Phytoplankton functional type modelling: Running before we can walk? A critical evaluation of the current state of knowledge

作者：Shimoda Yuko; Arhonditsis George B^*

来源：Ecological Modelling, 2016, 320: 29-43.

DOI：10.1016/j.ecolmodel.2015.08.029

• Mathematical models
• Resource competition
• Phytoplankton functional grouping
• Ecological diversity
• Cyanobacteria

In the context of aquatic biogeochemical modelling, there is an increasing pressure to explicitly treat multiple biogeochemical cycles and to increase the functional diversity of biotic communities. In this study, we evaluate the capacity of 124 aquatic biogeochemical models to reproduce the dynamics of phytoplankton functional groups. Our analysis reinforces earlier findings that aquatic ecosystem modellers do not seem to consistently apply conventional methodological steps during the development of their models. Although there is an improvement relative to earlier critiques, significant portion of published studies did not properly assess model sensitivity to input vectors; aquatic ecosystem modellers are still reluctant to embrace optimization techniques during model calibration; and assess the ability of their models to support predictions in the extrapolation domain. We also found significant variability with respect to the mathematical representation of key physiological processes (e.g., growth strategies, nutrient kinetics, settling velocities) as well as group-specific characterizations typically considered in the pertinent literature. Cyanobacteria blooms are a major concern for water industries as they represent high risk for human health and economic costs for drinking water treatment, and thus one of the outstanding challenges is to offer credible modelling tools that can serve as early warning systems to assist with the operational control of cyanobacteria blooms. Our study suggests that the derivation of distinct functional groups from fairly heterogeneous planktonic assemblages poses challenging problems. Because of the still poorly understood ecology, we do not have robust group-specific parameterizations that can support predictions in a wide array of spatiotemporal domains. In this context, we argue that the most prudent strategies are the gradual incorporation of complexity, where possible and relevant, along with an open dialogue on how we can mathematically depict the interconnections among different phytoplankton subunits or even how we can frame the suitable data collection efforts.

• 出版日期2016-1-24