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      Predicting the potential distribution of Dactylorhiza hatagirea (D. Don) Soo-an important medicinal orchid in the West Himalaya, under multiple climate change scenarios

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          Abstract

          Climate variability coupled with anthropogenic pressures is the most critical driver in the Himalayan region for forest ecosystem vulnerability. Dactylorhiza hatagirea (D.Don) Soo is an important yet highly threatened medicinal orchid from the Himalayan region. Poor regenerative power and growing demand have resulted in the steep decline of its natural habitats populations. The present study aims to identify the habitat suitability of D. hatagirea in the Western Himalaya using the maximum entropy model (MaxEnt). The community climate system model (CCSM ver. 4) based on representative concentration pathways (RCPs) was used to determine suitable future areas. Sixteen least correlated (< 0.8) bioclimatic, topographical and geomorphic variables were used to construct the species climatic niche. The dominant contributing variables were elevation (34.85%) followed by precipitation of the coldest quarter (23.04%), soil type (8.77%), land use land cover (8.26%), mean annual temperature (5.51%), and temperature seasonality (5.11%). Compared to the present distribution, habitat suitability under future projection, i.e., RCP 4.5 and RCP 8.5 (2050 and 2070), was found to shift to higher elevation towards the northwest direction, while lower altitudes will invariably be less suitable. Further, as compared to the current distribution, the climatic niche space of the species is expected to expand in between11.41–22.13% in the near future. High habitats suitability areas are mainly concentrated in the forest range like Dharchula and Munsyari range, Pindar valley, Kedarnath Wildlife Sanctuary, West of Nanda Devi Biosphere Reserve, and Uttarkashi forest division. The present study delineated the fundamental niche baseline map of D. hatagirea in the Western Himalayas and highlighted regions/areas where conservation and management strategies should be intensified in the next 50 years. In addition, as the species is commercially exploited illegally, the information gathered is essential for conservationists and planners who protect the species at the regional levels.

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          A Coefficient of Agreement for Nominal Scales

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            Maximum entropy modeling of species geographic distributions

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              Novel methods improve prediction of species’ distributions from occurrence data

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                Author and article information

                Contributors
                Role: InvestigationRole: MethodologyRole: SoftwareRole: Writing – original draft
                Role: InvestigationRole: MethodologyRole: SoftwareRole: Writing – original draft
                Role: ConceptualizationRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                17 June 2022
                2022
                : 17
                : 6
                : e0269673
                Affiliations
                [1 ] Center for Biodiversity Conservation and Management, G. B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, Uttarakhand, India
                [2 ] Center for Environment Assessment and Climate Change, G. B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, Uttarakhand, India
                [3 ] Department of Botany, D. S. B. Campus, Kumaun University, Nainital, Uttarakhand, India
                Instituto Federal de Educacao Ciencia e Tecnologia Goiano - Campus Urutai, BRAZIL
                Author notes

                Competing Interests: No authors have competing interest

                Author information
                https://orcid.org/0000-0003-0063-9050
                Article
                PONE-D-21-16347
                10.1371/journal.pone.0269673
                9205508
                9b8a6028-ce0c-4d41-a335-0a9cfc9255fc
                © 2022 Singh et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 May 2021
                : 25 May 2022
                Page count
                Figures: 7, Tables: 4, Pages: 19
                Funding
                No funding available of this work
                Categories
                Research Article
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Change
                Biology and Life Sciences
                Ecology
                Habitats
                Ecology and Environmental Sciences
                Ecology
                Habitats
                Biology and Life Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Terrestrial Environments
                Forests
                Biology and Life Sciences
                Ecology
                Ecological Niches
                Ecology and Environmental Sciences
                Ecology
                Ecological Niches
                Earth Sciences
                Atmospheric Science
                Meteorology
                Snow
                Ecology and Environmental Sciences
                Conservation Science
                Research and Analysis Methods
                Simulation and Modeling
                Climate Modeling
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Modeling
                Earth Sciences
                Geography
                Cartography
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                All relevant data are in the paper and supporting information files.

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