Among bacteria and archaea, maximum relative growth rate, cell diameter, and genome size are widely regarded as important influences on ecological strategy. Via the most extensive data compilation so far for these traits across all clades and habitats, we ask whether they are correlated and if so how. Overall, we found little correlation among them, indicating they should be considered as independent dimensions of ecological variation. Nor was correlation evident within particular habitat types. A weak nonlinearity (6% of variance) was found whereby high maximum growth rates (temperature-adjusted) tended to occur in the midrange of cell diameters. Species identified in the literature as oligotrophs or copiotrophs were clearly separated on the dimension of maximum growth rate, but not on the dimensions of genome size or cell diameter.

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

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

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

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

Body size is an important trait of any organism, including phytoplankton, because it affects physiological and morphological performance, reproduction, population growth rate and competitive interactions. Understanding how interacting top-down and bottom-up factors influence phytoplankton cell size in different aquatic environments is still a challenge. Structural equation modeling (SEM) is a comprehensive multivariate statistical tool for detecting cause-effect relationship among different variables and their hierarchical structure in complex networks (e.g. trophic interactions in ecosystems). Here, several SEM models were employed to investigate the direct and indirect interaction pathways affecting the phytoplankton size structure in 44 mostly eutrophic and hypereutrophic permanent lakes in western Turkey. Among the 15 environmental variables tested, only rotifers and Carlson's Trophic Index (TSI) had significant direct positive effect on the mean phytoplankton size and size variance, respectively. The results indicate that both bottom-up and top-down factors significantly affect phytoplankton community size structure in eutrophic and hypereutrophic lakes in warm climates. Rotifer grazing increased the abundance of large-sized phytoplankton species, such as filamentous and colonial cyanobacteria and TSI affected phytoplankton size variance, with a higher size variance in hypereutrophic lakes.

This dataset reports the size-fractionated chlorophyll a from multivariate mesocosm experiments conducted with a natural phytoplankton community from Narragansett Bay, RI. These data were assessed in Anderson et al. The Interactive Effects of Temperature and Nutrients on a Spring Phytoplankton Community (in prep). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/848948 Copyright: https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0

This dataset reports the elemental composition of phytoplankton communities from multivariate mesocosm experiments conducted with a natural phytoplankton community from Narragansett Bay, RI. These data were assessed in Anderson et al. The Interactive Effects of Temperature and Nutrients on a Spring Phytoplankton Community (in prep). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/848587 Copyright: https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0

This dataset represents microscopy cell counts from multivariate mesocosm experiments conducted with a natural phytoplankton community from Narragansett Bay, RI. These data were assessed in Anderson et al. The Interactive Effects of Temperature and Nutrients on a Spring Phytoplankton Community (in prep). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/848977 Copyright: https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0