increase variability in fawn recruitment beyond certain finite 

 mathematical and biological limits. Fawn recruitment cannot 

 be less than zero no matter how bad the year and practically 

 cannot be higher than about 1.8 fawns per 2-year-old and older 

 female, no matter how good the conditions. Because of those 

 considerations, we can place fawn-rearing conditions and 

 recruitment levels into limited categories. 



If forage quality and fawn-rearing years are rated on a 

 scale of 1-10, with 10 being the best and 1 the worst, we can 

 illustrate scenarios indicating that random variation can 

 mimic properties of density-dependence. For example, at the 

 most extreme end, a year that was at the best level for 

 fawn-rearing and recruitment (10) can only be followed by a 

 year that is equal to it (10) or worse (1-9). Random chance 

 dictates that the year following the best year will usually 

 (90% probability) be worse. If year A was an 8 for 

 fawn-rearing conditions, or years A and B were 9 and 8, by 

 random chance the next year is more likely to be worse (1-7, 

 70%) than equal or better (8-10, 30%). Random environmental 

 variation can lead, over time, to any possible successive 

 combination of years, but regression to the mean and random 

 chance dictate that, on average, relatively poorer 

 fawn-rearing years will follow relatively good fawn-rearing 

 years and vice versa. Thus, it will appear than an increase 

 in deer density (resulting from good years) is followed by a 

 decrease in recruitment. Also, the increase in non-productive 

 yearlings automatically lowers population recruitment rates to 

 some extent. Alternatively, a year or 2 of good fawn 

 recruitment often follows several years of declining deer 

 density (resulting from poor recruitment) . When observed over 

 the short-term, these scenarios appear to represent 

 density-dependent fawn recruitment. The same scenarios, 

 however, can result from randomly varying environmental 

 conditions and regression to the mean. 



Any data purporting to prove density-dependent 

 relationships must show that it occurs to a greater or more 

 precise degree than would appear to occur because of random 

 variation. Longer-term studies can place this phenomena in 

 perspective and indicate, at least on this area, that similar 

 levels of increases and of decreases in recruitment occurred 

 over a wide range of densities. The importance of long-term 

 studies (20 years +) in interpretation of cause and effect can 

 be illustrated by our data. A study on our area starting in 

 1973 and continuing for 7 years (through 1979) would have 

 indicated that fawn survival increased as density increased 

 (Fig. 11.2). We do not mean to imply here that fawn survival 

 does increase with density, only that it is not necessarily 

 related to density. Most wildlife/population ecologists 

 consider 7 years to be a long-term study. Certainly most 

 published studies, including most indicating support for 



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