Seasonal Studies of the Phytoplankton Off Woods Hole, Massachusetts

Lillick, Lois C.

doi:10.2307/1537608

Cited by 43 publications

(11 citation statements)

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“…Blooms of large-celled species and chain-forming diatoms are more commonly found in fall and winter than at other times of year (e.g., Lillick 1937;Riley 1947;Glibert et al 1985). When analyzed with the approach described in this article, our Imaging FlowCytobot observations capture this seasonal transition in unprecedented detail.…”

Section: Fig 4 Grid Search Results Showing 10-fold Cross-validationmentioning

confidence: 90%

Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

Sosik

Olson

2007

Limnology & Ocean Methods

376

327

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High-resolution photomicrographs of phytoplankton cells and chains can now be acquired with imagingin-flow systems at rates that make manual identification impractical for many applications. To address the challenge for automated taxonomic identification of images generated by our custom-built submersible Imaging FlowCytobot, we developed an approach that relies on extraction of image features, which are then presented to a machine learning algorithm for classification. Our approach uses a combination of image feature types including size, shape, symmetry, and texture characteristics, plus orientation invariant moments, diffraction pattern sampling, and co-occurrence matrix statistics. Some of these features required preprocessing with image analysis techniques including edge detection after phase congruency calculations, morphological operations, boundary representation and simplification, and rotation. For the machine learning strategy, we developed an approach that combines a feature selection algorithm and use of a support vector machine specified with a rigorous parameter selection and training approach. After training, a 22-category classifier provides 88% overall accuracy for an independent test set, with individual category accuracies ranging from 68% to 99%. We demonstrate application of this classifier to a nearly uninterrupted 2-month time series of images acquired in Woods Hole Harbor, including use of statistical error correction to derive quantitative concentration estimates, which are shown to be unbiased with respect to manual estimates for random subsamples. Our approach, which provides taxonomically resolved estimates of phytoplankton abundance with fine temporal resolution (hours for many species), permits access to scales of variability from tidal to seasonal and longer.

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Section: Fig 4 Grid Search Results Showing 10-fold Cross-validationmentioning

confidence: 90%

Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

Sosik

Olson

2007

Limnology & Ocean Methods

376

327

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“…Other workers have monitored specific organic compounds such as amino acids (Riley and Segar, 1970) and hydrocarbons and fatty acids (Schultz and Quinn, 1977) in coastal regions and also noted the coincidence of specific compound level increases with phytoplankton blooms. Consequently, it would be expected that certain volatiles would increase in concentration during local spring (and fall) algal blooms (Fish, 19l1;Lillick, 1937;Yentsch and Ryther, 1959).…”

Section: Sumrymentioning

confidence: 99%

Volatile organic compounds in seawater

Gschwend¹

1979

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“…In Long Island Sound, with a mean depth of 20 m, January and February increases have been obscrvcd by Riley (1956). In depths of 30 m, maxima have been reported in late January in the coastal water south of Woods Hole (Lillick 1937) and in late February in Block Island Sound (Riley 1952). The vernal augmentation begins in March in waters of 30 to 55 m on Georgcs Bank (Riley 1941).…”

Section: Ecology Of the Seasonal Cyclementioning

confidence: 99%

Phytoplankton of the North Central Sargasso Sea, 1950–521

Riley¹

1957

Limnology & Oceanography

322

168

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ADSTRACT U. S. Weather Ship personnel operating at Lat. 35"N, Long. 48"W obtained approximately weekly collections of water samples for phytoplankton enumeration at five depths between 0 and 150 m for a two-year period beginning in February, 1950. Temperature and Secchi disk measurements and zooplankton collections also were made. The average concentration of phytoplankton was sparse, but it extended through a long vertical column, in agreement with previous observations.There was a diatom increase in April of each year, which appeared to be analogous to the vernal augmentation in temperate waters although of miniature size. The seasonal minimum occurred in autumn, and the population tended to be larger in winter than in summer. Destruction of the seasonal thermocline between December and March presumably increased the rate of nutrient supply at that season, but light and turbulence were critical factors. Hence the development of winter diatom pulses was correlated with the stability of the water column. The species composition was mainly subtropical or ubiquitous, but occasional localized concentrations of temperate-water diatoms suggested eddy transfer from the north. Analysis of previous oceanographic observations in the region by three independent methods indicated an average daily rate of net phytoplankton production of about 0.15 g carbon per m2 of sea surface, or a quarter to a third of the observed rates in highly productive temperate waters.

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Seasonal Studies of the Phytoplankton Off Woods Hole, Massachusetts

Cited by 43 publications

References 0 publications

Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

Volatile organic compounds in seawater

Phytoplankton of the North Central Sargasso Sea, 1950–521

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