Process-dependence of biogenic feedback effects in models of plankton dynamics.

Abstract

The prospect of human-induced climate change has stimulated research into several biological processes that might affect climate. One such process that has attracted a substantial research effort is the so-called CLAW hypothesis (Charlson et al. 1987). This hypothesis suggests that marine plankton ecosystems may effectively regulate climate by a feedback associated with the production of dimethylsulphide (DMS). Charlson et al. (1987) observed that some of the DMS produced by marine ecosystems is transferred from the ocean to the atmosphere where it is the major source of cloud condensing nuclei (CCN) over the remote oceans. The aerosols resulting from biogenic DMS emissions can have a direct effect on the solar radiative forcing experienced by the Earth through scattering, absorption and reflection and can also lead to increased cloud formation; the CLAW hypothesis proposes that these mechanisms could regulate climate. Charlson et al (1987) argued that an increase in global temperature would lead to increased biogenic DMS emissions from the ocean and result in an increase in scattering, cloud cover and cloud albedo that would increase the proportion of the incoming solar radiation reflected back into space (thus changing the global albedo), and thereby cooling the planet. The objective of this paper is to examine the implications of the climate regulation process proposed by Charlson et al. (1987) for the dynamics of the ecosystems that produce it. Cropp et al. (2007) developed a simple plankton model that incorporated the DMS feedback mechanism and compared its dynamics to the same ecosystem model without the feedback. These simulations revealed that the presence of the feedback generally enhanced the stability of the ecosystem by making it more resilient to perturbation. In this research, we compare the effect of the feedbacks on a similar NPZ ecosystem model that has a greater range of dynamical behaviour than the model used by Cropp et al. (2007). The results of simulations with the new feedback model are compared to the results of Cropp et al. (2007) to elucidate the influence of the model formulation on the effects of the feedback