DOI: 10.25349/d9tk64
title: Data For: Herbarium specimens provide reliable estimates of phenological responsiveness to climate at unparalleled taxonomic and spatiotemporal scales

description: Understanding the effects of climate change on the phenological structure
 of plant communities will require measuring variation in sensitivity among
 thousands of co-occurring species across regions. Herbarium collections
 provide vast resources with which to do this, but may also exhibit biases
 as sources of phenological data. Despite general recognition of these
 caveats, validation of herbarium-based estimates of phenological
 sensitivity against estimates obtained using field observations remain
 rare and limited in scope. Here, we leveraged extensive datasets of
 herbarium specimens and of field observations from the USA National
 Phenology Network for 21 species in the United States and, for each
 species, compared herbarium- and field-based standardized estimates of
 peak flowering dates and of sensitivity of peak flowering time to
 geographic and interannual variation in mean spring minimum temperatures
 (TMIN). We found strong agreement between herbarium- and field-based
 estimates for standardized peak flowering time (r=0.91, p&lt;0.001)
 and for the direction and magnitude of sensitivity to both geographic TMIN
 variation (r=0.88, p &lt;0.001) and interannual TMIN variation
 (r=0.82, p&lt;0.001). This agreement was robust to substantial
 differences between datasets in 1) the long-term TMIN conditions observed
 among collection and phenological monitoring sites and 2) the interannual
 TMIN conditions observed in the time periods encompassed by both datasets
 for most species. Our results show that herbarium-based sensitivity
 estimates are reliable among species spanning a wide diversity of life
 histories and biomes, demonstrating their utility in a broad range of
 ecological contexts, and underscoring the potential of herbarium
 collections to enable phenoclimatic analysis at taxonomic and
 spatiotemporal scales not yet captured by observational data.  
description: Phenological data
 The dataset of field
 observations consisted of all records of flowering onset and termination
 available in the USA National Phenology Network database (NPNdb),
 representing an initial 1,105,764 phenological observations. To ensure the
 quality of the observational data, we retained only observations for which
 we could determine that the dates of onset and termination of flowering
 had an arbitrary maximum error of 14 days. To do this, we filtered the
 data to include only records for which the date on which the first open
 flower on an individual was observed was preceded by an observation of the
 same individual without flowers no more than 14 days prior, and for which
 the date on which the last flower was recorded was followed by an
 observation of the same individual without flowers no more than 14 days
 later. After filtering, field observations in our data had an average
 maximum error of 6.4 days for the onset of flowering, and of 6.6 days for
 the termination of flowering. The herbarium dataset was constructed using
 an initial 894,392 digital herbarium specimen records archived by 72
 herbaria across North America. We excluded from analysis all specimens not
 explicitly recorded as being in flower, or for which GPS coordinates or
 dates of collection were not available. We further filtered both datasets
 by only retaining species that were found in both datasets and that were
 represented by observations at a minimum of 15 unique sites in the NPN
 dataset. For each species, and to more closely match the geographic ranges
 covered by each dataset, we filtered the herbarium dataset to include only
 specimens within the range of latitudes and longitudes represented by the
 field observations in the NPN data. Finally, we retained only species
 represented by 70 or more herbarium specimens to ensure sufficient sample
 sizes for phenoclimatic modeling. This procedure identified a final
 set of 21 native species represented in 3,243 field observations across
 1,406 unique site-year combinations, and a final sample of 5,405 herbarium
 specimens across 4,906 unique site-year combinations. For the herbarium
 dataset, sample sizes ranged from 69 unique sites and 74 specimens
 for<em> Prosopis velutina</em>, to 1,323 unique sites
 containing 1,368 specimens for <em>Achillea millefolium</em>.
 Sample sizes in the NPN dataset ranged from 15 unique sites with 74
 observations for <em>Impatiens capensis, </em>108 unique sites
 with 321 observations for <em>Cornus
 florida</em><em>.</em> These 21 species represented 15
 families and 17 genera, spanning a diverse range of life-history
 strategies and growth forms, including evergreen and deciduous shrubs and
 trees (e.g., <em>Quercus agrifolia </em>and <em>Tilia
 americana</em>, respectively), as well as herbaceous perennials
 (e.g., <em>Achillea millefolium</em>) and annuals (e.g.,
 <em>Impatiens capensis</em>). Our focal species covered a wide
 variety of biomes and regions including Western deserts (e.g.,
 <em>Fouquieria splendens</em>), Mediterranean shrublands and
 oak woodlands (e.g., <em>Baccharis pilularis, Quercus
 agrifolia</em>), and Eastern deciduous forests (e.g.,
 <em>Quercus rubra, Tilia Americana</em>). To estimate flowering dates in
 the herbarium dataset, we employed the day of year of collection
 (henceforth ‘DOY’) of each specimen collected while in flower as a proxy.
 Herbarium specimens in flower could have been collected at any point
 between the onset and termination of their flowering period and botanists
 may preferentially collect individuals in their flowering peak for many
 species. Therefore, herbarium specimen collection dates are more likely to
 reflect peak flowering dates than flowering onset dates. To maximize the
 phenological equivalence of the field and herbarium datasets, we used the
 median date between onset and termination of flowering for each individual
 in each year in the NPN data as a proxy for peak flowering time. Due to
 the maximum error of 14 days for flowering onset and termination dates in
 the NPN dataset, median flowering dates also had a maximum error of 14
 days, with an average maximum error among observations of 6.5 days. To
 account for the artificial DOY discontinuity between December
 31<sup>st</sup> (DOY = 365 or 366 in a leap year) to January
 1<sup>st</sup> (DOY = 1), we converted DOY in both datasets
 into a circular variable using an Azimuthal correction. Climate data Daily minimum temperatures
 mediate key developmental processes including the break of dormancy,
 floral induction, and anthesis. Therefore, we used minimum surface
 temperatures averaged over the three months leading up to (and including)
 the mean flowering month for each species (hereafter ‘TMIN’) as the
 climatic correlate of flowering time in this study; consequently, the
 specific months over which temperatures were averaged varied among
 species. Using TMIN calculated over different time periods instead (e.g.,
 during spring for all species) did not qualitatively affect our results.
 Then, we partitioned variation among sites into spatial and temporal
 components, characterizing TMIN for each observation by the long-term mean
 TMIN at its site of collection (henceforth ‘TMIN normals’), and by the
 deviation between its TMIN in the year of collection (for the three-month
 window of interest) and its long-term mean TMIN (henceforth ‘TMIN
 anomalies’). For each site, we obtained a monthly time series of TMIN from
 January, 1901, and December, 2016, using ClimateNA v6.30, a software
 package that interpolates 4km<sup>2</sup> resolution climate
 data from PRISM Climate Group from Oregon State University,
 (http://prism.oregonstate.edu) to generate elevation-adjusted climate
 estimates. To calculate TMIN normals, we averaged observed TMIN for the
 three months leading up to the mean flowering date of each species across
 all years between 1901 and 2016 for each site. TMIN anomalies relative to
 long-term conditions were calculated by subtracting TMIN normals from
 observed TMIN conditions in the year of collection. Therefore, positive
 and negative values of the anomalies respectively reflect
 warmer-than-average and colder-than-average conditions in a given
 year. Analysis We also provide R code to
 reproduce all results presented in the main text and the supplemental
 materials of our study. This code includes 1) all steps necessary to merge
 herbarium and field data into a single dataset ready for analysis, 2) the
 formulation and specification of the varying-intercepts and varying-slopes
 Bayesian model used to generate herbarium- vs. field-based estimates of
 phenology and its sensitivity to TMIN<sub>sp</sub>, 3) the
 steps required to process the output of the Bayesian model and to obtain
 all metrics required for the analyses in the paper, and 4) the code used
 to generate each figure. Contributing Herbaria
 Data used in this study was
 contributed by the Yale Peabody Museum of Natural History, the George
 Safford Torrey Herbarium at the University of Connecticut, the Acadia
 University Herbarium, the Chrysler Herbarium at Rutgers University, the
 University of Montreal Herbarium, the Harvard University Herbarium, the
 Albion Hodgdon Herbarium at the University of New Hampshire, the Academy
 of Natural Sciences of Drexel University, the Jepson Herbarium at the
 University of California-Berkeley, the University of California-Berkeley
 Sagehen Creek Field Station Herbarium, the California Polytechnic State
 University Herbarium, the University of Santa Cruz Herbarium, the Black
 Hills State University Herbarium, the Luther College Herbarium, the Minot
 State University Herbarium, the Tarleton State University Herbarium, the
 South Dakota State University Herbarium, the Pittsburg State University
 Herbarium, the Montana State University-Billings Herbarium, the Sul Ross
 University Herbarium, the Fort Hays State University Herbarium, the Utah
 State University Herbarium, the Brigham Young University Herbarium, the
 Eastern Nevada Landscape Coalition Herbarium, the University of Nevada
 Herbarium, the Natural History Museum of Utah, the Western Illinois
 University Herbarium, the Eastern Illinois University Herbarium, the
 Northern Illinois University Herbarium, the Morton Arboretum Herbarium,
 the Chicago Botanic Garden Herbarium, the Field Museum of Natural History,
 the University of Wisconsin-Madison Herbarium, the University of Michigan
 Herbarium, the Indiana University Herbarium, the Universidad de Sonora
 Herbarium, the Centro de Investigaciones Biológicas del Noroeste, S. C.,
 the Instituto Politécnico Nacional, CIIDIR Unidad Durango, the University
 of California-Riverside Herbarium, the San Diego State University
 Herbarium, the Granite Mountains Desert Research Center, the University of
 South Carolina Herbarium, the Auburn University Museum of Natural History,
 the Clemson University Herbarium, the Eastern Kentucky University
 Herbarium, the College of William and Mary Herbarium, the Appalachian
 State University Herbarium, the University of North Carolina Herbarium,
 the University of Memphis Herbarium, the Mississippi State University
 Herbarium, the University of Mississippi Herbarium, the University of
 Southern Mississippi Herbarium, the Mississippi Museum of Natural Science,
 the Marshall University Herbarium, the Longwood University Herbarium, the
 Herbarium of Western Carolina University, the Northern Kentucky University
 Herbarium, the Salem College Herbarium, the Troy University Herbarium, the
 Arizona State University Herbarium, the University of Arizona Herbarium,
 the Desert Botanical Garden, the Deaver Herbarium, the Navajo Nation
 Department of Fish and Wildlife, the Grand Canyon National Park Herbarium,
 the University of New Mexico Herbarium, the Western New Mexico University 
 Herbarium, the Museum of Northern Arizona, the Gil National Forest
 Herbarium, the Arizona Western College Herbarium, and the Natural History
 Institute.
description: The README_Ramirez-Parada_Park_Mazer.txt contains relevant usage
 notes.