Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data

Statistical habitat modelling is often flagged as a cost-effective decision tool for species management. However, data that can produce predictions with the desired precision are difficult to collect, especially for species with spatially extensive and dynamic distributions. Data from platforms of o...

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Published in:Marine Ecology Progress Series
Main Authors: Isojunno, Saana, Matthiopoulos, Jason, Evans, Peter G H
Format: Article in Journal/Newspaper
Language:English
Published: 2012
Subjects:
Gam
Online Access:https://risweb.st-andrews.ac.uk/portal/en/researchoutput/harbour-porpoise-habitat-preferences(bb617f9e-789c-41ab-9f1f-1734281e8782).html
https://doi.org/10.3354/meps09415
https://research-repository.st-andrews.ac.uk/bitstream/10023/16207/1/MarEcolProgSer448p155.pdf
id ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/bb617f9e-789c-41ab-9f1f-1734281e8782
record_format openpolar
spelling ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/bb617f9e-789c-41ab-9f1f-1734281e8782 2023-05-15T16:33:21+02:00 Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data Isojunno, Saana Matthiopoulos, Jason Evans, Peter G H 2012-02-23 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/harbour-porpoise-habitat-preferences(bb617f9e-789c-41ab-9f1f-1734281e8782).html https://doi.org/10.3354/meps09415 https://research-repository.st-andrews.ac.uk/bitstream/10023/16207/1/MarEcolProgSer448p155.pdf eng eng info:eu-repo/semantics/openAccess Isojunno , S , Matthiopoulos , J & Evans , P G H 2012 , ' Harbour porpoise habitat preferences : robust spatio-temporal inferences from opportunistic data ' , Marine Ecology Progress Series , vol. 448 , pp. 155-170 . https://doi.org/10.3354/meps09415 Generalized additive models Habitat model Wales Model selection Tidal environments Phocoena phocoena Non-linear interactions Multi-model inference article 2012 ftunstandrewcris https://doi.org/10.3354/meps09415 2021-12-26T14:31:19Z Statistical habitat modelling is often flagged as a cost-effective decision tool for species management. However, data that can produce predictions with the desired precision are difficult to collect, especially for species with spatially extensive and dynamic distributions. Data from platforms of opportunity could be used to complement or help design dedicated surveys, but robust inference from such data is challenging. Furthermore, regression models using static covariates may not be sufficient for animals whose habitat preferences change dynamically with season, environmental conditions or foraging strategy. More flexible models introduce difficulties in selecting parsimonious models. We implemented a robust model-averaging framework to dynamically predict harbour porpoise Phocoena phocoena occurrence in a strongly tidal and topographically complex site in southwest Wales using data from a temporally intensive platform of opportunity. Spatial and temporal environmental variables were allowed to interact in a generalized additive model (GAM). We used information criteria to examine an extensive set of 3003 models and average predictions from the best 33. In the best model, 3 main effects and 2 tensorproduct interactions explained 46% of the deviance. Model-averaged predictions indicated that harbour porpoises avoided or selected steeper slopes depending on the tidal flow conditions; when the tide started to ebb, occurrence was predicted to increase 3-fold at steeper slopes. Article in Journal/Newspaper Harbour porpoise Phocoena phocoena University of St Andrews: Research Portal Gam ENVELOPE(-57.955,-57.955,-61.923,-61.923) Marine Ecology Progress Series 448 155 170
institution Open Polar
collection University of St Andrews: Research Portal
op_collection_id ftunstandrewcris
language English
topic Generalized additive models
Habitat model
Wales
Model selection
Tidal environments
Phocoena phocoena
Non-linear interactions
Multi-model inference
spellingShingle Generalized additive models
Habitat model
Wales
Model selection
Tidal environments
Phocoena phocoena
Non-linear interactions
Multi-model inference
Isojunno, Saana
Matthiopoulos, Jason
Evans, Peter G H
Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
topic_facet Generalized additive models
Habitat model
Wales
Model selection
Tidal environments
Phocoena phocoena
Non-linear interactions
Multi-model inference
description Statistical habitat modelling is often flagged as a cost-effective decision tool for species management. However, data that can produce predictions with the desired precision are difficult to collect, especially for species with spatially extensive and dynamic distributions. Data from platforms of opportunity could be used to complement or help design dedicated surveys, but robust inference from such data is challenging. Furthermore, regression models using static covariates may not be sufficient for animals whose habitat preferences change dynamically with season, environmental conditions or foraging strategy. More flexible models introduce difficulties in selecting parsimonious models. We implemented a robust model-averaging framework to dynamically predict harbour porpoise Phocoena phocoena occurrence in a strongly tidal and topographically complex site in southwest Wales using data from a temporally intensive platform of opportunity. Spatial and temporal environmental variables were allowed to interact in a generalized additive model (GAM). We used information criteria to examine an extensive set of 3003 models and average predictions from the best 33. In the best model, 3 main effects and 2 tensorproduct interactions explained 46% of the deviance. Model-averaged predictions indicated that harbour porpoises avoided or selected steeper slopes depending on the tidal flow conditions; when the tide started to ebb, occurrence was predicted to increase 3-fold at steeper slopes.
format Article in Journal/Newspaper
author Isojunno, Saana
Matthiopoulos, Jason
Evans, Peter G H
author_facet Isojunno, Saana
Matthiopoulos, Jason
Evans, Peter G H
author_sort Isojunno, Saana
title Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
title_short Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
title_full Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
title_fullStr Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
title_full_unstemmed Harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
title_sort harbour porpoise habitat preferences:robust spatio-temporal inferences from opportunistic data
publishDate 2012
url https://risweb.st-andrews.ac.uk/portal/en/researchoutput/harbour-porpoise-habitat-preferences(bb617f9e-789c-41ab-9f1f-1734281e8782).html
https://doi.org/10.3354/meps09415
https://research-repository.st-andrews.ac.uk/bitstream/10023/16207/1/MarEcolProgSer448p155.pdf
long_lat ENVELOPE(-57.955,-57.955,-61.923,-61.923)
geographic Gam
geographic_facet Gam
genre Harbour porpoise
Phocoena phocoena
genre_facet Harbour porpoise
Phocoena phocoena
op_source Isojunno , S , Matthiopoulos , J & Evans , P G H 2012 , ' Harbour porpoise habitat preferences : robust spatio-temporal inferences from opportunistic data ' , Marine Ecology Progress Series , vol. 448 , pp. 155-170 . https://doi.org/10.3354/meps09415
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.3354/meps09415
container_title Marine Ecology Progress Series
container_volume 448
container_start_page 155
op_container_end_page 170
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