Seeing the forest for the trees : tree species effects on soil microbial communities and nutrient cycling dynamics
Bibliographic record
Abstract
Tree species influence soils above and belowground communities through leaf litter and root inputs. Soil microbial communities can directly influence tree growth and development through processes such as decomposition of leaves, and indirectly through chemical transformation of nutrients in soils as an influence of altered C:N ratios due to leaf litter and root inputs. This thesis aims to document some of the mechanisms by which trees influence soil microbial communities and nitrogen cycling processes \nlike gross and net ammonification and nitrification. This thesis also aims to determine the role of site nitrogen status in modulating those tree species effects. The effects of tree species on ammonification and nitrification rates in forest floors and mineral soils were explored, and related to functional genetic markers for ammonia-oxidation by archaea and bacteria (amoA AOA and AOB), bacterial \ndenitrification (nirS and nirK), and the general markers for bacteria (16S) and fungi (ITS). Two paired \nhigh-resolution laboratory methods were used to investigate the relationships between trees, soils, and the microbial communities, including molecular techniques such as quantitative polymerase chain reaction (qPCR) to target gene abundances in soils, and 15N pool-dilution experiments to understand how ammonium and nitrate are produced and consumed in soils. Soil samples were collected from two \ncommon garden experiments, named EP571 in Canada (Ribbons et al. 2016), and in Denmark, and both 15N and qPCR-based techniques were used to determine tree species effects and attribute N cycling processes to the abundances of functional genes. At EP571, western red cedar (Thuja plicata) forest floor nitrogen transformation rates differed from Douglas-fir (Pseudotsuga menziesii), Sitka \nspruce (Picea sitchensis), and western hemlock (Tsuga heterophylla), which corresponded with western red cedar having highest abundances of bacterial 16S and amoA AOA genes. \nA manipulative mesocosm (the Rhizotron) in Wales was used to determine how mixtures and monocultures of seedling species influenced tree growth, soil physical properties and soil microbial community structure and function within the first three years of growth. Within the Rhizotron \nexperiment both alder (Alnus rubra) and Douglas-fir grew taller when grown in mixtures compared with monocultures of each species. Sycamore maple (Acer pseudoplatanus) acquired slightly greater aboveground biomass when planted in mixtures with common oak (Quercus robur), which attained \nless biomass in mixtures than monocultures. C:N ratios of leaves, stems, roots, and rhizospheric soils were determined to see if mixtures influenced C:N in trees. Rhizospheric soil microbial communities (including bacterial and fungal markers and the 4 genes tied to N cycling) were compared among the 4 tree species in the Rhizotron. Soil samples for microbial analyses were collected before seedlings were planted, and just before the experiment was harvested. These data show differences in height, biomass and C:N ratios between species can be observed at a seedling growth stage, but microbial communities may require longer exposure to develop. Lastly, the Bangor Diverse experiment was used to further \nexplore diversity and mixture effects on soil microbial communities and N transformations. We found few mixture or monoculture tree species effects on mineral soil microbial communities or net nitrification or ammonification rates. Collectively, these stories shed light on the important functional role of soil microbes in forest soil N cycling. This thesis also highlights the use of isotope and \nmicrobial techniques for parsing out relationships between site, tree species identity and ecosystem functions, with the largest links observed between gross ammonification and microbial communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".