thu_further_reading.Rmd

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title: "Further reading"
output: html_document
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# Further reading

1.  Dauby, G, Stévart, T, Droissart, V, et al. ConR: An R package to assist large‐scale multispecies preliminary conservation assessments using distribution data. Ecol Evol. 2017; 7: 11292– 11303. https://doi.org/10.1002/ece3.3704 

2. Tara A. Pelletier, Bryan C. Carstens, David C. Tank, Jack Sullivan, Anahí Espíndola (2019) Predicting plant conservation priorities on a global scale
Proceedings of the National Academy of Sciences, 115 (51) 13027-13032; DOI: 10.1073/pnas.1804098115

3. Zizka, A., Silvestro, D., Vitt, P. and Knight, T.M. (2021), Automated conservation assessment of the orchid family with deep learning. Conservation Biology. https://doi.org/10.1111/cobi.13616

4.  Panter, CT, Clegg, RL, Moat, J, Bachman, SP, Klitgård, BB, White, RL. To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species. Conservation Science and Practice. 2020; 2:e311. https://doi.org/10.1111/csp2.311

5. Walker BE, Leao TCC, Bachman SP, Bolam FC and Nic Lughadha E (2020) Caution Needed When Predicting Species Threat Status for Conservation Prioritization on a Global Scale. Front. Plant Sci. 11:520. doi: 10.3389/fpls.2020.00520