Dispersal-competition tradeoff in microbiomes in the quest for land colonization

Ancestor microbes started colonizing inland habitats approximately 2.7 to 3.5 billion years ago. With some exceptions, the key physiological adaptations of microbiomes associated with marine-to-land transitions have remained elusive. This is essentially caused by the lack of suitable systems that depict changes in microbiomes across sufficiently large time scales. Here, we investigate the adaptive routes taken by microbiomes along a contemporary gradient of land formation. Using functional trait-based metagenomics, we show that a switch from a microbial 'dispersal' to a 'competition' response modus best characterizes the microbial trait changes during this eco-evolutionary trajectory. The 'dispersal' modus prevails in microbiomes at the boundary sites between land and sea. It encompasses traits conferring cell chemosensory and motile behaviors, thus allowing the local microbes to exploit short-lived nutritional patches in high-diffusion microhabitats. A systematic transition towards the 'competition' modus occurs progressively as the soil matures, which is likely due to forces of viscosity or strain that favor traits for competition and chemical defense. Concomitantly, progressive increases in the abundances of genes encoding antibiotic resistance and complex organic substrate degradation were found. Our findings constitute a novel perspective on the ecology and evolution of microbiome traits, tracking back one of the most seminal transitions in the evolutionary history of life

A new modeling approach estimates the relative importance of different community assembly processes

The relative importance of niche-based (e.g., competitive or stress-based) and stochastic (e.g., random dispersal) processes in structuring ecological communities is frequently analyzed by studying trait distributions of co-occurring species. While filtering processes, such as the exclusion of stress-intolerant species from particular habitats, increase the trait similarity between co-occurring species, other processes, such as resource competition, can limit the similarity of co-occurring species. Comparing the observed trait distribution patterns in communities to null expectations from randomized communities (e.g., a draw of the same observed richness from the regional pool) therefore gives a first indication of the dominant process driving community assembly. However, such comparisons do not inform us about the relative contribution of these different processes in shaping community compositions in case of their joint operation (a likely scenario). Using an Approximate Bayesian Computation approach, we develop a new method that allows inference of the relative importance of dispersal, filtering, and limiting similarity processes for the assembly of observed communities with known species and trait composition. We applied this approach to a tree community data set, collected across 20 plots along strong rainfall and fire gradients in a South African savanna. Based on comparisons with simulations, we find that our new approach is powerful in identifying which community assembly scenario has the highest probability to generate the observed trait distribution patterns, while traditional null model comparisons perform poorly in detecting signs of limiting similarity. For the studied savanna tree communities, our analysis yields that dispersal processes are most important in shaping the functional trait distribution patterns. Furthermore, our models indicate that filtering processes were relatively most important in areas with high fire frequencies, while limiting similarity processes were relatively most important in areas with low fire frequency and high rainfall. We conclude that our new method is a promising improvement on current approaches to estimate the relative importance of community assembly processes across different species groups, ecosystems, and biomes. Future model modifications (e.g., the inclusion of individual-based processes) could provide further steps in uncovering the underlying assembly processes behind observed community patterns

Competition, predation, and migration: individual choice patterns of Serengeti migrants captured by hierarchical models

Large-herbivore migrations occur across gradients of food quality or food abundance that are generally determined by underlying geographic patterns in rainfall, elevation, or latitude, in turn causing variation in the degree of interspecific competition and the exposure to predators. However, the role of top-down effects of predation as opposed to the bottom-up effects of competition for resources in shaping migrations is not well understood. We studied 30 GPS radio-collared wildebeest and zebra migrating seasonally in the Serengeti-Mara ecosystem to ask how predation and food availability differentially affect the individual movement patterns of these co-migrating species. A hierarchical analysis of movement trajectories (directions and distances) in relation to grass biomass, high-quality food patches, and predation risk show that wildebeest tend to move in response to food quality, with little attention to predation risk. In contrast, individual zebra movements reflect a balance between the risk of predation and the access to high-quality food of sufficient biomass. Our analysis shows how two migratory species move in response to different attributes of the same landscape. Counterintuitively and in contrast to most other animal movement studies, we find that both species move farther each day when resources are locally abundant than when they are scarce. During the wet season when the quality of grazing is at its peak, both wildebeest and zebra move the greatest distances and do not settle in localized areas to graze for extended periods. We propose that this punctuated movement in highquality patches is explained by density dependency, whereby large groups of competing individuals (up to 1.65 million grazers) rapidly deplete the localized grazing opportunities. These findings capture the roles of predation and competition in shaping animal migrations, which are often claimed but rarely measured

Rocky outcrops form islands of high and unique tree biodiversity within an ocean of grass in Serengeti National Park

African savannahs are characterised by a high plant diversity, partly resulting from a high turnover in community compositions across space. However, it is poorly understood what is driving this spatial turnover in plant communities. Here, we investigate to which extent the presence of rocky outcrops (also called kopjes) explains the community composition of trees in an African savannah, and how we can understand the responses of tree species to rocky outcrops by their functional traits. Along a precipitation gradient, we visited 24 sites in Serengeti National Park (Tanzania). At each site, we characterised tree communities, as well as their functional traits, in both a kopje and an adjacent open savannah plot (matrix plot). We found that kopjes harboured elevated tree abundances and species richness. Their dominant trees were more often evergreen, had a higher specific leaf area, a lower leaf nitrogen content and a lower spine density, than dominant trees in the savannah matrix. Differences in tree communities between kopjes and savannah matrix plots were generally the largest at sites with low precipitation. Our results indicate that kopjes are strong drivers of tree biodiversity, possibly due to locally increased soil moisture and low fire frequencies. The uniqueness of kopje tree communities may have important implications for higher trophic levels and ecosystem functioning.</p