A comparison of herbarium and citizen science phenology datasets for detecting response of flowering time to climate change in Denmark

Anders P. Tøttrup,Natalie Iwanycki Ahlstrand,Richard B. Primack

doi:10.1007/s00484-022-02238-w

Anders P. Tøttrup, Natalie Iwanycki Ahlstrand + Show 1 more

Open Access

https://doi.org/10.1007/s00484-022-02238-w

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Abstract

Phenology has emerged as a key metric to measure how species respond to changes in climate. Innovative means have been developed to extend the temporal and spatial range of phenological data by obtaining data from herbarium specimens, citizen science programs, and biodiversity data repositories. These different data types have seldom been compared for their effectiveness in detecting environmental impacts on phenology. To address this, we compare three separate phenology datasets from Denmark: (i) herbarium specimen data spanning 145 years, (ii) data collected from a citizen science phenology program over a single year observing first flowering, and (iii) data derived from incidental biodiversity observations in iNaturalist over a single year. Each dataset includes flowering day of year observed for three common spring-flowering plant species: Allium ursinum (ramsons), Aesculus hippocastanum (horse chestnut), and Sambucus nigra (black elderberry). The incidental iNaturalist dataset provided the most extensive geographic coverage across Denmark and the largest sample size and recorded peak flowering in a way comparable to herbarium specimens. The directed citizen science dataset recorded much earlier flowering dates because the program objective was to report the first flowering, and so was less compared to the other two datasets. Herbarium data demonstrated the strongest effect of spring temperature on flowering in Denmark, possibly because it was the only dataset measuring temporal variation in phenology, while the other datasets measured spatial variation. Herbarium data predicted the mean flowering day of year recorded in our iNaturalist dataset for all three species. Combining herbarium data with iNaturalist data provides an even more effective method for detecting climatic effects on phenology. Phenology observations from directed and incidental citizen science initiatives will increase in value for climate change research in the coming years with the addition of data capturing the inter-annual variation in phenology.

Highlights

Phenology has emerged as a key indicator of how species respond to climate change (Cleland et al 2007; Tang et al 2016)
These various new and traditional phenology approaches are increasingly regarded as complementary because they cover different spatial and temporal scales (Spellman and Mulder 2016; Willis et al 2017). They have seldom been quantitatively compared for their ability to detect the impacts of climate change on phenology (Taylor et al, 2019). We address this gap with an explicit quantitative comparison of three phenology datasets for their relative sensitivities in detecting the response of flowering to climate over time and space in Denmark: (i) phenology data derived from herbarium specimens spanning 145 years (“herbarium dataset,” n = 110), (ii) data from a directed phenology citizen science project collected from a single year (“citizen science dataset,” n = 104), and (iii) phenology data derived from incidental biodiversity observations using iNaturalist over a single year (“iNaturalist dataset,” n = 403)
The iNaturalist dataset was found to have a mean flowering day of year (DOY) intermediate to the other two datasets, or 1.5 to 3 weeks earlier than the mean flowering DOY derived from herbarium observations, which likely is due to the advanced warm weather in the year 2020

Summary

Introduction

Phenology has emerged as a key indicator of how species respond to climate change (Cleland et al 2007; Tang et al 2016). To overcome the sparsity of long-term and spatially widespread phenology datasets, scientists have been developing innovative new methods (Cleland et al 2007). Herbarium specimens are increasingly used to recreate long-term phenology observations of flowering, leaf out, and fruiting over the past 100–150 years and over broad geographical regions (Primack et al 2004; Willis et al 2017). Directed citizen science initiatives and community biodiversity data repositories such as iNaturalist are providing new sources of phenology data covering broad geographic regions (iNaturalist, 2021). These new phenology data sources are growing fast; herbarium specimen digitization is happening at unprecedented rates, and the expansion of

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