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