Multistate Ornstein–Uhlenbeck approach for practical estimation of movement and resource selection around central places
Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patt...
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Published in: | Methods in ecology and evolution Vol. 12; no. 3; pp. 507 - 519 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
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London
John Wiley & Sons, Inc
01-03-2021
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Abstract | Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patterns, such as the impacts of air and water flow on movement.
Here, we develop a practical, multi‐stage approach for statistical inference into the behavioural mechanisms underlying how habitat and dynamic energy landscapes—in this case how airflow increases or decreases the energetic efficiency of flight—shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry.
The application to golden eagles revealed the effects of habitat variables that align with predicted behavioural ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely.
This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein–Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions. |
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AbstractList | Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patterns, such as the impacts of air and water flow on movement.
Here, we develop a practical, multi‐stage approach for statistical inference into the behavioural mechanisms underlying how habitat and dynamic energy landscapes—in this case how airflow increases or decreases the energetic efficiency of flight—shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry.
The application to golden eagles revealed the effects of habitat variables that align with predicted behavioural ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely.
This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein–Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions. Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patterns, such as the impacts of air and water flow on movement. Here, we develop a practical, multi‐stage approach for statistical inference into the behavioural mechanisms underlying how habitat and dynamic energy landscapes—in this case how airflow increases or decreases the energetic efficiency of flight—shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry. The application to golden eagles revealed the effects of habitat variables that align with predicted behavioural ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely. This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein–Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions. Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patterns, such as the impacts of air and water flow on movement.Here, we develop a practical, multi‐stage approach for statistical inference into the behavioural mechanisms underlying how habitat and dynamic energy landscapes—in this case how airflow increases or decreases the energetic efficiency of flight—shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry.The application to golden eagles revealed the effects of habitat variables that align with predicted behavioural ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely.This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein–Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions. |
Author | Booms, Travis L. Breed, Greg A. Barger, Christopher P. Eisaguirre, Joseph M. Goddard, Scott D. Sutherland, Chris |
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Cites_doi | 10.1890/06-1985.1 10.1201/9781315117744 10.1086/671257 10.1016/S0304-3800(97)00153-1 10.1002/env.2402 10.1371/journal.pone.0034033 10.1007/s10651-007-0036-x 10.2307/2346830 10.1111/j.1365-2664.2012.02185.x 10.2307/1374834 10.1111/rssc.12007 10.1098/rsif.2014.0333 10.1002/ece3.4823 10.3389/fevo.2019.00317 10.1890/04-0953 10.1111/biom.13052 10.3356/rapt-50-01-70-75.1 10.1007/s10980-005-0093-2 10.1080/00031305.2019.1665584 10.1098/rspb.2018.1779 10.1007/s00285-007-0149-8 10.3356/0892-1016-53.4.393 10.2307/2529305 10.1111/2041-210X.12578 10.1111/1365-2664.12768 10.2173/tbna.684.p 10.1073/pnas.0800375105 10.1002/ecy.1615 10.2307/1370452 10.1002/wics.1506 10.1111/j.1541-0420.2007.00943.x 10.1002/ece3.1306 10.1111/1365-2656.12087 10.1111/2041-210X.12528 10.1111/1365-2656.13267 10.1111/j.1474-919X.2011.01181.x 10.1890/0012-9658(2002)083[2240:SUAMIH]2.0.CO;2 10.1890/0012-9658(2006)87[3021:WDAEOR]2.0.CO;2 10.1201/9780429243653 10.1890/15-0472.1 10.1016/j.rse.2015.02.028 10.1515/9781400849734 10.1371/journal.pone.0035548 10.1002/ece3.4189 10.1016/j.stamet.2012.12.001 10.1098/rsif.2015.0530 10.1098/rspb.2014.0231 10.2307/1936988 10.1111/2041-210X.12150 10.1890/08-0874.1 |
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Snippet | Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been... |
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SubjectTerms | Air flow Animal behavior Bayesian biased random walk Breeding seasons continuous time model Ecological effects empirical Bayes Environmental effects Foraging habitats golden eagle Habitats Home range Interspecific relationships Markov process movement model Programming languages recursive Bayes Satellite tracking Satellites Statistical inference Telemetry Water flow |
Title | Multistate Ornstein–Uhlenbeck approach for practical estimation of movement and resource selection around central places |
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