Nutrients (P, N, Si) and growth conditions for diatoms and Oscillatoria spp. in lakes of south-eastern Norway

Løvstad, Øivind; Bjørndalen, Knut

doi:10.1007/bf00006137

Cited by 12 publications

(7 citation statements)

References 10 publications

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“…Inspection of the data also indicated that even in the NES data set, there was no consistent change in the correlations between nutrient supply and nutrient availabilities for states at different latitudes. Seasonal patterns in nutrient availabilities relative to supply are undoubtedly strong in some areas (e.g., Lovstad and Bjorndalen 1990), but they do not seem likely explanations for the general pattern of positive correlations in nutrient availabilities found in these data sets.…”

Section: Resultsmentioning

confidence: 78%

Do nutrient-competition models predict nutrient availabilities in limnetic ecosystems?

Leibold

1997

Oecologia

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Recent theory on resource competition, predicated on the importance of hypothesized trade-offs between minimum requirements for nutrient resources, predicts that there should be negative correlations between the supply rate of major limiting nutrients and the availability of at least some secondary nutrients and/or among the availabilities of different limiting nutrients. However, an analysis of four data sets from large-scale surveys of lakes shows mostly positive correlations among the availabilities and supplies of nutrients. In contrast, a fifth data set, obtained in an area of high acidification, does show several important negative correlations that are consistent with the nutrient competition models. Further analyses suggest two possible explanations for the preponderance of positive correlation. Negative correlations between nutrients and light indicate that an important trade-off among species regulating phytoplankton may involve low light requirements versus low nutrient requirements. The existence of negative correlations in nutrient availabilities in acidic lakes (where herbivory appears less important than in buffered lakes) also suggests that another important trade-off may involve an ability to minimize loss rates (especially due to grazing) versus an overall ability to exploit nutrient resources.

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Section: Resultsmentioning

confidence: 78%

Do nutrient-competition models predict nutrient availabilities in limnetic ecosystems?

Leibold

1997

Oecologia

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“…2. These include biological uptake and sedimentation (e.g., Schelske 1975;Løvstad and Bjørndalen 1990). Net sedimentation is likely higher in deeper lakes during summer, where the settled nitrogen is trapped in the hypolimnion, while it may return to the surface water again in shallow lakes after mineralization and nitrification in the surface sediments.…”

Section: Resultsmentioning

confidence: 99%

“…In our study nitrate-nitrogen (NO 3 -N) was considered to be the sum of NO 3 -N and nitrite-nitrogen (NO 2 -N), since exclusive NO 3 -N measurements were not available for all lakes. To describe changes in surface NO 3 -N concentrations from spring to summer, we assumed a first-order decay (Løvstad and Bjørndalen 1990) and fitted an exponential function to all 748 available May to August measurements from 100 lakes, giving us the relative NO 3 -N loss rate k,…”

Section: Methodsmentioning

confidence: 99%

Nitrate‐depleted conditions on the increase in shallow northern European lakes

Weyhenmeyer

Jeppesen

Adrian

et al. 2007

Limnology & Oceanography

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We determined relative nitrate‐nitrogen (NO3‐N) loss rates in 100 north‐mid‐European lakes from late spring to summer by using the exponential function N2 = N1e−k(t2−t2), where N1 and N2 are NO3‐N concentrations at the beginning (t1) and the end (t2) of the time interval, respectively, and k is the specific NO3‐N loss rate. We found that k decreased with increasing lake depth. Adjusting k to the lake depth (kadj), we observed that kadj was positively related to spring NO3‐N concentrations, but this relationship became insignificant at mean lake depths exceeding 12.5 m. A relationship between kadj and spring NO3‐N concentrations in lakes shallower than 12.5 m implies that changes in spring NO3‐N concentrations influence the NO3‐N loss rate and thereby summer NO3‐N concentrations. Time series from one Estonian, one German, and 14 Swedish lakes shallower than 12.5 m since 1988 revealed that May to August NO3‐N concentrations have decreased over time everywhere, and the number of time periods exhibiting a NO3‐N depleted condition, i.e., NO3‐N levels below 10 mg L−1, in these lakes has tripled since 1988. We explained the decreasing NO3‐N concentrations by a reduction in external nitrogen loading including atmospheric deposition, and by changes in climate. The observed prolongation of NO3‐N depleted conditions might be one possible explanation for the increasing occurrence of nitrogen‐fixing cyanobacteria in a variety of lake ecosystems.

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“…The fact that diatoms are favoured by low temperatures is well known from the literature (e.g. Munawar and Munawar 1975, Baker and Baker 1981, Løvstad and Bjørndalen 1990 and the negative correlation with SiO 2 -Si is the result of depletion of this important nutrient during peaks in diatom biomass.…”

Section: Resultsmentioning

confidence: 95%

The influence of downstream changes in water quality on phytoplankton composition in the Vaal River, South Africa

Vuuren¹,

Pieterse²

2005

African Journal of Aquatic Science

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Links between spatial differences in phytoplankton composition and changes in environmental variables in the Vaal River, South Africa, were investigated. Multivariate analysis showed that the most important environmental variables influencing algal abundance were turbidity, conductivity, nutrient concentrations and temperature. Of these variables conductivity, phosphorus, nitrogen and SiO 2 -Si showed spatial differences in concentration. The average nutrient concentrations (phosphorus, nitrogen and SiO 2 -Si) showed downstream decreases, while the average conductivity increased in a downstream direction. Spatial changes in phytoplankton composition could also be illustrated and were especially apparent when the contribution of Cyanobacteria (bluegreen bacteria or blue-green algae), Bacillariophyceae and Euglenophyceae to the total algal composition was taken into account.

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Nutrients (P, N, Si) and growth conditions for diatoms and Oscillatoria spp. in lakes of south-eastern Norway

Cited by 12 publications

References 10 publications

Do nutrient-competition models predict nutrient availabilities in limnetic ecosystems?

Do nutrient-competition models predict nutrient availabilities in limnetic ecosystems?

Nitrate‐depleted conditions on the increase in shallow northern European lakes

The influence of downstream changes in water quality on phytoplankton composition in the Vaal River, South Africa

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