Miniaturised bidirectional acoustic tag to enhance marine animal tracking studies

2021 ◽  
Author(s):  
Ivan Masmitja ◽  
Daniel Corregidor ◽  
Juan Manuel Lopez ◽  
Enoc Martinez ◽  
Joan Navarro ◽  
...  
Keyword(s):  
Marine Animal ◽  
Animal Tracking

scholarly journals Translating Marine Animal Tracking Data into Conservation Policy and Management

2019 ◽  
Vol 34 (5) ◽  
pp. 459-473 ◽  
Author(s):  
Graeme C. Hays ◽  
Helen Bailey ◽  
Steven J. Bograd ◽  
W. Don Bowen ◽  
Claudio Campagna ◽  
...  
Keyword(s):  
Conservation Policy ◽  
Marine Animal ◽  
Tracking Data ◽  
Animal Tracking

scholarly journals Ecological insights from three decades of animal movement tracking across a changing Arctic

Science ◽  
2020 ◽  
Vol 370 (6517) ◽  
pp. 712-715
Author(s):  
Sarah C. Davidson ◽  
Gil Bohrer ◽  
Eliezer Gurarie ◽  
Scott LaPoint ◽  
Peter J. Mahoney ◽  
...  
Keyword(s):  
Animal Movement ◽  
The Arctic ◽  
Reproductive Phenology ◽  
Marine Animal ◽  
Animal Tracking ◽  
Public Data ◽  
Migration Phenology ◽  
Species Specific ◽  
Increasing Temperature ◽  
Collaborative Data Analysis

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Marine animal tracking with classical and emerging localization algorithms

2020 ◽  
Vol 5 (48) ◽  
pp. eabf0892
Author(s):  
Dana R. Yoerger
Keyword(s):  
Marine Animal ◽  
Marine Animals ◽  
Animal Tracking ◽  
Localization Algorithms ◽  
Acoustic Tags

Localization algorithms applied to acoustic tags for tracking marine animals can also be used to localize marine robots.

scholarly journals BonZeb: open-source, modular software tools for high-resolution zebrafish tracking and analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicholas C. Guilbeault ◽  
Jordan Guerguiev ◽  
Michael Martin ◽  
Isabelle Tate ◽  
Tod R. Thiele
Keyword(s):  
High Resolution ◽  
Open Loop ◽  
Ease Of Use ◽  
Neural Mechanisms ◽  
Animal Tracking ◽  
Larval Zebrafish ◽  
Optogenetic Stimulation ◽  
Modular Software ◽  
Behavioral Tracking ◽  
Experimental Protocols

AbstractWe present BonZeb—a suite of modular Bonsai packages which allow high-resolution zebrafish tracking with dynamic visual feedback. Bonsai is an increasingly popular software platform that is accelerating the standardization of experimental protocols within the neurosciences due to its speed, flexibility, and minimal programming overhead. BonZeb can be implemented into novel and existing Bonsai workflows for online behavioral tracking and offline tracking with batch processing. We demonstrate that BonZeb can run a variety of experimental configurations used for gaining insights into the neural mechanisms of zebrafish behavior. BonZeb supports head-fixed closed-loop and free-swimming virtual open-loop assays as well as multi-animal tracking, optogenetic stimulation, and calcium imaging during behavior. The combined performance, ease of use and versatility of BonZeb opens new experimental avenues for researchers seeking high-resolution behavioral tracking of larval zebrafish.

scholarly journals Analysis of local habitat selection and large-scale attraction/avoidance based on animal tracking data: is there a single best method?

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Moritz Mercker ◽  
Philipp Schwemmer ◽  
Verena Peschko ◽  
Leonie Enners ◽  
Stefan Garthe
Keyword(s):  
Habitat Selection ◽  
Large Scale ◽  
Error Rates ◽  
Process Models ◽  
Statistical Hypothesis ◽  
Type I ◽  
Tracking Data ◽  
Selection Models ◽  
Animal Tracking ◽  
Step Selection

Abstract Background New wildlife telemetry and tracking technologies have become available in the last decade, leading to a large increase in the volume and resolution of animal tracking data. These technical developments have been accompanied by various statistical tools aimed at analysing the data obtained by these methods. Methods We used simulated habitat and tracking data to compare some of the different statistical methods frequently used to infer local resource selection and large-scale attraction/avoidance from tracking data. Notably, we compared spatial logistic regression models (SLRMs), spatio-temporal point process models (ST-PPMs), step selection models (SSMs), and integrated step selection models (iSSMs) and their interplay with habitat and animal movement properties in terms of statistical hypothesis testing. Results We demonstrated that only iSSMs and ST-PPMs showed nominal type I error rates in all studied cases, whereas SSMs may slightly and SLRMs may frequently and strongly exceed these levels. iSSMs appeared to have on average a more robust and higher statistical power than ST-PPMs. Conclusions Based on our results, we recommend the use of iSSMs to infer habitat selection or large-scale attraction/avoidance from animal tracking data. Further advantages over other approaches include short computation times, predictive capacity, and the possibility of deriving mechanistic movement models.

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