ERL Evidence for Resilient Livestock: The ERA Livestock Data Ecosystem

Repository Overview

This repository is part of the Evidence for Resilient Agriculture (ERA) data ecosystem, focusing on livestock data. It demonstrates ERA’s capacity to integrate and analyze diverse datasets on livestock management practices, feed types, and productivity outcomes. The repository supports research on agricultural resilience, helping identify sustainable practices to enhance productivity, environmental sustainability, and resilience under diverse contexts.

Explore the rendered HTML files for detailed documentation:

• Guide to Livestock Data Analysis in ERA Dataset

• ERL Feed Data Analysis

• Update of 2024-2025 Livestock Extraction

• Diet items for emission calculator

• Use of Ai for Extraction

• Diet Ingredient Classification

- Data for feed intake estimations

Key Features

• Data Integration: Merges datasets on feed practices, weight gain, and livestock outcomes.
• Interactive Analysis: Includes Shiny apps for exploring livestock data distributions with dynamic filtering.
• Metadata Exploration: Connects outcomes with metadata for contextual insights.

Repository Contents

1. Guide to Livestock Data Analysis in ERA Dataset

   • Provides a roadmap for leveraging ERA livestock datasets.
   • Includes practical steps for data cleaning, visualization, and advanced analysis.

2. ERL Feed Data Analysis

   • Combines feed intake, weight gain, and nutritional data for livestock analysis.
   • Evaluates relationships between feed types (e.g., tree fodder) and animal productivity.
   • Highlights synergies and trade-offs among practices.

3. Update of 2024-2025 Livestock Extraction

   • Subsets and processes livestock management data to focus on specific practices and outcomes.
   • Harmonizes units for cross-study comparability.
   • Links observations to metadata for an integrated view.

Background

The Evidence for Resilient Agriculture (ERA) initiative is a comprehensive ecosystem of modular projects designed to synthesize evidence supporting sustainable agricultural development. ERA is built on a shared data management system and a controlled vocabulary, facilitating consistent and scalable analysis across diverse geographies and contexts.

This repository is part of Evidence for Resilient Livestock (ERL), a subset of ERA that focuses specifically on livestock management practices. ERL takes a deep dive into the livestock components of ERA, particularly experimental data on animal feeding practices. By leveraging the ERA data model, ERL provides tools and analyses to explore how different feed types and practices impact livestock productivity, resilience, and sustainability. This repository gives users access to ERA's livestock data model and enables detailed analysis of animal feed experiments, offering insights that extend beyond the broader ERA publication.

Getting Started

1. Clone the repository: bash git clone https://github.com/ERAgriculture/ERL.git cd ERL
2. Open the Rmd files in RStudio.

About the Team

This repository is maintained by the team at the Alliance of Bioversity International and CIAT, part of the Climate Action Lever. The team specializes in synthesizing agricultural data, enabling evidence-based decision-making for resilient and sustainable farming practices.

Key Contributors:

• Todd S. Rosenstock: Lead Scientist on Climate and Agriculture. Email: t.rosenstock@cgiar.org
  
• Peter Steward: Specialist in data synthesis and climate analysis for agronomy and livestock. Email: p.steward@cgiar.org
  
• Namita Joshi: Research Specialist, coordinating data extraction and livestock data analysis. Email: n.joshi@cgiar.org
  

This project is licensed under the GPL-3.0 License.

Acknowledgment

This work is funded by the CGIAR Livestock & Climate Initiative, supporting ERA’s mission of providing actionable insights into resilient agricultural practices.

For more details, please consult the foundational ERA publication:
Rosenstock, T.S., Steward, P., Joshi, N. et al. Effects of changing farming practices in African agriculture. Sci Data 11, 958 (2024)
(DOI: 10.1038/s41597-024-03805-z).

For questions or contributions, please create an issue or contact the maintainers.