Factors influencing detection of density dependence in British birds : II. Longevity and population variability

Oecologia. 1996 Oct;108(1):54-63. doi: 10.1007/BF00333214.

Abstract

If censuses are taken at less than generation intervals, the number of successive censuses in which a given individual is recorded will depend on longevity. Repeatedly recording the same individuals could produce under-estimates of population variability and influence detection of density dependence. We investigated this possibility in 60 time series of abundances of British birds compiled from the Common Birds Census data and then used simple population models to illustrate the proposed mechanism. Species had average lifespans of 2-10 years and were censused annually. Density dependence was detected (at P<0.05) much more frequently in bird species with long lifespans than in those with short lifespans; 75% of the 12 longest-lived species showed density dependence compared to 46% of all species. Population variability measured in annual censuses (termed "annual variability") was lower in bird species with longer lifespans. We used discrete time models based on difference equations to demonstrate how longevity influences population variability and detection of density dependence in series of annual censuses. A model in which only first-year birds experienced density dependence was rejected because annual variability was greater and detection of density dependence was less likely when longevity was greater, the opposite of the observed effects of longevity in birds. A model in which all age classes experienced density dependence gave time series with lower annual variability and in which density dependence was detected more frequently when longevity was greater, which is the pattern observed in British birds. Analysis of data from this model showed that the amount of density dependence actually present caused only small changes in annual variability, whereas detection of density dependence from simulated series was strongly influenced by annual variability. The high annual variability of series from short-lived bird species could mask any density dependence that was present. Correcting for trends lead us to detect density dependence in 75% of the 12 longest lived bird species. There is no reason to believe that this rate is not also representative of short-lived species.

Keywords: Common Birds Census; Discrete-time models; Longevity; Population variability; Time series analysis.