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Title: Improvements of a dynamic global vegetation model and simulations of carbon and water at an upland-oak forest.

Abstract

The interest in the development and improvement of the dynamic global vegetation models (DGVMs), which have the potential to simulate fluxes of carbon, water and nitrogen, and vegetation dynamics in an integrated system has been increasing. In this paper, some numerical schemes and a higher resolution soil texture dataset are employed to improve the Sheffield Dynamic Global Vegetation Model (SDGVM). Using the eddy covariance-based measurements, we then test the standard version of the SDGVM and the modified version of the SDGVM. Detailed observations of daily carbon and water fluxes made at the upland oak forest on the Walker Branch Watershed in Tennessee, USA offered a unique opportunity for these comparisons. The results revealed that, the modified version of the SDGVM did a reasonable job of simulating the carbon flux, water flux and the variation of soil water content. However, at the end of the growing season, it failed to simulate the dynamics of limitations on the soil respiration and as a result underestimated the soil respiration. It was also noted that the modified version overestimated the increase in soil water content following summer rainfall, which was attributed to an inadequate representation of the ground water and thermal cycle.

Authors:
 [1];  [1];  [2];  [3];  [4];  [3]
  1. Chinese Academy of Sciences
  2. Beijing Normal University
  3. University of Sheffield
  4. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oak Ridge National Environmental Research Park
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
931286
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: Advances in Atmospheric Sciences; Journal Volume: 24; Journal Issue: 2
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; CARBON; FORESTS; GROUND WATER; NITROGEN; OAKS; PLANTS; RESOLUTION; RESPIRATION; SOILS; TENNESSEE; TEXTURE; WATER; WATERSHEDS

Citation Formats

Mau, J., Wang, B., Dai, Yongjiu, Woodward, F. I., Hanson, Paul J, and Lomas, M. R. Improvements of a dynamic global vegetation model and simulations of carbon and water at an upland-oak forest.. United States: N. p., 2007. Web. doi:10.1007/s00376-007-0311-7.
Mau, J., Wang, B., Dai, Yongjiu, Woodward, F. I., Hanson, Paul J, & Lomas, M. R. Improvements of a dynamic global vegetation model and simulations of carbon and water at an upland-oak forest.. United States. doi:10.1007/s00376-007-0311-7.
Mau, J., Wang, B., Dai, Yongjiu, Woodward, F. I., Hanson, Paul J, and Lomas, M. R. Mon . "Improvements of a dynamic global vegetation model and simulations of carbon and water at an upland-oak forest.". United States. doi:10.1007/s00376-007-0311-7.
@article{osti_931286,
title = {Improvements of a dynamic global vegetation model and simulations of carbon and water at an upland-oak forest.},
author = {Mau, J. and Wang, B. and Dai, Yongjiu and Woodward, F. I. and Hanson, Paul J and Lomas, M. R.},
abstractNote = {The interest in the development and improvement of the dynamic global vegetation models (DGVMs), which have the potential to simulate fluxes of carbon, water and nitrogen, and vegetation dynamics in an integrated system has been increasing. In this paper, some numerical schemes and a higher resolution soil texture dataset are employed to improve the Sheffield Dynamic Global Vegetation Model (SDGVM). Using the eddy covariance-based measurements, we then test the standard version of the SDGVM and the modified version of the SDGVM. Detailed observations of daily carbon and water fluxes made at the upland oak forest on the Walker Branch Watershed in Tennessee, USA offered a unique opportunity for these comparisons. The results revealed that, the modified version of the SDGVM did a reasonable job of simulating the carbon flux, water flux and the variation of soil water content. However, at the end of the growing season, it failed to simulate the dynamics of limitations on the soil respiration and as a result underestimated the soil respiration. It was also noted that the modified version overestimated the increase in soil water content following summer rainfall, which was attributed to an inadequate representation of the ground water and thermal cycle.},
doi = {10.1007/s00376-007-0311-7},
journal = {Advances in Atmospheric Sciences},
number = 2,
volume = 24,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}
  • Observed responses of upland-oak vegetation of the eastern deciduous hardwood forest to changing CO2, temperature, precipitation and tropospheric ozone (O3) were derived from field studies and interpreted with a stand-level model for an 11-year range of environmental variation upon which scenarios of future environmental change were imposed. Scenarios for the year 2100 included elevated [CO2] and [O3] (1385ppm and 120 ppb, respectively), warming (14 1C), and increased winter precipitation (120% November-March). Simulations were run with and without adjustments for experimentally observed physiological and biomass adjustments. Initial simplistic model runs for single-factor changes in CO2 and temperature predicted substantial increases (1191%more » or 508 gCm 2 yr 1) or decreases ( 206% or 549 gCm 2 yr 1), respectively, in mean annual net ecosystem carbon exchange (NEEa 266 23 gCm 2 yr 1 from 1993 to 2003). Conversely, single-factor changes in precipitation or O3 had comparatively small effects on NEEa (0% and 35%, respectively). The combined influence of all four environmental changes yielded a 29% reduction in mean annual NEEa. These results suggested that future CO2-induced enhancements of gross photosynthesis would be largely offset by temperature-induced increases in respiration, exacerbation of water deficits, and O3-induced reductions in photosynthesis. However, when experimentally observed physiological adjustments were included in the simulations (e.g. acclimation of leaf respiration to warming), the combined influence of the year 2100 scenario resulted in a 20% increase in NEEa not a decrease. Consistent with the annual model's predictions, simulations with a forest succession model run for gradually changing conditions from 2000 to 2100 indicated an 11% increase in stand wood biomass in the future compared with current conditions. These model-based analyses identify critical areas of uncertainty for multivariate predictions of future ecosystem response, and underscore the importance of long term field experiments for the evaluation of acclimation and growth under complex environmental scenarios.« less
  • Models represent our primary method for integration of small-scale, processlevel phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the evaluation of 13 stand-level models varying in their spatial, mechanistic, and temporal complexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons weremore » obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiological processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions.« less
  • To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of othermore » fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.« less
  • Whole-tree harvesting increased the export of biomass N, P, K, and Ca by 2.6, 2.9, 3.1, 3.3, and 2.6 times, respectively, compared to sawlog harvesting in an upland mixed oak forest in eastern Tennessee. Whole-tree harvesting after leaf fall reduced the potential drains of N, P, K, and Ca by 7, 7, 23, and 5% respectively, compared with potential removal by harvesting during the growing season. Due to low soil Ca content and high Ca content in woody tissues, whole-tree harvesting depleted total ecosystem Ca to a much greater extent than N, P, or K. Soil reserves and atmospheric inputsmore » may be adequate to sustain total N, P, and K supplies with whole-tree harvesting, but soil amendments may be necessary to sustain Ca supplies.« less