MetaCommunityMetrics.jl
A collection of tools and utilities for analyzing metacommunities in Julia.
Welcome to the documentation for MetaCommunityMetrics. Here you can find guides and reference material on how to use the functions.
An Overview
This package is a comprehensive toolkit designed to characterize the spatiotemporal structure and dynamics of a metacommunity—a network of communities linked by the dispersal of multiple, interacting species, each with unique niche breadths. It includes functions to calculate a range of specific metrics, which have been previously implemented in R and proven valuable for metacommunity analysis.
However, they usually come with high computational costs, especially for large species community datasets. To address this issue, MetaCommunityMetrics.jl was developed in Julia, a programming language known for its efficiency in handling computationally intensive tasks. This implementation significantly improves the efficiency of calculating these metrics, making it a powerful tool for metacommunity analysis.
These metrics include:
- Beta diversity decompositions in space/time: total diversity, species replacement (turnover), and richness differences for both presence-absence and abundance data
- Dispersal-niche continuum index to evaluate the degree to which communities are influenced by dispersal processes and niche breadth
- Niche overlap indices to determine the extent of niche sharing among species within the metacommunity
- The proportion of sites occupied by each species
- The variability of community composition across different spatial and temporal scales
- Niche hypervolume measurements (individual species, average, and between-species dissimilarities)
Getting Started
Installation
To install MetaCommunityMetrics, use the following command:
using Pkg
Pkg.add("MetaCommunityMetrics")Acessing Help File
For all the functions in this package, detailed instructions and examples can be accessed here or by switching to help mode in the Julia REPL. To switch to help mode in the Julia REPL, user can press ? at an empty julia> prompt , then type a keyword (e.g. the name of the function) to retrieve the corresponding help file.
Function Documentation
Comparison between Julia and R implementations
Accessing the Sample Data for exploring the functions
This package used a subset of rodent data that is available in the Portal Project: a long-term study of a Chihuahuan desert ecosystem (Ernest et al. 2018) as the sample data. The rodent abundance data were selected from 2010 to 2023. Abundance data were collected monthly across 24 sites, and 21 species were recorded in total. There are 117 sampling events in total. Most sampling occurred monthly, though some months during the selected period were not sampled. Additionally, we simulated spatial coordinates, temperature, and precipitation data for all sampling sites, as these are required by some functions in our package.
Before using any functions from this package, we need to remove species that were absent and sites that were empty during the entire selected period, as this can occur when subsetting data. For computational convenience, we converted sampling dates to integers and stored them as Sampling_date_order. The sample data provide by our package has been already filtered based on these two conditions. The scripts to download and wrangle the original data can be found here:
To assess the sample data, use the following command:
using MetaCommunityMetrics
load_sample_data()Example
julia> using MetaCommunityMetrics
julia> load_sample_data()
53352×12 DataFrame
Row │ Year Month Day Sampling_date_order plot Species Abundance Presence Latitude Longitude standardized_temperature standardized_precipitation
│ Int64 Int64 Int64 Int64 Int64 String3 Int64 Int64 Float64 Float64 Float64 Float64
───────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ 2010 1 16 1 1 BA 0 0 35.0 -110.0 0.829467 -1.4024
2 │ 2010 1 16 1 2 BA 0 0 35.0 -109.5 -1.12294 -0.0519895
3 │ 2010 1 16 1 4 BA 0 0 35.0 -108.5 -0.409808 -0.803663
4 │ 2010 1 16 1 8 BA 0 0 35.5 -109.5 -1.35913 -0.646369
5 │ 2010 1 16 1 9 BA 0 0 35.5 -109.0 0.0822 1.09485
⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
53348 │ 2023 3 21 117 9 SH 0 0 35.5 -109.0 -0.571565 -0.836345
53349 │ 2023 3 21 117 10 SH 0 0 35.5 -108.5 -2.33729 -0.398522
53350 │ 2023 3 21 117 12 SH 1 1 35.5 -107.5 0.547169 1.03257
53351 │ 2023 3 21 117 16 SH 0 0 36.0 -108.5 -0.815015 0.95971
53352 │ 2023 3 21 117 23 SH 0 0 36.5 -108.0 0.48949 -1.59416
53342 rows omittedReferences
Ernest, S. M., Yenni, G. M., Allington, G., Bledsoe, E. K., Christensen, E. M., Diaz, R. M., ... & Valone, T. J. (2018). The Portal Project: a long-term study of a Chihuahuan desert ecosystem. BioRxiv, 332783. https://doi.org/10.1101/332783