Candide and Botanical Software: technology cultivating garden visitation and collection management
DOI:
https://doi.org/10.24823/Sibbaldia.2021.318Keywords:
Botanical Software, Plant Records, Visitor Management, Collection ManagementAbstract
Abstract
It is clear that the biodiversity crisis and overarching threat of climate change are having a fundamental impact on the biology of the planet. Botanic gardens, and related institutions, are uniquely positioned as centres of expertise in plant biodiversity. Their efforts in the exploration and documentation of biodiversity are also a fundamental prerequisite for the conservation of plants. The systematised and structured documentation of a garden’s collection of plant material, together with the collection policy and overall mission, characterises an institution as a botanic garden. However, the currently available tools and processes are not cost-effective, accessible at a global level, and do not provide the necessary efficiency for the needs and workflows of botanic gardens and plant collection management. In the context of gardens and visitation, there is also a growing disconnection between people and plants, particularly in an increasingly urbanised world.
Here, we present numerous innovative initiatives towards tackling these challenges, assisted by technology. We discuss the application of machine-learning in the automatic identification of plants (including composite tools such as Augmented Reality), and digital engagement through mobile-based complementations to visitors’ experiences. We also explore the documentation of quality data for botanical collections, and how advancements in collection management systems will play a major role in the efforts of the botanic garden community, and use of their richly-diverse plant collections in the vanguard of research, conservation, education, and visitation. Thus, ongoing technological developments in tools for botanic gardens and their visitors, present positive and influential contributions in tackling global challenges associated with plant conservation and engaging the broadest and most diverse audiences.
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Ballantyne, R., Packer, J., and Hughes, K. 2008. Environmental awareness, interests and motives of botanic gardens visitors: Implications for interpretive practice. Tourism Management 29(3): 439-444.
Blackmore, S., and Oldfield, S. 2017. Mounting a fundamental defence of the plant kingdom. In Plant Conservation Science and Practice: The Role of Botanic Gardens. Edited by S. Blackmore and S. Oldfield. Cambridge University Press, Cambridge, UK. pp. 1–8.
British Nutrition Foundation. 2014. National Pupil Survey 2014. UK Survey Results. Available from https://www.nutrition.org.uk/attachments/698_UK%20Pupil%20Survey%20Results%202014.pdf [accessed 14/01/2021]
Carson, R. 1962. Silent Spring. Houghton Mifflin Harcourt.
Chien, Y.-C., Su, Y.-N., Wu, T.-T., and Huang, Y.-M. 2019. Enhancing students’ botanical learning by using augmented reality. Universal Access in the Information Society 18(2): 231-241.
Clatworthy, J., Hinds, J., and Camic, P.M. 2013. Gardening as a mental health intervention: A review. Mental Health Review Journal 18(4): 214-225.
Connell, J. 2004. The purest of human pleasures: the characteristics and motivations of garden visitors in Great Britain. Tourism Management 25(2): 229-247.
Connell, J., and Meyer, D. 2004. Modelling the visitor experience in the gardens of Great Britain. Current Issues in Tourism 7(3): 183-216.
Dahlgren, G. 1989. An updated angiosperm classification. Botanical Journal of the Linnean Society 100(3): 197-203.
Ellis, E.C. 2011. Anthropogenic transformation of the terrestrial biosphere. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369(1938): 1010-1035.
Ellis, E.C., Klein Goldewijk, K., Siebert, S., Lightman, D., and Ramankutty, N. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography 19(5): 589-606.
GBIF Secretariat. 2019. GBIF Science Review 2019. Available from 10.15468/QXXG-7K93 [accessed 19/01/2021]
Gratzfeld, J. 2016. From Idea to Realisation: BGCI's Manual on Planning, Developing and Managing Botanic Gardens. Botanic Gardens Conservation International, Richmond, UK.
Hall, C., and Knuth, M. 2019. An update of the literature supporting the well-being benefits of plants: A review of the emotional and mental health benefits of plants. Journal of Environmental Horticulture 37(1): 30-38.
Havinga, R., and Ostgaard, H. 2016. Barcodes are dead, long live barcodes! Improving the inventory of living plant collections using optical technology. Sibbaldia: The Journal of Botanic Garden Horticulture(14): 133-140.
Hoekstra, B. 2000. Plant blindness: The ultimate challenge to botanists. The American Biology Teacher 62(2): 82-83.
Jones, H. 2020a. What plant is that? Tests of automated image recognition apps for plant identification on plants from the British flora. AoB Plants 12(6): plaa052.
Jones, H. 2020b. Artificial Intelligence for plant identification on smartphones and tablets. BSBI News 144: 34-40.
Keniger, L.E., Gaston, K.J., Irvine, K.N., and Fuller, R.A. 2013. What are the benefits of interacting with nature? International Journal of Environmental Research and Public Health 10(3): 913-935.
Lewis, S.L., and Maslin, M.A. 2015. Defining the anthropocene. Nature 519(7542): 171-180.
Louv, R. 2008. Last Child in the Woods: Saving Our Children from Nature-Deficit Disorder. Algonquin Books.
Ma, C., Zhang, H.H., and Wang, X. 2014. Machine learning for Big Data analytics in plants. Trends in Plant Science 19(12): 798-808.
Mahood, E.H., Kruse, L.H., and Moghe, G.D. 2020. Machine learning: A powerful tool for gene function prediction in plants. Applications in Plant Sciences 8(7): e11376.
Niemi, H., and Multisilta, J. 2016. Digital storytelling promoting twenty-first century skills and student engagement. Technology, Pedagogy and Education 25(4): 451-468.
Rakow, D., and Lee, S. 2011. Public garden management: A complete guide to the planning and administration of botanical gardens and arboreta. John Wiley & Sons.
Singh, A., Ganapathysubramanian, B., Singh, A.K., and Sarkar, S. 2016. Machine learning for high-throughput stress phenotyping in plants. Trends in Plant Science 21(2): 110-124.
Thorogood, C. 2020. Astonishing plants. Trends in Plant Science 25(9): 833-836.
Voltaire. 1759. Candide, ou l'Optimisme. Cramer, Geneva.
Vujcic, M., Tomicevic-Dubljevic, J., Grbic, M., Lecic-Tosevski, D., Vukovic, O., and Toskovic, O. 2017. Nature based solution for improving mental health and well-being in urban areas. Environmental Research 158: 385-392.
Wäldchen, J., and Mäder, P. 2018. Machine learning for image based species identification. Methods in Ecology and Evolution 9(11): 2216-2225.
Wäldchen, J., Rzanny, M., Seeland, M., and Mäder, P. 2018. Automated plant species identification—Trends and future directions. PLOS Computational Biology 14(4): e1005993.
Wandersee, J.H., and Schussler, E.E. 1999. Preventing plant blindness. The American Biology Teacher 61(2): 82-86.
White, S., Feiner, S., and Kopylec, J. Virtual vouchers: Prototyping a mobile augmented reality user interface for botanical species identification. In 3D User Interfaces (3DUI'06). 2006. IEEE. pp. 119-126.
Williams, S.J., Jones, J.P.G., Gibbons, J.M., and Clubbe, C. 2015. Botanic gardens can positively influence visitors’ environmental attitudes. Biodiversity and Conservation 24(7): 1609-1620.
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2021-06-03
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Candide and Botanical Software: technology cultivating garden visitation and collection management. (2021). Sibbaldia: The International Journal of Botanic Garden Horticulture, 20, 163-174. https://doi.org/10.24823/Sibbaldia.2021.318
