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218 results for “CLASSIFICATION AND TAXONOMY”
Taxonomy, distribution and classification of ecosystem-types, integrating the recent IUCN function-based typology and local conceptualizations
<p>1. Introduction:</p> <p>This dataset is a work in progress. It compiles data gathered on ecosystem-types and their distribution based on a series of field studies led by the author, in Seychelles and West and Central Africa (Senterre 2014, Senterre & Wagner 2014, Senterre 2016, Senterre et al. 2017, 2019, 2020, 2021a, 2022). The aims of this dataset are:</p> <p>a. To share in an explicit and transparent way data on proposed taxonomies of ecosystems, i.e. conceptualizations of ecosystem-types, including explicit ecosystem names and management of synonymies.</p> <p>b. To develop ecosystem red listing based on transparent and falsifiable distribution raw data, combining distribution modeling (maps) and in situ observation of individual stand occurrences.</p> <p>c. To illustrate in detail how to deal with ecosystem data following the approach described in Senterre et al. (2021b) (i.e. "ecosystemology" approach).</p> <p>d. To integrate the above approach with the newly developed function-based typology of ecosystems (Keith et al. 2022), therefore contributing to bridging the persistent gap between the global and the local scales in ecosystem descriptions and classifications.</p> <p> </p> <p>2. Context and versions:</p> <p>This dataset was initially planned for publication on GBIF (Global Biodiversity Information Facility), as part of a project developed for the review of Key Biodiversity Areas in Seychelles: "Mainstreaming recent species and ecosystem distribution data into Key Biodiversity Areas assessments in Seychelles" (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>).</p> <p>In the first version of the GBIF dataset (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>), we proposed an analysis of the potential 'core' and 'extension' files available in GBIF for a publication of ecosystem-type names (and synonymies) and their corresponding occurrences recorded from field observations. This is an original analysis of taxonomic principles managed entirely at the scale of local observable objects, and their history of identifications or interpretations.</p> <p>Toward the end of the above-mentioned GBIF project, considering the limitations and gaps currently present in GBIF, it was decided to restrict the GBIF dataset to a simple 'metadata' entry and to publish the complete version of this dataset in Zenodo. This allows to include all tables needed, as well as all required fields without having to accommodate them within the limited GBIF structure (see metadata description on GBIF for more details). The fields of the tables published here are described in the GBIF metadata entry and in the ecosystemology paper (Senterre et al. 2021b).</p> <p> </p> <p>3. New development on typology aspects:</p> <p>In addition, considering that the new IUCN global typology of ecosystems is now published (Keith et al. 2022), we have reviewed in detail the possibility of integration of ecosystems conceptualized using our ecosystemology approach within the new IUCN typology. The result of this analysis is being considered for a publication, and this Zenodo dataset would then be published in full (i.e. including all typology aspects) as supplementary materials. In the meantime, I would be happy to discuss any of these aspects with whoever is interested.</p> <p> </p> <p>4. Access to ecosystem data for conservation actors:</p> <p>Finally, the actual data (published here) on ecosystem-types, their names, synonymies, classification, distribution, and red list status are compiled into a format that we designed to be useful to conservation actors in the form of interactive webpages (produced with R as shiny apps). This development is based on very limited resources, and the author is still quite new to R, so any help or feedback on ways to improve the scripts would be very much welcomed.</p> <p>The interactive page is available here (currently filtered to Seychelles' data only, although the dataset contains data beyond the Seychelles): https://shiny.bio.gov.sc/bioeco/</p> <p>The R scripts are available on Github: https://github.com/bsenterre/ecosystemology</p> <p> </p> <p>5. Tables contained in this dataset:</p> <p>a. Ecosystem taxonomy tables:</p> <p>ecoSpecies: Contains the list of all ecosystem-type names with their unique identifier.</p> <p>ecoOccurrences: Contains the list of individual stand occurrences, including ecosystem characters as standardized in Senterre et al. (2021b; i.e. virtual ecosystem specimen).</p> <p>ecoSpeciesProfiles: Contains basic metadata on ecosystem-types, such as their Red List evaluations.</p> <p>ecoIdentifications: Contains all the different interpretations/identifications (referring to the table ecoSpecies or to higher levels of classification, see below) made on the stands observed in the ecoOccurrences table.</p> <p> </p> <p>b. Ecosystem typology tables (TO BE ADDED LATER):</p> <p>IUCNL3: This is just a transcription, as is, of the IUCN global typology version 2.1.</p> <p>IUCNL3BIOCrossover: This table defines and comments correspondences between BIOL2 (the level 2 of the typology used by us) and the IUCN typology L3 (level 3).</p> <p>BIOL2: This is a variation based on the IUCN typology, here our level 2.</p> <p>BIOL3: This is a variation based on the IUCN typology, here our level 3.</p> <p>BIOL4: This is a variation based on the IUCN typology, here our level 4.</p> <p>ecoGenus: This is a general type of stand (thus excluding any regional ecosystem connotation), defined at a local scale and never combined with any geographic connotation (see ecosystemology paper: Senterre et al. 2021b).</p> <p>ecoFamily: This is a generalized version of the ecoGenus (i.e. still excluding any regional, sub-regional or geographic aspect).</p> <p>ecoOrder: This is a further generalized version of the ecoGenus (see also Senterre et al. 2020).</p> <p>lifeZone: This is a basic and incomplete list of life zones as defined following the Holdridge (1967) approach, with some additional elements proposed in Senterre et al. (2021b).</p> <p> </p> <p>6. Literature cited:</p> <p>Holdridge, L. R. 1967. Life zone ecology. Tropical Science Center, San Jose, Costa Rica.</p> <p>Keith, D. A., J. R. Ferrer-Paris, E. Nicholson, M. J. Bishop, B. A. Polidoro, E. Ramirez-Llodra, M. G. Tozer, J. L. Nel, R. Mac Nally, E. J. Gregr, K. E. Watermeyer, F. Essl, D. Faber-Langendoen, J. Franklin, C. E. R. Lehmann, A. Etter, D. J. Roux, J. S. Stark, J. A. Rowland, N. A. Brummitt, U. C. Fernandez-Arcaya, I. M. Suthers, S. K. Wiser, I. Donohue, L. J. Jackson, R. T. Pennington, T. M. Iliffe, V. Gerovasileiou, P. Giller, B. J. Robson, N. Pettorelli, A. Andrade, A. Lindgaard, T. Tahvanainen, A. Terauds, M. A. Chadwick, N. J. Murray, J. Moat, P. Pliscoff, I. Zager, and R. T. Kingsford. 2022. A function-based typology for Earth’s ecosystems. . Nature 610:513–518. doi:10.1038/s41586-022-05318-4.</p> <p>Senterre, B. 2014. Mapping habitat-types within the Hummingbird site at Dugbe (Liberia, West Africa). Consultancy Report, Missouri Botanical Garden. P. 56. https://doi.org/10.13140/RG.2.2.32628.48003.</p> <p>Senterre, B. 2016. Habitat-type ground-truthing and assessment of ecosystem conservation value in the Bel Air Alufer mining site (Guinea, West Africa), with recommendations for improving the draft map of land cover types. Consultancy Report, Missouri Botanical Garden, A study conducted for Alufer Mining Limited. P. 54.</p> <p>Senterre, B., E. Bidault, and T. Stévart. 2019. Identification et évaluation des écosystèmes menacés du Mont Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 106. https://doi.org/10.13140/RG.2.2.13242.93129.</p> <p>Senterre, B., E. Bidault, T. Stévart, and P. P. Lowry II. 2020. Assessment of Key Biodiversity Areas in the Lofa-Gola-Mano & Nimba complexes (West Africa) using ecosystem criteria. Final Report, Missouri Botanical Garden. P. 146. 10.13140/RG.2.2.17934.89924.</p> <p>Senterre, B., E. Bidault, T. Stévart, M. Wagner, and P. Lowry. 2017. Mapping habitat-types in south-east Kouilou (Republic of Congo). Consultancy Report, Missouri Botanical Garden (MBG), Africa and Madagascar Department, St. Louis, Missouri, USA. P. 163.</p> <p>Senterre, B., R. M. Bristol, G. Gendron, and E. Henriette. 2021a. Fine-tuning conservation priorities in Seychelles at the landscape scale, using global KBA guidelines with both species and ecosystem criteria. Consultancy Report, United Nations Development Programme, GOS/UNDP/GEF Programme Coordination Unit, Victoria, Seychelles.</p> <p>Senterre, B., P. P. Lowry II, E. Bidault, and T. Stévart. 2021b. Ecosystemology: a new approach toward a taxonomy of ecosystems. . Ecological Complexity 47:100945. doi:https://doi.org/10.1016/j.ecocom.2021.100945.</p> <p>Senterre, B., A.-H. Paradis, E. Bidault, T. Stévart, and P. P. Lowry II. 2022. Qualité et distribution des savanes montagnardes du Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 73. http://dx.doi.org/10.13140/RG.2.2.13433.34401.</p> <p>Senterre, B., and M. Wagner. 2014. Mapping Seychelles habitat-types on Mahé, Praslin, Silhouette, La Digue and Curieuse. Consultancy Report, Government of Seychelles, United Nations Development Programme, Victoria, Seychelles. P. 119. https://doi.org/10.13140/RG.2.1.4558.6009.</p>
Linked collectors and determiners for: Revisiting the taxonomy and molecular systematics of Sesamia stemborers (Lepidoptera: Noctuidae: Apameini: Sesamiina): updated classification and comparative evaluation of species delimitation methods.
Natural history specimen data linked to collectors and determiners held within, "Revisiting the taxonomy and molecular systematics of Sesamia stemborers (Lepidoptera: Noctuidae: Apameini: Sesamiina): updated classification and comparative evaluation of species delimitation methods". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/0dedf555-acec-471d-a197-0a2cfe1a1329">https://bionomia.net/dataset/0dedf555-acec-471d-a197-0a2cfe1a1329</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/0dedf555-acec-471d-a197-0a2cfe1a1329">https://gbif.org/dataset/0dedf555-acec-471d-a197-0a2cfe1a1329</a>. Formatted as a Frictionless Data package.
Figs 83-88 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 83-88: Male terminalia. (83) Tarsostenodes tentus. (84) T. vesica. (85) Tarsostenus antehelvis. (86) T. bicolor. (87) T. hilaris. (88) T. univittatus.
Figs 71-82 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 71-82: Male terminalia. (71) Blackburniella apicula. (72) B. intricata. (73) Paratillus carus. (74) P. atali. (75) Tarsostenodes albonotatus. (76) T. cribripennis. (77) T. gibbus. (78) T. guttulus. (79) T. howensis. (80) T. leucogramma. (81) T. morulus. (82) T. simulator.
Figs 63-66 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 63-66: Habitus. (63) Tarsostenodes tentus. (64) T. vesica. (65) Tarsostenus antehelvis. (66) T. bicolor.
Figs 67-70 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 67-70: Habitus. (67) Tarsostenus hilaris. (68) T. kanak. (69) T. tricolor. (70) T. univittatus.
Figs 22-40 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 22-40: Pronota. (22) Paratillus carus. (23) Tarsostenodes cribripennis. (24) T. guttulus. (25) T. albonotatus. (26) Blackburniella apicula. (27) B. intricata. (28) Tarsostenodes simulator. (29) T. bullatus. (30) T. tentus. (31) T. gibbus. (32) T. leucogramma. (33) T. howensis. (34) T. vesica. (35) Tarsostenus hilaris. (36) Tarsostenus. univittatus. (37) T. morulus. (38) T. bicolor. (39) T. kanak. (40) Paratillus atali.
Figs 41-43 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 41-43: Various organs. 41-42 Pronota. (41) Tarsostenus tricolor. (42) T. antehelvis. 43 Elytron. T. bullatus.
Figs 2-21 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Figs 2-21: Antennae. (2) Paratillus carus. (3) Tarsostenus bicolor. (4) T. kanak. (5) Tarsostenodes tentus. (6) T. guttulus. (7) T. simulator. (8) Tarsostenus univittatus. (9) Tarsostenodes morulus. (10) Blackburniella intricata. (11) Tarsostenodes albonotatus. (12) T. gibbus. (13) T. leucogramma. (14) Tarsostenus antehelvis. (15) Blackburniella apicula. (16) Tarsostenus tricolor. (17) Paratillus atali. (18) Tarsostenodes vesica. (19) T. cribripennis. (20) Tarsostenus hilaris. (21) Tarsostenodes howensis.
Figure:1 Fish classification and taxonomy in Artificial Intelligence Applications in Fish Classification and Taxonomy: Advancing Our Understanding of Aquatic Biodiversity
Figure:1 Fish classification and taxonomy
Species abundance information improves sequence taxonomy classification accuracy - Qiita data
<p><a href="https://qiime2.org">QIIME 2</a> Artifacts containing microbiome samples, organised by EMPO 3 classification.</p> <p>Used to test <a href="https://library.qiime2.org/plugins/q2-clawback/">q2-clawback</a>.</p> <p>Downloaded from <a href="https://qiita.ucsd.edu">Qiita</a>. Draws from the following Qiita study ids:</p> <p>11113[1], 11444, 1716, 10369[2], 990[3], 2080, 1713, 894, 1289, 1883, 1673, 1288, 10353, 2192[4], 10323, 678, 1773, 662, 1799, 864, 1481, 1024[5], 1064, 2182, 10934, 1674, 1795[6], 10273, 10283[7], 10422[8], 804, 10308, 1056[9], 2382[5], 1240, 889, 1041, 1717, 1222, 11149, 11669, 807[10], 10245, 1711, 1721, 910, 1001, 895, 550[11], 1747[12], 713[13], 755, 861, 958[14], 11161[15], 11154[16], 945, 723, 1715, 1714, 10798.</p> <p>References<br> 1. Schulfer, A. F. et al. Nat Microbiol 3, 234–242 (2017).<br> 2. Ruhe, J. et al. Front Plant Sci 7 (2016).<br> 3. O'Brien, S. L. et al. Environ Microbiol 18, 2039–2051 (2016).<br> 4. Lax, S. et al. Science 345, 1048–1052 (2014).<br> 5. Zarraonaindia, I. et al. mBio 6 (2015).<br> 6. Navas-Molina, J. A. et al. in Methods Enzymol 371–444 (2013).<br> 7. Fang, X. et al. Front Microbiol 9 (2018).<br> 8. Tripathi, A. et al. mSystems 3 (2018).<br> 9. Delsuc, F. et al. Mol Ecol 23, 1301–1317 (2013).<br> 10. Gibbons, S. M. et al. PLoS ONE 9, e97435 (2014).<br> 11. Caporaso, J. G. et al. Genome Biol 12, R50 (2011).<br> 12. Hyde, E. R. et al. mSystems 1 (2016).<br> 13. Brazelton, W. J., Nelson, B. & Schrenk, M. O. Front Microbiol 2 (2012).<br> 14. Vitaglione, P. et al. Am J Clin Nutr 101, 251–261 (2014).<br> 15. Spirito, C. M., Marzilli, A. M. & Angenent, L. T. Environ Sci Technol 52, 13438–13447 (2018).<br> 16. Pham, V. T. H. et al. Sci Rep 7 (2017).</p>
Species abundance information improves sequence taxonomy classification accuracy - HMP and NCBI data
<p>Data used to test <a href="https://library.qiime2.org/plugins/q2-clawback/">q2-clawback</a> using taxonomic weights derived from shotgun sequencing experiments.</p> <p>Includes reference sequences and taxonomies derived from the NCBI RefSeq database[1] and paired amplicon and shotgun sequencing results downloaded from the Human Microbiome Project[2].</p> <p>References<br> 1. O’Leary, N. A. et al. en. Nucleic Acids Res. 44, D733–45 (2016).<br> 2. Huttenhower, C. et al. Nature 486, 207 (2012).</p>
Antipatterns in Software Classification Taxonomies - Data
<p>Embeddings for The Perils and Pitfalls of Classifying Software Systems paper</p>
Fig. 93 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 93: Geographic distribution of species as noted.
Fig. 92 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 92: Geographic distribution of Tarsostenodes guttulus.
Fig. 91 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 91: Geographic distribution of species as noted.
Fig. 90 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 90: Geographic distribution of Tarsostenodes simulator.
Fig. 50 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 50: Phylogenetic hypothesis of the species of the Tarsostenodes complex.
Fig. 1 in Classification, natural history, and evolution of Tarsosteninae (Coleoptera: Cleroidea: Cleridae). Part IV. Taxonomy of the Tarsostenodes complex of Australia, New Caledonia, New Guinea, and Tasmania
Fig. 1: Habitus of Tarsostenodes cribripennis.
A benchmark Arabic dataset for question classification with AAFAQ taxonomy
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