For the first time in 100 years: South American bat rediscovered after a century

The finding increases the range of the species by about 280 km, and highlights the importance of protected areas in the conservation of wildlife.

The Strange Big-eared Brown Bat, Histiotus alienus, was first described by science in 1916, by the British zoologist Oldfield Thomas. The description of the species was based on a single specimen captured in Joinville, Paraná, in southern Brazil.

For more than 100 years, the species had never been captured, being known only by its holotype—the specimen that bears the name, and represents morphological and molecular traits of a species—deposited in The Natural History Museum in London, United Kingdom. Now, after a century, the species has been rediscovered. Scientists Dr Vinícius C. Cláudio, Msc Brunna Almeida, Dr Roberto L.M. Novaes, and Dr Ricardo Moratelli, Fundação Oswaldo Cruz, Brazil and Dr Liliani M. Tiepolo, and Msc Marcos A. Navarro, Universidade Federal do Paraná, Brazil have published details on the sighting in a paper in the open access journal ZooKeys.

During field expeditions of the research project Promasto (Mammals from Campos Gerais National Park and Palmas Grasslands Wildlife Refuge) in 2018, the researchers captured one specimen of big-eared bat at Palmas Grassland Wildlife Refuge.  To catch it, they used mist-nets—equipment employed during the capture of bats and birds—set at the edge of a forest patch. When they compared it to the Tropical Big-eared Brown Bat (Histiotus velatus), commonly captured in the region, they found it was nothing like it.

The unidentified big-eared bat specimen was then collected and deposited at the Museu Nacional in Rio de Janeiro, Brazil, for further studies.

After comparing this puzzling specimen against hundreds of other big-eared brown bats from almost all the species in the genus, the researchers were able to conclusively identify the bat as a Strange Big-eared Brown Bat and confirm its second known record. “Since the description of several the species within the genus is more than one hundred years old and somewhat vague, comparisons and data presented by us will aid the correct identification of big-eared brown bats,” they say.

The Strange Big-eared Brown Bat has oval, enlarged ears that are connected by a very low membrane; general dark brown coloration in both dorsal and ventral fur; and about 100 to 120 mm in total length. This combination of characters most resembles the Southern Big-eared Brown Bat (Histiotus magellanicus), in which the membrane connecting ears is almost absent.

The only known record of the Strange Big-eared Brown Bat until now was from Joinville, Santa Catarina state, southern Brazil, which is about 280 kilometers away from where it was spotted in 2018. So far, the species is known to occur in diverse terrains, from dense rainforests to araucaria and riparian forests and grasslands, at altitudes from sea level to over 1200 m a.s.l.

This increase in the distribution of the species, however, does not represent an improvement on its conservation status: the species is currently classified as Data Deficient by the International Union for the Conservation of Nature. Its habitat, the highly fragmented Atlantic Forest, is currently under pressure from agricultural activity.

But there is still hope: “The new record of H. alienus in Palmas is in a protected area, which indicates that at least one population of the species may be protected,” the researchers write in their study.

Research article:

Cláudio VC, Almeida B, Novaes RLM, Navarro MA, Tiepolo LM, Moratelli R (2023) Rediscovery of Histiotusalienus Thomas, 1916 a century after its description (Chiroptera, Vespertilionidae): distribution extension and redescription. ZooKeys, 1174, 273–287. doi: 10.3897/zookeys.1174.108553

FAIR biodiversity data in Pensoft journals thanks to a routine data auditing workflow

Data audit workflow provided for data papers submitted to Pensoft journals.

To avoid publication of openly accessible, yet unusable datasets, fated to result in irreproducible and inoperable biological diversity research at some point down the road, Pensoft takes care for auditing data described in data paper manuscripts upon their submission to applicable journals in the publisher’s portfolio, including Biodiversity Data JournalZooKeysPhytoKeysMycoKeys and many others.

Once the dataset is clean and the paper is published, biodiversity data, such as taxa, occurrence records, observations, specimens and related information, become FAIR (findable, accessible, interoperable and reusable), so that they can be merged, reformatted and incorporated into novel and visionary projects, regardless of whether they are accessed by a human researcher or a data-mining computation.

As part of the pre-review technical evaluation of a data paper submitted to a Pensoft journal, the associated datasets are subjected to data audit meant to identify any issues that could make the data inoperable. This check is conducted regardless of whether the dataset are provided as supplementary material within the data paper manuscript or linked from the Global Biodiversity Information Facility (GBIF) or another external repository. The features that undergo the audit can be found in a data quality checklist made available from the website of each journal alongside key recommendations for submitting authors.

Once the check is complete, the submitting author receives an audit report providing improvement recommendations, similarly to the commentaries he/she would receive following the peer review stage of the data paper. In case there are major issues with the dataset, the data paper can be rejected prior to assignment to a subject editor, but resubmitted after the necessary corrections are applied. At this step, authors who have already published their data via an external repository are also reminded to correct those accordingly.

“It all started back in 2010, when we joined forces with GBIF on a quite advanced idea in the domain of biodiversity: a data paper workflow as a means to recognise both the scientific value of rich metadata and the efforts of the the data collectors and curators. Together we figured that those data could be published most efficiently as citable academic papers,” says Pensoft’s founder and Managing director Prof. Lyubomir Penev.
“From there, with the kind help and support of Dr Robert Mesibov, the concept evolved into a data audit workflow, meant to ‘proofread’ the data in those data papers the way a copy editor would go through the text,” he adds.
“The data auditing we do is not a check on whether a scientific name is properly spelled, or a bibliographic reference is correct, or a locality has the correct latitude and longitude”, explains Dr Mesibov. “Instead, we aim to ensure that there are no broken or duplicated records, disagreements between fields, misuses of the Darwin Core recommendations, or any of the many technical issues, such as character encoding errors, that can be an obstacle to data processing.”

At Pensoft, the publication of openly accessible, easy to access, find, re-use and archive data is seen as a crucial responsibility of researchers aiming to deliver high-quality and viable scientific output intended to stand the test of time and serve the public good.

CASE STUDY: Data audit for the “Vascular plants dataset of the COFC herbarium (University of Cordoba, Spain)”, a data paper in PhytoKeys

To explain how and why biodiversity data should be published in full compliance with the best (open) science practices, the team behind Pensoft and long-year collaborators published a guidelines paper, titled “Strategies and guidelines for scholarly publishing of biodiversity data” in the open science journal Research Ideas and Outcomes (RIO Journal).

Audit finds biodiversity data aggregators ‘lose and confuse’ data

In an effort to improve the quality of biodiversity records, the Atlas of Living Australia (ALA) and the Global Biodiversity Information Facility (GBIF) use automated data processing to check individual data items. The records are provided to the ALA and GBIF by museums, herbaria and other biodiversity data sources.

However, an independent analysis of such records reports that ALA and GBIF data processing also leads to data loss and unjustified changes in scientific names.

The study was carried out by Dr Robert Mesibov, an Australian millipede specialist who also works as a data auditor. Dr Mesibov checked around 800,000 records retrieved from the Australian MuseumMuseums Victoria and the New Zealand Arthropod Collection. His results are published in the open access journal ZooKeys, and also archived in a public data repository.

“I was mainly interested in changes made by the aggregators to the genus and species names in the records,” said Dr Mesibov.

“I found that names in up to 1 in 5 records were changed, often because the aggregator couldn’t find the name in the look-up table it used.”

data_auditAnother worrying result concerned type specimens – the reference specimens upon which scientific names are based. On a number of occasions, the aggregators were found to have replaced the name of a type specimen with a name tied to an entirely different type specimen.

The biggest surprise, according to Dr Mesibov, was the major disagreement on names between aggregators.

“There was very little agreement,” he explained. “One aggregator would change a name and the other wouldn’t, or would change it in a different way.”

Furthermore, dates, names and locality information were sometimes lost from records, mainly due to programming errors in the software used by aggregators to check data items. In some data fields the loss reached 100%, with no original data items surviving the processing.

“The lesson from this audit is that biodiversity data aggregation isn’t harmless,” said Dr Mesibov. “It can lose and confuse perfectly good data.”

“Users of aggregated data should always download both original and processed data items, and should check for data loss or modification, and for replacement of names,” he concluded.

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Original source:

Mesibov R (2018) An audit of some filtering effects in aggregated occurrence records. ZooKeys 751: 129-146. https://doi.org/10.3897/zookeys.751.24791