Title of article :
Viral infection as a regulator of oceanic phytoplankton populations
Author/Authors :
C.J. Rhodes، نويسنده , , J.E. Truscott، نويسنده , , A.P. Martin، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Abstract :
Viruses are the most abundant organism in seawater across all the worldʹs oceans. Though they are believed to be capable of infecting all phytoplankton species their role in regulating plankton population levels is not well understood. In order to gain an understanding of the potential influence of viruses on phytoplankton population dynamics, particularly ‘blooms’, two plankton ecosystem models with explicit representation of viruses and virally infected phytoplankton are presented, and an initial investigation into their range of behaviours explored. The models are extensions of well-established plankton ecosystem models that now permit the possibility of viral infection and mortality of phytoplankton. Ecological and epidemiological parameters from a number of sources are used to furnish the models. The models are shown to be capable of capturing known features of phytoplankton population dynamics in the presence of viruses: viruses can stably co-exist in the plankton ecosystem without the need to invoke other stabilising processes, and infection can serve to suppress primary production and phytoplankton abundance whilst boosting nutrient levels. Intuitively, viral infection will be most effective when phytoplankton is high. We therefore use the two models to investigate the influence of viral infection on ‘blooms’ in two independent ways: first with a seasonally-forced variability and second with a triggered transient event. It is demonstrated that the impact of viruses can be very noticeable during episodes of enhanced phytoplankton density found during ’blooms’. Viruses serve to attenuate the intensity and duration of these transient events in a manner consistent with observations.
Keywords :
zooplankton , Ecological modelling , Predator–prey modelling , viral infection , Epidemic modelling , phytoplankton
Journal title :
Journal of Marine Systems
Journal title :
Journal of Marine Systems