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2,474 results for “Northeast”
Ramped Pyrolysis Oxidation (RPO) coupled radiocarbon (14C-DOC) and stable carbon (13C-DOC), high-resolution molecular composition (FT-ICR MS), and biodegradable dissolved organic carbon (BDOC) of groundwater, river water, and lagoon water in northeast Alaska, 2017
Supra-permafrost groundwater (SPGW), river water, and lagoon water were sampled near Kaktovik, AK to assess the reactivity and origin of dissolved organic matter (DOM) across interconnected hydrologic systems during late summer. Water samples were collected on August 17th 2017 from SPGW along the beach of Jago Lagoon (Jago GW), surface water from the Jago River’s main channel above tidal influence (Jago R), and from the water column of Kaktovik Lagoon at 2–3 m depth (KA LW). Measurements were made from grab samples for river and lagoon water, and from a composite sample for SPGW gathered from 10 individual shoreline locations. Data include dissolved organic carbon concentration (DOC, mg C L-1), Ramped Pyrolysis Oxidation (RPO) derived fraction compositions of 13C-DOC (δ13C ‰), 14C-DOC (in fraction modern), and method/instrumental error in the 14C and 13C results, and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) molecular composition and summarized compound classes. Biodegradable DOC (BDOC) bottle experiments were performed using all three sample types, where DOC concentration was subsequently measured at 2, 7, 14, and 28 days. FT-ICR MS composition was subsequently measured at the 28-day timepoint to track changes in molecular formulae and compound class relative abundance following biodegradation. Data from RPO serial thermal oxidation include temperature and normalized CO2 profiles for each background sample. Thermal-oxidation profiles of CO2 were transformed into non-parametric activation energy (E) distributions using an inverse model. Model output includes C mass of oxidized CO2 (µg C), Tmax (K), Emax (kJ mol-1), Emean (kJ mol-1), Estd (kJ mol-1), and p(0,E)max of user-defined sample fractions. FT-ICR MS results include a summary table of the relative abundance of compound classes (e.g., unsaturated phenolic, polyphenolic, aliphatic, condensed aromatics, peptide-like) and elemental groupings (e.g., CHO-type, CHON-type, CHOS-type, CHON
PIE LTER surface elevation table (SET) pin height data from twelve marsh sites in northeast Massachusetts.
Surface elevation table (SET) measurements from 26 SETs at 9 marsh sites in the Plum Island Sound Long-Term Ecological Research Site in the Great Marsh, Massachusetts. SET measurements are useful for determining the relative elevation change of marsh sediments. Precise measurements of sediment elevation in marshes is useful for determining rates of elevation change in response to changes in sea level.
Zooplankton abundance from net tows on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018
This data package provides abundance data for zooplankton collected during seasonal transect cruises conducted as part of the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) program, ongoing since 2018. Zooplankton are collected at standard NES-LTER transect stations (L1–L11) and the Martha’s Vineyard Coastal Observatory (MVCO) via oblique tows, using a 61-cm Bongo net with two mesh sizes (335 µm and 150 µm). The transect extends southward from near Martha’s Vineyard, Massachusetts, reaching approximately 150 km offshore along longitude 70 deg 53 min W, covering the continental shelf from nearshore to the shelf break, with sampling depths between 20 and 200 meters. Only the 335-µm mesh data is included here, as samples from this net are preserved on board and shipped to Morski Instytut Rybacki in Szczecin, Poland, where they are counted and identified to the lowest possible taxonomic level. Counts of taxa identified are provided by the NOAA’s Northeast Fisheries Science Center. Samples from the 150 um are preserved for other purposes and will be published as a separate data package. This second version of the data package includes staged and unstaged abundance data in volumetric (100 m³) and aerial (10 m²) units from the 335-µm net. Supplemental tables provide metadata for the cruises and stations.
NECCPB-1: The first cropland parcel boundary dataset from meter-level imagery of Northeast China
<p>The Northeast China Plain is one of the world's three largest black soil regions, characterized by high organic matter content, rich nutrients, and strong water retention capabilities. Suitable climate conditions and abundant rainfall promote the growth of crops such as corn, soybeans, and rice, making it one of the main grain production bases in China, accounting for about one-fifth of the country's grain output. The grain production in the Northeast China black soil region is crucial for food security in China and globally. This area's farmland parcels are the basic units of agricultural production and the cornerstone of precision agriculture management, providing detailed information on cultivated land location, boundaries, shape, and area. Utilizing this parcel-scale information, governments and farm managers can devise more precise planting strategies and optimize management methods, thereby enhancing the quality and productivity of crops, ensuring a continuous food supply, and promoting sustainable agricultural development.</p> <p>The first cropland parcel boundary dataset from meter-level imagery of Northeast China (NECCPB-1) was developed based on deep learning models and a custom-designed automatic parcel merging strategy. A total of 10.22 TB of very-high-resolution (VHR) imagery was downloaded and uploaded, covering the entire region of Northeast China and an area of 1,240,000 km². After further removal of non-cropland regions based on phenological differences, 32,395,946 parcels were obtained.</p> <p> Rigorous validation using manually drawn reference parcels demonstrated that this dataset had high accuracy in parcel delineation (Extraction Precision, EP: 0.85) and high consistency with the reference parcels (|Completeness Deviation|, |CompD|: 0.02; Intersection over Union, IoU: 0.90). Further comparison with official Third Survey reports confirmed the high reliability of the NECCPB-1 dataset, which exhibited an average relative difference of -3.6% and an absolute relative difference of 9.8%.</p> <p>A series of cross-validations with seven widely used cropland datasets (ESA_GLC10, ESRI_GLC10, FROM_GLC10, CLD10, GLAD250, GFSAD30, and SinoLC-1). The recall, precision, and F1 scores of the NECCPB-1 were calculated as 0.91, 0.93, and 0.92, respectively, using publicly validated sample points of land cover. Moreover, NECCPB-1 performed best regarding cropland completeness, achieving an intersection ratio (IR) of 0.94, as calculated using the reference parcels.</p> <p>Due to the extensive size of the dataset and potential policy considerations, access to the data will be granted based on specific inquiries. Please contact us at zhengjia@iga.ac.cn or guotianhao@iga.ac.cn for further details. Please indicate your purpose and other details. Thank you!</p>
Fish and consumer data collected from Northeast Shark Slough, Everglades National Park (FCE) from September 2006 to September 2008
Three 1m2 throwtrap sites were selected randomly within a few meters of the location. All fish and macroinvertebrates were sampled within each trap using a seine; the trap is determined to be clear of fish and macroinvertebrates once three empty seines are recovered. The count is reset whenever a fish or invertebrate is caught. Once the trap is determined to be clear, five sweeps are done using a couple of nets. The count resets whenever fish is caught, while an extra sweep is added whenever an invertebrate is captured. The trap is finally cleared once the fifth sweep doesn't capture any organisms. All captured organisms are anesthesized in a plastic cup filled with water and MS222; they are then preserved using a 10% formaldehyde solution for identification and archiving in the lab
Vegetation data collected from Northeast Shark River Slough, Everglades National Park, Florida, USA, September 2006 - April 2025
This project was established in 2006 to document the pattern of abundance of key ecological indicators (e.g., surface water, soil, floc, periphyton and sawgrass) across the NESRS landscape. A total of 30 sites were established and monitored in 2006, 2007 and 2008. After the completion of 1-mile bridge in 2012, additional 10 new sites were established to observe the ecological impact of 1-mile bridge (known as Bridge & Census sites). In 2015, additional 40 sites were established along eight transects (T1-T8, known as near canal sites) in ENP marshes starting at, and roughly perpendicular to the L-29 canal. The purpose of these sites was to monitor the potential effects of Modified Water Deliveries (MWD) operations on changing nutrient concentrations and ratios in key ecological compartments due to increased downstream discharges from the L-29 canal beneath the 1-mile and 2.6-mile bridges and culverts along Tamiami Trail. Data collection is complete.
Size-fractionated net primary productivity (NPP) estimates based on 13C uptake during cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect, ongoing since 2019
This dataset consists of primary production measurements based on uptake of carbon-13 added as 13C-bicarbonate during 24-h deckboard incubations of seawater. Sampling occurred on cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect during summer, fall, and winter, starting in summer 2019. Net primary production (NPP) was determined from particulate organic carbon (POC) content and associated stable isotope enrichment. Three data tables are included: 1. Depth-specific primary productivity based on fractional light levels of the surface irradiance with reference to the profile of photosynthetically active radiation (PAR). 2. Integrated primary productivity. 3. Natural abundance POC. The tables derive from the raw data included as other entities.
Diet composition for small pelagic fishes across the Northeast U.S. Continental Shelf for NES-LTER, ongoing since 2013
These data represent the diet composition of small pelagic fishes assessed by the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) project. The six species of fish in this dataset represent a subset of the species collected in bottom trawls conducted by the NOAA Fisheries Northeast Ecosystems Surveys from Cape Hatteras to the Gulf of Maine. Sampling occurred in the Spring and Fall seasons. Fish were frozen and stomach content analyses were conducted by the Fisheries Oceanography and Larval Fish Ecology Lab at the Woods Hole Oceanographic Institution. Data are counts and length measurements for prey items examined under a dissecting microscope. Prey species were matched to the lowest taxonomic level in the Integrated Taxonomic Information System (ITIS) for scientific name and taxonomic serial number. The dataset was supplemented with geospatial and temporal information from NOAA Fisheries trawl databases.
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2017
This package provides a concatenated table of events recorded on seasonal Transect cruises for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) and other opportunistic cruises within the transect region. Events were recorded onboard with Rolling Deck to Repository (R2R) event logger (elog) software. Event listings include date, time, ship's position, instrument, and action for over the side operations, underway data collection, and other miscellaneous events during the cruise. The event log is used post-cruise in physical sample cataloging and data integration. Cruises are seasonal and include NES-LTER dedicated voyages, spring and fall cruises in collaboration with the Ocean Observatories Initiative (OOI), and additional opportunistic cruises.
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) cruises to the Martha's Vineyard Coastal Observatory (MVCO) ongoing since 2017
This package provides a table of cruises to the Martha's Vineyard Coastal Observatory for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER). The majority of events are single day cruises, however, samples missing an MVCO Event Number were collected on multi-day NES-LTER transect cruises aboard larger research vessels. The same sampling protocols for CTD and bongo collection are used on both cruise types. Sampling frequency is approximately monthly, with NES-LTER sampling ongoing since 2017. Cruises involve collection of water column bottle samples, surface bucket samples, and zooplankton net tow samples, as well as ship-provided data. NES-LTER transect cruises will have more extensive underway and acoustic data which can be found by searching by cruise at https://www.rvdata.us/data. The event number for each cruise is provided, along with date, vessel name, cruise identifier where applicable, link to data location (for CTD, ADCP, and other underway data), and checklist of six data types.
Dissolved Organic Carbon (DOC) and Dissolved Total Nitrogen (DTN) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2022
Dissolved organic carbon and dissolved total nitrogen are measured from discrete bottle samples collected during CTD rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) transect cruises (ongoing since 2022). Sampling frequency is approximately seasonal. Sample collection is paired with particulate organic carbon at surface, subsurface chlorophyll max, and sometimes a third depth. Samples are filtered directly from the CTD rosette and acidified in the field, then analyzed using a Shimadzu TOC-LCPH total organic carbon analyzer coupled to a TNM-L analyzer for total nitrogen. Values are reported in micromoles per liter.
Zooplankton sample inventory for Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018
This dataset provides an inventory of physical samples collected from zooplankton bongo and/or ring net tows conducted during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. The NES-LTER transect, located south of Martha’s Vineyard, Massachusetts, comprises standard stations L1-L11 and extends 150 km offshore. Dedicated NES-LTER cruises target all four seasons: winter, spring, summer, and fall. Samples are collected via oblique tows with a 61-cm bongo net fitted with 150- and 335-micron mesh nets, as well as a ring net with a 20-micron mesh net. During earlier spring and fall cruises along the NES-LTER Transect, in collaboration with the Ocean Observatories Initiative, samples were collected through vertical tows using a ring net with a 150-micron mesh. Samples collected are distributed among various laboratories for DNA metabarcoding, stable isotopes analysis, and morphological identification.
Particulate organic carbon (POC) and nitrogen (PON) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2017
Particulate organic carbon and nitrogen are measured from discrete bottle samples collected during CTD-rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises (ongoing since 2017). Sampling frequency is approximately seasonal. Samples were filtered and collected on combusted glass fiber filters, pelletized using ultra clean tin disks, and combusted using a Flash EA1112 CHN analyzer to calculate concentrations of particulate organic carbon and particulate organic nitrogen in micromoles per liter. Values are also reported as concentrations in micrograms per liter and carbon to nitrogen molar ratio.
Daily Rainfall Anomalies in the Brazilian Northeast (DRA-BNE)
<p>This dataset contains the daily precipitation anomalies in the Brazilian northeast calculated from the GPCP dataset (combined sources of precipitation measurement) in the period from 1996-10-01 to 2021-07-31, in the geographic boundaries 42°W - 30°W/20.5°S - 0°. The GPCP dataset has an original resolution of 1 degree, but this dataset was interpolated by the bilinear method, obtaining a resolution of 0.25 degrees.</p>
Northeast Pacific deoxygenation and volcanism during the last deglaciation
<p><strong>File structure:</strong></p> <p><strong>Source data</strong></p> <ul> <li>Contains source data to main text and extended data figures. Data sources are identified within and listed below.</li> </ul> <p> </p> <p><strong>Computer codes</strong></p> <ul> <li><strong>Geochemical inversion</strong> –</li> </ul> <ul> <li>“Data for geochemical inversion.xlsx”: contains Gulf of Alaska sediment and volcanic/terrigenous endmember geochemical data used for data inversion.</li> <li>“geochemical inversion.r”: R script used to perform geochemical inversion.</li> <li>“GOA inversion fraction.csv”: Result of the geochemical inversion, including the volcanic and terrigenous fractions in each Gulf of Alaska sediment sample.</li> <li>“GOA inversion residual.csv”: Result of the geochemical inversion, including the residuals of each element.</li> <li><strong>cluster volcanic geochemical data </strong>– <ul> <li> “Database of volcanic geochemistry.xlsx”: compiled database of the geochemistry of volcanic endmember samples.</li> <li> “cluster.r”: R script used to perform cluster analysis on the volcanic samples.</li> <li> “Clustered volcanic data.csv”: the results of cluster analysis.</li> <li> “Dendroplot.r”: R script used to plot the dendrogram for the cluster analysis.</li> <li> “dendro 15 complete euclidean.pdf”: The dendrogram.</li> <li> “Volcanic endmembers.csv”: final geochemical volcanic endmembers based on the cluster analysis.</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>Global volcanic eruption compilation –</strong></li> </ul> <ul> <li>“eruption.database.intcal20.xlsx”: This file includes the eruption database compiled by this study, as well as the previous compilation of Huybers and Langmuir 2009 EPSL (referred to as HL09).</li> <li>“eruption.ratio.R” and “volc.freq.R”: These are R scripts that compute the eruption frequency of glaciated and unglaciated volcanoes using the eruption database. “eruption.ratio.R”calls the function inside “volc.freq.R”.</li> <li>“Volcanic eruption summary.xlsx”: This file contains the outputs of the R scripts.</li> </ul> <p> </p> <ul> <li><strong>PISM sensitivity experiment – </strong></li> </ul> <ul> <li>“ciscyc.5km.epica.ts.10a.nc” and other netcdf files: The output of PISM sensitivity experiments, from <em>Seguinot. (2020). Cordilleran ice sheet glacial cycle simulations continuous variables [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3606536">https://doi.org/10.5281/zenodo.3606536</a></em>. Click the link to see the documentation of these files.</li> <li>“temperature timeseries.xlsx”: the temperature forcing used in the sensitivity experiments.</li> <li>“PISM sensitivity.r”: R script used to analyse the PISM sensitivity experiments, including data binning, lag correlation and regression between ice sheeting response and temperature forcing.</li> <li>“PISM sensitivity.xlsx”: Output of the R script.</li> <li>“GOA.calibration.csv”: SST record from the Gulf of Alaska site 85JC/U1419, calibrated using bayspline.</li> <li>“GOA.Ensemble.csv”: 1000 ensemble output of the bayspline calibration.</li> <li>“predict ice volume SST.r”: R script used to predict the response of CIS ice volume to GOA SST forcing. The script will call the results of PISM sensitivity experiments in “PISM sensitivity.xlsx” and the GOA SST forcing in “GOA.calibration.csv” and “GOA.calibration.csv”.</li> <li>“PISM ice vol GOA SST.csv”: predicted PISM ice vol based on GOA SST forcing and taking into account all sensitivity experiments and the uncertainty in SST reconstruction.</li> <li>“PISM ice vol GOA SST model.csv”: predicted PISM ice vol based on GOA SST forcing based on each sensitivity experiment and the uncertainty in SST reconstruction.</li> </ul> <p> </p> <p><strong>Please cite the following studies when using the data, in addition to citing the present study:</strong></p> <p><strong>GOA age model, IRD and MAR:</strong></p> <p>Walczak, M. H. et al. Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans. Science 370, 716–720 (2020).</p> <p>Velle, J. H. et al. High resolution inclination records from the Gulf of Alaska, IODP Expedition 341 Sites U1418 and U1419. Geophys. J. Int. 229, 345–358 (2022).</p> <p>Heaton, T. J. et al. Marine20—The Marine Radiocarbon Age Calibration Curve (0–55,000 cal BP). Radiocarbon 62, 779–820 (2020).</p> <p><strong>GOA SST: </strong></p> <p>Praetorius, S. K. et al. North Pacific deglacial hypoxic events linked to abrupt ocean warming. Nature 527, 362–366 (2015).</p> <p>Romero, O. E., LeVay, L. J., McClymont, E. L., Müller, J. & Cowan, E. A. Orbital and Suborbital-Scale Variations of Productivity and Sea Surface Conditions in the Gulf of Alaska During the Past 54,000 Years: Impact of Iron Fertilization by Icebergs and Meltwater. Paleoceanogr. Paleoclimatology 37, e2021PA004385 (2022).</p> <p>Tierney, J. E. & Tingley, M. P. BAYSPLINE: A New Calibration for the Alkenone Paleothermometer. Paleoceanogr. Paleoclimatology 33, 281–301 (2018).</p> <p><strong>GOA benthic foraminifera assemblage:</strong></p> <p>Belanger, C. L., Sharon, Du, J., Payne, C. R. & Mix, A. C. North Pacific deep-sea ecosystem responses reflect post-glacial switch to pulsed export productivity, deoxygenation, and destratification. Deep Sea Res. Part Oceanogr. Res. Pap. 164, 103341 (2020).</p> <p>Sharon, Belanger, C., Du, J. & Mix, A. Reconstructing Paleo-oxygenation for the Last 54,000 Years in the Gulf of Alaska Using Cross-validated Benthic Foraminiferal and Geochemical Records. Paleoceanogr. Paleoclimatology 36, e2020PA003986 (2021).</p> <p><strong>GOA productivity:</strong></p> <p>Romero, O. E., LeVay, L. J., McClymont, E. L., Müller, J. & Cowan, E. A. Orbital and Suborbital-Scale Variations of Productivity and Sea Surface Conditions in the Gulf of Alaska During the Past 54,000 Years: Impact of Iron Fertilization by Icebergs and Meltwater. Paleoceanogr. Paleoclimatology 37, e2021PA004385 (2022).</p> <p>Addison, J. A. et al. Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope. Paleoceanography 27, PA1206 (2012).</p> <p><strong>GOA bulk sediment neodymium isotopes:</strong></p> <p>Du, J., Haley, B. A., Mix, A. C., Walczak, M. H. & Praetorius, S. K. Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO 2 concentrations. Nat. Geosci. 11, 749–755 (2018).</p> <p><strong>GOA volcanic endmember data compilation:</strong></p> <p>Cameron, C. E., Snedigar, S. F. & Nye, C. J. Alaska Volcano Observatory geochemical database. DDS 8 http://www.dggs.alaska.gov/pubs/id/29120 (2014) doi:10.14509/29120.</p> <p>Sarbas, B., Jochum, K. P., Nohl, U. & Hofmann, A. W. GEOROC, the MPI geochemical rock database: a new tool for geochemists. Eos Trans. AGU 80, F1184 (1999).</p> <p><strong>Global and regional volcanic eruption data compilation:</strong></p> <p>Huybers, P. & Langmuir, C. Feedback between deglaciation, volcanism, and atmospheric CO2. Earth Planet. Sci. Lett. 286, 479–491 (2009).</p> <p>Global Volcanism Program, 2013. Volcanoes of the World, v. 4.8.7. 10.5479/si.GVP.VOTW4-2013. (2013).</p> <p>Bryson, R. U., Bryson, R. A. & Ruter, A. A calibrated radiocarbon database of late Quaternary volcanic eruptions. EEarth Discuss 1, 123–134 (2006).</p> <p>Watt, S. F. L., Pyle, D. M. & Mather, T. A. The volcanic response to deglaciation: Evidence from glaciated arcs and a reassessment of global eruption records. Earth-Sci. Rev. 122, 77–102 (2013).</p> <p>Crosweller, H. S. et al. Global database on large magnitude explosive volcanic eruptions (LaMEVE). J. Appl. Volcanol. 1, 4 (2012).</p> <p>Cameron, C. E., Snedigar, S. F. & Nye, C. J. Alaska Volcano Observatory geochemical database. DDS 8 http://www.dggs.alaska.gov/pubs/id/29120 (2014) doi:10.14509/29120.</p> <p>Praetorius, S. et al. Interaction between climate, volcanism, and isostatic rebound in Southeast Alaska during the last deglaciation. Earth Planet. Sci. Lett. 452, 79–89 (2016).</p> <p>Wilcox, P. S. et al. A new set of basaltic tephras from Southeast Alaska represent key stratigraphic markers for the late Pleistocene. Quat. Res. 92, 246–256 (2019).</p> <p>Davies, L. J., Jensen, B. J. L., Froese, D. G. & Wallace, K. L. Late Pleistocene and Holocene tephrostratigraphy of interior Alaska and Yukon: Key beds and chronologies over the past 30,000 years. Quat. Sci. Rev. 146, 28–53 (2016).</p> <p><strong>GIA models:</strong></p> <p>Roy, K. & Peltier, W. R. Relative sea level in the Western Mediterranean basin: A regional test of the ICE-7G_NA (VM7) model and a constraint on late Holocene Antarctic deglaciation. Quat. Sci. Rev. 183, 76–87 (2018).</p> <p>Lambeck, K., Purcell, A. & Zhao, S. The North American Late Wisconsin ice sheet and mantle viscosity from glacial rebound analyses. Quat. Sci. Rev. 158, 172–210 (2017).</p> <p><strong>PISM sensitivity experiments and temperature forcing:</strong></p> <p>Seguinot, J., Rogozhina, I., Stroeven, A. P., Margold, M. & Kleman, J. Numerical simulations of the Cordilleran ice sheet through the last glacial cycle. The Cryosphere 10, 639–664 (2016).</p> <p>Seguinot. (2020). Cordilleran ice sheet glacial cycle simulations continuous variables [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3606536</p> <p>Dansgaard, W. et al. Evidence for general instability of past climate from a 250-kyr ice-core record. Nature 364, 218–220 (1993).</p> <p>Andersen, K. K. et al. High-resolution record of Northern Hemisphere climate extending into the last interglacial period. Nature 431, 147–151 (2004).</p> <p>Jouzel, J. et al. Orbital and Millennial Antarctic Climate Variability over the Past 800,000 Years. Science 317, 793–796 (2007).</p> <p>Petit, J. R. et al. Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399, 429–436 (1999).</p> <p>Herbert, T. D. et al. Collapse of the California Current During Glacial Maxima Linked to Climate Change on Land. Science 293, 71–76 (2001).</p> <p><strong>Be10 data compilation:</strong></p> <p>Lesnek, A. J., Briner, J. P., Baichtal, J. F. & Lyles, A. S. New constraints on the last deglaciation of the Cordilleran Ice Sheet in coastal Southeast Alaska. Quat. Res. 96, 140–160 (2020).</p> <p>Haeussler, P. J. et al. Late Quaternary deglaciation of Prince William Sound, Alaska. Quat. Res. 1–20 (2021) doi:10.1017/qua.2021.33.</p> <p>Walcott, C. K., Briner, J. P., Baichtal, J. F., Lesnek, A. J. & Licciardi, J. M. Cosmogenic ages indicate no MIS 2 refugia in the Alexander Archipelago, Alaska. Geochronology 4, 191–211 (2022).</p> <p>Briner, J. P. et al. The last deglaciation of Alaska. Cuad. Investig. Geográfica 43, 429–448 (2017).</p> <p>Tulenko, J. P., Briner, J. P., Young, N. E. & Schaefer, J. M. Beryllium-10 chronology of early and late Wisconsinan moraines in the Revelation Mountains, Alaska: Insights into the forcing of Wisconsinan glaciation in Beringia. Quat. Sci. Rev. 197, 129–141 (2018).</p> <p>Menounos, B. et al. Cordilleran Ice Sheet mass loss preceded climate reversals near the Pleistocene Termination. Science 358, 781–784 (2017).</p> <p>Dulfer, H. E., Margold, M., Engel, Z., Braucher, R. & Team, A. Using 10Be dating to determine when the Cordilleran Ice Sheet stopped flowing over the Canadian Rocky Mountains. Quat. Res. 102, 222–233 (2021).</p> <p>Lesnek, A. J., Briner, J. P., Lindqvist, C., Baichtal, J. F. & Heaton, T. H. Deglaciation of the Pacific coastal corridor directly preceded the human colonization of the Americas. Sci. Adv. 4, eaar5040 (2018).</p> <p>Tulenko, J. P., Briner, J. P., Young, N. E. & Schaefer, J. M. The last deglaciation of Alaska and a new benchmark 10Be moraine chronology from the western Alaska Range. Quat. Sci. Rev. 287, 107549 (2022).</p>
Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries
<p>Datasets required to run code for contribution:</p> <p>Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries</p> <p>Jana WE Jeglinski, Holly I Niven, Sarah Wanless, Robert T. Barrett, Mike P. Harris, Jochen Dierschke and Jason Matthiopoulos</p> <p>Extension of a Bayesian metapopulation model fit to colony census data for all Northeast Atlantic colonies of the Northern gannet (<em>Morus bassanus</em>) described in Jeglinski et al. (2023) to investigate mechanistic relationships with climate and forecast metapopulation dynamics under two climate scenarios. </p>
Data and Analysis for Kaplanis, Denny, and Raimondi 2024, "Vertical distribution of rocky intertidal organisms shifts with sea-level variability on the Northeast Pacific Coast".
<p>This repository contains all the data and R scripts used to produce all analyses and figures for Kaplanis, Denny, and Raimondi 2024, as well as all intermediate outputs and final figures. To access this content, download and unzip the intertidalvertdist folder (for intertidal vertical distribution). The R Project is titled "intertidalvertdist". All pertinent information needed to access data, replicate the analyses, and produce figures is contained within the README file, but a brief desciption is below.</p> <p><br>Directory Architecture:</p> <p>Data:<br>Contains all data. Within this folder are two subdirectories - Raw Data, and Processed Data. Raw Data are unmanipulated, straight from the data source. Processed Data are outputs from scripted data wrangling and transformations. </p> <p>Within each of these folders are two more subdirectories: Tide Gauge Data, and MARINe Data. These are the two data sources used in this manuscript - monthly sea-level data from The National Oceanic and Atmospheric Administration Center for Operational Oceanographic Products and Services (NOAA CO-OPS) tide gauge stations, and long-term rocky intertidal biological monitoring data from Multi-Agency Rocky Intertidal Network (MARINe) survey sites.</p> <p>Scripts:<br>All R scripts are contained within the Scripts folder. The scripts have the prefix IVD (for intertidal vertical distribution), then a name that indicates the major function of the code. The scripts either downloads data, manipulates data, conducts analyses, and/or produces a figure.</p> <p>Outputs:<br>Any figures and tables from preliminary analyses, but that are not used in the final manuscript, are saved in Outputs.</p> <p>Figures:<br>All final figures and tables are contained in the Figures folder. All figures are produced by scripts, except Figs. 1 and 2, which are schematics produced manually in a graphics editor. This folder contains two other folders: Supplemenatary Figures, and Partial Regression Plots. Partial Regression plots are the same as the final Figures 8-12, except they are grouped by taxa rather than by explanatory variable.</p> <p>Data Processing Workflow - Overview: <br>Tide Gauge Data (Data/Raw Data/Tide Gauge Data/individual stations) were downloaded using the NOAA Co-Ops API URL Builder (https://tidesandcurrents.noaa.gov/api-helper/url-generator.html), merged, then analyzed. Three MARINe data sets from the Coastal Biodiversity Survey (CBS) were accessed via data requests (https://marine.ucsc.edu/explore-the-data/contact/data-request-form.html). The first MARINe dataset (Data/Raw Data/MARINe Data/CBS_Percent Cover Data, both First Sample and Full Sample) was used to determine the top ten most abundant taxa (hereafter termed “dominant taxa”) across CBS survey sites during the monitoring period of 2001-01-01 to 2021-09-30. The second MARINe dataset (Data/Raw Data/MARINe Data/CBS_Elevation Data) was used to describe the upper limits of vertical distribution of dominant taxa through time. The third MARINe dataset (Data/Raw Data/MARINe Data/CBS_Presence Data) was used to visualize latitudinal distribution of taxa.</p> <p>Location information for Tide Gauge Stations and CBS Survey Sites were assembled into a table (Data/Raw Data/CBS_Tide Gauge_Data.csv)</p> <p>Tide Gauge Data were processed first, then MARINe Data. To replicate this workflow follow the steps described in the README file, in order.</p>
Daily Anomalies of the Surface Atmospheric Fluxes of the Brazilian Northeast (DASAF-BNE)
<p>This dataset contains the daily anomalies of the main atmospheric fluxes throughout the Brazilian NE region. Geographically it is framed at 42.5°W - 29.75°E/20.5°S - 1.25°N, in the time range from 1979-01-01 12:00:00 to 2017-12-31 12:00:00. The DASAF-BNE dataset with a spatial resolution of 1 degree was the basis for the calculation of the daily anomalies, they were interpolated by the bilinear method to obtain a resolution of 0.25 degrees.</p>
Monthly Anomalies of Oceanographic Parameters in the Brazilian Northeast (MAOP-BNE)
<p>This dataset is formed by the anomalies of the main oceanic parameters: potential temperature, salinity, surface heat flux, mixed layer depth, sea surface height, density, wind forcings and marine currents, this is calculated from the monthly mean dataset SODA with an original resolution of 1/2 degree, which was interpolated with the bilinear method at 1/4 degree. The time period is from 1980-01-16 to 2017-12-12 and is geographically limited by 42°W - 30°W / 20°S - 0°.</p> <p>In this dataset, the coordinate system of the currents and the wind forcings are different from the coordinate system of the rest of the variables, for that reason they are in separate files.</p>
Data for 'The value of shifting cultivation for biodiversity in Northeast India'
Shifting cultivation is a widespread land-use in many tropical countries that also harbours significant levels of biodiversity. Increasing frequency of cultivation cycles and expansion into old-growth forests have intensified the impacts of shifting cultivation on biodiversity and carbon sequestration. We assessed how bird diversity responds to shifting cultivation and the potential for co-benefits for both biodiversity and carbon in such landscapes to inform carbon-based payments for ecosystem service (PES) schemes. We conducted this study in Nagaland, Northeast India. We surveyed above-ground carbon stocks and bird communities across various stages of a shifting cultivation system and old-growth forest using composite carbon sampling plots and repeated point counts directly overlaying the carbon plots in both summer and winter. We assessed species diversity using species accumulation and rarefaction curves based on Hill numbers. We fitted a linear mixed-effect model to assess the relationship between species richness and fallow age. We also examined possible co-benefits between carbon and biodiversity from fallow regeneration in terms of relative community similarity to old-growth forest across carbons stocks. Farmland and secondary forests regenerating on fallowed land had similar bird species richness to old-growth forests in summer and relatively higher species richness in winter. Within regenerating fallows, we did not find any strong evidence that fallow age influenced bird species richness. Bird community resemblance to old-growth forest increased with secondary forest maturity, correlating also with carbon stocks in summer. However, bird community assemblage did not show a strong association with habitat types and carbon stocks during winter. This study underscores the important role of traditional non-intensive shifting cultivation in providing refuges for biodiversity within heterogeneous habitat mosaics. Effectively managing these landscapes is crucial f
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
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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.