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131 results for “species-richness”
Data from: A pre-Miocene Irano-Turanian cradle: origin and diversification of the species-rich monocot genus Gagea (Liliaceae)
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Data from: Genetic diversity is largely unpredictable but scales with museum occurrences in a species-rich clade of Australian lizards
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Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes
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Figure 3 in Prospects for using DNA barcoding to identify spiders in species-rich genera
Figure 3. Bar graph with standard errors showing the differences in mean (in black) and maximum (in grey) intraspecific divergence as well as nearest-neighbor distance (in white) between the three geographical distribution categories.
Data from: Legume phylogeny and classification in the 21st century: progress, prospects and lessons for other species-rich clades
The Leguminosae, the third-largest angiosperm family, has a global distribution and high ecological and economic importance. We examine how the legume systematic research community might join forces to produce a comprehensive phylogenetic estimate for the ca. 751 genera and ca. 19,500 species of legumes and then translate it into a phylogeny-based classification. We review the current state of knowledge of legume phylogeny and highlight where problems lie, for example in taxon sampling and phylogenetic resolution. We review approaches from bioinformatics and next-generation sequencing, which can facilitate the production of better phylogenetic estimates. Finally, we examine how morphology can be incorporated into legume phylogeny to address issues in comparative biology and classification. Our goal is to stimulate the research needed to improve our knowledge of legume phylogeny and evolution; the approaches that we discuss may also be relevant to other species-rich angiosperm clades.
FIGURE 2 in Iguanian species-richness in the Andes of boreal Patagonia: Evidence for an additional new Liolaemus lizard from Argentina lacking precloacal glands (Iguania, Liolaeminae)
FIGURE 2. Male (a) and female (b) of Liolaemus tregenzai in life.
Supplementary material 2 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Molecular phylogeny of Garcinia L. based on psbM-trnD and Bayesian inference
Figure 1 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Figure 1 Some Garcinia New Caledonian species (except E from Fiji) and morphological features AG. balansae (Munzinger 4916), fruiting branch BG. balansae (Munzinger 4916), bark CG. sp. "JT814" (Munzinger 7282), habit DG. sp. "JT814" (Munzinger 7282), bark EG. vitiensis (Munzinger 7377), fruiting branch FG. neglecta (Munzinger 2690), fruit GG. comptonii (sin voucher), fruit.
Figure 3 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Figure 3 Molecular phylogeny of Garcinia L. based on a combined chloroplast DNA dataset and Bayesian inference. Posterior probabilities (PP) and bootstrap support values (BS), obtained respectively by the Bayesian inference and Maximum Likelihood (ML) analysis, are indicated at each node of the cladogram. Nodes were collapsed when PP < 0.50. The lineages/sections discussed in the text are highlighted, and species names appear in colors depending on their native distribution areas: light green, Tropical Africa; dark green, Madagascar and Western Indian Ocean islands; grey, Southeast Asia; purple, Australia; orange, New Guinea; red, New Caledonia; dark blue, Southwest Pacific islands. Distribution information was taken from the Plants of the World Online website (POWO 2023; also see the table of vouchers). A few species occur in several regions, and the color of the main (largest) region was used. All accessions were newly sequenced in this study.
Supplementary material 1 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
List of taxa and accessions used in this study
Figure 2 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Figure 2 Molecular phylogeny of Garcinia L. based on ITS sequences and Bayesian inference. Posterior probabilities (PP) and bootstrap support values (BS), obtained respectively by the Bayesian inference and Maximum Likelihood (ML) analysis, are indicated at each node of the cladogram. Nodes were collapsed when PP < 0.50. The lineages/sections discussed in the text are highlighted, and species names appear in colors depending on their native distribution areas: light blue, Central and South America; light green, Tropical Africa; dark green, Madagascar and Western Indian Ocean islands; grey, Southeast Asia; purple, Australia; orange, New Guinea; red, New Caledonia; dark blue, Southwest Pacific islands. Distribution information was taken from the Plants of the World Online website (POWO 2023; also see the table of vouchers). A few species occur in several regions, and the color of the main (largest) geographic region was used. Accessions in bold were newly sequenced in this study.
Supplementary material 4 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Molecular phylogeny of Garcinia L. based on rps16-trnK and Bayesian inference
Supplementary material 3 from: Gaudeul M, Sweeney P, Munzinger J (2024) An updated infrageneric classification of the pantropical species-rich genus Garcinia L. (Clusiaceae) and some insights into the systematics of New Caledonian species, based on molecular and morphological evidence. PhytoKeys 239: 73-105. https://doi.org/10.3897/phytokeys.239.112563
Molecular phylogeny of Garcinia L. based on trnQ-rps16 and Bayesian inference
Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers
<p>This data set was sampled and used for the following publication:<br>Popp, M.R., Kalwij, J.M. Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers. Sci Rep 13, 13892 (2023). http://dx.doi.org/10.1038/s41598-023-40989-7.</p> <p>The data set contains RGB orthomosaics sampled via a DJI Phantom 4 Pro at approx. 1.2 cm GSD in the folder /out.<br>Folder /shp contains subfolders that hold shapefiles delineating tree crowns by species as polygons. Species names are given in SpeciesList.csv. Encoding of the values for species/groups of species used in the study to consecutive integers can be found in class_encoding.csv.</p>
Reproductive character displacement and potential underlying drivers in a species-rich and florally diverse lineage of tropical angiosperms (Ruellia; Acanthaceae)
Reproductive character displacement is a pattern whereby sympatric lineages diverge more in reproductive character morphology than allopatric lineages. This pattern has been observed in many plant species, but comparably few have sought to disentangle underlying mechanisms. Here, in a diverse lineage of Neotropical plants (Ruellia; Acanthaceae), we present evidence of reproductive character displacement in a macroevolutionary framework (i.e., among species) and document mechanistic underpinnings. In a series of inter-specific hand pollinations in a controlled glasshouse environment, we found that crosses between species that differed more in overall flower size, particularly in style length, were significantly less likely to produce viable seeds. Further, species pairs that failed to set seed were more likely to have sympatric distributions in nature. Competition for pollinators and reinforcement to avoid costly inter-specific mating could both result in these patterns and are not mutually exclusive processes. Our results add to growing evidence that reproductive character displacement contributes to exceptional floral diversity of angiosperms.
Figure 3 from: Zumstein P, Bruelheide H, Fichtner A, Schuldt A, Staab M, Härdtle W, Zhou H, Assmann T (2021) What shapes ground beetle assemblages in a tree species-rich subtropical forest? In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 907-927. https://doi.org/10.3897/zookeys.1044.63803
Figure 3 Relationships between ground beetle biomass and canopy cover (A) and herb cover (B). Black lines indicate significant relationships at p < 0.05 obtained from mixed-effects models (keeping other significant predictors fixed at their means) with grey areas indicating the 95% confidence intervals. Points (slightly jittered to improve visibility) represent observed values per trap. The fixed-effects explained 30% of the variation in ground beetle biomass.
Figure 4 from: Zumstein P, Bruelheide H, Fichtner A, Schuldt A, Staab M, Härdtle W, Zhou H, Assmann T (2021) What shapes ground beetle assemblages in a tree species-rich subtropical forest? In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 907-927. https://doi.org/10.3897/zookeys.1044.63803
Figure 4 Representatives of ground beetles from pitfall traps and flight interception traps in Gutianshan NP ACarabus kiukiangensisBCarabus davidisCLioptera erotyloidesDTricondyla macrodera.
Figure 2 from: Zumstein P, Bruelheide H, Fichtner A, Schuldt A, Staab M, Härdtle W, Zhou H, Assmann T (2021) What shapes ground beetle assemblages in a tree species-rich subtropical forest? In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 907-927. https://doi.org/10.3897/zookeys.1044.63803
Figure 2 Relationships between ground beetle species richness and canopy cover (A) and herb cover (B). Black lines indicate significant relationships at p < 0.05 obtained from mixed-effects models (keeping other significant predictors fixed at their means) with grey areas indicating the 95% confidence intervals. Points represent observed values per trap. Note that some traps had similar richness and predictor values. The fixed-effects explained 12% of the variation in ground beetle species richness.
Figure 1 from: Zumstein P, Bruelheide H, Fichtner A, Schuldt A, Staab M, Härdtle W, Zhou H, Assmann T (2021) What shapes ground beetle assemblages in a tree species-rich subtropical forest? In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 907-927. https://doi.org/10.3897/zookeys.1044.63803
Figure 1 Relationships between ground beetle abundance and canopy cover (A), herb cover (B) and pH-value of the soil (C). Black lines indicate significant relationships at p < 0.05 obtained from mixed-effects models (keeping other significant predictors fixed at their means) with grey areas indicating the 95% confidence intervals. Points represent observed values per trap. Note that some traps had similar abundance and predictor values. The fixed-effects explained 22% of the variation in ground beetle abundance.
Figure 1 from: Dole SA, Hulcr J, Cognato AI (2021) Species-rich bark and ambrosia beetle fauna (Coleoptera, Curculionidae, Scolytinae) of the Ecuadorian Amazonian Forest Canopy. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 797-813. https://doi.org/10.3897/zookeys.1044.57849
Figure 1 A species accumulation curves for Onkone Gare B species accumulation curves for Tiputini C species richness estimators for Onkone Gare D species richness estimators for Tiputini E species accumulation curves for both sites combined F species richness estimators for both sites combined.
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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.