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

Abstract Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. Highly mobile waterfowl, which can exploit res...

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Main Authors: Fiona McDuie, Michael L. Casazza, Cory T. Overton, Mark P. Herzog, C. Alexander Hartman, Sarah H. Peterson, Cliff L. Feldheim, Joshua T. Ackerman
Format: Article
Language:English
Published: BMC 2019-02-01
Series:Movement Ecology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40462-019-0146-8
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author Fiona McDuie
Michael L. Casazza
Cory T. Overton
Mark P. Herzog
C. Alexander Hartman
Sarah H. Peterson
Cliff L. Feldheim
Joshua T. Ackerman
author_facet Fiona McDuie
Michael L. Casazza
Cory T. Overton
Mark P. Herzog
C. Alexander Hartman
Sarah H. Peterson
Cliff L. Feldheim
Joshua T. Ackerman
author_sort Fiona McDuie
collection DOAJ
description Abstract Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. Highly mobile waterfowl, which can exploit resources over large spatial extents, are excellent models to understand relationships between movements and resource usage, landscape interactions and specific habitat needs. Methods We tracked 3 species of dabbling ducks with GPS-GSM transmitters in 2015–17 to examine fine-scale movement patterns over 24 h periods (30 min interval), dividing movement pathways into temporally continuous segments and spatially contiguous patches. We quantified distances moved, area used and time allocated across the day, using linear and generalized linear mixed models. We investigated behavior through relationships between these variables. Results Movements and space-use were small, and varied by species, sex and season. Gadwall (Mareca strepera) generally moved least (FFDs: 0.5–0.7 km), but their larger foraging patches resulted from longer within-area movements. Pintails (Anas acuta) moved most, were more likely to conduct flights > 300 m, had FFDs of 0.8–1.1 km, used more segments and patches per day that they revisited more frequently, resulting in the longest daily total movements. Females and males differed only during the post-hunt season when females moved more. 23.6% of track segments were short duration (1–2 locations), approximately 1/3 more than would be expected if they occurred randomly, and were more dispersed in the landscape than longer segments. Distance moved in 30 min shortened as segment duration increased, likely reflecting phases of non-movement captured within segments. Conclusions Pacific Flyway ducks spend the majority of time using smaller foraging and resting areas than expected or previously reported, implying that foraging areas may be highly localized, and nutrients obtainable from smaller areas. Additionally, movement reductions over time demonstrates behavioral adjustments that represent divergent energetic demands, the detection of which is a key advantage of higher frequency data. Ducks likely use less energy for movement than currently predicted and management, including distribution and configuration of essential habitat, may require reconsideration. Our study illustrates how fine-scale movement data from tracking help understand and inform various other fields of research.
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spelling doaj.art-21811535fea64fa9b18b54c82ff96b482022-12-21T23:55:10ZengBMCMovement Ecology2051-39332019-02-017111710.1186/s40462-019-0146-8GPS tracking data reveals daily spatio-temporal movement patterns of waterfowlFiona McDuie0Michael L. Casazza1Cory T. Overton2Mark P. Herzog3C. Alexander Hartman4Sarah H. Peterson5Cliff L. Feldheim6Joshua T. Ackerman7San Jose State University Research Foundation, Moss Landing Marine LaboratoriesU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationCalifornia Department of Water Resources, Suisun Marsh ProgramU.S. Geological Survey, Western Ecological Research Center, Dixon Field StationAbstract Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. Highly mobile waterfowl, which can exploit resources over large spatial extents, are excellent models to understand relationships between movements and resource usage, landscape interactions and specific habitat needs. Methods We tracked 3 species of dabbling ducks with GPS-GSM transmitters in 2015–17 to examine fine-scale movement patterns over 24 h periods (30 min interval), dividing movement pathways into temporally continuous segments and spatially contiguous patches. We quantified distances moved, area used and time allocated across the day, using linear and generalized linear mixed models. We investigated behavior through relationships between these variables. Results Movements and space-use were small, and varied by species, sex and season. Gadwall (Mareca strepera) generally moved least (FFDs: 0.5–0.7 km), but their larger foraging patches resulted from longer within-area movements. Pintails (Anas acuta) moved most, were more likely to conduct flights > 300 m, had FFDs of 0.8–1.1 km, used more segments and patches per day that they revisited more frequently, resulting in the longest daily total movements. Females and males differed only during the post-hunt season when females moved more. 23.6% of track segments were short duration (1–2 locations), approximately 1/3 more than would be expected if they occurred randomly, and were more dispersed in the landscape than longer segments. Distance moved in 30 min shortened as segment duration increased, likely reflecting phases of non-movement captured within segments. Conclusions Pacific Flyway ducks spend the majority of time using smaller foraging and resting areas than expected or previously reported, implying that foraging areas may be highly localized, and nutrients obtainable from smaller areas. Additionally, movement reductions over time demonstrates behavioral adjustments that represent divergent energetic demands, the detection of which is a key advantage of higher frequency data. Ducks likely use less energy for movement than currently predicted and management, including distribution and configuration of essential habitat, may require reconsideration. Our study illustrates how fine-scale movement data from tracking help understand and inform various other fields of research.http://link.springer.com/article/10.1186/s40462-019-0146-8Activity budgetsAnimal movementContagion indexEnergeticsFine-scale movementHigh frequency GPS
spellingShingle Fiona McDuie
Michael L. Casazza
Cory T. Overton
Mark P. Herzog
C. Alexander Hartman
Sarah H. Peterson
Cliff L. Feldheim
Joshua T. Ackerman
GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
Movement Ecology
Activity budgets
Animal movement
Contagion index
Energetics
Fine-scale movement
High frequency GPS
title GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
title_full GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
title_fullStr GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
title_full_unstemmed GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
title_short GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl
title_sort gps tracking data reveals daily spatio temporal movement patterns of waterfowl
topic Activity budgets
Animal movement
Contagion index
Energetics
Fine-scale movement
High frequency GPS
url http://link.springer.com/article/10.1186/s40462-019-0146-8
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