2015
DOI: 10.2134/advagricsystmodel6.2013.0004
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CQESTR Simulation of Dryland Agroecosystem Soil Organic Carbon Changes under Climate Change Scenarios

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Cited by 11 publications
(11 citation statements)
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“…Soil C models are especially useful tools to examine the impact of management practices on SOC over time when considering long‐term climate change (Gollany et al, 2012b; Gollany, 2016). In soil C models, the major driver of C stocks is C inputs from crop yield and the subsequent additions of crop biomass (Rickman et al, 2002; Liang et al, 2009).…”
mentioning
confidence: 99%
“…Soil C models are especially useful tools to examine the impact of management practices on SOC over time when considering long‐term climate change (Gollany et al, 2012b; Gollany, 2016). In soil C models, the major driver of C stocks is C inputs from crop yield and the subsequent additions of crop biomass (Rickman et al, 2002; Liang et al, 2009).…”
mentioning
confidence: 99%
“…Furthermore, increasing SOC is essential to ecosystem functioning due to its positive effects on cation exchange capacity, pH, soil fertility, soil microbes, soil aggregate stability and structure, erosion, aeration, and water retention (Alberts and Moldenhauer, 1981; Gollany et al, 1992; Six et al, 2000; Kong et al, 2005; van Keulen, 2001; Janzen, 2006). The loss of C from dryland PNW soils after conversion from native prairie to agricultural cropping is well documented (Rasmussen and Collins, 1991; Rasmussen and Albrecht, 1998; Gollany, 2016). Using long‐term data, Liebig et al (2005) estimated an average relative SOM loss of 34 ± 14% in the top 30‐cm depth in the northwestern United States and western Canada after conversion from native prairie or forest to crop production.…”
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confidence: 99%
“…It is not feasible to determine effects of climate change on SOC in agroecosystems due to the slow process and the complex interactions between management factors, climate, and edaphic properties (Gollany, 2016). The potential impacts of climate change on C cycling and SOC accrual and loss in agroecosystems have been assessed by process‐based models.…”
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confidence: 99%
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“…Six climate and crop yield scenarios were simulated for both cropping systems based on the inclusion or exclusion of climate change and five rates of crop yield increase or decrease over the predictive period. This is similar to the approach used by Gollany (2016). The baseline scenario assumed that crop yields and biomass inputs remained at the 1996 to 2014 average and that climate (mean monthly air temperature and precipitation) remained at the 2005 to 2014 average.…”
Section: Methodsmentioning
confidence: 99%