- The model:
- Calculating dissimilarity among pond communities to use as the multivariate response
- Determining multivariate predictors summarizing the local environment
- Identifying spatial vectors to use as structural connectivity predictors
- Optimizing resistance surfaces and using them as functional connectivity predictors
- Community differentiation attributable purely to the local environment versus structural connectivity versus functional connectivity
- Species diversity and connectivity:
- Classifying ponds based on local environmental characteristics and comparing differences in community composition and blue and green connectivity among pond classes
- Determining the relationship between connectivity and the biological diversity across pond communities, and how this relationship may vary based on pond class
To run the R scripts:
source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/Input.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/LandCover_250mRadius.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/Connectivity.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/dbRDA.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/Diversity_Differentiation.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/Connectivity_Biodiversity.R"); source("https://raw.githubusercontent.com/chazhyseni/pond_conn/master/R/Maps.R")
To run Circuitscape:
cd ~
git clone https://github.com/chazhyseni/pond_conn
cd pond_conn
Then, in Julia:
using Pkg
Pkg.add("Circuitscape")
compute("Circuitscape/Blue/Input/Blue_CS_parameters.ini")
compute("Circuitscape/BlueGreen/Input/BlueGreen_CS_parameters.ini")
compute("Circuitscape/Green/Input/Green_CS_parameters.ini")