Dual thermal ecotypes coexist within a nearly genetically identical population of the unicellular marine cyanobacterium Synechococcus.

The extent and ecological significance of intraspecific functional diversity within marine microbial populations is still poorly understood, and it remains unclear if such strain-level microdiversity will affect fitness and persistence in a rapidly changing ocean environment. In this study, we cultured 11 sympatric strains of the ubiquitous marine picocyanobacterium Synechococcus isolated from a Narragansett Bay (RI) phytoplankton community thermal selection experiment. Thermal performance curves revealed selection at cool and warm temperatures had subdivided the initial population into thermotypes with pronounced differences in maximum growth temperatures. Curiously, the genomes of all 11 isolates were almost identical (average nucleotide identities of >99.99%, with >99% of the genome aligning) and no differences in gene content or single nucleotide variants were associated with either cool or warm temperature phenotypes. Despite a very high level of genomic similarity, sequenced epigenomes for two strains showed differences in methylation on genes associated with photosynthesis. These corresponded to measured differences in photophysiology, suggesting a potential pathway for future mechanistic research into thermal microdiversity. Our study demonstrates that present-day marine microbial populations can harbor cryptic but environmentally relevant thermotypes which may increase their resilience to future rising temperatures.

The ecological causes of functional distinctiveness in communities.

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.

A general framework for species-abundance distributions: Linking traits and dispersal to explain commonness and rarity.

Species-abundance distributions (SADs) describe the spectrum of commonness and rarity in a community. Beyond the universal observation that most species are rare and only a few common, more-precise description of SAD shape is controversial. Furthermore, the mechanisms behind SADs and how they vary along environmental gradients remain unresolved. We lack a general, non-neutral theory of SADs. Here, we develop a trait-based framework, focusing on a local community coupled to the region by dispersal. The balance of immigration and exclusion determines abundances, which vary over orders-of-magnitude. The local trait-abundance distribution (TAD) reflects a transformation of the regional TAD. The left-tail of the SAD depends on scaling exponents of the exclusion function and the regional species pool. More-complex local dynamics can lead to multimodal TADs and SADs. Connecting SADs with trait-based ecological theory provides a way to generate more-testable hypotheses on the controls over commonness and rarity in communities.

Shape matters: the relationship between cell geometry and diversity in phytoplankton.

Size and shape profoundly influence an organism's ecophysiological performance and evolutionary fitness, suggesting a link between morphology and diversity. However, not much is known about how body shape is related to taxonomic richness, especially in microbes. Here we analyse global datasets of unicellular marine phytoplankton, a major group of primary producers with an exceptional diversity of cell sizes and shapes and, additionally, heterotrophic protists. Using two measures of cell shape elongation, we quantify taxonomic diversity as a function of cell size and shape. We find that cells of intermediate volume have the greatest shape variation, from oblate to extremely elongated forms, while small and large cells are mostly compact (e.g. spherical or cubic). Taxonomic diversity is strongly related to cell elongation and cell volume, together explaining up to 92% of total variance. Taxonomic diversity decays exponentially with cell elongation and displays a log-normal dependence on cell volume, peaking for intermediate-volume cells with compact shapes. These previously unreported broad patterns in phytoplankton diversity reveal selective pressures and ecophysiological constraints on the geometry of phytoplankton cells which may improve our understanding of marine ecology and the evolutionary rules of life.

Resource Competition and Host Feedbacks Underlie Regime Shifts in Gut Microbiota.

AbstractThe spread of an enteric pathogen in the human gut depends on many interacting factors, including pathogen exposure, diet, host gut environment, and host microbiota, but how these factors jointly influence infection outcomes remains poorly characterized. Here we develop a model of host-mediated resource competition between mutualistic and pathogenic taxa in the gut that aims to explain why similar hosts, exposed to the same pathogen, can have such different infection outcomes. Our model successfully reproduces several empirically observed phenomena related to transitions between healthy and infected states, including (1) the nonlinear relationship between pathogen inoculum size and infection persistence, (2) the elevated risk of chronic infection during or after treatment with broad-spectrum antibiotics, (3) the resolution of gut dysbiosis with fecal microbiota transplants, and (4) the potential protection from infection conferred by probiotics. We then use the model to explore how host-mediated interventions-namely, shifts in the supply rates of electron donors (e.g., dietary fiber) and respiratory electron acceptors (e.g., oxygen)-can potentially be used to direct gut community assembly. Our study demonstrates how resource competition and ecological feedbacks between the host and the gut microbiota can be critical determinants of human health outcomes. We identify several testable model predictions ready for experimental validation.

Climate Change-Driven Regime Shifts in a Planktonic Food Web.

AbstractPredicting how food webs will respond to global environmental change is difficult because of the complex interplay between the abiotic forcing and biotic interactions. Mechanistic models of species interactions in seasonal environments can help understand the effects of global change in different ecosystems. Seasonally ice-covered lakes are warming faster than many other ecosystems and undergoing pronounced food web changes, making the need to forecast those changes especially urgent. Using a seasonally forced food web model with a generalist zooplankton grazer and competing cold-adapted winter and warm-adapted summer phytoplankton, we show that with declining ice cover, the food web moves through different dynamic regimes, from annual to biennial cycles, with decreasing and then disappearing winter phytoplankton blooms and a shift of maximum biomass to summer season. Interestingly, when predator-prey interactions were not included, a declining ice cover did not cause regime shifts, suggesting that both are needed for regime transitions. A cluster analysis of long-term data from Lake Baikal, Siberia, supports the model results, revealing a change from regularly occurring winter blooms of endemic diatoms to less frequent winter bloom years with decreasing ice cover. Together, the results show that even gradual environmental change, such as declining ice cover duration, may cause discontinuous or abrupt transitions between dynamic regimes in food webs.

Nitrogen limitation inhibits marine diatom adaptation to high temperatures.

Ongoing climate change is shifting species distributions and increasing extinction risks globally. It is generally thought that large population sizes and short generation times of marine phytoplankton may allow them to adapt rapidly to global change, including warming, thus limiting losses of biodiversity and ecosystem function. Here, we show that a marine diatom survives high, previously lethal, temperatures after adapting to above-optimal temperatures under nitrogen (N)-replete conditions. N limitation, however, precludes thermal adaptation, leaving the diatom vulnerable to high temperatures. A trade-off between high-temperature tolerance and increased N requirements may explain why N limitation inhibited adaptation. Because oceanic N limitation is common and likely to intensify in the future, the assumption that phytoplankton will readily adapt to rising temperatures may need to be reevaluated.

Evolutionarily stable communities: a framework for understanding the role of trait evolution in the maintenance of diversity.

Biological diversity depends on the interplay between evolutionary diversification and ecological mechanisms allowing species to coexist. Current research increasingly integrates ecology and evolution over a range of timescales, but our common conceptual framework for understanding species coexistence requires better incorporation of evolutionary processes. Here, we focus on the idea of evolutionarily stable communities (ESCs), which are theoretical endpoints of evolution in a community context. We use ESCs as a unifying framework to highlight some important but under-appreciated theoretical results, and we review empirical research relevant to these theoretical predictions. We explain how, in addition to generating diversity, evolution can also limit diversity by reducing the effectiveness of coexistence mechanisms. The coevolving traits of competing species may either diverge or converge, depending on whether the number of species in the community is low (undersaturated) or high (oversaturated) relative to the ESC. Competition in oversaturated communities can lead to extinction or neutrally coexisting, ecologically equivalent species. It is critical to consider trait evolution when investigating fundamental ecological questions like the strength of different coexistence mechanisms, the feasibility of ecologically equivalent species, and the interpretation of different patterns of trait dispersion.

Rapid thermal adaptation in a marine diatom reveals constraints and trade-offs.

Rapid evolution in response to environmental change will likely be a driving force determining the distribution of species across the biosphere in coming decades. This is especially true of microorganisms, many of which may evolve in step with warming, including phytoplankton, the diverse photosynthetic microbes forming the foundation of most aquatic food webs. Here we tested the capacity of a globally important, model marine diatom Thalassiosira pseudonana, for rapid evolution in response to temperature. Selection at 16 and 31°C for 350 generations led to significant divergence in several temperature response traits, demonstrating local adaptation and the existence of trade-offs associated with adaptation to different temperatures. In contrast, competitive ability for nitrogen (commonly limiting in marine systems), measured after 450 generations of temperature selection, did not diverge in a systematic way between temperatures. This study shows how rapid thermal adaptation affects key temperature and nutrient traits and, thus, a population's long-term physiological, ecological, and biogeographic response to climate change.

Temperature-nutrient interactions exacerbate sensitivity to warming in phytoplankton.

Temperature and nutrients are fundamental, highly nonlinear drivers of biological processes, but we know little about how they interact to influence growth. This has hampered attempts to model population growth and competition in dynamic environments, which is critical in forecasting species distributions, as well as the diversity and productivity of communities. To address this, we propose a model of population growth that includes a new formulation of the temperature-nutrient interaction and test a novel prediction: that a species' optimum temperature for growth, Topt , is a saturating function of nutrient concentration. We find strong support for this prediction in experiments with a marine diatom, Thalassiosira pseudonana: Topt decreases by 3-6 °C at low nitrogen and phosphorus concentrations. This interaction implies that species are more vulnerable to hot, low-nutrient conditions than previous models accounted for. Consequently the interaction dramatically alters species' range limits in the ocean, projected based on current temperature and nitrate levels as well as those forecast for the future. Ranges are smaller not only than projections based on the individual variables, but also than those using a simpler model of temperature-nutrient interactions. Nutrient deprivation is therefore likely to exacerbate environmental warming's effects on communities.

Using neural ordinary differential equations to predict complex ecological dynamics from population density data.

Simple models have been used to describe ecological processes for over a century. However, the complexity of ecological systems makes simple models subject to modelling bias due to simplifying assumptions or unaccounted factors, limiting their predictive power. Neural ordinary differential equations (NODEs) have surged as a machine-learning algorithm that preserves the dynamic nature of the data (Chen et al. 2018 Adv. Neural Inf. Process. Syst.). Although preserving the dynamics in the data is an advantage, the question of how NODEs perform as a forecasting tool of ecological communities is unanswered. Here, we explore this question using simulated time series of competing species in a time-varying environment. We find that NODEs provide more precise forecasts than autoregressive integrated moving average (ARIMA) models. We also find that untuned NODEs have a similar forecasting accuracy to untuned long-short term memory neural networks and both are outperformed in accuracy and precision by empirical dynamical modelling . However, we also find NODEs generally outperform all other methods when evaluating with the interval score, which evaluates precision and accuracy in terms of prediction intervals rather than pointwise accuracy. We also discuss ways to improve the forecasting performance of NODEs. The power of a forecasting tool such as NODEs is that it can provide insights into population dynamics and should thus broaden the approaches to studying time series of ecological communities.

Eco-evolutionary emergence of macroecological scaling in plankton communities.

Macroecological scaling patterns, such as between prey and predator biomass, are fundamental to our understanding of the rules of biological organization and ecosystem functioning. Although these scaling patterns are ubiquitous, how they arise is poorly understood. To explain these patterns, we used an eco-evolutionary predator-prey model parameterized using data for phytoplankton and zooplankton. We show that allometric scaling relationships at lower levels of biological organization, such as body-size scaling of nutrient uptake and predation, give rise to scaling relationships at the food web and ecosystem levels. Our predicted macroecological scaling exponents agree well with observed values across ecosystems. Our findings explicitly connect scaling relationships at different levels of biological organization to ecological and evolutionary mechanisms, yielding testable hypotheses for how observed macroecological patterns emerge.

Refocusing the microbial rare biosphere concept through a functional lens.

The influential concept of the rare biosphere in microbial ecology has underscored the importance of taxa occurring at low abundances yet potentially playing key roles in communities and ecosystems. Here, we refocus the concept of rare biosphere through a functional trait-based lens and provide a framework to characterize microbial functional rarity, a combination of numerical scarcity across space or time and trait distinctiveness. We demonstrate how this novel interpretation of the rare biosphere, rooted in microbial functions, can enhance our mechanistic understanding of microbial community structure. It also sheds light on functionally distinct microbes, directing conservation efforts towards taxa harboring rare yet ecologically crucial functions.

Functional traits explain phytoplankton community structure and seasonal dynamics in a marine ecosystem.

A fundamental yet elusive goal of ecology is to predict the structure of communities from the environmental conditions they experience. Trait-based approaches to terrestrial plant communities have shown that functional traits can help reveal the mechanisms underlying community assembly, but such approaches have not been tested on the microbes that dominate ecosystem processes in the ocean. Here, we test whether functional traits can explain community responses to seasonal environmental fluctuation, using a time series of the phytoplankton of the English Channel. We show that interspecific variation in response to major limiting resources, light and nitrate, can be well-predicted by lab-measured traits characterising light utilisation, nitrate utilisation and maximum growth rate. As these relationships were predicted a priori, using independently measured traits, our results show that functional traits provide a strong mechanistic foundation for understanding the structure and dynamics of ecological communities.

The biogeography of marine plankton traits.

Changes in marine plankton communities driven by environmental variability impact the marine food web and global biogeochemical cycles of carbon and other elements. To predict and assess these community shifts and their consequences, ecologists are increasingly investigating how the functional traits of plankton determine their relative fitness along environmental and biological gradients. Laboratory, field and modelling studies are adopting this trait-based approach to map the biogeography of plankton traits that underlies variations in plankton communities. Here, we review progress towards understanding the regulatory roles of several key plankton functional traits, including cell size, N2 -fixation and mixotrophy among phytoplankton, and body size, ontogeny and feeding behaviour for zooplankton. The trait biogeographical approach sheds light on what structures plankton communities in the current ocean, as well as under climate change scenarios, and also allows for finer resolution of community function because community trait composition determines the rates of significant processes, including carbon export. Although understanding of trait biogeography is growing, uncertainties remain that stem, in part, from the paucity of observations describing plankton functional traits. Thus, in addition to recommending widespread adoption of the trait-based approach, we advocate for enhanced collection, standardisation and dissemination of plankton functional trait data.

Industrial-strength ecology: trade-offs and opportunities in algal biofuel production.

Microalgae represent one of the most promising groups of candidate organisms for replacing fossil fuels with contemporary primary production as a renewable source of energy. Algae can produce many times more biomass per unit area than terrestrial crop plants, easing the competing demands for land with food crops and native ecosystems. However, several aspects of algal biology present unique challenges to the industrial-scale aquaculture of photosynthetic microorganisms. These include high susceptibility to invading aquatic consumers and weeds, as well as prodigious requirements for nutrients that may compete with the fertiliser demands of other crops. Most research on algal biofuel technologies approaches these problems from a cellular or genetic perspective, attempting either to engineer or select algal strains with particular traits. However, inherent functional trade-offs may limit the capacity of genetic selection or synthetic biology to simultaneously optimise multiple functional traits for biofuel productivity and resilience. We argue that a community engineering approach that manages microalgal diversity, species composition and environmental conditions may lead to more robust and productive biofuel ecosystems. We review evidence for trade-offs, challenges and opportunities in algal biofuel cultivation with a goal of guiding research towards intensifying bioenergy production using established principles of community and ecosystem ecology.

A three-way trade-off maintains functional diversity under variable resource supply.

The resources that organisms depend on often fluctuate over time, and a variety of common traits are thought to be adaptations to variable resource supply. To understand the trait structure of communities, it is necessary to understand the functional trade-offs that determine what trait combinations are possible and which species can persist and coexist in a given environment. We compare traits across phytoplankton species in order to test for proposed trade-offs between maximum growth rate, equilibrium competitive ability for phosphorus (P), and ability to store P. We find evidence for a three-way trade-off between these traits, and we use empirical trait covariation to parameterize a mechanistic model of competition under pulsed P supply. The model shows that different strategies are favored under different conditions of nutrient supply regime, productivity, and mortality. Furthermore, multiple strategies typically coexist, and the range of traits that persist in the model is similar to the range of traits found in real species. These results suggest that mechanistic models informed by empirical trait variation, in combination with data on the trait structure of natural communities, will play an important role in uncovering the mechanisms that underlie the diversity and structure of ecological communities.

Functional traits explain phytoplankton responses to environmental gradients across lakes of the United States.

Ecological communities exhibit regular shifts in structure along environmental gradients, but it has proved difficult to dissect the mechanisms by which environmental conditions determine the relative success of species. Functional traits may provide a link between environmental drivers and mechanisms of community membership, but this has not been well tested for phytoplankton, which dominate primary production in many aquatic ecosystems. Here we test whether functional traits of phytoplankton can explain how species respond to gradients of light and phosphorus across U.S. lakes. We find that traits related to light utilization and maximum growth rate can predict species' differential responses to the relative availability of these resources. These results show that laboratory-measured traits are predictive of species' performance under natural conditions, that functional traits provide a mechanistic foundation for community ecology, and that variation in community structure is predictable in spite of the complexity of ecological communities.

Successional dynamics in the seasonally forced diamond food web.

Plankton seasonal succession is a classic example of nonequilibrium community dynamics. Despite the fact that it has been well studied empirically, it lacks a general quantitative theory. Here we investigate a food web model that includes a resource, two phytoplankton, and a shared grazer-the diamond food web-in a seasonal environment. The model produces a number of successional trajectories that have been widely discussed in the context of the verbal Plankton Ecology Group model of succession, such as a spring bloom of a good competitor followed by a grazer-induced clear-water phase, setting the stage for the late-season dominance of a grazer-resistant species. It also predicts a novel, counterintuitive trajectory where the grazer-resistant species has both early- and late-season blooms. The model often generates regular annual cycles but sometimes produces multiyear cycles or chaos, even with identical forcing each year. Parameterizing the model, we show how the successional trajectory depends on nutrient supply and the length of the growing season, two key parameters that vary among water bodies. This model extends nonequilibrium theory to food webs and is a first step toward a quantitative theory of plankton seasonal succession.

Transient dynamics and the destabilizing effects of prey heterogeneity.

The presence of prey heterogeneity and weakly interacting prey species is frequently viewed as a stabilizer of predator-prey dynamics, countering the destabilizing effects of enrichment and reducing the amplitude of population cycles. However, prior model explorations have largely focused on long-term, dynamic attractors rather than transient dynamics. Recent theoretical work shows that the presence of prey that are defended from predation can have strongly divergent effects on dynamics depending on time scale: prey heterogeneity can counteract the destabilizing effects of enrichment on predator-prey dynamics at long time scales but strongly destabilize systems during transient phases by creating long periods of low predator/prey abundance and increasing extinction probability (an effect that is amplified with increasing enrichment). We tested these general predictions using a planktonic system composed of a zooplankton predator and multiple algal prey. We first parameterized a model of our system to generate predictions and tested these experimentally. Our results qualitatively supported several model predictions. During transient phases, presence of defended algal prey increased predator extinctions at low and high enrichment levels compared to systems with only a single edible prey. This destabilizing effect was moderated at higher dilution rates, as predicted by our model. When examining dynamics beyond initial oscillations, presence of the defended prey increased predator-prey temporal variability at high nutrient enrichment but had no effect at low nutrient levels. Our results highlight the importance of considering transient dynamics when assessing the role of stabilizing factors on the dynamics of food webs.