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Lemos-Costa, P.

Publications and source records attributed to Lemos-Costa, P..

3 recordsLinked to original sources

Robust coexistence in ecological competitive communities

Darwin already recognized that competition is fiercest among conspecifics, a principle that later made intraspecific competition central to ecological theory through concepts such as niche differentiation and limiting similarity. Beyond shaping coexistence, strong intraspecific competition can also stabilize community dynamics by ensuring that populations return to equilibrium after disturbance. Here we investigate a more fundamental question: how intraspecific competition influences the very existence of a steady state (feasibility) in large random ecological communities dominated by competition. We show that, analogous to classical results on stability, there is a critical level of intraspecific competition above which a feasible steady state is guaranteed to exist. We derive a general expression for the probability of feasibility and prove that, asymptotically (as species number grows), the transition to stability occurs before the transition to feasibility with probability one. Thus, in large competitive communities, any feasible equilibrium is automatically stable. This ordering persists even when many species in the initial pool cannot coexist and extinctions occur: the dynamics prune the community, shifting feasibility and stability thresholds but never reversing their order. These results imply that large competitive communities generically converge to a globally stable equilibrium, making sustained oscillations or chaos unlikely--consistent with experimental observations.

ecology↗

Phylogeny structures species' interactions in experimental ecological communities

The advent of molecular phylogenetics provided a new perspective on the structure and function of ecological communities. In particular, the hypothesis that traits responsible for species interactions are largely determined by shared evolutionary history has suggested the possibility of connecting the phylogeny of ecological communities to their functioning. However, statistical tests of this link have yielded mixed results. Here we propose a novel framework to test whether phylogeny influences the patterns of coexistence and abundance of species assemblages, and apply it to analyze data from large biodiversity-ecosystem functioning experiments. In our approach, phylogenetic trees are used to parameterize species interactions, which in turn determine the abundance of species in a specified assemblage. We use a maximum likelihood-based approach to score models parameterized with a given phylogenetic tree. To test whether evolutionary history structures interactions, we fit and score ensembles of randomized trees, allowing us to determine if phylogenetic information helps to predict species abundances. Moreover, we can determine the contribution of each branch of the tree to the likelihood, revealing particular clades in which interaction strengths are closely tied to phylogeny. We find strong evidence of phylogenetic signal across a range of published experiments and a variety of models. The flexibility of our framework permits incorporation of ecological information beyond phylogeny, such as functional groups or traits, and provides a principled way to test hypotheses about which factors shape the structure and function of ecological communities.

ecology↗

Modeling ecological communities when composition is manipulated experimentally

O_LIIn an experimental setting, the composition of ecological communities can be manipulated directly. Starting from a pool of n species, one can co-culture species in different combinations, spanning mono-cultures, pairs of species, and all the way up to the full pool. Here we advance methods aimed at inferring species interactions from data sets reporting the density attained by species in a variety of sub-communities formed from the same pool. C_LIO_LIFirst, we introduce a fast and robust algorithm to estimate parameters for simple statistical models describing these data, which can be combined with likelihood maximization approaches. Second, we derive from consumer-resource dynamics statistical models with few parameters, which can be applied to study systems where only a small fraction of the potential sub-communities have been observed. Third, we show how a Weighted Least Squares (WLS) framework can be used to account for the fact that species abundances often display a strong relationship between means and variances. C_LIO_LITo illustrate our approach, we analyze data sets spanning plants, bacteria, phytoplankton, as well as simulations, recovering a good fit to the data and demonstrating the ability to predict experiments out-of-sample. C_LIO_LIWe greatly extend the applicability of recently proposed methods, opening the door for the analysis of larger pools of species. C_LI

ecology↗