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在当前和未来气候变化情景下的 诊断和潜在入侵风险。

Diagnosis and potential invasion risk of under current and future climate change scenarios.

机构信息

Division of Entomology, Indian Agricultural Research Institute, New Delhi, Delhi, India.

Crop Protection, ICAR-Central Institute for Subtropical Horticulture, Lucknow, Uttar Pradesh, India.

出版信息

PeerJ. 2022 Aug 25;10:e13868. doi: 10.7717/peerj.13868. eCollection 2022.

Abstract

BACKGROUND AND OBJECTIVE

Invasive thrips, Karny recently reported in India, causing a widespread severe infestation in more than 0.4 million ha of chilli ( L.) growing areas. This species is native to Thailand and most prevalent in other South East Asian countries. Large scale cultivation of the major host plants (chilli and papaya), and favourable climatic conditions in India and other countries similar to native range of expected to favour its further spread and establishment to new areas.

MATERIALS AND METHODS

The present study was undertaken to confirm invasive thrips species identity through both morphological and molecular approaches and predict its potential invasion using the maximum entropy (MaxEnt) algorithm.

RESULTS

The model predicted species range in respect of discrimination of suitable and unsuitable areas for its occurrence both in current and future climatic scenarios. The model provided a good fit for species distribution with a high value of area under the curve (0.957). The jackknife test indicated annual mean temperature and precipitation were found to be the most important bioclimatic variable in determining the distribution of . High suitability areas were predicted in the countries wherever its occurrence was reported with high discrimination ability of suitable and unsuitable areas. Key distinguishing morphological characters of were illustrated through high-resolution scanning electron microscopic images.

CONCLUSION

The identity of the thrips causing wide spread damage in chilli confirmed through morphological and molecular approaches. Key identifying characters were described through high resolution scanning electron microscopic images for accurate identification of the species. MaxEnt model identified high suitability regions for the potential establishment of in India and other parts of the world. This study facilitates forecasting of further spread and also suggests imposing strict domestic quarantine measures to curtail its establishment in the new areas.

摘要

背景与目的

最近在印度发现的入侵性蓟马,导致超过 40 万公顷的辣椒(L.)种植区遭受广泛而严重的侵害。这种蓟马原产于泰国,在其他东南亚国家最为普遍。主要寄主植物(辣椒和木瓜)的大规模种植,以及印度和其他与原生范围相似的国家有利的气候条件,预计将有利于其进一步向新地区传播和定殖。

材料与方法

本研究通过形态学和分子学方法来确认入侵性蓟马的物种身份,并利用最大熵(MaxEnt)算法预测其潜在的入侵。

结果

该模型预测了物种的分布范围,以便区分其在当前和未来气候情景下的适宜和不适宜地区。该模型对物种分布的拟合度较好,曲线下面积(AUC)值较高(0.957)。Jackknife 测试表明,年平均温度和降水被认为是决定分布的最重要的生物气候变量。在有报道称其发生的国家,高适宜性地区被预测到,对适宜和不适宜地区的区分能力较高。通过高分辨率扫描电子显微镜图像,展示了入侵性蓟马的关键形态学特征。

结论

通过形态学和分子学方法确认了在辣椒上造成广泛破坏的蓟马的身份。通过高分辨率扫描电子显微镜图像描述了关键的识别特征,以准确鉴定该物种。MaxEnt 模型确定了在印度和世界其他地区入侵性蓟马潜在建立的高适宜性地区。这项研究有助于预测其进一步的传播,并建议实施严格的国内检疫措施,以遏制其在新地区的建立。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6019/9420409/5421318c6e2c/peerj-10-13868-g001.jpg

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