Bridging data silos to holistically model plant macrophenology

Abstract

● Phenological shifts to global climate change impact ecosystem functions. There are various data sources from which spatiotemporal, and taxonomic phenological data may be obtained: mobilized herbaria, community-science initiatives, observatory networks, and remote-sensing. However, analyses conducted to date have generally relied on single sources of data, thus treating alternative data sources as isolated silos. ● Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources, that offer partially non-overlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at macroecological scales. Here, we describe data harmonization as the direct integration of disparate sources of phenological data using a common schema. ● We highlight existing methods for data harmonization that can be applied to phenological data: data-design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. ● Data harmonization is not a new concept in ecology but the harmonization of phenological data is long overdue. We aim to highlight the need for better data harmonization providing a roadmap for how harmonized phenological data may fill data gaps while simultaneously integrated into analyses

Code and data availability

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