New paper: The apportionment of dietary diversity in wildlife

I am excited to share my first principal-author paper of my PhD, The apportionment of dietary diversity in wildlife, which was recently published in PNAS.

In this paper, we questioned whether wildlife biology might be influenced by persistent stereotypes, particularly when researchers inadvertently reinforce these preconceptions by highlighting behaviors that align with existing assumptions about species-specific dietary patterns. Our paper's title draws inspiration from Richard Lewontin's seminal 1972 work, The Apportionment of Human Diversity, in which Lewontin used genetic data to demonstrate that the majority of human genetic variation occurs within populations rather than between populations. Acknowledging that unfounded categorizations of human races arose from historical and social constructs that differ starkly from these descriptors of wildlife guilds, we considered how Lewontin’s data-driven insights could serve as a model to more appropriately understand how variation is apportioned among wildlife groups—and whether this might challenge ecologists’ preconceived notions about how species fit into complex food webs.

We used dietary DNA metabarcoding and a computational ('machine learning') algorithm to help us figure out how many different diet groupings exist within Yellowstone’s herds of large herbivores, and whether each species has a unique diet type. What we show is that dietary differences between species ("niche partitioning”) are smaller than everyone had previously assumed – far less pronounced than similar research on African savannas. Instead, members of different species could have a lot of overlap in their diets and the amount of overlap depended on where and when they were feeding. Combining DNA technology with AI enabled us to break through long-standing stereotypes about what these animals eat, and look at the evidence in new ways.