2018
DOI: 10.1098/rstb.2017.0394
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Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States

Abstract: Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens rep… Show more

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Cited by 94 publications
(187 citation statements)
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“…For example, the mismatch between the spatial distribution of vegetation productivity and the density of FLUXNET sites 167 highlights the need to expand the current network from the mid-latitudes to the tropics, where the most photosynthesis takes place. Also, growing crowd-sourced observations by citizen scientists, such as the CrowdCurio phenology observations over the eastern USA 168 , can provide valuable data that complement the more expensive professional ground observation networks. These increasing types and amounts of data, together with the rapid development of deep learning 169 and process modelling 11 , offer promising tools for improving our understanding of vegetation greening 169 .…”
Section: Discussionmentioning
confidence: 99%
“…For example, the mismatch between the spatial distribution of vegetation productivity and the density of FLUXNET sites 167 highlights the need to expand the current network from the mid-latitudes to the tropics, where the most photosynthesis takes place. Also, growing crowd-sourced observations by citizen scientists, such as the CrowdCurio phenology observations over the eastern USA 168 , can provide valuable data that complement the more expensive professional ground observation networks. These increasing types and amounts of data, together with the rapid development of deep learning 169 and process modelling 11 , offer promising tools for improving our understanding of vegetation greening 169 .…”
Section: Discussionmentioning
confidence: 99%
“…However, the direction and magnitude of these shifts differ, and some species exhibit delayed phenological responses to warming (Peñuelas et al 2002;Sherry et al 2007;Dunnell & Travers 2011;Cook et al 2012;Liancourt et al 2012) or no response to warming (Bradley et al 1999;Peñuelas et al 2002;Liancourt et al 2012;CaraDonna et al 2014). Variable responses to warming may result from differential effects of climate change on early-vs. late-season flowering species (Sherry et al 2007;Park et al 2018) or variation among species in the degree to which phenology is regulated by photoperiod vs. temperature (Chuine et al 2010). Furthermore, because species respond differently to climate change, global warming also may alter phenological synchrony, or the degree of overlap in the flowering times of interacting species (Harrington et al 1999;Stenseth & Mysterud 2002;Visser et al 2004;CaraDonna et al 2014;Kharouba et al 2018;Zohner et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Phenological patterns often vary widely across geographic ranges (Zhang et al., ; Hereford et al., ), which can greatly complicate attempts to understand phenological shifts through time. For example, higher‐latitude species are generally more responsive to temperature changes (Root et al., ; Parmesan ; Post et al., ; but see Park et al., ). In the present study, geospatial factors (i.e., latitude and longitude) explained most of the variation in flowering time in T. perfoliata .…”
Section: Discussionmentioning
confidence: 99%