Nitrogen additions affect litter quality and soil biochemical properties in a peatland of Northeast China

Song, Yanyu; Song, Changchun; Meng, Hu; Swarzenski, Christopher M.; Wang, Xianwei; Tan, Wenwen

doi:10.1016/j.ecoleng.2016.12.025

Cited by 53 publications

(18 citation statements)

References 79 publications

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“…Several previous field-scale surveys and N-fertilization experiments carried out in north-western European heathlands provided strong evidence of the impact of N deposition on soil nutrients, indicated by an increase in extractable N-NH 4 + and N-NO 3 − under high-N inputs (e.g., Phoenix et al, 2012;Southon et al, 2013). Similar results were also reported from other systems such as subalpine forests (Boot et al, 2016), permafrost peatlands (Song et al, 2017), and semiarid Mediterranean shrublands (Ochoa-Hueso et al, 2013. In Cantabrian marginal montane heathlands, we only observed an increase in soil extractable N-NH 4 + in the chronic high N treatment (N56; 10 years), but no changes in soil extractable N-NO 3 − .…”

Section: Time-and Dose-related Effects Of N Fertilizationsupporting

confidence: 77%

“…The observed N-driven changes in soil nutrient contents may also be related to the alteration in the functioning of soil microorganisms and the resulting soil extracellular enzyme activities, determined by the levels of metabolic nutrient demands (Jian et al, 2016;Ochoa-Hueso et al, 2011;Sinsabaugh and Follstad, 2012;Song et al, 2017). We reported a significant rise in the activity of the acid phosphatase enzyme in response to N fertilization, especially in the chronic high N treatment (N56).…”

Section: Figmentioning

confidence: 85%

“…ing, tissue and litter chemistry or plant susceptibility to biotic (e.g., pathogen or pests) and abiotic (e.g., frost or drought) stressors] (Bähring et al, 2017;Jones and Power, 2012;Marcos et al, 2003;Meyer-Grünefeldt et al, 2016;Southon et al, 2013;Taboada et al, 2016). Elevated N inputs stimulate N mineralization rates (Phoenix et al, 2012), resulting in increased soil extractable N-NH 4 + and N-NO 3 − (Boot et al, 2016;Song et al, 2017;Southon et al, 2013). This enhanced soil N availability may cause either an increase (Du et al, 2014;Haugwitz et al, 2011) or decrease (Ajwa et al, 1999;Boot et al, 2016) in the nutrient contents of the soil microbial biomass, altering the cycles of soil C and N (Contosta et al, 2015;Ramírez et al, 2012;Zhu et al, 2015), and the ericoid mycorrhizal (ERM) fungal community associated with Calluna in nutrient-poor environments (Caporn et al, 1995;Yesmin et al, 1996).…”

Section: U N C O R R E C T E D P R O O Fmentioning

confidence: 99%

“…This enhanced soil N availability may cause either an increase (Du et al, 2014;Haugwitz et al, 2011) or decrease (Ajwa et al, 1999;Boot et al, 2016) in the nutrient contents of the soil microbial biomass, altering the cycles of soil C and N (Contosta et al, 2015;Ramírez et al, 2012;Zhu et al, 2015), and the ericoid mycorrhizal (ERM) fungal community associated with Calluna in nutrient-poor environments (Caporn et al, 1995;Yesmin et al, 1996). Since soil microorganisms are considered the primary sources of soil enzymes, and these are involved in nutrient metabolism and decomposition processes (Fatemi et al, 2016;Ramírez et al, 2012;Sinsabaugh and Follstad, 2012;Song et al, 2017;Zhu et al, 2015), an increase in N inputs is expected to alter soil enzymatic activities such as acid phosphatase (P cycle), urease (N cycle) and β-glucosidase (C cycle) (Ajwa et al, 1999;Jian et al, 2016;Ochoa-Hueso et al, 2011. These variations very likely affect the storage, turnover and uptake of soil nutrients (Cenini et al, 2016;Jones and Power, 2012).…”

Section: U N C O R R E C T E D P R O O Fmentioning

confidence: 99%

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Time- and age-related effects of experimentally simulated nitrogen deposition on the functioning of montane heathland ecosystems

Calvo-Fernández

Taboada

Fichtner

et al. 2018

Science of The Total Environment

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Ecosystems adapted to low nitrogen (N) conditions such as Calluna-heathlands are especially sensitive to enhanced atmospheric N deposition that affects many aspects of ecosystem functioning like nutrient cycling, soil properties and plant-microbial-enzyme relationships. We investigated the effects of five levels of experimentally-simulated N deposition rates (i.e., N fertilization treatments: 0, 10, 20 and 50kgNhayr for 3years, and 56kgNhayr for 10years) on: plant, litter, microbial biomass and soil nutrient contents, soil extracellular enzymatic activities, and plant root ericoid mycorrhizal colonization. The study was conducted in marginal montane Calluna-heathlands at different developmental stages resulting from management (young/building-phase and mature-phase). Our findings revealed that many soil properties did not show a statistically significant response to the experimental addition of N, including: total N, organic carbon (C), C:N ratio, extractable N-NO, available phosphorus (P), urease and β-glucosidase enzyme activities, and microbial biomass C and N. Our results also evidenced a considerable positive impact of chronic (10-year) high-N loading on soil extractable N-NH, acid phosphatase enzyme activity, Calluna root mycorrhizal colonization by ericoid fungi, Calluna shoot N and P contents, and litter N content and N:P ratio. The age of heathland vegetation influenced the effects of N addition on ericoid mycorrhizal colonization, resulting in higher colonized roots in young heathlands at the control, low and medium N-input rates; and in mature ones at the high and chronically high N rates. Also, young heathlands exhibited greater soil extractable N-NO, available P, microbial biomass N, Calluna shoot N and P contents, and litter N content, compared to mature ones. Our results highlighted that accounting for the N-input load and duration, as well as the developmental stage of the vegetation, is important for assessing the effects of added N, particularly at the heathlands' southern distribution limit.

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Section: Time-and Dose-related Effects Of N Fertilizationsupporting

confidence: 77%

Section: Figmentioning

confidence: 85%

Section: U N C O R R E C T E D P R O O Fmentioning

confidence: 99%

Section: U N C O R R E C T E D P R O O Fmentioning

confidence: 99%

See 2 more Smart Citations

Time- and age-related effects of experimentally simulated nitrogen deposition on the functioning of montane heathland ecosystems

Calvo-Fernández

Taboada

Fichtner

et al. 2018

Science of The Total Environment

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“…About 70-80% of the N consumed by dairy cows is excreted in manure (feces and urine), which can result in substantial losses of N to the atmosphere via ammonia (NH3) (Chai et al, 2014;Bell et al, 2016;Chai et al, 2016), nitrous oxide (N2O) (Chadwick et al, 1999) and nitrogen oxides (NOx) (Gu et al, 2012), and to groundwater and surface waters via leaching, erosion, and runoff (Thorburn et al, 2011;Ma et al, 2016). These loses in turn may further degrade the quality of soil, air, water, and natural ecosystems (Galloway et al, 2008;Conley et al, 2009;Song et al, 2017). Global manure nutrient management contributes an estimated 5% of anthropogenic N2O emissions to the atmosphere (Owen and Silver, 2015).…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Dong¹,

Dong²,

Beauchemin³

et al. 2018

Transactions of the ASABE

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Abstract. Manure nitrogen (N) output from dairy cattle is a major environmental concern in China. Various empirical models are available to predict manure N output from dairy cattle, but the accuracy and precision of these models has not been assessed for Chinese conditions. The objective of this study was to evaluate the performance of extant models that predict different forms of manure N output for lactating dairy cows in China with the aim of identifying the best-fit and most suitable prediction models. A total of 35 empirical models were evaluated for their ability to predict N excretion of dairy cows in China fed a wide range of diets. The data set consisted of 99 treatment means from 32 publications with information on animal and dietary characteristics and N output flows. Performance of the models was evaluated using root mean square prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. A model (eq. 19) based on N intake (NI) was selected as best for predicting fecal N excretion (RMSPE = 15.8% and CCC = 0.75). Another model that also used NI as an input variable was most suitable for predicting urinary N (RMSPE = 26.0% and CCC = 0.63, eq. 14) and total N (RMSPE = 15.8% and CCC = 0.81, eq. 31). Models predicting urinary urea N (UUN) and urinary N / total N performed poorly. Overall, the deviation of the regression line from the equality line (y = x line) for even the best-fit urinary, fecal, and total N excretion models demonstrated the need to develop improved models for use under Chinese conditions. Using N output data from dairy cows in China to develop manure N output models may help improve environmental stewardship of the dairy industry in China. Keywords: Dairy cows, Evaluation, Manures, Model performance, Nitrogen excretion.

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Effects of Nitrogen Deposition on Nitrogen-Mineralizing Enzyme Activity and Soil Microbial Community Structure in a Korean Pine Plantation

Zhang

Jin

et al. 2020

Microb Ecol

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Nitrogen additions affect litter quality and soil biochemical properties in a peatland of Northeast China

Cited by 53 publications

References 79 publications

Time- and age-related effects of experimentally simulated nitrogen deposition on the functioning of montane heathland ecosystems

Time- and age-related effects of experimentally simulated nitrogen deposition on the functioning of montane heathland ecosystems

Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Effects of Nitrogen Deposition on Nitrogen-Mineralizing Enzyme Activity and Soil Microbial Community Structure in a Korean Pine Plantation

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