Relevant bibliographies by topics / Spring bloom

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Spring bloom'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Spring bloom"

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Chiswell, Stephen M., Karl A. Safi, Sylvia G. Sander, Robert Strzepek, Michael J. Ellwood, Angela Milne, and Philip W. Boyd. "Exploring mechanisms for spring bloom evolution: contrasting 2008 and 2012 blooms in the southwest Pacific Ocean." Journal of Plankton Research 41, no. 3 (January 9, 2018): 329–48. http://dx.doi.org/10.1093/plankt/fbz017.

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AbstractObservations from two research cruises made in 2008 and 2012 to east of New Zealand are put into context with satellite data to contrast and compare surface chlorophyll a evolution in the two years in order to explore mechanisms of phytoplankton bloom development in the southwest Pacific Ocean. In 2008, surface chlorophyll a largely followed the long-term climatological cycle, and 2008 can be considered a canonical year, where the autumn bloom is triggered by increasing vertical mixing at the end of summer and the spring bloom is triggered by decreasing vertical mixing at the end of winter. In contrast, 2012 was anomalous in that there was no autumn bloom, and in early spring there were several periods of sustained increase in surface chlorophyll a that did not become fully developed spring blooms. (In this region, we consider spring blooms to occur when surface chlorophyll a exceeds 0.5 mg m-3). These events can be related to alternating episodes of increased or decreased vertical mixing. The eventual spring bloom in October was driven by increased ocean cooling and wind stress (i.e. increased mixing) and paradoxically was driven by mechanisms considered more appropriate for autumn rather than spring blooms.
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Record, Nicholas R., William M. Balch, and Karen Stamieszkin. "Century-scale changes in phytoplankton phenology in the Gulf of Maine." PeerJ 7 (May 2, 2019): e6735. http://dx.doi.org/10.7717/peerj.6735.

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The phenology of major seasonal events is an important indicator of climate. We analyzed multiple datasets of in situ chlorophyll measurements from the Gulf of Maine dating back to the early 20th century in order to detect climate-scale changes in phenology. The seasonal cycle was consistently characterized by a two-bloom pattern, with spring and autumn blooms. The timing of both spring and autumn blooms has shifted later in the year at rates ranging from ∼1 to 9 days per decade since 1960, depending on the phenology metric, and trends only emerged at time scales of >40 years. Bloom phenology had only weak correlations with major climate indices. There were stronger associations between bloom timing and physical and chemical variables. Autumn bloom initiation correlated strongly with surface temperature and salinity, and spring bloom with nutrients. A later spring bloom also correlated with an increased cohort ofCalanus finmarchicus, suggesting broader ecosystem implications of phytoplankton phenology.
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Mignot, A., R. Ferrari, and K. A. Mork. "Spring bloom onset in the Nordic Seas." Biogeosciences Discussions 12, no. 16 (August 21, 2015): 13631–73. http://dx.doi.org/10.5194/bgd-12-13631-2015.

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Abstract. The North Atlantic spring bloom is a massive annual growth event of marine phytoplankton, tiny free-floating algae that form the base of the ocean's food web and generates a large fraction of the global primary production of organic matter. The conditions that trigger the onset of the spring bloom in the Nordic Seas, at the northern edge of the North Atlantic, are studied using in-situ data from five bio-optical floats released above the Arctic Circle. It is often assumed that spring blooms start as soon as phytoplankton cells daily irradiance is sufficiently abundant that division rates exceed losses. The bio-optical float data instead suggest the tantalizing hypothesis that Nordic Seas blooms start when the photoperiod, the number of daily light hours experienced by phytoplankton, exceeds a critical value, independently of division rates. This bloom behavior may be explained by realizing that photosynthesis is impossible during polar nights and phytoplankton enters in a dormant stage in winter, only to be awaken by a photoperiodic trigger. While the first accumulation of biomass recorded by the bio-optical floats is consistent with the photoperiod hypothesis, it is possible that some biomass accumulation started before the critical photoperiod but at levels too low to be detected by the fluorometers. Thus more precise observations are needed to test the photoperiod hypothesis.
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Dickman, Steven. "The flowers that bloom next spring." Nature 339, no. 6223 (June 1989): 325. http://dx.doi.org/10.1038/339325c0.

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Tracy, Sarah J. "Buds Bloom in a Second Spring." Qualitative Inquiry 22, no. 1 (September 10, 2015): 17–24. http://dx.doi.org/10.1177/1077800415603397.

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Brody, Sarah R., and M. Susan Lozier. "Characterizing upper-ocean mixing and its effect on the spring phytoplankton bloom with in situ data." ICES Journal of Marine Science 72, no. 6 (February 4, 2015): 1961–70. http://dx.doi.org/10.1093/icesjms/fsv006.

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Abstract Since publication, the Sverdrup hypothesis, that phytoplankton are uniformly distributed within the ocean mixed layer and bloom once the ocean warms and stratifies in spring, has been the conventional explanation of subpolar phytoplankton spring bloom initiation. Recent studies have sought to differentiate between the actively mixing section of the upper ocean and the uniform-density mixed layer, arguing, as Sverdrup implied, that decreases in active mixing drive the spring bloom. In this study, we use in situ data to investigate the characteristics and depth of active mixing in both buoyancy- and wind-driven regimes and explore the idea that the shift from buoyancy-driven to wind-driven mixing in the late winter or early spring creates the conditions necessary for blooms to begin. We identify the bloom initiation based on net rates of biomass accumulation and relate changes in the depth of active mixing to changes in biomass depth profiles. These analyses support the idea that decreases in the depth of active mixing, a result of the transition from buoyancy-driven to wind-driven mixing, control the timing of the spring bloom.
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Mignot, Alexandre, Raffaele Ferrari, and Kjell Arne Mork. "Spring bloom onset in the Nordic Seas." Biogeosciences 13, no. 11 (June 15, 2016): 3485–502. http://dx.doi.org/10.5194/bg-13-3485-2016.

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Abstract. The North Atlantic spring bloom is a massive annual growth event of marine phytoplankton, tiny free-floating algae that form the base of the ocean's food web and generates a large fraction of the global primary production of organic matter. The conditions that trigger the onset of the spring bloom in the Nordic Seas, at the northern edge of the North Atlantic, are studied using in situ data from six bio-optical floats released north of the Arctic Circle. It is often assumed that spring blooms start as soon as phytoplankton cells daily irradiance is sufficiently abundant that division rates exceed losses. The bio-optical float data instead suggest the tantalizing hypothesis that Nordic Seas blooms start when the photoperiod, the number of daily light hours experienced by phytoplankton, exceeds a critical value, independently of division rates. The photoperiod trigger may have developed at high latitudes where photosynthesis is impossible during polar nights and phytoplankton enters into a dormant stage in winter. While the first accumulation of biomass recorded by the bio-optical floats is consistent with the photoperiod hypothesis, it is possible that some biomass accumulation started before the critical photoperiod but at levels too low to be detected by the fluorometers. More precise observations are needed to test the photoperiod hypothesis.
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Groetsch, Philipp M. M., Stefan G. H. Simis, Marieke A. Eleveld, and Steef W. M. Peters. "Spring blooms in the Baltic Sea have weakened but lengthened from 2000 to 2014." Biogeosciences 13, no. 17 (September 8, 2016): 4959–73. http://dx.doi.org/10.5194/bg-13-4959-2016.

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Abstract. Phytoplankton spring bloom phenology was derived from a 15-year time series (2000–2014) of ship-of-opportunity chlorophyll a fluorescence observations collected in the Baltic Sea through the Alg@line network. Decadal trends were analysed against inter-annual variability in bloom timing and intensity, and environmental drivers (nutrient concentration, temperature, radiation level, wind speed).Spring blooms developed from the south to the north, with the first blooms peaking mid-March in the Bay of Mecklenburg and the latest bloom peaks occurring mid-April in the Gulf of Finland. Bloom duration was similar between sea areas (43 ± 2 day), except for shorter bloom duration in the Bay of Mecklenburg (36 ± 11 day). Variability in bloom timing increased towards the south. Bloom peak chlorophyll a concentrations were highest (and most variable) in the Gulf of Finland (20.2 ± 5.7 mg m−3) and the Bay of Mecklenburg (12.3 ± 5.2 mg m−3).Bloom peak chlorophyll a concentration showed a negative trend of −0.31 ± 0.10 mg m−3 yr−1. Trend-agnostic distribution-based (Weibull-type) bloom metrics showed a positive trend in bloom duration of 1.04 ± 0.20 day yr−1, which was not found with any of the threshold-based metrics. The Weibull bloom metric results were considered representative in the presence of bloom intensity trends.Bloom intensity was mainly determined by winter nutrient concentration, while bloom timing and duration co-varied with meteorological conditions. Longer blooms corresponded to higher water temperature, more intense solar radiation, and lower wind speed. It is concluded that nutrient reduction efforts led to decreasing bloom intensity, while changes in Baltic Sea environmental conditions associated with global change corresponded to a lengthening spring bloom period.
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Lewandowska, Aleksandra M., Maren Striebel, Ulrike Feudel, Helmut Hillebrand, and Ulrich Sommer. "The importance of phytoplankton trait variability in spring bloom formation." ICES Journal of Marine Science 72, no. 6 (April 9, 2015): 1908–15. http://dx.doi.org/10.1093/icesjms/fsv059.

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Abstract About 60 years ago, the critical depth hypothesis was proposed to describe the occurrence of spring phytoplankton blooms and emphasized the role of stratification for the timing of onset. Since then, several alternative hypotheses appeared focusing on the role of grazing and mixing processes such as turbulent convection or wind activity. Surprisingly, the role of community composition—and thus the distribution of phytoplankton traits—for bloom formation has not been addressed. Here, we discuss how trait variability between competing species might influence phytoplankton growth during the onset of the spring bloom. We hypothesize that the bloom will only occur if there are species with a combination of traits fitting to the environmental conditions at the respective location and time. The basic traits for formation of the typical spring bloom are high growth rates and photoadaptation to low light conditions, but other traits such as nutrient kinetics and grazing resistance might also be important. We present concise ideas on how to test our theoretical considerations experimentally. Furthermore, we suggest that future models of phytoplankton blooms should include both water column dynamics and variability of phytoplankton traits to make realistic projections instead of treating the phytoplankton bloom as an aggregate community phenomenon.
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Kristiansen, S., T. Farbrot, and LJ Naustvoll. "Spring bloom nutrient dynamics in the Oslofjord." Marine Ecology Progress Series 219 (2001): 41–49. http://dx.doi.org/10.3354/meps219041.

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Dissertations / Theses on the topic "Spring bloom"

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Hemmings, John Christopher Paul. "Quantitative modelling of spatial variability in the north Atlantic spring phytoplankton bloom." Thesis, University of Southampton, 1999. https://eprints.soton.ac.uk/42095/.

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The effects of variability in the physical environment on the development of the spring phytoplankton bloom are investigated using a physically forced model of the annual plankton cycle in the ocean mixed layer. The model is optimised to fit survey data from the eastern North Atlantic, collected over a 1500 x 1500 km area between 39N and 54N, from April-June 1991, establishing the feasibility of using spatially distributed point-in-time data in model calibration. Measurements made below the seasonal pycnocline show the existence of an empirical relationship between preformed nitrate and salinity in this area, allowing salinity-based estimates of pre-bloom mixed layer nitrate concentration to be made. These estimates provide important additional constraints for the model. The observed spatio-temporal patterns, at scales between 36 km and 1500 km, in nutrients, chlorophyll and measures of bloom progression derived from these data with reference to pre-bloom nitrate are discussed, together with the corresponding patterns in seasonal stratification. During the spring bloom, when biogeochemical concentrations vary rapidly in response to the developing stratification, absence of data defining its history limits the value of comparison between point-in-time observations and model results. Predictions of variation in stratification at the seasonal time-scale from general circulation models (GCMs) can be used in place of observational data to force ecosystem models. However, the degree to which observations are used to constrain the model solutions should allow for both model error in stratification and misrepresentation of the seasonal development of stratification by the observations. The latter occurs due to sampling error associated with short-term fluctuations. It can be corrected for if a suitable contemporary sea surface temperature data set is available to define the variation of mixed layer temperature at the seasonal time-scale. It is shown that the accuracy of the GCM predictions can be improved by the application of meteorology specific to the year of observation. It is also shown that the sensitivity of the ecosystem model predictions to error in the physical forcing can be reduced by matching model and observations by a stratification measure, rather than by time, when comparing fields. The survey data show an important contribution to the stratification arising from the 'tilting' action of vertical shear on pre-existing horizontal buoyancy gradients in the winter¬ time mixed layer. This effect was severely underestimated by the GCM. The discrepancy can be accounted for by the absence of density fronts and mesoscale dynamics in the model. Ecosystem model results suggest that spatial variance in Zooplankton grazing, due to the effect of differences in the depth and duration of winter-time mixing on the over-wintering success of plankton populations, is one of the major factors controlling the spatial and temporal characteristics of the phytoplankton bloom.
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Henson, Stephanie Anne. "Physical controls on spring bloom dynamics in the Irminger Basin, North Atlantic." Thesis, University of Southampton, 2005. https://eprints.soton.ac.uk/25128/.

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Much of the primary production in northern latitudes is associated with the relatively short spring phytoplankton bloom. Quantifying the bloom is essential to understanding export production and energy transfer to higher trophic levels. This study focuses on the physical forcing controlling the spring bloom in the Irminger Basin (IB), situated between Greenland and Iceland. In situ data are available from four cruises to the region carried out under the UK Marine Productivity programme. This data set is extended with six years of SeaWiFS satellite chlorophyll-a concentration (chl-a) data, together with the corresponding model net heat flux (NCEP reanalysis) and satellite measured wind speed (QuikSCAT), sea surface temperature (SST; AVHRR) and photosynthetically available radiation (PAR; SeaWiFS). The remotely sensed data are complemented by a 1-D vertical mixing model and temperature and salinity profiles from Argo drifting profilers. The seasonality in temperature-nutrient (TN) relationships is investigated and the TN relationships are improved by including chlorophyll in the regressions. Basin-wide, daily estimates of nitrate, phosphate and silicate are made from satellite SST and chl-a. The study focuses on three biogeographical zones determined by cluster and Empirical Orthogonal Function analysis of SeaWiFS chl-a data. The three areas have distinct chl-a signatures and cover the East Greenland shelf, the Reykjanes Ridge and the Central Basin. An ANOVA analysis reveals that significant interannual variability is occurring in chlorophyll-a. An objective method for determining the start day of the spring bloom is described. Interannual variability in the timing of the initiation of the bloom and its magnitude and duration is discussed. The influence of the prevailing meteorology on chl-a in different seasons are investigated using generalized linear modelling. Whilst net heat flux and PAR are the dominating factors in spring, wind speed and SST become increasingly influential during summer and autumn. A method for estimating time series of Sverdrup’s critical depth from remotely sensed PAR and attenuation coefficient data is outlined. It is found that the spring bloom never begins before the mixed layer depth becomes shallower than the critical depth, and there is a delay of ~10 days. Specific criteria for the start of the bloom in terms of net heat flux and PAR are determined. The effect of nutrient depletion on the decline of the bloom is discussed. The East Greenland coastal zone is used as an example of the lasting impact that anomalous meteorological conditions can have on the following spring’s bloom. In 2002 the East Greenland region experienced anomalously low chl-a concentrations. Strong easterly winds, associated with the tip-jet phenomena, occurred throughout winter and spring and net heat flux was anomalously low in 2002. The spring bloom in the Irminger Basin can be affected by large scale climatic events, such as shifts in the North Atlantic Oscillation. Finally, the timing of nutrient depletion and its impact on community succession is considered. The possibility of iron limitation in the basin is discussed. A lower bound estimate of export production is made based on the timing of silica availability, and hence diatom dominance, of the spring bloom. The contributions to export production by diatoms and non-diatoms are estimated.
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Tian, Tian [Verfasser]. "Spring bloom dynamics in a coastal marine ecosystem : identification of key processes / Tian Tian." Kiel : Universitätsbibliothek Kiel, 2011. http://d-nb.info/1020166770/34.

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Wolfe, Megan Amelia. "Impact of wind and river flow on the timing of the Rivers Inlet spring phytoplankton bloom." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27081.

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The primary objective of this masters study is to develop an understanding of the physical processes driving the timing of the spring phytoplankton bloom in Rivers Inlet. The spring bloom is initiated as light limitation is lifted causing an increase in growth which overcomes loses due to grazing and advection. The bloom is terminated by nitrate exhaustion. The physical system can impact the spring bloom through variations of winds, cloud coverage, and river input. Strong winds showed two effects. First, strong winds increased the mixing layer depth which decreased the amount of light available for phytoplankton, thus delaying the timing of the spring bloom. Second, large outflow winds caused flushing events to occur resulting in rapid horizontal advection removing the plankton population from the area. River discharge has two opposite effects on the timing of the spring bloom. High river discharge causes the water column to stratify, reducing the mixing layer depth which provides more light available for growth and results in an earlier bloom. High discharge will also result in higher upwelling advection leading to a larger advective loss term for phytoplankton, delaying the bloom. Changes in cloud coverage will directly affect the incoming solar radiation and the light available for photosynthesis. A coupled bio-physical model is used to explore the driving forces involved in the timing of the spring phytoplankton bloom in Rivers Inlet, British Columbia, Canada. The primary control on the timing of the spring bloom in Rivers Inlet is wind speed and direction. Secondary control on the timing is due to freshwater flow; high river discharge delays the bloom in Rivers Inlet. Single outflow wind events can result in a 7 day delay in the bloom timing. The shift in bloom timing resulting from multiple outflow wind events is greater than the sum of the individual wind events. Implications of flushing events in fjords along the British Columbia coastline are also discussed.
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Bárbulo, Diego. "Influence of sea ice seeding on the spring phytoplankton bloom : An experimental study in the Gulf of Bothnia." Thesis, Umeå universitet, Institutionen för ekologi, miljö och geovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-148586.

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The influence of sea ice seeding on the northern Baltic Sea´s pelagic phytoplankton spring bloom was studied in a laboratory experiment in which microcosms mimicked sea conditions. On March 26th, 2018, samples (ice cores and seawater) were taken from land-fast ice at a coastal station in the Gulf of Bothnia. The seeding experiment lasted for 9 days, during which a 12:12 hours light:dark incubation took place. Four different treatments (two with ice and two without it) were set up in twelve incubated microcosms. Samples for analyses were taken on days 0, 3, 6 and 9. On day 0, measurements were carried out on four melted ice cores and on seawater. On the remaining days analyses were performed on the incubated microcosms. The measured variables were: chlorophyll a, phytoplankton abundance, bacterial abundance, conductivity and nutrients (TDN and TDP). The most abundant algal species were identified in a qualitative analysis. The obtained data were processed to calculate the average and standard deviations and to assess the existence of statistically significant differences among the treatments. A significant increase in chlorophyll a, phytoplankton and heterotrophic bacteria abundances was detected. A parallel decline in the nutrient concentrations was observed. A relationship between phytoplankton´s degree of influence and cell-size is suggested: cells > 3µm were more abundant in ice than in seawater, and the opposite tendency was appreciated for cells < 3 µm. My study shows that sea ice seeding can have a marked seeding effect on the size structure of the spring phytoplankton bloom.
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Anthony, Brooke Allen Murray Bruce A. "Making students' writing bloom the effect of scaffolding oral inquiry using Bloom's taxonomy on writing in response to reading and reading comprehension of fifth graders /." Auburn, Ala., 2007. http://repo.lib.auburn.edu/EtdRoot/2007/SPRING/Curriculum_and_Teaching/Dissertation/Brooks_Anthony_dissertation.pdf.

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Luengen, Allison Christine. "Investigating the spring bloom in San Francisco Bay : links between water chemistry, metal cycling, mercury speciation, and phytoplankton community composition /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2007. http://uclibs.org/PID/11984.

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Schock, Kevin A. "An analysis of a persistent isotherm tilt during early-spring and its effect on the diatom bloom : Lake Washington, Seattle, WA /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/10177.

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Hobbs, Erin B. "Distribution and feeding behavior of early life stages of the northern shrimp, Pandalus borealis, in relation to the spring phytoplankton bloom in the western Gulf of Maine /." Restricted access (UM), 2008. http://libraries.maine.edu/gateway/oroauth.asp?file=orono/etheses/37803141.pdf.

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Seward, Lindsay C. N. "The Relationship between Green Sea Urchin Spawning, Spring Phytoplankton Blooms, and the Winter-Spring Hydrography at Selected Sites in Maine." Fogler Library, University of Maine, 2002. http://www.library.umaine.edu/theses/pdf/SewardLCN2002.pdf.

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Books on the topic "Spring bloom"

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Woodworth, Viki. Do zebras bloom in the spring? Plymouth, MN: Child's World, 1998.

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Cimarusti, Marie Torres. Peek-a-bloom! New York: Dutton Children's Books, 2010.

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Walsh, John Joseph. Satellite detection of phytoplankton export from the Mid-Atlantic Bight during the 1979 spring bloom. [Washington DC: National Aeronautics and Space Administration, 1986.

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H, Miller Robert. Frog Lake: A spring of blood. Warburg, Alta: Tipi Pub., 2006.

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Saratoga in bloom: 150 years of glorious gardens. Camden, Me: Down East Books, 2010.

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Durschmied, Erik. Blood of Revolution: From the Reign of Terror to the Arab Spring. New York: Arcade Publishing, 2013.

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Belles & blooms: Cape Fear Garden Club and the North Carolina Azalea Festival. Wilmington, N.C: Cape Fear Garden Club, 2004.

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Mir, Sadia, and Bateiha Summer Al-Jarrah. Spring Bloom. Bin Khalifa University Press, Hamad, 2019.

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New York Botanical Garden. Spring in Bloom: Special Occasions Calendar. Hudson Park Press, 2000.

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Watercolor in Bloom: Painting the Spring and Summer Garden. North Light Books, 2007.

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Book chapters on the topic "Spring bloom"

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Dahl, Einar, Odd Lindahl, Eystein Paasche, and Jahn Throndsen. "The Chrysochromulina polylepis Bloom in Scandinavian Waters During Spring 1988." In Novel Phytoplankton Blooms, 383–405. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-75280-3_23.

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Dahl, Einar, Odd Lindahl, Eystein Paasche, and Jahn Throndsen. "The Chrysochromulina polylepis bloom in Scandinavian waters during spring 1988." In Coastal and Estuarine Studies, 383–405. Washington, D. C.: American Geophysical Union, 1989. http://dx.doi.org/10.1029/ce035p0383.

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Zheng, Xiaoshen, and Hao Wei. "Analysis of Chlorophyll Concentration during the Phytoplankton Spring Bloom in the Yellow Sea Based on the MODIS Data." In Lecture Notes in Computer Science, 254–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15615-1_31.

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Cloern, James E., and Alan D. Jassby. "Year-to-Year Fluctuation of the Spring Phytoplankton Bloom in South San Francisco Bay: An Example of Ecological Variability at the Land-Sea Interface." In Ecological Time Series, 139–49. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-6881-0_10.

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Cloern, James E., and Alan D. Jassby. "Year-to-Year Fluctuation of the Spring Phytoplankton Bloom in South San Francisco Bay: An Example of Ecological Variability at the Land-Sea Interface." In Ecological Time Series, 139–49. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1769-6_10.

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Dong-sheng, Ding, Li Jing, Shi Xiao-yong, Zhang Chuan-song, Wang Xiu-lin, Li Ke-qiang, Liang Sheng-kang, and Wang Li-sha. "The Studies on the Distributons of Nutrient Structure during Spring and Summer in 2005 in Frequent Harmful Algal Bloom Occurrence Areas in East China Sea." In Advances in Intelligent and Soft Computing, 193–200. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29455-6_28.

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Bährle-Rapp, Marina. "blood." In Springer Lexikon Kosmetik und Körperpflege, 70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_1224.

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Akpan, Ben. "Mastery Learning—Benjamin Bloom." In Springer Texts in Education, 149–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43620-9_11.

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Meybohm, Patrick, Adina Kleinerüschkamp, and Kai Zacharowski. "Patient Blood Management." In Springer Reference Medizin, 211–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-54507-2_167.

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Bährle-Rapp, Marina. "Calf Blood Extract." In Springer Lexikon Kosmetik und Körperpflege, 84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_1535.

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Conference papers on the topic "Spring bloom"

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Park, Kyung-Ae, and Kyung-Ryul Kim. "Sea ice and spring bloom in the East Japan Sea." In SPIE Asia-Pacific Remote Sensing, edited by Robert J. Frouin, Hong Rhyong Yoo, Joong-Sun Won, and Aiping Feng. SPIE, 2010. http://dx.doi.org/10.1117/12.873243.

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Na Nakorn, Kulit, Yusheng Ji, and Kultida Rojviboonchai. "Bloom Filter for Fixed-Size Beacon in VANET." In 2014 IEEE Vehicular Technology Conference (VTC 2014-Spring). IEEE, 2014. http://dx.doi.org/10.1109/vtcspring.2014.7022849.

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Fox, R. D., J. F. R. Gower, and T. A. Curran. "Slocum glider observations during the spring bloom in the Strait of Georgia." In OCEANS 2009. IEEE, 2009. http://dx.doi.org/10.23919/oceans.2009.5422346.

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Luo, Huajun, Defu Liu, Daobin Ji, and Yingping Huang. "Dissolved Oxygen Characteristics of Spring Algal Bloom in Xiangxi Bay of Three Gorges Reservoir." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5515102.

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Semovski, Sergey V., Bogdan Wozniak, and Ryszard Hapter. "Chlorophyll sounding data in the bio-optical model of the Gulf of Gdansk spring bloom." In Ocean Optics XII, edited by Jules S. Jaffe. SPIE, 1994. http://dx.doi.org/10.1117/12.190071.

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Willette, T. M., T. Cooney, and K. Hyer. "Some Processes Affecting Mortality of Juvenile Fishes During the Spring Bloom in Prince William Sound, Alaska." In Ecosystem Approaches for Fisheries Management. Alaska Sea Grant, University of Alaska Fairbanks, 1999. http://dx.doi.org/10.4027/eafm.1999.141.

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Comeau, A. J., M. R. Lewis, J. J. Cullen, R. S. Adams, J. Andrea, S. Feener, S. D. McLean, et al. "Monitoring the Spring Bloom in an Ice Covered Fjord with the Land/Ocean Biogeochemical Observatory (LOBO)." In Oceans 2007. IEEE, 2007. http://dx.doi.org/10.1109/oceans.2007.4449185.

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Weeks, Alison R., Ian S. Robinson, James Aiken, and G. F. Moore. "Maintaining a phytoplankton bloom in low mixed layer illumination in the Bellinghausen Sea in the Austral Spring, 1992." In Ocean Optics XII, edited by Jules S. Jaffe. SPIE, 1994. http://dx.doi.org/10.1117/12.190035.

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Eilertsen, Hans-Christian, Geir A. Hansen, Harald Svendsen, and Else N. Hegseth. "Onset of the spring phytoplankton bloom in the Barents Sea: influence of changing light regime and other environmental factors." In High Latitude Optics, edited by Hans-Christian Eilertsen. SPIE, 1993. http://dx.doi.org/10.1117/12.165507.

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Kikas, Villu, Nelli Norit, Aet Meerits, Natalja Kuvaldina, Inga Lips, and Urmas Lips. "High-resolution monitoring of environmental state variables in the surface layer of the Gulf of Finland (during a dynamic spring bloom in March-May 2010)." In 2010 IEEE/OES Baltic International Symposium (BALTIC). IEEE, 2010. http://dx.doi.org/10.1109/baltic.2010.5621627.

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Reports on the topic "Spring bloom"

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Aller, R. C., J. J. Aller, J. K. Cochran, and C. Lee. Multiple measurement of the coupling between benthic carbon fluxes and bioturbation activity during the spring bloom''. Office of Scientific and Technical Information (OSTI), January 1992. http://dx.doi.org/10.2172/6881040.

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Aller, R. C., J. J. Aller, J. K. Cochran, and C. Lee. Multiple measurement of the coupling between benthic carbon fluxes and bioturbation activity during the ``spring bloom``. Progress report 1992. Office of Scientific and Technical Information (OSTI), December 1992. http://dx.doi.org/10.2172/10142643.

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Chris Harnish, MS, CSCS, HFS, Chris Harnish, MS, CSCS, HFS. How does Sprint Training Impact Blood Sugar and Inflammation? Experiment, March 2014. http://dx.doi.org/10.18258/2296.

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Viksna, Ludmila, Oksana Kolesova, Aleksandrs Kolesovs, Ieva Vanaga, and Seda Arutjunana. Clinical characteristics of COVID-19 patients (Latvia, Spring 2020). Rīga Stradiņš University, December 2020. http://dx.doi.org/10.25143/fk2/hnmlhh.

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Abstract:
Data include following variables: Demographics, epidemiological history, comorbidities, diagnosis, complications, and symptoms on admission to the hospital. Also, body’s temperature and SpO2. Blood cells: white cells count (WBC), neutrophils (Neu), lymphocytes (Ly), eosinophils (Eo) and monocytes (Mo), percentages of segmented and banded neutrophils, erythrocytes (RBC), platelet count (PLT), hemoglobin (Hb), and hematocrit (HCT); Inflammatory indicators: erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP); Tissue damage indicators: alanine aminotransferase (ALT), lactate dehydrogenase (LDH), and troponin T (TnT); Electrolytes: potassium and sodium concentration; Renal function indicators: creatinine and glomerular filtration rate (GFR); Coagulation tests: D-dimer, prothrombin time, and prothrombin index on admission to the hospital.
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