Micro-scale variability enhances trophic transfer and potentially sustains biodiversity in plankton ecosystems

Abstract

We develop moment closure approximations to represent micro-scale spatial variability in the concentrations of nutrients (N), phytoplankton (P) and zooplankton (Z) in an NPZ model, which we apply to examine the impact of different levels of micro-scale variability on both ecosystem dynamics and trophic transfer. Accounting explicitly for both the mean-field and fluctuating components of each prognostic variable in the NPZ model yields different dynamics for the mean-field concentrations, as well as lower phytoplankton biomass and greater zooplankton biomass, compared to the conventional NPZ model without micro-scale variability. The biomass of zooplankton consistently increases with increasing total micro-scale variability, and a minimum threshold of such variability is required for the existence of stable steady state solutions in the NPZ closure model. Compared to the conventional NPZ model, the domain of parameter space over which stable solutions exist is larger than for the NPZ closure model, and this stable domain widens with increasing total variability. The latter result suggests that natural systems with greater micro-scale variability may have the potential to sustain greater biodiversity. We find that with the NPZ closure model: (1) the stability domains increases with micro-scale variability, (2) increase of the level of total micro-scale variability enhances trophic transfer, i.e. increases the biomass of zooplankton, and (3) the coefficient of variation (CV) of phytoplankton increases with micro-scale variability.

Nutrient Patchiness, Phytoplankton Surge-Uptake, and Turbulent History: A Theoretical Approach and Its Experimental Validation

“…More fundamentally, these results highlight the importance of ocean variability at minute spatial and temporal scales in the structure and function of marine ecosystems. In this context, the approach presented here is consistent with previous studies showing how the understanding and subsequent modelling of intermittent distributions-or more generally small-and micro-scale variability-can enhance trophic transfer, interspecific competition, and eventually sustain biodiversity in plankton ecosystems [74][75][76][77][78][79].…”

Micro-scale patchiness enhances trophic transfer efficiency and potential plankton biodiversity

“…Although we have observations of CV only, a consistently strong and positive relationship exists between CV and micro-scale variability, β (Fig. S13 in Appendix, see also 14 ). The highest modelled values of TE were obtained for β values corresponding to observed phytoplankton CV from open ocean waters (Fig.…”

“…Here parameter R is the maximum rate of zooplankton grazing on phytoplankton, and is the half-saturation constant of the z-grazing functional response. The above three functional responses are widely used in planktonic modelling 2,4,12,14,16,23–25 .…”

“…Recent observations have revealed ubiquitous intermittency in phytoplankton distributions at the micro ( mm ) scale 8–11 , and a few recent modelling studies have suggested that this micro-scale variability impacts plankton ecosystem dynamics and biodiversity 12–14 . Modelling is an essential tool for studying complex food webs, by linking the observed ecological patterns with experimental findings to understand mechanisms and make future predictions.…”

“…Although this is reasonable for examining patterns at the meso- ( km ) to global scales, it is not realistic for plankton, which experience micro-scale variability in aquatic environments where predator-prey overlap can substantially enhance trophic transfer 15,16 . Similar to a recent study that addressed variability at the scale of ocean fronts 16 , we have recently used the Reynolds decomposition and a truncated Taylor series to develop ‘moment closure’ models accounting for micro-scale variability in the distributions of Nutrients and Phytoplankton (NP closure model) 12 , and also Zooplankton (NPZ closure model) 14 . Compared to conventional ecosystem models based on the mean-field approach, these closure models yield considerably different dynamics.…”