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D. Time Analysis <br />The re aression analysis that Droduces the results listed in Table 9 <br />(Regression of Reclamation Area Age including 1979 area data) and Table <br />10 (Regression of Reclamation Area Age excluding 1979 area data) seems to <br />be based comnletely on 1988 collected data. The authors analyze data <br />collected in the same year from four reclaimed areas. Because the areas <br />were reclaimed in different years the implication is that these data <br />portray the successional pattern vrhich would develop in one area in <br />different years after revegetation. While this seems a logical <br />assumption, it is suspect and conclusions drawn from such an analysis <br />should be viewed only as hypotheses worthy of further study. One of the <br />potential complicating factors in this case is that weather and seeding <br />practices have not been continuous for the reveoetated areas. Weather <br />characteristics, for instance rainfall, add much variability to the <br />revegetation results. The same seed mix can result in different species <br />compositions depending on the rainfall. Thus, Dlots reclaimed in <br />different years but sampled in the same year have developed under <br />different conditions, responded to different stresses, and do not <br />represent a time sequence. It cannot be proven how close or far from a <br />true time sequence this data is. This point is corroborated by Halpein <br />(1989) who states on page 704: <br />"In many terrestial systems, models of successional change have developer <br />largely from studies that use stands of different ages arranged <br />chronologically to portray temporal sequences. Interpretation of these <br />chronosequences is necessarily based on the assumption that <br />predisturbance vegetation, environment, and post disturbance influences <br />are uniforn among sites. As a Consequence, species patterns ostensibly <br />associated with successional age may be confounded by historical or <br />stochastic phenomena. To remove these confounding factors, studies baser <br />on the repeated observation of permanent plots have been employed. <br />However, for permanent plot studies to be useful in understanding the <br />dynamics of short-lived species or populations with episodic fluctuation, <br />lone-term, frequent sampling is necessary." <br />c. Interpretation of Rea ression Analysis <br />The authors interpret the results of regression analysis as Droof of <br />influence, concluding for example that certain herb species which are <br />negatively correlated to woody elant density, actually physically <br />decrease wooey pan density. The argument against drawing such <br />conclusions is summarized by Hoel (1970) on page 192: <br />"The interpretation of a correlation coefficient as a measure of the <br />strength of the linear relationship between the variables is a purely <br />mathematical interpretation and is completely devoid of any cause or <br />effect implications. The fact that these two variables tend to increase <br />or decrease together does not imply that one has any direct or indirect <br />effect on the other. Both may be influenced by other variables in suci~ a <br />manner as to give rise to a strong mathematical relationship." <br />-4- <br />