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3,788 results for “indices”
Paleo Sea Level Proxies and Indicators for Greenland
<p>This repository contains the spreadsheets containing the paleo sea level data in ODS spreadsheet and tab delimited text formats. I also included the bibtex file that has all of the references used in the spreadsheet. For updates, please<br>go to the main GAPSLIP database on Github:</p><p>https://github.com/evangowan/paleo_sea_level</p><p>Version 1.0.1 corrects some of the place names.</p>
Indicative distribution map for Ecosystem Functional Group MT1.2 Muddy Shorelines
<p>This archive contains indicative distribution maps and profiles for <strong>MT1.2 Muddy Shorelines</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>
Data for: Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population
<p><span>The fitness of immigrants and their descendants produced within recipient populations fundamentally underpins the genetic </span><span>and population dynamic</span><span> consequences of immigration. </span><span>I</span><span>mmigrants can </span><span>in principle </span><span>induce contrasting genetic effects on fitness across generations, reflecting multi-faceted additive, dominance, and epistatic effects. Y</span><span>et, full multi-generational and sex-specific fitness effects of regular immigration have not been quantified within naturally structured systems, precluding inference on underlying genetic architectures </span><span>and population outcomes</span><span>. We used four decades of song sparrow </span><span>(<em>Melospiza melodia</em>)</span> <span>life-history and pedigree data to quantify fitness of natural immigrants, natives, and their F1, F2, and backcross descendants, and test for evidence of non-additive genetic effects. Values of key fitness components (including adult lifetime reproductive success and zygote survival) of F1 offspring of immigrant-native matings substantially exceeded their parent mean, indicating strong heterosis. Meanwhile, F2 offspring of F1-F1 matings had notably low values, indicating surprisingly strong epistatic breakdown. Further, magnitudes of effects varied among fitness components, and</span> <span>differed between female</span><span>s</span><span> and male</span><span>s</span><span> descendants. These results demonstrate that strong non-additive genetic effects on fitness can arise within </span><span>weakly </span><span>structured </span><span>and fragmented </span><span>populations </span><span>experiencing </span><span>frequent </span><span>natural </span><span>immigration. </span><span>Such effects will substantially affect the net </span><span>degree of effective gene flow and resulting local genetic introgression and adaptation.</span></p>
Indicative distribution map for Ecosystem Functional Group T4.5 Temperate subhumid grasslands
<p>This archive contains indicative distribution maps and profiles for <strong>T4.5 Temperate subhumid grasslands</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>
Victorian Coastal Monitoring Program: (1) VCMP Sites; (2) VCMP Coastal Erosion Indicators
<p>This dataset was produced by the Victorian Coastal Monitoring Program (VCMP), Department of Energy, Environment and Climate Action, Victoria State Government, Australia.</p><p><a href="https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program">https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program</a> </p><p><a href="https://www.marineandcoasts.vic.gov.au/__data/assets/pdf_file/0023/625352/VCMP_Erosion-Indicators_April_2023.pdf">https://www.marineandcoasts.vic.gov.au/__data/assets/pdf_file/0023/625352/VCMP_Erosion-Indicators_April_2023.pdf</a></p><p>[ADD LINK TO VCMP SITES METADATA REPORT - ONCE PUBLISHED TO VCMP WEBSITE]</p><p>Products include: </p><p>(1) Complete processed shorelines dataset ('VCMP Sites'), including drone and satellite data, with transects, shorelines, time series, and cross-sections for drone surveys</p><p>(2) Summary outputs ('VCMP Coastal Erosion Indicators'), including the Erosion Warning Indicator (<i>EWI</i>) summary statistics and Erosion Hotspot Detector (<i>EHD</i>) outputs. </p><p>Survey data in this repository were updated to the start of 2023. </p><p>Regularly updated outputs for all VCMP products, including pre-processed VCMP drone data (digital surface models and orthomosaics) can be accessed through the Victorian government (contact <a href="mailto:vcmp@delwp.vic.gov.au">vcmp@delwp.vic.gov.au</a>; <a href="https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program">https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program</a>). </p><p>'VCMP Sites' and 'VCMP Coastal Erosion Indicator' outputs and a wide array of marine and coastal data are viewable through the decision support portal CoastKit (<a href="https://mapshare.vic.gov.au/coastkit/">https://mapshare.vic.gov.au/coastkit/</a>). </p><p>Select outputs are also downloadable in spatial file format through DataShare Victoria (<a href="https://datashare.maps.vic.gov.au/search?q=vcmp">https://datashare.maps.vic.gov.au/search?q=vcmp</a>).</p>
Digitalization indicators and date on FDI for CEE and Balkan countries
<p>The data representing digitalization indicators and data for the foreign direct investment for the CEE and Balkan countries. </p>
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details).
Text-fig. 1. Situation of Early Miocene plant localities. a: Central Europe with Brno area and other fossil sites mentioned in text (1 – Znojmo and Přímětice, 2 – Oberdorf, 3 – Modrý Kameň Basin, 4 – Lipovany, 5 – Ipolytarnóc; CZ – the Czech Republic, PL – Poland, SK – Slovakia, H – Hungary, A – Austria, D – Germany). b: Brno area with Líšeň municipal district indicated. c: Líšeň municipal district with fossil sites indicated by asterisk. in A New Early Miocene (Ottnangian) Flora Of The "Rzehakia Beds" From Brno-Líšeň
Text-fig. 1. Situation of Early Miocene plant localities. a: Central Europe with Brno area and other fossil sites mentioned in text (1 – Znojmo and Přímětice, 2 – Oberdorf, 3 – Modrý Kameň Basin, 4 – Lipovany, 5 – Ipolytarnóc; CZ – the Czech Republic, PL – Poland, SK – Slovakia, H – Hungary, A – Austria, D – Germany). b: Brno area with Líšeň municipal district indicated. c: Líšeň municipal district with fossil sites indicated by asterisk.
UN digitalization indices 2003-2022
<p>Data are organized in a separate sheet for each of the indices: E-Government Rank,E-Government Index,E-Participation Index, Online Service Index, Human Capital Index, Telecommunication Infrastructure Index</p><p>Data comes from United Nations Department of Economic and Social Affairs (https://publicadministration.un.org/egovkb/en-us/data-center).</p>
Country Digitalization Indicators : Thailand
<p> </p> <p>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381)</em></p>
DESI 2022 indicator detailed data
<p>EUROSTAT detailed data for the DESI 2022 indicator (from 2013, if available):</p><ul><li>At least basic digital skills</li><li>ICT specialists</li><li>Female ICT specialists</li><li>Fixed very high capacity network coverage</li><li>5G coverage</li><li>SMEs with a basic level of digital intensity</li><li>AI</li><li>Cloud</li><li>Big data</li><li>Digital public services for citizens</li><li>Digital public services for businesses</li></ul><p>Source: https://ec.europa.eu/eurostat</p>
Peatland restoration in Norway – evaluation of ongoing monitoring and identification of plant indicators of restoration success
<p>Norway launched a national action plan on wetland restoration in 2016. So far, 90% of the restoration effort has been on peatland restoration, with about 140 mires restored so far. There are three main restoration goals stated in the action plan: 1) Limit greenhouse gas (GHG) emissions, 2) climate adaptation, and 3) improve ecological condition. Quantifying the outcome of the restoration actions is necessary to evaluate whether the goals of the action plan are met. A vegetation monitoring protocol was suggested before restoration started and has been implemented at five restoration sites. As the peatland restoration effort in Norway is increasing, it is timely to evaluate if the data currently collected can measure peatland restoration outcomes. We evaluate the monitoring protocol based on statistical analyses of the data collected at two sites, describe how indicator species can be identified using generalized composition data used as the basis for classifying habitats in Norway (EcoSyst framework), and suggest the way forward for peatland restoration monitoring in Norway. Data collected according to the monitoring protocol can document changes in species composition at restoration sites but has limitations when the ecological complexity at the sites increases and reference sites are unavailable. We argue that adjusting the monitoring protocol will: 1) Facilitate alignment with existing peatland research; 2) connect better with monitoring programs where data is collected applying EcoSyst framework principles; and 3) enable upscaling to cover the wide variation emerging in peatland restoration.</p>
Deliverable 2.3: Biodiversity impact estimates and documentation for indicators on multi-dimensional biodiversity aspects ready for use in WP3
<p>To quantify human-driven impacts on biodiversity, we used advanced modeling techniques paired with a few key variables such as habitat quality, vegetation structure, climate, and topography to develop an innovative predictive model that estimates both 1) current biodiversity patterns and distributions and 2) a baseline model of biodiversity. By comparing both of these models, we are able to identify regions with significant human-driven reductions in species richness, endemism, and species composition across both of our focus regions, South America and Africa.</p> <p>The files provided in this repository (1 km2 resolution) include:</p> <p>1- Species richness (number of species).</p> <p>2- Endemism (species rarity). For this metric, we used the corrected weight endemism index, which is the inverse of a species’ range size and effectively assigns higher scores to species with more restricted distributions. For this index, we used species ranges found within our study area (of South America and Africa).</p> <p>3- Species composition of vertebrates, invertebrates, and plants (which species occur in a given location). This metric, also known as beta diversity, summarizes which sets of species occur at each location. For this, we used the Sorensen index metric, as it does not depend on species absence data.</p> <p>These results provide a improve in previous deliverable 2.2.</p>
Key Performance Indicators
<p>Key Performance Indicators for NBS impact assessment, evaluated for the implemented NBS during the proGIreg project, in agreement with the European Framework described in "Evaluating the impact of nature-based solutions: a handbook for practitioners'' (2021, <a href="https://data.europa.eu/doi/10.2777/244577" target="_blank" rel="noopener noreferrer">https://data.europa.eu/doi/10.2777/244577</a>)."</p> <p><em>Baldacchini, C., Calfapietra, C. (2023): Living Labs impact at the district level, Deliverable No.4.8, proGIreg. Horizon 2020 Grant Agreement No 776528, European Commission, pp 93.</em></p> <p><em>Baldacchini, C., Calfapietra, C. (2023): Living Labs impact at the NBS level, Deliverable No.4.9, proGIreg. Horizon 2020 Grant Agreement No 776528, European Commission, 86 pp.</em></p>
Figure 5 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 5. Principal components analysis of the relative abundance (mol %, logit- transformed) of individual NLFAs of Trochosa ruricola using body size (small, large), flooding index (FI), plant species richness (SR), plant functional group richness (FG), presence of grasses (Gr), legumes (Leg), small herbs (SH) and tall herbs (TH) as supplementary variables.
Figure 4 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 4. Variations in δ15N signatures of Trochosa ruricola as affected by flooding index (P = 0.04, R2 = 0.12) and body size (small, large; P <0.01).
Figure 1 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 1. Variations in δ15N and δ13C signatures of Harpalus rufipes (black) and Trochosa ruricola (pink) across the study site of the Jena Experiment.
Figure 3 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 3. Principal components analysis of the relative abundance (mol %, logit-transformed) of individual NLFAs of Harpalus rufipes using flooding index (FI), plant species richness (SR), plant functional group richness (FG), presence of grasses (Gr), legumes (Leg), small herbs (SH) and tall herbs (TH) as supplementary variables.
Fig.ç1.M aps and photograph showing the sampling locality for Echinoderes ohtsukai sp. nov. A, Map of eastern Asia; B, enlargement of the rectangle in A; C, enlargement of the area indicated by the black circle in B; D, photograph of the sampling locality; white arrow indicates the Kamogawa River and dotted circle indicates the sampling site. in A New Brackish-water Species of Echinoderes (Kinorhyncha: Cyclorhagida) from the Seto Inland Sea, Japan
Fig.ç1.M aps and photograph showing the sampling locality for Echinoderes ohtsukai sp. nov. A, Map of eastern Asia; B, enlargement of the rectangle in A; C, enlargement of the area indicated by the black circle in B; D, photograph of the sampling locality; white arrow indicates the Kamogawa River and dotted circle indicates the sampling site.
Supporting dataset for manuscript "Estimating the microarthropod diversity in cropping systems by comparing ecological indices across Europe" by Bigiotti et al. 2025
<p>This dataset contains counts of mesofauna individuals classified as Biological Forms (BF). It represent the raw data used for all indices calculation in the manuscript entitled "Microarthropod communities' diversity for soil health assessment: comparing several ecological indices across Europe" by authors Gaia Bigiotti, Francesco Vitali, Stefano Mocali, Giovanni L’Abate, Eligio Malusà, Dawid Kozacki, Irena Bertoncelj, Morgane Ourry, Massimo Pugliese, Heinrich Maisel, Expedito Olimi, Maria Grazia Tommasini, Carlo Jacomini, and Lorenzo D’Avino.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.