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Food Web of Sarracenia Purpurea in United States and Canada 1999-2011
How food webs are structured and how their structure and dynamics vary through time and space is a central focus of research in community ecology. We documented structural variation in the aquatic food web inhabiting pitcher-shaped leaves of the carnivorous pitcher plant Sarracenia purpurea across the geographic range of the plant (from Florida north to Labrador and west to British Columbia); examined temporal variation in this food web with detailed experiments in Massachusetts and Vermont; experimentally manipulated top-down and bottom-up processes in this food web in Massachusetts; and developed a dynamic simulation model of this food web that incorporates metacommunity dynamics.
Assessing Plant Phenological Character Displacement Across the Eastern United States Since 1895
Reproductive character displacement has long been hypothesized to be a key determinant of speciation and co-existence in flowering plants. A central tenet of this hypothesis is that reproductive traits of close relatives growing in sympatry diverge more than they do where close relatives do not grow together. However, this idea remains untested across taxa and at large spatial scales. Here, we use data collected from tens of thousands of herbarium specimens to examine evidence for character displacement in flowering time for 91 closely-related pairs of animal-pollinated angiosperm species in the eastern USA. We see no evidence for overall phenological divergence in sympatry across regions, clades, or life histories. Rather our results indicate widespread convergence of flowering times in sympatry for species pairs that generally tend to flower close in time. We also find that climate change could alter the nature of these convergent flowering events by shifting them further apart in a majority species pair comparisons. Specifically, congeneric species in New England and the Atlantic Coastal Plain are projected to flower 2–4 days further apart, on average, by the mid-21st century as warming temperatures drive species-specific phenological shifts within genera. This may have significant consequences for species interactions and gene flow, especially if current sympatric convergence in flowering times has resulted from facilitative interactions between species.
Harmonized Palmer Drought Severity Indices throughout the Contiguous United States for HydroBASINS basins
In times of a changing hydroclimate and growing human population, there is a need to assess how various climatic and demand conditions influence water availability on the landscape. Tendency for drought conditions is a prime example of a key hydroclimatic metric that is useful for understanding water retention in the surrounding landscape. However, merging drought climatological data with co-located aquatic data is challenging. To facilitate national-scale analyses of basin-level drought conditions (i.e., Palmer Drought Severity Index; PDSI) with co-located water quality data, we present aggregated PDSI data for the contiguous United States. Data are aggregated using the HydroBASINS basin shapefiles. HYBAS_ID is retained to enable merging with HydroBASINS parent datasets.
Harmonized Soil Organic Carbon and Phosphorus Data for the Contiguous United States
Soil organic carbon (SOC) and soil phosphorus can strongly influence adjacent water quality by introducing nutrients into aquatic ecosystems and also altering the light environment of those ecosystems. However, national-scale data are uncommon, and even when available, they are usually not aggregated in a manner that is expeditiously merged with basin-level data. To facilitate national-scale analyses of soil data with co-located water quality data, we present aggregated SOC and soil phosphorus data for the Contiguous United States. Data are aggregated using the HydroBASINS basin shapefiles. HYBAS_ID is retained to enable merging with HydroBASINS parent datasets.
Assessing Plant Phenological Patterns in the Eastern United States Over the Last 120 Years
Phenology is a key biological trait of an organism’s success and is one of the best indicators of its response to recent climate change. Plants are among the most well-studied organisms in this regard, but observational data bearing on this topic are largely restricted to woody species of the northern hemisphere, mostly from ca. the last three decades. Recent research has demonstrated that mobilized online herbarium specimens provide important, albeit mostly neglected, information on plant phenology. Here, we use the web tool CrowdCurio to crowdsource phenological data from more than 10,000 herbarium specimens representing 30 flowering plant species broadly distributed across the eastern United States. Our results, spanning 120 years and generated from over 2,000 crowdsourcers, clarify numerous aspects of plant phenology. First, they reveal that plant reproductive phenology is significantly advancing in response to warming, which is consistent with previous studies. Second, among those species with broad latitudinal ranges, populations from more southern latitudes are significantly more phenologically sensitive to temperature than those from northern populations. Last, contrary to some recent findings, plants in warmer, less variable climates may be much more dynamic, on average, in their phenological sensitivity. Our results are robust to a variety of confounding factors and span large phylogenetic distances and myriad life histories. These may represent more global trends in the latitudinal gradient of phenological response with myriad potential ecological and evolutionary consequences, and leads us to hypothesize that phenological sensitivity across species' ranges is driven by adaptation to local climates.
Using Phenology to Forecast Species Distributions across the Eastern United States in the 2070s
Studies that use species distribution models (SDMs) to document the relationship between species’ geographic range and environmental conditions rarely consider functional traits, such as phenology, that strongly affect species’ demography and fitness. Using more than 120,000 herbarium specimens representing 360 plant species across the eastern United States, we created a novel “phenology-informed” SDM that integrates dynamic phenological responses to changing climates. Compared to standard SDMs based only on abiotic variables, our phenology-informed SDMs forecast significantly lower species habitat loss, and less species turnover within communities under climate change. These results suggest that phenotypic plasticity and/or local adaptation in phenology may help many species adjust their ecological niches and persist in their habitats during periods of rapid environmental change. By modeling historical data that link phenology, climate and species distributions, our findings reveal how species’ reproductive phenology mediates their geographic distributions along environmental gradients and affect regional biodiversity patterns under future climate changes. More importantly, our newly developed model also circumvents the need for mechanistic models that explicitly link traits to occurrences for each species, and could thus facilitate the deployment of trait-based SDMs across unprecedented spatial and taxonomic scales.
A derecho climatology over the United States from 2004 to 2021
<p><em>We develop the high-resolution (4 km and hourly) </em><em>observational derecho and derecho-producing mesoscale convective system (MCS) dataset over the United States east of the Rocky Mountains from </em><em>2004 to 2021 by using a </em><em>MCS </em><em>dataset generated by the Python Flexible Object Tracker </em><em>(PyFLEXTRKR) software, bow echoes detected by a semantic segmentation </em><em>convolutional neural network, gust speed</em><em>s from the Integrated Surface Database and the Storm Events Database, and physically based identification criteria.</em></p>
White Pine Blister Rust (WPBR) Plot Data from the Western United States
As one of North America’s most damaging tree diseases, white pine blister rust (WPBR) is expected to continue to affect high-elevation five-needle (High-5) pine species in the near future. In order to better understand and estimate the risk it poses to white pines, data was compiled from independent studies across the Western U.S. from 1983-2025. This WPBR disease occurrence data includes nearly 6700 points, which were classified into two epidemic types: established or invading, based on the disease intensity value and the amount of time the disease had been present in the area.
Bridging data silos to holistically model plant macrophenology data, Contiguous United States, 2013-2021
Phenological responses to climate change can have dire implications for ecosystem functions. Despite the availability of diverse datasets (e.g., herbarium specimens, community science initiatives, observatory networks, and remote sensing), holistic modeling of plant events across scales remains limited due to fragmented data and disciplinary silos. This is an important topic that has been overdue for attention. Here we use two different plant phenological datasets, herbarium and USA-NPN (includes NEON), to look at the overall flowering period of Acer rubrum between 2013-2021, distributed across the Contiguous United States. We harmonize the data to demonstrate its use to leverage the spatial and biological organizational scales at which these data are captured. Both datasets include phenophase status (presence or absence) across the flowering season (day of year). These harmonized data exemplify their usefulness to holistically model plant phenology using an integrated species distribution model framework, while accounting for the heterogeneity across data types (presence-only, presence-absence). These data can be used to explore general questions about intraspecific synchrony of Acer rubrum flowering phenology across populations, or questions with coarser scales of interest (e.g., community level, global scales).
Summertime methane and carbon dioxide emission rates and associated variables from a national-scale survey of 146 reservoirs in the United States, 2016-2023
Reservoirs are globally important sources of greenhouse gases, but the magnitude of their emissions is highly uncertain. Here we present data for 146 reservoirs from two surveys of reservoir methane and carbon dioxide emissions, one at the regional scale in the midwestern United States and one at the national scale in the conterminous United States, plus data from one reservoir in Washington and another in Puerto Rico. At all reservoirs, ebullitive and diffusive emissions and basic physiochemistry were measured at 15-70 locations during one 22 to 64-hour period during the summers of 2016-2023, with four reservoirs revisited a second time. Concomitant water chemistry measurements were also made at an index site. The dataset is comprised of two geospatial files and seven .csv files containing greenhouse gas emissions, water chemistry, morphology, and other relevant data. These data comprise the largest multi-reservoir emissions dataset ever assembled using consistent measurement methods.
Net Ecosystem Carbon Balance of Grazing Lands across the continental United States, 2013-2023
Grazing lands underpin U.S. beef production, store roughly one-third of global soil organic carbon, deliver multiple ecosystem services, and are closely tied to the prosperity and resilience of rural communities. In this study, we calculated net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink or source, by integrating carbon uptake from photosynthesis, and carbon loss through ecosystem respiration, enteric fermentation and manure from livestock. Our objective was to synthesize multiple years of annual NECB of grazing lands measured by eddy covariance towers from 16 pastures across seven USDA Long-term Agroecosystem Research Network (LTAR) sites and enteric fermentation and manure emissions derived from the stocking rates. We evaluated annual NECB against mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, soil, fire history, grazing pressure index (GPI) and fertilization history. We found: (1) grazing lands were a carbon sink or neutral in most sites, and NECB was not significantly different between grasslands and shrublands, mesic and xeric conditions, and fertilized and unfertilized sites; (2) NECB increased with precipitation and temperature, but decreased with a higher GPI; and (3) precipitation, temperature, and GPI interacted such that temperature had a positive effect when MAP was greater than 700 mm and GPI had a negative effect when MAP was less than 1000 mm. Thus, most grazing lands in our study function as a carbon sink unless coupled with water deficit, low temperature, or heavy grazing. NECB is most sensitive to precipitation when water was limited with high interannual variability. Future work to improve our understanding of NECB on grazing lands should directly measure enteric fermentation and ecosystem emissions in different systems and add measurements on carbon loss through wind erosion and leaching.
Carbon Isotope and Ring Width Measurements from Tree Rings of Selected Canopy Species at Six Sites in the Eastern United States
Forest Water Use Efficiency (WUE) is defined as the ratio of carbon uptake per unit water vapor loss via transpiration. Micrometeorological measurements suggest that forest WUE has dramatically increased over the last two decades, in excess of what would be expected from increases in atmospheric carbon dioxide concentrations. Coinciding with observed trends in forest WUE have been marked decreases in acid deposition throughout much of North America and Europe. There is evidence that acid deposition may impact forest WUE, either by altering the availability of nutrients in forest soils or by directly affecting foliar physiology. Changes in WUE could also lead to changes in stream discharge from forested catchments. The hypothesized response of forests to changing levels of acid deposition is not currently considered in the land surface components of global climate models (GCMs). Since carbon dioxide and water vapor are the two most important greenhouse gases, it is vital to accurately model their land-atmosphere exchange. This research uses a catchment-based approach to investigate the effects of changing acid deposition on forest WUE. Tree ring carbon isotopes reconstruct historical WUE time series within six catchments that have been differentially impacted by acid deposition due to distinctions between their underlying bedrock mineralogy and geological histories. The research also capitalizes on experimental treatments that have altered soil biogeochemistry in paired catchment designs (Bear Brook, ME; Hubbard Brook, NH; and Fernow Experimental Forest, WV). Additional watersheds that vary in underlying bedrock chemistry are also used in this research to examine tree-ring WUE time series as natural experiments along a base-cation gradient. These watersheds include Sleepers River, VT; Hubbard Brook, NH; Cone Pond Watershed, NH; and Shenandoah National Park, VA.
LAGOS-NE v.1.054.1 - Lake water quality time series and geophysical data from a 17-state region of the United States
Time series of mean summer total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP) and chlorophyll values from 2913 unique lakes in the Midwest and Northeast United States. Epilimnetic nutrient and chlorophyll observations were derived from the Lake Multi-Scaled Geospatial and Temporal Database LAGOS-NELIMNO version 1.054.1, and come from 54 disparate data sources. These data were used to assess long-term monotonic changes in water quality from 1990-2013, and the potential drivers of those trends (Oliver et al., submitted). Summer was used to approximate the stratified period, which was defined as June 15 to September 15. The median number of observations per summer for a given lake was 2, but ranged from 1 to 83. The rules for inclusion in the database were that, for a given water quality parameter, a lake must have an observation in each period of 1990-2000 and 2001-2011. Additionally, observations must span at least 5 years. Each unique lake with nutrient or chlorophyll data also has supporting geophysical data, including climate, atmospheric deposition, land use, hydrology, and topography derived at the lake watershed (variable prefix “iws”) and HUC 4 (variable prefix “hu4”) scale. Lake-specific characteristics, such as depth and area, are also reported. The geospatial data came from LAGOS-NEGEO version 1.03. For more specific information on how LAGOS-NE was created, see Soranno et al. 2015. Soranno P.A., Bissell E.G., Cheruvelil K.S., Christel S.T., Collins S.M., Fergus C.E., Filstrup C.T., Lapierre J.-F., Lottig N.R., Oliver S.K., Scott C.E., Smith N.J., Stopyak S., Yuan S., Bremigan M.T., Downing J.A., Gries C., Henry E.N., Skaff N.K., Stanley E.H., Stow C.A., Tan P.-N., Wagner T., and Webster K.E. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse. Gigascience 4: 28. doi: 10.1186/s13742-015-0067-4.
United States LEMIS wildlife trade data curated by EcoHealth Alliance
<p>Shared here are United States Fish and Wildlife Service (USFWS) Law Enforcement Management Information System (LEMIS) data on wildlife and wildlife product imports into the United States. This data was obtained via Freedom of Information Act (FOIA) requests by EcoHealth Alliance.</p> <p>Data were curated, cleaned, and made accessible via an R package interface: <a href="https://github.com/ecohealthalliance/lemis">https://github.com/ecohealthalliance/lemis</a>.</p> <p>Additionally, a summary of a portion of the data can be found in Smith et al. 2017, <em>EcoHealth </em>(<a href="https://doi.org/10.1007/s10393-017-1211-7">https://doi.org/10.1007/s10393-017-1211-7</a>).</p> <p>l<strong>emis_2000_2014_cleaned.csv</strong>: This file represents the compiled, cleaned LEMIS data from 2000-2014. This data is identical to the version 1.1.0 dataset available through the <strong>lemis </strong>R package.</p> <p><strong>lemis_codes.csv</strong>: Full values for all coded values used in the LEMIS data. Identical to the output from the <strong>lemis </strong>R package function "lemis_codes()".</p> <p><strong>lemis_metadata.csv</strong>: Data fields and field descriptions for all variables in the LEMIS data. Identical to the output from the <strong>lemis </strong>R package function "lemis_metadata()".</p> <p><strong>raw_data.zip</strong>: This archive contains all of the raw LEMIS data files that are processed and cleaned with the code contained in the 'data-raw' subdirectory of the <strong>lemis </strong>R package repository.</p>
LAGOS-NE Shallow Lakes: a dataset of lake variables and multi-scaled ecological context variables used to predict and compare trophic status and TP:CHLa relationships between shallow and non-shallow lakes in the Upper Midwest and Northeastern United States.
We conducted a macroscale study of 2,210 shallow lakes (mean depth ≤ 3m or a maximum depth ≤ 5m) in the Upper Midwestern and Northeastern U.S. We asked: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4,360 non-shallow lakes, and do results differ by hydrologic connectivity class? To answer this question, we assembled the LAGOS-NE Shallow Lakes dataset described herein, a dataset derived from existing LAGOS-NE, LAGOS-DEPTH, and LAGOS-CLIMATE datasets. Response data variables were the median of available summer (e.g., 15 June to 15 September) values of total phosphorus (TP) and chlorophyll a (CHLa). Predictor variables were assembled at two spatial scales for incorporation into hierarchical models. At the local or lake-specific scale (including the individual lake, its inter-lake watershed [iws] or corresponding HU12 watershed), variables included those representing land use/cover, hydrology, climate, morphometry, and acid deposition. At the regional scale (e.g., HU4 watershed), variables included a smaller set of predictor variables for hydrology and land use/cover. The dataset also includes the unique identifier assigned by LAGOS-NE(lagoslakeid); the latitude and longitude of the study lakes; their maximum and mean depths along with a depth classification of Shallow or non-Shallow; connectivity class (i.e., whether a lake was classified as connected (with inlets and outlets) or unconnected (lacking inlets); and the zone id for the HU4 to which each lake belongs. Along with the database, we provide the R scripts for the hierarchical models predicting TP or CHLa (TPorCHL_predictive_model.R), and the TP—CHLa relationship (TP_CHL_CSI_Model.R) for depth and connectivity subsets of the study lakes.
Nitrogen fixation (acetylene reduction) and denitrification (acetylene block) data from streams across ecoclimatic domains in the United States, 2017-2019
We conducted a cross-ecoregion study to test the hypothesis that N-fixation and denitrification would co-occur in streams and rivers across a range of reactive N concentrations. Between 2017 and 2019, we sampled 30 streams in 13 ecoregions, using chambers to quantify N-fixation using acetylene reduction and denitrification using acetylene block. 25 of the study streams were part of the National Ecological Observatory Network or the StreamPULSE network, which provided data on water temperature, light, nutrients, discharge and metabolism. Although N-fixation and denitrification occur under contrasting environmental conditions, we found that they co-occurred in ca. 40% of stream ecosystems surveyed, and microbes capable of carrying out each process were found in all surveyed streams. This dataset includes the chamber data used to calculate nitrogen fixation and denitrification rates, stream substrate information used to scale rates from substrate to whole-reach scale, and a variety of reach-to-landscape scale covariates used to evaluate predictors of rates across the study streams.
Daily river metabolism using oxygen flux at 75 sites in Mongolia or the United States in steppe ecoregions
We obtained GIS data to indicate local geomorphology and watershed-scale values for land use, climate, slope, and elevation for each sampling site. We selected our sites using the GIS-based program RESonate (Williams et al., 2013) to represent replicates in multiple watersheds of different geomorphic patches or Functional Process Zones (FPZs). The FPZs are reoccurring longitudinal geomorphic patches that are hypothesized to control biocomplexity, including community composition and system productivity (Thorp et al., 2006). A detailed description of the FPZ delineation methodology we employed has been provided previously (Maasri et al., 2019a; Erdenee et al., 2021). We classified each study site hierarchically by country, ecoregion, river basin, upper (streams higher in the watershed) or lower (low slope rivers of lower elevations), and relatively constrained valley or wide valley. This approach allowed us to assess reach-scale properties that could directly influence the physiological controls most often collected alongside metabolism data. This provided a framework to evaluate how we may understand the determinants of metabolism at multiple scales. We studied three large-scale temperate steppe ecoregions (Terminal Basin, TB; Montane Steppe, MS; and Grassland Steppe, GS) as characterized by Olson et al. (2001) and updated by Dinerstein et al. (2017) in two countries (Mongolia and the United States, Fig. 2). We aggregated our large-scale ecoregions for the US as follows: TB = Great Basin shrub steppe and Sierra Nevada forest, MS = South Central Rockies forest and Wyoming Basin shrub steppe, GS = Nebraska Sand Hills mixed grasslands and Northern Shortgrass prairie. We aggregated our large-scale ecoregions for Mongolia as follows: TB = Altai mountains forest and forest steppe, Gobi Lakes Valley desert steppe, Great Lakes Basin desert steppe, and Khangai Mountains alpine meadows, MS = Selenge-Orkhon forest steppe and Syan Mountains conifer forests, GS = Daurian Forest s
High-Frequency and Water Quality Monitoring Data of Long Pond at Grafton Lakes State Park, New York, United States, 2024
This collection of datasets contains high frequency data captured through Hobo, Minidot, and water level sensors, as well as data collected from manual sampling days. Long Pond is located in Grafton New York, USA named for its long shape and shallower depth (max depth is around 8 meters). Using a buoy, sensors were attached to a rope at the deepest point discoverable and deployed. Data covers all information recorded from 2024-04-30 to 2024-10-09. Times are recorded in Eastern Standard Time. Temperature Readings were taken every 10 minutes at 1 meter intervals by both Minidots and hobo sensors (1.52-7.52 m). Dissolved Oxygen was similarly collected every 10 minutes by the Minidots at depths 1.52, 6.52, and 7.52 meters. Manual measurements (YSI and Secchi disk) were recorded on sampling days, as well as water samples that were assessed for water quality parameters from the top and bottom of the lake. Water level data was also collected in 12 hour intervals.
NEON Provisional Continuous and Field Discharge - Water Year 2024 (2023-10-01 - 2024-09-30), United States
As of the date of this publication in EDI, NEON publishes one-minute continuous discharge data that have been corrected and gap-filled in the Continuous Discharge (DP4.00130.001, https://data.neonscience.org/data-products/DP4.00130.001) data product. As part of a recent manuscript describing the data quality improvements to NEON's continuous discharge data brought on my implementation of corrections and gap-filling, a mixture of released and provisional NEON data were downloaded. To ensure the reproducibility of the data set used to conduct the analysis presented in the manuscript, the downloaded provisional data, which is subject to change, is saved as a static data set in this EDI publication. The same is done for the Discharge Field Collection (DP1.20048.001, https://data.neonscience.org/data-products/DP1.20048.001) data product, which is used in the same analysis.
Oyster Paleobiology along the South Atlantic Coast of the United States
This dataset includes morphometric data collected from 37,805 oyster shells (Crassostrea virginica) from 15 Late Archaic (ca. 4500-3500 cal. BP) through Mississippian (ca. 1150 – 370 cal. BP) period archaeological sites situated along the South Atlantic Coast of the United States. Variations in oyster size is an important proxy for paleoenvironment and human population pressures. These data are part of a larger project examining oyster ecosystem stability and Native American oyster harvesting practices over the last 5,000 years. Oyster measurements were collected by many undergraduate and graduate students from multiple universities. Carey Garland added to and cleaned the data sheet between August 2018 and May 2019. The dataset was structured to include the Island, site name, time period, and provenience (e.g., unit, level, etc.) associated with each oyster measured. The original oyster database contains sensitive information, such as the specific location of archaeological sites. If a professional archaeologist needs site location information, they can contact the Georgia Archaeological Site File.
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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.