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In forests, total belowground carbon (C) flux (TBCF) is a large component of the C budget and represents a critical pathway for delivery of plant C to soil. Reducing uncertainty around regional estimates of forest C cycling may be aided by incorporating knowledge of controls over soil respiration and TBCF. Photosynthesis, and presumably TBCF, declines with advancing tree size and age, and photosynthesis increases yet C partitioning to TBCF decreases in response to high soil fertility. We hypothesized that these causal relationships would result in predictable patterns of TBCF, and partitioning of C to TBCF, with natural variability in leaf area index (LAI), soil nitrogen (N), and tree height in subalpine forests in the Rocky Mountains, USA. Using three consecutive years of soil respiration data collected from 22 0.38-ha locations across three 1-km² subalpine forested landscapes, we tested three hypotheses: (1) annual soil respiration and TBCF will show a hump-shaped relationship with LAI; (2) variability in TBCF unexplained by LAI will be related to soil nitrogen (N); and (3) partitioning of C to TBCF (relative to woody growth) will decline with increasing soil N and tree height. We found partial support for Hypothesis 1 and full support for Hypotheses 2 and 3. TBCF, but not soil respiration, was explained by LAI and soil N patterns (r² = 0.49), and the ratio of annual TBCF to TBCF plus aboveground net primary productivity (ANPP) was related to soil N and tree height (r² = 0.72). Thus, forest C partitioning to TBCF can vary even within the same forest type and region, and approaches that assume a constant fraction of TBCF relative to ANPP may be missing some of this variability. These relationships can aid with estimates of forest soil respiration and TBCF across landscapes, using spatially explicit forest data such as national inventories or remotely sensed data products. [ABSTRACT FROM AUTHOR]

Forest carbon stocks and fluxes vary with forest age, and relationships with forest age are often used to estimate fluxes for regional or national carbon inventories. Two methods are commonly used to estimate forest age: observed tree age or time since a known disturbance. To clarify the relationships between tree age, time since disturbance and forest carbon storage and cycling, we examined stands of known disturbance history in three landscapes of the southern Rocky Mountains. Our objectives were to assess the similarity between carbon stocks and fluxes for these three landscapes that differed in climate and disturbance history, characterize the relationship between observed tree age and time since disturbance and quantify the predictive capability of tree age or time since disturbance on carbon stocks and fluxes. Carbon pools and fluxes were remarkably similar across the three landscapes, despite differences in elevation, climate, species composition, disturbance history, and forest age. Observed tree age was a poor predictor of time since disturbance. Maximum tree age overestimated time since disturbance for young forests and underestimated it for older forests. Carbon pools and fluxes were related to both tree age and disturbance history, but the relationships differed between these two predictors and were generally less variable for pools than for fluxes. Using tree age in a relationship developed with time since disturbance or vice versa increases errors in estimates of carbon stocks or fluxes. Little change in most carbon stocks and fluxes occurs after the first 100 years following stand-replacing disturbance, simplifying landscape scale estimates. We conclude that subalpine forests in the Central Rocky Mountains can be treated as a single forest type for the purpose of assessment and modeling of carbon, and that the critical period for change in carbon is < 100 years. [ABSTRACT FROM AUTHOR]

The article focuses on the carbon cycle in Alaska, with an emphasis on the potential implications of carbon responses in the state for the climate and carbon management policies in the U.S. Topics covered include the assessment of carbon dynamics in Alaska, drivers of historical and projected carbon cycle dynamics, and the effects of climate change on drivers and carbon dynamics.