Redundant relationships in multiplex food sharing networks increase food security in a nutritionally precarious environment

TL;DR

This study shows that redundant relationships in multiplex food sharing networks among horticulturalists reduce food insecurity, highlighting the importance of network structure in mitigating nutritional risk in precarious environments.

Contribution

The paper introduces new network measures that incorporate varying levels of structural information to analyze the role of redundancy in food sharing networks.

Findings

Redundant relationships correlate with fewer skipped meals.

Network structure influences food security in high-risk environments.

Redundancy helps mitigate risks in human foraging strategies.

Abstract

Specialization is a hallmark of humans. Specialization in the real world (with imperfectly sorted partners, imperfectly calibrated supply and demand, and high failure risk) requires redundancy in relationships, which prevents specialists from going hungry when some of their partners fail to capture highly variable food items and derive the most value when dividing surplus harvests. The burgeoning field of multilayer network analysis offers tools to test for the effect of redundant relationships in food sharing networks on hunger. We derive measures that include progressively more network structure: measures without any network structure, those that only include information about individuals, and those that include all information about individuals and domains. We test for the effects of these measures in a sample of horticulturalists living in the savannahs of the Guyana Shield, a nutritionally precarious environment. Having redundant relationships is associated with a lower incidence of reported skipped meals. This provides evidence that redundancy in food sharing networks may mitigate risk associated with the foraging strategies necessary to support a large-brained, generalist omnivore. This result has consequences for broader debates in the field of human evolution such as why humans live in groups with low relatedness.