Marine bacteria exhibit a bipolar distribution

Abstract

The microbial cosmopolitan dispersion hypothesis often invoked to explain distribution patterns driven by high connectivity of oceanographic water masses and widespread dispersal ability has never been rigorously tested. By using a global marine bacterial dataset and iterative matrix randomization simulation, we show that marine bacteria exhibit a significantly greater dispersal limitation than predicted by our null model using the "everything is everywhere" tenet with no dispersal limitation scenario. Specifically, marine bacteria displayed bipolar distributions (i.e., species occurring exclusively at both poles and nowhere else) significantly less often than in the null model. Furthermore, we observed fewer taxa present in both hemispheres but more taxa present only in a single hemisphere than expected under the null model. Each of these trends diverged further from the null expectation as the compared habitats became more geographically distant but more environmentally similar. Our metaanalysis supported a latitudinal gradient in bacterial diversity with higher richness at lower latitudes, but decreased richness toward the poles. Bacteria in the tropics also demonstrated narrower latitudinal ranges at lower latitudes and relatively larger ranges in higher latitudes, conforming to the controversial macroecological pattern of the "Rapoport rule." Collectively, our findings suggest that bacteria follow biogeographic patterns more typical of macroscopic organisms, and that dispersal limitation, not just environmental selection, likely plays an important role. Distributions of microbes that deliver critical ecosystem services, particularly those in polar regions, may be vulnerable to the same impacts that environmental stressors, climate warming, and degradation in habitat quality are having on biodiversity in animal and plant species.ICoMM | MIRADA-LTERS | microbial biogeography | macroecology

Advection shapes Southern Ocean microbial assemblages independent of distance and environment effects

“…To obtain a better understanding of the advection effect, it would be useful to determine whether specific taxonomic or physiological groups are more amenable to dispersal by advection; for example, through the formation of dormant spores 7,13 , copiotroph resting states (for example, Photobacterium angustum 28 ) or through the inherent stress resistance states of some oligotrophs (for example, Sphingopyxis alaskensis 28 ). As it is possible that an unmeasured environmental variable (for example, iron concentration; microenvironmental factors owing to particle attachment) also correlates with both advection and community composition, future studies should address this.…”

“…Hence, it would be expected that locations that are closely connected by advection would have more similar compositions than those that are not, even when the environment effect is accounted for. Indeed, advection is often invoked to explain observations of microbial diversity or abundance, which do not seem attributable to environmental selection (for example, refs [13][14][15][16]. The exchange of very small volumes of water between marine microbial mesocosms has been found to greatly reduce their b-diversity (in this case, compositional differences between communities from different mesocosms) even under consistent environmental conditions 17 .…”

Global diversity and biogeography of deep-sea pelagic prokaryotes

“…However, our estimate of the total prokaryotic richness in the bathypelagic ocean estimated at 3600 OTUs is consistent with previous estimates that found a total richness of 10 846 OTUs with half of them corresponding to singletons (Zinger et al, 2011). This represents a small fraction (~3% and 5.5%) of the total oceanic plankton bacterial richness found by recent surveys with comparable methodologies: a previous study combining 509 benthic and pelagic marine samples ranging from 0 to 5400 m depth found a total richness of~120 000 OTUs (Zinger et al, 2011), whereas a total richness of 65 500 OTUs was detected in a different study using data from 277 epipelagic samples (243 of which were also included in the previous one) from the Arctic, Atlantic, Pacific and Southern Oceans (Sul et al, 2013). This would suggest that only a small fraction of all oceanic microbes are found in the deep ocean.…”

Biogeographic patterns in ocean microbes emerge in a neutral agent-based model

“…Such a model can be used as a null hypothesis, where deviation from observed patterns can help quantify the effect of the omitted factors (e.g., selection) (6,15,16). A neutral model can also be used to directly predict biogeographic patterns resulting from neutral processes.…”