Global change effects on the carbon cycle in arid ecosystems: the Patagonian steppe as a model ecosystem
-------Global change encompasses changes in the composition of the atmosphere, in climate, land use, and biodiversity, all of them ultimately resulting from unprecedented human activity (Walker and Steffen 1996). The four components of global change interact with each other in multiple ways including changes in the composition of the atmosphere (e.g. CO2), which affect climate, and changes in climate and land use, which affect biodiversity. This project addresses the effects of climate and land use change on the functioning of arid ecosystems. We use the Patagonian steppe as a model system. The Patagonian steppe is particularly well suited to test our hypotheses because of the accumulated knowledge, and because of the spatial heterogeneity of this system characterized by a two-phase mosaic vegetation structure. Net primary production and decomposition are fundamental processes in the carbon cycle, controlling the total energy available for ecosystem processes, and ecosystem carbon storage. To a very large extent, our understanding of ecosystems must begin with an understanding of these processes. Despite the fact that we have been studying these processes for the past 30 or more years, there are still a large number of basic questions for which we do not have adequate answers. Ecosystems dominated by perennial grasses are unique among ecosystems in their storage of carbon and biologically active elements in soil organic matter (Clark and Woodmansee 1992). Temperate grasslands have been estimated to contain 18% of global soil C (Ajtay et al. 1979), more than any other ecosystem except tundra. Primary production and climate change: water and nitrogen interactions. A generalization about annual aboveground net primary production (ANPP) in grasslands that has been confirmed repeatedly is that ANPP is linearly related to annual precipitation (Walter 1971, Lauenroth 1979, Rutherford 1980, Sala et al. 1988, Milchunas and Lauenroth 1993). A common feature of all of the models is that they were constructed using geographic data sets. These data sets have typically consisted of pairs of values of ANPP and mean annual precipitation (MAP) for a number of different locations. We refer to these as spatial or regional models. We conducted an analysis of a long-term ANPP data set for a single site that allowed us to ask if a spatial model was applicable to a temporal data set (Lauenroth and Sala 1992). The answer was no and the differences between the spatial and temporal models were very interesting and significant. Inter-annual variability in ANPP was linearly and significantly related to annual precipitation but the slope of the temporal model was less and the intercept greater than the spatial model. This resulted in the temporal model predicting lower ANPP than the spatial model at high values of annual precipitation. Visual examination of the time series of ANPP and annual precipitation revealed some interesting time lags in the recovery of ANPP from dry conditions even when the subsequent precipitation was substantially above the mean. These time lags contributed significantly to the departure of the temporal model from the spatial model at high annual precipitation and suggested the presence of biotic constraints on ANPP. --------One of the objectives of this research project is to understand the mechanisms that result in the observed lags in the recovery of primary production following a drought. We hypothesize that the lags are likely the result of an interaction between population, community, and ecosystem processes. -------We are currently carrying out a manipulative field experiment where we reduced incoming precipitation by 30, 55, and 80% simulating droughts of different intensity.
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