OOS 43-6 - Testing the State-Factors-Interactive-Controls hypothesis using eddy covariance

The state factor-interactive-controls hypothesis is a pervasive concept in ecosystem ecology. The concept is adopted by ecologists whenever a gradient analysis is used (a chrono-sequence or a climate gradient). In this framework ecosystem processes are controlled by state factors that are not themselves influenced by ecosystem processes at local scales. The state factors in this framework are climate, potential biota, topography, geological parent material, and time. Because whole ecosystem process measurements are labor intensive and seldom measured in a consistent way, it has been challenging to test this framework in terrestrial ecosystems. The last two decades have seen the growth of the Ameriflux network in North America; similar measurements of ecosystem carbon, water and energy exchange made across a wide range of ecosystem types. We tested whether gross primary productivity, estimated using the eddy covariance method across 40 ecosystems in North America conformed to the State-Factor-Interactive-Controls hypothesis. To estimate state factors we combined satellite observations, digital elevation models, geological and soil maps and climate re-analysis. By limiting our analysis to sites with more than 8 years of data we were able to remove the effect of short term direct controls (light, temperature, moisture etc) on gross primary productivity. We found significant interactive effects of climate and geological substrate (p < 0.05) and a strong direct effect of climate on average gross primary productivity (p < 0.05). We also found a strong effect of biota on the variation that was not explained by state factors. Together these findings provide support for the state factors-interactive-controls hypothesis and suggest new opportunities for ecological synthesis using networks of ecological data. We also demonstrate how this approach can be used to more robustly benchmark and improve terrestrial biosphere models.