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34 results for “large animals”
Data from: Overall dynamic body acceleration measures activity differently on large vs small aquatic animals
<p>Acceleration-based proxies for activity and energy expenditure are widely used in bio-logging studies of animal movement and locomotion to explore biomechanical strategies, energetic costs of behaviour, habitat use and the impact of anthropogenic disturbance. The foremost such proxy is Overall Dynamic Body Acceleration (ODBA) along with variants VeDBA and PDBA. This technique, which involves summing the magnitude of high-pass-filtered acceleration signals (the so-called dynamic acceleration) over a reference interval, has been applied to animals as diverse as shags, lobsters, humans and whales. The relationship between ODBA and energy use has been tested empirically on animals small enough to house in laboratory facilities and arguments have been offered for why the method should be generally applicable, however validations on larger animals are scant.</p> <p><span>Here, we examine how body size impacts ODBA and its variants under steady locomotion in large aquatic animals, using cetaceans as model species. To do this, we first develop a simplified mathematical model for the acceleration signals that would be measured by a tag on a swimming animal. We then test this model with empirical data gathered using bio-logging tags on whale species covering nearly an order of magnitude difference in body length from 1.3 m harbour porpoises to 12 m sperm whales.</span></p> <p><span>We show that the motions measured by ODBA can be fundamentally different in small compared to large aquatic animals. Whereas dynamic acceleration in small animals is predominantly due to specific acceleration (i.e., actual accelerative motions generated by muscle action), in larger aquatic animals body rotations (i.e., changes in orientation that accompany swimming and manoeuvring) can dominate the measured acceleration. </span></p> <p><span>As body rotations do not necessarily increase in magnitude as swimming speed increases, ODBA may under-estimate the relative cost of behaviours or responses to disturbance in large aquatic animals. This does not lessen the value of ODBA for small animals, but it raises a caution against uncritical use on larger animals. For large aquatic animals, activity proxies that specifically remove body rotations using gyroscopes or magnetometers may provide more consistent estimates of energy use although these methods are yet to be validated.</span></p>
Data from: The travel speeds of large animals are limited by their heat-dissipation capacities
<div> <h2>Purpose</h2> <p>This is an extension of the travel speed dataset published by Dyer et al. 2023 in PLOS Biology that includes additional metadata. Data follow the same aggregation to species level by grouping records across unique combinations of study and species while preserving variation across important categorical covariates (listed below). </p> </div> <div> <h2>Scripts</h2> <ul> <li><code>scripts/modelling/fit_model.R</code>: Fits mechanistic locomotion models to aggregated data using RStan. Plots predictions and outputs parameter estimates of competing models.</li> </ul> </div> <div> <h2>Data Columns</h2> <p>Each heading below describes a column of the travel speed dataset.</p> <p><strong>move_speed_ref</strong>: Unique reference number for each study reporting animal travel speed. The corresponding references are contained within the supplementary reference list file.</p> <p><strong>move_mass_ref</strong>: Unique reference number for each study reporting animal body mass. The corresponding references are contained within the supplementary reference list file.</p> <p><strong>scientific_name</strong>: Scientific name of the species according to the taxonomy of the Global Biodiversity Information Facility (accessed via GBIF.org during 2022). A small number of studies that report only the genus name or common name of the species are reported in our dataset as <em>Genus sp.</em> (e.g. <em>Gazella sp.</em>). One study, which estimated the travel speed and body mass of an unknown species of mouse via camera traps, is reported in our dataset as <em>Amazon mouse sp.</em></p> <p><strong>move_movement_mode</strong>: Categorical value indicating whether the reported travel speed corresponds to an animal engaged in flying, running, or swimming. This allows species to be accommodated that are capable of multi-modal locomotion (e.g. northern elephant seal, <em>Mirounga angustirostris</em>).</p> <p><strong>taxon_group</strong>: Categorical value indicating membership to one of eight animal groups (amphibian, arthropod, cnidarian, bird, fish, mammal, mollusc, reptile).</p> <p><strong>thermo_reg</strong>: Categorical value indicating thermoregulatory strategy, i.e. the contribution of metabolic heat production to the maintenance of core body temperature during rest:<br>- <strong>ectotherm</strong>: negligible contribution, body temperature matches ambient temperature<br>- <strong>mesotherm</strong>: weak contribution with partial thermal stability, as in tunas, lamnid sharks, and leatherback sea turtles<br>- <strong>endotherm</strong>: strong contribution with metabolic stability even when ambient temperatures are significantly below body temperature</p> <p><strong>move_medium</strong>: Categorical value indicating whether the animal’s travel speed was measured during locomotion within the terrestrial realm (air) or aquatic realm (water).</p> <p><strong>move_speed_method</strong>: Categorical value indicating whether travel speed was estimated directly (i.e. instantaneously via direct observation in real-time, animal-attached speedometer, or video recording) or indirectly from higher-resolution telemetry data (i.e. from changes in an animal’s spatial coordinates at intervals < 30 minutes apart).</p> <p><strong>move_study_condition</strong>: Categorical value indicating whether travel speed was estimated under natural field conditions or under a controlled laboratory setting such as within an aquarium or mesocosm. Travel speeds of the smallest animals (e.g. arthropods) can only feasibly be estimated within a controlled setting.</p> <p><strong>move_avgspeed_value</strong>: Categorical value indicating whether average travel speed was reported as a mean or median within the original study.</p> <p><strong>move_bodymass_kg</strong>: Continuous value indicating the average adult body mass (units: kilograms) of the species. In cases where the study’s reference numbers <code>move_speed_ref</code> and <code>move_mass_ref</code> differ, we referred to secondary literature sources to assign the average adult body mass of the species. In cases where only body length was given, we used published allometric equations to estimate the wet body mass.</p> <p><strong>move_avgspeed_ms</strong>: Continuous value indicating the average (geometric mean) travel speed (units: metres per second) of the species reported within the study.</p> <p><strong>move_speed_source</strong>: Categorical value indicating the sampling level at which travel speed measurements were reported within the study.<br>- <code>indv</code>: travel speed reported from an individual animal. - <code>avgs</code>: travel speed reported as an average (mean or median) across multiple individuals from the same species.</p> <p><strong>move_individuals_n</strong>: Integer value indicating the number of individual animals from which travel speed measurements were obtained within the study.</p> <p><strong>move_measurements_n</strong>: Integer value indicating the number of travel speed measurements taken across individuals within the study. This value can exceed <code>move_individuals_n</code> when repeated measurements were made from the same individuals.</p> <p><strong>move_ygeo_min</strong>: Continuous value indicating the minimum reported latitude (decimal degrees) of the study location(s).</p> <p><strong>move_ygeo_max</strong>: Continuous value indicating the maximum reported latitude (decimal degrees) of the study location(s).</p> <p><strong>move_xgeo_min</strong>: Continuous value indicating the minimum reported longitude (decimal degrees) of the study location(s).</p> <p><strong>move_xgeo_max</strong>: Continuous value indicating the maximum reported longitude (decimal degrees) of the study location(s).</p> <p><strong>move_date_min</strong>: Earliest reported date of data collection within the study (format: YYYY-MM-DD).</p> <p><strong>move_date_max</strong>: Latest reported date of data collection within the study (format: YYYY-MM-DD).</p> <p><strong>move_study_country</strong>: Country in which the study was conducted.</p> <p><strong>move_study_location</strong>: A description of the study location.</p> </div> <div> <h2>Version Notes</h2> <p>This updated version of the travel speed dataset extends the aggregated dataset published in <br>Dyer et al. 2023, PLOS Biology<strong> </strong>through the inclusion of additional metadata fields.<br>Metadata follow the same aggregation to species level by grouping records across unique combinations of study and species while preserving variation across important categorical covariates (listed above).</p> <div> <h3>Key Updates</h3> <ul> <li><strong>Added spatial metadata</strong>: minimum and maximum latitude/longitude, study country, and study location.</li> <li><strong>Added temporal metadata</strong>: earliest and latest reported dates of data collection (YYYY-MM-DD).</li> <li><strong>Refined sampling information</strong>: number of individuals (<code>move_individuals_n</code>) and number of speed measurements (<code>move_measurements_n</code>) are now reported, where available.</li> </ul> </div> </div>
Data from: Overall dynamic body acceleration measures activity differently on large vs small aquatic animals
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Pro-efferocytic nanotherapies reduce vascular inflammation without inducing anemia in a large animal model of atherosclerosis
GEO Series GSE270259. Sus scrofa. 11 samples. Type: Expression profiling by high throughput sequencing.
Molecular Signatures of HFpEF: Systems Biology in a Cardiac-Centric Large Animal Model
GEO Series GSE181184. Felis catus. 36 samples. Type: Expression profiling by high throughput sequencing.
Cell and tissue adaptation in the pulmonary autograft in a large animal model of the Ross procedure
GEO Series GSE269818. Ovis aries. 22 samples. Type: Expression profiling by high throughput sequencing.
Circular RNAs are a large class of animal RNAs with regulatory potency (PAR-CLIP)
GEO Series GSE43573. Homo sapiens. 4 samples. Type: Other.
Circular RNAs are a large class of animal RNAs with regulatory potency
GEO Series GSE43574. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing; Other.
Circular RNAs are a large class of animal RNAs with regulatory potency (RNA-Seq)
GEO Series GSE43572. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Chondrodystrophic Dogs as a Pre-clinical Large Animal Model of Discogenic Back Pain
GEO Series GSE288418. Canis lupus familiaris. 24 samples. Type: Expression profiling by high throughput sequencing.
Mechanotransduction inhibition prevents scarring and yields regeneration in a large animal model
GEO Series GSE219158. Homo sapiens; Sus scrofa. 13 samples. Type: Expression profiling by high throughput sequencing.
β3 agonist administration before reperfusion reduces infarct size and improves long term cardiac function in small and large animal models of myocardial infarction
GEO Series GSE42999. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Pathophysiological features of disease in a large animal model of COPD
GEO Series GSE242416. Ovis aries. 54 samples. Type: Expression profiling by high throughput sequencing.
Large animal model of chronic thromboembolic pulmonary hypertension
<p>Echocardiographic, histological and mRNA expression data.</p>
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