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

Multifunctionality promotes the prosperity of riverine planktonic diatoms in plateau

Interpreting the biogeographic distribution and underlying mechanisms of functional traits not only contributes to revealing the spatiotemporal dynamics of species biodiversity but also helps to maintain ecological stability during environmental variations. However, little is known about the functional profiles of diatom communities over large river systems. Herein, we provided the first blueprints about the spatiotemporal distributions and driving forces of functional traits for both planktonic and sedimentary diatoms over the 6030 km continuum of the Yangtze River, with the help of the high-throughput sequencing and functional identification. By investigating the 28 functional traits affiliated into five categories, we found that planktonic diatom functions showed clearer landform-heterogeneity patterns (ANOSIM R = 0.336) than sedimentary functions (ANOSIM R = 0.172) along the river, represented by life-forms and ecological-guilds prominent in water-plateau as well as cell-sizes and life-forms particularly in sediment-plateau. Planktonic diatom functions also displayed higher richness and network complexity in plateau (richness: 58.70 ± 9.30, network edges: 65) than in non-plateau regions (23.82 ± 13.16, 16), promoting the stability and robustness of diatom functions against the high-radiation and low-temperature plateau environment. Environmental selection (mainly exerted by PAR, UV, and Tw) played crucial roles in determining the functional variations of planktonic diatoms (explaining 80.5%) rather than sedimentary diatoms (14.5%) between plateau and non-plateau regions. Meanwhile, planktonic diatom traits within life-forms were identified to be well responsive to the ecological environment quality (r = 0.56-0.60, P < 0.001) in the Yangtze. This study provided comprehensive insights into the multifunctionality of diatoms and their responses to environmental disturbance and environment quality, which helps to develop effective strategies for maintaining ecological stability in changing river environments.

A comparison of two gene regions for assessing community composition of eukaryotic marine microalgae from coastal ecosystems

Two gene regions commonly used to characterise the diversity of eukaryotic communities using metabarcoding are the 18S ribosomal DNA V4 and V9 gene regions. We assessed the effectiveness of these two regions for characterising diverisity of coastal eukaryotic microalgae communities (EMCs) from tropical and temperate sites. We binned amplicon sequence variants (ASVs) into the high level taxonomic groups: dinoflagellates, pennate diatoms, radial centric diatoms, polar centric diatoms, chlorophytes, haptophytes and 'other microalgae'. When V4 and V9 generated ASV abundances were compared, the V9 region generated a higher number of raw reads, captured more diversity from all high level taxonomic groups and was more closely aligned with the community composition determined using light microscopy. The V4 region did resolve more ASVs to a deeper taxonomic resolution within the dinoflagellates, but did not effectively resolve other major taxonomic divisions. When characterising these communities via metabarcoding, the use of multiple gene regions is recommended, but the V9 gene region can be used in isolation to provide high-level community biodiversity to reflect relative abundances within groups. This approach reduces the cost of sequencing multiple gene regions whilst still providing important baseline ecosystem function information.

An integrated individual-level trait-based phytoplankton dataset from transitional waters

Functional trait-based approaches have undergone an extraordinary expansion in phytoplankton ecology. Morpho-functional traits have been shown to vary both within and between populations and species, potentially affecting individual fitness and the network of inter-individual relationships. Here we integrate six fully harmonized phytoplankton morpho-functional trait datasets, characterized by a fine data grain, reporting individual-level data over a large biogeographical area. Datasets refer to transitional water ecosystems, from five biogeographical areas: Northern Atlantic Ocean (Scotland), South-Western Atlantic Ocean (Brazil), South-Western Pacific Ocean (Australia), Indo Pacific Ocean (Maldives) and Mediterranean Sea (Greece and Turkey). The integrated dataset includes 127311 individual phytoplankton records with sampling locations, taxonomic and morphometric information according to Darwin Core standards and semantic annotations. The six FAIR datasets are openly available in the LifeWatch Italy data portal. The datasets have already been used for morpho-functional analyses and hypothesis testing on phytoplankton guilds at different levels of data aggregation and scale, from local to global.

Macrosystem community change in lake phytoplankton and its implications for diversity and function

Aim

We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints.

Location

Finland.

Time period

1977-2017.

Major taxa

Phytoplankton.

Methods

We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a "region of common profile" approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development.

Results

We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities.

Main conclusions

Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novel community types, but only a minor part of this reshuffling could be linked to temporal environmental change.

Trophic strategies explain the ocean niches of small eukaryotic phytoplankton

A large fraction of marine primary production is performed by diverse small protists, and many of these phytoplankton are phagotrophic mixotrophs that vary widely in their capacity to consume bacterial prey. Prior analyses suggest that mixotrophic protists as a group vary in importance across ocean environments, but the mechanisms leading to broad functional diversity among mixotrophs, and the biogeochemical consequences of this, are less clear. Here we use isolates from seven major taxa to demonstrate a tradeoff between phototrophic performance (growth in the absence of prey) and phagotrophic performance (clearance rate when consuming Prochlorococcus). We then show that trophic strategy along the autotrophy-mixotrophy spectrum correlates strongly with global niche differences, across depths and across gradients of stratification and chlorophyll a. A model of competition shows that community shifts can be explained by greater fitness of faster-grazing mixotrophs when nutrients are scarce and light is plentiful. Our results illustrate how basic physiological constraints and principles of resource competition can organize complexity in the surface ocean ecosystem.

Ecology and evolution of competitive trait variation in natural phytoplankton communities under selection

Competition for limited resources is a major force in structuring ecological communities. Species minimum resource requirements (R*s) can predict competitive outcomes and evolve under selection in simple communities under controlled conditions. However, whether R*s predict competitive outcomes or demonstrate adaptive evolution in naturally complex communities is unknown. We subjected natural phytoplankton communities to three types of resource limitation (nitrogen, phosphorus, light) in outdoor mesocosms over 10 weeks. We examined the community composition weekly and isolated 21 phytoplankton strains from seven species to quantify responses to the selection of R* for these resources. We investigated the evolutionary change in R*s in the dominant species, Desmodesmus armatus. R*s were good predictors of species changes in relative abundance, though this was largely driven by the success of D. armatus across several treatments. This species also demonstrated an evolutionary change in R*s under resource limitation, supporting the potential for adaptive trait change to modify competitive outcomes in natural communities.

The spatiotemporal variations in microalgae communities in vertical waters of a subtropical reservoir

The construction of cascade reservoirs increases eutrophication and exacerbates algal blooms and thus threatens water quality. Previous studies on the microalgae in reservoir have mainly focused on the spatio-temporal patterns of surface microalgae communities at the horizontal scale, while few studies have simultaneously considered the successions of microalgae in vertical profiles including the sediments and the effects of the nutrients release and microalgae in sediments on microalgae in upper waters. In this study, we investigated the effects of microalgae and physico-chemical parameters in waters and sediments on the successions of vertical microalgae communities in Xipi Reservoir, Southeast China. The seasonal variations in microalgae compositions decreased gradually from the surface water (the dominance of Cryptophyta and Chlorophyta in spring, Chlorophyta and Cyanophyta in summer, and relatively uniform in autumn and winter) to the sediment (the dominance of Bacillariophyta throughout the year), which was influenced by the variations of physico-chemical factors in different layers. The spatio-temporal variations in microalgae communities in waters was attributing to not only the heterogeneities of the stratification, and the physico-chemical factors such as water temperature, pH, and nutrient concentrations, especially for phosphorus in the water column, but also the combinations of phosphorus release and microalgae composition in sediments. Environmental changes would be especially problematic for microalgae groups such as Cryptophyta, Dinophyta and Chlorophyta that were sensitive to the changes of temperature and nutrients. Our results are helpful for an extensive understanding of the dynamics of microalgae communities in reservoir, and contribute to reservoir management for ensuring the safety of drinking water.

Life history mediates the association between parasite abundance and geographic features

Though parasites are ubiquitous in marine ecosystems, predicting the abundance of parasites present within marine ecosystems has proven challenging due to the unknown effects of multiple interacting environmental gradients and stressors. Furthermore, parasites often are considered as a uniform group within ecosystems despite their significant diversity. We aim to determine the potential importance of multiple predictors of parasite abundance in coral reef ecosystems, including reef area, island area, human population density, chlorophyll-a, host diversity, coral cover, host abundance, and island isolation. Using a model selection approach within a database of more than 1200 individual fish hosts and their parasites from 11 islands within the Pacific Line Islands archipelago, we reveal that geographic gradients, including island area and island isolation, emerged as the best predictors of parasite abundance. Life history moderated the relationship; parasites with complex life cycles increased in abundance with increasing island isolation, while parasites with direct life cycles decreased with increasing isolation. Direct life cycle parasites increased in abundance with increasing island area, though complex life cycle parasite abundance was not associated with island area. This novel analysis of a unique dataset indicates that parasite abundance in marine systems cannot be predicted precisely without accounting for the independent and interactive effects of each parasite's life history and environmental conditions.

Effects of Vertical Spatial Overlap on Phytoplankton Diversity under Experimentally Altered Lake Stratification Regimes

In phytoplankton communities, competitive exclusion might occur when functionally similar species are impeded from regulating their positions along light and nutrient gradients to reduce niche overlap. Greater spatial overlap (SO) between species due to water column mixing could thus promote competitive exclusion, reducing community taxonomic diversity. However, greater SO could also promote coexistence of functionally different taxa. Using data from a whole-lake experiment, we investigated the effects of SO and other relevant environmental factors on phytoplankton diversity across the water columns of lake basins with different thermocline manipulations. We estimated SO using an in situ fluorometer, and overall community diversity microscopically. Using structured equation models, we estimated directional relationships between phytoplankton diversity, SO, the lake physical structure and the zooplankton community. No significant effect of SO on phytoplankton taxonomic diversity was observed, but higher SO was associated with greater functional diversity. Change in lake physical structure and in the zooplankton community also affected diversity, with a negative response to increased top-down interactions. Overall, despite the fact that the alteration of water column stratification structure and top-down interactions were stronger drivers of phytoplankton diversity in our system, some effect of spatial overlap on the outcome of inferred competitive interactions were observable.

Stressor richness intensifies productivity loss but mitigates biodiversity loss

Ecosystems are subject to a multitude of anthropogenic environmental changes. Experimental research in the field of multiple stressors has typically involved varying the number of stressors, here termed stressor richness, but without controlling for total stressor intensity. Mistaking stressor intensity effects for stressor richness effects can misinform management decisions when there is a trade-off between mitigating these two factors. We incorporate multiple stressors into three community models and show that, at a fixed total stressor intensity, increasing stressor richness aggravates joint stressor effects on ecosystem functioning, but reduces effects on species persistence and composition. In addition, stressor richness weakens the positive selection and negative complementarity effects on ecosystem function. We identify the among-species variation of stressor effects on traits as a key determinant of the resulting community-level stressor effects. Taken together, our results unravel the mechanisms linking multiple environmental changes to biodiversity and ecosystem function.

The evolution of competitive ability for essential resources

Competition for limiting resources is among the most fundamental ecological interactions and has long been considered a key driver of species coexistence and biodiversity. Species' minimum resource requirements, their R*s, are key traits that link individual physiological demands to the outcome of competition. However, a major question remains unanswered-to what extent are species' competitive traits able to evolve in response to resource limitation? To address this knowledge gap, we performed an evolution experiment in which we exposed Chlamydomonas reinhardtii for approximately 285 generations to seven environments in chemostats that differed in resource supply ratios (including nitrogen, phosphorus and light limitation) and salt stress. We then grew the ancestors and descendants in a common garden and quantified their competitive abilities for essential resources. We investigated constraints on trait evolution by testing whether changes in resource requirements for different resources were correlated. Competitive abilities for phosphorus improved in all populations, while competitive abilities for nitrogen and light increased in some populations and decreased in others. In contrast to the common assumption that there are trade-offs between competitive abilities for different resources, we found that improvements in competitive ability for a resource came at no detectable cost. Instead, improvements in competitive ability for multiple resources were either positively correlated or not significantly correlated. Using resource competition theory, we then demonstrated that rapid adaptation in competitive traits altered the predicted outcomes of competition. These results highlight the need to incorporate contemporary evolutionary change into predictions of competitive community dynamics over environmental gradients. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Limited evidence for common interannual trends in Baltic Sea summer phytoplankton biomass

The Baltic Sea summer phytoplankton community plays an important role in biogeochemical cycling and in the transfer of energy through the food web via zooplankton. We aimed to improve the understanding of the degree to which large-scale versus local environmental dynamics regulate phytoplankton dynamics by analyzing time series at the Baltic Sea scale. We used dynamic factor analysis to study if there are common patterns of interannual variation that are shared (“common trends”) among summer phytoplankton total and class-level biomass time series observed across Baltic Sea latitudinal gradients in salinity and temperature. We evaluated alternative hypotheses regarding common trends among summer phytoplankton biomass: Baltic Sea-wide common trends; common trends by geography (latitude and basin); common trends differing among functional groups (phytoplankton classes); or common trends driven by both geography and functional group. Our results indicated little support for a common trend in total summer phytoplankton biomass. At a finer resolution, classes had common trends that were most closely associated with the cryptophyte and cyanobacteria time series with patterns that differed between northern and southern sampling stations. These common trends were also very sensitive to two anomalous years (1990, 2008) of cryptophyte biomass. The Baltic Sea Index, a regional climate index, was correlated with two common class trends that shifted in mean state around the mid-1990s. The limited coherence in phytoplankton biomass variation over time despite known, large-scale, ecosystem shifts suggests that stochastic dynamics at local scales limits the ability to observe common trends at the scale of monitoring data collection.

The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton

Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.

Trait-environment interactions affect plant establishment success during restoration

Establishment and persistence are central to community assembly and are determined by how traits interact with the environment to determine performance (trait-environment interactions). Community assembly studies have rarely considered such trait-environment interactions, however, which can lead to incorrect inferences about how traits affect assembly. We evaluated how functional traits, environmental conditions, and trait-environment interactions structure plant establishment, as a measure of performance. Within 12 prairie restorations created by sowing 70 species, we quantified environmental conditions and counted individuals of each seeded species to quantify first-year establishment. Three trait-environment interactions structured establishment. Leaf nitrogen interacted with herbivore pressure, as low leaf nitrogen species established relatively better under higher herbivory than species with high leaf nitrogen. Soil moisture interacted with root mass fraction (RMF), with low-RMF species establishing better with low soil moisture and higher-RMF species better on wetter soils. Specific leaf area (SLA) interacted with light availability, as low-SLA species established better under high light conditions and high-SLA species under low light conditions. Our work illustrates how community assembly can be better described by trait-environment interactions than correlating traits or environment with performance. This knowledge can assist species selection to maximize restoration success.

Correlates of different facets and components of beta diversity in stream organisms

Recently, community ecology has emphasized the multi-facetted aspects of biological diversity by linking species traits and the environment. Here, we explored environmental correlates of taxonomically-based and traits-based compositional distances using a comprehensive data set of diatom and macroinvertebrate communities. We also explored the responses of different beta diversity components (i.e., overall beta diversity, turnover, and nestedness) of beta diversity facets (i.e., taxonomically and traits-based beta diversity) to environmental distances. Partial Mantel tests were used to test the relationships between beta diversity and environmental distance (while controlling for spatial distances). Taxonomically-based beta diversity varied much more than traits-based beta diversity, indicating strong functional convergence. We found that taxonomically-based beta diversity was largely driven by the turnover component. However, the nestedness component contributed more to overall traits-based beta diversity than the turnover component. Taxonomically-based beta diversity was significantly correlated with environmental distances for both diatoms and macroinvertebrates. Thus, we found support for the role of environmental filtering as a driver of community dissimilarities of rather different biological groups. However, the strength of these relationships between beta diversity and environmental distances varied depending on the biological group, facet, component, and the way which the environmental variables were selected to calculate the explanatory (distance) matrix. Our results indicated that both taxonomically and traits-based approaches are still needed to better understand patterns and mechanisms affecting the organization of biological communities in streams. This is because different facets of biological communities may be driven by different mechanisms.

Allometric scaling and morphological variation in sinking rate of phytoplankton

Since the first decades of the last century, several hypotheses have been proposed on the role of phytoplankton morphology in maintaining a favorable position in the water column. Here, by an extensive review of literature on sinking rate and cell volume, we firstly attempted to explore the dependency of sinking rate on morphological traits using the allometric scaling approach. We found that sinking rate tends to increase with increasing cell volume showing the allometric scaling exponent of 0.43, which is significantly different than the Stokes' law exponent of 0.66. The violation of the 2/3 power rule clearly indicates that cell shape changes as size increases. Both size and shape affect how phytoplankton sinking drives nutrient acquisition and losses to sinking. Interestingly, from an evolutionary perspective, simple and complex cylindrical shapes can get much larger than spherical and spheroidal shapes and sink at similar rates, but simple and complex cylindrical shapes cannot get small enough to sink slower than small spherical and spheroidal shapes. Cell shape complexity is a morphological attribute resulting from the combination of two or more simple geometric shapes. While the effect of size on sinking rate is well documented, this study deepens the knowledge on how cell shape or geometry affect sinking rates that still needs further consideration.

A Randomized Trait Community Clustering approach to unveil consistent environmental thresholds in community assembly

Similarities and differences of phenotypes within local co-occurring species hold the key to inferring the contribution of stochastic or deterministic processes in community assembly. Developing both phylogenetic-based and trait-based quantitative methods to unravel these processes is a major aim in community ecology. We developed a trait-based approach that: (i) assesses if a community trait clustering pattern is related to increasing environmental constraints along a gradient; and (ii) determines quantitative thresholds for an environmental variable along a gradient to interpret changes in prevailing community assembly drivers. We used a regional set of natural shallow saline ponds covering a wide salinity gradient (0.1-40% w/v). We identify a consistent discrete salinity threshold (ca. 5%) for microbial community assembly drivers. Above 5% salinity a strong environmental filtering prevailed as an assembly force, whereas a combination of biotic and abiotic factors dominated at lower salinities. This method provides a conceptual approach to identify consistent environmental thresholds in community assembly and enables quantitative predictions for the ecological impact of environmental changes.

Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtii's gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticity's interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity.

Proteome evolution under non-substitutable resource limitation

Resource limitation is a major driver of the ecological and evolutionary dynamics of organisms. Short-term responses to resource limitation include plastic changes in molecular phenotypes including protein expression. Yet little is known about the evolution of the molecular phenotype under longer-term resource limitation. Here, we combine experimental evolution of the green alga Chlamydomonas reinhardtii under multiple different non-substitutable resource limitation regimes with proteomic measurements to investigate evolutionary adaptation of the molecular phenotype. We demonstrate convergent proteomic evolution of core metabolic functions, including the Calvin-Benson cycle and gluconeogenesis, across different resource limitation environments. We do not observe proteomic changes consistent with optimized uptake of particular limiting resources. Instead, we report that adaptation proceeds in similar directions under different types of non-substitutable resource limitation. This largely convergent evolution of the expression of core metabolic proteins is associated with an improvement in the resource assimilation efficiency of nitrogen and phosphorus into biomass.

Organisms could respond to essential resource limitation by increasing metabolic efficiency or resource acquisition ability. Here, the authors experimentally evolve green algae under different resource limitations and show convergent evolution of core metabolism rather than resource specialization.

Trait selection and co-existence of phytoplankton in partially mixed systems: Trait based modelling and potential of an aggregated approach

Trait selection and co-existence in phytoplankton communities in partially mixed water columns is investigated using trait based modelling. In the models employed, trait selection results from phytoplankton competition for two limiting resources, light and nutrients. The study employs spatially resolved models, in which the phytoplankton community is represented as a large number of trait-groups characterized by fixed trait combinations (trade-offs). Results from the trait-group resolving model (RM) are compared to results from an aggregated trait based model with adaptive traits (AM). Differences in specific production resulting from a trade-off between the half saturation constants of light and nutrients are sufficient to support evolutionary stable co-existence confirming that co-existence does not require differences in resource consumption. If abiotic conditions lead to the selection of a single trait group in RM, AM provides excellent approximations of the development of total biomass, average community trait and trait variance in the phytoplankton community. However, if selection leads to bimodal trait distributions, e.g. to co-existence of two trait groups (or species), functionally important properties of the phytoplankton community cannot be adequately represented by the aggregated information provided by AM. Because the increase in variance due to the development of bimodal trait distributions cannot be distinguished from an increase in variance due to an increase in trait diversity, the development of trait variance in AM models is not a reliable measure of trait diversity. Furthermore, AM may not provide reliable simulations of trophic interactions if the performance of the consumers depends on the traits of their resources. However, AM may support exploration of the consequences of environmental conditions and of the parameterization of species for co-existence within communities.

Comparison of microbial taxonomic and functional shift pattern along contamination gradient

BACKGROUND

The interaction mechanism between microbial communities and environment is a key issue in microbial ecology. Microbial communities usually change significantly under environmental stress, which has been studied both phylogenetically and functionally, however which method is more effective in assessing the relationship between microbial communities shift and environmental changes still remains controversial.

RESULTS

By comparing the microbial taxonomic and functional shift pattern along heavy metal contamination gradient, we found that both sedimentary composition and function shifted significantly along contamination gradient. For example, the relative abundance of Geobacter and Fusibacter decreased along contamination gradient (from high to low), while Janthinobacterium and Arthrobacter increased their abundances. Most genes involved in heavy metal resistance (e.g., metc, aoxb and mer) showed higher intensity in sites with higher concentration of heavy metals. Comparing the two shift patterns, there were correlations between them, because functional and phylogenetic β-diversities were significantly correlated, and many heavy metal resistance genes were derived from Geobacter, explaining their high abundance in heavily contaminated sites. However, there was a stronger link between functional composition and environmental drivers, while stochasticity played an important role in formation and succession of phylogenetic composition demonstrated by null model test.

CONCLUSIONS

Overall our research suggested that the responses of functional traits depended more on environmental changes, while stochasticity played an important role in formation and succession of phylogenetic composition for microbial communities. So profiling microbial functional composition seems more appropriate to study the relationship between microbial communities and environment, as well as explore the adaptation and remediation mechanism of microbial communities to heavy metal contamination.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Margalef revisited: A new phytoplankton mandala incorporating twelve dimensions, including nutritional physiology

Building on the classic depiction of the progression from a diatom to a dinoflagellate bloom as a function of nutrients and turbulence, known as the "Margalef mandala", a new conceptual model or mandala is presented here. The new mandala maps twelve response or effects traits, or environmental characteristics, related to different phytoplankton functional types: (1) relative preference for chemically reduced vs chemically oxidized forms of nitrogen; (2) relative availability of inorganic nitrogen and phosphorus; (3) adaptation to high vs low light and the tendency to be autotrophic vs mixotrophic; (4) cell motility; (5) environmental turbulence; (6) pigmentation quality; (7) temperature; (8) cell size; (9) relative growth rate; (10) relative production of bioactive compounds such as toxins or reactive oxygen species (ROS); (11) r vs K strategy; and (12) fate of the production in terms of grazing. The new mandala serves to highlight the differences and trade-offs between traits and/or environmental conditions, and illustrates some traits tend to track each other, a concept that may be helpful in trait-based modeling approaches and in understanding environmental factors associated with harmful algal blooms. It is hoped that this new mandala captures some of our recent insight into phytoplankton physiology and functional traits, and has contemporary relevance in light of anthropogenic changes in nutrient form and ratio.

A trait-based framework for stream algal communities

The use of trait-based approaches to detect effects of land use and climate change on terrestrial plant and aquatic phytoplankton communities is increasing, but such a framework is still needed for benthic stream algae. Here we present a conceptual framework of morphological, physiological, behavioural and life-history traits relating to resource acquisition and resistance to disturbance. We tested this approach by assessing the relationships between multiple anthropogenic stressors and algal traits at 43 stream sites. Our "natural experiment" was conducted along gradients of agricultural land-use intensity (0-95% of the catchment in high-producing pasture) and hydrological alteration (0-92% streamflow reduction resulting from water abstraction for irrigation) as well as related physicochemical variables (total nitrogen concentration and deposited fine sediment). Strategic choice of study sites meant that agricultural intensity and hydrological alteration were uncorrelated. We studied the relationships of seven traits (with 23 trait categories) to our environmental predictor variables using general linear models and an information-theoretic model-selection approach. Life form, nitrogen fixation and spore formation were key traits that showed the strongest relationships with environmental stressors. Overall, FI (farming intensity) exerted stronger effects on algal communities than hydrological alteration. The large-bodied, non-attached, filamentous algae that dominated under high farming intensities have limited dispersal abilities but may cope with unfavourable conditions through the formation of spores. Antagonistic interactions between FI and flow reduction were observed for some trait variables, whereas no interactions occurred for nitrogen concentration and fine sediment. Our conceptual framework was well supported by tests of ten specific hypotheses predicting effects of resource supply and disturbance on algal traits. Our study also shows that investigating a fairly comprehensive set of traits can help shed light on the drivers of algal community composition in situations where multiple stressors are operating. Further, to understand non-linear and non-additive effects of such drivers, communities need to be studied along multiple gradients of natural variation or anthropogenic stressors.

Microbiomes in light of traits: A phylogenetic perspective

A focus on the phenotypic characteristics of microorganisms-their traits-offers a path for interpreting the growing amount of microbiome data. We review key aspects of microbial traits, as well as approaches used to assay their phylogenetic distribution. Recent studies reveal that microbial traits are differentially conserved across the tree of life and appear to be conserved in a hierarchical fashion, possibly linked to their biochemical complexity. These results suggest a predictive framework whereby the genetic (or taxonomic) resolution of microbiome variation among samples provides information about the traits under selection. The organizational parallels seen among human and free-living microbiomes seem to support this idea. Developments in this framework may offer predictions not only for how microbial composition responds to changing environmental conditions, but also for how these changes may alter the health or functioning in human, engineered, and environmental systems.

Phytoplankton traits predict ecosystem function in a global set of lakes

Predicting ecosystem function from environmental conditions is a central goal of ecosystem ecology. However, many traditional ecosystem models are tailored for specific regions or ecosystem types, requiring several regional models to predict the same function. Alternatively, trait-based approaches have been effectively used to predict community structure in both terrestrial and aquatic environments and ecosystem function in a limited number of terrestrial examples. Here, we test the efficacy of a trait-based model in predicting gross primary production (GPP) in lake ecosystems. We incorporated data from >1000 United States lakes along with laboratory-generated phytoplankton trait data to build a trait-based model of GPP and then validated the model with GPP observations from a separate set of globally distributed lakes. The trait-based model performed as well as or outperformed two ecosystem models both spatially and temporally, demonstrating the efficacy of trait-based models for predicting ecosystem function over a range of environmental conditions.

Common Ancestry Is a Poor Predictor of Competitive Traits in Freshwater Green Algae

Phytoplankton species traits have been used to successfully predict the outcome of competition, but these traits are notoriously laborious to measure. If these traits display a phylogenetic signal, phylogenetic distance (PD) can be used as a proxy for trait variation. We provide the first investigation of the degree of phylogenetic signal in traits related to competition in freshwater green phytoplankton. We measured 17 traits related to competition and tested whether they displayed a phylogenetic signal across a molecular phylogeny of 59 species of green algae. We also assessed the fit of five models of trait evolution to trait variation across the phylogeny. There was no significant phylogenetic signal for 13 out of 17 ecological traits. For 7 traits, a non-phylogenetic model provided the best fit. For another 7 traits, a phylogenetic model was selected, but parameter values indicated that trait variation evolved recently, diminishing the importance of common ancestry. This study suggests that traits related to competition in freshwater green algae are not generally well-predicted by patterns of common ancestry. We discuss the mechanisms by which the link between phylogenetic distance and phenotypic differentiation may be broken.

Microbial resource utilization traits and trade-offs: implications for community structure, functioning, and biogeochemical impacts at present and in the future

Trait-based approaches provide a mechanistic framework to understand and predict the structure and functioning of microbial communities. Resource utilization traits and trade-offs are among key microbial traits that describe population dynamics and competition among microbes. Several important trade-offs have been identified for prokaryotic and eukaryotic microbial taxa that define contrasting ecological strategies and contribute to species coexistence and diversity. The shape, dimensionality, and hierarchy of trade-offs may determine coexistence patterns and need to be better characterized. Laboratory measured resource utilization traits can be used to explain temporal and spatial structure and dynamics of natural microbial communities and predict biogeochemical impacts. Global environmental change can alter microbial community composition through altering resource utilization by different microbes and, consequently, may modify biogeochemical impacts of microbes.

Seeing the forest for the genes: using metagenomics to infer the aggregated traits of microbial communities

Most environments harbor large numbers of microbial taxa with ecologies that remain poorly described and characterizing the functional capabilities of whole communities remains a key challenge in microbial ecology. Shotgun metagenomic analyses are increasingly recognized as a powerful tool to understand community-level attributes. However, much of this data is under-utilized due, in part, to a lack of conceptual strategies for linking the metagenomic data to the most relevant community-level characteristics. Microbial ecologists could benefit by borrowing the concept of community-aggregated traits (CATs) from plant ecologists to glean more insight from the ever-increasing amount of metagenomic data being generated. CATs can be used to quantify the mean and variance of functional traits found in a given community. A CAT-based strategy will often yield far more useful information for predicting the functional attributes of diverse microbial communities and changes in those attributes than the more commonly used analytical strategies. A more careful consideration of what CATs to measure and how they can be quantified from metagenomic data, will help build a more integrated understanding of complex microbial communities.