Partitioning interannual variability in net ecosystem exchange between climatic variability and functional change

Interannual. variability (IAV) in net ecosystem exchange of carbon (NEE) is a critical factor in projections of future ecosystem changes. However, our understanding of IAV is limited because of the difficulty in isolating its numerous causes. We proposed that IAV in NEE is primarily caused by climatic variability, through its direct effects on photosynthesis and respiration and through its indirect effects on carbon fluxes (i.e., the parameters that govern photosynthesis and respiration), hereafter called functional change. We employed a homogeneity-of-slopes model to identify the functional change contributing to IAV in NEE and nighttime ecosystem respiration (R-E). The model uses multiple regression analysis to relate NEE and R-E with climatic variables for individual years and for all years. If the use of different slopes for each year significantly improves the model fitting compared to the use of one slope for all years, we consider that functional change exists, at least on annual time scales. With the functional change detected, we then partition the observed variation in NEE or R-E to four components, namely, the functional change, the direct effect of interannual climatic variability, the direct effect of seasonal climatic variation, and random error. Application of this approach to a data set collected at the Duke Forest AmeriFlux site from August 1997 to December 2001 indicated that functional change, interannual climatic variability, seasonal climatic variation and random error explained 9.9, 8.9, 59.9 and 21.3%, respectively, of the observed variation in NEE and 13.1, 5.0, 38.1 and 43.8%, respectively, of the observed variation in R-E.