Welcome to The Natural History Museum repository
The Natural History Museum is an international leader in the study of the natural world. Our science describes the diversity of nature, promotes an understanding of its past, and supports the anticipation and management of the impact of human activity on the environment.
The Museum's repository provides free access to publications produced by more than 300 scientists working here. Researchers at the Museum study a diverse range of issues, including threats to Earth's biodiversity, the maintenance of delicate ecosystems, environmental pollution and disease. The accessible repository showcases this broad research output.
The repository was launched in 2016 with an initially modest number of journal publications in its database. It now includes book chapters and blogs from Museum scientists.
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A Novel Automated Mass Digitisation Workflow for Natural History Microscope SlidesThe Natural History Museum, London (NHM) has embarked on an ambitious programme to digitise its collections. One aim of the programme has been to improve the workflows and infrastructure needed to support high-throughput digitisation and create comprehensive digital inventories of large scientific collections. This paper presents the workflow developed to digitise the entire Phthiraptera (parasitic lice) microscope slide collection (70,663 slides). Here we describe a novel process of semi-automated mass digitisation using both temporary and permanent barcode labels applied before and during slide imaging. By using a series of barcodes encoding information associated with each slide (i.e. unique identifier, location in the collection and taxonomic name), we can run a series of automated processes, including file renaming, image processing and bulk import into the NHM’s collection management system. We provide data on the comparative efficiency of these processes, illustrating how simple activities, like automated file renaming, reduces image post-processing time, minimises human error and can be applied across multiple collection types.
Species‐level image classification with convolutional neural network enables insect identification from habitus images1. Changes in insect biomass, abundance, and diversity are challenging to track at sufficient spatial, temporal, and taxonomic resolution. Camera traps can capture habitus images of ground-dwelling insects. However, currently sampling involves manually detecting and identifying specimens. Here, we test whether a convolutional neural network (CNN) can classify habitus images of ground beetles to species level, and estimate how correct classification relates to body size, number of species inside genera, and species identity. 2. We created an image database of 65,841 museum specimens comprising 361 carabid beetle species from the British Isles and fine-tuned the parameters of a pretrained CNN from a training dataset. By summing up class confidence values within genus, tribe, and subfamily and setting a confidence threshold, we trade-off between classification accuracy, precision, and recall and taxonomic resolution. 3. The CNN classified 51.9% of 19,164 test images correctly to species level and 74.9% to genus level. Average classification recall on species level was 50.7%. Applying a threshold of 0.5 increased the average classification recall to 74.6% at the expense of taxonomic resolution. Higher top value from the output layer and larger sized species were more often classified correctly, as were images of species in genera with few species. 4. Fine-tuning enabled us to classify images with a high mean recall for the whole test dataset to species or higher taxonomic levels, however, with high variability. This indicates that some species are more difficult to identify because of properties such as their body size or the number of related species. 5. Together, species-level image classification of arthropods from museum collections and ecological monitoring can substantially increase the amount of occurrence data that can feasibly be collected. These tools thus provide new opportunities in understanding and predicting ecological responses to environmental change.
Persistence of intense, climate-driven runoff late in Mars historyMars is dry today, but numerous precipitation-fed paleo-rivers are found across the planet’s surface. These rivers’ existence is a challenge to models of planetary climate evolution. We report results indicating that, for a given catchment area, rivers on Mars were wider than rivers on Earth today. We use the scale (width and wavelength) of Mars paleo-rivers as a proxy for past runoff production. Using multiple methods, we infer that intense runoff production of >(3–20) kg/m2 per day persisted until <3 billion years (Ga) ago and probably <1 Ga ago, and was globally distributed. Therefore, the intense runoff production inferred from the results of the Mars Science Laboratory rover was not a short-lived or local anomaly. Rather, precipitation-fed runoff production was globally distributed, was intense, and persisted intermittently over >1 Ga. Our improved history of Mars’ river runoff places new constraints on the unknown mechanism that caused wet climates on Mars.
Access to Marine Genetic Resources (MGR): Raising Awareness of Best-Practice Through a New Agreement for Biodiversity Beyond National Jurisdiction (BBNJ)Better scientific knowledge of the poorly-known deep sea and areas beyond national jurisdiction (ABNJ) is key to its conservation, an urgent need in light of increasing environmental pressures. Access to marine genetic resources (MGR) for the biodiversity research community is essential to allow these environments to be better characterised. Negotiations have commenced under the auspices of the United Nations Convention on the Law of the Sea (UNCLOS) to develop a new treaty to further the conservation and sustainable use of marine biological diversity in ABNJ. It is timely to consider the relevant issues with the development of the treaty underway. Currently uncertainties surround the legal definition of MGR and scope of related benefit-sharing, against a background of regional and global governance gaps in ABNJ. These complications are mirrored in science, with recent major advances in the field of genomics, but variability in handling of the resulting increasing volumes of data. Here, we attempt to define the concept of MGR from a scientific perspective, review current practices for the generation of and access to MGR from ABNJ in the context of relevant regulations, and illustrate the utility of best-practice with a case study. We contribute recommendations with a view to strengthen best-practice in accessibility of MGR, including: funder recognition of the central importance of taxonomy/biodiversity research; support of museums/collections for long-term sample curation; open access to data; usage and further development of globally recognised data standards and platforms; publishing of datasets via open-access, quality controlled and standardised data systems and open access journals; commitment to best-practice workflows; a global registry of cruises; and lastly development of a clearing house to further centralised access to the above. We argue that commitment to best-practice would allow greater sharing of MGR for research and extensive secondary use including conservation and environmental monitoring, and provide an exemplar for access and benefit-sharing (ABS) to inform the biodiversity beyond national jurisdiction (BBNJ) process.
On the front line of modern data-management and Open Access publishing: Two years of PhytoKeys – the fastest growing journal in plant systematicsPhytoKeys was launched on the 1st of November 2010 as a novel, peer-reviewed, openaccess outlet for plant biodiversity research (Penev et al. 2010a). The journal quickly gained the support of the international botanical community and since its launch continues to grow in reputation and volume.