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  • Cambridge University Press (CUP)  (2)
  • 2020-2024  (2)
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  • Cambridge University Press (CUP)  (2)
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  • 2020-2024  (2)
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  • 1
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 2021
    In:  The Journal of Agricultural Science Vol. 159, No. 7-8 ( 2021-09), p. 500-510
    In: The Journal of Agricultural Science, Cambridge University Press (CUP), Vol. 159, No. 7-8 ( 2021-09), p. 500-510
    Abstract: Tossa ( Corchorus olitorius L.) is a significant cash crop, cultivated commercially in the lower flood plain of Bangladesh. The climatic regimes in Bangladesh are changing as well as the world does. However, this species is threatened by climate change. Occurrences of data on threatened and endangered species are frequently sparse which makes it difficult to analyse the species suitable habitat distribution using various modelling approaches. The current paper used maximum entropy (Maxent) and educational global climate model (EdGCM) modelling to predict and conserve the suitable habitat distributions for Tossa species in Bangladesh to the year 2100. Nine environmental variables, 239 occurrence data and two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) were used for the Maxent modelling to project the impact of climate change on the Tossa distributions. Furthermore, the EdGCM was used to study the climatic space suitability for the Tossa species in the context of Bangladesh. Both of the climatic scenarios were used for the prediction to the year 2100. The Maxent model performed better than random for the Tossa species with a high AUC value of 0.86. Under the RCP scenarios, the Maxent model predicted habitat reduction for RCP4.5 is 2%, RCP8.5 is 9% and EdGCM is 10.2% from the current localities. The predictive modelling approach presented here is promising and can be applied to other important species for conservation planning, monitoring and management, especially those under the threat of extinction due to climate change.
    Type of Medium: Online Resource
    ISSN: 0021-8596 , 1469-5146
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2021
    detail.hit.zdb_id: 1498349-7
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  • 2
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 2020
    In:  The Journal of Agricultural Science Vol. 158, No. 6 ( 2020-08), p. 471-478
    In: The Journal of Agricultural Science, Cambridge University Press (CUP), Vol. 158, No. 6 ( 2020-08), p. 471-478
    Abstract: Longan is an economically important sub-tropical fruit tree native to southern China and southeast Asia. Its production has been affected significantly by climate change, but the underlying reasons remain unclear. Herein, the potential growing areas of longan were simulated by the Maxent model under current and future conditions. The results showed excellent prediction performance, with an area under curve of 〉 0.9 for model training and validation. The key environmental variables identified were mean temperature of the coldest quarter, minimum temperature of the coldest month, annual mean temperature and mean temperature of the driest quarter. The optimum suitable areas of longan were found to be concentrated mainly in south-western, southern and eastern China, with a slight increase in optimum suitable areas under two different emission scenarios of three global climatic models. However, its future potential growing areas were predicted to differ among provinces or cities. Suitable growing areas in Sichuan, Jiangxi, Guangxi and Chongqing will first increase and then remain approximately unchanged between the 2050s and 2070s; those in Yunnan, Guangdong and Hainan will remain approximately unchanged from the present to the 2070s; those in Fujian and Guizhou will fluctuate slightly from the present to the 2050s and then increase to the 2070s; those in Taiwan will first decrease and then increase. In summary, the major future production areas of longan will be Guangdong, Hainan and Guangxi provinces, followed by Chongqing, Yunnan, Fujian and Taiwan. Thus, this study serves as a useful guide for the management of longan.
    Type of Medium: Online Resource
    ISSN: 0021-8596 , 1469-5146
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1498349-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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