Dynamic, mechanistic, molecular‐level modelling of cyanobacteria: Anabaena and nitrogen interaction
Year: 2016
Type: article
Abstract: Phytoplankton (eutrophication, biogeochemical) models are important tools for ecosystem research and management, but they generally have not been updated to include modern biology. Here, we present a dynamic, mechanistic, molecular-level (i.e. gene, transcript, protein, metabolite) model of Anabaena - nitrogen interaction. The model was developed using the pattern-oriented approach to model definition and parameterization of complex agent-based models. It simulates individual filaments, each with individual cells, each with genes that are expressed to yield transcripts and proteins. Cells metabolize various forms of N, grow and divide, and differentiate heterocysts when fixed N is depleted. The model is informed by observations from 269 laboratory experiments from 55 papers published from 1942 to 2014. Within this database, we identified 331 emerging patterns, and, excluding inconsistencies in observations, the model reproduces 94% of them. To explore a practical application, we used the model to simulate nutrient reduction scenarios for a hypothetical lake. For a 50% N only loading reduction, the model predicts that N fixation increases, but this fixed N does not compensate for the loading reduction, and the chlorophyll a concentration decreases substantially (by 33%). When N is reduced along with P, the model predicts an additional 8% reduction (compared to P only).
Source: Environmental Microbiology
Language: English
Subfield: Environmental Chemistry
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
Awards: Dimensions: Collaborative Research: Anthropogenic nutrient input drives genetic, functional and taxonomic biodiversity in hypereutrophic Lake Taihu, China, Dimensions: Collaborative Research: Anthropogenic nutrient input drives genetic, functional and taxonomic biodiversity in hypereutrophic Lake Taihu, China, Dimensions: Collaborative Research: Anthropogenic nutrient input drives genetic, functional and taxonomic biodiversity in hypereutrophic Lake Taihu, China, Dimensions: Collaborative Research: Anthropogenic nutrient input drives genetic, functional and taxonomic biodiversity in hypereutrophic Lake Taihu, China
OpenAlex ID: W2336498335
