Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12,170
datasets available to search
ShareScore release 0.7.1
Dataset results
12,170 results for “simulations”
Simulating Intrastand Movement of Hemlock Woolly Adelgid at Harvard Forest 2009
The hemlock woolly adelgid (HWA), Adelges tsugae Annand (Hemiptera: Adelgidae), has spread rapidly across the eastern USA since its introduction from Japan 60 years ago, causing widespread mortality of both eastern hemlock [Tsuga canadensis (L.) Carriere] and Carolina hemlock [Tsuga caroliniana Engelm. (Pinaceae)]. Although HWA spread patterns have been repeatedly analyzed at regional scales, comparatively little is known about its dispersal potential within and between hemlock stands. As the small size and clonal nature of HWA make it nearly impossible to identify the source populations of dispersing individuals, we simulated intrastand HWA movement in the field by monitoring the movement of clumps of fluorescent powder that are slightly larger than HWA, but much easier to detect in the forest understory. Using three hemlock trees with three colors of fluorescent powder as source populations, we detected dispersal events at the farthest distances within our trapping array (400 m). However, more than 90% of dispersal events were less than 25 m. Dispersal patterns were similar from all three source trees and the distribution of dispersal distances in all cases could be described by lognormal probability density functions with mean dispersal distance of 12-14 m, suggesting that dispersal was relatively independent of location of source trees. In general, we documented tens of thousands of passive dispersal events in the forest understory despite the presence of a dense forest canopy. Thus, even under relatively light-wind conditions, particles of similar dimensions to HWA are capable of intra-stand movement, suggesting that a large population of HWA could rapidly infest other trees within several hundred meter radius, or beyond.
Vegetation Response in Simulated Hurricane Experiment at Harvard Forest since 1990
Wind disturbance profoundly shapes temperate forests but few studies have evaluated patterns and mechanisms of long-term forest dynamics following major windthrows. In 1990, we initiated a large hurricane simulation experiment in a 0.8 ha manipulation (pulldown) and 0.6 ha control area of a maturing Quercus rubra-Acer rubrum forest in New England. We toppled 276 trees in the pulldown, using a winch and cable, in the northwesterly direction of natural treefall from major hurricanes. Eighty percent of canopy trees and two-thirds of all trees greater than 5 cm dbh suffered direct and indirect damage. We used twenty years of measurements to evaluate the trajectory and mechanisms of forest response after intense disturbance. Based on the patch size and disturbance magnitude, we expected pioneer tree and understory species to drive succession. The first decade of analyses emphasized tree seedling establishment and sprouting by damaged trees as the dominant mechanisms of forest recovery in this extensive damaged area. However, despite 80% canopy damage and 8000 m2 patch size, surviving overstory and advance regeneration controlled longer-term forest development. Residual oaks make up 42% of stand basal area after 20 years. The new cohort of trees, dominated by black birch advance regeneration, contributes 30% of stand basal area. There were shifts in understory vegetation composition and cover, but few species were gained or lost after 20 years. Stand productivity rebounded quickly (litterfall recovered to pre-disturbance levels in six years), but we predict that basal area in the pulldown will lag behind the control (which gained 6 m2/ha over 20 years) for decades to come. This controlled experiment showed that although the scale and intensity of damage were great, abundant advance regeneration, understory vegetation, and damaged trees remained, allowing the forest to resist changes in ecosystem processes and invasion by new species.
Fuel Loading in Simulated Hurricane Experiment at Harvard Forest since 1993
Wind disturbance profoundly shapes temperate forests but few studies have evaluated patterns and mechanisms of long-term forest dynamics following major windthrows. In 1990, we initiated a large hurricane simulation experiment in a 0.8 ha manipulation (pulldown) and 0.6 ha control area of a maturing Quercus rubra-Acer rubrum forest in New England. We toppled 276 trees in the pulldown, using a winch and cable, in the northwesterly direction of natural treefall from major hurricanes. Eighty percent of canopy trees and two-thirds of all trees greater than 5 cm dbh suffered direct and indirect damage. An enormous input of dead wood was one result of the manipulation. Many perceive an increased risk of wildfire after trees are blown down, but this depends on the amount, size, and persistence of the dead wood inputs.
Root Exudation Simulation Experiment in a Red Oak Stand at Harvard Forest 2011
Root exudation is thought to increase the activity of microbes and the exoenzymes they synthesize, leading to accelerated rates of carbon (C) mineralization and nutrient cycling in rhizosphere soils relative to bulk soils. The nitrogen (N) content of microbial biomass and exoenzymes may introduce a stoichiometric constraint on the ability of microbes to effectively utilize the root exudates, particularly if the exudates are rich in C but low in N. We combined a theoretical model of microbial activity with an exudation experiment to test the hypothesis that the ability of soil microbes to utilize root exudates for the synthesis of additional biomass and exoenzymes is constrained by N availability. The field experiment simulated exudation by automatically pumping solutions of chemicals often found in root exudates (“exudate mimics”) containing C alone or C in combination with N (C:N ratio of 10) through microlysimeter “root simulators” into intact forest soils in two 50-day experiments. The delivery of C-only exudate mimics increased microbial respiration but had no effect on microbial biomass or exoenzyme activities. By contrast, experimental delivery of exudate mimics containing both C and N significantly increased microbial respiration, microbial biomass, and the activity of exoenzymes that decompose low molecular weight components of soil organic matter (SOM, e.g., cellulose, amino sugars), while decreasing the activity of exoenzymes that degrade high molecular weight SOM (e.g., polyphenols, lignin). The modeling results were consistent with the experiments; simulated delivery of C-only exudates induced microbial N-limitation, which constrained the synthesis of microbial biomass and exoenzymes. Exuding N as well as C alleviated this stoichiometric constraint in the model, allowing for increased exoenzyme production, the priming of decomposition, and a net release of N from SOM (i.e., mineralization). The quantity of N released from SOM in the model simulations was
LANDIS-II PnET Simulation of Recent Trends in Forest Change in New England 2010-2060
The future forests of eastern North America will be shaped by at least three broad drivers: (i) vegetation change and natural disturbance patterns associated with the protracted recovery following colonial era land use, (ii) a changing climate, and (iii) a land-use regime that consists of geographically variable rates and intensities of forest harvesting, clearing for development, and land protection. We evaluated the aggregate and relative importance of these factors for the future forests of New England, USA by simulating a continuation of the recent trends in these drivers for fifty-years, nominally spanning 2010 to 2060. The models explicitly incorporate the modern distribution of tree species and the geographical variation in climate and land-use change. Using a cellular land-cover change model in combination with a physiologically-based forest landscape model, we conducted a factorial simulation experiment to assess changes in aboveground carbon (AGC) and forest composition. In the control scenario that simulates a hypothetical absence of any future land use or future climate change, the simulated landscape experienced large increases in average AGC—an increase of 53% from 2010 to 2060 (from 4.2 to 6.3 kg m-2). By 2060, climate change increased AGC stores by 8% relative to the control while the land-use regime reduced AGC by 16%. Among land uses, timber harvesting had a larger effect on AGC storage and changes in tree composition than did forest conversion to non-forest uses, with the most pronounced impacts observed on private corporate-owned land in northern New England. Our results demonstrate a large difference between the landscape’s potential to store carbon and the landscape’s current trajectory, assuming a continuation of the modern land-use regime. They also reveal aspects of the land-use regime that will have a disproportionate impact on the ability of the landscape to store carbon in the future, such as harvest regimes on corporate-owned lands. This
Trace Gas Fluxes and Soil N Dynamics in Simulated Hurricane Experiment at Harvard Forest 1989-1991
This study examined the fluxes of greenhouse gases between soils and the atmosphere in the Simulated Hurricane Experiment. The abstract from the published paper (see Methods) is reproduced below. "Fluxes of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) between soils and the atmosphere were measured monthly for one year in a 77-year-old temperate hardwood forest following a simulated hurricane blowdown. Emissions of CO2 and uptake of CH4 for the control plot were 4.92 MT C ha-1 y-1 and 3.87 kg C ha-1 y-1, respectively, and were not significantly different from the blowdown plot. Annual N2O emissions in the control plot (0.23 kg N ha-1 y-1) were low and were reduced 78% by the blowdown. Net N mineralization was not affected by the blowdown. Net nitrification was greater in the blowdown than in the control, however, the absolute rate of net nitrification, as well as the proportion of mineralized N that was nitrified, remained low. Fluxes of CO2 and CH4 were correlated positively to soil temperature, and CH4 uptake showed a negative relationship to soil moisture. Substantial resprouting and leafing out of downed or damaged trees, and increased growth of understory vegetation following the blowdown, were probably responsible for the relatively small differences in soil temperature, moisture, N availability, and net N mineralization and net nitrification between the control and blowdown plots, thus resulting in no change in CO2 or CH4 fluxes, and no increase in N2O emission."
Four-Chamber Human Heart Model for the Simulation of Cardiac Electrophysiology and Cardiac Mechanics
<p><strong>Changes in version 1.1 compared to version 1.0:</strong></p> <ul> <li>Ventricular fiber orientation changed to 66° on the endocardial and −41° on the epicardial surface</li> <li>Electrophysiology mesh was resampled</li> <li>Updated material tags in EP mesh</li> <li>Further details can be found in the <a href="https://github.com/KIT-IBT/CardioMechanics/tree/main">CardioMechanics GitHub repository</a> new reference paper:</li> </ul> <blockquote> <p>Gerach, T.; Loewe, A. Differential effects of mechano-electric feedback mechanisms on whole-heart activation, repolarization, and tension. <em>The Journal of Physiology</em> <strong>2024. </strong>https://doi.org/10.1113/JP285022 </p> </blockquote> <p>This repository contains a four-chamber model of the human heart which is ready to use for simulations of cardiac electrophysiology and cardiac mechanics problems. When using this dataset, please also cite the accompanying paper</p> <blockquote> <p>Gerach, T.; Schuler, S.; Fröhlich, J.; Lindner, L.; Kovacheva, E.; Moss, R.; Wülfers, E.M.; Seemann, G.; Wieners, C.; Loewe, A. Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach. <em>Mathematics</em> <strong>2021</strong>, <em>9</em>, 1247. https://doi.org/10.3390/math9111247</p> </blockquote> <p>The cardiac anatomy was manually segmented from magnetic resonance imaging (MRI) data of a 33 year old male volunteer. The volunteer provided informed consent and the study was approved by the IRB of Heidelberg University Hospital (Fritz et al., 2014).<br>The MRI data were acquired using a 1.5 T MR tomography system and consist of a static whole heart image stack taken during diastasis as well as time-resolved images in several long and short axis slices. Based on the segmentation, we first labeled the atria and the ventricles. The geometry was extended by a representation of the mitral valve, the tricuspid valve, the aortic valve and the pulmonary valve. Additionally, we closed the endo- and epicardial surfaces of the atria and added truncated pulmonary veins, vena cavae as well as the ascending aorta and pulmonary artery. Furthermore, we added a concentric layer of tissue around the entire heart which phenomenologically represents the influence of the pericardium and the surrounding tissue.</p> <p>Two tetrahedral meshes were created using Gmsh (Geuzaine et al., 2009): (1) the mechanical reference domain (<strong>M.vtu</strong>) with 128,976 elements (on average 3.17 mm edge length) and (2) the electrophysiological reference domain (<strong>EP.vtu</strong>) as a subset of M with 50,058,295 elements (on average 0.4 mm edge length).<br>We used rule-based methods to assign the myofiber orientation on EP: Wachter et al. (2015) was used for the atria and Bayer et al. (2012) for the ventricles. The fiber angle in the ventricles was chosen as +60° and -60° on the endocardial and epicardial surface, respectively. The sheet angle was set to -65° on the endocardium and 25° on the epicardium. Github repositories to these fiber generation tools are given in the sidebar. All geometry files are given in millimeter (mm).</p> <ul> <li><strong>Data:</strong><br>We provide time resolved data evaluated from cine MRI data, which can be used for model calibration. <ul> <li>Wall thickening (<strong>17AHA_WT.txt</strong>) / fractional wall thickening (<strong>17AHA_fractionalWT.txt</strong>) in the 17 AHA segments of the left ventricle</li> <li>Atrioventricular plane displacement (<strong>AVPD.txt</strong>) and velocity (<strong>AVPV.txt</strong>) as well as the displacement of all tracked points used for AVPD calculation (<strong>AVPD_trackedPoints.txt</strong>)</li> <li>Left and right ventricular volume (<strong>Volume_LV_RV.txt</strong>). RV volume is only available for end-diastole and end systole.</li> </ul> </li> <li><strong>Surfaces:</strong><br>This directory contains *.stl files with triangulated surfaces on which boundary conditions can be applied. <ul> <li><strong>cavityXX.stl</strong>: blood volume of the LV, RV, LA, RA</li> <li><strong>epicard.stl</strong>: the whole epicardium</li> <li><strong>outerPeri.stl</strong> and <strong>outerTrunks.stl</strong>: surfaces for Dirichlet boundary conditions</li> <li><strong>master.stl </strong>and <strong>slave.stl</strong>: surfaces used for the frictionless contact problem described in Fritz et al. (2014)</li> </ul> </li> <li><strong>TetGen:</strong><br>Contains the geometry <strong>M.vtu</strong> in the TetGen file format. T4 mesh with 4 node tetrahedrons and 3 node triangles. <ul> <li>.bases: fiber, sheet, and normal orientation at quadrature points of all elements</li> <li>.node: vertex coordinates</li> <li>.ele: list of tetrahedra</li> <li>.sur: list of triangles</li> </ul> </li> <li><strong>EP.vtu:</strong><br>Contains the cell arrays Fiber and Material.</li> <li><strong>M.vtu:</strong><br>Contains the cell arrays Fiber, Sheet, Sheetnormal, Material, and Label.</li> <li><strong>LabelIDs.txt:</strong><br>List of Label and Material identification numbers and corresponding anatomical structures.</li> </ul> <p> </p>
Size scalability of Monte Carlo simulations applied to oxidized polypyrrole systems: Data and Codes
<p>This work generalizes our recently proposed coarse grained force field (CGFF) for halogen oxidized PPy in the condensed phases and introduces a novel implementation of the Nettropolis Monte Carlo (MMC) simulation based on the CGFF that enables simulations of polymer systems with more than<br>100000 particles. The MMC implementation utilizes a combination of CPU and GPUs and exploits a numerical approximation based on polynomial piecewise interpolation for the calculation of the CGFF pairwise additive terms. Our simulations evidence that the oxidized PPy thermodynamic and structural properties are consistent as the system size is scaled up. Predicted properties include density, enthalpy, potential energy, heat capacity, coefficient of thermal expansion, caloric curve, glass transition temperature range, compressibility, bulk modulus, radial distribution functions, and polymer chain characteristics.</p>
Soil dissolved organic matter and greenhouse gas fluxes from intact Delmarva Bay wetland soil cores during laboratory simulation of groundwater level rise
Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces as surface water and groundwater levels fluctuate seasonally and these variable water levels influence wetland carbon cycling. Seasonal changes in groundwater levels determine which soils are hydrologically connected to the wetland surface water-groundwater continuum and therefore which soils act as carbon sources. To quantify groundwater-mediated soil dissolved organic matter (DOM) and greenhouse gas (CO2 and CH4) fluxes, we performed a laboratory simulation of groundwater rise on intact soil cores. Soil cores were collected from four Delmarva Bay wetlands located in the low-relief landscape of the Delmarva Peninsula in the Mid-Atlantic United States. At each wetland, two cores (length = 60 cm, diameter = 10.2 cm) were collected: one from within the wetland basin and the second from the transitional zone near the edge of the wetland basin (total number of cores collected = 8). To characterize seasonal hydrologic conditions at each wetland site where intact soil cores were collected (e.g., mean water level, number of saturation events, duration of saturation), we used high frequency water level data collected in wetland center and upland groundwater monitoring wells. In the lab, cores were re-saturated with groundwater over 15 days and after cores were fully re-saturated, core water levels were maintained for an additional 25 days. Water levels in each head tank and soil core were manually recorded on sub-daily timesteps. Rhizon soil porewater samplers were installed at 8, 20, and 40 cm below the soil surface reflecting the expected depths of the O, A, and B soil horizons across the wetland sites. Source groundwater, soil porewater, and exfiltrated surface water samples were collected daily from the soil cores and analyzed for pH, ORP, and DOM concentration (dissolved organic carbon) and DOM composition (absorbance and fluorescence metrics). Discrete measurements of CO2 and CH4 fluxes were
Data for: Simulated postfire tree regeneration suggests reorganization of Greater Yellowstone forests during the 21st century
Tree regeneration underpins forest resilience, but how postfire tree regeneration will change with future climate and fire regimes is difficult to anticipate. Areas of sparse and failed postfire tree regeneration have been documented in western US forests, but how future recovery pathways will unfold is uncertain. We conducted a simulation study in the Greater Yellowstone Ecosystem (GYE; United States) using a process-based model, iLand, to ask how rates, composition, and spatial patterns of postfire tree regeneration vary with 21st-century climate. Subalpine forest and fire dynamics were simulated through 2100 under four climate scenarios, 2 × 2 factorial of aridity (wet and dry) and temperature (warm and hot), in five GYE landscapes. We tallied postfire tree seedling density by species in simulated fires (> 400 ha) at five years postfire. This data set contains three data sets to reproduce analyses for changes rates of regeneration, proportion of burned cells with regeneration failure, and postfire reorganization pathways. We include the data and R scripts used for these three analyses in the publication associated with these data.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation A - increased Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation J - doubled Phase II decomposition
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with doubled Phase II soil organic matter decomposition compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation C - increased Phase I and Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase I and Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation D - reduced Phase I and Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with reduced Phase I and Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year. .
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation B - increased Phase I soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase I soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation F - increased N deposition
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased N deposition compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation E - reduced Phase I soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with decreasing Phase I soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation I - doubled Phase I decomposition
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with doubled Phase I soil organic matter decomposition compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation H - increased N and P deposition
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased N and P deposition compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation G - increased P deposition
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased P deposition compared to the base simulation. Data is presented for day 250 of each year.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.