How realistic features effect steady state stability of an Arctic marine food web model

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. Generalized modeling is applied to a food web model with species of high ecological significance for the Southern Beaufort Sea. Generalized modeling is a powerful method that provides a linear stability analysis for systems with uncertainty in data and underlying physical processes. We find that including realistic characteristics into the model, like predator-specific foraging traits or habitat constraints increases food-web stability. The absence of a fierce top predator (killer whale, polar bear) also significantly increases the portion of stable webs. Adding ecosystem background noise in terms of minor ecosystem members results in a peak in stability at an optimum value of 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.