added 2 research items
Modelling the assembly rules and ecosystem stability of planktonic communities over the global ocean (MARES)
Background: Ecolocial interctions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions by associations across time and space, which can be represented as association networks. Links in these networks could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally-driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not. Results: We present EnDED (Environmentally-Driven Edge Detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally-driven. The four approaches are Sign Pattern, Overlap, Interaction Information, and Data Processing Inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1,087 edges, of which 60 were true interactions but 1,026 false associations (i.e. environmentally-driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally-driven edges—87% Sign Pattern and Overlap, 67% Interaction Information, and 44% Data Processing Inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally-driven associations). The addition of noise to the simulated datasets did not alter qualitatively these results. After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 14.2% of the associations were environmentally-driven, while individual methods predicted 31.4% (Data Processing Inequality), 38.3% (Interaction Information), and up to 83.4% (Sign Pattern as well as Overlap). Conclusions: To reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally-driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest to use EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses.
Microbial modelling is today a central aspect of ecological theory applied to microorganisms. Ecological theory and numerical modelling are essential for developing a deeper understanding of the mechanisms that shape the assembly and evolution of microbial communities. Microbes have complex interactions among them and with their local environment, and can display a very rich set of spatio-temporal dynamics. Modelling microbes is thus a challenging enterprise that needs to be subject to experimental validation. This chapter provides a review of the state-of-the-art of models in microbial ecology, ranging from the microscopic (e.g. resource uptake) to the macroscopic level (e.g. spatial organisation). Special emphasis is given to the modelling of eco-evolutionary dynamics and social interactions of microbial communities, and to the tradeoffs that mediate them. Microbial food webs are also an important focus of analysis, based on system theory. The overarching point of view is the use of numerical models to improve our understanding of how microbial communities operate and affect ecosystem functioning.
With global climate change altering marine ecosystems, research on plankton ecology is likely to navigate uncharted seas. Yet, a staggering wealth of new plankton observations, integrated with recent advances in marine ecosystem modeling, may shed light on marine ecosystem structure and functioning. A EuroMarine foresight workshop on the " Impact of climate change on the distribution of plankton functional and phylogenetic diversity " (PlankDiv) identified five grand challenges for future plankton diversity and macroecology research: (1) What can we learn about plankton communities from the new wealth of high-throughput " omics " data? (2) What is the link between plankton diversity and ecosystem function? (3) How can species distribution models be adapted to represent plankton biogeography? (4) How will plankton biogeography be altered due to anthropogenic climate change? and (5) Can a new unifying theory of macroecology be developed based on plankton ecology studies? In this review, we discuss potential future avenues to address these questions, and challenges that need to be tackled along the way.
Biodiversity is known to be an important determinant of ecosystem-level functions and processes. Although theories have been proposed to explain the generally positive relationship between, for example, biodiversity and productivity, it remains unclear which mechanisms underlie the observed variations in Biodiversity-Ecosystem Function (BEF) relationships. Using a continuous trait-distribution model for a phytoplankton community of gleaners competing with opportunists, and subjecting it to differing frequencies of disturbance, we find that species selection tends to enhance temporal species complementarity, which is maximised at high disturbance frequency and intermediate functional diversity. This leads to the emergence of a trade-off whereby increasing diversity tends to enhance short-term adaptive capacity under frequent disturbance while diminishing long-term productivity under infrequent disturbance. BEF relationships therefore depend on both disturbance frequency and the timescale of observation.
The number of species of autotrophic communities can increase ecosystem productivity through species complementarity or through a selection effect which occurs when the biomass of the community approaches the monoculture biomass of the most productive species. Here we explore the effect of resource supply on marine primary productivity under the premise that the high local species richness of phytoplankton communities increases resource use through transient selection of productive species. Using concurrent measurements of phytoplankton community structure, nitrate fluxes into the euphotic zone and productivity from a temperate coastal ecosystem, we find that observed productivities are best described by a population growth model in which the dominant species of the community approach their maximum growth rates. We interpret these results as evidence of species selection in communities containing a vast taxonomic repertory. The prevalence of selection effect was supported by open ocean data that show an increase in community dominance across a gradient of nutrient availability. These results highlight the way marine phytoplankton optimize resources and sustain world food stocks. We suggest that the maintenance of phytoplankton species richness is essential to sustain marine primary productivity since it guarantees the occurrence of highly productive species.