In this study, a 1D model of reservoir hydrodynamics DYRESM has been applied to Sau Reservoir, a river valley reservoir in the North-Eastern Spain. Simulation is undertaken for 3 years (1995-1997). Meteorological input data measured at the dam are only available from May of 1997. In this case the simulation results fit measured temperatures very well. In the remaining periods, some meteorological data (radiation, wind and rainfall) were obtained from two nearby stations. Simulated temperature distribution in 1996 is close to the observed one. In 1995, however, the simulated result is far from the observed data. Inflows, outflow and local meteorological events such as storms and gusts of wind seem to be responsible for the differences. By changing some parameters, the effects of flow, light extinction coefficient and outlet elevation on thermal stratification are investigated. Simulations demonstrate that the inflow with high temperature is the main factor controlling the thermal structure in Sau Reservoir and demonstrate that the effect of residence time on thermal stratification is manifested mainly by the changes in the depth of thermocline.

The zooplankton of 18 reservoirs of South China was investigated in 2000. 61 Rotifera species, 23 Cladoceras and 14 Copepodas were identified. The most frequent Rotifera genera were Keratella, Brachionus, Trichocerca, Diurella, Ascomorpha, Polyarthra, Ploesoma, Asplanchna, Pompholyx and Conochilus. Bosmina longirostris, Bosminopsis deitersi, Diaphanosoma birgei, D. brachyurum and Moina micrura were typical of Cladocera in the reservoirs. Phyllodiaptomus tunguidus, Neodiaptomus schmackeri and Mesocyclops leuckarti were the most frequent Copepoda and M. leuckarti dominated Copepoda in most reservoirs. High zooplankton species richness with low abundance was characteristic of the throughflowing reservoir, whereas low species richness with low abundance was found in the reservoir with the longest retention time. Relative high abundance and medium species diversity were the distinction of intermediate retention time reservoirs.

Empirical biomass spectra in which biomass is measured in logarithmically equal body size intervals are different from those measured in linearly equal size intervals. Moreover, the scales of body size used by different authors may differ, e. g., length, volume, equivalent!sphere diameter and body mass. The discrete models derived to explain the regularity of the empirical spectra are dependent on the choice of size-scales and size!intervals. Hence, evaluating the effect of size scales and intervals on biomass spectra is helpful for understanding the size!structures of ecosystems. In the present contribution, we analyse the relationships between the size measures used frequently in expressing the empirical data and discuss the difference between the biomass spectra organized in logarithmically equal size intervals and those in linearly equal size intervals. On this basis, we present the distribution function of biomass spectral density and transformation to different size scales. After dexthe effect of size intervals on the distribution functions of biomass spectral density, we give an example of the calculation of this effect by assuming that the distribution function of biomass spectral density is an allometric relationship. Finally, we explore the influence of size intervals on the validity of three discrete models developed by Kerr, Sheldon and co!workers and Borgman.

The paper analyzes the overall diversity of trophic structures and processes at the organizational level of ecosystems. The overall diversity based on Lindeman's trophic dynamics is considered as one-dimensional diversity. By unfolding ecosystems, trophic structures and processes of ecosystems are expressed in two-dimensional space along compartment and trophic level axes. By use of the Shannon-Weaver diversity index, the overall diversity of two-dimensional distributions of standing stocks or throughflows, which are significantly different from those defined in one-dimensional space, is determined. When flows between compartments are partitioned across trophic levels we can determine the overall diversity of three-dimensional distribution of throughflows over two compartment axes and a trophic level axis. The relationships between these overall diversity indexes defined in the different dimensional spaces are formulated by use of trophic niches and trophic functions as suggested by Higashi et al. (1992). The three-dimensional diversity of throughflows fall into three parts. The first identifies the overall diversity of two-dimensional distribution along compartment and trophic level axes. The second indicates the average diversity of resources utilized in an ecosystem. The third specifies the transfer efficiency of flows in an ecosystem. The three-dimensional diversity of throughflows may support a new framework to understand trophic structures and processes. Two real ecosystems are examined through the calculation of overall diversity indexes. The results confirm the differences between diversity indexes defined in different dimensions. Out of all the diversity indexes, those related to paths (to the third-dimension) are more powerful to reveal differences in trophic structures and processes between the two ecosystems.

A mechanistic model is developed to present the photosynthetic response of phytoplankton to irradiance at the physiological level. The model is operated on photosynthetic units (PSU), and each PSU is assumed to have two states: reactive and activated. Light absorption that drives a reactive PSU into the activated state results from the e!ective absorption of the PSU. Transitions between the two states are asymmetrical in rate. A PSU in the reactive state becomes activated much faster than it recovers from the activated state to the reactive one. The turnover time for an activated PSU to transit into the reactive one is defined by the turnover time of the electron transport chain. The present model yields a photosynthesis-irradiance curve (PE-curve) in a hyperbola, which is described by three physiological parameters: effective cross-section (σPSII), turnover time of electron transport chain (τ) and number of PSUs (N). The PE-curve has an initial slope of σpus×N, a half-saturated irradiance of 1/(τσPSII), and a maximal photosynthetic rate of τN/at the saturated irradiance. The PE-curve from the present model is comparable to the empirical function based on the target theory described by the Poisson distribution.