MeadoWatch: a long-term community-science database of wildflower phenology in Mount Rainier National Park

We present a long-term and high-resolution phenological dataset from 17 wildflower species collected in Mt. Rainier National Park, as part of the MeadoWatch (MW) community science project. Since 2013, 500+ unique volunteers and scientists have gathered data on the timing of four key reproductive phenophases (budding, flowering, fruiting, and seeding) in 28 plots over two elevational gradients alongside popular park trails. Trained volunteers (87.2%) and UW scientists (12.8%) collected data 3-9 times/week during the growing season, using a standardized method. Taxonomic assessments were highly consistent between scientists and volunteers, with high accuracy and specificity across phenophases and species. Sensitivity, on the other hand, was lower than accuracy and specificity, suggesting that a few species might be challenging to reliably identify in community-science projects. Up to date, the MW database includes 42,000+ individual phenological observations from 17 species, between 2013 and 2019. However, MW is a living dataset that will be updated through continued contributions by volunteers, and made available for its use by the wider ecological community.

Methods
Open-Data-MeadoWatch Project
MeadoWatch coordinator and contact: Prof. Dr. Janneke Hille Ris Lambers. [e-mail] University of Washington - ETHZürich Prof. Dr. Elli Theobald Dr. Meera Sethi PhD Candidate Aji John Dr. Rubén D. Manzanedo Prof. Dr. Berry Bross Dr. Joshua Jenkins Ms. Kloss-Schmidt Dr. Emmilia Lia Ms. Annie Schiffer Ms. Jordana Sevigny Ms. Anna Wilson Dr. Yonit Yogev

Permanent website of MeadoWatch and more info: http://www.meadowatch.org/ https://www.youtube.com/channel/UCGBFTKxf8FIWswMDxBavpuQ/featured

PUBLICATIONS LINKED TO THE MEADOWATCH DATABASE

Manzanedo, R.D., John, A., Sethi, M.L., Theobald, E.J., Brosi, B., Jenkins, J., Kloss-Schmidt, A., Lia, E., Schiffer, A., Sevigny, J., Wilson, A., Yogev, Y., & Hille Ris Lambers, J. (Under review). MeadoWatch: a long-term community-science database of wildflower phenology in Mount Rainier National Park. Scientific Data

Hille Ris Lambers, J., Cannistra, A. F., John, A., Lia, E., Manzanedo, R. D., Sethi, M., Sevigny, J., Theobald, E. J., Waugh, J. K. (2021) Climate change impacts on natural icons: do phenological shifts threaten the relationship between peak wildflowers and visitor satisfaction? Climate Change Ecology

Breckheimer, I. K., Theobald, E. J., Cristea, N. C., Wilson, A. K., Lundquist, J. D., Rochefort, R. M., & HilleRisLambers, J. (2020). Crowd‐sourced data reveal social–ecological mismatches in phenology driven by climate. Frontiers in Ecology and the Environment, 18(2), 76-82.

John, A., Ong, J., Theobald, E. J., Olden, J. D., Tan, A., & HilleRisLambers, J. (2020). Detecting Montane Flowering Phenology with CubeSat Imagery. Remote Sensing, 12(18), 2894.

Wilson, A., Bacher, K., Breckheimer, I., Lundquist, J., Rochefort, R., Theobald, E., ... & HilleRisLambers, J. (2017). Monitoring wildflower phenology using traditional science, citizen science, and crowd sourcing. Park Sci, 33, 17-26.

Repository content
RAW DATA. Please check the 'Final data' folder:

MW_PhenoDat_2013_2019_anonymized.csv -- Phenological records. Information on date, transect id, observer, and phenological state per flowering species.

MW_SiteInfo_2013_2019_anonymized.csv -- Latitude and longitude location (WGS84), elevation, and forest type for each MW site

MW_metadata.xlsx -- metadata information for all variables and files. As well as equivalency in species names (4 letter code to full botanical name)

MW_SDDall.csv -- snow disappearance data and minimum soil temperature data

MW_Phenocurves.csv -- parameters and data to reconstruct the curves in HilleRisLambers et al. 2021 and in the data exploration tool

MW_Volunteer_info_2013_2019_anonymized.csv -- contains information for the MW volunteers, including observer, first participation, first year of training and training type