UW Aquatic & Fishery Sciences Quantitative Seminar

Neil Banas

UW, Oceanography

Adding complex trophic interactions to a plankton nutrient-cycling model: emergent long-term variability and emergent community structure

This talk explores the relationship between trophic complexity, diversity patterns, and the predictability of overall ecosystem function, in a "toy" model of phytoplankton-microzooplankton nutrient cycling. The model, though mechanistically simple, resolves 40 size classes each of phytoplankton (1-20 µm) and small zooplankton (21-460 µm), in order to resolve one level of trophic interactions in detail. Inclusion of complex predator-prey linkages and realistic prey preferences yields a system with an emergent pattern of phytoplankton diversity consistent with global ocean observations, i.e., a parabolic relationship between diversity (as measured by the Shannon evenness) and biomass. It also yields significant long-term time evolution, which places limits on the extent to which the community response to nutrient forcing can be predicted from forcing in a pragmatic sense. When a simple annual cycle in nutrient supply is repeated exactly for many years, transient fluctuations up to a factor of two in spring bloom magnitude persist for 10-20 years before a stable seasonal biomass cycle is achieved. When the amplitude of the nutrient-supply annual cycle is given a random interannual modulation, these long-lived transients add significant noise to the relationship between annual-mean nutrient supply and annual-mean biomass. This noise ranges from 0% to 40% depending on the grazer size selectivity. In general, unpredictability on the bloom timescale is damped when food-web complexity is increased by making grazers less selective, while unpredictability on the interannual scale shows the opposite pattern.

These results suggests a new strategy for ensemble ecosystem forecasting and uncertainty estimation, analogous to methods common in circulation and climate modeling.