Large-scale citizen science programs can support ecological and climate change assessments

Abstract

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.