Distribution and community-level effects of the Chinese mystery snail (Bellamya chinensis) in northern Wisconsin lakes

Managing invasive species requires information about their distributions and potential effects, but community-level impacts of invasive animals remain poorly understood. The Chinese mystery snail (Bellamya chinensis) is a large invasive gastropod that achieves high densities in waters across North America, yet little is known about its ecological significance in invaded systems. We surveyed 44 lakes to describe the patterns and determinants of B. chinensis distributions in northern Wisconsin, USA, and to assess the likelihood of effects on native snail communities in the invaded systems. B. chinensis was widespread among surveyed lakes (21 of 42 lakes with snails) and its occurrence was correlated with indicators of lake productivity and anthropogenic dispersal vectors (boat landings, distance to population centers, shoreline housing density). Some native snail species tended not to occur at sites where B. chinensis was abundant; among these was Lymnaea stagnalis, which suffered reduced survival in the presence of B. chinensis in a recently published mesocosm study. However, there was no difference in overall snail assemblage structure at either the site or lake level as a function of B. chinensis presence or abundance. Lake occurrences of many snail species have apparently been lost over time, but a comparison to a 1930s survey showed that there was no increased likelihood of species loss in lakes invaded by B. chinensis (or by the invasive crayfish Orconectes rusticus). Although B. chinensis is widespread and sometimes abundant in northern Wisconsin lakes, it does not appear to have strong systematic impacts on native snail assemblages.     

Accumulation of unglycosylated liver secretory glycoproteins in the rough endoplasmic reticulum

Previous studies in this laboratory (1) have shown that tunicamycin-treatment inhibits the secretion of three secretory glycoproteins--alpha 2-macroglobulin, ceruloplasmin, and alpha 1-protease inhibitor in human hepatoma (Hep G2) cell cultures. In the present study, we have investigated (i) their site of accumulation within the endoplasmic reticulum/Golgi pathway, and (ii) the solubility characteristics of these unglycosylated proteins. Using percoll density gradient centrifugation, we found that tunicamycin-treatment markedly inhibited the transport of alpha 2-macroglobulin, ceruloplasmin and alpha 1-protease inhibitor from the rough endoplasmic reticulum. However, there was no detectable changes in their solubility properties as both the glycosylated and unglycosylated species were associated with the 100,000 xg supernatant fraction following disruption of the microsomal fraction (i) with 0.2% Triton X-100 and (ii) by repeated freeze-thaw cycles. Also no evidence of protein aggregation was detected by liquid chromatography of the unglycosylated proteins on Bio-Gel A-1.5 column.     

An artificial neural network approach for studying phytoplankton succession

Artificial neural networks are used to model phytoplankton succession and gain insight into the relative strengths of bottom-up and top-down forces shaping seasonal patterns in phytoplankton biomass and community composition. Model comparisons indicate that patterns in chlorophyll aconcentrations response instantaneously to patterns in nutrient concentrations (phosphorous (P), nitrite and nitrate (NO₂/NO₃–N) and ammonium (NH₄–H) concentrations) and zooplankton biomass (daphnid cladocera and copepoda biomass); whereas lagged responses in an index of algal community composition are evident. A randomization approach to neural networks is employed to reveal individual and interacting contributions of nutrient concentrations and zooplankton biomass to predictions of phytoplankton biomass and community composition. The results show that patterns in chlorophyll aconcentrations are directly associated with P, NO₂/NO₃–N and daphnid cladocera biomass, as well as related to interactions between daphnid cladocera biomass, and NO₂/NO₃–N and P. Similarly, patterns in phytoplankton community composition are associated with NO₂/NO₃–N and daphnid cladocera biomass; however show contrasting patterns in nutrient– zooplankton and zooplankton–zooplankton interactions. Together, the results provide correlative evidence for the importance of nutrient limitation, zooplankton grazing and nutrient regeneration in shaping phytoplankton community dynamics. This study shows that artificial neural networks can provide a powerful tool for studying phytoplankton succession by aiding in the quantification and interpretation of the individual and interacting contributions of nutrient limitation and zooplankton herbivory on phytoplankton biomass and community composition under natural conditions.