Proper management of white-tailed deer (Odocoileus virginianus) populations is important because of the popularity of this species for sport hunting and the ecological and economic damage deer can cause. Managers and biologists have relied for decades on relatively inexpensive and easily collected data from hunter-harvested deer to provide information for making harvest management decisions. We obtained long-term (15–31 years duration, median = 26 years) data sets for 9 populations in the southeastern United States that spanned several physiographic provinces and a wide range of densities (3–32 deer/km2) that varied by a factor of 1.67–5.50 within populations over the study period. Recruitment models using a simple quadratic expression related fawn density to adult female and total adult densities. Models included densities lagged 1 and 2 years in addition to contemporary data. Recruitment models indicated that density-dependent dynamics were operative for 8 of the 9 populations. While the 2-year lag was the preferred context for these models, the 1-year lag was nearly as strong, indicating that recruitment responded to changes in density more quickly than physical condition. Validations using data from 3 additional, independent populations showed that predicted and observed densities were highly correlated (r = 0.45–0.96). That one population on exceptionally poor habitat did not show a significant density-dependent response for recruitment may suggest that some habitats are too poor for such a process to be operative or detectable. The efficacy of time lags also should serve to caution managers not to look for immediate responses in herds. Although the populations examined in this study provided long-duration data that undoubtedly captured a great deal of stochasticity resulting from density-independent factors, significant density-dependent relationships were still detected.
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