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It has been proposed that microbial predator and prey densities are related through sublinear power laws. We revisited previously published biomass and abundance data and fitted Power‐law Biomass Scaling Relationships (PBSRs) between marine microzooplankton predators (Z) and phytoplankton prey (P), and marine viral predators (V) and bacterial prey (B). We analysed them assuming an error structure given by Type II regression models which, in contrast to the conventional Type I regression model, accounts for errors in both the independent and the dependent variables. We found that the data support linear relationships, in contrast to the sublinear relationships reported by previous authors. The scaling exponent yields an expected value of 1 with some spread in different datasets that was well‐described with a Gaussian distribution. Our results suggest that the ratiosZ/P, andV/Bare on average invariant, in contrast to the hypothesis that they systematically decrease with increasingPand B, respectively, as previously thought.

 

The influence of viruses on nutrient cycles and energy transfer in aquatic systems is important, yet still being determined. We developed a dynamic model to capture the population dynamics of algal hosts and their viruses. The model was fitted to literature data of population dynamics during laboratory one‐step infection experiments. Model parameters that underlie population dynamics were quantified in diverse algal groups, covering 7 different algal classes, 14 different host genera, and 32 different virus genotypes. The hypothesis that trade‐offs exist between traits that underlie population dynamics was evaluated. We report a possible virus size‐dependent trade‐off between the rate at which viruses can initiate infection, and the efficiency of carbon transfer from hosts to viruses upon lysis. We hypothesize that slower rates of infection in large viruses, due to slower rates of molecular diffusion, are compensated by enhanced utilization of host resources. Our approach provides a quantitative trait‐framework for understanding and quantifying virus activity in diverse natural communities.

 

ABSTRACT The mechanisms driving cyanobacterial harmful algal blooms (HABs) like those caused by Microcystis aeruginosa remain elusive, but improved defense against viral predation has been implicated for success in eutrophic environments. Our genus-level analyses of 139,023 genomes revealed that HAB-forming cyanobacteria carry vastly more restriction modification systems per genome (RMPG) than nearly all other prokaryotic genera, suggesting that viral defense is a cornerstone of their ecological success. In contrast, picocyanobacteria that numerically dominate nutrient-poor systems have the fewest RMPG within the phylum Cyanobacteria . We used classic resource competition models to explore the hypothesis that nutrient enrichments drive ecological selection for high RMPG due to increased host-phage contact rate. These classic models, agnostic to the mechanism of defense, explain how nutrient loading can select for increased RMPG but, importantly, fail to explain the extreme accumulation of these defense systems. However, extreme accumulation of RMPG can be achieved in a novel “memory” model that accounts for a unique activity of restriction modification systems: the accidental methylation of viral DNA by the methyltransferase. The methylated virus “remembers” the RM defenses of its former host and can evade these defenses if they are present in the next host. This viral memory leads to continual RM system devaluation; RMs accumulate extensively because the benefit of each addition is diminished. Our modeling leads to the hypothesis that nutrient loading and virion methylation drive the extreme accumulation of RMPG in HAB-forming cyanobacteria. Finally, our models suggest that hosts with different RMPG values can coexist when hosts have unique sets of RM systems. IMPORTANCE Harmful algal blooms (HABs), caused by cyanobacteria like Microcystis aeruginosa , are a global threat to water quality and use across the planet. Researchers have agreed that nutrient loading is a major contributor to HAB persistence. While we may understand the environmental conditions that cause HABs, we still struggle in identifying the mechanisms that explain why these organisms have a competitive edge against other, less ecologically hazardous organisms. Our interdisciplinary approach in microbiology, mathematical population modeling, and genomics allows us to use nearly 70 years of research in restriction modification systems to show that HAB-forming cyanobacteria are exceptional in their ability to defend against viruses, and this capacity is intimately tied to nutrient loading. Our hypothesis suggests that defense against viral predation is a fundamental pillar of cyanobacterial ecological strategy and an important contributor to HAB dynamics. 

Environmentally driven variability in the elemental stoichiometry of ocean plankton plays a key role in ocean biogeochemical processes. Recent studies have identified clear regional variability in C:N:P, but less is known about the environmental regulation of diel variability in plankton elemental stoichiometry. Here, we quantified the amplitude of the diel variability in C:N of surface ocean particles (<30 μm,C:N_amp) across large latitudinal gradients in the Indian and Atlantic Oceans. We commonly observed diel oscillations in C:N and biome‐specific variability inC:N_amp. Temperature emerged as the strongest predictor ofC:N_amp, relative to the supply of nitrate. We propose thatC:N_ampis positively related to photosynthesis and respiration and thus phytoplankton growth rates. We find that independent growth rate proxies and an ecosystem model support this hypothesis. In addition, the temperature sensitivity ofC:N_amphas aQ₁₀of 1.78 corroborating studies of phytoplankton growth rates. Surface communities across the Indian Ocean transect had a very small dependency on nitrate, whereas recycled nitrogen sources were by far the most preferred and the ratio of recycled‐N:nitrate utilization increased with increasingC:N_amp. To predict future changes inC:N_amp, we combined our statistical model with data from the fifth Coupled Model Intercomparison Project for the years 1990 and 2090. The results suggest that future rising temperatures will yield increasedC:N_amp. Collectively, our results imply that rising surface ocean temperatures lead to elevated phytoplankton growth rates supported by recycled nutrients.

 

Are the oceans turning into deserts? Rising temperature, increasing surface stratification, and decreasing vertical inputs of nutrients are expected to cause an expansion of warm, nutrient deplete ecosystems. Such an expansion is predicted to negatively affect a trio of key ocean biogeochemical features: phytoplankton biomass, primary productivity, and carbon export. However, phytoplankton communities are complex adaptive systems with immense diversity that could render them at least partially resilient to global changes. This can be illustrated by the biology of theProchlorococcus“collective.” Adaptations to counter stress, use of alternative nutrient sources, and frugal resource allocation can allowProchlorococcusto buffer climate‐driven changes in nutrient availability. In contrast, cell physiology is more sensitive to temperature changes. Here, we argue that biogeochemical models need to consider the adaptive potential of diverse phytoplankton communities. However, a full understanding of phytoplankton resilience to future ocean changes is hampered by a lack of global biogeographic observations to test theories. We propose that the resilience may in fact be greater in oligotrophic waters than currently considered with implications for future predictions of phytoplankton biomass, primary productivity, and carbon export.

 

The sinking of carbon fixed via net primary production (NPP) into the ocean interior is an important part of marine biogeochemical cycles. NPP measurements follow a log‐normal probability distribution, meaning NPP variations can be simply described by two parameters despite NPP's complexity. By analyzing a global database of open ocean particle fluxes, we show that this log‐normal probability distribution propagates into the variations of near‐seafloor fluxes of particulate organic carbon (POC), calcium carbonate, and opal. Deep‐sea particle fluxes at subtropical and temperate time‐series sites follow the same log‐normal probability distribution, strongly suggesting the log‐normal description is robust and applies on multiple scales. This log‐normality implies that 29% of the highest measurements are responsible for 71% of the total near‐seafloor POC flux. We discuss possible causes for the dampening of variability from NPP to deep‐sea POC flux, and present an updated relationship predicting POC flux from mineral flux and depth.

 

Viruses and microzooplankton grazers represent major sources of mortality for marine phytoplankton and bacteria, redirecting the flow of organic material throughout the world's oceans. Here, we investigate the use of nonlinear population models of interactions between phytoplankton, viruses and grazers as a means to quantitatively constrain the flow of carbon through marine microbial ecosystems. We augment population models with a synthesis of laboratory‐based estimates of prey, predator and viral life history traits that constrain transfer efficiencies. We then apply the model framework to estimate loss rates in the California Current Ecosystem (CCE). With our empirically parameterized model, we estimate that, of the total losses mediated by viruses and microzooplankton grazing at the focal CCE site, 22 ± 3%, 46 ± 27%, 3 ± 2% and 29 ± 20% were directed to grazers, sloppy feeding (as well as excretion and respiration), viruses and viral lysate respectively. We identify opportunities to leverage ecosystem models and conventional mortality assays to further constrain the quantitative rates of critical ecosystem processes.