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171 results for “deciduous forest”
Tree Growth in Hemlock and Deciduous Forests at Harvard Forest HEM and LPH Towers 2000-2005
Tree growth was measured to determine tree ages and growth rates and to quantify carbon storage in these forests, and to detect changes in growth and carbon storage that could be associated with climate changes or historic disturbances.
Net Carbon Exchange of a Young Upper-Slope Deciduous Forest at Harvard Forest LPH Tower 2002-2010
This data set contains sensible heat exchange, water vapor exchange and carbon exchange as well as environmental data for a deciduous forest dominated by red oak (Quercus rubra). It is 1.1 km WNW of the EMS tower where continuous eddy covariance measurements began in 1992 (see HF004). The High Deciduous site is about 385 m a.s.l., or 35 m higher in elevation than the EMS, which is situated in a relatively low area near a stream. The forest near this eddy covariance tower is broadly similar in species composition to the EMS site, but it is younger and shorter in stature. The site was cleared for pasture, but not deeply plowed or planted, in the 18th and19th centuries. Agriculture on the site was abandoned near the end of the 19th century. The forest within 200 to 300 m of the eddy covariance tower to the NW, W, SW, and S burned in an intense fire in 1957, which left few or no surviving trees.
Stream Macroinvertebrates in Hemlock and Deciduous Watersheds at Harvard Forest 2005-2007
Tsuga canadensis (Eastern Hemlock) is a common forest species that is declining throughout its range in the eastern United States because of the invasion of an non-native forest pest, Adelges tsugae (Hemlock Woolly Adelgid). This pest kills infected trees, and over time, infected stands are replaced by deciduous forests. The conversion of forests from Hemlock to deciduous species is predicted to impact the hydrology, chemistry, and biology of associated headwater streams. In this study, we examined the macroinvertebrate communities of two adjacent headwater streams with differing Hemlock influence in central Massachusetts. Abundance, taxa richness, diversity, and unique taxa were generally greater in the deciduous stream. Differences in the distribution of functional feeding groups were observed: the Hemlock stream had a greater percentage of collector-gatherers while the deciduous stream had a greater percentage of shredders and predators. These findings suggest that macroinvertebrate communities in streams draining Hemlock and deciduous watersheds may differ in structure and function, and that anticipated Hemlock mortality may impact the region’s stream ecology.
Crown Traits of Broadleaf Deciduous Trees at NEON Forest Sites (2018-2022)
Using NEON Airborne Observation Platform (AOP) measurements collected in 2018-2022 from nine broadleaf deciduous NEON forest sites, we quantified a broad suite of structural metrics and spectral reflectance indices for 305 tree crowns that were delineated in the field by NEON and met our data quality criteria. For each tree crown, we used 1-m^3 voxelated AOP LiDAR data to compute structural metrics, including plant area index (PAI), leaf area index (LAI), top rugosity, maximum canopy height (MAXCH), mean outer canopy height (MOCH), rumple, accumulative plant area density and accumulative LiDAR intensity at multiple tree heights. We used AOP imaging spectrometer to compute several spectral indices, including NDVI, NIRv, EVI, NDWI and chlorophyll index of red edge/green. The data are suitable for ecophysiological studies at tree crown and/or species level. The broad spatial extent allows for the exploration of variability in structure and function of common north American tree species across wide environmental gradients.
Dataset to manuscript: Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India
<p>Raw data to the manuscript entitled "Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India" by Severin-Luca Bellè, Jean Riotte, Muddu Sekhar, Laurent Ruiz, Marcus Schiedung and Samuel Abiven.</p> <p>Data files include all raw data of soil cores (20211111_Raw_data.zip), data measured on composited samples (20211111_Composite_data.zip) and DRIFT spectra (20211111_DRIFT_data.zip).</p> <p>Files ending with var_names are the README files.</p>
Indicative distribution map for Ecosystem Functional Group T2.2 Deciduous temperate forests
<p>This archive contains indicative distribution maps and profiles for <strong>T2.2 Deciduous temperate forests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera I: Site Attribute Data 2022
This dataset contains site characteristics collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Data includes detailed site characteristics collected at the site level. Each site included three 10 m * 2 m plots (A, B, and C) laid in a single 30 m transect (or, where constrained, in parallel).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera II: Tree Inventory Data 2022
This dataset contains tree combustion measurements collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Tree species, diameters (DBH where possible, otherwise BD), condition (living/dead, standing/fallen, etc), and component combustion are recorded for every tree in each 10 m * 2 m plot.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera III: Shrub Inventory Data
This dataset contains shrub combustion measurements collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Shrub species, stem diameters (BD), and component combustion were recorded for every shrub in each 10 m * 2 m plot.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera IV: Organic Soil Carbon and Nitrogen Content from Organic Soil Samples 2022
This dataset contains lab-quantified (and some field-measured) characteristics for post-fire residual organic soil samples collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Lab analyses were conducted in summer and fall of 2022 at UAF and NAU.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera V: Organic Soil Depth 2022
This dataset contains field-measured characteristics for post-fire residual organic soil samples and for additional organic soil depths collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VI: Mineral Soil Sample and pH Data 2022
This dataset contains field- and lab-measured characteristics for post-fire mineral soil samples collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Lab analyses were conducted in fall of 2022 at NAU.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VII: Coarse and Fine Woody Debris Inventory 2022
This dataset contains characteristics of coarse woody debris and snags collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VIII: Seedling Inventory 2022
This dataset contains characteristics of post-fire seedlings and resprouts collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera IX: metrics derived from All Raw Data Collected Plus Data from Previous Studies on the 2004 Alaska Wildfires Included in Analysis 2022
This data set includes metrics derived from field and lab data collected for deciduous and mixed deciduous-confier plots collected in the summer of 2022 (Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019)), as well as additional data for conifer plots from previous studies of the Taylor Highway Complex (2004), Dall Creek/Yukon Crossing (2004), and Boundary (2004) fires. Those additional data were acquired from: https://www.lter.uaf.edu/d1/d1-detail/id/773 and https://daac.ornl.gov/ABOVE/guides/ABoVE_Plot_Data_Burned_Sites.html. From this complete data set of 333 plots, 311 plots were used in analyses in Black at al. (NCC) paper: "Increased deciduous tree dominance reduces wildfire carbon losses in boreal forests". Plots excluded (from 2022 FiSL data) were poplar-dominated, mixed poplar/conifer dominated, missing soil C data, or conifer-dominated (adventituous root heights were not recorded consistently at sites in 2022 making it impossible to estimate pre-fire conifer stand organic soil C pools for 2022-collected conifer plots). Only 2005-collected conifer plots were used in NCC paper analyses. For all plots, in addition to field/lab derived site characteristics and combustion metrics, post hoc remotely sensed metrics were derived: pre-fire NDVI/EVI-2 trends, 1980-2010 climate normals, and DOB weather metrics.
Code and data for SylvanSeeds, a seed germination database for temperate deciduous forests
<p>This is a version of record of the manuscript's data and code as accepted by the Journal of Vegetation Science.</p>
Evaluating Nitrate Removal and Travel Times in a Bare Deciduous Forest Soil Using a Tracer-Based Soil Column Experiment
<p> </p> <p>This dataset summarizes the experimental data from a study investigating the relationship between hydrodynamic properties, transport age characteristics (traced using the conservative tracer bromide), and nitrate consumption by native microbial communities in a deciduous forest soil near Lausanne, Switzerland.</p> <h4><strong>Experimental Setup</strong></h4> <ul> <li>Native soil was <strong>collected, sieved, and packed</strong> into homogeneous soil columns (lysimeters) with a porosity of <strong>0.4</strong>.</li> <li>To stimulate microbial activity, the soil underwent <strong>carbon amendment</strong> for several weeks before the experiment.</li> <li>On <strong>June 10, 2021</strong>, a <strong>pulse of bromide and nitrate</strong> (referred to as <strong>SPIKE</strong>) was applied to the bare soil that had undergone carbon amendment.</li> <li>The dataset covers experimental conditions recorded from <strong>May 25, 2021, to August 12, 2021</strong>.</li> </ul> <h4><strong>Included Data & Models</strong></h4> <ol> <li><strong><strong>SPIKE experiment (<strong>pulse of bromide and nitrate</strong>)</strong></strong> <ul> <li> <ul> <li><strong><strong>all other files (see table_of_contents.html and overview.pdf)</strong></strong></li> </ul> </li> </ul> </li> <li> <p><strong>HYDRUS-1D Simulations</strong></p> <ul> <li>The dataset includes HYDRUS-1D simulation files to reproduce <strong>nitrate and bromide breakthrough curves</strong>: <ul> <li><strong>0_Nitrate-double-compartment.zip</strong></li> <li><strong>0_Bromide-double-compartment.zip</strong></li> </ul> </li> </ul> </li> <li> <p><strong>Soil Characterization using Multi-Step Outflow (MSOM) Method</strong></p> </li> </ol> <ul> <li> <ul> <li>Before the main experiment, the <strong>multi-step outflow method</strong> was performed to characterize the soil. The original experimental data was collected at a <strong>15-minute resolution</strong> but has been <strong>upscaled to hourly resolution</strong> to reduce noise and facilitate data handling.<br> <ul> <li><strong>multi-step_outflow_method.csv</strong></li> </ul> </li> </ul> </li> </ul> <ol> <li> <ul> <li>The processed data (at <strong>hourly resolution</strong>) and <strong>HYDRUS-1D inverse modeling simulations</strong> for soil parameter estimation are provided under two configurations: <ul> <li><strong>config_1_MSOM.zip</strong></li> <li><strong>config_2_MSOM.zip</strong></li> </ul> </li> </ul> </li> </ol> <p> </p>
Data_Schönauer et al. (2023)_Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest
<p>Data used in</p> <p>Schönauer, M., Hietz, P., Schuldt, B., and Rewald, B. (2023). Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest. Frontiers in plant science 14, 1127292. doi: 10.3389/fpls.2023.1127292</p>
An Isotopic Approach to Partition Evapotranspiration in a Mixed Deciduous Forest at the University of Michigan Biological Station, Pellston, MI (2017)
Transpiration (T) is perhaps the largest fluxes of water from the land surface to the atmosphere and is susceptible to changes in climate, land use and vegetation structure. However, predictions of future transpiration fluxes vary widely and are poorly constrained. Stable water isotopes can help expand our understanding of land–atmosphere water fluxes but are limited by a lack of observations and a poor understanding of how the isotopic composition of transpired vapour (δT) varies. Here, we present isotopic data of water vapour, terrestrial water and plant water from a deciduous forest to understand how vegetation affects water budgets and land–atmosphere water fluxes. We measured subdiurnal variations of δ18OT from three tree species and used water isotopes to partition T from evapotranspiration (ET) to quantify the role of vegetation in the local water cycle. We find that δ18OT deviated from isotopic steady‐state during the day but find no species‐specific patterns. The ratio of T to ET varied from 53% to 61% and was generally invariant during the day, indicating that diurnal evaporation and transpiration fluxes respond to similar atmospheric and micrometeorological conditions at this site. Finally, we compared the isotope‐inferred ratio of T to ET with results from another ET partitioning approach that uses eddy covariance and sap flux data. We find broad midday agreement between these two partitioning techniques, in particular, the absence of a diurnal cycle, which should encourage future ecohydrological isotope studies. Isotope‐inferred estimates of transpiration can inform land surface models and improve our understanding of land–atmosphere water fluxes.
Figure 31 in Population ecology of Ctenolepisma (C.) udumalpetense (Insecta: Zygentoma: Lepismatidae) in a deciduous forest floor of the Trimurti Dam, Tamil Nadu, India
Figure 31. Monthly changes in mean biomass in each row of C. (C.) udumalpetense per month per m2 (Vertical line indicates SE).
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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)
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