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13,618 results for “biology”
Species diversity and plant dominance influence grassland stability in response to extreme climatic events and anthropogenic drivers across three LTER sites: Cedar Creek, Konza Prairie, and Kellogg Biological Station, 1982-2023.
The data in this package is associated with the analysis for a manuscript titled "Multiple community properties drive ecosystem resistance and resilience to extreme climate events across mesic grasslands". The files include compiled data on plant biomass production, species abundance, experimental treatments, extreme climate event values, and calculated diversity and stability measures from grassland plots in experiments at CDR, KBS, and KNZ LTER sites.
Physical soil characteristics, microbial community composition, extracellular enzymatic activity, biologically based phosphorus (BBP) pools, and available phosphorus from two soil depths, four microhabitats, and four landforms at the Jornada Experimental Range, 2021.
This dataset contains physical soil characteristics, PLFA based microbial community composition, extracellular enzymatic activity, nitrate and ammonium activity, and phosphorus availability in various phosphorus pools (Biologically Based Phosphorus, potassium sulfate, Olsen-P). Soils were collected from two depths (0-2cm, 2-30 cm), four microhabitats (grass, shrub, biocrust, interspace), and four landforms (alluvial flat, alluvial fan remnant, erosional scarplet, fan piedmont – see coordinates) within the Jornada Experimental Range in July 2021 to answer questions about how these variables change across these spatial scales in drylands. This project was a collaboration between researchers at New Mexico State University and The University of Texas at El Paso as part of the Drylands Critical Zone Thematic Cluster within the Critical Zone Network. This dataset is complete.
Managing Crop Yield Risk at the Kellogg Biological Station, Hickory Corners, MI (2022 to 2023)
Dataset Abstract As farmers adapt to changing climate, they modify practices and technologies to manage evolving risk. Adaptive changes may be as small as adjusting a crop insurance coverage level or as large as investing in an irrigation system. Farmer attitudes toward risk and their subjective perceptions of the evolving probability distributions of crop yields drive adaptation decisions. To understand climate change adaptation behavior by farmers, we undertook the study “Elicitation and Estimation of Risk Preference and Subjective Probabilities to Understand Farmer Decisions on Climate Change Adaptation.” We interviewed 44 Michigan corn and soybean farmers to elicit mathematical expressions of their risk attitudes. During the interviews, each completed two sets of lottery choices, the first using 25 general risky gambles and the second using 18 risky gambles in a crop farming context that enable econometric estimation of risk attitudes (using variants of Expected Utility Theory). Next, they answered questions about corn yield probability distributions over the past ten years and the next ten years (triangular distributions of minimum, most likely, and maximum values) with no water management, irrigation, tile drainage, and drought-resistant seed. After that, they reported on water management investments that they have made in past and intend to make in future. Finally, they provided background information about themselves and their farms. This study (MSU Study ID: STUDY00007871) was submitted to the Michigan State University Institutional Review Board (IRB) by principal investigator Scott Swinton. On July 5, 2022, it was determined to be exempt under 45 CFR 46.104(d) 3(i)(B). Data collection took place during September 2022 through March 2023. Farmer respondents completed the survey instrument on Qualtrics with assistance from graduate students in Agricultural, Food, and Resource Economics at Michigan State University at various MSU Extension offices and restaura
GLBRC Aboveground Plant Biomass at the Kellogg Biological Station, Hickory Corners MI (2008 to 2023), and the Arlington Research Station,Arlington, WI (2008 to 2014)
Dataset Abstract Aboveground biomass of BCSE herbaceous perennial crop treatments (G4 starting in 2021, G5-G7, G9-G10). Peak biomass samples were sorted to species from 2009-2017 but are left “unsorted” from 2018 onward. original data source http://lter.kbs.msu.edu/datasets/82
Data from the Forest Resilience Threshold Experiment, University of Michigan Biological Station, 2024
During the 2024 field season, data collection efforts led by the FoRTE crew centered on understanding forest ecosystem dynamics and carbon cycling processes in a temperate forest landscape. Comprehensive datasets were gathered to evaluate structural and functional responses across multiple forest strata. Measurements included diameter at breast height (DBH) for canopy, subcanopy, and seedling layers, alongside a detailed subcanopy census to assess understory composition and diversity. Soil respiration (Rs) was monitored to quantify carbon fluxes, while fern density and distribution were documented to explore their role in forest microclimates and nutrient cycling. Photosynthetically active radiation (PAR) readings provided insights into light availability and its impact on primary production. Advanced remote sensing tools, including LiDAR and normalized difference vegetation index (NDVI), were employed to characterize canopy structure, vegetation health, and spatial heterogeneity. These diverse datasets collectively contribute to a robust framework for analyzing forest resilience, recovery, and carbon sequestration potential following disturbance, advancing our understanding of ecosystem processes in the face of environmental change.
Greenhouse gas partial pressure (CO2, CH4, N2O) and environmental variables (physical, chemical, and biological) measured in urban ponds of Barcelona during summer and winter (2023-2024)
This dataset provides information on the partial pressure of greenhouse gases (CO₂, CH₄, and N₂O) measured in 41 artificial urban ponds—28 naturalized and 13 non-naturalized—using the headspace technique. Additionally, GPS coordinates, as well as physical, chemical, and biological variables for each pond, are included. Data were collected during the summer and winter seasons, during daytime. Furthermore, a subset of 16 ponds (8 naturalized and 8 non-naturalized) was also sampled at night in both seasons. All samples were taken from the water surface.
Landscape of fear and safety summer 2025 data from University of Michigan Biological Station stream research facilities
Predator prey interactions are often driven by sensory cues and these cues play a role in non-consumptive effects. We are interested in the role that chemical cues (from predators) play in resource use by one of fish common prey, crayfish. We created flow through mesocosms and populated them with crayfish and various configurations of shelters and food. Then we presented to the crayfish predator cues (from large mouth bass) and measured behavioral responses from midnight to 4 am.
Non-Targeted Screening of Organic Compounds in Environmental and Biological Matrices Related to Children's Environmental Exposure in South Florida, 2022-2024
This dataset provides a comprehensive list of chemicals relevant to children’s exposure from both dietary and non-dietary sources, across five environmental and biological matrices: drinking water (n = 206), food (n = 203), urine (n = 183), soil (n = 178), and household dust (n = 164). Samples were collected between May 2022 and June 2024 in Miami-Dade and Broward counties, Florida. A non-targeted screening approach using high-resolution mass spectrometry (HRMS) coupled with liquid chromatography was employed for analysis, with matrix-specific preparation methods: online solid-phase extraction (SPE) for water and urine, QuEChERS for food, and accelerated solvent extraction (ASE) for soil and dust. Analyses were conducted in full-scan mode under both positive and negative electrospray ionization to maximize compound detection coverage. Compound identification was performed using Compound Discoverer software, incorporating spectral and structural databases such as mzCloud, ChemSpider, ClassyFire, and MassList. Annotations were based on exact mass, mass error threshold (<5ppm), predicted molecular formula, retention time alignment, isotopic pattern fit, MS/MS spectral similarity, and match confidence levels derived from integrated spectral libraries and database scoring algorithms. Quality assurance was maintained through the use of quality control (QC) samples across all matrices and analytical batches. The integration of non-targeted analysis, matrix-optimized extraction, and rigorous QA/QC practices makes this dataset a valuable resource for environmental exposomics, chemical risk assessment, and evidence-based public health policy development.
Forest tree, woody debris, root ingrowth, soil respiration and characterization data from long-term research plots for LTREB at the University of Michigan Biological Station
The NSF-funded project "LTREB: Drivers of temperate forest carbon storage from canopy closure through successional time" (2014-2024) supports research to meet the following goals: 1) elucidate mechanisms responsible for changes in C storage over decades to centuries; 2) link processes leading to persistence and resilience of forest C storage following disturbance; 3) quantify the effects of potential drivers such as forest structure, N availability, climate change, and atmospheric deposition on decadal and longer-term trajectories of C storage. Field activities for this research are conducted at the University of Michigan Biological Station (UMBS) on a pair of chronosequences and several old reference forests. Synthesis activities utilize data collected from these field sites in support of the LTREB project, as well as data synthesized from other sources (e.g., long-term UMBS plot data, AmeriFlux data, FIA data) all intended to address the core questions of the LTREB project. This dataset has been compiled and expanded over a series of versions, with new data types and observations appended periodically. Presently, the dataset includes observations from tree inventory censuses, woody debris sampling, fine root ingrowth cores, soil respiration measurements, and two sets of soil collections aimed at quantifying a range of physical, chemical, and biological properties of soil.
Hubbard Brook Experimental Forest: Stream Biology Camera Traps, 2020-2024
This dataset comprises daily images positioned to view streams above the weirs at Hubbard Brook for watersheds 1, 2, 3, 4, 5, 6, and 9. Cameras are programmed to take one image per day at ~12:00 pm ET. Each file is timestamped with the image metadata, but also within the file name, and structured to enable temporal trend analysis for end-users. The cameras used are BUSHNELL model number 119R3, and data are collected on SIM cards and manually downloaded every six months. Data gaps are minimal and generally associated with battery failures. These data are designed to capture stream dynamics over time for the purpose of visual pattern analysis, environmental monitoring, and machine learning applications. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
MCR LTER: Coral Reef: Dead coral skeletons impair key recovery processes following coral bleaching; data for Kopecky et al., 2024 Global Change Biology
The data included in this data package were collected on the North shore of Moorea, French Polynesia, from 2015-2023 to explore how dead coral skeletons (e.g,, left after coral bleaching events) influence critical processes tied to coral reef resilience. Together, these various datasets were used for analyses in the manuscript entitled "Changing disturbance regimes, material legacies, and stabilizing feedbacks: dead coral skeletons impair key recovery processes following coral bleaching", published in Global Change Biology. These data are in support of a publication Kopecky et al. (2024) Global Change Biology, and were a part of the thesis of K. Kopecky. The manuscript title and author list are as follows: Changing disturbance regimes, material legacies, and stabilizing feedbacks: dead coral skeletons impair key recovery processes following coral bleaching. Kai Kopecky, Russell J. Schmitt, Sally J. Holbrook. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 22-24354 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2024). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Long Term Mammal Data from Powdermill Biological Station 1979-1999
This is a 20-year record of small mammal trapping from the Powdermill Biological Station, Rector, PA 15677 collected by Joseph F. Merritt. It is included here as a comparative source of small mammal data.
The local extinction of Cedrus atlantica in the Iberian Peninsula could have been completed due to biological interaction
<p>This data set is used to explore the possibility that <em>Cedrus atlantica</em> (Endl.) Carrière and <em>Pinus nigra</em> Arnold could have interacted in the past, mutually excluding each other in the areas with suitable conditions for both species and, where, ultimately, the one that was most competitive would remain. The species show very well differenciated niches and a distribution of their habitats segregated by continents (<em>P. nigra</em> in Europe and <em>C. atlantica</em> in Africa), which responds to differences in climatic affinities. However, the contact of their distributions in bordering areas suggests that <em>C. atlantica</em> maintained its presence in the Iberian Peninsula until recent times, and that <em>P. nigra</em> could have displaced it due to its higher prevalence on the continent.</p>
Invasion Biology WikiProject Scientific Papers: Text Data Mining and LLM-based Information Extraction of Species, Locations, Habitats, and Ecosystems
<p>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>.</p> <p>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>.</p> <p>Of the 49,438 queried DOIs, the ASK database provided:</p> <ul> <li><strong>Total DOIs processed:</strong> 12,636</li> <li><strong>DOIs with neither abstract nor full-text:</strong> 36 (abstract token count was less than 10)</li> <li><strong>DOIs with abstracts but no full-text:</strong> 12,636</li> <li><strong>DOIs with both abstract and full-text:</strong> 2,834</li> </ul> <p>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>.</p> <p>The accompanying GitHub repository provides access to the code and scripts used at various stages of the information extraction (IE) process.</p> <p><strong>Theme of the Study:</strong><br>"Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Models."</p>
Dataset of "Elucidation of factors shaping reactivity of 5'-deoxyadenosyl – a prominent organic radical in biology"
<p>This study investigates the factors modulating the reactivity of 5'-deoxyadenosyl (5'dAdo•) radical, a potent hydrogen atom abstractor, present in the active sites of radical SAM enzymes, but otherwise undergoing a rapid self-decay in aqueous solution. Here, we compare hydrogen atom abstraction (HAA) reactions between native substrates of radical SAM enzymes and 5'dAdo• in aqueous solution and in two enzymatic microenvironments and reveal that HAA efficiency of 5'dAdo• depends on (i) formation of 5'dAdo• in a pre-ordered complex with a substrate, which attenuates the unfavorable effect of substrate:5'dAdo• complex formation, (ii) hindering the conformational change associated with self-decay by performing the reaction in a tight cavity. The enzymatic cavity, however, does not have a strong effect on the HAA activity of 5'dAdo•. We performed an analysis of HAA performed by 5'dAdo• based on the three-component thermodynamic model incorporating the diagonal effect of the free energy of reaction, and the off-diagonal effect of asynchronicity and frustration. The study is based on the straightforward relationship between the off-diagonal thermodynamic effects and the electronic-structure descriptor – the redistribution of charge between the reactants during the reaction. It allows to access HAA-competent redox and acidobasic properties of 5'dAdo• that are otherwise unavailable due to its instability upon one-electron reduction and protonation. The results show that all reactions feature a favourable thermodynamic driving force and tunneling, the latter of which lowers systematically barriers by ~2 kcal mol-1. In addition, most of the reaction experience a favourable off-diagonal thermodynamic contribution. In HAA reactions, 5'dAdo• acts as a weak oxidant as well as a base, also 5'dAdo•-promoted HAA reactions proceed with quite low degree of asynchronicity of proton and electron transfer. Finally, the study elucidates the crucial and dual role of asynchronicity. It directly lowers the barrier as a part of the off-diagonal thermodynamic contribution, but also indirectly increases the non-thermodynamic part of the barrier by controlling the adiabatic coupling between proton and electron transfer. The latter signals that the reaction proceeds as a hydrogen atom transfer rather than a proton-coupled electron transfer.</p>
A biodiversity dataset graph: Biological Associations in TaxonWorks hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 hash://md5/686007de79cc2a49ab23fd3debe56e3f
<p>The intended use of this archive is to facilitate (meta-)analysis of Biological Associations captured in TaxonWorks [1]. TaxonWorks is an integrated web-based workbench for taxonomists and biodiversity scientists. It allows you to capture, organize, and enrich your data; share it with collaborators; and package it for analysis and publication. </p> <p>This dataset provides versioned snapshots of the TaxonWorks network as tracked by Preston [2,3,4] during 2024-05-07 using:</p> <pre><code>preston track -u https://sfg.taxonworks.org</code></pre> <p>. In addition, this dataset provides a processed version of the biological associations using the "preston tw-stream" command as generated by the following bash script:</p> <pre><code>#!/bin/bash # # Generates GloBI interaction JSON Lines from provided provenance log as generated by preston tw-stream. # /usr/local/bin/preston cat hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154\ | /usr/local/bin/preston tw-stream </code></pre> <p><br>The script itself was executed using:</p> <pre><code>cat transform.sh | preston bash </code></pre> <p>The execution of this transform.sh script (with content id hash://sha256/6dfe3c4ebf877bed73aebbe88c7d388bf894c569578ed7b28ca68e57a6afe43b), as well as their results, is captured within this datasets also. A rdf/quads formatted machine readable version of the workflow execution description can be found via:</p> <pre><code>preston cat hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 </code></pre> <p>And, the resulting JSON Lines file has content id (or signature) hash://sha256/4c2b8642251ced5985660d63c565efa6e5a9bf3d12b3b0c0d9ac577905f5e897 and is also included as interactions.json to facilitate access. </p> <p>The first json record can be generated using:</p> <pre><code>preston cat hash://sha256/4c2b8642251ced5985660d63c565efa6e5a9bf3d12b3b0c0d9ac577905f5e897\ | head -n1\ | jq . </code></pre> <p>or, provided that the interactions.json has content id starting with hash://sha256/4c2b86...</p> <pre><code>cat interactions.json\ | head -n1\ | jq . </code></pre> <p>This produces the following (formatted) json object:</p> <pre><code>{<br> "http://www.w3.org/ns/prov#wasDerivedFrom": "hash://sha256/fdbf13dc5f3d9c5afbc03db62699e2ce2724c499b7d91d8b0bf31e39409b153a",<br> "http://www.w3.org/1999/02/22-rdf-syntax-ns#type": "application/vnd.taxonworks+json",<br> "referenceId": "https://sfg.taxonworks.org/api/v1/sources/213218",<br> "interactionId": "https://sfg.taxonworks.org/api/v1/biological_associations/227664",<br> "taxonRootsResolved": 2,<br> "referenceResolved": true,<br> "referenceCitation": "@article{213218,\n author = {Monzen, Kota},\n journal = {Annual Report of the Gakugei Faculty of the Iwate University},\n pages = {24-38},\n title = {Revision of the Japanese gall wasps with the descriptions of new genus, subgenus, species and subspecies (II). Cynipidae (Cynipinae) Hymenoptera.},\n volume = {6},\n year = {1954}\n}\n",<br> "interactionTypeId": "gid://taxon-works/BiologicalRelationship/69",<br> "interactionTypeName": "gall",<br> "sourceTaxonName": "Neuroterus hakonensis",<br> "sourceTaxonId": "gid://taxon-works/TaxonName/1174121",<br> "sourceTaxonRank": "species",<br> "sourceTaxonAuthorship": "Ashmead, 1904",<br> "sourceTaxonPath": "Root | Cynipidae | Neuroterus | Neuroterus hakonensis",<br> "sourceTaxonPathIds": "gid://taxon-works/TaxonName/623170 | gid://taxon-works/TaxonName/1170060 | gid://taxon-works/TaxonName/1170097 | gid://taxon-works/TaxonName/1174121",<br> "sourceTaxonPathNames": "nomenclatural rank | family | genus | species",<br> "targetTaxonName": "Quercus",<br> "targetTaxonId": "gid://taxon-works/TaxonName/1173543",<br> "targetTaxonRank": "genus",<br> "targetTaxonAuthorship": "",<br> "targetTaxonPath": "Root | Fagaceae | Quercus",<br> "targetTaxonPathIds": "gid://taxon-works/TaxonName/623170 | gid://taxon-works/TaxonName/1173542 | gid://taxon-works/TaxonName/1173543",<br> "targetTaxonPathNames": "nomenclatural rank | family | genus"<br>}<br></code></pre> <p>In this example, a claim is made that, according to https://sfg.taxonworks.org/api/v1/sources/213218 [6] Neuroterus hakonensis (a gall wasp) has a primary host in the genus of Quercus (oak tree). </p> <p>In total, 237,068 such claims can be found in the generated resource with alias interactions.json and content id starting with hash://sha256/4c2b86... .</p> <p>In addition, the archive preston.tar.gz to allow for batch download. The archive contains three types of files: index files, provenance logs and data files. In addition, index files have been individually included in this dataset publication to facilitate remote access. Index files provide a way to links provenance files in time to establish a versioning mechanism. Provenance files describe how, when, what and where the TaxonWorks content was retrieved. For more information, please visit https://preston.guoda.bio or https://doi.org/10.5281/zenodo.1410543 . </p> <p>To retrieve and verify the downloaded TaxonWorks biodiversity dataset graph, download preston.tar.gz. Then, extract the archive into a "data" folder. Alternatively, you can use the preston[2] command-line tool to "clone" this dataset using:</p> <pre><code>java -jar preston.jar clone --remote https://zenodo.org/record/11151783/files </code></pre> <p>After that, verify the index of the archive by reproducing the following provenance log history:</p> <pre><code> java -jar preston.jar history --log tsv</code></pre> <p>to be:</p> <pre><code>hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154 </code><br><code>hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb</code><br><code>hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ff5e709305e593c87711e897b6341b94e775e2f312aa6d4ae5ed6120babd6f5e urn:uuid:0659a54f-b713-4f86-a917-5be166a14110 http://purl.org/pav/hasVersion hash://sha256/ff5e709305e593c87711e897b6341b94e775e2f312aa6d4ae5ed6120babd6f5e </code></pre> <p><br>To check the integrity of the extracted archive, confirm that each line produce by the command "preston verify" produces lines as shown below, with each line including "CONTENT_PRESENT_VALID_HASH". Depending on hardware capacity, this may take a while.</p> <pre><code>java -jar preston.jar verify</code></pre> <p>Note that a copy of the java program "preston", preston.jar, is included in this publication. The program runs on java 8+ virtual machine using "java -jar preston.jar", or in short "preston". </p> <p>Files in this data publication:</p> <p>--- start of file descriptions ---</p> <p>-- description of archive and its contents (a rendition of this file) --<br>README</p> <p>-- biological associations indexed from TaxonWorks expressed in a GloBI [5] compatible JSON Lines file --<br>interactions.json</p> <p>-- first 10 biological associations indexed from TaxonWorks expressed in a GloBI [5] compatible JSON Lines file --<br>interactions-10.json</p> <p>-- executable java jar containing preston [2,3,4] v0.8.5-SNAPSHOT. --<br>preston.jar</p> <p>-- preston archive containing TaxonWorks data files, associated provenance logs and a provenance index --<br>preston.tar.gz</p> <p>-- individual provenance index files --</p> <p>1fed32bf78298d7ecc3d9f36d106f1d7d7773a8b9a5e47af6632f36c1f82adb5<br>29306c5c144c3d7fd21be344d8b6b554b6f6efa3b8f8f5c0b27cdf0e88785652<br>2a5de79372318317a382ea9a2cef069780b852b01210ef59e06b640a3539cb5a<br>d31ff1ef1dea88c5952181a4f30e7ea7862873aa5f66430451275aa6d08d329e<br>deb84d69224af488da585186f88cafc58e978db5f9897de624cc9b02c0c83742<br>e9c34683f1e826f68f841f3419bd5ee9c0fa18be04713a6fd3364f226c7c5f2f<br>f98d36a9dc7bd833c93b3b61130865628f7bc2f7bb0920e95afcd16fba3dc6a8<br>ffb41d48979ceb964fbfbeb68cb60b584b759950087fdcc012521b866249bc39</p> <p>--- end of file descriptions ---</p> <p>This work is funded in part by grant NSF OAC 1839201, NSF DBI 1901932, NSF DBI 1901926, and NSF DBI 2102006 from the National Science Foundation.<br> </p>
BioReCer Main biological feedstock flows database
<p>BioReCer aims at assessing and complementing current certification schemes for biological resources according to the new EU sustainability goals to enhance bio-based circular systems.</p> <p>This will be achieved by including new criteria that align with EU taxonomy and EU corporate due diligence regulations into guidelines for certifying biological resources’ sustainability, origin, tracking and traceability (T&T), and by ensuring applicability at EU and global scale.</p> <p>By promoting the sustainability and trade of biological resources, BioReCer will increase the added value, use, as well as social acceptance of bio-based products.</p> <p>Part of the specific objectives of the project is to map the current European biomass flows in 4 main sectors:</p> <ol> <li>Fishery</li> <li>Urban waste and wastewater</li> <li>Agriculture</li> <li>Forestry</li> </ol> <p>This database presents information on over 30 biomass feedstocks from across this sectors and is estimated to cover approx. 90% of the available secondary biological feedstocks in the EU. </p> <p>Table 1 shows the amount of secondary biomass produced by feedstock and their fates.</p> <p>Table 2 shows the amount of primary biomass prodused, imported and exported to and from Europe.</p> <p>This database is based on the work done for derivable 2.1 - Main biological feedstocks flows.</p>
Environmental and biological data associated with captive-reared Delta Smelt Study, Sacramento-San Joaquin Delta, CA, January-March 2019
The endangered Delta Smelt Hypomesus transpacificus is an osmerid fish endemic to the upper San Francisco Estuary. A captive breeding program for the species led by the Fish Culture and Conservation Laboratory (FCCL), University of California, Davis, began in 1996 to create a refuge population. In order to better understand how captive Delta Smelt would fare in conditions outside of the hatchery, we placed captive-reared fish in enclosures in the Sacramento San-Joaquin Delta, and evaluated their ability to survive, feed, and maintain condition. Fish were acclimated in the hatchery at FCCL, tagged, swabbed, weighed, measured, and transferred to enclosures in the field. There were three types of enclosures (n=2 for each type), varying in mesh size and wrap condition. In January 2019, 384 adult Delta Smelt (243 days post hatch) were transferred to enclosures in Rio Vista. In February 2019, 360 adult Delta Smelt (278 days post hatch) were transferred to enclosures in the Deepwater Shipping Channel. For each deployment, fish remained in enclosures for approximately one month, then were retrieved from enclosures, euthanized, identified, weighed and measured. A subset were also analyzed for diet contents. During the one-month long deployments, cages were checked for biofouling, damage, and dead fish, and water quality measurements and zooplankton samples were collected.
US_UMB and US_UMd Ameriflux towers biometric plot data at the University of Michigan Biological Station, Pellston, MI (1997 to 2024)
These are the annual leaf litterfall carbon fluxes and average soil respiration measurements for the two flux towers (reference, aka 'AmeriFlux' and treatment, aka 'FASET') at UMBS.
Biological and Physical Monitoring Data of Restored Oyster Reef in Savannah River, Savannah, GA from May 2023 - February 2025
For the purposes of this study, we constructed two oyster reefs in Savannah, GA, USA using standard spat-on-shell restoration methodology. Reefs were constructed 1-2 meters from the marsh edge to reduce wave energy as it approached the shoreline, similar to a breakwater. We then conducted monitoring on the biological function of the reef, including live juvenile oyster coverage, size, and abundance for approximately 18 months. We also quantified the energy flux of waves offshore and onshore of the reef using water pressure measurements to determine the capability of these reefs at reducing wave energy. The oyster reefs in this study decreased wave energy by up to 40% compared to paired, non-reef control sites. Constructed oyster reefs also experienced healthy oyster population growth throughout the study, with live juvenile coverage of 17-40% almost 18 months post-deployment. This study took place in an erosion-prone area due to recreational and commercial boating traffic at the nearby Port of Savannah. Our results indicate that using restored oyster reefs as living shorelines is a technique with high potential for preventing shoreline loss in coastal areas vulnerable to anthropogenically-caused erosion. Restored Reef Site 1: 32.067957°, -80.985005° Control Site 1: 32.0675194°, -80.986369° Restored Reef Site 2: 32.062663°, -80.965147° Control Site 2: 32.063261°, -80.965889°
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.