Abstract
Predicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long-standing problem focus either on the role of the environment, using trait-based filtering approaches, or on quantifying biotic interactions with process-based community dynamics models. We introduce a novel approach that uses functional traits to parameterize a process-based model. By combining the two approaches we make use of the extensive literature on traits and community filtering as a convenient means of reducing the parameterization requirements of a complex population dynamics model whilst retaining the power to capture the processes underlying community assembly. Using arable weed communities as a case study, we demonstrate that this approach results in predictions that show realistic distributions of traits and that trait selection predicted by our simulations is consistent with in-field observations. We demonstrate that trait-based filtering approaches can be combined with process-based models to derive the emergent distribution of traits. While initially developed to predict the impact of crop management on functional shifts in weed communities, our approach has the potential to be applied to other annual plant communities if the generality of relationships between traits and model parameters can be confirmed.
Highlights
In our subsequent analyses we only considered the community of 15 annuals to align with the scope of our model and excluded crop volunteers as their population dynamics are driven by repeated reintroduction
Predicting the relative abundance of species along environmental gradients or following changes in management practices is a fundamental goal in community ecology
Our approach, which links trait-based environmental filtering with a process-based community model, allows both the divergent and convergent selection pressures of environmental filters and biotic interactions to be considered in combination
Summary
Within this ecosystem service framework, it is more important to predict the impact of change on the functioning of the emergent biological community than on taxonomic composition (Fig. 1 A; Dıaz et al, 2007a) Meeting this challenge requires a unified approach that combines the theories of 1) habitat filtering and niche differentiation, 2) biotic interactions and competitive exclusion, and 3) stochastic demographic events (neutral theory). These processes, together with historical and evolutionary factors (which determine the regional species pool) all play a role in determining the local ecological community in a given environment (D’Amen et al, 2017). Trait-based filtering approaches that identify the abiotic and biotic filters acting on regionally available pools of species and determine those with favourable combinations of traits that can persist in a given habitat (Keddy, 1992) have been applied across several taxa
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