Fluctuating asymmetry as a putative marker of human-induced stress in avian conservation

Abstract

As anthropogenic stress increasingly affects the viability of natural populations of animals and plants, conservation ecologists are challenged to identify vulnerable populations before their demographic and/or genetic properties become irreversibly affected. Since traditional biomarkers of anthropogenic stress are often cumbersome to measure, and populations may thus go extinct before appropriate data can be obtained, there is a growing interest in individual-based markers that do not require repeated captures, are relatively easy to measure, and allow mitigating action one step ahead. One such marker, left-right asymmetry in bilateral symmetrical traits (“fluctuating asymmetry”, FA) has become an established bioassay of the quality and health of individuals and populations in evolutionary-ecological studies. However, the lack of a theoretical framework that predicts under which ecological conditions relationships between FA, stress and fitness can be expected, continues to hamper the use of FA in applied conservation. Here, we briefly review the concept, measurement and analysis of FA, and appraise its expediency in a selection of 21 avian studies covering environmental or genetic stress commonly encountered in conservation biology. The majority of studies met the basic statistical requirements of FA analysis, and two-thirds reported significant, positive relationships with environmental or genetic stress, although with substantial variation among traits, stresses, ages and sexes. In most cases, the observed heterogeneity in relationships with FA could be explained by taking into account both methodological and conceptual issues. Effect sizes ranged from very small (0.02) to very large (0.76), with a weighted average of 0.30, indicating that on average 9% of variance in the variable of interest was explained by FA. Given the intrinsic difficulties associated with FA analysis, conservation ecologists are advised to combine information from FA with that of other individual-based biomarkers, such as the study of growth-bar dimensions on developing feathers.