Does N2 fixation amplify the temperature dependence of ecosystem metabolism?. Issue 3 (1st March 2015) - Welter, Jill R.; Benstead, Jonathan P.; Cross, Wyatt F.; Hood, James M.; Huryn, Alexander D.; Johnson, Philip W.; Williamson, Tanner J.
Abstract : Variation in resource supply can cause variation in temperature dependences of metabolic processes (e.g., photosynthesis and respiration). Understanding such divergence is particularly important when using metabolic theory to predict ecosystem responses to climate warming. Few studies, however, have assessed the effect of temperature–resource interactions on metabolic processes, particularly in cases where the supply of limiting resources exhibits temperature dependence. We investigated the responses of biomass accrual, gross primary production (GPP), community respiration (CR), and N2 fixation to warming during biofilm development in a streamside channel experiment. Areal rates of GPP, CR, biomass accrual, and N2 fixation scaled positively with temperature, showing a 32‐ to 71‐fold range across the temperature gradient (~7°–24°C). Areal N2 ‐fixation rates exhibited apparent activation energies (1.5–2.0 eV; 1 eV = ~1.6 × 10 −19 J) approximating the activation energy of the nitrogenase reaction. In contrast, mean apparent activation energies for areal rates of GPP (2.1–2.2 eV) and CR (1.6–1.9 eV) were 6.5‐ and 2.7‐fold higher than estimates based on metabolic theory predictions (i.e., 0.32 and 0.65 eV, respectively) and did not significantly differ from the apparent activation energy observed for N2 fixation. Mass‐specific activation energies for N2 fixation (1.4–1.6 eV), GPP (0.3–0.5 eV), and CR (no observed temperature relationship) were near or lower than theoretical predictions. We attribute the divergence of areal activation energies from those predicted by metabolic theory to increases in N2 fixation with temperature, leading to amplified temperature dependences of biomass accrual and areal rates of GPP and R. Such interactions between temperature dependences must be incorporated into metabolic models to improve predictions of ecosystem responses to climate change.