We compiled and analyzed long-term data, including chemical, physical and phytoplankton community data, for the Lake Biwa ecosystem from 1962 to 2003. Analyses on environmental data indicate that Lake Biwa had experienced intensified eutrophication (according to total phosphorus concentration) in the late 1960s and returned to a less eutrophic status around 1985, and then exhibited rapid warming and thus increased water column stability since 1990. Total phytoplankton cell volume largely followed the trend of total phosphorus concentration, albeit short-term fluctuations existed. However, phytoplankton community shifted dramatically in response to those changes of environmental states. These shifts were cause by changes in trophic status driven by phosphorus loadings and physical properties in the water column driven by warming. Moreover, most phytoplankton species did not show a strong linear correlation with environmental variables, suggesting nonlinear transitions among different states.

We compiled and analyzed long-term (1961–2005) zooplankton community data in response to environmental variations in Lake Biwa. Environmental data indicate that Lake Biwa had experienced eutrophication (according to total phosphorus concentration) in the late 1960s and recovered to a normal trophic status around 1985, and then exhibited warming since 1990. Total zooplankton abundance showed a significant correlation with total phytoplankton biomass. Following a classic pattern, cladoceran/calanoid and cyclopoid/calanoid abundance ratio was related positively to eutrophication. Zooplankton community exhibited a significant response to the boom and bust of phytoplankton biomass as a consequence of eutrophication-reoligotriphication and warming. Moreover, our analyses suggest that the Lake Biwa ecosystem exhibited a hierarchical response across trophic levels; that is, higher trophic levels may show a more delayed response or no response to eutrophication than lower ones. <br><br> We tested the hypothesis that phytoplankton community can better explain the variation of zooplankton community than bulk environmental variables, considering that phytoplankton community may directly affects zooplankton succession through predator-prey interactions. Using a variance partition approach, however, we did not find strong evidence to support this hypothesis. We further aggregate zooplankton according to their feeding types (herbivorous, carnivorous, omnivorous, and parasitic) and taxonomic groups, and analyzed the aggregated data. While the pattern remains similar, the results are less clear comparing with the results based on finely resolved data. Our research explored the efficacy of using zooplankton as bio-indicators to environmental changes at various data resolutions

We compiled and analyzed long-term (1961–2005) zooplankton community data in response to environmental variations in Lake Biwa. Environmental data indicate that Lake Biwa had experienced eutrophication (according to the total phosphorus concentration) in the late 1960s and recovered to a normal trophic status around 1985, and then has exhibited warming since 1990. Total zooplankton abundance showed a significant correlation with total phytoplankton biomass. Following a classic pattern, the cladoceran/calanoid and cyclopoid/calanoid abundance ratio was related positively to eutrophication. The zooplankton community exhibited a significant response to the boom and bust of phytoplankton biomass as a consequence of eutrophication-reoligotriphication and warming. Moreover, our analyses suggest that the Lake Biwa ecosystem exhibited a hierarchical response across trophic levels; that is, higher trophic levels may show a more delayed response or no response to eutrophication than lower ones. <br><br> We tested the hypothesis that the phytoplankton community can better explain the variation of the zooplankton community than bulk environmental variables, considering that the phytoplankton community may directly affect the zooplankton succession through predator-prey interactions. Using a variance partition approach, however, we did not find strong evidence to support this hypothesis. We further aggregated zooplankton according to their feeding types (herbivorous, carnivorous, omnivorous, and parasitic) and taxonomic groups, and analyzed the aggregated data. While the pattern remains similar, the results are less clear comparing the results based on finely resolved data. Our research suggests that zooplankton can be bio-indicators of environmental changes; however, the efficacy depends on data resolution

Understanding how ecosystems will respond to climate changes requires unravelling the network of functional responses and feedbacks among biodiversity, physicochemical environments, and productivity. These ecosystem components not only change over time but also interact with each other. Therefore, investigation of indi

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