Multi-trait diversification in marine diatoms in constant and warmed environments.

Phytoplankton are photosynthetic marine microbes that affect food webs, nutrient cycles and climate regulation. Their roles are determined by correlated phytoplankton functional traits including cell size, chlorophyll content and cellular composition. Here, we explore patterns of evolution in interrelated trait values and correlations. Because both chance events and natural selection contribute to phytoplankton trait evolution, we used population bottlenecks to diversify six genotypes of Thalassiosirid diatoms. We then evolved them as large populations in two environments. Interspecific variation and within-species evolution were visualized for nine traits and their correlations using reduced axes (a trait-scape). Our main findings are that shifts in trait values resulted in movement of evolving populations within the trait-scape in both environments, but were more frequent when large populations evolved in a novel environment. Which trait relationships evolved was population-specific, but greater departures from ancestral trait correlations were associated with lower population growth rates. There was no single master trait that could be used to understand multi-trait evolution. Instead, repeatable multi-trait evolution occurred along a major axis of variation defined by several diatom traits and trait relationships. Because trait-scapes capture changes in trait relationships and values together, they offer an insightful way to study multi-trait variation.

Genus-Wide Transcriptional Landscapes Reveal Correlated Gene Networks Underlying Microevolutionary Divergence in Diatoms.

Marine microbes like diatoms make up the base of marine food webs and drive global nutrient cycles. Despite their key roles in ecology, biogeochemistry, and biotechnology, we have limited empirical data on how forces other than adaptation may drive diatom diversification, especially in the absence of environmental change. One key feature of diatom populations is frequent extreme reductions in population size, which can occur both in situ and ex situ as part of bloom-and-bust growth dynamics. This can drive divergence between closely related lineages, even in the absence of environmental differences. Here, we combine experimental evolution and transcriptome landscapes (t-scapes) to reveal repeated evolutionary divergence within several species of diatoms in a constant environment. We show that most of the transcriptional divergence can be captured on a reduced set of axes, and that repeatable evolution can occur along a single major axis of variation defined by core ortholog expression comprising common metabolic pathways. Previous work has associated specific transcriptional changes in gene networks with environmental factors. Here, we find that these same gene networks diverge in the absence of environmental change, suggesting these pathways may be central in generating phenotypic diversity as a result of both selective and random evolutionary forces. If this is the case, these genes and the functions they encode may represent universal axes of variation. Such axes that capture suites of interacting transcriptional changes during diversification improve our understanding of both global patterns in local adaptation and microdiversity, as well as evolutionary forces shaping algal cultivation.

Space-for-time substitutions in climate change ecology and evolution.

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Thermal trait variation may buffer Southern Ocean phytoplankton from anthropogenic warming.

Despite the potential of standing genetic variation to rescue communities and shape future adaptation to climate change, high levels of uncertainty are associated with intraspecific trait variation in marine phytoplankton. Recent model intercomparisons have pointed to an urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change, including Southern Ocean (SO) surface waters, which are among the most rapidly warming habitats on Earth. Because SO phytoplankton growth responses to warming sea surface temperature (SST) are poorly constrained, we developed a high-throughput growth assay to simultaneously examine inter- and intra-specific thermal trait variation in a group of 43 taxonomically diverse and biogeochemically important SO phytoplankton called diatoms. We found significant differential growth performance among species across thermal traits, including optimum and maximum tolerated growth temperatures. Within species, coefficients of variation ranged from 3% to 48% among strains for those same key thermal traits. Using SO SST projections for 2100, we predicted biogeographic ranges that differed by up to 97% between the least and most tolerant strains for each species, illustrating the role that strain-specific differences in temperature response can play in shaping predictions of future phytoplankton biogeography. Our findings revealed the presence and scale of thermal trait variation in SO phytoplankton and suggest these communities may already harbour the thermal trait diversity required to withstand projected 21st-century SST change in the SO even under severe climate forcing scenarios.

Rapid evolution allows coexistence of highly divergent lineages within the same niche.

Marine microbial communities are extremely complex and diverse. The number of locally coexisting species often vastly exceeds the number of identifiable niches, and taxonomic composition often appears decoupled from local environmental conditions. This is contrary to the view that environmental conditions should select for a few locally well-adapted species. Here we use an individual-based eco-evolutionary model to show that virtually unlimited taxonomic diversity can be supported in highly evolving assemblages, even in the absence of niche separation. With a steady stream of heritable changes to phenotype, competitive exclusion may be weakened, allowing sustained coexistence of nearly neutral phenotypes with highly divergent lineages. This behaviour is robust even to abrupt environmental perturbations that might be expected to cause strong selection pressure and an associated loss of diversity. We, therefore, suggest that rapid evolution and individual-level variability are key drivers of species coexistence and maintenance of microbial biodiversity.

The need for unrealistic experiments in global change biology.

Climate change is an existential threat, and our ability to conduct experiments on how organisms will respond to it is limited by logistics and resources, making it vital that experiments be maximally useful. The majority of experiments on phytoplankton responses to warming and CO2 use only two levels of each driver. However, to project the characters of future populations, we need a mechanistic and generalisable explanation for how phytoplankton respond to concurrent changes in temperature and CO2. This requires experiments with more driver levels, to produce response surfaces that can aid in the development of predictive models. We recommend prioritising experiments or programmes that produce such response surfaces on multiple scales for phytoplankton.

Predictability of thermal fluctuations influences functional traits of a cosmopolitan marine diatom.

Evolutionary theory predicts that organismal plasticity should evolve in environments that fluctuate regularly. However, in environments that fluctuate less predictably, plasticity may be constrained because environmental cues become less reliable for expressing the optimum phenotype. Here, we examine how the predictability of +5°C temperature fluctuations impacts the phenotype of the marine diatom Thalassiosira pseudonana. Thermal regimes were informed by temperatures experienced by microbes in an ocean simulation and featured regular or irregular temporal sequences of fluctuations that induced mild physiological stress. Physiological traits (growth, cell size, complexity and pigmentation) were quantified at the individual cell level using flow cytometry. Changes in cellular complexity emerged as the first impact of predictability after only 8-11 days, followed by deleterious impacts on growth on days 13-16. Specifically, cells with a history of irregular fluctuation exposure exhibited a 50% reduction in growth compared with the stable reference environment, while growth was 3-18 times higher when fluctuations were regular. We observed no evidence of heat hardening (increasingly positive growth) with recurrent fluctuations. This study demonstrates that unpredictable temperature fluctuations impact this cosmopolitan diatom under ecologically relevant time frames, suggesting shifts in environmental stochasticity under a changing climate could have widespread consequences among ocean primary producers.

Mucospheres produced by a mixotrophic protist impact ocean carbon cycling.

Mixotrophic protists (unicellular eukaryotes) that engage in both phototrophy (photosynthesis) and phago-heterotrophy (engulfment of particles)-are predicted to contribute substantially to energy fluxes and marine biogeochemical cycles. However, their impact remains largely unquantified. Here we describe the sophisticated foraging strategy of a widespread mixotrophic dinoflagellate, involving the production of carbon-rich 'mucospheres' that attract, capture, and immobilise microbial prey facilitating their consumption. We provide a detailed characterisation of this previously undescribed behaviour and reveal that it represents an overlooked, yet quantitatively significant mechanism for oceanic carbon fluxes. Following feeding, the mucospheres laden with surplus prey are discarded and sink, contributing an estimated 0.17-1.24 mg m-2 d-1 of particulate organic carbon, or 0.02-0.15 Gt to the biological pump annually, which represents 0.1-0.7% of the estimated total export from the euphotic zone. These findings demonstrate how the complex foraging behaviour of a single species of mixotrophic protist can disproportionally contribute to the vertical flux of carbon in the ocean.

A High-Throughput Assay for Quantifying Phenotypic Traits of Microalgae.

High-throughput methods for phenotyping microalgae are in demand across a variety of research and commercial purposes. Many microalgae can be readily cultivated in multi-well plates for experimental studies which can reduce overall costs, while measuring traits from low volume samples can reduce handling. Here we develop a high-throughput quantitative phenotypic assay (QPA) that can be used to phenotype microalgae grown in multi-well plates. The QPA integrates 10 low-volume, relatively high-throughput trait measurements (growth rate, cell size, granularity, chlorophyll a, neutral lipid content, silicification, reactive oxygen species accumulation, and photophysiology parameters: ETRmax, Ik, and alpha) into one workflow. We demonstrate the utility of the QPA on Thalassiosira spp., a cosmopolitan marine diatom, phenotyping six strains in a standard nutrient rich environment (f/2 media) using the full 10-trait assay. The multivariate phenotypes of strains can be simplified into two dimensions using principal component analysis, generating a trait-scape. We determine that traits show a consistent pattern when grown in small volume compared to more typical large volumes. The QPA can thus be used for quantifying traits across different growth environments without requiring exhaustive large-scale culturing experiments, which facilitates experiments on trait plasticity. We confirm that this assay can be used to phenotype newly isolated diatom strains within 4 weeks of isolation. The QPA described here is highly amenable to customisation for other traits or unicellular taxa and provides a framework for designing high-throughput experiments. This method will have applications in experimental evolution, modelling, and for commercial applications where screening of phytoplankton traits is of high importance.

Biodiversity of marine microbes is safeguarded by phenotypic heterogeneity in ecological traits.

Why, contrary to theoretical predictions, do marine microbe communities harbor tremendous phenotypic heterogeneity? How can so many marine microbe species competing in the same niche coexist? We discovered a unifying explanation for both phenomena by investigating a non-cooperative game that interpolates between individual-level competitions and species-level outcomes. We identified all equilibrium strategies of the game. These strategies represent the probability distribution of competitive abilities (e.g. traits) and are characterized by maximal phenotypic heterogeneity. They are also neutral towards each other in the sense that an unlimited number of species can co-exist while competing according to the equilibrium strategies. Whereas prior theory predicts that natural selection would minimize trait variation around an optimum value, here we obtained a mathematical proof that species with maximally variable traits are those that endure. This discrepancy may reflect a disparity between predictions from models developed for larger organisms in contrast to our microbe-centric model. Rigorous mathematics proves that phenotypic heterogeneity is itself a mechanistic underpinning of microbial diversity. This discovery has fundamental ramifications for microbial ecology and may represent an adaptive reservoir sheltering biodiversity in changing environmental conditions.

Growth strategies of a model picoplankter depend on social milieu and pCO2.

Phytoplankton exist in genetically diverse populations, but are often studied as single lineages (single strains), so that interpreting single-lineage studies relies critically on understanding how microbial growth differs with social milieu, defined as the presence or absence of conspecifics. The properties of lineages grown alone often fail to predict the growth of these same lineages in the presence of conspecifics, and this discrepancy points towards an opportunity to improve our understanding of the factors that affect lineage growth rates. We demonstrate that different lineages of a marine picoplankter modulate their maximum lineage growth rate in response to the presence of non-self conspecifics, even when resource competition is effectively absent. This explains why growth rates of lineages in isolation do not reliably predict their growth rates in mixed culture, or the lineage composition of assemblages under conditions of rapid growth. The diversity of growth strategies observed here are consistent with lineage-specific energy allocation that depends on social milieu. Since lineage growth is only one of many traits determining fitness in natural assemblages, we hypothesize that intraspecific variation in growth strategies should be common, with more strategies possible in ameliorated environments that support higher maximum growth rates, such as high CO2 for many marine picoplankton.

The evolution of trait correlations constrains phenotypic adaptation to high CO2 in a eukaryotic alga.

Microbes form the base of food webs and drive biogeochemical cycling. Predicting the effects of microbial evolution on global elemental cycles remains a significant challenge due to the sheer number of interacting environmental and trait combinations. Here, we present an approach for integrating multivariate trait data into a predictive model of trait evolution. We investigated the outcome of thousands of possible adaptive walks parameterized using empirical evolution data from the alga Chlamydomonas exposed to high CO2. We found that the direction of historical bias (existing trait correlations) influenced both the rate of adaptation and the evolved phenotypes (trait combinations). Critically, we use fitness landscapes derived directly from empirical trait values to capture known evolutionary phenomena. This work demonstrates that ecological models need to represent both changes in traits and changes in the correlation between traits in order to accurately capture phytoplankton evolution and predict future shifts in elemental cycling.

Selective constraints on global plankton dispersal.

Marine microbial communities are highly interconnected assemblages of organisms shaped by ecological drift, natural selection, and dispersal. The relative strength of these forces determines how ecosystems respond to environmental gradients, how much diversity is resident in a community or population at any given time, and how populations reorganize and evolve in response to environmental perturbations. In this study, we introduce a globally resolved population-genetic ocean model in order to examine the interplay of dispersal, selection, and adaptive evolution and their effects on community assembly and global biogeography. We find that environmental selection places strong constraints on global dispersal, even in the face of extremely high assumed rates of adaptation. Changing the relative strengths of dispersal, selection, and adaptation has pronounced effects on community assembly in the model and suggests that barriers to dispersal play a key role in the structuring of marine communities, enhancing global biodiversity and the importance of local historical contingencies.

The role of changes in environmental quality in multitrait plastic responses to environmental and social change in the model microalga Chlamydomonas reinhardtii.

Intraspecific variation plays a key role in species' responses to environmental change; however, little is known about the role of changes in environmental quality (the population growth rate an environment supports) on intraspecific trait variation. Here, we hypothesize that intraspecific trait variation will be higher in ameliorated environments than in degraded ones. We first measure the range of multitrait phenotypes over a range of environmental qualities for three strains and two evolutionary histories of Chlamydomonas reinhardtii in laboratory conditions. We then explore how environmental quality and trait variation affect the predictability of lineage frequencies when lineage pairs are grown in indirect co-culture. Our results show that environmental quality has the potential to affect intraspecific variability both in terms of the variation in expressed trait values, and in terms of the genotype composition of rapidly growing populations. We found low phenotypic variability in degraded or same-quality environments and high phenotypic variability in ameliorated conditions. This variation can affect population composition, as monoculture growth rate is a less reliable predictor of lineage frequencies in ameliorated environments. Our study highlights that understanding whether populations experience environmental change as an increase or a decrease in quality relative to their recent history affects the changes in trait variation during plastic responses, including growth responses to the presence of conspecifics. This points toward a fundamental role for changes in overall environmental quality in driving phenotypic variation within closely related populations, with implications for microevolution.