Distinct respiratory responses of soils to complex organic substrate are governed predominantly by soil architecture and its microbial community

Factors governing the turnover of organic matter (OM) added to soils, including substrate quality, climate, environment and biology, are well known, but their relative importance has been difficult to ascertain due to the interconnected nature of the soil system. This has made their inclusion in mechanistic models of OM turnover or nutrient cycling difficult despite the potential power of these models to unravel complex interactions. Using high temporal-resolution respirometery (6 min measurement intervals), we monitored the respiratory response of 67 soils sampled from across England and Wales over a 5 day period following the addition of a complex organic substrate (green barley powder). Four respiratory response archetypes were observed, characterised by different rates of respiration as well as different time-dependent patterns. We also found that it was possible to predict, with 95% accuracy, which type of respiratory behaviour a soil would exhibit based on certain physical and chemical soil properties combined with the size and phenotypic structure of the microbial community. Bulk density, microbial biomass carbon, water holding capacity and microbial community phenotype were identified as the four most important factors in predicting the soils’ respiratory responses using a Bayesian belief network. These results show that the size and constitution of the microbial community are as important as physico-chemical properties of a soil in governing the respiratory response to OM addition. Such a combination suggests that the 'architecture' of the soil, i.e. the integration of the spatial organisation of the environment and the interactions between the communities living and functioning within the pore networks, is fundamentally important in regulating such processes

Acute sensitivity of nematode taxa to CuSO4 and relationships with feeding-type and life-history classification

The acute sensitivity to CuSO4 of a broad range of nematode taxa was analyzed in order to assess the potential of changes to nematode community structure to serve as a practical tool for the bioindication of heavy-metal pollution. An easy-to-use experimental set-up was developed along with an appropriate mathematical response model in order to quantify the response characteristics of nematodes to CuSO4 pressure. Three similar experiments were conducted using water, dune sand, and sandy soil as media, each of which was subjected to 12 increasing concentrations of CuSO4. In total, 130 response curves representing 70 nematode taxa were produced and analyzed. CuSO4 concentrations were normalized for differences in efficiency among media due to different adsorption. At low CuSO4 concentrations, many taxa exhibited stimulation rather than inhibition regarding recovery efficiency. At higher concentrations, the concentration level at which 50% of the nematode population was recovered after a 24-h incubation (recovery concentration 50% [RC50]) varied widely among taxa and ranged from 0.01 to 4 mM/L CuSO4 (normalized to water). Stimulation of recovery efficiency and RC50 were negatively correlated with the colonizer-persister (C-P) classification of taxa, which discriminates nematodes according to their reproductive potential. The maturity index, which relates to a nematode community's state of disturbance and eutrophication, was negatively correlated with CuSO4 concentration. The properties of the applied test method are discussed as are the relationships between the investigated short-term toxicity effects and long-term toxicity processes in the field. From the large range of observed RC50 values, it is concluded that a meaningful sensitivity classification of nematodes should be possible and thus would allow for a sensitive bioindication of heavy-metal pollution. From the correlation between RC50 and C-P classification, the authors further conclude that the maturity index will, in addition to enrichment and disturbance, respond to heavy-metal pollution and thus may serve as a general indicator of soil health

A GIS-based model of Serengeti grassland bird species

In this study we assess possible benefits of using satellite sensor data in large-scale landscape ecology. The study was conducted on the Serengeti Plains, Tanzania, combining (1) records from a bird survey, (2) local measurements of vegetation structure and precipitation, and (3) a habitat map derived from a Landsat satellite image classification. The question of whether ground-based or satellite data explained more of the species-environment relationships was explored by means of multivariate regression. On average across all 62 bird species recorded, the combination of satellite-based and groundbased data improved explained variance (R2 = 0.26), as compared to satellite sensor data, or ground-based data alone (R2 = 0.18 and 0.21, respectively). In spite of this low level of explained variance in the regressions, a classification of bird species according to utilised parameter space yielded reasonable results. Satellite image data seem to be suited to this kind of investigation. Ostrich 2007, 78(2): 259–26

Interactions between nematodes and microbial communities in a tropical soil following manipulation of the soil food web

The carrying capacity for microflora and nematofauna was manipulated (using a bactericide, a fungicide, manure or a growing millet plant) in a poor tropical soil, in order to identify relationships between the soil microbes and nematodes and to assess the influences of these organisms on nitrogen flux. The experiment was conducted for 4 months in containers under greenhouse conditions, with analyses of soil, nematofauna and microbial characteristics at regular intervals. Manure input and initial bactericide application led to a significant increase in bacterial-feeding and fungal-feeding nematodes of coloniser-persister classes 1 and 2, respectively, whereas high manure input stimulated omnivorous nematodes (i.e. Microdorylaimus rapsus) which became the dominant trophic group. Changes in abundance of the different bacterial-feeding nematode taxa between treatments seemed to be more related to changes in the structure of the microbial communities than to the total amount of micro-organisms, as suggested by the RISA fingerprint analysis of the bacterial communities. Canonical analysis of nematode feeding guilds, combined with soil microbial and mineral nitrogen parameters as well as multiple regression showed that the bacterial-feeding nematodes influenced the inorganic N content in the soil whereas microbial biomass was determined by total nematode abundance and not by any specific trophic group. (C) 2004 Elsevier Ltd. All rights reserved