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30,265 results for “Functionality”
Ants and Ecosystem Function in Hemlock Removal Experiment at Harvard Forest 2006-2014
Eastern hemlock (Tsuga canadensis) is a foundation species in eastern North American forests. Hemlock stands host unique assemblages of flora and fauna, and the structure of these assemblages is expected to change as hemlock declines due to infestation by the hemlock woolly adelgid (Adelges tsugae) and is removed by pre-emptive salvage logging. A 2003 survey of hemlock stands in central Connecticut and Massachusetts showed that ant species richness and abundance is substantially greater in logged and adelgid-infested hemlock stands than it is in intact hemlock stands (see HF065) and we hypothesized that we would see similar changes in ant species diversity following application of treatments in the Hemlock Removal Experiment at the Simes Tract (see HF118). We further hypothesized that because ants are known to modulate ecosystem function in other habitats that observed changes in ant species diversity would be accompanied by changes in ecosystem processes including soil respiration rate and nitrogen availability. In April 2006, we established a set of sub-plots in all eight canopy manipulation plots of the Hemlock Removal Experiment. In each canopy manipulation plot, we installed two ant exclosure plots, two disturbance control plots, and two control plots. Ant species richness and abundance, as well as effectiveness of the exclosures, is monitored with pitfall traps monthly during the summer. Soil nitrogen availability is measured using resins that are collected every three months, and soil respiration is measured bi-weekly during the growing season.
Plant community responses to functional group and species removals along biodiversity experiment vegetation transects at the Jornada Basin LTER site, 1997-2002
This dataset contains vegetative cover data of plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected with the objective to distinguish the differential effects of plant community biomass, functional groups, and biodiversity within functional groups on ecosystem and plant community function. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. Following treatments, vegetative data was collected by sampling each plot along three transects twice a year (Spring and Fall) for 5 years from 1997-2002 (no data collected in 1998). This data set consists of the date of collection, plot number, treatment type, transect number, quadrat number, species codes, two diameters, height, condition, count, record IDs, and error codes. This study is complete.
Impacts of Climate Warming on Trophic Function at Harvard Forest and Duke Forest 2013
Forest floor food webs play pivotal roles in carbon cycling, but they are rarely considered in models of carbon fluxes, including soil carbon dioxide emissions (respiration), under climatic warming. The indirect effects of invertebrates on heterotrophic respiration through interactions with microbial communities are significant and will be altered by warming. However, the interactive effects of invertebrates and warming on microbes and heterotrophic respiration in the field are poorly understood. In this study we combined field and common garden laboratory approaches to examine relationships between warming, forest floor food web structure, and heterotrophic respiration. We found that soil animals can overwhelm the effects of warming (to 5 degrees Celsius above ambient) on heterotrophic respiration. In particular, the presence of higher trophic levels and burrowing detritivores strongly determined heterotrophic respiration rates in temperate forest soils, dictating the ecosystem response to warming. These effects were, however, context-dependent, with greater effects in a lower-latitude site. Without isolating and including the significant impact of invertebrates, climate models will be incomplete, hindering well-informed policy decisions.
Plant species-level responses to functional group and species removals in biodiversity experiment plots at the Jornada Basin LTER site, 1999
This dataset contains individual species size data in vegetation plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected with the objective to distinguish the differential effects of plant community biomass, functional groups, and biodiversity within functional groups on ecosystem and plant community function. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. In 1999, this pilot study attempted to assess individual species responses of representative individuals in these treatments. Ten randomly selected individuals of eight plant species were measured in each experimental plot, and this dataset reports volumetric data (diameters and height) for each. The study was designed as an individual-based complement to the transect data in EDI dataset knb-lter-jrn.210121001 but was not continued past 1999. This dataset is complete.
Indicative distribution maps for Ecosystem Functional Groups - Level 3 of IUCN Global Ecosystem Typology
<p>This dataset includes the current version of the indicative distribution maps and profiles for <strong>Ecosystem Functional Groups</strong> - Level 3 of IUCN Global Ecosystem Typology (v2.1). Please refer to Keith <em>et al.</em> (2020) and Keith et al. (2022).</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes for each functional group of ecosystems to enable any ecosystem type to be assigned to a group.</p> <p>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. Most maps were prepared using a coarse-scale template (e.g. ecoregions), but some were compiled from higher resolution spatial data where available (see details in profiles). Higher resolution mapping is planned in future publications.</p> <p>We emphasise that spatial representation of Ecosystem Functional Groups does not follow higher-order groupings described in respective ecoregion classifications. Consequently, when Ecosystem Functional Groups are aggregated into<strong> functional biomes</strong> (Level 2 of the Global Ecosystem Typology), spatial patterns may differ from those of biogeographic biomes. Differences reflect the distinctions between functional and biogeographic interpretations of the term, “biome”.</p>
Data from “Larval and juvenile Longfin Smelt diets as a function of fish size and prey density in the San Francisco Estuary”
This publication includes the raw data from the manuscript: Lojkovic Burris, Z. P., R. D. Baxter, and C. E. Burdi. 2022. Larval and juvenile Longfin Smelt diets as a function of fish size and prey density in the San Francisco Estuary. California Fish and Wildlife Journal 108:e11. http://www.doi.org/10.51492/cfwj.108.11 Data includes the diets of larval and juvenile Longfin Smelt in the San Francisco Estuary from 2005 to 2008 in the form of diet by number, diet by weight, macroinvertebrate prey lengths, prey length-weight equations, and prey weight conversions.
Ant Functional Diversity in Temperate Zone Forests: A Comparison with Neotropical Ants 2010
Predicted impacts of climatic change on ant functional diversity and distributions in eastern North American forests Aims--Climatic change is expected to rearrange species assemblages and ultimately affect organism-mediated ecosystem processes. We focus on identifying patterns and relationships between common ant species (representing 99% of total ant records) richness and functional diversity; modelling how these patterns may change at local and regional scales in future climatic conditions; and interpreting how these changes might influence ant-mediated ecosystem processes. Location--Forested ecosystems of eastern North America. Methods--We used a previously published dataset to evaluate functional diversity at 67 sites in the eastern U.S. and quantified 14 taxonomic, morphometric and natural history traits for 70 common ant species in the region. We used functional diversity metrics, functional groups and species distribution modelling methods to address our aims. We used stacked species distribution models and stacked functional group models to predict species assemblages and functional richness at the 67 sites and at a regional scale for current and future climatic conditions. Results--Species richness and functional diversity are positively correlated throughout the region. Under future climate scenarios, species richness and functional group richness were predicted to decrease in southern ecoregions and increase in northern ecoregions. This may be due to increased thermal stress for species in the southern extent of their ranges and increased habitat suitability in the northern ecoregions. Decomposers, arthropod community regulators and seed dispersers are forecast to be the most threatened ant functional groups. Main Conclusions--Climate change will likely lead to major changes in ant species richness and functional group richness in the forests of the north-eastern United States, and this may substantially alter ant-mediated ecosystem processes and services
Linking Community Dynamics and Ecosystem Function at Harvard Forest 1996-2000
Human activities are effecting profound changes in the structure and function of natural ecosystems. A comprehensive understanding of current ecosystem dynamics and future responses to global change requires an integrated investigation of ecological processes at many levels of organization. My thesis research addressed this goal by examining interactions between community- and ecosystem-level dynamics in mixed conifer broad-leaved forests in eastern North America. I addressed the nature of canopy-seedling feedbacks in mixed forests by relating seedling regeneration patterns in contrasting stand types to understory conditions (EXPERIMENT 1), and by directly manipulating resource availability to separate the individual effects of particular resources (EXPERIMENT 2). To investigate how nitrogen deposition will influence future forest composition, I examined the impact of increased nitrogen availability on regeneration of both coniferous and broad-leaved tree species under both closed canopy (EXPERIMENT 3) and simulated gap (EXPERIMENT 4) conditions. Future changes in forest composition might then influence whole-ecosystem productivity. I used two scaling approaches (leaf-level aggregation, EXPERIMENT 5; whole-tree sap flow, EXPERIMENT 6), I examined how the dominant coniferous and broad-leaved species in mixed temperate forests differed in their contributions to canopy-level photosynthesis.
Effects of Long-Term Soil Warming on Ecosystem Function at Harvard Forest 2019
Across biomes, soil biodiversity promotes ecosystem functions. However, whether this relationship will be maintained within ecosystems under climate change is uncertain. Here, using two long-term soil warming experiments, we investigated how warming affects the relationship between ecosystem functions and bacterial diversity across seasons, soil horizons, and warming duration. Soils were sampled from these warming experiments located at the Harvard Forest Long-Term Ecological Research (LTER) site, where soils had been heated +5°C above ambient for 13 or 28 years at the time of sampling. We assessed seven measurements representative of different ecosystem functions and nutrient pools. We also surveyed bacterial community diversity. We found that ecosystem function was significantly affected by season, with autumn samples having a higher intercept than summer samples in our model, suggesting a higher overall baseline of ecosystem function in the fall. The effect of warming on bacterial diversity was similarly affected by season, where warming in the summer was associated with decreased bacterial evenness in the organic horizon. Despite the decreased bacterial evenness in the warmed plots, we found that the relationship between ecosystem function and bacterial diversity was unaffected by warming or warming duration. Our findings highlight that season is a consistent driver of ecosystem function as well as a modulator of climate change effects on bacterial community evenness.
Functional Traits of Selected Tree Species in Harvard Forest, New Hampshire, and Southern Quebec 2015
Increasing evidence suggests that species' phenological responses may predict their performance with warming, but this work has generally ignored whether phenology is correlated with other traits known to drive plant performance. This is perhaps surprising given that interest in functional traits has also increased in recent decades, yet within the functional traits literature there has been an equally limited consideration of phenology, perhaps because robustly estimating it is time-intensive, and simple field estimates will show extreme variation across sites of different latitudes and climate regimes. Here we collected a suite of trait data on the same species for which we collected phenological data (see related dataset HF314, Leaf and Flower Phenology of Woody Plant Species at Harvard Forest and Southern Quebec 2015) to help address this gap. We focused on populations of trees in temperate forests in the Northeast face, which face different environmental conditions across their ranges. This project measured functional traits of trees at two to four sites, to provide a foundation for studies on the relationship between range shift, phenology, and functional traits.
Annual Aboveground Net Primary Productivity by plant functional groups across grassland-shrubland ecotones at 3 sites in the Jornada Basin, 2006-ongoing
The objective of this ongoing study is to investigate how pulses of precipitation translate into pulses of plant aboveground net primary productivity (NPP) across grassland to shrubland ecotones in the northern Chihuahuan Desert. This dataset consists of annual aboveground net primary productivity estimates by plant functional groups in three habitat vegetation zones (grassland, ecotone, and shrubland) at three grassland-to-shrubland ecotone sites in the Jornada Basin, Dona Ana County, New Mexico, USA. The annual ANPP estimates are derived from plant cover measurements (see methods). Due to its growth form, Yucca elata (YUEL), in the leaf succulent functional group, has been found to produce large errors in interyear biomass estimates. This data package separates biomass estimates for YUEL and non-YUEL leaf succulents so that users can decide whether to combine them or keep them separate. In general, the authors recommend against using the YUEL estimates for most purposes. Data collection is ongoing with new observations in spring and fall of each year; data from both annual sampling times are required to estimate annual ANPP.
MCR LTER: Coral Reef: Modeling the effects of selectively fishing key functional groups of herbivores on coral resilience; data for Cook et al., 2023 Ecosphere
These data and code were generated in support of the manuscript: Cook DT, Schmitt RJ, Holbrook SJ, and HV Moeller, Ecosphere. To investigate the impacts of selectively harvesting functional groups of herbivorous fishes on coral resilience, we used a dynamic model that is grounded by the coral reef system in Moorea, French Polynesia. Our model simulates the fraction of a reef occupied through time by classes of key benthic spaceholders (coral, two stages of macroalgae, and turf). Benthic and fishing dynamics are linked through the harvesting of two functional groups of herbivorous fishes. We utilize data collected on the abundance of fishes on the reef and in the catch in Moorea, French Polynesia to inform our model and to empirically explore patterns of fishing selectivity. These data and code were published in Ecosphere and were a part of the thesis of D. Cook (2023). This manuscript uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological Research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through 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 2005-2023).
The influence of heart rate variability biofeedback on cardiac regulation and functional brain connectivity
Open the record for dataset details and reuse information.
Indicative distribution map for Ecosystem Functional Group MT2.2 Large seabird and pinniped colonies
<p>This archive contains indicative distribution maps and profiles for <strong>MT2.2 Large seabird and pinniped colonies</strong>, 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 <em>et al.</em> (2020) and Keith <em>et al.</em> (2022) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group F2.10 Subglacial lakes
<p>This archive contains indicative distribution maps and profiles for <strong>F2.10 Subglacial lakes</strong>, 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 <em>et al.</em> (2020) and Keith <em>et al.</em> (2022) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
iEEG Data for "Functional Group Bridge for Simultaneous Regression and Support Estimation"
<p>The repository contains analysis scripts and data used in Wang Z, Magnotti J, Beauchamp MS, Li M. Functional Group Bridge for Simultaneous Regression and Support Estimation, 2020. The data contains high-gamma brain responses across 8 subjects from "congruency" audio-visual experiment.</p>
FuTRES (Functional Trait Resource for Environmental Studies) data store archival copy - 5/21/2022
<p> </p> <p>The Functional Trait Resource for Environmental Studies (FuTRES) project is a collaborative project among four universities (University of Oregon, University of Arizona, University of Florida, and Howard University). The key deliverables of FuTRES are a workflow for assembling functional trait data measured at the specimen level, a database to serve that data, and scientific publications demonstrating the utility of the assembled data. This dataset represents the FuTRES datastore as of 5/21/2022, providing an archive that is timestamped and providing all data that is not currently embargoed by providers. The column headers for FuTRES data are: basisOfRecord,catalogNumber,class,collectionCode,country,decimalLatitude,decimalLongitude,diagnosticID,eventID,family,genus,individualID,institutionCode,lifeStage,locality,mapped_project,materialSampleID,maximumChronometricAge,maximumChronometricAgeReferenceSystem,maximumElevationInMeters,measurementMethod,measurementSide,measurementType,measurementUnit,measurementValue,minimumChronometricAge,minimumChronometricAgeReferenceSystem,minimumElevationInMeters,observationID,occurrenceID,occurrenceRemarks,order,reproductiveCondition,samplingProtocol,scientificName,sex,specificEpithet,stateProvince,verbatimElevation,verbatimEventDate,verbatimLatitude,verbatimLocality,verbatimLongitude,verbatimMeasurementUnit,yearCollected,projectID,inferred_traits. The traits available and number of records for each trait: </p> <ul> <li><a href="https://futres-data-interface.netlify.app/">length (1,790,883)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tail length (520,281)</a></li> <li><a href="https://futres-data-interface.netlify.app/">body length (456,165)</a></li> <li><a href="https://futres-data-interface.netlify.app/">pes length (413,668)</a></li> <li><a href="https://futres-data-interface.netlify.app/">ear length to notch (397,073)</a></li> <li><a href="https://futres-data-interface.netlify.app/">external ear length (397,073)</a></li> <li><a href="https://futres-data-interface.netlify.app/">body mass (373,949)</a></li> <li><a href="https://futres-data-interface.netlify.app/">weight (373,949)</a></li> <li><a href="https://futres-data-interface.netlify.app/">width (7,429)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus width (1,705)</a></li> <li><a href="https://futres-data-interface.netlify.app/">metacarpal bone of digit 3 proximal articular breadth (783)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 1 occlusal surface width (782)</a></li> <li><a href="https://futres-data-interface.netlify.app/">metacarpal bone of digit 3 breadth (716)</a></li> <li><a href="https://futres-data-interface.netlify.app/">metacarpal bone of digit 3 depth (706)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus length (649)</a></li> <li><a href="https://futres-data-interface.netlify.app/">long bone length (637)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary molar tooth 1 occlusal surface width (605)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus trochlea breadth (596)</a></li> <li><a href="https://futres-data-interface.netlify.app/">epiphysis width (581)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus breadth (560)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus medial depth (549)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tooth row length (498)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower tooth row length (425)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia distal width (413)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 1 occlusal surface length (402)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 4 occlusal surface width (361)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 3 occlusal surface length (343)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur width (301)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus length (297)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus width (293)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 2 occlusal surface width (261)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 2 occlusal surface length (260)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia diaphysis width (260)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 2 occlusal surface length (242)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia length (228)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia distal breadth (208)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia distal depth (201)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 2 occlusal surface width (197)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 4 occlusal surface length (187)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 4 occlusal surface width (185)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 1 occlusal surface length (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 1 occlusal surface width (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">premolar tooth 3 occlusal surface width (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary canine tooth to premolar tooth 3 length (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 3 occlusal surface length (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 3 occlusal surface width (184)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary molar tooth 1 occlusal surface length (180)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary molar tooth 1 occlusal surface length (177)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary molar tooth 1 occlusal surface width (177)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 4 occlusal surface length (176)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 4 occlusal surface width (176)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia proximal width (162)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 3 occlusal surface length (159)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 2 occlusal surface length (155)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 2 occlusal surface width (155)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia diaphysis breadth (145)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary molar tooth 2 occlusal surface length (120)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary molar tooth 2 occlusal surface width (119)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia diaphysis depth (111)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 2 occlusal surface width (106)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 2 occlusal surface length (105)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper premolar tooth 1 occlusal surface length (105)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 1 occlusal surface length (105)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary premolar tooth 1 occlusal surface width (105)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia proximal breadth (85)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 3 occlusal surface length (81)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 1 occlusal surface length (79)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary premolar tooth 1 occlusal surface width (79)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary molar tooth 2 occlusal surface length (78)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper secondary molar tooth 2 occlusal surface width (78)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus trochlea breadth (76)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus medial trochlear height (74)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus trochlear height at sagittal crest (74)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus trochlear sulcus height (74)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia proximal depth (73)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper molar tooth 1-2 length (73)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper tooth row length (73)</a></li> <li><a href="https://futres-data-interface.netlify.app/">anterior tibial tuberosity length (70)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus distal depth (69)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur length (67)</a></li> <li><a href="https://futres-data-interface.netlify.app/">ulna width (67)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia medial length (63)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus diaphysis breadth (57)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus diaphysis depth (54)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower secondary molar tooth 3 occlusal surface length (51)</a></li> <li><a href="https://futres-data-interface.netlify.app/">trochlea tali length (49)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur diaphysis breadth (45)</a></li> <li><a href="https://futres-data-interface.netlify.app/">forelimb zeugopod bone length (45)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur distal breadth (44)</a></li> <li><a href="https://futres-data-interface.netlify.app/">ulna length (42)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur proximal breadth (40)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus length from trochlea to caput (38)</a></li> <li><a href="https://futres-data-interface.netlify.app/">calcaneus length (37)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur caput depth (37)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus length from trochlea to ventral tubercle (37)</a></li> <li><a href="https://futres-data-interface.netlify.app/">humerus proximal breadth (37)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur diaphysis depth (36)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur distal depth (36)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur trochlea breadth (32)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur proximal depth (31)</a></li> <li><a href="https://futres-data-interface.netlify.app/">molar tooth 3 occlusal surface width (30)</a></li> <li><a href="https://futres-data-interface.netlify.app/">talus lateral length (30)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper molar tooth 3 occlusal surface length (30)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper molar tooth 3 occlusal surface width (30)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur length from caput to lateral condyle (28)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur length from greater trochanter to medial condyle (28)</a></li> <li><a href="https://futres-data-interface.netlify.app/">body length with tail (25)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower molar tooth 1 occlusal surface length (23)</a></li> <li><a href="https://futres-data-interface.netlify.app/">lower molar tooth 2 occlusal surface length (23)</a></li> <li><a href="https://futres-data-interface.netlify.app/">ulna depth across the process anaconaeus (23)</a></li> <li><a href="https://futres-data-interface.netlify.app/">ulna proximal articular breadth (23)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper molar tooth 1 occlusal surface length (22)</a></li> <li><a href="https://futres-data-interface.netlify.app/">olecranon depth (21)</a></li> <li><a href="https://futres-data-interface.netlify.app/">olecranon length (21)</a></li> <li><a href="https://futres-data-interface.netlify.app/">upper molar tooth 2 occlusal surface length (21)</a></li> <li><a href="https://futres-data-interface.netlify.app/">breadth of calcaneal body (18)</a></li> <li><a href="https://futres-data-interface.netlify.app/">calcaneus width (18)</a></li> <li><a href="https://futres-data-interface.netlify.app/">tibia lateral length (14)</a></li> <li><a href="https://futres-data-interface.netlify.app/">femur length from caput to medial condyle (5)</a></li> <li><a href="https://futres-data-interface.netlify.app/">radius distal width (3)</a></li> <li><a href="https://futres-data-interface.netlify.app/">radius length (3)</a></li> <li><a href="https://futres-data-interface.netlify.app/">radius proximal articular width (3)</a></li> <li><a href="https://futres-data-interface.netlify.app/">radius proximal width (3)</a></li> <li><a href="https://futres-data-interface.netlify.app/">radius width (3)</a></li> <li><a href="https://futres-data-interface.netlify.app/">body height (1)</a></li> <li><a href="https://futres-data-interface.netlify.app/">height (1)</a></li> </ul>
Dataset of "Asparagine-Modified Magnetic Graphene Oxide: An Efficient and Green Nanocatalyst for Synthesis of 5-oxodihydropyrano[3,2-c]chromenes and dihydropyrano[2,3- c]pyrazole derivatives and the Density functional theory calculation".
<p>The primary focus of this study involved the fabrication of a novel nanocatalyst Fe3O4-supported asparagine functionalized graphene oxide (Fe3O4@GO-N-(Asparagine)). The catalyst was synthesized through a four-step procedure.</p>
Indicative distribution map for Ecosystem Functional Group M1.10 Rhodolith/Maërl beds
<p>This archive contains indicative distribution maps and profiles for <strong>M1.10 Rhodolith/Maërl beds</strong>, 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 <em>et al.</em> (2020) and Keith <em>et al.</em> (2022) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
DAS Control over the spatial correlation of silica perforations in thin films as a function of solution conditions
<p><span>Dataset production context : A perforated silica layer with structural correlation is engineered using sol-gel chemistry, applied to large-scale flat and curved sur-faces. The anion(s) used in the preparation give tailored spatial correlation, and control over perforation size and density. Surface structuration is rapidly and reproducibly created using water and salts as inexpensive and ecofriendly reagents.</span></p>
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.