Through proxy and scale: how measurement choices shape narratives of shoreline change and vulnerability across embayed sandy beaches of southern Ireland

Shoreline change assessments are central to coastal management and adaptation planning, yet they commonly rely on a limited number of indicators used as proxies for complex coastal behaviour. Because interpretations of shoreline dynamics and vulnerability depend strongly on measurement methods and observational scales, this study examines how different monitoring approaches influence interpretations of soft coastline shoreline change along the energetic Atlantic coast of southern Ireland. A three-year multi-method monitoring programme (2023–2025) was conducted across five embayed unconsolidated sandy beach systems, integrating long-term aerial imagery and vegetation-line change, Sustainable Coastal Vulnerability Index outputs, repeated seasonal RTK-GNSS cross-shore profiles, high-resolution UAV-derived orthophotos and digital surface models, and targeted post-storm field assessments. Results show that different monitoring methods produce distinct but complementary narratives of shoreline behaviour. Long-term vegetation lines and derived change rates emphasise boundary translation but can mask shorter-term accelerations, regime shifts, or localised erosion hotspots. SCVI classifications provide effective broad-scale screening of exposure and receptors but may misrepresent physical susceptibility where local sediment dynamics or recovery processes are not captured. In contrast, field surveys and UAV-derived topographic datasets reveal spatially variable sediment dynamics, with erosion and accretion occurring simultaneously across different sectors of the same beach systems. These differences highlight the need for monitoring strategies that combine complementary datasets. Based on these findings, an evidence-based tiered monitoring strategy is proposed and distinguishes proxy-based screening, routine cross-shore profile monitoring, and targeted UAV surveys in spatially complex settings, reducing interpretive bias in assessments of shoreline change and coastal vulnerability.