Pimm, S. L. et al. Emerging technologies to conserve biodiversity. Trends Ecol. Evol. 30, 685–696 (2015).
Google Scholar
Marvin, D. C. et al. Integrating technologies for scalable ecology and conservation. Glob. Ecol. Conserv. 7, 262–275 (2016).
Google Scholar
Wall, J., Wittemyer, G., Klinkenberg, B. & Douglas-Hamilton, I. Novel opportunities for wildlife conservation and research with real-time monitoring. Ecol. Appl. 24, 593–601 (2014).
Google Scholar
Snaddon, J., Petrokofsky, G., Jepson, P. & Willis, K. J. Biodiversity technologies: tools as change agents. Biol. Lett. 9, 20121029 (2013).
Google Scholar
Pettorelli, N., Safi, K., Turner, W. Satellite remote sensing, biodiversity research and conservation of the future. Philos. Trans. R. Soc. B Biol. Sci. 369, 20130190 (2014).
Ripperger, S. P. et al. Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging. PLOS Biol. 18, e3000655 (2020).
Google Scholar
Xu, H., Wang, K., Vayanos, P. & Tambe, M. Strategic coordination of human patrollers and mobile sensors with signaling for security games. 8 (2018).
Liu, Y. et al. AI for Earth: Rainforest conservation by acoustic surveillance. 2 (2019).
Joppa, L. N. Technology for nature conservation: an industry perspective. Ambio 44, 522–526 (2015).
Google Scholar
Koh, L. P. & Wich, S. A. Dawn of drone ecology: low-cost autonomous aerial vehicles for conservation. Trop. Conserv. Sci. 5, 121–132 (2012).
Google Scholar
Hahn, N. et al. Unmanned aerial vehicles mitigate human–elephant conflict on the borders of Tanzanian Parks: a case study. Oryx 51, 513–516 (2017).
Google Scholar
Pomerantz, A. et al. Real-time DNA barcoding in a rainforest using nanopore sequencing: opportunities for rapid biodiversity assessments and local capacity building. GigaScience 7, (2018).
Van Doren, B. M. & Horton, K. G. A continental system for forecasting bird migration. Science 361, 1115–1118 (2018).
Google Scholar
Howson, P. Building trust and equity in marine conservation and fisheries supply chain management with blockchain. Mar. Policy 115, 103873 (2020).
Google Scholar
Speaker, T. et al. A global community-sourced assessment of the state of conservation technology. Conserv. Biol. cobi. https://doi.org/10.1111/cobi.13871 (2022).
Google Scholar
Pearce, J. M. Building research equipment with free Open-Source Hardware. Science 337, 1303–1304 (2012).
Google Scholar
Gibb, R., Browning, E., Glover-Kapfer, P. & Jones, K. E. Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring. Methods Ecol. Evol. 10, 169–185 (2019).
Google Scholar
current constraints and future priorities for development. Glover-Kapfer, P., Soto-Navarro, C. A. & Wearn, O. R. Camera-trapping version 3.0. Remote Sens. Ecol. Conserv. 5, 209–223 (2019).
Google Scholar
Norouzzadeh, M. S. et al. Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. Proc. Natl. Acad. Sci. 115, E5716–E5725 (2018).
Google Scholar
Berger-Tal, O. & Lahoz-Monfort, J. J. Conservation technology: the next generation. Conserv. Lett. 11, 1–6 (2018).
Google Scholar
Hill, A. P. et al. AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment. Methods Ecol. Evol. 9, 1199–1211 (2018).
Google Scholar
Zárybnická, M., Kubizňák, P., Šindelář, J. & Hlaváč, V. Smart nest box: a tool and methodology for monitoring of cavity-dwelling animals. Methods Ecol. Evol. 7, 483–492 (2016).
Google Scholar
Kalmár, G. et al. Animal-Borne Anti-Poaching System. in Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services 91–102 (ACM, 2019). https://doi.org/10.1145/3307334.3326080.
Weise, F. J. et al. Lions at the gates: Trans-disciplinary design of an early warning system to improve human-lion coexistence. Front. Ecol. Evol. 6, 242 (2019).
Google Scholar
Beery, S., Van Horn, G. & Perona, P. Recognition in Terra Incognita. in Proceedings of the European Conference on Computer Vision (ECCV) (eds. Ferrari, V., Hebert, M., Sminchisescu, C. & Weiss, Y.) 472–489 (Springer International Publishing, 2018). https://doi.org/10.1007/978-3-030-01270-0_28.
Crego, R. D., Masolele, M. M., Connette, G. & Stabach, J. A. Enhancing animal movement analyses: spatiotemporal matching of animal positions with remotely sensed data using google earth engine and R. Remote Sens. 13, 4154 (2021).
Google Scholar
Gorelick, N. et al. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).
Google Scholar
Vulcan. EarthRanger. https://earthranger.com.
Ahumada, J. A. et al. Wildlife insights: A platform to maximize the potential of camera trap and other passive sensor wildlife data for the planet. Environ. Conserv. 47, 1–6 (2020).
Google Scholar
Lahoz-Monfort, J. J. et al. A call for international leadership and coordination to realize the potential of conservation technology. Bioscience 69, 823–832 (2019).
Google Scholar
Group Gets – AudioMoth. https://groupgets.com/manufacturers/open-acoustic-devices/products/audiomoth.
Kulits, P., Wall, J., Bedetti, A., Henley, M. & Beery, S. ElephantBook: A semi-automated human-in-the-loop system for elephant re-identification. in ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS) 88–98 (ACM, 2021). https://doi.org/10.1145/3460112.3471947.
Pardo, L. E. et al. Snapshot Safari: A large-scale collaborative to monitor Africa’s remarkable biodiversity. South Afr. J. Sci. 117, (2021).
Iacona, G. et al. Identifying technology solutions to bring conservation into the innovation era. Front. Ecol. Environ. 17, 591–598 (2019).
Google Scholar
Cooper, R. G. What’s next?: After stage-gate. Res.-Technol. Manag. 57, 20–31 (2014).
Google Scholar
Cooper, R. G. The drivers of success in new-product development. Ind. Mark. Manag. 76, 36–47 (2019).
Google Scholar
Pearce, J. M. The case for open source appropriate technology. Environ. Dev. Sustain. 14, 425–431 (2012).
Google Scholar
Mair, J., Battilana, J. & Cardenas, J. Organizing for society: A typology of social entrepreneuring models. J. Bus. Ethics 111, 353–373 (2012).
Google Scholar
Meissner, D. Public-private partnership models for science, technology, and innovation cooperation. J. Knowl. Econ. 10, 1341–1361 (2019).
Google Scholar
Likert, R. A technique for the measurement of attitudes. Arch. Psychol. 22, 1–55.
Mayer, A. L. & Wellstead, A. M. Questionable survey methods generate a questionable list of recommended articles. Nat. Ecol. Evol. 2, 1336–1337 (2018).
Google Scholar
Archie, K. M., Dilling, L., Milford, J. B. & Pampel, F. C. Climate Change and Western Public Lands: a Survey of U.S. Federal Land Managers on the Status of Adaptation Efforts. Ecol. Soc. 17 (2012).
Jimenez, M. F. et al. Underrepresented faculty play a disproportionate role in advancing diversity and inclusion. Nat. Ecol. Evol. 3, 1030–1033 (2019).
Google Scholar
Christensen, R. ordinal – Regression Models for Ordinal Data. R package version 2019.12-10. (2019).
R Core Team. R: A language and environment for statistical computing. (2020).
Arnold, T. W. Uninformative parameters and model selection using Akaike’s information criterion. J. Wildl. Manag. 74, 1175–1178 (2010).
Google Scholar
QSR International Pty Ltd. Nvivo 12 Pro. (2020).
Glesne, C. Making words fly: Developing understanding through interviewing. Becom. Qual. Res. Introd. 3, (2006).
Creswell, J. W. & Creswell, J. D. Research design: Qualitative, quantitative, and mixed methods approaches. (Sage publications 2017).
Source: Ecology - nature.com
