Environmental controls on carbon dioxide flux from black spruce coarse woody debris

Carbon dioxide flux from coarse woody debris (CWD) is an important source of CO₂ in forests with moderate to large amounts of CWD. A process-based understanding of environmental controls on CWD CO₂ flux (R CWD) is needed to accurately model carbon exchange between forests and the atmosphere. The objectives of this study were to: (1) use a laboratory incubation factorial experiment to quantify the effect of temperature (T CWD), water content (W C), decay status, and their interactions on R CWD for black spruce [Picea mariana (Mill.) BSP] CWD; (2) measure and model spatial and temporal dynamics in T CWD for a boreal black spruce fire chronosequence; and (3) validate the R CWD model with field measurements, and quantify potential errors in estimating annual R CWD from this model on various time steps. The R CWD was positively correlated to T CWD (R ²=0.37, P<0.001) and W C (R ²=0.18, P<0.001), and an empirical R CWD polynomial model that included T CWD and W C interactions explained 74% of the observed variation of R CWD. The R CWD estimates from the R CWD model excellently matched the field measurements. Decay status of CWD significantly (P<0.001) affected R CWD. The temperature coefficient (Q ₁₀) averaged 2.5, but varied by 141% across the 5–42°C temperature range, illustrating the potential shortcomings of using a constant Q ₁₀. The CWD temperature was positively correlated to air temperature (R ²=0.79, P<0.001), with a hysteresis effect that was correlated to CWD decay status and stand leaf area index . Ignoring this temperature hysteresis introduced errors of –1% to +32% in annual R CWD estimates. Increasing T CWD modeling time step from hourly to daily or monthly introduced a 5–11% underestimate in annual R CWD. The annual R CWD values in this study were more than two-fold greater than those in a previous study, illustrating the need to incorporate spatial and temporal responses of R CWD to temperature and water content into models for long-term R CWD estimation in boreal forest ecosystems.