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1,445 results for “species richness.”
Species richness and abundance of vascular epiphytes along an elevation gradient
<p>Because of the difficulty in sampling and the logistics of identifying canopy-dwelling plants, the number of inventories quantifying tropical epiphytes is limited. This has resulted in a substantial gap in knowledge, even though forest canopies contain significant biodiversity and forest biomass. In the case of Volcán Maderas, multiple ecological and taxonomic research initiatives have been conducted. However, for vascular epiphytes, georeferenced specific spatial descriptions were lacking and a standardized effort for documenting species richness was non-existent. We provide a detailed qualitative and quantitative assessment of the vascular epiphyte flora and its spatial distribution. These data shed light on important plant assemblages across elevational gradients that can be used for monitoring and understanding adaptive strategies to drought conditions.</p>
Figure 3 in Abundance, species richness and diversity of the orb-weaving spider families Araneidae, Nephilidae and Tetragnathidae in natural habitats in Trinidad, West Indies
Figure 3. The absence of a relationship between mean niche breadth of species and observed species richness at a locality, for 46 localities with natural habitats; r = −0.12, P = 0.42.
Figure 2 in Abundance, species richness and diversity of the orb-weaving spider families Araneidae, Nephilidae and Tetragnathidae in natural habitats in Trinidad, West Indies
Figure 2. The weak relationship between observed species richness and abundance of individuals in the sample, for 46 localities with natural habitats; r = 0.45, P = 0.002.
Data from: Assessing species richness trends: declines of bees and bumblebees in the Netherlands since 1945.
Estimating and predicting temporal trends in species richness is of general importance, but notably difficult because detection probabilities of species are imperfect and many datasets were collected in an opportunistic manner. We need to improve our capabilities to assess richness trends using datasets collected in unstandardized procedures with potential collection bias. Two methods are proposed and applied to estimate richness change, which both incorporate models for sampling effects and detection probability: (1) non-linear species accumulation curves with an error variance model and (2) Pradel capture-recapture models. The methods are used to assess nationwide temporal trends (1945-2018) in the species richness of wild bees in the Netherlands. Previously, a decelerating decline in wild bee species richness was inferred for part of this dataset. Among the species accumulation curves, those with non-constant changes in species richness are preferred. However, when analysing data subsets, constant changes became selected for non-Bombus bees (for samples in collections) and bumblebees (for spatial grid cells sampled in three periods). Smaller richness declines are predicted for non-Bombus bees than bumblebees. However, when relative losses are calculated from confidence intervals limits, they overlap and touch zero loss. Capture-recapture analysis applied to species encounter histories infers a constant colonization rate per year and constant local species survival for bumblebees and other bees. This approach predicts a 6% reduction in non-Bombus species richness from 1945 to 2018 and a significant 19% reduction for bumblebees. Statistical modelling to detect species richness time trends should be systematically complemented with model checking and simulations to interpret the results. Data inspection, assessing model selection bias and comparisons of trends in data subsets were essential model checking strategies in this analysis. Opportunistic data will not satisfy the assumptions of most models and this should be kept in mind throughout.
Supplementary material 2 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Table S2. Specimen data used in the DNA barcoding analyses
Supplementary material 3 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Checklist and nomenclatural summary of the Japanese species of Enicospilus
Figure 9 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 9 Enicospilus abdominalis (Szépligeti, 1906) ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
Figure 8 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 8 Intraspecific variation of the body colour in E. shikokuensis (Uchida, 1928) A paler (SEN42) B darker (SEN41) individuals.
Figure 7 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 7 Intraspecific variation of the fore wing sclerite development in E. shikokuensis (Uchida, 1928) A the proximal and distal sclerites separated and the central sclerite weak (SEN42) B the proximal and distal sclerites confluent and the central sclerite strong (SEN41).
Supplementary material 1 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Table S1. Specimens examined
Figure 58 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 58 Heat maps of regional patterns A number of specimens B number of sampling events C number of collectors D number of species.
Figure 56 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 56 Individual-based extrapolated species accumulation curve, comparing each zone rarefied to 2,000 individuals (LR = latitudinal ranges).
Figure 59 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 59 Individual-based species accumulation curve, comparing the observed and estimated numbers of Enicospilus species in Japan, based on ACE and Chao 1 estimators.
Figure 6 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 6 Bayesian majority-rule consensus tree based on a barcoding gene (BIPP = the Bayesian inference posterior probabilities; MLBS = the maximum likelihood bootstrap percentages).
Figure 57 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 57 Latitudinal pattern of Enicospilus species richness across Japan. Coloured bars indicate observed species number and extended non-coloured bars indicate saturation species richness, estimated by individual-based extrapolation methods based on Chao1 richness estimator in EstimateS v.9.1.0 software application. Enicospilus species richness across Japan significantly decreases towards the north (Spearman's rank correlation coefficient = -0.89, p-value = 0.03).
Figure 55 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 55 Enicospilus zeugos Chiu, 1954, stat. rev. ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
Figure 53 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 53 Enicospilus yezoensis (Uchida, 1928) ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
Figure 54 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 54 Enicospilus yonezawanus (Uchida, 1928) ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
Figure 51 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 51 Enicospilus vestigator (Smith, 1858) ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
Figure 52 from: Shimizu S, Broad GR, Maeto K (2020) Integrative taxonomy and analysis of species richness patterns of nocturnal Darwin wasps of the genus Enicospilus Stephens (Hymenoptera, Ichneumonidae, Ophioninae) in Japan. ZooKeys 990: 1-144. https://doi.org/10.3897/zookeys.990.55542
Figure 52 Enicospilus xanthocephalus Cameron, 1905 ♀ from Japan A habitus B head, frontal view C head, dorsal view D head, lateral view E mesosoma, lateral view F central part of fore wing.
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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.