Time series analysis and mixed models for studying the dynamics of net N mineralization in a soil catena at Gondelsheim (S–W Germany)

Kuzyakova, Irina; Turyabahika, Francis; Stahr, Karl

doi:10.1016/j.geoderma.2006.06.003

Cited by 13 publications

(25 citation statements)

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“…These results indicate that N fertilization does not consistently influence PMN an and when it does, it most often reduces PMN an . The variable effect of N fertilization on PMN an in this study is similar to the findings of others (Fernández et al, 2017;Kuzyakova et al, 2006;Ma et al, 1999). Furthermore, soil properties influenced the effect of N fertilization on PMN an , namely total C, total organic C, SOM, C to N, clay content, and V5 soil NO 3 -N concentration (Figure 3).…”

Section: Nitrogen Fertilization Effect On Pmn An At the V5 Corn Develsupporting

confidence: 89%

“…Second, most soil samples collected for PMN an analysis are obtained before spring N fertilizer application. However, the application of N fertilizer before soil sampling results in greater variability of N mineralization (Fernández et al, 2017;Kuzyakova et al, 2006;Ma, Dwyer, & Gregorich, 1999). Understanding the influence of N fertilizer application on N mineralization has important practical implications because most agricultural fields receive some N fertilizer before or at planting to optimize corn yield.…”

Section: Core Ideasmentioning

confidence: 99%

“…First, most soil samples collected for PMN an analysis are obtained early in the spring when limited mineralization has taken place. These mineralization rates increase through the spring as temperatures increase and change throughout the remainder of the growing season (Culman, Snapp, Green, & Gentry, 2013;Fernández, Fabrizzi, & Naeve, 2017;Kuzyakova, Turyabahika, & Stahr, 2006;Sierra, 1996). However, the differences between early and later season soil and weather conditions and their influence on PMN an have not been investigated.…”

Section: Introductionmentioning

confidence: 99%

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Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Clark

Veum

Fernández

et al. 2020

Soil Science Soc of Amer J

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Understanding the variables that affect the anaerobic potentially mineralizable N (PMN an) test should lead to a standard procedure of sample collection and incubation length, improving PMN an as a tool in corn (Zea mays L.) N management. We evaluated the effect of soil sample timing (preplant and V5 corn development stage [V5]), N fertilization (0 and 180 kg ha −1) and incubation length (7, 14, and 28 d) on PMN an (0-30 cm) across a range of soil properties and weather conditions. Soil sample timing, N fertilization, and incubation length affected PMN an differently based on soil and weather conditions. Preplant vs. V5 PMN an tended to be greater at sites that received < 183 mm of precipitation or < 359 growing degree-days (GDD) between preplant and V5, or had soil C/N ratios > 9.7:1; otherwise, V5 PMN an tended to be greater than preplant PMN an. The PMN an tended to be greater in unfertilized vs. fertilized soil in sites with clay content > 9.5%, total C < 24.2 g kg −1 , soil organic Abbreviations: AWDR, Abundant and well-distributed rainfall; GDD, Growing degree-day; PMN an , Anaerobic potentially mineralizable N; SDI, Shannon diversity index; SOM, Soil organic matter. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Section: Nitrogen Fertilization Effect On Pmn An At the V5 Corn Develsupporting

confidence: 89%

Section: Core Ideasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Clark

Veum

Fernández

et al. 2020

Soil Science Soc of Amer J

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“…Net N mineralization and nitrification rates were measured via the in situ incubation method (Kuzyakova et al, ; Reichmann et al, ). Both N transformation rates were measured 5 times each year, with 3 times in the dry season and twice in the wet season.…”

Section: Methodsmentioning

confidence: 99%

Intensified Precipitation Seasonality Reduces Soil Inorganic N Content in a Subtropical Forest: Greater Contribution of Leaching Loss Than N₂O Emissions

et al. 2019

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Soil nitrogen (N) loss has been predicted to intensify with increased global precipitation changes. However, the relative contributions of leaching and gaseous N emissions to intensified N losses are largely unknown. Thus, we simulated intensified precipitation seasonality in a subtropical forest by extending the dry season via rainfall exclusion and increasing the wet‐season storms via irrigation without changing the total annual precipitation. Extending the dry season length increased the monthly mean soil NO3− content by 25%–64%, net N mineralization rate by 32%–40%, and net nitrification rate by 25%–28%. After adding water in the wet season, the monthly NO3− leaching was enhanced by 43% in the relatively dry year (2013, 2,094‐mm annual rainfall), but reduced by 51% in the relatively wet year (2014, 1,551 mm). In contrast, the monthly mean N2O emissions were reduced by 24% in 2013 but increased by 78% in 2014. Overall, the annual inorganic N content was decreased significantly by the precipitation changes. Decrease of soil inorganic N might be linked to the enhanced NO3− leaching in 2013, and be linked to the increased N2O emissions in 2014. However, in both years the annual total amount of N lost through leaching was significantly greater than that through N2O emissions. The enhanced N2O emissions driven by wet‐season storms were correlated with an increase in nirS abundance. Our results suggest that increased frequency of droughts and storms will decrease soil inorganic N content in warm and humid subtropical forests mainly through enhanced leaching losses.

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“…This exploration can be conducted by statistical techniques or Fourier analysis with the proper adaptation to enable a statistical rather than deterministic function. The combination of techniques that comprise this approach is called spectral analysis (Faes et al, 2004;Kuzyakova et al, 2006). One of the main objectives of spectral analysis is to determine, from a data series, the amount of significant cycles and their respective frequency.…”

Section: Methodsmentioning

confidence: 99%

Environmental Monitoring Model for a Drainage Basin Obtained through Spectral Analysis of Time Series

Faht¹,

Silva²,

Pinheiro³

et al. 2012

Water Environment Research

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BSTRACT: The quality of results of an environmental monitoring plan is limited to the weakest component, which could be the analytical approach or sampling method. Considering both the possibilities and the fragility that sampling methods offer, this environmental monitoring study focused on the uncertainties caused by the time component. Four time series of nutrient concentration at two sampling points (PBt and PB2) in the Ribeirao Garcia basin in Blumenau, Brazil, which were significantly correlated to the spatial component, were considered with a 2-hour resolution to develop efficient sampling models. These models were based on the time at which there was the highest tendency toward adverse environmental effects. Fourier spectral analysis was used to evaluated the time series and resulted in two sampling models: (1) the SMCP (Sampling Model for Critical Period) that operated with 100% efficiency for registering the highest concentration of nutrients and was valid for 83% of the studied parameters; and (2) the SMGCP (Sampling Model for Global Critical Period) that operated with 83 and 50% efficiency for PBl and PB2, respectively Water Environ. Res., 84, 662 (2012).

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Time series analysis and mixed models for studying the dynamics of net N mineralization in a soil catena at Gondelsheim (S–W Germany)

Cited by 13 publications

References 12 publications

Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Intensified Precipitation Seasonality Reduces Soil Inorganic N Content in a Subtropical Forest: Greater Contribution of Leaching Loss Than N₂O Emissions

Environmental Monitoring Model for a Drainage Basin Obtained through Spectral Analysis of Time Series

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Time series analysis and mixed models for studying the dynamics of net N mineralization in a soil catena at Gondelsheim (S–W Germany)

Cited by 13 publications

References 12 publications

Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen

Intensified Precipitation Seasonality Reduces Soil Inorganic N Content in a Subtropical Forest: Greater Contribution of Leaching Loss Than N2O Emissions

Environmental Monitoring Model for a Drainage Basin Obtained through Spectral Analysis of Time Series

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Intensified Precipitation Seasonality Reduces Soil Inorganic N Content in a Subtropical Forest: Greater Contribution of Leaching Loss Than N₂O Emissions