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Estimating spawning Green Sturgeon (Acipenser medirostris Ayres, 1854) abundance using side scan sonar and N-mixture models
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Data to support manuscript: A Comparison of Two ROV Survey Methods Used to Estimate Fish Assemblages and Densities Around a California Oil Platform
This fish dataset was collected at platform Harmony, between Aug 25 and Aug 26, 2018. The ROV fish survey was done with two methods: industry (mimicking an inspection survey conducted for platform structural inspections) and biological method. Due to differences between the two methods in the positioning of the ROV vis a vis the jacket crossbeams, fish densities and diversities were different between the two methods at the platform bottom. This dataset provides fish counts and the relevant survey parameters (transect length and depth).
Estimated wetland vegetation cover comparing reference and muskrat disturbed areas
Biota that act as ecosystem engineers are increasingly recognized as effective components of habitat restoration as they can continuously alter and shape their environments without human intervention. Muskrats are considered ecosystem engineers and are relatively common in North American wetlands. While muskrat impacts to large areas have been documented, few studies have quantified the impact of muskrats on ecosystem biodiversity. We conducted a field study in wetlands along the Upper St. Lawrence River (New York, USA) to investigate the effects of muskrat herbivory and structure building on plant biodiversity in cattail-invaded wetlands. The data collected are separated into two main groups, i.e. “reference” vegetation surveys and “muskrat” vegetation surveys. “Reference” surveys were conducted for the partial grant fulfillment funded by the New York Department of Environmental Conservation [contract AM10165] and the National Fish and Wildlife Foundation special project administered by the United States Fish and Wildlife Service, Partners for Fish and Wildlife Program, New York Field Office, Cortland, NY [grant number #2005-0129-055/58859]. “Muskrat” surveys were conducted for the Masters project by Z.X. Kua. The five datasets include 1) Reference quadrat plant taxa estimated cover (n = 1912), 2) Reference quadrat cattail measurements (n = 737), 3) Muskrat-disturbed quadrat plant taxa estimated cover (n = 1886), 4) Muskrat-disturbed quadrat cattail measurements (n = 582), and 5) Wetland plant taxa lookup table for vegetation survey (n = 135).
Comparisons among five canopy-cover estimating methods in five Douglas-fir/western hemlock structure types in the western Oregon Cascades
Estimates of forest canopy cover are widely used in forest research and management, yet methods used to quantify canopy cover and the estimates they provide vary greatly. Four ground-based techniques for estimating overstory cover -line- intercept, spherical densiometer, moosehorn, and hemispherical photography-and cover estimates generated using the Forest Vegetation Simulator (FVS) were compared in five Douglas- fir/western hemlock structure types in western Oregon. Differences in cover estimates among the ground-based methods did not depend on the structure type in which they were measured (p=0.33). As expected, estimates of cover increased and within-stand variability decreased with increasing angle of view among techniques. However, the moosehorn provided the most conservative estimates of vertical-projection overstory cover. The FVS-generated cover was consistently lower (by up to 44%, 17% on average) than the ground-based estimates and is not advised as a substitute for ground-based measures in these forest types. Regression equations are provided to allow conversion among canopy cover estimates developed with the four ground-based methods.
Characterization of burned and unburned moist acidic tundra soils for estimating C and N loss from the 2007 Anaktuvuk River Fire, sampled in 2008.
This file contains the soil profile data for burned and unburned moist acidic tundra sites used to estimate C and N loss from the Anaktuvuk River Fire (2007). These sites were sampled in summer of 2008. Unburned sites were used to develop a method for estimating soil organic layer depth and plant biomass, and for determining the characteristics of unburned soil organic layers. In burned sites, we characterized residual organic soils and used biometric measurements of tussocks to reconstruct pre-fire soil organic layer depth. Together, these measurements were used to reconstruct pre-fire soil and plant carbon and nitrogen pools and estimate ecosystem losses of these elements during the fire.
Estimates of C and N loss from moist acidic tundra sites burned in the 2007 Anaktuvuk River Fire.
Estimated mean pre-fire C and N pools, and C and N loss from 20 sites in the Anaktuvuk River Fire (2007). These sites were sampled in summer of 2008. In each site, we characterized residual organic soils and used biometric relationships developed in unburned sites to reconstruct pre-fire soil organic layer depth, and plant and soil C and N pools. We then estimated fire-driven losses of C and N from plant and soil organic layer pools.
Seeing the light: high temporal frequency (5-10min resolution) measurements of dissolved oxygen, photosynthetically active radiation, temperature, and depth used to estimate metabolism in restored and unrestored Baltimore streams.
The continually increasing global population residing in urban landscapes impacts numerous ecosystem functions and services provided by urban streams. Urban stream restoration is often employed to offset these impacts and conserve or enhance the various functions and services these streams provide. Despite the assumption that ‘if you build it, [the function] will come’, current understanding of the effects of urban stream restoration on stream ecosystem functions are based on short term studies which may not capture variation in restoration effectiveness over time. We quantified the impact of stream restoration on nutrient and energy dynamics of urban streams by studying 10 urban stream reaches (five restored, five unrestored) in the Baltimore, Maryland, USA, region over a two-year period. We measured gross primary production (GPP) and ecosystem respiration (ER) at the whole-stream scale continuously throughout the study and nitrate (NO3-N) spiraling rates seasonally (spring, summer, autumn) across all reaches. There was no significant restoration effect on NO3-N spiraling across reaches. However, there was a significant canopy cover effect on NO3-N spiraling, and directly comparing paired sets of unrestored-restored reaches showed that restoration does affect NO3-N spiraling after accounting for other environmental variation. Furthermore, there was a change in GPP:ER seasonality, with restored and open-canopied reaches exhibiting higher GPP:ER during summer. The restoration effect, though, appears contingent upon altered canopy cover, which is likely to be a temporary effect of restoration and is a driver of multiple ecosystem services, e.g., habitat, riparian nutrient processing. Our results suggest that decision-making about stream restoration, including evaluations of nutrient benefits, clearly needs to consider spatial and temporal dynamics of canopy cover and tradeoffs among multiple ecosystem services. Here we provide the raw dissolved oxygen, temperature, li
Data to estimate stand density and average basal diameter from unburned black spruce stands used in the effects of variations in post-fire organic layer thickness studies in the Delta Junction region, 1995-2003
This database contains data on basal diameter and distances from a center point to the trees sampled, which is used to estimate stand density in unburned black spruce plots used in an analysis of variations in the depths of surface organic layers found in burned and unburned black spruce stands, and the effects of variations in depth of burning on soil temperature and moisture, and organic layer carbon stocks. Data for the overall study were collected between 1995 and 2003 by Eric Kasischke (University of Maryland), Kathy O?Neill (Duke University), and Jill Johnstone (University of Alaska Fairbanks). Sites were located in burned black spruce stands within the perimeters of three recent fires (1987, 1994, and 1999), unburned black spruce stands adjacent to the burned stands, and within one black spruce stand that burned in 1956. The three fires were: (a) the 1987 Granite Creek fire located 15 km to the east of Delta Junction, Alaska USA, bordering the Alaska Highway on the North and Jarvis Creek on the south; the 1994 Hajdukovich Creek fire located 45 km southeast of Delta Junction Alaska, USA, bordering the Alaska Highway to the North and the Gerstle River to the West, and the 1999 Donnelly Flats fire, located 8 km south of Delta Junction, bordering Jarvis Creek to the east and the Richardson Highway on the west. Data that were collected and are in databases associated with this project include: (1) organic layer depths in burned stands; (2) organic layer depths in unburned stands; (3) basal diameters of overstory trees in unburned stands and distance measures that can be used to estimate stand density; (4) mineral soil temperature and moisture data in burned stands; (5) mineral soil temperature and moisture data in unburned stands; and (6) bulk density and percent carbon data from different organic layers in unburned stands.
Fire Severity Estimates: 2001 Survey Line Burn
Field-based estimates of fire severity for 85 plots located near the Tanana River in the Survey Line Burn. Composite Burn Index estimates were taken during June-August 2002. The locations of each plot are stored as differentially corrected GPS files and as an ArcGIS point shapefile. Digital aerial photography of the post-fire area from August and September 2002 are in the data base. Database also includes remotely sensed fire severity indices of the entire Survey Line Burn including the Normalized Burn Ratio from a 21-July-2002 Landsat ETM+ image and the differenced Normalized Burn Ratio from a 6-June-2001 pre-fire Landsat ETM+ image and the post-fire 21-July-2002 Landsat ETM+ image.
MODIS Leaf Area Index estimates for Alaska: 2002
The MODIS Leaf Area Index (LAI) Product is a global product produced every 8 days. The Leaf Area Index is estimated by a radiative transfer model assuming a given distribution of biome types within each pixel. The LAI Product was evaluated for the period of May 2002 to September 2002. The temporal pattern of spring greenup and fall senescence appeared reasonable across a large latitudinal transect from the Kenai Peninsula to the Arctic Coastal Plain. The temporal pattern also appeared reasonable across an elevational transect from Bonanza Creek Experimental Forest to Caribou Poker Creek Research Watershed to Eagle Summit. The positional accuracy and spatial pattern LAI was judged excellent by comparing the M2002 maximum LAI for the Survey Line Burn with a Landsat ETM+ image. However, there were two consistent problems with the LAI index at all spatial scales. First, a dip in maximum LAI during the green-up period most likely indicated cloud contamination of pixels. Second, the maximum 2002 LAI estimate was unrealistically high (>6.5) in many areas of Alaska. The accuracy of global estimates of leaf area and vegetation indices are suspect for high latitude areas due to several factors: 1) There is no tundra or taiga biome used in the leaf area index radiative transfer model. 2) Although a cloud-screen algorithm is applied on the front-end of processing, sub-pixel cloud contamination may occur over much of Alaska. 3) Subpixel broadleaf shrubs may lead to an overestimate of leaf area index and inflate vegetation indices.This dataset contains MOD15 leaf area index (LAI) and fraction of photosynthetically absorbed radiation (FPAR) for most of Alaska during the 2002 growing season. The data are in hdf format, with one file for each MODIS tile, for each 8-day composite period. The original quality control bits are included in each hdf file. The data are in the integerized sinusoidal projection with approzimately 1-km pixel size. The files were submitted in winzip format. T
Estimated Age of Carbon within the Soil Organic Layer for Murphy Dome study site in 2013
This file contains radiocarbon data used to estimate age of the soil organic layer for black spruce and Alaska paper birch forest in the Murphy Dome fire scar near Fairbanks, AK. All information was collected in summer 2013 and subsequently processed and analyzed in the laboratory.
Estimates of Forest Structure, Successional Trajectory, and Carbon and Nitrogen Pools Across the 2004 Wildfire Network Sites
This dataset contains stand structure and ecosystem carbon and nitrogen pool data measured in 2005 and 2006. It includes in situ measurements of post-fire residual above and belowground carbon and nitrogen pools, reconstructions of pre-fire pools and estimates of losses. Successional trajectory was calculated from measurements of tree seedling density and biomass made in 2017.
Eight Mile Lake Research Watershed, Thaw Gradient: Foliar mineral element concentrations, stocks and annual litterfall fluxes estimated for July 2017
In this study, we are asking the question: how permafrost degradation may influence foliar mineral element cycling with changing subarctic tundra vegeatation? We are answering this question by using a combination of field measurements (aboveground biomass, foliar biomass, foliar net primary productivity (NPP)) and laboratory measurements (mineral element foliar concentration: Al, Ca, Fe, K, Mn, P, S, Si, and Zn) to evaluate the mineral element foliar stocks and the mineral element foliar fluxes upon annual litterfall. We covered 7 vascular plant species and 2 groups of non-vascular species (mosses and lichens) from an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change (active layer, water table depth, and vegetation composition) due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. Elemental analyses of plant species typical from a moist acidic tundra, combined with aboveground biomass and NPP measurements, brought key information on the influence of the vegetation composition on the litter elemental composition, and thereby the plant nutrient cycling across the subarctic tundra.
Estimates of White Spruce density at two elevations from 1600-present
Paleoecological investigations of ecosystem responses to past climate change can provide insight into plausible scenarios of response to future change and can elucidate factors that may influence the overall predictability of such responses. There is particular interest in the rate at which subarctic Picea populations respond to climate change, as the rate of conversion from tundra to forest may affect the rate of future climate warming. We investigated recent changes in the structure and distribution of treeline white spruce forests in the White Mountains and the Alaska Range. Treeline advance was ubiquitous, but asynchronous in time, occurring significantly earlier in the White Mountains in interior Alaska than in the Alaska Range. The mean lag between initiation of recruitment and forest development was estimated at approximately 200 years, similar to what modeling studies have found. Although continued advance of Picea is the most likely scenario of future change, the recent history of treeline advance suggests that nonlinear responses to warming may be likely due to nonlinear growth responses of individual trees to temperature, limitation of Picea establishment in highly permafrost-affected sites, and decreasing seed availability as the advancing front moves farther from dense seed sources. All of these factors may cause Picea populations to respond nonlinearly to future warming, and these potential nonlinearities caution against uncritical extrapolation from recent trends.
Point-Quarter Harvested Plant Weight Measurements to Estimate Shrub ANPP in a Chihuahuan Desert Creosote Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (2007- present)
In an effort to better quantify NPP of Creosotebush in the Five-Points region, it was decided to test the Point-Quarter method against the standard 1-m2 quadrat method that has been in use since 1998. Transects were laid out across the 5 mammal trapping webs as well as across burned and unburned plots of the Mixed Shrub site (MS). Repeat measures of the same bushes are performed seasonally. Whole shrubs of various size classes are collected and sorted and weighed to develop regressions for biomass.
SGS-LTER CO2 Elevation Study: Visual estimates of plant cover on the OTC project on the Central Plains Experimental Range, Nunn, Colorado, USA 1997 - 2001
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. Every month, during the growing season, from 1997-2001, 10 small quadrats were placed in ambient and elevated CO2 open-top-chambers, and plant cover, by species, was visually estimated. In general, elevated CO2 caused an increase in one C3 grass species, Stipa comata, and a small increase in forbs.
STEPPS 2000 Year Forest Composition Estimates, Upper Midwest US, Level 2
Forest ecosystems in eastern North America have been in flux for the last several thousand years, well before Euro-American land clearance and the 20th-century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatio-temporal pollen-vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2,100 to 300 years ago. Using this approach, we find evidence for large changes in the relative abundance of some species, and significant changes in community composition. However, these changes took place against a regional background of changes that were small in magnitude or not statistically significant, suggesting complexity in the spatio-temporal patterns of forest dynamics. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2000 years. Despite range in-filling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15-20 km in Minnesota and northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2,000 years.This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.
STEPPS 8000 Year Forest Composition Estimates, Northeastern US, Level 2
These reconstructions of forest composition in the northeastern US for the last 8,000 years help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. These reconstructions are based on 1) the pollen–vegetation model (PVM) STEPPS, 2) a network of fossil and modern pollen data mostly drawn from the Neotoma Paleoecology Database (www.neotomadb.org), and 3) a vegetation calibration dataset based on a spatial statistical model of relative tree abundances from the Township Proprietor Survey (TPS) from the early EuroAmerican settlement period. STEPPS is a process-based Bayesian Hierarchical Model that is run in two stages: a parameterization stage based upon spatial data layers of forest composition and pollen assemblages, and a prediction stage based on fossil pollen assemblages. The statistical modeling of the TPS forest data and relative abundances is described by Paciorek et al. (2016, PLoS One, doi: 10.1371/journal.pone.0150087) and is available at EDI as PalEON Products msb.paleon.1 (doi: 10.6073/pasta/8544e091b64db26fdbbbafd0699fa4f9) and msb.paleon.4 (doi: 10.6073/pasta/3c4844cfe8beff6b173b62034d1cb5d8). The parameterization of STEPPS and comparison to REVEALS, a different widely used PVM, is described by Trachsel et al. (2020, Quaternary Research, doi:10.1017/qua.2019.81). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales. The parameterized STEPPS model was then run for a network of fossil pollen records from the Neotoma Paleoecology Database to produce post
A database for benchmarking organ dose estimates and uncertainties in CT
<p>This database includes patient images and associated verified Monte Carlo based estimates of organ doses that may be used for benchmarking different organ dose estimation techniques against a reference standard.</p>
Machine learning estimates of eddy covariance carbon flux in a scrub in the Mexican highland
<p>Arid and semi-arid ecosystems contain relatively high species diversity and are subject to intense use, in particular extensive cattle grazing, which has favoured the expansion and encroachment of perennial thorny shrubs into the grasslands, thus decreasing the value of the rangeland. However, these environments have been shown to positively impact global carbon dynamics. Machine learning and remote sensing had enhanced our knowledge about carbon dynamics, but they need to be further developed and adapted to particular analysis. We measured the net ecosystem exchange of C (NEE) with the Eddy Covariance (EC) method and estimated GPP in a thorny scrub at Bernal in Mexico. We tested the agreement between EC estimates and remotely sensed GPP estimates from MODIS, and also with two alternative modelling methods: ordinary least squares multiple regression (OLS) or ensembles of machine learning algorithms (EML). The variables used as predictors were Moderate Resolution Spectroradiometer (MODIS) spectral bands, vegetation indices and products, as well as gridded environmental variables. The Bernal site was a carbon sink despite it was overgrazed, the average NEE during fifteen months of 2017 and 2018 was -0.78 g C m<sup>-2</sup> d<sup>-1</sup> and the flux was negative or neutral during the measured months. The probability of agreement (θs) represented the agreement between observed and estimated values of GPP across the range of measurement. According to the mean value of θs, agreement was higher for the EML (0.6) followed by OLS (0.5) and then MODIS (0.24). This graphic metric was more informative than r<sup>2</sup> (0.98, 0.67, 0.58 respectively) to evaluate the model performance. This was particularly true for MODIS because the maximum θs of 4.3 was for measurements of 0.8 g C m<sup>-2</sup> d<sup>-1</sup> and then decreased steadily below 1 θs for measurements above 6.5 g C m<sup>-2</sup> d<sup>-1 </sup>for this scrub vegetation. In the case of EML and OLS the θs was stable across the range of measurement. We used an EML for the Ameriflux site US-SRM, which is similar in vegetation and climate, to predict GPP at Bernal, but θs was low (0.16) indicating the local specificity of this model. Although cacti were an important component of the vegetation, the night time flux was characterized by positive NEE, suggesting that the photosynthetic dark-cycle flux of cacti was lower than ecosystem respiration. The discrepancy between MODIS and EC GPP estimates stresses the need to understand the limitations of both methods.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.