Standardised data on initiatives-STARDIT: Beta version.

BACKGROUND AND OBJECTIVE: There is currently no standardised way to share information across disciplines about initiatives, including fields such as health, environment, basic science, manufacturing, media and international development. All problems, including complex global problems such as air pollution and pandemics require reliable data sharing between disciplines in order to respond effectively. Current reporting methods also lack information about the ways in which different people and organisations are involved in initiatives, making it difficult to collate and appraise data about the most effective ways to involve different people. The objective of STARDIT (Standardised Data on Initiatives) is to address current limitations and inconsistencies in sharing data about initiatives. The STARDIT system features standardised data reporting about initiatives, including who has been involved, what tasks they did, and any impacts observed. STARDIT was created to help everyone in the world find and understand information about collective human actions, which are referred to as 'initiatives'. STARDIT enables multiple categories of data to be reported in a standardised way across disciplines, facilitating appraisal of initiatives and aiding synthesis of evidence for the most effective ways for people to be involved in initiatives. This article outlines progress to date on STARDIT; current usage; information about submitting reports; planned next steps and how anyone can become involved. METHOD: STARDIT development is guided by participatory action research paradigms, and has been co-created with people from multiple disciplines and countries. Co-authors include cancer patients, people affected by rare diseases, health researchers, environmental researchers, economists, librarians and academic publishers. The co-authors also worked with Indigenous peoples from multiple countries and in partnership with an organisation working with Indigenous Australians. RESULTS AND DISCUSSION: Over 100 people from multiple disciplines and countries have been involved in co-designing STARDIT since 2019. STARDIT is the first open access web-based data-sharing system which standardises the way that information about initiatives is reported across diverse fields and disciplines, including information about which tasks were done by which stakeholders. STARDIT is designed to work with existing data standards. STARDIT data will be released into the public domain (CC0) and integrated into Wikidata; it works across multiple languages and is both human and machine readable. Reports can be updated throughout the lifetime of an initiative, from planning to evaluation, allowing anyone to be involved in reporting impacts and outcomes. STARDIT is the first system that enables sharing of standardised data about initiatives across disciplines. A working Beta version was publicly released in February 2021 (ScienceforAll.World/STARDIT). Subsequently, STARDIT reports have been created for peer-reviewed research in multiple journals and multiple research projects, demonstrating the usability. In addition, organisations including Cochrane and Australian Genomics have created prospective reports outlining planned initiatives. CONCLUSIONS: STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems.

All major problems, including complex global problems such as air pollution and pandemics, require reliable data sharing between disciplines in order to respond effectively. Such problems require evidence-informed collaborative methods, multidisciplinary research and interventions in which the people who are affected are involved in every stage. However, there is currently no standardised way to share information about initiatives and problem-solving across and between fields such as health, environment, basic science, manufacturing, education, media and international development. A multi-disciplinary international team of over 100 citizens, experts and data-users has been involved in co-creating STARDIT to help everyone in the world share, find and understand information about collective human actions, which are referred to as 'initiatives'. STARDIT is an open access data-sharing system to standardise the way that information about initiatives is reported, including information about which tasks were done by different people. Reports can be updated at all stages, from planning to evaluation, and can report impacts in many languages, using Wikidata. STARDIT is free to use, and data can be submitted by anyone. Report authors can be verified to improve trust and transparency, and data checked for quality. STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems. Among its main benefits, STARDIT offers those carrying out research and interventions access to standardised information which enables well-founded comparisons of the effectiveness of different methods. This article outlines progress to date; current usage; information about submitting reports; planned next steps and how anyone can become involved.

Oxpeckers Help Rhinos Evade Humans.

Evolutionary theory expects social, communicative species to eavesdrop most on other species' alarm calls [e.g., 1, 2] but also that solitary-living species benefit most from eavesdropping [3, 4]. Examples of solitary species responding to the alarm calls of other species, however, are limited and unconvincing [3-5]. The Swahili name for the red-billed oxpecker (Buphagus erythrorynchus) is Askari wa kifaru, the rhinos' guard [6]. Black rhino (Diceros bicornis) are a solitary-living, non-vocal species and are critically endangered through hunting. We searched Hluhluwe-iMfolozi Park, South Africa, for rhinoceros for 27 months with and without the aid of radio telemetry and conducted 86 experimental, unconcealed approaches to 11 rhino, without or with varying numbers of resident oxpecker. Oxpeckers enabled rhinos to evade detection by us in 40% to 50% of encounters. Alarm-calling by oxpeckers significantly improved the rate and distance that rhinos detected our approach from 23% to 100% and 27 ± 6 m to 61 ± 4 m, respectively. Every additional oxpecker improved detection distance by 9 m. Rhinos alerted by oxpeckers' alarm calls never re-oriented in our direction but moved to face downwind. Thus, oxpeckers' calls communicate only threat proximity, not direction, and rhinos assume the hunter is stalking from downwind. We confirm that oxpeckers guard rhinos and the importance of depredation, not sociality, in the evolution of eavesdropping [4, 7]. Conservationists should consider reintroducing oxpeckers to rhino populations, reinstating their anti-human sentinel [8]. VIDEO ABSTRACT.

Standardising Home Range Studies for Improved Management of the Critically Endangered Black Rhinoceros.

Comparisons of recent estimations of home range sizes for the critically endangered black rhinoceros in Hluhluwe-iMfolozi Park (HiP), South Africa, with historical estimates led reports of a substantial (54%) increase, attributed to over-stocking and habitat deterioration that has far-reaching implications for rhino conservation. Other reports, however, suggest the increase is more likely an artefact caused by applying various home range estimators to non-standardised datasets. We collected 1939 locations of 25 black rhino over six years (2004-2009) to estimate annual home ranges and evaluate the hypothesis that they have increased in size. A minimum of 30 and 25 locations were required for accurate 95% MCP estimation of home range of adult rhinos, during the dry and wet seasons respectively. Forty and 55 locations were required for adult female and male annual MCP home ranges, respectively, and 30 locations were necessary for estimating 90% bivariate kernel home ranges accurately. Average annual 95% bivariate kernel home ranges were 20.4 ± 1.2 km(2), 53 ± 1.9% larger than 95% MCP ranges (9.8 km(2) ± 0.9). When home range techniques used during the late-1960s in HiP were applied to our dataset, estimates were similar, indicating that ranges have not changed substantially in 50 years. Inaccurate, non-standardised, home range estimates and their comparison have the potential to mislead black rhino population management. We recommend that more care be taken to collect adequate numbers of rhino locations within standardized time periods (i.e., season or year) and that the comparison of home ranges estimated using dissimilar procedures be avoided. Home range studies of black rhino have been data deficient and procedurally inconsistent. Standardisation of methods is required.