Evaluating the definition and distribution of spring ephemeral wildflowers in eastern North America

PREMISE

The herbaceous layer accounts for the majority of plant biodiversity in eastern North American forests, encompassing substantial variation in life history strategy and function. One group of early-season herbaceous understory species, colloquially referred to as spring ephemeral wildflowers, are ecologically and culturally important, but little is known about the prevalence and biogeographic patterns of the spring ephemeral strategy.

METHODS

We used observations collected by the Global Biodiversity Information Facility (GBIF) to quantify the ephemerality of 559 understory forb species across eastern North America and classify them according to a continuous ephemerality index (ranging from 0 = never ephemeral to 1 = always ephemeral). We then used this information to model where ephemeral forbs were most common across the landscape with the goal of identifying geographic and environmental drivers important to their distributions and ranges.

RESULTS

Only 3.4% of all understory wildflower species were spring ephemerals in all parts of their range, and 18.4% (103 species) were ephemeral in at least part of their range. Spring ephemerals peaked in absolute species richness and relative proportion at mid latitudes.

CONCLUSIONS

Spring ephemeral phenology is an important shade-avoidance strategy for a large segment of the total understory species in temperate deciduous forests. In North America, the strategy is relatively most important for forest understories at mid latitudes. The definitions of spring ephemerality we provide here serve as an important ecological context for conservation priorities and to evaluate responses of this biodiverse group to future environmental change.

Herbarium specimens reveal century-long trait shifts in poison ivy due to anthropogenic CO2 emissions

PREMISE

Previous experimental studies have shown that poison ivy (Toxicodendron radicans; Anacardicaceae) responds to elevated CO2 with increased leaf production, water-use efficiency, and toxicity (allergenic urushiol). However, long-term field data suggest no increase in poison ivy abundance over time. Using herbarium specimens, we examined whether poison ivy and other species shifted leaf traits under natural conditions with increasing atmospheric CO2 (pCO2 ) over the past century.

METHODS

We measured stomatal density, leaf area, leaf N, leaf C:N, leaf carbon isotope discrimination (Δleaf ), and intrinsic water-use efficiency (iWUE) from 327 specimens collected from 1838 to 2020 across Pennsylvania. We compared poison ivy's responses to two evolutionarily related tree species, Toxicodendron vernix and Rhus typhina (Anacardiacae) and one ecological analog, Parthenocissus quinquefolia (Vitaceae), a common co-occurring liana.

RESULTS

Stomatal density significantly decreased (P < 0.05) in poison ivy and the ecologically similar liana P. quinquefolia over the past century, but did not change in the related trees T. vernix and R. typhina. None of these species showed significant trends in changes in leaf N or C:N. Surprisingly, in poison ivy, but not the other species, Δleaf increased with increased pCO2 , corresponding to significant declines in iWUE over time.

CONCLUSIONS

In contrast to the results of short-term experimental studies, iWUE decreased in poison ivy over the last century. Trait responses to pCO2 varied by species. Herbarium specimens suggest that realized long-term plant physiological responses to increased CO2 may not be reflected in short-term experimental growth studies, highlighting the value of collections.

Fast but steady: An integrated leaf-stem-root trait syndrome for woody forest invaders

Successful control and prevention of biological invasions depend on identifying traits of non-native species that promote fitness advantages in competition with native species. Here, we show that, among 76 native and non-native woody plants of deciduous forests of North America, invaders express a unique functional syndrome that combines high metabolic rate with robust leaves of longer lifespan and a greater duration of annual carbon gain, behaviours enabled by seasonally plastic xylem structure and rapid production of thin roots. This trait combination was absent in all native species examined and suggests the success of forest invaders is driven by a novel resource-use strategy. Furthermore, two traits alone-annual leaf duration and nuclear DNA content-separated native and invasive species with 93% accuracy, supporting the use of functional traits in invader risk assessments. A trait syndrome reflecting both fast growth capacity and understorey persistence may be a key driver of forest invasions.

Using Convolutional Neural Networks to Efficiently Extract Immense Phenological Data From Community Science Images

Community science image libraries offer a massive, but largely untapped, source of observational data for phenological research. The iNaturalist platform offers a particularly rich archive, containing more than 49 million verifiable, georeferenced, open access images, encompassing seven continents and over 278,000 species. A critical limitation preventing scientists from taking full advantage of this rich data source is labor. Each image must be manually inspected and categorized by phenophase, which is both time-intensive and costly. Consequently, researchers may only be able to use a subset of the total number of images available in the database. While iNaturalist has the potential to yield enough data for high-resolution and spatially extensive studies, it requires more efficient tools for phenological data extraction. A promising solution is automation of the image annotation process using deep learning. Recent innovations in deep learning have made these open-source tools accessible to a general research audience. However, it is unknown whether deep learning tools can accurately and efficiently annotate phenophases in community science images. Here, we train a convolutional neural network (CNN) to annotate images of Alliaria petiolata into distinct phenophases from iNaturalist and compare the performance of the model with non-expert human annotators. We demonstrate that researchers can successfully employ deep learning techniques to extract phenological information from community science images. A CNN classified two-stage phenology (flowering and non-flowering) with 95.9% accuracy and classified four-stage phenology (vegetative, budding, flowering, and fruiting) with 86.4% accuracy. The overall accuracy of the CNN did not differ from humans (p = 0.383), although performance varied across phenophases. We found that a primary challenge of using deep learning for image annotation was not related to the model itself, but instead in the quality of the community science images. Up to 4% of A. petiolata images in iNaturalist were taken from an improper distance, were physically manipulated, or were digitally altered, which limited both human and machine annotators in accurately classifying phenology. Thus, we provide a list of photography guidelines that could be included in community science platforms to inform community scientists in the best practices for creating images that facilitate phenological analysis.

Macrophenology: insights into the broad-scale patterns, drivers, and consequences of phenology

Plant phenology research has surged in recent decades, in part due to interest in phenological sensitivity to climate change and the vital role phenology plays in ecology. Many local-scale studies have generated important findings regarding the physiology, responses, and risks associated with shifts in plant phenology. By comparison, our understanding of regional- and global-scale phenology has been largely limited to remote sensing of green-up without the ability to differentiate among plant species. However, a new generation of analytical tools and data sources-including enhanced remote sensing products, digitized herbarium specimen data, and public participation in science-now permits investigating patterns and drivers of phenology across extensive taxonomic, temporal, and spatial scales, in an emerging field that we call macrophenology. Recent studies have highlighted how phenology affects dynamics at broad scales, including species interactions and ranges, carbon fluxes, and climate. At the cusp of this developing field of study, we review the theoretical and practical advances in four primary areas of plant macrophenology: (1) global patterns and shifts in plant phenology, (2) within-species changes in phenology as they mediate species' range limits and invasions at the regional scale, (3) broad-scale variation in phenology among species leading to ecological mismatches, and (4) interactions between phenology and global ecosystem processes. To stimulate future research, we describe opportunities for macrophenology to address grand challenges in each of these research areas, as well as recently available data sources that enhance and enable macrophenology research.

Data integration enables global biodiversity synthesis

The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world's largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

Global Change Biology: Museum Specimens Are More Than Meet the Eye

Dead museum specimens are finding new life, providing critical data about otherwise hidden impacts of human-caused environmental change. New research powerfully leverages decades of plant collections to uncover global responses in floral pigmentation linked to ozone and climate change.

Herbarium-based measurements reliably estimate three functional traits

PREMISE

The use of functional traits has surged in recent decades, providing new insights ranging from individual plant fitness to ecosystem processes. Global plant trait databases have advanced our understanding of plant functional diversity, but they remain incomplete because of geographic and taxonomic biases. Herbarium specimens may help fill these gaps by providing trait information across space and time. We tested whether herbarium specimen-derived measurements are reliable estimates of three important, commonly measured functional traits-specific leaf area (SLA), branch wood specific gravity, and leaf thickness.

METHODS

Leaves and branches were collected from species cultivated at Fairchild Tropical Botanic Garden and Florida International University in Miami, FL, USA. Fresh components of SLA (area), branch wood specific gravity (volume), and leaf thickness were measured following standard trait measurement protocols. We compared these trait values to corresponding measurements using plant tissues dried in a plant press following standard herbarium plant collecting protocols.

RESULTS

Herbarium-derived trait measurements (dried tissues) were highly correlated with those measured using fresh tissues following standard protocols (SLA: R² = 0.72-0.97, p < 0.01; wood specific gravity: R² = 0.74-0.75, p < 0.01; leaf thickness: R² = 0.96, p < 0.01). However, except for leaf thickness, linear model slope or intercept coefficients differed from 1, indicating herbarium-derived trait measurements may provide biased estimates of fresh traits without the use of correction factors.

CONCLUSIONS

Herbarium-derived traits cannot always be used interchangeably with those measured from fresh tissues because of tissue shrinkage. However, herbarium-derived trait data still have the potential to drastically expand the temporal, geographic, and taxonomic scope of global trait databases.

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.

Digitization and the Future of Natural History Collections

Natural history collections (NHCs) are the foundation of historical baselines for assessing anthropogenic impacts on biodiversity. Along these lines, the online mobilization of specimens via digitization—the conversion of specimen data into accessible digital content—has greatly expanded the use of NHC collections across a diversity of disciplines. We broaden the current vision of digitization (Digitization 1.0)—whereby specimens are digitized within NHCs—to include new approaches that rely on digitized products rather than the physical specimen (Digitization 2.0). Digitization 2.0 builds on the data, workflows, and infrastructure produced by Digitization 1.0 to create digital-only workflows that facilitate digitization, curation, and data links, thus returning value to physical specimens by creating new layers of annotation, empowering a global community, and developing automated approaches to advance biodiversity discovery and conservation. These efforts will transform large-scale biodiversity assessments to address fundamental questions including those pertaining to critical issues of global change.

The Changing Uses of Herbarium Data in an Era of Global Change: An Overview Using Automated Content Analysis

Widespread specimen digitization has greatly enhanced the use of herbarium data in scientific research. Publications using herbarium data have increased exponentially over the last century. Here, we review changing uses of herbaria through time with a computational text analysis of 13,702 articles from 1923 to 2017 that quantitatively complements traditional review approaches. Although maintaining its core contribution to taxonomic knowledge, herbarium use has diversified from a few dominant research topics a century ago (e.g., taxonomic notes, botanical history, local observations), with many topics only recently emerging (e.g., biodiversity informatics, global change biology, DNA analyses). Specimens are now appreciated as temporally and spatially extensive sources of genotypic, phenotypic, and biogeographic data. Specimens are increasingly used in ways that influence our ability to steward future biodiversity. As we enter the Anthropocene, herbaria have likewise entered a new era with enhanced scientific, educational, and societal relevance.

Utilizing herbarium specimens to quantify historical mycorrhizal communities

PREMISE OF THE STUDY

Mycorrhiza are critical to ecosystem functioning, but a lack of historical baseline data limits our understanding of the long-term belowground effects of global change. Herbarium specimens may provide this needed insight. However, it is unknown whether DNA of arbuscular mycorrhizal fungi (AMF) can be reliably extracted from vascular plant specimen roots.

METHODS

We sampled roots from herbarium specimens of four herbaceous forest species collected in western Pennsylvania between 1881-2008. Using molecular methods (terminal restriction fragment length polymorphism and sequence analysis), we quantified AMF communities from specimen roots and tested for contamination.

RESULTS

We successfully amplified AMF DNA from 44% (21/48) of the root but not leaf samples, indicating specimen contamination was negligible. As expected, there were significant differences in AMF composition between plant species (P < 0.05). However, no differences in AMF communities were detected through time, possibly due to limited sample size and low amplification rates in recent collections.

DISCUSSION

Herbaria have potential as sources of valuable belowground microbial data to answer questions across geographic, temporal, and taxonomic scales otherwise not feasible. Ongoing methodological developments will only magnify this potential. Further tests are needed to determine curatorial practices that maximize this innovative use of herbarium specimens.

Carbon gain phenologies of spring-flowering perennials in a deciduous forest indicate a novel niche for a widespread invader

Strategies of herbaceous species in deciduous forests are often characterized by the timing of life history phases (e.g. emergence, flowering, leaf senescence) relative to overstory tree canopy closure. Although springtime photosynthesis is assumed to account for the majority of their annual carbon budgets, the 12-month photosynthetic trajectories of forest herbs have not been quantified. We measured the temporal dynamics of carbon assimilation for seven native herbaceous perennials and the biennial Alliaria petiolata, a widespread invader in eastern North American forests. We assessed the relative importance of spring, summer, and autumn to species-level annual carbon budgets. Spring-emerging species showed significant variation in carbon assimilation patterns. High spring irradiance before canopy closure accounted for 39-100% of species-level annual carbon assimilation, but summer and autumn accounted for large proportions of some species' carbon budgets (up to 58% and 19%, respectively). Alliaria was phenologically unique, taking advantage both autumn and spring irradiance. Although spring-emerging understory species are often expected to rely on early-season irradiance, our results highlight interspecific differences and the importance of mid-late season carbon gain. Phenological strategies of forest herbs are a continuum rather than discrete categories, and invasive species may follow strategies that are underrepresented in the native flora.

iNaturalist as a tool to expand the research value of museum specimens

PREMISE OF THE STUDY

Innovative approaches to specimen collection and curation are needed to maximize the utility of natural history collections in a new era of data use. Associated data, such as digital images from the field, are routinely collected with recent herbarium specimens. However, these data often remain inaccessible and are rarely curated alongside the associated physical specimens, which limits future data use.

METHODS AND RESULTS

We leveraged the widely used citizen science platform, iNaturalist, to permanently associate field-collected data to herbarium specimens, including information not well preserved in traditional specimens. This protocol improves the efficiency and accuracy of all steps from the collecting event to specimen curation and enhances the potential uses of specimens.

CONCLUSIONS

iNaturalist provides a standardized and cost-efficient enhancement to specimen collection and curation that can be easily adapted for specific research goals or other collection types beyond herbaria.

Effects of deer on the photosynthetic performance of invasive and native forest herbs

Overabundant generalist herbivores can facilitate non-native plant invasions, presumably through direct and indirect modifications to the environment that affect plant performance. However, ecophysiological mechanisms behind ungulate-mediated plant invasions have not been well-studied. At a long-term Odocoileus virginianus (white-tailed deer) exclusion site in a temperate deciduous forest, we quantified deer-mediated ecophysiological impacts on an invasive biennial Alliaria petiolata (garlic mustard) and two palatable native herbaceous perennials, Maianthemum racemosum and Trillium grandiflorum. In mid-summer, we found that leaf-level light availability was higher in unfenced areas compared with areas fenced to exclude deer. Alliaria in unfenced areas exhibited 50 % higher mean maximum photosynthetic rates compared with fenced areas. Further, specific leaf area decreased by 48 % on average in unfenced areas, suggesting leaf structural responses to higher light levels. Similarly, Maianthemum had 42 % higher mean photosynthetic rates and 33 % decreased mean specific leaf area in unfenced areas, but these functional advantages were likely countered by high rates of deer herbivory. By contrast, Trillium exhibited significantly lower (26 %) maximum photosynthetic rates in unfenced areas, but SLA did not differ. Deer-mediated differences in light saturated photosynthetic rates for all three species were only significant during months with overstory tree canopy cover, when light availability in the herb layer was significantly lower in fenced areas. Alliaria's enhanced photosynthetic rates implicate overabundant deer, a situation that is nearly ubiquitous across its invaded range. Collectively, our results provide empirical evidence that generalist herbivores can alter non-native plant physiology to facilitate invasion.

Invaders do not require high resource levels to maintain physiological advantages in a temperate deciduous forest

Non-native, invasive plants are commonly typified by trait strategies associated with high resource demands and plant invasions are often thought to be dependent upon site resource availability or disturbance. However, the invasion of shade-tolerant woody species into deciduous forests of the Eastern United States seems to contradict such generalization, as growth in this ecosystem is strongly constrained by light and, secondarily, nutrient stress. In a factorial manipulation of light and soil nitrogen availability, we established an experimental resource gradient in a secondary deciduous forest to test whether three common, woody, invasive species displayed increased metabolic performance and biomass production compared to six co-occurring woody native species, and whether these predicted differences depend upon resource supply. Using hierarchical Bayesian models of photosynthesis that included leaf trait effects, we found that invasive species exhibited functional strategies associated with higher rates of carbon gain. Further, invader metabolic and growth-related attributes were more responsive to increasing light availability than those of natives, but did not fall below average native responses even in low light. Surprisingly, neither group showed direct trait or growth responses to soil N additions. However, invasive species showed increased photosynthetic nitrogen use efficiencies with decreasing N availability, while that of natives remained constant. Although invader advantage over natives was amplified in higher resource conditions in this forest, our results indicate that some invasive species can maintain physiological advantages over co-occurring natives regardless of resource conditions.

Resource-use strategies of native and invasive plants in Eastern North American forests

Studies in disturbed, resource-rich environments often show that invasive plants are more productive than co-occurring natives, but with similar physiological tradeoffs. However, in resource-limited habitats, it is unclear whether native and invasive plants have similar metabolic constraints or if invasive plants are more productive per unit resource cost - that is, use resources more efficiently. Using a common garden to control for environment, we compared leaf physiological traits relating to resource investments, carbon returns, and resource-use efficiencies in 14 native and 18 nonnative invasive species of common genera found in Eastern North American (ENA) deciduous forest understories, where growth is constrained by light and nutrient limitation. Despite greater leaf construction and nitrogen costs, invaders exhibited greater instantaneous photosynthetic energy-use efficiency (PEUE) and marginally greater photosynthetic nitrogen-use efficiency (PNUE). When integrated over leaf lifespan (LL), these differences were magnified. Differences in efficiency were driven by greater productivity per unit leaf investment, as invaders exhibited both greater photosynthetic abilities and longer LL. Our results indicate that woody understory invaders in ENA forests are not constrained to the same degree by leaf-based metabolic tradeoffs as the native understory flora. These strategy differences could be attributable to pre-adaptation in the native range, although other explanations are possible.