Find research datasets worth reusing

opencc-by-4.0Nov 2022View details →

Dataset of lightning flashovers on medium voltage distribution lines

This synthetic dataset was generated from Monte Carlo simulations of lightning flashovers on medium voltage (MV) distribution lines. It is suitable for training machine learning models for classifying lightning flashovers on distribution lines. The dataset is hierarchical in nature (see below for more information) and class imbalanced. Following five different types of lightning interaction with the MV distribution line have been simulated: (1) direct strike to phase conductor (when there is no shield wire present on the line), (2) direct strike to phase conductor with shield wire(s) present on the line (i.e. shielding failure), (3) direct strike to shield wire with backflashover event, (4) indirect near-by lightning strike to ground where shield wire is not present, and (5) indirect near-by lightning strike to ground where shield wire is present on the line. Last two types of lightning interactions induce overvoltage on the phase conductors by radiating EM fields from the strike channel that are coupled to the line conductors. Three different methods of indirect strike analysis have been implemented, as follows: Rusck's model, Chowdhuri-Gross model and Liew-Mar model. Shield wire(s) provide shielding effects to direct, as well as screening effects to indirect, lightning strikes. Dataset consists of two independent distribution lines, with heights of 12 m and 15 m, each with a flat configuration of phase conductors. Twin shield wires, if present, are 1.5 m above the phase conductors and 3 m apart [2]. CFO level of the 12 m distribution line is 150 kV and that of the 15 m distribution line is 160 kV. Dataset consists of 10,000 simulations for each of the distribution lines. Dataset contains following variables (features): <ul> <li>'dist': perpendicular distance of the lightning strike location from the distribution line axis (m), generated from the Uniform distribution [0, 500] m,</li> <li>'ampl': lightning current amplitude of the strike (kA), generated from the Log-Normal distribution (see IEC 60071 for additional information),</li> <li>'front': lightning current wave-front time (us), generated from the Log-Normal distribution; it needs to be emphasized that amplitudes (ampl) and wave-front times (front), as random variables, have been generated from the appropriate bivariate probability distribution which includes statistical correlation between these variates,</li> <li>'veloc': velocity of the lightning return-stroke current defined indirectly through the parameter "w" that is generated from the Uniform distribution [50, 500] m/us, which is then used for computing the velocity from the following relation: v = c/sqrt(1+w/I), where "c" is the speed of light in free space (300 m/us) and "I" is the lightning-current amplitude,</li> <li>'shield': binary indicator that signals presence or absence of the shield wire(s) on the line (0/1), generated from the Bernoulli distribution with a 50% probability,</li> <li>'Ri': average value of the impulse impedance of the tower's grounding (Ohm), generated from the Normal distribution (clipped at zero on the left side) with median value of 50 Ohm and standard deviation of 12.5 Ohm; it should be mentioned that the impulse impedance is often much larger than the associated grounding resistance value, which is why a rather high value of 50 Ohm have been used here,</li> <li>'EGM': electrogeometric model used for analyzing striking distances of the distribution line's tower; following options are available: 'Wagner', 'Young', 'AW', 'BW', 'Love', and 'Anderson', where 'AW' stands for Armstrong & Whitehead, while 'BW' means Brown & Whitehead model; statistical distribution of EGM models follows a user-defined discrete categorical distribution with respective probabilities: p = [0.1, 0.2, 0.1, 0.1, 0.3, 0.2],</li> <li>'ind': indirect stroke model used for analyzing near-by indirect lightning strikes; following options were implemented: 'rusk' for the Rusck's model, 'chow' for the Chowdhuri-Gross model (with Jakubowski modification) and 'liew' for the Liew-Mar model; statistical distribution of these three models follows a user-defined discrete categorical distribution with respective probabilities: p = [0.6, 0.2, 0.2],</li> <li>'CFO': critical flashover voltage level of the distribution line's insulation (kV),</li> <li>'height': height of the phase conductors of the distribution line (m),</li> <li>'flash': binary indicator that signals if the flashover has been recorded (1) or not (0). This variable is the outcome/label (i.e. binary class).</li> </ul> Mathematical background used for the analysis of lightning interaction with the MV distribution line can be found in the references cited below. References: <ol> <li>A. R. Hileman, "Insulation Coordination for Power Systems", CRC Press, Boca Raton, FL, 1999.</li> <li>J. A. Martinez and F. Gonzalez-Molina, "Statistical evaluation of lightning overvoltages on overhead distribution lines using neural networks," in IEEE Transactions on Power Delivery, vol. 20, no. 3, pp. 2219-2226, July 2005.</li> <li>A. Borghetti, C. A. Nucci and M. Paolone, An Improved Procedure for the Assessment of Overhead Line Indirect Lightning Performance and Its Comparison with the IEEE Std. 1410 Method, IEEE Transactions on Power Delivery, Vol. 22, No. 1, 2007, pp. 684-692.</li> </ol>

opencc-by-4.0Jan 2023View details →

Global taxonomic occurrence grids using GBIF data for species distribution models.

To achieve large geographic coverage, species occurrence databases that are composed of ad hoc species data collections such as that provided by the Global Biodiversity Information Facility (GBIF) are often used. A drawback to using these data is their geographic sampling bias, in which some regions are more intensively sampled than others, while other areas have very little to none reported sampling effort. Uneven sampling effort can mislead conclusions about biodiversity patterns and species distributions (Gotelli & Colwell, 2001; Lobo, 2008). Here we provide taxonomic occurrence grids to help mitigate the effects of sampling bias in species distribution modeling. These grids can be used to exclude areas of (a custom-defined) low sampling effort from the background when sampling for pseudo-absences’ (Phillips et al., 2009; Barbet-Massin et al.,2012). The occurrence grids have a 1 degree spatial resolution using WGS 84 as the geographic coordinate system. Each 1 degree grid cell contains the number of records present in GBIF corresponding to a specific taxonomic group: plants, mammals, reptiles, amphibians, birds and molluscs. To construct the occurrence grids, we used the 1- by 1-degree world latitude and longitude vector grid provided by ESRI (Redlands, California). It has a custom license which permits it reuse as long as ESRI is cited. It was downloaded from : <a href="https://www.arcgis.com/home/item.html?id=f11bcdc5d484400fa926dcce68de3df7">https://www.arcgis.com/home/item.html?id=f11bcdc5d484400fa926dcce68de3df7</a> To map spatial sampling effort, the number of georeferenced occurrences corresponding to each taxonomic group contained by each 1- by 1-degree grid cell were counted. The grids were then converted to GeoTIFFs. The raster values correspond to the number of occurrences reported for the grid cells. For the purposes of the <a href="https://osf.io/7dpgr/">TrIAS project</a>, grid cells with fewer than 5 occurrences were removed. The TrIAS taxonomic occurrence grids are used as inputs to the TrIAS risk modelling and mapping workflow: https://github.com/trias-project/risk-modelling-and-mapping. Full (with all grid cells containing at least one occurrence) taxonomic occurrence grids are also provided. GBIF data for each taxonomic group were downloaded using the following criteria: “Basis of Record”: Observation, Machine Observation, Human Observation, Specimen, Material sample, Literature Occurrence, Unknown evidence., "HasCoordinate is true", "HasGeospatialIssue is false", "TaxonKey is Amphibia", "Year 1975-2005". Raster Attributes <table> <tbody> <tr> <td> Attribute </td> <td> Description </td> </tr> <tr> <td> OID </td> <td> numeric row ID </td> </tr> <tr> <td> Value </td> <td> the number of records contained in the grid cell </td> </tr> <tr> <td> Count </td> <td> the number of times the value appears in the raster </td> </tr> </tbody> </table>     The extent of each taxonomic occurrence grid: <ul> <li> longitude -180.0; latitude -90.0 (southwest corner) </li> <li> longitude 180.0; latitude 90.0 (northeast corner) </li> </ul>   Files: TrIAS taxonomic occurrence grids amphib_1deg_min5.tif birds_1deg_min5.tif mammals_1deg_min5.tif molluscs_1deg_min5.tif reptiles_1deg_min5.tif   Raw taxonomic occurrence grids amphib_1deg_grid.tif birds_1deg_grid.tif mammals_1deg_grid.tif molluscs_1deg_grid.tif reptiles_1deg_grid.tif

opencc-by-3.0Sep 2022View details →

MCMC samples of the posterior distribution from the paper "TESS spots a mini-neptune interior to a hot saturn in the TOI-2000 system"

This dataset contains the Hamiltonian Monte Carlo samples of the posterior distribution of the planetary and stellar parameters from the paper "TESS Spots a Mini-Neptune Interior to a Hot Saturn in the TOI-2000 System". The file format, NetCDF, is based on HDF5, and is meant to be read by the Python package <a href="https://python.arviz.org/en/latest/">ArviZ</a>. Hot jupiters (P < 10 d, M > 60 M&oplus;) are almost always found alone around their stars, but four out of hundreds known have inner companion planets. These rare companions allow us to constrain the hot jupiter's formation history by ruling out high-eccentricity tidal migration. Less is known about inner companions to hot Saturn-mass planets. We report here the discovery of the TOI-2000 system, which features a hot Saturn-mass planet with a smaller inner companion. The mini-neptune TOI-2000 b (2.70 ± 0.15 R&oplus;, 11.0 ± 2.4 M&oplus;) is in a 3.10-day orbit, and the hot saturn TOI-2000 c (\(8.14^{+0.31}_{-0.30}\) R&oplus;, \(81.7^{+4.7}_{-4.6}\) M&oplus;) is in a 9.13-day orbit. Both planets transit their host star TOI-2000 (TIC 371188886, V = 10.98, TESS magnitude = 10.36), a metal-rich ([Fe/H] = \(0.439^{+0.041}_{-0.043}\)) G dwarf 174 pc away. TESS observed the two planets in sectors 9–11 and 36–38, and we followed up with ground-based photometry, spectroscopy, and speckle imaging. Radial velocities from HARPS allowed us to confirm both planets by direct mass measurement. In addition, we demonstrate constraining planetary and stellar parameters with MIST stellar evolutionary tracks through Hamiltonian Monte Carlo under the PyMC framework, achieving higher sampling efficiency and shorter run time compared to traditional Markov chain Monte Carlo. Having the brightest host star in the V band among similar systems, TOI-2000 b and c are superb candidates for atmospheric characterization by the JWST, which can potentially distinguish whether they formed together or TOI-2000 c swept along material during migration to form TOI-2000 b.

opencc-by-4.0Dec 2022View details →

Current and future global distribution of potential biomes under climate change scenarios

Probability and uncertainty maps showing the potential current and future natural vegetation on a global scale under three different climate change scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) predicted using ensemble machine learning. Current (2022 - 2023)   conditions are calculated on historical long term averages (1979 - 2013), while future projections cover two different epochs: 2040 - 2060 and 2061 - 2080. Files are named according to the following naming convention, e.g.: <ul> <li>biomes_graminoid.and.forb.tundra.rcp85_p_1km_a_20610101_20801231_go_epsg.4326_v20230410</li> </ul> with the following fields: <ul> <li>generic theme: biomes,</li> <li>variable name: graminoid.and.forb.tundra.rcp85,</li> <li>variable type, e.g. probability ("p"), hard class ("c"), model deviation ("md")</li> <li>spatial resolution: 1km,</li> <li>depth reference, e.g. below ("b"), above ("a") ground or at surface ("s"),</li> <li>begin time (YYYYMMDD): 20610101,</li> <li>end time: 20801231,</li> <li>bounding box, e.g. global land without Antarctica ("go"),</li> <li>EPSG code: epsg.4326,</li> <li>version code, e.g. creation date: v20230410.</li> </ul> We provide probability and hard class layers using a revised classification system of the <a href="https://www.jstor.org/stable/2846196">BIOME 6000 project</a> explained in the work of <a href="https://doi.org/10.7717/peerj.5457">Hengl et al. (2018)</a>. The 20 classes from this classification system have then been aggregated in 6 biome classes following the <a href="https://global-ecosystems.org/page/typology">IUCN Global Ecosystem Typology</a> classification system. For probability layers, the uncertainty (model deviation: md) is calculated as the standard deviation of the predicted values of the base learners of the ensemble model. The higher the standard deviation the more uncertain the model is regarding the right value to assign to the pixel. For hard class layers the uncertainty is calculated using the margin of victory (<a href="https://doi.org/10.1016/j.rse.2020.112148">Calderón-Loor et al., 2021</a>) defined as the difference between the first and the second highest class probability value in a given pixel. High values would be measures of low uncertainty, while low values would indicate a high uncertainty. It is highly recommended to use the md layers to properly interpret the results of the map. Styling files are provided in both .SLD and .QML format; two different styling files are provided for the uncertainty of the probability layers and the hard classes due to the different interpretation of the chosen uncertainty metrics. The R scripts and a tutorial will be uploaded to the <a href="https://github.com/Envirometrix/PNVmaps">PNVmaps Github repository</a>, where previous versions of the biomes maps from <a href="https://doi.org/10.7717/peerj.5457">Hengl et al. (2018)</a> is currently hosted. To cite the maps and the methodology, it is possible to refer to the scientific publication: Bonannella C, Hengl T, Parente L, de Bruin S. 2023. Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation. PeerJ 11:e15593 <a href="https://doi.org/10.7717/peerj.15593">https://doi.org/10.7717/peerj.15593</a>

opencc-by-4.0Jun 2023View details →

Test experiments with distributed acoustic sensing and hydrophone arrays for locating underwater sounds.

Whales and dolphins rely on sound for navigation and communication, making them an intriguing subject for studying language evolution. Traditional hydrophone arrays have been used to record their acoustic behavior, but optical fibers have emerged as a promising alternative. This study explores the use of distributed acoustic sensing (DAS), a technique that detects local stress in optical fibers, for underwater sound recording. An experiment was conducted in Lake Zurich, where a fiber-optic cable and a self-made hydrophone array were deployed. A test signal was broadcasted at various locations, and the resulting data was synchronized and consolidated into files. Analysis revealed distinct frequency responses in the DAS channels and provided insights into sound propagation in the lake. Challenges related to cable sensitivity, sample rate, and broadcast fidelity were identified. This dataset serves as a valuable resource for advancing acoustic sensing techniques in underwater environments, especially for studying marine mammal vocal behavior.

opencc-by-4.0Jul 2021View details →

Indicative distribution map for Ecosystem Functional Group T1.4 Tropical heath forests

This archive contains indicative distribution maps and profiles for T1.4 Tropical heath forests, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith et al. (2020) for details. The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

openCC0Sep 2022View details →

Linking temporal changes in species composition and biomass in a globally distributed grassland experiment: The Nutrient Network

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition, and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonization, and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained, or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e., local extinctions) were balanced by gains (i.e. colonization). Under fertilization, the decline in species richness resulted from increased species loss and from decreases in species gained. Biomass increase under fertilization resulted mostly from species that persist, and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition, and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained, or persisting.

openCC (other)Apr 2025View details →

Lake Tahoe Particle size distribution (PSD) Profile data

Profiles of particle size distribution (PSD) taken at Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details

openCC (other)Apr 2025View details →

Lake Tahoe particle size distribution (PSD) data for discrete water samples

Particle size distribution data measured on discrete water samples from Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details

openCC (other)Apr 2024View details →

REU data set from summer of 2022. Project was designed to understand how crayfish (Faxonius rusticus) respond to chemical cues from largemouth bass predators under different shelter distributions.

Research into predator–prey interactions has focused on the landscape of fear and nonconsumptive effects that result from prey responses. Prey behavior is influenced by predator presence and the location and quality of foraging resources in habitats. These areas have been fruitful, but the role of prey refuges has lagged. We investigated how refuge spatial distribution and quality influence prey behavior. To determine the role of the landscape of safety (LOS) in prey decision-making, we altered spatial relationships between refuges, refuge quality, and predation threats in mesocosms. Mesocosms were constructed such that prey only received predatory chemical cues. We employed a behavioral assay including largemouth bass (Micropterus salmoides (Lacepède, 1802): predator) and virile crayfish (Faxonius rusticus (Girard, 1852): prey). Crayfish shelter use was significantly influenced by quality and spatial relationship of shelters to predatory threats, and the interaction of these two factors. Particularly, crayfish used high-quality shelters more often when located closer to predatory cues than farther away and did not use low-quality shelters more than controls. High-quality shelter usage decreased as threat level (measured by gape ratio) decreased. These results support the idea that prey utilize an LOS, and information contained in these two landscapes may alter behavioral decisions.

openCC0Mar 2025View details →

Stomatal Distribution and Post-fire Recovery: Intra- and Interspecific Variation in Plants of the Pyrogenic Florida Scrub, 2023-2024

Premise of the study: Amphistomy is the presence of stomata on both leaf surfaces. This distribution of stomata can increase photosynthesis, but is relatively infrequent, which is often attributed to high costs such as water loss. This study takes place in the Florida scrub- a hot, dry, shrub-dominated habitat that naturally experiences fire. However, decades of anthropogenic suppression and the reintroduction of controlled burns has created varied fire regimes across the region. In this study, we investigated the links between amphistomy and fire by determining (1) how common the trait is in this habitat, and (2) within-species variation before and after experimental fire, and across a time-since-fire gradient (0.25 - 50 years). Methods: We (1) surveyed 116 plant species across scrub habitats for amphistomy presence, and (2) experimentally and observationally investigated intraspecific variation in stomatal traits in response to fire for two post-fire resprouting species of palmetto, Serenoa repens and Sabal etonia (Arecaceae). Key results: Amphistomy was present in 62.9% of all surveyed species and 85.7% of post-fire obligate reseeders, suggesting amphistomy may be beneficial in this group and in the Florida scrub conditions. The stomatal ratio (upper/total stomatal density) was generally stable in response to fire. Stomatal density decreased following fire in S. etonia, with both species experiencing high variation in the post-fire years. Conclusions: Amphistomy is common in this habitat and relatively stable within species in response to fire, while stomatal density responds plastically during postfire regrowth.

openCC0Jul 2021View details →

Stem maps of eight 1 ha forest plots distributed around Ann Arbor, MI and around the University of Michigan Biological Station (UMBS)

In this project we established a network of forest inventory plots to gather the data needed to forecast future forest performance under global change. Data collected from forest inventory plots, i.e., size and location of individual trees from all ages and species, have been shown to be particularly useful to link tree species demographic rates (survival, growth, age at maturity, fecundity) with community characteristics (assemblages and species turnovers), and are also widely used to estimate biomass removal (logging) and biomass production (carbon sequestration).

Mollusc population size distribution monitoring: Fall 2000 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Fall 2000 report of infaunal and epifaunal mollusc species' size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0305a1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Spring 2001 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Spring 2001 report of infaunal and epifaunal mollusc species size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0305b1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Spring 2002 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Spring 2002 report of infaunal and epifaunal mollusc species' size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in formalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0412a1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Fall 2002 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Fall 2002 report of infaunal and epifaunal mollusc species' size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in formalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0412b1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Spring 2003 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Spring 2003 report of infaunal and epifaunal mollusc species size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0501a1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Fall 2003 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Fall 2003 report of infaunal and epifaunal mollusc species size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0502a1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Fall 2005 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Fall 2005 report of infaunal and epifaunal mollusc species' size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0704a1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.

Mollusc population size distribution monitoring: Spring 2004 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh, monitoring sites 1-10

This data set is the Spring 2004 report of infaunal and epifaunal mollusc species' size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in fomalin, transferred to and preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or small etched rulers under a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-0704b1. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.