Overlooked climate parameters best predict flowering onset: Assessing phenological models using the elastic net

Tracking hidden dimensions of plant biogeography from herbaria

Plants are diverse, but investigating their ecology and evolution in nature across geographic and temporal scales to predict how species will respond to global change is challenging. With their geographic and temporal breadth, herbarium data provide physical evidence of the existence of a species in a place and time. The remarkable size of herbarium collections along with growing digitization efforts around the world and the possibility of extracting functional traits and geographic data from preserved plant specimens makes them invaluable resources for advancing our understanding of changing species distributions over time, functional biogeography, and conserving plant communities. Here, I synthesize core aspects of plant biogeography that can be gleaned from herbaria along changing distributions, attributes (functional biogeography), and conservation biogeography across the globe. I advocate for a collaborative, multisite, and multispecies research to harness the full potential of these collections while addressing the inherent challenges of using herbarium data for biogeography and macroecological investigations. Ultimately, these data present untapped resources and opportunities to enable predictions of plant species' responses to global change and inform effective conservation planning.

Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America

Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (plasticity) or local adaptation remains unresolved. Here we used 1,038,027 herbarium specimens representing 1,605 species from the continental United States to measure flowering-time sensitivity to temperature over time (Stime) and space (Sspace). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates and among ecoregions differing in species composition. Parameters Sspace and Stime were positively correlated (r = 0.87), of similar magnitude and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in late summer and delayed flowering in autumn in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (for example, southeastern United States plains) to their nearly equal importance throughout the season (for example, Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering-time variation along temperature gradients, with local adaptation having a widespread but comparatively limited role.

Current and lagged climate affects phenology across diverse taxonomic groups

The timing of life events (phenology) can be influenced by climate. Studies from around the world tell us that climate cues and species' responses can vary greatly. If variation in climate effects on phenology is strong within a single ecosystem, climate change could lead to ecological disruption, but detailed data from diverse taxa within a single ecosystem are rare. We collated first sighting and median activity within a high-elevation environment for plants, insects, birds, mammals and an amphibian across 45 years (1975-2020). We related 10 812 phenological events to climate data to determine the relative importance of climate effects on species' phenologies. We demonstrate significant variation in climate-phenology linkage across taxa in a single ecosystem. Both current and prior climate predicted changes in phenology. Taxa responded to some cues similarly, such as snowmelt date and spring temperatures; other cues affected phenology differently. For example, prior summer precipitation had no effect on most plants, delayed first activity of some insects, but advanced activity of the amphibian, some mammals, and birds. Comparing phenological responses of taxa at a single location, we find that important cues often differ among taxa, suggesting that changes to climate may disrupt synchrony of timing among taxa.

Context-dependent concordance between physiological divergence and phenotypic selection in sister taxa with contrasting phenology and mating systems

PREMISE

The study of phenotypic divergence of, and selection on, functional traits in closely related taxa provides the opportunity to detect the role of natural selection in driving diversification. If the strength or direction of selection in field populations differs between taxa in a pattern that is consistent with the phenotypic difference between them, then natural selection reinforces the divergence. Few studies have sought evidence for such concordance for physiological traits.

METHODS

Herbarium specimen records were used to detect phenological differences between sister taxa independent of the effects on flowering time of long-term variation in the climate across collection sites. In the field, physiological divergence in photosynthetic rate, transpiration rate, and instantaneous water-use efficiency were recorded during vegetative growth and flowering in 13 field populations of two taxon pairs of Clarkia, each comprising a self-pollinating and a outcrossing taxon.

RESULTS

Historically, each selfing taxon flowered earlier than its outcrossing sister taxon, independent of the effects of local long-term climatic conditions. Sister taxa differed in all focal traits, but the degree and (in one case) the direction of divergence depended on life stage. In general, self-pollinating taxa had higher gas exchange rates, consistent with their earlier maturation. In 6 of 18 comparisons, patterns of selection were concordant with the phenotypic divergence (or lack thereof) between sister taxa.

CONCLUSIONS

Patterns of selection on physiological traits measured in heterogeneous conditions do not reliably reflect divergence between sister taxa, underscoring the need for replicated studies of the direction of selection within and among taxa.

Science and Management Advancements Made Possible by the USA National Phenology Network's Nature's Notebook Platform

The USA National Phenology Network was established in 2007 to formalize standardized phenology monitoring across the country. The aims of the network are to collect, store, and share phenology data and information to support scientific discovery, decision-making, an appreciation for phenology, and equitable engagement within the network. To support these aims, the network launched Nature's Notebook, a rigorous platform for monitoring plant and animal phenology, in 2009.

Since the launch of Nature's Notebook, participants across the country have contributed over 30 million phenology records. The participants range from backyard observers with an interest in nature to researchers and natural resource managers asking specific questions. We survey the breadth of studies and applied decisions that have used Nature's Notebook and the consequent data. The dimensionality of the data set maintained by the network is a function of Nature's Notebook users; this insight is key to shaping the network’s future data collection activities.

Forest wildflowers bloom earlier as Europe warms: lessons from herbaria and spatial modelling

Today plants often flower earlier due to climate warming. Herbarium specimens are excellent witnesses of such long-term changes. However, the magnitude of phenological shifts may vary geographically, and the data are often clustered. Therefore, large-scale analyses of herbarium data are prone to pseudoreplication and geographical biases. We studied over 6000 herbarium specimens of 20 spring-flowering forest understory herbs from Europe to understand how their phenology had changed during the last century. We estimated phenology trends with or without taking spatial autocorrelation into account. On average plants now flowered over 6 d earlier than at the beginning of the last century. These changes were strongly associated with warmer spring temperatures. Flowering time advanced 3.6 d per 1°C warming. Spatial modelling showed that, in some parts of Europe, plants flowered earlier or later than expected. Without accounting for this, the estimates of phenological shifts were biased and model fits were poor. Our study indicates that forest wildflowers in Europe strongly advanced their phenology in response to climate change. However, these phenological shifts differ geographically. This shows that it is crucial to combine the analysis of herbarium data with spatial modelling when testing for long-term phenology trends across large spatial scales.

Ecological Quality Response to Multi-Scenario Land-Use Changes in the Heihe River Basin

To investigate the spatial-temporal effects of land-use changes on ecological quality and future trends, an integrated framework combining the Dyna-CLUE model and the remote sensing ecological index (RSEI) was developed. Land-use changes from 2000 to 2035 were simulated and projected under the current trend scenario (CTS), economic development scenario (EDS) and ecological protection scenario (EPS) in the Heihe River Basin, while the RSEI was predicted using the elastic net regression (machine learning method); finally, the predicted results were synthesized and analyzed. The results showed that forest, grassland and water were positively correlated with ecological quality, with the green space coverage under the CTS, EPS and EDS accounting for 34.15%, 70.65% and 34.72% of the total transferred land area, respectively. The increase in the area of build-up land and unutilized land was detrimental to ecological quality, with the area of building land in the EDS being 1.75 times larger than in the year 2000. The EDS contributes to the sustainable development of the upstream area and the EPS is more conducive to the midstream and downstream areas by limiting the expansion of build-up land and by developing unutilized land in a limited way to increase the area of green space after reconciling economic conditions. Projection results promote the rational allocation of various land-use types in the future (semi) arid region, such as artificial forestation, unutilized land development and restriction of urban expansion, and also lay the foundation for the formulation of policies such as water allocation and ecological protection to facilitate the sustainable development of regional society, economy and ecology.

Region-specific phenological sensitivities and rates of climate warming generate divergent temporal shifts in flowering date across a species' range

PREMISE

Forecasting how species will respond phenologically to future changes in climate is a major challenge. Many studies have focused on estimating species- and community-wide phenological sensitivities to climate to make such predictions, but sensitivities may vary within species, which could result in divergent phenological responses to climate change.

METHODS

We used 743 herbarium specimens of the mountain jewelflower (Streptanthus tortuosus, Brassicaceae) collected over 112 years to investigate whether individuals sampled from relatively warm vs. cool regions differ in their sensitivity to climate and whether this difference has resulted in divergent phenological shifts in response to climate warming.

RESULTS

During the past century, individuals sampled from warm regions exhibited a 20-day advancement in flowering date; individuals in cool regions showed no evidence of a shift. We evaluated two potential drivers of these divergent responses: differences between regions in (1) the degree of phenological sensitivity to climate and (2) the magnitude of climate change experienced by plants, or (3) both. Plants sampled from warm regions were more sensitive to temperature-related variables and were subjected to a greater degree of climate warming than those from cool regions; thus our results suggest that the greater temporal shift in flowering date in warm regions is driven by both of these factors.

CONCLUSIONS

Our results are among the first to demonstrate that species exhibited intraspecific variation in sensitivity to climate and that this variation can contribute to divergent responses to climate change. Future studies attempting to forecast temporal shifts in phenology should consider intraspecific variation.

Advancing frost dates have reduced frost risk among most North American angiosperms since 1980

In recent decades, the final frost dates of winter have advanced throughout North America, and many angiosperm taxa have simultaneously advanced their flowering times as the climate has warmed. Phenological advancement may reduce plant fitness, as flowering prior to the final frost date of the winter/spring transition may damage flower buds or open flowers, limiting fruit and seed production. The risk of floral exposure to frost in the recent past and in the future, however, also depends on whether the last day of winter frost is advancing more rapidly, or less rapidly, than the date of onset of flowering in response to climate warming. This study presents the first continental-scale assessment of recent changes in frost risk to floral tissues, using digital records of 475,694 herbarium specimens representing 1,653 angiosperm species collected across North America from 1920 to 2015. For most species, among sites from which they have been collected, dates of last frost have advanced much more rapidly than flowering dates. As a result, frost risk has declined in 66% of sampled species. Moreover, exotic species consistently exhibit lower frost risk than native species, primarily because the former occupy warmer habitats where the annual frost-free period begins earlier. While reducing the probability of exposure to frost has clear benefits for the survival of flower buds and flowers, such phenological advancement may disrupt other ecological processes across North America, including pollination, herbivory, and disease transmission.

A new fine-grained method for automated visual analysis of herbarium specimens: A case study for phenological data extraction

PREMISE

Herbarium specimens represent an outstanding source of material with which to study plant phenological changes in response to climate change. The fine-scale phenological annotation of such specimens is nevertheless highly time consuming and requires substantial human investment and expertise, which are difficult to rapidly mobilize.

METHODS

We trained and evaluated new deep learning models to automate the detection, segmentation, and classification of four reproductive structures of Streptanthus tortuosus (flower buds, flowers, immature fruits, and mature fruits). We used a training data set of 21 digitized herbarium sheets for which the position and outlines of 1036 reproductive structures were annotated manually. We adjusted the hyperparameters of a mask R-CNN (regional convolutional neural network) to this specific task and evaluated the resulting trained models for their ability to count reproductive structures and estimate their size.

RESULTS

The main outcome of our study is that the performance of detection and segmentation can vary significantly with: (i) the type of annotations used for training, (ii) the type of reproductive structures, and (iii) the size of the reproductive structures. In the case of Streptanthus tortuosus, the method can provide quite accurate estimates (77.9% of cases) of the number of reproductive structures, which is better estimated for flowers than for immature fruits and buds. The size estimation results are also encouraging, showing a difference of only a few millimeters between the predicted and actual sizes of buds and flowers.

DISCUSSION

This method has great potential for automating the analysis of reproductive structures in high-resolution images of herbarium sheets. Deeper investigations regarding the taxonomic scalability of this approach and its potential improvement will be conducted in future work.

Generating segmentation masks of herbarium specimens and a data set for training segmentation models using deep learning

PREMISE

Digitized images of herbarium specimens are highly diverse with many potential sources of visual noise and bias. The systematic removal of noise and minimization of bias must be achieved in order to generate biological insights based on the plants rather than the digitization and mounting practices involved. Here, we develop a workflow and data set of high-resolution image masks to segment plant tissues in herbarium specimen images and remove background pixels using deep learning.

METHODS AND RESULTS

We generated 400 curated, high-resolution masks of ferns using a combination of automatic and manual tools for image manipulation. We used those images to train a U-Net-style deep learning model for image segmentation, achieving a final Sørensen-Dice coefficient of 0.96. The resulting model can automatically, efficiently, and accurately segment massive data sets of digitized herbarium specimens, particularly for ferns.

CONCLUSIONS

The application of deep learning in herbarium sciences requires transparent and systematic protocols for generating training data so that these labor-intensive resources can be generalized to other deep learning applications. Segmentation ground-truth masks are hard-won data, and we share these data and the model openly in the hopes of furthering model training and transfer learning opportunities for broader herbarium applications.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

Herbarium records indicate variation in bloom-time sensitivity to temperature across a geographically diverse region

Anthropogenic warming's effects on phenology across environmental and temporal gradients are well recognized. Long-term phenological monitoring data are often limited in duration and geographic scope, but recent efforts to digitize herbaria collections make it possible to reliably reconstruct historic flowering phenology across broad geographic scales and multiple species, lending to an increased understanding of community response to climate change. In this study, we examined collection dates (1901 to 2015) of 8540 flowering specimens from 39 native species in the Pacific Northwest (PNW) region of North America. We hypothesized that flowering phenology would be sensitive to temperature but that sensitivity would vary depending on blooming season and geographic range position. As expected, we found that early-season bloomers are more sensitive to temperature than later-season bloomers. Sensitivity to temperature was significantly greater at low elevations and in the maritime (western) portion of the PNW than at higher elevations and in the eastern interior, respectively. The elevational and longitudinal effects on flowering sensitivity reflect spring "arriving" earlier at low elevations and in the maritime portion of the PNW. These results demonstrate that phenological responses to warming vary substantially across climatically diverse regions, warranting careful and nuanced consideration of climate warming's effects on plant phenology.

A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of Streptanthus tortuosus

PREMISE

Herbarium 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 that DOY accurately 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.

METHODS

Here 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 in PCMs to control for phenological variation among specimens of Streptanthus tortuosus (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit.

RESULTS

Including PI in PCMs increased the model R 2 relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant.

DISCUSSION

Our protocol provides a simple, quantitative phenological metric for any observed plant. Including PI in PCMs increases R 2 and enables predictions of the DOY of any phenophase under any specified climatic conditions.

Spring- and fall-flowering species show diverging phenological responses to climate in the Southeast USA

Plant phenological shifts (e.g., earlier flowering dates) are known consequences of climate change that may alter ecosystem functioning, productivity, and ecological interactions across trophic levels. Temperate, subalpine, and alpine regions have largely experienced advancement of spring phenology with climate warming, but the effects of climate change in warm, humid regions and on autumn phenology are less well understood. In this study, nearly 10,000 digitized herbarium specimen records were used to examine the phenological sensitivities of fall- and spring-flowering asteraceous plants to temperature and precipitation in the US Southeastern Coastal Plain. Climate data reveal warming trends in this already warm climate, and spring- and fall-flowering species responded differently to this change. Spring-flowering species flowered earlier at a rate of 1.8-2.3 days per 1 °C increase in spring temperature, showing remarkable congruence with studies of northern temperate species. Fall-flowering species flowered slightly earlier with warmer spring temperatures, but flowering was significantly later with warmer summer temperatures at a rate of 0.8-1.2 days per 1 °C. Spring-flowering species exhibited slightly later flowering times with increased spring precipitation. Fall phenology was less clearly influenced by precipitation. These results suggest that even warm, humid regions may experience phenological shifts and thus be susceptible to potentially detrimental effects such as plant-pollinator asynchrony.

Temperature controls phenology in continuously flowering Protea species of subtropical Africa

PREMISE OF THE STUDY

Herbarium specimens are increasingly used as records of plant flowering phenology. However, most herbarium-based studies on plant phenology focus on taxa from temperate regions. Here, we explore flowering phenologic responses to climate in the subtropical plant genus Protea (Proteaceae), an iconic group of plants that flower year-round and are endemic to subtropical Africa.

METHODS

We present a novel, circular sliding window approach to investigate phenological patterns developed for species with year-round flowering. We employ our method to evaluate the extent to which site-to-site and year-to-year variation in temperature and precipitation affect flowering dates using a database of 1727 herbarium records of 25 Protea species. We also explore phylogenetic conservatism in flowering phenology.

RESULTS

We show that herbarium data combined with our sliding window approach successfully captured independently reported flowering phenology patterns (r = 0.93). Both warmer sites and warmer years were associated with earlier flowering of 3-5 days/°C, whereas precipitation variation had no significant effect on flowering phenology. Although species vary widely in phenological responsiveness, responses are phylogenetically conserved, with closely related species tending to shift flowering similarly with increasing temperature.

DISCUSSION

Our results point to climate-responsive phenology for this important plant genus and indicate that the subtropical, aseasonally flowering genus Protea has temperature-driven flowering responses that are remarkably similar to those of better-studied northern temperate plant species, suggesting a generality across biomes that has not been described elsewhere.

PhenoForecaster: A software package for the prediction of flowering phenology

PREMISE OF THE STUDY

Predicting the flowering times of angiosperm taxa is a goal of mounting importance in the face of future climate change, with applications not only in plant biology and ecology, but also horticulture, agriculture, and invasive species management. To date, no tool is available to facilitate predictions of flowering phenology using multivariate phenoclimatic models. Such a tool is needed by researchers and other stakeholders who need to predict phenological activity, but are unfamiliar with phenoclimate modeling techniques. PhenoForecaster allows users of any background to conduct species-specific phenological predictions using an intuitive graphical interface and provides an estimate of each prediction's accuracy.

METHODS AND RESULTS

Elastic net regression techniques were used to develop species-specific models capable of predicting the flowering dates of 2320 angiosperm species.

CONCLUSIONS

PhenoForecaster is the first stand-alone package to make phenological modeling directly accessible to users without the need for in-depth phenological observations.

Patterns and biases in an Arctic herbarium specimen collection: Implications for phenological research

PREMISE OF THE STUDY

Herbarium specimens are increasingly used in phenological studies. However, natural history collections can have biases that influence the analysis of phenological events. Arctic environments, where remoteness and cold climate govern collection logistics, may give rise to unique or pronounced biases.

METHODS

We assessed the presence of biases in time, space, phenological events, collectors, taxonomy, and plant traits across Nunavut using herbarium specimens accessioned at the National Herbarium of Canada (CAN).

RESULTS

We found periods of high and low collection that corresponded to societal and institutional events; greater collection density close to common points of air and sea access; and preferences to collect plants at the flowering phase and in peak flower, and to collect particular taxa, flower colours, growth forms, and plant heights. One-quarter of collectors contributed 90% of the collection.

DISCUSSION

Collections influenced by temporal and spatial biases have the potential to misrepresent phenology across space and time, whereas those shaped by the interests of collectors or the tendency to favour particular phenological stages, taxa, and plant traits could give rise to imbalanced phenological comparisons. Underlying collection patterns may vary among regions and institutions. To guide phenological analyses, we recommend routine assessment of any herbarium data set prior to its use.

Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States

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 representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.