Emerging technologies for biological recording
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Technology has played an important role in biological recording for hundreds of years, from the invention of the microscope to the microprocessor. We review current and emerging technologies that are changing the way we study and record the natural world. From websites to smartphones, data capture is becoming easier, faster and more accessible. Increases in data volume and wider participation raises concerns over data quality, which are being addressed with accurate sensors, automated validation tools, and verification platforms that utilize expert taxonomists and collective intelligence to ensure the highest level of quality possible. Data curation and interoperability have been transformed in the information age. The need to collate data at continental and global scales and across institutions continues to drive the formation of standardized data formats and taxonomies. Once collated these data can be analysed using high-performance computing, and used to provide valuable feedback in the form of interactive visualizations, computer-generated text or even game-like rewards. We also address issues arising from these technological developments. For example: how will the role of the expert naturalist change? Is biological recording undergoing a revolutionary or evolutionary process? How is technology leading to the empowerment of the public?
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New tools and technologies to detect new invasions, including image recognition, machine learning, and remote sensing, will be influential in advancing citizen science for surveillance and monitoring of IAS.
“The emergence of new tools and technologies to detect new invasions, including image recognition, use of machine learning, and remote sensing, will be influential in advancing citizen science for surveillance and monitoring of IAS (August et al., 2015; Terry, Roy, & August, 2020).”
From Scientists' warning on invasive alien species (2020) · cites this paper as August et al., 2015
Section 3.1.3 describes image-based species identification and machine-learning recognition, while section 2.3 describes UAV imagery for mapping species occurrence. The Additional information section says rapid sharing and online reporting can aid invasive-species surveillance and response. The paper does not specifically establish that image recognition, machine learning, and remote sensing will detect new invasions or advance citizen-science surveillance of invasive alien species as a group. (LLM, conf=0.82)
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Lintott, C. J., Schawinski, K., Slosar, A., Land, K., Bamford, S., Thomas, D., Raddick, M. J., Nichol, R. C., Szalay, A., Andreescu, D., et al. (2008) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2008.13689.x · Cited by 1,488 · see citing works
Stowell, D., & Plumbley, M. D. (2014) · PeerJ · doi:10.7717/peerj.488 · Cited by 295 · see citing works
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Research works printed but not linked: 23
- Anderson SE, Dave AS, Margoliash D. 1996. Template-based automatic recognition of birdsong syllables from continuous recordings. Journal of the Acoustical Society of America 100: 1209-1219.
- Ansine J. 2013. Reaching the public through iSpot: your place to share nature. Science Communication -a practical guide for scientists. Oxford: Wiley Blackwell, 257-259.
- Blake S, Siddharthan A, Nguyen H, Sharma N, Robinson AM, O'Mahony E, Darvil B, Mellish C, van der Wal R. 2012. Natural Language Generation for Nature Conservation: Automating Feedback to help Volunteers identify Bumblebee Species. Proceedings of COLING 2012.311-324.
- Briggs F, Lakshminarayanan B, Neal L, Fern XZ, Raich R, Hadley SJK, Hadley AS, Betts MG. 2012. Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach. Journal of the Acoustical Society of America 131: 4640-4650.
- Chesmore ED, Ohya E. 2004. Automated identification of field-recorded songs of four British grasshoppers using bioacoustic signal recognition. Bulletin of entomological research 94: 319-330.
- CODATA-ICSTI Task Group on Data Citation Standards and Practices. 2013. Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data. Data Science Journal 12: CIDCR1-CIDCR75.
- Deloitte. 2013. The Deloitte Consumer Review Beyond the hype: The true potential of mobile.
- Deterding S, Sicart M, Nacke L, O'Hara K, Dixon D. 2011. Gamification. using game-design elements in non-gaming contexts. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems -CHI EA '11: 2425.
- Doupe AJ, Kuhl PK. 1999. Birdsong and human speech: Common themes and mechanisms. Annual Review of Neuroscience 22: 567-631.
- Freenberg A. 1999. Questioning Technology. Routledge.
- Haklay M. 2013. Citizen Science and Volunteered Geographic Information -overview and typology of participation. In: Sui D, Elwood S, Goodchild M, eds. Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice. Dordrecht: Springer Netherlands, 105-122.
- Kumar N, Belhumeur PN, Biswas A, Jacobs DW, Kress WJ, Lopez IC, Soares JVB. 2012. Leafsnap: A computer vision system for automatic plant species identification. Computer Vision -ECCV 2012, Lecture Notes in Computer Science.502-516.
- Maclean IMD, Wilson RJ. 2011. Recent ecological responses to climate change support predictions of high extinction risk. Proceedings of the National Academy of Sciences of the United States of America 108: 12337-12342.
- Nimis PL, Lebbe R V. 2010. Tools for Identifying Biodiversity: Progress and Problems. Proceedings of the International Congress, Paris, September 20-22, 2010.
- Prestopnik N, Crowston K. 2012. Purposeful Gaming & Socio-Computational Systems: A Citizen Science Design Case. Proceedings of the 17th ACM international conference on Supporting group work: 75-84.
- Saylor M. 2012. The Mobile Wave: How Mobile Intelligence Will Change Everything. Perseus Books/Vanguard Press.
- Shirky C. 2010. Cognitive Surplus: Creativity and Generosity in a Connected Age. Penguin Group.
- Sliwa J, Benoist E. 2011. Pervasive Computing -The Next Technical Revolution. 2011 Developments in E-systems Engineering. IEEE, 621-626.
- Snaddon J, Petrokofsky G, Jepson P, Willis KJ. 2013. Biodiversity technologies: tools as change agents. Biology letters 9: 20121029.
- Van Strien AJ, van Swaay C a. M, Termaat T. 2013. Opportunistic citizen science data of animal species produce reliable estimates of distribution trends if analysed with occupancy models (V Devictor, Ed.). Journal of Applied Ecology 50: 1450-1458.
- Trolliet F, Huynen M claude, Vermeulen C, Hambuckers A. 2014. Use of camera traps for wildlife studies . A review. 18: 446-454.
- Walters CL, Freeman R, Collen A, Dietz C, Fenton MB, Jones G, Obrist MK, Puechmaille SJ, Sattler T, Siemers BM, et al. 2012. A continental-scale tool for acoustic identification of European bats. Journal of Applied Ecology 49: 1064-1074.
- Warf B, Sui D. 2010. From GIS to neogeography: ontological implications and theories of truth. Annals of GIS 16: 197-209.
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Scientists' warning on invasive alien species
Pyšek, P., Hulme, P. E., Simberloff, D., Bacher, S., Blackburn, T. M., Carlton, J. T., Dawson, W., Essl, F., Foxcroft, L. C., Genovesi, P., et al. (2020) · Biological Reviews · doi:10.1111/brv.12627 · Cited by 2,234 · see citing works
A Vision for Global Biodiversity Monitoring With Citizen Science
(2018) · Advances in Ecological Research · doi:10.1016/bs.aecr.2018.06.003 · Cited by 228 · see citing works
Self-citationCitizen science and wildlife biology: Synergies and challenges
Frigerio, D., Pipek, P., Kimmig, S., Winter, S., Melzheimer, J., Diblíková, L., Wachter, B., & Richter, A. (2018) · Ethology · doi:10.1111/eth.12746 · Cited by 86 · see citing works
Groom, Q., Strubbe, D., Adriaens, T., Davis, A. J. S., Desmet, P., Oldoni, D., Reyserhove, L., Roy, H. E., & Vanderhoeven, S. (2019) · Citizen Science: Theory and Practice · doi:10.5334/cstp.238 · Cited by 45 · see citing works
- Authors
- August, T., Harvey, M., Lightfoot, P., Kilbey, D., Papadopoulos, T., & Jepson, P.
- Affiliations
- Natural Environment Research Council (GB)
- The Open University (GB)
- National Forum for Biological Recording; UK
- University of Bristol (GB)
- University of Oxford (GB)
- Corresponding author
- August, Tom
- Venue
- Biological Journal of the Linnean Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-04-20
- Volume
- 115
- Issue
- 3
- Pages
- 731-749
- ISSN
- 0024-4066 (ISSN-L)
- OpenAlex
- W1790430563
- Cited by
- 141
- References
- 2
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 6 · 2023: 10 · 2022: 13 · 2021: 14 · 2020: 10 · 2019: 19 · 2018: 14 · 2017: 6 · 2016: 13 · 2015: 21
- FWCI
- 48.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Biological Journal of the Linnean Society (publishedVersion, other-oa)
- NERC Open Research Archive (Natural Environment Research Council) (acceptedVersion)
- Open Research Online (The Open University) (submittedVersion)
- Funders
- Joint Nature Conservation Committee
- Natural Environment Research Council (NEC04932)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Earth and Planetary Sciences › Geology › Environmental Monitoring and Data Management
- Keywords
- biological recording, citizen science, data quality, automated validation, collective intelligence, data curation, interoperability, standardized data formats, high-performance computing, interactive visualization, citizen empowerment, emerging technologies
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