scholarly journals Enhanced chlorophyll-<i>a</i> concentration in the wake of Sable Island, eastern Canada, revealed by two decades of satellite observations: a response to grey seal population dynamics?

2021 ◽  
Vol 18 (23) ◽  
pp. 6115-6132
Author(s):  
Emmanuel Devred ◽  
Andrea Hilborn ◽  
Cornelia Elizabeth den Heyer
Keyword(s):  
Time Series ◽  
Phytoplankton Biomass ◽  
Standing Stock ◽  
Satellite Observations ◽  
Trophic Levels ◽  
Leeward Side ◽  
Grey Seal ◽  
Scotian Shelf ◽  
Eastern Canada ◽  
Chl A

Abstract. Elevated surface chlorophyll-a (chl-a) concentration ([chl-a]), an index of phytoplankton biomass, has been previously observed and documented by remote sensing in the waters to the southwest of Sable Island (SI) on the Scotian Shelf in eastern Canada. Here, we present an analysis of this phenomenon using a 21-year time series of satellite-derived [chl-a], paired with information on the particle backscattering coefficient at 443 nm (bbp(443), a proxy for particle suspension) and the detritus/gelbstoff absorption coefficient at 443 nm (adg(443), a proxy to differentiate water masses and presence of dissolved organic matter) in an attempt to explain some possible mechanisms that lead to the increase in surface biomass in the surroundings of SI. We compared the seasonal cycle, 8 d climatology and seasonal trends of surface waters near SI to two control regions located both upstream and downstream of the island, away from terrigenous inputs. Application of the self-organising map (SOM) approach to the time series of satellite-derived [chl-a] over the Scotian Shelf revealed the annual spatio-temporal patterns around SI and, in particular, persistently high phytoplankton biomass during winter and spring in the leeward side of SI, a phenomenon that was not observed in the control boxes. In the vicinity of SI, a significant increase in [chl-a] and adg(443) during the winter months occurred at a rate twice that of the ones observed in the control boxes, while no significant trends were found for the other seasons. In addition to the increase in [chl-a] and adg(443) within the plume southwest of SI, the surface area of the plume itself expanded by a factor of 5 over the last 21 years. While the island mass effect (IME) explained the enhanced biomass around SI, we hypothesised that the large increase in [chl-a] over the last 21 years was partly due to an injection of nutrients by the island's grey seal colony, which has increased by 200 % during the same period. This contribution of nutrients from seals may sustain high phytoplankton biomass at a time of year when it is usually low following the fall bloom. A conceptual model was developed to estimate the standing stock of chl-a that can be sustained by the release of nitrogen (N) by seals. Comparison between satellite observations and model simulations showed a good temporal agreement between the increased abundance of seal on SI during the breeding season and the phytoplankton biomass increase during the winter. We found that about 20 % of chl-a standing stock increase over the last 21 years could be due to seal N fertilisation, the remaining being explained by climate forcing and oceanographic processes. Although without in situ measurements for ground truthing, the satellite data analysis provided evidence of the impact of marine mammals on lower trophic levels through a fertilisation mechanism that is coupled with the IME with potential implications for conservation and fisheries.

scholarly journals Enhanced chlorophyll-a concentration in the wake of Sable Island, eastern Canada, revealed by two decades of satellite observations: a response to grey seal population dynamics?

2021 ◽  
Author(s):  
Emmanuel Devred ◽  
Andrea Hilborn ◽  
Cornelia den Heyer
Keyword(s):  
Time Series ◽  
Chlorophyll A ◽  
Phytoplankton Biomass ◽  
Satellite Observations ◽  
Eastern Canada ◽  
Chlorophyll A Concentration ◽  
Chl A ◽  
Seal Population ◽  
Good Agreement

Abstract. Elevated surface chlorophyll-a concentration, an index of phytoplankton biomass, has been previously observed and documented by remote sensing in the waters to the southwest of Sable Island (SI) on the Scotian Shelf in eastern Canada. Here, we present a detailed analysis of this phenomenon using a 20-year time series of satellite-derived chlorophyll-a concentration (chl-a), paired with information on the particle backscattering coefficient at 443 nm (bbp(443)) and the detritus/gelbstoff absorption coefficient at 443 nm (adg(443) ) in an attempt to explain the possible mechanisms that lead to the increase in surface biomass in the surroundings of SI. We compared the seasonal cycle, climatology and trends of surface waters near SI to two control regions located both upstream and downstream of the island, away from terrigenous inputs. Application of the self-organizing maps approach (SOMs) to the time series of satellite-derived chl-a over the Scotian Shelf revealed the annual spatio-temporal patterns around SI and, in particular, persistently high phytoplankton biomass during winter and spring in the leeward side of SI, a phenomenon that is not observed in the control boxes. Time series analysis of the satellite archive evidenced a long-term increase in chl-a and adg(443), and a long-term decrease in bbp(443) in all regions. In the close vicinity of SI, the increase of chl-a and adg(443) during the winter months occurred at a rate twice that of the ones observed in the control boxes. In addition to the increase of the chl-a and adg(443) within the plume southward of SI, the surface area of the plume itself has also expanded by a factor of five over the last 20 years. While the island mass effect (IME) is certainly contributing to the enhanced biomass around SI, we hypothesize that the large increase in chl-a over the last 20 years is due to an injection of nutrients by the island’s grey seal colony, which has increased by about 300 % over the last twenty years. The contribution of nutrients from seals may sustain high phytoplankton biomass at a time of year when it is usually low. A conceptual model was developed to describe the annual variation of seal abundance on SI and estimate the standing stock of chl-a concentration that can be sustained by the release of nitrogen. Comparison between satellite observations and model simulations showed a very good agreement between the seal population increase on SI during the breeding season and the phytoplankton biomass increase during the winter. In addition, the 20-year satellite-derived trend in chlorophyll-a concentration showed a good agreement with the increasing trend in seal population on SI during the same time period. The satellite data analysis supports the concept of top-down control of marine mammals over lower trophic levels through a fertilisation mechanism, although these results could not be confirmed without in situ measurements for ground truthing. Our findings challenge the idea that the IME is restricted to islands with strong bathymetric slope located in oligotrophic waters of mid-latitudes and tropics, and demonstrate that enhanced marine production can occur in other oceanic regions, with potentially substantial implications for conservation and fisheries.

scholarly journals Phytoplankton Phenology in the Coastal Zone of Cyprus, Based on Remote Sensing and In Situ Observations

2021 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Monica Demetriou ◽  
Dionysios E. Raitsos ◽  
Antonia Kournopoulou ◽  
Manolis Mandalakis ◽  
Spyros Sfenthourakis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Phytoplankton Biomass ◽  
Trophic Levels ◽  
Data Availability ◽  
Ocean Colour ◽  
Chl A ◽  
In Situ Data

Alterations in phytoplankton biomass, community structure and timing of their growth (phenology), are directly implicated in the carbon cycle and energy transfer to higher trophic levels of the marine food web. Due to the lack of long-term in situ datasets, there is very little information on phytoplankton seasonal succession in Cyprus (eastern Mediterranean Sea). On the other hand, satellite-derived measurements of ocean colour can only provide long-term time series of chlorophyll (an index of phytoplankton biomass) up to the first optical depth (surface waters). The coupling of both means of observations is essential for understanding phytoplankton dynamics and their response to environmental change. Here, we use 23 years of remotely sensed, regionally tuned ocean-colour observations, along with a unique time series of in situ phytoplankton pigment composition data, collected in coastal waters of Cyprus during 2016. The satellite observations show an initiation of phytoplankton growth period in November, a peak in February and termination in April, with an overall mean duration of ~4 months. An in-depth exploration of in situ total Chl-a concentration and phytoplankton pigments revealed that pico- and nano-plankton cells dominated the phytoplankton community. The growth peak in February was dominated by nanophytoplankton and potentially larger diatoms (pigments of 19’ hexanoyloxyfucoxanthin and fucoxanthin, respectively), in the 0–20 m layer. The highest total Chl-a concentration was recorded at a station off Akrotiri peninsula in the south, where strong coastal upwelling has been reported. Another station in the southern part, located next to a fish farm, showed a higher contribution of picophytoplankton during the most oligotrophic period (summer). Our results highlight the importance of using available in situ data coupled to ocean-colour remote sensing, for monitoring marine ecosystems in areas with limited in situ data availability.

Towards a balanced presentation and objective interpretation of acoustic and trawl survey data, with specific reference to the eastern Scotian Shelf

2016 ◽  
Vol 73 (12) ◽  
pp. 1914-1921 ◽  
Author(s):  
J. Michael Jech ◽  
Ian H. McQuinn
Keyword(s):  
Atlantic Cod ◽  
Management Strategies ◽  
Pelagic Fish ◽  
Trophic Levels ◽  
Fish Abundance ◽  
Forage Fish ◽  
Specific Reference ◽  
Trawl Survey ◽  
Scotian Shelf ◽  
Eastern Canada

A debate has developed over the ecosystem consequences following the collapse of Atlantic cod throughout the coastal waters of eastern Canada. The explosive increase in pelagic fish abundance in scientific bottom-trawl catches on the eastern Scotian Shelf has been interpreted as being due to either (i) a “pelagic outburst” of forage fish abundance resulting from predator release or conversely (ii) a change in pelagic fish vertical distribution leading to a “suprabenthic habitat occupation” thereby increasing their availability to bottom trawls. These two interpretations have diametrically opposing ecological consequences and suggest different management strategies for these important forage fish species. We argue that an objective evaluation of the available evidence supports the hypothesis that the abundance of forage fish has not increased in response to the demise of cod and other top predators, and the reliance on a single sampling gear with low catchability has biased and will continue to bias the interpretation of demographic trends of pelagic fish populations. We advocate that multiple sampling technologies providing alternative perspectives are needed for the monitoring and management of the various trophic levels if we are to achieve a balanced and objective understanding of marine ecosystems.

scholarly journals Phytoplankton biomass, composition, and productivity along a temperature and stratification gradient in the Northeast Atlantic Ocean

2013 ◽  
Vol 10 (1) ◽  
pp. 1793-1829 ◽  
Author(s):  
W. H. van de Poll ◽  
G. Kulk ◽  
K. R. Timmermans ◽  
C. P. D. Brussaard ◽  
H. J. van der Woerd ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Phytoplankton Biomass ◽  
Nutrient Concentration ◽  
North Atlantic Ocean ◽  
Standing Stock ◽  
Biomass Composition ◽  
Nutrient Concentrations ◽  
Exponential Relationship ◽  
Near Surface ◽  
Chl A

Abstract. The North Atlantic Ocean experiences considerable variability in sea surface temperature (SST, >10 m) on seasonal and inter-annual time-scales. Relationships between SST and vertical density stratification, nutrient concentrations, and phytoplankton biomass, composition, and absorption were assessed in spring and summer from latitudes 30–62° N. Furthermore, a bio-optical model was used to estimate productivity for five phytoplankton groups. Nutrient concentration (integrated from 0–125 m) was inversely correlated with SST in spring and summer. SST was also inversely correlated with near surface (0–50 m) Chl a and productivity for stratified stations. However, near surface Chl a showed an exponential relationship with SST, whereas a linear relationship was found for productivity and SST. The response of phytoplankton to changes in SST is therefore most likely to be observed by changes in Chl a rather than productivity. The discrepancy between relationships of Chl a and productivity were probably related to changes in phytoplankton cell size. The contribution of cyanobacteria to water column productivity correlated positively with SST and inversely with nutrient concentration. This suggests that a rise in SST (over a 13–23 °C range) stimulates productivity by cyanobacteria at the expense of haptophytes, which showed an inverse relationship to SST. At higher latitudes, where rising SST may prolong the stratified season, haptophyte productivity may expand at the expense of diatom productivity. Depth integrated Chl a (0–410 m) was greatest in the spring at higher latitudes, where stratification in the upper 200 m was weakest. This suggests that stronger stratification does not necessarily result in higher phytoplankton biomass standing stock in this region.

Deep learning approach to reconstruct satellite ocean color time series in the global ocean

2021 ◽  
Author(s):  
Joana Roussillon ◽  
Ronan Fablet ◽  
Lucas Drumetz ◽  
Thomas Gorgues ◽  
Elodie Martinez
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Phytoplankton Biomass ◽  
Decadal Variability ◽  
Temporal Structure ◽  
Ocean Color ◽  
Global Scale ◽  
Global Ocean ◽  
Chl A ◽  
Reconstruction Performance

&lt;p&gt;Phytoplankton plays a key role in the carbon cycle and constitutes the basis of the marine food web. Its seasonal and interannual cycles are relatively well-known on a global scale thanks to continuous ocean color satellite observations acquired since 1997. The satellite-derived chlorophyll-a concentrations (Chl-a, a proxy of phytoplankton biomass) time series are still too short to investigate phytoplankton biomass low-frequency variability. However, it is a vital prerequisite before being able to confidently detect anthropogenic signals, as natural decadal variability can accentuate, weaken or even mask out any anthropogenic trends. Machine learning appears as a promising tool to reconstruct Chl-a past signals (including periods before satellite Chl-a era), and deep learning models seem particularly relevant to explore the spatial and/or temporal structure of the data.&lt;/p&gt;&lt;p&gt;Here, different neural network architectures have been tested on a 18-year satellite and re-analysis dataset to infer Chl-a from physical predictors. Their ability to reconstruct spatial and temporal (seasonal and interannual) variations on a global scale will be presented. Convolutional neural networks (CNN) better capture Chl-a spatial fields than models that do not account for the structure of the data, such as multi-layer perceptrons (MLPs). We also assess how the selection of training period may affect the reconstruction performance. This is a necessary step before being able to reconstruct any past Chl-a multi-decadal time series with confidence, which is the ultimate goal of this work.&lt;/p&gt;&lt;p&gt;Our study also addresses the carbon footprint associated with the use of GPU resources when training the CNN. GPUs are energy intensive, and their use in geosciences is expected to grow fast. Systematically reporting the computational energy costs in the geoscience community studies would provide an overview of models energy-efficiency on different kinds of datasets and may encourage actions to reduce consumption when possible.&lt;/p&gt;

Dynamics of annual nutrinets and bloom-forming cyanobacteria, revealed by daily observation in a hyper-eutrophic lake

2020 ◽  
Author(s):  
Mengyuan Zhu ◽  
Guangwei Zhu ◽  
Hans Paerl ◽  
Wei Zhang ◽  
Hai Xu
Keyword(s):  
Water Column ◽  
Phytoplankton Biomass ◽  
Lake Taihu ◽  
Eutrophic Lake ◽  
Trophic Levels ◽  
Monitoring Data ◽  
Limiting Factors ◽  
Nutrient Concentrations ◽  
Nitrogen And Phosphorus ◽  
Chl A

&lt;p&gt;Daily monitoring over a period of one year in Lake Taihu, China, included chlorophyll a (Chl-a) and nutrient measurements, determining the taxonomic composition of the phytoplankton community and various water column physicochemical parameters. Chl-a and nutrient concentrations showed strong circadian variations &amp;#8210; Chl-a rised during daylight hours, while ammonium and phosphate rised at night. Chl-a concentrations also showed strong seasonal variations, with one annual peak in spring and another from summer to autumn, dominated by Dolichospermum spp. and Microcystis spp. respectively. Temperature appeared to exert the most important effect in this species succession. A nutrient&amp;#8210;Chl-a balance calculation indicated that both nitrogen and phosphorus in the water column could be limiting factors for phytoplankton growth during bloom periods. Over two thirds of particulate nutrients was attributed to phytoplankton biomass during blooms. Daily (or weekly) monitoring data provided more precise description of water quality, capturing short-term peaks in phytoplankton biomass, and reduced risks of under- or overestimating trophic levels in lakes, which always happened when using monthly monitoring data.&lt;/p&gt;

scholarly journals Satellite-Derived Protein Concentration of Phytoplankton in the Southwestern East/Japan Sea

2021 ◽  
Vol 9 (2) ◽  
pp. 189
Author(s):  
Hyeonji Bae ◽  
Dabin Lee ◽  
Jae Joong Kang ◽  
Jae Hyung Lee ◽  
Naeun Jo ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Japan Sea ◽  
Biological Properties ◽  
Measured Data ◽  
Trophic Levels ◽  
Coefficient Of Determination ◽  
P Value ◽  
Chl A ◽  
Major Factors

The cellular macromolecular contents and energy value of phytoplankton as primary food source determine the growth of higher trophic levels, affecting the balance and sustainability of oceanic food webs. Especially, proteins are more directly linked with basic functions of phytoplankton biosynthesis and cell division and transferred through the food chains. In recent years, the East/Japan Sea (EJS) has been changed dramatically in environmental conditions, such as physical and chemical characteristics, as well as biological properties. Therefore, developing an algorithm to estimate the protein concentration of phytoplankton and monitor their spatiotemporal variations on a broad scale would be invaluable. To derive the protein concentration of phytoplankton in EJS, the new regional algorithm was developed by using multiple linear regression analyses based on field-measured data which were obtained from 2012 to 2018 in the southwestern EJS. The major factors for the protein concentration were identified as chlorophyll-a (Chl-a) and sea surface nitrate (SSN) in the southwestern EJS. The coefficient of determination (r2) between field-measured and algorithm-derived protein concentrations was 0.55, which is rather low but reliable. The satellite-derived estimation generally follows the 1:1 line with the field-measured data, with Pearson’s correlation coefficient, which was 0.40 (p-value < 0.01, n = 135). No remarkable trend in the long-term annual protein concentration of phytoplankton was found in the study area during our observation period. However, some seasonal difference was observed in winter protein concentration between the 2003–2005 and 2017–2019 periods. The algorithm is developed for the regional East/Japan Sea (EJS) and could contribute to long-term monitoring for climate-associated ecosystem changes. For a better understanding of spatiotemporal variation in the protein concentration of phytoplankton in the EJS, this algorithm should be further improved with continuous field surveys.

scholarly journals Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

2020 ◽  
Vol 13 (1) ◽  
pp. 30
Author(s):  
Wenlong Xu ◽  
Guifen Wang ◽  
Long Jiang ◽  
Xuhua Cheng ◽  
Wen Zhou ◽  
...  
Keyword(s):  
South China Sea ◽  
Chlorophyll A ◽  
South China ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
The South China Sea ◽  
Spatiotemporal Variability ◽  
The South ◽  
Chl A ◽  
China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

Predation by Sharks on the Grey Seal (Halichoerus grypus) in Eastern Canada

1983 ◽  
Vol 40 (3) ◽  
pp. 267-271 ◽  
Author(s):  
Paul Brodie ◽  
Brian Beck
Keyword(s):  
Key Words ◽  
Population Size ◽  
Halichoerus Grypus ◽  
Longline Fishery ◽  
Grey Seal ◽  
Eastern Canada ◽  
The Past ◽  
Harbour Seals ◽  
Commercially Important ◽  
Important Fish

The increase in population size of the grey seal (Halichoerus grypus) off eastern Canada over the past 20 yr may be attributed to a decrease in shark stocks, their supposed predators. Reduction of the shark population is presumed to have resulted from a directed longline fishery and, of greater significance, from a change in the fishery for swordfish (Xiphias gladius) from selective harpooning to pelagic longlining, which has produced a large bycatch of sharks. The resulting enhanced survival of grey seals is reflected in greater infestation of commercially important fish species by the codworm (Phocanema decipiens).Key words: grey seals, harbour seals, sharks, swordfish, codworm, predation, fisheries

Physical forcing and the dynamics of the pelagic ecosystem in the eastern tropical Pacific: simulations with ENSO-scale and global-warming climate drivers

2003 ◽  
Vol 60 (9) ◽  
pp. 1161-1175 ◽  
Author(s):  
George M Watters ◽  
Robert J Olson ◽  
Robert C Francis ◽  
Paul C Fiedler ◽  
Jeffrey J Polovina ◽  
...  
Keyword(s):  
Global Warming ◽  
Phytoplankton Biomass ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Trophic Levels ◽  
Eastern Tropical Pacific ◽  
Ecosystem Models ◽  
Pelagic Ecosystem ◽  
Physical Forcing ◽  
Physical Effects

We used a model of the pelagic ecosystem in the eastern tropical Pacific Ocean to explore how climate variation at El Niño – Southern Oscillation (ENSO) scales might affect animals at middle and upper trophic levels. We developed two physical-forcing scenarios: (1) physical effects on phytoplankton biomass and (2) simultaneous physical effects on phytoplankton biomass and predator recruitment. We simulated the effects of climate-anomaly pulses, climate cycles, and global warming. Pulses caused oscillations to propagate through the ecosystem; cycles affected the shapes of these oscillations; and warming caused trends. We concluded that biomass trajectories of single populations at middle and upper trophic levels cannot be used to detect bottom-up effects, that direct physical effects on predator recruitment can be the dominant source of interannual variability in pelagic ecosystems, that such direct effects may dampen top-down control by fisheries, and that predictions about the effects of climate change may be misleading if fishing mortality is not considered. Predictions from ecosystem models are sensitive to the relative strengths of indirect and direct physical effects on middle and upper trophic levels.

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