Prediction of daily reference evapotranspiration by a multiple regression method based on weather forecast data

Prediction of daily reference evapotranspiration (ET ₀) is the basis of real-time irrigation scheduling. A multiple regression method for ET ₀ prediction based on its seasonal variation pattern and public weather forecast data was presented for application in East China. The forecasted maximum temperature (T _max), minimum temperature (T _min) and weather condition index (WCI) were adopted to calculate the correction coefficient by multilinear regression under five time-division regimes (10 days, monthly, seasonal, semi-annual and annual). The multiple regression method was tested for its feasibility for ET ₀ prediction using forecasted weather data as the input, and the monthly regime was selected as the most suitable. Average absolute error (AAE) and root mean square error (RMSE) were 0.395 and 0.522 mm d^?1, respectively. ET ₀ prediction errors increased linearly with the increase in temperature prediction error. A temperature error within 3 K is likely to result in acceptable ET ₀ predictions, with AAE and average absolute relative error (AARE) <0.142 mm d^?1 and 5.8%, respectively. However, one rank error in WCI results in a much larger error in ET ₀ prediction due to the high sensitivity of the correction coefficient to WCI and the large relative error in WCI caused by one rank deviation. Improving the accuracy of weather forecasts, especially for WCI prediction, is helpful in obtaining better estimations of ET ₀ based on public weather data.     

Comparison of modeling approaches to quantify residue architecture effects on soil temperature and water

RZ-SHAW is a hybrid model, comprised of modules from the Simultaneous Heat and Water (SHAW) model integrated into the Root Zone Water Quality Model (RZWQM) that allows more detailed simulation of different residue types and architectures that affect heat and water transfer at the soil surface. RZ-SHAW allows different methods of surface energy flux evaluation to be used: (1) the SHAW module, where evapotranspiration (ET) and soil heat flux are computed in concert with a detailed surface energy balance; (2) the Shuttleworth–Wallace (S–W) module for ET in which soil surface temperature is assumed equal air temperature; and (3) the PENFLUX module, which uses a Penman transformation for a soil slab under incomplete residue cover. The objective of this study was to compare the predictive accuracy of the three RZ-SHAW modules to simulate effects of residue architecture on net radiation, soil temperature, and water dynamics near the soil surface. The model was tested in Akron, Colorado in a wheat residue-covered (both standing and flat) no-till (NT) plot, and a reduced till (RT) plot where wheat residue was incorporated into the soil. Temperature difference between the soil surface and ambient air frequently exceeded 17 °C under RT and NT conditions, invalidating the isothermal assumption employed in the S–W module. The S–W module overestimated net radiation (R_n) by an average of 69 Wm⁻² and underestimated the 3-cm soil temperature (T_s3) by 2.7 °C for the RT plot, attributed to consequences of the isothermal assumption. Both SHAW and PENFLUX modules overestimated midday T_s3 for RT conditions but underestimated T_s3 for NT conditions. Better performances of the SHAW and PENFLUX surface energy evaluations are to be expected as both approaches are more detailed and consider a more discretized domain than the S–W module. PENFLUX simulated net radiation slightly better than the SHAW module for both plots, while T_s3 was simulated the best by SHAW, with a mean bias error of +0.1 °C for NT and +2.7 °C for RT. Simulation results for soil water content in the surface 30 cm (θ_v30) were mixed. The NT conditions were simulated best by SHAW, with mean bias error for θ_v30 within 0.006 m³ m⁻³; RT conditions were simulated best by the PENFLUX module, which was within 0.010 m³ m⁻³.     

Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables?

Ecological and hydrological models applied over regional domains generally require the input of spatial meteorological time series. We investigate the potential improvements to space–time regionalisations of sparse meteorological data sets when including information on temporal correlations between successive measurements of minimum temperature (T_min), maximum temperature (T_max) and precipitation (P) from 112 stations across Central Oregon. We compared a number of increasingly complex geostatistical models based on Kriging with a baseline inverse distance weighting algorithm. We varied the number of interpolation data used in both space and time and assessed the impact on interpolation skill. Furthermore, we assessed the error and bias reduction resulting from aggregating estimates over increasingly large temporal supports. We hypothesised that incorporating temporal information would decrease errors, and that error and bias would be reduced when considering estimates aggregated over longer time periods. We found that, contrary to our expectations, incorporation of information on temporal autocorrelation decreased interpolation skill by ～5% for T_min and T_max. However, inclusion of temporal autocorrelation improved results for P by ～10%. Increasing the temporal aggregation of estimates was shown to decrease error by up to 50% and bias by up to 30% (daily vs. annual support). These results indicate that instantaneous error may be diluted for phase lagged or integrating elements of the state vector, such as soil moisture, when implementing such surfaces in modelling applications. Results were more successful for temperature than precipitation (daily % error for jack-knife estimates of T_min = 52, T_max = 13, P = 97), reflecting the stochastic nature of precipitation, and problems with non-linearity for the Kriging algorithm.     

Interpreting the dependence of soil respiration on soil temperature and water content in a boreal aspen stand

Continuous half-hourly measurements of soil CO₂ efflux made between January and December 2001 in a mature trembling aspen stand located at the southern edge of the boreal forest in Canada were used to investigate the seasonal and diurnal dependence of soil respiration (R_s) on soil temperature (T_s) and water content (θ). Daily mean R_s varied from a minimum of 0.1 μmol m⁻² s⁻¹ in February to a maximum of 9.2 μmol m⁻² s⁻¹ in mid-July. Daily mean T_s at the 2-cm depth was the primary variable accounting for the temporal variation of R_s and no differences between Arrhenius and Q₁₀ response functions were found to describe the seasonal relationship. R_s at 10 °C (R_s10) and the temperature sensitivity of R_s (Q_10Rs) calculated at the seasonal time scale were 3.8 μmol m⁻² s⁻¹ and 3.8, respectively. Temperature normalization of daily mean R_s (R_sN) revealed that θ in the 0–15 cm soil layer was the secondary variable accounting for the temporal variation of R_s during the growing season. Daily R_sN showed two distinctive phases with respect to soil water field capacity in the 0–15 cm layer (θ_fc, 0.30 m³ m⁻³): (1) R_sN was strongly reduced when θ decreased below θ_fc, which reflected a reduction in microbial decomposition, and (2) R_sN slightly decreased when θ increased above θ_fc, which reflected a restriction of CO₂ or O₂ transport in the soil profile.Diurnal variations of half-hourly R_s were usually out of phase with T_s at the 2-cm depth, which resulted in strong diurnal hysteresis between the two variables. Daily nighttime R_s10 and Q_10Rs parameters calculated from half-hourly nighttime measurements of R_s and T_s at the 2-cm depth (when there was steady cooling of the soil) varied greatly during the growing season and ranged from 6.8 to 1.6 μmol m⁻² s⁻¹ and 5.5 to 1.3, respectively. On average, daily nighttime R_s10 (4.5 μmol m⁻² s⁻¹) and Q_10Rs (2.8) were higher and lower, respectively, than the values obtained from the seasonal relationship. Seasonal variations of these daily parameters were highly correlated with variations of θ in the 0–15 cm soil layer, with a tendency of low R_s10 and Q_10Rs values at low θ. Overall, the use of seasonal R_s10 and Q_10Rs parameters led to an overestimation of daily ranges of half-hourly R_s (ΔR_s) during drought conditions, which supported findings that the short-term temperature sensitivity of R_s was lower during periods of low θ. The use of daily nighttime R_s10 and Q_10Rs parameters greatly helped at simulating ΔR_s during these periods but did not improve the estimation of half-hourly R_s throughout the year as it could not account for the diurnal hysteresis effect.     

The distribution of volatile isoprenoids in the soil horizons around Pinus halepensis trees

We measured the terpene concentration in pentane and water extracts from soil horizons (litter, organic, top and low mineral) and from roots growing in top and low mineral horizons on a distance gradient from Pinus halepensis L. trees growing alone on a grassland. Terpene concentrations in pentane were higher than in water extracts, although β-caryophyllene showed relatively high solubility in water. The litter and roots were important sources of terpenes in soil. Alpha-pinene dominated in roots growing in both “top” (A1) and “low” (B) mineral horizons (123 ± 36 μg g⁻¹ or 14 ± 5 mg m⁻²) and roots in low mineral horizon (270 ± 91 μg g⁻¹ or 7 ± 2 mg m⁻²). Beta-caryophyllene dominated in litter (1469 ± 331 μg g⁻¹ or 2004 ± 481 mg m⁻²). Terpene concentration in soil decreased with increasing distance to the trunk. This is likely to be related to changes in litter and roots type on the distance gradient from pine to grass and herbs. The relative contributions of all compounds, except α-pinene, were similar in the mineral soils and litter. This suggests that litter of P. halepensis is probably the main source of major terpene compounds. However, long-term emissions of α-pinene from P. halepensis roots might also contribute to α-pinene concentrations in rhizosphere soils.     

Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia

Pluviographic data at 15 min interval from 6 stations in Pulau Penang of Peninsular Malaysia were used to compute rainfall erosivity factor (R) for the revised universal soil loss equation (RUSLE). Three different modelling procedures were applied for the estimation of monthly rainfall erosivity (EI₃₀) values. While storm rainfall (P) and duration (D) data were used in the first approach, the second approach used monthly rainfall for days with rainfall ≥ 10 mm (rain₁₀) and monthly number of days with rainfall ≥ 10 (days₁₀). The third approach however used the Fournier index as the independent variable. Based on the root mean squared error (RMSE) and the percentage error (PE) criteria, models developed using the Fournier index approach was adjudged the best with an average PE value of 0.92 and an average RMSE value of 164.6. Further, this approach was extended to the development of a regional model. Using data from additional sixteen stations and the Fournier index based regional model, EI₃₀ values were computed for each month. ArcView GIS was used to generate monthly maps of EI₃₀ values and also annual rainfall erosivity (R). The rainfall erosivity factor (R) in the region was estimated to vary from 9000 to 14,000 MJ mm ha^− 1 h^− 1 year^− 1.     

Estimating parameters for the Kostiakov-Lewis infiltration model from soil physical properties

Purpose

Infiltration modeling is an important tool to describe the process of water infiltration in the soil. However, direct measurements of the parameters of infiltration models are usually time-consuming and laborious. The present study proposed an effective method to estimate parameters of the Kostiakov-Lewis model (a classical infiltration model) from soil physical properties (SPPs).

Materials and methods

Parameters k, α, and f₀ of the Kostiakov-Lewis infiltration models were measured in 240 double-ring field experiments in Shanxi Province, China. SPPs at the corresponding experimental points were measured at the topsoil layer (TL, 0–20 cm) and the top-subsoil layer (TSL, 0–20 and 20–40 cm). The Kennard-Stone (KS) sampling method and principal component analysis (PCA) were used for dividing training samples and extracting principal components (PCs) of SPPs, respectively. Partial least squares (PLS), back-propagation neural networks (BPNNs), and a support vector machine (SVM) were used to establish models for estimating k, α, and f₀ with the SPPs of TL and TSL as the input variables (IV).

Results and discussion

The differences in soil density (BD), texture, and moisture content (θ_v) were found in topsoil and subsoil, but loading distributions of SPPs on PCs present different degrees of correlation. Moreover, SVM produced the most accurate estimation among these three methods for using the SPP of TL and TSL as inputs. The highest accuracy for k estimations was obtained by SVM using the SPP of TL as IV; R and RMSE in the model test process were 0.78 and 0.3 cm min^?1, respectively. However, using SPP of TSL as IV obtained the highest accuracy for both α and f₀ estimations with the SVM method (R values were 0.71 and 0.82, respectively, and RMSE values were 0.03 and 0.018 cm min^?1) in the model testing.

Conclusions

The SVM method with SPPs as inputs is an effective and practical method for estimating the parameters of the Kostiakov-Lewis infiltration model.

     

Distillery effluents effect on soil organic carbon and aggregate stability of a Vertisol in India

Distillery effluent, a waste by-product of distillery industries, is usually applied to arable land near the distilleries as irrigation water or as a soil amendment. To evaluate the effect of distillery effluent, both spent wash (SW) and post-methanated effluent (PME), on soil organic carbon and aggregate stability, a field experiment on a soybean (Glysine max L.)–wheat (Triticum aestivum L.) system was conducted for five years on a Vertisol of central India. The treatments were control (no fertilizer or manure or SW or PME, T₁), 100% NPK + farmyard manure (FYM) @ 4 Mg ha⁻¹ to soybean (T₂), four graded levels of SW, viz., 2.5 cm SW to soybean and none to wheat (T₃), 2.5 cm SW to soybean and 1.25 cm to wheat (T₄), 5 cm SW to soybean and none to wheat (T₅), 5 cm SW to soybean and 2.5 cm to wheat (T₆), and four graded levels of PME, viz., 2.5 cm PME to soybean and none to wheat (T₇), 2.5 cm PME to soybean and 1.25 cm to wheat (T₈), 5 cm PME to soybean and none to wheat (T₉), 5 cm PME to soybean and 2.5 cm to wheat (T₁₀). The organic carbon of the surface (0–15 cm) soil that received either PME or SW (treatments T₃–T₁₀), was significantly (P < 0.05) higher than in treatments T₁ and T₂. The mean weight diameter (MWD) of water stable aggregates in this soil layer was also significantly higher in treatments T₃–T₁₀, compared with T₁ and T₂. The MWD showed a positive linear relationship with the organic carbon content of the soil (R² = 0.54**). The proportion of macro-aggregates was higher in SW treated plots than PME, no distillery effluents and NPK + FYM treatments. However, the micro-aggregates showed the reverse trend. The macro-aggregate-associated carbon was higher in SW treated plots. It was highest in T₆ and lowest in T₁. The plots receiving the PME and SW showed increased soil organic carbon, MWD, percentage macro- and micro-aggregate-associated carbon than T₁ and T₂. Application of distillery effluents increased the aggregate stability of the Vertisol through enhanced soil organic carbon as well as the aggregate-associated carbon. So application of SW or PME could be a viable option for soil aggregate stability and enhanced productivity.     

Contribution of fine roots to ecosystem biomass and net primary production in black spruce, aspen, and jack pine forests in Saskatchewan

Fine root (<2 mm) processes contribute to and exhibit control over a large pool of labile carbon (C) in boreal forest ecosystems because of the high proportion of C allocated to fine root net primary production (NPP), and the rapid decomposition of fine roots relative to aboveground counterparts. The objective of this study was to determine the contribution of fine roots to ecosystem biomass and NPP in a mature black spruce (Picea mariana Mill.) (OBS), aspen (Populus tremuloides Michx.) (OA), and jack pine (Pinus banksiana Lamb.) (OJP) stand, and an 11-year-old harvested jack pine (HJP) stand in Saskatchewan. Estimates of fine root biomass and NPP were obtained from nine minirhizotron (MR) tubes at each of the four Boreal Ecosystem Research and Monitoring Sites (BERMS). Fine root data were collected once a month for May–September in 2003 and 2004. Additional C biomass and NPP data for various components of the forest stands were obtained from Gower et al. (1997) and Howard et al. (2004). Annual fine root biomass averaged 3.10 ± 0.89, 1.71 ± 0.49, 1.62 ± 0.32, and 2.96 ± 0.67 Mg C ha⁻¹ (means ± S.D.) at OBS, OA, OJP, and HJP, respectively, comprising between 1 and 6% of total stand biomass. Annual fine root NPP averaged 2.66 ± 0.97, 2.03 ± 0.43, 1.44 ± 0.43, and 2.16 ± 0.81 Mg C ha⁻¹ year⁻¹ (means ± S.D.) at OBS, OA, OJP, and HJP, respectively, constituting between 41 and 71% of total stand NPP. Results of this study indicate that fine roots produce a large amount of C in boreal forests. It is speculated that fine root NPP may control a large amount of labile C-cycling in boreal forests and that fine root responses to environmental and anthropogenic stress may be an early indicator of impaired ecosystem functioning.     

Spatial structures of N2O, CO2, and CH4 fluxes from Acacia mangium plantation soils during a relatively dry season in Indonesia

We investigated spatial structures of N₂O, CO₂, and CH₄ fluxes during a relatively dry season in an Acacia mangium plantation stand in Sumatra, Indonesia. The fluxes and soil properties were measured at 1-m intervals in a 1 × 30-m plot (62 grid points) and at 10-m intervals in a 40 × 100-m plot (55 grid points) at different topographical positions of the upper plateau, slope, and valley bottom in the plantation. Spatial structures of each gas flux and soil property were identified using geostatistical analysis. The means (±SD) of N₂O, CO₂, and CH₄ fluxes in the 10-m grids were 0.54 (±0.33) mg N m⁻² d⁻¹, 2.81 (±0.71) g C m⁻² d⁻¹, and −0.84 (±0.33) mg C m⁻² d⁻¹, respectively. This suggests that A. mangium soils function as a larger source of N₂O than natural forest soils in the adjacent province on Sumatra during the relatively dry season, while CO₂ and CH₄ emissions from the A. mangium soils were less than or consistent with those in the natural forest soils. Multiple spatial dependence of N₂O fluxes within 3.2 m (1-m grids) and 35.0 m (10-m grids), and CO₂ fluxes within 1.8 m (1-m grids) and over 65 m (10-m grids) was detected. From the relationship among N₂O and CO₂ gas fluxes, soil properties, and topographic elements, we suggest that the multiple spatial structures of N₂O and CO₂ fluxes are mainly associated with soil resources such as readily mineralizable carbon and nitrogen in a relatively dry season. The soil resource distributions were probably controlled by the meso- and microtopography. Meanwhile, CH₄ fluxes were spatially independent in the A. mangium soils, and the water-filled pore space appeared to mainly control the spatial distribution of these fluxes.     

Sorptive interaction between goethite and strongly reducing organic substances from anaerobic decomposition of green manures

Strongly reducing organic substances (SROS) and iron oxides exist widely in soils and sediments and have been implicated in many soil and sediment processes. In the present work, the sorptive interaction between goethite and SROS derived from anaerobic decomposition of green manures was investigated by differential pulse voltammetry (DPV). Both green manures, Astragalus sinicus (Astragalus) and Vicia varia (Vicia) were chosen to be anaerobically decomposed by the mixed microorganisms isolated from paddy soils for 30 d to prepare different SROS. Goethite used in experiments was synthesized in laboratory. The anaerobic incubation solutions from green manures at different incubation time were arranged to react with goethite, in which SROS concentration and Fe(II) species were analyzed. The anaerobic decomposition of Astragalus generally produced SROS more in amount but weaker in reducibility than that of Vicia in the same incubation time. The available SROS from Astragalus that could interact with goethite was 0.69 ± 0.04, 0.84 ± 0.04 and 1.09 ± 0.03 cmol kg⁻¹ as incubated for 10, 15 and 30 d, respectively, for Vicia, it was 0.12 ± 0.03, 0.46 ± 0.02 and 0.70 ± 0.02 cmol kg⁻¹. One of the fates of SROS as they interacted with goethite was oxidation. The amounts of oxidizable SROS from Astragalus decreased over increasing incubation time from 0.51 ± 0.05 cmol kg⁻¹ at day 10 to 0.39 ± 0.04 cmol kg⁻¹ at day 30, but for Vicia, it increased with the highest reaching to 0.58 ± 0.04 cmol kg⁻¹ at day 30. Another fate of these substances was sorption by goethite. The SROS from Astragalus were sorbed more readily than those from Vicia, and closely depended upon the incubation time, whereas for those from Vicia, the corresponding values were remarkably less and apparently unchangeable with incubation time. The extent of goethite dissolution induced by the anaerobic solution from Vicia was greater than that from Astragalus, showing its higher reactivity.     

Environmental control of net ecosystem CO2 exchange in a treed, moderately rich fen in northern Alberta

Peatlands cover about 21% of the landscape and contain about 80% of the soil carbon stock in western Canada. However, the current rates of carbon accumulation and the environmental controls on ecosystem photosynthesis and respiration in peatland ecosystems are poorly understood. As part of Fluxnet-Canada, we continuously measured net ecosystem carbon dioxide exchange (NEE) using the eddy covariance technique in a treed fen dominated by stunted Picea mariana and Larix laricina trees during August 2003–December 2004. The total carbon stock in the ecosystem was approximately 51,000 g C m⁻², with only 540 g C m⁻² contributed by live above ground vegetation. The NEE measurements were used to parameterize simple physiological models to assess temporal variation in maximum ecosystem photosynthesis (A_max) and ecosystem respiration rate at 10 °C (R₁₀). During mid-summer the ecosystem had a relatively high A_max (approx. 30 μmol m⁻² s⁻¹) with relatively low R₁₀ (approx. 4 μmol m⁻² s⁻¹). The peak mid-day NEE uptake rate during July and August was 10 μmol m⁻² s⁻¹. The ecosystem showed large seasonal variation in photosynthetic and respiratory activity that was correlated with shifts in temperature, with both spring increases and fall decreases in A_max well predicted by the mean daily air temperature averaged over the preceding 21 days. Leaf-level gas exchange and spectral reflectance measurements also suggested that seasonal changes in photosynthetic activity were primarily controlled by shifts in temperature. Ecosystem respiration was strongly correlated with changes in ecosystem photosynthesis during the growing season, suggesting important links between plant activity and mycorrhizae and microbial activity in the shallow layers of the peat. Only very low rates of respiration were observed during the winter months. During 2004, the peatland recorded a net annual gain of 144 g C m⁻² year⁻¹, the result of a difference between gross photosynthesis of 713 and total ecosystem respiration of 569 g C m⁻² year⁻¹.     

Net ecosystem productivity of boreal aspen forests under drought and climate change: Mathematical modelling with Ecosys

The net ecosystem productivity (NEP) of boreal aspen is strongly affected by comparative rates of annual potential evapotranspiration (E_a) and precipitation (P_a). Changes in E_a versus P_a during future climate change will likely determine changes in aspen NEP and consequently the magnitude of the carbon sink/source of a significant part of the boreal forest. We hypothesize that the effects of E_a versus P_a on aspen NEP can be modelled with a soil–root–canopy hydraulic resistance scheme coupled to a canopy energy balance closure scheme that determines canopy water status and thereby CO₂ uptake. As part of the ecosystem model ecosys, these schemes were used to model diurnal declines in CO₂ and latent heat (LE) exchange during a 3-year drought (2001–2003) at the Fluxnet-Canada Research Network (FCRN) southern old aspen site (SOA). These declines were consistent with those measured by eddy covariance (EC) at SOA, except that ecosystem CO₂ effluxes modelled during most nights were larger that those measured by EC or gap-filled from other EC measurements. Soil CO₂ effluxes in the model were close to, but sometimes smaller than, those measured by automated surface chambers at SOA. Diurnal declines in CO₂ exchange during the drought caused declines in annual NEP in the model, and in gap-filled EC measurements (model versus EC in g C m⁻²: 275 versus 367 ± 110 in 2001, 82 versus 144 ± 43 in 2002 and 23 versus 104 ± 31 in 2003). Lower modelled NEP was attributed to the larger modelled CO₂ effluxes. Ecosys was then used to predict changes in aspen net biome productivity (NBP = NEP − C lost from disturbance) caused by 6-year versus 3-year recurring droughts during 100-year fire cycles under current climate versus climate change projected under the IPCC SRES A1B scenario. Although NBP was adversely affected during recurring 6-year droughts under current climate, it recovered quickly during non-drought years so that long-term NBP was maintained at 4 g C m⁻² year⁻¹. NBP rose by 10, 108 and 126 g C m⁻² year⁻¹ during the first, second and third centuries under climate change with recurring 3-year droughts, indicating a gradual rise in sink activity by boreal aspen. However recurring 6-year droughts during climate change caused recurring negative NBP (C losses), gradually depleting aspen C reserves and eventually causing dieback of the aspen overstory during the third century of climate change. This dieback was followed by a large decline in NBP.We conclude that NBP of boreal aspen will rise gradually under current projections of climate change, except under prolonged (e.g. 6 years) recurring droughts, which would eventually cause aspen to die back and substantial amounts of C to be lost.     

Soil carbon sequestration with continuous no-till management of grain cropping systems in the Virginia coastal plain

Carbon sequestration in agroecosystems represents a significant opportunity to offset a portion of anthropogenic CO₂ emissions. Climatic conditions in the Virginia coastal plain and modern production practices make it possible for high annual photosynthetic CO₂ fixation. There is potential to sequester a substantial amount of C, and concomitantly improve soil quality, with the elimination of tillage for crop production in this region. The objectives of our research were to: (1) measure C sequestration rate with continuous no-till management of grain cropping systems of the Virginia middle coastal plain; (2) determine the influence of biosolids application history on C content and its interaction with tillage management; and (3) evaluate the impact of continuous no-till C stratification as an indicator of soil quality. Samples were collected from 63 sites in production fields using a rotation of corn (Zea mays L.)–wheat (Triticum aestivum L.) or barley (Hordeum vulgare L.)/soybean double-crop (Glysine max L.) across three soil series [Bojac (coarse-loamy, mixed, semiactive, thermic Typic Hapludults), Altavista (fine-loamy, mixed semiactive, thermic Aquic Hapludults), and Kempsville (fine-loamy, siliceous, subactive, thermic Typic Hapludults)] with a history of continuous no-till management ranging from 0 to 14 years. Thirty-two of the sites had a history of biosolids application. Five soil cores were collected at each site from 0–2.5, 2.5–7.5 and 7.5–15 cm and analyzed for bulk density and soil C. Bulk density in the 0–2.5 cm layer decreased and C stratification ratio (0–2.5 cm:7.5–15 cm) increased with increasing duration of continuous no-till due to the accumulation of organic matter at the soil surface. A history of biosolids application resulted in an increase of 4.19 ± 1.93 Mg C ha⁻¹ (0–15 cm). Continuous no-till resulted in the sequestration of 0.308 ± 0.280 Mg C ha⁻¹ yr⁻¹ (0–15 cm). Our results provide quantitative validation of the C sequestration rate and improved soil quality with continuous no-till management in the region using on-farm observations.     

Methane turnover and temperature response of methane-oxidizing bacteria in permafrost-affected soils of northeast Siberia

The abundance, activity, and temperature response of aerobic methane-oxidizing bacteria were studied in permafrost-affected tundra soils of northeast Siberia. The soils were characterized by both a high accumulation of organic matter at the surface and high methane concentrations in the water-saturated soils. The methane oxidation rates of up to 835 nmol CH₄ h⁻¹ g⁻¹ in the surface soils were similar to the highest values reported so far for natural wetland soils worldwide. The temperature response of methane oxidation was measured during short incubations and revealed maximum rates between 22 °C and 28 °C. The active methanotrophic community was characterized by its phospholipid fatty acid (PLFA) concentrations and with stable isotope probing (SIP). Concentrations of 16:1ω8 and 18:1ω8 PLFAs, specific to methanotrophic bacteria, correlated significantly with the potential methane oxidation rates. In all soils, distinct 16:1 PLFAs were dominant, indicating a predominance of type I methanotrophs. However, long-term incubation of soil samples at 0 °C and 22 °C demonstrated a shift in the composition of the active community with rising temperatures. At 0 °C, only the concentrations of 16:1 PLFAs increased and those of 18:1 PLFAs decreased, whereas the opposite was true at 22 °C. Similarly, SIP with ¹³CH₄ showed a temperature-dependent pattern. When the soils were incubated at 0 °C, most of the incorporated label (83%) was found in 16:1 PLFAs and only 2% in 18:1 PLFAs. In soils incubated at 22 °C, almost equal amounts of ¹³C label were incorporated into 16:1 PLFAs and 18:1 PLFAs (33% and 36%, respectively). We concluded that the highly active methane-oxidizing community in cold permafrost-affected soils was dominated by type I methanotrophs under in situ conditions. However, rising temperatures, as predicted for the future, seem to increase the importance of type II methanotrophs, which may affect methane cycling in northern wetlands.     

Photosynthetic light use efficiency of three biomes across an east–west continental-scale transect in Canada

Light use efficiency (LUE) is used widely in scaling and modeling contexts. However, the variation and biophysical controls on LUE remain poorly documented. Networks of eddy covariance (EC) towers offer an opportunity to quantify _g, the ratio of P, gross primary productivity, to Q_a, absorbed photosynthetically active radiation (PAR), across climate zones and vegetation types. Using data from the Fluxnet Canada Research Network (n = 24 sites) in 2004, we examined the relationship between daily and yearly _g, driving variables, and site characteristics on a site-specific and plant functional type (PFT) basis using tree regression and linear regression. Data were available for three biomes: grassland, forest, and wetland. Yearly _g values ranged from 0.1 to 3.6 g C MJ⁻¹ Q_a overall. Daily _g was highest in the grassland (daily median ± interquartile range: 3.68 ± 1.98 g C MJ⁻¹ Q_a), intermediate in the forested biome (0.84 ± 0.82 g C MJ⁻¹ Q_a), and lowest for the wetlands (0.65 ± 0.54 g C MJ⁻¹ Q_a). The most important biophysical controls were light and temperature, to the exclusion of water-related variables: a homogeneity of slopes model explained c. 75% of the variation in daily _g. For a subset of sites with diffuse PAR data, the ratio of diffuse to total PAR, a proxy for cloudiness, was a key predictor. On the yearly time scale, _g was related to leaf area index and mean annual temperature. Aggregating to PFTs did not show functional convergence within any PFT except for the three wetland sites and the Picea mariana toposequence at the daily time step, and when using the Köppen climate classification on a yearly time step. The general lack of conservative daily _g behavior within PFTs suggests that PFT-based parameterizations are inappropriate, especially when applied on shorter temporal scales.     

Soil properties and crop yields on a vertisol in India with application of distillery effluent

Distillery effluent, a foul smelling, dark coloured by-product of distillery industries, is usually applied as irrigation water or as an amendment to arable land in some areas which are in the vicinity of the distillery industries. A field experiment on soybean–wheat system was conducted for 3 consecutive years in a Vertisol of central India to evaluate the effect of distillery effluent (DE) as an amendment on soil properties and crop productivity. The treatments were control (no fertilizer or manure or DE, T₁), 100% NPK + FYM @ 4 Mg ha⁻¹ to soybean (T₂) and four graded levels of DE, viz.: 2.5 cm DE to soybean and wheat on residual nutrition (T₃), 2.5 cm DE to soybean and 1.25 cm to wheat (T₄), 5 cm DE to soybean and wheat on residual nutrition (T₅), 5 cm DE to soybean and 2.5 cm to wheat (T₆). The organic carbon, microbial biomass carbon and electrical conductivity (EC) of the surface (0–10 cm) soil increased significantly with application of DE compared to T₁ and T₂, but the soil pH was not affected. The EC increased from 0.47 dS m⁻¹ and 0.58 dS m⁻¹, respectively, in T₁ and T₂ to 1.52 dS m⁻¹ in T₆, where highest dose of DE was applied. This indicated a slight build-up of salinity with DE application. The application of DE showed a significant improvement in the physical properties of the soil. The mean weight diameter (MWD), saturated hydraulic conductivity, water retention at field capacity and available water content were significantly (P < 0.05) higher, while bulk density (BD) and penetration resistance of the surface soil were significantly lower (P < 0.05) in all DE treated plots except in T₃ than those in T₁ and T₂. The fractions of WSA of more than 1 mm diameter in T₆, T₅ and T₄ were, respectively, 141%, 107% and 116% more than the control. The MWD showed a positive linear relationship with the organic carbon (r = 0.84^**) and microbial biomass carbon (r = 0.90^**) of the soil. A significant (P < 0.01) negative linear relationship (r = 0.70^**) was found between soil organic carbon and BD. Except T₃, all the DE treated plots recorded significantly higher total and microporosity of the soil than control. Water retention at permanent wilting point and macroporosity of the soil were not affected by treatment. The seed yield of soybean in all the DE treatments was similar with T₂ (1.86 Mg ha⁻¹) but significantly more than control (1.28 Mg ha⁻¹). The DE application levels have not affected the seed yield of soybean. In wheat highest grain yield was recorded in T₂ (3.47 Mg ha⁻¹), which was similar with T₄ (3.16 Mg ha⁻¹), T₅ (3.22 Mg ha⁻¹) and T₆ (3.46 Mg ha⁻¹). DE application up to T₄ level was found suitable from productivity, salinity and sustainability point of view. The study showed that judicious application of DE as an amendment to the agricultural field could be considered as a viable option for safe disposal of this industrial waste.     

Phosphorus release during decomposition of crop residues under conventional and zero tillage

Field experiments were conducted at Fort Vermilion (58°23′N 116°02′W), Alberta, to determine phosphorus (P) release patterns from red clover (Trifolium pratense) green manure (GM), field pea (Pisum sativum), canola (Brassica rapa) and monoculture wheat (Triticum aestivum) residues in the 7th and 8th years of conventional and zero tillage. Phosphorus contained in crop residues ranged from 1.5 kg ha⁻¹ in pea to 9.2 kg ha⁻¹ in clover GM, both under zero tillage. The patterns of P release over a 52-week period sometimes varied with tillage, i.e., a greater percentage of GM residue P was released under conventional tillage than under zero tillage in the first 2–10 weeks of residue placement. Wheat residues resulted in net P immobilization under zero tillage, but the amounts immobilized were less than 1 kg ha⁻¹. When net P mineralization occurred, the percentage of P released ranged from 24% of wheat P under conventional tillage to 74% of GM P under conventional tillage. The amounts of P released were 0.4 kg ha⁻¹ from wheat, 0.8 kg ha⁻¹ from canola, 0.4 kg ha⁻¹ from pea and 5.1–5.6 kg ha⁻¹ from clover GM residues. Therefore, only GM residues recycled agronomically significant amounts of P for use by subsequent crops in rotation. Phosphorus release was positively correlated with residue P concentration and negatively correlated with C/P and lignin/P ratios.     

Eight years of carbon dioxide exchange above a mixed forest at Borden, Ontario

This paper summarizes results from 8 years (1996–2003) of eddy covariance-based ecosystem CO₂ exchange measurements at the Borden Forest Research Station (44°19′N, 79°56′W). The site represents a mid-latitude, 100-year-old, mixed deciduous and coniferous forest dominated by red maple, aspen and white pine. The years 1996 and 1997 were relatively cold, had a late spring and received below average photosynthetic photon flux density (PPFD). This contrasts with an early spring, warmer soil and air temperatures during 1998–1999, and with distinctly wet year of 2000 and dry years of 2001–2003. The combination of early spring, warmer air and soil temperature and relatively high level of PPFD was associated with higher net ecosystem productivity (NEP) that peaked during 1999. Photosynthetic capacity was reduced and NEP showed a mid-growing season depression during the dry years of 2001–2003. Annual average ecosystem respiration (R) determined from a light response model was 30% less than R derived from a logistic respiration equation, relating night time CO₂ flux and soil temperature. However these independently determined R values were well correlated indicating that the site is unaffected by fetch and spatial heterogeneity problems. Based on the combined 8 years of growing season daytime data, an air temperature of 20–25 °C and a vapor pressure deficit (VPD) of 1.3 kPa were found to be the optimal conditions for CO₂ uptake by the canopy. Over the 1996–2003 period, the forest sequestered carbon at an average rate of 140 ± 111 gC m⁻² y⁻¹. The corresponding gross ecosystem photosynthesis (GEP) and R over this period were 1116 ± 93 gC m⁻² y⁻¹ and 976 ± 68 gC m⁻² y⁻¹, respectively. The annual carbon sequestration ranged from 19 gC m⁻² in 1996 to 281 gC m⁻² in 1999. However, these estimates were sensitive to frictional velocity threshold () used for screening data associated with poor turbulent mixing at night. Increasing from 0.2 m s⁻¹ (based on the inflection point in the nighttime CO₂ flux vs. u_* relationship) to 0.35 m s⁻¹ (determined using a selection algorithm based on change-point detection) modified the 8-year mean NEP estimate from 140 ± 111 gC m⁻² y⁻¹ to 65 ± 120 gC m⁻² y⁻¹. Both approaches show that the Borden forest was a low to moderate sink of carbon over the 8-year period.     

Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome

The controls on uptake and release of CO₂ by tropical rainforests, and the responses to a changing climate, are major uncertainties in global climate change models. Eddy-covariance measurements potentially provide detailed data on CO₂ exchange and responses to the environment in these forests, but accurate estimates of the net ecosystem exchange of CO₂ (NEE) and ecosystem respiration (R_eco) require careful analysis of data representativity, treatment of data gaps, and correction for systematic errors. This study uses the comprehensive data from our study site in an old-growth tropical rainforest near Santarem, Brazil, to examine the biases in NEE and R_eco potentially associated with the two most important sources of systematic error in Eddy-covariance data: lost nighttime flux and missing canopy storage measurements. We present multiple estimates for the net carbon balance and R_eco at our site, including the conventional “u* filter”, a detailed bottom-up budget for respiration, estimates by similarity with ²²²Rn, and an independent estimate of respiration by extrapolation of daytime Eddy flux data to zero light. Eddy-covariance measurements between 2002 and 2006 showed a mean net ecosystem carbon loss of 0.25 ± 0.04 μmol m⁻² s⁻¹, with a mean respiration rate of 8.60 ± 0.11 μmol m⁻² s⁻¹ at our site. We found that lost nocturnal flux can potentially introduce significant bias into these results. We develop robust approaches to correct for these biases, showing that, where appropriate, a site-specific u* threshold can be used to avoid systematic bias in estimates of carbon exchange. Because of the presence of gaps in the data and the day–night asymmetry between storage and turbulence, inclusion of canopy storage is essential to accurate assessments of NEE. We found that short-term measurements of storage may be adequate to accurately model storage for use in obtaining ecosystem carbon balance, at sites where storage is not routinely measured. The analytical framework utilized in this study can be applied to other Eddy-covariance sites to help correct and validate measurements of the carbon cycle and its components.