On the public citation graph
Opportunistically collected photographs can be used to estimate large-scale phenological trends
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/2017gl076933openalex-snapshot
Multidecadal Changes and Interannual Variation in Springtime Phenology of North American Temperate and Boreal Deciduous Forests
inferredcites →https://doi.org/10.1002/ajb2.1174openalex-snapshot
Phenological sequences: how early‐season events define those that follow
inferredcites →https://doi.org/10.1002/aps3.11315openalex-snapshot
Methods for broad‐scale plant phenology assessments using citizen scientists’ photographs
inferredcites →https://doi.org/10.1002/aps3.1193openalex-snapshot
iN aturalist as a tool to expand the research value of museum specimens
inferredcites →https://doi.org/10.1002/aps3.1231openalex-snapshot
Integrating herbarium specimen observations into global phenology data systems
inferredcites →https://doi.org/10.1002/ecy.1996openalex-snapshot
Climate drives phenological reassembly of a mountain wildflower meadow community
inferredcites →https://doi.org/10.1007/978-0-387-98141-3openalex-snapshot
ggplot2: Elegant Graphics for Data Analysis
inferredcites →https://doi.org/10.1007/bf02447512openalex-snapshot
The modifiable areal unit problem and implications for landscape ecology
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/10.1016/j.agrformet.2019.107694openalex-snapshot
Time to branch out? Application of hierarchical survival models in plant phenology
inferredcites →https://doi.org/10.1016/j.tree.2017.03.015openalex-snapshot
Old Plants, New Tricks: Phenological Research Using Herbarium Specimens
inferredcites →https://doi.org/10.1038/nature01286openalex-snapshot
A globally coherent fingerprint of climate change impacts across natural systems
inferredcites →https://doi.org/10.1038/s41559-017-0350-0openalex-snapshot
A statistical estimator for determining the limits of contemporary and historic phenology
inferredcites →https://doi.org/10.1038/sdata.2018.227openalex-snapshot
Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010
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/10.1111/biom.12533openalex-snapshot
ADRIAN BADDELEY, EGE RUBAK, AND ROLF TURNER, Spatial Point Patterns: Methodology and Applications with R. Boca Raton, FL: CRC Press
inferredcites →https://doi.org/10.1111/ele.12399openalex-snapshot
Quantifying ecological memory in plant and ecosystem processes
inferredcites →https://doi.org/10.1111/ele.13134openalex-snapshot
To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments
inferredcites →https://doi.org/10.1111/gcb.12420openalex-snapshot
The seasonal timing of warming that controls onset of the growing season
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.13472openalex-snapshot
Confounding effects of spatial variation on shifts in phenology
inferredcites →https://doi.org/10.1111/nph.12957openalex-snapshot
Back to the future for plant phenology research
inferredcites →https://doi.org/10.1111/nph.14855openalex-snapshot
Widespread sampling biases in herbaria revealed from large‐scale digitization
inferredcites →https://doi.org/10.1126/science.aaf7671openalex-snapshot
The broad footprint of climate change from genes to biomes to people
inferredcites →https://doi.org/10.1139/b87-279openalex-snapshot
The reproductive biology of boreal forest herbs. II. Phenology of flowering and fruiting
inferredcites →https://doi.org/10.1146/annurev-ecolsys-110316-022706openalex-snapshot
Process-Based Models of Phenology for Plants and Animals
inferredcites →https://doi.org/10.1175/jcli-d-14-00736.1openalex-snapshot
Trends and Natural Variability of Spring Onset in the Coterminous United States as Evaluated by a New Gridded Dataset of Spring Indices
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.i13openalex-snapshot
topicmodels : An R Package for Fitting Topic Models
inferredcites →https://doi.org/10.1890/09-1340.1openalex-snapshot
Spatiotemporal exploratory models for broad‐scale survey data
inferredcites →https://doi.org/10.1890/110236openalex-snapshot
The current state of citizen science as a tool for ecological research and public engagement
inferredcites →https://doi.org/10.21373/gbif.10109150588812214openalex-snapshot
GBIF Occurrence Download
inferredcites →https://doi.org/10.32614/r.manualsopenalex-snapshot
R: A Language and Environment for Statistical Computing
inferredcites →https://doi.org/10.32614/rj-2011-002openalex-snapshot
testthat: Get Started with Testing
inferredcites →https://doi.org/10.32614/rj-2011-011openalex-snapshot
Creating and Deploying an Application with (R)Excel and R
inferredcites →https://doi.org/10.32614/rj-2016-014openalex-snapshot
Spatio-Temporal Interpolation using gstat
inferredcites →https://doi.org/10.3389/fpls.2018.00517openalex-snapshot
The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data
inferredcites →https://doi.org/10.3390/rs8090726openalex-snapshot
Season Spotter: Using Citizen Science to Validate and Scale Plant Phenology from Near-Surface Remote Sensing
inferredcites →https://doi.org/10.3732/ajb.1000363openalex-snapshot
Shifts in the flowering phenology of the northern Great Plains: Patterns over 100 years
inferredcites →https://doi.org/10.3897/biss.3.37303openalex-snapshot
iNaturalist is an Unexploited Source of Plant-Insect Interaction Data
inferredcites →https://doi.org/10.5066/f78s4n1vopenalex-snapshot
USA National Phenology Network In-Situ Phenology Observation Data
inferredcites →https://doi.org/10.7717/peerj.7720openalex-snapshot
Estimating flowering transition dates from status-based phenological observations: a test of methods
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/ece3.10213openalex-snapshot
Citizen science data reveal regional heterogeneity in phenological response to climate in the large milkweed bug, Oncopeltus fasciatus
inferred← citeshttps://doi.org/10.1007/978-3-030-86688-4_17openalex-snapshot
Caterpillar Patterns in Space and Time: Insights From and Contrasts Between Two Citizen Science Datasets
inferred← citeshttps://doi.org/10.1016/j.agrformet.2022.109133openalex-snapshot
Citizen science helps predictions of climate change impact on flowering phenology: A study on Anemone nemorosa
inferred← citeshttps://doi.org/10.1111/2041-210x.13448openalex-snapshot
The accuracy of phenology estimators for use with sparsely sampled presence‐only observations
inferred← citeshttps://doi.org/10.1111/ele.13731openalex-snapshot
Method matters: pitfalls in analysing phenology from occurrence records
inferred← citeshttps://doi.org/10.1111/nph.18361openalex-snapshot
The ecological implications of intra‐ and inter‐species variation in phenological sensitivity
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