Abstract
Rapid growth in the digitisation of the world’s natural history collections substantially simplifies scientific access to taxonomic and biogeographic information. Despite recent efforts to collate more than two centuries of biodiversity inventories into comprehensive databases, these collections suffer limitations across spatial, temporal and taxonomic dimensions. We assessed taxonomic shortfalls in preserved specimens from 296 plant families native to Australia, for which records have been collated into the Australasian Virtual Herbarium (AVH), specifically addressing the following questions: (1) Based on the number of specimen records per species, which Australian native plant families are under- or over-represented in the collection of preserved specimens digitised in the AVH? (2) To what extent does the distribution of collectors among plant families, or the area occupied by plant families, explain patterns of taxonomic representativeness? We found that the number of preserved specimens per family is not proportional to the family’s known species richness. For 29% of Australia’s plant families (i.e. 86), the number of digitised records constitutes < 50% of the number expected given species richness within those families. Further, only 34% of families (100) have at least 20 specimens digitised for each species recorded in the AVH. Families occupying small areas (< 200 grid cells) are more likely to be under-represented taxonomically, while there is a strong positive correlation between the number of unique collectors and the extent of taxonomic over-representation. A sound understanding of biodiversity is critical for megadiverse countries such as Australia, and identifying biases in digital inventories may help with establishing future sampling and digitisation strategies to enhance taxonomic representation.
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References
Ahonen I, Muona J, Piippo S (2003) Inferring the phylogeny of the Lejeuneaceae (Jungermanniopsida): a first appraisal of molecular data. Bryologist 106(2):297–309
Ahrends A et al (2011) Conservation and the botanist effect. Biol Conserv 144(1):131–140. https://doi.org/10.1016/j.biocon.2010.08.008
Bebber DP et al (2012) Big hitting collectors make massive and disproportionate contribution to the discovery of plant species. Proc R Soc B 279:2269–2274. https://doi.org/10.1098/rspb.2011.2439
Bonnet X, Shine R, Lourdais O (2002) Taxonomic chauvinism. Trends Ecol Evol 17(1):1–3. https://doi.org/10.1016/S0169-5347(01)02381-3
Ceballos G, Ehrlich PR, Barnosky AD, García A, Pringle RM, Palmer TM (2015) Accelerated modern human–induced species losses: entering the sixth mass extinction. Sci Adv. https://doi.org/10.1126/sciadv.1400253
Chapman AD (2009) Numbers of living species in Australia and the world
Clark JA, May RM (2002) Taxonomic bias in conservation research. Science 297:191
Farrier D, Whelan R, Mooney C (2007) Threatened species listing as a trigger for conservation action. Environ Sci Policy 10:219–229
Feeley KJ, Silman MR (2011a) The data void in modeling current and future distributions of tropical species. Glob Change Biol 17:626–630. https://doi.org/10.1111/j.1365-2486.2010.02239.x
Feeley KJ, Silman MR (2011b) Keep collecting: accurate species distribution modelling requires more collections than previously thought. Divers Distrib 17:1132–1140. https://doi.org/10.1111/j.1472-4642.2011.00813.x
Garcillán PP, Ezcurra E (2011) Sampling procedures and species estimation: testing the effectiveness of herbarium data against vegetation sampling in an oceanic island. J Veg Sci 22:273–280. https://doi.org/10.1111/j.1654-1103.2010.01247.x
Geijzendorffer IR et al (2016) Bridging the gap between biodiversity data and policy reporting needs: an essential biodiversity variables perspective. J Appl Ecol 53(5):1341–1350. https://doi.org/10.1111/1365-2664.12417
González-Orozco CE et al (2016) Phylogenetic approaches reveal biodiversity threats under climate change. Nat Clim Change 6:1110. https://doi.org/10.1038/nclimate3126
Graham CH, Ferrier S, Huettman F, Moritz C, Peterson AT (2004) New developments in museum-based informatics and applications in biodiversity analysis. Trends Ecol Evol 19:497–503
Grand J, Cummings MP, Rebelo TG, Ricketts TH, Neel MC (2007) Biased data reduce efficiency and effectiveness of conservation reserve networks. Ecol Lett 10:364–374
Guerin GR, Biffin E, Baruch Z, Lowe AJ (2016) Identifying centres of plant biodiversity in South Australia. PLoS ONE 11:e0144779
Halme P, Kuusela S, Juslén A (2015) Why taxonomists and ecologists are not, but should be, carpooling? Biodivers Conserv 24:1831–1836
Haque MM, Nipperess DA, Gallagher RV, Beaumont LJ (2017) How well documented is Australia’s flora? Understanding spatial bias in vouchered plant specimens. Aust Ecol 42:690–699. https://doi.org/10.1111/aec.12487
Haque MM, Nipperess DA, John BB, Beaumont LJ (2018) A journey through time: exploring temporal patterns among digitised plant specimens from Australia. Syst Biodivers 16(6):604–613
Holmes MW et al (2016) Natural history collections as windows on evolutionary processes. Mol Ecol 25:864–881
Hortal J, Jiménez-Valverde A, Gómez JF, Lobo JM, Baselga A (2008) Historical bias in biodiversity inventories affects the observed environmental niche of the species. Oikos 117:847–858
Hortal J, de Bello F, Diniz-Filho JAF, Lewinsohn TM, Lobo JM, Ladle RJ (2015) Seven shortfalls that beset large-scale knowledge of biodiversity. Annu Rev Ecol Evol Syst 46:523–549. https://doi.org/10.1146/annurev-ecolsys-112414-054400
Lawler JJ et al (2006) Conservation science: a 20-year report card. Front Ecol Environ 4(9):473–480
Lee C, Nicholas M (2018) Redlistr: tools for the IUCN red list of ecosystems and species. R package version 1.0.1. https://CRAN.R-project.org/package=redlistr
Mace GM (2004) The role of taxonomy in species conservation. Philos Trans R Soc B 359:711–719
Mallett K, Orchard A (2002) Flora of Australia Volume 43, Poaceae 1: introduction and atlas. Australian Biological Resources Study and CSIRO
Meyer C, Weigelt P, Kreft H (2016) Multidimensional biases, gaps and uncertainties in global plant occurrence information. Ecol Lett 19:992–1006. https://doi.org/10.1111/ele.12624
Penn MG, Cafferty S, Carine M (2018) Mapping the history of botanical collectors: spatial patterns, diversity, and uniqueness through time. Syst Biodivers 16:1–13. https://doi.org/10.1080/14772000.2017.1355854
Petersen FT, Meier R (2003) Testing species-richness estimation methods on single-sample collection data using the Danish Diptera. Biodivers Conserv 12:667–686
Pillon Y, Chase Mark W (2006) Taxonomic exaggeration and its effects on orchid conservation. Conserv Biol 21:263–265. https://doi.org/10.1111/j.1523-1739.2006.00573.x
Proença V et al (2017) Global biodiversity monitoring: from data sources to essential biodiversity variables. Biol Conserv 213:256–263. https://doi.org/10.1016/j.biocon.2016.07.014
R Development Core Team (2018) R development core team. In: A language and environment for statistical computing. R Founder for Statistical Computing, Vienna. https://www.r-project.org
Rands MRW et al (2010) Biodiversity conservation: challenges beyond 2010. Science 329:1298–1303. https://doi.org/10.1126/science.1189138
Schmidt-Lebuhn AN, Knerr NJ, Kessler M (2013) Non-geographic collecting biases in herbarium specimens of Australian daisies (Asteraceae). Biodivers Conserv 22:905–919. https://doi.org/10.1007/s10531-013-0457-9
Silcock JL, Healy AJ, Fensham RJ (2015) Lost in time and space: re-assessment of conservation status in an arid-zone flora through targeted field survey. Aust J Bot 62(8):674–688. https://doi.org/10.1071/BT14279
Stropp J et al (2016) Mapping ignorance: 300 years of collecting flowering plants in Africa. Glob Ecol Biogeogr 25:1085–1096
Sullivan BL et al (2017) Using open access observational data for conservation action: a case study for birds. Biol Conserv 208:5–14. https://doi.org/10.1016/j.biocon.2016.04.031
Ter Steege H, Haripersaud PP, Banki OS, Schieving F (2011) A model of botanical collectors’ behavior in the field: never the same species twice. Am J Bot 98:31–37. https://doi.org/10.3732/ajb.1000215
Troudet J, Grandcolas P, Blin A, Vignes-Lebbe R, Legendre F (2017) Taxonomic bias in biodiversity data and societal preferences. Sci Rep 7:9132. https://doi.org/10.1038/s41598-017-09084-6
Walsh JC, Watson JEM, Bottrill MC, Joseph LN, Possingham HP (2012) Trends and biases in the listing and recovery planning for threatened species: an Australian case study. Oryx 47:134–143. https://doi.org/10.1017/S003060531100161X
Ward DF (2012) More than just records: analysing natural history collections for biodiversity planning. PLoS ONE 7:e50346
Wilson JR, Procheş Ş, Braschler B, Dixon ES, Richardson DM (2007) The (bio)diversity of science reflects the interests of society. Front Ecol Environ 5(8):409–414. https://doi.org/10.1890/060077.1
Zopfi H-J (1993) Ecotypic variation in Rhinanthus alectorolophus (Scopoli) Pollich (Scrophulariaceae) in relation to grassland management: I. Morphological delimitations and habitats of seasonal ecotypes. Flora 188:15–39
Acknowledgements
We thank Dr Rachael Gallagher and Stuart Allen for their assistance in data retrieval from Australasian Virtual Herbarium (AVH) via Atlas of Living Australia (ALA). MH was funded by a Macquarie University Research Excellence Scholarship (iMQRES).
Funding
The Study was funded by Macquarie University (Grant id 43503721) through Macquarie University Research Excellence Scholarship (iMQRES).
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Haque, M.M., Beaumont, L.J. & Nipperess, D.A. Taxonomic shortfalls in digitised collections of Australia’s flora. Biodivers Conserv 29, 333–343 (2020). https://doi.org/10.1007/s10531-019-01885-7
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DOI: https://doi.org/10.1007/s10531-019-01885-7