Movement patterns of threeAthalia sawflies in relation to the spatio-temporal distributions of their habitats

1992 ◽  
Vol 34 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Koukichi Nagasaka
Keyword(s):  
Movement Patterns ◽  
Spatio Temporal

scholarly journals Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

2014 ◽  
Vol 11 (99) ◽  
pp. 20140542 ◽  
Author(s):  
Nathan F. Putman ◽  
Erica S. Jenkins ◽  
Catherine G. J. Michielsens ◽  
David L. G. Noakes
Keyword(s):  
Magnetic Field ◽  
Temporal Variation ◽  
Ocean Circulation ◽  
Sockeye Salmon ◽  
Movement Patterns ◽  
Oncorhynchus Gorbuscha ◽  
Migration Routes ◽  
Long Distance ◽  
Spatio Temporal ◽  
Olfactory Imprinting

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye ( Oncorhynchus nerka ) and pink ( Oncorhynchus gorbuscha ) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species.

Movement Patterns in Spatio‐temporal Data

2008 ◽  
pp. 726-732 ◽  
Author(s):  
Joachim Gudmundsson ◽  
Patrick Laube ◽  
Thomas Wolle
Keyword(s):  
Movement Patterns ◽  
Temporal Data ◽  
Spatio Temporal

Movement Patterns in Spatio-Temporal Data

2017 ◽  
pp. 1362-1370
Author(s):  
Joachim Gudmundsson ◽  
Patrick Laube ◽  
Thomas Wolle
Keyword(s):  
Movement Patterns ◽  
Temporal Data ◽  
Spatio Temporal

scholarly journals Animal daily mobility patterns analysis using resting event networks

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Maxime Lenormand ◽  
Hervé Pella ◽  
Hervé Capra
Keyword(s):  
Temporal Resolution ◽  
Fish Species ◽  
General Problem ◽  
Animal Movement ◽  
Movement Patterns ◽  
Conservation Strategies ◽  
Mobility Patterns ◽  
Daily Mobility ◽  
Recent Advances ◽  
Spatio Temporal

AbstractCharacterizing the movement patterns of animals is crucial to improve our understanding of their behavior and thus develop adequate conservation strategies. Such investigations, which could not have been implemented in practice only a few years ago, have been facilitated through the recent advances in tracking methods that enable researchers to study animal movement at an unprecedented spatio-temporal resolution. However, the identification and extraction of patterns from spatio-temporal trajectories is still a general problem that has relevance for many applications. Here, we rely on the concept of resting event networks to identify the presence of daily mobility patterns in animal spatio-temporal trajectories. We illustrate our approach by analyzing spatio-temporal trajectories of several fish species in a large hydropeaking river.

Movement patterns of whale sharks in Cenderawasih Bay, Indonesia, revealed through long-term satellite tagging

2020 ◽  
Vol 26 (4) ◽  
pp. 353
Author(s):  
Megan M. Meyers ◽  
Malcolm P. Francis ◽  
Mark Erdmann ◽  
Rochelle Constantine ◽  
Abraham Sianipar
Keyword(s):  
State Space Model ◽  
Movement Patterns ◽  
Horizontal Movement ◽  
Whale Sharks ◽  
Spatio Temporal ◽  
Abiotic And Biotic Factors ◽  
Satellite Tagging ◽  
Warm Temperate ◽  
Switching State

Whale sharks, Rhincodon typus, are found circumglobally in tropical and warm temperate seas, exhibiting a range of residency and movement patterns. To determine spatio-temporal habitat use by juvenile male whale sharks in Cenderawasih Bay, Indonesia, we collected data from June 2015 to November 2016 using 16 fin-mounted satellite tags that provided exceptionally long track durations. Fifteen tags transmitted for 48–534 days (mean=321±33, s.e.), with 13 tags transmitting for ≥220 days. Four sharks remained within the bay for the duration of the study, while of the 11 sharks that travelled outside the bay, eight left between March and May 2016. They ranged throughout coastal and offshore waters, travelling up to 5144km away from Cenderawasih Bay, with a mean horizontal speed of only 3.3km day−1±0.70, s.e. A switching state space model was fitted to satellite fix data to identify behavioural states. It revealed that sharks spent an average of 81% of their time in foraging-related behaviours, mostly in shallow waters (median depth=35m), with travelling observed mainly over deeper waters (median depth=1284m). The movement patterns reveal variable periods of residency, with individual patterns of horizontal movement most likely in response to different abiotic and biotic factors, including food availability, which may trigger seasonal dispersal.

scholarly journals GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Fiona McDuie ◽  
Michael L. Casazza ◽  
Cory T. Overton ◽  
Mark P. Herzog ◽  
C. Alexander Hartman ◽  
...  
Keyword(s):  
Movement Patterns ◽  
Gps Tracking ◽  
Tracking Data ◽  
Spatio Temporal

Expertise and the Spatio-Temporal Characteristics of Anticipatory Information Pick-up from Complex Movement Patterns

Perception ◽  
10.1068/p6438 ◽  
2010 ◽  
Vol 39 (6) ◽  
pp. 745-760 ◽  
Author(s):  
Sean Müller ◽  
Bruce Abernethy ◽  
Michael Eid ◽  
Rohan McBean ◽  
Matthew Rose
Keyword(s):  
Movement Patterns ◽  
Temporal Characteristics ◽  
Spatio Temporal ◽  
Complex Movement
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