Phytoplankton diversity affects biomass and energy production differently during community development

Evolution Under Competition Increases Population Production by Reducing the Density-Dependence of Net Energy Fluxes and Growth

Competition can drive rapid evolution, but forecasting how species evolve in communities remains difficult. Life history theory predicts that evolution in crowded environments should maximize population production, with intra- and inter-specific competition producing similar outcomes if species compete for similar resources. Despite its appeal, this prediction has rarely been tested in communities. To test its generality and identify its physiological basis, we used experimental evolution to maintain four species of marine phytoplankton alone or together in a community for 4.5 months. We then quantified changes in their metabolism, demography, and competitive ability at two timepoints (~60 and 120 generations) in common garden experiments. One species was outcompeted during the evolution experiment. For the other three, we found the same evolutionary outcome: species evolved greater biovolume production regardless of competition treatment but did so either by increasing max. population size or individual cell size. Biovolume production increased because of the differential evolution of photosynthesis and respiration under intense competition. These metabolic changes meant that intraspecific competition decreased, and cells maintained higher rates of net energy production and growth as populations neared the stationary phase. Overall, these results show that intra- and inter-specific competition influence physiological and population parameters similarly in species that compete for essential resources. Life history theory thus provides a valuable base for predicting how species evolve in communities, and our results show how these predictions relate to the evolution of metabolism and competitive ability.

Biomass competition connects individual and community scaling patterns

Both metabolism and growth scale sublinearly with body mass across species. Ecosystems show the same sublinear scaling between production and total biomass, but ecological theory cannot reconcile the existence of these nearly identical scalings at different levels of biological organization. We attempt to solve this paradox using marine phytoplankton, connecting individual and ecosystem scalings across three orders of magnitude in body size and biomass. We find that competitive interactions determined by biomass slow metabolism in a consistent fashion across species of different sizes. These effects dominate over species-specific peculiarities, explaining why community composition does not affect respiration and production patterns. The sublinear scaling of ecosystem production thus emerges from this metabolic density-dependence that operates across species, independently of the equilibrium state or resource regime. Our findings demonstrate the connection between individual and ecosystem scalings, unifying aspects of physiology and ecology to explain why growth patterns are so strikingly similar across scales.

Global epistasis and the emergence of function in microbial consortia

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

Anthropogenic nutrients and phytoplankton diversity in Kenya's coastal waters: An ecological quality assessment of sea turtle foraging sites

We assessed ecological quality status (EQS) of coastal waters following claims of increasing sea turtle fibro-papillomatosis (FP) infections in Kenya, a disease hypothesized to be associated with 'poor' ecological health. We established widespread phosphate (P) and silicate (Si) limitation, dissolved ammonium contamination and an increase in potential harmful algal blooming species. Variations in the EQS was established in the sites depending on the indicators used and seasons. Generally, more sites located near hotels, tidal creeks, and estuarine areas showed 'poor', and 'bad' EQS during rainy period compared to dry season. Additionally, 90.1 % of the sites in 'poor' and 'bad' EQS based on dissolved inorganic nitrogen. Low dissolved oxygen, elevated temperature, salinity and ammonium, 'poor' EQS based on DIN, and potential bio-toxin-producing phytoplankton species characterized the FP prevalent areas, specifically during the dry season suggesting environmental stress pointing to the hypothesized connection between ecological and sea turtle health.

Metabolic evolution in response to interspecific competition in a eukaryote

Competition drives rapid evolution, which, in turn, alters the trajectory of ecological communities. These eco-evolutionary dynamics are increasingly well-appreciated, but we lack a mechanistic framework for identifying the types of traits that will evolve and their trajectories. Metabolic theory offers explicit predictions for how competition should shape the (co)evolution of metabolism and size, but these are untested, particularly in eukaryotes. We use experimental evolution of a eukaryotic microalga to examine how metabolism, size, and demography coevolve under inter- and intraspecific competition. We find that the focal species evolves in accordance with the predictions of metabolic theory, reducing metabolic costs and maximizing population carrying capacity via changes in cell size. The smaller-evolved cells initially had lower population growth rates, as expected from their hyper-allometric metabolic scaling, but longer-term evolution yielded important departures from theory: we observed improvements in both population growth rate and carrying capacity. The evasion of this trade-off arose due to the rapid evolution of metabolic plasticity. Lineages exposed to competition evolved more labile metabolisms that tracked resource availability more effectively than lineages that were competition-free. That metabolic evolution can occur is unsurprising, but our finding that metabolic plasticity also co-evolves rapidly is new. Metabolic theory provides a powerful theoretical basis for predicting the eco-evolutionary responses to changing resource regimes driven by global change. Metabolic theory needs also to be updated to incorporate the effects of metabolic plasticity on the link between metabolism and demography, as this likely plays an underappreciated role in mediating eco-evolutionary dynamics of competition.

The community-function landscape of microbial consortia

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.