The inertia of C gains in grasslands and shrublands of South America: Changes across environmental gradients

Background/Question/Methods

Global climate models predict an increased incindence of extreme weather events, such as droughts. Given the documented regional relationship between precipitation and primary production, we expect that grasslands and shrublands (from semi-arid to sub-humid) be among the most affected biomes. The effects of these extreme weather events on carbon gains is expected to be also  deferred, as vegetation in these systems shows inertial dynamics partially associated to its dependence on water resources. 

         In order characterize the inertial dynamics of carbon gains and the effects of extreme precipitation events we constructed monthly time series of spectral estimators of aboveground net primary production from 1982 to the present, by splicing NDVI images from LTDR and MODIS satellite platforms and applying local calibrations of the Monteith model. Monthly precipitation was obtained from ground weather stations or from the TRMM mission . These estimates were obtained for an environmental gradient that encompass from the Patagonian steppes in southern Argentina (MAP < 200 mm, MAT < 10°C) to the Rio de la Plata grasslands in northern Uruguay (MAP > 1000 mm, MAT > 15°C).  

The ANPP and precipitation time series were decomposed in trend, seasonal and residual components. We estimated the autocorrelation and partial autocorrelation functions of the residual time series, in order to study the serial dependencies (inertia) not associated to the trends or seasonal dynamics. These analyses were done also for the available precipitation series. We also constructed the empirical residual distribution in order to establish the incidence of monthly ANPP and precipitation below those expected under the mean and seasonal behaviour.  The correlation between the residual series from ANPP and precipitation was estimated and its significance assesed by means of bootstrap.      

Results/Conclusions

We found that the inertia in ANPP (as assessed by the maximum significant lag in the correlation functions) is in general greater in the drier portion of the gradient, the patagonian steppes. We found also that the incidence of negative anomalies (residual ANPP and precipitation) is increasing in magnitude and frequencies. The correlation between the negative anomalies of ANPP of precipitation is slightly higher in the drier portion of the gradient.