Decadal analysis of chlorophyll fluorescence, algal blooms and driving factors from a fixed-point observing system in the Northern Adriatic Sea

Understanding the dynamics of coastal marine ecosystems is fundamental for assessing environmental health and addressing anthropogenic impacts. This study analyzes a decade-long dataset of high-resolution Chlorophyll fluorescence (ChlF) measurements collected hourly from August 2012 to December 2022 at the E1 meteo-oceanographic buoy (Böhm et al. 2016). The buoy is located in the Northern Adriatic Sea (44° 08.58’ N; 12° 34.20’ E), approximately 100 km south of the Po River delta and 7 km northeast of Rimini, Italy. As part of the “Delta del Po and Costa Romagnola” (Bergami and Riminucci 2025) research site within the Italian LTER network and the PNRR ITINERIS project, the E1 station provides a unique platform for multidisciplinary research and long-term environmental monitoring. ChlF data, collected by the WET Labs ECO Triplet (now SeaBird Scientific), reveal significant seasonal and interannual variations in chlorophyll concentration, estimates from in situ ChlF, ranging from below detection limits to a maximum daily average of 41 μg/L. Together with ChlF, other meteorological, chemical, and physical parameters such as temperature (TEMP), dissolved oxygen (DO), salinity (SAL), turbidity (TURB), and wind speed (WS) were incorporated for this study (Riminucci et al. 2024, Riminucci et al. 2025 ). A total of 40 distinct algal bloom events were identified using ChlF concentration thresholds and growth rate dynamics (Trombetta et al. 2019). The analysis of bloom frequency revealed two main periods of bloom events per year (Fig. 1), with the identified blooms lasting an average of 13±10 days. During these events, ChlF concentration increased to an average of 6.5 μg/L, indicating substantial algal growth, compared to a baseline of 2.8 μg/L observed outside bloom periods. The most intense blooms occurred in spring, driven by nutrient inputs and increased sunlight, while summer blooms were weaker, less frequent, and shorter in duration due to thermal stratification. In contrast, autumn and winter saw a resurgence of bloom activity, influenced by freshwater inflow, nutrient resuspension, and strong mixing. These seasonal patterns underscore the dynamic interplay between temperature, wind, and nutrient availability in shaping phytoplankton dynamics. Principal Component Analysis (PCA) was conducted to identify key relationships among environmental variables and their influence on algal blooms (Fig. 2). The strong correlation between ChlF and DO during bloom periods reflects the role of photosynthesis in elevating oxygen levels. TEMP and SAL are linked due to seasonal stratification, while WS and TURB highlight wind-driven physical disturbances, such as sediment resuspension and waves. Overall, PCA captures both seasonal and biological processes, including bloom dynamics, as well as physical disturbances driven by wind and water movement. Seasonal factors govern bloom dynamics, with spring and late autumn/winter supporting phytoplankton growth due to favourable nutrient availability and stable conditions, while summer stratification limits blooms. These findings underscore the interplay of biological and physical drivers in shaping the ecosystem response over the decade. Two bloom types were identified: Single-Peak Blooms, typical in spring, characterized by rapid growth and short durations, and Multi-Peak Blooms, more common in autumn, with extended periods due to intermittent nutrient apportion. Nutrient-rich freshwater inputs from the Po River, nitrogen and phosphorus, and seasonal cycles of phytoplankton play a significant role in driving these blooms. Diatoms such as Skeletonema marinoi dominate the winter bloom, while spring and autumn blooms are diatom-driven, modulated by rainfall and nutrient runoff (Grilli et al. 2020, Totti et al. 2019). Summer, characterized by water column stratification, generally exhibits lower ChlF concentrations unless disturbed by storms or mixing events that reintroduce nutrients into surface waters. These findings emphasize the complex seasonal and environmental drivers shaping bloom dynamics. This study introduces a methodological framework for detecting coastal algal blooms by analyzing patterns derived from in-situ fluorescence measurements, offering insights into bloom dynamics. While challenges such as data gaps due to sensor maintenance and biofouling, the findings underscore the value of long-term, high-frequency observations in understanding environmental processes and managing coastal ecosystems. Future research should focus on integrating complementary datasets, such as nutrient concentrations or satellite observations, to deepen the understanding of bloom drivers. Additionally, expanding datasets temporally, by including more years, and spatially, by incorporating other monitoring systems (e.g., fixed-point stations), will further enhance the robustness and applicability of the framework.