Engineering topics

Xu, Chongang

Publications and source records attributed to Xu, Chongang.

2 records

DOE OSTI2022

Stem respiration and growth in a central Amazon rainforest

Tropical forests cycle a large amount of CO 2 between the land and atmosphere, with a substantial portion of the return flux due tree respiratory processes. However, in situ estimates of woody tissue respiratory fluxes and carbon use efficiencies (CUEW) and their dependencies on physiological processes including stem wood production (Pw) and transpiration in tropical forests remain scarce. In this work, we synthesize monthly Pw and daytime stem CO 2 efflux (ES) measurements over one year from 80 trees with variable biomass accumulation rates in the central Amazon. On average, carbon flux to woody tissues, expressed in the same stem area normalized units as ES, averaged 0.90 ± 1.2 µmol m -2 s -1 for Pw, and 0.55 ± 0.33 µmol m -2 s -1 for daytime ES. A positive linear correlation was found between stem growth rates and stem CO 2 efflux, with respiratory carbon loss equivalent to 15 ± 3% of stem carbon accrual. CUEW of stems was non-linearly correlated with growth and was as high as 77-87% for a fast-growing tree. Diurnal measurements of stem CO 2 efflux for three individuals showed a daytime reduction of ES by 15-50% during periods of high sap flow and transpiration. The results demonstrate that high daytime ES fluxes are associated with high CUE W during fast tree growth, reaching higher values than previously observed in the Amazon Basin (e.g. maximum CUEW up to 77-87%, versus 30-56%). The observations are consistent with the emerging view that diurnal dynamics of stem water status influences growth processes and associated respiratory metabolism.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

The Impact of Alternative Trait-Scaling Hypotheses for the Maximum Photosynthetic Carboxylation Rate (V (sub cmax)) on Global Gross Primary Production

The maximum photosynthetic carboxylation rate (V (sub cmax)) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V(sub cmax) distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 petagrams of Carbon (PgC) per year, 65 percent of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27percent coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r equals 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V(sub cmax) variation in the field, particularly in northern latitudes.

chlorophyll fluorescence↗