Potamoplankton and primary productivity in the River Danube

Dokulil, Martin T.

doi:10.1007/s10750-013-1589-3

Cited by 22 publications

(21 citation statements)

References 57 publications

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“…Using yearly or decadal median data, light conditions might contribute the most to the unaccounted variability in Chl. Light limitation was shown to prevail even during low flow in several medium-to large-sized rivers of this study (Uherkovich, 1971;Dokulil, 2006;Istvánovics et al, 2010;Istvánovics & Honti, 2011). Shading by aquatic and riparian macrovegetation might be important in low gradient smallto medium-sized rivers and in headwater streams of forested catchments, respectively.…”

Section: Determinants Of Sestonic Chlmentioning

confidence: 63%

“…The typical longitudinal profile of light availability, however, is not monotonous. Headwater streams of forested catchments can be heavily shaded by the terrestrial canopy cover either seasonally or year-round, while in the deep channels of large lowland rivers inorganic turbidity often restricts light availability (Vannote et al, 1980;Reynolds & Descy, 1996;Dokulil, 2006;Istvánovics et al, 2010). Thus, the highest autotrophic productivity is expected in medium-sized rivers and in large floodplain rivers tightly connected with backwater habitats (Vannote et al, 1980;Hein et al, 2003, Thorp et al, 2006.…”

Section: Introductionmentioning

confidence: 99%

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Efficiency of nutrient management in controlling eutrophication of running waters in the Middle Danube Basin

Istvánovics

Honti

2012

Hydrobiologia

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Nutrient emission dropped significantly during the last two decades in the Danube Basin. To assess the effect of reduced nutrient loads on the trophic status of running waters, this regional study analyzed the relationships between nutrients (P and N) and suspended chlorophyll (Chl) using long-term monitoring data in Hungary. Including the upstream catchments of trans-boundary rivers, the study covered an approximate area of 400,000 km 2 , equivalent to the half of the entire Danube catchment. Decadal median Chl was unrelated to P and N concentrations in the whole data set and weakly related to total P (TP) at natural-moderately polluted (N-MP) sites, which were distinguished from highly polluted (HP) sites by using cutoff values for chloride, chemical oxygen demand and TP. At both the N-MP sites and most of the HP sites, Chl increased with channel length. This indicated that water residence time was a more important determinant of Chl than nutrients. Nutrient concentrations showed a significant downward trend in time at half of our sites. With a nearly equal frequency, a parallel trend might or might not occur in Chl. The apparent efficiency of nutrient management was expressed as the quotient of the slopes of linear trends in Chl and nutrients. At sites within 150 km from source, this efficiency was marginal. In larger rivers, efficiency improved steeply. The highest efficiency was observed in the downstream reach of the Danube (upstream length [1,300 km) where P availability might frequently limit algal growth. The results suggest that eutrophication management in rivers should be based on Chl response functions, rather than universal nutrient criteria. Four Chl response classes were identified based on the observed longitudinal P and Chl gradients.

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Section: Determinants Of Sestonic Chlmentioning

confidence: 63%

Section: Introductionmentioning

confidence: 99%

Efficiency of nutrient management in controlling eutrophication of running waters in the Middle Danube Basin

Istvánovics

Honti

2012

Hydrobiologia

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“…Although kinetics of resuspension is poorly known in rivers, our estimates seemed realistic compared with the few observations (Cushing, Minshall & Newbold, ; Newbold et al ., ). Solving dynamic equations of meroplanktonic algal growth in rivers (Istvánovics & Honti, ) using these values, apparent

G_{normalriver}^{R}

of 2.5 day −1 could be reproduced within the range of metabolic parameters (Chl‐specific rate of maximum photosynthesis and respiration, light saturation constant) typical in large rivers (Descy et al ., ; Descy, Gosselain & Evrard, ; Vörös et al ., ; Dokulil, ).…”

Section: Discussionmentioning

confidence: 99%

“…Light and silica frequently limit instantaneous growth rates of phytoplankton in rivers (Reynolds & Descy, ; Koch, Guelda & Bukaveckas, ; Descy et al ., ; Dokulil, ). Before developing the phytoplankton module of the TAPIR model (eqn 3), we assessed whether these resources might determine mean biomass capacity in the Someş River.…”

Section: Discussionmentioning

confidence: 99%

“…Flow variability results in lower nutrient-specific biomass yield (Søballe & Kimmel, 1987;Mischke, Venohr & Behrendt, 2011) and weaker biotic interactions (competition, grazing) in rivers compared to lakes, where longer water residence time allows for more efficient material cycling and energy transfer. The intensity of both bottom-up and top-down controls increases during low flow in rivers, although phytoplankton rarely deplete available nutrients (Reynolds & Descy, 1996;Mischke et al, 2011;Dokulil, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Phytoplankton growth in relation to network topology: time‐averaged catchment‐scale modelling in a large lowland river

Istvánovics

Honti

Kovács³

et al. 2014

Freshwater Biology

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Summary Using the unregulated, eutrophic Someş River (Romania/Hungary), a tributary of the Upper Tisza River as a model system, we related phytoplankton growth to the structure of river network modified by human intervention. The Time‐Averaged Phytoplankton Increase in Rivers (TAPIR) model was developed by adding two new modules (nitrogen emission and phytoplankton growth) to the PHOSFATE model. The latter was a raster‐based, long‐term average GIS tool that computed the flow tree, mean hydrology and phosphorus concentration at fine spatial resolution in the entire catchment. Long‐term monitoring data at the outflow and phytoplankton profiles obtained along the Someş River in 2012 were used to calibrate the models. In summer 2012, a few centric diatom species dominated the phytoplankton, with mean apparent net growth rate of 2.5 day−1 along a ˜100‐km‐long upstream section of the Someş River. This high growth rate was explained by enhanced benthic retention of meroplanktonic diatoms, while further downstream mean algal biomass varied between 80 and 100 mg Chl m−3. The TAPIR model realistically reproduced observed mean biomass profiles of phytoplankton in the Someş River. According to modelling results, P‐determined biomass capacity prevented further growth of algae along the lower two‐thirds of the river. Channel slope and form were important reach‐scale determinants of phytoplankton recruitment, while the absence of large tributaries along the Someş River resulted in marginal longitudinal changes in dilution and light availability. Therefore, phytoplankton might achieve high biomass in a wide range of instantaneous net growth rates realised under strongly fluctuating environmental conditions, which combined with the abundant nutrients from urban areas underpins advanced eutrophication. Large montane reservoirs on tributaries increased mean water age at the outflow of the Someş catchment by an order of magnitude compared with pristine conditions, but had a negligible overall impact on the phytoplankton of the Someş River. Growth of river phytoplankton is intrinsically linked with network topology, including spatial distribution of nutrient inputs. Stochastic variability in discharge tends to destabilise, while specific network properties may stabilise phytoplankton growth in large rivers. Shallow rivers support meroplanktonic diatoms that, depending on discharge, may have adequate time to develop summer blooms, making shallow rivers particularly susceptible to eutrophication.

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Differences in organic matter and bacterioplankton between sections of the largest Arctic river: Mosaic or continuum?

Gladyshev

Kolmakova

Толомеев

et al. 2015

Limnology & Oceanography

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We studied biogeochemical characteristics, including organic carbon and nitrogen contents, fatty acid (FA) composition, stable isotope ratios, and primary production in conjunction with species composition of bacterioplankton, using next generation sequencing, in the Yenisei River along a distance ∼1800 km. Basing on FA composition of particulate organic matter (POM) and on other indicators of sources of POM, the river was subdivided into four sections. The upper section 1, situated in mountain region, was the net source of high‐quality autochthonous organic matter, produced primarily by diatoms and partly consumed by specialized bacteria species. Section 2 in plain taiga was net sink of high quality allochthonous and autochthonous organic matter, produced by cyanobacteria and green algae. Section 3 was net sink of organic matter, primarily allochthonous, consumed by the specialized species of bacteria. The lowest section 4, situated in tundra, was primarily the conduit of recalcitrant terrestrial organic matter, but also the net source of autochthonous organic matter, produced by diatoms. Biogeochemical traits of sections of the Yenisei River evidently shaped dominant species composition of bacterioplankton of these sections. Regarding the biogeochemical and microbiological data, we concluded that the Yenisei River ecosystem complexly combines features of river mosaic, river continuum, and “neutral pipe.”

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Potamoplankton and primary productivity in the River Danube

Cited by 22 publications

References 57 publications

Efficiency of nutrient management in controlling eutrophication of running waters in the Middle Danube Basin

Efficiency of nutrient management in controlling eutrophication of running waters in the Middle Danube Basin

Phytoplankton growth in relation to network topology: time‐averaged catchment‐scale modelling in a large lowland river

Differences in organic matter and bacterioplankton between sections of the largest Arctic river: Mosaic or continuum?

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