Environmental DNA (eDNA) based fish biodiversity assessment of 2 two Himalayan rivers of Nepal reveals diversity differences and 3 highlights new species distribution records

Abstract

between the two sites indicated low similarity in fish diversity between the TR and KR. This study 48 demonstrated the utility of eDNA as a non-invasive technique for biodiversity assessment which 49 is particularly useful in areas like Nepal with scarce data on fish species distribution.

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Nepal is rich in water resources with over 745,000 hectares of land being covered with water (1). 52 This has made Nepal a country with the highest per capita hydropower potentials in the world with  altering, fragmenting or entirely destroying aquatic habitats (7). An increasing demand for 68 renewable energy has resulted in an accelerated growth in hydropower development across the 69 world including Nepal, impacting the aquatic biodiversity of previously free-flowing rivers (8,9). 70 Incorporation of various mitigation and management measures, such as carefully designed 71 construction plan, a comprehensive environmental impact assessments (EIA), habitat restoration, 72 along with stringently enforced conservation laws can prevent or mitigate potential harmful impact This manuscript is a preprint and has not been peer reviewed. The copyright holder has made the manuscript available under a Creative Commons Attribution 4.0 International (CC BY) license and consented to have it forwarded to EarthArXiv for public posting. license EarthArXiv 4 73 on aquatic ecosystems. For this, it is critical to assess status of river systems so as to generate 74 robust baseline datasets that can be used for successful EIA to monitor potential impacts of human 75 activities (10).

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Environmental DNA (eDNA) analysis is a scientific technique that involves the use of genetic 78 material collected from a given environment to identify and monitor presence and abundance of 79 species in that ecosystem (11). This analysis has been used as a rapid assessment tool not only to 80 evaluate existing biodiversity but also to monitor the extent and magnitude of biodiversity loss.

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Fish species monitoring has traditionally been conducted through physical sampling followed by   After initial quality assessment of raw MiSeq reads using FastQC v0.11.9 (15), and filtering using 176 Trimmomatic v0.39 (16), the cleaned reads were processed using QIIME2 v2021.11.0 pipeline 177 (17). We performed de-noising of paired-end reads by trimming, merging and removing chimeric 178 sequences using the DADA2 plugin (18). We processed the denoised sequences for fish DNA 179 filtering, which will only retain sequences belonging to fishes and filters out all other non-fish

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This manuscript is a preprint and has not been peer reviewed. The copyright holder has made the manuscript available under a Creative Commons Attribution 4.0 International (CC BY) license and consented to have it forwarded to EarthArXiv for public posting. license EarthArXiv

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Fish diversity comparisons between two river systems 206 We analyzed fish diversity within (alpha diversity) and between (beta diversity) the two study river having sequencing depth less than the diversity value were excluded from this diversity analyses. 214 We analyzed the rarefied abundance data with a Kruskal-Wallis pairwise test to evaluate the alpha-

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This manuscript is a preprint and has not been peer reviewed.  Barilius bendelisis MN178258 Least concern 4 Barilius vagra MN178261 Least concern 5 Botia lohachata MN178273 Least concern 6 Channa gachua MN178287 Least concern 7 Crossocheilus MN178267 Least concern 8 Glyptothorax gracilis MK993528 Data Deficient 9 Glyptothorax trilineatus MN172316 Least concern 10 Labeo bata MN178270 Least concern 11 Labeo boggut MN172308 Least concern 12 Mastacembelus armatus MN178296 Least concern 13 Neolissochilus hexagonolepis taxonomy at either family, genus or species level (Fig 3, S1 table). About 16% of ASVs were 251 unassigned, because they did not meet consensus taxonomy assignment thresholds. We identified 252 24 OTUs in the TR and 46 OTUs in the KR. Among these, 19 OTUs were common in both river 253 basins, 27 were found only in KR and five were found only in TR (S1 Table and     tests, the alpha diversity in TR was significantly lower than KR (Fig 5). distances. This large difference in beta diversity index between the two river systems indicates a 294 low level of similarity in fish diversity between TR and KR river systems (Fig 6).   cause for concern. Because many of these species are food fishes, and eDNA can come from fish for Nepali fishes presented here will be extremely beneficial to facilitate species monitoring.

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This manuscript is a preprint and has not been peer reviewed. The copyright holder has made the manuscript available under a Creative Commons Attribution 4.0 International (CC BY) license and consented to have it forwarded to EarthArXiv for public posting.

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This manuscript is a preprint and has not been peer reviewed. The copyright holder has made the manuscript available under a Creative Commons Attribution 4.0 International (CC BY) license and consented to have it forwarded to EarthArXiv for public posting. license EarthArXiv