Recovery of Soil C and N in a Tropical Pasture: Passive and Active Restoration

2013 ◽  
Vol 26 (3) ◽  
pp. 201-210 ◽  
Author(s):  
L. L. Roa‐Fuentes ◽  
C. Martínez‐Garza ◽  
J. Etchevers ◽  
J. Campo
Keyword(s):  
Tropical Pasture ◽  
Soil C ◽  
Active Restoration ◽  
Soil C And N ◽  
C And N

SOIL C AND N AS INDICATORS OF VINEYARD SOIL QUALITY IN THE RAVNI KOTARI REGION OF CROATIA

2020 ◽  
Author(s):  
Sonia C. Clemens ◽  
◽  
Mia Brkljaca ◽  
Delaina Pearson ◽  
C. Brannon Andersen
Keyword(s):  
Soil Quality ◽  
Soil C ◽  
Vineyard Soil ◽  
Soil C And N ◽  
C And N

scholarly journals Spatially Related Sampling Uncertainty in the Assessment of Labile Soil Carbon and Nitrogen in an Irish Forest Plantation

2021 ◽  
Vol 11 (5) ◽  
pp. 2139
Author(s):  
Junliang Zou ◽  
Bruce Osborne
Keyword(s):  
Spatial Variability ◽  
Soil Carbon ◽  
Sampling Effort ◽  
Limited Information ◽  
Sampling Area ◽  
Soil C ◽  
Distribution Maps ◽  
Soil C And N ◽  
C And N ◽  
Highly Correlated

The importance of labile soil carbon (C) and nitrogen (N) in soil biogeochemical processes is now well recognized. However, the quantification of labile soil C and N in soils and the assessment of their contribution to ecosystem C and N budgets is often constrained by limited information on spatial variability. To address this, we examined spatial variability in dissolved organic carbon (DOC) and dissolved total nitrogen (DTN) in a Sitka spruce forest in central Ireland. The results showed moderate variations in the concentrations of DOC and DTN based on the mean, minimum, and maximum, as well as the coefficients of variation. Residual values of DOC and DTN were shown to have moderate spatial autocorrelations, and the nugget sill ratios were 0.09% and 0.10%, respectively. Distribution maps revealed that both DOC and DTN concentrations in the study area decreased from the southeast. The variability of both DOC and DTN increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. The cokriging technique performed better than the ordinary kriging for predictions of DOC and DTN, which are highly correlated. This study provides a statistically based assessment of spatial variations in DOC and DTN and identifies the sampling effort required for their accurate quantification, leading to improved assessments of forest ecosystem C and N budgets.

Impacts of irrigation on soil C and N stocks in grazed grasslands depends on aridity and irrigation duration

Geoderma ◽  
2021 ◽  
Vol 399 ◽  
pp. 115109
Author(s):  
Paul L. Mudge ◽  
Jamie Millar ◽  
Jack Pronger ◽  
Alesha Roulston ◽  
Veronica Penny ◽  
...  
Keyword(s):  
Soil C ◽  
Soil C And N ◽  
C And N

scholarly journals C and N urban soil budget and its spatial differentiation in comparison with natural areas in the Wroclaw region of Poland

2018 ◽  
Vol 45 ◽  
pp. 00085
Author(s):  
Izabela Sówka ◽  
Yaroslav Bezyk ◽  
Maxim Dorodnikov
Keyword(s):  
Urban Soil ◽  
Spatial Differentiation ◽  
Clay Content ◽  
Dry Mass ◽  
Microbial Biomass C ◽  
Natural Areas ◽  
Soil C ◽  
Soil C And N ◽  
C And N ◽  
Natural Grassland

An assessment of C and N balance in urban soil compared to the natural environment was carried out to evaluate the influence of biological processes along with human-induced forcing. Soil C and N stocks were quantified on the samples (n=18) collected at 5 - 10 cm depth from dominated green areas and arable lands in the city of Wroclaw (Poland) and the relatively natural grassland located ca. 36 km south-west. Higher soil carbon and nitrogen levels (C/N ratio = 11.8) and greater microbial biomass C and N values (MBC = 95.3, MBN = 14.4 mg N kg-1) were measured in natural grassland compared with the citywide lawn sites (C/N ratio = 15.17, MBC = 84.3 mg C kg-1, MBN = 11.9 mg N kg-1), respectively. In contrast to the natural areas, the higher C and N concentration was measured in urban grass dominated soils (C = 2.7 % and N = 0.18 % of dry mass), which can be explained mainly due to the high soil bulk density and water holding capacity (13.8 % clay content). The limited availability of soil C and N content was seen under the arable soil (C = 1.23 %, N = 0.13 %) than in the studied grasslands. In fact, the significantly increased C/N ratios in urban grasslands are largely associated with land conversion and demonstrate that urban soils have the potential to be an important reservoir of C.

Simulation of protozoa-induced mineralization of bacterial carbon and nitrogen

1992 ◽  
Vol 72 (3) ◽  
pp. 201-216 ◽  
Author(s):  
P. M. Rutherford ◽  
N. G. Juma
Keyword(s):  
N Mineralization ◽  
Ecological Research ◽  
Clay Loam ◽  
Glucose Addition ◽  
Soil C ◽  
Carbon And Nitrogen ◽  
Soil C And N ◽  
C And N ◽  
Typic Cryoboroll ◽  
Bacterial C

Modelling in soil ecological research is a means of linking the dynamics of microbial and faunal populations to soil processes. The objectives of this study were (i) to simulate bacterial-protozoan interactions and flows of C and N in clay loam Orthic Black Chernozemic soil under laboratory condtions; and (ii) to quantify the flux of C and N (inputs and outputs) through various pools using the simulation model. The unique features of this model are: (i) it combines the food chain with specific soil C and N pools, and (ii) it simultaneously traces the flows of C, 14C, N and 15N. It was possible to produce a model that fitted the data observed for the soil. The simulated CO2-C evolved during the first 12 d was due mainly to glucose addition (171 μg C g−1 soil) and cycling of C in the soil (160 μg C g−1 soil). During this interval, bacterial C uptake was 5.5-fold greater than the initial bacterial C pool size. In the first 12 d protozoa directly increased total CO2-C evolution by 11% and increased NH4-N mineralization 3-fold, compared to soil containing only bacteria. Mineralization of C and N was rapid when bacterial numbers were increased as a result of glucose addition. Key words: Acanthamoeba sp., modelling, N mineralization-immobilization, organic matter, Pseudomonas sp., Typic Cryoboroll

scholarly journals Patterns of water infiltration and soil degradation over a 120-yr chronosequence from forest to agriculture in western Kenya

2011 ◽  
Vol 8 (4) ◽  
pp. 6993-7015 ◽  
Author(s):  
G. Nyberg ◽  
A. Bargués Tobella ◽  
J. Kinyangi ◽  
U. Ilstedt
Keyword(s):  
Bulk Density ◽  
Soil Degradation ◽  
Agricultural Land ◽  
Infiltration Rate ◽  
Water Infiltration ◽  
Native Forest ◽  
Western Kenya ◽  
Soil C ◽  
Soil C And N ◽  
C And N

Abstract. Soil degradation is commonly reported in the tropics where forest is converted to agriculture. Much of the native forest in the highlands of western Kenya has been converted to agricultural land in order to feed the growing population, and more land is being cleared. In tropical Africa, this land use change results in progressive soil degradation, as the period of cultivation increases. Sites that were converted to agriculture at different times can be evaluated as a chronosequence; this can aid in our understanding of the processes at work, particularly those in the soil. Both levels and variation of infiltration, soil carbon and other parameters are influenced by management within agricultural systems, but they have rarely been well documented in East Africa. We constructed a chronosequence for an area of western Kenya, using two native forest sites and six fields that had been converted to agriculture for varying lengths of time. We assessed changes in infiltrability (the steady-state infiltration rate), soil C and N, bulk density, δ13C, and the proportion of macro- and microaggregates in soil along a 119 yr chronosequence of conversion from natural forest to agriculture. Infiltration, soil C and N, decreased rapidly after conversion, while bulk density increased. Median infiltration rates fell to about 15 % of the initial values in the forest and C and N values dropped to around 60 %, whilst the bulk density increased by 50 %. Despite high spatial variability in infiltrability, these parameters correlated well with time since conversion and with each other. Our results indicate that landscape planners should include wooded elements in the landscape in sufficient quantity to ensure water infiltration at rates that prevent runoff and erosion. This should be the case for restoring degraded landscapes, as well as for the development of new agricultural areas.

Decoupled Soil Labile Carbon and Nitrogen Dynamics Triggered by Urban Vegetation

2021 ◽  
Author(s):  
Xiaolin Dou ◽  
Meng Lu ◽  
Liding Chen
Keyword(s):  
Land Use ◽  
Urban Forest ◽  
Urban Ecosystems ◽  
Isotopic Analysis ◽  
C Sequestration ◽  
Bare Soil ◽  
N Dynamics ◽  
Soil C ◽  
Soil C And N ◽  
C And N

Abstract Purpose Studies about soil carbon (C) and nitrogen (N) dynamics with land use change are urgently needed for urban ecosystems. We used fractionation of soils combined with stable isotopic analysis to examine soil C and N cycles after decadal forest and lawn planting in the Pearl River Delta, China. Methods Soil samples from bare soil (CK) and four land use treatments (55 and 20 years of forest plantation, F-55 and F-20; 55 and 20 years of lawn plantation, L-55 and L-20) were split into different chemical fractions. Then we analyzed the C and N contents, C/N ratio, δ13C and δ15N, C and N recalcitrant indices (RIC, RIN), and a C pool management index (CPMI).Results Forest vegetation substantially enhanced soil organic carbon (SOC) caused by the recalcitrant (RC) and labile C (LC) pools, while the larger soil organic nitrogen (SON) was ascribed to the increased recalcitrant N (RN). Enhanced LC but minor changes in labile N (LN) suggested a decoupled C and N in labile fractions of the forest soils. In contrast, the larger LN, and the enhanced decomposition of SOC, indicated that the lawns may have inhibited N mineralization of labile pools, also suggesting a decoupled C and N turnover and leading to low RIN values. Conclusions Urban forest and lawn plantations significantly changed the soil C and N dynamics, and emphasized the inconsistency between C and N processes, especially in labile pools, which would eventually lead to minor changes in N and limit the ecosystem C sequestration.

scholarly journals Parameter-induced uncertainty quantification of soil N<sub>2</sub>O, NO and CO<sub>2</sub> emission from Höglwald spruce forest (Germany) using the LandscapeDNDC model

2012 ◽  
Vol 9 (10) ◽  
pp. 3983-3998 ◽  
Author(s):  
K.-H. Rahn ◽  
C. Werner ◽  
R. Kiese ◽  
E. Haas ◽  
K. Butterbach-Bahl
Keyword(s):  
Greenhouse Gas ◽  
Trace Gas ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Gas Emissions ◽  
Soil C ◽  
Trace Gas Emissions ◽  
Soil Atmosphere ◽  
Soil C And N ◽  
C And N

Abstract. Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development. The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used. Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes.

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