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Updated: Jan 20, 2026
13:18
Data Collection on Marine Litter Ingestion in Sea Turtles and Thresholds for Good Environmental Status
Published on: May 18, 2019
12.6K
Seagrass and hydrographic data for the Mediterranean Sea
Dimitrios Effrosynidis1, Avi Arampatzis1, Georgios Sylaios2
1Database & Information Retrieval Research Unit, Department of Electrical & Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece.
Data in Brief
|August 28, 2019
Summary
This study presents a comprehensive Mediterranean seagrass dataset with 1,771 presence and 1,284 absence locations. It includes 217 environmental and human parameters, ideal for ecological analysis and machine learning.
Area of Science:
- Marine Biology
- Ecology
- Data Science
Background:
- Seagrass ecosystems are vital marine habitats.
- Comprehensive datasets are crucial for understanding seagrass distribution and health.
- Existing data for Mediterranean seagrass is fragmented.
Purpose of the Study:
- To create the most extensive dataset of seagrass presence and absence in the Mediterranean Sea.
- To integrate diverse environmental and human-related parameters for ecological analysis.
- To facilitate data analysis and machine learning applications for seagrass research.
Main Methods:
- Compiled 1,771 seagrass presence locations across major families (Cymodoceaceae, Zosteraceae, Posidoniaceae, Hydrocharitaceae, Ruppiaceae).
- Generated 1,284 algorithmically determined seagrass absence locations.
- Integrated 217 biological, chemical, physical, and human parameters from public data sources.
Main Results:
- A comprehensive dataset covering seagrass distribution in the Mediterranean.
- Rich environmental and anthropogenic data linked to seagrass locations.
- Dataset suitable for advanced ecological modeling and machine learning.
Conclusions:
- The dataset represents a significant advancement for Mediterranean seagrass research.
- Enables in-depth analysis of factors influencing seagrass distribution and health.
- Supports the development of predictive models for seagrass conservation.
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