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首页> 外文期刊>Current Science: A Fortnightly Journal of Research >Inventory and characterization of new populations through ecological niche modelling improve threat assessment
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Inventory and characterization of new populations through ecological niche modelling improve threat assessment

机译：通过生态利基模型的新群体的库存与表征改善威胁评估

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Categorization of species under different threat classes is a pre-requisite for planning, management and monitoring of any species conservation programme. However, data availability, particularly at the population level, has been a major bottleneck in the correct categorization of threatened species. Till date, threat assessments have been mostly based on expert opinion and/or herbarium records. The availability of primary data on distribution of species and their population attributes is limited in India because of inadequate field survey, which has been ascribed to resource constraints and inaccessibility. In this study, we demonstrate that ecological niche modelling (ENM) can be an economical and effective tool to guide surveys overcoming the above two constraints leading to the discovery of new populations of threatened species. Such data lead to improved threat assessment and more accurate categorization. We selected 14 threatened plants comprising 5 trees (Acer hookeri Miq., Bhesa robusta (Roxb.) Ding Hou, Gynocardia odorata Roxb., Ilex venulosa Hook. f. and Lagerstroemia minu-ticarpa Debb. ex P.C. Kanjilal), 8 herbs (Angelica glauca Edgew., Aquilegia nivalis Falc. ex Jackson, Artemisia amygdalina DC., Begonia satrapis C.B. Clarke, Corydalis cashmeriana Royle, Dactylorhiza hatagirea (D. Don) Soo, Podophyllum hexandrum Royle, and Rheum australe D. Don), and 1 pteridophyte (Angiopteris evecta (Forst.) Hoffm.) having distribution range in North East India, Eastern and Western Himalaya, and Jammu and Kashmir. The study was carried out between 2012 and 2016. ENM-based survey led to the discovery and characterization of 348 new populations. The data so obtained helped in assigning conservation status to 10 species, which earlier were never classified due to data deficiency. Using the new population and distribution data of the remaining four species, only one was confirmed regarding its existing status and two species were classified as 'Critically endangered' instead of the present classification as 'Endangered'. The fourth species was classified as 'Critically endangered' against the earlier category of 'Least concerned'.
机译：不同威胁类别下物种的分类是规划，管理和监测任何物种保护计划的先决条件。但是，数据可用性，特别是在人口层面，这是正确分类威胁物种的主要瓶颈。截至日期，威胁评估主要基于专家意见和/或植物标目记录。由于实地调查不足，印度的物种分布及其人口属性的主要数据的可用性是有限的，这已经归因于资源限制和可接近性。在这项研究中，我们证明了生态利基造型（eNM）可以是一种经济且有效的工具，可以导致调查克服上述两个限制，导致发现威胁物种的新群体。这些数据导致改善威胁评估和更准确的分类。我们选择了14种威胁的植物，包括5棵树（宏碁Hookeri Miq。，伯肯·罗布斯塔（Roxb）丁侯，Gynocardia Odorata Roxb。F。和Lagerstroemia minu-ticarpa博士。前PC Kanjilal），8草药（Angelica） Glauca Edgew。，Aquilegia Nivalis Falc。前杰克逊，艾蒿amygdalina dc。，秋海棠Satrapis CB Clarke，Corydalis Cashmeriana Royle，Dactylorhiza Hatagirea（D. Don）Soo，Podophyllum Hexandrum Royle和Rheum Australe D. Don）和1奈瑟翁（ Angiopteris Eventa（Forst。）霍夫姆。）在西北印度，东方和西方喜马拉雅亚和Jammu和Kashmir的分销范围。该研究是在2012年和2016年间进行的。基于恩马的调查导致了348个新人的发现和表征。如此获得的数据有助于将节约状态分配给10种，由于数据缺乏，早期从未被分类过。使用剩余四种物种的新人口和分布数据，只有一个人确认其现有地位，两种物种被归类为“危险地濒危”而不是“濒临威胁”的分类。第四种物种被归类为“严重濒临灭绝”的“最不明关联”。

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