How realistic features affect the stability of an Arctic marine food web model

• Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science
• Main Authors: Awender, Stefan, Wackerbauer, Renate, Breed, Greg A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: AIP Publishing 2024
• Subjects: Applied Mathematics; General Physics and Astronomy; Mathematical Physics; Statistical and Nonlinear Physics; Arctic; Beaufort Sea; Killer Whale; Sea ice; Killer whale
• Online Access: http://dx.doi.org/10.1063/5.0176718; https://pubs.aip.org/aip/cha/article-pdf/doi/10.1063/5.0176718/18572911/013122_1_5.0176718.pdf

Rapid sea-ice decline and warmer waters are threatening the stability of Arctic ecosystems and potentially forcing their restructuring. Mathematical models that support observational evidence are becoming increasingly important. We develop a food web model for the Southern Beaufort Sea based on species with high ecological significance. Generalized modeling is applied to study the impact of realistic characteristics on food web stability; a powerful method that provides a linear stability analysis for systems with uncertainty in data and underlying physical processes. We find that including predator-specific foraging traits, weighted predator–prey interactions, and habitat constraints increase food-web stability. The absence of a fierce top predator (killer whale, polar bear, etc.) also significantly increases the portion of stable webs. Adding ecosystem background noise in terms of a collective impact of latent, minor ecosystem members shows a peak in stability at an optimum, relatively small background pressure. These results indicate that refining models with more realistic detail to account for the complexity of the ecological system may be key to bridge the gap between empirical observations and model predictions in ecosystem stability.