Evidence map›Paper›PMID 40474615›Full record

ReviewThe New phytologist2026

Bridging data silos to holistically model plant macrophenology.

Lizbeth G Amador, Tadeo H Ramirez-Parada, Isaac W Park, Susan J Mazer, Aaron M Ellison, Margaret O'Brien, Eric R Sokol, Colin A Smith, Charles C Davis, Sydne Record

Abstract readReview
In one paragraph

Review in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lizbeth G AmadorDepartment of Wildlife, Fisheries, and Conservation Biology, University of Maine, Orono, ME, 04469, USA.ORCID https://orcid.org/0009-0002-7238-1247
Tadeo H Ramirez-ParadaDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, 93106, USA.ORCID https://orcid.org/0000-0002-9900-8373
Isaac W ParkDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, 93106, USA.ORCID https://orcid.org/0000-0001-5539-1641
Susan J MazerDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, 93106, USA.ORCID https://orcid.org/0000-0001-8080-388X
Aaron M EllisonDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, 22 Divinity Avenue, Cambridge, MA, 02138, USA.ORCID https://orcid.org/0000-0003-4151-6081
Margaret O'BrienMarine Science Institute, University of California, Santa Barbara, CA, 93111, USA.ORCID https://orcid.org/0000-0002-1693-8322
Eric R SokolNational Ecological Observatory Network, Battelle, Boulder, CO, 80301, USA.ORCID https://orcid.org/0000-0001-5923-0917
Colin A SmithCenter for Limnology, University of Wisconsin, Madison, WI, 53706, USA.ORCID https://orcid.org/0000-0003-2261-9931
Charles C DavisDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, 22 Divinity Avenue, Cambridge, MA, 02138, USA.ORCID https://orcid.org/0000-0001-8747-1101
Sydne RecordDepartment of Wildlife, Fisheries, and Conservation Biology, University of Maine, Orono, ME, 04469, USA.ORCID https://orcid.org/0000-0001-7293-2155

Funding

Division of Biological Infrastructure 2223103Division of Biological Infrastructure 2223104Division of Environmental Biology 1556768Division of Environmental Biology 2105903Division of Environmental Biology 2105907Division of Environmental Biology 2105932Maine Agricultural and Forest Experiment Station 22425
6 · The paper itself

Abstract

Phenological 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.

Indexed as

Models, BiologicalPlantsEcosystemdata harmonizationdata managementontologiesscalesSDMs

Identifiers

PMID40474615
PMCPMC13278655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.