Factors affecting the timing of surface scums and epilimnetic blooms of blue-green algae in a eutrophic lake

1997 ◽  
Vol 54 (9) ◽  
pp. 1965-1975 ◽  
Author(s):  
P A Soranno
Keyword(s):  
Atmospheric Pressure ◽  
Algal Blooms ◽  
Algal Biomass ◽  
Eutrophic Lake ◽  
Lake Surface ◽  
Factors Affecting ◽  
Blue Green Algae ◽  
Lake Mendota ◽  
Green Algal ◽  
Using Data

Blue-green algal blooms, which can occur mixed throughout the epilimnion or as scums at the lake surface, develop in response to a variety of factors. However, it is still unclear what conditions suggest that blooms are imminent or how far in advance blooms can be forecast. I assessed the predictability of surface scums and epilimnetic blooms from limnological, physical, and meteorological variables using data sampled daily during summer and fall 1993 in Lake Mendota, Wisconsin. Daily chlorophyll a (a measure of blue-green algal biomass) was correlated to some weather, physical, and grazing variables at lags ranging from 0 to 9 days. Conditions immediately preceding surface scums were variable, making predictions difficult. However, during surface scums, Secchi disk depth, wind velocity, atmospheric pressure, and precipitation were significantly different than when the scums were absent. Based on predictors examined in this study, I developed criteria that identify the conditions sufficient for scums to form. In Lake Mendota, conditions sufficient for surface scum formation (proper weather and water column conditions and a pre-existing algal population) occur much more often than scums are observed. This study shows the importance of weather in determining both epilimnetic blue-green algal biomass and surface scum formation.

Enhancement of Autotrophic Production by Nutrient Addition in a Coastal Rainforest Stream on Vancouver Island

1978 ◽  
Vol 35 (1) ◽  
pp. 28-34 ◽  
Author(s):  
John G. Stockner ◽  
K. R. S. Shortreed
Keyword(s):  
Algal Biomass ◽  
Algal Growth ◽  
N:P Ratio ◽  
Visual Observation ◽  
Nutrient Addition ◽  
Appreciable Effect ◽  
Blue Green Algae ◽  
Species Succession ◽  
Green Algal ◽  
Enrichment Experiments

In 1976 streamside nutrient-enrichment experiments were conducted using wooden troughs. Tripling of the PO4-P concentration, with or without a similar increase of NO3-N, increased algal biomass on the troughs by 8 times after 35 days. Increasing NO3-N alone had no appreciable effect on algal growth. A sloughing of algal biomass in August 1976 is believed to have been due to the instability of the heavy algal mat on the troughs and to the very poor light conditions that prevailed throughout August. Visual observation indicated that the relatively heavy algal population in Carnation Creek rapidly declined concurrent with the decline in the troughs. The percentage of diatoms in the algal assemblage remained the same in all troughs, and Fragilaria vaucheriae replaced Achnanthes minutissima as dominant on the phosphorus enriched trough. No shift to green or blue-green algal dominated assemblages occurred despite alteration of the N:P ratio. The dynamics of species succession, distribution, and growth, with and without nutrient addition, are discussed. Key words: stream fertilization, autotrophic production, algal succession, N:P ratio, algal distribution, rainforest, algal biomass, diatoms, blue-green algae

Factors Influencing the Abundance of Blue-Green Algae in Florida Lakes

1989 ◽  
Vol 46 (7) ◽  
pp. 1232-1237 ◽  
Author(s):  
Daniel E. Canfield Jr. ◽  
Edward Phlips ◽  
Carlos M. Duarte
Keyword(s):  
Green Algae ◽  
Algal Biomass ◽  
Strongly Correlated ◽  
Blue Green Algae ◽  
Florida Lakes ◽  
Relative Contribution ◽  
Green Algal ◽  
Factors Influencing ◽  
Total Phytoplankton ◽  
Algal Abundance

Phytoplankton samples collected from 165 Florida lakes were examined to determine relationships between blue-green algal abundance and environmental conditions. Blue-green algal biomass in the Florida samples was weakly correlated (r = −0.34) with water transparency and the concentration of total nitrogen (TN) (r = 0.47) and total phosphorus (TP) (r = 0.33). The relative contribution of blue-green algae to total phytoplankton biomass, however, did not decrease with TN/TP > 29. Blue-green algal biomass was strongly correlated (r = 0.90) to total algal biomass, and blue-green algae became consistently dominant when total algal biomass exceeded 100 mg/L.

Patterns in Algal Recruitment from Sediment to Water in a Dimictic, Eutrophic Lake

1994 ◽  
Vol 51 (12) ◽  
pp. 2825-2833 ◽  
Author(s):  
Lars-Anders Hansson ◽  
Lars G. Rudstam ◽  
Timothy B. Johnson ◽  
Patricia Soranno ◽  
Yvonne Allen
Keyword(s):  
Water Column ◽  
Algal Blooms ◽  
Standing Stock ◽  
Algal Species ◽  
Euphotic Zone ◽  
Eutrophic Lake ◽  
Sediment Surface ◽  
Lake Mendota ◽  
Ceratium Hirundinella ◽  
Key Factor

In the large, dimictic, and highly productive Lake Mendota (Wisconsin, USA), the recruitment rates from sediment to water were determined for some characteristic and dominating algal species during a 1-yr cycle. Quantifying recruitment in relation to abundance in the water on a whole-lake basis revealed that recruitment usually accounted for less than 1% of the total standing stock of each species per day, indicating that recruitment may not be an important population variable in Lake Mendota, but may instead function as an inoculum for future growth in the water column. The recruitment of Cryptomonas erosa and Ceratium hirundinella showed a dephasing among sites, suggesting that algae on the sediment surface rise into the water column in response to some depth-related cue. With the exception of one recruitment period for Aphanizomenon, no recruitment was recorded below the thermocline during the stratification period, indicating that a variable associated with stratified conditions affected algal movements from the hypolimnion to the euphotic zone. We argue that the understanding of recruitment patterns from sediment to water is a key factor in managing algal blooms in highly productive lakes.

Evaluation of Total Phosphorus as a Predictor of the Relative Biomass of Blue-green Algae with Emphasis on Alberta Lakes

1987 ◽  
Vol 44 (7) ◽  
pp. 1337-1342 ◽  
Author(s):  
Annette M. Trimbee ◽  
E. E. Prepas
Keyword(s):  
Green Algae ◽  
Total Phosphorus ◽  
Algal Biomass ◽  
Dynamic Equilibrium ◽  
Empirical Models ◽  
Total Biomass ◽  
New Model ◽  
Blue Green Algae ◽  
Model Based ◽  
Green Algal

The relative biomass of blue-green algae in freshwater (total dissolved solids < 500 mg∙L−1) Alberta lakes was consistently underestimated by two recent empirical models based on total nitrogen (TN), total phosphorus (TP), Secchi disc depth (SD), and depth of the mixed layer (Zm). We regrouped the data used in these empirical models to eliminate the potential biases introduced by including data from lakes not in dynamic equilibrium and generated a new model based on TP. This new model accounted for 11% more of the variation in relative blue-green algal biomass than the original model based on TN, TP, SD, and Zm and 21% more than the model based on TN to TP ratios and SD to Zm ratios. This new model was also a much better predictor of the relative biomass of blue-green algae in Alberta lakes than the original models. In addition, for lakes in Alberta, TP was a much better predictor of total blue-green algal biomass than TN or the TN to TP ratio. Our analyses suggest that for large numbers of lakes, TP may be as good or better an indicator of relative and total biomass of blue-green algae than TN or TN to TP ratios.

Phosphorus loading reductions needed to control blue-green algal blooms in Lake Mendota

1998 ◽  
Vol 55 (5) ◽  
pp. 1169-1178 ◽  
Author(s):  
Richard C Lathrop ◽  
Stephen R Carpenter ◽  
Craig A Stow ◽  
Patricia A Soranno ◽  
John C Panuska
Keyword(s):  
Algal Blooms ◽  
Management Practices ◽  
Phosphorus Loading ◽  
Balance Model ◽  
Load Reduction ◽  
Lake Water Quality ◽  
Time Step ◽  
Data Set ◽  
Lake Mendota ◽  
Green Algal

We evaluated the reductions in P loading needed to control blue-green algal blooms in Lake Mendota, Wisconsin. After developing a 21-year loading data set, we used a P mass balance model expressed as a difference equation with an annual time step indexed from mid-April. We defined and estimated a loss parameter lambda as the proportion of the lake's April P concentration lost through sedimentation and outflow during the following year. Using the distribution of annual lambda 's and input loadings, we predicted the steady-state distribution of April P concentrations that would result from scenarios of altered inputs due to changes in management practices. These results were then linked to the probability of summer blue-green algal blooms. For no load reduction, the probability of a bloom (>2 mg algae ·L-1) on any summer day is about 60%. This probability decreases to 20% with a load reduction of 50%. Our approach illustrates how managers can consider reducing the frequency of extreme events like algal blooms, which may correspond more to the public's perception of lake water quality than average conditions.

Phytoplankton succession in a Eutrophic lake with special reference to blue-green algal blooms

Hydrobiologia ◽  
1972 ◽  
Vol 39 (3) ◽  
pp. 321-334 ◽  
Author(s):  
Chang K. Lin
Keyword(s):  
Special Reference ◽  
Algal Blooms ◽  
Eutrophic Lake ◽  
Phytoplankton Succession ◽  
Green Algal

How Can We Use Fluorescence And Artificial Intelligence To Better Control Blue-Green Algal Blooms?

2018 ◽  
Author(s):  
Edoardo Bertone ◽  
Michele A. Burford ◽  
David P. Hamilton
Keyword(s):  
Artificial Intelligence ◽  
Algal Blooms ◽  
Green Algal

scholarly journals Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402198925
Author(s):  
Isidoro Guzmán-Raja ◽  
Manuela Guzmán-Raja
Keyword(s):  
Data Envelopment Analysis ◽  
High Efficiency ◽  
Sport Performance ◽  
Data Envelopment ◽  
Professional Football ◽  
Efficiency Measure ◽  
Factors Affecting ◽  
Football Clubs ◽  
Main Factors ◽  
Using Data

Professional football clubs have a special characteristic not shared by other types of companies: their sport performance (on the field) is important, in addition to their financial performance (off the field). The aim of this paper is to calculate an efficiency measure using a model that combines performance (sport and economic) based on data envelopment analysis (DEA). The main factors affecting teams’ efficiency levels are investigated using cluster analysis. For a sample of Spanish football clubs, the findings indicate that clubs achieved a relatively high efficiency level for the period studied, and that the oldest teams with the most assets had the highest efficiency scores. These results could help club managers to improve the performance of their teams.

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