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36 results for “landcover”
Kananaskis/Willmore Camera and Landcover Data
<p>Anthropogenic landscape change is a leading driver of biodiversity loss. Preceding dramatic changes such as wildlife population declines and range shifts, more subtle responses may signal impending larger-scale change. For example, disturbance-induced shifts to species' activity patterns may disrupt temporal niche partitioning along the 24-h time axis, compromising community structure via altered competitive interactions. We investigated the impacts of human landscape disturbance on species' activity patterns and temporal niche partitioning in the Canadian Rocky Mountain carnivore guild using camera trap images collected across two regions encompassing a wide gradient of human footprint. Applying kernel density estimation techniques, we tested for carnivore species' activity shifts 1) between a low versus high disturbance landscape, and 2) in relation to site-scale disturbance. To test our hypothesis that human disturbance impacts species' temporal niche partitioning, we modelled activity overlap between co-occurring carnivore species in relation to natural and anthropogenic landscape features, as well as carnivore community composition. Multiple carnivore species altered activity patterns between the low versus high disturbance landscapes and camera sites, but these shifts varied considerably among species. While wolves appeared to increase nocturnal activity in relation to disturbance, coyote activity consistently trended towards cathemerality and marten increased diurnal activity. Detecting effects of landscape disturbance on activity overlap between co-occurring species was highly sensitive to site-level detection sample sizes, and our results suggest altered temporal niche partitioning between marten and wolverine in relation to forest cover. This study indicates that mesocarnivores may respond differently and perhaps indirectly to anthropogenic disturbance compared to apex predators. Apex predator shifts to nocturnality may facilitate a 'behavioural release' in mesocarnivores. This may be a likely component of mesocarnivore population release, with important management implications for ecological communities on disturbed landscapes.</p>
Predator biomass, prey biomass landcover and climate data from spotted hyaena and lion sites in Africa
<p class="Thesisnormal">The spotted hyaena (<i>Crocuta crocuta</i> Erxleben) and the lion (<i>Panthera leo</i> Linnaeus) are two of the most abundant and charismatic large mammalian carnivores in Africa and yet both are experiencing declining populations and significant pressures from environmental change. However, with few exceptions, most studies have focused on influences upon spotted hyaena and lion populations within individual sites, rather than synthesising data from multiple locations. This has impeded the identification of over-arching trends behind the changing biomass of these large predators.</p> <p class="Thesisnormal">Using Partial Least Squares regression models, influences upon population biomass were therefore investigated, focusing upon prey biomass, temperature, precipitation and vegetation cover. Additionally, as both species are in competition with one other for food, the influence of competition and evidence of environmental partitioning were assessed.</p> <p class="Thesisnormal">Our results indicate that spotted hyaena<i> </i>biomass is more strongly influenced by environmental conditions than lion, with larger hyaena populations in areas with warmer winters, cooler summers, less drought and more semi-open vegetation cover.</p> <p class="Thesisnormal">Competition was found to have a negligible influence upon spotted hyaena and lion populations, and environmental partitioning is suggested, with spotted hyaena population biomass greater in areas with more semi-open vegetation cover. Moreover, spotted hyaena is most heavily influenced by the availability of medium-sized prey biomass, whereas lion is influenced more by large size prey biomass. Given the influences identified upon spotted hyaena populations in particular, the results of this study could be used to highlight populations potentially at greatest risk of decline, such as in areas with warming summers and increasingly arid conditions.</p>
Kananaskis/Willmore Camera and Landcover Data
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Coyote behavioral state data and landcover files
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Data for: Wild bees and landcover: bee species’ body size does not predict the scale of effect, but bee phenology predicts association with landcover type
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Predator biomass, prey biomass landcover and climate data from spotted hyaena and lion sites in Africa
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Iowa herptile detection histories and landcover metrics
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New England Landscape Futures Landcover
<p>Description to be added at future date.</p>
A dataset to model Levantine landcover and land-use change triggered by climate change, the Arab Spring and COVID-19
<p>The Levant region is highly vulnerable to climate change, experiencing prolonged heat waves that have led to societal crises and population displacement. Since 2010, the area has been marked by socio-political turmoil, including the Syrian civil war, which has strained neighbouring countries like Jordan due to the influx of Syrian refugees. Jordan, in particular, has seen rapid population growth and significant changes in land use and infrastructure, leading to over-exploitation of the landscape through irrigation and construction. This article uses climate data, satellite imagery, and land cover information to illustrate the substantial increase in construction activity and highlights the intricate relationship between climate change predictions and current socio-political developments in the Levant.</p>
Bird communities across varying landcover types in a Neotropical city
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NACP Peatland Landcover Type and Wildfire Burn Severity Maps, Alberta, Canada
This data set provides landcover maps of (1) peatland type (bog, fen, marsh, swamp) with levels of biomass (open, forested) and (2) Burn Severity Index (BSI) (Dyrness and Norum, 1983) for four wildfire areas in northern Alberta, Canada. The four wildfire sites include the Utikuma fire site of 2011, Kidney Lake fire site of 2011, Fort McMurray west fire site of 2009, and Fort McMurray east fire site of 2009. The peatland classification at 12.5-m resolution (fen vs. bog including treed vs. open vs. shrubby) at each wildfire site was based on a pre-burn 2007 multi-date, multi-sensor fusion (Optical-IR, C-band and L-band SAR) approach. Over 350 field locations were sampled in central Alberta to train and validate the peatland type maps. The additional site, Wabasca, was an unburned site. Burn severity was measured in the field using the Burn Severity Index (BSI) (Dyrness and Norum 1987), a qualitative assessment of burnt moss that uses a 1-5 scale, with 1 being unburnt and 5 being severely burnt. The field data of ground consumption were correlated with Landsat pre- and post-burn imagery, specific to peatlands, to develop multivariate models for calculating burn severity and %-not-sphagnum-moss. These models were used to generate the Burn Severity Maps at 30-m resolution (percent unburned moss, and the burn severity index (BSI)). All sites were visited in 2013 for field measurements and the Utikuma site was also visited in 2012 for field measurements. Additional biophysical data for the various peatlands (aboveground biomass – tree and shrub, plant heights, density, etc. were collected and will be provided in another data set.
Aboveground Biomass, Landcover, and Degradation, Kalimantan Forests, Indonesia, 2014
This dataset provides estimates of aboveground biomass, percent canopy cover, mean canopy height, landcover, and forest degradation index products for forests in Kalimantan, Indonesia (Island of Borneo) representative of conditions in late 2014. Data were combined from several sources including field sampling, airborne lidar, satellite measurements, a forest-type land cover map, and integrated into a random forest algorithm to produce these estimates.
BOREAS RSS-15 SIR-C and TM Biomass and Landcover Maps of the NSA and SSA
As part of BOREAS, the RSS-15 team conducted an investigation using SIR-C , X-SAR and Landsat TM data for estimating total above-ground dry biomass for the SSA and NSA modeling grids and component biomass for the SSA. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass were used to estimate biomass density across the landscape. The procedure involved image classification with SAR and Landsat TM data and development of simple mapping techniques using combinations of SAR channels. For the SSA, the SIR-C data used were acquired on 06-Oct-1994, and the Landsat TM data used were acquired on September 2, 1995. The maps of the NSA were developed from SIR-C data acquired on 13-Apr-1994.
ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014
This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites.
Spanish national forest landcover database for MEGAN3
<p>This is the adapted version of the Spanish National Forest Inventory for MEGAN3 applications.</p>
yxzsjayfan/myData: GLOBMAP LAI and Landcover data
<p>Monthly GLOBMAP LAI dataset and global landcover data at 0.5°×0.5° resolution</p>
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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.