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Identifying conservation technology needs, barriers, and opportunities

  • Pimm, S. L. et al. Emerging technologies to conserve biodiversity. Trends Ecol. Evol. 30, 685–696 (2015).

    Article 

    Google Scholar 

  • Marvin, D. C. et al. Integrating technologies for scalable ecology and conservation. Glob. Ecol. Conserv. 7, 262–275 (2016).

    Article 

    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).

    Article 

    Google Scholar 

  • Snaddon, J., Petrokofsky, G., Jepson, P. & Willis, K. J. Biodiversity technologies: tools as change agents. Biol. Lett. 9, 20121029 (2013).

    Article 

    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).

    CAS 
    Article 

    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).

    Article 

    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).

    Article 

    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).

    Article 

    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).

    ADS 
    Article 

    Google Scholar 

  • Howson, P. Building trust and equity in marine conservation and fisheries supply chain management with blockchain. Mar. Policy 115, 103873 (2020).

    Article 

    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).

    Article 

    Google Scholar 

  • Pearce, J. M. Building research equipment with free Open-Source Hardware. Science 337, 1303–1304 (2012).

    ADS 
    CAS 
    Article 

    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).

    Article 

    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).

    Article 

    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).

    CAS 
    Article 

    Google Scholar 

  • Berger-Tal, O. & Lahoz-Monfort, J. J. Conservation technology: the next generation. Conserv. Lett. 11, 1–6 (2018).

    Article 

    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).

    Article 

    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).

    Article 

    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).

    Article 

    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).

    ADS 
    Article 

    Google Scholar 

  • Gorelick, N. et al. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).

    ADS 
    Article 

    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).

    MathSciNet 
    Article 

    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).

    Article 

    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).

    Article 

    Google Scholar 

  • Cooper, R. G. What’s next?: After stage-gate. Res.-Technol. Manag. 57, 20–31 (2014).

    ADS 

    Google Scholar 

  • Cooper, R. G. The drivers of success in new-product development. Ind. Mark. Manag. 76, 36–47 (2019).

    Article 

    Google Scholar 

  • Pearce, J. M. The case for open source appropriate technology. Environ. Dev. Sustain. 14, 425–431 (2012).

    Article 

    Google Scholar 

  • Mair, J., Battilana, J. & Cardenas, J. Organizing for society: A typology of social entrepreneuring models. J. Bus. Ethics 111, 353–373 (2012).

    Article 

    Google Scholar 

  • Meissner, D. Public-private partnership models for science, technology, and innovation cooperation. J. Knowl. Econ. 10, 1341–1361 (2019).

    Article 

    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).

    Article 

    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).

    Article 

    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).

    Article 

    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

    European-wide forest monitoring substantiate the neccessity for a joint conservation strategy to rescue European ash species (Fraxinus spp.)

    Finding her way to fusion