In light of climate change and allied changes to marine ecosystems, mathematical models have become an important tool to simulate local through to global marine production, biodiversity and for projections of the future state of the ocean. However, outcomes of these models and consequently their predictive ability are strongly driven by operator choices of i) which plankton groups to represent and ii) the specification of organisms, affecting simulated interactions with the environment and other biota. Over recent years model studies, laboratory experiments and a better ecological understanding of the pelagic ecosystem have enabled several advancements on these fundamental issues. However many of these have not yet found their place in standard approaches used in marine ecosystem modelling.
There are some obvious omissions in most models. Groups such as viruses and bacteria are often not accounted for even though they are recognised as important players in biogeochemical cycling as well as in structuring the planktonic food web. Gelatinous plankton, including important invasive species are often ignored, but have been identified as important predators and competitors with e.g. zooplanktivorous fishes. Similarly fish larvae, and other meroplankter, are also given short shrift in modelling descriptions. Furthermore, the common modelling practice of classifying plankton in distinct (photo-) autotrophic and heterotrophic lifeforms appears unsuitable as many planktonic organisms are now known to be mixotrophic.
Specifications that drive the emergent interactions between plankton groups and between plankton and environmental variables rely largely on empirical relationships often with considerable uncertainties. These relationships are often extrapolated for circumstances very different from their origin with little regard for them being fit for purpose, e.g. for modelling future-scenarios. Adaptation and acclimation to changing environmental conditions alter physiology, morphology and behaviour, which in term can render extrapolation of fixed empirical relationships inaccurate if not inappropriate.
Mechanistic model representations on the other hand have the potential to enhance the fundamental understanding of the underlying principles; and consistent with revised empirical knowledge, they can provide more robust platforms valid for a wider range of circumstances.
We invite contributions that aim to advance dynamic planktonic ecosystem modelling through a better characterisation of planktonic groups or of individual organisms. In particular we welcome improved representations of previously miss- or under-represented planktonic players, the revisiting of justifications for model structures for functional groups, and studies replacing purely empirical descriptions with more generic relationships having a mechanistic basis. Different approaches have their own merits in addressing these challenges, and we thus invite contributions from diverse schools of modelling, theoretical and experimental approaches. It is our hope that such an intensified effort will not only provide a better ecological understanding of the plankton structure and dynamics, but ultimately also increase the generality as well as the predictive capability of marine ecosystem models.
In light of climate change and allied changes to marine ecosystems, mathematical models have become an important tool to simulate local through to global marine production, biodiversity and for projections of the future state of the ocean. However, outcomes of these models and consequently their predictive ability are strongly driven by operator choices of i) which plankton groups to represent and ii) the specification of organisms, affecting simulated interactions with the environment and other biota. Over recent years model studies, laboratory experiments and a better ecological understanding of the pelagic ecosystem have enabled several advancements on these fundamental issues. However many of these have not yet found their place in standard approaches used in marine ecosystem modelling.
There are some obvious omissions in most models. Groups such as viruses and bacteria are often not accounted for even though they are recognised as important players in biogeochemical cycling as well as in structuring the planktonic food web. Gelatinous plankton, including important invasive species are often ignored, but have been identified as important predators and competitors with e.g. zooplanktivorous fishes. Similarly fish larvae, and other meroplankter, are also given short shrift in modelling descriptions. Furthermore, the common modelling practice of classifying plankton in distinct (photo-) autotrophic and heterotrophic lifeforms appears unsuitable as many planktonic organisms are now known to be mixotrophic.
Specifications that drive the emergent interactions between plankton groups and between plankton and environmental variables rely largely on empirical relationships often with considerable uncertainties. These relationships are often extrapolated for circumstances very different from their origin with little regard for them being fit for purpose, e.g. for modelling future-scenarios. Adaptation and acclimation to changing environmental conditions alter physiology, morphology and behaviour, which in term can render extrapolation of fixed empirical relationships inaccurate if not inappropriate.
Mechanistic model representations on the other hand have the potential to enhance the fundamental understanding of the underlying principles; and consistent with revised empirical knowledge, they can provide more robust platforms valid for a wider range of circumstances.
We invite contributions that aim to advance dynamic planktonic ecosystem modelling through a better characterisation of planktonic groups or of individual organisms. In particular we welcome improved representations of previously miss- or under-represented planktonic players, the revisiting of justifications for model structures for functional groups, and studies replacing purely empirical descriptions with more generic relationships having a mechanistic basis. Different approaches have their own merits in addressing these challenges, and we thus invite contributions from diverse schools of modelling, theoretical and experimental approaches. It is our hope that such an intensified effort will not only provide a better ecological understanding of the plankton structure and dynamics, but ultimately also increase the generality as well as the predictive capability of marine ecosystem models.
