posted on 2022-03-28, 14:44authored byMd Mohasinul Haque
Understanding biases and errors in natural history collections (NHCs) is of paramount importance for the validity of conservation and environmental studies. We explored spatial biases in Australia's virtual herbarium (AVH), a database containing more than 7,000,000 records of ~21,000 native species, recorded from across the continent. Specifically, we assessed spatial patterns of sampling and representativeness of the floristic composition of AVH data. Location Australia Methods Biases were explored by calculating a sampling allocation index (SAI, ratio of observed to expected records) and an index of inventory completeness (C-index) based on the ratio of observed to estimated species richness, at multiple spatial scales. Representativeness was determined by the spatial resolution at which the AVH data most closely approximates the composition of vegetation survey plot data gathered at the local scale (0.04 ha). Results SAI indicated that sampling of Australia’s native flora has been severely geographically biased, with comparatively few records from arid and subtropical regions. While the C–index demonstrated that resolution can significantly impact patterns of spatial bias, Tasmania and the Northern Territory generally retained high C–index values. Finally, we found that a 16 ha buffer surrounding the vegetation survey plots was required for AVH data to match 90% of the species known to occur at the plot level. Main Conclusions Significant spatial biases exist within the AVH. Failure to account for these, when using this database may have serious ramifications for biogeographic studies and conservation planning. We suggest that studies similar to ours be used to assist in planning future systematic surveys and species inventories, and when identifying areas of conservation priority across the continent of Australia.
History
Notes
Bibliography: leaves 33-38
Theoretical thesis.
Awarding Institution
Macquarie University
Degree Type
Thesis MRes
Degree
MRes, Macquarie University, Faculty of Science and Engineering, Department of Biological Sciences