Long-term dynamics of production in western Mediterranean seagrass meadows: Trade-offs and legacies of past disturbances

Abstract

Seagrasses are marine angiosperms that can form highly productive, and valuable underwater meadows, which are currently in regression. A reliable assessment of their status and future evolution requires studies encompassing long-term temporal scales. With the aim of understanding seagrass ecosystem dynamics over the last centuries and millennia, twelve sediment cores were studied from seagrass meadows located along the Andalusian coast and at the Cabrera Island (western Mediterranean). This study is pioneer in using Fourier Transform Infrared (FTIR) spectroscopy as a tool to study environmental change in seagrass sediments. FTIR is a form of vibrational spectroscopy that provides information about the sediment chemical composition. Principal Component Analysis (PCA) was used to summarise spatio-temporal data of the FTIR vibratory peaks in combination with climate and geochemical proxy data. Several PCA signals were identified: (1) one likely related to the relative changes of the main primary producers and the sedimentary environment (carbonate or siliciclastic sediments, with aromatic or aliphatic organic matter); (2) the marine community production (polysaccharides, total organic matter content and biogenic silica); and (3) the seagrass production (aromatics, carbohydrates, phenols, proteins and lipids). A decrease of seagrass production along the mainland coast was evident since AD ~1850, which may be due to combined negative impacts of seawater warming, local anthropogenic impacts, and extreme setting conditions. The legacy of these combined stressors might have influenced the current poor state of seagrass meadows in the Alboran Sea. Our results also revealed a significant long-term trade-off between the level of seagrass production and its temporal stability (calculated as the inverse of the coefficient of variation). This study provides a reliable baseline data, helping to assess the magnitude of seagrass regression and its drivers. This paleoecological information can help design more targeted management plans and identify meadows where local management could be more efficient.