Distribution and summer diapause of Canthocamptus staphylinus (Jurine) (Copepoda: Harpacticoida) in Lake Ladoga
The spatial distribution of Canthocamptus staphylinus (Jurine) in Lake Ladoga was examined. C. staphylinus is one of the most numerous species of harpacticoids in the lake. It can dwell in almost all littoral biotopes. In profundal biotopes strongly exposed to anthropogenic influence (pollution and eutrophication) only this species of harpacticoid was found. A peculiarity of C. staphylinus biology is that in summer individuals are in the resting stage as cysts. In summer active individuals were found in littoral habitats at a water temperature of 20 °C, but their number was small in comparison with cold periods of the year. In the littoral zone the relative number of individuals in cysts was clearly related to water temperature. Twelve degrees temperature appears to be critical for development of littoral populations of C. staphylinus.
A parthenogenetic life cycle in a population of Canthocamptus Staphylinus (Copepoda, Harpacticoida)
The harpacticoid copepod Canthocamptus staphylinus (Jurine) was shown to reproduce parthenogenetically in an oligotrophic Finnish lake. The population was univoltine with peaks of egg production in winter and early spring. Young from both peaks became adults in spring and aestivated as cysts. Laboratory experiments suggested that either high temperature (12 °C or more) or long days will inhibit egg production, but that both factors together are needed to induce encystment. Embryonic survival was low, on the average only 60%. The population was limited by low food levels in winter, and it is suggested that food shortage prevents the species from colonizing the profundal zone of oligotrophic lakes.
Evidence of spurious results along with spatially autocorrelated errors in the context of geographically weighted regression for two independent SAR(1) processes
AbstractThe aim of this paper is to examine the performance of the geographically weighted regression (GWR) technique in terms of recognizing linear relationships at the local level. Using a Monte Carlo analysis with two independent spatially autocorrelated SAR(1) processes, this study finds that spurious behavior exists at the local level along with spatially autocorrelated errors. Therefore, GWR estimation results must be interpreted with caution.
