Evolutionary consequences of multidriver environmental change in an aquatic primary producer

The use of experimentally evolved coral photosymbionts for reef restoration

The heat tolerance of corals is largely determined by their microbial photosymbionts (Symbiodiniaceae, colloquially known as zooxanthellae). Therefore, manipulating symbiont communities may enhance the ability of corals to survive summer heatwaves. Although heat-tolerant and -sensitive symbiont species occur in nature, even corals that harbour naturally tolerant symbionts have been observed to bleach during summer heatwaves. Experimental evolution (i.e., laboratory selection) of Symbiodiniaceae cultures under elevated temperatures has been successfully used to enhance their upper thermal tolerance, both in vitro and, in some instances, following their reintroduction into corals. In this review, we present the state of this intervention and its potential role within coral reef restoration, and discuss the next critical steps required to bridge the gap to implementation.

Herbivory and elevated levels of CO2 and nutrients separately, rather than synergistically, impacted biomass production and allocation in invasive and native plant species

Large parts of the Earth are experiencing environmental change caused by alien plant invasions, rising atmospheric concentration of carbon dioxide (CO2 ), and nutrient enrichments. Elevated CO2 and nutrient concentrations can separately favour growth of invasive plants over that of natives but how herbivory may modulate the magnitude and direction of net responses by the two groups of plants to simultaneous CO2 and nutrient enrichments remains unknown. In line with the enemy release hypothesis, invasive plant species should reallocate metabolites from costly anti-herbivore defences into greater growth following escape from intense herbivory in the native range. Therefore, invasive plants should have greater growth than native plants under simultaneous CO2 and nutrient enrichments in the absence of herbivory. To test this prediction, we grew nine congeneric pairs of invasive and native plant species that naturally co-occurred in grasslands in China under two levels each of nutrient enrichment (low-nutrient vs. high-nutrient), herbivory (with herbivory vs. without herbivory) and under ambient (412.9 ± 0.6 ppm) and elevated (790.1 ± 6.2 ppm) levels of CO2 concentrations in open top chambers in a common garden. Elevated CO2 and nutrient enrichment separately increased total plant biomass, while herbivory reduced it regardless of the plant invasive status. High-nutrient treatment caused the plants to allocate a significantly lower proportion of total biomass to roots, while herbivory induced an opposite pattern. Herbivory suppressed total biomass production more strongly in native plants than invasive plants. The plants exhibited significant interspecific and intergeneric variation in their responses to the various treatment combinations. Overall, these results suggest that elevated CO2 and nutrients and herbivory may separately, rather than synergistically, impact productivity of the invasive and co-occurring native plant species in our study system. Moreover, interspecific variation in resource-use strategies was more important than invasive status in determining plant responses to the various treatment combinations.

Long-term adaptation to elevated temperature but not CO2 alleviates the negative effects of ultraviolet-B radiation in a marine diatom

Multifaceted changes in marine environments as a result of anthropogenic activities are likely to have a compounding impact on the physiology of marine phytoplankton. Most studies on the combined effects of rising pCO₂, sea surface temperature, and UVB radiation on marine phytoplankton were only conducted in the short-term, which does not allow to test the adaptive capacity of phytoplankton and associated potential trade-offs. Here, we investigated populations of the diatom Phaeodactylum tricornutum that were long-term (∼3.5 years, ∼3000 generations) adapted to elevated CO₂ and/or elevated temperatures, and their physiological responses to short-term (∼2 weeks) exposure of two levels of ultraviolet-B (UVB) radiation. Our results showed that while elevated UVB radiation showed predominantly negative effects on the physiological performance of P. tricornutum regardless of adaptation regimes. Elevated temperature alleviated these effects on most of the measured physiological parameters (e.g., photosynthesis). We also found that elevated CO₂ can modulate these antagonistic interactions, and conclude that long-term adaptation to sea surface warming and rising CO₂ may alter this diatom's sensitivity to elevated UVB radiation in the environment. Our study provides new insights into marine phytoplankton's long-term responses to the interplay of multiple environmental changes driven by climate change.

Tracking contemporary microbial evolution in a changing ocean

Ocean microbes are fundamental for the functioning of the Earth system. Yet, our understanding of how they are reacting to global change in terms of evolution is limited. Microbes typically grow in large populations and reproduce quickly, which may allow them to rapidly adapt to environmental stressors compared to larger organisms. However, genetic evidence of contemporary evolution in wild microbes is scarce. We must begin coordinated efforts to establish new microbial time-series and explore novel tools, experiments, and data to fill this knowledge gap. The development of coordinated microbial 'genomic' observatories will provide the unprecedented opportunity to track contemporary microbial evolution in the ocean and explore the role of evolution in enabling wild microbes to respond to global change.

Predicting effects of multiple interacting global change drivers across trophic levels

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Population-specific vulnerability to ocean change in a multistressor environment

Variation in environmental conditions across a species' range can alter their responses to environmental change through local adaptation and acclimation. Evolutionary responses, however, may be challenged in ecosystems with tightly coupled environmental conditions, where changes in the covariance of environmental factors may make it more difficult for species to adapt to global change. Here, we conduct a 3-month-long mesocosm experiment and find evidence for local adaptation/acclimation in populations of red sea urchins, Mesocentrotus franciscanus, to multiple environmental drivers. Moreover, populations differ in their response to projected concurrent changes in pH, temperature, and dissolved oxygen. Our results highlight the potential for local adaptation/acclimation to multivariate environmental regimes but suggest that thresholds in responses to a single environmental variable, such as temperature, may be more important than changes to environmental covariance. Therefore, identifying physiological thresholds in key environmental drivers may be particularly useful for preserving biodiversity and ecosystem functioning.

Elevated CO2 reduces copper accumulation and toxicity in the diatom Thalassiosira pseudonana

The projected ocean acidification (OA) associated with increasing atmospheric CO₂ alters seawater chemistry and hence the bio-toxicity of metal ions. However, it is still unclear how OA might affect the long-term resilience of globally important marine microalgae to anthropogenic metal stress. To explore the effect of increasing pCO₂ on copper metabolism in the diatom Thalassiosira pseudonana (CCMP 1335), we employed an integrated eco-physiological, analytical chemistry, and transcriptomic approach to clarify the effect of increasing pCO₂ on copper metabolism of Thalassiosira pseudonana across different temporal (short-term vs. long-term) and spatial (indoor laboratory experiments vs. outdoor mesocosms experiments) scales. We found that increasing pCO₂ (1,000 and 2,000 μatm) promoted growth and photosynthesis, but decreased copper accumulation and alleviated its bio-toxicity to T. pseudonana. Transcriptomics results indicated that T. pseudonana altered the copper detoxification strategy under OA by decreasing copper uptake and enhancing copper-thiol complexation and copper efflux. Biochemical analysis further showed that the activities of the antioxidant enzymes glutathione peroxidase (GPX), catalase (CAT), and phytochelatin synthetase (PCS) were enhanced to mitigate oxidative damage of copper stress under elevated CO₂. Our results provide a basis for a better understanding of the bioremediation capacity of marine primary producers, which may have profound effect on the security of seafood quality and marine ecosystem sustainability under further climate change.

Evidence for evolutionary adaptation of mixotrophic nanoflagellates to warmer temperatures

Mixotrophs, organisms that combine photosynthesis and heterotrophy to gain energy, play an important role in global biogeochemical cycles. Metabolic theory predicts that mixotrophs will become more heterotrophic with rising temperatures, potentially creating a positive feedback loop that accelerates carbon dioxide accumulation in the atmosphere. Studies testing this theory have focused on phenotypically plastic (short-term, non-evolutionary) thermal responses of mixotrophs. However, as small organisms with short generation times and large population sizes, mixotrophs may rapidly evolve in response to climate change. Here, we present data from a 3-year experiment quantifying the evolutionary response of two mixotrophic nanoflagellates to temperature. We found evidence for adaptive evolution (increased growth rates in evolved relative to acclimated lineages) in the obligately phototrophic strain, but not in the facultative phototroph. All lineages showed trends of increased carbon use efficiency, flattening of thermal reaction norms, and a return to homeostatic gene expression. Generally, mixotrophs evolved reduced photosynthesis and higher grazing with increased temperatures, suggesting that evolution may act to exacerbate mixotrophs' effects on global carbon cycling.

Increased genetic diversity loss and genetic differentiation in a model marine diatom adapted to ocean warming compared to high CO2

Although high CO2 and warming could act interactively on marine phytoplankton, little is known about the molecular basis for this interaction on an evolutionary scale. Here we explored the adaptation to high CO2 in combination with warming in a model marine diatom Phaeodactylum tricornutum. Whole-genome re-sequencing identifies, in comparison to populations grown under control conditions, a larger genetic diversity loss and a higher genetic differentiation in the populations adapted for 2 years to warming than in those adapted to high CO2. However, this diversity loss was less under high CO2 combined with warming, suggesting that the evolution driven by warming was constrained by high CO2. By integrating genomics, transcriptomics, and physiological data, we found that the underlying molecular basis for this constraint is associated with the expression of genes involved in some key metabolic pathways or biological processes, such as the glyoxylate pathway, amino acid and fatty acid metabolism, and diel variability. Our results shed new light on the evolutionary responses of marine phytoplankton to multiple environmental changes in the context of global change and provide new insights into the molecular basis underpinning interactions among those multiple drivers.

Experimental evolution reveals the synergistic genomic mechanisms of adaptation to ocean warming and acidification in a marine copepod

Metazoan adaptation to global change relies on selection of standing genetic variation. Determining the extent to which this variation exists in natural populations, particularly for responses to simultaneous stressors, is essential to make accurate predictions for persistence in future conditions. Here, we identified the genetic variation enabling the copepod Acartia tonsa to adapt to experimental ocean warming, acidification, and combined ocean warming and acidification (OWA) over 25 generations of continual selection. Replicate populations showed a consistent polygenic response to each condition, targeting an array of adaptive mechanisms including cellular homeostasis, development, and stress response. We used a genome-wide covariance approach to partition the allelic changes into three categories: selection, drift and replicate-specific selection, and laboratory adaptation responses. The majority of allele frequency change in warming (57%) and OWA (63%) was driven by shared selection pressures across replicates, but this effect was weaker under acidification alone (20%). OWA and warming shared 37% of their response to selection but OWA and acidification shared just 1%, indicating that warming is the dominant driver of selection in OWA. Despite the dominance of warming, the interaction with acidification was still critical as the OWA selection response was highly synergistic with 47% of the allelic selection response unique from either individual treatment. These results disentangle how genomic targets of selection differ between single and multiple stressors and demonstrate the complexity that nonadditive multiple stressors will contribute to predictions of adaptation to complex environmental shifts caused by global change.

Strong selective environments determine evolutionary outcome in time‐dependent fitness seascapes

The impact of fitness landscape features on evolutionary outcomes has attracted considerable interest in recent decades. However, evolution often occurs under time‐dependent selection in so‐called fitness seascapes where the landscape is under flux. Fitness seascapes are an inherent feature of natural environments, where the landscape changes owing both to the intrinsic fitness consequences of previous adaptations and extrinsic changes in selected traits caused by new environments. The complexity of such seascapes may curb the predictability of evolution. However, empirical efforts to test this question using a comprehensive set of regimes are lacking. Here, we employed an in vitro microbial model system to investigate differences in evolutionary outcomes between time‐invariant and time‐dependent environments, including all possible temporal permutations, with three subinhibitory antimicrobials and a viral parasite (phage) as selective agents. Expectedly, time‐invariant environments caused stronger directional selection for resistances compared to time‐dependent environments. Intriguingly, however, multidrug resistance outcomes in both cases were largely driven by two strong selective agents (rifampicin and phage) out of four agents in total. These agents either caused cross‐resistance or obscured the phenotypic effect of other resistance mutations, modulating the evolutionary outcome overall in time‐invariant environments and as a function of exposure epoch in time‐dependent environments. This suggests that identifying strong selective agents and their pleiotropic effects is critical for predicting evolution in fitness seascapes, with ramifications for evolutionarily informed strategies to mitigate drug resistance evolution.

Changes in the growth rate of Chlamydomonas reinhardtii under long-term selection by temperature and salinity: Acclimation vs. evolution

We investigated the roles of acclimation and different components involved in evolution (adaptation, chance and history) on the changes in the growth rate of the model freshwater microalga Chlamydomonas reinhardtii P. A. Dang. exposed to selective temperature and salinity. Three C. reinhardtii strains previously grown during one year in freshwater medium and 20 °C were exposed to 5 °C temperature increase and a salinity of 5 g L^-1 NaCl. Cultures under each selective scenario and in combination (increase of salinity and temperature), were propagated until growth rate achieved an invariant mean value for 6 months (100-350 generations, varying as a function of scenario and strain). The changes of the growth rate under increased temperature were due to both adaptation and acclimation, as well as history. However, acclimation was the only mechanism detected under salinity increase as well as in the selective scenario of both temperature and salinity, suggesting that genetic variability would not allow survival at salinity higher than that to which experimental populations were exposed. Therefore, it could be hypothesized that under a global change scenario an increase in salinity would be a greater challenge than warming for some freshwater phytoplankton.

Rapid evolution generates synergism between multiple stressors: Linking theory and an evolution experiment

Global change encompasses many co-occurring anthropogenic stressors. Understanding the interactions between these multiple stressors, whether they be additive, antagonistic or synergistic, is critical for ecosystem managers when prioritizing which stressors to mitigate in the face of global change. While such interactions between stressors appear prevalent, it remains unclear if and how these interactions change over time, as the majority of multiple-stressor studies rarely span multiple generations of study organisms. Although meta-analyses have reported some intriguing temporal trends in stressor interactions, for example that synergism may take time to emerge, the mechanistic basis for such observations is unknown. In this study, by analysing data from an evolution experiment with the rotifer Brachionus calyciflorus (~35 generations and 31,320 observations), we show that adaptation to multiple stressors shifts stressor interactions towards synergism. We show that trade-offs, where populations cannot optimally perform multiple tasks (i.e. adapting to multiple stressors), generate this bias towards synergism. We also show that removal of stressors from evolved populations does not necessarily increase fitness and that there is variation in the evolutionary trajectories of populations that experienced the same stressor regimes. Our results highlight outstanding questions at the interface between evolution and global change biology, and illustrate the importance of considering rapid adaptation when managing or restoring ecosystems subjected to multiple stressors under global change.

Refocusing multiple stressor research around the targets and scales of ecological impacts

Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.

Using phenotypic plasticity to understand the structure and evolution of the genotype-phenotype map

Deciphering the genotype-phenotype map necessitates relating variation at the genetic level to variation at the phenotypic level. This endeavour is inherently limited by the availability of standing genetic variation, the rate of spontaneous mutation to novo genetic variants, and possible biases associated with induced mutagenesis. An interesting alternative is to instead rely on the environment as a source of variation. Many phenotypic traits change plastically in response to the environment, and these changes are generally underlain by changes in gene expression. Relating gene expression plasticity to the phenotypic plasticity of more integrated organismal traits thus provides useful information about which genes influence the development and expression of which traits, even in the absence of genetic variation. We here appraise the prospects and limits of such an environment-for-gene substitution for investigating the genotype-phenotype map. We review models of gene regulatory networks, and discuss the different ways in which they can incorporate the environment to mechanistically model phenotypic plasticity and its evolution. We suggest that substantial progress can be made in deciphering this genotype-environment-phenotype map, by connecting theory on gene regulatory network to empirical patterns of gene co-expression, and by more explicitly relating gene expression to the expression and development of phenotypes, both theoretically and empirically.

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.

Selection Experiments in the Sea: What Can Experimental Evolution Tell Us About How Marine Life Will Respond to Climate Change?

AbstractRapid evolution may provide a buffer against extinction risk for some species threatened by climate change; however, the capacity to evolve rapidly enough to keep pace with changing environments is unknown for most taxa. The ecosystem-level consequences of climate adaptation are likely to be the largest in marine ecosystems, where short-lived phytoplankton with large effective population sizes make up the bulk of primary production. However, there are substantial challenges to predicting climate-driven evolution in marine systems, including multiple simultaneous axes of change and considerable heterogeneity in rates of change, as well as the biphasic life cycles of many marine metazoans, which expose different life stages to disparate sources of selection. A critical tool for addressing these challenges is experimental evolution, where populations of organisms are directly exposed to controlled sources of selection to test evolutionary responses. We review the use of experimental evolution to test the capacity to adapt to climate change stressors in marine species. The application of experimental evolution in this context has grown dramatically in the past decade, shedding light on the capacity for evolution, associated trade-offs, and the genetic architecture of stress-tolerance traits. Our goal is to highlight the utility of this approach for investigating potential responses to climate change and point a way forward for future studies.

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.

The Adaptive Potential of the Middle Domain of Yeast Hsp90

The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Adaptive responses of free-living and symbiotic microalgae to simulated future ocean conditions

Marine microalgae are a diverse group of microscopic eukaryotic and prokaryotic organisms capable of photosynthesis. They are important primary producers and carbon sinks but their physiology and persistence are severely affected by global climate change. Powerful experimental evolution technologies are being used to examine the potential of microalgae to respond adaptively to current and predicted future conditions, as well as to develop resources to facilitate species conservation and restoration of ecosystem functions. This review synthesizes findings and insights from experimental evolution studies of marine microalgae in response to elevated temperature and/or pCO₂ . Adaptation to these environmental conditions has been observed in many studies of marine dinoflagellates, diatoms and coccolithophores. An enhancement in traits such as growth and photo-physiological performance and an increase in upper thermal limit have been shown to be possible, although the extent and rate of change differ between microalgal taxa. Studies employing multiple monoclonal replicates showed variation in responses among replicates and revealed the stochasticity of mutations. The work to date is already providing valuable information on species' climate sensitivity or resilience to managers and policymakers but extrapolating these insights to ecosystem- and community-level impacts continues to be a challenge. We recommend future work should include in situ experiments, diurnal and seasonal fluctuations, multiple drivers and multiple starting genotypes. Fitness trade-offs, stable versus plastic responses and the genetic bases of the changes also need investigating, and the incorporation of genome resequencing into experimental designs will be invaluable.

Meta-analysis of multiple driver effects on marine phytoplankton highlights modulating role of pCO2

Responses of marine primary production to a changing climate are determined by a concert of multiple environmental changes, for example in temperature, light, pCO₂ , nutrients, and grazing. To make robust projections of future global marine primary production, it is crucial to understand multiple driver effects on phytoplankton. This meta-analysis quantifies individual and interactive effects of dual driver combinations on marine phytoplankton growth rates. Almost 50% of the single-species laboratory studies were excluded because central data and metadata (growth rates, carbonate system, experimental treatments) were insufficiently reported. The remaining data (42 studies) allowed for the analysis of interactions of pCO₂ with temperature, light, and nutrients, respectively. Growth rates mostly respond non-additively, whereby the interaction with increased pCO₂ profusely dampens growth-enhancing effects of high temperature and high light. Multiple and single driver effects on coccolithophores differ from other phytoplankton groups, especially in their high sensitivity to increasing pCO₂ . Polar species decrease their growth rate in response to high pCO₂ , while temperate and tropical species benefit under these conditions. Based on the observed interactions and projected changes, we anticipate primary productivity to: (a) first increase but eventually decrease in the Arctic Ocean once nutrient limitation outweighs the benefits of higher light availability; (b) decrease in the tropics and mid-latitudes due to intensifying nutrient limitation, possibly amplified by elevated pCO₂ ; and (c) increase in the Southern Ocean in view of higher nutrient availability and synergistic interaction with increasing pCO₂ . Growth-enhancing effect of high light and warming to coccolithophores, mainly Emiliania huxleyi, might increase their relative abundance as long as not offset by acidification. Dinoflagellates are expected to increase their relative abundance due to their positive growth response to increasing pCO₂ and light levels. Our analysis reveals gaps in the knowledge on multiple driver responses and provides recommendations for future work on phytoplankton.

Spatial Distribution of Phytoplankton Community Composition and Their Correlations with Environmental Drivers in Taiwan Strait of Southeast China

Large-scale dinoflagellate blooms have appeared in recent decades in the Taiwan Strait, Southeast China. To study spatial variability of phytoplankton community composition, physical and chemical environmental drivers in surface seawater of the Taiwan Strait, we conducted cruises in May and July 2019. Cell numbers of dinoflagellates were significantly higher than that of diatoms in most sampling stations during the cruise in May, whereas diatoms were the major contributor to autotrophic biomass in July. Phytoplankton community shifted from a dinoflagellate- and diatom-dominated system in May to diatom dominance in July. The dominant phytoplankton species (genera) were the harmful algal bloom dinoflagellates Prorocentrum donghaiense and Scrippsiella trochoidea and the diatoms Coscinodiscus in May, and Rhizosolenia, Pseudo-nitzschia, and Guinardia in July. Cell densities of dinoflagellates and P. donghaiense reduced exponentially with increasing seawater temperature and salinity and decreasing dissolved inorganic nitrogen (DIN) concentrations. Based on the results of our work and previous studies, it becomes obvious that harmful dinoflagellate blooms are likely to be a major component of the planktonic food web in the Taiwan Strait at a temperature of 17.0–23.0 °C, a salinity of 29.0–33.0 psu, and a DIN concentration higher than 2.0 μmol L–1.

Phenotypic trait variability as an indication of adaptive capacity in a cosmopolitan marine diatom

Determining the adaptive capacity of marine phytoplankton is important in predicting changes in phytoplankton responses to ocean warming. Phytoplankton may consist of high levels of standing phenotypic and genetic variability, the basis of rapid evolution; however, few studies have quantified trait variability within and amongst closely related diatom species. Using 35 clonal cultures of the ubiquitous marine diatom Leptocylindrus isolated from six locations, spanning 2000 km of the south-eastern Australian coastline, we found evidence of significant intraspecific morphological and metabolic trait variability, which for 8 of 9 traits (growth rate, biovolume, C:N, silica deposition, silica incorporation rate, chl-a, and photosynthetic efficiency under dark adapted, growth irradiance, and high-light adaptation) were greater within a species than between species. Moreover, only two traits revealed a latitudinal trend with strains isolated from lower latitudes showing significantly higher silicification rates and protein:lipid content compared to their higher latitude counterparts. These data mirror recent studies on diatom intraspecific genetic diversity, which has found comparable levels of genetic diversity at a single site to those thousands of kilometres apart, and provide evidence of a functional role of diatom diversity that will allow for rapid adaptation via ecological selection on standing variation in response to changing conditions.

Quality-quantity trade-offs drive functional trait evolution in a model microalgal 'climate change winner'

Phytoplankton are the unicellular photosynthetic microbes that form the base of aquatic ecosystems, and their responses to global change will impact everything from food web dynamics to global nutrient cycles. Some taxa respond to environmental change by increasing population growth rates in the short-term and are projected to increase in frequency over decades. To gain insight into how these projected 'climate change winners' evolve, we grew populations of microalgae in ameliorated environments for several hundred generations. Most populations evolved to allocate a smaller proportion of carbon to growth while increasing their ability to tolerate and metabolise reactive oxygen species (ROS). This trade-off drives the evolution of traits that underlie the ecological and biogeochemical roles of phytoplankton. This offers evolutionary and a metabolic frameworks for understanding trait evolution in projected 'climate change winners' and suggests that short-term population booms have the potential to be dampened or reversed when environmental amelioration persists.

Evolution, Microbes, and Changing Ocean Conditions

Experimental evolution and the associated theory are underutilized in marine microbial studies; the two fields have developed largely in isolation. Here, we review evolutionary tools for addressing four key areas of ocean global change biology: linking plastic and evolutionary trait changes, the contribution of environmental variability to determining trait values, the role of multiple environmental drivers in trait change, and the fate of populations near their tolerance limits. Wherever possible, we highlight which data from marine studies could use evolutionary approaches and where marine model systems can advance our understanding of evolution. Finally, we discuss the emerging field of marine microbial experimental evolution. We propose a framework linking changes in environmental quality (defined as the cumulative effect on population growth rate) with population traits affecting evolutionary potential, in order to understand which evolutionary processes are likely to be most important across a range of locations for different types of marine microbes.

Company matters: The presence of other genotypes alters traits and intraspecific selection in an Arctic diatom under climate change

Arctic phytoplankton and their response to future conditions shape one of the most rapidly changing ecosystems on the planet. We tested how much the phenotypic responses of strains from the same Arctic diatom population diverge and whether the physiology and intraspecific composition of multistrain populations differs from expectations based on single strain traits. To this end, we conducted incubation experiments with the diatom Thalassiosira hyalina under present-day and future temperature and pCO2 treatments. Six fresh isolates from the same Svalbard population were incubated as mono- and multistrain cultures. For the first time, we were able to closely follow intraspecific selection within an artificial population using microsatellites and allele-specific quantitative PCR. Our results showed not only that there is substantial variation in how strains of the same species cope with the tested environments but also that changes in genotype composition, production rates, and cellular quotas in the multistrain cultures are not predictable from monoculture performance. Nevertheless, the physiological responses as well as strain composition of the artificial populations were highly reproducible within each environment. Interestingly, we only detected significant strain sorting in those populations exposed to the future treatment. This study illustrates that the genetic composition of populations can change on very short timescales through selection from the intraspecific standing stock, indicating the potential for rapid population level adaptation to climate change. We further show that individuals adjust their phenotype not only in response to their physicochemical but also to their biological surroundings. Such intraspecific interactions need to be understood in order to realistically predict ecosystem responses to global change.

Investigating cumulative effects across ecological scales

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.

Community- and ecosystem-level effects of multiple environmental change drivers: Beyond null model testing

Understanding the joint effect of multiple drivers of environmental change is a key scientific challenge. The dominant approach today is to compare observed joint effects with predictions from various types of null models. Drivers are said to combine synergistically (antagonistically) when their observed joint effect is larger (smaller) than that predicted by the null model. Here, I argue that this approach does not promote understanding of effects on important community- and ecosystem-level variables such as biodiversity and ecosystem function. I use ecological theory to show that different mechanisms can lead to the same deviation from a null model's prediction. Inversely, I show that the same mechanism can lead to different deviations from a null model's prediction. These examples illustrate that it is not possible to make strong mechanistic inferences from null models. Next, I present an alternative framework to study such effects. This framework makes a clear distinction between two different kinds of drivers (resource ratio shifts and multiple stressors) and integrates both by incorporating stressor effects into resource uptake theory. I show that this framework can advance understanding because of three reasons. First, it forces formalization of "multiple stressors," using factors that describe the number and kind of stressors, their selectivity and dynamic behaviour, and the initial trait diversity and tolerance among species. Second, it produces testable predictions on how these factors affect biodiversity and ecosystem function, alone and in combination with resource ratio shifts. Third, it can fail in informative ways. That is, its assumptions are clear, so that different kinds of deviations between predictions and observed effects can guide new experiments and theory improvement. I conclude that this framework will more effectively progress understanding of global change effects on communities and ecosystems than does the current practice of null model testing.

Extent of adaptation is not limited by unpredictability of the environment in laboratory populations of Escherichia coli

Environmental variability is on the rise in different parts of the earth, and the survival of many species depends on how well they cope with these fluctuations. Our current understanding of how organisms adapt to unpredictably fluctuating environments is almost entirely based on studies that investigate fluctuations among different values of a single environmental stressor such as temperature or pH. How would unpredictability affect adaptation when the environment fluctuates between qualitatively very different kinds of stresses? To answer this question, we subjected laboratory populations of Escherichia coli to selection over ~ 260 generations. The populations faced predictable and unpredictable environmental fluctuations across qualitatively different selection environments, namely, salt and acidic pH. We show that predictability of environmental fluctuations does not play a role in determining the extent of adaptation, although the extent of ancestral adaptation to the chosen selection environments is of key importance.

Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change-A review

Marine life is controlled by multiple physical and chemical drivers and by diverse ecological processes. Many of these oceanic properties are being altered by climate change and other anthropogenic pressures. Hence, identifying the influences of multifaceted ocean change, from local to global scales, is a complex task. To guide policy-making and make projections of the future of the marine biosphere, it is essential to understand biological responses at physiological, evolutionary and ecological levels. Here, we contrast and compare different approaches to multiple driver experiments that aim to elucidate biological responses to a complex matrix of ocean global change. We present the benefits and the challenges of each approach with a focus on marine research, and guidelines to navigate through these different categories to help identify strategies that might best address research questions in fundamental physiology, experimental evolutionary biology and community ecology. Our review reveals that the field of multiple driver research is being pulled in complementary directions: the need for reductionist approaches to obtain process-oriented, mechanistic understanding and a requirement to quantify responses to projected future scenarios of ocean change. We conclude the review with recommendations on how best to align different experimental approaches to contribute fundamental information needed for science-based policy formulation.