Large-scale citizen science programs can support ecological and climate change assessments
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Crimmins_2022_Environ._Res._Le ...
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School of Natural Resources and the Environment, University of ArizonaDepartment of Environmental Science, University of Arizona
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2022
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Crimmins, T. M., & Crimmins, M. A. (2022). Large-scale citizen science programs can support ecological and climate change assessments. Environmental Research Letters, 17(6).Journal
Environmental Research LettersRights
Copyright © 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Large-scale citizen science programs have the potential to support national climate and ecosystem assessments by providing data useful in estimating both status and trends in key phenomena. In this study, we demonstrate how opportunistic, unbalanced observations of biological phenomena contributed through a national-scale citizen science program can be used to (a) identify and evaluate candidate biotic climate change indicators and (b) generate yearly estimates of status of selected indicators. Using observations of plant phenology contributed to Nature's Notebook, the USA National Phenology Network's citizen science program, we demonstrate a procedure for identifying biotic indicators as well as several approaches leveraging these opportunistically-sampled data points to generate yearly status measures. Because the period of record for this dataset is relatively short and inconsistently sampled (13 yr), we focus on estimates of status, though over time, these measurements could be leveraged to also estimate trends. We first applied various spatial, seasonal, and biological criteria to narrow down the list of candidate indicators. We then constructed latitude-elevation models for individual species-phenophase events using all observations. This allowed us to visualize differences between predicted and reported phenophase onset dates in a year as anomalies, with the expectation that these anomalies - representing earlier or later activity in the species of interest - reflect plant response to local springtime temperatures. Plotting yearly anomalies revealed regions with geographic coherence as well as outliers. We also show how yearly anomaly values can be reduced to a single measure to characterize the early or late nature of phenological activity in a particular year. Finally, we demonstrate how the latitude-elevation models can be leveraged to characterize the pace at which phenological transitions occur along latitude gradients on a year-by-year basis. © 2022 The Author(s).Note
Open access journalISSN
1748-9318Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1088/1748-9326/ac72b7
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Except where otherwise noted, this item's license is described as Copyright © 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.