Global relationship between phytoplankton diversity and productivity in the ocean

Abstract

The shape of the productivity–diversity relationship (PDR) for marine phytoplankton has been suggested to be unimodal, that is, diversity peaking at intermediate levels of productivity. However, there are few observations and there has been little attempt to understand the mechanisms that would lead to such a shape for planktonic organisms. Here we use a marine ecosystem model together with the community assembly theory to explain the shape of the unimodal PDR we obtain at the global scale. The positive slope from low to intermediate productivity is due to grazer control with selective feeding, which leads to the predator-mediated coexistence of prey. The negative slope at high productivity is due to seasonal blooms of opportunist species that occur before they are regulated by grazers. The negative side is only unveiled when the temporal scale of the observation captures the transient dynamics, which are especially relevant at highly seasonal latitudes. Thus selective predation explains the positive side while transient competitive exclusion explains the negative side of the unimodal PDR curve. The phytoplankton community composition of the positive and negative sides is mostly dominated by slow-growing nutrient specialists and fast-growing nutrient opportunist species, respectively.

Ecosystem metabolism in salt marsh tidal creeks and ponds : applying triple oxygen isotopes and other gas tracers to novel environments

“…The patterns of regional variability in Shannon-Weaver diversity ( Figure 5) provide an additional basis for identifying and discussing the relationship between phytoplankton communities and production rates. Phytoplankton community diversity has been proposed to scale to phytoplankton biomass [Irigoien et al 2004, Vallina et al 2014 and net primary production rates [Napoléon et al 2014] in a manner similar to terrestrial vegetation. Regional means of gross primary production (which can be scaled to NPP, section 2.2.2) and diversity correlate significantly (p=0.009), and the correlations between variance of diversity, production rates, nutrients, and chlorophyll between regions (Table S4) suggests that they share a common underlying driver (e.g.…”

Bridging the Gap between Knowing and Modeling Viruses in Marine Systems—An Upcoming Frontier

“…In this model, viruses infect bacteria and both phytoplankton groups with the resulting mortality calculated based on a fixed infection rate for each group and dependent on virus and host densities (type-I functional response), while the decay of viruses is calculated with a quadratic mortality rate. Vallina et al (2014), on the other hand, uses a global model application to study the relationship between phytoplankton diversity and productivity, with as much as 64 phytoplankton species, two predator size-classes (micro-and meso-zooplankton) and several element cycles. However, the model has no mixotrophs and viral activity, nor it has an explicit representation of the microbial loop, but instead a constant degradation rates of bacterial remineralization.…”

Современные Тенденции Развития Биологии Водных Экосистем

“…Основой современных мо-делей является мультидисциплинарный подход. Так, рассмотрены, в частности, механизмы физико-биолого-биогеохимических взаимодействий в мезомасштабе [48], механизмы, контролирующие раз-мерные характеристики и функциональное разнообразие сообществ фитопланктона в зависимости от концентрации биогенных элементов, избирательного выедания [70] и осаждения фитопланктона [8], роль разнообразия фитопланктона в возникновении океанической стехиометрии [13].…”