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Tree Ring Data from Rooster Hill in Adirondack State Park NY 1828-2015
Is it possible to reconstruct aboveground carbon/biomass from tree rings? If so, how far back in time can researchers go when using tree-ring data in the reconstruction of past biomass? Answers to these questions will have a significant impact on our understanding of dynamics in the terrestrial carbon sink. Long tree-ring records of biomass can reveal intra-annual to annual to multidecadal variations that cannot be resolved by forest census data that is not conducted at annual time steps. Additionally, while these dynamics might be resolved using remote sensing, most remotely-sensed products are only two decades or less in length. By having long records of carbon biomass, we can then identify not only the dominant drivers of biomass, but how the importance of these drivers might change during different eras as environmental factors change (e.g., climate, air pollution, disturbance). To test these and other questions, we collected tree-ring records from two 30m radius plots set Rooster Hill in New York State. We chose this location because it has oak dominated mixed forests that can be compared to the long-term forests being studied for carbon dynamics at the Harvard Forest. We can convert these data to biomass using allometric equations and compare tree-ring inferred aboveground biomass to the census data going back in time to understand forest recovery and carbon dynamics in a heavily disturbance forest.
Ecological Impacts of Hurricanes Across the Yucatan Peninsula 1851-2000
This study used computer modeling to study the impacts of hurricanes across the Yucatan Peninsula since 1851. For details on methods and results please see the published paper (Boose, E. R., D. R. Foster, A. Barker Plotkin and B. Hall. 2003. Geographical and historical variation in hurricanes across the Yucatan Peninsula. In Lowland Maya Area: Three Millennia at the Human-Wildland Interface. A. Gomez-Pompa, M. F. Allen, S. Fedick and J. J. Jimenez-Osornio, eds. Haworth Press, New York, NY. In press). The Abstract from the paper is reproduced below. "The ecological impacts of hurricanes across the Yucatan Peninsula over the last 150 years were investigated using a simple meteorological model (HURRECON) developed at Harvard Forest as well as a database of historical hurricane data (HURDAT) maintained by the U. S. National Hurricane Center. All hurricanes over the period 1851-2000 with sustained winds of hurricane force (33 meters/sec) within 300 kilometers of the study region were analyzed (n = 105). Each storm was reconstructed to produce estimates of wind damage on the Fujita scale across the region. Individual reconstructions were then compiled to study cumulative impacts of all 105 storms. "Results showed considerable variation in hurricane activity from year to year, and from decade to decade, while at the half-century scale there was an increase in hurricane intensity since the mid-nineteenth century. Ninety percent of the hurricanes causing F1 damage or higher (on the Fujita scale) occurred in the months of August, September, and October. A strong spatial gradient in hurricane frequency and intensity extended across the region from northeast to southwest, resulting from (1) the greater number of hurricanes to the north, (2) the east to west movement of most hurricanes across the area, and (3) the tendency for most hurricanes to weaken significantly after landfall. For example, during the study period, northeastern parts of the peninsula experienced a minimum of
Raw neutron counts from a soil water content hydroprobe at 15 NPP study sites at the Jornada Basin LTER, 1989-2019
This data package contains raw neutron count data for monthly soil water probe measurements made at 15 net primary production (NPP) study locations on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Once a month, soil water content measurements are made at 10 depths (where possible) at each of 10 access tubes at each of the 15 NPP sites using a neutron probe (CPN Model 503DR Hydroprobe). This dataset consists of the count of thermalized neutrons at 30 cm depth intervals to a maximum depth of 300 cm. These counts are subsequently converted to volumetric water content as provided in a separate EDI package (knb-lter-jrn.210013003). The NPP sites these measurements are made at represent the 5 dominant vegetation types of the Jornada Basin, which consist of 3 shrub (creosotebush, mesquite dune, and tarbush) and 2 grass (upland grassland and playa) types. Three NPP sites are located in each of the types. Collection of this dataset was discontinued when the neutron probe instrument was replaced in mid-2019. Neutron probe soil water content data are still collected from the same NPP locations using a new instrument, and the raw neutron counts and corrected VWC data are found in EDI dataset knb-lter-jrn.210013003. This dataset is complete.
Plant community responses to functional group and species removals along biodiversity experiment vegetation transects at the Jornada Basin LTER site, 1997-2002
This dataset contains vegetative cover data of plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected with the objective to distinguish the differential effects of plant community biomass, functional groups, and biodiversity within functional groups on ecosystem and plant community function. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. Following treatments, vegetative data was collected by sampling each plot along three transects twice a year (Spring and Fall) for 5 years from 1997-2002 (no data collected in 1998). This data set consists of the date of collection, plot number, treatment type, transect number, quadrat number, species codes, two diameters, height, condition, count, record IDs, and error codes. This study is complete.
Aeolian dust weights sampled by BSNE collectors quarterly from the CSIS study at Jornada Basin LTER, 2012-ongoing
This dataset contains weights of windblown dust collected by BSNE collectors at long-term observation plots that are part of the Jornada Basin LTER Cross-Scale Interaction Study (CSIS) located at the Jornada Experimental Range. There are 15 experimental blocks (or sites) in this study. Within each block, there are 4 plots with different experimental treatments: 1 control, 1 with mesquite herbicide applied, 1 with connectivity modifiers (Conmods) installed, and 1 with Conmods AND mesquite herbicide applied. The intent of Conmods is to decrease gap size between perennial vegetation. The plots are 8 x 8 meters and have an 8 x 8 meter buffer zone on both the upwind and downwind sides of the plot. There are two BSNE (aeolian dust collector) stands per experimental plot positioned at the edge of the upwind and downwind 8m x 8m buffers. Each stand has 3 collectors positioned at heights of 10 cm, 30 cm, and 50 cm, and all collector openings face the prevailing wind direction. Upwind BSNEs collected the amount of dust entering the plot, and the downwind BSNEs collected the amount of dust moving off the plot. These collectors estimate the effectiveness of the plot surface in obstructing wind blown dust. This study is ongoing with data collected quarterly each year.
Annual precipitation and photo-derived vegetation and litter cover (2013-2021) used for analysis in the manuscript “Growing grasses in the desert: Multi-scale Interactions and State Change Reversal in Drylands”
This dataset contains water year precipitation collected from meteorological stations, litter and vegetation cover values derived from overhead photos, and litter and soil accumulation in lateral photos in a long-term experiment (2013-2021) of cross-scale interactions (CSIs) at the Jornada Basin LTER site in southern New Mexico, U.S.A. Manipulations were initiated in 2013 at 15 experimental blocks, each with 4 treatment plots: plant-scale herbicide of mesquite shrubs, patch-scale connectivity modifiers (ConMods), herbicide + ConMods, control without manipulations. Litter, soil, and vegetation cover were estimated using repeat overhead photographs of microplots within treatment and control plots. Litter and soil accumulation were estimated from lateral photos of ConMods. This dataset utilized QuickBird imagery from 2011 to assess ground cover classes within the Jornada Basin, focusing on bare ground, herbaceous, and shrub cover. Daily precipitation data collected from 13 meteorological stations were used to calculate water year (1 October-30 September) precipitation from 2013 through 2021. This dataset provides supporting data for the manuscript "Growing grasses in the desert: Multi-scale Interactions and State Change Reversal in Drylands" by Peters et al.
Observed phenological indicators and environmental drivers at global change experiments at the Jornada Basin LTER site, 2014-2020
This dataset contains plant phenological data extracted from phenocams installed at a global exchange experiment involving Chihuahuan desert plant communities at the Jornada Basin LTER site in southern New Mexico, U.S.A. Cycles of plant growth, termed phenology, are tightly linked to environmental controls, and our overarching objective in this study is to determine if temperature or precipitation are relatively more important for determining shrub and grass greenup date (start of season) and senescence date (end of season). At these camera locations, we experimentally manipulated incoming precipitation at the Jornada Basin LTER for over a decade and recorded plant leaf phenology at the daily scale for seven years using phenocams. The data here are derived from raw "phenocam" camera data collected at two ongoing studies at the Jornada Basin LTER site, one studying ecosystem responses to long term changes in water and nitrogen availability, and one studying plant productivity and partitioning responses to water availability and herbivory (studies 349 and 456, respectively). Phenocams at the sites have collected images since 2014, and basic color and greenness data extracted from those images are available in a companion dataset on EDI (knb-lter-jrn.210574001). This dataset includes the derived annual and quarterly phenological indices and greenness indices for each plot monitored by phenocams, and temperature and precipitation variables aggregated to the same frequency. The dataset also includes R code and input files used to generate these derived data. See Currier and Sala 2022 for more details. This study is ongoing.
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Pelagic, epilimnetic production estimates in Sparkling, Trout (Wisconsin), Acton (Ohio), and Castle (California) Lakes (USA) calculated using 14C and free-water O2 metabolism methods, 2007 - 2017
Concurrent daily estimates of pelagic, eplilimnetic production (mmol C m3 d) generated from 14C incubations and diel changes in high frequency dissolved oxygen data (free-water). Original data derived from the North Temperate Lakes Long Term Ecological Research program (Sparkling [2007-2013], Trout [2007-2012] Lakes), Castle Lake Research Station (Castle Lake [2014-2017]), and Center for Aquatic and Watershed Sciences (Acton Lake [2010-2014]). 14C production estimates were generated as part of each research programs core data collection. Free-water production estimates generated using high frequency sensor data provided by research programs and Phillips (2020) time-varying, Bayesian metabolism model.
Cascade project at North Temperate Lake LTER – Daily Respiration Data for Whole Lake Nutrient Additions 2013-2015
Daily estimates of ecosystem respiration and values of covariates from surface waters of Paul, Peter, and Tuesday lakes from mid-May to early September for the years 2013, 2014, and 2015. Inorganic nitrogen and phosphorus were added to Peter and Tuesday lakes each year while Paul Lake was an unfertilized reference.
Aboveground net primary productivity data for Saddle grid, 1992 - ongoing.
Total aboveground live vascular biomass was clipped from 50x20 cm plots in areas near the saddle grid permanent plots on Niwot Ridge to measure net primary productivity. NDVI measurements were also included in some years.
Soil moisture and snowdepth measurements in the Black Sand experiment for East Knoll, Audubon, Lefty, Soddie and Trough, 2018 - 2024.
The purpose of the Black Sand experiment is to measure treatment effects on date of snowmelt on Niwot Ridge. Five sites with paired plots (treatment and control) were implemented across Niwot as part of the extended summer research program in order to understand the effects of earlier snowmelt. This dataset contains measurements of snowdepth throughout the melt season, manual measurements of volumetric water content and temperature data as an indication of snowmelt timing.
Ice thickness at Green Lake 4, 1984 - ongoing.
Thickness of seasonal ice cover in high alpine lakes can be influenced by local environmental change, including changes in temperature and winter precipitation. Increased winter precipitation can increase the insulating effects of snow cover on lake surfaces or increase water storage in the lake’s catchment, both of which may decrease ice thickness (Caine 2002). To assess long-term trends in seasonal ice thickness, as well as sensitivity to environmental drivers, measurements of ice thickness are taken approximately monthly throughout the winter at Green Lake 4.
Plant species composition in black sand extended growing season experiment, 2018 - 2023.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows in a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot of each block by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to these plots after snow had naturally melted. This dataset includes measurements of plant species composition.
ANPP, NDVI and canopy height in black sand extended growing season experiment, 2019 - 2023.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. This dataset includes measurements of aboveground net primary productivity, plant canopy height and NDVI.
Aboveground net primary productivity calibration of indirect measurements, 2022 - 2023.
An aboveground net primary productivity (ANPP) calibration of indirect measurements experiment was conducted in order to improve our method for estimating ANPP in the tundra. Multiple methods were used to indirectly and one to directly measure ANPP across tundra plant communities on Niwot Ridge.
Datos brutos de mensajes publicados en usuarios vinculados a medios informativos digitales españoles en X, FB y Web
<p>Datos brutos recabados en el marco del proyecto Hatemedia (PID2020-114584GB-I00), financiado por <strong>MCIN/ AEI /10.13039/501100011033.</strong></p> <p>Los datos recopilados corresponden a cinco medios informativos digitales, tomados como casos de estudio en el proyecto al que corresponde estos datos, tanto en la plataforma X, como en FB y en sus portales web; durante 2021-2022.</p> <p>El proceso de recolección de estos datos fueron recolectados, a partir del procedimiento expuesto en:</p> <p>Ruiz-Iniesta, Almudena; Blanco Valencia, Xiomara; Pérez, Daniel; De Gregorio Vicente, Oscar; José Cubillas, Juan; Julio Montero Díaz, https://orcid.org/0000-0002-4145-7424; et al. (2024). Informe final sobre el scrapeo de datos brutos obtenidos en medios informativos digitales españoles en X, FB y Web. figshare. Presentation. https://doi.org/10.6084/m9.figshare.25187591.v2</p> <p>Los datos fueron recolectados con el apoyo de la empresa colaboradora: <a href="https://www.possibleinc.com/?lang=en">Possible Inc</a> </p> <p>Para más información del proyecto, ingresar en: https://www.hatemedia.es/</p> <p>Si deseas tener acceso a estos datos, contactar con los IPs del proyecto, a traves de: elias.said@unir.net, en copia a julio.montero@unir.net</p>
Cadenza Challenge (CAD2): databases for rebalancing classical music task
<h1>Cadenza</h1> <p>Please, cite CadenzaWoodwind as</p> <blockquote> <p><strong>Gerardo Roa-Dabike , Trevor J. Cox , Alex J. Miller , Bruno M. Fazenda , Simone Graetzer , Rebecca R. Vos , Michael A. Akeroyd , Jennifer Firth , William M. Whitmer , Scott Bannister , Alinka Greasley , Jon P. Barker , The Cadenza Woodwind Dataset: Synthesised Quartets for Music Information Retrieval and Machine Learning, Data in Brief (2024), doi: https://doi.org/10.1016/j.dib.2024.111199</strong></p> </blockquote> <p>This is the training and validation data for the rebalancing classic music task from the <a href="https://cadenzachallenge.org/">Second Cadenza Machine Learning Challenge (CAD2).</a></p> <p>The Cadenza Challenges are improving music production and processing for people with a hearing loss. According to The World Health Organization, 430 million people worldwide have a disabling hearing loss. Hearing aid users report several issues when listening to music, including distortion in the bass, difficulties in perceiving the full range of the music, especially high-frequency pitches, and a tendency to miss the impact of quieter parts of compositions [1]. In a pilot study, we found giving listeners sliders to allow them to rebalance different instruments in a classical music ensemble was desirable.</p> <p>Overview of files:</p> <ol> <li>CadenzaWoodwind. Synthesized dataset of small ensembles of woodwind instruments for training and validation.</li> <li>EnsembleSet_Mix_1. A subset of the synthesised <a href="../records/6519024">EnsembleSet [7]</a> for training and validation (Mix_1 render).</li> <li>Real Data for Tuning: <a href="../api/records/12664932/draft/files/Stereo_Reverb_Real_Data_For_Tuning.zip/content" target="_blank" rel="noopener noreferrer">Stereo_Reverb_Real_Data_For_Tuning.zip</a>.</li> <li>metadata.zip contains audiograms, scene details, target gains and compressor settings.</li> </ol> <p>The audio files are in FLAC format in the .zip archives. The json files contain metadata.</p> <p>More details below.</p> <p> </p>
LAGOS-US RESERVOIR: Data module classifying conterminous U.S. lakes 4 hectares and larger as natural lakes or reservoirs
The LAGOS-US RESERVOIR data module (hereafter, RESERVOIR) classifies all 137,465 lakes > 4 hectares in the conterminous U.S. into one of the following three categories using a machine-learning predictive model based on visual interpretation of lake outlines and a classification rule based on lake shape. Natural Lakes (NLs) are defined as lakes that are likely to be entirely or mostly naturally-formed and that do not have large, flow-altering structures on or near them; Reservoir Class A’s (RSVR_A) are defined as lakes that are likely to be either human-made or highly human-altered by the presence of a relatively large water control structure that appears to significantly change the flow of water; and Reservoir Class B’s (RSVR_Bs) are lakes that are likely to be entirely human-made based on isolation from rivers and a highly angular shape that is rarely, if ever, seen in natural lakes also often. We trained the machine learning models on 12,162 manually-classified lakes to assign probabilities of a lake being in 1 of 2 of the categories (NL or RSVR), then we further classified the RSVR classification into either A or B based on NHD Fcodes, isolation, and angularity. The data module includes a detailed User Guide, metadata tables, and a data table that includes information such as location, lake geometry, surface water connectivity class, and official name. Using our definition, our classification indicates that over 46 % of lakes > 4 ha in the conterminous U.S. are reservoir lakes. These data can be combined with other LAGOS-US data modules and U.S. national databases using unique lake identifiers to study both reservoir lakes and natural lakes at broad scales.
Juvenile Salmonid Emigration Monitoring in the Lower American River, California.
Overview Operation of rotary screw traps on the Lower American River is part of a collaborative effort by the U.S. Fish and Wildlife Service, Pacific States Marine Fisheries Commission, and the California Department of Fish and Wildlife. The primary objectives of the study are to collect data that can be used to estimate the passage of juvenile fall-run Chinook Salmon Oncorhynchus tshawytscha and to quantify the raw catch of steelhead Oncorhynchus mykiss as well as winter, spring, and late fall runs of Chinook Salmon. Secondary objectives of the trapping operations focus on collecting biological data on juvenile salmonids and gathering environmental data that will be used to develop models that correlate environmental parameters with salmonid size, temporal presence, abundance, and production. The data package contains seven datasets including: raw catch, trap operation, environmental, and trap efficiency data. Raw Catch – Chinook Dataset This dataset covers ALL Chinook Salmon captured by the rotary screw traps. This spreadsheet includes biological data on: 1) unmarked fall-, spring-, and winter-run Chinook Salmon 2) marked (adipose clipped OR "fin clip") hatchery origin Chinook Salmon 3) recaptured marked fall-run (BBY OR "Pigment / Dye", Photonic Dye, and VIE OR "Elastomer") Chinook Salmon utilized in trap efficiency trials. Raw Catch – Steelhead Dataset This dataset covers ALL steelhead captured by the rotary screw traps. This spreadsheet includes biological data on: 1) unmarked (natural origin) steelhead 2) marked (adipose clipped OR "fin clip") hatchery origin steelhead 3) recaptured marked steelhead utilized in trap efficiency trials. Raw Catch – ByCatch Dataset This dataset provides biological data on ALL catch (EXCLUDING Chinook Salmon or steelhead) captured by the rotary screw traps. All catch in this table is of natural origin. Trap Operations Dataset This dataset provides trap operation data for each trap visit. Specifically, it includes data on the visit
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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.