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1,445 results for “species richness.”

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zenodo40/100

Fig. 7 in Scorpions of the Brandberg Massif, Namibia: Species richness inversely correlated with altitude

Fig. 7. Brandberg Massif (Namibia), just below summit of Massif in Goaseb (Ga-Asab) Gorge, facing south to gravel plains, dry year. Rocky slopes, habitat of Brandbergia haringtoni Prendini, 2003, Hadogenes tityrus (Simon, 1888) and Uroplectes planimanus (Karsch, 1879).

opencc-by-4.0Dec 2008View details →
zenodo40/100

Fig. 6 in Scorpions of the Brandberg Massif, Namibia: Species richness inversely correlated with altitude

Fig. 6. Brandberg Massif (Namibia), upper slopes of Massif in Goaseb (Ga-Asab) Gorge, facing northeast, wet year. Dominant vegetation, Cyphostemma currorii (Hook.f.) Desc. and Ozoroa crassinervia (Engl.) R. Fern & A. Fern. Rocky slopes, habitat of Brandbergia haringtoni Prendini, 2003, Lisposoma elegans Lawrence, 1928, Hadogenes tityrus (Simon, 1888), and Uroplectes planimanus (Karsch, 1879). Woody vegetation, habitat of Uroplectes otjimbinguensis (Karsch, 1879).

opencc-by-4.0Dec 2008View details →
zenodo40/100

Fig. 8 in Scorpions of the Brandberg Massif, Namibia: Species richness inversely correlated with altitude

Fig. 8. Brandberg Massif (Namibia), Wasserfallfläche, plateau on summit of Massif, facing southwest, wet year. Dominant vegetation, Boscia albitrunca (Burch.) Gilg & Gilg-Ben., Cyphostemma currorii (Hook.f.) Desc. and Euphorbia sp. Rocky flats and slopes, habitat of Lisposoma elegans Lawrence, 1928, Hadogenes tityrus (Simon, 1888) and Uroplectes planimanus (Karsch, 1879). Sandy flats, habitat of Parabuthus brevimanus (Thorell, 1876) and Opistophthalmus carinatus (Peters, 1861). Woody vegetation, habitat of Uroplectes otjimbinguensis (Karsch, 1879).

opencc-by-4.0Dec 2008View details →
zenodo40/100

Fig. 27 in Terrestrial mollusc species richness and diversity in Omo Forest Reserve, Ogun State, Nigeria

Fig. 27. Sample-based species accumulation curves for terrestrial molluscs in Omo Forest Reserve, Ogun State, Nigeria. Plotted values are means based on 100 randomisations of sample accumulation order (without replacement). Solid line, species observed; dashed lines, 95 % confidence limit.

opencc-by-4.0Apr 2013View details →
zenodo40/100

Figs 23–26 in Terrestrial mollusc species richness and diversity in Omo Forest Reserve, Ogun State, Nigeria

Figs 23–26. (23–25) Urocyclidae: (23) Thapsia oscitans, H 8.8 mm; (24) Trochozonites talcosus, H 8.3 mm; (25) Trochozonites adansoniae, H 6.3 mm; (26) Aillyidae, Aillya camerunensis, H 4.4 mm. Scale bars = 5 mm (Figs 23–25) and 1 mm (Fig 26).

opencc-by-4.0Apr 2013View details →
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Figs 13–22 in Terrestrial mollusc species richness and diversity in Omo Forest Reserve, Ogun State, Nigeria

Figs 13–22. Streptaxidae: (13) Gonaxis camerunensis, H 9 mm; (14) Ptychotrema okei, H 9.9 mm; (15) Ptychotrema sp., H 9.8 mm; (16) Ptychotrema shagamuense, H 15.8 mm; (17) Gulella monodon, H 6.48 mm; (18) Gulella reesi, H 5.92 mm; (19) Gulella io, H 3.64 mm; (20) Gulella jongkindi, H 4.08 mm; (21) Gulella cf. opoboensis, H 3.24 mm; (22) Tomostele musaecola, H 3.84 mm. Scale bars = 5 mm (Figs 13–16) and 1 mm (Figs 17–22).

opencc-by-4.0Apr 2013View details →
dryad40/100

Patterns of species richness and turnover in endemic amphibians of the Guineo-Congolian rainforest

<p><strong>Aim</strong>: The African Guineo-Congolian (GC) region is a global biodiversity hotspot with high species endemism, bioclimatic heterogeneity, complex landscape features, and multiple biogeographic barriers. Bioclimatic and geographic variables influence global patterns of species richness and endemism, but their relative importance varies across taxa and regions and is poorly understood for many faunas. We characterized patterns of richness and turnover in endemic amphibians of the GC biodiversity hotspot and evaluated the relative roles of geographic distance and bioclimatic variables in predicting turnover. </p> <p><strong>Location</strong>: West and Central Africa. </p> <p><strong>Major taxa studied</strong>: Amphibians</p> <p><strong>Methods</strong>: We compiled species-occurrence records via field sampling, online databases, and taxonomic literature. Our study used 1205 unique georeferenced records of 222 amphibian species endemic to the GC region. Patterns of species richness were mapped onto a grid with a spatial resolution of 0.5° × 0.5°. We estimated weighted endemism and tested whether endemism was higher than the expected species richness (randomization test). We quantified species turnover using generalized dissimilarity modelling to evaluate the processes underlying observed patterns of species richness in GC endemic amphibians. We explored bioregionalization using agglomerative hierarchical clustering based on the unweighted pair group method with arithmetic averages. </p> <p><strong>Results</strong>: We identified six areas within the lower GC region – forests in Southern Nigeria, Cameroon, Equatorial Guinea, Gabon, Republic of Congo, and Democratic Republic of Congo – as having high species richness of endemic amphibians. The randomization test returned four major areas of significant weighted endemism: Nigeria-Cameroon mountains, forest regions of the Democratic Republic of Congo, Cote d'Ivoire, and Ghana. Our analysis revealed five bioregions for amphibian endemism, four of which were located within the lower Guineo-Congolian forest. Species turnover was strongly related to the geographic distance between grid cells; contributing bioclimatic variables included precipitation of the warmest quarter, mean temperature of the wettest quarter, and mean diurnal temperature range.  </p> <p><strong>Main conclusions</strong>: Our results indicate that geographic distance between grid cells is the primary determinant of turnover in GC endemic amphibians, with secondary but significant effects of rainfall- and temperature-related variables. Our results identify key areas of endemic amphibian richness that could be prioritized for conservation actions.</p>

opencc-zeroMay 2023View details →
zenodo40/100

Figures 2–5 in One size doesn′t fit all: Singularities in bat species richness and activity patterns in wind-energy complexes in Brazil and implications for environmental assessment

Figures 2–5. Bat activity based on the pooled number of echolocation pulses per hour in four wind-energy complexes in northeastern Brazil, from September 2015 to January 2017: (2) Curva dos Ventos, municipality of Caetité, state of Bahia; (3) Cristal, municipality of Morro do Chapéu, state of Bahia; (4) Modelo, municipality of João Câmara, state of Rio Grande do Norte; (5) Fonte dos Ventos, municipality of Tacaratu, state of Pernambuco.

opencc-by-4.0Apr 2022View details →
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Figure 1 in One size doesn′t fit all: Singularities in bat species richness and activity patterns in wind-energy complexes in Brazil and implications for environmental assessment

Figure 1. Wind-energy complexes in northeastern Brazil studied for the presence and activity of insectivorous bats from September 2015 to January 2017.

opencc-by-4.0Apr 2022View details →
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FIGURE 3 in Inferring global species richness from megatransect data and undetected species estimates

FIGURE 3 Latitudinal distribution of currently valid species of Pholcidae. Numbers of Pholci- dae species (x-axis) known from different latitudes (y-axis; N, north; S, south), with the land mass distribution shown in grey (from www.ecoclimax.com; excluding Antarctica). Pholcidae species richness is slightly shifted towards the north, possibly as a result of the unbalanced land masses and/or taxonomists' biases, but most diversity is in tropical regions.

opencc-by-4.0May 2019View details →
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FIGURE 2 in Inferring global species richness from megatransect data and undetected species estimates

FIGURE 2 Cumulative percentages of new species (y-axis) as a function of cumulative field days (x-axis) (left) and cumulative number of total (upper/blue line) and new (lower/red line) species (y-axis) as a function of culumative field days (x-axis) (right), for the three major tropical megatransects shown on the map. Each green dot represents a sampling locality. For raw data of all geographic regions, see supplementary tables S1–S5.

opencc-by-4.0May 2019View details →
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FIGURE 1 in Inferring global species richness from megatransect data and undetected species estimates

FIGURE 1 Cumulative curve of currently valid species of Pholcidae (y-axis) as a function of time (x-axis). The curve suggests that we are far from approaching a complete taxonomic knowledge of the family.

opencc-by-4.0May 2019View details →
dryad40/100

Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness

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publicSep 2025View details →
dryad40/100

Data from: Species richness and evenness of European bird communities show differentiated responses to measures of productivity

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publicMay 2024View details →
dryad40/100

Environmental controls on butterfly occurrence and species richness in Israel: The importance of temperature over rainfall

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publicJul 2022View details →
dryad40/100

Patterns of functional diversity along latitudinal gradients of species richness in eleven fish families

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publicDec 2022View details →
dryad40/100

Midpoint attractor models resolve the mid-elevation peak in Himalayan plant species richness

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publicSep 2021View details →
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Species richness: a pivotal factor mediating the effects of land use intensification and climate on grassland multifunctionality

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publicMar 2024View details →
dryad40/100

Data from: An effective method for ecosystem-scale manipulation of bird abundance and species richness

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publicOct 2019View details →
dryad40/100

Patterns of species richness and turnover in endemic amphibians of the Guineo-Congolian rainforest

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publicMay 2023View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record