Phytoplankton community succession and dynamics using optical approaches

The phytoplankton in coastal regions are responding to constant environmental changes, thus the use of proxies derived from in situ frequent time-series observations and validated from traditional microscopic or pigment methods can be a solution for detecting rapid responses of community dynamics and succession. In this study, we combined in situ high-frequency (every 30 min from May to September 2017) optical and hydrographic data from a moored buoy and weekly discrete samplings to track phytoplankton community dynamics and succession in Mausund Bank, a highly productive region of the coast of Norway. Three hydrographic regimes were observed: mixing period (MP) in spring, onset of stratification (transient period, TP) in summer and a stratified period (SP) in fall, with occasional strong winds that disrupted the surface stratification in the beginning of September. A bloom dominated by the diatom Skeletonema costatum was observed in the MP due to intense mixing and nutrient availability, while flagellates prevailed in nutrient-poor waters during the TP, followed by a bloom dominated by rhizosolenid diatoms (Proboscia alata and Guinardia delicatula), when stratification peaked. A mixed assemblage of diatoms (e.g. Pseudo-nitzschia), coccolithophores and dinoflagellates occurred during the SP, as strong winds reintroduced nutrients to surface waters. Through pigment (chemotaxonomy) and microscopic observations, we tested, for the first time in a coastal region, whether an ‘optical community index’ derived from in situ measurements of chlorophyll a fluorescence (Fchla) and optical particulate backscattering (bbp) is suitable to differentiate between diatom versus flagellate dominance. We found a negative relationship between Fchla:bbp and diatom:flagellate, contrary to previous observations, possibly because of the influence of non-algal contribution (e.g. zooplankton, fecal pellets and detritus) to the bbp pool in highly productive systems. This finding suggests that such relationship is not universal and that other parameters are needed to refine the optical community index in coastal regions

Contrasting phytoplankton-zooplankton distributions observed through autonomous platforms, in-situ optical sensors and discrete sampling

Plankton distributions are remarkably ‘patchy’ in the ocean. In this study, we investigated the contrasting phytoplankton-zooplankton distributions in relation to wind mixing events in waters around a biodiversity-rich island (Runde) located off the western coast of Norway. We used adaptive sampling from AUV and shipboard profiles of in-situ phytoplankton photo-physiology and particle identification (copepods, fecal pellets and the dinoflagellate Tripos spp.) and quantification using optical and imaging sensors. Additionally, traditional seawater and net sampling were collected for nutrient and in-vitro chlorophyll a concentrations and phytoplankton and meso-zooplankton abundances. Persistent strong wind conditions (~5 days) disrupted the stratification in offshore regions, while stratification and a subsurface chlorophyll maximum (SCM) were observed above the base of the mixed layer depth (MLD ~30 m) in inshore waters. Contrasting phytoplankton and zooplankton abundances were observed between inshore (with the presence of a SCM) and offshore waters (without the presence of a SCM). At the SCM, phytoplankton abundances (Tripos spp., the diatom Proboscia alata and other flagellates) were half (average of 200 cell L-1) of those observed offshore. On the contrary, meso-zooplankton counts were ~6× higher (732 ind m-3 for Calanus spp.) inshore (where a SCM was observed) compared to offshore areas. In parallel, fecal pellets and ammonium concentrations were high (>1000 ind m-3 for the upper 20 m) at the SCM, suggesting that the shallow mixed layer might have increased encounter rates and promoted strong grazing pressure. Low nutrient concentrations (< 1μM for nitrate) were found below the MLD (60 m) in offshore waters, suggesting that mixing and nutrient availability likely boosted phytoplankton abundances. The size of the absorption cross-section (σPII’) and yield of photosystem II photochemistry under ambient light (φPII’) changed according to depth, while the depth-related electron flow (JPII) was similar between regions, suggesting a high degree of community plasticity to changes in the light regime. Our results emphasize the importance of using multiple instrumentation, in addition to traditional seawater and net sampling for a holistic understanding of plankton distributions.publishedVersio

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

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

Biogeography of spring phytoplankton communities from the Labrador Sea: drivers, trends, ecological traits and biogeochemical implications

The Labrador Sea is a high latitude sea of the sub-Arctic region known to be an important oceanic sink for atmospheric CO2 due to intensive convective mixing during winter and the development of extensive phytoplankton blooms that occur during spring and summer. Therefore, a broad-scale investigation of the response of phytoplankton community composition to environmental forcing is essential for understanding planktonic food-web organization and biogeochemical functioning in the Labrador Sea. The aim of the research included in this thesis is to investigate the biogeographical and biochemical aspects of phytoplankton communities resulting from the contrasting hydrographical zones that divide the Labrador Sea into distinct ecological provinces. In Chapter 2, the phytoplankton community structure from near surface waters during spring and early summer (2011 to 2014) was investigated in detail, including species composition and environmental controls. This initial results demonstrated that the Labrador Sea spring and early summer blooms were composed of contrasting phytoplankton communities, for which taxonomic segregation appeared to be controlled by the physical and chemical characteristics of the dominant water masses. In Chapter 3, further work included an investigation of spring phytoplankton communities from surface waters of the Labrador Sea using pigment-based data and CHEMTAX analysis over ten-years (2005-2014). The photophysiological parameters (derived from photosynthesis-irradiance curves) and biochemical (particulate organic carbon to nitrogen ratio (POC:PON)) values differed among distinct phytoplankton communities. These results have provided a baseline of current distributions and an evaluation of the biogeochemical role of spring phytoplankton communities in the Labrador Sea, which will improve our understanding of potential long-term responses of phytoplankton communities in high-latitude oceans to a changing climate. In Chapter 4, potential indicator phytoplankton species of Atlantic and Arctic waters were investigated during spring in the Labrador Sea to identify possible functional traits driving biogeography. Future implications in trait biogeography and species distributions under a global warming scenario are discussed. In Chapter 5, a synthesis of the main findings of each result Chapter is included, in addition to schematic representation of the environmental controls on phytoplankton communities and species/classes succession from May to June in the Labrador Sea. Work that would increment our knowledge of phytoplankton from the Labrador Sea is suggested together with a final conclusion

Underwater Hyperspectral Imaging of Arctic Macroalgal Habitats during the Polar Night Using a Novel Mini-ROV-UHI Portable System

We describe an Underwater Hyperspectral Imager (UHI) deployed on an instrumentcarrying platform consisting of two interconnected mini-ROVs (Remotely Operated Vehicle) for the mapping and monitoring of Arctic macroalgal habitats in Kongsfjorden (Svalbard) during the Polar Night. The mini-ROV-UHI system is easy to transport, assemble and deploy from shore, even under the dark, icy and cold conditions of the Arctic Polar Night. The system can be operated by two persons, keeping the operational costs low. In vivo hyperspectral reflectance of collected specimens of brown, red and green macroalgae was measured with a spectrometer in the lab to provide a spectral library for supervised pigment group classification based on UHI photomosaics. The in situ UHI-photomosaics provided detailed information of the areal coverage of the seafloor substrate (16%), as well as brown (51% habitat cover), red (18%), and green (14%) macroalgae, with spatial resolution in the range of cm and spectral resolution of 2 nm. The collected specimens from the mapped area were also used for species identification and health state evaluation. This innovative UHI sampling method provides significant information about macroalgal distribution and physiology, and due to its flexibility in terms of deployment, it is applicable to a variety of environments

Phytoplankton community succession and dynamics using optical approaches

The phytoplankton in coastal regions are responding to constant environmental changes, thus the use of proxies derived from in situ frequent time-series observations and validated from traditional microscopic or pigment methods can be a solution for detecting rapid responses of community dynamics and succession. In this study, we combined in situ high-frequency (every 30 min from May to September 2017) optical and hydrographic data from a moored buoy and weekly discrete samplings to track phytoplankton community dynamics and succession in Mausund Bank, a highly productive region of the coast of Norway. Three hydrographic regimes were observed: mixing period (MP) in spring, onset of stratification (transient period, TP) in summer and a stratified period (SP) in fall, with occasional strong winds that disrupted the surface stratification in the beginning of September. A bloom dominated by the diatom Skeletonema costatum was observed in the MP due to intense mixing and nutrient availability, while flagellates prevailed in nutrient-poor waters during the TP, followed by a bloom dominated by rhizosolenid diatoms (Proboscia alata and Guinardia delicatula), when stratification peaked. A mixed assemblage of diatoms (e.g. Pseudo-nitzschia), coccolithophores and dinoflagellates occurred during the SP, as strong winds reintroduced nutrients to surface waters. Through pigment (chemotaxonomy) and microscopic observations, we tested, for the first time in a coastal region, whether an ‘optical community index’ derived from in situ measurements of chlorophyll a fluorescence (Fchla) and optical particulate backscattering (bbp) is suitable to differentiate between diatom versus flagellate dominance. We found a negative relationship between Fchla:bbp and diatom:flagellate, contrary to previous observations, possibly because of the influence of non-algal contribution (e.g. zooplankton, fecal pellets and detritus) to the bbp pool in highly productive systems. This finding suggests that such relationship is not universal and that other parameters are needed to refine the optical community index in coastal regions

Information-driven robotic sampling in the coastal ocean

Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such features. We present methods that capitalize on information from ocean models and in situ measurements, using Gaussian process modeling and objective functions, allowing sampling efforts to be concentrated to regions with high scientific interest. We demonstrate how to combine and correlate marine data from autonomous underwater vehicles, model forecasts, remote sensing satellite, buoy, and ship‐based measurements, as a means to cross‐validate and improve ocean model accuracy, in addition to resolving upper water‐column interactions. Our work is focused on the west coast of Mid‐Norway where significant influx of Atlantic Water produces a rich and complex physical–biological coupling, which is hard to measure and characterize due to the harsh environmental conditions. Results from both simulation and full‐scale sea trials are presented.Nansen Legacy Program, Grant/AwardNumber:27272; Senter for Autonome Marine Operasjoner og Systemer,Grant/Award Number: 223254; Norges Forskningsråd,Grant/Award Number: 255303/E40; European Union's Seventh Framework Programme(FP7/2007–2013), Grant/Award Number: 270180publishedVersio

Toward adaptive robotic sampling of phytoplankton in the coastal ocean

Currents, wind, bathymetry, and freshwater runoff are some of the factors that make coastal waters heterogeneous, patchy, and scientifically interesting—where it is challenging to resolve the spatiotemporal variation within the water column. We present methods and results from field experiments using an autonomous underwater vehicle (AUV) with embedded algorithms that focus sampling on features in three dimensions. This was achieved by combining Gaussian process (GP) modeling with onboard robotic autonomy, allowing volumetric measurements to be made at fine scales. Special focus was given to the patchiness of phytoplankton biomass, measured as chlorophyll a (Chla), an important factor for understanding biogeochemical processes, such as primary productivity, in the coastal ocean. During multiple field tests in Runde, Norway, the method was successfully used to identify, map, and track the subsurface chlorophyll a maxima (SCM). Results show that the algorithm was able to estimate the SCM volumetrically, enabling the AUV to track the maximum concentration depth within the volume. These data were subsequently verified and supplemented with remote sensing, time series from a buoy and ship-based measurements from a fast repetition rate fluorometer (FRRf), particle imaging systems, as well as discrete water samples, covering both the large and small scales of the microbial community shaped by coastal dynamics. By bringing together diverse methods from statistics, autonomous control, imaging, and oceanography, the work offers an interdisciplinary perspective in robotic observation of our changing oceans.publishedVersio

Contrasting phytoplankton-zooplankton distributions observed through autonomous platforms, in-situ optical sensors and discrete sampling

Plankton distributions are remarkably ‘patchy’ in the ocean. In this study, we investigated the contrasting phytoplankton-zooplankton distributions in relation to wind mixing events in waters around a biodiversity-rich island (Runde) located off the western coast of Norway. We used adaptive sampling from AUV and shipboard profiles of in-situ phytoplankton photo-physiology and particle identification (copepods, fecal pellets and the dinoflagellate Tripos spp.) and quantification using optical and imaging sensors. Additionally, traditional seawater and net sampling were collected for nutrient and in-vitro chlorophyll a concentrations and phytoplankton and meso-zooplankton abundances. Persistent strong wind conditions (~5 days) disrupted the stratification in offshore regions, while stratification and a subsurface chlorophyll maximum (SCM) were observed above the base of the mixed layer depth (MLD ~30 m) in inshore waters. Contrasting phytoplankton and zooplankton abundances were observed between inshore (with the presence of a SCM) and offshore waters (without the presence of a SCM). At the SCM, phytoplankton abundances (Tripos spp., the diatom Proboscia alata and other flagellates) were half (average of 200 cell L-1) of those observed offshore. On the contrary, meso-zooplankton counts were ~6× higher (732 ind m-3 for Calanus spp.) inshore (where a SCM was observed) compared to offshore areas. In parallel, fecal pellets and ammonium concentrations were high (>1000 ind m-3 for the upper 20 m) at the SCM, suggesting that the shallow mixed layer might have increased encounter rates and promoted strong grazing pressure. Low nutrient concentrations (< 1μM for nitrate) were found below the MLD (60 m) in offshore waters, suggesting that mixing and nutrient availability likely boosted phytoplankton abundances. The size of the absorption cross-section (σPII’) and yield of photosystem II photochemistry under ambient light (φPII’) changed according to depth, while the depth-related electron flow (JPII) was similar between regions, suggesting a high degree of community plasticity to changes in the light regime. Our results emphasize the importance of using multiple instrumentation, in addition to traditional seawater and net sampling for a holistic understanding of plankton distributions

Contrasting phytoplankton-zooplankton distributions observed through autonomous platforms, in-situ optical sensors and discrete sampling

Plankton distributions are remarkably ‘patchy’ in the ocean. In this study, we investigated the contrasting phytoplankton-zooplankton distributions in relation to wind mixing events in waters around a biodiversity-rich island (Runde) located off the western coast of Norway. We used adaptive sampling from AUV and shipboard profiles of in-situ phytoplankton photo-physiology and particle identification (copepods, fecal pellets and the dinoflagellate Tripos spp.) and quantification using optical and imaging sensors. Additionally, traditional seawater and net sampling were collected for nutrient and in-vitro chlorophyll a concentrations and phytoplankton and meso-zooplankton abundances. Persistent strong wind conditions (~5 days) disrupted the stratification in offshore regions, while stratification and a subsurface chlorophyll maximum (SCM) were observed above the base of the mixed layer depth (MLD ~30 m) in inshore waters. Contrasting phytoplankton and zooplankton abundances were observed between inshore (with the presence of a SCM) and offshore waters (without the presence of a SCM). At the SCM, phytoplankton abundances (Tripos spp., the diatom Proboscia alata and other flagellates) were half (average of 200 cell L-1) of those observed offshore. On the contrary, meso-zooplankton counts were ~6× higher (732 ind m-3 for Calanus spp.) inshore (where a SCM was observed) compared to offshore areas. In parallel, fecal pellets and ammonium concentrations were high (>1000 ind m-3 for the upper 20 m) at the SCM, suggesting that the shallow mixed layer might have increased encounter rates and promoted strong grazing pressure. Low nutrient concentrations (< 1μM for nitrate) were found below the MLD (60 m) in offshore waters, suggesting that mixing and nutrient availability likely boosted phytoplankton abundances. The size of the absorption cross-section (σPII’) and yield of photosystem II photochemistry under ambient light (φPII’) changed according to depth, while the depth-related electron flow (JPII) was similar between regions, suggesting a high degree of community plasticity to changes in the light regime. Our results emphasize the importance of using multiple instrumentation, in addition to traditional seawater and net sampling for a holistic understanding of plankton distributions