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Effects of forest cover on richness of threatened fish species in Japan
- Publication Year :
- 2022
-
Abstract
- Estuaries -- one of the most vulnerable ecosystems globally -- face anthropogenic threats, including biodiversity loss and the collapse of sustainable fisheries. Determining the factors contributing to the maintenance of estuarine biodiversity, especially that of fish, is vital for promoting estuarine conservation and sustainability. We used environmental DNA metabarcoding analysis to determine fish species composition in 22 estuaries around Japan and measured watershed-scale land-use factors (e.g., population size, urban area percentage, and forest area percentage). We sought to test the hypothesis that the richness of the most vulnerable estuarine fish species (i.e., registered by the Japanese Ministry of the Environment in the national species red-list) is determined by watershed-scale land-use factors. The richness of such species was greater where forest cover was highest; thus, forest cover contributes to their conservation. The proportion of agriculture cover was associated with low species richness of red-listed fishes (redundancy analysis, adjusted R² = 43.9% of total variance, df = 5, F = 5.3843, p = 0.0001). The number of red-listed species increased from 3 to 12 along a watershed land-use gradient ranging from a high proportion of agriculture cover to a large proportion of forest cover. Furthermore, the results showed that throughout Japan all the examined watersheds that were covered by >74.8% forest had more than the average (6.7 species per site) richness of red-listed fish species. This result can be attributed to the already high average forest cover in Japan of 67.2%. Our results demonstrate how the land use of watersheds can affect the coastal sea environment and its biodiversity and suggest that proper forest management in conjunction with land-use management may be of prime importance for threatened fish species and coastal ecosystems in general.
Details
- Database :
- OAIster
- Notes :
- English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1458639681
- Document Type :
- Electronic Resource