MAREA
MAREA evaluates the effectiveness of marine reserves by integrating ecological, socioeconomic, and governance indicators using standardized data formats and causal inference methods.
Key Features:
- Holistic Objective Assessment: Evaluates marine reserves across ecological, socioeconomic, and governance dimensions to assess multiple stated objectives.
- Standardized Data Collection and Formatting: Provides guidance for standardized data collection and formatting to enable consistent input and comparisons across case studies.
- Causal Inference Analysis: Applies rigorous causal inference analysis to determine whether and how reserves achieve objectives, including analysis of user-provided data in real-time.
- Cross-Comparative Capability: Standardizes state-of-the-art inference methods to facilitate comparisons across locations, monitoring protocols, and analysis approaches.
Scientific Applications:
- Reserve effectiveness evaluation: Quantifies ecological and socioeconomic outcomes of marine reserves to inform research and management.
- Comparative analyses: Enables cross-site comparisons of reserve outcomes across different locations and monitoring protocols.
- Evidence-based and adaptive management: Supports policymakers, conservationists, and managers with analyses that inform evidence-based decision-making and adaptive management.
Methodology:
Uses standardized data collection and formatting and applies rigorous causal inference analysis and state-of-the-art inference methods to analyze user-provided ecological, socioeconomic, and governance indicators, including real-time analysis of input data.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 6/19/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Villaseñor-Derbez JC, Faro C, Wright M, Martínez J, Fitzgerald S, Fulton S, Mancha-Cisneros MdM, McDonald G, Micheli F, Suárez A, Torre J, Costello C. A user-friendly tool to evaluate the effectiveness of no-take marine reserves. PLOS ONE. 2018;13(1):e0191821. doi:10.1371/journal.pone.0191821. PMID:29381762. PMCID:PMC5790253.