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Comparison of large‐scale citizen science data and long‐term study data for phenology modeling

https://doi.org/10.1002/ecy.2568
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ecs2.1436openalex-snapshot
Emerging opportunities and challenges in phenology: a review
inferredcites →https://doi.org/10.1002/ecy.1996openalex-snapshot
Climate drives phenological reassembly of a mountain wildflower meadow community
inferredcites →https://doi.org/10.1002/ecy.2568openalex-snapshot
Comparison of large‐scale citizen science data and long‐term study data for phenology modeling
inferredcites →https://doi.org/10.1006/jtbi.2000.2178openalex-snapshot
A Unified Model for Budburst of Trees
inferredcites →https://doi.org/10.1007/978-0-387-98141-3openalex-snapshot
ggplot2: Elegant Graphics for Data Analysis
inferredcites →https://doi.org/10.1007/978-3-319-24277-4openalex-snapshot
ggplot2
inferredcites →https://doi.org/10.1007/978-94-007-0632-3_14openalex-snapshot
Plant Development Models
inferredcites →https://doi.org/10.1007/978-94-007-6925-0_15openalex-snapshot
Plant Development Models
inferredcites →https://doi.org/10.1007/s00484-014-0789-5openalex-snapshot
Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications
inferredcites →https://doi.org/10.1007/s00484-014-0892-7openalex-snapshot
Assessing accuracy in citizen science-based plant phenology monitoring
inferredcites →https://doi.org/10.1007/s00484-015-1036-4openalex-snapshot
Estimating the onset of spring from a complex phenology database: trade-offs across geographic scales
inferredcites →https://doi.org/10.1007/s00484-018-1540-4openalex-snapshot
How training citizen scientists affects the accuracy and precision of phenological data
inferredcites →https://doi.org/10.1016/j.advwatres.2011.04.013openalex-snapshot
Parallel distributed computing using Python
inferredcites →https://doi.org/10.1016/j.agrformet.2007.09.013openalex-snapshot
Regional phenological models for forecasting the start and peak of the Quercus pollen season in Spain
inferredcites →https://doi.org/10.1016/j.agrformet.2012.05.001openalex-snapshot
Shortcomings of classical phenological forcing models and a way to overcome them
inferredcites →https://doi.org/10.1016/j.agrformet.2012.09.012openalex-snapshot
Climate change, phenology, and phenological control of vegetation feedbacks to the climate system
inferredcites →https://doi.org/10.1016/j.agrformet.2015.11.007openalex-snapshot
Evaluating phenological models for the prediction of leaf-out dates in six temperate tree species across central Europe
inferredcites →https://doi.org/10.1016/j.biocon.2013.05.025openalex-snapshot
Realising the full potential of citizen science monitoring programs
inferredcites →https://doi.org/10.1016/j.cois.2017.05.015openalex-snapshot
Interactions between bee foraging and floral resource phenology shape bee populations and communities
inferredcites →https://doi.org/10.1016/j.ecolind.2017.02.024openalex-snapshot
Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations
inferredcites →https://doi.org/10.1016/j.tree.2007.04.003openalex-snapshot
Shifting plant phenology in response to global change
inferredcites →https://doi.org/10.1023/a:1008202821328openalex-snapshot
Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
inferredcites →https://doi.org/10.1029/2012gl054431openalex-snapshot
Predicting changes in temperate forest budburst using continental‐scale observations and models
inferredcites →https://doi.org/10.1038/nature11014openalex-snapshot
Warming experiments underpredict plant phenological responses to climate change
inferredcites →https://doi.org/10.1038/s41598-018-23804-6openalex-snapshot
Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing
inferredcites →https://doi.org/10.1038/sdata.2018.28openalex-snapshot
Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
inferredcites →https://doi.org/10.1073/pnas.1118364109openalex-snapshot
Divergent responses to spring and winter warming drive community level flowering trends
inferredcites →https://doi.org/10.1073/pnas.1323073111openalex-snapshot
Shifts in flowering phenology reshape a subalpine plant community
inferredcites →https://doi.org/10.1098/rstb.2012.0489openalex-snapshot
Nonlinear flowering responses to climate: are species approaching their limits of phenological change?
inferredcites →https://doi.org/10.1111/1365-2745.12774openalex-snapshot
Phenological responsiveness to climate differs among four species of Quercus in North America
inferredcites →https://doi.org/10.1111/ele.12854openalex-snapshot
Interannual bumble bee abundance is driven by indirect climate effects on floral resource phenology
inferredcites →https://doi.org/10.1111/gcb.12095openalex-snapshot
Regional unified model‐based leaf unfolding prediction from 1960 to 2009 across northern China
inferredcites →https://doi.org/10.1111/gcb.12593openalex-snapshot
Process‐based models not always better than empirical models for simulating budburst of Norway spruce and birch in Europe
inferredcites →https://doi.org/10.1111/gcb.12896openalex-snapshot
Predicting a change in the order of spring phenology in temperate forests
inferredcites →https://doi.org/10.1111/gcb.13122openalex-snapshot
Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States
inferredcites →https://doi.org/10.1111/gcb.13383openalex-snapshot
Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break
inferredcites →https://doi.org/10.1111/gcb.14002openalex-snapshot
New insights on plant phenological response to temperature revealed from long‐term widespread observations in China
inferredcites →https://doi.org/10.1111/j.1365-2486.2011.02562.xopenalex-snapshot
Terrestrial biosphere models need better representation of vegetation phenology: results from the N orth A merican C arbon P rogram S ite S ynthesis
inferredcites →https://doi.org/10.1111/j.1365-3040.1995.tb00356.xopenalex-snapshot
Phenotypic plasticity of the phenology of seven European tree species in relation to climatic warming
inferredcites →https://doi.org/10.1111/j.1461-0248.2008.01250.xopenalex-snapshot
Global change and species interactions in terrestrial ecosystems
inferredcites →https://doi.org/10.1111/j.1461-0248.2012.01765.xopenalex-snapshot
Forecasting phenology: from species variability to community patterns
inferredcites →https://doi.org/10.1146/annurev-ecolsys-102209-144636openalex-snapshot
Citizen Science as an Ecological Research Tool: Challenges and Benefits
inferredcites →https://doi.org/10.1146/annurev-ecolsys-110316-022706openalex-snapshot
Process-Based Models of Phenology for Plants and Animals
inferredcites →https://doi.org/10.1371/journal.pone.0182919openalex-snapshot
USA National Phenology Network’s volunteer-contributed observations yield predictive models of phenological transitions
inferredcites →https://doi.org/10.1525/bio.2009.59.7.12openalex-snapshot
Data-intensive Science: A New Paradigm for Biodiversity Studies
inferredcites →https://doi.org/10.18637/jss.v040.i03openalex-snapshot
Dates and Times Made Easy with lubridate
inferredcites →https://doi.org/10.18637/jss.v040.i06openalex-snapshot
DEoptim : An R Package for Global Optimization by Differential Evolution
inferredcites →https://doi.org/10.1890/09-1549.1openalex-snapshot
Reconciling multiple data sources to improve accuracy of large-scale prediction of forest disease incidence
inferredcites →https://doi.org/10.1890/110281openalex-snapshot
From Caprio's lilacs to the USA National Phenology Network
inferredcites →https://doi.org/10.2307/1931815openalex-snapshot
A Critique of the Heat Unit Approach to Plant Response Studies
inferredcites →https://doi.org/10.2307/1935214openalex-snapshot
Effects of Rainfall and Temperature on the Distribution and Behavior of Larrea Tridentata (Creosote‐Bush) in the Mojave Desert of Nevada
inferredcites →https://doi.org/10.2307/2403139openalex-snapshot
Thermal Time, Chill Days and Prediction of Budburst in Picea sitchensis
inferredcites →https://doi.org/10.2307/2404467openalex-snapshot
Predicting the Timing of Budburst in Temperate Trees
inferredcites →https://doi.org/10.25080/majora-92bf1922-00aopenalex-snapshot
Data Structures for Statistical Computing in Python
inferredcites →https://doi.org/10.32614/r.manualsopenalex-snapshot
R: A Language and Environment for Statistical Computing
inferredcites →https://doi.org/10.6073/pasta/765084e2b4a5ec389403238c58784572openalex-snapshot
Hubbard Brook Experimental Forest (US Forest Service): Routine Seasonal Phenology Measurements, 1989 - present

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1002/aps3.11338openalex-snapshot
Low‐cost observations and experiments return a high value in plant phenology research
inferred← citeshttps://doi.org/10.1002/eap.2025openalex-snapshot
Automated data‐intensive forecasting of plant phenology throughout the United States
inferred← citeshttps://doi.org/10.1002/ece3.6954openalex-snapshot
Using community photography to investigate phenology: A case study of coat molt in the mountain goat (Oreamnos americanus) with missing data
inferred← citeshttps://doi.org/10.1007/s00484-021-02152-7openalex-snapshot
An empirical method to account for climatic adaptation in plant phenology models
inferred← citeshttps://doi.org/10.1007/s00484-022-02238-wopenalex-snapshot
A comparison of herbarium and citizen science phenology datasets for detecting response of flowering time to climate change in Denmark
inferred← citeshttps://doi.org/10.1007/s00484-023-02502-7openalex-snapshot
Ten best practices for effective phenological research
inferred← citeshttps://doi.org/10.1007/s00484-025-02892-wopenalex-snapshot
Changes in cranberry phenology from 1958 to 2022: Implications for spring frost protection in Massachusetts, United States
inferred← citeshttps://doi.org/10.1007/s00484-025-02972-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00484-026-03197-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10336-023-02114-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11258-023-01377-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44248-026-00118-xopenalex-snapshot
Fixed pre-season weather windows eliminate endogeneity bias in interval-censored survival models of grapevine phenology
inferred← citeshttps://doi.org/10.1016/j.agrformet.2019.107694openalex-snapshot
Time to branch out? Application of hierarchical survival models in plant phenology
inferred← citeshttps://doi.org/10.1016/j.biocon.2023.110079openalex-snapshot
Citizen science participant motivations and behaviour: Implications for biodiversity data coverage
inferred← citeshttps://doi.org/10.1016/j.csag.2024.100008openalex-snapshot
Near surface camera informed agricultural land monitoring for climate smart agriculture
inferred← citeshttps://doi.org/10.1016/j.ecochg.2021.100032openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ecoinf.2023.102314openalex-snapshot
Mapping cherry blossom phenology using a semi-automatic observation system with street level photos
inferred← citeshttps://doi.org/10.1016/j.ecolind.2025.114484openalex-snapshot
Deriving exploratory temperature-based phenological indicators under data-limited conditions: integrating ERA5 and citizen science
inferred← citeshttps://doi.org/10.1016/j.eja.2023.126945openalex-snapshot
Climate warming may accelerate apple phenology but lead to divergent dynamics in late-spring frost and poor pollination risks in main apple production regions of China
inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e16144openalex-snapshot
Computational biogeographic distribution of the fall armyworm (Spodoptera frugiperda J.E. Smith) moth in eastern Africa
inferred← citeshttps://doi.org/10.1038/s41597-022-01206-8openalex-snapshot
MeadoWatch: a long-term community-science database of wildflower phenology in Mount Rainier National Park
inferred← citeshttps://doi.org/10.1038/s41598-022-16104-7openalex-snapshot
Consistent trait-temperature interactions drive butterfly phenology in both incidental and survey data
inferred← citeshttps://doi.org/10.1038/s41598-023-50688-yopenalex-snapshot
Losing ground: projections of climate-driven bloom shifts and their implications for the future of California’s almond orchards
inferred← citeshttps://doi.org/10.1086/730783openalex-snapshot
Historical Field Records Reveal Habitat as an Ecological Correlate of Locomotor Phenotypic Diversity in the Radiation of Neotropical Geophagini Fishes
inferred← citeshttps://doi.org/10.1093/aobpla/plae058openalex-snapshot
Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity
inferred← citeshttps://doi.org/10.1093/biosci/biaa044openalex-snapshot
Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research
inferred← citeshttps://doi.org/10.1093/biosci/biab020openalex-snapshot
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inferred← citeshttps://doi.org/10.1101/2023.04.13.536831openalex-snapshot
Spatiotemporal Mapping of Cherry Blossom Blooming by Semi-Automatic Observation System with Street-Level Photos
inferred← citeshttps://doi.org/10.1101/2024.12.21.628886openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/1365-2435.14275openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/ecog.07115openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/icad.70098openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/nph.70249openalex-snapshot
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inferred← citeshttps://doi.org/10.1142/s0219877022300014openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0282750openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0295298openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fcosc.2020.600943openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpls.2022.805738openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpls.2023.1150956openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/f17020287openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs12172760openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs14092017openalex-snapshot
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inferred← citeshttps://doi.org/10.7287/peerj.7720v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Estimating flowering transition dates from status-based phenological observations: a test of methods (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.7720v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Estimating flowering transition dates from status-based phenological observations: a test of methods (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.7720v0.1/reviews/3openalex-snapshot
Peer Review #3 of "Estimating flowering transition dates from status-based phenological observations: a test of methods (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.7720v0.2/reviews/2openalex-snapshot
Peer Review #2 of "Estimating flowering transition dates from status-based phenological observations: a test of methods (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj.7720openalex-snapshot
Estimating flowering transition dates from status-based phenological observations: a test of methods
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