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12,309 results for “Americas”
Bayesian Analysis of Tree Distributions Across Space and Time in Eastern North America 2010-2011
The distributions of many organisms are spatially autocorrelated, but it is unclear whether including spatial terms in species distribution models (SDMs) improves projections of future species distributions. We provide the first comparative test of a purely spatial SDM, a purely non-spatial SDM, and an SDM that combines spatial and environmental information. Spatial SDMs provided better fits to the calibration data, more accurate predictions of a hold-out validation data set of modern trees, and lower false positive rates at all time periods than non-spatial SDMs. Hindcasted projection of spatial SDMs had higher variance than those of non-spatial SDMs. Overall predictive performance of non-spatial and spatial SDMs varied temporally and as a function of niche overlap. Ecological modelers should include spatial terms in SDMs used for projecting future distributions of species.
Modeling Range Expansion of Hemlock Woolly Adelgid in Eastern North America 1951-2009
Range expansion by native and non-native species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. This R code allows simulation of the spread of the hemlock woolly adelgid (HWA, Adelges tsugae) under climatic conditions experienced from December of 1951 until March of 2009. The code describes a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in winter temperature and hemlock abundance to model range expansion of HWA. The model is parameterized using multi-year datasets describing population and dispersal dynamics of HWA and is applied to eastern North America.
Regional Distribution and Abundance of Eastern Hemlock in Eastern North America 2010
We developed comprehensive maps on the distribution and abundance of hemlock for the purposes of mapping the host distribution, and modeling the spread, of the hemlock woolly adelgid. Multiple statistical models were used to map the distribution of hemlock. Hemlock occurrence data were taken from the FIA database and multiple environmental predictors were gathered from various databases as described in methods. The raster map depicts the predicted abundance of hemlock m2 basal area per hectare) across its range in eastern North America.
Annual Maps of Mean Winter Temperature for Eastern North America 1951-2009
We developed annual raster maps depicting spatiotemporal variation in mean winter temperature for the purposes of modeling the spread of the hemlock woolly adelgid. The maps are based on the PRISM and WorldClim datasets as described in methods.
Canopy Phenology and Greenness Indices at 13 Sites across North America 2003-2012
This data set contains camera-derived color index data, which serve as a proxy for canopy phenology. The data set spans 13 geographically distinct research sites, including 17 different cameras it total, each of which was mounted on a eddy flux tower for intercomparison of canopy and photosynthesis phenology. Each site was dominated by one of three PFTs: deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops (see HF215-01 for details). On each eddy covariance tower, a digital camera was installed in a fixed position, with a view across the top of the canopy. Most cameras collected photos, which were saved in 24-bit JPEG format, at 30-60 minute intervals, 12-24 hours a day. Time series were first visually inspected for camera shifts and changes in field of view. Noting these changes, we processed the image archives to extract regions of interest (ROI) that encompassed all portions of the full canopy within the foreground. To quantify canopy greenness, we calculated the green chromatic coordinate (GCC), which is widely used to monitor canopy development and identify phenological phase changes, as follows: GCC = DNG / (DNR + DNG + DNB) where DN is the digital number and R, G and B denote the red, green and blue channels, respectively. The Excess Green (ExG) index was then calclated as follows: ExG = 2 * DNG - (DNR + DNB) To characterize canopy coloration in fall, the red chromatic coordinate (RCC) was calculated using the same form as GCC, substituting DNR in the numerator. Indices have been smoothed along a 3-day interval, using a 90th percentile filter (Sonnentag et al. 2012). For each deciduous broadleaf site, there are three files – one each for GCC, ExG and RCC. For the grassland and evergreen needleleaf sites, there are two files, one each for GCC and ExG.
Synthesis of Sarracenia Research in North America 1982-2018
This archive includes the raw data and code (R scripts) required to reproduce all of the analyses and figures in the book Scaling Sarracenia: Ecology of a Model System by Aaron M. Ellison and Nicholas J. Gotelli. The book is a synthesis of our 25 years of research on the northern (a.k.a. purple) pitcher plant Sarracenia purpurea viewed through the conceptual lens of “scale”: scaling ecological phenomena through levels of biological organization with a model organism, across time and space, and using macroecological relationships.
Scaling Sarracenia in North America 1900-2100
Scaling in Ecology with a Model System synthesizes central theories from ecology, biogeography, and macroecology through the lens of scale and scaling across spatiotemporal extents and grains, levels of biological organization, and with dimensionless ratios. In this book, we link 25 years of detailed natural history observations and laboratory and field experiments on the “Sarracenia microecosystem” (the northern pitcher plant, Sarracenia purpurea, and its associated food web of microbes and macrobes) with new models and analyses to generate novel insights into ecophysiology and stoichiometry; demography and species distribution models; food webs and trophic dynamics; and tipping points and regime shifts. Our work addresses the Sarracenia microecosystem at a hierarchy of spatial scales: individual pitchers within plants, plants within bogs, and bogs within landscapes, all of which can be treated as replicate “island” ecosystems that can be studied throughout the United States east of the Mississippi River and Canada east of the Rocky Mountains. Through integrated studies of its proteomics, physiology, population dynamics, community ecology, and ecosystem processes, the Sarracenia microecosystem has emerged as a model system for experimental ecology. Our synthetic work clearly illustrates that working with the Sarracenia microecosystem can yield new results and understanding of the importance of ecosystem-wide disturbances and anthropogenically-driven environmental and climatic change. They also show that research with the experimentally tractable Sarracenia microecosystem proceeds much more rapidly than studies of larger, more slowly changing ecosystems such as forests, grasslands, lakes, and streams that are more difficult to replicate and experimentally manipulate.
High-frequency dissolved oxygen, water temperature, wind speed, and radiation data; stream and in-lake nutrient concentration data; and daily metabolism and nutrient loading estimates for 16 lakes in North America and Northern Europe.
In lakes, ecosystem structure and processes are influenced by gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP). The rates of these metabolic processes are often controlled by resource availability, which often reflects catchment loads. Although the relationship between catchment loads and in-lake nutrient concentrations may be well defined in specific lakes, we explored how watershed vs. in-lake predictors of metabolism compare across lake types. To do this, we combined stream loads of carbon (C), nitrogen (N), and phosphorus (P) with high frequency in situ monitoring of lake metabolism and in-lake C, N, and P concentrations from 16 lakes spanning a range of latitudes (39 to 64 degrees N), inflowing stream (0 - 6 streams), and trophic status (oligotrophic to eutrophic). The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP, R, and NEP derived from those data. In addition, the data package includes in-lake and stream concentrations of dissolved organic carbon, total nitrogen, and total phosphorus and stream discharge data. The package also includes estimates of daily carbon, nitrogen and phosphorus loading to each lake derived from the stream concentrations and discharge.
Vegetation Patterns in Northeastern North America 1500-2000
Over the last few centuries, human activities have changed the landscape of northeastern North America from mostly forested to a patchwork of forest, farmland and logged areas, back in many areas to mostly forested. Meanwhile, there have been many rapid changes in the composition of the remaining forests, for example, the amounts of hemlock (Tsuga canadensis) and beech (Fagus grandifolia) have decreased while the amount of birch (Betula spp.) has increased. How stable have been the basic vegetational patterns under the onslaught of these landscape and compositional changes? In preliminary analyses, the assemblages of major tree taxa have been zoned for every other century, using optimal splitting by information content and other techniques, to study changes in vegetation groupings over the last 500 years. Several patterns seem to be emerging on a centennial scale: First, vegetation patterns were changing in the centuries before European colonization of the area. Second, the number of zones (vegetation types, based on pollen), was greater in 1700 and 1900 than in 1500 or now. Third, the zone boundaries have moved north from 1500 to the present. Further analyses, including several more data sets will be used to refine these conclusions and to suggest explanations for the changes.
Iceland as stepping stone for intercontinental spread of highly pathogenic avian influenza H5N1 virus between Europe and North America: data set on phylogeographic analysis
<p>Highly pathogenic avian influenza viruses (HPAIV) subtype H5 clade 2.3.4.4b have widely spread within the northern hemisphere since 2020 and threaten wild bird populations as well as poultry production. For the very first time, HPAIV were detected in wild birds and, subsequently, in poultry holdings in Iceland.</p> <p>Here, we present phylogeographic evidence that Iceland has been used as a stepping stone for HPAIV translocation from Northern Europe to North America in 2021 and describe two independent incursions of HPAI H5N1 clade 2.3.4.4b viruses of two different genotypes to Iceland in 2021 and 2022.</p>
Global monthly percentage of vegetation cover (MODIS FCover MODV1A product: America, Pacific)
<p>Monthly Global FCover product generated from MODIS data. Dataset represent monthly gap-filled FCover estimates the period 2000-2015 over Pacific and America. FCover was estimated using linear spectral mixture analysis and interpolated using empirical orthogonal functions algorithm to take advantage of all non-missing available pixels in both the spatial and temporal dimensions to gap-fill missing satellite observations. The global product of vegetation cover (as percentage of cover) based on MODIS images with monthly variation can be used as a critical support for several indicators related to ecologically based modelling.</p>
Journey North - Oriole observations by volunteer community scientists across Central and North America (1997-2020)
This data package contains oriole migration data consisting of 14,476 total observational reports from 1997 - 2020 across North and Central America. These data were collected by 7,331 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Oriole Project is an ongoing study of oriole phenology conducted at broad spatial and temporal scales. Since 1997, community scientists have tracked first arrival dates and breeding and feeding behavior as well as the onset of fall migration and presence of oriole species throughout the winter months in the United States. Focal species are the Baltimore Oriole (Icterus galbula), Bullock’s Oriole (Icterus bullockii), and Orchard Oriole (Icterus spurius fuertesi). Observers also provide estimates of the number of birds sighted. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day, do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence not abundance. Researchers are encouraged to read the rich information provided by volunteers in their comments. These comments provide qualitative information about observational reports. Researchers are also encouraged to refer to submitted photographs that also provide context for observational reports. The Journey North Oriole Project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
Journey North - Common Loon and Ice-Out observations by volunteer community scientists across North America (1997-2020)
This data package contains Common Loon migration and ice melt data consisting of 9,800 total observational reports from 1997 - 2020 across North America. These data were collected by 1,437 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Loon and Ice-Out Project is an ongoing study of loon and ice melt phenology conducted at broad spatial and temporal scales. Since 1997, community scientists have tracked first arrival dates of Common Loons (Gavia immer) and ice that has melted from bodies of water in the United States. Observers also provide estimates of the number of birds sighted. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day, do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence not abundance. Researchers are encouraged to read the rich information provided by volunteers in their comments. These comments provide qualitative information about observational reports. Researchers are also encouraged to refer to submitted photographs that also provide context for observational reports. The Journey North Common Loon and Ice-Out Project Project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
DRIFteRS: A dataset of drift invertebrate densities in streams and rivers across western North America, 1997–2024
Prey availability is among the most influential and highly variable determinants of fish growth and freshwater habitat carrying capacity, yet it remains understudied compared to physical habitat variables (Rosenfeld et al. 2014; Weber et al. 2017; Ouellet et al. 2025). We often lack a clear understanding of how much food is available to fishes, how it varies spatially and temporally, and how it influences responses to restoration (Wipfli et al. 2010; Ouellet et al. 2025; Rossi et al. 2024). Drift invertebrates—the primary food source for juvenile salmonids and other drift-foraging fishes—play a pivotal role in these dynamics. To better understand the spatial and temporal variability of drift invertebrate abundance and biomass across the freshwater range of drift-feeding salmonids in western North America, we compiled the DRIFteRS dataset (DRift Invertebrates For salmonids in River Systems). The dataset encompasses 6,159 samples of drift invertebrates, and, for a subset of drift samples, associated benthic invertebrate density data, collected from 1,360 reaches on 459 unique rivers and streams spanning 55 river basins considered hydrologically independent (i.e., not nested within the same larger watershed) across British Columbia, Canada, and the U.S. states of Alaska, Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. Sample sites represent a diverse array of river and stream habitats (e.g., headwater, mainstem, side channel), in watersheds with diverse land uses (e.g., urban, wilderness, agricultural), and disturbance histories (e.g., fire, restoration). Collected between 1997 and 2024, the data span the full calendar year and capture daily and seasonal patterns in drift abundance and biomass densities. When paired with water quality and quantity data as well as remotely sensed environmental landscape data, such as land use / land cover, climate, and disturbance history, channel morphology, and riparian vegetation compo
Leaf Angle of North America Broadleaf Deciduous Trees: 2021 - 2023
Leaf angle, defined as the angle between the leaf normal (perpendicular to the leaf surface) and the zenith, strongly influences albedo, photosynthesis, and evapotranspiration. We installed remote time-lapse cameras mounted level with the sunlit treetops at each of the ten National Ecological Observatory Network (NEON) tower to measure and track seasonal changes of leaf angle for 11 tree species across three years of 2021, 2022 and 2023. We measured the (x, y) coordinates of each leaf’s petiole and tip and tracked their changes over time on a weekly basis. From these coordinates, we computed the leaf angle for each leaf throughout the growing season across three years of weekly observations.
Ecosystem Responses to Hurricanes across North America, the Caribbean, and Taiwan; 1985 to 2018
Tropical cyclones play an increasingly important role in shaping ecosystems. Understanding and generalizing their responses is challenging because of meteorological variability among storms and its interaction with ecosystems. Data here represent the responses of ecosystems to hurricanes from across North America, the Caribbean and Taiwan. Data across a variety of ecosystems are represented here including wetlands, estuaries, marine, terrestrial and fresh water systems. These data measure a variety of different parameters to understand ecosystem response such as biogeochemical, hydrological and physical measurements as well as the abundance of mobile and sedentary biota. Meteorological data characterizing tropical cyclones are also presented and are derived from: IBTrACS: International Best Track Archive for Climate Stewardship Global storm track data set for all recorded low pressure systems and tropical cyclones dating back to 1842. Data includes timestamped spatial information on storm center location as well as meteorological readings of wind speed, wind direction, and barometric pressure. Most importantly for the purposes of this data set, wind speeds at various distances from storm center are provided, which allows for the development of a model of wind speed with distance for different category storms. GRIDMET: University of Idaho Gridded Surface Meteorological Dataset The Gridded Surface Meteorological dataset provides high spatial resolution (~4-km) daily surface fields of temperature, precipitation, winds, humidity and radiation across the contiguous United States from 1979. The dataset blends the high resolution spatial data from PRISM with the high temporal resolution data from the National Land Data Assimilation System (NLDAS) to produce spatially and temporally continuous fields that lend themselves to additional land surface modeling. This dataset contains provisional products that are replaced with updated versions when the complete source data becom
Heterotrophic Respiration from Nine Nutrient Network Grasslands in North America
This experiment tracks the response of soil heterotrophic respiration (i.e., soil organic matter decomposition), enzyme expression, and microbial biomass in nine US grasslands participating in the globally-distributed Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year). These samples in the present dataset were collected at the same time as soil and plant samples for https://doi.org/10.6073/pasta/7f984c2ed9e63754577ee711e6d74a6e.
ConFire Model input/output for South America
<p>ConFIRE input and output used in the submission of Kelley et al. "Low Climatic Influence found in 2019 Amazonia Fires".</p> <p>"input" dir including "amazon_inference_data-2002-MCDBA_obs-TERRA_M__T.csv", just contains a csv file of all common grid data in other "input" subdirectories, which can be used in "optimise_run_model/bayesian_inference.ipynb" notebook. The files in the subdirectories are then used to make gridded model output using "optimise_run_model/make_model_output.ipynb".</p> <p>Output, also provided, is summerized in the files in "outputs/sampled_posterior_ConFire_solutions/constant_post_2018_full_2002_BG2020/"</p> <p>The three files contain:</p> <ul> <li>fire_summary_frequancy_of_counts.nc - Contains one spatial variable (long name "firecount frequency of occurrence") is the probability of a fire count (along the model_level_number dimension) at a particular month (time dimension) according to the models full posterior, <span class="math-tex">\(P(y_j)\)</span>(see papers supplementary). All months start on Jan 2001. </li> <li>fire_summary_precentile.nc - Contains one spatial variable (long name "firecount at percentile"), the fire count at each percentile of the full posterior in 1% increments from 1-99% (along the model_level_number dimension). Note, by definition, the 0a nd 100% percentile is 0 and <span class="math-tex">\(\infty \)</span> .</li> <li>fire_summary_observed_liklihood.nc - the position ( "variable_0") and p-value ("variable") of MCD64A1 in the model posterior.</li> <li>model_summary.nc - Summary of each variable of ConFire: <ul> <li>"burnt_area": burnt area or fire count summary, described as percentiles as per "fire_summary_precentile", but this time just assessing parameter uncertainty, i.e <span class="math-tex">\(P(\beta | Y_s)\)</span> in supplementary of paper.</li> <li>All other variables describe different model controls in the same "burnt_area". Full information on how controls are constructed can be found in Kelley et al. (2019) with updates listed in supplementary of this paper. <ul> <li>"fuel_continuity", "moisture_content", "ignitions", "suppression" are the actual values of the control</li> <li>"standard_<<control>>" is the standard limitation imposed by the control.</li> <li>"potential_<<control>> is the potential limitation</li> <li>"sensitivity_<<control>> is the senstivity of fire to a particular control.<br> <br> See Kelley et al. 2019 for the definition of limitation types and sensitivity</li> </ul> </li> </ul> </li> </ul> <p>Kelley, D.I., Bistinas, I., Whitley, R. <em>et al.</em> How contemporary bioclimatic and human controls change global fire regimes. <em>Nat. Clim. Chang.</em> <strong>9, </strong>690–696 (2019) doi:10.1038/s41558-019-0540-7</p> <p> </p>
Paleomagnetic data for Beaver, Kent & Dalziel in Tectonics (2022), "Paleomagnetic Constraints From South Georgia On The Tectonic Reconstruction Of The Early Cretaceous Rocas Verdes Marginal Basin System Of Southernmost South America"
<p>Text data files of paleomagnetic data from Tables in: Beaver, D. G., D. V. Kent, and I. W. D. Dalziel (2022), Paleomagnetic Constraints From South Georgia On The Tectonic Reconstruction Of The Early Cretaceous Rocas Verdes Marginal Basin System Of Southernmost South America: Tectonics, in press.</p> <p><strong>Table 1.</strong> Site Mean Stable Paleomagnetic Directions from South Georgia.</p> <p><strong>Table 2.</strong> Site Mean Stable Directions for Differential Tilt Test of South Georgia Sites With Structural Control.</p> <p><strong>Table 3.</strong> Tectonic Rotations Inferred from Available Paleomagnetic Results from Rocas Verde Rock Units of Late Cretaceous Age in Fuegian Andes and South Georgia.<br> </p>
The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America
<p><strong>Title: </strong>The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America.</p> <p><strong>Authors:</strong> Dalagnol, Ricardo; Wagner, Fabien Hubert; Galvão, Lênio Soares; Aragão, Luiz Eduardo Oliveira e Cruz.</p> <p><strong>Contact:</strong> Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>27 Jan 2022 - MANVI v2 was released!</strong> All data were reprocessed and improved. It is advised to re-download the whole series instead of combining v1 and v2. The dataset now covers years 2000-2021.</p> <p><strong>23 May 2019 - MANVI v1 was released.</strong> It covers years 2000-2018.</p> <p> </p> <p><strong>Data:</strong> MODIS (MAIAC) EVI and NDVI indices</p> <p><strong>Scale factor</strong>: 10000</p> <p><strong>Coverage:</strong> South America land</p> <p><strong>Time period:</strong> 2000 to 2021 (starting in 2000, Julian day 64)</p> <p><strong>Spatial resolution:</strong> 1 km</p> <p><strong>Temporal resolution:</strong> 16 days</p> <p><strong>Coordinate reference system:</strong> geographic projection, datum WGS-84</p> <p><strong>Processing details:</strong></p> <ul> <li>The original MODIS (MAIAC) data were described by Lyasputin et al. 2011 (<a href="https://doi.org/10.1029/2010JD014986">https://doi.org/10.1029/2010JD014986</a>). The daily MODIS (MAIAC) surface reflectance data from collection 6, acquired from Terra and Aqua satellites, are available from the MCD19A1 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1</a>). The Bidirectional Reflectance Distribution Function (BRDF) model parameters are available from MCD19A3 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3</a>)</li> <li>The daily MCD19A1 data at 1 km spatial resolution were normalized using the BRDF parameters and Ross-Thick Li-Sparse (RTLS) model considering a fixed nadir view and a 45 deg. solar zenith angle using the parameters from the MCD19A3 product</li> <li>The daily data were aggregated into 16-day composites by the pixel’s median. The 16-day composites always start from Day Of Year (DOY) 016 and end with DOY 352. Therefore, the remaining days from 352 to 365/366 were not used. This procedure was used to facilitate inter-annual comparisons</li> <li>The tiles that cover the South America were mosaicked and re-projected from sinusoidal to geographic projection</li> <li>The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were calculated using standard formulas. The EVI parameters were: C1 = 6, C2 = 7.5, L = 1, G = 2.5</li> </ul> <p><strong>File(s) format:</strong></p> <ul> <li>Zip files for EVI and NDVI - one per year: <ul> <li>Inside them there are raster files with ".tif" format, one per 16-day window. The filename syntax is "maiac_southamerica_DATA_YYYYDOY.tif", where YYYY is the year (e.g. 2000), and the DOY is the Julian day of the last day of the composite window, i.e. YYYYDOY for January 2005 for DOY from 001 to 016 is 2005016, from DOY 017 to 032 is 2005032, etc.</li> </ul> </li> <li>Csv files with the YYYYDOY and "real" dates for the time period</li> </ul> <p><strong>Code:</strong> <a href="https://github.com/ricds/maiac_processing">https://github.com/ricds/maiac_processing</a></p> <p><strong>Acknowledgements:</strong> This work was funded by São Paulo Research Foundation – FAPESP, Brazil, grant 2015/22987-7. We thank NASA, and especially Yujie Wang and Alexei Lyapustin, for providing the freely available MODIS (MAIAC) data.</p> <p> </p> <p><strong>Dataset usage</strong>: This dataset is a product of the first author's PhD work and lots of hours of coding and patience. It is free to use, but if you use this dataset in your work, please make sure to properly cite the repository. We also welcome users to invite us for collaboration.</p> <p> </p> <p><strong>For use of this dataset please cite:</strong></p> <p>Dalagnol, Ricardo; Wagner, Fabien Hubert; Galvão, Lênio Soares; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America". (Version v2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3159487">https://doi.org/10.5281/zenodo.3159487</a></p> <p> </p> <p><strong>More information: </strong>contact Ricardo Dalagnol (ricds@hotmail.com). We also have the MODIS (MAIAC) BRDF-corrected bands 1-8, EVI, NDVI at 1 km with 16-day and monthly aggregation composites.</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.