Although natural populations are typically subjected to multiple stressors, most past research has focused on single stressors and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 151 ecological three-stressor interactions from 45 published papers. We found that 89% (n=134) of the three-stressor combinations resulted in new or different interactions than previously reported. We also found substantial levels of emergent properties—interactions that are only revealed when all three stressors are present. Antagonism was the most prevalent net interaction whereas synergy was the most prevalent emergent interaction. Understanding multiple stressor interactions is crucial for fundamental questions in ecology and also has implications for conservation biology and population management.

Understanding which foodwebs thrive or collapse is a major challenge that has been mostly studied in terms of topology and interaction strength. Yet the relative importance of these properties is hotly debated due to limited research on how they interact and which forces generate them. Here, we construct a foodweb model that incorporates mass-based constraints on density dependence, maximum consumption rate, and the likelihood and strength of interactions, which in turn control overall topologies and interaction strength distributions. Our model predicts both stability and connectivity that closely match real foodwebs ranging widely in size (29-163 species) and connectivity (113-1086 interactions). Despite their absence in most research, density dependence and maximum consumption rate are not only required to accurately predict stability but have stronger impacts than the more-frequently-studied interaction strength. Our results demonstrate that predicting foodweb stability requires simultaneously considering multiple foodweb properties—all of which naturally emerge from species masses.