We use metacommunity simulations to understand how local and regional community assembly dynamics influence the regional biodiversity patterns that we observe in the McMurdo Dry Valleys ecosystem. A metacommunity refers to a network of communities in an ecosystem that are connected to one another by the dispersal of biota among sites. For example, ponds in the McMurdo Dry Valleys share common diatom species that are likely dispersed among neighboring ponds by wind.
We have written a metacommunity model for the R programming language (MCSim, Sokol et al. 2015) to explore what biodiversity patterns look like for different metacommunity connectivity scenarios. This gives us the opportunity to model alternative hypotheses and explore how biodiversity metrics, such as beta-diversity, can be expected to respond to changing ecosystem connectivity for different sets of assumptions about the underlying dynamics that could potentially control biodiversity in the Dry Valleys.
Field Sample Analysis and Model Approach
MCSim for the R statistical language. Latest version available on Github at https://github.com/sokole/MCSim (version used for this work is https://github.com/sokole/MCSim/releases/tag/v0.4.1.9001)
Data Input Files
The input files used for the Metacommunities simulations, all the empirical data used are included in a Zip file (see above). Four csv files contain information on the communities densities. These include the following taxa (coded): Ataylor, Ccymat, Claevis, Cmolest, Fpellic, Holigot, Hantzsc, Habundan, Hamphiox, Hmuelle, Helongat, Humidoph, Hhyperaus, Haustral, Hparall, Lutico, Laustro, Ldolia, Lgauss, Llaeta, Levolut Lmuticop LmLevk, LmWest, Lpermutic, Lvermeu Matomu Mpermit Mvar1, Mueller Mmerid Msupra, Mperaus, Nseibig, Nshack Ngrega Nlineo, Ncommu, Nwesto, Ppapil, Slatis, Lunknown, Cheam1Input locations are in two files, including UTM coordinates as well as Lat/Lon coordinates. The lake index serves as linkage for chemical, physical and taxa data.
Data Output Files
Output files for example metacommunity simulations. Simulation results include species counts for each timestep from two different simulation scenarios. Example R code necessary to run these simulation scenarios is included
R-code. Best refer to github link, but here an example for Diatoms is included in the Output ZIP file. Eric provided you with a nice tutorial on how to use the MCSim simulation, follow it at: http://rpubs.com/sokole/159425
Modeling code is managed in github, and the data output snapshots are stored here.