Opportunities and challenges in deriving phytoplankton diversity measures from individual trait-based data obtained by scanning flow-cytometry.

摘要: In the context of understanding and predicting effects human-induced environmental change (EC) on biodiversity (BD), consequences BD for ecosystem functioning (EF), microbial ecologists face challenge linking individual level variability in functional traits to larger scale processes. Since lower at genetic, individual, population levels largely determines functionality resilience natural populations communities, measures promise link EC-induced physiological, ecological evolutionary responses EF. Intraspecific trait differences, while representing among least understood aspects have recently become easier measure due new technology. For example, recent advance scanning flow-cytometry (SCF), automation phytoplankton sampling integration with sensors allow morphological physiological algae high spatial temporal resolution. Here we present emerging features automated SFC data from communities opportunities that they provide complex aquatic communities. We highlight some current limitations future needs, particularly focusing large amount that, purpose EC-BD-EF link, need be translated into meaningful indices. review available diversity indices despite having been designed mean values species level, can adapted individual-based links theory. conclude considering computational, mathematical issues, a set multi-dimensional address richness, evenness divergence overall community space represent most promising metrics study using data.