## Functional traits

Similar to local species abundance/richness versus species pools, there seems to be filtering effects that limit the functional traits of species (trait space) in a local community. In part this was [initially proposed](@fox1993assembly) by separating species into feeding guilds, but since that time additional intricacies have been introduced by separating species by multi-dimensional functional traits.

![*An example of feeding guilds.* Source: [Brian O'Neill; YouTube](https://www.youtube.com/watch?v=mMV1zoiHnlo&t=66s)](images/clipboard-3615832052.png){fig-align="center" width="332"}

If abiotic filters were the only factor limiting local functional traits, you would expect to see traits focused around an optimum based on abiotic conditions (*left*), instead we often see traits "spread out" across a larger convex hull (*right*) similar to what we see for local species richness vs. species pools:

![Source: [Mittelbach & McGill 2019](@mittelbach2019community)](images/clipboard-1516943365.png){fig-align="center" width="431"}

![*In this real world example, functional diversity of British birds (red) is much lower than predicted (blue) indicating filtering is occurring beyond abiotic filtering.* Source: [Petchey et. al 2007](@petchey2007low)](images/clipboard-328875550.png){fig-align="center" width="344"}

Current research has revealed that conducting the types of community assembly analyses covered in this lab but focusing on functional traits instead of species identities are often more accurate for predicting community structure and are more generalizable for making conservation suggestions. Because of this, there has been a recent explosion of interest in compiling species trait data.

![*Note the consistent relationship among the functional trait leaf mass per unit area (LMA) with both mean annual temperature (MAT) and mean annual rainfall (MAR), despite very different species compositions (red dots) worldwide.* Source: [Wright et. al 2004](@wright2004worldwide)](images/clipboard-1127715636.png){fig-align="center" width="444"}

## Community Phylogenetics

All of the statements above about functional traits can be applied to phylogenetic similarity. However, although phylogenetic distance is more readily available than trait data, it is not a perfect proxy without fine-tuning. This is because the simplifications that all traits are conserved and that traits are not labile are often both incorrect.

# Lab 8 - Exercises

-   Set-up your environment

-   Find, load, and describe a dataset of functional traits or community phylogenetics (for this assignment, you can assume all traits are conserved and that traits are not labile). Note that you may need to find more than one dataset to explore each of the filters we are interested in.

-   Clean and wrangle your dataset

-   Similar to those we conducted in lab 8, analyze your data (i.e. explore dispersal, biotic, abiotic

    filters) and plot your results

-   Write a brief conclusion. Note the strengths and weaknesses of using your dataset to explore community assembly filters in the region of your dataset over using species abundance or richness.

------------------------------------------------------------------------

# References
