Although the core of the BoutScout project focuses on developing multi-sensor dataloggers for automated nest monitoring, a significant complementary outcome emerged from our fieldwork: the creation of the Nestling Growth App, a Python-based platform for modeling and visualizing nestling growth patterns. @jcguerra10 , @bmgarrido , and @Mantolehmann 

This tool was born from our need to analyze the biometric data collected during manual nest checks — measurements of body mass, wing, and tarsus length taken alongside sensor deployment in active nests. We realized that many researchers, especially in tropical regions, face barriers when trying to analyze and compare nestling growth due to the lack of accessible tools.

The Nestling Growth App solves this by offering a user-friendly interface to fit and compare five biological growth models (Logistic, Gompertz, Richards, von Bertalanffy, and EVF). It supports multilingual use (English, Spanish, Portuguese), handles real-world field data, and outputs high-quality plots and tables — with no coding required.

🖥️ How to install it on your computer:

1. Make sure Python is installed (we recommend version 3.9 or later).
2. Open your terminal (Command Prompt or Anaconda Prompt).

3. Run the command:

   pip install nestling-growth-app

4. Once installed, launch the app by typing:

   nestling-app

   

This will open the interface in your default web browser and you're ready to analyze!

Now available on PyPI and GitHub, the app is a powerful open-source tool for anyone studying avian growth. We’re proud that this development, rooted in practical field challenges, has become part of BoutScout’s broader impact on avian conservation science.