Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography

Abstract Identifying and understanding ecological drivers that influence wildlife populations is challenging but critical for conservation. This typically requires integrating long‐term data on both the population and potential drivers within statistical models that are suitable for analysing these...

Full description

Bibliographic Details
Published in:Aquatic Conservation: Marine and Freshwater Ecosystems
Main Authors: Caillat, Marjolaine, Cordes, Line, Thompson, Paul, Matthiopoulos, Jason, Smout, Sophie
Other Authors: Marine Scotland
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2019
Subjects:
Online Access:http://dx.doi.org/10.1002/aqc.3130
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Faqc.3130
https://onlinelibrary.wiley.com/doi/pdf/10.1002/aqc.3130
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/aqc.3130
id crwiley:10.1002/aqc.3130
record_format openpolar
spelling crwiley:10.1002/aqc.3130 2024-06-02T08:07:48+00:00 Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography Caillat, Marjolaine Cordes, Line Thompson, Paul Matthiopoulos, Jason Smout, Sophie Marine Scotland 2019 http://dx.doi.org/10.1002/aqc.3130 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Faqc.3130 https://onlinelibrary.wiley.com/doi/pdf/10.1002/aqc.3130 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/aqc.3130 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Aquatic Conservation: Marine and Freshwater Ecosystems volume 29, issue S1, page 101-118 ISSN 1052-7613 1099-0755 journal-article 2019 crwiley https://doi.org/10.1002/aqc.3130 2024-05-03T12:04:00Z Abstract Identifying and understanding ecological drivers that influence wildlife populations is challenging but critical for conservation. This typically requires integrating long‐term data on both the population and potential drivers within statistical models that are suitable for analysing these complex relationships. State‐space models offer one method for integrating such data. Once implemented within a Bayesian framework, these analyses can control for multifactorial influences on populations, allowing one to extract otherwise undetectable correlations between the environment and the underlying, inferred demography. In the Moray Firth, Scotland, harbour seals have been counted annually for 30 years (1988–2018). A Bayesian state‐space model was used to explore whether patterns in vital rates were correlated to changes in prey abundance, inter‐specific competition (grey seal abundance), environmental variables [the North Atlantic Oscillation (NAO) and sea‐surface temperature], or level of biotoxins (saxitoxin and domoic acid) in the Moray Firth waters. The credible interval of the posterior distributions of three of these covariate coefficients (sandeel proxy, NAO and grey seal abundance) suggested that there was a relationship between those covariates and vital rates. Both the sandeel proxy and NAO showed a positive correlation with fecundity, whereas grey seal abundance had a negative impact on pup survival. This work demonstrates how an integrated state‐space modelling approach can bring together diverse data sets and point to important interactions with prey, and with other predators in the system. This suggests that the wider‐scale management of UK harbour seal populations with their contrasting temporal trends needs to account for variation in the marine ecosystem at appropriate spatial scales, in line with current policy concerning spatial planning in the marine environment. Article in Journal/Newspaper harbour seal North Atlantic North Atlantic oscillation Wiley Online Library Aquatic Conservation: Marine and Freshwater Ecosystems 29 S1 101 118
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Identifying and understanding ecological drivers that influence wildlife populations is challenging but critical for conservation. This typically requires integrating long‐term data on both the population and potential drivers within statistical models that are suitable for analysing these complex relationships. State‐space models offer one method for integrating such data. Once implemented within a Bayesian framework, these analyses can control for multifactorial influences on populations, allowing one to extract otherwise undetectable correlations between the environment and the underlying, inferred demography. In the Moray Firth, Scotland, harbour seals have been counted annually for 30 years (1988–2018). A Bayesian state‐space model was used to explore whether patterns in vital rates were correlated to changes in prey abundance, inter‐specific competition (grey seal abundance), environmental variables [the North Atlantic Oscillation (NAO) and sea‐surface temperature], or level of biotoxins (saxitoxin and domoic acid) in the Moray Firth waters. The credible interval of the posterior distributions of three of these covariate coefficients (sandeel proxy, NAO and grey seal abundance) suggested that there was a relationship between those covariates and vital rates. Both the sandeel proxy and NAO showed a positive correlation with fecundity, whereas grey seal abundance had a negative impact on pup survival. This work demonstrates how an integrated state‐space modelling approach can bring together diverse data sets and point to important interactions with prey, and with other predators in the system. This suggests that the wider‐scale management of UK harbour seal populations with their contrasting temporal trends needs to account for variation in the marine ecosystem at appropriate spatial scales, in line with current policy concerning spatial planning in the marine environment.
author2 Marine Scotland
format Article in Journal/Newspaper
author Caillat, Marjolaine
Cordes, Line
Thompson, Paul
Matthiopoulos, Jason
Smout, Sophie
spellingShingle Caillat, Marjolaine
Cordes, Line
Thompson, Paul
Matthiopoulos, Jason
Smout, Sophie
Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
author_facet Caillat, Marjolaine
Cordes, Line
Thompson, Paul
Matthiopoulos, Jason
Smout, Sophie
author_sort Caillat, Marjolaine
title Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
title_short Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
title_full Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
title_fullStr Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
title_full_unstemmed Use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
title_sort use of state‐space modelling to identify ecological covariates associated with trends in pinniped demography
publisher Wiley
publishDate 2019
url http://dx.doi.org/10.1002/aqc.3130
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Faqc.3130
https://onlinelibrary.wiley.com/doi/pdf/10.1002/aqc.3130
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/aqc.3130
genre harbour seal
North Atlantic
North Atlantic oscillation
genre_facet harbour seal
North Atlantic
North Atlantic oscillation
op_source Aquatic Conservation: Marine and Freshwater Ecosystems
volume 29, issue S1, page 101-118
ISSN 1052-7613 1099-0755
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/aqc.3130
container_title Aquatic Conservation: Marine and Freshwater Ecosystems
container_volume 29
container_issue S1
container_start_page 101
op_container_end_page 118
_version_ 1800752929863368704