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229 results for “community biodiversity”
Supplementary material 3 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Use Cases
Figure 8 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 8 The FAIR Data Place (FDP) built by JRA-05 will provide a one-stop point for searching bi- and multi-directionally linked FAIR data across domains to serve multiple research purposes.
Figure 3 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 3 The GBIO Framework identified 20 components as essential elements of biodiversity informatics and organised as four layers: Cul- ture, Data, Evidence and Understanding (from Hobern et al. 2019).
Figure 1 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 1 Access to data and services along the entire data and research life cycle in biodiversity science.
Figure 6 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 6 Conceptual framework for FAIR data acquisition and delivery across RIs and through a central federated search engine (FAIR Data Place, FDP).
Figure 2 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 2 BiCIKL's concept on horizontal linkage across both ESFRI and other research infrastructures.
Figure 5 from: Penev L, Koureas D, Groom Q, Lanfear J, Agosti D, Casino A, Miller J, Arvanitidis C, Cochrane G, Hobern D, Banki O, Addink W, Kõljalg U, Copas K, Mergen P, Güntsch A, Benichou L, Benito Gonzalez Lopez J, Ruch P, Martin CS, Barov B, Demirova I, Hristova K (2022) Biodiversity Community Integrated Knowledge Library (BiCIKL). Research Ideas and Outcomes 8: e81136. https://doi.org/10.3897/rio.8.e81136
Figure 5 Data liberation and prospective publishing workflows bridging data from various resources into an interoperable and re-usable FAIR data pool.
Figure 8 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 8 - Ecological characterization of the avian community of the Karen Mogensen Reserve. Percentage of the recorded species based on: A Phenology B Habitat type C Height level D Forest dependency category.
Figure 7 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 7 - Passeriformes observed within the Karen Mogensen Reserve. A Chiroxiphia linearis (Pipridae), a species typical of Central American tropical dry forests reaching its southernmost range border in the area B Campylorhynchus capistratus nicoyae (Troglodytidae), a subspecies endemic to NW Costa Rica, which reaches its southernmost breeding areas in the surveyed zone C Catharus aurantiirostris (Turdidae), species characterized by a local isolated breeding population D Hylocichla mustelina (Turdidae), regular winter visitor in the Karen Mogensen Reserve, but never recorded before from the Nicoya Peninsula. Photographs by: M. Dal Zotto (A, B, D) and G. Romeo (C).
Figure 6 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 6 - Non-passerine birds observed within the Karen Mogensen Reserve. A Crax rubra (Cracidae), a globally vulnerable species that reproduces in the area B Amazona autumnalis (Psittacidae), species resident and potentially breeding in the area, characterized by declining populations and considered threatened on a national scale C Sarcoramphus papa (Cathartidae), species resident in the area, with declining populations and considered locally threatened D Chlorostilbon canivetii (Trochilidae), female at nest, characterized by traits (e.g., the colour of the lower mandible) which resemble the congeneric C. assimilis E Trogon melanocephalus (Trogonidae) and F Eumomota superciliosa (Momotidae), two species that reach their southernmost range border approximately in the surveyed zone. Photographs by: M. Dal Zotto (F) and G. Romeo (A, B, C, D, E).
Figure 5 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 5 - Species accumulation curves based on the surveys from 2005 to 2017. "Sobs" is the permuted observed species accumulation (1000 permutations).
Figure 2 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 2 - Innermost part of the Karen Mogensen Reserve, with altitudes (above), vegetation unities and their age (below), and hydrographic network shown.
Figure 4 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 4 - Avian richness of the Karen Mogensen Reserve. Histograms reporting the number of recorded species for each of the non-passerine orders (A) and of the passerine families (B).
Figure 1 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 1 - Map of Costa Rica and the Karen Mogensen Reserve. The areas in white, bordered by red lines, are parts of the Karen Mogensen Reserve added to the original nucleus over years. The area filled by a striped pattern represents the biological corridor of the Nicoya Peninsula and the additional protected forested land adjacent to the Karen Mogensen Reserve. "R" shows the position of the Research Station. Red dots are the fixed points, yellow lines are the transects used for the data collection during the surveys; green dots represent the transects endpoints. Numbers and Roman numerals refer to Table 1.
Figure 3 from: Dal Zotto M, Romeo G, Mena Aguilar LA, Sonetti D, Pederzoli A (2017) The avian community of the Karen Mogensen Reserve, a wealth of biodiversity within the poorly investigated and threatened environments of northwestern Costa Rica. ZooKeys 722: 101-135. https://doi.org/10.3897/zookeys.722.14606
Figure 3 - Main habitats of the Karen Mogensen Reserve. A, Moist forest B Dry forest C Dry to moist transitional forest D Forest borders and grassland. Photographs by: M. Dal Zotto (A, C, D) and G. Romeo (B).
Supplementary material 1 from: Bylemans J, Gleeson DM, Lintermans M, Hardy CM, Beitzel M, Gilligan DM, Furlan EM (2018) Monitoring riverine fish communities through eDNA metabarcoding: determining optimal sampling strategies along an altitudinal and biodiversity gradient. Metabarcoding and Metagenomics 2: e30457. https://doi.org/10.3897/mbmg.2.30457
: Data type: Microsoft Word Document (.docx)
Supplementary material 2 from: Bylemans J, Gleeson DM, Lintermans M, Hardy CM, Beitzel M, Gilligan DM, Furlan EM (2018) Monitoring riverine fish communities through eDNA metabarcoding: determining optimal sampling strategies along an altitudinal and biodiversity gradient. Metabarcoding and Metagenomics 2: e30457. https://doi.org/10.3897/mbmg.2.30457
: Data type: statistical data
Supplementary material 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Detailed design of the Field Experiment
Supplementary material 2 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Brief description of the Field Experiment
Figure 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 1 A. Conceptual diagram of the mechanistic approach of the planned Research Unit. B. Conceptual scheme of the proposed evolutionary niche shifts in plant monocultures and mixtures. This idea feeds into our understanding of how evolutionary history influences the ecological interactions of species that compete for growth factors, ultimately defining biotope space (gray rectangle; Hutchinson 1978). Graphically depicted, species (ellipses) in mixture will show increasing niche differentiation over time due to competition (niche overlap). Thus, history of selection in diverse communities is expected to result in greater interspecific differences (less overlap of ellipses) and more specialization (smaller ellipses) than a history of isolation (monocultures). In monocultures, species will experience strong selection pressure by accumulating soil-borne pathogens, and species may invest energy in chemical and morphological defense traits (depicted by ellipses shifting towards the same corner of the habitat space). Plants in mixtures together may exploit more available biotope space than single monocultures, causing increasing diversity effects on ecosystem functions over time. However, there is limited support for this assumption for traits related to light (e.g., Lipowsky et al. 2015, Roscher et al. 2015) and resource use (Jesch et al. 2018) so far.
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.