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Published on: April 19, 2018
Bridging data silos to holistically model plant macrophenology.
Lizbeth G Amador1,2, Tadeo H Ramirez-Parada3, Isaac W Park3,4
1Department of Wildlife, Fisheries, and Conservation Biology, University of Maine, Orono, ME, 04469, USA.
The New Phytologist
|June 6, 2025
Summary
Global climate change impacts ecosystems. Harmonizing diverse phenological data sources, like herbaria and remote sensing, is crucial for a comprehensive understanding of these ecological shifts.
Area of Science:
- Ecology
- Climate Change Science
- Data Science
Background:
- Phenological responses to global climate change significantly affect ecosystem functions.
- Current phenological data analyses often rely on single sources, limiting macroecological understanding.
- Disparate data sources (herbaria, community science, observatories, remote sensing) offer complementary, yet often siloed, information.
Purpose of the Study:
- To propose a vision for harmonizing diverse phenological data sources.
- To enable deeper understanding of phenological responses at macroecological scales.
- To provide a roadmap for integrating disparate data into ecological analyses.
Main Methods:
- Highlighting existing data harmonization methods applicable to phenology: data design patterns, metadata standards, and ontologies.
- Describing the integration of harmonized multi-source phenological data into analyses.
- Discussing the use of automated extraction techniques for data integration.
Main Results:
- A detailed vision for the harmonization of phenological data is presented.
- Methods for direct integration of disparate phenological data sources using a common schema are outlined.
- The potential for harmonized data to fill analytical gaps is demonstrated.
Conclusions:
- Data harmonization is essential for advancing ecological research on phenological shifts.
- Integrating diverse phenological data sources is overdue and critical for comprehensive analysis.
- The proposed roadmap facilitates the integration of harmonized phenological data, enhancing ecological insights.
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