The Relationship between Population Size and Temporal Variability in Population Size
The relationship between population size and temporal variability in population size was examined using 2387 populations of 203 species from the Global Population Dynamics Database. Population variability, relative to population size, was assayed by regressing the standard deviation of population size against mean population size. Linear regression produced slopes that were less than one in 165 of 203 species. Thus, temporal fluctuations in population size became significantly weaker as population size increased. Similarly, the slope was significantly less than one for a single regression including all 2387 populations, regardless of taxonomic classification. The slopes of the regression lines did not differ for major taxonomic groupings, but the Y-intercept was significantly lower for birds than for the other taxonomic groupings. Factor analysis was used to examine the highly correlated parameters: data reliability, population size and taxonomic lineage. Population size was obviously the most important parameter affecting temporal variation in population size, data reliability was also very important, but taxonomy was of little or no importance. The relationship between temporal variation in population size and mean population size, predicted from the data, was used to predict the probability of extinction assuming a normal distribution of population sizes. This simple model predicts that populations of vertebrates will have to number in the thousands for long-term conservation to be effective.
D. H. Reed and G. R. Olbricht, "The Relationship between Population Size and Temporal Variability in Population Size," Animal Conservation, vol. 7, no. 1, pp. 1-8, Wiley-Blackwell, Jan 2004.
The definitive version is available at https://doi.org/10.1017/S1367943004003476
Mathematics and Statistics
Keywords and Phrases
Conservation; Population Size; Regression Analysis; Temporal Variation; Aves; Vertebrata
International Standard Serial Number (ISSN)
Article - Journal
© 2004 Wiley-Blackwell, All rights reserved.
01 Jan 2004