THE TEMPORALLY INTEGRATED MONITORING OF ECOSYSTEMS (TIME) PROJECT DESIGN .1. CLASSIFICATION OF NORTHEAST LAKES USING A COMBINATION OF GEOGRAPHIC, HYDROGEOCHEMICAL, AND MULTIVARIATE TECHNIQUES

This investigation is part of the Temporally Integrated Monitoring of Ecosystems (TIME) project, an effort to meet the difficult challenge o f monitoring surface water quality in the northeastern United States f or signs of change in response to the Clean Air Act Amendments of 1990 . The overall objective of the study was to develop a unified scheme f or classifying lakes in the northeast into relatively homogeneous grou ps and improve the likelihood of detecting water quality trends in the region. The study approach involved combining the best elements of se veral procedures recently used for defining regional subpopulations of lakes; these were termed the hydrogeochemical model (HM), geographica l model (GM), and multivariate statistical model (MSM). Lake and water shed data from the U.S. Environmental Protection Agency Eastern Lake S urvey (ELS) were used to evaluate the classification methods and their modifications, After preliminary comparisons were made of the three c lassification schemes, it was concluded that the resulting subpopulati ons indicated that there was meaningful similarity among methods but t hat the significant dissimilarity reflected distinctive attributes of each classification method, These differences were deemed important. a ccordingly, integration of the methods entailed efforts to preserve pa rts of each. This was accomplished by assigning each lake of the ELS d ata set into a lake cluster that bad been defined by jointly applying the HM and GM methods. Subsequently, the jointly classified clusters w ere aggregated by coupling an application of the MSM (cluster analysis ) with subjective judgment regarding termination of the process of clu ster formation. This integration of procedures gave rise to nine subpo pulations that separated mainly on the basis of hydrogeochemical facto rs, though geographic influences also were evident in the results, The integrated classification procedure provided an explicit method invol ving the combination of several kinds of data to yield lake subpopulat ions. Although the process of integrating this information may stand a lone as a useful exercise, the results obtained from the integrated cl assification model exhibited less dispersion than those formed by the parent procedures. This is an important consideration when subpopulati on homogeneity is wanted as a means to improve trend detection. From t he view of statistical efficiency, therefore, the integrated procedure may be considered to be more optimal than the parent schemes, When th e complexity of the integrated approach is considered, however, we con clude that the next most precise classification scheme, the HM approac h, may be preferred over the integrated classification for use in the design of an actual monitoring program.