Hypertrophic phytoplankton and the Intermediate Disturbance Hypothesis

Rojo, Carmen; Cobelas, Miguel Álvarez

doi:10.1007/bf00008842

Cited by 28 publications

(11 citation statements)

References 34 publications

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“…The observed general pattern of low pollutants with decrease in values for the zooplankton and phytoplankton diversity as we move downstream form Site A to Site C is similar to previously reported trends [57]. However, this diversity index greatly varies from study to another study, which makes it very difficult to make comparison among the studies and draw a common conclusion because of environmental variabilities among the studies [58].…”

Section: Shannon-wiener Diversity Indexessupporting

confidence: 86%

Evaluation of Spatial-Temporal Variations of Water Quality and Plankton Assemblages and Its Relationship to Water Use in Kulekhani Multipurpose Reservoir, Nepal

Adhikari¹,

Shrestha²,

Bam³

et al. 2017

JEP

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Spatial and temporal variation in planktons and water quality parameters were investigated in order to determine the effects of seasonal water use on reservoir water quality and planktons' diversity in Kulekhani Multipurpose Reservoir, Nepal. This study also focuses on interactions among various water quality parameters with planktons and how such interactions can affect the second major utility, the fish farming in the reservoir. The analyses of seasonal water samples collected from three different sampling locations in the reservoir showed that select water quality parameters varied significantly (P < 0.05) with sampling seasons (transparency: 30 -250 cm, pH: 7 -7.5, alkalinity: 30 -120 mg/L, DO: 6 -11.5 mg/L, CO 2 : 0.1 -1.1 mg/L) and sampling locations (phosphate: 0.1 -0.25 mg/L, nitrate 0.01 -0.19 mg/L) in the reservoir. Three groups of zooplankton and four classes of phytoplankton, respectively with eleven and twelve genera, were identified and quantified in the reservoir.Among them, Cyclops, Asplanchana, and Keratella were most dominant zooplanktons while Synedra, Melosira and Peridinum were the most dominant phytoplankton in the reservoir water. The abundance of select zooplanktons (Cyclops, Keratella, Polyanthra), and phytoplankton (Navicula, Melosira, Amphora, Chroococcus, Staurastrum, Scendesmus) showed significant interaction between sampling sites and sampling seasons, while the other varied only with sampling seasons and/or sites. These results showed that seasonal water level fluctuations, along with the variation of water quality para- meters, change the abundance and diversity of planktons' in the reservoir. Such changes can negatively impact the fish in cage culture, affecting the livelihood of people extensively relying on these fish farming.

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Section: Shannon-wiener Diversity Indexessupporting

confidence: 86%

Evaluation of Spatial-Temporal Variations of Water Quality and Plankton Assemblages and Its Relationship to Water Use in Kulekhani Multipurpose Reservoir, Nepal

Adhikari¹,

Shrestha²,

Bam³

et al. 2017

JEP

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“…In a hypereutrophic gravel-pit lake, Rojo and Cobelas (1993) found seven periods of stability or "equilibrium" phases lasting 2-10 weeks. Sommer (1986) divided the season into 24 phases with reference to shifts in species dominance; only five of these were controlled by physical events.…”

Section: Discussionmentioning

confidence: 99%

Phytoplankton functional attributes along trophic gradient and season

Seip

Reynolds

1995

Limnology & Oceanography

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Each of the following phytoplankton functional attributes could be described by significant (P < 0.05) response surfaces defined by trophic status (T) from oligotrophy to hypertrophy and season (S) from early vernal period to late summer: phytoplankton cell volume, growth rate, the ratio between minimum quotas of total N and total P, affinity for P, half-saturation constant for growth with respect to P, and temperature optimum and light optimum for growth. Sinking rate could not be so described. The response surfaces were calculated by multiple regressions, including first-and second-order terms of T and S and the interaction term T. S. Although the data base was rather limited (number of phytoplankton species ranged from 10 to 3 I), the resulting surfaces often reflected a corresponding attribute of the water along T and S (e.g. phytoplankton temperature optimum for growth reflected water temperature). The results support the frequent use of physical factors as explanatory variables for the distribution and abundance of phytoplankton.The abundance of phytoplankton species and the species structure of phytoplankton assemblages vary along trophic and seasonal gradients (Reynolds 1980(Reynolds , 1984b. Because phytoplankton species with similar functional attributes (such as size, maximum growth rate, and optimum temperature for growth) also share similar ecologies (Reynolds 1988), we wanted to find out whether it is possible to give a statistically significant description of the attributes along trophic gradient (T, measured as the level of total P concentration) and season (S, related to day of the year). Discussions of species successions often imply such functional relationships. For example, Sommer (1986, p. 6) wrote that "in eutrophic lakes where P is not limiting during early spring, the higher maximum growth rate makes nanoplanktonic algae such as small Centrales and Rhodomonas dominant." The functional attributes of an alga might also relate directly its position in a seasonal succession of algae. Statement 5 of the PEGmodel of seasonal succession of planktonic events in fresh waters states that "there then (after herbivore grazing) follows a 'clear-water' equilibrium phase which persists until inedible algae species develop in significant numbers" (Sommer et al. 1986, p. 435.) Because inedibility is often related to biovolumes, e.g. volumes > -15 x 1 O3 pm3 (diam, 30 pm, Carpenter et al. 1993), herbivory and not season may be a primary vehicle for the presence of large-size algae or algal colonies. Several more statements about the relationship between algal attributes and species abundance could be listed and some of these would be partly confounding. Our quest, then, is a statistical pattern along trophy and season persisting "through" the web of biotic interactions. Materials and methodsWe use literature values for phytoplankton attributes. Our basic idea is that data should not be screened before the data are included in the analysis; instead, screening should be a consequence of the stati...

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“…Many studies of disturbance in planktonic systems have focused on changes in depth or stability of the surface mixed layer (Chorus and Schlag 1993, Rojo and Alvarez Cobelas 1993, Flö der and Sommer 1999. Mixed layer depth determined (in meters) during sampling events was thus included as an index of distur-bance.…”

Section: Measures Of Disturbancementioning

confidence: 99%

Limiting Resources, Disturbance, and Diversity in Phytoplankton Communities

Grover

Chrzanowski

2004

Ecological Monographs

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Phytoplankton diversity, limiting resources, and disturbance were studied in two reservoirs, Eagle Mountain Lake (EML) and Joe Pool Lake (JPL), in north Texas, USA, for three summer growing seasons and two winters. Availabilities of phosphorus, nitrogen, and silicon were measured as chemical concentrations, and availability of light was measured as irradiance during the photoperiod, averaged over the depth of the surface mixed layer. A resource was defined as limiting whenever its availability fell below a threshold, treated as a parameter to be fitted. Depth of the surface mixed layer and wind speed were taken as indices of disturbance associated with episodic mixing. Hydrological disturbance was gauged by rainfall, inflow, and the variation of lake level. We found that diversity was strongly and significantly correlated with the number of limiting resources in one lake (JPL), but not the other (EML). The onset of nitrogen and phosphorus limitation during the summer growing season is associated with increased phytoplankton diversity in JPL. Regression modeling detected decreasing relationships between diversity and disturbance indices in one lake (JPL), but concave-down relationships in the other (EML), though the peaks of these relationships did not lie within the usual range of disturbance. Predictive regressions for diversity incorporating both limiting resources and disturbance were partitioned into unique and shared effects of these factors. There was a large unique effect of the number of limiting resources in JPL, but otherwise the shared effects were large relative to unique effects.

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Hypertrophic phytoplankton and the Intermediate Disturbance Hypothesis

Cited by 28 publications

References 34 publications

Evaluation of Spatial-Temporal Variations of Water Quality and Plankton Assemblages and Its Relationship to Water Use in Kulekhani Multipurpose Reservoir, Nepal

Evaluation of Spatial-Temporal Variations of Water Quality and Plankton Assemblages and Its Relationship to Water Use in Kulekhani Multipurpose Reservoir, Nepal

Phytoplankton functional attributes along trophic gradient and season

Limiting Resources, Disturbance, and Diversity in Phytoplankton Communities

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