Non-random correlation of species dynamics in tropical tree communities

International audienceThe importance of environmental stochasticity for tropical tree dynamics has been recently stressed by several studies. This has spurred the development of a 'time-averaged neutral model' of community dynamics by Kalyuzhny and colleagues that extends the neutral model by incorporating environmental stochasticity. We here show that this framework can be used to assess the presence of non-random correlations between species dynamics. Indeed, the time-averaged neutral model makes the simplifying assumption that species responses to environmental variation are uncorrelated. We therefore propose to use this model as a null hypothesis against which observed community dynamics can be compared. This study makes five contributions. First, we describe a novel time-averaged neutral model of community dynamics that is close to, but more flexible than the one previously proposed by Kalyuzhny and colleagues. Second, we develop an inference method based on approximate Bayesian computation (ABC) and demonstrate the identifiability of the model parameters from community time series data. Third, we develop a test of the significance of environmental stochasticity, and a method to quantify its contribution to population variance. Fourth, we develop a test of non-random correlation between species dynamics. Fifth, we apply these developments to three datasets of tropical tree dynamics. We evidence both a strong contribution of environmental stochasticity to population variance in the three datasets, and a non-random correlation of species dynamics in one of them. We finally discuss the implications of these results for the modelling of tropical tree community dynamics

Predicting stochastic community dynamics in grasslands under the assumption of competitive symmetry

International audienceCommunity dynamics is influenced by multiple ecological processes such as environmental spatiotemporal variation, competition between individuals and demographic stochasticity. Quantifying the respective influence of these various processes and making predictions on community dynamics require the use of a dynamical framework encompassing these various components. We here demonstrate how to adapt the framework of stochastic community dynamics to the peculiarities of herbaceous communities, by using a short temporal resolution adapted to the time scale of competition between herbaceous plants, and by taking into account the seasonal drops in plant aerial biomass following winter, harvesting or consumption by herbivores. We develop a hybrid inference method for this novel modelling framework that both uses numerical simulations and likelihood computations. Applying this methodology to empirical data from the Jena biodiversity experiment, we find that environmental stochasticity has a larger effect on community dynamics than demographic stochasticity, and that both effects are generally smaller than observation errors at the plot scale. We further evidence that plant intrinsic growth rates and carrying capacities are moderately predictable from plant vegetative height, specific leaf area and leaf dry matter content. We do not find any trade-off between demographical components, since species with larger intrinsic growth rates tend to also have lower demographic and environmental variances. Finally, we find that our model is able to make relatively good predictions of multi-specific community dynamics based on the assumption of competitive symmetr

Le rôle des dynamiques transitoires dans les changements ontogénétiques du root-shoot ratio

International audienceSimple models of herbaceous plant growth based on optimal partitioning theory predict, at steady state, an isometric relationship between shoot and root biomass during plant ontogeny: i.e. a constant root-shoot ratio. This prediction has received mixed empirical support, suggesting either that optimal partitioning is too coarse an assumption to model plant biomass allocation, or that additional processes need to be modelled to account for empirical findings within the optimal partitioning framework. Here we use simulations to test two potential explanations for observed non-isometric relationships, namely root senescence and transient growth dynamics. We build a simple plant growth model based on optimal partitioning theory combined with empirically measured plant functional traits. We assess its ability to reproduce various experimental plant growth patterns, namely relative growth rate, root weight ratio and root nitrogen content. We then test whether this realistically parameterized minimal model can reproduce empirically observed non-isometric relationships during plant ontogeny, and whether additional model ingredients may produce non-isometric trajectories. We finally compare our model predictions regarding the transient dynamics of allometric relationships with experimental findings.We find that our simple model based on optimal partitioning theory is able to accurately reproduce overall plant growth patterns, but fails at explaining non-isometric growth trajectories. Among the additional model ingredients tested, only transient dynamics produces non-isometric growth trajectories. The role of transient dynamics in the shape of root-shoot relationships is further supported by our re-analysis of a plant growth experiment. Our model with the inclusion of transient dynamics enables to reconcile theoretical predictions based on optimal partitioning with empirically measured ontogenetic root-shoot allometries