Extracting more out of relocation data: building movement models as mixtures of random walks

We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.

The Effect of Broadleaf Canopies on Survey-grade Horizontal GPS/GLONASS Measurements

A study was conducted to empirically determine the degradation of survey-grade GPS horizontal position measurements due to the effects of broadleaf forest canopies. The measurements were taken using GPS/GLONASS-capable receivers measuring C/A and P-codes, and carrier phase. Fourteen survey markers were chosen in central Connecticut to serve as reference markers for the study. These markers had varying degrees of sky obstruction due to overhanging tree canopies. Sky obstruction was measured by photographing the sky with a 35mm reflex camera fitted with a hemispherical lens. The negative was scanned and the image mapped using an equal- area projection to remove the distortion caused by the lens. The resulting digital image was thresholded to produce a black-and-white image in which a count of the black pixels is a measure of sky-area obstruction. The locations of the markers were determined independently before the study. During the study, each marker was occupied for four 20-minute sessions over the period of one week in mid-July, 1999. The location of the study markers produced relatively long baselines, as compared with similar studies. We compared the accuracy of GPS-only vs. GPS&GLONASS as a function of sky obstruction. Based on our results, GLONASS observations did not improve or degrade the accuracy of the position measurements. There is a loss of 2mm of accuracy per percent of sky obstruction for both GPS only and GPS&GLONASS.

Position Errors Caused by GPS Height of Instrument Blunders

Height of instrument (HI) blunders in GPS measurements cause position errors. These errors can be pure vertical, pure horizontal, or a mixture of both. There are different error regimes depending on whether both the base and the rover both have HI blunders, if just the base has an HI blunder, or just the rover has an HI blunder. The resulting errors are on the order of 30 cm for receiver separations of 1000 km for an HI blunder of 2 m. Given the complicated nature of the errors, we believe it would be difficult, if not impossible, to detect such errors by visual inspection. This serves to underline the necessity to enter GPS HI's correctly.

Position Errors Caused by GPS HI Blunders

Height of instrument (HI) blunders in GPS measurements cause position errors. These errors can be pure vertical, pure horizontal, or a mixture of both. There are different error regimes depending on whether both the base and the rover both have HI blunders, if just the base has an HI blunder, or just the rover has an HI blunder. The resulting errors are on the order of 30 cm for receiver separations of 1000 km for an HI blunder of 2 m. Given the complicated nature of the errors, we believe it would be difficult, if not impossible, to detect such errors by visual inspection. This serves to underline the necessity to enter GPS HIs correctly.