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217 results for “forest model”
Comparing mixed models and Random Forest association tests using naturalGWAS and a Striped Bass SNP dataset
Open the record for dataset details and reuse information.
Urban Forest Effects Model (UFORE) to calculate forest structure and function from sample ground data. Two part set.
Within the City of Baltimore, 195 permanent 1/10 circular plots were established based on a stratified random sample among land uses in 1999. These plots were re-measured in 2004 and 2009 and will be re-measured again in 2014. On each plot, all trees (as defined as woody vegetation with a stem diameter at 4.5 ft (dbh) greater than one-inch) are recorded. For each tree, data are recorded on species, dbh, height, crown width, condition, crown competition, percent canopy missing and distance and direction to nearby residential buildings. These data are analyzed using the i-Tree model (www.itreetools.org) to assess ecosystem services and values. However, more importantly, these plots along with a comparable set of plots established in Syracuse, NY in 1999 are the first and most spatially comprehensive set of long-term urban forest monitoring data within cities globally. These data are being used to understand how urban forest structure and associated ecosystem services are changing through time in the City of Baltimore.
The role of fire in the carbon dynamics of the boreal forest II. - Eurasia model simulations of historical fire disturbance and carbon dynamics (1000-2002).
The boreal forest contains large reserves of carbon, and across this region wildfire is a common occurrence. To improve the understanding of how wildfire influences the carbon dynamics of this region, methods were developed to incorporate the spatial and temporal effects of fire into the Terrestrial ecosystem Model (TEM). The historical role of fire on carbon dynamics of the boreal region was evaluated within the context of ecosystem responses to changing atmospheric CO2 and climate. These results show that the role of historical fire on boreal carbon dynamics resulted in a net carbon sink; however, fire plays a major role in the interannual and decadal scale variation of source/sink relationships. To estimate the effects of future fire on boreal carbondynamics, spatially and temporally explicit empirical relationships between climate andfire were quantified. Fuel moisture, monthly severity rating, and air temperature explained a significant proportion of observed variability in annual area burned. These relationships were used to estimate annual area burned for future scenarios of climate change and were coupled to TEM to evaluate the role of future fire on the carbon dynamics of the North American boreal region for the 21st Century. Simulations with TEM indicate that boreal North America is a carbon sink in response to CO2 fertilization, climate variability, and fire, but an increase in fire leads to a decrease in the sink strength. While this study highlights the importance of fire on carbon dynamics in the boreal region, there are uncertainties in the effects of fire in TEM simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. Future studies should incorporate the role of dynamic vegetation to more accurately represent post-fire successional pr
The role of fire in the carbon dynamics of the boreal forest III. - North America model simulations of historical fire disturbance and carbon dynamics (1900-2100).
The boreal forest contains large reserves of carbon, and across this region wildfire is a common occurrence. To improve the understanding of how wildfire influences the carbon dynamics of this region, methods were developed to incorporate the spatial and temporal effects of fire into the Terrestrial ecosystem Model (TEM). The historical role of fire on carbon dynamics of the boreal region was evaluated within the context of ecosystem responses to changing atmospheric CO2 and climate. These results show that the role of historical fire on boreal carbon dynamics resulted in a net carbon sink; however, fire plays a major role in the interannual and decadal scale variation of source/sink relationships. To estimate the effects of future fire on boreal carbondynamics, spatially and temporally explicit empirical relationships between climate andfire were quantified. Fuel moisture, monthly severity rating, and air temperature explained a significant proportion of observed variability in annual area burned. These relationships were used to estimate annual area burned for future scenarios of climate change and were coupled to TEM to evaluate the role of future fire on the carbon dynamics of the North American boreal region for the 21st Century. Simulations with TEM indicate that boreal North America is a carbon sink in response to CO2 fertilization, climate variability, and fire, but an increase in fire leads to a decrease in the sink strength. While this study highlights the importance of fire on carbon dynamics in the boreal region, there are uncertainties in the effects of fire in TEM simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. Future studies should incorporate the role of dynamic vegetation to more accurately represent post-fire successional pr
Modelling Avian Habitat Suitability in Boreal Forest using Structural and Spectral Remote Sensing Data
<p>Data used in research regarding avian habitat suitability models in Harry's River Watershed in Newfoundland, Canada</p>
Provisioning forest and conservation science with European tree species distribution models under climate change
<p>Estimating shifts in the current range of forest tree species is crucial for formulating adaptive management strategies such as assisted migration. Ecological niche models have been the most widely used tools to estimate the potential climatic suitability of species worldwide. The reliability of such estimations depends on the model algorithm and the input data such as climate and species occurrence. We developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The distribution models shall be the basis for follow-up studies in forest and conservation science.</p>
Detailed global modelling of soil organic carbon in cropland, grassland and forest soils
<p>Supporting information of the paper: Morais, T.G., Teixeira, R.F.M., Domingos, T. 2019. Detailed global modelling of soil organic carbon in cropland, grassland and forest soils. PloS One.</p> <p>Version 2 includes raster files (.tif) for each land use class (including: Attainable SOC stock, mineralization rate, and fator K).</p>
Data from: Cats under cover: habitat models indicate a high dependency on woodlands by Atlantic Forest felids
Four Neotropical small and medium felids—the ocelot, jaguarundi, margay and southern tiger cat—have overlapping geographic distributions in the endangered Atlantic Forest. Local studies show that these felids avoid areas with high human impact, but the three smaller ones use human-modified areas more frequently than do ocelots. To understand how landscape changes affect the habitat distribution of these four felids in the Atlantic Forest of Argentina, we used maximum entropy models to analyze the effect of environmental and anthropogenic factors. We estimated niche breadth and overlap among these felids. The conversion of the native forest to land uses without trees was the most important variable that determined the habitat distribution of the four species. For all four species the optimal habitat covered less than 1/3 of the study area and corresponds mainly to the native forest areas. Nearly 50 percent of these areas had some level of protection. The niche width was higher for the small felids than for ocelots. Niche overlap was high for all species pairs, but higher among the small felids and lower for each of these with the ocelot. The four felids were negatively affected by native forest loss, with ocelots being more sensitive than the smaller felids. The conversion of unprotected forest areas to other types of land uses would imply a greater habitat loss for these felids. The protection of current remnants of Atlantic Forest in Argentina is important for the long-term conservation of the four felids.
Data from: Modeling seasonal surface temperature variations in secondary tropical dry forests
Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15–20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6–8 K warmer than the intermediate successional stages and were 9–10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0–1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs.
Data from: Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar
1. Recent studies have underlined the importance of climatic variables in determining tree height and biomass in tropical forests. Nonetheless, the effects of climate on tropical forest carbon stocks remain uncertain. In particular, the application of process-based dynamic global vegetation models have led to contrasting conclusions regarding the potential impact of climate change on tropical forest carbon storage. 2. Using a correlative approach based on a bioclimatic envelope model and data from 1771 forest plots inventoried during the period 1996-2013 in Madagascar over a large climatic gradient, we show that temperature seasonality, annual precipitation and mean annual temperature are key variables in determining forest aboveground carbon density. 3. Taking into account the explicative climate variables, we obtained an accurate (R2 = 70% and RMSE = 40 Mg.ha-1) forest carbon map for Madagascar at 250 m resolution for the year 2010. This national map was more accurate than previously published global carbon maps (R 2 ≤ 26% and RMSE ≥ 63 Mg.ha −1 ). 4. Combining our model with the climatic projections for Madagascar from seven IPCC CMIP5 global climate models following the RCP 8.5, we forecast an average forest carbon stock loss of 17% (range: 7-24%) by the year 2080. For comparison, a spatially homogeneous deforestation of 0.5% per year on the same period would lead to a loss of 30% of the forest carbon stock. 5. Synthesis: Our study shows that climate change is likely to induce a decrease in tropical forest carbon stocks. This loss could be due to a decrease in the average tree size and to shifts in tree species distribution, with the selection of small-statured species. In Madagascar, climate-induced carbon emissions might be, at least, of the same order of magnitude as emissions associated to anthropogenic deforestation.
Data from: A mechanistic and empirically-supported lightning risk model for forest trees
<ol> <li>Tree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood. </li> <li>We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure, and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone-based maps of tree crowns and censuses of all trees within a 50-ha forest dynamics plot on Barro Colorado Island, Panama. </li> <li>The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent > canopy >>> subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighboring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters.</li> <li>These patterns suggest that lightning influences forest structure and the global carbon budget by nonrandomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests.</li> </ol> <p><b>Synthesis:</b> Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (<15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighboring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics, and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.</p>
Data from: Assessing cumulative impacts of forest development on the distribution of furbearers using expert-based habitat modeling
Cumulative impacts of anthropogenic landscape change must be considered when managing and conserving wildlife habitat. Across the central-interior of British Columbia, Canada, industrial activities are altering the habitat of furbearer species. This region has witnessed unprecedented levels of anthropogenic landscape change following rapid development in a number of resource sectors, particularly forestry. Our objective was to create expert-based habitat models for three furbearer species: fisher (Pekania pennanti), Canada lynx (Lynx canadensis), and American marten (Martes americana) and quantify habitat change for those species. We recruited 10 biologist and 10 trapper experts and then used the analytical hierarchy process to elicit expert knowledge of habitat variables important to each species. We applied the models to reference landscapes (i.e., registered traplines) in two distinct study areas and then quantified the change in habitat availability from 1990 to 2013. There was strong agreement between expert groups in the choice of habitat variables and associated scores. Where anthropogenic impacts had increased considerably over the study period, the habitat models showed substantial declines in habitat availability for each focal species (78% decline in optimal fisher habitat, 83% decline in optimal lynx habitat, and 79% decline in optimal marten habitat). For those traplines with relatively little forest harvesting, the habitat models showed no substantial change in the availability of habitat over time. The results suggest that habitat for these three furbearer species declined significantly as a result of the cumulative impacts of forest harvesting. Results of this study illustrate the utility of expert knowledge for understanding large-scale patterns of habitat change over long time periods.
Data from: Nest survival modeling using a multi-species approach in forests managed for timber and biofuel feedstock
1. Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine-dominated landscapes. These pine plantations are important for early-successional bird species, as short rotation times continually maintain early successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA. 2. We adapted hierarchical models using hyper-parameters to incorporate information from both common and rare species to understand community-level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community-level demographic parameter estimates. We illustrate use of this approach in generating both species-level and community-wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper-prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single-species approach using surrogate species. Using single species models, we were unable to generate estimates below a sample size of 21 nests per species. 3. Community model species-level survival and parameter estimates were similar to those generated by five single species models, with improved precision in community model parameters. 4. Covariates of nest placement indicated that switchgrass at the nest site (< 4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival. 5. Synthesis and applications. Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km2), although at a local scale (50 m2) switchgrass negatively influenced nest survival. A likely explanation supported by previous research is intercropping shifted community composition, favouring species with greater disturbance tolerance.
Data from: Conservation versus livelihoods: spatial management of non-timber forest product harvests in a two-dimensional model
Areas of high biodiversity often coincide with communities living in extreme poverty. As a livelihood support, these communities often harvest wild products from the environment. But harvest activities can have negative impacts on fragile and globally important ecosystems. This paper examines trade-offs in ecological protection and community welfare from the harvest of wild products. With a novel model and empirical evidence, I show that management of harvest activity does not always resolve these trade-offs. In a model of continuous harvests in a two-dimensional landscape, managed harvest activity improves welfare, but is uniformly bad for other ecosystem services that are sensitive to the presence (as opposed to the intensity) of human activity. Empirical results from a unique dataset of mushroom harvesters in Yunnan, China suggest more experienced, poorer, and more vulnerable individuals tend to rely on more distant harvests. Thus, policies that limit the extent of forest travel, such as protected areas, may protect fragile ecosystems but can have a disproportionately negative effect on those most vulnerable.
Dataset for Ha and Aylward 'Automated classification of giant virus genomes using a random forest model built on trademark protein families'
<ul><li>Genome sets used for model training and testing</li><li>Custom Python script that generated fragmented genomes at random completeness levels</li></ul>
HRFMD (Hydrological model based Random Forest Model Diagnostics) results
<p>Results accompanying the publication titled: Advancing Hydrological Model Diagnostics: An Exploratory Approach Using Random Forest Models and Large-sample Catchment Dataset</p>
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
<p>Code to reproduce the work in the manuscript ' A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest', Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, Feijuan Li, submitted to GMD.</p>
Data needed to reproduce analysis from "Frost matters: Incorporating late-spring frost in a dynamic vegetation model regulates regional productivity dynamics in European beech forests"
<p>Data to reproduce analysis from "Frost matters: Incorporating late-spring frost in a dynamic vegetation model regulates regional productivity dynamics in European beech forests".</p> <p>This includes:</p> <ol> <li>Tree ring data (meyer, bdn, principe, dittmar)</li> <li>LPJ-GUESS model output (frost_validation, frost_sensitivity, runs_22012024_revision)</li> <li>Data used for plotting</li> </ol>
Watershed-geochemical model to simulate dissolved and particulate 137Cs discharge from a forested catchment
<p>Data of simulation results for Figure 5, Figure 8, and Figure S4.</p>
SynPhoRest - Synthetic Photorealistic Forest Dataset with Depth Information for Machine Learning Model Training
<p><strong>SynPhoRest </strong>is a synthetic dataset collected on virtual forests. It features RGB images, semantic segmentation maps, depth maps and the projection of LIDAR point clouds on the RGB FOV for two different LIDAR scanning patterns. The dataset has a total of 3154 frames.<br> <br> A description of the available data follows:</p> <p><strong>RGB images</strong></p> <ul> <li>Resolution: 848 x 480 pixels.</li> <li>PNG files with 8 bits encoding per channel.</li> </ul> <p><strong>Segmentation Maps</strong></p> <ul> <li>Resolution: 848 x 480 pixels.</li> <li>PNG files with a single 8 bit channel.</li> <li>Classes are encoded as follows:</li> <li> <table> <thead> <tr> <th scope="col"><strong>Value</strong></th> <th scope="col"><strong>Class</strong></th> </tr> </thead> <tbody> <tr> <td>0</td> <td>Background</td> </tr> <tr> <td>1</td> <td>Soil</td> </tr> <tr> <td>2</td> <td>Traversable</td> </tr> <tr> <td>3</td> <td>Canopy</td> </tr> <tr> <td>4</td> <td>Fuel</td> </tr> <tr> <td>5</td> <td>Trunks</td> </tr> </tbody> </table> <p>Fuel represents flammable material such as shrubbery and grass.</p> </li> </ul> <p><strong>Depth Maps</strong></p> <ul> <li>Resolution: 848 x 480 pixels.</li> <li>PNG files with a single 16 bit channel</li> <li>The depth value is encoded in the unsigned integer format.</li> <li>Infinite depth is represented by the value 65535.</li> <li>To obtain the depth values in meters, the original values must by divided by 256.</li> <li>The FOV of the virtual depth camera was the same as the FOV of the RGB camera.</li> </ul> <p><strong>LIDAR Point Cloud Projections on the RGB Camera FOV</strong></p> <ul> <li>Resolution: 848 x 480 pixels.</li> <li>PNG files with a single 16 bit channel.</li> <li>The distance values are encoded in the unsigned integer format.</li> <li>To obtain the distance values in meters the original values must by divided by 256.</li> <li>On average, the projection images have a point density of 5.5%. In practice, this means that 5.5% of the pixels in the projection image have distance information.</li> <li>Two LIDAR Point Cloud Projections were made available. One for a LIDAR with a repeating line pattern and other resembling the commercially available Livox Horizon LIDAR scanner.</li> </ul>
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.