Nematode-associated microbial taxa do not correlate with host phylogeny, geographic region or feeding morphology in marine sediment habitats.

Studies of host-associated microbes are critical for advancing our understanding of ecology and evolution across diverse taxa and ecosystems. Nematode worms are ubiquitous across most habitats on earth, yet little is known about host-associated microbial assemblages within the phylum. Free-living nematodes are globally abundant and diverse in marine sediments, with species exhibiting distinct buccal cavity (mouth) morphologies that are thought to play an important role in feeding ecology and life history strategies. Here, we investigated patterns in marine nematode microbiomes, by characterizing host-associated microbial taxa in 281 worms isolated from a range of habitat types (deep-sea, shallow water, methane seeps, Lophelia coral mounds, kelp holdfasts) across three distinct geographic regions (Arctic, Southern California and Gulf of Mexico). Microbiome profiles were generated from single worms spanning 33 distinct morphological genera, using a two-gene metabarcoding approach to amplify the V4 region of the 16S ribosomal RNA (rRNA) gene targeting bacteria/archaea and the V1-V2 region of the 18S rRNA gene targeting microbial eukaryotes. Contrary to our expectations, nematode microbiome profiles demonstrated no distinct patterns either globally (across depths and ocean basins) or locally (within site); prokaryotic and eukaryotic microbial assemblages did not correlate with nematode feeding morphology, host phylogeny or morphological identity, ocean region or marine habitat type. However, fine-scale analysis of nematode microbiomes revealed a variety of novel ecological interactions, including putative parasites and symbionts, and potential associations with bacterial/archaeal taxa involved in nitrogen and methane cycling. Our results suggest that in marine habitats, free-living nematodes may utilize diverse and generalist foraging strategies that are not correlated with host genotype or feeding morphology. Furthermore, some abiotic factors such as geographic region and habitat type do not appear to play an obvious role in structuring host-microbe associations or feeding preferences.

Can the source-sink hypothesis explain macrofaunal abundance patterns in the abyss? A modelling test.

Low food availability is a major structuring force in deep-sea benthic communities, sustaining only very low densities of organisms in parts of the abyss. These low population densities may result in an Allee effect, whereby local reproductive success is inhibited, and populations are maintained by larval dispersal from bathyal slopes. This slope-abyss source-sink (SASS) hypothesis suggests that the abyssal seafloor constitutes a vast sink habitat with macrofaunal populations sustained only by an influx of larval 'refugees' from source areas on continental slopes, where higher productivity sustains greater population densities. Abyssal macrofaunal population densities would thus be directly related to larval inputs from bathyal source populations. We evaluate three predictions derived from the SASS hypothesis: (i) slope-derived larvae can be passively transported to central abyssal regions within a single larval period, (ii) projected larval export from slopes to the abyss reproduces global patterns of macrofaunal abundance and (iii) macrofaunal abundance decreases with distance from the continental slope. We find that abyssal macrofaunal populations are unlikely to be sustained solely through influx of larvae from slope sources. Rather, local reproduction probably sustains macrofaunal populations in relatively high-productivity abyssal areas, which must also be considered as potential larval source areas for more food-poor abyssal regions.

A tri-oceanic perspective: DNA barcoding reveals geographic structure and cryptic diversity in Canadian polychaetes.

BACKGROUND: Although polychaetes are one of the dominant taxa in marine communities, their distributions and taxonomic diversity are poorly understood. Recent studies have shown that many species thought to have broad distributions are actually a complex of allied species. In Canada, 12% of polychaete species are thought to occur in Atlantic, Arctic, and Pacific Oceans, but the extent of gene flow among their populations has not been tested. METHODOLOGY/PRINCIPAL FINDINGS: Sequence variation in a segment of the mitochondrial cytochrome c oxidase I (COI) gene was employed to compare morphological versus molecular diversity estimates, to examine gene flow among populations of widespread species, and to explore connectivity patterns among Canada's three oceans. Analysis of 1876 specimens, representing 333 provisional species, revealed 40 times more sequence divergence between than within species (16.5% versus 0.38%). Genetic data suggest that one quarter of previously recognized species actually include two or more divergent lineages, indicating that richness in this region is currently underestimated. Few species with a tri-oceanic distribution showed genetic cohesion. Instead, large genetic breaks occur between Pacific and Atlantic-Arctic lineages, suggesting their long-term separation. High connectivity among Arctic and Atlantic regions and low connectivity with the Pacific further supports the conclusion that Canadian polychaetes are partitioned into two distinct faunas. CONCLUSIONS/SIGNIFICANCE: Results of this study confirm that COI sequences are an effective tool for species identification in polychaetes, and suggest that DNA barcoding will aid the recognition of species overlooked by the current taxonomic system. The consistent geographic structuring within presumed widespread species suggests that historical range fragmentation during the Pleistocene ultimately increased Canadian polychaete diversity and that the coastal British Columbia fauna played a minor role in Arctic recolonization following deglaciation. This study highlights the value of DNA barcoding for providing rapid insights into species distributions and biogeographic patterns in understudied groups.

Predicting the distribution and ecological niche of unexploited snow crab (Chionoecetes opilio) populations in Alaskan waters: a first open-access ensemble model.

Populations of the snow crab (Chionoecetes opilio) are widely distributed on high-latitude continental shelves of the North Pacific and North Atlantic, and represent a valuable resource in both the United States and Canada. In US waters, snow crabs are found throughout the Arctic and sub-Arctic seas surrounding Alaska, north of the Aleutian Islands, yet commercial harvest currently focuses on the more southerly population in the Bering Sea. Population dynamics are well-monitored in exploited areas, but few data exist for populations further north where climate trends in the Arctic appear to be affecting species' distributions and community structure on multiple trophic levels. Moreover, increased shipping traffic, as well as fisheries and petroleum resource development, may add additional pressures in northern portions of the range as seasonal ice cover continues to decline. In the face of these pressures, we examined the ecological niche and population distribution of snow crabs in Alaskan waters using a GIS-based spatial modeling approach. We present the first quantitative open-access model predictions of snow-crab distribution, abundance, and biomass in the Chukchi and Beaufort Seas. Multi-variate analysis of environmental drivers of species' distribution and community structure commonly rely on multiple linear regression methods. The spatial modeling approach employed here improves upon linear regression methods in allowing for exploration of nonlinear relationships and interactions between variables. Three machine-learning algorithms were used to evaluate relationships between snow-crab distribution and environmental parameters, including TreeNet, Random Forests, and MARS. An ensemble model was then generated by combining output from these three models to generate consensus predictions for presence-absence, abundance, and biomass of snow crabs. Each algorithm identified a suite of variables most important in predicting snow-crab distribution, including nutrient and chlorophyll-a concentrations in overlying waters, temperature, salinity, and annual sea-ice cover; this information may be used to develop and test hypotheses regarding the ecology of this species. This is the first such quantitative model for snow crabs, and all GIS-data layers compiled for this project are freely available from the authors, upon request, for public use and improvement.