{"paper_id":"26255eef-758b-49da-9aa1-eb147a1d5883","body_text":"Downloads\nDownload Preprint\nAuthors\nLizbeth G Amador ,\nTadeo Ramirez-Parada,\nIsaac W Park,\nSusan J. Mazer,\nAaron M Ellison,\nMargaret O'Brien,\nEric R Sokol,\nColin A Smith,\nCharles Davis ,\nSydne Record\nAbstract\nPhenological response to global climate change can 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 these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, 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 overdue. We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses.\nDOI\nhttps://doi.org/10.32942/X2TS68\nSubjects\nEcology and Evolutionary Biology, Life Sciences, Plant Sciences\nKeywords\nData harmonization, data management, Ontologies, Scales, SDMs\nDates\nPublished: 2025-01-29 15:30\nLast Updated: 2025-06-10 03:06\nOlder Versions\nLicense\nNo Creative Commons license\nAdditional Metadata\nConflict of interest statement:\nL. G. A. and S. R. are in a working group with Daijiang Li, Kai Zhu, and Tong Qui who may appear as 419 potential reviewers. The authors have no other conflicts of interest to disclose.\nData and Code Availability Statement:\nThe data used to create graphs from Box 1 are openly available in Environmental Data Initiative (EDI) at http://doi.org/[doi in progress], reference number [reference number in progress]. Additionally, the data derived in this article are available from USA-National Phenology Network at http://doi.org/10.5066/F78S4N1V, National Ecological Observatory Network at https://www.neonscience.org/data, Dryad at https://datadryad.org/stash, and EDI at https://edirepository.org/. These data were derived from the following resources available in the public domain: Switzer J, Chamberlain S, Marsh L, Wong K (2024). _rnpn: Interface to the National 'Phenology' Network 'API'_. R package version 1.2.8.0, . NEON (National Ecological Observatory Network). 2024. Plant phenology observations, DP1.10055.001 (RELEASE-2023). 2013-2021 for Region: Contiguous United States. Dataset accessed May 2023 via the USA National Phenology Network at http://doi.org/10.5066/F78S4N1V. Park, Isaac et al. (2023). Herbarium-Derived Phenological Data in North America [Dataset]. Dryad. https://doi.org/10.25349/D9WP6S. Accessed Feb 2023 Park, D., A. Williams, E. Law, A. Ellison, and C. Davis. 2023. Assessing Plant Phenological Patterns in the Eastern United States Over the Last 120 Years ver 5. Environmental Data Initiative. https://doi.org/10.6073/pasta/bfb70a1701ef23f686fcc73840e6ae17 (Accessed 2023- 08).\nLanguage:\nEnglish","source_license":"Public-Domain","license_restricted":false}