Temporal and spatial variability of coccolithophore blooms in the eastern Bering Sea, 1998-2001

Iida, Takuya; Saitoh, Setsuo; Miyamura, T.; Toratani, Mitsuhiro; Fukushima, Hajime; Shiga, Naonobu

doi:10.1016/s0079-6611(02)00076-9

Cited by 43 publications

(34 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PIC estimates suggest that coccolithophores are very abundant from March to October and reach a maximum in September. It appears that both NOBM and the bio-optical algorithm attribute much of the summer and fall Chl to diatoms rather than coccolithophores, in contrast to in situ (Iida et al, 2002) and remote sensing observations (Fig. 8c).…”

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 70%

“…6c), yet its monthly climatology is closer to the one revealed by PIC and in situ data compared to NOBM and the bio-optical model. It is puzzling, however, that PIC does not reveal a maximum spring coccolithophore peak seen in Iida et al (2002) and simulated by all the models. Regardless of the discrepancies between timing and magnitude of diatom and coccolithophore blooms in the NEPac, it is clear that PhytoANN correctly predicts that coccolithophores are at least as dominant as diatoms in the region.…”

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 82%

“…Analyzing the seasonality of coccolithophore blooms in the Bering Sea, Iida et al (2002) found significant interannual variability in the peak areal coverage between 1998 and 2001. The general pattern, however, suggested a spring peak between April and May and a fall peak between August and September.…”

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 99%

See 2 more Smart Citations

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

et al. 2013

View full text Add to dashboard Cite

Abstract.Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and biooptical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phytoPFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom-coccolithophore coexistence in the subpolar highnitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

show abstract

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 70%

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 82%

Section: A P Palacz Et Al: Ecological Indicators Of Pfts In Hnlc Wmentioning

confidence: 99%

See 1 more Smart Citation

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

et al. 2013

View full text Add to dashboard Cite

show abstract

“…At the same time, coccolithophores and prasinophytes, having higher half-saturation constants for light-dependent growth, are likely to increase under this scenario at NABE (Table 7). Stimulation of coccolithophores by prolonged stratification has been observed in the Bering Sea, where an unusually long stratification period in 1997 and 1998 had lead to massive coccolithophore blooms (Napp and Hunt, 2001;Iida et al, 2002). Recent global satellite data analysis also showed strong association of coccolithophore blooms with highly stratified conditions (Iglesias-Rodrígues et al, 2002).…”

Section: Discussionmentioning

confidence: 98%

Multi-nutrient, multi-group model of present and future oceanic phytoplankton communities

et al. 2006

View full text Add to dashboard Cite

Abstract. Phytoplankton community composition profoundly affects patterns of nutrient cycling and the dynamics of marine food webs; therefore predicting present and future phytoplankton community structure is crucial to understand how ocean ecosystems respond to physical forcing and nutrient limitations. We develop a mechanistic model of phytoplankton communities that includes multiple taxonomic groups (diatoms, coccolithophores and prasinophytes), nutrients (nitrate, ammonium, phosphate, silicate and iron), light, and a generalist zooplankton grazer. Each taxonomic group was parameterized based on an extensive literature survey. We test the model at two contrasting sites in the modern ocean, the North Atlantic (North Atlantic Bloom Experiment, NABE) and subarctic North Pacific (ocean station Papa, OSP). The model successfully predicts general patterns of community composition and succession at both sites: In the North Atlantic, the model predicts a spring diatom bloom, followed by coccolithophore and prasinophyte blooms later in the season. In the North Pacific, the model reproduces the low chlorophyll community dominated by prasinophytes and coccolithophores, with low total biomass variability and high nutrient concentrations throughout the year. Sensitivity analysis revealed that the identity of the most sensitive parameters and the range of acceptable parameters differed between the two sites. We then use the model to predict community reorganization under different global change scenarios: a later onset and extended duration of stratification, with shallower mixed layer depths due to increased greenhouse gas concentrations; increase in deep water nitrogen; decrease in deep water phosphorus and increase or decrease in iron concentration. To estimate uncertainty in our predictions, we used a Monte Carlo sampling of the parameter space where future scenarios were run using parameter combinations that produced acceptable modern day outcomes and the robustCorrespondence to: E. Litchman (litchman@msu.edu) ness of the predictions was determined. Change in the onset and duration of stratification altered the timing and the magnitude of the spring diatom bloom in the North Atlantic and increased total phytoplankton and zooplankton biomass in the North Pacific. Changes in nutrient concentrations in some cases changed dominance patterns of major groups, as well as total chlorophyll and zooplankton biomass. Based on these scenarios, our model suggests that global environmental change will inevitably alter phytoplankton community structure and potentially impact global biogeochemical cycles.

show abstract

“…The eight sub-cores collected at each site were used for various chemical and biological (diatom assemblage) analyses, with the longest sub-core being used for organic matter analysis ( Figure 1 and Table 1). A coccolithophorid bloom-specific algorithm [Iida et al, 2002] was used to identify large coccolithophorid blooms over the middle and inner continental shelf on SeaWiFS images (Figure 1). This algorithm allows accurate estimation of the spatial and temporal distributions of coccolithophorid blooms, although areas of "bright" color observed by SeaWiFS are not always indicative of coccolithophorid blooms because the water color produced by substantial empty and broken diatom frustules can mimic the appearance of E. huxleyi blooms [Broerse et al, 2003].…”

Section: Sediment Coresmentioning

confidence: 99%

Enhancement of coccolithophorid blooms in the Bering Sea by recent environmental changes

Harada

Sato

Oguri

et al. 2012

Global Biogeochemical Cycles

View full text Add to dashboard Cite

[1] Since 1997, ocean color satellite images have revealed large-scale blooms of the coccolithophorid Emiliania huxleyi in the eastern Bering Sea. The blooms are often sustained over several months and have caused ecosystem changes in the Arctic Ocean, as well as in the Bering Sea. We examined continental shelf sediment profiles of alkenone, a biomarker for E. huxleyi, covering the past $70 years. The alkenone records suggest that large E. huxleyi blooms are a novel feature in the Bering Sea as they have occurred only since the late 1970s. Recent changes in alkenone content were closely related to the 1976-77 climatic regime shift in the North Pacific, implying that warming and freshening of Bering Sea waters promoted E. huxleyi blooms. The production rate of diatoms (total valves in sediment samples), the dominant primary producers in the Bering Sea, also increased during the past several decades. However, the ratio of alkenone content to total diatom valves in the sediments increased as E. huxleyi production increased, suggesting that the increase in the E. huxleyi production rate frequently exceeded the increase in the diatom production rate. Overall, our results indicate a possible subarctic region ecosystem shift driven by climate change.

show abstract

Temporal and spatial variability of coccolithophore blooms in the eastern Bering Sea, 1998-2001

Cited by 43 publications

References 13 publications

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

Multi-nutrient, multi-group model of present and future oceanic phytoplankton communities

Enhancement of coccolithophorid blooms in the Bering Sea by recent environmental changes

Contact Info

Product

Resources

About