Phytoplankton and Planktonic Protozoa of the Offshore Waters of the Gulf of Maine

Bigelow, Henry B.; Lillick, Lois C.; Sears, Mary

doi:10.2307/1005545

Cited by 53 publications

(17 citation statements)

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“…The genera Parafavella and Ptychocylis are typical components of the plankton of northern hemisphere cold waters . These genera are common in the Gulf of Maine (Bigelow et al 1940) and its estuaries (Sanders 1987), and have also been found in Narragansett Bay (Verity 1987) and Long Island Sound (Gold & Morales 1975b) as rare vagrants in the winter months. If the Cape Cod …”

Section: Discussionmentioning

confidence: 98%

Plankton studies in Buzzards Bay, Massachusetts, USA. IV. Tintinnids, 1987 to 1988

Pierce¹,

Turner²

1994

Mar. Ecol. Prog. Ser.

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Tintinnids were collected from Buzzards Bay. Massachusetts. USA, from October 1987 to September 1988. Tintinnids were collected by screening 3 1 of seawater with a 20 pm mesh. Eight stations throughout the bay were sampled at monthly or twice-monthly intervals. A total of 30 species of tlntinnids were recorded, half of which were members of the genus Tintinnopsis. Tintinnid abundances ranged from 0 to 3.3 X 103 cells I-'. Tintinnlds were least abundant at the Cape Cod Canal and in northern Buzzards Bay, and most abundant at the New Bedford sewage outfall. Unlike dinoflagellates, tintinnids did not show higher abundances in New Bedford Harbor than in the main part of the bay. The effect of screening tintinnid samples with a 20 pm mesh screen was examined by comparisons of abundance of tintinnids in screened and unscreened whole-water samples concentrated by gravitational sedimentation. Tintinnid abundance estimates were significantly higher in the screened samples.

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Section: Discussionmentioning

confidence: 98%

Plankton studies in Buzzards Bay, Massachusetts, USA. IV. Tintinnids, 1987 to 1988

Pierce¹,

Turner²

1994

Mar. Ecol. Prog. Ser.

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“…The timing of spring blooms is naturally variable (Bigelow et al 1940) and often very difficult to determine exactly, because mostly data are not resolved highly enough (i.e., under a week) to allow more than a subjective analysis. This is compounded by the fact that phytoplankton blooms are also difficult to describe mathematically from in situ data (see also Rolinski et al 2007).…”

Section: Discussionmentioning

confidence: 99%

Resilience of North Sea phytoplankton spring bloom dynamics: An analysis of long‐term data at Helgoland Roads

Wiltshire

Malzahn

Wirtz³

et al. 2008

Limnology & Oceanography

264

235

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Analyzing one of the most extensive long-term data series in the North Sea, the Helgoland Roads time series, we investigated the changes in the factors that potentially drive phytoplankton bloom dynamics in the German Bight. We compared the changes in these factors with the changes in the spring bloom phenology. We combined zooplankton, nutrient, weather, and phytoplankton data to analyze whether there has been a shift in trophic interactions in the North Sea affecting the spring bloom timing. The potential influence of temperature, with a mean increase of 1.5uC, was investigated. We showed that the German Bight around Helgoland is a highly dynamic system and has undergone considerable change in the last 30 yr. Nutrient levels, temperature, underwater light climate and wind speed have all changed. However, the spring bloom dynamics have hardly changed at all. We showed that the spring bloom tends to come later in warmer years but that this is not directly correlated with the overall warming trend. The known regime shift of the late 1980s is clearly visible in our data in terms of average phytoplankton winter densities and average cell size, but even so the start of the spring bloom has not changed.

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“…Understanding phytoplankton bloom dynamics and its relationship with environmental factors has long been the focus of ecosystem studies in the Gulf of Maine and adjacent regions (e.g. Bigelow 1926, Bigelow et al 1940, Cushing 1959, Townsend & Spinard 1986, Thomas et al 2003, Ji et al 2006. In recent years, interannual variations of phytoplankton bloom dynamics have been better detected with the help of field surveys (e.g.…”

Section: Introductionmentioning

confidence: 99%

Interannual variability in phytoplankton blooms and plankton productivity over the Nova Scotian Shelf and in the Gulf of Maine

Song¹,

Ji²,

Stock³

et al. 2011

Mar. Ecol. Prog. Ser.

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A 1D ecosystem model, driven by surface heat and wind forcing and relaxed toward observed salinity profiles, was applied to simulate the interannual and decadal scale variability of phytoplankton blooms and plankton production from 1984 to 2007 in the Nova Scotian Shelf (NSS) and Gulf of Maine (GoM) region. The model captured the mean observed timing and magnitude of the spring (SPB) and fall phytoplankton bloom (FPB) in both systems, as well as observed interannual variations in SPB peak timing. Model simulations for both the GoM and NSS exhibited marked interannual variability in SPB and FPB timing (± 2 to 3 wk) and magnitude (up to ~1 mg chlorophyll m -3 ). Earlier SPBs and delayed FPBs are linked to enhanced water column stability generated by less saline surface water or sharper salinity gradients over the top 50 m of the water column. The modeled variation in annual primary productivity, mesozooplankton productivity, and particle export flux was modest (<10% of the mean). Years with high primary production were weakly associated with early SPBs (GoM: r = -0.205; NSS: r = -0.51), but there was no significant relationship with water column stability. This suggests that variation in annual productivity in the GoM and NSS reflects a combination of variation in light limitation (which is alleviated by increased water column stability) and nutrient limitation (which is exacerbated by increased water column stability) that offset and are of near equal importance when averaged over the year. Interannual variations in fisheries production due to changes in annual productivity are thus likely secondary to profound shifts in fisheries recruitment and production that have been linked to variations in SPB and FPB timing. KEY WORDS: Phytoplankton bloom · Interannual variability · Modeling · Nova Scotian Shelf · Gulf of Maine Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 426: [105][106][107][108][109][110][111][112][113][114][115][116][117][118] 2011 related environmental change might have caused significant decadal shifts in the state of the pelagic ecosystems in the NSS-GoM region (e.g. Durbin et al. 2003, Frank et al. 2005, Greene & Pershing 2007, Ji et al. 2007), presumably through a bottom-up process. Understanding phytoplankton bloom dynamics and its relationship with environmental factors has long been the focus of ecosystem studies in the Gulf of Maine and adjacent regions (e.g. Bigelow 1926, Bigelow et al. 1940, Cushing 1959, Townsend & Spinard 1986, Thomas et al. 2003, Ji et al. 2006. In recent years, interannual variations of phytoplankton bloom dynamics have been better detected with the help of field surveys (e.g. Durbin et al. 2003) and advances in technology such as remote sensing (e.g. Thomas et al. 2003, Ji et al. 2007) and continuous plankton recorders (e.g. Sameoto 2001, Greene & Pershing 2007. Most of these recent studies have focused on the spring phytoplankton bloom (SPB). There has been little analysis of the potential impacts of c...

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Phytoplankton and Planktonic Protozoa of the Offshore Waters of the Gulf of Maine

Cited by 53 publications

References 0 publications

Plankton studies in Buzzards Bay, Massachusetts, USA. IV. Tintinnids, 1987 to 1988

Plankton studies in Buzzards Bay, Massachusetts, USA. IV. Tintinnids, 1987 to 1988

Resilience of North Sea phytoplankton spring bloom dynamics: An analysis of long‐term data at Helgoland Roads

Interannual variability in phytoplankton blooms and plankton productivity over the Nova Scotian Shelf and in the Gulf of Maine

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