Journal Article
Spatio-Temporal Modeling of SST for the Assessment of Climate Risk over Aquaculture in the Coast of the Valencian Region
Laura Aixalà-Perelló; Irene Lopez-Mengual; Javier Atalah; Juan Aparicio; J. David Ballester-Berman; David Conesa; Aitor Forcada; Jonatan A. González; Antonio López-Quílez; Pablo Sanchez-Jerez; Xavier Barber
Journal of Marine Science and Engineering · Vol. 14, Issue 5 · pp. 432 · 2026
Abstract
Climate change poses significant risks to Mediterranean aquaculture, with sea surface temperature (SST) identified as a critical stressor affecting cultivated species. This study aims to assess climate-related risks for coastal aquaculture in the Valencian Community (Spain) by analyzing SST spatiotemporal variability and predicting future trends. A multi-method approach was employed, combining ARIMA models for 10-year predictions at eight coastal locations, Bayesian hierarchical models (BHM) fitted via INLA for spatiotemporal analysis of maximum SST and temperature range (2000–2024), and Generalized Additive Models (GAM) to evaluate relationships with climate indices (NAO, AMO, ENSO). Results revealed a consistent warming trend since the 1990s, with ARIMA predictions indicating maximum SST values of 27.2 ± 0.1 °C in September over the next decade. The spatiotemporal model showed effective spatial correlation ranges of 246 km for maximum SST and 207 km for SST range. Anomalous warming years (2003, 2006, 2018, 2023–2024) coincided with documented marine heatwave events. The GAM explained 98.2% of deviance, with AMO showing significant influence (p