Micropaleontological research can create great quantities of data. The use of computers has increased the ability to collect and manage this data. Since time and resources are limited it is important to extract and understand as much useful information as possible from these large data sets in a timely fashion.
Pareto analysis allows for determination of which few of the many variables significantly affect measured end results. This methodology has traditionally been used to design and optimize industrial processes (Haaland 1989). We have applied Pareto analysis to a set of data containing relative abundances of arcellaceans and formaminifera from sediment-water interface samples from different environments. Previous research on arcellaceans indicate that Centropyxis aculeata (Ehrenberg 1832) is tolerant of brackish conditions (Scott 1977; Scott and Medioli 1980; Collins 1996), while Difflugia corona (Wallich 1864) and Lagenodifflugia vas (Medioli and Scott 1983) are opportunistic species in stressed lacustrine environments (Boudreau 1999). Cribroelphidium gunteri (Cole 1931) is a euryhaline marine foraminifera. However, it has also been found alive in non marine settings including the stressed environment caused by salt spring injection of waters, up to and including brines, in northern Lake Winnipegosis, Manitoba (Boudreau 1999; Patterson et al. 1997; McKillop et al. 1992). In this paper we will demonstrate how Pareto analysis allowed us to quickly and easily identify the main environmental factors contributing to the abundance of these different species and to determine whether the unusual conditions found in Lake Winnipegosis modified their preferred habitats.