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Abstract Global warming has caused widespread shifts in plant phenology among species in the temperate zone, but it is unclear how population‐level responses will scale to alter the structure of the flowering season at the community level. This knowledge gap exists largely because—while the climatic sensitivity of first flowering within populations has been studied extensively—little is known about the responsiveness of the duration of a population's flowering period. This limits our ability to anticipate how the entire flowering periods of co‐occurring species may continue to change under warming. Nonetheless, flowering sensitivity to temperature often varies predictably among species between and within communities, which may help forecast temperature‐related changes to a community's flowering season. However, no studies—empirical or theoretical—have assessed how patterns of variation in flowering sensitivity among species could scale to alter community‐level flowering changes under warming. Here, we provide a conceptual overview of how variation in the sensitivity of flowering onset and duration among species can mediate changes to a community's flowering season due to warming trends. Specifically, we focus on the effects of differences in (1) the mean sensitivity of flowering onset and duration among communities and (2) the sensitivity of flowering onsets and durations among species flowering sequentially through the season within a community. We evaluated the manner and degree in which these forms of between‐species variation in sensitivity might affect the structure of the flowering season—both independently and interactively—using simulations, which covered a wide but empirically informed range of parameter values and combinations representing distinct community‐level patterns. Our findings predict that communities across the temperate zone will exhibit varied and often contrasting flowering responses to warming across biomes, underscoring that accounting for the temperature sensitivity of both phenological onset and duration among species is essential for understanding community‐level flowering dynamics in a warming world. 

Summary Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue. We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses. 

PremiseHerbarium specimens have been used to detect climate‐induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption thatDOYaccurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno‐climatic models (PCMs) designed to predict the effects of climate on flowering date. MethodsHere we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use inPCMs to control for phenological variation among specimens ofStreptanthus tortuosus(Brassicaceeae) when testing for the effects of climate onDOY. We demonstrate that includingPIas an independent variable improves model fit. ResultsIncludingPIinPCMs increased the modelR²relative toPCMs that excludedPI; regression coefficients for climatic parameters, however, remained constant. DiscussionOur protocol provides a simple, quantitative phenological metric for any observed plant. IncludingPIinPCMs increasesR²and enables predictions of theDOYof any phenophase under any specified climatic conditions.