Frair JL, Fieberg J, Hebblewhite M, Cagnacci F, DeCesare NJ, Pedrotti L. Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philos Trans R Soc B Biol Sci. 2010;365(1550):2187–200. Perhaps the unsprung weight, thanks to the 20in Rays forged aluminium wheels, is reduced over that of the standard GT-R. It’s got that sort of light-on-its-feet feel, which is pretty impressive given that it’s a 1740kg car. geom_path(data = cdat, aes(x = location.long, y = location.lat, color = year, group = tag.local.identifier)) + Ropert-Coudert Y, Kato A, Baudat J, Bost C-A, Le Maho Y, Naito Y. Time/depth usage of Adélie penguins: an approach based on dive angles. Polar Biol. 2001;24(6):467–70. where \({\text{sign}}\left( {{\text{NGb}}_{z} } \right)\) is allocated the value + 1 when \({\text{NGb}}_{z}\) is non-negative and − 1, when \({\text{NGb}}_{z}\) is negative (recovers directionality of \({\text{NGb}}_{z}\), subsequent to the square-root). Taken together then, in R, pitch and roll are computed according to, (R 24:25) with outputs within the range of − 90° to + 90° for pitch and − 180° to + 180° for roll, and this is the formula we use in the tilt-compensated method outlined below (and within Additional file 2).

Ropert-Coudert Y, Wilson RP. Trends and perspectives in animal-attached remote sensing. Front Ecol Environ. 2005;3(8):437–44.where \({\text{Lat}}_{0}\), \({\text{ Lat}}_{i}\) and \({\text{Lon}}_{0}\), \({\text{ Lon}}_{i}\) are the previous and present latitude and longitude coordinates, respectively (in radians), \(h\) is the (present) heading (in radians) and \(q\) is the (present) distance coefficient. Diebel J. Representing attitude: Euler angles, unit quaternions, and rotation vectors. Technical Report , vol. 58. Stanford: Stanford University; 2006. p. 1–35. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales, Grupo GEA, IPATEC-UNCO-CONICET, San Carlos de Bariloche, Río Negro, Argentina

or ‘external’ current flow vectors). The heading and speed of tidal-/air-currents. Current integration Willener AST, Handrich Y, Halsey LG, Strike S. Effect of walking speed on the gait of king penguins: an accelerometric approach. J Theor Biol. 2015;387:166–73. where \(m\) is the multiplicative coefficient and \(c\) is a constant [ 10, 69]. Here, a user can define various bouts of movement from motion sensor data (e.g., via various machine-learning approaches (for review see Farrahi et al. [ 170]) or the Boolean-based LoCoD method [ 101]) and/or substrate condition (e.g., via GPS), to be cross-referenced when allocating variants of the speed coefficients. As a simple example, in R, should walking (coded for as 1) and running (coded for as 2) be teased apart from all other (non-moving) data (coded for as 0) within a Marked Events vector (ME), then ME can be used to allocate various \(m\) (and if applicable, \(c\)) values using simple ‘ifelse’ statements (R 39:40). Gheorghe MV, Bodea MC. Calibration optimization study for tilt-compensated compasses. IEEE Trans Instrum Meas. 2018;67(6):1486–94. can be displayed here. This fact is indicated by the white downward-pointing arrows in the title panel. Weonly a certain amount of vertical space available for the plotting, and not the whole depth of the pile-up Nissan GT-R gains new grille and special-edition Nismo variant 2023 Nissan GT-R gains new grille and special-edition Nismo variant rFactor 2 is also an evolving product, which will be updated and added to for many years, so the list of features will expand! Features

Hochscheid S. Why we mind sea turtles’ underwater business: a review on the study of diving behavior. J Exp Mar Biol Ecol. 2014;450:118–36.Halsey LG, Shepard ELC, Hulston CJ, Venables MC, White CR, Jeukendrup AE, Wilson RP. Acceleration versus heart rate for estimating energy expenditure and speed during locomotion in animals: tests with an easy model species, Homo sapiens. Zoology. 2008;111(3):231–41. Marcus Rowcliffe J, Carbone C, Kays R, Kranstauber B, Jansen PA. Bias in estimating animal travel distance: the effect of sampling frequency. Methods Ecol Evol. 2012;3(4):653–62. Multiple mathematically sophisticated algorithms have been developed to correct distortions from each magnetometer channel’s output [e.g., 23, 149, 150, 151, 152]. We provide an annotated R script— Gundog.Compass (Additional file 2) that corrects both soft and hard iron distortions from tri-axial magnetometry data and subsequently computes tilt-compensated heading (0° to 360°). Within this function, there are two main methods of correction to choose from, based on the mathematical protocols outlined by Vitali [ 153]—least-square error approximation (constructing an ellipsoid rotation matrix) and Winer [ 154]—scale biases with simple orthogonal rescaling (avoiding matrices altogether). We expand on this user-defined functionality, as well as outlining the causes of soft and hard iron distortions and the initial calibration procedure required to correct such distortions within Additional file 1: Text S3. Tilt-compensated heading derivation The tilt-compensated compass method is a well-known practice for deriving heading [e.g., 21, 22, 81]. Correct coordinate system axis alignment and suitable calibration of tri-axial magnetometry data [cf. 149] are crucial pre-processors, without which, heading estimates would likely incorporate substantial error [cf. 21, 149]. The tilt-compensated compass method described below (following the framework outlined by Pedley [ 21]), requires the aerospace ( x-North, y-East, z-Down) (right-handed) coordinate system, or ‘NED’ (cf. Additional file 1: Text S2, Fig. S1). We provide examples of axis alignment, outline the importance of transforming between coordinate frames (relative to the Earths fixed frame) and recommend a universal configuration calibration procedure to aid correct axis alignment within Additional file 1: Text S2.

Wiltschko R. Magnetic orientation in animals, vol. 33. Berlin: Springer Science & Business Media; 2012.In R, the formulae to calculate the great-circle distance and great circular bearing are saved within the disty (R 61) and beary (R 62) functions, respectively, where lon1, lat1, long2 and lat2 represent longitude and latitude positions (decimal format) at \(t_{i}\) and \(t_{i + 1}\), ( \(t\) representing time). Essentially they constitute run-length encoded numeric vectors or matrices associated to a particular genomic coordinate range. There can be multiple samples in a single data set, and the plotting method provides tools to incorporate sample group information. Tonini MH, Palma ED. Tidal dynamics on the North Patagonian Argentinean Gulfs. Estuar Coast Shelf Sci. 2017;189:115–30. Department of Agriculture, Land Reform and Rural Development, Government of South Africa, Pretoria, 001, South Africa Another way to visualize movement data is to show where the caribou are at different times of the year. Here we will use day of year (DOY) in different colors to show where the caribou are through the seasons. So DOY 1 is January 1st and DOY 365 is December 31st. DOY 182 will be the peak of summer which will also be the midpoint of the color ramp. In this map DOY 182 is green so summer will be the greener colors and purple/red will be winter. ggmap(sq_map) +