Assessing conservation efforts against threats to wild orchids in China

Liu, Hong; Liu, Zhong‐Jian; Jin, Xiao‐Hua; Gao, Jiang-Yun; C, Yan; Liu, Qiang; Zhang, Diyang

doi:10.1016/j.biocon.2020.108484

Cited by 28 publications

(19 citation statements)

References 30 publications

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“…Our results confirmed that many orchid species need conservation (Dixon 2003; Fay 2018; Wraith & Pickering 2018; Liu et al. 2020). There is an abundance of expertise and information available to successfully implement conservation strategies for both terrestrial (Swarts & Dixon 2009, 2017) and epiphytic species (Cribb et al.…”

Section: Discussionsupporting

confidence: 85%

Automated conservation assessment of the orchid family with deep learning

Zizka

Silvestro

Vitt

et al. 2020

Conservation Biology

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Section: Discussionsupporting

confidence: 85%

Automated conservation assessment of the orchid family with deep learning

Zizka

Silvestro

Vitt

et al. 2020

Conservation Biology

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“…Orchids are the second largest flowering plant family after Asteraceae. In addition to being an "ideal model" group for research on the biodiversity and evolution of interactions (Selosse, 2014), this family represents a "flagship" group for the protection of endangered plants globally (Liu et al, 2015a(Liu et al, , 2020Zhang et al, 2017). There are nearly 30,000-35,000 species of orchids worldwide (ca.10% of angiosperms; The Plant List, 2013; Chase et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Progress and Prospects of Mycorrhizal Fungal Diversity in Orchids

Yang

et al. 2021

Front. Plant Sci.

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Orchids form mycorrhizal symbioses with fungi in natural habitats that affect their seed germination, protocorm growth, and adult nutrition. An increasing number of studies indicates how orchids gain mineral nutrients and sometime even organic compounds from interactions with orchid mycorrhizal fungi (OMF). Thus, OMF exhibit a high diversity and play a key role in the life cycle of orchids. In recent years, the high-throughput molecular identification of fungi has broadly extended our understanding of OMF diversity, revealing it to be a dynamic outcome co-regulated by environmental filtering, dispersal restrictions, spatiotemporal scales, biogeographic history, as well as the distribution, selection, and phylogenetic spectrum width of host orchids. Most of the results show congruent emerging patterns. Although it is still difficult to extend them to all orchid species or geographical areas, to a certain extent they follow the “everything is everywhere, but the environment selects” rule. This review provides an extensive understanding of the diversity and ecological dynamics of orchid-fungal association. Moreover, it promotes the conservation of resources and the regeneration of rare or endangered orchids. We provide a comprehensive overview, systematically describing six fields of research on orchid-fungal diversity: the research methods of orchid-fungal interactions, the primer selection in high-throughput sequencing, the fungal diversity and specificity in orchids, the difference and adaptability of OMF in different habitats, the comparison of OMF in orchid roots and soil, and the spatiotemporal variation patterns of OMF. Further, we highlight certain shortcomings of current research methodologies and propose perspectives for future studies. This review emphasizes the need for more information on the four main ecological processes: dispersal, selection, ecological drift, and diversification, as well as their interactions, in the study of orchid-fungal interactions and OMF community structure.

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“…It is well established that many species in the Orchid family need conservation attention (Dixon 2003;Wraith & Pickering 2018;Fay 2018;Liu et al 2020), and there is an abundance of expertise and information available to successfully implement conservation strategies for both terrestrial (Swarts & Dixon 2009 and epiphytic species (Cribb et al 2003;Swarts & Dixon 2017;Fay 2018). Most species are facing more than one threat and have limited distributions (Wraith & Pickering 2018).…”

Section: Orchid Extinction Riskmentioning

confidence: 99%

Automated conservation assessment of the orchid family using deep learning

Zizka

Silvestro

Vitt

et al. 2020

Preprint

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IUCN Red List assessments are essential for prioritizing conservation needs but are resourceintensive and therefore only available for a fraction of global species richness. Tropical plant species are particularly under-represented on the IUCN Red List. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. Here, we present automated conservation assessments for 13,910 species of the diverse and globally distributed Orchid family (Orchidaceae), based on a novel method using a deep neural network (IUC-NN), most of which (13,049) were previously unassessed by the IUCN Red List. We identified 4,342 (31.2 % of the evaluated orchid species) as Possibly Threatened with extinction (equivalent to the IUCN categories CR, EN, or VU) and point to Madagascar, East Africa, south-east Asia, and several oceanic islands as priority areas for orchid conservation. Furthermore, the Orchid family provides a model, to test the sensitivity of automated assessment methods to issues with data availability, data quality and geographic sampling bias. IUC-NN identified threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias compared to the IUCN Red List, and was robust against low data availability and geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in achieving goals of identifying the species that are at greatest risk of extinction.

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Assessing conservation efforts against threats to wild orchids in China

Cited by 28 publications

References 30 publications

Automated conservation assessment of the orchid family with deep learning

Automated conservation assessment of the orchid family with deep learning

Progress and Prospects of Mycorrhizal Fungal Diversity in Orchids

Automated conservation assessment of the orchid family using deep learning

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