Schrödinger's phenotypes: Herbarium specimens show two‐dimensional images are both good and (not so) bad sources of morphological data

Herbarium specimens reveal links between Capsella bursa-pastoris leaf shape and climate

Studies into the evolution and development of leaf shape have connected variation in plant form, function, and fitness. For species with consistent leaf margin features, patterns in leaf architecture are related to both biotic and abiotic factors. However, for species with inconsistent leaf margin features, quantifying leaf shape variation and the effects of environmental factors on leaf shape has proven challenging. To investigate leaf shape variation in species with inconsistent shapes, we analyzed approximately 500 digitized Capsella bursa-pastoris specimens collected throughout the continental U.S. over a 100-year period with geometric morphometric modeling and deterministic techniques. We generated a morphospace of C. bursa-pastoris leaf shapes and modeled leaf shape as a function of environment and time. Our results suggest C. bursa-pastoris leaf shape variation is strongly associated with temperature over the C. bursa-pastoris growing season, with lobing decreasing as temperature increases. While we expected to see changes in variation over time, our results show that level of leaf shape variation is consistent over the 100-year period. Our findings showed that species with inconsistent leaf shape variation can be quantified using geometric morphometric modeling techniques and that temperature is the main environmental factor influencing leaf shape variation.

Floral Diversity and Pollination Syndromes in Agave subgenus Manfreda

The genus Agave is an ecological keystone of American deserts and both culturally and economically important in Mexico. Agave is a large genus of about 250 species. The radiation of Agave is marked by an initial adaptation to desert environments and then a secondary diversification of species associated with pollinator groups, such as hummingbirds and nocturnal moths. Phylogenetic analyses place Agave subgenus Manfreda, or the "herbaceous agaves," in a monophyletic clade that likely evolved in part as an adaptation to novel pollination vectors. Here, we present a morphological and observational study assessing the evolution of floral form in response to pollinator specialization within this understudied group. We found significant visitation by hummingbirds and nocturnal moths to several species within the Agave subgenus Manfreda. These observations also align with our morphological analyses of floral organs and support the evolution of distinct pollination syndromes. We found that not all floral morphology is consistent within a pollination syndrome, suggesting hidden diversity in the evolution of floral phenotypes in Agave. We also characterize the morphological variation between herbarium and live specimens, demonstrating that special consideration needs to be made when combining these types of data. This work identifies the potential for studying the functional evolution of diverse floral forms within Agave and demonstrates the need to further explore ecological and evolutionary relationships to understand pollinator influence on diversification in the genus.

Quantifying error in occurrence data: Comparing the data quality of iNaturalist and digitized herbarium specimen data in flowering plant families of the southeastern United States

iNaturalist has the potential to be an extremely rich source of organismal occurrence data. Launched in 2008, it now contains over 150 million uploaded observations as of May 2023. Based on the findings of a limited number of past studies assessing the taxonomic accuracy of participatory science-driven sources of occurrence data such as iNaturalist, there has been concern that some portion of these records might be misidentified in certain taxonomic groups. In this case study, we compare Research Grade iNaturalist observations with digitized herbarium specimens, both of which are currently available for combined download from large data aggregators and are therefore the primary sources of occurrence data for large-scale biodiversity/biogeography studies. Our comparisons were confined regionally to the southeastern United States (Florida, Georgia, North Carolina, South Carolina, Texas, Tennessee, Kentucky, and Virginia). Occurrence records from ten plant families (Gentianaceae, Ericaceae, Melanthiaceae, Ulmaceae, Fabaceae, Asteraceae, Fagaceae, Cyperaceae, Juglandaceae, Apocynaceae) were downloaded and scored on taxonomic accuracy. We found a comparable and relatively low rate of misidentification among both digitized herbarium specimens and Research Grade iNaturalist observations within the study area. This finding illustrates the utility and high quality of iNaturalist data for future research in the region, but also points to key differences between data types, giving each a respective advantage, depending on applications of the data.

From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2

Premise

Quantitative plant traits play a crucial role in biological research. However, traditional methods for measuring plant morphology are time consuming and have limited scalability. We present LeafMachine2, a suite of modular machine learning and computer vision tools that can automatically extract a base set of leaf traits from digital plant data sets.

Methods

LeafMachine2 was trained on 494,766 manually prepared annotations from 5648 herbarium images obtained from 288 institutions and representing 2663 species; it employs a set of plant component detection and segmentation algorithms to isolate individual leaves, petioles, fruits, flowers, wood samples, buds, and roots. Our landmarking network automatically identifies and measures nine pseudo-landmarks that occur on most broadleaf taxa. Text labels and barcodes are automatically identified by an archival component detector and are prepared for optical character recognition methods or natural language processing algorithms.

Results

LeafMachine2 can extract trait data from at least 245 angiosperm families and calculate pixel-to-metric conversion factors for 26 commonly used ruler types.

Discussion

LeafMachine2 is a highly efficient tool for generating large quantities of plant trait data, even from occluded or overlapping leaves, field images, and non-archival data sets. Our project, along with similar initiatives, has made significant progress in removing the bottleneck in plant trait data acquisition from herbarium specimens and shifted the focus toward the crucial task of data revision and quality control.

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery

This study provides an accurate and efficient method to reconstruct detailed and high-resolution digital 3D models of carpological materials by photogrammetric method, in which only about 100 to 150 images are required for each model reconstruction. The 3D models reflect the realistic morphology and genuine color of the carpological materials. The 3D models are scaled to represent the true size of the materials even as small as 3 mm in diameter. The interfaces are interactive, in which the 3D models can be rotated in 360° to observe the structures and be zoomed to inspect the macroscopic details. This new platform is beneficial for developing a virtual herbarium of carpological collection which is thus the most important to botanical authentication and education.

Digitized collections elucidate invasion history and patterns of awn polymorphism in Microstegium vimineum

PREMISE

Digitized collections can help illuminate the mechanisms behind the establishment and spread of invasive plants. These databases provide a record of traits in space and time that allows for investigation of abiotic and biotic factors that influence invasive species.

METHODS

Over 1100 digitized herbarium records were examined to investigate the invasion history and trait variation of Microstegium vimineum. Presence-absence of awns was investigated to quantify geographic patterns of this polymorphic trait, which serves several functions in grasses, including diaspore burial and dispersal to germination sites. Floret traits were further quantified, and genomic analyses of contemporary samples were conducted to investigate the history of M. vimineum's introduction and spread into North America.

RESULTS

Herbarium records revealed similar patterns of awn polymorphism in native and invaded ranges of M. vimineum, with awned forms predominating at higher latitudes and awnless forms at lower latitudes. Herbarium records and genomic data suggested initial introduction and spread of the awnless form in the southeastern United States, followed by a putative secondary invasion and spread of the awned form from eastern Pennsylvania. Awned forms have longer florets, and floret size varies significantly with latitude. There is evidence of a transition zone with short-awned specimens at mid-latitudes. Genomic analyses revealed two distinct clusters corresponding to awnless and awned forms, with evidence of admixture.

CONCLUSIONS

Our results demonstrate the power of herbarium data to elucidate the invasion history of a problematic weed in North America and, together with genomic data, reveal a possible key trait in introduction success: presence or absence of an awn.

Digital morphometrics: Application of MorphoLeaf in shape visualization and species delimitation, using Cucurbitaceae leaves as a model

PREMISE

Plant leaves are one of the most important organs for plant identification due to their variability across different taxonomic groups. While traditional morphometrics has contributed tremendously to reducing the problems accompanying plant identification and morphology-based species delimitation, image-analysis digital solutions have made it easy to detect more characters to complement existing leaf data sets.

METHODS

Here, we apply MorphoLeaf to generate a morphometric data set from 140 leaf specimens of seven Cucurbitaceae species via landmark extraction, the reparameterization of leaf contours, and data quantification and normalization. A statistical analysis was performed on the resulting data set.

RESULTS

A principal component analysis revealed that leaf blade area, blade perimeter, tooth area, tooth perimeter, the measure of the distance from tooth position to the tip, and the measure of the distance from tooth position to the base are important and informative landmarks that contribute to the variation within the species studied.

DISCUSSION

MorphoLeaf can be applied to quantitatively track leaf diversity, thereby functionally integrating morphometrics and shape visualization into the digital identification of plants. The success of digital morphometrics in leaf outline analyses presents researchers with opportunities to carry out more accurate image-based research in areas such as plant development, evolution, and phenotyping.

Automated Extraction of Phenotypic Leaf Traits of Individual Intact Herbarium Leaves from Herbarium Specimen Images Using Deep Learning Based Semantic Segmentation

With the increase in the digitization efforts of herbarium collections worldwide, dataset repositories such as iDigBio and GBIF now have hundreds of thousands of herbarium sheet images ready for exploration. Although this serves as a new source of plant leaves data, herbarium datasets have an inherent challenge to deal with the sheets containing other non-plant objects such as color charts, barcodes, and labels. Even for the plant part itself, a combination of different overlapping, damaged, and intact individual leaves exist together with other plant organs such as stems and fruits, which increases the complexity of leaf trait extraction and analysis. Focusing on segmentation and trait extraction on individual intact herbarium leaves, this study proposes a pipeline consisting of deep learning semantic segmentation model (DeepLabv3+), connected component analysis, and a single-leaf classifier trained on binary images to automate the extraction of an intact individual leaf with phenotypic traits. The proposed method achieved a higher F1-score for both the in-house dataset (96%) and on a publicly available herbarium dataset (93%) compared to object detection-based approaches including Faster R-CNN and YOLOv5. Furthermore, using the proposed approach, the phenotypic measurements extracted from the segmented individual leaves were closer to the ground truth measurements, which suggests the importance of the segmentation process in handling background noise. Compared to the object detection-based approaches, the proposed method showed a promising direction toward an autonomous tool for the extraction of individual leaves together with their trait data directly from herbarium specimen images.

Citizen science and online data: Opportunities and challenges for snake ecology and action against snakebite

The secretive behavior and life history of snakes makes studying their biology, distribution, and the epidemiology of venomous snakebite challenging. One of the most useful, most versatile, and easiest to collect types of biological data are photographs, particularly those that are connected with geographic location and date-time metadata. Photos verify occurrence records, provide data on phenotypes and ecology, and are often used to illustrate new species descriptions, field guides and identification keys, as well as in training humans and computer vision algorithms to identify snakes. We scoured eleven online and two offline sources of snake photos in an attempt to collect as many photos of as many snake species as possible, and attempt to explain some of the inter-species variation in photograph quantity among global regions and taxonomic groups, and with regard to medical importance, human population density, and range size. We collected a total of 725,565 photos-between 1 and 48,696 photos of 3098 of the world's 3879 snake species (79.9%), leaving 781 "most wanted" species with no photos (20.1% of all currently-described species as of the December 2020 release of The Reptile Database). We provide a list of most wanted species sortable by family, continent, authority, and medical importance, and encourage snake photographers worldwide to submit photos and associated metadata, particularly of "missing" species, to the most permanent and useful online archives: The Reptile Database, iNaturalist, and HerpMapper.

Reversing extinction trends: new uses of (old) herbarium specimens to accelerate conservation action on threatened species

Although often not collected specifically for the purposes of conservation, herbarium specimens offer sufficient information to reconstruct parameters that are needed to designate a species as 'at-risk' of extinction. While such designations should prompt quick and efficient legal action towards species recovery, such action often lags far behind and is mired in bureaucratic procedure. The increase in online digitization of natural history collections has now led to a surge in the number new studies on the uses of machine learning. These repositories of species occurrences are now equipped with advances that allow for the identification of rare species. The increase in attention devoted to estimating the scope and severity of the threats that lead to the decline of such species will increase our ability to mitigate these threats and reverse the declines, overcoming a current barrier to the recovery of many threatened plant species. Thus far, collected specimens have been used to fill gaps in systematics, range extent, and past genetic diversity. We find that they also offer material with which it is possible to foster species recovery, ecosystem restoration, and de-extinction, and these elements should be used in conjunction with machine learning and citizen science initiatives to mobilize as large a force as possible to counter current extinction trends.

MycoNews 2020: President's message, news, reports, awards, personalia, book news, and correspondence

This second annual edition of MycoNews starts with a message from IMA President Wieland Meyer regarding the steps being taken to legally incorporate the Association in Switzerland. News is provided on progress in the arrangements for IMC12 (Amsterdam 2022), release of the State of World’s Plants and Fungi report, mycology under the Coronavirus pandemic, and two new biodiversity initiatives in The Netherlands. Reports are presented from the: 1st International Symposium on Tropical African Mycology (Benin 2019); Recent Advances in the Biodiversity, Biology, and Biotechnology of Fungi (Pondicherry 2019); the 4th International Malassezia Workshop (virtual 2020); Dutch Design Week (2020), and UK Fungus Day (2020). An honour awarded to Francis Martin is recorded. Birthday greetings from IMA go to John Walker, José Dianese, Richard Harris, Tomasz Majewski, David Malloch, and John Sheard. Tributes are paid to the passing of John Peberdy, Anthony Trinci, and Balamuri Vittal. This contribution continues with news of 10 new mycological books published in 2019 or 2020 and concludes with a letter on the appropriateness of adopting the term ‘Funga’.