A predictive model of community assembly that incorporates intraspecific trait variation.
Community assembly involves two antagonistic processes that select functional traits in opposite directions. Environmental filtering tends to increase the functional similarity of species within communities leading to trait convergence, whereas competition tends to limit the functional similarity of species within communities leading to trait divergence. Here, we introduce a new hierarchical Bayesian model that incorporates intraspecific trait variation into a predictive framework to unify classic coexistence theory and evolutionary biology with recent trait-based approaches. Model predictions exhibited a significant positive correlation (r = 0.66) with observed relative abundances along a 10 °C gradient in mean annual temperature. The model predicted the correct dominant species in half of the plots, and accurately reproduced species' temperature optimums. The framework is generalizable to any ecosystem as it can accommodate any species pool, any set of functional traits and multiple environmental gradients, and it eliminates some of the criticisms associated with recent trait-based community assembly models.
Department of Biological Sciences, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand.
Daniel C
DC
Laughlin
Department of Statistics, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand.
Chaitanya
C
Joshi
Department of Systems Ecology, VU University Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, the Netherlands.
Peter M
PM
van Bodegom
School of Forestry, Northern Arizona University, PO Box 15018, Flagstaff, Arizona 86011.
Zachary A
ZA
Bastow
School of Forestry, Northern Arizona University, PO Box 15018, Flagstaff, Arizona 86011.
Peter Z
PZ
Fulé
D001499:Bayes Theorem; D005075:Biological Evolution; D017753:Ecosystem; D004777:Environment; D005544:Forecasting; D014644:Genetic Variation; D008962:Models, Theoretical; D013696:Temperature