The University of Southampton
University of Southampton Institutional Repository

Spatial models of carbon, nitrogen and sulphur stable isotope distributions (isoscapes) across a shelf sea: An INLA approach

Spatial models of carbon, nitrogen and sulphur stable isotope distributions (isoscapes) across a shelf sea: An INLA approach
Spatial models of carbon, nitrogen and sulphur stable isotope distributions (isoscapes) across a shelf sea: An INLA approach
Spatial models of variation in the isotopic composition of structural nutrients across habitats (isoscapes) offer information on physical, biogeochemical and anthropogenic processes occurring across space, and provide a tool for retrospective assignment of animals or animal products to their foraging area or geographic origin. The isotopic differences among reference samples used to construct isoscapes may vary spatially and according to non‐spatial terms (e.g. sampling date, or among individual or species effects). Partitioning variance between spatially dependent and spatially independent terms is a critical but overlooked aspect of isoscape creation with important consequences for the design of studies collecting reference data for isoscape creation and the accuracy and precision of isoscape models.

We introduce the use of integrated nested Laplace approximation (INLA) to construct isoscape models. Integrated nested Laplace approximation provides a computationally efficient framework to construct spatial models of isotopic variability explicitly addressing additional variation introduced by including multiple reference species (or other recognized sources of variance).

We present carbon, nitrogen and sulphur isoscape models extending over c. 1 million km2 of the UK shelf seas. Models were built using seven different species of jellyfish as spatial reference data and a suite of environmental correlates. Compared to alternative isoscape prediction methods, INLA‐spatial isotope models show high spatial precision and reduced variance. We briefly discuss the likely biogeochemical explanations for the observed spatial isotope distributions. We show for the first time that sulphur isotopes display systematic spatial variation across open marine shelf seas and may therefore be a useful additional tool for marine spatial ecology.

The INLA technique provides a promising tool for generating isoscape models and associated uncertainty surfaces where reference data are accompanied by multiple, quantifiable sources of uncertainty
2041-210X
St John Glew, Kate
8f3bc334-6c9b-4280-bd3c-2ca3290f0650
Graham, Laura
bc76bad7-f0fd-4e94-acf9-c7450ec36ae2
McGill, Rona A.R.
05d52b44-2ef7-4178-b84c-bd39b57563ea
Trueman, Clive
d00d3bd6-a47b-4d47-89ae-841c3d506205
St John Glew, Kate
8f3bc334-6c9b-4280-bd3c-2ca3290f0650
Graham, Laura
bc76bad7-f0fd-4e94-acf9-c7450ec36ae2
McGill, Rona A.R.
05d52b44-2ef7-4178-b84c-bd39b57563ea
Trueman, Clive
d00d3bd6-a47b-4d47-89ae-841c3d506205

St John Glew, Kate, Graham, Laura, McGill, Rona A.R. and Trueman, Clive (2019) Spatial models of carbon, nitrogen and sulphur stable isotope distributions (isoscapes) across a shelf sea: An INLA approach. Methods in Ecology and Evolution. (doi:10.1111/2041-210X.13138).

Record type: Article

Abstract

Spatial models of variation in the isotopic composition of structural nutrients across habitats (isoscapes) offer information on physical, biogeochemical and anthropogenic processes occurring across space, and provide a tool for retrospective assignment of animals or animal products to their foraging area or geographic origin. The isotopic differences among reference samples used to construct isoscapes may vary spatially and according to non‐spatial terms (e.g. sampling date, or among individual or species effects). Partitioning variance between spatially dependent and spatially independent terms is a critical but overlooked aspect of isoscape creation with important consequences for the design of studies collecting reference data for isoscape creation and the accuracy and precision of isoscape models.

We introduce the use of integrated nested Laplace approximation (INLA) to construct isoscape models. Integrated nested Laplace approximation provides a computationally efficient framework to construct spatial models of isotopic variability explicitly addressing additional variation introduced by including multiple reference species (or other recognized sources of variance).

We present carbon, nitrogen and sulphur isoscape models extending over c. 1 million km2 of the UK shelf seas. Models were built using seven different species of jellyfish as spatial reference data and a suite of environmental correlates. Compared to alternative isoscape prediction methods, INLA‐spatial isotope models show high spatial precision and reduced variance. We briefly discuss the likely biogeochemical explanations for the observed spatial isotope distributions. We show for the first time that sulphur isotopes display systematic spatial variation across open marine shelf seas and may therefore be a useful additional tool for marine spatial ecology.

The INLA technique provides a promising tool for generating isoscape models and associated uncertainty surfaces where reference data are accompanied by multiple, quantifiable sources of uncertainty

Text
Glew_et_al-2019-Methods_in_Ecology_and_Evolution - Version of Record
Available under License Creative Commons Attribution.
Download (2MB)

More information

Accepted/In Press date: 5 December 2018
e-pub ahead of print date: 15 January 2019

Identifiers

Local EPrints ID: 427809
URI: http://eprints.soton.ac.uk/id/eprint/427809
ISSN: 2041-210X
PURE UUID: 55889c77-5191-48ac-b0ce-620dbb1c138a

Catalogue record

Date deposited: 29 Jan 2019 17:30
Last modified: 06 Oct 2020 21:57

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×