Print PageUnderstanding the factors that drive the dynamic nature of aboveground net primary productivity (ANPP) is a focus for many ecological studies. Precipitation is known to play an important role in limiting ANPP and shifts in precipitation totals, seasonality, and variability are predicted with climate change. Previous studies at individual sites show that seasonal precipitation amounts can explain more variability in ANPP than annual totals. We examined whether ANPP is more sensitive to seasonal precipitation amounts than annual precipitation and if the response to seasonal precipitation depends on ecosystem type or plant functional group. We used long term ANPP data from 14 sites with a total of 36 different plant communities to test whether seasonal precipitation correlated with ANPP better than total annual precipitation. We created five ‘seasons’ by estimating the length of the growing season and dividing it into three equal parts and incorporated carryover effects by including an equal length pre-growing season period. The rest of the year was included as a dormant period, stretching from then end of the previous growing season to the start of the pre-season. Models including these periods, alone and in combination were compared using AICc to models using total precipitation to explain ANPP.
Results/Conclusions
Of the 36 individual community-level ANPP records examined, 21 had statistically supported models where precipitation explained annual variance in ANPP. Precipitation during the middle of the growing season was the most common predictor in the best models, showing up in almost half of the significant models. The other two periods of the growing season were the next most common predictors. Total precipitation was the single best predictor of ANPP in only three cases, although it tied with a seasonal model for the best model in several cases. Including seasonal precipitation as a predictor increased the amount of variation explained using adjusted R2 by up to 0.77. Improvements in models including seasonal precipitation were not correlated with ecosystem type or plant growth form. Our results indicate that examining precipitation amounts during specific parts of the year, even done in a simple manner, can significantly improve predictions of ANPP across a wide range of ecosystems and plant types. These broad results have important implications for attempts to predict ANPP due to current variation in precipitation and with future climate change.
