The influence of vegetation and soil type on the speciation of iron in soil water

Soluble organic matter derived from exotic Pinus species has been shown to form stronger complexes with iron (Fe) than that derived from most native Australian species. It has also been proposed that the establishment of exotic Pinus plantations in coastal southeast Queensland may have enhanced the solubility of Fe in soils by increasing the amount of organically complexed Fe, but this remains inconclusive. In this study we test whether the concentration and speciation of Fe in soil water from Pinus plantations differs significantly from soil water from native vegetation areas. Both Fe redox speciation and the interaction between Fe and dissolved organic matter (DOM) were considered; Fe - DOM interaction was assessed using the Stockholm Humic Model. Iron concentrations (mainly Fe 2+) were greatest in the soil waters with the greatest DOM content collected from sandy podosols (Podzols), where they are largely controlled by redox potential. Iron concentrations were small in soil waters from clay and iron oxide-rich soils, in spite of similar redox potentials. This condition is related to stronger sorption on to the reactive clay and iron oxide mineral surfaces in these soils, which reduces the amount of DOM available for electron shuttling and microbial metabolism, restricting reductive dissolution of Fe. Vegetation type had no significant influence on the concentration and speciation of iron in soil waters, although DOM from Pinus sites had greater acidic functional group site densities than DOM from native vegetation sites. This is because Fe is mainly in the ferrous form, even in samples from the relatively well-drained podosols. However, modelling suggests that Pinus DOM can significantly increase the amount of truly dissolved ferric iron remaining in solution in oxic conditions. Therefore, the input of ferrous iron together with Pinus DOM to surface waters may reduce precipitation of hydrous ferric oxides (ferrihydrite) and increase the flux of dissolved Fe out of the catchment. Such inputs of iron are most probably derived from podosols planted with Pinus.

Soil type does not affect seed ageing when soil water potential and temperature are controlled

To investigate the effects of soil type on seed persistence in a manner that controlled for location and climate variables, three weed species—Gomphocarpus physocarpus (swan plant), Avena sterilis ssp. ludoviciana (wild oat) and Ligustrum lucidum (broadleaf privet)—were buried for 21 months in three contrasting soils at a single location. Soil type had a significant effect on seed persistence and seedling vigour, but soil water content and temperature varied between soils due to differences in physical and chemical properties. Warmer, wetter conditions favoured shorter persistence. A laboratory-based test was developed to accelerate the rate of seed ageing within soils, using controlled superoptimal temperature and moisture conditions (the soil-specific accelerated ageing test, SSAAT). The SSAAT demonstrated that soil type per se did not influence seed longevity. Moreover, the order in which seeds aged was the same whether aged in the field or SSAAT, with L. lucidum being shortest-lived and A. sterilis being longest-lived of the three species.

Soil carbon stock in the tropical rangelands of Australia: Effects of soil type and grazing pressure, and determination of sampling requirement.

On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.

Influence of soil type on the properties of termite mound nests in Southern India

Termite mounds are conspicuous features in many tropical ecosystems. Their shape and soil physicochemical properties have been suggested to result from the termites ecological need to control the temperature and humidity within their nests and protect themselves from predators. This study aimed to determine the influence of the parent soil properties on the shape and soil physical and chemical properties of termite mounds. Termite mounds built by the fungus-growing termite species Odontotermes obesus were compared in two forests with different soil properties (Ferralsol or Luvisol) in Southern India. Our findings confirm that soil properties influence the physicochemical characteristics of mound material and may affect the shape, but these impacts are mostly independent of the size of the mounds (i.e., the age of the colonies). Mound walls were more enriched in clay and impoverished in C and N in the Luvisol than the Ferralsol. However, their shape was more complex in the Ferralsol than the Luvisol, suggesting a possible link between the clay content in soil and the shape of termite mounds. The results also suggest that clay becomes enriched in O. obesus mound walls through a more passive process rather than solely by particle selection, and that termite mound shape results from the soil properties rather than the ecological needs of termites. In conclusion, although ecologists have mainly focused upon the influence of termite ecological needs on their nest properties, this study highlights the need for a better understanding about the role of the soil pedological properties and, as a consequence, how these properties drive the establishment and survival of termites in tropical ecosystems. (C) 2015 Elsevier B.V. All rights reserved.

Effects of soil type on leaching and runoff transport of rare earth elements and phosphorous in laboratory experiments

Through leaching experiments and simulated rainfall experiments, characteristics of vertical leaching of exogenous rare earth elements (REEs) and phosphorus (P) and their losses with surface runoff during simulated rainfall in different types of soils (terra nera soil, cinnamon soil, red soil, loess soil, and purple soil) were investigated. Results of the leaching experiments showed that vertical transports of REEs and P were relatively low, with transport depths less than 6 cm. The vertical leaching rates of REEs and P in the different soils followed the order of purple soil > terra nera soil > red soil > cinnamon soil > loess soil. Results of the simulated rainfall experiments (83 mm h(-1)) revealed that more than 92% of REEs and P transported with soil particles in runoff. The loss rates of REEs and P in surface runoff in the different soil types were in the order of loess soil > terra nera soil > cinnamon soil > red soil > purple soil. The total amounts of losses of REEs and P in runoff were significantly correlated.

Relation of soil type to the income and crops on farms in Tompkins County, New York.

Thesis (M.S. in Agr.)--Cornell Univ., 1917.

Electronic nose evaluation of onion headspace volatiles and bulb quality as affected by nitrogen, sulphur and soil type

Edaphic factors affect the quality of onions (Allium cepa). Two experiments were carried out in the field and glasshouse to investigate the effects of N (field: 0, 120 kg ha(-1); glasshouse: 0, 108 kg ha(-1)), S (field: 0, 20 kg ha(-1); glasshouse: 0, 4.35 kg ha(-1)) and soil type (clay, sandy loam) on onion quality. A conducting polymer sensor electronic nose (E-nose) was used to classify onion headspace volatiles. Relative changes in the E-nose sensor resistance ratio (%dR/R) were reduced following N and S fertilisation. A 2D Principal Component Analysis (PCA) of the E-nose data sets accounted for c. 100% of the variations in onion headspace volatiles in both experiments. For the field experiment, E-nose data set clusters for headspace volatiles for no N-added onions overlapped (D-2 = 1.0) irrespective of S treatment. Headspace volatiles of N-fertilised onions for the glasshouse sandy loam also overlapped (D-2 = 1.1) irrespective of S treatment as compared with distinct separations among clusters for the clay soil. N fertilisation significantly (P < 0.01) reduced onion bulb pyruvic acid concentration (flavour) in both experiments. S fertilisation increased pyruvic acid concentration significantly (P < 0.01) in the glasshouse experiment, especially for the clay soil, but had no effect on pyruvic acid concentration in the field. N and S fertilisation significantly (P < 0.01) increased lachrymatory potency (pungency), but reduced total soluble solids (TSS) content in the field experiment. In the glasshouse experiment, N and S had no effect on TSS. TSS content was increased on the clay by 1.2-fold as compared with the sandy loam. Onion tissue N:water-soluble SO42- ratios of between five and eight were associated with greater %dR/R and pyruvic acid concentration values. N did not affect inner bulb tissue microbial load. In contrast, S fertilisation reduced inner bulb tissue microbial load by 80% in the field experiment and between 27% (sandy loam) and 92% (clay) in the glasshouse experiment. Overall, onion bulb quality discriminated by the E-nose responded to N, S and soil type treatments, and reflected their interactions. However, the conventional analytical and sensory measures of onion quality did not correlate with %dR/R.

Evaluation of eight spring onion genotypes, sulphur nutrition and soil-type effects with an electronic nose

Genotype, sulphur (S) nutrition and soil-type effects on spring onion quality were assessed using a 32-conducting polymer sensor E-nose. Relative changes in sensor resistance ratio (% dR/R) varied among eight spring onion genotypes. The % dR/R was reduced by S application in four of the eight genotypes. For the other four genotypes, S application gave no change in % dR/R in three, and increased % dR/R in the other. E-nose classification of headspace volatiles by a two-dimensional principal component analysis (PCA) plot for spring onion genotypes differed for S fertilisation vs. no S fertilisation. Headspace volatiles data set clusters for cv. 'White Lisbon' grown on clay or on sandy loam overlapped when 2.9 [Mahalanobis distance value (D2) = 1.6], or 5.8-(D2 = 0.3) kg S ha-1 was added. In contrast, clear separation (D2 = 7.5) was recorded for headspace volatile clusters for 0 kg S hd-1 on clay vs. sandy loam. Addition of 5.8 kg S ha-1 increased pyruvic acid content (mmole g-1 fresh weight) by 1.7-fold on average across the eight genotypes. However, increased S from 2.9 to 5.8 kg ha-1 did not significantly (P > 0.05) influence % dR/R, % dry matter (DM) or total soluble solids (TSS) contents, but significantly (P < 0.05) increased pyruvic acid content. TSS was significantly (P < 0.05) reduced by S addition, while % DM was unaffected. In conclusion, the 32-conducting polymer E-nose discerned differences in spring onion quality that were attributable to genotype and to variations in growing conditions as shown by the significant (P < 0.05) interaction effects for % dR/R.

Effect of soil type on burrowing behavior and cocoon formation in the green-striped burrowing frog, Cyclorana alboguttata

This study examined the effect of soil type on burrowing behaviour and cocoon formation during aestivation in the green-striped burrowing frog, Cyclorana alboguttata (Gunther, 1867). Given a choice, frogs always chose to burrow in wet sand in preference to wet clay. Frogs buried themselves faster and dug deeper burrows in sandy soil. However, under my laboratory conditions, there was little difference in the pattern of soil drying between the two soil types. Frogs in both sand and clay soil experienced hydrating conditions for the first 3amonths and dehydrating conditions for the last 3amonths of the 6-month aestivation period, and cocoons were not formed until after 3amonths of aestivation. After 6amonths, there were more layers in the cocoons of frogs aestivating in sand than those aestivating in clay. Frogs were able to absorb water from sandy soil with water potentials greater than -400akPa, but lost water when placed on sand with a water potential of -1000akPa.

Does the acid hydrolysis-incubation method measure meaningful soil organic carbon pools?

The literature was reviewed and analyzed to determine the feasibility of using a combination of acid hydrolysis and CO2-C release during long-term incubation to determine soil organic carbon (SOC) pool sizes and mean residence times (MRTs). Analysis of 1100 data points showed the SOC remaining after hydrolysis with 6 M HCI ranged from 30 to 80% of the total SOC depending on soil type, depth, texture, and management. Nonhydrolyzable carbon (NHC) in conventional till soils represented 48% of SOC; no-till averaged 56%, forest 55%, and grassland 56%. Carbon dates showed an average of 1200 yr greater MRT for the NHC fraction than total SOC. Longterm incubation, involving measurement of CO2 evolution and curve fitting, measured active and slow pools. Active-pool C comprised 2 to 8% of the SOC with MRTs of days to months; the slow pool comprised 45 to 65% of the SOC and had MRTs of 10 to 80 yr. Comparison of field C-14 and (13) C data with hydrolysis-incubation data showed a high correlation between independent techniques across soil types and experiments. There were large differences in MRTs depending on the length of the experiment. Insertion of hydrolysis-incubation derived estimates of active (C-a), slow (C-s), and resistant Pools (C-r) into the DAYCENT model provided estimates of daily field CO2 evolution rates. These were well correlated with field CO2 measurements. Although not without some interpretation problems, acid hydrolysis-laboratory incubation is useful for determining SOC pools and fluxes especially when used in combination with associated measurements.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design