Background and aims Changes in soil moisture availability seasonally and as a result of climatic variability would influence soil nitrogen (N) cycling in different land use systems. This study aimed ...to understand mechanisms of soil moisture availability on gross N transformation rates. Methods A laboratory incubation experiment was conducted to evaluate the effects of soil moisture content (65 vs. 100% water holding capacity, WHC) on gross N transformation rates using the 15N tracing technique (calculated by the numerical model FLUAZ) in adjacent grassland and forest soils in central Alberta, Canada. Results Gross N mineralization and gross NH4+ immobilization rates were not influenced by soil moisture content for both soils. Gross nitrification rates were greater at 100 than at 65% WHC only in the forest soil. Denitrification rates during the 9 days of incubation were 2.47 and 4.91 mg N kg−1 soil d−1 in the grassland and forest soils, respectively, at 100% WHC, but were not different from zero at 65% WHC. In the forest soil, both the ratio of gross nitrification to gross NH4+ immobilization rates (N/IA) and cumulative N2O emission were lower in the 65 than in the 100% WHC treatment, while in the grassland soil, the N/IA ratio was similar between the two soil moisture content treatments but cumulative N2O emission was lower at 65% WHC. Conclusions The effect of soil moisture content on gross nitrification rates differ between forest and grassland soils and decreasing soil moisture content from 100 to 65% WHC reduced N2O emissions in both soils.
Background and purpose To date, very few studies have investigated the effects of litter decomposition on gross nitrogen (N) transformations and N retention in subtropical forest soils. In this ...study, six forest soils were taken from two contrasting forest types (broad-leaved vs. coniferous) in the humid subtropical zones of China to investigate the effects of litter decomposition on gross N transformations. Methods A ¹⁵N tracing experiment was conducted to investigate the effects of litter decomposition (at a rate of 0.5 % w/w) on soil gross N transformations rates in broad-leaved and coniferous forests. Results Litter decomposition enhanced gross N mineralization and NH₄⁺ immobilization rates by 45.9-79.0 % and 553-563 %, respectively. There was a shift from net N mineralization to net N immobilization in each of the forest soils, which was due to litter decomposition. In contrast, gross nitrification rates were unaffected by litter decomposition for each of the forest soils, while gross NO₃⁻ immobilization rates were stimulated significantly by litter decomposition in broadleaved forest soils but not in coniferous forest soils. On average, 39.4 % of the total NO₃⁻ produced was immobilized into organic-N in broad-leaved forest soils due to litter decomposition. Therefore, the decrease in net nitrification rates caused by litter decomposition was attributed to increasing gross NO₃⁻ immobilization rates rather than decreasing gross nitrification rates. During 15 days of incubation, the decomposition of litter increased cumulative N₂O emissions by 55-76 % and 100-640 % in broad-leaved forest and coniferous forest soils, respectively, but there was no effect on the cumulative N₂O emissions for both forest soil types. Conclusions The combined results suggest that the decomposition of litter stimulates N₂O emissions but reduces NH₄⁺ and NO₃⁻ accumulation in forest soils, and thus a delay in N availability for plant N uptake or leaching.
Clinically relevant neuroanatomy is challenging to teach, learn and remember since many functionally important structures are visualized best using histology stains from serial 2D planar sections of ...the brain. In clinical patients, the locations of specific structures then must be inferred from spatial position and surface anatomy. A 3D MRI dataset of neuroanatomy has several advantages including simultaneous multi-planar visualization in the same brain, direct end-user manipulation of the data and image contrast identical to clinical MRI. We created 3D MRI datasets of the postmortem brain with high spatial and contrast resolution for simultaneous multi-planar visualization of complex neuroanatomy.
Whole human brains (
= 6) were immersion-fixed in 4% formaldehyde for 4 weeks, then washed continuously in water for 48 h. The brains were imaged on a clinical 3-T MRI scanner with a 64-channel head and neck coil using a 3D T2-weighted sequence with 400-micron isotropic resolution (voxel = 0.064 mm
; time = 7 h). Besides resolution, this sequence has multiple adjustments to improve contrast compared to a clinical protocol, including 93% reduced turbo factor and 77% reduced effective echo time.
This MRI microscopy protocol provided excellent contrast resolution of small nuclei and internal myelinated pathways within the basal ganglia, thalamus, brainstem, and cerebellum. Contrast was sufficient to visualize the presence and variation of horizontal layers in the cerebral cortex. 3D isotropic resolution datasets facilitated simultaneous multi-planar visualization and efficient production of specific tailored oblique image orientations to improve understanding of complex neuroanatomy.
We created an unlabeled high-resolution digital 3D MRI dataset of neuroanatomy as an online resource for readers to download, manipulate, annotate and use for clinical practice, research, and teaching that is complementary to traditional histology-based atlases. Digital MRI contrast is quantifiable, reproducible across brains and could help validate novel MRI strategies for
structure visualization.
INTRODUCTIONQuantitative T2 mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve ...(EMC) algorithm to identify T2 changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).METHODSThe EMC algorithm uses Bloch simulations to model T2 decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T2 values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation.RESULTSCompared to conventional exponential T2 modeling, EMC fitting provided more accurate estimations of T2 with less variance across scans, MRI systems, and healthy individuals. Thalamic T2 was increased 8.5% in RRMS subjects (p < 0.001) and could be used to discriminate RRMS from healthy controls well (AUC = 0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T2 associated with RRMS diagnosis (all p < 0.05). In healthy controls, we also observed statistically significant T2 differences for different white and gray matter structures.CONCLUSIONSThe EMC algorithm precisely characterizes T2 values, and is able to detect subtle T2 changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T2 variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale.
In order to take best advantage of the electrical resistivity data, kriging spatial component technique was applied to separate the small and large-scale structures of resistivity data. Then the ...spatial structures in resistivity data which are poorly correlated with soil water content are filtered out prior to integrating resistivity data into water content estimation in the soil of a 10ha area located in the Picardie region (Northern of France). The soil water content was measured until 1.2m depth in 81 sites with 0.3m increments by gravimetric method. The resistivity was exhaustively measured for three different depths: 0.5m, 1m, and 2m. The resistivity data represents a set of 5656 measurement points for each of the three depths over the 10ha study area. The methodology involves successively: (1) a principal component analysis (PCA) on the electrical measurements for the three depths of soil; (2) a geostatistical filtering of the local component and noise in the first component (PC1) of PCA which account for 90% of the variance in the electrical measurements for the three depths of soil. Results have shown that the correlation between water content of soil profile (W) and PC1 is highly improved when the local component and noise were filtered out. Finally, the influence of the smoothness of the external drift function on the quality of estimates of a target variable was empirically demonstrated. Indeed, the estimates of W were highly improved when the external drift function used in kriging is much smoother: the large scale of PC1 instead of PC1.
► The geostatistical filtering improves the quality of soil's electrical resistivity. ► The structures poorly correlated with a target should be filtered prior to estimation. ► The smoothness effect of the external drift in the estimation was demonstrated.
Development and use of models to predict and study the production and the environmental impacts of biomass cropping systems are of great interest for their sustainable development. Improvements were ...made to the research version of the STICS crop-soil model in order to simulate biomass production and environmental impacts of Miscanthus x giganteus cropping systems in the long term. This research version was then validated on a large database and in various pedoclimatic environments in France and UK. The model accurately simulated biomass production and nitrogen (N) content in aboveground biomass, from planting until 4 to 20 years of cultivation. The model efficiency (EF) was 0.80 and 0.64 for biomass and N content, respectively, and the values of relative RMSE were 23 and 31 %. Soil water and mineral N contents were also satisfactorily predicted (EF = 0.96 and 0.42; relative RMSE = 10 and 72 %). The model accurately reproduced the effect of management practices on the harvested biomass and N export. Yield gap analysis using simulations with and without active stresses revealed that Miscanthus x giganteus biomass production was limited by both water and N availability during the establishment phase but mainly limited by water availability during the post-establishment phase. The STICS crop-soil model can accurately predict Miscanthus x giganteus biomass production and environmental impacts such as water drainage and nitrate leaching and compare strategies with varying N fertilization, irrigation and harvest date.
Miscanthus × giganteus is often regarded as one of the most promising crops to produce sustainable bioenergy. This perennial crop, renowned for its high productivity associated with low input ...requirements, in particular regarding fertilizers, is thought to have low environmental impacts, but few data are available to confirm this. Our study aimed at assessing nitrate leaching from Miscanthus × giganteus crops in farmers' fields, thus including a wide range of soil and cropping system conditions. We focused on the first years of growth after planting as experimental studies have suggested that Miscanthus × giganteus, once established, results in low nitrate leaching. We combined on‐farm measurements and modeling to estimate drainage, leached nitrogen, and nitrate concentration in drainage water in 38 fields located in Center‐East France during two winters (November 2010 to March 2011, November 2011 to March 2012).
Nitrate leaching and nitrate concentration in drainage water were on average very low. Nitrate leaching averaged 6 kg N ha−1 whereas nitrate concentration averaged 12 mg l−1. These low values are attributable to the low estimates of drainage water (mean = 166 mm) but also to the low soil mineral nitrogen contents measured at the beginning of winter (mean = 37 kg N ha−1). Our results were, however, very variable, mainly due to the crop age: nitrate leaching and nitrate concentration were critically higher during the winter following the first growth year of Miscanthus × giganteus, reflecting the low development of the crop. This variability was also explained by the range of soil and cropping conditions explored in the on‐farm design: shallow and/or sandy soils as well as fields where establishment failed had a higher risk of nitrate leaching.
Abstract The purpose of this study is to assess the image quality and diagnostic accuracy of non-contrast quadruple inversion-recovery balanced-SSFP MRA (QIR MRA) for detection of aortoiliac disease ...in a clinical population. QIR MRA was performed in 26 patients referred for routine clinical gadolinium-enhanced MRA (Gd-MRA) for known or suspected aortoiliac disease. Non-contrast images were independently evaluated for image quality and degree of stenosis by two radiologists, using consensus Gd-MRA as the reference standard. Hemodynamically significant stenosis (≥50%) was found in 10% (22/226) of all evaluable segments on Gd-MRA. The sensitivity and specificity for stenosis evaluation by QIR MRA for the two readers were 86%/86% and 95%/93% respectively. Negative predictive value and positive predictive value were 98%/98% and 63%/53% respectively. For stenosis evaluation of the aortoiliac region QIR MRA showed good agreement with the reference standard with high negative predictive value and a tendency to overestimate mild disease presumably due to the flow-dependence of the technique. QIR MRA could be a reasonable alternative to Gd-MRA for ruling out stenosis when contrast is contraindicated due to impaired kidney function or in patients who undergo abdominal MRA for screening purposes. Further work is necessary to improve performance and justify routine clinical use.
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•SOC stocks (0−60 cm) did not differ between tillage treatments after 47 years.•C mineralization rates in each soil layer were calculated using 13C natural tracing.•C mineralization ...rates were correlated with C inputs but not with tillage intensity.•AMG model could reproduce the evolution of SOC and C4 stocks in the soil profile.•Reduced tillage increased mineralization rate in the topsoil and decreased it below.
In spite of the large number of studies conducted on the drivers of soil organic carbon (SOC) stocks, there is still no consensus on the impact of tillage on the distribution and turnover rate of SOC in the soil profile. Few studies have characterized precisely the turnover of SOC using 13C natural tracing or simulated the SOC evolution per soil layer. In this study, we combined several approaches (diachronic analysis of SOC stocks, isotopic tracing and modelling) for characterizing the SOC evolution per soil layer in one of the oldest tillage experiments comparing no-till (NT), shallow till (ST) and full inversion tillage (FIT) combined with six crop managements. The new measurements made in 2017 reported in this paper confirm that i) tillage had no effect on SOC stocks integrated over the old ploughed layer (∼0−28 cm) or deeper (∼0−58 cm) and ii) reduced tillage affected the SOC distribution in the soil profile, with SOC storage in the upper layer (∼0−10 cm) offset by a SOC loss in the underlying layer (∼10−28 cm). The change in rotation (from C4 to C3 crops) in two crop management treatments allowed to quantify the decrease in C4 stocks during 19 years and calculate the specific mineralization rates relative to tillage treatments and soil layers. The mineralization rates did not vary significantly between tillage treatments in the whole (old) ploughed layer (∼0−28 cm) but varied according to depth and tillage. The highest rates were found in the layer 0−5 cm of NT or ST and the lowest rates in the layer 10−28 cm of the same tillage treatments. The rates were highly correlated with estimated C inputs and particulate organic matter contents in each layer, but not with tillage intensity. The evolution of total SOC and C4 stocks of each soil layer was simulated with AMG model during 47 years. The standard model (with a single mineralization rate) gave a good prediction of SOC evolution when applied to the whole profile (∼0−28 cm) but not for each individual layer. Including a relationship between C input and mineralization rate in the model allowed to well simulate the SOC evolution in all soil layers. This study shows that the main effect of a change in tillage on SOC storage is the change in the distribution of C input throughout the profile and the corresponding variation of the priming effect rather than the change in physical soil disturbance.
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