Litter quality of C3 perennial grasses and soil inorganic nitrogen in a semiarid rangeland of central Argentina

2008 ◽  
Vol 72 (9) ◽  
pp. 1684-1689 ◽  
Author(s):  
R.J. Andrioli ◽  
R.A. Distel
2009 ◽  
Vol 18 (6) ◽  
pp. 665 ◽  
Author(s):  
Erin M. Goergen ◽  
Jeanne C. Chambers

Woodland expansion affects grasslands and shrublands on a global scale. Prescribed fire is a potential restoration tool, but recovery depends on nutrient availability and species responses after burning. Fire often leads to long-term losses in total nitrogen, but presence of native legumes can influence recovery through addition of fixed nitrogen. We examined the effects of prescribed fire in the central Great Basin, Nevada, USA, on density, biomass and nutrient content of a native legume, Lupinus argenteus (Pursh), and the effects of Lupinus presence and prescribed fire on soil inorganic nitrogen and on neighboring plant functional groups. We examined three treatments – 1 year post-burn, 3 years post-burn and unburned control in three replicate blocks. Extractable soil inorganic nitrogen was variable and, despite a tendency towards increased inorganic nitrogen 1 year post-burn, differences among treatments were not significant. Extractable soil inorganic nitrogen was higher in Lupinus presence regardless of time since fire. Lupinus density increased after fire mainly owing to increased seedling numbers 3 years post-burn. Fire did not affect Lupinus tissue N and P concentrations, but cover of perennial grasses and forbs was higher in Lupinus presence. The invasive annual grass Bromus tectorum had low abundance and was unaffected by treatments. Results indicate that Lupinus has the potential to influence succession through modification of the post-fire environment.


Crop Science ◽  
2003 ◽  
Vol 43 (1) ◽  
pp. 247 ◽  
Author(s):  
David J. Lee ◽  
Daniel C. Bowman ◽  
D. Keith Cassel ◽  
Charles H. Peacock ◽  
Thomas W. Rufty

2014 ◽  
Vol 319 ◽  
pp. 161-168 ◽  
Author(s):  
Kevan J. Minick ◽  
Brian D. Strahm ◽  
Thomas R. Fox ◽  
Eric B. Sucre ◽  
Zakiya H. Leggett ◽  
...  

2014 ◽  
Vol 94 (3) ◽  
pp. 435-452 ◽  
Author(s):  
S. Liu ◽  
J. Y. Yang ◽  
C. F. Drury ◽  
H. L. Liu ◽  
W. D. Reynolds

Liu, S., Yang, J. Y., Drury, C. F., Liu, H. L. and Reynolds, W. D. 2014. Simulating maize (Zea mays L.) growth and yield, soil nitrogen concentration, and soil water content for a long-term cropping experiment in Ontario, Canada. Can. J. Soil Sci. 94: 435–452. A performance assessment of the Decision Support Systems for Agrotechnology Transfer (DSSAT) model (v4.5) including the CERES-Maize and CENTURY modules was conducted for continuous maize production under annual synthetic fertilization (CC-F) and no fertilization (CC-NF) using field data from a long-term (53-yr) cropping experiment in Ontario, Canada. The assessment was based on the accuracy with which DSSAT could simulate measured grain yield, above-ground biomass, leaf area index (LAI), soil inorganic nitrogen concentration, and soil water content. Model calibration for maize cultivar was achieved using grain yield measurements from CC-F between 2007 and 2012, and model evaluation was achieved using soil and crop measurements from both CC-F and CC-NF for the same 6-yr period. Good model–data agreement for CC-F grain yields was achieved for calibration (index of agreement, d=0.99), while moderate agreement for CC-NF grain yields was achieved for evaluation (d=0.79). Model–data agreement for above-ground biomass was good (d=0.83–1.00), but the model consistently underestimated for CC-F and overestimated for CC-NF. DSSAT achieved good model–data agreement for LAI in CC-F (d=0.82–0.99), but moderate to poor agreement in CC-NF (d=0.46–0.64). The CENTURY module of DSSAT simulated soil inorganic nitrogen concentrations with moderate to good model–data agreement in CC-F (d=0.74–0.88), but poor agreement in CC-NF (d=0.40–0.50). The model–data agreement for soil water content was moderate in 2007 and 2008 for both treatments (d=0.60–0.76), but poor in 2009 (d=0.46–0.53). It was concluded that the DSSAT cropping system model provided generally good to moderate simulations of continuous maize production (yield, biomass, LAI) for a long-term cropping experiment in Ontario, Canada, but generally moderate to poor simulations of soil inorganic nitrogen concentration and soil water content.


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