Animal MoveLab

Overview

Animal MoveLab is a local-first Shiny/Golem platform designed for animal movement ecology analysis. It provides a robust and reproducible environment for scientists to import, process, visualize, and analyze animal tracking data.

The application is built incrementally, following a detailed project roadmap, to ensure that each feature is modular and well-defined.

Current Features

The application currently supports the foundational steps of a typical movement analysis workflow:

• Project Setup & Metadata:

  • Define project-level metadata (Project Name, Researcher, Species).
  • Save metadata to a project.yml file for provenance and reproducibility.
  • Create standardized folder structures for analysis work packages (ANALYSES/WPn, OUTPUT/WPn).

• Data Import & Processing:

  • Import raw animal track data from CSV files.
  • Specify the Coordinate Reference System (CRS) of the source data via its EPSG code.
  • Define a target analysis CRS to standardize all project data.
  • The application automatically transforms the data to the target CRS.

• Data Persistence:

  • The processed, CRS-corrected spatial data is automatically saved as a cleaned_tracks.gpkg file in the project's GPS/ directory. This GeoPackage file serves as the canonical, cleaned data source for all subsequent analyses.

• Data Loading & Visualization:

  • Load the cleaned GeoPackage data back into the application at any time.
  • Visualize the animal movement track with an interactive plot.
  • Dynamically select the columns to be used for the X and Y axes.
  • The plot automatically displays the CRS of the data, providing clear visual feedback.
  • View the raw data in a searchable, sortable table.

• Environmental Data Integration:

  • Import environmental data as GeoTIFF raster layers (e.g., DEM, land cover).
  • Reproject environmental layers to the common project analysis CRS.
  • Extract covariate values from multiple raster layers at each GPS location.

• Core Space-Use Analysis:

  • Calculate classic home range estimators: Minimum Convex Polygon (MCP) and Kernel Density Estimation (KDE).
  • Calculate modern, statistically robust home ranges using Autocorrelated Kernel Density Estimation (AKDE) via the ctmm package.
  • View and compare area estimates for all calculated home ranges in a summary table.
  • Visualize and compare all calculated home range polygons on a single map, overlaid on the movement track.
  • Export any calculated home range polygon as a Shapefile for use in GIS software.

• Habitat Use & Selection:

  • Extract environmental covariate data for both used and available points.
  • Fit Resource Selection Function (RSF) models to analyze habitat selection.
  • Generate prediction maps of relative habitat suitability.
  • Fit Step-Selection Function (SSF) models to analyze fine-scale habitat selection in relation to movement.

Quick Start Guide

1. Launch the Application.
2. Set Project Metadata: In the "Project Management" panel, enter your project's name, researcher, and species, then click "Save Metadata".
3. Import Data:
   • In the "Data Import" panel, click "Choose CSV File" to select your raw data file. The CSV must contain columns named x and y for the coordinates.
   • Enter the "Source EPSG Code" for your raw data (e.g., 4326 for WGS84).
   • Enter the desired "Target Analysis EPSG Code" for your project.
   • Click "Import and Process Data".
4. View Data: The movement track plot and data table will automatically update with the imported and transformed data. Note the CRS displayed in the plot's caption.
5. Create Analysis Folders: In the "Project Management" panel, enter a number and click "Create WP Folders" to create standardized directories for storing analysis outputs.
6. Reload Data: In future sessions, you can click "Load Cleaned GPS Data" to load the processed cleaned_tracks.gpkg file directly without needing to re-import the raw CSV.
7. Import Environmental Data: In the sidebar, use the "Import Environmental Layer" section to upload GeoTIFF files for your study area.
8. Extract Covariates: Navigate to the "Habitat Use" tab. Select the desired raster layers and click "Extract Covariate Data" to append the environmental data to your tracking data.
9. Analyze Space-Use: Navigate to the "Space-Use Analysis" tab. Click the buttons to calculate MCP, KDE, and/or AKDE. View the results in the table and map, and export the polygons using the download button.
10. Analyze Habitat Use: Navigate to the "Habitat Use" tab to run RSF or SSF analyses and generate prediction maps.

Future Work

This application is under active development. Future enhancements may include advanced movement analysis, reporting, and user experience improvements.