An experimental test of the Community Assembly by Trait Selection (CATS) model.

Robert T Strahan ,Daniel C Laughlin,Margaret M Moore

doi:10.1371/journal.pone.0206787

Abstract

The Community Assembly by Trait Selection (CATS) model of community assembly predicts species abundances along environmental gradients in relatively undisturbed vegetation. Here we ask whether this model, when calibrated with data from natural plant communities, can predict the abundances of five dominant grass species (Bouteloua gracilis, Elymus elymoides, Festuca arizonica, Muhlenbergia montana, and Poa fendleriana) in a greenhouse experiment that manipulated light and soil properties. To address this question, we used generalized additive models (GAMs) to model community-weighted mean (CWM) seed mass, mean Julian flowering date, and specific root length (SRL) as non-linear functions of two environmental variables (soil pH and pine basal area) in natural vegetation. The model-fitted CWM traits were then used as constraints in the CATS model to predict the relative abundance of the five grass species that were seeded in a mixture at equal densities into a 2×2 factorial experiment with soil parent material and light level as crossed factors. Light was the most important factor influencing seedling community composition, especially the abundances of Bouteloua gracilis and Poa fendleriana. The model-predicted relative abundances were significantly correlated with the observed relative abundances, and the model accurately predicted the dominant species in every treatment. P. fendleriana was correctly predicted to be the most abundant species in both shade treatments and the sun-basalt treatment, and B. gracilis was correctly predicted to be the most abundant species in the sun-limestone treatment. Our results provide experimental evidence that environmental filtering of the species pool occurs in the early stages of community assembly (including germination, emergence, and early growth), and that trait-based models calibrated with data from natural plant communities can be used to predict the outcome of the early stages of community assembly under experimental conditions.

Highlights

community-weighted mean (CWM) trait values were calculated from field data, which consisted of herbaceous plant communities occupying a series of 96 permanent 1 m2 quadrats located across a 700 km2 landscape surrounding Flagstaff, Arizona, USA
This study examined the generality of a trait-based model by predicting the outcome of the early phase of community assembly under experimental conditions
Environmental filtering is an important process in the early stages of community assembly, but light exhibited stronger effects on the germination, emergence, and early growth phases than soil parent material

Summary

Introduction

Trait-based models of community assembly by environmental filtering assume that species with functional trait values that confer the highest probability of survival, growth, and reproduction in a given environment will be the dominant species in that environment [1,2,3]. Trait-based model predicts species abundances under experimental conditions. We test whether the predictions of a trait-based model of community assembly calibrated in natural vegetation can accurately predict the abundances of five dominant grasses under experimental conditions. Given that species possessing these trait values will be more abundant, a CWM trait will be biased towards trait values conferring higher fitness [5] A thorough description of the CATS model can be found in Shipley et al 2006 [5]

Methods

Results

Conclusion