Dataset Information

Annual patterns of macroalgal blooms in the Yellow Sea during 2007-2017.

ABSTRACT: The world's largest macroalgal blooms caused by Ulva prolifera have occurred in the Yellow Sea for 11 consecutive years. The area covered by blooms has been approximately 500 km2 in previous years, while in 2017, the maximum area decreased significantly to 312 km2. In this study, we concluded that species competition between Ulva and Sargassum (fast rise of the golden tides), extreme high sea surface temperature and harvest for floating Ulva macroalgae were the three critical factors influencing the sharp reduction in covered area for blooms in 2017. In addition, analysis of annual variations of Pyropia aquaculture area in the Southern Yellow Sea over the past two decades revealed that a great expansion in "Sansha" regions was mainly responsible for the initial blooms in 2007, and that this expansion supported the great biomass of the blooms in following years. Based on these findings, we suggest comprehensive utilization of the macroalgal blooms is a feasible way to control them.

SUBMITTER: Zhang J

PROVIDER: S-EPMC6331115 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Annual patterns of macroalgal blooms in the Yellow Sea during 2007-2017.

Zhang Jianheng J Shi Jinting J Gao Song S Huo Yuanzi Y Cui Jianjun J Shen Hui H Liu Guiyan G He Peimin P

PloS one 20190114 1

The world's largest macroalgal blooms caused by Ulva prolifera have occurred in the Yellow Sea for 11 consecutive years. The area covered by blooms has been approximately 500 km2 in previous years, while in 2017, the maximum area decreased significantly to 312 km2. In this study, we concluded that species competition between Ulva and Sargassum (fast rise of the golden tides), extreme high sea surface temperature and harvest for floating Ulva macroalgae were the three critical factors influencing ...[more]

PMID: 30640934

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Project description:Conservation of long-distance migratory species poses unique challenges. Migratory connectivity, that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas, is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration by feeding extensively and, in some cases, molting their flight feathers. These additional migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess linkages between discrete locations or entities, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of 672 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of breeding, molting, wintering, and migratory staging. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual cycle movement patterns, including the central importance of staging and molting sites in James Bay, the St. Lawrence River, and southern New England to multi-species annual cycle habitat linkages, and highlight the value of Long-tailed Ducks (Calengula haemalis) as an umbrella species to represent the movement patterns of multiple sea duck species. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

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Dataset Information

Annual patterns of macroalgal blooms in the Yellow Sea during 2007-2017.

Publications

Annual patterns of macroalgal blooms in the Yellow Sea during 2007-2017.

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