Albani Rocchetti Giulia, Armstrong Chelsey Geralda, Abeli Thomas, Orsenigo Simone, Jasper Caroline, Joly Simon, Bruneau Anne, Zytaruk Maria, Vamosi Jana C
Department of Science, University Roma Tre, Viale G. Marconi, 446, Roma, 00154, Italy.
Indigenous Studies, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
New Phytol. 2021 Apr;230(2):433-450. doi: 10.1111/nph.17133. Epub 2021 Jan 13.
Although often not collected specifically for the purposes of conservation, herbarium specimens offer sufficient information to reconstruct parameters that are needed to designate a species as 'at-risk' of extinction. While such designations should prompt quick and efficient legal action towards species recovery, such action often lags far behind and is mired in bureaucratic procedure. The increase in online digitization of natural history collections has now led to a surge in the number new studies on the uses of machine learning. These repositories of species occurrences are now equipped with advances that allow for the identification of rare species. The increase in attention devoted to estimating the scope and severity of the threats that lead to the decline of such species will increase our ability to mitigate these threats and reverse the declines, overcoming a current barrier to the recovery of many threatened plant species. Thus far, collected specimens have been used to fill gaps in systematics, range extent, and past genetic diversity. We find that they also offer material with which it is possible to foster species recovery, ecosystem restoration, and de-extinction, and these elements should be used in conjunction with machine learning and citizen science initiatives to mobilize as large a force as possible to counter current extinction trends.
虽然植物标本通常并非专门为保护目的而采集,但它们提供了足够的信息来重建将一个物种指定为“濒危”所需的参数。虽然这些指定应该促使针对物种恢复采取迅速有效的法律行动,但这种行动往往远远滞后,并且陷入官僚程序之中。自然历史藏品在线数字化的增加现在导致了关于机器学习用途的新研究数量激增。这些物种出现情况的数据库现在配备了能够识别珍稀物种的先进技术。对导致此类物种数量下降的威胁的范围和严重性估计的关注度增加,将提高我们减轻这些威胁并扭转物种数量下降趋势的能力,克服当前许多受威胁植物物种恢复的障碍。到目前为止,采集的标本已被用于填补系统分类学、分布范围和过去遗传多样性方面的空白。我们发现,它们还提供了能够促进物种恢复、生态系统恢复和复活灭绝物种的材料,并且这些要素应与机器学习和公民科学倡议结合使用,以动员尽可能强大的力量来应对当前的灭绝趋势。