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Correlation of native and exotic species richness: a global meta-analysis finds no invasion paradox across scales
This data set is also available on the Dryad Digital repository (link : https://doi.org/10.5061/dryad.59kv753) This dataset was created for investigating the biotic resistance hypothesis, that is, the idea that species‐rich communities are more successful at resisting invasion by exotic species than are species‐poor communities. It has been argued that native–exotic richness relationships (NERR) are negative at small spatial scales and positive at large scales, but evidence for the role of spatial scale on NERR has been contradictory. However, no formal quantitative synthesis had previously examined whether NERR is scale‐dependent across multiple studies, and previous studies on NERR have not distinguished spatial grain and extent, which may drive very different ecological processes Therefore, a global systematic review was carried out to create this dataset, which includes 204 individual cases of observational (non‐experimental) NERRs from 101 publications. Further, the above-mentioned hypotheses were investigated using a hierarchical mixed‐effects meta‐analysis, which showed that NERR was indeed highly scale dependent across studies and increased with the log of grain size. Also, no clear patterns of NERR across different spatial extents were found, suggesting that extent plays a less important role in determining NERR than does grain, although there was a complex interaction between extent and grain size. Almost all studies on NERR were found to have been conducted in North America, western Europe, and a few other regions, with little information on tropical or Arctic regions. NERR was also found to increase northward in temperate regions and vary with longitude. These results were published in the paper titled Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales (Peng et al. 2018), which represents the first global quantitative analysis of scale‐based NERR.
The effects of land-use history and the contemporary landscape on non-native plant invasion at local and regional scales in the French Broad Watersheds, 2007
Determining what factors explain the distribution of non-native invasive plants that can spread in forest-dominated landscapes could advance understanding of the invasion process and identify forest areas most susceptible to invasion. The researchers conducted roadside surveys to determine the presence and abundance of 15 non-native plant species known to invade forests in western North Carolina, USA. Prior to sampling, the researchers identified 15 non-native invasive plant species that were of concern in the study region. Generalized linear models were used to examine how contemporary and historic land use, landscape context, and topography influenced presence and abundance of the species at local and regional scales.
Pino Gate Prairie Dog Study: Landscape-scale Vegetation Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (1999-2002)
Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and co-occur in the arid grasslands of the southwestern United States and in Mexico. Their keystone status is attributed primarily to the effects of their burrowing and foraging behavior, but they differ ecologically in several important respects. We studied the comparative functional roles of these species where they co-occur at the Sevilleta National Wildlife Refuge, New Mexico, focusing on their impacts on grassland vegetation. We found that vegetation cover, structure, and species richness varied across a gradient extending out from the mound centers, and these patterns differed between prairie dog and kangaroo rat mounds. Certain species and functional groups of plants associated differentially with mounds and landscape patches occupied by prairie dogs and banner-tailed kangaroo rats. Where both species co-occurred locally there was greater soil disturbance, more organic material from their feces, and higher activity of other animals. The overall effect of these rodents was to create a mosaic of different patches across the landscape such that their combined activities increased andscape heterogeneity and plant species richness. Our results demonstrate complementary effects of two co-occurring keystone species on their associated biotic communities.
Pino Gate Prairie Dog Study: Mound-scale Vegetation Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2002)
Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and co-occur in the arid grasslands of the southwestern United States and in Mexico. Their keystone status is attributed primarily to the effects of their burrowing and foraging behavior, but they differ ecologically in several important respects. We studied the comparative functional roles of these species where they co-occur at the Sevilleta National Wildlife Refuge, New Mexico, focusing on their impacts on grassland vegetation. We found that vegetation cover, structure, and species richness varied across a gradient extending out from the mound centers, and these patterns differed between prairie dog and kangaroo rat mounds. Certain species and functional groups of plants associated differentially with mounds and landscape patches occupied by prairie dogs and banner-tailed kangaroo rats. Where both species co-occurred locally there was greater soil disturbance, more organic material from their feces, and higher activity of other animals. The overall effect of these rodents was to create a mosaic of different patches across the landscape such that their combined activities increased landscape heterogeneity and plant species richness. Our results demonstrate complementary effects of two co-occurring keystone species on their associated biotic communities.
Pino Gate Prairie Dog Study: Landscape-scale Ground-Dwelling Arthropod Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2001)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.), and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. Many arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was great habitat heterogeneity and increased arthropod diversity.
Pino Gate Prairie Dog Study: Mound-scale Ground-Dwelling Arthropod Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2001)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems,and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. Many arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was greater habitat heterogeneity and increased arthropod diversity. there was great habitat heterogeneity and increased arthropod diversity.
Pino Gate Prairie Dog Study: Landscape-scale Grasshopper Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2002)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. any arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was greater habitat heterogeneity and increased arthropod diversity.
Pino Gate Prairie Dog Study: Mound-scale Grasshopper Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2001)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. Many arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was greater habitat heterogeneity and increased arthropod diversity.
Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Soil Temperature Data (2006-2013)
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees. Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for whi
Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Water Potential Data (2006-2013)
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees.  Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for w
Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Sap Flow Data (2006-2013)
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees.  Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for w
Genome–scale approach to study the genetic relatedness among Brucella melitensis strains - wgMLST schema for Brucella melitensis
<p><strong>wgMLST schema for <em>Brucella melitensis</em></strong></p> <p> </p> <p><strong>Schema creation</strong></p> <p>The wgMLST schema was created using the 60 complete genomes of <em>Brucella melitensis </em>available at <a href="https://enterobase.warwick.ac.uk/species/index/ecoli">NCBI</a>, as of January 2019, with the chewBBACA v2.0.11 suite (<a href="https://github.com/B-UMMI/chewBBACA">https://github.com/B-UMMI/chewBBACA</a>), using a training file generated by Prodigal v2.6.3 from the <em>B. melitensis</em> 16M reference genome (RefSeq Accession NC_003317 and NC_003318). For curation and validation, the wgMLST schema was further populated with 212 additional draft genomes: 157 draft genomes (downloaded from NCBI in January 2019) and 55 draft genomes assembled with<a href="https://github.com/B-UMMI/INNUca"> INNUca v3.1</a> (PRJEB30030).</p> <p>File 'Bmelitensis_wgMLST_2656_schema.tar.gz' contains the wgMLST schema formatted for chewBBACA and includes a total of 2656 loci.</p>
Chronicles of Nature Calendar, a Long-term and Large-scale Multitaxon Database on Phenology
<p>We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.</p> <p>The recording scheme implemented at nature reserves offers unique opportunities for addressing community-level change across replicate local communities. These data have been systematically collected not as independent monitoring efforts, but using a shared and carefully standardized protocol adapted for each local community. Thus, variability in observation effort is of much less concern than in most other distributed cross-taxon phenological monitoring schemes. To enable analyses of higher-level taxonomical groups, we have included taxonomic classifications for the species in the database.</p> <p>The compilation of the data in a common database was initiated in the context of the project “Linking environmental change to biodiversity change: long-term and large-scale data on European boreal forest biodiversity” (EBFB), funded for 2011-2015 by the Academy of Finland, and continued with the help of other funding to OO since 2016. We organized a series of project meetings that were essential for data acquisition, digitalization and unification. These meetings were organized in Ekaterinburg (Russia) by the Institute of Plant and Animal Ecology, Ural Branch of RAS (Russian Academy of Sciences) in 2011; in Petrozavodsk (Russia) by the Forest Research Institute, at the Karelian Research Center, RAS in 2013; in Miass (Russia) by the Ilmen Nature Reserve in 2014; in Krasnoyarsk (Russia) by the Stolby Nature Reserve in 2014; in Artybash (Russia) by the Altaisky Nature Reserve in 2015; in Listvyanka, Lake Baikal (Russia) by the Zapovednoe Pribajkalje Nature Reserve in 2016; in Roztochja (Ukraine) by the Ministry of Natural Resources of Ukraine in 2016; in Puschino (Russia) by the Prioksko-Terrasnyj Nature Reserve in 2017, in Vyshinino (Russia) by the Kenozero National Park in 2018, and in St Petersburg (Russia) by the Komarov Botanical Institute of the Russian Academy of Sciences in 2019.</p> <p>The compilation of the data in a common database was initiated in the context of the project “Linking environmental change to biodiversity change: long-term and large-scale data on European boreal forest biodiversity” (EBFB), funded for 2011-2015 by the Academy of Finland, and continued with the help of other funding to OO since 2016. We organized a series of project meetings that were essential for data acquisition, digitalization and unification. These meetings were organized in Ekaterinburg (Russia) by the Institute of Plant and Animal Ecology, Ural Branch of RAS (Russian Academy of Sciences) in 2011; in Petrozavodsk (Russia) by the Forest Research Institute, at the Karelian Research Center, RAS in 2013; in Miass (Russia) by the Ilmen Nature Reserve in 2014; in Krasnoyarsk (Russia) by the Stolby Nature Reserve in 2014; in Artybash (Russia) by the Altaisky Nature Reserve in 2015; in Listvyanka, Lake Baikal (Russia) by the Zapovednoe Pribajkalje Nature Reserve in 2016; in Roztochja (Ukraine) by the Ministry of Natural Resources of Ukraine in 2016; in Puschino (Russia) by the Prioksko-Terrasniy Nature Reserve in 2017, in Vyshinino (Russia) by the Kenozero National Park in 2018, and in St Petersburg (Russia) by the Komarov Botanical Institute of the Russian Academy of Sciences in 2019.</p> <p>The compilation of the data into a common database was conducted by the database coordinators (EM and CL) in Helsinki (Finland). Those participants that already held the data in digital format submitted it in the original format, and those that had the data only in paper format digitized it using Excel-based templates developed in the project meetings. Submitted data were processed by the database coordinators according to the following steps:</p> <p> </p> <ol> <li>The data were formatted so that each observation (the phenological date of a particular event in a particular locality and year) formed one row in the data table (e.g. un-pivoting tables that involved several years as the columns). The phenological event names were split into event type (e.g. “first occurrence“) and species name.</li> <li>The event type names (provided originally typically in Russian) were translated into English and the species names (usually provided in Russian) were identified to scientific names, using dictionaries that were partly developed and verified in the project meetings. All scientific names were periodically verified by mapping them to the Global Biodiversity Information Facility (GBIF) backbone taxonomy.</li> <li>We associated each data record with the following set of information fields: (1) project name, i.e. the source organization, (2) dataset name, (3) locality name, (4) unique taxon identifier, (5) scientific taxon name, and (6) event type.</li> <li>We imported the data records in the main database (maintained as an EarthCape database at <a href="https://ecn.ecdb.io">https://ecn.ecdb.io</a>). During the import, the taxonomic names, locality names, and dataset names were matched against already existing records.</li> </ol> <p>There are at least 200 National Parks and Nature Reserves that collect Chronicles of Nature Book data (in Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine and Uzbekistan). Out of these, the current database covers data from 62 organizations, with the highest coverage in European Russia. The collection of new data continues in most parks. Thus, the database is not complete, and we aim to support the database with updates, depending on the interest of new partners to join, as well as resources and funding. The technical validation procedures described below will also be applied to any new information included in the database.</p> <p>Data is available as a data package (<a href="http://frictionlessdata.io/docs/data-package/#tabular-data">http://frictionlessdata.io/docs/data-package/#tabular-data</a>) and will be updated with new versions as project goes on.</p>
Repository for: Reddin et al. 2020. Marine clade sensitivities to climate change conform across time scales
<p>Contains R code and data to produce the main results (and some supplementary results) of the publication, Reddin et al. <em>Marine clade sensitivities to climate change conform across time scales</em>.</p>
Supplementary Files to "Towards a global understanding of vegetation-climate dynamics at multiple time scales"
<p><strong>TimeSeriesPaper_main_processing.html</strong></p> <p>Html version of Jupyter notebook exemplifying main data analysis steps in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020). Please see the publication for further details. Notebook written in Julia v0.6</p> <p><strong>Fig2_Co_Oscillation_Regimes.nc</strong></p> <p>Data underlying Fig. 2 in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020).</p> <p>Classification of land surface by dominant scale of variability in Normalized Difference Vegetation Index (NDVI), air temperature, and precipitation. Dominant scale of variability was determined after Fourier decomposition, separately for each grid cell and summarized as unique combinations between variables (S - short-term, A - seasonal, L - longer-term, T - trend, listed in order NDVI, air temperature, precipitation). The semi-annual cycle is included in the seasonal band. Please see the publication for further details.</p>
Data to "Near-optimal combination of disparity across a log-polar scaled visual field"
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Maiello, G., Chessa, M., Bex, P. J., & Solari, F. (2020) Near-optimal combination of disparity across a log-polar scaled visual field. <em>PLOS Computational Biology, 16</em>(4), e1007699. <a href="https://doi.org/10.1371/journal.pcbi.1007699">https://doi.org/10.1371/journal.pcbi.1007699</a></p>
Research data supporting "Atomic-Scale Patterning of Arsenic in Silicon by Scanning Tunneling Microscopy"
<p>Research data supporting the publication: Stock, T. J. Z, <em>et. al.</em>, <strong>2020</strong>, Atomic-Scale Patterning of Arsenic in Silicon by Scanning Tunneling Microscopy, <em>ACS Nano</em>, https://dx.doi.org/10.1021/acsnano.9b08943</p>
ProGene - A Large-scale, High-Quality Protein-Gene Annotated Benchmark Corpus
<p>The Pro(tein)/Gene corpus was developed at the JULIE Lab Jena under supervision of Prof. Udo Hahn.</p> <p>The goals of the annotation project were</p> <ul> <li>to construct a consistent and (as far as possible) subdomain-independent/-comprehensive protein-annotated corpus</li> <li>to differentiate between protein families and groups, protein complexes, protein molecules, protein variants (e.g. alleles) and elliptic enumerations of proteins.</li> </ul> <p>The corpus has the following annotation levels / entity types:</p> <ul> <li>protein</li> <li>protein_familiy_or_group</li> <li>protein_complex</li> <li>protein_variant</li> <li>protein_enum</li> </ul> <p>For definitions of the annotation levels, please refer to the Proteins-guidelines-final.doc file that is found in the download package.</p> <p>To achieve a large coverage of biological subdomains, document from multiple other protein / gene corpora were reannotated. For further coverage, new document sets were created. All documents are abstracts from PubMed/MEDLINE. The corpus is made up of the union of all the documents in the different subcorpora.<br> All document are delivered as MMAX2 (http://mmax2.net/) annotation projects.</p>
Lyman-alpha tomographic map of the large-scale matter distribution using the eBOSS - Stripe 82 data
<p><strong>Lyman-alpha tomography map using DR16 eBOSS data</strong></p> <p>This data release contains products associated to the Lyman-alpha large-scale tomographic map realized with the 16<sup>th</sup> data release of SDSS-eBOSS. The densest Lyman-alpha forest set of eBOSS in the Stripe 82 field is used : 220 deg<sup>2</sup> wide field with a 37 deg<sup>-2</sup> density. A Lyman-alpha flux contrast map over a volume of 0.94 h<sup>-3</sup>Gpc<sup>3</sup> is obtained. Voids and protoclusters are detected in this portion of the sky.</p> <p>For more details : see https://arxiv.org/abs/2004.01448</p> <p>All the data detailed below can be opened by using the short python script read_data_release.py.</p> <p><strong>Pixels and map data</strong></p> <p>The pixel file pixels_lya_tomography_stripe82.bin was used to create the Lya tomographic map map_lya_tomography_stripe82.bin by using the dachshund algorithm (https://github.com/caseywstark/dachshund).</p> <p>Pixel and map file are in the binary numpy format. Pixels are created from 8999 Lya forests positioned from -43° to +45° in the RA(J2000) direction, from -1.25° to +1.25° in the DEC(J2000) direction and from z=2.1 to z=3.2. The (RA,DEC,z) coordinates are converted to (X,Y,Z) coordinates in Mpc.h<sup>-1</sup>. The pixel file shares the same origin than the map. Each pixel is defined by a set of five floats corresponding to (X, Y, Z, σ, 𝛿) where 𝛿 is the Lyman-alpha flux contrast and σ its associated error based on pipeline noise.</p> <p>The map is also a binary numpy file. It contains a (6354,181,834) Mpc.h<sup>-1</sup> cube of Lyman-alpha flux contrast with a pixel shape (2928,90,417). The origin of the map (0,0,0) corresponds to the coordinates RA=-43°, DEC=-1.25° and z=2.1 and in the cube coordinate to (X,Y,Z)=(0,0,0) Mpc.h<sup>-1</sup>.</p> <p>Note that to obtain this map, the pixel file was first separated to parallelize the tomographic procedure. In comparison to the map detailed in the linked article, this map is rebinned to be less voluminous. Furthermore, a mask is applied to the map where the distance to the nearest line-of-sight of the pixel file is below 20 Mpc.h<sup>-1</sup>. At these locations, map flux contrast is put to 0.</p> <p> </p> <p><strong>Derived catalog data</strong></p> <p>Voids and proto-cluster searches are applied to the tomographic map. The results of this procedure, along with additional catalog cut is given in this data release. Catalogs of voids (catalog_voids_lya_stripe82_*.fits) and proto-clusters (catalog_protoclusters_lya_stripe82_*.fits) are given in the (X,Y,Z) and (RA,DEC,z) coordinates of the map, sharing the same origin. The catalogs are in the FITS format which can be opened with the fitsio python library.</p>
Replication code and data for: "Machine Learning Predicts Large Scale Declines in Native Plant Phylogenetic Diversity."
<p>Replication code and data for the paper: "Machine Learning Predicts Large Scale Declines in Native Plant Phylogenetic Diversity." The following files are included in this repository:</p> <p>1) R scripts (numbered 0 through 9) include replication code for data analysis</p> <p>2) Datasets (6 zip folders) contain the data analyzed in the R scripts</p> <p> </p> <p> </p>
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.