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298 results for “abundance distribution”
Ant Distribution and Abundance in New England 1990-2014
The Ants of New England project is a multi-investigator, multi-year effort to document the occurrence, distribution, and relative abundance of ants (Hymenoptera: Formicidae) in the six New England states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine). The project was initiated in 1999 as a more narrowly-focused effort aimed at determining ant species diversity in bogs and surrounding forests in Massachusetts and Vermont using standard methods (pitfall trapping, timed baiting, litter collection, and visual searching; Gotelli and Ellison 2002, Ellison et al. 2002). Subsequent detailed analysis of collection methods revealed that reliable estimates of ant species occurrences, distribution, and abundance in this geographic region could be obtained using only visual searching and litter collection (Ellison et al. 2007). Following this analysis, we carried out an initial survey of ant occurrences, distribution, and abundances in Massachusetts in 2007. The 2007 survey was focused on ants living in natural community types as defined by the Massachusetts Natural Heritage and Endangered Species Program (Swain and Kearsley 2001) and located in properties of high conservation and education value owned by Massachusetts Audubon Society and The Trustees of Reservations. The primary goals for the 2007 survey were: (1) To describe and quantify patterns of distribution and abundance of ants across Massachusetts and to determine the regional "species pool" of ants that could ground local studies on ants (for example, the Warm Ants project at Harvard Forest). (2) To provide a baseline from which to assess long-term effects of climate change on species distributions. (3) To develop a set of indicator species to be used to determine efficacy of ongoing and proposed management strategies and to reveal effects of future disturbances and habitat degradation. (4) To compare with ongoing or planned quantitative surveys of birds and plants at sites owned by conse
Regional Distribution and Abundance of Eastern Hemlock in Eastern North America 2010
We developed comprehensive maps on the distribution and abundance of hemlock for the purposes of mapping the host distribution, and modeling the spread, of the hemlock woolly adelgid. Multiple statistical models were used to map the distribution of hemlock. Hemlock occurrence data were taken from the FIA database and multiple environmental predictors were gathered from various databases as described in methods. The raster map depicts the predicted abundance of hemlock m2 basal area per hectare) across its range in eastern North America.
Native and invasive species abundance distributions in lakes at North Temperate Lakes LTER 1979-2010
These data were compiled from multiple sources. We collated data on the abundance or density of aquatic invasive and native species sampled in more than 20 sites using the same methods. To control for sampling methodology and allow comparisons among native and invasive species, we only included data where both invasive and native species from a taxonomic group were sampled using the same methods across multiple sites. Exceptions were made to include rusty crayfish (Orconectes rusticus) in its native range and zebra mussel (Dreissena polymorpha) data.
Madison community science field campaign to assess abundance and distribution of invasive jumping worms.
Asian pheretimoid earthworms of the genera Amynthas and Metaphire (jumping worms) are leading a new wave of co-invasion into Northeastern and Midwestern states, with potential consequences for native organisms and ecosystem processes. However, little is known about their distribution, abundance, and habitat preferences in urban landscapes – areas which likely influence range expansion via human-driven spread. We led a participatory field campaign to assess jumping worm distribution and abundance in Madison, Wisconsin in September of 2017. By compressing 250 person-hours of sampling effort into a single day, we quantified presence and abundance of three jumping worm species across different land-cover types (forest, grassland, open space, residential lawns and gardens), finding that urban green spaces differed in invasibility. We show that community science can be powerful for researching invasive species while engaging the public in conservation. This approach was particularly effective here, where broad spatial sampling was required within a short temporal window.
Simulated metagenomes with quality and abundance distributions derived from real samples
<p>Species abundances and quality values were derived from the following list of samples:</p> <pre><code>SAMEA2466896 SAMEA2466916 SAMEA2466952 SAMEA2466953 SAMEA2466965 SAMEA2466996 SAMEA2467015 SAMEA2467039 SAMEA2621010 SAMEA2621033 SAMEA2621107 SAMEA2621155 SAMEA2621229 SAMEA2621247 SAMEA2621300 SAMEA2622357 </code></pre> <p>Reference abundances (.abund files) were generated using <a href="https://github.com/motu-tool/mOTUs_v2">mOTUs profiler</a>.<br> Metagenomes were simulated with <a href="https://sourceforge.net/projects/cmessi/">cMESSi</a> using <a href="http://progenomes.embl.de/data/repGenomes/representatives.contigs.fasta.gz">proGenomes' representative contigs</a> for species and the aforementioned abundances. In cases where a <em>ref_mOTU_v2</em> corresponded to more than one genome, the abundance of said <em>ref_mOTU</em> was distributed equally over all genomes.<br> GFF location files were produced using location information generated by cMESSi.<br> Two variants of truth values were obtained by intersecting coordinates of simulated reads with coordinates of <a href="http://eggnogdb.embl.de">eggNOG</a> orthologous groups (OG at NOG level) as predicted by <a href="https://github.com/jhcepas/eggnog-mapper">eggNOG-mapper</a>.</p> <ol> <li>.cog-simulated files contain the NOG distribution that was effectively simulated, <em>i.e.</em> a count of the number of reads overlapping with genes annotated with each NOG. A read overlapping multiple genes is considered for each gene. If a gene possesses multiple NOG annotations, each annotation gets assigned the total number of overlapping reads. Longer genes will (in expectation) generate more reads, all else being equal.</li> <li>.cog-distribution file contains the expected distribution for every NOG on all samples. The number of genes annotated with each NOG is multiplied by the abundance of the corresponding species. Length of the gene is not taken into account.</li> </ol> <p>If you use this dataset, please cite: <a href="https://www.biorxiv.org/node/111718.full">NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language</a></p>
Wetland abundance and distribution changes in Sycamore Creek, Arizona, USA (2014-2019)
The primary objective of this project is to understand how long-term climate variability and change influence the structure and function of desert streams via effects on hydrologic disturbance regimes. Climate and hydrology are intimately linked in arid landscapes; for this reason, desert streams are particularly well suited for both observing and understanding the consequences of climate variability and directional change. Researchers try to (1) determine how climate variability and change over multiple years influence stream biogeomorphic structure (i.e., prevalence and persistence of wetland and gravel-bed ecosystem states) via their influence on factors that control vegetation biomass, and (2) compare interannual variability in within-year successional patterns in ecosystem processes and community structure of primary producers and consumers of two contrasting reach types (wetland and gravel-bed stream reaches). This dataset was collected to understand: (1) the spatial pattern of wetland distribution and abundance; (2) the influence of multi-annual variability in hydrological regime on wetland distribution and abundance; and (3) the mechanism of the resilience of wetland to different disturbances in terms of hydrology (i.e., drying and flooding).
Estimation of Abundance and Distribution of Salt Marsh Plants from Images Using Deep Learning
Recent advances in computer vision and machine learning, most notably deep convolutional neural networks (CNNs), are exploited to identify and localize various plant species in salt marsh images. Three different approaches are explored that provide estimations of abundance and spatial distribution at varying levels of granularity in terms of spatial resolution. In the coarsest-grained approach, CNNs are tasked with identifying which of six plant species are present/absent in large patches within the salt marsh images. CNNs with diverse topological properties and attention mechanisms are shown capable of providing accurate estimations with > 90% precision and recall in the case of the more abundant plant species whereas the performance of the CNNs is observed to decline in the case of less common plant species. Estimation of percent cover of each plant species is performed at a finer spatial resolution, where smaller image patches are extracted and the CNNs tasked with identifying the plant species or substrate at the center of the image patch. In an ecological setting, several image patches (~100) are extracted and classified using this approach to estimate the percent cover of the various plant species in the image. For the percent cover estimation task, the CNNs are observed to exhibit a performance profile similar to that for the presence/absence estimation task, but with an ~ 5–10% reduction in precision and recall. Finally, estimation of the spatial distribution of the various plant species is performed via semantic segmentation of the input images at the finest level of granularity in terms of spatial resolution. The Deeplab-V3 semantic segmentation architecture is observed to provide very accurate estimations for abundant plant species; however, a significant degradation in performance is observed in the case of less abundant plant species and, in extreme cases, rare plant classes are seen to be ignored entirely. Overall, a clear trade-off is observed between
MACREL software benchmark data set: Simulated metagenomes with sequencing quality, errors profile and abundance distributions derived from real samples
<p>These metagenomes were used in the benchmarking of FACS pipeline, and were designed after NGLess benchmark dataset (doi.org/10.5281/zenodo.2560288). Metagenomes were simulated with <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/art/index.cfm">ART-bin-MountRainier-2016.06.05</a> using real abundance profiles (.abund files) available <a href="https://doi.org/10.5281/zenodo.2560288">elsewhere</a>, and <a href="http://progenomes1.embl.de/data/repGenomes/representatives.contigs.fasta.gz">proGenomes' representative contigs</a> as reference genomes. There are available metagenomes with 40, 60 and 80 M (million of reads) based in the reference genomes and abundances of the following samples:</p> <pre><code>SAMEA2466916 SAMEA2466953 SAMEA2466965 SAMEA2621107 SAMEA2621229 SAMEA2621247</code></pre> <p>To convert them from the CRAM format back to fastq files:</p> <pre><code> ## 1. converting from cram to bam format: samtools view -b -T refgenome.fa -o file.bam file.cram ## 2. sorting the bam file: samtools sort -n file.bam -o input_sorted.bam # sort reads by identifier-name (-n) ## 3. converting from bam to fastq format: bedtools bamtofastq -i input_sorted.bam -fq output_r1.fastq -fq2 output_r2.fastq </code></pre> <p> </p>
Distribution and abundance of canopy trees in floodplain forests of the Wisconsin River 1999 - 2001
The Wisconsin River Floodplain Project aimed to identify landscape indicators that are well correlated with specific aspects of ecological function. This is a crucial research need requiring an integrated approach that combines landscape monitoring with field studies. Large river-floodplain systems are among the most diverse and dynamic landscapes in the US, providing many important societal values, but relatively little effort has been devoted to development and testing of landscape indicators for these systems. We developed and tested ecological indicators for large river-floodplain landscapes along reaches of the Wisconsin River to determine which landscape metrics are most useful for monitoring population, community and ecosystem processes in large river-floodplain landscapes. Spatially extensive field sampling was combined with landscape analysis in nine reaches of the Wisconsin River sampling to quantify the ability of landscape indicators to predict ecological variables over broad scales. Landscape indicators were evaluated by their utility for detecting changes in the structure and function of the Wisconsin River floodplain landscape that were related to modification of the natural flow regime, historical land use, and current land-use patterns. Our field studies were concentrated in floodplain forest in nine 12 to 20-km reaches along the lower 400 km of the Wisconsin River.
Spatial and temporal distribution and abundance of moths in the Andrews Experimental Forest, 1994 to 2008
The distribution and abundance of macromoth species is strongly influenced by geographical (region-neighboring plots) scale, elevation, aspect, plant community, management regime, and time of year. Noctural macromoths have been observed at a total of 263 sample sites throughout the Andrews Forest watershed since 1994. Only a limited subset of these sites is sampled each year. From 2004 to 2008, 20 sites were sampled consistently using a hierarchical sampling design stratified by elevation and vegetation type. Moths are sampled using blacklight traps deployed for one night every two weeks at each site from April through October. A total of 503 species have been observed, and approximately 300 species may be observed in any given year. The watershed can be divided into 13 distinct zones. The northwest ridge above the Andrews headquarters has the highest number of species (n = 321) and the lowest number of species occurred at upper Lookout Creek (n = 239). Each of 13 zones is missing ca. 200 of the 500 resident species, suggesting that heterogeneity in the landscape is important. A breakdown of the species into functional groups based on larval feeding habits: conifers, hardwood, herb, mix, unknown shows that 43% of Andrews species rely on a hardwoods and 63% rely on hardwoods and herbaceous angiosperms. Conifer-feeders only represent 8% of moth species. However, moths associated with conifer hosts are the most abundant; for instance, in the zone representing the midlevel of Carpenter Mountain 67% of moth individuals are conifer feeders, but only 14% of the species feed on conifers. In contrast, within the zone represented by the Headquarters site, only 32% of the individual moths feed on conifers whereas 56% feed on hardwoods. Moth biogeographic zones correspond to elevation zones and to potential vegetation.
Spatial and temporal distribution and abundance of butterflies in the Andrews Experimental Forest, 1994-1996
This database contains information on species abundance according to date and location within the H.J. Andrews Experimental Forest Lookout Creek watershed. The database provides the information needed to assess patterns in the abundance of butterflies across time and space. The distribution and abundance of butterfly species on the Andrews Forest is strongly influenced by geographical scale, elevation, aspect, plant community, management regime, and time of year. Patterns of distribution and abundance are based on an historical total of 80 species, of which 73 are resident species and about 55 of which may be observed in any given year. Butterflies were surveyed at two- week intervals from late April through early October over a three-year period (1994-6). Approximately one-third of the watershed was covered during each visit, thus each area was sampled at about 6 week intervals within each sample season.
Model outputs for occurrence and hunting data‐based models of wild boar distribution and abundance, July 2019 update
<p>These maps are wild boar habitat suitability outputs based on newly available data of wild boar, and models for predicting wild boar relative abundance using hunting yields.</p> <p><strong>Objectives</strong>:</p> <p>- Validation of previously produced hunting yield maps and new ones<br> - Downscaling to 10x10 km grid<br> - Downscaling to 2x2 km grid</p> <p><strong>Model settings and predictors: </strong> <br> - Model from ENETWILD report August 2019<br> - Assuming cells as municipality in 10x10 km grid downscaling<br> - Assuming cells as hunting grounds in 2x2 km grid downscaling </p> <p><strong>Conclusions guiding future methodological steps</strong><br> - To update wild boar hunting yield data for some specific regions;<br> - To increase hunting yield data resolution;<br> - To explore model independent parametrization for each bioregion.</p> <p><strong>Files:</strong></p> <p>August_2019_HY_nut00_10x10 >> Model outputs based on hunting yield GLM analyses<br> August_2019_occurrences_bioclim >> Model outputs based on Bioclim analyses<br> August_2019_occurrences_glm >> Model outputs based on Generalised linear model<br> August_2019_occurrences_ksvm >> Model outputs based on Support vector Machine analyses<br> August_2019_occurrences_maxent >> Model outputs based on Maxent analyses<br> August_2019_occurrences_randomForest>> Model outputs based on Random Forest analyses</p> <p>---------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>These maps are models obtained in intermediate phases of the ENETWILD project based on available information. <br> There are frequent updates in order to improve the results. For methodological approach and details check the paper: </p> <p>ENETWILD‐consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, G. Body, A. Cohen, R. Soriguer, J. Vicente (2019). ENETwild modelling of wild boar distribution and abundance: update of occurrence and hunting data‐based models. EFSA Supporting Publications, 16(8), 1674E.<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fefsa.onlinelibrary.wiley.com%2Fdoi%2Fabs%2F10.2903%2Fsp.efsa.2019.EN-1674&data=02%7C01%7C%7Ca8ad922eefde42f5cb5208d7c5054851%7C406a174be31548bdaa0acdaddc44250b%7C1%7C0%7C637194498792136402&sdata=fqdiYEOqYIlHaDbp5a7kVdGQ6FWuFEydJNhSWOghH%2FQ%3D&reserved=0">https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/sp.efsa.2019.EN-1674</a></p> <p>.</p> <p>Permission for reuse occurrence outputs records is granted under the terms of a CC-BY-NC license.<br> Permission for reuse hunting yield outputs is granted under the terms indicated by EFSA.</p>
Figure 4 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 4. Copepod species composition (centre) and copepodid stage structures of the dominant species (left: Oyashio region, right: Okhotsk Sea). All data are integrated means of a 0– 500 m water column based on the IONESS samples in the Oyashio region (St. 19) and Okhotsk Sea (St. OK24) from October to November 1996. Error bars for the copepodid stage indicate standard deviations of each daily duplicate.
Figure 3 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 3. Vertical distribution of zooplankton biovolume in the Oyashio region (upper panels) and Okhotsk Sea (lower panels) from September to December in 1996–1998. Note that the biovolume axes are not the same between panels. Tc: thermocline.
Data from: Geographic distribution of terpenoid chemotypes in Tanacetum vulgare mediates tansy aphid occurrence but not abundance
<p>Intraspecific variation of specialized metabolites in plants, such as terpenoids, are used to determine chemotypes. Tansy (<em>Tanacetum vulgare</em> L.) exhibits diverse terpenoid profiles that affect insect communities. However, it is not fully known whether patterns of their chemical composition and associated insects vary beyond the community scale. Here, we investigated the geographic distribution of mono- and sesquiterpenoid chemotypes in tansy leaves and their relationships with specific insect communities across Germany. We sampled tansy leaves from ten plants with and five plants without aphids in each of 26 sites along a north-south and west-east transect in Germany. Hexane-extracted metabolites from leaf tissues were analyzed by gas chromatography-mass spectrometry (GC-MS). Plant morphological traits, aphid occurrence and abundance, and occurrence of ants were recorded locally. The effect of plant chemotype, plant morphological parameters, and abiotic site parameters such as soil types, temperature and precipitation on insect occurrences were analyzed. Plants clustered into four monoterpenoid and four sesquiterpenoid chemotype classes. Monoterpene classes differed in their latitudinal distribution, whereas sesquiterpenes were more evenly distributed across the transect. Aphid and ant occurrence was influenced by monoterpenoids. Plants of monoterpenoid class 1 were colonized by aphids and ants significantly more often than expected by chance, whereas in other classes there were no significant differences. Aphid abundance was affected by soil type, and average annual temperature positively correlated with the occurrence of ants. We found significant geographic patterns in the distribution of tansy chemodiversity and show that monoterpenoids affect aphid and ant occurrence, while the soil type can influence aphid abundance. We show that geographic variation in plant chemistry influences insect community assembly on tansy plants.</p>
Fig. 3 in Observations On Species Abundance Distribution In Fly Collections
Fig. 3. Frequency polygons of 2-moving averaged frequencies. X and Y refer to the artificial collection containing the first 46 319 individuals and the last 46 524 individuals in the combined collection
Fig. 4 in Observations On Species Abundance Distribution In Fly Collections
Fig. 4. Further frequency polygons of 2-moving averaged frequencies. A, B and C refer to artificial collections mentioned in the text. Details see at Fig. 1.
Fig. 2 in Observations On Species Abundance Distribution In Fly Collections
Fig. 2. Frequency polygons of 2-moving averaged frequencies relating to combined collections. The 2003–2004 polygon is shifted in the figure by two abundance classes to the right. Details see at Fig. 1.
Fig. 2 in Abundance And Summer Distribution Of A Local Stock Of Black Sea Bottlenose Dolphins, Tursiops Truncatus (Cetacea, Delphinidae), In Coastal Waters Near Sudak (Ukraine, Crimea)
Fig. 2. Sightings of bottlenose dolphins near Sudak in 2011–2012. Sightings are indicated by circles of different size, depending on the group size category; sightings during the line transect survey (LTS) on August 4, 2012, are marked as filled circles, and other sightings (non LTS) are marked as empty circles. The LTS transects are shown as a zigzag line, and the LTS area is bordered by a contour line.
Рис. 2. Распределение Значений биомассы и численности Macoma balthica по станциЯм отбора проб. Fig. 2. Distribution of the Macoma balthica biomass and abundance values at sampling stations. in Species composition and distribution of bivalve mollusks in plankton and benthos in Nevelsky Strait in summer
Рис. 2. Распределение Значений биомассы и численности Macoma balthica по станциЯм отбора проб. Fig. 2. Distribution of the Macoma balthica biomass and abundance values at sampling stations.
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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.