Standardised Data on Initiatives – STARDIT: Beta Version

There is currently no standardised way to share information across disciplines about initiatives, including felds 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 efectively. Current reporting methods also lack information about the ways in which diferent people and organisations are involved in initiatives, making it difcult to collate and appraise data about the most efective ways to involve diferent 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 fnd 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

Too close and too far: quantifying black rhino displacement and location error during research

Observer impacts on animal behaviour concern conservation managers and researchers of critically endangered species, like black rhino (Diceros bicornis). Repeated observations are sometimes necessary, but may distress and displace animals. Information from more remote observations using radio-triangulation is limited and includes larger measurement errors. We investigated the influence of observer visits on average daily displacement by 14 black rhinos in Hluhluwe-iMfolozi Park, South Africa, and the accuracy of triangulated locations with increasing observer distance and the time to complete bearing sets. Fortnightly observer visits for 34 months that often disturbed rhino (52% of visits) had an insignificant impact on daily movements. However, increasing observer distance from rhino, and the time taken to triangulate, were both significant explanations of rhino location error. We recommend that measures to quantify and minimize observer influence become standard monitoring protocol and that bearings for radio-triangulation of black rhino locations occur from <1 km (not >2 km), and be completed within 30 minutes. Reporting measures for spatial error and observer influence permit the development of objective thresholds for data inclusion to improve radio-telemetry data and inter-study comparisons of black rhino range studies

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 km2, 53 ±1.9% larger than 95% MCP ranges (9.8 km2 ± 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.Publisher PDFPeer reviewe

Incremental 95% MCP accumulation curve showing the number of locations required to more accurately estimate the dry season (Apr-Sep) home ranges for black rhino in Hluhluwe-iMfolozi Park (HiP), South Africa.

<p>Note that the horizontal dashed line represents the within 10% level of the total home range recommended for increased accuracy.</p

Historical sequence of home range estimates for black rhino <i>Diceros bicornis minor</i> in Hluhluwe-iMfolozi Park, South Africa.

<p>Included for comparison are the four home range estimates from this study where different analysis techniques were used (i.e., Hitchin’s [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150571#pone.0150571.ref045" target="_blank">45</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150571#pone.0150571.ref046" target="_blank">46</a>] visual approximation technique, 95% MCP’s, 90% and 95% kernels). Standard error is included for home range estimates where possible. Note that the unshaded (white) bars represents average range sizes for female rhino, whereas the shaded (light grey) bar represents male averages. The darker shaded bar (dark grey) represents the home range average for males and females combined, as Reid et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150571#pone.0150571.ref008" target="_blank">8</a>] did not report estimates for the different sexes.</p

Incremental 95% MCP accumulation curve showing the number of locations required to more accurately estimate the annual (any consecutive 12-months) home ranges for black rhino in Hluhluwe-iMfolozi Park (HiP), South Africa.

<p>Note that the horizontal dashed line represents the within 10% level of the total home range recommended for increased accuracy.</p

Incremental 95% MCP accumulation curve showing the number of locations required to more accurately estimate the wet season (Oct-Mar) home ranges for black rhino in Hluhluwe-iMfolozi Park (HiP), South Africa.

<p>Note that the horizontal dashed line represents the within 10% level of the total home range recommended for increased accuracy.</p