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Lookup NU author(s): Emeritus Professor Nick Polunin
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 The Author(s)Isoscapes – spatial models of stable isotope ratios – are powerful tools for understanding biogeochemical cycles, food web structure, and ecological connectivity. In marine systems, however, broad-scale isoscapes are difficult to constrain because reference datasets are typically heterogeneous and opportunistic. Bayesian hierarchical models implemented through Integrated Nested Laplace Approximation (INLA) provide an efficient framework for modeling spatial patterns while accounting for non-spatial variance. We tested whether broad-scale geographic baseline isoscapes could be constrained for the Mediterranean Sea using INLA models applied to an opportunistically compiled dataset from this semi-enclosed basin, where strong environmental gradients are expected but spatially explicit baselines remain lacking. We assembled the most comprehensive dataset of δ13C and δ15N values to date for low-trophic-level, primarily epipelagic food web compartments (> 6,000 samples from > 600 sites). Although discrete regions of relatively high and low δ values were identified, particularly for δ15N, semivariograms and model outputs indicated only short-range spatial autocorrelation (ca. 40 km for δ13C; 65 km for δ15N) within this large dataset. Environmental covariates improved model fit for δ15N values but did not enhance predictive performance or alter spatial predictions. Our results demonstrate that even advanced spatial models may not compensate where sampling design is structurally mismatched relative to unknown but structured spatial and non-spatial sources of isotopic variation. Coordinated sampling designed to capture spatial variability while accounting for major sources of non-spatial variance is required to develop robust marine isoscapes supporting ecological and management applications in the Mediterranean Sea and similar regions.
Author(s): Magozzi S, Trueman CN, Cobain MRD, MacKenzie KM, John Glew KS, Canseco JA, Diaz-Delgado E, Fanelli E, Rumolo P, Cartes JE, Espinasse B, Agnetta D, Albo-Puigserver M, Alomar C, Alvisi F, Badalamenti F, Banaru D, Berto D, Bonanno A, Bonaviri C, Bongiorni L, Buyukates Y, Calafat Frau AM, Camatti E, Cantoni C, Cardona L, Carlier A, Castellano M, Chaikalis S, Chiggiato J, Cibic T, Conan P, Conese I, Coppari M, Costalago D, Cresson P, D'Ambra I, Dahnke K, Darnaude AM, Deudero S, Ezgeta-Balic D, Giani M, Gogou A, Gregori G, Guy-Haim T, Harmelin-Vivien ML, Jennings S, Karageorgis AP, Koppelmann R, Lampadariou N, Langone L, Lienart C, Mazzocchi MG, Mazzola A, Meador TB, Merquiol L, Metzke M, Miserocchi S, Mobius J, Mostajir B, Mousseau L, Navarro J, Ogrinc N, Pansera M, Pantoja-Gutierrez S, Papiol V, Parinos C, Pasqual C, Pavlidou A, Pedrosa-Pamies R, Pinnegar J, Polunin NVC, Protopapa M, Repeta DJ, Sabatino N, Sachs JP, Sanchez-Vidal A, Sara G, Savoye N, Schroeder A, Skylaki E, Sigman DM, Signa G, Sisma-Ventura G, Stavrakaki I, Struck U, Tesan-Onrubia JA, Tesi T, Uzundumlu S, Valls M, Vizzini S, Zervoudaki S, Zgozi SW, Zoppini A, Zorica B, Willis TJ
Publication type: Article
Publication status: Published
Journal: Progress in Oceanography
Year: 2026
Volume: 248
Print publication date: 01/09/2026
Online publication date: 07/07/2026
Acceptance date: 02/07/2026
Date deposited: 04/08/2026
ISSN (print): 0079-6611
ISSN (electronic): 1873-4472
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.pocean.2026.103794
DOI: 10.1016/j.pocean.2026.103794
Data Access Statement: All data and R code used in this study are publicly available on Zenodo (Magozzi and Cobain, 2026).
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