FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1996965103> ?p ?o ?g. }

• W1996965103 endingPage "2053" @default.
• W1996965103 startingPage "2038" @default.
• W1996965103 abstract "Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C4 perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C4 grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m−2 for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m−2 for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC." @default.
• W1996965103 created "2016-06-24" @default.
• W1996965103 creator A5011079741 @default.
• W1996965103 creator A5032179615 @default.
• W1996965103 creator A5080328321 @default.
• W1996965103 creator A5081172633 @default.
• W1996965103 creator A5082050789 @default.
• W1996965103 date "2010-08-01" @default.
• W1996965103 modified "2023-10-16" @default.
• W1996965103 title "Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses" @default.
• W1996965103 cites W1600393891 @default.
• W1996965103 cites W1965161741 @default.
• W1996965103 cites W1966515524 @default.
• W1996965103 cites W1978909890 @default.
• W1996965103 cites W1980414281 @default.
• W1996965103 cites W1996568490 @default.
• W1996965103 cites W2000991454 @default.
• W1996965103 cites W2001350202 @default.
• W1996965103 cites W2008169516 @default.
• W1996965103 cites W2010784770 @default.
• W1996965103 cites W2011142156 @default.
• W1996965103 cites W2017628975 @default.
• W1996965103 cites W2017765383 @default.
• W1996965103 cites W2021113509 @default.
• W1996965103 cites W2025932222 @default.
• W1996965103 cites W2027824171 @default.
• W1996965103 cites W2029326511 @default.
• W1996965103 cites W2031895263 @default.
• W1996965103 cites W2033481223 @default.
• W1996965103 cites W2037664038 @default.
• W1996965103 cites W2039435098 @default.
• W1996965103 cites W2039699080 @default.
• W1996965103 cites W2045371216 @default.
• W1996965103 cites W2046857879 @default.
• W1996965103 cites W2048863863 @default.
• W1996965103 cites W2056425951 @default.
• W1996965103 cites W2057040031 @default.
• W1996965103 cites W2057433825 @default.
• W1996965103 cites W2060304250 @default.
• W1996965103 cites W2064645317 @default.
• W1996965103 cites W2064667935 @default.
• W1996965103 cites W2066100113 @default.
• W1996965103 cites W2069890710 @default.
• W1996965103 cites W2075245402 @default.
• W1996965103 cites W2081613282 @default.
• W1996965103 cites W2082612871 @default.
• W1996965103 cites W2087964947 @default.
• W1996965103 cites W2096466966 @default.
• W1996965103 cites W2100250663 @default.
• W1996965103 cites W2104990636 @default.
• W1996965103 cites W2110313694 @default.
• W1996965103 cites W2110588131 @default.
• W1996965103 cites W2120249050 @default.
• W1996965103 cites W2120496201 @default.
• W1996965103 cites W2122207098 @default.
• W1996965103 cites W2125491431 @default.
• W1996965103 cites W2136198931 @default.
• W1996965103 cites W2137318586 @default.
• W1996965103 cites W2140082872 @default.
• W1996965103 cites W2145744344 @default.
• W1996965103 cites W2147423506 @default.
• W1996965103 cites W2152783233 @default.
• W1996965103 cites W2154409236 @default.
• W1996965103 cites W2158370478 @default.
• W1996965103 cites W2161425709 @default.
• W1996965103 cites W2164180320 @default.
• W1996965103 cites W2170743438 @default.
• W1996965103 cites W2171074980 @default.
• W1996965103 cites W2171757568 @default.
• W1996965103 cites W2174939835 @default.
• W1996965103 cites W2180426220 @default.
• W1996965103 cites W2188385721 @default.
• W1996965103 cites W2268623274 @default.
• W1996965103 cites W2314815741 @default.
• W1996965103 cites W3146968787 @default.
• W1996965103 cites W4379650377 @default.
• W1996965103 doi "https://doi.org/10.1016/j.ecolmodel.2010.05.013" @default.
• W1996965103 hasPublicationYear "2010" @default.
• W1996965103 type Work @default.
• W1996965103 sameAs 1996965103 @default.
• W1996965103 citedByCount "37" @default.
• W1996965103 countsByYear W19969651032012 @default.
• W1996965103 countsByYear W19969651032013 @default.
• W1996965103 countsByYear W19969651032014 @default.
• W1996965103 countsByYear W19969651032015 @default.
• W1996965103 countsByYear W19969651032016 @default.
• W1996965103 countsByYear W19969651032017 @default.
• W1996965103 countsByYear W19969651032018 @default.
• W1996965103 countsByYear W19969651032019 @default.
• W1996965103 countsByYear W19969651032020 @default.
• W1996965103 countsByYear W19969651032022 @default.
• W1996965103 crossrefType "journal-article" @default.
• W1996965103 hasAuthorship W1996965103A5011079741 @default.
• W1996965103 hasAuthorship W1996965103A5032179615 @default.
• W1996965103 hasAuthorship W1996965103A5080328321 @default.
• W1996965103 hasAuthorship W1996965103A5081172633 @default.
• W1996965103 hasAuthorship W1996965103A5082050789 @default.
• W1996965103 hasConcept C110872660 @default.

• next