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 meta-analysis 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.

Fig. 1.

Sampling locations of 277 marine epipelagic bacterial communities from the Arctic, Atlantic, Pacific, and Southern oceans spanning latitudes 72.4°N to 75.6°S. Samples include ones from the International Census of Marine Microbes and Palmer Station in Antarctica as part of the Microbial Inventory Research Across Diverse Aquatic Long Term Ecological Research Sites project.

Fig. 2.

Nonrandom global biogeographical patterns of marine epipelagic bacteria. (A) A schematic illustration of the bipolar taxon distribution, where taxa occur only above the subtropics on both sides of the equator. Table (Right) compares observed bipolar-distributed taxa vs. expected ones. (B) A schematic illustration of a paired-taxon distribution. The numbers of observed, expected, and the ratio of observed-to-expected paired taxa are shown in the graph (Right). (C) A schematic illustration of a hemisphere-asymmetrical taxon distribution, whereby taxa occur only above a boundary latitude in a selected hemisphere. The numbers of observed, expected, and the ratio of observed-to-expected hemisphere-asymmetrical taxa are shown in the graph (Right). All expected numbers of taxa and P values were obtained from null-simulation (i.e., random-distribution) based matrix randomization processes with 1,000 iterations.

Fig. 3.

A latitudinal gradient in marine epipelagic bacterial diversity. We calculated bacterial richness by using parametric methods implemented in the CatchAll program (44). Pearson correlation r values were between natural log-transformed estimated richness values and absolute latitudes. A similar correlation was obtained with richness estimation with normalized datasets (subsampling to minimum numbers of reads). Our correlation values between latitude and estimated richness were also similar to those from previous amplified ribosomal intergenic spacer analysis results (23) with 100 data points at 57 locations (Pearson r = −0.422).

Fig. 4.

Limited bacterial latitudinal ranges by taxonomic group. Relationship between bacterial latitudinal range sizes and latitude to test conformation to the Rapoport rule. Each point represents a median latitudinal range for each sample with taxa of a given taxonomy (n = numbers of taxa used in the calculation; “slope” indicates slope of linear regression).

Fig. 5.

Limited bacterial temperature ranges by taxonomic group. Relationship between bacterial temperature range sizes and temperature to see if broader mean temperature range sizes were measured in colder locations than in moderate or warmer locations. Each point represents the median temperature range for each dataset with taxa of a given taxonomy (n = numbers of taxa used in the calculation; “slope” indicates slope of linear regression).