Sentence examples for telemetry datasets from inspiring English sources

Designing conservation strategies that protect wide-ranging marine species is a significant challenge, but integrating regional telemetry datasets and synthesizing modeled movements and behavior offer promise for uncovering distinct at-sea areas that are important habitats for imperiled marine species.

New advances in the processing of satellite telemetry datasets, however, allow us to robustly consider observation error.

For instance, many of the sea turtle and telemetry datasets were fed into SEAMAP from the Satellite Tracking and Analysis Tool (STAT) available at SeaTurtle.org [5].

For satellite telemetry datasets, the number of animals per record was always one even though one individual tag may have multiple observations each with a different location, depending on how often data were recorded and published.

Hence, to further assess connectivity, we contrasted our previous population genetics findings with a large radio-telemetry dataset (n = 11 194 locations n = 379 elk collected from 2002 2009).

Potential high quality marine mammal, seabird, and sea turtle datasets, defined as dedicated surveys or satellite telemetry tag data with the minimum required variables, were identified by searching through literature (gray and peer-reviewed), websites, and after consultations with experts within the research network.

Thus, a relevant question of practicality is, "what assumptions or auxiliary data are necessary to reliably estimate population trends with age-at-harvest data?" Auxiliary datasets previously considered have included those generated by radio telemetry studies to inform survival probabilities [1], [2] and mark-recovery studies to inform survival and harvest rates [6].

Analysis of the datasets in question revealed that total daily activity was not significantly different in either the telemetry or the RW.

The EFD telemetry has two categories, the continuous (medium) and bust (high) modes, as part of PWE's continuous- and burst-mode datasets.

This can happen in a number of ways: through the use of predictive analytics set across multiple datasets in real-time; through the delivery of stratified medical pathways, drawing on patient, environmental, social and genetic data to anticipate treatment pathways; through the correlation, analysis and interpretation of telehealth, telemetry and genomic data to treat disease pre-emptively.

"We just lost telemetry," she told him.