Models of functional ecospace diversification within life-habit frameworks (functional-trait spaces) are increasingly used across community ecology, functional ecology, and paleoecology. In general, these models can be represented by four basic processes, three that have driven causes and one that occurs through a passive process. The driven models include redundancy (caused by forms of functional canalization), partitioning (specialization), and expansion (divergent novelty), but they also share important dynamical similarities with the passive neutral model. In this second of two companion articles, Monte Carlo simulations of these models are used to illustrate their basic statistical dynamics across a range of data structures and implementations. Ecospace frameworks with greater numbers of characters (functional traits) and ordered (multistate) character types provide more distinct dynamics and greater ability to distinguish the models, but the general dynamics tend to be congruent across all implementations. Classification-tree methods are proposed as a powerful means to select among multiple candidate models when using multivariate data sets. Well-preserved Late Ordovician (type Cincinnatian) samples from the Kope and Waynesville formations are used to illustrate how these models can be inferred in empirical applications. Initial simulations overestimate the ecological disparity of actual assemblages, confirming that actual life habits are highly constrained. Modifications incorporating more realistic assumptions (such as weighting potential life habits according to actual frequencies and adding a parameter controlling the strength of each model's rules) provide better correspondence to actual assemblages. Samples from both formations are best fit by partitioning (and to lesser extent redundancy) models, consistent with a role for local processes. When aggregated as an entire formation, the Kope Formation pool remains best fit by the partitioning model, whereas the entire Waynesville pool is better fit by the redundancy model, implying greater beta diversity within this unit. The ‘ecospace’ package is provided to implement the simulations and to calculate their dynamics using the R statistical language.
You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither BioOne nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the BioOne website.
Vol. 42 • No. 2