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It is an interactive Python tool for modelling and visualizing nestling growth using deterministic models. Designed for ornithologists and ecologists, it supports weight and tarsus/wing analysis, AIC/BIC-based model selection, and bilingual interfaces (EN/ES). The app is built with Dash and runs via a command-line launcher (nestling-app
). It’s part of the BoutScout project funded by WILDLABS, developed by Jorge Lizarazo, Juan C. Guerra, and Gustavo Londoño to support accessible growth analysis of nestling birds. Available via PyPI and open source for community use.
Cost range
- Free
Where to buy
Website
External Resources
Conservation Challenges
WILDLABS Content
Pinned
Related
Specifications
Interactive modelling tool for nestling development studies
Interactive modelling tool for nestling development studies
The Nestling Growth App is an open-source, user-friendly web application for visualizing and modelling the growth of bird nestlings. Designed for ornithologists and field ecologists, it fits biological growth models (Logistic, Gompertz, Richards, Von Bertalanffy, EVF) to field data on weight, wing, or tarsus length. Users can upload their own CSV files, compare model fits using AIC/BIC, and export publication-ready plots. The app supports English, Spanish, and Portuguese. It is part of the BoutScout project, funded by WILDLABS.
Installation with Anaconda (recommended)
To get started:
- Install Anaconda (if you haven’t already): https://www.anaconda.com/download
- Open Anaconda Prompt and run:
Create and open an enviroment for the API
conda create -n nestlings python=3.9 -y
conda activate nestlings
then open your envieroment. You'll need to do so each time you want to open the app. But only install the package once as follows:
pip install nestling-growth-app
You only need to do this once. Your virtual environment will be named nestlings
, but you can use any name you prefer.
▶️ Running the App
Once installed, just open your envieroment and launch the app by typing in your enviroment:
nestling-app
Your default browser will open automatically, or you can visit:
👉 http://localhost:8050
Take into account:
Its focus on deterministic models means it may not meet the needs of users looking for more complex statistical approaches like mixed-effects models. Also, being a local web app, it requires users to install dependencies and run it from the command line, which may be a barrier for those unfamiliar with Anaconda prompt at once. And yet it is just three-line code.