Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
542
datasets available to search
ShareScore release 0.7.1
Dataset results
542 results for “Hawaiian Islands”
Global Airborne Observatory: Hawaiian Islands Live Coral Cover in 2019
<p>An airborne mapping approach combining laser-guided imaging spectroscopy and deep learning models was used to quantify the geographic distribution of live corals to 16 m water depth throughout the eight main Hawaiian Islands. Full metadata and methods are provided in:</p> <p>Asner, G.P., N.R. Vaughn, J. Heckler, D.E. Knapp, C. Balzotti, E. Shafron, R.E. Martin, B.J. Neilson, J.M. Gove. 2020. Large-scale mapping of live corals to guide reef conservation. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.2017628117.</p> <p>Asner, G.P., N.R. Vaughn, J. Heckler. 2020. Global Airborne Observatory: Hawaiian Islands Live Coral Cover in 2019 (Version 3.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4292660</p> <p>Use of our data requires that you cite both of these sources together. In addition, we ask that these data be used to make the world a better place.</p> <p>The data are in standard GeoTIFF file format organized by island.</p> <p>These data files will be updated as further improvements are made.</p>
Global Airborne Observatory: Hawaiian Islands Reef Rugosity 2019+2020
<p><strong>Summary</strong></p> <p>Coral reef rugosity maps were developed by the Global Airborne Observatory (GAO) team at the Center for Global Discovery and Conservation Science at Arizona State University. The maps show high-resolution seafloor rugosity derived from airborne imaging spectroscopy data collected by the GAO in January 2019 and January 2020.</p> <p><strong>Data Use Requirements</strong></p> <p>Use of these data must acknowledge the source its funders as:</p> <p>“The bathymetry and rugosity data maps were created by the Global Airborne Observatory, Center for Global Discovery and Conservation Science, Arizona State University. The project received financial support from the Lenfest Ocean Program, The Battery Foundation, John D. and Catherine T. MacArthur Foundation, Avatar Alliance Foundation, State of Hawaiʻi Division of Aquatic Resources, State of Hawaiʻi Department of Planning, National Oceanic and Atmospheric Administration.”</p> <p>In addition, provide citations to the following two publications on any materials or presentations utilizing the data or products and results derived from the data:</p> <p>Asner, G.P., N.R. Vaughn, C. Balzotti, P.G. Brodrick, and J. Heckler. 2020. High-resolution reef bathymetry and coral habitat complexity from airborne imaging spectroscopy. <em>Remote Sensing</em> 12:310 (doi:10.3390/rs12020310)</p> <p>Asner, G.P., N.R. Vaughn, S.A. Foo, J. Heckler, and R.E. Martin. 2021. Drivers of reef habitat complexity throughout the Main Hawaiian Islands. <em>Frontiers in Marine Science </em>8:631842. (doi: 10.3389/fmars.2021.631842)</p> <p><strong>Map Properties</strong></p> <p>There are two types of map products available as part of this collection: fine rugosity, and coarse rugosity. Except for Hawaii Island, there are three separate map files for each of the Main Hawaiian Islands (Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Hawaii Island was large enough that it needed to be split into quarters for manageability, and each of the three maps are available for all quarters (12 maps total). Coordinates for all maps refer to the UTM Coordinate System, Zone 4 North using datum WGS-84, with the exception of those for Hawaii Island which refer to Zone 5 North.</p> <p>The rugosity maps in meters at a 2-meter spatial resolution up to approximately 22 meters in depth, where data quality allowed. To minimize the effect of water properties, these maps are built using a blend of data from both the 2019 and 2020 collection periods. Fine-scale rugosity seeks high frequency changes on the seafloor arising from coral colonies, rocks, and other bottom features that generate local habitat variability, and coarse-scale rugosity is more responsive to variations in larger terrain features resulting from geologic, reef-scale accretion, and subsidence processes. Fine-scale rugosity maps are produced at 2-meter horizontal resolution, but each pixel represents the conditions of a 6-meter square window centered at the given pixel. Similarly, coarse-scale rugosity maps are produced at 6-meter resolution, but each pixel represents the conditions of a 54-meter square window centered at the given pixel. Rugosity values in the maps are unitless and range from 0.0 (low rugosity) to 100.0 (high rugosity).</p> <p><strong>Methods</strong></p> <p>We computed island-wide maps of rugosity at two resolution using a standard planar image rugosity metric on the GAO blended bathymetry maps (Asner, Gregory. P., Vaughn, Nicholas, & Heckler, Joseph. (2020). Global Airborne Observatory: Hawaiian Islands Live Coral Cover in 2019. Zenodo. <a href="http://doi.org/10.5281/zenodo.4292660">http://doi.org/10.5281/zenodo.4292660</a>). Prior to running the algorithm, missing data of less than two pixels in width were filled using an inverse-distance weighted average of the three nearest neighboring pixels. Fine-scale rugosity was computed using a 3 x 3 pixel (6 x 6 meters) moving window on the original 2-meter resolution bathymetric maps. Coarse-scale rugosity was computed by first down-sampling the 2-meter depth maps to 6-meter resolution using a mean filter. The rugosity metric was then computed using a 9 x 9 pixel (54.0 x 54.0 m) moving window on the 6-meter depth maps. The distribution of raw rugosity algorithm output values is extremely skewed and difficult to interpret. Thus, the rugosity maps contain rugosity values that are transformed in such a way that they have an approximate uniform [0,1] distribution. This both reduces the influence of noisy depth pixels and gives a more meaningful scale upon which to interpret the maps.</p>
Global Airborne Observatory: Hawaiian Islands Bathymetry 2019+2020
<p><strong>Summary</strong></p> <p>Bathymetry maps were developed by the Global Airborne Observatory (GAO) team at the Center for Global Discovery and Conservation Science at Arizona State University. The maps show high-resolution benthic depth, derived from airborne imaging spectroscopy data collected by the GAO in January 2019 and January 2020.</p> <p><strong>Data Use Requirements</strong></p> <p>Use of these data must acknowledge the source its funders as:</p> <p>“The bathymetry and rugosity data maps were created by the Global Airborne Observatory, Center for Global Discovery and Conservation Science, Arizona State University. The project received financial support from the Lenfest Ocean Program, The Battery Foundation, John D. and Catherine T. MacArthur Foundation, Avatar Alliance Foundation, State of Hawaiʻi Division of Aquatic Resources, State of Hawaiʻi Department of Planning, National Oceanic and Atmospheric Administration.”</p> <p>In addition, provide citations to the following two publications on any materials or presentations utilizing the data or products and results derived from the data:</p> <p>Asner, G.P., N.R. Vaughn, C. Balzotti, P.G. Brodrick, and J. Heckler. 2020. High-resolution reef bathymetry and coral habitat complexity from airborne imaging spectroscopy. <em>Remote Sensing</em> 12:310 (doi:10.3390/rs12020310)</p> <p>Asner, G.P., N.R. Vaughn, S.A. Foo, J. Heckler, and R.E. Martin. 2021. Drivers of reef habitat complexity throughout the Main Hawaiian Islands. <em>Frontiers in Marine Science </em>8:631842. (doi: 10.3389/fmars.2021.631842)</p> <p><strong>Map Properties</strong></p> <p>There are multiple map products available as part of this collection. Except for Hawaii Island, there are three separate map files for each of the Main Hawaiian Islands (Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Hawaii Island was large enough that it needed to be split into quarters for manageability, and each of the three maps are available for all quarters. Coordinates for all maps refer to the UTM Coordinate System, Zone 4 North using datum WGS-84, with the exception of those for Hawaii Island which refer to Zone 5 North.</p> <p>The blended bathymetry maps give modeled depth as a floating-point values in meters at a 2-meter spatial resolution up to approximately 22 meters in depth, where data quality allowed. To minimize the effect of water properties, these maps are built using a blend of data from both the 2019 and 2020 collection periods.</p> <p><strong>Methods</strong></p> <p>GAO spectrometer data for Hawaii were collected in 1.3 km wide flight line strips and the flights were planned such that individual flight lines overlap each other by about 50%, giving at least two passes of coverage per year of collection. Thus, we have two or more passes of data over most of the Hawaiian coastlines. Details of data collection protocols can be found in <strong><em>Asner et al. (2020) and Asner et al. (2021)</em></strong>. To build the blended bathymetry maps, we identified areas with sufficient sunlight and low surface glint for each flight line, and then applied GAO-created a neural network model to derive estimated depth of each pixel in such areas.</p>
Data to support Whitney JL, Coleman RR, Deakos MH "Genomic evidence indicates small island-resident populations and sex-biased behaviors of Hawaiian Reef Manta Rays"
<p>Datasets supporting the manuscript: Whitney JL, Coleman RR, Deakos MH "Genomic evidence indicates small island-resident populations and sex-biased behaviors of Hawaiian Reef Manta Rays". <em>BMC Ecology and Evolution </em><strong>23</strong>, 31 (2023). https://doi.org/10.1186/s12862-023-02130-0</p> <p>Nuclear data:</p> <p>"Mobula-alfredi_nuclear_reference_RAD_contigs.fasta" is a fasta of 359,751 contigs that serve as the reference for nuclear alignment of genotypes to RAD loci. Contigs begin and end with GATC cut site.</p> <p>Mobula-alfredi_nuclear_all_2048snps_38genotypes.vcf is a VCF file with all 2048 nuclear SNPs in final filtered SNP dataset. 38 genotypes are included from Maui Nui and Hawaii Island. This 2048 SNPs includes both 2038 neutral and 10 outlier SNPs. </p> <p>Mobula-alfredi_nuclear_neutral_2038snps_38genotypes.vcf is a VCF file with 2038 neutral nuclear SNPs genotyped in 38 individuals from Maui Nui and Hawaii Island. </p> <p>Mobula-alfredi_nuclear_outliers_10snps_38genotypes.vcf is a VCF file with 10 outlier SNPs genotyped in 38 individuals from Maui Nui and Hawaii Island. </p> <p>Structure (.str) files are also provided in addition to VCFs. In all files Population prefixes M=Maui Nui and K=Hawaii Island. </p> <p>Mitochondrial data:</p> <p>Mobula-alfredi_mitogenome_34haplotypes_9sites_min4x.vcf is a VCF file with 9 variant sites across the mitogenome haplotyped in 34 individuals from Maui Nui and Hawaii Island. </p> <p>Mobula-alfredi_mitogenome_34haplotypes_allsites_min4x.fasta is a FASTA file with whole mitogenomes aligned to OP562409 [https://www.ncbi.nlm.nih.gov/nuccore/OP562409]. Sites with less than 4x coverage were masked with Ns. </p> <p>Mobula-alfredi_mitogenome_reference_OP562409.fasta is a FASTA file containing the <em>Mobula alfredi</em> reference mitogenome OP562409 [https://www.ncbi.nlm.nih.gov/nuccore/OP562409].</p> <p> </p>
Figures 6–9 in Adventive Thysanoptera Species in the Hawaiian Islands: New Records and Putative Host Associations
Figures 6–9. Thrips new to Hawaii. 6. Head and pronotum of Adraneothrips alajuela. 7. Abdominal tergites 1 and 2 of A. alajuela. 8. Head and pronotum of Azaleothrips siamensis. 9. Head and antenna of Sophiothrips annulatus.
Figures 1–5 in Adventive Thysanoptera Species in the Hawaiian Islands: New Records and Putative Host Associations
Figures 1–5. Thrips new to Hawaii. 1. Leaf-damage on Colocasia esculenta by Biltothrips minutus (photo: S. Chun). 2. Head of Indusiothrips seshadrii. 3. Head and pronotum of Monilothrips kempi. 4. Head and thorax of Trichromothrips priesneri. 5. Forewing of Coremothrips pallidus.
Figure 2 in Characterization of a Small Population of the Orangeblack Hawaiian Damselfly (Megalagrion xanthomelas) in Anchialine Pools at Kaloko-Honokōhau National Historical Park, Hawai'i Island
Figure 2. Male Megalagrion xanthomelas perched on pickleweed (A), a tandem pair of M. xanthomelas perched on a small branch (B), and four of the core pools where M. xanthomelas were surveyed (C–F). Note that the female M. xanthomelas (B) is probing the tip of her abdomen on the side of a branch that is above the surface of the water. The wetness of the branch suggests that it will be submerged during high tide.
Figure 5 in First Record of the Coffee Berry Borer, Hypothenemus hampei (Ferrari, 1867), on the Hawaiian Island of Lanai (Coleoptera: Curculionidae: Scolytinae)
Figure 5. Map indicating the approximate locations (black stars) of the four CBB sampling sites on the island of Lanai. Inset: Position of Lanai (in black) within the Hawaiian Islands archipelago.
Figure 3 in First Record of the Coffee Berry Borer, Hypothenemus hampei (Ferrari, 1867), on the Hawaiian Island of Lanai (Coleoptera: Curculionidae: Scolytinae)
Figure 3. Lindgren funnel trap deployed in dryland forest at The Nature Conservancy Kanepuu Preserve, July 2020. Photograph by C.P.D.T. Gillett.
Figure 1 in First Record of the Coffee Berry Borer, Hypothenemus hampei (Ferrari, 1867), on the Hawaiian Island of Lanai (Coleoptera: Curculionidae: Scolytinae)
Figure 1. Dorsal and lateral views of an adult female specimen of Hypothenemus hampei (Ferrari, 1867), the coffee berry borer, from Munro Trail, Lanai. Length of specimen: 1.6 mm. Photograph by C.P.D.T. Gillett.
Figure 1 in Characterization of a Small Population of the Orangeblack Hawaiian Damselfly (Megalagrion xanthomelas) in Anchialine Pools at Kaloko-Honokōhau National Historical Park, Hawai'i Island
Figure 1. Location of Kaloko-Honokōhau National Historical Park along the Kona Coast of Hawai'i. Anchialine pools supporting Megalagrion xanthomelas are located centrally in the Park between Kaloko and 'Aimakapā Fishponds.
Figure 4 in Characterization of a Small Population of the Orangeblack Hawaiian Damselfly (Megalagrion xanthomelas) in Anchialine Pools at Kaloko-Honokōhau National Historical Park, Hawai'i Island
Figure 4. Frequency of ovipositing behavior on substrates relative to the water surface in the five core pools where most observations were made and in all seven core pools combined. Ovipositing behavior was rarely observed at two core pools (7 and 58) and those data are not displayed individually.
Figure 2 in First Record of the Coffee Berry Borer, Hypothenemus hampei (Ferrari, 1867), on the Hawaiian Island of Lanai (Coleoptera: Curculionidae: Scolytinae)
Figure 2. Lindgren funnel trap deployed on the native plant Freycinetia arborea in mesic / "cloud" forest alongside Munro Trail on Lanaihale, Lanai, July 2020. Photograph by C.P.D.T. Gillett.
Figure 1 in First Report of African Fig Fly, Zaprionus indianus Gupta (Diptera: Drosophilidae), on the Island of Maui, Hawaii, USA, in 2017 and Potential Impacts to the Hawaiian Entomofauna
Figure 1. Thorax (a) and front tibia (b) of Zaprionus indianus collected on Maui. The lack of a white spot on the scutellum, and the presence of tibial spines, separates this species from Zaprionus ghesquierei.
Figure 1 in The History of Little Fire Ant Wasmannia auropunctata Roger in the Hawaiian Islands: Spread, Control, and Local Eradication
Figure 1. Number of known locations infested with Wasmannia auropunctata on Hawaii island between 1999 and 2007. Data sourced from Conant and Hirayama (2000); Motoki et al. (Motoki et al. 2013), P. Conant (pers. com.) and informal reports from Hawaii Department of Agriculture.
Figure 4 in The History of Little Fire Ant Wasmannia auropunctata Roger in the Hawaiian Islands: Spread, Control, and Local Eradication
Figure 4. Map of Kauai showing location infested by Wasmannia auropuntata (2012). Currently this site is putatively ant free.
Figure 2 in The History of Little Fire Ant Wasmannia auropunctata Roger in the Hawaiian Islands: Spread, Control, and Local Eradication
Figure 2. Location of properties infested with Wasmannia auropunctata in January 2007 prepared by Hawaii Department of Agriculture.
Figure 6 in The History of Little Fire Ant Wasmannia auropunctata Roger in the Hawaiian Islands: Spread, Control, and Local Eradication
Figure 6. Locations of known sites on Oahu infested with Wasmannia auropunctata. (currently the infestation in Mililani and the original infestation in Waimanalo are putatively ant-free)
Figures 5a–f in Trapping Records of Fruit Fly Pest Species (Diptera: Tephritidae) on Oahu (Hawaiian Islands): Analysis of Spatial Population Trends
Figures 5a–f. Mean (± S.E.) captures in different habitats for B. cucurbitae in cuelure and torula yeast (a, b), B. dorsalis in methyl eugenol and torula yeast (c, d) and C. capitata in trimedlure and torula yeast (e, f) traps. Units are flies per trap per day in male lure and per week in torula yeast traps.
Figure 4A-B. Migration pathways from the Laniakea, O in Ocean pathways and residential foraging locations for satellite tracked green turtles breeding at French Frigate Shoals in the Hawaiian Islands
Figure 4A-B. Migration pathways from the Laniakea, O'ahu foraging site to French Frigate Shoals for two females and one male. The male tracking documented a round-trip migration with the return to Laniakea followed by a move to Kāne'ohe Bay, O'ahu. Year of tracking is indicated on the map.
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.