Monitoring Algal Blooms with Complementary Sensors on Multiple Spatial and Temporal Scales

Abstract

Climate change, and other human-induced impacts, are severely increasing the intensity and occurrences of algal blooms in coastal regions (IPCC, 2022). Ocean warming, marine heatwaves, and eutrophication promote suitable conditions for rapid phytoplankton growth and biomass accumulation. An increase in such primary producers provides food for marine organisms, and phytoplankton play an important global role in fixing atmospheric carbon dioxide and producing much of the oxygen we breathe. But harmful algal blooms (HABs) can also form, and they may adversely affect the ecosystem by reducing oxygen availability in the water, releasing toxic substances, clogging fish gills, and diminishing biodiversity. Understanding, forecasting, and ultimately mitigating HAB events could reduce their impact on wild fish populations, help aquaculture producers avoid losses, and facilitate a healthy ocean.

Phytoplankton respond rapidly to changes in the environment, and measuring the distribution of a bloom and its species composition and abundance is essential for determining its ecological impact and potential for harm. Satellite remote sensing of chlorophyll concentration has been used extensively to observe the development of algal blooms. Although this tool has wide spatial and temporal (nearly daily) coverage, it is limited to surface ocean waters and cloud-free days. Microscopic analyses of water and net samples allow much closer examination of the species present in a bloom and their abundance, but this is a time-consuming process that collects only discrete point samples, sparsely distributed in space and time. Neither of these methods alone captures the rapid evolution of algal blooms, the spatial and temporal patchiness of their distributions, or their high local variability. In situ optical devices and imaging sensors mounted on mobile platforms such as autonomous underwater vehicles (AUVs) and uncrewed surface vehicles (USVs) capture fine-scale temporal trends in plankton communities, while uncrewed aerial vehicles (UAVs) complement satellite remote sensing. Use of such autonomous platforms offers the flexibility to react to local conditions with adaptive sampling techniques in order to examine the marine environments in real time.

Here we present an integrated approach to observing blooms—an “observational pyramid”—that includes both classical and newer, complementary observation methods (Figure 1). We aim to identify trends in phytoplankton blooms in a region with strong aquaculture activity on the Atlantic coast of mid-Norway. Field campaigns were carried out in consecutive springs (2021 and 2022) in Frohavet, an area of sea sheltered by the Froan archipelago (Figure 2). The region is a shallow, highly productive basin with abundant fishing and a growing aquaculture industry. Typically, there are one or more large algal blooms here during the spring months. We use multi-instrumentation from macro- to a microscale perspectives, combined with oceanographic modeling and ground truthing, to provide tools for early algal bloom detection.