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124 results for “distributed sampling”
Biases and distribution patterns in hard-bodied microscopic animals (Acari: Halacaridae): Size doesn't matter, but generalism and sampling effort do
<span>Aim</span> <p><span>The interplay between distribution ranges, species traits, and sampling and taxonomic biases remain elusive amongst microscopic animals. This ignorance obscures our understanding of the diversity patterns of a major component of biodiversity. Here, we used marine Halacaridae to explore whether differences between marine provinces can explain their distribution patterns or if differential sampling efforts across regions prevent any macroecological inference. Furthermore, we test if certain functional traits influence their distribution patterns.</span></p> <span>Location</span> <p><span>Europe.</span></p> <span>Results</span> <p><span>Whereas geographical variables provided a better explanation for differences in species composition, sampling effort and distance from marine biological stations accounted for the majority of differences in European Halacaridae richness. Species occurring in more habitats showed broader geographical ranges and accumulated more records. Species traits like body size affected the distribution of halacarid species.</span></p> <span>Main conclusions</span> <p><span>We propose that the sampling effort of halacarid mites in Europe might be explained by two different cognitive biases: the convenience of selecting certain sampling localities compared to others, and the tendency of zoologists to scrutinize habitats where their target organisms are more common.</span></p>
Data from: Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
<p>Collecting fine-scale occurrence data for marine species across large spatial scales is logistically challenging but is important to determine species distributions and for conservation planning. Inaccurate descriptions of species ranges could result in designating protected areas with inappropriate locations or boundaries. Optimising sampling strategies, therefore, is a priority for scaling up survey approaches using tools such as environmental DNA (eDNA) to capture species distributions. In a marine context, commercial vessels, such as ferries, could provide sampling platforms allowing access to under-sampled areas and repeatable sampling over time to track community changes. However, sample collection from commercial vessels could be biased and may not represent biological and environmental variability. Here, we evaluate whether sampling along Mediterranean ferry routes can yield unbiased biodiversity survey outcomes, based on perfect knowledge from a stacked species distribution model (SSDM) of marine megafauna from online data repositories. Simulations to allocate sampling point locations were carried out representing different sampling strategies (random vs regular), frames (ferry routes vs unconstrained) and number of sampling points. SSDMs were remade from different sampling simulations and compared to the 'perfect knowledge' SSDM to quantify the bias associated with different sampling strategies. Ferry routes detected more species and were able to recover known patterns in species richness at smaller sample sizes better than unconstrained sampling points. However, to minimise potential bias, ferry routes should be chosen to cover the variability in species composition and its environmental predictors in the SSDMs. The workflow presented here can be used to design effective sampling strategies using commercial vessel routes globally, including for eDNA analyses. This approach has potential to provide a cost-effective method to access remote oceanic areas on a regular basis and can recover meaningful data on spatiotemporal biodiversity patterns.</p>
Data from: Flexible methods for species distribution modeling with small samples
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Data from: Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
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Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models
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Biases and distribution patterns in hard-bodied microscopic animals (Acari: Halacaridae): Size doesn’t matter, but generalism and sampling effort do
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Data from: Disequilibrium oxygen isotope distribution among aqueously altered minerals in Ryugu asteroid returned samples
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Data from: Sample size guidelines for mapping migration corridors and population distributions using tracking data
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Data from: Demographic and ecogeographic factors limit wild grapevine spread at the southern edge of its distribution range - wild grapevine sampling locations, Maxent input files, morphological and microsatellite data
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Data from: Genetic analysis of museum samples suggests temporal stability in the Mexican nonbreeding distribution of a neotropical migrant
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e052 Field B Microplot Arthropod Sweepnet Sampling:Interactive Effects of Fertility and Distribution on Plant Community Diversity and Structure
There are four levels of nitrogen, corresponding to treatments A, C, F and G in E001, applied at the same time as in that experiment. For a description of fertilizer added to E052, see file fertilization details. There are four levels of soil disturbance designated 1, 2, 3 and 4. Level 1: undisturbed Level 2: 1 pass with a 7 HP Honda rear-tined rototiller with the elevator set to till to a depth of 9 inches Level 3: 2 passes or however many required to produce about 50% bare ground Level 4: 3 passes or however many required to produce 100% bare ground. This requires 3 passes in some plots but 5 or 6 in others. In addition, all woody vegetation not destroyed by tilling is cut at the base. Rototilling is applied in late April. Each fertilization treatment receives each disturbance treatment, for a total of sixteen treatments. There are four replicates of each of the sixteen treatments. In addition, the four extreme ends (lowest N, lowest disturbance; highest N, lowest disturbance, etc. ) are replicated an additional ten times. Treatments are applied in a completely randomized design. Each of the 104 plots is 5m x 5m. Measurements taken at E052 will include: 1) species abundances, 2) community biomass allocation to leaves/roots/stems/flowers, 3) above and below ground net primary production and 4) rates of nitrogen mineralization. For a list of treatments, see the treatment layouts in file trmte52. The plots in E052 are enclosed by a fence to exclude mammalian herbivores. Galvanized welded-wire hardware cloth with 6mm x 6mm openings was buried to a depth of 50cm. Additional hardware cloth extends 60cm above the ground and poultry netting extends to 2m above the ground. In 1990, ten plots of each of four treatments (N1D1, N1D4, N4D1, N4D4, where N is the level of nitrogen added and D is the disturbance treatment) were randomly selected for the competition experiment. The above and belowground effects of neighbors on transplanted grass seedlings were measured using three
Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample specific ion distributions
<p>Data generated and analyzed in "Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample specific ion distributions"</p> <p>Boris Sarvin<sup>‡1</sup>, Shoval Lagziel<sup>‡2</sup>, Nikita Sarvin<sup>1</sup>, Dzmitry Mukha<sup>1</sup>, Praveen Kumar<sup>1</sup>, Elina Aizenshtein<sup>3</sup>, Tomer Shlomi *<sup>123</sup></p> <p><sup>1</sup> Faculty of Biology, Technion – Israel Institute of Technology, 32000 Haifa, Israel.</p> <p><sup>2</sup> Faculty of Computer Science, Technion – Israel Institute of Technology, 32000 Haifa, Israel.</p> <p><sup>3</sup> Lokey Center for Life Science and Engineering, Technion – Israel Institute of Technology, 32000 Haifa, Israel.</p> <p><sup>‡</sup> BS and SL contributed equally to this work.</p>
Data from: Comparing the prediction of joint species distribution models with respect to characteristics of sampling data
Biotic interactions have been rarely included in traditional species distribution models, wherein Joint Species Distribution Models (JSDMs) emerge as a feasible approach to incorporate environmental factors and interspecific interactions simultaneously, making it a powerful tool for analyzing the structure and assembly processes of biotic communities. However, the predictability and statistical robustness of JSDMs are largely unknown because of the lack of research efforts for those newly developed models. This study systematically evaluated the performances of five JSDMs in predicting the occurrence and biomass of multiple species, with a particular focus on diverse characteristics of sampling data, including type of response variables, number of sampling sites, and the number of species included in models. In general, most models yielded satisfactory performances on fitting to observed data and on the estimation of environmental effects; however, they showed less well performances in evaluating species associations, and their predictability had large variations. The JSDMs showed inconsistent performances between the goodness-of-fit and predictability in cross-validation, and the Boral model was relatively robust than others. The predictability of JSDMs was less influenced by sample sizes and substantially improved by incorporating rare species. This study contributes to an appropriate model selection and application of JSDMs.
Data from: Accounting for observation processes across multiple levels of uncertainty improves inference of species distributions and guides adaptive sampling of environmental DNA
Understanding factors that influence observation processes is critical for accurate assessment of underlying ecological processes. When indirect methods of detection, such as environmental DNA, are used to determine species presence, additional levels of uncertainty from observation processes need to be accounted for. We conducted a field trial to evaluate observation processes of a terrestrial invasive species (wild pigs- Sus scrofa) from DNA in water bodies. We used a multi-scale occupancy analysis to estimate different levels of observation processes (detection, p): the probability DNA is available per sample (θ), the probability of capturing DNA per extraction (γ), and the probability of amplification per qPCR run (δ). We selected four sites for each of three water body types and collected 10 samples per water body during two months (September and October 2016) in central Texas. Our methodology can be used to guide sampling adaptively to minimize costs while improving inference of species distributions. Using a removal sampling approach was more efficient than pooling samples, and was unbiased. Availability of DNA varied by month, was considerably higher when water pH was near neutral, and was higher in ephemeral streams relative to wildlife guzzlers and ponds. To achieve a cumulative detection probability greater than 90% (including availability, capture, and amplification), future studies should collect 20 water samples per site, conduct at least 2 extractions per sample, and conduct 5 qPCR replicates per extraction. Accounting for multiple levels of uncertainty of observation processes improved estimation of the ecological processes and provided guidance for future sampling designs.
Distribution. Verified records based on analyzed specimens are from NE Afghanistan, N Pakistan (Khyber Pakhtunkhwa and Punjab), and NW & N India (Jammu and Kashmir, Punjab, and Sikkim), but distribution likely includes other regions of NW India (Himachal Pradesh, Uttarakhand) and SW China (S Tibet [= Xizang]); it probably also occurs in Nepal, although further sample comparison is needed. in Vespertilionidae
Distribution. Verified records based on analyzed specimens are from NE Afghanistan, N Pakistan (Khyber Pakhtunkhwa and Punjab), and NW & N India (Jammu and Kashmir, Punjab, and Sikkim), but distribution likely includes other regions of NW India (Himachal Pradesh, Uttarakhand) and SW China (S Tibet [= Xizang]); it probably also occurs in Nepal, although further sample comparison is needed.
Subspecies and Distribution. N. n. noctula Schreber, 1774 — throughout Europe from Great Britain, France, and Spain E to W Russia, W Kazakhstan, and SW Turkmenistan, including S Scandinavia, Gotland and Oland Is, and Cyprus (Cyprus records somewhat tentatively regarded as this subspecies). Absent throughout much of Iberia and is locally extinct in Portugal. N. n. lebanoticus D. L.. Harrison, 1962 — WC & SW Syria, Lebanon, and NE Israel. N. n. mecklenburzevi Kuzyakin, 1934 — SC & E Kazakhstan, SC Russia, W Uzbekistan, Tajikistan, Kyrgyzstan, and NW China (Xinjiang). The species may be present in N Africa, with two records claimed from Algeria in 1858, but these may represent N. lasiopterus; further sampling is needed. in Vespertilionidae
Subspecies and Distribution. N. n. noctula Schreber, 1774 — throughout Europe from Great Britain, France, and Spain E to W Russia, W Kazakhstan, and SW Turkmenistan, including S Scandinavia, Gotland and Oland Is, and Cyprus (Cyprus records somewhat tentatively regarded as this subspecies). Absent throughout much of Iberia and is locally extinct in Portugal. N. n. lebanoticus D. L.. Harrison, 1962 — WC & SW Syria, Lebanon, and NE Israel. N. n. mecklenburzevi Kuzyakin, 1934 — SC & E Kazakhstan, SC Russia, W Uzbekistan, Tajikistan, Kyrgyzstan, and NW China (Xinjiang). The species may be present in N Africa, with two records claimed from Algeria in 1858, but these may represent N. lasiopterus; further sampling is needed.
Distribution. Known only from the type locality in S Somalia, with no subsequent records, although this might reflect a lack of sampling. in Chrysochloridae
Distribution. Known only from the type locality in S Somalia, with no subsequent records, although this might reflect a lack of sampling.
Distribution. Endemic to C & SE Sulawesi; known from various lowland and more mountainous regions, including Mt Rorekatimbo, Mt Gandangdewata, Mt Balease, and Mt Nokilalaki. Together with the Elongated White-toothed Shrew (C. elongata) this is the only wild shrew occurring on the SE peninsula, but lack of adequate sampling in most pristine areas of S Sulawesi hinders precise biogeographical inferences. in Soricidae
Distribution. Endemic to C & SE Sulawesi; known from various lowland and more mountainous regions, including Mt Rorekatimbo, Mt Gandangdewata, Mt Balease, and Mt Nokilalaki. Together with the Elongated White-toothed Shrew (C. elongata) this is the only wild shrew occurring on the SE peninsula, but lack of adequate sampling in most pristine areas of S Sulawesi hinders precise biogeographical inferences.
Distribution. Confined to the upper slopes of Mt Kinabalu, although one damaged skull from Sarawak could represent this species. This would extend its range further S to other high mountains of Borneo, butit is unlikely, given the currently negative results in other high mountains of Sabah that have been sampled. in Soricidae
Distribution. Confined to the upper slopes of Mt Kinabalu, although one damaged skull from Sarawak could represent this species. This would extend its range further S to other high mountains of Borneo, butit is unlikely, given the currently negative results in other high mountains of Sabah that have been sampled.
FIGURE 3 in Hypogean presumably sister species Quedius repentinus sp. n. from Altai and Q. roma from Sikhote-Alin (Coleoptera: Staphylinidae): a disjunct distribution or poorly sampled Siberia?
FIGURE 3. Quedius repentinus sp.n.: A, C, D, F–H (holotype), B (paratype, female), E (paratype, male); A, B, habitus; C, aedeagus (laterally); D, same (in parameral view); E, paramere, underside (side facing median lobe); F, tergite X; G, sternite IX; H, sternite VIII. Scale bars: A–D, F–H = 1 mm, E = 0.2 mm.
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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.