to the study of <strong>Nanni et al., 2020</strong> "Quantification of seasonal and diurnal dynamics of subglacial channels using seismic observations on an Alpine Glacier." accepted for publication in The Cryosphere on March 9th 2020.</p> <p>You can find additional information on the "<strong>README_data_NANNI_2020_glacier</strong>"</p>
Fig. 7 in Population dynamics of Prochilodus nigricans (Characiformes: Prochilodontidae) in the Putumayo River
Fig. 7. Standard length-converted catch curves (SL) and mortality estimates for Prochilodus nigricans females (a), males (b) and all individuals (sexed and unsexed) combined (c) calculated from the von Bertalanffy growth function parameters at a mean temperature of 27°C. Z, M and F represent the instantaneous rates of total, natural and fishing mortality, respectively. E is the exploitation rate (E = F.Z-1). Black dots = data points in the curve on which the regression was fitted.
Fig. 6 in Population dynamics of Prochilodus nigricans (Characiformes: Prochilodontidae) in the Putumayo River
Fig. 6. Standard length at first sexual maturity for males (black dots) and females (white circles) of Prochilodus nigricans in the Putumayo River.
Fig. 5 in Population dynamics of Prochilodus nigricans (Characiformes: Prochilodontidae) in the Putumayo River
Fig. 5. Standard length frequency histograms and the corresponding von Bertalanffy growth function for females (a) and males (b) between January 2015 and April 2017 and for all individuals (sexed and unsexed) combined of Prochilodus nigricans in the Putumayo River between 2009 and 2017 (c-f).
Fig. 4 in Population dynamics of Prochilodus nigricans (Characiformes: Prochilodontidae) in the Putumayo River
Fig. 4. Mean monthly values of the gonado-somatic index (GSI) and monthly proportions of breeding females for Prochilodus nigricans in the Putumayo River in relation to the water level (black smoothed line).
Fig. 3 in Population dynamics of Prochilodus nigricans (Characiformes: Prochilodontidae) in the Putumayo River
Fig. 3. Changes in the body condition, expressed by the log10-transformed standard length (LS) and total (Wt) mass relationships, of females (a) and males (b) Prochilodus nigricans during the different hydrological seasons. Relationships for females: y=3.1631x-1.8544. r2=0.9151 (Low); y=2.8597x-1.4749. r2=0.8917 (Rising); y=2.6298x-1.1517. r2=0.8772 (High); y=2.8619x-1.4652. r2=0.9552 (Receding). Relationships for males: y=2.8206x-1.4231. r2=0.871 (Low); y=2.6672x-1.2156. r2=0.8705 (Rising); y=2.3268x-0.7462. r2=0.8687 (High); y=2.8927x-1.5134. r2=0.9569 (Receding).
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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.