Comparison of the UKMO and GFDL GCM climate projections in NPP simulations for southern loblolly pine stands

Abstract

We used the process model BIOMASS version 13.0 to simulate contemporary net pnmary production (NPP) and NPP response to climate prolections for a doubhng of atmospheric CO2 concentration from 2 general circulation models (GCMs) that vary in their CO2 sensitivity: the less sensitive GFDL and the more sensitive UKMO. Increased GCM sensitivity to CO2 is reflected in increased predictions in the magnitude, vanation, and range of the clunate variables. Smulations used a 40 yr historical climate record, and 2 stand and site conditions to standardize the total NPP response estimates for eighteen 1x1" grid cells across the southern U n~t e d States. Contemporary NPP and NPP response estimates from the 18 cells were smoothed using a cell search algonthm to obtain a n NPP response index matrix for the entlre loblolly pine (Pinus taeda) forest-type We conducted a sensitivity analysis of the environmental variables projected to change in a 2xC0, environment to help interpret simulation output. Contemporary NPP varied from 2.5 to 8.5 Mg C ha-' yr-' over the range of loblolly pine High leaf area index (LA1) sirnulations had 1.5 to 2 times the productlvity of low LA1 simulations, but the regional patterns were similar, NPP was correlated with regional ddferences in precipitation and temperature. The NPP response to future climate and atmospheric changes depended on the GCM used, and on the stand and site condition assumed. Inter-annual estimates for the 18 cell simulations resulted in a +22 to + 8 4 % NPP response for the GFDL climate projections and a -30 to +94% NPP response for the UKMO clunate prolections. The 40-year average NPP response for the smoothed data ranged from + 4 3 to + 6 5 % and 1 to + 9 4 % for the GFDL and the UKMO climate prolections, respectively. Consequently, the magnitude and range of the 40-year average NPP response to the climate prolections was directly correlated with the GCM CO2 sensitivity. Although ~ncreased CO2 sensitivity resulted in broader extremes in the predicted temperature response, precipitation response for the 2 models was similar. The NPP response was also correlated with the patterns in predicted climate change, w~t h regional differences coupled to local climatic conditions. Climate projections from both models produced similar NPP responses when predicted temperatures and precipitation regvnes were similar. Elevated ambient CO2 had a greater effect on NPP response than temperature or precipitation in the sensitivity comparisons. Simulations indicate that a CO2 fertilizer effect, assuming no CO2 acclimation, more than compensates for decllnes in productlvity over most of the loblolly pine forest-type associated with projected decreased precipitation and/or projected low to moderate increases in temperature and, therefore, increased maintenance respiration costs.

A bioclimatic model for the distribution of Sphagnum‐dominated peatlands in North America under present climatic conditions

“…However, validating predictions for the future is impossible and this has led to many questions regarding the accuracy of the models. This problem is exacerbated by the fact that predictions by different GCMs may often produce very different results (Sampson et al. , 1996; Williams et al.…”

Simulated soil CO2 efflux and net ecosystem exchange in a 70-year-old Belgian Scots pine stand using the process model SECRETS

“…The model runs on a daily time step, except for photosynthesis that runs on an hourly (or user defined) time step ( figure 1). We modified the process model BIOMASS [23], as adapted for loblolly pine (P. taeda L.) [36] to create the internal structure for SECRETS. Four major changes to BIO-MASS were made.…”

“…If daily assimilate is negative, or if the estimated foliage production plus foliage R C is higher than available assimilate, C is removed from labile C storage in an amount necessary to meet production and foliage R C requirements. Carbon storage is assumed proportional to standing biomass (5% for stem, and 12% for foliage and fine roots) [36]. A similar approach is used for fine roots, although fine root production is estimated from needle-litterfall [27].…”