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5 results for “pine restoration”
Output raster datasets from Apalachicola Regional Restoration Initiative Open Pine Ecological Condition Model (2023)
<p>Output raster datasets from the 2023 Ecological Condition Model (ECM) for open pine ecosystems in the Apalachicola Regional Restoration Initiative (ARRI) area of the eastern Florida Panhandle. Our goal was to develop an ECM that would span all lands in the Apalachicola Regional Restoration Initiative (ARRI) area. As such, we used only datasets that were available throughout this region and did not rely on any corporate data layers from specific landowners. Furthermore, we sought to assess ecological condition at a high enough resolution to inform management decisions down to the level of individual forest stands. By taking this approach, we hoped to create ecological condition scores that could be used to inform restoration activities across all lands, and which could be updated through time to measure progress and to gauge the effectiveness of management activities.</p> <p>Output raster datasets include ecological condition for canopy, midstory and groundcover/shrub layers as well as overall ecological condition. Each raster contains ranked scores of estimated ecological condition: 1- Excellent, 2- Good, 3-Fair, and 4-Poor. </p> <p>NOTE- These outputs were created using tools stored in this repository: <a href="https://doi.org/10.5281/zenodo.8236853">https://doi.org/10.5281/zenodo.8236853</a> as well as several raster input layers stored in this repository: https://doi.org/10.5281/zenodo.8234220. </p> <p> </p> <p> </p> <p> </p>
Input raster datasets for Apalachicola Regional Restoration Initiative Open Pine Ecological Condition Model (2023)
<p>Input raster datasets used to create an Ecological Condition Model (ECM) for open pine ecosystems in the Apalachicola Regional Restoration Initiative area of the eastern Florida Panhandle. Our goal was to develop an ECM that would span all lands in the Apalachicola Regional Restoration Initiative (ARRI) area. As such, we used only datasets that were available throughout this region and did not rely on any corporate data layers from specific landowners. Furthermore, we sought to assess ecological condition at a high enough resolution to inform management decisions down to the level of individual forest stands. By taking this approach, we hoped to create ecological condition scores that could be used to inform restoration activities across all lands, and which could be updated through time to measure progress and to gauge the effectiveness of management activities.</p> <p> </p> <p> </p>
Data from: Sugar pine association genetics and performance in a post-fire restoration planting
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Data from: Using metagenomics to show the efficacy of forest restoration in the New Jersey Pine Barrens
The Franklin Parker Preserve within the New Jersey Pine Barrens contains 5,000 acres of wetlands habitat, including old-growth Atlantic White Cedar (or AWC; Chamaecyparis thyoides) swamps, cranberry bogs, and former cranberry bogs undergoing restoration into AWC forests. This study showed that the C-use efficiency was greater in the old-growth AWC soils than in soils from 8-year old mid-stage restored AWC stands, which were greater than found in soil from 4-year old AWC stands—the latter two stands being restored from long-term cranberry bogs. A metagenomic analysis of eDNA extracted from these soils showed that the C-cycle trends were associated with increases in the relative numbers of DNA sequences from several copiotrophic bacterial groups (Bacteroidetes, and Proteobacteria), complex C decomposing fungal groups ( Sordiomycetes, Mortierellales, and Thelephorales), and collembolan and formicid invertebrates. All groups are indicators of successionally more advanced soils, and critical for soil C-cycle activities. These data suggest that the restoration activities studied are enhancing critical guilds of soil biota, and increasing C-use efficiency in the soils of restored habitats, and that the use of metagenomic analysis of soil eDNA can be used in the development of assessment models for soil recovery of wetlands following restoration.
Data from: Using metagenomics to show the efficacy of forest restoration in the New Jersey Pine Barrens
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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.
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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.