Applying the concept of niche breadth to understand urban tree mortality in the UK.

Accelerated climate change has raised concerns about heightened vulnerability of urban trees, spurring the need to reevaluate their suitability. The urgency has also driven the widespread application of climatic niche-based models. In particular, the concept of niche breadth (NB), the range of environmental conditions that species can tolerate, is commonly estimated based on species occurrence data over the selected geographic range to predict species response to changing conditions. However, in urban environments where many species are cultivated out of the NB of their natural distributions, additional empirical evidence beyond presence and absence is needed not only to test the true tolerance limits but also to evaluate species' adaptive capacity to future climate. In this research, mortality trends of Acer and Quercus species spanning a 21-year period (2000-2021) from tree inventories of three major UK botanic gardens - the Royal Botanic Gardens, Kew (KEW), Westonbirt, the National Arboretum (WESB), and the Royal Botanic Garden Edinburgh (RBGE) - were analyzed in relation to their NB under long-term drought stress. As a result, Acer species were more responsive to drought and heat stress. For Acer, positioning below the lower limits of the precipitation of warmest quarter led to an increase in the probability of annual mortality by 1.2 and 1.3 % at KEW and RBGE respectively. In addition, the mean cumulative mortality rate increased corresponding to an increase in the number of niche positions below the lower limits of the selected bioclimatic variables. On the other hand, Quercus species in general exhibited comparable resilience regardless of their niche positions. Moreover, Mediterranean oaks were most tolerant, with cumulative mortality rates that were lower than those of native oaks in the UK. These findings further highlight the importance of incorporating ecological performance and recognizing species-specific adaptive strategies in climatic niche modeling.

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.

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.