Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification.

Caesalpinioideae is the second largest subfamily of legumes (Leguminosae) with ca. 4680 species and 163 genera. It is an ecologically and economically important group formed of mostly woody perennials that range from large canopy emergent trees to functionally herbaceous geoxyles, lianas and shrubs, and which has a global distribution, occurring on every continent except Antarctica. Following the recent re-circumscription of 15 Caesalpinioideae genera as presented in Advances in Legume Systematics 14, Part 1, and using as a basis a phylogenomic analysis of 997 nuclear gene sequences for 420 species and all but five of the genera currently recognised in the subfamily, we present a new higher-level classification for the subfamily. The new classification of Caesalpinioideae comprises eleven tribes, all of which are either new, reinstated or re-circumscribed at this rank: Caesalpinieae Rchb. (27 genera / ca. 223 species), Campsiandreae LPWG (2 / 5-22), Cassieae Bronn (7 / 695), Ceratonieae Rchb. (4 / 6), Dimorphandreae Benth. (4 / 35), Erythrophleeae LPWG (2 /13), Gleditsieae Nakai (3 / 20), Mimoseae Bronn (100 / ca. 3510), Pterogyneae LPWG (1 / 1), Schizolobieae Nakai (8 / 42-43), Sclerolobieae Benth. & Hook. f. (5 / ca. 113). Although many of these lineages have been recognised and named in the past, either as tribes or informal generic groups, their circumscriptions have varied widely and changed over the past decades, such that all the tribes described here differ in generic membership from those previously recognised. Importantly, the approximately 3500 species and 100 genera of the former subfamily Mimosoideae are now placed in the reinstated, but newly circumscribed, tribe Mimoseae. Because of the large size and ecological importance of the tribe, we also provide a clade-based classification system for Mimoseae that includes 17 named lower-level clades. Fourteen of the 100 Mimoseae genera remain unplaced in these lower-level clades: eight are resolved in two grades and six are phylogenetically isolated monogeneric lineages. In addition to the new classification, we provide a key to genera, morphological descriptions and notes for all 163 genera, all tribes, and all named clades. The diversity of growth forms, foliage, flowers and fruits are illustrated for all genera, and for each genus we also provide a distribution map, based on quality-controlled herbarium specimen localities. A glossary for specialised terms used in legume morphology is provided. This new phylogenetically based classification of Caesalpinioideae provides a solid system for communication and a framework for downstream analyses of biogeography, trait evolution and diversification, as well as for taxonomic revision of still understudied genera.

The disambiguation of people names in biological collections.

Scientific collections have been built by people. For hundreds of years, people have collected, studied, identified, preserved, documented and curated collection specimens. Understanding who those people are is of interest to historians, but much more can be made of these data by other stakeholders once they have been linked to the people's identities and their biographies. Knowing who people are helps us attribute work correctly, validate data and understand the scientific contribution of people and institutions. We can evaluate the work they have done, the interests they have, the places they have worked and what they have created from the specimens they have collected. The problem is that all we know about most of the people associated with collections are their names written on specimens. Disambiguating these people is the challenge that this paper addresses. Disambiguation of people often proves difficult in isolation and can result in staff or researchers independently trying to determine the identity of specific individuals over and over again. By sharing biographical data and building an open, collectively maintained dataset with shared knowledge, expertise and resources, it is possible to collectively deduce the identities of individuals, aggregate biographical information for each person, reduce duplication of effort and share the information locally and globally. The authors of this paper aspire to disambiguate all person names efficiently and fully in all their variations across the entirety of the biological sciences, starting with collections. Towards that vision, this paper has three key aims: to improve the linking, validation, enhancement and valorisation of person-related information within and between collections, databases and publications; to suggest good practice for identifying people involved in biological collections; and to promote coordination amongst all stakeholders, including individuals, natural history collections, institutions, learned societies, government agencies and data aggregators.

A botanical demonstration of the potential of linking data using unique identifiers for people.

Natural history collection data available digitally on the web have so far only made limited use of the potential of semantic links among themselves and with cross-disciplinary resources. In a pilot study, botanical collections of the Consortium of European Taxonomic Facilities (CETAF) have therefore begun to semantically annotate their collection data, starting with data on people, and to link them via a central index system. As a result, it is now possible to query data on collectors across different collections and automatically link them to a variety of external resources. The system is being continuously developed and is already in production use in an international collection portal.

People are essential to linking biodiversity data.

People are one of the best known and most stable entities in the biodiversity knowledge graph. The wealth of public information associated with people and the ability to identify them uniquely open up the possibility to make more use of these data in biodiversity science. Person data are almost always associated with entities such as specimens, molecular sequences, taxonomic names, observations, images, traits and publications. For example, the digitization and the aggregation of specimen data from museums and herbaria allow us to view a scientist's specimen collecting in conjunction with the whole corpus of their works. However, the metadata of these entities are also useful in validating data, integrating data across collections and institutional databases and can be the basis of future research into biodiversity and science. In addition, the ability to reliably credit collectors for their work has the potential to change the incentive structure to promote improved curation and maintenance of natural history collections.

A benchmark dataset of herbarium specimen images with label data.

BACKGROUND: More and more herbaria are digitising their collections. Images of specimens are made available online to facilitate access to them and allow extraction of information from them. Transcription of the data written on specimens is critical for general discoverability and enables incorporation into large aggregated research datasets. Different methods, such as crowdsourcing and artificial intelligence, are being developed to optimise transcription, but herbarium specimens pose difficulties in data extraction for many reasons. NEW INFORMATION: To provide developers of transcription methods with a means of optimisation, we have compiled a benchmark dataset of 1,800 herbarium specimen images with corresponding transcribed data. These images originate from nine different collections and include specimens that reflect the multiple potential obstacles that transcription methods may encounter, such as differences in language, text format (printed or handwritten), specimen age and nomenclatural type status. We are making these specimens available with a Creative Commons Zero licence waiver and with permanent online storage of the data. By doing this, we are minimising the obstacles to the use of these images for transcription training. This benchmark dataset of images may also be used where a defined and documented set of herbarium specimens is needed, such as for the extraction of morphological traits, handwriting recognition and colour analysis of specimens.

Digitization protocol for scoring reproductive phenology from herbarium specimens of seed plants.

PREMISE OF THE STUDY: Herbarium specimens provide a robust record of historical plant phenology (the timing of seasonal events such as flowering or fruiting). However, the difficulty of aggregating phenological data from specimens arises from a lack of standardized scoring methods and definitions for phenological states across the collections community. METHODS AND RESULTS: To address this problem, we report on a consensus reached by an iDigBio working group of curators, researchers, and data standards experts regarding an efficient scoring protocol and a data-sharing protocol for reproductive traits available from herbarium specimens of seed plants. The phenological data sets generated can be shared via Darwin Core Archives using the Extended MeasurementOrFact extension. CONCLUSIONS: Our hope is that curators and others interested in collecting phenological trait data from specimens will use the recommendations presented here in current and future scoring efforts. New tools for scoring specimens are reviewed.

The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels.

At the Royal Botanic Garden Edinburgh (RBGE) the use of Optical Character Recognition (OCR) to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add data extracted from the OCR text prior to being sorted based on Collector and/or Country. Using images of the specimens, a team of six digitisers then added data to the specimen records. To investigate whether the data from OCR aid the digitisation process, they completed a series of trials which compared the efficiency of data entry between sorted and unsorted batches of specimens. A survey was carried out to explore the opinion of the digitisation staff to the different sorting options. In total 7,200 specimens were processed. When compared to an unsorted, random set of specimens, those which were sorted based on data added from the OCR were quicker to digitise. Of the methods tested here, the most successful in terms of efficiency used a protocol which required entering data into a limited set of fields and where the records were filtered by Collector and Country. The survey and subsequent discussions with the digitisation staff highlighted their preference for working with sorted specimens, in which label layout, locations and handwriting are likely to be similar, and so a familiarity with the Collector or Country is rapidly established.

Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach.

Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow.The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow.

Big hitting collectors make massive and disproportionate contribution to the discovery of plant species.

Discovering biological diversity is a fundamental goal--made urgent by the alarmingly high rate of extinction. We have compiled information from more than 100,000 type specimens to quantify the role of collectors in the discovery of plant diversity. Our results show that more than half of all type specimens were collected by less than 2 per cent of collectors. This highly skewed pattern has persisted through time. We demonstrate that a number of attributes are associated with prolific plant collectors: a long career with increasing productivity and experience in several countries and plant families. These results imply that funding a small number of expert plant collectors in the right geographical locations should be an important element in any effective strategy to find undiscovered plant species and complete the inventory of the world flora.

A phylogenetic reappraisal of the Peltophorum group (Caesalpinieae: Leguminosae) based on the chloroplast trnL-F, rbcL and rps16 sequence data.

The monophyly of the Peltophorum group, one of nine informal groups recognized by Polhill in the Caesalpinieae, was tested using sequence data from the trnL-F, rbcL, and rps16 regions of the chloroplast genome. Exemplars were included from all 16 genera of the Peltophorum group, and from 15 genera representing seven of the other eight informal groups in the tribe. The data were analyzed separately and in combined analyses using parsimony and Bayesian methods. The analysis method had little effect on the topology of well-supported relationships. The molecular data recovered a generally well-supported phylogeny with many intergeneric relationships resolved. Results show that the Peltophorum group as currently delimited is polyphyletic, but that eight genera plus one undescribed genus form a core Peltophorum group, which is referred to here as the Peltophorum group sensu stricto. These genera are Bussea, Conzattia, Colvillea, Delonix, Heteroflorum (inedit.), Lemuropisum, Parkinsonia, Peltophorum, and Schizolobium. The remaining eight genera of the Peltophorum group s.l. are distributed across the Caesalpinieae. Morphological support for the redelimited Peltophorum group and the other recovered clades was assessed, and no unique synapomorphy was found for the Peltophorum group s.s. A proposal for the reclassification of the Peltophorum group s.l. is presented.