Find research datasets worth reusing

openCC (other)Dec 2022View details →

WSC 2006: Spatial interactions among ecosystem services in the Yahara Watershed

Understanding spatial distributions, synergies and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are win win exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3 percent of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services. Documentation: Refer to the supporting information of the follwing paper for full details on data sources, methods and accuracy assessment: Qiu, Jiangxiao, and Monica G. Turner. "Spatial interactions among ecosystem services in an urbanizing agricultural watershed." Proceedings of the National Academy

openCC (other)Dec 2022View details →

Spatial variability in water chemistry of four Wisconsin aquatic ecosystems - High speed limnology Environmental Science and Technology datasets

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. We developed a new sensor platform to continuously samples surface water at a range of speeds (0 to > 45 km hr-1) resulting in high-density, meso-scale spatial data. Here, we archive data associated with an Environmental Science and Technology publication. Data include a single spatial survey of the following aquatic ecosystems: Lake Mendota, Allequash Creek, Pool 8 of the Upper Mississippi River, and Trout Bog. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected).

openCC (other)Oct 2023View details →

Bee species abundance and composition in three ecosystem types at the Sevilleta National Wildlife Refuge, New Mexico, USA

This study was designed to examine community- or population-level fluctuations in bee species at the Sevilleta National Wildlife Refuge, both intra- and inter-annually. From 2002 to 2019, passive funnel traps were used to collect bees at three sites, each representing a different ecosystem type of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland). Bees were collected during each month from March through October, and were identified to species by taxonomic experts.

openCustomMay 2022View details →

Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2008 data.

This dataset consists of participant responses in one of two economic experiments conducted on Virginia's Eastern Shore during 2008 and 2009 by Elizabeth C. Smith used to gauge resident preferences and willingness-to-pay for ecosystem restoration activities. This dataset was designed to be used to examine a practical method to implement an individualized pricing approach to public good provision, grounded in Lindahl's marginal benefit theory. The study's focus was on ecosystem valuation and market approaches that have potential to provide public goods, examining the potential to generate revenues for public goods from consumers. While willingness-to-pay measurement techniques have been used to assess preferences for many environmental goods, this research goes a step further to explore real money auctions that generate revenues sufficient to pay for restoration activities. The data from the field experiments conducted in coastal Virginia were used, along with laboratory experiment data, to evaluate the performance of auction mechanisms in generating revenues relative to potential (Hicksian) willingness to pay for marginal increments in public goods. The field execution of this experiment involved residents of Virginia's Eastern Shore and local public goods. This application involved half-acre increments of ecosystem restoration for sea grass habitat in coastal lagoons, plantings for migratory bird habitat, and, in some auctions, clam-based increments of water quality services, defined as delaying the harvest of clams for six months beyond normal harvest by an existing aquaculture firm. To perform these tasks, participants were provided a budget, between $90 and $150. The auctioneer described for participants the ecosystem services that may result from additional ecosystem restoration associated with each activity. The actual levels of ecosystem restoration provided were based on aggregate offers reaching a pre-determined (but unknown to the participants) provision p

openCustomMay 2022View details →

Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2009 data.

opencc-by-4.0Oct 2023View details →

Indicative distribution map for Ecosystem Functional Group MT2.2 Large seabird and pinniped colonies

This archive contains indicative distribution maps and profiles for MT2.2 Large seabird and pinniped colonies, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022) for details. 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).

opencc-by-4.0Nov 2023View details →

Indicative distribution map for Ecosystem Functional Group F2.10 Subglacial lakes

This archive contains indicative distribution maps and profiles for F2.10 Subglacial lakes, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022) for details. 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).

opencc-by-4.0Oct 2024View details →

Invasion Biology WikiProject Scientific Papers: Text Data Mining and LLM-based Information Extraction of Species, Locations, Habitats, and Ecosystems

This dataset contains the abstract and full-text for publication DOIs from the Invasion Biology WikiProject (DOI: <a href="https://www.doi.org/10.5281/zenodo.12518036">10.5281/zenodo.12518036</a>). The data was retrieved using the <a href="https://ask.orkg.org/">ask.orkg.org</a> <a href="https://api.ask.orkg.org/docs#tag/Semantic-Neural-Search/operation/explore_documents_index_explore_get">API</a>. For the <a href="https://github.com/jd-coderepos/invasion-biology-IE/blob/main/scripts/ask-doi-list-fulltext-search.py">script</a> used to obtain the data, refer to the accompanying GitHub repository: <a href="https://github.com/jd-coderepos/invasion-biology-IE/" target="_blank" rel="noopener">https://github.com/jd-coderepos/invasion-biology-IE/</a>. The resulting CSV file includes the following fields: <code>"ASK ID"</code>, <code>"DOI"</code>, <code>"Title"</code>, <code>"Abstract"</code>, and <code>"Full-text"</code>. Of the 49,438 queried DOIs, the ASK database provided: <ul> <li>Total DOIs processed: 12,636</li> <li>DOIs with neither abstract nor full-text: 36 (abstract token count was less than 10)</li> <li>DOIs with abstracts but no full-text: 12,636</li> <li>DOIs with both abstract and full-text: 2,834</li> </ul> The second part of the dataset contains structured information extracted from the publications using the GPT-4o Large Language Model. This structured data is included in the zipped folder <code>structured-publications.zip</code>. The accompanying GitHub repository provides access to the code and scripts used at various stages of the information extraction (IE) process. Theme of the Study: "Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Models."

opencc-by-4.0Apr 2024View details →

Reservoir ecosystems support large pools of fish biomass

Supplemental data for "Reservoir ecosystems support large pools of fish biomass". Parisek, C.A., F.A., De Castro, J.D. Colby, G.R. Leidy, S. Sadro, A.L. Rypel. Reservoir ecosystems support large pools of fish biomass. Sci Rep 14, 9428 (2024). https://doi.org/10.1038/s41598-024-59730-z

opencc-by-4.0Jul 2024View details →

Antarctic Ecosystem Inventory: Spatial data for Ice-free lands v1.0

This is Antarctica’s first comprehensive ecosystem map of ice-free lands. The data comprise a spatially explicit 3-tiered hierarchical ecosystem classification with nine Major Environment Types (tier 1), 33 Habitat Complexes (tier 2) and 269 Bioregional Ecosystem Types (tier 3). These Bioregional Ecosystem Types are aligned with ‘level 4’ of the IUCN Global Ecosystem Typology (Keith et al. 2022).  The spatial data are available in raster format (TIF) at 100 m resolution in the Polar Stereographic Projected Coordinate System (GCS_WGS_1984) for all known ice-free areas south from latitude -57.330551 decimal degrees South (pdf map shows extent of ice-free areas in relation to terrestrial ice and ice shelves). A value attribute table (VAT) provides text fields containing codes and full names for each unit in each level of the classification hierarchy and the spatial extent of tier 3 units in hectares. Methods of development, source data and uses of the inventory are detailed by Tóth et al. (2025a). Descriptive profiles for tier 1 and 2 units are available in Tóth et al. (2025b). References Keith, D.A., Ferrer-Paris, J.R., Nicholson, E., Bishop, M.J., Polidoro, B.A., Ramirez-Llodra, E., Tozer, M.G., Nel, J.L., Nally, R. Mac, Gregr, E.J., Watermeyer, K.E., Essl, F., Faber-Langendoen, D., Franklin, J., Lehmann, C.E.R., Etter, A., Roux, D.J., Stark, J.S., Rowland, J.A., Brummitt, N.A., Fernandez-Arcaya, U.C., Suthers, I.M., Wiser, S.K., Donohue, I., Jackson, L.J., Pennington, R.T., Iliffe, T.M., Gerovasileiou, V., Giller, P., Robson, B.J., Pettorelli, N., Andrade, A., Lindgaard, A., Tahvanainen, T., Terauds, A., Chadwick, M.A., Murray, N.J., Moat, J., Pliscoff, P., Zager, I. & Kingsford, R.T. (2022) A function-based typology for Earth’s ecosystems. Nature 610, 513–518. [doi: 10.1038/s41586-022-05318-4]. Tóth, A.B., Terauds, A., Chown, S.L., Hughes, K.A., Convey, P., Hodgson, D.A., Cowan, D.A., Gibson, J., Leihy, R.I., Murray, N.J., Robinson, S.A., Shaw, J.D., Stark, J.S., Stevens, M.I., van den Hoff, J., Wasley, J. and Keith D.A. (2025a). A dataset of Antarctic ecosystems in ice-free lands: classification, descriptions, and maps. Scientific Data 12, 133. [https://doi.org/10.1038/s41597-025-04424-y]  Tóth, A.B., Terauds, A., Chown, S.L., Hughes, K.A., Convey, P., Hodgson, D.A., Cowan, D.A., Gibson, J., Leihy, R.I., Murray, N.J., Robinson, S.A., Shaw, J.D., Stark, J.S., Stevens, M.I., van den Hoff, J., Wasley, J. & Keith D.A. (2025b). Antarctic Ecosystem Inventory: Descriptive profiles for ice-free lands v1.0. DOI: 110.5281/zenodo.14625890. Australian Antarctic Data Centre.

opencc-by-4.0Oct 2023View details →

Indicative distribution map for Ecosystem Functional Group M1.10 Rhodolith/Maërl beds

This archive contains indicative distribution maps and profiles for M1.10 Rhodolith/Maërl beds, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022) for details. 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).

opencc-by-4.0Jul 2018View details →

Majadas de Tietar: Ecosystem level and understorey carbon, water, and energy fluxes in a Mediterranean tree-grass ecosystem

This dataset contains a subset of measurements collected at the experimental site Majadas de Tietar. We collected ecosystem level and understorey carbon, water, and energy fluxes in a Mediterranean Savanna using the eddy covariance technique and a series of meteorological sensors for the time period December 2015 - February 2018. The dataset is used for the development of a series of R packages including 'bigleaf' (Knauer et al., 2018). The experimental site is collected in Majadas de Tietar (Casals et al., 2009) located in western Spain (39°56′25″N 5°46′29″W). The ecosystem is a typical “Iberic Dehesa”, which is characterized by an herbaceous stratum of native pasture and sparse trees, for the majority (~98%) Quercus ilex. The tree density is about 20–25 trees/ha⁠, the fractional cover of trees is about 20%, mean DBH of 46 cm, and a canopy height of about 8 m. (El-Madany et al., 2018). The herbaceous layer is composed of native annual species of the three main functional plant forms (grasses, forbs and legumes), whose fractional cover varies seasonally and is characterized by important inter-annual variations in the seasonal dynamics related to the onset of the dry period. Fluxes were measured with the eddy covariance technique with two different systems, one at ecosystem scale to characterize the fluxes of the whole ecosystem (15.5 m above ground), and one at 1.65 m above ground in an open space to measure the fluxes of the well-established understory grass layer. The description of the set-up, equipment and processing used to calculate ecosystem scale fluxes are described in El-Madany et al., (2018), while for the understory tower can be found in Perez-Priego et al., (2017). The dataset is composed of two files: 'ESLMa_MainTower', which is the ecosystem eddy covariance system, and 'ESLMa_SubCanopy', which is the understory eddy covariance system. The dataset contains half-hourly, processed eddy covariance of the ecosystem and understory tower, as well as the main biometeorological data used in the big-leaf package (net radiation, soil heat fluxes, horizontal wind velocity, atmospheric pressure, precipitation, air temperature). All the processing was conducted with EddyPro software (version 5.2.0, LI-COR Biosciences Inc., Lincoln, NE, USA) and the ustar filtering, gap-filling and partitioning with the R package REddyProc (Wutzler et al., 2018). The variables and the units are described in the Readme.txt file released with the dataset. References Casals, P. et al., 2009. Soil CO2 efflux and extractable organic carbon fractions under simulated precipitation events in a Mediterranean Dehesa. Soil Biol. Biochem. 41, 1915–1922. <a href="https://doi.org/10.1016/j.soilbio.2009.06.015">https://doi.org/10.1016/j.soilbio.2009.06.015</a>. El-Madany, T.S.,et al., 2018. Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem 21. <a href="https://doi.org/10.1016/j.agrformet.2018.07.010">https://doi.org/10.1016/j.agrformet.2018.07.010</a> Knauer, J., et al., 2018. bigleaf - An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data. PLOS ONE, doi:10.1371/journal.pone.0201114 Perez-Priego O,  et al., 2017. Evaluation of eddy covariance latent heat fluxes with independent lysimeter and sapflow estimates in a Mediterranean savannah ecosystem. Agricultural and Forest Meteorology. 236: 87-99. doi: 10.1016/j.agrformet.2017.01.009. Wutzler, T., et al., 2018. Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences Discuss., p. 1-39.

opencc-by-4.0Mar 2023View details →

Data from: Coastal upwelling drives ecosystem temporal variability from the surface to the abyssal seafloor.

Abstract Long-term biological time series that monitor ecosystems across the ocean’s full water column are extremely rare. As a result, classic paradigms have yet to be tested. One such paradigm is that variations in coastal upwelling drive changes in marine ecosystems throughout the water column. We examine this hypothesis by using data from three multi-decadal time series spanning surface (0 m), midwater (200-1000 m), and benthic (~ 4000 m) habitats in the central California Current Upwelling System. Data include microscopic counts of surface plankton, video quantification of midwater animals, and imaging of benthic seafloor invertebrates. Taxon-specific plankton biomass and midwater and benthic animal densities were separately analyzed with principal component analysis. Within each community, the first mode of variability corresponds to most taxa increasing and decreasing over time, capturing seasonal surface blooms and lower-frequency midwater and benthic variability. When compared to local wind-driven upwelling variability, each community correlates to changes in upwelling damped over distinct timescales. This suggests that periods of high upwelling favor increases in organism biomass or density from the surface ocean through the midwater down to the abyssal seafloor. These connections most likely occur directly via changes in primary production and vertical carbon flux, and to a lesser extent indirectly via other oceanic changes. The timescales over which species respond to upwelling are taxon-specific and are likely linked to the longevity of phytoplankton blooms (surface) and of animal life (midwater and benthos), that dictate how long upwelling-driven changes persist within each community.   Data set description This data set includes 3 files, one for each community. The files contain plankton biomass (for the surface community) or animal density (for midwater and benthos communities) as a function of sampling time and taxonomic group.  <ul> <li>surface.csv: autotrophic and heterotrophic surface plankton sampled in Monterey Bay by CTD-rosette and analyzed by epifluorescence microscopy and flow cytometry</li> <li>midwater.csv: midwater animals observed by ROV in the Monterey Bay mesopelagic zone from 200-1000m</li> <li>benthos.csv: benthic animals observed by ROV in a ~ 4000 m abyssal seafloor habitat at the base of the Monterey deep-sea fan</li> </ul> Detailed description (see additional details and references in <a href="https://www.pnas.org/doi/10.1073/pnas.2214567120">Messié et al., 2023</a>): Surface time series: Plankton biomass was estimated from surface plankton counts collected using ship-based CTD-rosette at station M1 in Monterey Bay (122.022°W, 36.747°N). This station is part of a 3-station time series program operating in Monterey Bay since 1989 at 3-4 week intervals. Epifluorescence microscopy was used to enumerate and size auto- and heterotrophic plankton. Starting in 1998, flow cytometry samples provided more precise numbers for Synechococcus and eukaryotic picoplankton (Prochlorococcus was not included as no information is available prior to 1998). Standard geometric equations (e.g., ellipsoid, sphere, cylinder, pennate diatom shape) were used to calculate biovolumes of individual cells, and biomass of each plankton group was assessed using biovolume-based carbon conversions. For picoplankton an average value per cell was used: 82 fgC cell-1 for Synechococcus and 530 fgC cell-1 for eukaryotic picophytoplankton (red fluorescing picoplankton). Diatom biovolumes were converted to biomass using log10(Biomass) = 0.76 log10(Volume) - 0.29 where Biomass is in gC and Volume is in 𝜇m3. The ciliate conversion was Biomass = 0.08 * Volume. For all other plankton we used log10(Biomass) = 0.94 log10(Volume) - 0.6. Midwater time series: Quantitative mesopelagic video transects were conducted at a single station in Monterey Bay (Midwater 1, 36°42′N, 122°02′W). The station is located over the axis of the Monterey Submarine Canyon, where the water column is approximately 1600 m deep. Data were collected using remotely operated vehicles (ROVs). Estimates of animal densities using ROV imaging underestimate some groups (notably fishes), but provide a more complete view of life in the ocean than traditional methods such as nets and acoustics, particularly for gelatinous animals. The ROVs conducted horizontal video transects while moving at about 0.5 m s-1 for 10 min. Data for this paper come from approximately monthly transects made at 100 m intervals between 200 - 1000 m from 1997-2017. These years were chosen because the entire mesopelagic water column was more evenly surveyed than in the years prior. In each transect, the community of animals was annotated by professional annotators using the open-source Video Annotation and Referencing System (VARS) software. Annotators identified organisms in transect video to the lowest taxon possible; in many cases to species. We selected 63 taxonomic groups defined at the highest possible taxonomic resolution; annotations not included represent 31% of the total (84% of which are euphausiids, chaetognaths, and unidentified appendicularians). Calibrated cameras on MBARI ROVs and accurate measurement of ROV speed through water, allow for the calculation of volume for each transect. Animal density was calculated for each taxonomic group and each depth-specific transect as the number of individuals divided by the corresponding transect volume, further averaged over the water column from 200 - 1000 m. Midwater transecting methods and their efficacy are well-documented. Benthic time series: Two comparable methods were used to assess benthic communities at Station M (34°50′N, 123°00′W). From 1989-2005, the identification to the lowest possible taxon, and quantity of benthic animals were recorded from images taken by a camera-sled towed along a horizontal transect above the sea floor at a speed of approximately 1 m s-1, taking a film image every 4-5 seconds (water depth ~ 4,100 m). The developed film was projected by a Beseler model 23C-II enlarger for annotation of identifiable animals in images. From 2006-2018, benthic communities were assessed using ROV video transects recorded from approximately 1.3 m above the sea floor, with a view of approximately 1 m wide, and length typically approximately 1 km. Water depth for these transects was approximately 4,000 m, the lower depth limit of the ROV. Animals visible in the video were identified and annotated using VARS. The 2006 change in sampling method and in time series location and depth was found to have little impact on the megafauna time series.

opencc-by-4.0Jul 2023View details →

Technical Leverage Analysis in the Python Ecosystem

Technical Leverage Analysis in the Python Ecosystem This dataset is the original dataset used in the publication [1]. It includes 21205 distinct package versions from the top 600 Python packages.  An online demo for computing the proposed metrics for real-world software libraries is also available under the following URL: https://techleverage.eu/. This work has been partially funded by the EU under the H2020 Program AssureMOSS (Grant n. 952647).  [1] DOI: 10.1007/s10664-023-10355-2

openCC0Jan 2023View details →

Photosynthetic quotients in aquatic ecosystems: data and code supporting Trentman et al. 2023 manuscript in L&O Letters

This study provides a summary of the mismatch between our current knowledge and the application of the photosynthetic quotient (PQ). We use data from the Upper Clark Fork River (UCFR) as a case study example of how the PQ may vary in space and time based on environmental conditions. Surface water sample measurements of dissolved oxygen (DO), temperature (T), nutrients (NO3-N, NH4-N, SRP), and several metabolism indicators are represented in this data product. Figures represent data from two sites on the mainstem of the Upper Clark Fork River (UCFR) over a roughly two-year period, from 2019 to 2021. Some measurements are derived from existing data products or manuscripts, including DOT (Valett, et al., 2023); nutrients (H. M. Valett, Dec. 2, 2022, pers. comm); air pressure (Deer Lodge Weather Station, 2023); underlying data for Trentman et al. (2023) Figure 2 and Figure 4e and 4f (via Burris, 1981); and SI-Figure2 USGS gage data (USGS, 2023). Products unique to this data product include metabolism data (Trentman, et al., 2023 (Figure 5)), chamber data supporting Trentman, et al., (2023) Figure 6, and code simulations/data. All analytes and variables are documented in the project data dictionary. For details on data collection methods, see the methods section, the manuscript, and/or referenced data products.

openCC (other)May 2023View details →

Ecosystem metabolism and associated environmental data for a forested, meadow and reforested reach of White Clay Creek, Chester Co., Pennsylvania; 1971-1975 and 1997-2010

Ecosystem metabolism data for a 3rd-order Piedmont stream were collected during two periods: P1- April 1971 – Dec 1975, and P2- May 1997 – January 2010. Measures were made in a meadow and a forested reach during each period and in a reforested (formerly meadow) reach during the latter years of P2. During P1, measures were made by transferring streambed substrata to chambers in water jackets located on the streambank and measuring dissolved oxygen changes over diel periods. During P2, open system measures of dissolved O2 change were made for several days in warm and cold seasons, with reaeration determined from a propane injection experiment. Metabolism estimates were determined from diel curves of dissolved O2 change. Photosynthetically active radiation (PAR) and chlorophyll were measured concurrent with many measurements in P1 and all measures during P2, and temperature with all measures. Water chemistry parameters (NH4-N, NO3-N, PO4-P, SiO2, Cl, SO4, total alkalinity, pH) associated with each run are included in the data set, as are days since storm of various thresholds. Field procedures, analytical methods and data analyses are detailed in Bott, T.L. & J. D. Newbold, 2023. A multi-year analysis of factors affecting ecosystem metabolism in forested and meadow reaches of a Piedmont Stream. Hydrobiologia

openCC (other)Dec 2024View details →

Rates and controls of nitrogen fixation in post-fire lodgepole pine forests, Greater Yellowstone Ecosystem, 2022

This dataset contains all the contents needed to reproduce the calculations and analyses done in the original paper associated with this dataset (Heumann et al. 2025 Ecology). The primary method used in this study was the Acetylene Reduction Assay (ARA) which measures the rate at which acetylene is reduced to ethylene in nitrogen-fixing organisms as a proxy for nitrogen fixation activity. We measured acetylene reduction rates in multiple cryptic niches (i.e., lichen, moss, pine litter, dead wood and mineral soil) in 34-year-old lodgepole pine stands in the Greater Yellowstone Ecosystem to explore the rates, temporal patterns, and climate controls on cryptic N fixation. Thus the foundation of this dataset is ethylene production rate measurements. All the data tables in this dataset contain either measured ethylene production rates or estimates of N fixation scaled from those ethylene production rates. Included with this are various physical measurements (e.g. dry mass, moisture content, incubation temperatures) that we included in our analyses in order to either scale up rates of N fixation using biomass estimates from field sites or explore temperature and moisture relationships with nitrogen fixation activity under controlled conditions. Included with this dataset are three R studio scripts used to run the calculations and analyses reported in the manuscript publication from this study.

openCC (other)Jan 2025View details →

Microclimate temperature effects propagate across scales in forest ecosystems, Berchtesgaden National Park, Bavaria, Germany

Context: Forest canopies shape subcanopy environments, affecting biodiversity and ecosystem processes. Empirical forest microclimate studies are often restricted to local scales and short-term effects, but forest dynamics unfold at landscape scales and over long time periods. Objectives: We developed the first explicit and dynamic implementation of microclimate temperature buffering in a forest landscape model and investigated effects on simulated forest dynamics and outcomes. Methods: We adapted the individual-based forest landscape and disturbance model iLand to use microclimate temperature for three processes [decomposition, bark beetle (Ips typographus L.) development, and tree seedling establishment]. We simulated forest dynamics with or without microclimate temperature buffering in a temperate European mountain landscape under historical climate and disturbance conditions.

openCC (other)Jan 2025View details →

CO2 Flux and Temperature Data for Estimating Thermal Acclimation in Ecosystem Respiration

We have compiled an extensive dataset of long-term, hourly CO2 flux measurements from 93 global eddy covariance sites to estimate the thermal response strength in nighttime ecosystem respiration. Flux data was sourced from AmeriFlux (https://ameriflux.lbl.gov/), FluxNet (https://fluxnet.org/), and ICOS (https://www.icos-cp.eu/). The processed data product encompasses five categories. (1) Long-term, directly measured, Ustar-filtered, hourly or subhourly nighttime ecosystem respiration, along with corresponding air temperature, soil temperature, and soil water content at the 93 sites. (2) Long-term gap-filled data, including hourly or subhourly net ecosystem exchange, air temperature, and soil temperature at these sites. (3) Annual topsoil (< 0.1 m) temperature and nighttime ecosystem respiration curves during the growing season, designed for calculating thermal response strength. (4) Estimated thermal response strength across these sites, detailed with geographic, climatic, soil, and vegetation conditions for each site. (5) An R script to calculate thermal response strength using the data product (3).