Skip to main content
Dryad logo

What is the best fitness measure in wild populations? A case study on the power of short-term fitness proxies to predict reproductive value

Citation

Alif, Vita Ziva et al. (2022), What is the best fitness measure in wild populations? A case study on the power of short-term fitness proxies to predict reproductive value, Dryad, Dataset, https://doi.org/10.5061/dryad.q83bk3jjw

Abstract

Fitness is at the core of evolutionary theory, but it is difficult to measure accurately. One way to measure long-term fitness is by calculating the individual’s reproductive value, which represents the expected number of allele copies an individual passes on to distant future generations. However, this metric of fitness is scarcely used because the estimation of individual’s reproductive value requires long-term pedigree data, which is rarely available in wild populations where following individuals from birth to death is often impossible. Wild study systems therefore use short-term fitness metrics as proxies, such as the number of offspring produced. This study obtained three frequently used short-term proxies for fitness obtained at different offspring life stages (eggs, hatchlings, fledglings and recruits), and compared their ability to predict reproductive values derived from the genetic pedigree of a wild passerine bird population. We used twenty years of precise field observations and a near-complete genetic pedigree to calculate reproductive success, individual growth rate and de-lifed fitness as lifetime fitness measures, and as annual de-lifed fitness. We compared the power of these metrics to predict reproductive values and lineage survival to the end of the study period. The three short-term fitness proxies predict the reproductive values and lineage survival only when measured at the recruit stage. There were no significant differences between the different fitness proxies at the same offspring stages in predicting the reproductive values and lineage survival. Annual fitness at one year old predicted reproductive values equally well as lifetime de-lifed fitness. However, none of the short-term fitness proxies was strongly associated with the reproductive values. In summary, the commonly short-term fitness proxies capture long-term fitness with intermediate accuracy at best, if measured at recruitment stage. As lifetime fitness measured at recruit stage and annual fitness in the first year of life were the best proxies of long-term fitness, we encourage their future use.