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  • … is a tool to explore the scale dependence of ecological data, inspired by Palmer & White.

  • … helps reveal whether and how observational data is affected by spatial scale—grain and extent.

  • … shows whether properties of a researched community (e.g., turnover, dissimilarity) vary when sampled at different spatial scales.

  • … provides results as raw CSV files, with optional graphical outputs. However, plots are not the main outcome and users are encouraged to use their favourite plotting tool.

  • … can explore the influence of spatial scale on virtually any phenomenon, since it necessitates only a column containing object identity (e.g., species, element, category), and optionally a quantitative value (e.g., units, individuals, count, concentration). However, to keep the documentation concise, we will focus on the analysis of a community of species.


  • … is not a statistical testing tool. Most outputs are descriptive, not inferential. This is a limitation of spatially point-based studies as sampling units are not independent. Moreover, data present in one observational scale contribute to data of higher scales, making inferential statistics biased.

  • … does not separate the effect of spatial scale from other potential drivers of community structure. It indicates whether spatial scale matters but does not rule out alternative explanations.

Installation

Python >= 3.12 is required to run seal. Python can be installed from the official source.

When Python is installed, run the following commands in the respective command line:

Linux (bash)

python -m venv ./venv
./venv/bin/activate
pip install seal-tool
seal --help

Windows (Powershell)

python -m venv ./venv
./venv/Scripts/Activate.ps1
pip install seal-tool
seal --help

For more detailed guide and additional ways to obtain seal see Installation.

Usage

First, ensure that the virtual environment seal is installed in is activated, which is not necessarily immediately after installation. (venv) should be displayed before the prompt to run seal. To activate the virtual environment and run seal run the following commands in the respective command line:

Linux:

source ./venv/bin/activate
seal --help

Windows PowerShell:

./venv/Scripts/activate.ps1
seal --help

General workflow

The general workflow is as follows:

seal preprocess --dataset ./datasets/my-data.csv --output ./datasets/my-data-fix.csv
seal analyse --taskfile ./tasks/my-task.toml
seal plot --taskfile ./tasks/my-task.toml

The first command, seal preprocess, is supplemental. It performs a couple of basic checks to reduce likelihood of incorrect data. E.g., multiple consecutive spaces skewing the results, invalid quadrat coordinates, or missing values.

Complete list of checks can be viewed upon calling seal preprocess --help.

The second command, seal analyse performs the actual analysis and accepts only one argument, --taskfile. Documentation on how to configure seal using a taskfile is available in the example taskfile or in the online documentation.

The last command, seal plot is also supplemental. Plots provided directly by seal can be useful for initial evaluation of the results, but are not (and can not be) optimized for all types of data. The preferred way is to use own post-processing or presentation solution e.g., loading the resulting CSV into R and examining it that way.

Development

See CONTRIBUTING.rst.

References

See bibliography.

Licenses

The source code—including the tests and documentation—is licensed under GPLv3.

./datasets/data-bmd-sl.csv is licensed under CC-BY-SA-4.0.

Acknowledgements

Initial seal protype was funded as part of Influence of sample grain and extent on coral reef fish richness, MUNI/IGA/1076/2021.

Metadata

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