Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests

P. E. Thornton, B. E. Law, Henry L. Gholz, Kenneth L. Clark, E. Falge, D. S. Ellsworth, A. H. Goldstein, R. K. Monson, D. Hollinger, M. Falk, J. Chen, J. P. Sparks

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Abstract

The effects of disturbance history, climate, and changes in atmospheric carbon dioxide (CO2) concentration and nitrogen deposition (Ndep) on carbon and water fluxes in seven North American evergreen forests are assessed using a coupled water-carbon-nitrogen model, canopy-scale flux observations, and descriptions of the vegetation type, management practices, and disturbance histories at each site. The effects of interannual climate variability, disturbance history, and vegetation ecophysiology on carbon and water fluxes and storage are integrated by the ecosystem process model Biome-BGC, with results compared to site biometric analyses and eddy covariance observations aggregated by month and year. Model results suggest that variation between sites in net ecosystem carbon exchange (NEE) is largely a function of disturbance history, with important secondary effects from site climate, vegetation ecophysiology, and changing atmospheric CO2 and Ndep. The timing and magnitude of fluxes following disturbance depend on disturbance type and intensity, and on post-harvest management treatments such as burning, fertilization and replanting. The modeled effects of increasing atmospheric CO2 on NEE are generally limited by N availability, but are greatly increased following disturbance due to increased N mineralization and reduced plant N demand. Modeled rates of carbon sequestration over the past 200 years are driven by the rate of change in CO2 concentration for old sites experiencing low rates of Ndep. The model produced good estimates of between-site variation in leaf area index, with mixed performance for between- and within-site variation in evapotranspiration. There is a model bias toward smaller annual carbon sinks at five sites, with a seasonal model bias toward smaller warm-season sink strength at all sites. Various lines of reasoning are explored to help to explain these differences.

Original languageEnglish
Pages (from-to)185-222
Number of pages38
JournalAgricultural and Forest Meteorology
Volume113
Issue number1-4
DOIs
StatePublished - Dec 2 2002
Externally publishedYes

Funding

P.E. Thornton was supported by NASA (grant no. W-19,953), NSF (grant no. DEB-9977066), USGS (grant no. 99CRAG0063) and the National Center for Atmospheric Research (NCAR), Boulder, CO. NCAR is sponsored by the National Science Foundation. B.E. Law was supported by NASA (grant no. NAG5-7531), and DOE (grant no. FG0300ER63014). We acknowledge the efforts of many people in the field data collection at the sites, analysis, and synthesis, including P. Anthoni, D. Moore and S. Van Tuyl. Appendix A Biome-BGC process descriptions . Many of the principle physical and biological processes represented in Biome-BGC are summarized below. The computer code itself contains extensive and explicit comments for all processes, as well as detailed descriptions of all model state and flux variables, including units and unit conversions. The code is available by request from P.E. Thornton. This study used version 4.1.1 of the Biome-BGC code. Canopy radiation . The plant canopy leaf area is divided into sunlit and shaded fractions on the basis of a radiation extinction coefficient that varies with leaf geometry. All plant physiological processes are calculated separately for the sunlit and shaded canopy fractions. Differences in leaf physiology between the sunlit and shaded fractions are parameterized as differences in SLA, with the mass-based nitrogen concentration and controls on stomatal conductance constant between sunlit and shaded fractions. Photosynthesis . Assimilation ( A ) on a unit projected leaf area basis for C3 plants is estimated independently for the sunlit and shaded canopy fractions, using a biochemical model ( Farquhar et al., 1980 , with kinetic parameters from Woodrow and Berry (1988) , de Pury and Farquhar (1997) ) and substitution from the CO 2 diffusion equation to eliminate the explicit dependency on intracellular CO 2 concentration. The maximum rate of carboxylation ( V C,max ) is calculated as a function of the specific activity of the Rubisco enzyme (act, itself a function of leaf temperature), the weight fraction of nitrogen in the Rubisco molecule (fnr), the fraction of total leaf nitrogen in the Rubisco enzyme (flnr), the specific leaf area (sla), and the leaf C:N ratio (C:N leaf ) as follows (dimensional analysis to the right): V C,max = act × flnr fnr × sla × C:N leaf , μmol CO 2 m 2 s = ( μmol CO 2 / g Rubisco s )( g N Rubisco / g N leaf ) ( g N Rubisco / g Rubisco )( m 2 / g C leaf )( g C leaf / g N leaf ) The model is very sensitive to the value for flnr, and when data is available we optimize this parameter by fitting to A–Ci curves. This approach requires knowing the leaf temperature as well as sla and C:N leaf for the measured leaves. One advantage of this formulation is that it makes explicit the dependence of V C,max on sla and C:N leaf . Values for fnr and act, as well as the temperature dependence of act, are assumed constant across all species. Stomatal conductance . A form of the Leuning model is used, which makes actual conductance a function of a minimum value and a series of multiplicative reductions based on incident radiation, vapor pressure deficit, leaf water potential, and night minimum temperature ( Running and Coughlan, 1988 ). There is no direct effect of changing atmospheric CO 2 concentration on stomatal conductance, which is in agreement with recent studies for woody vegetation ( Norby et al., 1999 ). One practical benefit of this formulation is that it is not necessary to iterate between the equations for CO 2 , water, and energy transfer at the leaf surface, as is the case, e.g., with the Ball-Berry model in which stomatal conductance is an explicit function of carbon assimilation. Evaporation and transpiration . Both processes are estimated using the Penman–Monteith equation. Available energy is partitioned between the canopy and the soil surface. Soil evaporation depends on the number of days since wetting. Energy available in the canopy is divided between the evaporation of water intercepted on the canopy and transpiration. Both these processes depend on the leaf-scale aerodynamic conductance, with transpiration depending in addition on stomatal conductance. Autotrophic respiration . Two types of autotrophic respiration are distinguished—maintenance respiration, which is calculated as a function of tissue mass, tissue nitrogen concentration, and tissue temperature, and growth respiration which is a simple proportion of total new carbon allocated to growth. Maintenance respiration costs are incurred regardless of current assimilation rate. Phenology . For all vegetation types, some growth can be stored for display during the following growing season. For this stored growth, the model developed by White et al. (1997) is used to estimate the middle of the leaf expansion and litterfall periods for deciduous broadleaf trees and for grasses. For all vegetation types the user has the option to specify the proportion of the total growing season during which stored growth is displayed. The growth that is not stored for display in the following growing season is displayed immediately, and so the overall seasonal growth signal consists of one component due to stored growth and a second component due to current growth. The current growth component has a strong dependency on the stored growth, since the stored growth augments the canopy leaf area and changes the growth potential independent of the current growing season conditions. This is essential to the development of new canopy in the spring for a deciduous system, and is also important for evergreen vegetation. Allocation of carbon and nitrogen . The C:N stoichiometry of new plant allocation is constant, defined by ratios between allocation to new leaf and to each of the other plant tissues (fine root, live and dead stem wood, live and dead coarse root wood). The C:N stoichiometry of total plant biomass changes over time as leaves and fine roots turn over to litter pools, while wood accumulates. All plant pools for C and N are completely prognostic, so leaf area responds to changes in climate, physiological parameterizations, disturbance regimes, and dynamics in the SOM pools over time. The availability of C from assimilation and the availability of N from plant mineral N uptake must be balanced to meet this constant C:N for new growth, which is achieved by down-regulating assimilation under conditions of chronic N limitation. Plant mineral nitrogen uptake . Plants compete with the N immobilizing processes in the litter and soil decomposition dynamics for one pool of soil mineral N. This competition is based on relative demand, which is set by the plant’s potential assimilation rate and the potential N immobilization rate due to decomposition, both estimated assuming current values for all the state variables. Actual assimilation and actual decomposition then proceed at either their potential rates if mineral N is not limiting, or at reduced rates if N is limiting. Litter and SOM pools . All plant litter is divided into three pools on the basis of the weight fractions of lignin, cellulose plus hemicellulose, and remaining mass in the litter. These litter pools undergo chemical degradation at different rates, producing a connected series of SOM pools. The model structure defines a converging cascade of progressively more recalcitrant SOM ( Thornton, 1998 ). Before entering the active litter pools, woody litter passes through a CWD pool that is subject only to physical degradation. C:N ratios for the litter pools depend on the inputs from plants, but C:N ratios for the SOM pools are fixed. Heterotrophic respiration . Litter and SOM decomposition produces a heterotrophic respiration flux, which depends on the size of the litter and SOM pools and their decomposition rate constants. These rate constants depend on soil temperature and soil moisture. Decomposition also depends on the availability of soil mineral N for those steps which are immobilizing N (see description of plant N uptake above). Appendix B

Keywords

  • Carbon budget
  • Carbon dioxide concentration
  • Ecosystem model
  • Ecosystem respiration
  • Eddy covariance
  • Evergreen needleleaf forest
  • Net ecosystem exchange
  • Nitrogen budget
  • Nitrogen deposition
  • Water budget

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