Using Stable Isotopes to Differentiate Trophic Feeding Channels within Soil Food Webs

The soil is probably the most diverse habitat there is, with organisms ranging in sizes from less than 1 μm to several metres in length. However, it is increasingly evident that we know little about the interactions occurring between these organisms, the functions that they perform as individual species, or together within their different feeding guilds. These interactions between groups of organisms and physical and chemical processes shape the soil as a habitat and influence the nature of the soil food web with consequences for the above‐ground vegetation and food web. Protists are known as one of the most abundant groups of bacterivores within the soil; however, they are also consumers of a number of other food sources. Even though they are responsible for a large proportion of the mineralisation of bacterial biomass and have a large impact on the C and N cycles within the soil they are regularly overlooked when investigating the complete soil food web. Recently, stable isotopes have been used to determine trophic interactions and here we describe how this technique has been used to highlight linkages between protists and the soil food web.     

Landscape-level seagrass–sediment relations in a coastal lagoon

We investigated the relationships between sediment (subaqueous soil) properties and eelgrass (Zostera marina L.) distribution to develop landscape-level soil-based strategies for choosing eelgrass restoration locations. Subaqueous soils were sampled and eelgrass cover determined for 14 soil-landscape units within a 116 ha area of Ninigret Pond, a coastal lagoon in Rhode Island, USA. Of the 14 soil-landscape units sampled for eelgrass cover, 52% had virtually no eelgrass cover (<10%), while 18% had high eelgrass cover (>90%). The Lagoon Bottom, Shallow Lagoon Bottom, Flood-tidal Delta Slope, and Barrier Cove subaqueous soil-landscape units had the highest eelgrass cover (66–100%). A weak relationship between eelgrass cover and water depths (r² = 0.10) was observed suggesting that properties other than water depth may also control eelgrass distribution. Subaqueous soils on landscapes with >60% eelgrass cover had relatively high levels of acid-volatile sulfides (>90 μg/g), high soil salinity levels (34–44 ppt), fine textures (silt loam), and relatively high total nitrogen levels (>0.15%). Four principal components accounted for 81% of the variability in eelgrass cover. The first component reflected particle-size distribution (i.e. sand, silt, and clay contents) effects and accounted for 43% of the variability. The other components suggested that eelgrass cover is correlated to carbonaceous remains, non-calcareous rock fragments and soil salinity. These data suggest that the current distribution of eelgrass within the study area is strongly influenced by physical and chemical subaqueous soil characteristics. Soil survey techniques proved useful for the delineation of sediment characteristics (e.g. texture, salinity) that influence eelgrass distribution patterns at landscape-level scales.     

A sensitive method for continuous measurement of the carbon dioxide evolution rate of soil samples

Summary A differential infrared CO₂ analyser combined with a 12 channel gas handling system have been used for the measurement of CO₂ evolution rates of soil samples. A constant flow of air over the soil was maintained during the incubation period. Automatic sequential measurement and recording of the increase of the CO₂ content of the flushed air of the 12 channels lasted 24 min with a dwell time of 2 min per channel. This technique has proven to be very useful for accurate and rapid measurement of the biological activities in untreated and treated soil.     

Whole-Plant Water use and Canopy Conductance of Cassava Under Iimited Available Soil Water and Varying Evaporative Demand

Cassava (Manihot esculenta Crantz), a perennial woody shrub, is known to be highly productive under favourable conditions and produce reasonably well under adverse conditions where other crops fail. Using constant heat sap flow sensors, sap flow density (F _d ) of cassava was monitored for 10 days in December 2002. Sap flow was highly correlated (R ² =0.72, P<0.05) to incoming solar radiation (R _s) than to other climatic factors. Using cross-correlation analysis, no time shift was detected between F _d and solar radiation, whereas vapour pressure deficit (VPD) lags F _d by 110 min. Solar radiation and VPD together explained 83% of diurnal variation in sap flow. Whole-plant transpiration ranged from 0.8 to 1.2 mm day⁻¹ and daily canopy conductance (g _c), computed based on the inverted Penman–Monteith model, varied between 0.7 and 2.1 mm s⁻¹ (mean = 1.4 ± 0.5 mm s⁻¹). For the measurement period, characterized by high evaporative demand coupled with low available soil water, transpiration accounted for 21% of the available energy and was only able to meet 24% of the atmospheric water demand. Average decoupling factor (Ω) of 0.05±0.02 estimated suggested that a 10% change in g _c may lead to more than 9% change in transpiration which further supports the notion that stomata play significant role in regulating cassava water use compared to other known mechanisms. Beyond light saturation (R _s >300 W m⁻²) and at higher VPD (>1.0 kPa), wind effects on the canopy transpiration under water stress condition were low, while VPD explains 94% of the observed variance in daily canopy conductance.     

Role of plant parasitic nematodes and abiotic soil factors in growth heterogeneity of sugarcane on a sandy soil in South Africa

A feature of many sugarcane fields is the patchy growth. This is often thought to be due to physical or chemical differences in the soil. In this paper we investigate the causes of growth heterogeneity of sugarcane on a sandy soil in KwaZulu-Natal, South Africa. To identify the factors that were associated with the good and poor areas, soil texture, pH, organic matter content and a number of soil chemical elements and nematode community data were subjected to principal component analysis (PCA). The numbers of each of the nematode species (Meloidogyne sp., Pratylenchus zeae, Helicotylenchus dihystera, Xiphinema elongatum and Paratrichodorus sp.) were first converted to relative proportions of ectoparasites and endoparasites. The data were collected from the 2nd ratoon crop of a nematicide trial, where half of the plots had been treated with aldicarb in the preceding two crops. Yields of control plots varied from 34.7 to 126.8 t cane ha^–1 and from 85.4 to 138.7 for the treated plots. The yield data were centred and normalised separately for the treated and control plots and the values projected on the trial map to study spatial distribution. Plots with above-average yields, whether treated or untreated, occurred in the lower part of the trial site. The PCA factorial values were also projected onto the map of the trial. According to the first factor of the analysis of the abiotic soil characteristics in the 0–20 cm surface layer, the trial site could be divided into two areas, one on the left and one on the right. PCA of the soil data from the 0–20 and 20–40 cm layers showed that there was little or no difference between the two that might explain the two growth areas. However, analysis of the nematode community distinguished two main areas that largely corresponded to the distribution of the plots of low and high yielding cane. Correlation analysis confirmed the relationship between nematodes and yield. H. dihystera was positively correlated with yield of cane whereas the reverse was true for the Meloidogyne species.     

Assessing the Risk of Soil Pollution around an Industrialized Mining Region Using a Geostatistical Approach

Knowledge of mobility of some heavy metals in coal mining areas is fundamental in order to understand their toxicity and geochemical behavior. This paper aims to map pollution and assess the risk to agricultural soils in a wider lignite opencast mining and industrial area. Geochemical data related to environmental studies show that the waste characteristics favor solubilization and mobilization of inorganic contaminants. The geochemical distribution of soil pollution is studied by the application of the Bayesian Maximum Entropy (BME) procedure, a versatile extension of geostatistics which allows merging spatial and temporal estimations in a single model. Results reveal a correlation range of contaminants concentrations up to 5000 m and indicate a potential forecasting range of up to five years. Inspection of the produced spatiotemporal maps indicates that the whole study area is contaminated by As and various heavy metals, a situation which seems to be more or less stable over time.