scholarly journals The Trumpeter Swan

Blue Jay ◽  
1953 ◽  
Vol 11 (4) ◽  
Author(s):  
Fred .G. Bard
Keyword(s):  
Trumpeter Swan

Environmental and Human Influences on Trumpeter Swan Habitat Occupancy in Alaska

The Condor ◽  
2009 ◽  
Vol 111 (2) ◽  
pp. 266-275 ◽  
Author(s):  
Joshua H. Schmidt ◽  
Mark S. Lindberg ◽  
Devin S. Johnson ◽  
Joel A. Schmutz
Keyword(s):  
Habitat Occupancy ◽  
Trumpeter Swan

Active Trumpeter Swan Nest on an Active Muskrat Lodge

2021 ◽  
Vol 81 (3) ◽  
Author(s):  
Paige C. Miller ◽  
David J. Delehanty
Keyword(s):  
Trumpeter Swan

Trumpeter Swan Abundance and Growth Rates in Yellowstone National Park

2009 ◽  
Vol 73 (5) ◽  
pp. 728-736 ◽  
Author(s):  
Kelly M. Proffitt ◽  
Terrence P. Mceneaney ◽  
P. J. White ◽  
Robert A. Garrott
Keyword(s):  
Growth Rates ◽  
Yellowstone National Park ◽  
National Park ◽  
Trumpeter Swan

scholarly journals Saving the Trumpeter Swan

Oryx ◽  
1951 ◽  
Vol 1 (4) ◽  
pp. 195-197
Author(s):  
Freda Davies
Keyword(s):  
Twentieth Century ◽  
North American ◽  
Cygnus Buccinator ◽  
Trumpeter Swan

Around the turn of the twentieth century, North American conservationists embarked on an intensive campaign to prevent the Trumpeter Swan (Cygnus buccinator) from following the Passenger Pigeon into extinction.

scholarly journals Zinc Toxicosis in a Free-flying Trumpeter Swan (Cygnus buccinator)

2004 ◽  
Vol 40 (4) ◽  
pp. 769-774 ◽  
Author(s):  
James W. Carpenter ◽  
Gordon A. Andrews ◽  
W. Nelson Beyer
Keyword(s):  
Cygnus Buccinator ◽  
Trumpeter Swan

scholarly journals Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

2021 ◽  
Author(s):  
David Wolfson ◽  
John Fieberg ◽  
David E Andersen
Keyword(s):  
Data Streams ◽  
Black Bear ◽  
Information Criterion ◽  
Physiological Status ◽  
Wide Audience ◽  
Piecewise Regression ◽  
Sandhill Crane ◽  
Biological Phenomena ◽  
Technological Advances ◽  
Trumpeter Swan

Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal's location, movement characteristics, external environmental conditions, and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide five example applications highlighting a variety of taxonomic species, data streams, timescales, and biological phenomena. These examples include a short-term behavioral response (flee and return) by a trumpeter swan (Cygnus buccinator) immediately following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose (Alces alces); a physiological response (spike in heart-rate) in a black bear (Ursus americanus) to a stressful stimulus (presence of a drone); a mortality event of a trumpeter swan signaled by changes in collar temperature and Overall Dynamic Body Acceleration; and an unsupervised method for identifying the onset, return, duration, and staging use of sandhill crane (Antigone canadensis) migration. We implement analyses using the mcp package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criterion and cross-validation measures. This approach uses simple modeling approaches that are accessible to a wide audience and is a straightforward means of assessing a variety of biologically relevant changes in animal behavior.

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