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A long-term monitoring dataset of fish assemblages in rocky tidepools on the northern coast of Taiwan.
Ho, Lin-Tai; Wang, Shen-Chih; Shao, Kwang-Tsao; Chen, I-Shiung; Chen, Hungyen.
Afiliación
  • Ho LT; National Museum of Marine Science and Technology, Keelung, 20248, Taiwan.
  • Wang SC; Institute of Marine Biology, National Taiwan Ocean University, Keelung, 20224, Taiwan.
  • Shao KT; National Museum of Marine Science and Technology, Keelung, 20248, Taiwan.
  • Chen IS; National Museum of Marine Science and Technology, Keelung, 20248, Taiwan.
  • Chen H; Institute of Marine Biology, National Taiwan Ocean University, Keelung, 20224, Taiwan.
Sci Data ; 7(1): 84, 2020 03 09.
Article en En | MEDLINE | ID: mdl-32152315
The assemblage of fish species in the rocky intertidal zone is highly affected by the destructive impact of human activities and has an extended impact on land-sea interactions. There are a few long-term research projects that have focused on rocky intertidal ecosystems, especially on the resident fish community. Here, we describe a long-term time series dataset of fish collected by counting the number of anesthetized fishes at sampling stations in rocky tidepools in the intertidal zones on the northern coast of Taiwan. The species assemblages were monitored seasonally at three stations from 1999 to 2018. In total, 144 samples containing 1,577 individuals belonging to 106 species were recorded in the surveys. The resulting data can be used as background information for conservation and resilience studies of the fish community in coastal areas and to establish reasonable conservation strategies. This study presents valuable data to ecologists and fisheries biologists interested in understanding the temporal patterns of species abundance, richness, and composition in relation to environmental factors, climate change, and anthropogenic pressures.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ecosistema / Conservación de los Recursos Naturales / Peces Límite: Animals País/Región como asunto: Asia Idioma: En Revista: Sci Data Año: 2020 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ecosistema / Conservación de los Recursos Naturales / Peces Límite: Animals País/Región como asunto: Asia Idioma: En Revista: Sci Data Año: 2020 Tipo del documento: Article País de afiliación: Taiwán