Contrasting patterns of plant and microbial diversity during long‐term ecosystem development
Bibliographic record
Abstract
Abstract Long‐term ecosystem development involves changes in plant community composition and diversity associated with pedogenesis and nutrient availability, but comparable changes in soil microbial communities remain poorly understood. In particular, it is unclear whether the diversity of plants and microbes respond to similar abiotic drivers, or become decoupled as resources change over long time‐scales. We characterized communities of archaea, bacteria and fungi in soils along a 2‐million‐year chronosequence of coastal dunes in a biodiversity hot spot in Western Australia. The chronosequence involves marked changes in soil pH and nutrient availability that drive major shifts in plant community composition and diversity as soils age. Patterns of α‐diversity for microbial groups differed along the chronosequence. Bacterial α‐diversity was greatest in intermediate‐aged soils; archaeal diversity was greater in young alkaline or intermediate‐aged soils, while fungal α‐diversity—like plant diversity—was greatest in old, strongly weathered soils where phosphorus is the limiting nutrient. Changes in microbial community composition along the chronosequence were explained primarily by the long‐term decline in soil pH, with a smaller influence of the relative abundance of plant nutrient‐acquisition strategies. However, changes between the prokaryote and fungal communities, and between fungal and plant communities, became increasingly decoupled along the chronosequence, demonstrating that the coordination of change in biological communities by abiotic drivers becomes weaker during long‐term ecosystem development. Several bacterial taxa, including DA101 (Verrucomicrobia), “Candidatus Solibacter” (Acidobacteria) and Gaiella (Actinobacteria), were particularly abundant on the oldest dunes, indicating that they are adapted to acquire phosphorus from extremely infertile soils. However, we cannot disentangle the influence of phosphorus from the long‐term decline in soil pH along the chronosequence. Synthesis. These results provide evidence for contrasting patterns of plant and microbial community composition and α‐diversity in response to acidification and nutrient depletion during long‐term pedogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 source (direct Gemma or distilled Codex), 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".