Cumulative Adversity Index: A Framework to Investigate the Effect of
Multiple Stressors in Natural Populations
Abstract
Early life experiences have a disproportionate impact on individuals’
fitness, but most research has focused on the effects of single
experiences, or stressors, often under controlled conditions. Protecting
natural populations that must contend with co-occurring stressors
requires a better understanding of how multiple early-life stressors
affect the health and ecology of natural systems. However, the
complexity of such research has limited its advancement. To address this
challenge, human studies adopted cumulative risk models that predict
adult health risk based on early adversity exposure. We propose a novel
framework on how to adapt such models to assess the health and ecology
of natural populations. In this framework we detail how and when to
develop various types of cumulative early adversity (CEA) indices for
wild populations. We then use a case study to demonstrate that such
indices can predict pup survival and adult longevity in a wild
population of yellow-bellied marmots (Marmota flaviventer). Our results
highlight that CEA indices yield unique insights and improve model fit.
With this framework we hope to spur further investigations on the impact
of cumulative adversity in natural systems, which is critical to inform
conservation and management in the Anthropocene.