Modeling trophic pathways, nutrient cycling, and dynamic stability in soils

By John C. Moore, K. McCann, P. C. Ruiter. 2005

242 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/bf923134d27c38db0281dc773849cee779d9897d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Y. Kuzyakov
2. J. Rousk
3. A. Gunina
4. K. Treseder
5. E. Bååth
6. M. Dippold
7. P. Brookes
8. B. Glaser

In Nature and Landscape Conservation

1. Y. Kuzyakov
2. A. Gunina
3. M. Dippold
4. B. Glaser
5. E. Bååth
6. J. Rousk
7. K. McGuire
8. Haiyan Chu

In Plant Science

1. J. Rousk
2. A. Gunina
3. P. Brookes
4. Y. Kuzyakov
5. M. Dippold
6. K. McGuire
7. K. Treseder
8. B. Glaser

Citations in the corpus

• Interactions Between Bacteria, Protozoa and Nematodes in Soil (2012, background): “The soil food web includes two major degradation pathways (Moore et al. 2005); the fungal pathway and the bacterial pathway (Fig.”
• Carbon flux through fungi and bacteria into the forest soil animal food web as indicated by compound-specific 13C fatty acid analysis (2012, result): “This is in line with the findings of Pollierer et al. (2007), showing that the dC signature of E.”
• Soil nitrogen cycling rates in low arctic shrub tundra are enhanced by litter feedbacks (2010, background): “This may in turn alter N cycling rates if soil organic matter decomposition, N mineralization rates and trophic interactions in fungal-dominated communities are slow relative to bacterial-dominated communities (Moore et al. 2005; Wardle et al. 2004).”
• Contrasting Soil pH Effects on Fungal and Bacterial Growth Suggest Functional Redundancy in Carbon Mineralization (2009, background): “There are potentially important differences between their properties, however, such as biomass elemental composition (21), nutrient demand (22, 53, 63, 65), turnover rate (54), metal tolerance (52), temperature dependence (51), and food web linkage (33, 37, 46).”
• Turnover of microbial groups and cell components in soil: 13 C analysis of cellular biomarkers (2017, background): “Bacteria and fungi have various chemical composition, which strongly contributes to their turnover rates in soil: for bacteria it consists 2.3-33 days, whereas for fungi it accounts for 130-150 days (Moore et al., 2005; Rousk and Baath, 2007; Waring et al., 2013).”
• Biochemical pathways of amino acids in soil: Assessment by position-specific labeling and 13C-PLFA analysis (2013, background): “Accordingly, enrichment of eukaryotic cell components takes longer (Moore et al., 2005).”
• Fate of low molecular weight organic substances in an arable soil: From microbial uptake to utilisation and stabilisation (2014, background): “…glucose utilisation compared to fungi, corresponds with the dominance of bacteria biomarkers, but can also be attributed to high competitive ability of bacteria to take up glucose compared to fungi (Moore et al., 2005) especially if low concentrations of LMWOS are applied (Reischke et al., 2014).”
• Microbial communities and their relevance for ecosystem models: Decomposition as a case study (2010, background): “, 1988), and there is some evidence frommodeling thatwhen disturbance shifts the balance from fungi to bacteria (or vice versa), ecosystemprocesses are significantlymodified (Moore et al., 2005).”
• Sugars in soil and sweets for microorganisms: Review of origin, content, composition and fate (2015, result): “Calculated glucose CMRT in MB is in accordance with estimated turnover times of bacterial (120e180 d) and fungal biomass (270 d) in soil (Moore et al., 2005; Rousk and Baath, 2007).”