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Local Governance in Ukraine during the full-scale Russian invasion. – Merged data from online surveys of local self-government authorities by the Congress of Local and Regional Authorities of the Council of Europe in 2022 and Kyiv School of Economics in 2024.
The dataset includes responses from two waves of online surveys targeting local self-government representatives in Ukraine, with a focus on crisis governance during the ongoing Russian war. The first wave was conducted from August 30 to September 20, 2022, by the Congress of Local and Regional Authorities of the Council of Europe, yielding 241 responses (16% of all Ukrainian local communities). The second wave was conducted by Kyiv School of Economics from January 1 to March 12, 2024, with 181 responses (14% of government-controlled municipalities). Data formats include CSV and SAV files, along with an XSL codebook for both waves. The merged dataset comprises 442 responses from small, medium, and large municipalities under varied security conditions, with a total file size of approximately 4 MB.
Invasive pneumococcal diseases in children and adults before and after introduction of the 10-valent pneumococcal conjugate vaccine into the Austrian national immunization program
<p>The dataset contains case-based data on invasive pneumococcal disease in Austria, 2009/01 to 2017/02, by year and month of diagnosis, serotype and clinical presentation. Cases are anonymised by using a random ID.</p>
Non-invasive modulation of human corticostriatal activity [Dataset]
<p>This dataset contains resting-state functional MRI data used in the study "Non-invasive modulation of human corticostriatal activity" (Caballero-Insaurriaga et al, PNAS, 2023).</p> <p>In this study two datasets were used: one from a transcranial static-magnetic-field stimulation (tSMS) experiment (tSMS20) and another one from the Human Connectome Project (HCP100). The tSMS20 dataset was originally acquired for a previous study tSMS over the Supplementary Motor Area (Pineda-Pardo et al, Commun Biol, 2019). The regions used in the study are also provided.</p> <p>As for the tSMS20 dataset, the stimulation protocol consisted of 30-minute tSMS using a single magnet placed over the supplementary motor area (SMA). Each subject underwent two stimulation sessions (real and sham) in two separate days, whose order was randomized. In each session, structural MRI was acquired before tSMS, and resting-state fMRI before and after. Structural images were T1-weighted (T1w), with 1 mm isotropic voxel. Functional data was acquired in 10 minutes-long sessions, TR/TE 2400/30 ms (250 volumes per session), with 3mm isotropic voxel. The preprocessed resting-state fMRI data are included in this repository (see dataset_description.txt file and Pineda-Pardo et al, Commun Biol, 2019 for more details)</p> <p>As for the HCP100 dataset, only the subject list is included, as data are already publicly available from the HCP initiative.</p> <p>If you use this data in a publication, please cite:</p> <p>Pineda-Pardo, J. A., Obeso, I., Guida, P., Dileone, M., Strange, B. A., Obeso, J. A., Oliviero, A. & Foffani, G. Static magnetic field stimulation of the supplementary motor area modulates resting-state activity and motor behavior. <em>Communications Biology</em> <strong>2,</strong> (2019)</p> <p>Caballero-Insaurriaga, J., Pineda-Pardo, J. A., Obeso, I., Oliviero, A. & Foffani, G. Non-invasive modulation of human corticostriatal activity. <em>Proceedings of the National Academy of Sciences of the United States of America</em> (2023)</p>
IPBES Invasive Alien Species Assessment, list of literature for Chapter 3
<p>This list of literature represents the literature reviewed for chapter 3 of IPBES thematic assessment of invasive alien species and their control. Please see respective data management report for more details.</p><p>For each data management report, please refer to below links:</p><p>3.2.1 Socio-cultural drivers and social values: <a href="http://doi.org/10.5281/zenodo.8031019">10.5281/zenodo.8031019</a></p><p>3.2.2.1 Regional and national changes in human population density: <a href="http://doi.org/10.5281/zenodo.8031519">10.5281/zenodo.8031519</a></p><p>3.2.2.2 Human migration: <a href="http://doi.org/10.5281/zenodo.8032105">10.5281/zenodo.8032105</a></p><p>3.2.2.3 International crises: armed conflict and humanitarian aid: <a href="http://doi.org/10.5281/zenodo.8032211">10.5281/zenodo.8032211</a></p><p>3.2.2.4 Urbanisation: <a href="http://doi.org/10.5281/zenodo.5553573">10.5281/zenodo.5553573</a></p><p>3.2.3.5 Externalities of negative impacts and cost: <a href="http://doi.org/10.5281/zenodo.8032327">10.5281/zenodo.8032327</a></p><p>3.2.4.1 Research: <a href="http://doi.org/10.5281/zenodo.5717444">10.5281/zenodo.5717444</a></p><p>3.2.4.2 Development of communication technology:<a href="http://doi.org/10.5281/zenodo.8035280">10.5281/zenodo.8035280</a></p><p>3.2.4.3 Breeding and genomic technologies: <a href="http://doi.org/10.5281/zenodo.5591058">10.5281/zenodo.5591058</a></p><p>3.2.5 Policies, governance, and institutions: <a href="http://doi.org/10.5281/zenodo.5717451">10.5281/zenodo.5717451</a></p><p>3.3.1.1 Introductions intentionally or accidentally from agriculture, forestry, fisheries, and aquaculture: <a href="http://doi.org/10.5281/zenodo.8035344">10.5281/zenodo.8035344</a></p><p>3.3.1.2 Fragmentation of ecosystems: <a href="http://doi.org/10.5281/zenodo.8035352">10.5281/zenodo.8035352</a></p><p>3.3.1.3 Creation of anthropogenic corridors: <a href="http://doi.org/10.5281/zenodo.5529361">10.5281/zenodo.5529361</a></p><p>3.3.1.5 Changes in landscape - seascape disturbance regimes (intensification and reduction): <a href="http://doi.org/10.5281/zenodo.8036425">10.5281/zenodo.8036425</a></p><p>3.3.1.6 Landscape and seascape degradation: <a href="http://doi.org/10.5281/zenodo.5533042">10.5281/zenodo.5533042</a></p><p>3.3.2.3 Mining (minerals, metal, oil, fossils fuels): <a href="http://doi.org/10.5281/zenodo.8036498">10.5281/zenodo.8036498</a></p><p>3.3.3.1 Eutrophication and nitrient deposition: <a href="http://doi.org/10.5281/zenodo.8036544">10.5281/zenodo.8036544</a></p><p>3.3.3.2 Other contaminants in water and soil: <a href="http://doi.org/10.5281/zenodo.5587987">10.5281/zenodo.5587987</a></p><p>3.3.3.3 Marine debris: <a href="http://doi.org/10.5281/zenodo.5588374">10.5281/zenodo.5588374</a></p><p>Box 3.8: <a href="http://doi.org/10.5281/zenodo.5588389">10.5281/zenodo.5588389</a></p><p>3.3.4.1 Temperature change: <a href="http://doi.org/10.5281/zenodo.8036828">10.5281/zenodo.8036828</a></p><p>3.3.4.2 Precipitation: <a href="http://doi.org/10.5281/zenodo.8036879">10.5281/zenodo.8036879</a></p><p>3.3.4.3 Climate extremes: <a href="http://doi.org/10.5281/zenodo.5533052">10.5281/zenodo.5533052</a></p><p>3.3.4.4 Carbon dioxide enrichment in air, water: <a href="http://doi.org/10.5281/zenodo.8037007">10.5281/zenodo.8037007</a></p><p>3.3.4.5 Fire regime changes: <a href="http://doi.org/10.5281/zenodo.5591070">10.5281/zenodo.5591070</a></p><p>3.3.4.6 sea level rise: <a href="http://doi.org/10.5281/zenodo.8037086">10.5281/zenodo.8037086</a></p><p>Box 3.9 Assisted colonisation: <a href="http://doi.org/10.5281/zenodo.5535113">10.5281/zenodo.5535113</a></p><p>3.3.5.1 Biotic facilitation: <a href="http://doi.org/10.5281/zenodo.5722695">10.5281/zenodo.5722695</a></p><p>3.3.5.2 Unintended consequences of management (including biological control): <a href="http://doi.org/10.5281/zenodo.8037235">10.5281/zenodo.8037235</a></p><p>3.4.1 Natural hazards: <a href="http://doi.org/10.5281/zenodo.5533488">10.5281/zenodo.5533488</a></p><p>3.5.4 Urbanisation and Pollution: <a href="http://doi.org/10.5281/zenodo.5588440">10.5281/zenodo.5588440</a></p><p>Figure 3.34: <a href="http://doi.org/10.5281/zenodo.7861162">10.5281/zenodo.7861162</a></p><p> </p>
Invasive grass litter suppresses a native grass species and promotes disease
Plant litter can alter ecosystems and promote plant invasions by altering resource availability, depositing phytotoxins, and transmitting microorganisms to living plants. Transmission of microorganisms from invasive plant litter to live plants may gain importance as invasive plants, which often escape pathogens upon introduction to a new range, acquire new pathogens over time. It is unclear, however, if invasive plant litter affects native plant communities by promoting disease. Microstegium vimineum is an invasive grass that suppresses native populations, in part through litter production, and has acquired new fungal leaf spot diseases since its introduction to the United States. In a greenhouse experiment, we evaluated how M. vimineum litter and its pathogens mediated competition with the native grass Elymus virginicus. Microstegium vimineum litter promoted disease on E. virginicus and suppressed establishment and biomass of both species. Litter had stronger negative effects on E. virginicus than M. vimineum, increasing the relative biomass of M. vimineum. Live plant competition reduced biomass of both species and live M. vimineum increased disease incidence on E. virginicus. Altogether, invasive grass litter suppressed both species, ultimately favoring the invasive species in competition, and increased disease incidence on the native species.
Invasion dynamics of quagga mussels within a Southern California reservoir and its spatially intermittent watershed
Since its discovery in Lake Mead, Nevada in 2007, the invasive quagga mussel (Dreissena rostriformis bugensis) spread throughout the lower Colorado River drainage and into connected Southern California water systems. In December 2013, quagga mussels were found in Lake Piru, California, a reservoir with no connection to the Colorado River drainage. An initial “boom” period occurred in the first year after colonization. High densities and settlement rates continued for three years while lake water levels were low and relatively stable, despite periodic removals of mussels from lake infrastructure. Mussels were initially restricted to hard substrates but were regularly found on soft sediments within two years of colonization. Storms in 2017 dramatically increased the lake level and deposited substantial sediment, which eliminated mussels on soft sediments and reduced the overall mussel population. Reproduction and juvenile settlement rebounded within 6 months, despite the low population of adult mussels in the lake. Environmental conditions, particularly fill status and water temperature, rather than adult density, appear to be the primary driver of veliger abundance in this system, while recruitment was primarily explained by veliger abundance. Elevated water releases from the reservoir increased the flux of veligers downstream and led to mussel recruitment >15 km downstream. Sustained establishment of quagga mussels downstream has not occurred in the Santa Clara River and seems unlikely due to the unstable habitat conditions. However, periodic downstream colonization increases the likelihood for the infestation to spread and impact agricultural and municipal water systems that receive water from the river.
Mohonk Preserve Stream Water Quality Invasive Species and Macroinvertebrate Sampling in from 2017-Present
The mission of the Mohonk Preserve is to protect the Shawangunk Mountains region and inspire people to care for, enjoy, and explore their natural world. Among these 8,000 acres are the vernal pools, permanent springs, tributaries, Humpo Marsh, and the Humpo Kill, and parts of the Kleine Kill and Coxing Kill watersheds within the Hudson River Drainage Basin. Not only are the areas around the Shawangunks established habitats for New York State (NYS) protected species, including an Audubon-designated Important Bird Area, but the watershed also encapsulates more than one agricultural land use area, as well as Rondout Creek, which is an important waterway for the New York City water supply. A conservation plan must be implemented in these areas in particular, keeping in line with the Mohonk Preserves goal to conserve the Shawangunk region for both humans and the greater ecosystem within it. Recognizing the immediate and long-term conservation needs of the streams in this region by employing volunteer data collection will be a catalyst to the Preserves understanding of which environmental threats of this area should be prioritized. The StreamWatch citizen science program will be the newest addition to an array of volunteer research areas, which include collection of weather data, phenology observations, monitoring of peregrine falcon breeding activities, and monitoring of fall hawk migration. Using concise stream monitoring protocol designed for volunteer safety and maximum data accuracy, StreamWatch will evaluate water quality using an array of parameters. Following thorough observation and assessment (which will include analyzing appearance and smell of the water, shape of the stream, canopy cover, nearby land uses, recent weather, and presence of riparian vegetation including invasive species) water quality will be evaluated by means of temperature, dissolved oxygen, pH, and turbidity measurements, in addition to a macroinvertebrate count. Width and depth will also be
Forest Invasibility in Communities in Southeastern New York
While biological invasions have been the subject of considerable attention both historically and recently the factors controlling the susceptibility of communities to plant invasions remain controversial. In order to examine relationships between plant community characteristics, soil characteristics, and nonnative plant invasion, we surveyed 44 sites in southeastern New York State, USA in the summer of 1998. We examined both plant community characteristics (diversity and species membership) and soil characteristics (litter depth, pH, nitrogen, calcium, magnesium, cation exchange capacity, phosphorus, and soil texture). The data collected was then used to study patterns of invasion both within and among broad forest community types, in order to determine what factors were most closely associated with the success of invasive plants
Invasive buffel grass (Cenchrus ciliaris) increases water stress and reduces growth of native foothills palo verde (Parkinsonia microphylla) seedlings in pot experiments
Although buffel grass (Cenchrus ciliaris) invasions on several continents have significant ecological impacts, little information is available on its effect on seedling emergence and establishment of native vegetation. In highly impacted areas of the Sonoran Desert of North America, perennial plants are particularly vulnerable during their seedling stage. We studied the impact of buffel grass on the emergence, survival, and water stress in the seedlings of a locally dominant native tree, the foothills palo verde (Parkinsonia microphylla), using two pot experiments. In the first experiment, we compared the germination, growth, and survival of concentric rings of palo verde seedlings around mature individuals of buffel grass, a native shrub of a similar diameter and height to buffel grass, or in a pot with bare soil. In the second experiment, we compared the competitive effects of buffel grass seedlings on palo verde seedlings with the effects of conspecific seedlings, again using germination, growth, and survival as metrics. We followed up both experiments by quantifying the ratio of stable carbon isotopes in the tissues of the palo verde seedlings, which can be an indicator of water stress. We found evidence of relatively greater water stress in palo verde seedlings grown with buffel grass seedlings in pots than those grown with no competitor, and reduced survival of palo verde seedlings when grown with mature buffel grass. Our results highlight the need for more manipulative studies of density to improve mechanistic understanding of population dynamics, and to forecast how populations and communities will respond in the long term to perturbations such as invasion.
Throw trap and electrofishing data collected during 1996–2022 from the Everglades, Florida, United States for the publication "Hydrology-mediated ecological function of a large wetland threatened by an invasive predator"
Asian swamp eels (Monopterus albus/javanensis complex) were first reported from Florida in 1997 and the Everglades in 2007; swamp eels have been established in Taylor Slough of Everglades National Park since 2014. This dataset incorporates plot-level mean densities (# of individuals per square meter) of common aquatic animals collected during 1996–2022 from 24 sites across four regions of the Everglades: Taylor Slough, Shark River Slough, Water Conservation Area 3, and the C-111 Panhandle. Prey species included are the six most common small fishes prior to swamp eel invasion of Taylor Slough (1996–2009) and the three common decapod species (two crayfish species and grass shrimp). An annual index of mean wet season electrofishing catch-per-unit-effort of swamp eels, Mayan cichlids (Mayaheros uruphthalmus), and the three other large 'top predator' fishes (Amia calva, Lepisosteus platyrhincus, Micropterus salmoides) is included for plots where electrofishing was performed from 1997-2021. Hydrologic measures used in analyses are included.
Geographical variation in vegetative growth and sexual reproduction of the invasive Spartina alterniflora in China
We studied patterns in vegetative growth and sexual reproduction of introduced S. alterniflora at 22 sites at 11 geographic locations over a latitudinal gradient of ~2000 km from Tanggu (39.05 °N, high latitude) to Leizhou (20.90 °N, low latitude) in China. We further evaluated the basis of phenotypic differences by growing plants from across the range in a common garden for 2 growing seasons. We found distinct latitudinal clines in plant height, shoot density, and sexual reproduction across latitude. Some traits exhibited linear relationships with latitude; others exhibited hump-shaped relationships. We identified correlations between plant traits and abiotic conditions such as mean annual temperature, growing degree days, tidal range, and soil nitrogen content. However, geographic variation in all but one trait disappeared in the common garden, indicating that variation largely due to phenotypic plasticity. Only a slight tendency for latitudinal variation in seed set persisted for two years in the common garden, suggesting that plants may be evolving genetic clines for this trait. Note that these data were collected as part of a National Natural Science Foundation of China (NSFC) funded study led by Yihui Zhang in collaboration with GCE-LTER.
Contrasting plant adaptation strategies to latitude in the native and invasive range of Spartina alterniflora: geographic survey (2014) and Common garden (2015-2017)
We examined trait differences and evolution across geographic clines among continents of the intertidal grass Spartina alterniflora within its invasive and native ranges. Between September and November 2014, we sampled vegetative and reproductive traits in the field at 20 sites over 20° latitude in China (invasive range) and 28 sites over 17° latitude in the US (native range). We grew both Chinese and US plants in a greenhouse common garden for three years (2015 - 2017) to determine if differences in performance of S. alterniflora between the introduced and native ranges were due to genetic differences or differences in abiotic conditions.
Data to support "Marks et al 2016. Assessment of control methods for the invasive seaweed Sargassum horneri in California, USA"
Determining the feasibility of controlling marine invasive algae through removal is critical to developing a strategy to manage their spread and impact. To inform control strategies, we investigated the efficacy and efficiency of removing an invasive seaweed, Sargassum horneri, from rocky reefs on Santa Catalina Island, southern California, USA. We tested the efficacy of removal as a means of reducing colonization and survivorship by clearing S. horneri from 60 m2 circular plots. We also examined whether S. horneri is able to regenerate from remnant holdfasts with severed stipes to determine whether efforts to control S. horneri require the complete removal of entire individuals. In addition, we developed efficiency metrics for manual removal with and without the aid of an underwater suction device. These data have been presented in: Marks, L.M., D.C. Reed and A.K. Obaza. 2016. Assessment of control methods for the invasive seaweed Sargassum horneri in California, USA. Management of Biological Invasions, DOI: 10.3391/mbi.2017.8.2.08, <ulink url="https://doi.org/10.3391/mbi.2017.8.2.08">https://doi.org/10.3391/mbi.2017.8.2.08</ulink>
Logical model for Molecular Pathways Enabling Tumour Cell Invasion and Migration
<p>Understanding the etiology of metastasis is very important in clinical perspective, since it is estimated that metastasis accounts for 90% of cancer patient mortality. Metastasis results from a sequence of multiple steps including invasion and migration. The early stages of metastasis are tightly controlled in normal cells and can be drastically affected by malignant mutations; therefore, they might constitute the principal determinants of the overall metastatic rate even if the later stages take long to occur. To elucidate the role of individual mutations or their combinations affecting the metastatic development, a logical model has been constructed that recapitulates published experimental results of known gene perturbations on local invasion and migration processes, and predict the effect of not yet experimentally assessed mutations. The model has been validated using experimental data on transcriptome dynamics following TGF-β-dependent induction of Epithelial to Mesenchymal Transition in lung cancer cell lines. A method to associate gene expression profiles with different stable state solutions of the logical model has been developed for that purpose. In addition, we have systematically predicted alleviating (masking) and synergistic pairwise genetic interactions between the genes composing the model with respect to the probability of acquiring the metastatic phenotype. We focused on several unexpected synergistic genetic interactions leading to theoretically very high metastasis probability. Among them, the synergistic combination of Notch overexpression and p53 deletion shows one of the strongest effects, which is in agreement with a recent published experiment in a mouse model of gut cancer. The mathematical model can recapitulate experimental mutations in both cell line and mouse models. Furthermore, the model predicts new gene perturbations that affect the early steps of metastasis underlying potential intervention points for innovative therapeutic strategies in oncology.</p> <p> </p> <p>Included files:</p> <ul> <li>Master Model: the model includes detailed regulation of the major players involved in the crosstalks between Notch and p53 pathways</li> <li>Modular Model: the model is a reduction of the master model. To reduce the master model, we lumped together some entities that belonged to a module.</li> </ul>
Potential effects of invasive plants on mosquito life-history traits.
<p>Invasive plants offer suitable oviposition sites for some vector species (a); invasive plant litter increases proliferation of immature vectors (b); dense canopy cover or thickets of invasive plants provide suitable micro-habitats for adult mosquitoes (c); nectariferous flowers (d) and extra-floral glands (e) of invasive plants are important sugar sources for adult vectors; invasive plants can influence the pathogen transmission ability of the vector (f).</p> <p>A grey-scaled version was published as Figure 1 in <a href="https://doi.org/10.3390/v13010032">Agha et al. (2020)</a>.</p> <p>Required software: <a href="https://krita.org/">Krita</a> and <a href="https://www.gimp.org/">Gimp</a>.</p>
Global Register of Introduced and Invasive Species: GRIIS DwCA
Published via GBIF by the Invasive Species Specialist Group (ISSG). The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified checklists (inventories) of introduced (alien) and invasive alien species at the country, territory, and associated island level. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 which is on-going, aims to achieve global coverage including non-party countries and all overseas territories of countries e.g. Netherlands, France and United Kingdom. Species belonging to all Kingdoms are covered as well as occurring in all Environment/systems. Country/ Territory/ Island checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records as well as those under review are presented on the online GRIIS website (www.griis.org). Individual species records are flagged with a __yes__ for verification. Only verified checklists/ species records are presented on the GBIF Portal. <p></p>https://www.gbif.org/dataset/search?publishing_org=cdef28b1-db4e-4c58-aa71-3c5238c2d0b5<p></p>
Country Compendium of the Global Register of Introduced and Invasive Species: Standardization to Records in World Flora Online or the World Checklist of Vascular Plants
<p>The <strong>Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS)</strong> is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. This compendium is available via <a href="https://zenodo.org/records/6348164">Zenodo</a> and was described by Pagad et al. <a href="https://www.nature.com/articles/s41597-022-01514-z">2022</a>:</p><ul><li>Shyama Pagad, Stewart Bisset, & Melodie A. McGeoch. (2022). Country Compendium of the Global Register of Introduced and Invasive Species. Dataset. (V1_0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6348164">https://doi.org/10.5281/zenodo.6348164</a></li><li>Pagad, S., Bisset, S., Genovesi, P. <i>et al.</i> Country Compendium of the Global Register of Introduced and Invasive Species. <i>Sci Data</i> <strong>9</strong>, 391 (2022). <a href="https://doi.org/10.1038/s41597-022-01514-z">https://doi.org/10.1038/s41597-022-01514-z</a></li></ul><p> </p><p>Here I provide direct and fuzzy matches for species listed for the Plantae Kingdom in GRIIS with accepted plant names in <strong>World Flora Online</strong> (<a href="https://www.worldfloraonline.org/downloadData">version 2023.03</a>; Borsch et al. <a href="https://doi.org/10.1002/tax.12373">2020</a>) or the <strong>World Checklist of Vascular Plants</strong> (<a href="https://doi.org/10.34885/nswv-8994">version 10</a>; Govaerts et al. <a href="https://www.nature.com/articles/s41597-021-00997-6">2021</a>). Matching was done in <i>R</i> through the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>). The taxonomic standardization process was similar to the one completed <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">during the preparation of the third major release</a> of the <a href="https://apps.worldagroforestry.org/products/switchboard">Agroforestry Species Switchboard</a> and when preparing the <strong>GlobalUsefulNativeTrees database</strong> (GlobUNT; <a href="https://worldagroforestry.org/output/globalusefulnativetrees">https://worldagroforestry.org/output/globalusefulnativetrees</a>) .</p><p>Where a matching species was found in GlobUNT, the species name in the GlobUNT database has been shown. GlobUNT has been described in the following publication: Kindt et al. (<a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) <strong>GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration</strong>. <i>Sci Rep</i> <strong>13</strong>, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a>.</p><p>The developments of this dataset and GlobUNT were supported by the Darwin Initiative to project DAREX001 of <a href="https://www.darwininitiative.org.uk/project/DAREX001/"><i>Developing a Global Biodiversity Standard certification for tree-planting and restoration</i></a> and by Norway's International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the <a href="https://www.worldagroforestry.org/project/provision-adequate-tree-seed-portfolio-ethiopia"><i>Provision of Adequate Tree Seed Portfolio</i></a> project in Ethiopia. </p>
Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing
<p><strong>Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing</strong></p> <p><strong>Latest version of files: repository_v2.0.zip, Behavior Data_v2.0.xlsx and MRI IDs Testing&Replication Cohort.xlsx (please ignore repository.zip)</strong></p> <p>Open data repository Knab et al. Prediction of stroke outcome in mice based on non-invasvive MRI and behavioral testing</p> <p>Open code and documentation of prediction models available via <a href="https://github.com/major-s/mouse-mcao-outcome-predictor">https://github.com/major-s/mouse-mcao-outcome-predictor</a></p> <p><strong>Content:</strong></p> <p>README.txt</p> <p>This information</p> <p><strong>dat</strong></p> <p>Contains MRI data in NIFTI format and secondary data from atlas registration. For documentation of atlas registration files see https://pubmed.ncbi.nlm.nih.gov/28829217/<br>Files used for the manuscript:<br>t2.nii: t2 weighted image acquired 24 h post stroke<br>masklesion.nii: manually delineated lesion<br>x_masklesion.nii: lesion in atlas space<br>ix_ANO.nii: Allen brain atlas in native space (i.e. matching t2.nii)<br>Lesion volume was calculated by volume of voxels unequal 0 in x_masklesion.nii<br>Overlap of regions defined by ix_ANO.nii with masklesion.nii were used for calculating percent damage in each atlas region</p> <p><strong>prediction_models</strong></p> <p>Contains separated training and test data as xlsx and csv files with lesion volumes in cubic mm of the Allen brain atlas space, percent damage per atlas region and behavioral data. The training data was used as input for training prediction models in MATLAB, the results were created using the test data.<br>The files have following sturcture:<br>Column 1: animal ID<br>Columns 2-537: MRI regions (column title corresponds to the region number as used in the Allen common coordinate framework)<br>Column 538: lesion volume<br>Column 539: initial performance (subacute deficit) = mean performance/deficit on days 2-6<br>Column 540: mean performance/deficit on days 2-6 = initial performance (subacute deficit) - this column equals column 539 but has different header which was used to train the residual from initial deficit<br>Column 541: residual performance/deficit<br>Column 542: test or training group<br>Consecutive rows contain data for each animal specified by the animal id</p> <p>The repository also contains all trained models, prediction results for the test data and tables with resulting median absolute error (MedAE) and 5th, 25th, 75th and 95 absolute error quantiles for each model.<br>The model files end with '_models.mat' and contain 50 independently trained models each. Each model version is specified by number 1-50.<br>The result files end with '_test_results.mat' or '_test_results.xlsx', files with MedAE and quantiles end with '_test_errors.xlsx' or '_test_errors.csv. The common part of filenames specifies the used paradigm<br>Folder 'subacute deficit prediction' contains:<br> - initial_performance_from_lesion_volume: prediction of subacute deficit using lesion volume<br> - initial_performance_from_segmented_mri: prediction of subacute deficit using segmented mri<br>Folder 'long-term outcome prediction' contains:<br> - lesion_volume: prediction of residual deficit using lesion volume<br> - segmented_mri: prediction of residual deficit using segmented_mri<br> - initial_performance: prediction of residual deficit using subacute deficit<br>Folder 'mri_inc_oob_imp' contains models trained using increasing number of mri segments sorted according to the out-of-bag importance. The number of used segments is given in the file name. The models, results and errors are separated in subfolders.</p> <p>Files with equal file name and different extension always contain the same data</p> <p><strong>templates</strong><br>Allen atlas, template, brain mask, hemisphere masks, tissue probability masks in NIFTI format including annotations of region IDs and parameter.m file for use in MATLAB toolbox ANTx2<br> </p>
The open D1NAMO dataset: A multi-modal dataset for research on non-invasive type 1 diabetes management
<p>The description of the dataset is available at <a href="https://doi.org/10.1016/j.imu.2018.09.003">https://doi.org/10.1016/j.imu.2018.09.003</a></p> <p>The usage of wearable devices has gained popularity in the latest years, especially for health-care and well being. Recently there has been an increasing interest in using these devices to improve the management of chronic diseases such as diabetes. The quality of data acquired through <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/wearable-sensor">wearable sensors</a> is generally lower than what medical-grade devices provide, and existing datasets have mainly been acquired in highly controlled clinical conditions. In the context of the <em>D1NAMO</em> project — aiming to detect <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/glycemic">glycemic</a> events through non-invasive <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/ecg-abnormality">ECG pattern</a> analysis — we elaborated a dataset that can be used to help developing health-care systems based on wearable devices in non-clinical conditions. This paper describes this dataset, which was acquired on 20 healthy subjects and 9 patients with type-1 diabetes. The acquisition has been made in real-life conditions with the <em>Zephyr BioHarness 3</em> wearable device. The dataset consists of <em>ECG</em>, <em>breathing</em>, and <em><a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/accelerometer">accelerometer</a></em> signals, as well as <em>glucose</em> measurements and annotated <em>food pictures</em>. We open this dataset to the scientific community in order to allow the development and evaluation of diabetes management algorithms.</p>
Scanning the horizon for invasive plant threats using a data-driven approach
<p>This repository holds the data and code for the manuscript "Scanning the horizon for invasive plant threats using a data-driven approach". </p> <p><strong>Contents</strong></p> <ul> <li>code: descriptions below</li> <li>data: descriptions below</li> <li>intermediate-data: datasets produced by processing original data (see code) or produced through horizon scan process (descriptions below)</li> <li>fl-plants-horizon-scan.Rproj: RStudio project for running R scripts</li> </ul> <p> </p> <table> <thead> <tr> <th scope="col">code</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>gcw_processing.R</td> <td>R script to format data downloaded from the Global Compendium of Weeds</td> </tr> <tr> <td>native_introduced_ranges.R</td> <td>R script to create map of native and introduced ranges of taxa on the final list</td> </tr> <tr> <td>random_draws_plant_families.R</td> <td>R script to evaluate over- and underrepresentation of plant families in initial and final list</td> </tr> <tr> <td>review_process_comparison.R</td> <td>R script to evaluate differences in scores before and after peer-review and consensus-building</td> </tr> <tr> <td>scores_certainty_pathways.R</td> <td>R script to create figures of scores, certainty, and pathways for final list</td> </tr> <tr> <td>risk_scores_analys.R</td> <td>R script to evaluate final risk scores</td> </tr> <tr> <td>pathways_process.R</td> <td>R script to process pathways to introduction data</td> </tr> <tr> <td>taxa_list_processing.R</td> <td>R script to create list used for rapid risk assessments from an initial list</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">data</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>cab_list_full.csv</td> <td>list of potential invasive species to Florida generated by CABI Horizon Scan Tool on November 15, 2019</td> </tr> <tr> <td>GCW_full_list_020420.csv</td> <td>Global Compendium of Weeds downloaded on February 4, 2020</td> </tr> <tr> <td>PlantAtlasDataExport-20191211-194219.csv</td> <td>Atlas of Florida plants downloaded December 11, 2019</td> </tr> <tr> <td>Taxon_x_List_GloNAF_vanKleunenetal2018Ecology_121119.csv</td> <td>GloNAF 1.2 database downloaded December 11, 2019</td> </tr> <tr> <td>the-plant-list</td> <td>The Plant List Database downloaded August 3, 2021</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">intermediate-data</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>federal_noxious_weed_list.csv</td> <td>manually formatted version of the USDA Federal Noxious Weed List downloaded March 16, 2020</td> </tr> <tr> <td>first_round_assessments_050120.csv</td> <td>rapid risk assessments for horizon scan pre-peer-review</td> </tr> <tr> <td>fl_prohibited_plants.csv</td> <td>manually compiled list of prohibited plants in Florida based on the Florida Noxious Weed List, Florida Prohibited Plants list, and Florida Invasive Species Council (all downloaded March 9, 2020)</td> </tr> <tr> <td>horizon_scan_plants_full_reviews_080321.csv</td> <td>rapid risk assessments for horizon scan post-peer-review and consensus-building</td> </tr> </tbody> </table> <p> </p>
ScienceDex guides
Understand access before you commit
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.