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94 results for “vegetation dynamics”
Long-term Dynamics of Vegetation and Environment in Central Massachusetts 1000-2000
Historical and ecological data from north-central Massachusetts suggest that widespread and intensive human disturbance after European settlement led to a shift in forest composition and obscured regional patterns of species abundance. A paleoecological approach was required to place recent forest dynamics in a long-term context. Pollen and charcoal data from 11 small lakes in north-central Massachusetts were used to reconstruct local vegetation dynamics and fire histories across the region over the past 1000 years. The sites are located across an environmental gradient. Paleoecological data indicate that prior to European settlement, there was regional variation in forest composition corresponding to differences in climate, substrate, and fire regime. Oak, chestnut and hickory were abundant at low elevations, whereas hemlock, beech, sugar maple, and yellow birch were common at high elevations. Fire appears to have been more frequent and/or intense at lower elevations, maintaining high abundances of oak, and archaeological data suggest Native American populations were greater in these areas. A change in forest composition at higher elevations, around 550 years before present, may be related to the Little Ice Age (a period of variable climate), fire, and/or activity by Native Americans, and led to regional convergence in forest composition. After European settlement, forest composition changed markedly in response to human disturbance and there was a sharp increase in rates of vegetation change. Regional patterns were obscured further, leading to homogenization of broad-scale forest composition. There is no indication from the pollen data that forests are returning to pre-European settlement forest composition, and rates of vegetation change remain high, reflecting continuing disturbance to the landscape, despite regional reforestation.
Long-term Vegetation Dynamics on the Massachusetts Coast from 2000 BP to Present
We use a retrospective approach to reconstruct the past distribution of fire in New England and to investigate the important drivers of this pattern across the period of European arrival to North America. Our study sites are in New England, and range from pitch pine and oak forests of coastal Massachusetts, pine and hardwood forests of central Massachusetts, and northern hardwood and spruce fir forests of northern Massachusetts and Vermont. We collected sediment profiles from 18 lakes across the study area to assess fossil charcoal and pollen abundance over the past 1000 years and including the time period of European arrival and settlement. Based on presettlement pollen composition, our study sites are divided into three vegetation types: 1) pitch pine and oak, 2) oak, pine, and hardwood, and 3) northern hardwoods. The abundance of presettlement charcoal in these lakes is closely related to climate and the composition of surrounding vegetation. Charcoal is most abundant in pitch pine forests and least common in northern hardwood and spruce forests. Following the arrival of Europeans, charcoal abundance increases, at most sites substantially, and vegetation composition changed in a direction of either greater dominance by pitch pine or white pine, depending on whether the forests were located in the southern or northern part of New England. The major factor influencing the distribution of fire across New England is climate, which has a direct effect on the physical conditions conducive to fire ignition and spread and an indirect effect on fire through its control on the distribution of vegetation at this spatial scale. We find evidence that other factors exert some control over local fire regimes as well including landforms and their impact on vegetation composition, firebreaks, and prevailing winds. Native Americans likely influenced the local occurrence of fire, but their impact on regional fire regimes in New England is not apparent from this or other studies. Ho
Long-term Vegetation Dynamics in Southwestern New Hampshire from 13000 BP to Present
The paleoecological record allows contemporary ecologists to put current phenomena into the context of a longer time-frame, thereby providing the opportunity to evaluate the importance of slowly operating processes, past cyclic or unusual events, disturbance regimes, and historically constrained phenomena. We briefly outline the environmental history of the Quaternary, discuss the spatial and temporal resolution of the paleoecological evidence for biotic change, and summarize data relevant to such current issues as the nature of the biotic community, the role of disturbance, stability versus rapid change, evolutionary theory, explanations of species diversity, and refugia theory. Finally, we offer examples of the utility of paleoecological techniques for ecologists and environmental scientists.
Riparian and upland understory vegetation lifeforms and leaf-litterfall ordination analyses in the Luquillo Forest Dynamics Plot
Riparian areas are proportionally a small component of the forested landscape, they are significant contributors to ecosystem process, terrestrial and aquatic linkages, plant community composition, as well to basal energy resources for aquatic fauna. We describe vegetation and leaf-litterfall composition in relation to past land use in riparian and upland locations in tropical wet forest, Luquillo Forest Dynamics Plot (LFDP), Luquillo Experimental Forest, Puerto Rico. Data collected from 2003 to 2005. Stratified sampling was conducted in riparian and upland areas of LFDP with high and low past land use. Understory vegetation life-form composition were sampled in plots. \<para\> Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.\</para\>
Tropical green roofs vegetation dynamics data
The data archive is here: https://doi.org/10.2737/RDS-2021-0024 please use this DOI when citing this dataset. This publication contains data collected in 2017 from three green roofs at the International Institute of Tropical Forestry in San Juan, Puerto Rico and one green roof at the Social Sciences Faculty of the University of Puerto Rico in Río Piedras. Data from these extensive green roofs include substrate depth as well as species counts within a sampled quadrant, as well as species identification information. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Simulations from the LPJmL3.5 dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the LPJmL3.5 dynamic global vegetation model are provided for two global simulations. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for each individual turnover-causing process in the model were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Simulations from the ORCHIDEE dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the ORCHIDEE dynamic global vegetation model are provided for two global simulations. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for mortality, leaf phenological turnover and fine root phenological turnover were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Simulations from the JULES dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the JULES dynamic global vegetation model are provided for two global simulations. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 1.875 x 1.25 degree spatial resolution. Carbon turnover fluxes for live vegetation for each individual turnover-causing process in the model were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Simulations from the LPJ-GUESS dynamic global vegetation model v3.0 for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the LPJ-GUESS dynamic global vegetation model v3.0 are provided for two global simulations. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for mortality, leaf phenological turnover and fine root phenological turnover were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest
<p>Dataset was used for the article "Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest".</p> <p>The related work proposes to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic).</p> <p>Abstract of the paper:</p> <p>A better knowledge of tree vegetative growth patterns and their relationship to environmental variables is crucial in understanding forest growth dynamics and how climate change may affect them. Generally less studied than reproductive structures, the phenology of tree vegetative growth mainly focuses on the analysis of growing shoots, from vegetative buds development to leaf fall. This growth process usually strongly differs between temperate and tropical regions. In temperate regions, this pattern is quite well known. Low winter temperatures impose a stop of the vegetative growth shoots and lead to the typical expression of an annual growth cycle for the vast majority of tree species. In moist tropical regions, on the other hand, the seasonality is much less marked. In addition, these regions contain a much wider variety of tree species. These two aspects lead to a tremendous diversity of phenological patterns that are still poorly known and understood. In particular, not much is known on the periodicity and timing of growth at individual trees, population, or community levels.</p> <p>The work carried out in this study aims to advance knowledge in this area, focusing more particularly on herbarium scans, as herbarium collections offer the promise of monitoring plant phenology over long time periods. However, such a study requires the ability to detect a sufficiently large number of growing shoots in herbarium collections to draw statistically relevant conclusions, which can be very costly if the work is done manually. Furthermore, herbarium collections traditionally focus on reproductive organs, and herbarium specimens showing growing shoots are pretty rare.</p> <p>We propose in this paper to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect these relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Our results show the relevance of using herbarium data for vegetative phenology research, as well as the potential of deep learning approaches for growth shoot detection.</p>
Vegetation Dynamics on Crete
<p>This dataset contains long-term vegetation dynamics assessments for the Island of Crete, Greece. 10+ years ago, Landsat time series analyses were inevitably limited to few expensive images from carefully selected acquisition dates. Yet, such a static selection may have introduced uncertainties when spatial or inter-annual variability in seasonal vegetation growth were large. As seminal pre-open-data-era papers are still heavily cited, variations of their workflows are still widely used, too. Thus, we here quantitatively assessed the level of agreement between an approach using carefully selected images, and a state-of-the-art analysis that uses all available images. Further details can be found in the corresponding paper.</p> <p><strong>Temporal Extent: </strong>1984-2006.</p> <p><strong>Spatial Extent:</strong> Crete, Greece</p> <p><strong>Data format: </strong>The data come in tiles of 30x30km. The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There are mosaics in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. </p> <p><strong>Sub-directories:</strong></p> <ul> <li>cso: Number of <em>Clear-Sky Observations </em>available for this study</li> <li>dem: <em>Digital Elevation Model</em> (SRTM filled with ASTER)</li> <li>vd-1.0: Vegetation Dynamics 1.0 (see paper) <ul> <li>bap: <em>Best Available Pixel</em> composites</li> <li>trend: monotonic trends fitted on BAPs</li> </ul> </li> <li>vd-2.0: Vegetation Dynamics 2.0 (see paper) <ul> <li>trend <ul> <li>monotonic trends fitted on <em>value of peak of season </em>phenometrics (VPS)</li> <li>monotonic trends fitted on value of <em>seasonal amplitude</em> phenometrics (VSA)</li> <li>change and piecewise monotonic trends fitted on <em>value of base level </em>phenometrics (VBL)</li> </ul> </li> <li>syndromes <ul> <li>syndrome classification for woody vegetation</li> <li>syndrome classification for herbaceous vegetation</li> <li>net cover change for woody vegetation</li> <li>net cover change for herbaceous vegetation</li> </ul> </li> </ul> </li> </ul> <p><strong>Further information:</strong><br> For further information, please see the publication.<br> A web-visualization of this dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/crete/">here</a>.</p> <p><strong>Publication:</strong><br> Frantz, D., Hostert, P., Rufin, P., Ernst, S., Röder, A., van der Linden, S. (2022): Revisiting the past: Replicability of a historic long-term vegetation dynamics assessment in the era of big data analytics. Remote Sensing 14(3), 597; https://doi.org/10.3390/rs14030597</p> <p><strong>Funding: </strong><br> This publication was financially supported by Geo.X, the Research Network for Geosciences in Berlin and Potsdam under grant number SO_087_GeoX, and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 414984028 - SFB 1404.</p>
Dataset: Human-vegetation dynamics in Holocene South-Eastern Norway based on radiocarbon-dated charcoal from archaeological excavations
<p>The repository contains radiocarbon data used in the paper <em>Human-vegetation dynamics in Holocene South-Eastern Norway based on radiocarbon-dated charcoal from archaeological excavations</em>, written by By Axel Mjærum, Kjetil Loftsgarden, and Steinar Solheim (University of Oslo).</p> <p>The paper is accepted for publication in The Holocene.</p> <p>ABSTRACT: Charcoal from archaeological contexts differs from off-site pollen samples as it is mainly a product of intentional human action. As such, analysis of charcoal from excavations is a valuable addition to studies of past vegetation and the interaction between humans and the environment. In this paper, we use a dataset consisting of 6,186 dated tree species samples from 1,239 archaeological sites as a proxy to explore parts of the Holocene forest development and human-vegetation dynamics in South-Eastern Norway.</p> <p>From the middle of the Late Neolithic (from <em>c</em>. 2000 BC) throughout the Early Iron Age (to <em>c</em>. AD 550) the region’s agriculture is characterized by fields, pastures, and fallow. Based on our data, we argue that these practices, combined with forest management, clearly altered the natural distribution of trees, and favoured some species of broadleaved trees. The past distribution of hazel (<em>Corylus avellana</em>) is an example of human impact on the vegetation. Today, hazel is not even among the 15 most common tree species, while it is one of the most prevalent species in the archaeological record before AD 550. The data indicate that this species was favoured already by the region’s Mesolithic hunter-fisher-gatherers, and that it was among the species that thrived extremely well in the early farming landscape. Secondly, our analysis also indicates that spruce (<em>Picea abies</em>) first formed large stands in the south-eastern parts of Norway <em>c</em>. 500 BC, centuries earlier than previously assumed. It is argued that this event, and a further westward expansion of spruce, was partly a consequence of a specific historical event – the first millennium BC farming expansion.</p>
Model codes and simulation data for "Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)"
<p>ModelE-BiomeE v1.0 model codes and data This folder contains the simulation data and model codes that were used in the paper ‘Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS’s Earth system model (ModelE-BiomeE v.1.0)’ (https://doi.org/10.5194/gmd-2022-72). We included the data simulated by ModelE-BiomeE v.1.0 with settings of full demography (folder FullDemography) and single cohort (folder SingleCohort), and initial settings of land grids and vegetation data (folder GlobalVegetation). The codes include the full ModelE 2.1, module BiomeE files in ModelE, and the standalone BiomeE. In the folder FullDemography, we have 4 netcdf files for global output and 25 files for single grids output. The files ‘FullDM_2588_JAN.nc’ and ‘FullDM_2588_JUL.nc’ are the original model output of January and July in the year 2588. The file ‘FullDM_2588_Annual.nc’ is the yearly summary of model simulations. The file ‘FullDM_Selected.nc’ is an annual summary of 588 years of model simulation only with selected variables. The csv files are for single grids output at the time steps of daily and yearly. The last digit 1~8 represents the sites of 'BNC','MNT','HF','OKR','KZ','SV','WGK','TPJ', respectively (Table 1). Table 1 Site ID and file number ['BNC', 'MNT', 'HF', 'OKR', 'KZ', 'SV', 'WGK', 'TPJ'] ['8991', '8992', '8993', '8994', '8995', '8996', '8997', '8998'] ['8971', '8972', '8973', '8974', '8975', '8976', '8977', '8978'] ['8961', '8962', '8963', '8974', '8965', '8966', '8977', '8968'] Please refer to Table 2 in the paper for the detail of these 8 sites. ‘DailyLAIGPP.csv’ is a summary of all ‘DailyEcosystem’ files with LAI and GPP data. We included the Python scripts that can be used to generate the figures in out paper (Plotting-BiomeE-MsTMIP.py, Plotting-Scatter-Comparison.py, PlottingBiomeEMaps.py, and PlottingGridOutput.py). For the convenience of readers (in reproducing our figures), we included the summary of reanalysis of the data from observations and MsTMIP in folder ‘Sum-Obs-Simu’. Please refer to the original sources listed in our paper for the detail of these data.</p>
Leaf water and stem cellulose oxygen isotope ratios simulated with global dynamic vegetation model LPX-Bern
<p>Description of leaf water and stem cellulose oxygen isotope ratios simulated with LPX-Bern</p> <p>Citation of describing paper:</p> <p>Keel SG, Joos F, Spahni R, Saurer M, Weigt RB, Klesse S. 2016. Simulating oxygen isotope ratios in tree ring cellulose using a dynamic global vegetation model, Biogeosciences, 13, 3869–3886, 2016 doi:10.5194/bg-13-3869-2016</p> <p>download: www.biogeosciences.net/13/3869/2016/</p> <p>General Information: Format: NetCDF, gridded</p> <p>Model: Dynamic global vegetation model LPX-Bern Version 1.0 (Land surface Processes and eXchanges, Bern) (Spahni et al., 2013; Stocker et al., 2013)</p> <p>Resolution: 3.75° x 2.5° lat/lon global Time: Monthly from Jan 1960 to Dec 2012</p> <p>Variables:</p> <p>cellu18: monthly stem cellulose δ18O (per mil) lw18: monthly leaf water δ18O (per mil) -2 NPP: monthly net primary production (g C m ) FPC: monthly fractional plant cover</p> <p>Dimensions: i=longitude, j=latitude, l=time, k=plant functional type Codes for plant functional types (k):</p> <ol> <li> <p>1 tropical broad-leaved evergreen</p> </li> <li> <p>2 tropical broad-leaved deciduous (raingreen)</p> </li> <li> <p>3 temperate needle-leaved evergreen</p> </li> <li> <p>4 temperate broad-leaved evergreen</p> </li> <li> <p>5 temperate broad-leaved deciduous (summergreen)</p> </li> <li> <p>6 boreal needle-leaved evergreen</p> </li> <li> <p>7 boreal needle-leaved deciduous (summergreen)</p> </li> <li> <p>8 boreal broad-leaved deciduous (summergreen)</p> </li> <li> <p>9 temperate herbaceous</p> </li> <li> <p>10 tropical herbaceous</p> </li> </ol>
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Active Layer Depth (ALD) in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes active layer depth (ALD) data across a 75x75m spatial domain in the Caribou-Poker Creeks Research Watershed. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Net Primary Production (NPP) for black spruce (Picea mariana) in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes net primary production (NPP) data for black spruce (Picea mariana) in the Caribou-Poker Creeks Research Watershed. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Net Primary Production (NPP) in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes net primary production (NPP) data for dominant tree species in the Caribou-Poker Creeks Research Watershed. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Specific Leaf Area (SLA) for alder (Alnus crispa) and black spruce (Picea mariana) in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes specific leaf area (SLA) data for two dominant tree species in the Caribou-Poker Creeks Research Watershed: alder (Alnus crispa) and black spruce (Picea mariana). Up to 10 leaf samples were collected per species per sampling location. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Slope data in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes landscape slope data. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
Carbon Dynamics Along a Permafrost Gradient at Caribou-Poker Creeks Research Watershed (CPCRW) in Interior Alaska: Specific Leaf Area (SLA) for alder (Alnus crispa) and black spruce (Picea mariana) in a 75x75m spatial domain along a permafrost and vegetation gradient.
This dataset includes depth-resolved soils data from September 2014 coring: soil pH, gravimetric soil moisture, roots/rocks, bulk density, humification indices as determined by FTIR, total elemental composition (carbon, nitrogen, sulfur), depth to mineral horizon, thickness of the moss layer, percent groundcover at the sampling location of several common species, and soil temperature at the time of coring. Project summary: Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which forest composition changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. This is an exploratory study to begin understanding SLA variation and controls thereof in a non-contiguous permafrost system.
ScienceDex guides
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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.