Your browser doesn't support javascript.
loading
Long-term monitoring dataset of fish assemblages in rocky tidepools on the southern coast of Taiwan.
Ho, Lin-Tai; Wang, Shen-Chih; Shao, Kwang-Tsao; Chen, I-Shiung; Chen, Hungyen.
Afiliação
  • Ho LT; Institute of Marine Biology, National Taiwan Ocean University, Keelung, 20224, Taiwan.
  • Wang SC; National Museum of Marine Science and Technology, Keelung, 20248, Taiwan.
  • Shao KT; Institute of Marine Biology, National Taiwan Ocean University, Keelung, 20224, Taiwan.
  • Chen IS; National Museum of Marine Science and Technology, Keelung, 20248, Taiwan.
  • Chen H; Biodiversity Research Center, Academia Sinica, Taipei, 11529, Taiwan.
Sci Data ; 9(1): 639, 2022 10 21.
Article em En | MEDLINE | ID: mdl-36271001
Long-term data of fish assemblages collected in the rocky intertidal zone provides a valuable resource for elucidating the temporal variations in species diversity and intertidal ecosystems. In this study, we describe a long-term time-series dataset of fish collected by counting the number of anesthetized fish at sampling stations in the rocky tidepools on the southern coast of Taiwan. The species assemblages were monitored seasonally at the two stations for 16 y (2000-2008 and 2012-2018). In total, 86 samples containing 5137 individuals belonging to 82 species were recorded. Our data can be used for elucidating the temporal variations in fish assemblages and intertidal ecosystems and as background information for the resilience of the fish community conservation in coastal areas. The current study presents valuable data for researchers to understand the temporal and spatial variations in species abundance, richness, diversity, and composition in relation to climate change, environmental factors, and human activities.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Peixes Limite: Animals / Humans País/Região como assunto: Asia Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Taiwan

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Peixes Limite: Animals / Humans País/Região como assunto: Asia Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Taiwan