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Simulating Gross Primary Productivity of Humid‐Temperate Pastures
Author(s) -
Skinner R. Howard,
Corson Michael S.,
Gilmanov Tagir G.
Publication year - 2008
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2007.0264
Subject(s) - pasture , environmental science , temperate climate , forage , productivity , growing season , primary production , fertilizer , agronomy , simulation modeling , atmospheric sciences , ecosystem , ecology , mathematics , biology , mathematical economics , economics , macroeconomics , geology
Although most pasture growth models simulate many above‐ and belowground components of the plant community, calibration and validation are usually based only on periodic measurements of aboveground forage yield. This research used daily measurements of gross primary productivity (GPP) to validate the photosynthesis subroutine of the Integrated Farm System Model (IFSM). The model was calibrated for a pasture grazed by beef cattle ( Bos taurus ) in 2003, then validated with data from 2004 through 2006. Predicted and observed annual yield differed by 14 ± 9%, whereas predicted GPP differed from observed GPP by only 7 ± 3%. Seasonal trends in GPP were also adequately simulated, although a slight overestimation in the spring and early‐summer and underestimation in the later half of the year occurred. Overestimation occurred when wintertime temperatures were above freezing or when N availability was high following fertilizer application. Late‐season underestimation was related to low soil N availability which resulted from excessive N uptake by plants earlier in the year. Only minor adjustments in model structure were needed to improve simulation of GPP. Most adjustments involved changes in parameter values, many of which are often difficult to find or lacking in the literature. Refinement of models to accurately simulate the seasonal distribution of physiological parameters such as GPP will help ensure that model structures correctly represent the true dynamics of C assimilation and pasture growth.