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799 results for “abundance data”
The data catalog for Metallicity and alpha-abundance for 48 million stars in low-extinction regions in the Milky Way
<p>Stellar chemistry contains information on the environment in which the star was born. Therefore, measuring the chemical abundances of stars in the Milky Way, such as the overall metallicity [M/H] and the alpha-abundance [alpha/M], is essential in Galactic astronomy.</p> <p>We estimate ([M/H], [alpha/M]) for giants and dwarfs in low dust extinction region from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 (Abdurro’uf et al. 2022) and the metal-poor star sample of Li et al. (2022).</p> <p>Here, we upload the catalogues of ([M/H], [alpha/M]) for 182 million stars. The data are divided into 10 fits files. The i-th file (i=1,2,...,10) contains stars with E(B-V) value between 0.1*(i-1) and 0.1*i. Because our machine-learning models are trained on stars with low dust extinction (E(B-V)<0.1), we recommend using 48 million stars with low-dust extinction region with 0<E(B-V)<0.1 (table_light_mh_am_0p0ebv0p1.fits). The description for each column of the data is shown in column_description.png. </p> <p>The source paper of this catalog:</p> <ul> <li>Kohei Hatori "Metallicity and alpha-abundance for 48 million stars in low-extinction regions in the Milky Way" <br>https://iopscience.iop.org/article/10.3847/1538-4357/ad9686</li> </ul> <p>References:</p> <div> <div> <div> <ul> <li>Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 1026 35, doi: 10.3847/1538-4365/ac4414</li> </ul> </div> </div> </div> <ul> <li>Li, H., Aoki, W., Matsuno, T., et al. 2022, ApJ, 931, 147, doi: 10.3847/1538-4357/ac6514</li> </ul> <p> </p>
CABO forest inventory survey data: Canopy-level spectra, species abundances, and environmental conditions
<p>This dataset contains the forest inventory survey data as aqcuired by airborne imaging spectroscopy (i.e., continuum removed spectral reflectance) and field inventory surveys (i.e., relative species abundance) for 65 field plots along a temperate-to-boreal forest gradient in southern Québec, Canada. Additionally, it contains plot-level average environmental variables (e.g., elevation, slope, etc.) and species-mean foliar traits. This data supports the manuscript titled "Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis" <em>in press </em>at <em>Ecological Monographs </em>(ID: ECM23-0177) and accompanying code (Crofts 2024) is archieved on Zenodo (<a href="https://doi.org/10.5281/zenodo.10735410)">doi: 10.5281/zenodo.10735410)</a>. Please refer to the methods section of the associated paper for methodological details, with additional details available at protocols.io (<a href="https://doi.org/10.17504/protocols.io.q26g7rn23vwz/v2">doi: 10.17504/protocols.io.q26g7rn23vwz/v2).</a> This data was aqcuired as a part of the Canadian Airborne Biodiversity Observatory (CABO; caboscience.org) and has the licence Creative Commons by Attribution (cc-by). Note: this dataset is also published of EcoSiS (<a href="https://ecosis.org/package/cabo-canopy-level-spectra-from-forest-sites)">https://ecosis.org/package/cabo-canopy-level-spectra-from-forest-sites)</a></p>
The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau (Data Set)
<p>This is the dataset which is generated from the manuscript entitled 'The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau'.</p> <p>The spatial resolution of this dataset is about 1 km, of which coordinates systems is WGS84.</p> <p>There are 6 layers of nematode abundance in this GeoTiff file:</p> <p>1. abd - Total Soil Nematode Abundance</p> <p>2. bact - Abundance of bacterivores</p> <p>3. fung - Abundance of fungivores</p> <p>4. herb - Abundance of plant parasite</p> <p>5. omni - Abundance of omnivores</p> <p>6. pred - Abundance of predators</p>
Data for Ecology Letters paper: Jack-of-all-trades paradigm meets long-term data: generalist herbivores are more widespread and locally less abundant.
<p>Data, R-code, and meta-data document for a 2022 paper in Ecology Letters that examines assumptions about associations between local abundance and dietary specialization using an 18-year dataset of caterpillar-plant interactions in Ecuador. </p>
Copper River, Alaska, Chinook Salmon Inriver Abundance Estimate 2018-2021 DATA ARCHIVE
<p>Long-term monitoring of returning adult Chinook salmon (<em>Oncorhynchus tshawytscha</em>) abundance on the Copper River, AK, has been conducted using fishwheels and two-sample mark-recapture methods since 2003. This data archive is from from the 2018-2021 field seasons. The annual objective was to estimate the inriver abundance of Copper River Chinook salmon such that the estimate was within 25% of the true abundance 95% of the time. This data represents annual catch, bycatch, tagging site data, recapture site data, session data, QC check tables, CPUE, mark-recapture matrix, mark-recapture stratification tables, effort, and daily catch matrix. </p> <p>See annual report for methodology, analyses and results @ http://akssf.org/default.aspx?id=3477 or contact the Alaska Sustainable Salmon Fund or U.S. Fish and Wildlife Service Office of Subsistence Management Fisheries Resource Monitoring Program or Native Village of Eyak DENR. </p> <p> </p>
Data for: Assortative mating in an ecological context: Effects of mate choice errors and relative species abundance on the frequency and asymmetry of hybridization
<p><span>The frequency and asymmetry of mixed-species mating set the initial stage for the ecological and evolutionary implications of hybridization. How such patterns of mixed-species mating, in turn, are influenced by the combination of mate choice errors and relative species abundance remain largely unknown. We develop a mathematical model that generates predictions for how relative species abundances and mate choice errors affect hybridization patterns. When mate choice errors are small (<5%) the highest frequency of hybridization occurs when one of the hybridizing species is at low abundance, but when mate choice errors are high (>5%) the highest hybridization frequency occurs when species occur in equal proportions. Furthermore, females of the less abundant species are overrepresented in mixed-species matings. We compare our theoretical predictions with empirical data on naturally hybridizing Ficedula flycatchers and find that hybridization is highest when the two species occur in equal abundance, implying rather high mate choice errors. We discuss ecological and evolutionary implications of our findings and encourage future work on hybrid zone dynamics that take demographic aspects, such as relative species abundance, into account.</span></p>
Data from: Worldwide impacts of landscape anthropization on mosquito abundance and diversity: a meta-analysis
<p><span>In recent decades, the emergence and resurgence of vector-borne diseases have been well documented </span><span>worldwide</span><span>, especially in tropical regions where protection and defence tools for human populations are still very limited. In this context, the </span><span>dynamics</span><span> of pathogens </span><span>are influenced by</span><span> landscape anthropization (i.e., urbanization, deforestation, and agricultural development)</span><span>,</span><span> and one of the mechanisms through which this occurs is a change in</span><span> the</span><span> abundance and/or diversity of the vectors. An increasing number of empirical studies </span><span>have </span><span>described heterogeneous effects of landscape anthropization on vector communities</span><span>; therefore</span><span>, it is difficult to have an overall picture of these effects on a global scale. Here, we performed a meta-analysis to quantify the impacts of landscape anthropization on a global scale on the presence/abundance and diversity of mosquitoes, the most important arthropods affecting human health. We obtained 338 effect sizes on 132 mosquito species, compiled from 107 studies in 52 countries </span><span>that</span><span> covered almost every part of the world. The results of the meta-analysis showed an overall decline of mosquito presence/abundance and diversity in response to urbanization, deforestation, and </span><span>agricultural</span><span> development, except for a few mosquito species</span><span> </span><span>that have been able to exploit landscape anthropization well. Our results highlighted that these few favoured mosquito species are those of global</span><span> concern. </span><span>They thus provide a better understanding of the overall effect of landscape anthropization on vector communities and</span><span>,</span><span> more importantly, suggest a greater risk of emergence and transmission of vector-borne diseases in human-modified landscapes.</span></p>
Data on the abundance of wild ungulates and large carnivores in the Roztocze National Park (south-east Poland), 2007-2022
<p>Data on the abundance of wild ungulates and large carnivores in the Roztocze National Park (south-east Poland), 2007-2022</p>
Extracting abundance information from DNA-based data
<p><span><span><span><span>The accurate extraction of species-abundance information from DNA-based data (metabarcoding, metagenomics) could contribute usefully to the reconstruction of diets and quantitative foodwebs, the inference of species interactions, the modelling of population dynamics and species distributions, the biomonitoring of environmental state and change, and the inference of false positives and negatives. However, capture bias, capture noise, species pipeline biases, and pipeline noise all combine to inject error into DNA-based datasets. This review focuses on methods for correcting the latter two error sources, as the first two are addressed extensively in the ecological survey literature. To extract abundance information from DNA-based data, it is useful to distinguish two concepts. (1) <em>Across</em>-species quantification describes relative species abundances within a single sample. (2) In contrast, <em>within</em>-species quantification describes how the abundance of each individual species varies across samples, where the samples could be a time series, an environmental gradient, or different experimental treatments. In the first part of this paper, we review methods to remove species pipeline biases and pipeline noise. In the second part, we provide a detailed protocol and demonstrate experimentally how to use a 'DNA spike-in' (an internal standard) to remove pipeline noise and recover within-species abundance information.</span></span></span></span></p>
Data from: Impact of human foraging on tree diversity, composition and abundance in a tropical rainforest
<p>These are summarised plot data from fifteen 40 m by 40 m sample plots established in Oban Division of Cross River National Park, Nigeria, between 23rd August 2019 and 9th September 2019. We have also included data summaries and RStudio codes used for analysis and generating results for the manuscript entitled: "Impact of human foraging on tree diversity, composition and abundance in a tropical rainforest", submitted for publication as an original research article in Biotropica. All data and R code required to generate the results as shown in the manuscript have been included. Complete tree species and plot data can be accessed at https://forestplots.net/.</p>
Data for [Changing abundance of magnetofossil morphologies in pelagic red clay around Minamitorishima, western North Pacific]
<p>----</p> <p>Note added in Aug 27, 2018.</p> <p>There is an error in the file sratios_MR15E01PC12.xlsx.</p> <p>Please refer to another upload, doi: 10.5281/zenodo.1404158.</p> <p>----</p> <p> </p> <p>This is the data used in the manuscript:</p> <p>Changing abundance of magnetofossil morphologies in pelagic red clay around Minamitorishima, western North Pacific</p>
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Data from: Semi-natural habitat, but not aphid amount or continuity, predicts lady beetle abundance across agricultural landscapes
<p>The amount of semi-natural habitat surrounding farm fields is a common but inconsistent predictor of natural enemy populations and predation services. Standard land cover metrics may not accurately capture the actual availability of limiting resources for natural enemies and can miss important dynamics across space and time. Theory from animal movement and landscape ecology predicts that regions with more, spatio-temporally continuous resources (i.e. food, shelter) should have larger predator populations and enhanced biological control. To test these predictions empirically, we designed a study measuring aphids, lady beetles, and predation services in agricultural landscapes in Wisconsin, USA. In two study years, we sampled lady beetles and aphids in 336 crop fields (corn, soybean, alfalfa, and small grains) and adjacent semi-natural habitat patches (grasslands and woodlands) across 24 1.5 km buffer landscapes at 4–7 time points each, and in one year we assessed predation rates with sentinel egg cards. We used aphid counts to model habitat-specific aphid phenologies, from which we calculated landscape indices of prey amount and continuity. These indices, along with semi-natural habitat area, were used to predict lady beetle abundance. While there were strong differences in the abundance and timing of aphids by habitat, semi-natural habitat amount was still a better predictor of lady beetle counts and sentinel egg predation than either aphid amount or continuity indices in these landscapes.</p> <p>Synthesis and application: Our findings confirm the robust relationship between lady beetles and semi-natural habitat in agricultural landscapes, and highlight the complexities of measuring fine-scale resource heterogeneity in real landscapes. Retaining or adding woodland and grassland patches in agricultural landscapes is likely to support larger lady beetle populations and enhance predation in crop fields. Our results suggest that these habitats may be more important for shelter than prey continuity, though this mechanism warrants further investigation. Future work should continue to refine experimental methods for the successful integration of landscape ecology and animal behavior to support conservation goals.</p>
Data from: A framework for modeling the impacts of searcher behavior on the efficiency of abundance surveys
<p>When planning abundance surveys, the impact of search effort on the quality of the density estimates is rarely considered. We constructed a time-budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search effort to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated resource density. This framework allowed us to determine how a surveyor should behave to produce optimal density estimates. Using data collected from quadrat and removal surveys of zebra mussels (<em>Dreissena polymorpha</em>) in central Minnesota, we applied this framework to evaluate potential improvements. By tuning searcher behavior, we find that density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey effort. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. Our results provide insights into how to improve the performance of many survey methods in high-density environments by either tuning searcher behavior or decoupling the estimation of resource density and detection probability.</p>
Data from: Performance of unmarked abundance models with data from machine-learning classification of passive acoustic recordings
<p>The ability to conduct cost-effective wildlife monitoring at scale is rapidly increasing due to availability of inexpensive autonomous recording units (ARUs) and automated species recognition, presenting a variety of advantages over human-based surveys. However, estimating abundance with such data collection techniques remains challenging because most abundance models require data that are difficult for low-cost monoaural ARUs to gather (e.g., counts of individuals, distance to individuals), especially when using the output of automated species recognition. Statistical models that do not require counting or measuring distances to target individuals in combination with low-cost ARUs provide a promising way of obtaining abundance estimates for large-scale wildlife monitoring projects but remain untested. We present a case study using avian field data collected in forests of Pennsylvania during the Spring of 2020 and 2021 using both traditional point counts and passive acoustic monitoring at the same locations. We tested the ability of the Royle-Nichols and time-to-detection models to estimate abundance of two species from detection histories generated by applying a machine-learning classifier to ARU-gathered data. We compared abundance estimates from these models to estimates from the same models fit using point-count data and to two additional models appropriate for point counts, the N-mixture model and distance models. We found that the Royle-Nichols and time-to-detection models can be used with ARU data to produce abundance estimates similar to those generated by a point-count based study but with greater precision. ARU-based models produced confidence or credible intervals that were on average 31.9% ( 11.9 SE) smaller than their point-count counterpart. Our findings were consistent across two species with differing relative abundance and habitat use patterns. The higher precision of models fit using ARU data is likely due to higher cumulative detection probability, which itself may be the result of greater survey effort using ARUs and machine-learning classifiers to sample significantly more time for focal species at any given point. Our results provide preliminary support the use of ARUs in abundance-based study applications, and thus may afford researchers a better understanding of habitat quality and population trends, while allowing them to make more informed conservation actions and recommendations.</p>
Data & Analysis Script for: Phylogenetic relatedness to native congeners drives insect abundance and diversity hosted by non-native trees
<p>The dataset contains all necessary data to reproduce the findings presented in Schweiger et al. 2023 - Phylogenetic relatedness to native congeners drives insect abundance and diversity hosted by non-native trees (submitted).</p> <p>The code necessary to reproduce the findings is included within this repository. The code contains comments. Please note, if you want to reproduce the findings you will have to change file path information matching your personal computer to be able to re-run the code.</p> <p>This data includes the biodiversity raw data collected for the manuscript. It <strong>does not </strong>include data used to calculate geographic, climatic or phylogenetic distances, as these data are freely available and necessary information to reproduce calculations are given within the Material & Methods section.</p> <p>All data is provided within one Excel file. Please, pay attention to the provided ReadMe sheet containing metadata information on the dataset.</p> <p>Please carefully read provided information within ReadMe, Metadata and Code description.</p>
Data for [Inverse magnetic susceptibility fabrics in pelagic sediment: Implications for magnetofossil abundance and alignment]
<p>Data for [Inverse magnetic susceptibility fabrics in pelagic sediment: Implications for magnetofossil abundance and alignment]</p>
Fig. 6 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids
Fig. 6. Percent similarity among bins averaged to 1 degree bins. A. om7 interval. B. om8 interval. C. om9 interval. The thicker the line, the greater the similarity between the two cells connected by the line.
Fig. 4 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids
Fig. 4. Correlations between richness per map and number of localities. A. om7 interval. B. om8 interval. C. om9 interval. The gap in the distribution of points for the om8 interval highlights the discontinuity between a group of maps with few taxa at a few localities and other maps with a large number of localities and high richness.
Fig. 5 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids
Fig. 5. Rarefaction curves for each interval, based on number of occurrences. The confidence envelope of the species richness for om9 departs significantly from those of om7 and om8 above 50 occurrences, but the significantly higher species−richness of om8 only becomes apparent at sample sizes of around 250 specimens, indicating that a few, rare taxa are boosting richness in the om8 interval.
ScienceDex guides
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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.