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In the context of maintenance of biodiversity and ecological functions, microbial ecologists face the challenge of linking individual level variability in functional traits to larger scale ecosystem processes. Phytoplankton cell size and shape are key traits under selection by environmental filters and species interactions. Spatial differences in resource availability shape species diversity according to their use efficiency. Niche partitioning promotes plankton diversity. Here, we explore how size and shape enter the diversity game. How does taxonomic and morpho-functional community structure vary at different spatial scales? What are the potential drivers shaping the structure of phytoplankton communities? We explore these questions by looking at the individual level variability in taxonomic and morphological traits in a biogeographical snapshot of natural phytoplankton communities in coastal ecosystems around the globe. We found that taxonomic variability is mainly concentrated at local and regional levels, whereas shape and size variability are mainly concentrated at a local level, despite the environmental heterogeneity of ecosystems. Species diversity was more variable than trait diversity from local to global spatial scales. We suggest that structural organization of phytoplankton communities in coastal ecosystems may follow a hierarchical pattern of trait organization, where a different combination of multiple functional traits may represent effective strategies and promote success under given environmental conditions as a resolution of Hutchinson's paradox.

Quantifying how environmental factors control the growth of phytoplankton communities is essential for building a mechanistic understanding of global biogeochemical cycles and aquatic food web dynamics. The strong effects of temperature on population growth rate have inspired two frameworksthe Eppley curve and the metabolic theory of ecologythat produce different quantitative relationships and employ distinct statistical approaches. Reconciling these relationships is necessary to ensure the accuracy of ecosystem models. In this paper, we develop ways to compare these frameworks, overcoming their methodological differences. Then, analyzing an extensive dataset (> 4200 growth rate measurements), we find that increases in population growth rate with temperature are consistent with metabolic theory, and weaker than previous estimates of the Eppley curve. A 10 degrees C temperature increase will increase growth rates by a factor of 1.53, rather than 1.88 as in previous studies of the Eppley curve. Size and functional group membership are also critical. Population growth rates decrease with size, but much less strongly that metabolic theory predicts. The growth rates of different functional groups scale similarly with temperature, but some groups grow faster than others, independent of temperature. Our results reconcile the analytical methods of the Eppley curve and metabolic theory, demonstrate that metabolic theory's temperature-scaling predictions are more accurate, and provide new insights into the factors controlling phytoplankton growth. To avoid over-estimating the effects of temperature on primary productivity, the parameterization of ecosystem models should be revised.

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

Lake Baikal, Siberia, is the most biodiverse freshwater lake on Earth. However, despite decades of painstaking limnological research on Baikal, broad spatial data on nutrient (nitrogen (N), phosphorus (P), silica (Si)) concentrations and temperature are sparse, as is our understanding of the bottom-up factors that limit phytoplankton in the lake. Earlier studies have suggested both N and P as limiting nutrients in Baikal, but the evidence, mostly based on elemental ratios, is limited and somewhat conflicting. We present experimental evidence that N and P co-limit phytoplankton productivity in some areas of Baikal during summer, along with the results of a comprehensive spatial survey of surface temperature, nutrients and chlorophyll a (Chl a) in Lake Baikal that support the experimental finding of colimitation. Surface water incubations from two trophically contrasting locations revealed co-limitation by N and P, as well as a positive effect of temperature (fluorescence after 5 d was similar to 10% higher at 15 degrees C than at 10 degrees C). In a linear model of the survey data (26 sampling locations), N, P, and their interaction (N x P) were all significant predictors of Chl a concentration, indicating that either N or P (or both) may limit summer phytoplankton, depending on location. In contrast to the incubation experiments, temperature was not a significant predictor of Chl a concentration across the 26 sites we sampled. Lake Baikal is undergoing rapid warming and increased nutrient loading, which may boost phytoplankton productivity in the lake; however, the magnitude of this response will depend on ratios of soluble N and P inputs.

Rising lake temperatures and changing nutrient inputs are believed to favour the spread of a toxic invasive cyanobacterium, Cylindrospermopsis raciborskii (Woloszynska) Seenayya and Subba Raju, in temperate lakes. However, most evidence for these hypotheses is observational or based on physiological measurements in monocultures. We lack clear experimental evidence relating temperature and nutrients to the competitive success of C. raciborskii. To address this, we performed a 2 x 2 factorial laboratory experiment to study the dynamics of mixed phytoplankton communities subjected to different levels of temperature and phosphorus over 51 days. We allowed C. raciborskii to compete with ten different species from major taxonomic groups (diatoms, green algae, cryptophytes, and cyanobacteria) typical of temperate lakes, under low and high summer temperatures (25 and 30 A degrees C) at two levels of phosphorus supply (1 and 25 A mu mol L-1). Cylindrospermopsis raciborskii dominated the communities and strongly decreased diversity under low-phosphorus conditions, consistent with the hypothesis that it is a good phosphorus competitor. In contrast, it remained extremely rare in high-phosphorus conditions, where fast-growing green algae dominated. Surprisingly, temperature played a negligible role in influencing community composition, suggesting that changes in summer temperature may not be important in determining C. raciborskii's spread.

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity. StoichFun_SEM_RichnessStoichFun_SEM_EvennessReadme_StoichFun Copyright: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication

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

The human gut microbiome develops over early childhood and aids in food digestion and immunomodulation, but the mechanisms driving its development remain elusive. Here we use data curated from literature and online repositories to examine trait-based patterns of gut microbiome succession in 56 infants over their first three years of life. We also develop a new phylogeny-based approach of inferring trait values that can extend readily to other microbial systems and questions. Trait-based patterns suggest that infant gut succession begins with a functionally variable cohort of taxa, adept at proliferating rapidly within hosts, which gradually matures into a more functionally uniform cohort of taxa adapted to thrive in the anoxic gut and disperse between anoxic patches as oxygen-tolerant spores. Trait-based composition stabilizes after the first year, while taxonomic turnover continues unabated, suggesting functional redundancy in the traits examined. Trait-based approaches powerfully complement taxonomy-based approaches to understanding the mechanisms of microbial community assembly and succession.