Validation of a Soil Temperature and Moisture Model in Southern Quebec, Canada

Perreault, Simon; Chokmani, Karem; Nolin, Michel C.; Bourgeois, Gaétan

doi:10.2136/sssaj2012.0311

Cited by 17 publications

(16 citation statements)

References 12 publications

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“…Abbreviations: P drop, drop determined by precipitation during recruitment; P lrc, natural log of the rate of increase determined by precipitation during recruitment; W lrc, natural log of the rate of increase determined by winter GDD (10 C) accumulated from October to March. than what actually occurred and contributed to premature giant ragweed emergence predictions for Models 1, 3, 10, and 11 in all site-years ( Figure 1). This finding is similar to that of Perreault et al (2013), who reported a mean bias of 2.5 C for STM 2 on loamy soils similar to soils at both of our study locations. The mean bias of the STM 2 among crop rotation and tillage timing treatments ranged from 1.7 to 3.9 C. Established alfalfa and wheat had the greatest mean bias values of 3.8 and 3.9 C, respectively, while soybean planted into soybean stubble had the lowest mean bias value of 1.7 C. The STM 2 does not account for changes in crop canopy during the growing season (Perreault et al 2013), which likely explains why the STM 2 predictions had a greater bias in established alfalfa and wheat, which were established earlier and in narrower rows compared with corn and soybean.…”

Section: Resultssupporting

confidence: 91%

Giant Ragweed (Ambrosia trifida) Emergence Model Performance Evaluated in Diverse Cropping Systems

Goplen¹,

Becker

Moon

et al. 2017

Weed Sci

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Accurate weed emergence models are valuable tools for scheduling planting, cultivation, and herbicide applications. Multiple models predicting giant ragweed emergence have been developed, but none have been validated in diverse crop rotation and tillage systems, which have the potential to influence weed emergence patterns. This study evaluated the performance of published giant ragweed emergence models across various crop rotations and spring tillage dates in southern Minnesota. Across experiments, the most robust model was a mixed-effects Weibull (flexible sigmoidal function) model predicting emergence in relation to hydrothermal time accumulation with a base temperature of 4.4 C, a base soil matric potential of −2.5 MPa, and two random effects determined by overwinter growing degree days (GDD) (10 C) and precipitation accumulated during seedling recruitment. The deviations in emergence between individual plots and the fixed-effects model were distinguished by the positive association between the lower horizontal asymptote (Drop) and maximum daily soil temperature during seedling recruitment. This finding indicates that crops and management practices that increase soil temperature will have a shorter lag phase at the start of giant ragweed emergence compared with practices promoting cool soil temperatures. Thus, crops with earlyseason crop canopies such as perennial crops and crops planted in early spring and in narrow rows will likely have a slower progression of giant ragweed emergence. This research provides a valuable assessment of published giant ragweed emergence models and illustrates that accurate emergence models can be used to time field operations and improve giant ragweed control across diverse cropping systems. Nomenclature: Giant ragweed, Ambrosia trifida L. AMBTR.

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Section: Resultssupporting

confidence: 91%

Giant Ragweed (Ambrosia trifida) Emergence Model Performance Evaluated in Diverse Cropping Systems

Goplen¹,

Becker

Moon

et al. 2017

Weed Sci

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“…4 and Table 4). Generally, LandscapeDNDC was able to simulate site differences in average soil water contents ranging from 9.0 ± 4.9-31.5 ± 5.2 vol.% (r 2 = 0.43) ( (Kröbel et al, 2010;Li et al, 2012;Perreault et al, 2013). Our study further confirms the finding that model performance for soil temperature predictions is higher than for soil moisture.…”

Section: Resultssupporting

confidence: 83%

Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea

Kim

Seo

Kraus

et al. 2015

Science of The Total Environment

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“… Note . Peat layer properties are derived from Thompson and Waddington () and Lukenbach et al (), sand properties from Huang, Barbour, Elshorbagy, Zettl, and Si (), and clay from Perreault, Chokmani, Nolin, and Bourgeois ().…”

Section: Methodsmentioning

confidence: 99%

“…Values of α were log‐normally distributed with average log ( α ) values of 0.603 ± 1.776 m −1 (± standard deviation), for the well‐decomposed samples average log ( α ) values were −0.434 ± 1.301 m −1 (Table ). Hydraulic parameters for sand (Table ) were derived from values for Northern Alberta in Huang et al (), and parameters for clay (Table ) were derived from Perreault et al () for heavy clay soils in Quebec, Canada.…”

Section: Methodsmentioning

confidence: 99%

Peat depth as a control on moss water availability under evaporative stress

Dixon

Kettridge

Moore

et al. 2017

Hydrological Processes

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Northern peatlands are a vital component of the global carbon cycle, containing large stores of soil organic carbon and acting as a long‐term carbon sink. Moss productivity is an important factor in determining whether these wetlands will retain this function under future climatic conditions. Research on unsaturated water flow in peatlands, which controls moss productivity during periods of evaporative stress, has focused on relatively deep bog systems. However, shallower peatlands and marginal connective wetlands can be essential components of many landscape mosaics. In order to better understand factors influencing moss productivity, water balance simulations using HYDRUS‐1D were run for different soil profile depths, compositions, and antecedent moisture conditions. Our results demonstrate a bimodal distribution of peatland realizations, either primarily conserving water by limiting evapotranspiration or maximizing moss productivity. For sustained periods of evaporative stress, both deep water storage and a shallow initial water table delay the onset of high vegetative stress, thus maximizing moss productivity. A total depth of sand and peat of 0.8 m is identified as the threshold above which increasing peat depth has no effect on changing vegetative stress response. In contrast, wetlands with shallow peat deposits (less than 0.5 m thick) are least able to buffer prolonged periods of evaporation due to limited labile water storage and will thus quickly experience vegetative stress and so limit evaporation and conserve water. With a predicted increase in the frequency and size of rain events in continental North America, the moss productivity of shallow wetland systems may increase, but also greater moisture availability will increase the likelihood they remain as wetlands in a changing climate.

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Validation of a Soil Temperature and Moisture Model in Southern Quebec, Canada

Cited by 17 publications

References 12 publications

Giant Ragweed (Ambrosia trifida) Emergence Model Performance Evaluated in Diverse Cropping Systems

Giant Ragweed (Ambrosia trifida) Emergence Model Performance Evaluated in Diverse Cropping Systems

Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea

Peat depth as a control on moss water availability under evaporative stress

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