Empirical Relationships Between Phytoplankton and Zooplankton Biomass in Lakes

1981 ◽  
Vol 38 (4) ◽  
pp. 458-463 ◽  
Author(s):  
Edward McCauley ◽  
Jaap Kalff
Keyword(s):  
Regression Analysis ◽  
Phytoplankton Biomass ◽  
Food Source ◽  
Phytoplankton Community ◽  
Zooplankton Biomass ◽  
Empirical Models ◽  
Crustacean Zooplankton ◽  
Functional Regression ◽  
Regression Equations ◽  
Empirical Relationships

Empirical models based on regression analysis were derived using published values of phytoplankton and crustacean zooplankton biomass from lakes. Equations presented predict crustacean zooplankton biomass from measures of phytoplankton biomass. Zooplankton biomass was shown to be positively related to phytoplankton biomass based on an inter-lake comparison. Analyses of functional regression equations suggest that the ratio of zooplankton to phytoplankton biomass decreases as phytoplankton biomass increases among lakes. It is hypothesized that variation in the biomass of nannoplankton, representing the principal food source for crustaceans present in the phytoplankton community, can account for the variation in the biomass of the crustacean zooplankton community.Key words: phytoplankton, zooplankton, biomass, nannoplankton

scholarly journals Effects of nitrogen enrichment on zooplankton biomass and N:P recycling ratios across a DOC gradient in northern-latitude lakes

Hydrobiologia ◽  
2021 ◽  
Author(s):  
A.-K. Bergström ◽  
A. Deininger ◽  
A. Jonsson ◽  
J. Karlsson ◽  
T. Vrede
Keyword(s):  
Community Composition ◽  
Resource Use ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
N Fertilization ◽  
Zooplankton Biomass ◽  
Nitrogen Enrichment ◽  
C:N:P Stoichiometry ◽  
Food Quantity ◽  
N Enrichment

AbstractWe used data from whole-lake studies to assess how changes in food quantity (phytoplankton biomass) and quality (phytoplankton community composition, seston C:P and N:P) with N fertilization affect zooplankton biomass, community composition and C:N:P stoichiometry, and their N:P recycling ratio along a gradient in lake DOC concentrations. We found that despite major differences in phytoplankton biomass with DOC (unimodal distributions, especially with N fertilization), no major differences in zooplankton biomass were detectable. Instead, phytoplankton to zooplankton biomass ratios were high, especially at intermediate DOC and after N fertilization, implying low trophic transfer efficiencies. An explanation for the observed low phytoplankton resource use, and biomass responses in zooplankton, was dominance of colony forming chlorophytes of reduced edibility at intermediate lake DOC, combined with reduced phytoplankton mineral quality (enhanced seston N:P) with N fertilization. N fertilization, however, increased zooplankton N:P recycling ratios, with largest impact at low DOC where phytoplankton benefitted from light sufficiently to cause enhanced seston N:P. Our results suggest that although N enrichment and increased phytoplankton biomass do not necessarily increase zooplankton biomass, bottom-up effects may still impact zooplankton and their N:P recycling ratio through promotion of phytoplankton species of low edibility and altered mineral quality.

scholarly journals Biogeochemical versus ecological consequences of modeled ocean physics

2017 ◽  
Vol 14 (11) ◽  
pp. 2877-2889 ◽  
Author(s):  
Sophie Clayton ◽  
Stephanie Dutkiewicz ◽  
Oliver Jahn ◽  
Christopher Hill ◽  
Patrick Heimbach ◽  
...  
Keyword(s):  
Primary Production ◽  
Ocean Circulation ◽  
Mixed Layer ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Resource Competition ◽  
Nutrient Supply ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Competition Theory

Abstract. We present a systematic study of the differences generated by coupling the same ecological–biogeochemical model to a 1°, coarse-resolution, and 1∕6°, eddy-permitting, global ocean circulation model to (a) biogeochemistry (e.g., primary production) and (b) phytoplankton community structure. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional and seasonal variations in primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths (MLDs) are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, differences in winter mixed layer depths, the timing of the onset of the spring bloom and vertical nutrient supply result in lower primary production in the eddy-permitting model. Counterintuitively, this does not drive a decrease in phytoplankton biomass but results in lower zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity. The use of frameworks, such as resource competition theory, provides a tractable way to explore the differences and similarities that occur. As this model has many similarities to other widely used biogeochemical models that also resolve multiple phytoplankton phenotypes, this study provides important insights into how the results of running these models under different physical conditions might be more easily understood.

Crustacean Zooplankton Communities of Acidic, Metal-Contaminated Lakes Near Sudbury, Ontario

1980 ◽  
Vol 37 (12) ◽  
pp. 2282-2293 ◽  
Author(s):  
N. D. Yan ◽  
R. Strus
Keyword(s):  
Phytoplankton Biomass ◽  
Quantitative Data ◽  
Zooplankton Biomass ◽  
Crustacean Zooplankton ◽  
Total Biomass ◽  
Metal Levels ◽  
Total Phytoplankton ◽  
Average Biomass ◽  
Average Size ◽  
Zooplankton Communities

Crustacean zooplankton data for 1973 to 1978 from Clearwater Lake, an acidic, metal-contaminated lake near Sudbury, Ontario, are presented and compared with data from four other contaminated lakes near Sudbury and six uncontaminated lakes in the Muskoka–Haliburton Region of Ontario. Species richness and community biomass were reduced in the contaminated lakes, the latter because of reductions in numbers and average size of community dominants. The greatest reductions were observed in the lake with the highest metal levels, Hannah Lake. Cladocera were much more important contributors to total biomass in the contaminated lakes, forming, for example, 80–96% of the average biomass for the ice-free period in Clearwater Lake. An average of 89% of all adult Crustacea observed in Clearwater Lake were Bosmina longirostris (O. F. Müller). Zooplankton biomass in the contaminated lakes, excluding Hannah Lake, was not significantly correlated with pH, with Cu, Ni, or TP concentrations, or with total phytoplankton biomass. While similarities existed, community structure was different from that of acidic lakes in the La Cloche Mountains that were not contaminated with Cu or Ni. Hypotheses relating to how acidification alters typical phytoplankton–zooplankton interactions were constructed. The scarcity of quantitative data required to test such hypotheses is emphasized.

scholarly journals Biogeochemical versus ecological consequences of modeled ocean physics

2016 ◽  
Author(s):  
Sophie Clayton ◽  
Stephanie Dutkiewicz ◽  
Oliver Jahn ◽  
Christopher Hill ◽  
Patrick Heimbach ◽  
...  
Keyword(s):  
Primary Production ◽  
Ocean Circulation ◽  
Mixed Layer ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Nutrient Supply ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Models

Abstract. Regional and idealized modeling studies have shown that increasing the physical resolution of biogeochemical models to include mesoscale and submesoscale dynamics can result in both increases and decreases in phytoplankton biomass and primary production, as well as changes in phytoplankton community structure. Here we present a systematic study of the differences generated by coupling the same ecological-biogeochemical model to a 1°, coarse-resolution, and 1/6°, eddy-permitting, global ocean circulation model. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional variations in integrated primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, deeper spring mixed layer depths in the eddy-permitting model result in increased light limitation during the spring bloom. Counter-intuitively, this does not drive a decrease in phytoplankton biomass, but is reflected in decreased primary production and zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity.

Studying the factors of regional insurance market development using the correlation and regression analysis

2020 ◽  
Vol 26 (7) ◽  
pp. 1610-1630
Author(s):  
E.L. Prokop'eva
Keyword(s):  
Regression Analysis ◽  
Federal District ◽  
Insurance Market ◽  
Market Development ◽  
Insurance Markets ◽  
Regression Equations ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Country Level ◽  
Inverse Effect

Subject. The article investigates and quantifies factors of insurance markets functioning in Russian regions, and reveals possibilities to manage them. Objectives. The purpose of the study is to substantiate regional factors that determine the specifics of regional insurance market development; to quantify them to increase the efficiency of regional insurance. Methods. The study draws on statistical methods, functional analysis, algorithm development, correlation and regression analysis. Results. I calculated coefficients of pair and multiple correlation with the indicators of insurance markets in the context of the subjects of the Russian Federation, and composed regression equations. Based on the analysis, I determined the algorithm for inverse effect of the insurance market on the economic, social, fiscal and environmental performance of the region, offered appropriate measures aimed at developing the economic potential of the region and its social sphere. Conclusions. The paper considers the case of the Republic of Khakassia, one of depressed subjects in the Siberian Federal District. The developed models can be used for other regions of Russia, given the geographical and economic features of development. The findings may help generate regional strategies for socio-economic development at the country level. The scientific contribution and the novelty of the work consist of systematizing and quantifying the factors affecting the insurance mechanisms of regional markets, and assessing the inverse effect of insurance mechanisms on integrated development of the region.

Regression analysis of indicators of a numerical experiment to determine the cooling time of oil

2020 ◽  
pp. 89-97
Author(s):  
A. U. Yakupov ◽  
D. A. Cherentsov ◽  
K. S. Voronin ◽  
Yu. D. Zemenkov
Keyword(s):  
Regression Analysis ◽  
Computer Experiment ◽  
Calculation Model ◽  
Cooling Time ◽  
Regression Coefficients ◽  
Fisher Criterion ◽  
Empirical Relationships ◽  
Factors Affecting ◽  
Oil Pipeline ◽  
Significant Regression

The article performed the processing of the results of a computer experiment to determine the cooling time of oil in a stopped oil pipeline. We proposed a calculation model in previous works that allows you to simulate the process of cooling oil.There was a need to verify the previously obtained results when conducting a laboratory experiment on a stand with soil. To conduct the experiment, it was necessary to conduct the planning of the experiment. The factors affecting the cooling time of oil in the oil pipeline, which will vary in the proposed experiment, are determined, empirical relationships are established. A regression analysis was carried out, and the dispersion homogeneity was checked using the Cochren criterion. The estimates of reproducibility variances are calculated. The adequacy hypothesis was tested using the Fisher criterion. Significant regression coefficients are established.

Differences between Nearshore and Offshore Phytoplankton Communities in Lake Ontario

1987 ◽  
Vol 44 (12) ◽  
pp. 2155-2163 ◽  
Author(s):  
I. M. Gray
Keyword(s):  
Chlorophyll A ◽  
Phytoplankton Biomass ◽  
Algal Biomass ◽  
Phytoplankton Community ◽  
Seasonal Pattern ◽  
Principal Component ◽  
Lake Ontario ◽  
Dominant Group ◽  
Phytoplankton Communities ◽  
Eutrophic Species

Differences between nearshore and offshore phytoplankton biomass and composition were evident in Lake Ontario in 1982. Phytoplankton biomass was characterized by multiple peaks which ranged over three orders of magnitude. Perhaps as a consequence of the three times higher current velocities at the northshore station, phytoplankton biomass ranged from 0.09 to 9.00 g∙m−3 compared with 0.10 to 2.40 g∙m−3 for the midlake station. Bacillariophyceae was the dominant group at the northshore station until September when Cyanophyta contributed most to the biomass (83%). Although Bacillariophyceae was the principal component of the spring phytoplankton community at the midlake station, phytoflagellates (49%) and Chlorophyceae (25%) were responsible for summer biomass, with the Chlorophyceae expanding to 80% in the fall. The seasonal pattern of epilimnetic chlorophyll a correlated with temperature. While chlorophyll a concentrations were similar to values from 1970 and 1972, algal biomass had declined and a number of eutrophic species (Melosira binderana, Stephanodiscus tenuis, S. hantzschii var. pusilla, and S. alpinus) previously found were absent in 1982.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Response of ocean phytoplankton community structure to climate change over the 21st century: partitioning the effects of nutrients, temperature and light

2010 ◽  
Vol 7 (12) ◽  
pp. 3941-3959 ◽  
Author(s):  
I. Marinov ◽  
S. C. Doney ◽  
I. D. Lima
Keyword(s):  
Climate Change ◽  
Community Structure ◽  
Sea Ice ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Vertical Mixing ◽  
Phytoplankton Community Structure ◽  
Marginal Sea ◽  
Small Phytoplankton ◽  
The Impact

Abstract. The response of ocean phytoplankton community structure to climate change depends, among other factors, upon species competition for nutrients and light, as well as the increase in surface ocean temperature. We propose an analytical framework linking changes in nutrients, temperature and light with changes in phytoplankton growth rates, and we assess our theoretical considerations against model projections (1980–2100) from a global Earth System model. Our proposed "critical nutrient hypothesis" stipulates the existence of a critical nutrient threshold below (above) which a nutrient change will affect small phytoplankton biomass more (less) than diatom biomass, i.e. the phytoplankton with lower half-saturation coefficient K are influenced more strongly in low nutrient environments. This nutrient threshold broadly corresponds to 45° S and 45° N, poleward of which high vertical mixing and inefficient biology maintain higher surface nutrient concentrations and equatorward of which reduced vertical mixing and more efficient biology maintain lower surface nutrients. In the 45° S–45° N low nutrient region, decreases in limiting nutrients – associated with increased stratification under climate change – are predicted analytically to decrease more strongly the specific growth of small phytoplankton than the growth of diatoms. In high latitudes, the impact of nutrient decrease on phytoplankton biomass is more significant for diatoms than small phytoplankton, and contributes to diatom declines in the northern marginal sea ice and subpolar biomes. In the context of our model, climate driven increases in surface temperature and changes in light are predicted to have a stronger impact on small phytoplankton than on diatom biomass in all ocean domains. Our analytical predictions explain reasonably well the shifts in community structure under a modeled climate-warming scenario. Climate driven changes in nutrients, temperature and light have regionally varying and sometimes counterbalancing impacts on phytoplankton biomass and structure, with nutrients and temperature dominant in the 45° S–45° N band and light-temperature effects dominant in the marginal sea-ice and subpolar regions. As predicted, decreases in nutrients inside the 45° S–45° N "critical nutrient" band result in diatom biomass decreasing more than small phytoplankton biomass. Further stratification from global warming could result in geographical shifts in the "critical nutrient" threshold and additional changes in ecology.

scholarly journals Determination of individual teleroentgenographic characteristics of the face profile in ukrainian young men and girls with orthognathic bite

2018 ◽  
pp. 28-34
Author(s):  
М. О. Dmitriev
Keyword(s):  
Regression Analysis ◽  
Soft Tissue ◽  
Young Women ◽  
Stepwise Regression ◽  
Young Men ◽  
Stepwise Regression Analysis ◽  
Regression Equations ◽  
Determination Coefficient ◽  
Normal Occlusion

Modern dentistry requires the definition of individualized values of teleroentgenographic indicators. To solve such problems, methods of regression and correlation analysis are increasingly used, which help to establish not only the existence of various relationships between the anatomical structures of the head and the parameters of the dento-jaw system, but also allow more accurately predict the change in the contour of soft facial tissue in response to orthodontic treatment. The purpose of the study is to develop mathematical models for the determination of individual teleroentgenographic characteristics of the facial soft tissues by studying the cephalometric indices of young men and women of Ukraine with normal occlusion and balanced faces and conducting a direct stepwise regression analysis. With the use of Veraviewepocs 3D device, Morita (Japan) from 38 young men (17 to 21 years of age) and 55 young women (aged from 16 to 20 years) with occlusal close to the orthognathic bite and balanced faces received side teleroentgenograms. The cephalometric analysis was performed using OnyxCeph³™ licensed software. Cephalometric points and measurements were made according to the recommendations of Downs W. B., Holdway R. A., McNamara J., Schwarz A. M., Schmuth G. P. F., Steiner C. C. and Tweed C. H. With the help of direct stepwise regression analysis, in the licensed package “Statistica 6.0”, regression models of individual teleroentgenographic characteristics of the profile of soft facial tissues were constructed. In young men with normal occlusion close to the orthognathic bite of 19 possible models, 11 were constructed with a determination coefficient from 0.638 to 0.930, and in young women – 12 models with a determination coefficient from 0.541 to 0.927. The conducted analysis of models showed that in young men most often the regression equations included – angle N_POG, parameters of which indicate a linear interjaw relation in the anterior-posterior direction (14.0%); angle GL_SNPOG, or index of convexity of the soft tissue profile (8.8%); MAX maxillary length (7.0%), and GL_SN_S index, which defines vertical correlations in the facial profile (5.3%). The young women most often models included – the angle N_POG (12.5%); angle GL_SNPOG (7.5%); soft tissue front angle P_OR_N (6.25%); the reference angle ML_NL and the profile angle T (by 5.0%); the angle AB_NPOG, the angle NBA_PTGN, which defines the direction of development of the mandible and the distance PN_A (3.75%). Thus, in the work with the help of the method of stepwise regression with inclusion, among Ukrainians of adolescence age, based on the characteristics of teleroentgenographic indicators, reliable models of individual teleroentgenographic characteristics of the profile of soft facial tissues were developed and analyzed.

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