When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems

Rapid evolution allows coexistence of highly divergent lineages within the same niche

Marine microbial communities are extremely complex and diverse. The number of locally coexisting species often vastly exceeds the number of identifiable niches, and taxonomic composition often appears decoupled from local environmental conditions. This is contrary to the view that environmental conditions should select for a few locally well-adapted species. Here we use an individual-based eco-evolutionary model to show that virtually unlimited taxonomic diversity can be supported in highly evolving assemblages, even in the absence of niche separation. With a steady stream of heritable changes to phenotype, competitive exclusion may be weakened, allowing sustained coexistence of nearly neutral phenotypes with highly divergent lineages. This behaviour is robust even to abrupt environmental perturbations that might be expected to cause strong selection pressure and an associated loss of diversity. We, therefore, suggest that rapid evolution and individual-level variability are key drivers of species coexistence and maintenance of microbial biodiversity.

Exploring evolution of maximum growth rates in plankton

Evolution has direct and indirect consequences on species-species interactions and the environment. However, Earth systems models describing planktonic activity invariably fail to explicitly consider organism evolution. Here we simulate the evolution of the single most important physiological characteristic of any organism as described in models-its maximum growth rate (μ_m). Using a low-computational-cost approach, we incorporate the evolution of μ_m for each of the plankton components in a simple Nutrient-Phytoplankton-Zooplankton -style model such that the fitness advantages and disadvantages in possessing a high μ_m evolve to become balanced. The model allows an exploration of parameter ranges leading to stresses, which drive the evolution of μ_m. In applications of the method we show that simulations of climate change give very different projections when the evolution of μ_m is considered. Thus, production may decline as evolution reshapes growth and trophic dynamics. Additionally, predictions of extinction of species may be overstated in simulations lacking evolution as the ability to evolve under changing environmental conditions supports evolutionary rescue. The model explains why organisms evolved for mature ecosystems (e.g. temperate summer, reliant on local nutrient recycling or mixotrophy), express lower maximum growth rates than do organisms evolved for immature ecosystems (e.g. temperate spring, high resource availability).

Reducing the arbitrary: fuzzy detection of microbial ecotones and ecosystems - focus on the pelagic environment

BACKGROUND

One of the central objectives of microbial ecology is to study the distribution of microbial communities and their association with their environments. Biogeographical studies have partitioned the oceans into provinces and regions, but the identification of their boundaries remains challenging, hindering our ability to study transition zones (i.e. ecotones) and microbial ecosystem heterogeneity. Fuzzy clustering is a promising method to do so, as it creates overlapping sets of clusters. The outputs of these analyses thus appear both structured (into clusters) and gradual (due to the overlaps), which aligns with the inherent continuity of the pelagic environment, and solves the issue of defining ecosystem boundaries.

RESULTS

We show the suitability of applying fuzzy clustering to address the patchiness of microbial ecosystems, integrating environmental (Sea Surface Temperature, Salinity) and bacterioplankton data (Operational Taxonomic Units (OTUs) based on 16S rRNA gene) collected during six cruises over 1.5 years from the subtropical frontal zone off New Zealand. The technique was able to precisely identify ecological heterogeneity, distinguishing both the patches and the transitions between them. In particular we show that the subtropical front is a distinct, albeit transient, microbial ecosystem. Each water mass harboured a specific microbial community, and the characteristics of their ecotones matched the characteristics of the environmental transitions, highlighting that environmental mixing lead to community mixing. Further explorations into the OTU community compositions revealed that, although only a small proportion of the OTUs explained community variance, their associations with given water mass were consistent through time.

CONCLUSION

We demonstrate recurrent associations between microbial communities and dynamic oceanic features. Fuzzy clusters can be applied to any ecosystem (terrestrial, human, marine, etc) to solve uncertainties regarding the position of microbial ecological boundaries and to refine the relation between the distribution of microorganisms and their environment.

Considering the Role of Adaptive Evolution in Models of the Ocean and Climate System

Numerical models have been highly successful in simulating global carbon and nutrient cycles in today's ocean, together with observed spatial and temporal patterns of chlorophyll and plankton biomass at the surface. With this success has come some confidence in projecting the century-scale response to continuing anthropogenic warming. There is also increasing interest in using such models to understand the role of plankton ecosystems in past oceans. However, today's marine environment is the product of billions of years of continual evolution-a process that continues today. In this paper, we address the questions of whether an assumption of species invariance is sufficient, and if not, under what circumstances current model projections might break down. To do this, we first identify the key timescales and questions asked of models. We then review how current marine ecosystem models work and what alternative approaches are available to account for evolution. We argue that for timescales of climate change overlapping with evolutionary timescales, accounting for evolution may to lead to very different projected outcomes regarding the timescales of ecosystem response and associated global biogeochemical cycling. This is particularly the case for past extinction events but may also be true in the future, depending on the eventual degree of anthropogenic disruption. The discipline of building new numerical models that incorporate evolution is also hugely beneficial in itself, as it forces us to question what we know about adaptive evolution, irrespective of its quantitative role in any specific event or environmental changes.

Geometrical envelopes: Extending graphical contemporary niche theory to communities and eco-evolutionary dynamics

Contemporary niche theory is a powerful structuring framework in theoretical ecology. First developed in the context of resource competition, it has been extended to encompass other types of regulating factors such as shared predators, parasites or inhibitors. A central component of contemporary niche theory is a graphical approach popularized by Tilman that illustrates the different outcomes of competition along environmental gradients, like coexistence and competitive exclusion. These food web modules have been used to address species sorting in community ecology, as well as adaptation and coexistence on eco-evolutionary time scales in adaptive dynamics. Yet, the associated graphical approach has been underused so far in the evolutionary context. In this paper, we provide a rigorous approach to extend this graphical method to a continuum of interacting strategies, using the geometrical concept of the envelope. Not only does this approach provide community and eco-evolutionary bifurcation diagrams along environmental gradients, it also sheds light on the similarities and differences between those two perspectives. Adaptive dynamics naturally merges with this ecological framework, with a close correspondence between the classification of singular strategies and the geometrical properties of the envelope. Finally, this approach provides an integrative tool to study adaptation between levels of organization, from the individual to the ecosystem.

Estimating planktonic diversity through spatial dominance patterns in a model ocean

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale.