Respiration Data Research Articles

Genomics and physiology of a marine flavobacterium encoding a proteorhodopsin and a xanthorhodopsin-like protein.

Proteorhodopsin (PR) photoheterotrophy in the marine flavobacterium Dokdonia sp. PRO95 has previously been investigated, showing no growth stimulation in the light at intermediate carbon concentrations. Here we report the genome sequence of strain PRO95 and compare it to two other PR encoding Dokdonia genomes: that of strain 4H-3-7-5 which shows the most similar genome, and that of strain MED134 which grows better in the light under oligotrophic conditions. Our genome analysis revealed that the PRO95 genome as well as the 4H-3-7-5 genome encode a protein related to xanthorhodopsins. The genomic environment and phylogenetic distribution of this gene suggest that it may have frequently been recruited by lateral gene transfer. Expression analyses by RT-PCR and direct mRNA-sequencing showed that both rhodopsins and the complete β-carotene pathway necessary for retinal production are transcribed in PRO95. Proton translocation measurements showed enhanced proton pump activity in response to light, supporting that one or both rhodopsins are functional. Genomic information and carbon source respiration data were used to develop a defined cultivation medium for PRO95, but reproducible growth always required small amounts of yeast extract. Although PRO95 contains and expresses two rhodopsin genes, light did not stimulate its growth as determined by cell numbers in a nutrient poor seawater medium that mimics its natural environment, confirming previous experiments at intermediate carbon concentrations. Starvation or stress conditions might be needed to observe the physiological effect of light induced energy acquisition.

Integrating spatial and temporal oxygen data to improve the quantification of in situ petroleum biodegradation rates

Accurate estimation of biodegradation rates during remediation of petroleum impacted soil and groundwater is critical to avoid excessive costs and to ensure remedial effectiveness. Oxygen depth profiles or oxygen consumption over time are often used separately to estimate the magnitude and timeframe for biodegradation of petroleum hydrocarbons in soil and subsurface environments. Each method has limitations. Here we integrate spatial and temporal oxygen concentration data from a field experiment to develop better estimates and more reliably quantify biodegradation rates. During a nine-month bioremediation trial, 84 sets of respiration rate data (where aeration was halted and oxygen consumption was measured over time) were collected from in situ oxygen sensors at multiple locations and depths across a diesel non-aqueous phase liquid (NAPL) contaminated subsurface. Additionally, detailed vertical soil moisture (air-filled porosity) and NAPL content profiles were determined. The spatial and temporal oxygen concentration (respiration) data were modeled assuming one-dimensional diffusion of oxygen through the soil profile which was open to the atmosphere. Point and vertically averaged biodegradation rates were determined, and compared to modeled data from a previous field trial. Point estimates of biodegradation rates assuming no diffusion ranged up to 58 mg kg−1 day−1 while rates accounting for diffusion ranged up to 87 mg kg−1 day−1. Typically, accounting for diffusion increased point biodegradation rate estimates by 15–75% and vertically averaged rates by 60–80% depending on the averaging method adopted. Importantly, ignoring diffusion led to overestimation of biodegradation rates where the location of measurement was outside the zone of NAPL contamination. Over or underestimation of biodegradation rate estimates leads to cost implications for successful remediation of petroleum impacted sites.

CO2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: Estimates from flux tower measurements

We analyzed net CO2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σVPD. In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100g CO2m−2year−1. The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America.

Respiratory sinus arrhythmia, shyness, and effortful control in preschool-age children

Resting respiratory sinus arrhythmia (RSA) and shyness were examined as predictors of effortful control (EC) in a sample of 101 preschool-age children. Resting RSA was calculated from respiration and heart rate data collected during a neutral film; shyness was measured using parents’, preschool teachers’, and classroom observers’ reports; and EC was measured using four laboratory tasks in addition to questionnaire measures. Principal components analysis was used to create composite measures of EC and shyness. The relation between RSA and EC was moderated by shyness, such that RSA was positively related to EC only for children high in shyness. This interaction suggests that emotional reactivity affects the degree to which RSA can be considered a correlate of EC. This study also draws attention to the need to consider the measurement context when assessing resting psychophysiology measures; shy individuals may not exhibit true baseline RSA responding in an unfamiliar laboratory setting.

Evaluation of mechanical accuracy for couch‐based tracking system (CBTS)

This study evaluated the mechanical accuracy of an in‐house–developed couch‐based tracking system (CBTS) according to respiration data. The overall delay time of the CBTS was calculated, and the accuracy, reproducibility, and loading effect of the CBTS were evaluated according to the sinusoidal waveform and various respiratory motion data of real patients with and without a volunteer weighing 75 kg. The root mean square (rms) error of the accuracy, the reproducibility, and the sagging measurements were calculated for the three axes (X, Y, and Z directions) of the CBTS. The overall delay time of the CBTS was 0.251 sec. The accuracy and reproducibility in the Z direction in real patient data were poor, as indicated by high rms errors. The results of the loading effect were within 1.0 mm in all directions. This novel CBTS has the potential for clinical application for tumor tracking in radiation therapy.PACS number: 87.55.ne

Persistent Metal Contamination Limits Lotic Ecosystem Heterotrophic Metabolism after More Than 100 Years of Exposure: A Novel Application of the Resazurin Resorufin Smart Tracer

Persistent stress from anthropogenic metal deposition in lotic ecosystems is a global concern. This long-term selective pressure shapes hyporheic microbial assemblages and influences ecosystem functional integrity. We hypothesized that, even after 100 years of adaptation opportunity, ecosystem function remains inhibited by sediment-associated metal stress and that the Resazurin Resorufin Smart Tracer can be used to quantify this impact. The Resazurin Resorufin Smart Tracer system is applied here in a novel capacity as an indicator of ecosystem function by quantifying ecosystem respiration of microbial communities. Hyporheic microbial communities exposed to differing magnitudes of chronic metal stress were compared to pristine reference sites in controlled column experiments. A Markov chain Monte Carlo technique was developed to solve the inverse smart tracer transport equation to derive community respiration data. Results suggest metals inhibit respiration by 13-30% relative to reference sites and this inhibition is directly related to the level of in situ metal stress. We demonstrate the first application of a hydrologic smart tracer as a functional indicator of ecological integrity within anthropogenically influenced flowing water systems and provide data suggesting resilience is limited in hyporheic ecosystems even after more than a century of microbial adaption to chronic pollutants.

Carbon balance in grapevines under different soil water supply: importance of whole plant respiration

Background and Aims: Net carbon gain commonly estimated from leaf photosynthesis measurements often overestimates grapevine production. This is usually attributed to canopy complexity and a lack of plant respiration data. The present study evaluates the significance of plant respiration in correcting this overestimation. Methods and Results: Non-grafted and non-productive young plants of four grapevine varieties were grown either under irrigation or controlled water stress for 30 days. Daily time courses of leaf photosynthesis and transpiration were determined along with measurements of leaf, stem and root respiration, from which whole plant carbon balance was estimated. Up to 30‐60% of carbon obtained by photosynthesis is used in respiration, with root respiration being the largest user of fixed carbon (up to 75%). Conclusions: Whole plant respiration represents a significant part of total carbon balance and accounts for the largest part of the discrepancy between photosynthesis-based estimates of plant production and actual plant production. Significance of the Study: The present study presents a quantitative evaluation of the importance of plant respiration in grapevine carbon balance and biomass production, highlighting that gas exchange studies aiming predict plant production should include estimates of respiration, especially of roots. Abbreviations AN net photosynthesis; AN/E instantaneous water use efficiency; AN/gs intrinsic water use efficiency; ANmax maximum leaf photosynthesis rate; E leaf transpiration rate; gs stomatal conductance; IRGA infrared gas analyzers; PB plant biomass; PCB plant carbon balance; RDleaf leaf dark respiration; Rroot root respiration; Rstem stem respiration; SWC soil water content; TBI total biomass increment; TDR Time Domain Reflectometry; d 13 C carbon isotope ratio; YMD midday leaf water potential.

Data fusion for estimating respiratory rate from a single-lead ECG

Respiratory rate, an important antecedent of patient deterioration, is inadequately recorded by hospital staff, partially due to the absence of a reliable automated technique for measuring it. The ECG has been proposed by several authors in recent years as a source of reliable respiratory information. Most algorithms proposed use either respiratory sinus arrhythmia (RSA) or the R-peak amplitude (RPA) modulation of the ECG. In this paper, we propose a novel method for estimating respiratory rate from the ECG which fuses frequency information from the two methods. The method was evaluated on data from 40 young and elderly subjects and validated against a “gold standard” respiratory rate obtained from simultaneously recorded respiration data. The fusion method outperformed the RSA and RPA methods, giving a mean absolute error of 0.81bpm for the young subject population and 0.84bpm for the elderly, using 1-min windows of data. Unlike other algorithms, the technique does not underperform at the lower or higher respiratory rates.

Biodegradability of organic matter in fire-affected mineral soils of Southern Spain

Incorporated into the soil, naturally formed pyrogenic organic matter (PyOM) is considered as highly recalcitrant, but direct estimation of PyOM decomposition rates are scarce. With this aim in mind, we subjected organic matter (OM) of fire-affected and unaffected soils to biochemical degradation under laboratory conditions and monitored CO2 production over a period of seven months. The soils derived from the Sierra de Aznalcóllar, Southern Spain, and were sampled 4 weeks and 5 years after a severe fire. Virtual fractionation of the solid-state 13C nuclear magnetic resonance (NMR) spectra of the fire-affected soils into fire-unaffected soil organic matter (SOM) and PyOM yielded charcoal C contributions of 30 to 50% to the total organic C (Corg) of the sample. Fitting the respiration data with a double exponential decay model revealed a fast carbon flush during the first three weeks of the experiment. Solid-state 13C NMR spectroscopy evidenced the contribution of aromatic moieties of the PyOM to this initial carbon release and to the biosynthesis of new microbial biomass. Considering the loss of microbiologically easily available fresh litter by wildfires, this relatively labile PyOM fraction may contribute to a fast recovery of a fire-affected site. The input of PyOM resulted in an increase of the mean residence time (MRT) of the slow OM pool of the soil by a factor of 3–4 to approximately 40 years. Assuming that under field conditions, the microbial activity corresponds to approximately 10% of the value observed under optimal laboratory conditions, MRTs of 500–600 years were estimated for the slow PyOM pool. The fact that these times are only 5–6 times longer than those calculated for fire-unaffected SOM rises doubts about the presumed big influence of PyOM as an additional C-sink in soils. On the other hand, although being small the difference in turnover rates is evident and has some major implication with respect to long-term alteration of the chemical composition of OM in fire-affected soils. In case of a reduced input of fresh litter, the preferential degradation of fire-unaffected SOM yields in a selective preservation of PyOM. To what extent this can alter soil properties, has still to be elucidated. In cultivated soils rarely affected by fire or with low charcoal input after burning of harvest, the impact of PyOM accumulation may be of minor importance. On the other hand, for soils regularly amended with high amounts of biochar or subjected to frequent natural or prescribed burnings, it may be an important factor.

Specific features of oil biodegradation in meadow-chestnut soils of the Stavropol region (model experiment)

Oil biodegradation in oil-contaminated meadow-chestnut soils under the impact of different biological preparations was studied in a model experiment. The soils differed from one another in the age of contamination and in the presence/absence of the stage of preliminary biological remediation. Background uncontaminated soils served as the control. To characterize oil degradation, the indices of basal respiration (BR) and dehydrogenase activity (DA) and data on oil concentrations in the soil were applied. It was shown that the most complete biodegradation of oil takes place in the soils with recent oil contamination in comparison with the soils contaminated with oil for 6.5 and 19.5 months. Maximum BR values were observed in the soils contaminated with oil for 19.5 months, whereas maximum DA values were observed in the soils contaminated with oil for 6.5 months. According to the multivariate analysis of variance, the major factors affecting the rate of oil biodegradation were the age of oil contamination, the biological preparation applied, and the presence (or absence) of the stage of preliminary biological remediation. These factors specified 18, 72, and 3% of the total variance of the residual oil content in the samples, respectively. The type of the applied biological preparations had the major effect on the BR and DA indices specifying 63 and 53% of their total variances, respectively. The results obtained in this study can be used as recommendations for remediation of oil-contaminated soils in the Stavropol region.

Shrub encroachment alters sensitivity of soil respiration to temperature and moisture

A greater abundance of shrubs in semiarid grasslands affects the spatial patterns of soil temperature, moisture, and litter, resulting in fertile islands with potentially enhanced soil metabolic activity. The goal of this study was to quantify the microsite specificity of soil respiration in a semiarid riparian ecosystem experiencing shrub encroachment. We quantified the response of soil respiration to different microsite conditions created by big mesquite shrubs (near the trunk and the canopy edge), medium‐sized mesquite, sacaton bunchgrasses, and open spaces. We hypothesized that soil respiration would be more temperature sensitive and less moisture sensitive and have a greater magnitude in shrub microsites compared with grass and open microsites. Field and incubation soil respiration data were simultaneously analyzed in a Bayesian framework to quantify the microsite‐specific temperature and moisture sensitivities and magnitude of respiration. The analysis showed that shrub expansion increases the heterogeneity of respiration. Respiration has greater temperature sensitivity near the shrub canopy edge, and respiration rates are higher overall under big mesquite compared with those of the other microsites. Respiration in the microsites beneath medium‐sized mesquites does not behave like a downscaled version of big mesquite microsites. The grass microsites show more similarity to big mesquite microsites than medium‐sized shrubs. This study shows there can be a great deal of fine‐scale spatial heterogeneity that accompanies shifts in vegetation structure. Such complexity presents a challenge in scaling soil respiration fluxes to the landscape for systems experiencing shrub encroachment, but quantifying this complexity is significantly important in determining overall ecosystem metabolic behavior.

Sleep/wake estimation using only anterior tibialis electromyography data.

BackgroundIn sleep efficiency monitoring system, actigraphy is the simplest and most commonly used device. However, low specificity to wakefulness of actigraphy was revealed in previous studies. In this study, we assumed that sleep/wake estimation using actigraphy and electromyography (EMG) signals would show different patterns. Furthermore, each EMG pattern in two states (sleep, wake during sleep) was analysed. Finally, we proposed two types of method for the estimation of sleep/wake patterns using only EMG signals from anterior tibialis muscles and the results were compared with PSG data.MethodsSeven healthy subjects and five patients (2 obstructive sleep apnea, 3 periodic limb movement disorder) participated in this study. Night time polysomnography (PSG) recordings were conducted, and electrooculogram, EMG, electroencephalogram, electrocardiogram, and respiration data were collected. Time domain analysis and frequency domain analysis were applied to estimate the sleep/wake patterns. Each method was based on changes in amplitude or spectrum (total power) of anterior tibialis electromyography signals during the transition from the sleep state to the wake state. To obtain the results, leave-one-out-cross-validation technique was adopted.ResultsTotal sleep time of the each group was about 8 hours. For healthy subjects, the mean epoch-by-epoch results between time domain analysis and PSG data were 99%, 71%, 80% and 0.64 (sensitivity, specificity, accuracy and kappa value), respectively. For frequency domain analysis, the corresponding values were 99%, 73%, 81% and 0.67, respectively. Absolute and relative differences between sleep efficiency index from PSG and our methods were 0.8 and 0.8% (for frequency domain analysis). In patients with sleep-related disorder, our proposed methods revealed the substantial agreement (kappa > 0.61) for OSA patients and moderate or fair agreement for PLMD patients.ConclusionsThe results of our proposed methods were comparable to those of PSG. The time and frequency domain analyses showed the similar sleep/wake estimation performance.

Response of soil respiration under different mycorrhizal strategies to precipitation and temperature

The symbiotic associations between plant roots and mycorrhizal fungi are almost ubiquitous. These interactions can produce a large amount of soil respiration (R s ) and respond strongly to such climatic changes as temperature and precipitation. The objective of the present study was to explore how interannual variations in environmental factors (i.e., temperature and precipitation) and biotic factors (leaf area index, LAI) influence soil respiration and its temperature sensitivity (appar - ent Q 10 ) in global forest ecosystems that are classified by the mycorrhizae of the dominant plants. Based on a global forest database, the mycorrhizal strategy of tree species over 200 site-years was determined. The R s on the global scale was largely controlled by temperature. When the mycorrhizal strategy was considered, the re- sponses of the R s to the mean annual temperature (MAT), mean annual precipitation (MAP) and LAI were highly variable among different mycorrhizal strategies. For example, the R s was explained mainly by the LAI for arbuscular mycorrhizal (AM) and AM+ ectomycorrhizal (ECM) types and by the MAT for ECM and ECM+EEM (ectendomycorrhizal) +NM (non-mycorrhizal) types. The apparent Q 10 of the R s was not significantly different. This study was the first to evaluate the influence of differ - ent mycorrhizal strategies on forest R s on the global scale. The mycorrhizal strategy plays an important role in the interpretation of the current soil respiration data.

Soil respiration at five sites along the Kalahari Transect: Effects of temperature, precipitation pulses and biological soil crust cover

There are increasing concerns that climatic and land use changes will enhance soil respiration rates and soil organic carbon loss, compromising agricultural productivity and further elevating atmospheric CO 2. Current understanding of dryland respiration is, however, insufficient to enable prediction of the consequences of these changes for dryland soils and CO 2 fluxes. The objectives of this paper are to present in- situ respiration data from five remote sites along a climatic gradient in the Kalahari of Botswana and to determine the effects of temperature, moisture and biological crust cover on soil CO 2 fluxes. Moisture was the primary limiting factor to efflux which increased with amount of simulated rainfall. On dry soils, mean CO 2 efflux was between 1.5 and 5.9 mg C m − 2 h − 1 . After 2 mm and 50 mm simulated wetting, mean rates increased to 4.0 to 21.8 and 8.6 to 41.5 mg C m − 2 h − 1 respectively. Once wet, soil CO 2 efflux increases with temperature, and sites at the hotter northern end of the transect lost more CO 2 than cooler southerly sites. Net respiration rates are, however, muted by autotrophic organisms in biological soil crusts which photosynthesise and take up CO 2. The temperature sensitivity of soil CO 2 efflux increased with moisture. Dry, 2 mm and 50 mm treated soils had a Q 10 of 1.1, 1.5 and 1.95 respectively. Our findings indicate that higher temperatures and a loss of biological crust cover will lead to greater soil C loss through respiration.

TheDualArrhenius andMichaelis–Menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales

AbstractDecomposition of soil carbon stocks is one of the largest potential biotic feedbacks to climate change. Models of decomposition of soil organic matter and of soil respiration rely on empirical functions that relate variation in temperature and soil water content to rates of microbial metabolism using soil‐Csubstrates. Here, we describe a unifying modeling framework to combine the effects of temperature, soil water content, and soluble substrate supply on decomposition of soluble soil‐Csubstrates using simple functions based on process concepts. The model's backbone is the Michaelis–Menten equation, which describes the relationship between reaction velocity and soluble organic‐CandO2substrate concentrations at an enzyme's reactive site, which are determined by diffusivity functions based on soil water content. Temperature sensitivity is simulated by allowing the maximum velocity of the reaction (Vmax) to vary according toArrhenius function. TheDualArrhenius andMichaelis–Menten kinetics (DAMM) model core was able to predict effectively observations from of laboratory enzyme assays of β‐glucosidase and phenol‐oxidase across a range of substrate concentrations and incubation temperatures. The model also functioned as well or better than purely empirical models for simulating hourly and seasonal soil respiration data from a trenched plot in a deciduous forest at theHarvard Forest, in northeasternUnitedStates. TheDAMMmodel demonstrates that enzymatic processes can be intrinsically temperature sensitive, but environmental constrains of substrate supply under soil moisture extremes can prevent that response to temperature from being observed. We discuss howDAMMcould serve as a core module that is informed by other modules regarding microbial dynamics and supply of soluble‐Csubstrates from plant inputs and from desorption of physically stabilized soil‐Cpools. Most importantly, it presents a way forward from purely empirical representation of temperature and moisture responses and integrates temperature‐sensitive enzymatic processes with constraints of substrate supply.

Mitochondrial lipid oxidation is impaired in cultured myotubes from obese humans

The skeletal muscle of obese humans is characterized by an inability to appropriately respond to alterations in substrate availability. The purpose of this study was to determine if this metabolic inflexibility with obesity is retained in mitochondria of human skeletal muscle cells raised in culture (HSkMC) and to identify potential mechanisms involved. Mitochondrial respiration was measured in permeabilized myotubes cultured from lean and obese individuals before and after a 24-h lipid incubation. Mitochondrial respiration (state 3) in the presence of lipid substrate (palmitoyl carnitine) increased by almost twofold after lipid incubation in HSkMC from lean, but not obese subjects, indicative of metabolic inflexibility with obesity. The 24-h lipid incubation increased mitochondrial DNA (mtDNA) copy number in HSkMC from lean subjects by +16% (P<0.05); conversely, mtDNA copy number decreased in myotubes cultured from obese individuals (-13%, P=0.06). When respiration data were normalized to mtDNA copy number and other indices of mitochondrial content (COX-IV protein content and CS activity), the significant treatment effects of lipid incubation persisted in the lean subjects, suggesting concomitant alterations in mitochondrial function; no similar adjustment was evident in HSkMC from obese individuals. These data indicate that the skeletal muscle of obese individuals inherently lacks metabolic flexibility in response to lipid exposure, which consists of an inability to increase mitochondrial respiration in the presence of lipid substrate and perhaps by an inability to induce mitochondrial proliferation.

Development of Real-Time Couch-Based Tracking System (CBTS) For Image Guided Radiotherapy: A Feasibility Study

Intra-fraction motions due to respiration in the thoracic and abdominal regions have been observed. Respiration-induced tumor motion can result in radiation-induced toxicity in the healthy tissue. The aim of this study is to evaluate the mechanical accuracy of couch-based tracking system (CBTS) according to the respiration data with measurement the accuracy and delay time of CBTS for clinical application. Position data of the 3 axes using AlignRT (Vision RT, UK) were obtained. The surface position data of the patient is transferred to the serial port in MCU through the RS-232C communication system. MCU generated an optimized control signal and produced the motor control signals in real time using a PID algorithm. And CBTS tracks the surface position data of three directions using three motors. Current couch position information according to the 3 axes was fed back to tracking program using the linear encoder and linear strip. The regular respiratory motion data is a sine wave representing artificial respiration with a constant cycle. The respiration data was recorded at a sampling period of 10 ms for 60 s. We evaluated the mechanical movement of CBTS according to the sine wave and volunteer data. The CBTS has a mechanical delay time between the respiration data and tracking data, and an inherent processing time that the respiration data is transferred to the serial port within micro controller unit (MCU). We can calculate the processing time using the data transfer rate of RS-232C. The overall delay time of CBTS was calculated as the sum of two delay time. The test was repeated at intervals of 60 seconds for 3 minutes. Then we calculated root mean square (rms) error, average error, and standard deviation error of accuracy in 3 directions (X, Y and Z directions) based on the phase difference between the respiration data and tracking data. The result of analyzing the acquisition-correction data shows that the root mean square error and standard deviation of measurement in 3 axes (X, Y, and Z directions) is 2.94 ± 1.67 mm, 2.99 ± 1.69 mm, 5.05 ± 3.02 mm, respectively. Overall delay time of CBTS is calculated about 2.34 × 10−4 sec as the sum of the inherent processing time and the average mechanical delay time of CBTS. This novel CBTS has the potential for clinical application for tumor tracking in radiation therapy. The effect of the delay time needs to be further evaluated from the view-point of dosimetric impact and plan degradation. Further studies are necessary to reduce the delay time, to investigate the novel tumor motion prediction algorithm for real-tracking radiotherapy.

Network design for soil CO 2 monitoring of the northern North American region

Abstract Soil respiration represents a source of CO 2 that greatly exceeds that of fossil fuel use and requires close monitoring in order to account for its contribution to net carbon exchange. While technological innovations continue to improve the quality of respiration monitoring, considerably less effort has been invested in the conceptual framework for monitoring networks. A network architecture and planning process is needed that allows us to anticipate the evolution of significant changes in this carbon pool, to ensure that expertise and resources are available at the appropriate times. In this study we outline a Monte Carlo network design process for large-area soil CO 2 respiration monitoring using ground-based soil efflux equipment. Our effort is designed to accommodate many different possible network parameters, such as various temporal evolutions of soil respiration, deployment schedules and the accessibility of remote areas. Sensitivity tests are used to show the dependence of an optimized network to each factor in order to inform the decision making process about the scope and distribution of required monitoring. We also evaluate whether inexpensive and already existing proxy sensors can augment the network performance. The soil region under consideration was predicted to cumulatively respire approximately 200 Pg of carbon over the next 50 years, with results suggesting the need for soil flux observational nodes in several parts of the North American Arctic, but especially in northwestern Canada, Alaska, and at points in the eastern Canadian Arctic Archipelago. The ideal network locations proved most sensitive to moisture and temperature changes and the associated response of the soil. Correspondingly, the sensitivity analysis showed that accurate temperature, moisture and respiration data is crucial to efficient network placement.

Salinity effects on carbon mineralization in soils of varying texture

In salt-affected soils, soil organic carbon (SOC) levels are usually low as a result of poor plant growth; additionally, decomposition of soil organic matter (SOM) may be negatively affected. Soil organic carbon models, such as the Rothamsted Carbon Model (RothC), that are used to estimate carbon dioxide (CO 2) emission and SOC stocks at various spatial scales, do not consider the effect of salinity on CO 2 emissions and may therefore over-estimate CO 2 release from saline soils. Two laboratory incubation experiments were conducted to assess the effect of soil texture on the response of CO 2 release to salinity, and to calculate a rate modifier for salinity to be introduced into the RothC model. The soils used were a sandy loam (18.7% clay) and a sandy clay loam (22.5% clay) in one experiment and a loamy sand (6.3% clay) and a clay (42% clay) in another experiment. The water content was adjusted to 75%, 55%, 50% and 45% water holding capacity (WHC) for the loamy sand, sandy loam, sandy clay loam and the clay, respectively to ensure optimal soil moisture for decomposition. Sodium chloride (NaCl) was used to develop a range of salinities: electrical conductivity of the 1:5 soil: water extract (EC 1:5) 1, 2, 3, 4 and 5 dS m −1. The soils were amended with 2% (w/w) wheat residues and CO 2 emission was measured over 4 months. Carbon dioxide release was also measured from five salt-affected soils from the field for model evaluation. In all soils, cumulative CO 2–C g −1 soil significantly decreased with increasing EC 1:5 developed by addition of NaCl, but the relative decrease differed among the soils. In the salt-amended soils, the reduction in normalised cumulative respiration (in percentage for the control) at EC 1:5 > 1.0 dS m −1 was most pronounced in the loamy sand. This is due to the differential water content of the soils, at the same EC 1:5; the salt concentration in the soil solution is higher in the coarser textured soils than in fine textured soils because in the former soils, the water content for optimal decomposition is lower. When salinity was expressed as osmotic potential, the decrease in normalised cumulative respiration with increasing salinity was less than with EC 1:5. The osmotic potential of the soil solution is a more appropriate parameter for estimating the salinity effect on microbial activity than the electrical conductivity (EC) because osmotic potential, unlike EC, takes account into salt concentration in the soil solution as a function of the water content. The decrease in particulate organic carbon (POC) was smaller in soils with low osmotic potential whereas total organic carbon, humus-C and charcoal-C did not change over time, and were not significantly affected by salinity. The modelling of cumulative respiration data using a two compartment model showed that the decomposition of labile carbon (C) pool is more sensitive to salinity than that of the slow C pool. The evaluation of RothC, modified to include the decomposition rate modifier for salinity developed from the salt-amended soils, against saline soils from the field, suggested that salinity had a greater effect on cumulative respiration in the salt-amended soils. The results of this study show (i) salinity needs to be taken into account when modelling CO 2 release and SOC turnover in salt-affected soils, and (ii) a decomposition rate modifier developed from salt-amended soils may overestimate the effect of salinity on CO 2 release.

Testing DNDC model for simulating soil respiration and assessing the effects of climate change on the CO 2 gas flux from Irish agriculture

Simulation models can be valuable to investigate potential effects of climate change on greenhouse gas emissions from terrestrial ecosystems. DNDC (the DeNitrification-DeComposition model) was tested against observed soil respiration data from adjacent pasture and arable fields in the Irish midlands. The arable field was converted from grassland approximately 50 years ago and managed since 2003 under two different tillage systems; conventional and reduced tillage. Both fields were located on the same soil type, classified as a free draining sandy loam soil derived from fluvial glacial gravels with low soil moisture holding capacity. Soil respiration measurements were made from January 2003 to August 2005. Three climate scenarios were investigated, a baseline of measured climatic data from a weather station at the field site, and high and low temperature sensitivity scenarios predicted by the Community Climate Change Consortium for Ireland (C4I) based on the Hadley Centre Global Climate Model (HadCM 3) and the Intergovernment Panel on Climate Change (IPCC) A1B emission scenario. The aims of this study were to use measured soil respiration rates to validate the DNDC model for estimating CO 2 efflux from these key Irish soils, investigate the effects of future climate change on CO 2 efflux and estimate the efflux uncertainties due to using different future climate projections. The results indicate that the DNDC model can reliably estimate soil respiration from the two fields examined. The model underestimated annual measured CO 2 efflux from the pasture by only13% (model efficiency: ME = 0.6; root mean square error: RMSE = 1.9 and mean absolute error: MAE = 6.3) and that from the arable conventional and reduced tillage by 9% (ME = 0.6; RMSE = 1.6 and MAE = 2.4) and 8% (ME = 0.23; RMSE = 1.8 and MAE = 2.9), respectively. Short-term land use change had no significant effects on CO 2 effluxes from soil. Using the high temperature sensitivity scenario, future C effluxes would increase by 15% for the pasture and 14 and 16% for the arable conventional and reduced tillage systems, respectively. However, under the low temperature sensitivity scenario, lower increases in the C efflux of 6% for the pasture and 5% for the arable field were predicted. The calculated annual CO 2 efflux uncertainties for using the high and low temperature sensitivity scenarios were 9% for the pasture and 8% for the arable field.