4.4 Article

Using satellite-derived sea surface temperature to predict the potential global range and phenology of the invasive kelp Undaria pinnatifida

期刊

BIOLOGICAL INVASIONS
卷 17, 期 12, 页码 3393-3408

出版社

SPRINGER
DOI: 10.1007/s10530-015-0965-5

关键词

Invasive species; Wakame; Seaweed; Biological invasion; Niche shift; Distribution

资金

  1. Auckland Council
  2. Waikato Regional Council

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Understanding the temperature tolerances and phenology of an invasive species is essential to predicting its potential range and impacts on receiving environments. Undaria pinnatifida is a kelp species native to Northern Asian waters where it has a winter annual growth cycle. At some introduced sites U. pinnatifida can persist year-round, which potentially exacerbates its impacts. In this study we synthesise information on the global distribution and phenology of U. pinnatifida and use satellite-derived sea surface temperature (SST) measurements to investigate how distribution and phenology relate to temperature regime. These relationships are used to predict the potential global range and phenology of U. pinnatifida. The overall thermal limits of U. pinnatifida were considered to be the areas where the range in SST minima overlaps with the range in SST maxima for existing populations. Undaria pinnatifida was found to occur in regions with maximum temperatures of 13.5-29.5 A degrees C and minimum temperatures of 0.1-15.5 A degrees C. The SST regime differed between native and introduced locations, and between locations with year-round and annual populations. All locations with year-round populations had a maximum SST < 20 A degrees C, whereas annual populations had maximum SST > 20 A degrees C; a finding consistent with the reported thermal parameters for U. pinnatifida gametogenesis. These results demonstrate that extensive areas of the world's coastline have SST regimes suitable for U. pinnatifida colonisation and are potentially at risk from invasion. When considered in combination with additional environmental factors influencing distribution success, this type of prediction mapping provides a valuable tool for invasive species management.

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