Viruses, microbes, and host macroorganisms form ecological units called holobionts. Here, a combination of metagenomic sequencing, metabolomic profiling, and epifluorescence microscopy was used to investigate how the different components of the holobiont including bacteria, viruses, and their associated metabolites mediate ecological interactions between corals and turf algae. The data demonstrate that there was a microbial assemblage unique to the coral-turf algae interface displaying higher microbial abundances and larger microbial cells. This was consistent with previous studies showing that turf algae exudates feed interface and coral-associated microbial communities, often at the detriment of the coral. Further supporting this hypothesis, when the metabolites were assigned a nominal oxidation state of carbon (NOSC), we found that the turf algal metabolites were significantly more reduced (i.e., have higher potential energy) compared to the corals and interfaces. The algae feeding hypothesis was further supported when the ecological outcomes of interactions (e.g., whether coral was winning or losing) were considered. For example, coral holobionts losing the competition with turf algae had higher Bacteroidetes-to-Firmicutes ratios and an elevated abundance of genes involved in bacterial growth and division. These changes were similar to trends observed in the obese human gut microbiome, where overfeeding of the microbiome creates a dysbiosis detrimental to the long-term health of the metazoan host. Together these results show that there are specific biogeochemical changes at coral–turf algal interfaces that predict the competitive outcomes between holobionts and are consistent with algal exudates feeding coral-associated microbes.

Human impacts are causing ecosystem phase shifts from coral- to algal-dominated reef systems on a global scale. As these ecosystems undergo transition, there is an increased incidence of coral-macroalgal interactions. Mounting evidence indicates that the outcome of these interaction events is, in part, governed by microbially mediated dynamics. The allocation of available energy through different trophic levels, including the microbial food web, determines the outcome of these interactions and ultimately shapes the benthic community structure. However, little is known about the underlying thermodynamic mechanisms involved in these trophic energy transfers. This study utilizes a novel combination of methods including calorimetry, flow cytometry, and optical oxygen measurements, to provide a bioenergetic analysis of coral-macroalgal interactions in a controlled aquarium setting. We demonstrate that the energetic demands of microbial communities at the coral-algal interaction interface are higher than in the communities associated with either of the macroorganisms alone. This was evident through higher microbial power output (energy use per unit time) and lower oxygen concentrations at interaction zones compared to areas distal from the interface. Increases in microbial power output and lower oxygen concentrations were significantly correlated with the ratio of heterotrophic to autotrophic microbes but not the total microbial abundance. These results suggest that coral-algal interfaces harbor higher proportions of heterotrophic microbes that are optimizing maximal power output, as opposed to yield. This yield to power shift offers a possible thermodynamic mechanism underlying the transition from coral- to algal-dominated reef ecosystems currently being observed worldwide. As changes in the power output of an ecosystem are a significant indicator of the current state of the system, this analysis provides a novel and insightful means to quantify microbial impacts on reef health.

Here, I discuss entropy and its use as a tool in fields of biology such as bioenergetics, ecology, and evolutionary biology. Statistical entropy concepts including Shannon’s diversity, configurational entropy, and informational entropy are discussed in connection to their use in describing the diversity, heterogeneity, and spatial patterning of biological systems. The use of entropy as a measure of biological complexity is also discussed, and I explore the extension of thermodynamic entropy principles to open, nonequilibrium systems operating in finite time. I conclude with suggestions for use of caliber, a metric similar to entropy but for time-dependent trajectories rather than static distributions, and propose the complementary notion of path information.

The microbialization of coral reefs predicts that microbial oxygen consumption will cause reef deoxygenation. Here we tested this hypothesis by analyzing reef microbial and primary producer oxygen metabolisms. Metagenomic data and in vitro incubations of bacteria with primary producer exudates showed that fleshy algae stimulate incomplete carbon oxidation metabolisms in heterotrophic bacteria. These metabolisms lead to increased cell sizes and abundances, resulting in bacteria consuming 10 times more oxygen than in coral incubations. Experiments probing the dissolved and gaseous oxygen with primary producers and bacteria together indicated the loss of oxygen through ebullition caused by heterogenous nucleation on algae surfaces. A model incorporating experimental production and loss rates predicted that microbes and ebullition can cause the loss of up to 67% of gross benthic oxygen production. This study indicates that microbial respiration and ebullition are increasingly relevant to reef deoxygenation as reefs become dominated by fleshy algae.

All organisms host a diversity of associated viruses, bacteria, and protists, collectively defined as the holobiont. While scientific advancements have enhanced the understanding of the functional roles played by various components of the holobiont, there is a growing need to integrate multiple types of molecular data into spatially and temporally resolved frameworks. To that end, we mapped 16S and 18S rDNA metabarcoding, metatranscriptomics, and metabolomic data onto three-dimensional reconstructions of coral colonies to examine microbial diversity, microbial gene expression, and biochemistry on two colonies of the ecologically important, reef-building coral,Orbicella faveolataand their competitors (i.e., adjacent organisms interacting with the corals: fleshy algae, turf algae, hydrozoans, and other corals). Overall, no statistically significant spatial patterns were observed among the samples for any of the data types; instead, strong signatures of the macroorganismal hosts (e.g., coral, algae, hydrozoa) were detected, in the microbiome, the transcriptome, and the metabolome. The 16S rDNA analysis demonstrated higher abundance of Firmicutes in the coral microbiome than in its competitors. A single bacterial amplicon sequence variant from the genusClostridiumwas found exclusively in allO. faveolatasamples. In contrast to microbial taxa, a portion of the functionally annotated bacterial RNA transcripts (6.86%) and metabolites (1.95%) were ubiquitous in all coral and competitor samples. Machine learning analysis of microbial transcripts revealed elevated T7-like cyanophage-encoded photosystem II transcripts inO. faveolatasamples, while sequences involved in bacterial cell division were elevated in turf algal and interface samples. Similar analysis of metabolites revealed that bacterial-produced antimicrobial and antifungal compounds were highly enriched in coral samples. This study provides insight into the spatial and biological patterning of the coral microbiome, transcriptome, and metabolome.

Applications of entropy principles to evolution and ecology are of tantamount importance given the central role spatiotemporal structuring plays in both evolution and ecological succession. We obtain here a qualitative interpretation of the role of entropy in evolving ecological systems. Our interpretation is supported by mathematical arguments using simulation data generated by the Tangled Nature Model (TNM), a stochastic model of evolving ecologies. We define two types of configurational entropy and study their empirical time dependence obtained from the data. Both entropy measures increase logarithmically with time, while the entropy per individual decreases in time, in parallel with the growth of emergent structures visible from other aspects of the simulation. We discuss the biological relevance of these entropies to describe niche space and functional space of ecosystems, as well as their use in characterizing the number of taxonomic configurations compatible with different niche partitioning and functionality. The TNM serves as an illustrative example of how to calculate and interpret these entropies, which are, however, also relevant to real ecosystems, where they can be used to calculate the number of functional and taxonomic configurations that an ecosystem can realize.