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      Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean

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          Abstract

          Photosynthetic picoeukaryotesx in the genus Micromonas show among the widest latitudinal distributions on Earth, experiencing large thermal gradients from poles to tropics. Micromonas comprises at least four different species often found in sympatry. While such ubiquity might suggest a wide thermal niche, the temperature response of the different strains is still unexplored, leaving many questions as for their ecological success over such diverse ecosystems. Using combined experiments and theory, we characterize the thermal response of eleven Micromonas strains belonging to four species. We demonstrate that the variety of specific responses to temperature in the Micromonas genus makes this environmental factor an ideal marker to describe its global distribution and diversity. We then propose a diversity model for the genus Micromonas, which proves to be representative of the whole phytoplankton diversity. This prominent primary producer is therefore a sentinel organism of phytoplankton diversity at the global scale. We use the diversity within Micromonas to anticipate the potential impact of global warming on oceanic phytoplankton. We develop a dynamic, adaptive model and run forecast simulations, exploring a range of adaptation time scales, to probe the likely responses to climate change. Results stress how biodiversity erosion depends on the ability of organisms to adapt rapidly to temperature increase.

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          Swarm: robust and fast clustering method for amplicon-based studies

          Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.
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            Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental gradients.

            Prochlorococcus is the numerically dominant phytoplankter in the oligotrophic oceans, accounting for up to half of the photosynthetic biomass and production in some regions. Here, we describe how the abundance of six known ecotypes, which have small subunit ribosomal RNA sequences that differ by less than 3%, changed along local and basin-wide environmental gradients in the Atlantic Ocean. Temperature was significantly correlated with shifts in ecotype abundance, and laboratory experiments confirmed different temperature optima and tolerance ranges for cultured strains. Light, nutrients, and competitor abundances also appeared to play a role in shaping different distributions.
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              A global pattern of thermal adaptation in marine phytoplankton.

              Rising ocean temperatures will alter the productivity and composition of marine phytoplankton communities, thereby affecting global biogeochemical cycles. Predicting the effects of future ocean warming on biogeochemical cycles depends critically on understanding how existing global temperature variation affects phytoplankton. Here we show that variation in phytoplankton temperature optima over 150 degrees of latitude is well explained by a gradient in mean ocean temperature. An eco-evolutionary model predicts a similar relationship, suggesting that this pattern is the result of evolutionary adaptation. Using mechanistic species distribution models, we find that rising temperatures this century will cause poleward shifts in species' thermal niches and a sharp decline in tropical phytoplankton diversity in the absence of an evolutionary response.
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                Author and article information

                Journal
                The ISME Journal
                ISME J
                Springer Nature America, Inc
                1751-7362
                1751-7370
                August 16 2018
                Article
                10.1038/s41396-018-0248-0
                b279bb39-dc2e-4ce7-8ae5-eabcfd95e5cd
                © 2018

                http://www.springer.com/tdm

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