“…The desmid genus Staurastrum, and dinoflagellates Peridinium which were found dominant in the present study are generally found in oligotrophic waters [35]. The presence of chrysophytes in combination with one or two other algal groups, which can be the cryptophytes, diatoms and/or dinoflagellates indicates oligotrophic or mesotrophic conditions [8]. Malek et al [42] in their study on the Bacillariophyceae dynamics indicated that Putrajaya Lake trophy interchanged between oligotrophic to mesotrophic.…”
The distribution of the phytoplankton community in different zones of Putrajaya Lake, Malaysia was analyzed from October 2009 to September 2010 to examine the zonal-distribution relationship. Three stations representing three different lake zones namely Station 1 (littoral zone), Station 2 (sub-littoral zone) and Station 3 (limnetic zone) were selected. Water transparency, temperature, pH, dissolved oxygen and conductivity were found to be important factors characterizing each zone. A total of 148 species from 77 genera were recorded throughout the sampling duration from October 2009 until September 2010. During this period, Chlorophyta was the most abundant group (59% of the total phytoplankton), followed by Pyrrhophyta (15%), Cyanobacteria (11%), Bacillariophyceae (9%), Chrysophyceae (3%), Cryptophyta (2%) and Euglenophyta (1%). The highest mean density of phytoplankton was recorded in the limnetic zone (433.94 ± 18.29 cells ml-1), followed by sub-littoral (292.94 ± 18.61 cells ml-1) and littoral zone (199.58 ± 13.56 cells ml-1). There was a significant difference in the Shannon-Wiener diversity index for phytoplankton diversity and abundance in all three zones (p<0.05) with limnetic zone demonstrating the highest species diversity. 150 Asma' Jamal et al. Species commonly found in the sub-littoral area also dominated both littoral and limnetic phytoplankton communities suggesting that sub-littoral zone acted as an interphase for phytoplankton adaptation and migration between the two different zones. The findings suggest that spatial distribution and diversity of the phytoplankton community can be affected significantly by local lake zonation characterized by environmental variations.
“…The desmid genus Staurastrum, and dinoflagellates Peridinium which were found dominant in the present study are generally found in oligotrophic waters [35]. The presence of chrysophytes in combination with one or two other algal groups, which can be the cryptophytes, diatoms and/or dinoflagellates indicates oligotrophic or mesotrophic conditions [8]. Malek et al [42] in their study on the Bacillariophyceae dynamics indicated that Putrajaya Lake trophy interchanged between oligotrophic to mesotrophic.…”
The distribution of the phytoplankton community in different zones of Putrajaya Lake, Malaysia was analyzed from October 2009 to September 2010 to examine the zonal-distribution relationship. Three stations representing three different lake zones namely Station 1 (littoral zone), Station 2 (sub-littoral zone) and Station 3 (limnetic zone) were selected. Water transparency, temperature, pH, dissolved oxygen and conductivity were found to be important factors characterizing each zone. A total of 148 species from 77 genera were recorded throughout the sampling duration from October 2009 until September 2010. During this period, Chlorophyta was the most abundant group (59% of the total phytoplankton), followed by Pyrrhophyta (15%), Cyanobacteria (11%), Bacillariophyceae (9%), Chrysophyceae (3%), Cryptophyta (2%) and Euglenophyta (1%). The highest mean density of phytoplankton was recorded in the limnetic zone (433.94 ± 18.29 cells ml-1), followed by sub-littoral (292.94 ± 18.61 cells ml-1) and littoral zone (199.58 ± 13.56 cells ml-1). There was a significant difference in the Shannon-Wiener diversity index for phytoplankton diversity and abundance in all three zones (p<0.05) with limnetic zone demonstrating the highest species diversity. 150 Asma' Jamal et al. Species commonly found in the sub-littoral area also dominated both littoral and limnetic phytoplankton communities suggesting that sub-littoral zone acted as an interphase for phytoplankton adaptation and migration between the two different zones. The findings suggest that spatial distribution and diversity of the phytoplankton community can be affected significantly by local lake zonation characterized by environmental variations.
“…Those levels are very close to r values of the stable period (1983 -1986) of Lake Kinneret (Table 1). While changes in the phytoplankton taxonomic composition took place at Lake Tahoe over that time period, and the species richness (number of species) has dropped by more than 30 % (from 129 in 1983 to 72 -81 in 2002 -2005; (Hunter et al, 1990;Winder and Hunter, in press), almost the same TTSS general pattern was evident (Fig. 1).…”
Both theoretical ecology and lake management practices acutely need quantitative assessment tools for the analysis of structural changes taking place in the plankton community. Size spectrum, a tool allowing such assessment, is usually based on size distributions of organisms irrespective of their taxonomy. The size-frequency distribution of taxonomic units in an assemblage, named by us traditional taxonomic size spectrum (TTSS), has been applied for over 70 years, but seldom in aquatic ecology. Longterm consistency of phytoplankton TTSS, evidenced even during pronounced ecosystem changes, was described for the subtropical and eutrophic Lake Kinneret, Israel. In the present study, we examine whether consistent TTSS patterns prevail across ecosystems, and apply the TTSS to the phytoplankton of the temperate and oligotrophic Lake Tahoe, USA.A typical annual TTSS pattern was revealed, and its details were analyzed quantitatively by hierarchical cluster analysis. The Tahoe TTSS similarity level during 4 years (Pearson r = 0.92 to 0.99) is comparable to that of the Kinneret during its stable period; even for pairs divided by >20 years, r > 0.8. While the Tahoe TTSS general pattern resembles that of Lake Kinneret, the two lakes are distinguishable by means of cluster analysis. A high similarity (r = 0.91) was found between the eight-year averaged TTSSs of the two lakes. The above results let us suppose that the longterm consistency of the aquatic assemblage taxonomic size structure pattern is a general phenomenon. This pattern deserves special attention at times of accelerated global climate change, acerbated by burgeoning anthropogenic impacts.
“… References: 1, Bowie et al [1985, Table 6‐5]; 2, Bowie et al [1985, Table 6–18]; 3, Bowie et al [1985, Table 6‐20]; 4, Chapra [1997, Figure 2.11]; 5, Chapra [1997]; 6, Bowie et al [1985, Table 6‐4]; 7, Marjanovic [1989, p. 326, Table 16]; 8, Bowie et al [1985, Table 6‐19]; 9, Hunter et al [1990]; 10, Schladow and Hamilton [1997]; 11, Bowie et al [1985, Table 5‐3]; 12, Bowie et al [1985, Table 5‐4]; 13, Eppley et al [1969]; 14, Chapra [1997, Table 33.1]; 15, Bowie et al [1985, Table 5‐5]; 16, Chapra [1997, p. 40]; 17, Swift et al [2006]; 18, Reuter and Miller [2000]; 19, Arhonditsis and Brett [2005]; 20, Omlin et al [2001]; 21, Romero et al [2004]; 22, O' Melia [1985]; 23, Casamitjana and Schladow [1993]; 24, Bowie et al [1985, Table 6‐10]; 25, Cerco et al [2004]; 26, Beutel [2000]. …”
[1] A quasi-two-dimensional lake clarity model (LCM) was developed to better understand the impacts of pollutant load on lake/reservoir water quality and to provide guidelines for lake/reservoir management and restoration. Though the LCM can be applied to any lake, the model was calibrated and validated using the available detailed data set of Lake Tahoe. The estimated and measured annual average Secchi depths demonstrate a very high degree of agreement with relative error of less than 6%. The sensitivity analysis was performed on those parameter(s)/load(s) found to have a large effect on lake clarity. Loading and settling rates of fine inorganic particles (<16 mm in diameter) were found to have the largest effect on lake clarity. Atmospheric load adds inorganic particles and nutrients to the surface layer, thus directly affecting lake clarity. Since maximum chlorophyll a concentration is observed in deep water (approximately 50 m below surface) during spring and summer, the Secchi depth (approximately 20-22 m) was found to be relatively insensitive to the change in chlorophyll a concentration in this deep layer. The model was used to simulate different load reduction scenarios to help answer questions such as how much load reduction is needed to restore Lake Tahoe's historic clarity of approximately 30 m and how quickly this change can be achieved? The LCM provides a firsthand scientific solution to managers that the historic clarity can be achieved if total reduction of nutrients and inorganic particles loads will be reduced to approximately 55% from all sources or approximately 75% from urban sources.Citation: Sahoo, G. B., S. G. Schladow, and J. E. Reuter (2010), Effect of sediment and nutrient loading on Lake Tahoe optical conditions and restoration opportunities using a newly developed lake clarity model, Water Resour. Res., 46, W10505,
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