Wednesday, March 23, 2011

Climatological determinants of woody cover in Africa, by S. P. Good & K. K. Caylor, PNAS, Vol. 108, No. 12

PNAS (March 22, 2011), Vol. 108, No. 12, pp. 4902-4907;  doi: 10.1073/pnas.1013100108



Climatological determinants of woody cover in Africa

  1. Stephen P. Good1 and 
  2. Kelly K. Caylor
  1. Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
  1. Edited* by Ignacio Rodriguez-Iturbe, Princeton University, Princeton, NJ 08544, and approved January 28, 2011 (received for review September 3, 2010)

Abstract

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that—as opposed to a relationship with only mean annual rainfall—the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.

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