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1,445 results for “species richness.”
Fig 1 in Quantifying zooplankton species: use of richness estimators
Fig 1. Sampling stations in the Hydroelectric Power Plant of Furnas reservoir, state of Minas Gerais, Brazil (A, Barranco Alto region; B, junction of rivers Verde and Sapucai - VSJ).
Fig. 5 in Quantifying zooplankton species: use of richness estimators
Fig. 5. Species accumulation curves, uniques and duplicates for the BA2 station of Furnas reservoir, state of Minas Gerais, Brazil from March 2011 to February 2012.
Fig. 3 in Quantifying zooplankton species: use of richness estimators
Fig. 3. Species accumulation curves, uniques and duplicates for the VSJ station in Furnas reservoir, state of Minas Gerais, Brazil, collected with vertical hauls.
Fig. 1. The Chao 1 in Estimating fossil ant species richness in Eocene Baltic amber
Fig. 1. The Chao 1 (top line) and ACE (bottom line) richness estimates computed using Colwell (2013); note the slightly lower ACE.
Linked collectors and determiners for: Species-richness in Neotropical Sericothripinae (Thysanoptera: Thripidae).
Natural history specimen data linked to collectors and determiners held within, "Species-richness in Neotropical Sericothripinae (Thysanoptera: Thripidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/e369a54d-eaac-4bda-97c6-00b28be9b359">https://bionomia.net/dataset/e369a54d-eaac-4bda-97c6-00b28be9b359</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/e369a54d-eaac-4bda-97c6-00b28be9b359">https://gbif.org/dataset/e369a54d-eaac-4bda-97c6-00b28be9b359</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: The genus Manota Williston (Diptera: Mycetophilidae) in Peruvian Amazonia, with description of sixteen new species and notes on local species richness.
Natural history specimen data linked to collectors and determiners held within, "The genus Manota Williston (Diptera: Mycetophilidae) in Peruvian Amazonia, with description of sixteen new species and notes on local species richness". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/276af928-cd8d-48ae-b5e9-0b673cc0f76f">https://bionomia.net/dataset/276af928-cd8d-48ae-b5e9-0b673cc0f76f</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/276af928-cd8d-48ae-b5e9-0b673cc0f76f">https://gbif.org/dataset/276af928-cd8d-48ae-b5e9-0b673cc0f76f</a>. Formatted as a Frictionless Data package.
Data for "Species richness and food-web structure jointly drive community biomass and its temporal stability in fish communities"
<p>Data for the paper "Species richness and food-web structure jointly drive community biomass and its temporal stability in fish communities" which is in minor revision in Ecology Letters (manuscript id:ELE-00589-2021.R1). A doi will be provided upon publication.</p> <p>Current citation: Danet, A., Mouchet, M., Bonnaffé, W., Thébault, E., & Fontaine, C. (In revision) Species<br> richness and food-web structure jointly drive total biomass and its temporal stability in<br> fish communities Minor revision in Ecology Letters.</p> <p>The repository constains data describing fish community monitoring across stream sections in metropolitan France over the period 1995-2018 by the French Office of Water and Aquatic Ecosystems (ONEMA) using electrofishing.</p> <p>The repository contains:</p> <ul> <li> description of fishing: fishing_protocol.csv <ul> <li>surface: sampled surface</li> <li>opcod: fishing operation code, a unique identifier for each sampling event</li> <li>station: unique identifier for each site</li> <li>nb_sp, nb_ind: number of species, number of individuals</li> </ul> </li> <li>geographical information: station_basin.csv <ul> <li>X, Y: spatial coordinates of the station, expressed in metres in Lambert93 (epsg:2154)</li> <li>basin: name of the hydrographic basin</li> </ul> </li> <li>environment: environment.csv ( _mean: mean, _med: median, _cv: coefficient of variation) <ul> <li>alt: altitude</li> <li>d_source: distance to source</li> <li>strahler: strahler order</li> <li>BOD: Biological Oxygen Demand</li> <li>temperature: water temperature</li> <li>flow: water flow</li> </ul> </li> <li>community data: community_data.csv <ul> <li>species: three digits code corresponding to a given species (see Table S1, Danet et al. in revision)</li> <li>nind: number of individuals</li> <li>biomass: biomass in gram</li> </ul> </li> <li>Length of each fish individual: fish_length.csv <ul> <li>length: length of the fish in millimeter</li> </ul> </li> <li>Inferred food-web: class_network.rda <ul> <li>data: <ul> <li>class_id: size class of a fish individual</li> </ul> </li> <li>network: these data.frame can be handled by igraph::graph_from_data_frame() <ul> <li>from, to: "to" eats "from"</li> </ul> </li> <li>composition: <ul> <li>sp_class: concatenation of species and class_id columns</li> <li>bm_std: biomass reported to the sampled surface</li> </ul> </li> </ul> </li> </ul> <p> </p> <p> </p>
Figure 2 in Spiders (Arachnida: Araneae) of Saba Island, Lesser Antilles: Unusually high species richness indicates the Caribbean Biodiversity Hotspot is woefully undersampled
Figure 2. Spider species richness by island area showing dramatic undersampling of most islands and lack of expected positive species-area relationship. Islands are ordered by size from smaller to larger as follows: Saba, Nevis, St. Kitts, Antigua, Grenada, Turks and Caicos, Barbados. See text for data sources.
Figure 1 in Spiders (Arachnida: Araneae) of Saba Island, Lesser Antilles: Unusually high species richness indicates the Caribbean Biodiversity Hotspot is woefully undersampled
Figure 1. Saba Island (17o38'N, 63o14'W), Lesser Antilles. Thirty-three collection sites mapped using Google Earth. Numbers correspond to sites listed in Table 1.
Midpoint attractor models resolve the mid-elevation peak in Himalayan plant species richness
<p>The midpoint attractor models (MPA) of species richness integrate a unimodal environmental favourability gradient and neutral effects forced by geometric constraints and thus extend ecologically neutral mid-domain model. However, both alternative MPA algorithms assume that underlying environmental favourability peaks within the modeling domain. Here, we used elevational distribution data for 1054 plant species occurring in NW Himalaya to explore species richness gradients and MPA performance in species groups defined by biogeography, taxonomy and life form. MPA models achieved an excellent fit, but the two MPA algorithms produced contrasting estimates of midpoint attractor location, especially for species groups with richness originating in lowlands. Therefore, we propose a modification of the MPA model accounting for the environmental favourability peak outside the study domain to reflect these situations. Biogeographic origin was more decisive for midpoint attractor location than taxonomic or life-form classification, indicating relatively low climatic niche conservatism in plants.</p>
FIG. 5 in Two new species of the genus Benthamia A. Rich. (Orchidaceae) from Madagascar, B. boiteaui Hervouet, sp. nov. and B. bosseri Hervouet, sp. nov.
FIG. 5. — Vegetation and granite outcrops near the summit of Ambondrombe (9.III.2009). Photograph by Jean-Michel Hervouet.
FIG. 3 in Two new species of the genus Benthamia A. Rich. (Orchidaceae) from Madagascar, B. boiteaui Hervouet, sp. nov. and B. bosseri Hervouet, sp. nov.
FIG. 3. — Benthamia bosseri Hervouet, sp. nov.: A, habit (after wild specimen); B, flower (Boiteau 4634); C, side view of flower; D, exploded view of perianth. Scale bars: A, 50 mm; B, 3 mm; C, 2 mm; D, 4 mm. Drawing by Alain Jouy.
FIG. 4 in Two new species of the genus Benthamia A. Rich. (Orchidaceae) from Madagascar, B. boiteaui Hervouet, sp. nov. and B. bosseri Hervouet, sp. nov.
FIG. 4. — Benthamia bosseri Hervouet,sp. nov.: typical arched spike with pendent second flowers. Summit of Ambondrombe (9.III.2009). Photograph by Jean-Michel Hervouet.
FIG. 2 in Two new species of the genus Benthamia A. Rich. (Orchidaceae) from Madagascar, B. boiteaui Hervouet, sp. nov. and B. bosseri Hervouet, sp. nov.
FIG. 2. — Benthamia boiteaui Hervouet, sp. nov.: spike of a wild specimen at the summit of Ambondrombe (9.III.2009). Photograph by Jean-Michel Hervouet.
FIG. 1 in Two new species of the genus Benthamia A. Rich. (Orchidaceae) from Madagascar, B. boiteaui Hervouet, sp. nov. and B. bosseri Hervouet, sp. nov.
FIG. 1. — Benthamia boiteaui Hervouet, sp. nov.: A, habit (after wild specimen); B, flower (Boiteau 4621); C, side view of flower; D, exploded view of perianth. Scale bars: A, 50 mm; B, 2 mm; C, D, 3 mm. Drawing by Alain Jouy.
Fig. 2 in The Latitudinal Distribution Of Sphingid Species Richness In Continental Southeast Asia: What Causes The Biodiversity 'Hot Spot' In Northern Thailand?
Fig. 2. Estimated local species richness (ACE) from nine quantitative light trapping sites. Fisher's α, an alternative measure of local diversity (not shown), is lowest at the Malaysian sites (α = 7–13) and highest at a montane site in Northwestern Thailand (α = 30), whereas the Vietnam sample and other Thai sites score intermediately (α = 11–21).
Fig. 1. A in The Latitudinal Distribution Of Sphingid Species Richness In Continental Southeast Asia: What Causes The Biodiversity 'Hot Spot' In Northern Thailand?
Fig. 1. A, Estimated species richness (simplified from Beck & Kitching, 2004); B, Sampling intensity (kernels of original distribution records, smoothed; software by Hooge et al., 1999); C, altitudinal zonation (from digital elevation model, http://www.ngdc.noaa.gov/mgg/global/ seltopo.html). Elevation classes are [m]: 0–500 (white), 501–1000, 1001–1500, 1501–2000,>2001 (black); D, Landscape types (simplified from remote sensing data, http://www-gvm.jrc.it/glc2000). Agricultural and highly disturbed areas are printed in light grey, mosaic and bush in dark grey and closed forests in black.
Fig. 3 in The Latitudinal Distribution Of Sphingid Species Richness In Continental Southeast Asia: What Causes The Biodiversity 'Hot Spot' In Northern Thailand?
Fig. 3. Abundance (number of species, y-axis) and the latitudinal mean of their range in four regions. Black bars indicate the approximate latitudinal extend of the regions under investigation.
Fig. 1 in Sampling effort and fish species richness in small terra firme forest streams of central Amazonia, Brazil
Fig. 1. Fish species accumulation curves estimated from samples obtained in 1st, 2nd, and 3rd order streams reaches located in the study areas of Biological Dynamics of Forest Fragments Project, Manaus, Amazonas State. The curves represent extrapolations from five reaches sampled in each stream segment.
Fig. 5. Estimated species richness E in Spatial and temporal variation of benthic fish assemblages during the extreme drought of 1997-98 (El Niño) in the middle rio Negro, Amazonia, Brazil
Fig. 5. Estimated species richness E(Sn) by strata at rio Negro (a-Sep, b-Nov 1997 and c-Feb 1998) and rio Branco (d-Sep
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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.