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3 results for “reburn”
Young forests and fire: Using lidar-imagery fusion to explore fuels and burn severity in a subalpine forest reburn, Grand Teton National Park, Wyoming.
Anticipating fire behavior as climate change and fire activity accelerate is an increasingly pressing management challenge in fire-prone landscapes. In subalpine forests adapted to infrequent, stand-replacing fire, self-limitation of burn severity in short-interval fire is incompletely understood. Spatially explicit fuels data can support assessments of landscape-scale fire risk and fuels feedbacks on burn severity. For a about 1,450 km2 largely forested landscape in the US Northern Rocky Mountains, we used airborne lidar and imagery to predict and map canopy and surface fuels. In a fire that burned mature ( greater than 125-year-old) and also reburned young (~30-year-old) subalpine forest, we then asked: (1) How do pre-fire fuels and burn severity compare between young and mature forests that burned under similar fire weather conditions? (2) How well do pre-fire fuels and forest structure predict burn severity under extreme versus moderate fire weather? Lidar-imagery fusion predicted fuel characteristics with high accuracy across forest and shrubland vegetation (R2 from 0.65-0.95). Young post-fire forests had abundant, densely packed canopy fuels, and both young and mature forests had similar canopy fuel loads and coarse wood biomass. Under similar weather conditions, young and mature forests burned at similar severity. Overall, fuels were weak predictors of burn severity and, surprisingly, better predicted severity under extreme (R2LMM(m) = 0.27) rather than moderate (R2LMM(m) = 0.15) fire weather. Our findings are relevant for subalpine landscapes increasingly dominated by young lodgepole pine (Pinus contorta var. latifolia) forests vulnerable to short-interval fire and provide a benchmark to assess how fuels influence burn severity in future fires. Fire managers should continually reassess fuels and update expectations about fire behavior as landscapes change. Although recovering post-fire forests can limit fire spread and severity for a period of time, our resu
Data for: Reburning before recovery: Effects of short-interval fire on subalpine forest nitrogen stocks and fluxes
In forests adapted to infrequent (>100-yr) stand-replacing fires, novel short-interval (<30-yr) fires have started to burn young forests before they recover from previous burns. Postfire tree regeneration is reduced, plant communities shift, soils are hotter and drier, but effects on biogeochemical cycling are unresolved. This study focused on how postfire nitrogen (N) stocks, N availability and N fixation varied in lodgepole pine (Pinus contorta var. latifolia) forests burned at long and short intervals in Grand Teton National Park (Wyoming, USA). This data package includes our field data from 2021 and 2022, along with laboratory analyses of foliar and litter chemistry, resin-sorbed N, and field measurements of N fixation. The data included here were also used to compute aboveground N stocks. Our study found that short-interval fires reduced and repartitioned aboveground N stocks, but soil N stocks were unaffected. Results indicate that these shifts in N pools and fluxes suggest reburns can markedly alter N cycling in subalpine forests. The citation for the publication associated with these data is: Turner, M. G., R. E. Heumann, N. G. Kiel, J. A. Warren, and C. C. Cleveland. Reburning before recovery: Effects of short-interval fire on subalpine forest nitrogen stocks and fluxes. Ecosystems (In press)
Trees have similar growth responses to first-entry fires and reburns following long-term fire exclusion
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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.