Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
39
datasets available to search
ShareScore release 0.9.0
Dataset results
39 results for “body mass estimation”
Dataset for: On the estimation of body mass in temnospondyls: A case study using the large-bodied Eryops and Paracyclotosaurus
Open the record for dataset details and reuse information.
Data from: Estimating body mass of free-living whales using aerial photogrammetry and 3D volumetrics
1. Body mass is a key life history trait in animals. Despite being the largest animals on the planet, no method currently exists to estimate body mass of free-living whales. 2. We combined aerial photographs and historical catch records to estimate the body mass of free-living right whales (Eubalaena sp.). First, aerial photogrammetry from unmanned aerial vehicles was used to measure the body length, width (lateral distance) and height (dorso-ventral distance) of free-living southern right whales (E. australis; 48 calves, 7 juveniles and 31 lactating females). From these data, body volume was estimated by modelling the whales as a series of infinitely small ellipses. The body girth of the whales was next calculated at three measurement sites (across the pectoral fin, the umbilicus and the anus) and a linear model was developed to predict body volume from the body girth and length data. To obtain a volume-to-mass conversion factor, this model was then used to estimate the body volume of eight lethally caught North Pacific right whales (E. japonica), for which body mass was measured. This conversion factor was consequently used to predict the body mass of the free-living whales. 3. The cross-sectional body shape (height-width ratio) of the whales was slightly flattened dorso-ventrally at the anterior end of the body, almost circular in the mid region, and significantly flattened in the lateral plane across the posterior half of the body. Compared to a circular cross-sectional model, our body mass model incorporating body length, width and height improved mass estimates by up to 23.6% (mean=6.1%, SD=5.27). Our model had a mean error of only 1.6% (SD=0.012), compared to 9.5% (SD=7.68) for a simpler body length-to-mass model. The volume-to-mass conversion factor was estimated at 754.63kg m-3 (SD=50.03). Predicted body mass estimates were within a close range of existing body mass measurements. 4. We provide a non-invasive method to accurately estimate body mass of free-living whales while accounting for both their structural size (body length) and relative body condition (body width). Our approach can be directly applied to other marine mammals by adjusting the model parameters (body mass model script provided).
Data from: Body mass estimates of an exceptionally complete Stegosaurus (Ornithischia: Thyreophora): comparing volumetric and linear bivariate mass estimation methods
Body mass is a key biological variable, but difficult to assess from fossils. Various techniques exist for estimating body mass from skeletal parameters, but few studies have compared outputs from different methods. Here, we apply several mass estimation methods to an exceptionally complete skeleton of the dinosaur Stegosaurus. Applying a volumetric convex-hulling technique to a digital model of Stegosaurus, we estimate a mass of 1560 kg (95% prediction interval 1082–2256 kg) for this individual. By contrast, bivariate equations based on limb dimensions predict values between 2355 and 3751 kg and require implausible amounts of soft tissue and/or high body densities. When corrected for ontogenetic scaling, however, volumetric and linear equations are brought into close agreement. Our results raise concerns regarding the application of predictive equations to extinct taxa with no living analogues in terms of overall morphology and highlight the sensitivity of bivariate predictive equations to the ontogenetic status of the specimen. We emphasize the significance of rare, complete fossil skeletons in validating widely applied mass estimation equations based on incomplete skeletal material and stress the importance of accurately determining specimen age prior to further analyses.
Figure 5 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 5. Box plots with whiskers showing the variation among locomotion modes of percentage prediction errors (%PE) for the multiple regression analysis (MR; grey) and the single regression analysis (SR; white) equations adjusted in modern birds. Box length shows the interquartile range (25th and 75th percentiles). The horizontal line within boxes indicates the median. Vertical lines show the 5–95% confidence limits. Points indicate values outside these limits (i.e. outliers). Black horizontal lines between the grey and white boxes show the %PE estimates obtained with the equation based on humeral length (HL), the osteological variable less affected by ecological groupings (as shown by its lower F-statistic values; see Tables 6 and 7). %PE values greater than zero indicate an underestimation and %PE values lower than zero indicate an overestimation. A, %PE variation with respect to groups of aerial locomotion. Abbreviations: CF, continuous flapping; FG, flapping and gliding; FB, flapping and bounding; S, soaring. B, %PE variation with respect to groups of non-aerial locomotion. Abbreviations: A, aquatic; TG, terrestrial ground-dwelling; TN, terrestrial non-ground-dwelling; ATG, aquatic and grounddwelling; TGN, perching and ground-dwelling.
Figure 1. Calibrated phylogeny for the main avian taxa. Tree topology was obtained from O in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 1. Calibrated phylogeny for the main avian taxa. Tree topology was obtained from O'Connor, Chiappe & Bell (2011) and divergence times are based on a 'literal' interpretation of the fossil record from Brockelhurst et al. (2012). Taxa abbreviations: Nth, Neornithes; Orph, Ornithuromorpha; Orn, Ornithothoraces; Orth, Ornithurae; Pyg, Pygostylia.
Figure 4 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 4. Biplots used in the selection of four variables for each fossil group of Mesozoic birds: humeral length (HL), femoral length (FL), diaphyseal craniocaudal width of ulna (dUW), and diaphyseal craniocaudal width of femur (dFWcc). Each predictor variable was plotted against a combination of the 14 remaining variables used for estimating body mass (BM; Table S3). The biplots show the regression line fitted for extant birds (grey circles) with the 95% confidence intervals for BM predictions (dotted lines). Following the procedure of selection of variables (see text), HL and FL were used for generating functions that can be applied to all fossil avian taxa. In contrast, dUW and dFWcc could not be incorporated into the functions adjusted for estimating BM in Archaeopterygidae and Enantiornithes, respectively.
Figure 3 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 3. Effects of weighting for the best-fitting multiple regression equation obtained from the modern data set (see Table 2). A, distribution of familiar residuals for unweighted data, and for data weighted by families. Each box plot with whiskers represents one family. Box length shows the interquartile range (25th and 75th percentiles). Horizontal lines indicate the 5–95% confidence limits. Asterisks show outliers. Abbreviations for families: Ac, Accipitridae; Ad, Alcedinidae; Ae, Aegothelidae; Al, Alcidae; An, Anatidae; Ap, Apodidae; Ar, Ardeidae; At, Artamidae; Au, Alaudidae; Ca, Caprimulgidae; Cc, Cacatuidae; Ch, Charadriidae; Ci, Ciconiidae; Co, Columbidae; Cn, Cinclidae; Cr, Coraciidae; Ct, Catharthidae; Cu, Cuculidae; Cv, Corvidae; Di, Diomedeidae; Fa, Falconidae; Fg, Fringillidae; Fr, Fregatidae; Ga, Gaviidae; Gr, Gruidae; He, Hemiprocnidae; Hi, Hirundinidae; La, Laridae; Ln, Lanidae; Me, Meleagridae; Mg, Megapodidae; Mo, Motacillidae; Mp, Meropidae; Ms, Musophagidae; Mu, Muscicapidae; Ot, Otididae; Pa, Paridae; Pc, Pelecanoididae; Pd, Podicipedidae; Pe, Pelecanidae; Ph, Phasianidae; Pic, Picidae; Pit, Pittidae; Pl, Phalacrocoracidae; Pn, Pandionidae; Po, Podargidae; Pr, Procellaridae; Ps, Psittacidae; Pt, Pteroclidae; Pu, Prunellidae; Ra, Rallidae; Re, Recurvirostridae; Ry, Rynchopidae; Sc, Stercoriidae; Sg, Strigidae; So, Scolopacidae; Sr, Sturnidae; St, Sternidae; Su, Sulidae; Sy, Sylviidae, Te, Tetraonidae; Th, Threskiornithidae; Tt, Tytonidae; Tu, Turdidae; Ty, Tyrannidae; Up, Upupidae. B, plot showing the variations of %MPE with the increase of individuals per family. The dashed line represents the unweighted multiple regression analysis (MR) and the grey line represents the weighted MR.
Figure 2 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 2. Illustration of osteological limb measurements used in this study and defined in Table 1: A, cranial aspect of the humerus; B, dorsal aspect of the ulna and the radius; C, dorsal aspect of the carpometacarpus; D, caudal aspect of the femur; E, caudal aspect of the tibiotarsus; F, cranial aspect of the tarsometarsus.
Figure 1 in How common is gigantism in insular fossil shrews? Examining the 'Island Rule' in soricids (Mammalia: Soricomorpha) from Mediterranean Islands using new body mass estimation models
Figure 1. Diagram of Mediterranean Islands showing endemic genera and species of soricids from the Plio–Quaternary to the present: white shrew silhouettes, current species; grey shrew silhouettes, extinct or with presence in the fossil record. From west to east: species of Nesiotites (extinct) from the Gymnesic Islands; species of Asoriculus (extinct) from the Corso-Sardinian complex; Asoriculus burgioi (extinct) from Sicily; Crocidura sicula sicula (present in the fossil record and extant) and Crocidura sicula esuae (extinct) from the Sicilian–Maltese archipelago; Crocidura zimmermanni (present in the fossil record and extant) from Crete; and Crocidura suaveolens praecypria (extinct) from Cyprus. See text for references.
Figure 2 in How common is gigantism in insular fossil shrews? Examining the 'Island Rule' in soricids (Mammalia: Soricomorpha) from Mediterranean Islands using new body mass estimation models
Figure 2. Chronological framework of the species used in the study: in black, species related to the tribe Nectogalini; in grey, Crocidura species. The circles highlight the species analysed from different sites sorted biochronologically (connected by a thick line), the squares highlight the species analysed from only one site, and the empty squares highlight the mainland (ancestor) species. Below the species: the site, locality, and molar/s used for estimating body mass are listed.
Figure 4 in How common is gigantism in insular fossil shrews? Examining the 'Island Rule' in soricids (Mammalia: Soricomorpha) from Mediterranean Islands using new body mass estimation models
Figure 4. Estimations of body masses (in g) of Nesiotites species (row A, lower molars) and Crocidura zimmermanni (row B, lower molars; and row C, upper molars) from different sites ordered chronologically (see Table 2 for site acronyms). The first column shows the predictions of body mass using all of the estimators (white square, LM1; black circle, WM1; grey circle, TRLM1; grey square, AAM1; white circle, TRAAM1) and the following columns represent each measurement separately (LM1, WM1, TRLM1, AAM1, and TRAAM1, respectively). In order to observe the fluctuation of the points, we linked the points with a line. Dotted lines in Nesiotites diagrams (row A) separate the three statistically different subgroups.
Figure 3 in How common is gigantism in insular fossil shrews? Examining the 'Island Rule' in soricids (Mammalia: Soricomorpha) from Mediterranean Islands using new body mass estimation models
Figure 3. Measurements of mandible, cranium, and postcranial bones. A, cranium: WOC, width of the occipital condyles. B, mandible: TRLM/1, tooth row length of lower molars. C, femur: FL, femur length; FTDp, proximal femoral transversal diameter; FAPDd, distal femoral anteroposterior diameter; FTDd, distal femoral transversal diameter. D, humerus: HL, humerus length; HAPDp, proximal humeral anteroposterior diameter; HAPDd, distal humeral anteroposterior diameter; HTDd, distal humeral transversal diameter. E, tibia: TL, tibia length; TAPDp, proximal tibia anteroposterior diameter; TTDp, proximal tibia transversal diameter; TTDd, distal tibia transversal diameter.
Figure 5 in How common is gigantism in insular fossil shrews? Examining the 'Island Rule' in soricids (Mammalia: Soricomorpha) from Mediterranean Islands using new body mass estimation models
Figure 5. Diagrams comparing the body mass (in g) of extant relatives and fossil species: A, extinct Asoriculus and Nesiotites species and the extant species of the tribe Nectogalini; B, extinct and extant Crocidura species. Lines indicate the body mass range of groups. See the legend for symbols.
Data from: Body mass estimates of an exceptionally complete Stegosaurus (Ornithischia: Thyreophora): comparing volumetric and linear bivariate mass estimation methods
Open the record for dataset details and reuse information.
Data from: Estimating body mass of free-living whales using aerial photogrammetry and 3D volumetrics
Open the record for dataset details and reuse information.
Data from: Estimating egg mass-body mass relationships in birds
Open the record for dataset details and reuse information.
mass properties in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
mass properties
Data from: The extinct, giant giraffid Sivatherium giganteum: skeletal reconstruction and body mass estimation
Open the record for dataset details and reuse information.
Novel Equations for Estimating Lean Body Mass in Patients With Chronic Kidney Disease
ClinicalTrials.gov study NCT04074278. IPD Sharing: NO. Countries: 1. Publications: 0.
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.