Two morphologically distinct new species of Nanhaipotamon Bott, 1968, are described from Huizhou, Guangdong Province, southern China. The smooth carapace and lack of flagellum on the third maxilliped exopod immediately separate N. incendium n. sp. from all other known Nanhaipotamon. It is also the first species of this genus to be recorded from a relatively high altitude of 700 m a.s.l. Nanhaipotamon aureomarginatum n. sp. is externally much more typical of species of its genus but can be distinguished from congeners by its unique male first gonopod. The two new species are more or less sympatric with a morphological disparate congener, which we tentatively assign as N. aff. aculatum Dai, 1997 and N. aff. hongkongense (Shen, 1940), respectively, but with different habitats. A genetic analysis using the mitochondrial cytochrome oxidase subunit I shows that while the two new species are sufficiently distinct from other known species of Nanhaipotamon, they have extraordinarily close relationships with their respective sympatric congeners, which calls for further investigation. The ecology of these two new species are also noted.
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http://dx.doi.org/10.11646/zootaxa.5026.2.4 | DOI Listing |
BMC Res Notes
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Bioinformatics Center, North-Eastern Hill University, Shillong, 793022, India.
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School of Life Sciences, Yunnan Normal University, Kunming, 650000, China.
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Biotechnology Major, Sangmyung University, Seoul, 03016, South Korea.
Numerous studies have proven the potential of deep learning models for classifying wildlife. Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade. Although deep learning models typically perform better with more input data, the available wildlife data are ordinarily limited, specifically for rare or endangered species.
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