Elsevier

Ecological Modelling

Volume 220, Issue 21, 10 November 2009, Pages 3089-3099
Ecological Modelling

Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela

https://doi.org/10.1016/j.ecolmodel.2009.08.016Get rights and content

Abstract

‘End-to-end’ models have been adopted in an attempt to capture more of the processes that influence the ecology of marine ecosystems and to make system wide predictions of the effects of fishing and climate change. Here, we develop an end-to-end model by coupling existing models that describe the dynamics of low (ROMS–N2P2Z2D2) and high trophic levels (OSMOSE). ROMS–N2P2Z2D2 is a biogeochemical model representing phytoplankton and zooplankton seasonal dynamics forced by hydrodynamics in the Benguela upwelling ecosystem. OSMOSE is an individual-based model representing the dynamics of several species of fish, linked through opportunistic and size-based trophic interactions. The models are coupled through a two-way size-based predation process. Plankton provides prey for fish, and the effects of predation by fish on the plankton are described by a plankton mortality term that is variable in space and time. Using the end-to-end model, we compare the effects of two-way coupling versus one-way forcing of the fish model with the plankton biomass field. The fish-induced mortality on plankton is temporally variable, in part explained by seasonal changes in fish biomass. Inclusion of two-way feedback affects the seasonal dynamics of plankton groups and usually reduces the amplitude of variation in abundance (top-down effect). Forcing and coupling lead to different predicted food web structures owing to changes in the dominant food chain which is supported by plankton (bottom-up effect). Our comparisons of one-way forcing and two-way coupling show how feedbacks may affect abundance, food web structure and food web function and emphasise the need to critically examine the consequences of different model architectures when seeking to predict the effects of fishing and climate change.

Introduction

Given current concerns about the effects of climate change, there has been a renewed interest in understanding and predicting the combined effects of climate and fishing on marine ecosystems (Cury et al., 2008). The relative effects of fishing and climate depend on the extent to which ecosystems are controlled by climate (bottom-up) or fishing (top-down) processes, with their relative dominance varying according to space and time (Frank et al., 2006). By representing the whole food web and by accounting for the dynamic forcing of both fishing and climate, end-to-end models provide a framework to better understand their combined effects (de Young et al., 2004, Cury et al., 2008). End-to-end models can be built by coupling sub-models of ecosystem components (e.g., physical environment, plankton populations, forage fish or top-predators), a process that allows suitable scales to be maintained for each sub-model (Travers et al., 2007). Coupling has been achieved in many ways (Travers et al., 2007). For example, hydrodynamic models have been used to force biological models (e.g., Lehodey et al., 2003) and biological models have been coupled through ecological processes including predation, excretion, egestion or natural mortality (e.g., Hermann et al., 2001, Megrey et al., 2007). Even though predation describes an interaction between organisms, it has often been treated as a one-way process with the prey field providing food for predators (and thus affecting their growth) but with the resulting predation mortality on prey not represented. This approach precludes the simulation of any top-down effects that propagate through the food web, such as the trophic cascades that have been reported in some ecosystems (e.g., Estes et al., 1998). However, this feedback has potentially important effects on ecosystem dynamics. For example, Megrey et al. (2007) showed that the dynamics of both zooplankton and fish were affected by predation feedback, and that the effects of this feedback could cascade to phytoplankton. Here, we investigate the effects of predation feedback on plankton dynamics and food web structure. We do this by comparing coupled plankton and high trophic level (HTL) models with one-way (forcing) and two-way (true coupling) configurations. Applying the coupled model to the southern Benguela ecosystem, we focus first on the simulated plankton dynamics, and then on the emergent food web structure associated with the different modes of coupling.

Section snippets

Materials and methods

The end-to-end model used in this study has been developed from two existing sub-models, ROMS–N2P2Z2D2 (Koné et al., 2005) and OSMOSE (Shin et al., 2004). Both have been applied independently to the southern Benguela ecosystem and represent the plankton communities (low trophic levels, LTL) and the HTL, respectively. These models have been coupled through the predation process only.

Results

The genetic algorithm runs converge to a set of calibrated parameters after 300 generations of genotypes, which make it possible to reproduce observed biomasses for the 11 HTL species. The plankton availability coefficients are estimated as 0.369 for flagellates, 0.016 for diatoms, 0.011 for ciliates and 0.113 for copepods (Table 2). This implies, for example, that only 11.3% of the integrated copepod production is effectively available to HTL organisms during a time step. The mortality rate

Fish-induced plankton mortality

The feedback from HTL organisms to plankton groups is predicted to vary seasonally. This seasonal variation is largely driven by the seasonality of the fish biomass. This includes seasonal spawning migrations of fish, particularly sardine and anchovy, in the spatially explicit OSMOSE model. Indeed, the high mortality rate observed in winter corresponds to the peak in lightfish biomass, the main predator of copepods. In OSMOSE, the food requirement of fish is correlated linearly with its

Conclusion

Considering predation feedback in the coupled ROMS–N2P2Z2D2–OSMOSE model has several effects on simulated population dynamics and food web structure at different levels. Predation mortality resulting from the HTL model reveals a spatial and temporal variability that is not usually considered in classical biogeochemical models. With the coupled model architecture, the effects of predation mortality can be tracked in the dynamics of plankton groups, that display non-linear responses. The first

Acknowledgements

This work was partially funded by the EUR-OCEANS Network of Excellence (contract of the European Commission No. FP6-511106), by the European Collaborative Project MEECE (contract of the European Commission No. FP7-212085) and by the French ANR CHALOUPE Project. Morgane Travers was supported by a EUR-OCEANS scholarship. We thank Pierrick Penven and Vamara Koné for providing the ROMS model and for fruitful discussions. We are grateful to Christian Mullon, and Fabienne Cazassus for their support

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