MetaCommunityMetrics.jl

A collection of metrics for analyzing ecological community datasets across space and time 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 metrics, which have been previously implemented in R and proven valuable for analysis of community composition.

However, they usually come with high computational costs, especially for large spatiotemporal 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 ecological community 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 index 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")

Accessing 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

• Beta Diversity
• DNCI
• Niche Overlap Index
• Occupied Patches Proportion
• Variability Metrics
• Hypervolume

Comparison between Julia and R implementations

• Validation Results
• Benchmarking Results

Accessing the Sample Data for exploring the functions

This package uses 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 provided 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:

• Downloading the rodent data
• Data Wrangling

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 omitted

Acknowledgment

We are grateful to the authors of the R packages and scripts that this package builds upon, and to everyone who has tried out MetaCommunityMetrics.jl and provided feedback — especially members of the Entomological Data Science Lab at Cornell University.

Several functions are translated or adapted from existing R code; full attribution details are also provided in the documentation for each function.

R Packages

Papers

Please refer to these sources for full details on the original implementations and licenses.

License

This project is licensed under the terms of the GNU General Public License v3.0. See the LICENSE file for more details.

Contributing

We welcome contributions from the community, especially those familiar with porting R packages to Julia! To contribute:

1. Fork the repository
2. Create a new branch
3. Make well commented commits
4. Submit a pull request

Please follow Julia community coding standards and ensure all tests pass.

Help Wanted

The following features are planned for future releases and are great opportunities for open-source contributors. See our open issues for details and to get started.

• beta_diversity(): add support for the remaining four coefficient families beyond the currently implemented Podani-Jaccard approach: Sørensen-based (Podani), Baselga-Sørensen, Baselga-Jaccard, and the Podani & Schmera (2011) relativized nestedness index. Reference implementation: adespatial::beta.div.comp.

• MVNH_dissimilarity(): add support for additional niche overlap metrics beyond Bhattacharyya distance: Pianka, MacArthur-Levins, and Morisita indices; also accept pre-computed covariance matrices and means as direct input. Reference implementation: MVNH::MVNH_dissimilarity.

• DNCI_multigroup(): add built-in visualizations (SIMPER/PerSIMPER/E-index plots), a symmetrize option for uneven group sizes, support for abundance data, and parallel computing. Reference implementation: DNCImper::DNCI_multigroup.

Reporting Issues and Needing Support

If you encounter bugs, have feature requests, or need any support, please open an issue on our GitHub Issues page.

References

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