U.S. Geological Survey, Wyoming Cooperative Fish and Wildlife Research Unit, Department 3166, 1000 E. University Avenue, University of Wyoming, Laramie, Wyoming 82071, USA.
lnstituto de Investigaciones Marinas y Costeras (IIMyC), CONICET-Universidad Nacional de Mar del Plata, Juan B. Justo 2550, (7600) Mar del Plata, Argentina.
Ecology. 2013 Oct;94(10):2188-94. doi: 10.1890/13-0445.1.
Global change is leading to shifts in the seasonal timing of growth and maturation for primary producers. Remote sensing is increasingly used to measure the timing of primary production in both aquatic and terrestrial ecosystems, but there is often a poor correlation between these results and direct observations of life-history responses of individual species. One explanation may be that, in addition to phenological shifts, global change is also causing shifts in community composition among species with different seasonal timing of growth and maturation. We quantified how shifts in species phenology and in community composition translated into phenological change in a diverse phytoplankton community from 1962 to 2000. During this time, the aggregate community spring-summer phytoplankton peak has shifted 63 days earlier. The mean taxon shift was only 3 days earlier, and shifts in taxa phenology explained only 40% of the observed community phenological shift. The remaining community shift was attributed to dominant early-season taxa increasing in abundance while a dominant late-season taxon decreased in abundance. In diverse producer communities experiencing multiple stressors, changes in species composition must be considered to fully understand and predict shifts in the seasonal timing of primary production.
全球变化正在导致初级生产者的生长和成熟的季节性时间发生变化。遥感技术越来越多地用于测量水生和陆地生态系统中初级生产的时间,但这些结果与对个别物种生命史响应的直接观测之间往往相关性较差。一种解释可能是,除了物候变化之外,全球变化还导致了具有不同生长和成熟季节性的物种组成的变化。我们从 1962 年到 2000 年,量化了物种物候变化和群落组成变化如何转化为多样性浮游植物群落的物候变化。在此期间,群落春季-夏季浮游植物峰值提前了 63 天。平均分类群的变化仅提前了 3 天,而分类群物候的变化仅解释了观察到的群落物候变化的 40%。剩余的群落变化归因于丰度增加的早期优势种和丰度减少的晚期优势种。在经历多种胁迫的多样生产社区中,必须考虑物种组成的变化,以充分理解和预测主要生产季节性时间的变化。