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Phenology––the timing of life-history events––is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current common practice of manually harvesting data from individual specimens greatly restricts our ability to scale data collection to entire collections. Recent investigations have demonstrated that machine-learning models can facilitate data collection from herbarium specimens. However, present attempts have focused largely on simplistic binary coding of reproductive phenology (e.g., flowering or not). Here, we use crowd-sourced phenological data of numbers of buds, flowers, and fruits of more than 3000 specimens of six common wildflower species of the eastern United States (Anemone canadensis, A. hepatica, A. quinquefolia, Trillium erectum, T. grandiflorum, and T. undulatum} to train a model using Mask R-CNN to segment and count phenological features. A single global model was able to automate the binary coding of reproductive stage with greater than 90% accuracy. Segmenting and counting features were also successful, but accuracy varied with phenological stage and taxon. Counting buds was significantly more accurate than flowers or fruits. Moreover, botanical experts provided more reliable data than either crowd-sourcers or our Mask R-CNN model, highlighting the importance of high-quality human training data. Finally, we also demonstrated the transferability of our model to automated phenophase detection and counting of the three Trillium species, which have large and conspicuously-shaped reproductive organs. These results highlight the promise of our two-phase crowd-sourcing and machine-learning pipeline to segment and count reproductive features of herbarium specimens, providing high-quality data with which to study responses of plants to ongoing climatic change.
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Herbarium data accurately predict the timing and duration of population‐level flowering displays
Forecasting the impacts of changing climate on the phenology of plant populations is essential for anticipating and managing potential ecological disruptions to biotic communities. Herbarium specimens enable assessments of plant phenology across broad spatiotemporal scales. However, specimens are collected opportunistically, and it is unclear whether their collection dates – used as proxies of phenological stages – are closest to the onset, peak, or termination of a phenophase, or whether sampled individuals represent early, average, or late occurrences in their populations. Despite this, no studies have assessed whether these uncertainties limit the utility of herbarium specimens for estimating the onset and termination of a phenophase. Using simulated data mimicking such uncertainties, we evaluated the accuracy with which the onset and termination of population‐level phenological displays (in this case, of flowering) can be predicted from natural‐history collections data (controlling for biases in collector behavior), and how the duration, variability, and responsiveness to climate of the flowering period of a species and temporal collection biases influence model accuracy. Estimates of population‐level onset and termination were highly accurate for a wide range of simulated species' attributes, but accuracy declined among species with longer individual‐level flowering duration and when there were temporal biases in sample collection, as is common among the earliest and latest‐flowering species. The amount of data required to model population‐level phenological displays is not impractical to obtain; model accuracy declined by less than 1 day as sample sizes rose from 300 to 1000 specimens. Our analyses of simulated data indicate that, absent pervasive biases in collection and if the climate conditions that affect phenological timing are correctly identified, specimen data can predict the onset, termination, and duration of a population's flowering period with similar accuracy to estimates of median flowering time that are commonplace in the literature.
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- PAR ID:
- 10512396
- Publisher / Repository:
- John Wiley & Sons Ltd on behalf of Nordic Society Oikos
- Date Published:
- Journal Name:
- Ecography
- ISSN:
- 0906-7590
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Plant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of particular concern are tropical biomes, which represent the most biodiverse and imperiled regions of the world. However, compared to temperate floras, we know little about phenological responses of tropical plants because long-term observational datasets from the tropics are sparse. Herbarium specimens have greatly increased our phenological knowledge in temperate regions, but similar data have been underutilized in the tropics and their suitability for this purpose has not been broadly validated. Here, we compare phenological estimates derived from field observational data (i.e., plot surveys) and herbarium specimens at various spatial and taxonomic scales to determine whether specimens can provide accurate estimations of reproductive timing and its spatial variation. Here we demonstrate that phenological estimates from field observations and herbarium specimens coincide well. Fewer than 5% of the species exhibited significant differences between flowering periods inferred from field observations versus specimens regardless of spatial aggregation. In contrast to studies based on field records, herbarium specimens sampled much larger geographic and climatic ranges, as has been documented previously for temperate plants, and effectively captured phenological responses across varied environments. Herbarium specimens are verified to be a vital resource for closing the gap in our phenological knowledge of tropical systems. Tropical plant reproductive phenology inferred from herbarium records are widely congruent with field observations, suggesting that they can (and should) be used to investigate phenological variation and their associated environmental cues more broadly across tropical biomes.more » « less
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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.more » « less
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Summary Herbarium specimens are widely distributed in space and time, thereby capturing diverse conditions. We reconstructed specimen ‘lived’ climate from knowledge of germination cues and collection dates for 14 annual species in theStreptanthus(s.l.) clade (Brassicaceae) to ask: which climate attributes best explain specimen phenological stage and estimated reproduction? Are climate effects on phenology and reproduction evolutionarily conserved?We used climate data geolocated to collection sites to reconstruct the climate experienced by specimens and to ask which aspects of climate best explain specimen reproductive traits. We mapped slopes of climate relationships with these traits on the phylogeny to explore evolutionary constraint and models of evolution.Precipitation amount and onset, more than temperature, best predicted specimen phenology, but weakly predicted reproduction. Earlier rainfall was associated with more phenological advancement, a relationship that showed phylogenetic signal. Few climate predictors explained specimen reproduction. Phenological compensation, interactions with other species, or challenges in estimating total reproduction from specimens may reduce the signal between climate and reproduction.We highlight the value of specimen‐tailored growing season estimates for reconstructing climate, incorporating evolutionary relationships in assessing responses to climate. We propose supplemental collection protocols to increase the utility of specimens for understanding climate impacts.more » « less
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Abstract Recent evidence suggests that community science and herbarium datasets yield similar estimates of species' phenological sensitivities to temperature. Despite this, two recent studies by Alecrim et al. (2023) and Miller et al. (2022) found very different results when using different data sources (community science and herbarium specimens, respectively) to investigate whether warming threatens wildflowers with phenological mismatch in relation to shading by deciduous trees.Here, we investigated whether differences between the two studies' results could be reconciled by testing four hypotheses related to model design, species, spatiotemporal data extent and phenophase.Hybrid model structures brought results from the two datasets closer together but did not fully reconcile the differences between the studies. Neither the species nor the phenophase selected for analysis seemed to be responsible for differences in results. Cropping the datasets to match spatial and temporal extents appeared to reconcile most differences but only at the cost of much higher uncertainty associated with reduced sample size.Synthesis: Our analysis suggests that although species‐level estimates of phenological sensitivity may be similar between community science and herbarium datasets, inherent differences in the types and extent of data may lead to contradictory inference about complex biotic interactions. We conclude that, until community science data repositories expand to match the range of climate conditions present in herbarium collections or until herbarium collections match the spatial extent and temporal frequency of community science repositories, ecological studies should ideally be evaluated using both datasets to test the possibility of biased results from either.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/ecog.06961
