Replies to Shen, Chen et al., and Yi and Zhou: Linear regression analysis misses effects of winter temperature on Tibetan vegetation uri icon

abstract

  • Shen (2) writes that linear regression could not detect a clear relationship between winter temperatures and beginning of growing season (BGS). This is not surprising. As has been shown many times, the primary driver of spring phenology is spring temperature, and this effect overlays smaller effects of temperature during other parts of the year. To tease such minor effects out of our dataset, we used partial least squares regression, which analyzed the impacts of both winter and spring temperatures on BGS dates. The results of this analysis showed that changes in spring greening resulted from the combined effects of winter and spring warming and not from winter warming alone. Linear regression is unlikely to detect minor effects. We do not understand the reasoning behind separately analyzing subperiods, because the same fundamental processes should determine BGS dates during the entire period, and a model of spring phenology should explain all green-up dates rather than only a selection

publication date

  • 2011
  • 2011