Engineering topics

Asao, Shinichi

Publications and source records attributed to Asao, Shinichi.

5 records

DOE OSTI2019

Decadal biomass increment in early secondary succession woody ecosystems is increased by CO 2 enrichment

Increasing atmospheric CO 2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO 2 -enrichment experiments in woody ecosystems that measured total NPP and biomass. CO 2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m –2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO 2 response of NPP (0.16 ± 0.03 kg C m –2 y –1 ) and the CO 2 -independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). Furthermore an ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO 2 -independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO 2 responses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Abstract Photodegradation accelerates litter decay in arid grasslands where plant growth and litter decay are strongly controlled by precipitation and evapotranspiration. However, the effects of photodegradation on ecosystem C and N dynamics are not well understood. We examined the effects using an ecosystem biogeochemical model DayCent‐ UV with photodegradation explicitly represented and validated. The model was parameterized for a California grassland where photodegradation was documented to release CO 2 from litter. The model was parameterized with an inverse modeling approach using an extensive data set of six years of daily observed carbon and water gas exchange (gross primary production, ecosystem respiration, and evapotranspiration), soil temperature, and soil moisture. DayCent‐ UV correctly simulated the seasonal patterns of the observed gas exchange and closely simulated the inter‐annual variation in the gas exchange and biomass production rates. The simulations suggested that the inter‐annual variation is driven more by actual evapotranspiration than by precipitation because a large portion of precipitation is lost as runoff during wet years. Photodegradation in DayCent‐ UV accelerated C and N cycling, decreasing system C and N by 9.2% and 9.5% and C and N residence times by 9.4% and 18.2%. Accelerated N cycling made a greater fraction of system N available for plants, increasing net N mineralization and plant production for a given amount of system N. Increased net N mineralization was due to decreased immobilization by microbes in the aboveground organic matter. Photodegradation did not alter the control on plant production by evapotranspiration. These results suggest that at the ecosystem level, the central effect of photodegradation is to suppress microbial activity. We conclude that photodegradation accelerates N cycling at the expense of microbes in this grassland, making it more efficient in supporting plant growth for a given amount of N in the system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

FACE-MDS Phase 2: Model Output

Model output from Phase 2 of the Free Air CO2 Enrichment Model Data Synthesis (FACE-MDS) project. Results from 12 models simulating six elevated CO2 experiments using the protocols, met data, and other data supplied in the accompanying dataset: Phase 2 Free Air CO2 Enrichment Model-Data Synthesis: Meteorological Data and Protocols. File naming convention can be found in the file 'facemds-file-table-modeldata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-modvars.xml'. We followed the ALMA v3 convention for meteorological variables and developed a hierarchical naming scheme for ecosystem variables. Additional info can be found in the protocols in the accompanying meteorological dataset (doi:10.15485/1480328). We replaced the original naming convention mentioned in the protocol with the one described in 'facemds-standard-name-table-modvars.xml'.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1 ). Comparison with data highlighted model failures particularly in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated six years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a mixed prairie grassland in Wyoming (USA). The GPP data were fitted to a mixed effects model that extended a light response model to include the effects of environmental (soil water content, vegetation greenness, nitrogen) and meteorological data (air temperature, vapor pressure deficit, photosynthetically active radiation) at current and past times. The stimulation of the cumulative six-year GPP by warming (20%, P=0.06) and eCO2 (19%, P=0.14) were primarily driven by enhanced C uptake during spring (96%, P=0.003) and fall (115%, P=0.001), respectively. These enhancements were consistent across each year, suggesting mechanisms for extending the growing season. Vapor pressure deficit from 1-3 days prior was the most significant predictor of temporalvariability in GPP and for explaining treatment differences in GPP, suggesting that atmospheric drought plays an important role for predicting GPP now and under future climate conditions.

54 ENVIRONMENTAL SCIENCES↗