Legacy effects post removal of a range-expanding shrub influence soil fungal communities and create negative plant-soil feedbacks for conspecific seedlings
Bibliographic record
Abstract
Soil legacy effects can have long-term impacts on soil microbial communities with implications for plant growth and community structure. These effects are well studied for invasive plants, particularly after removal of invasive species; however, we know less about the soil legacy effects post removal of native range expanding species. We used a controlled greenhouse experiment with a range-expanding sagebrush species (Artemisia rothrockii (Asteraceae)) to determine how multiple metrics of sagebrush seedling performance (plant-soil feedback (PSF) ratio, height, leaf functional traits, and root:shoot biomass) were influenced by soil legacy effects in both the native and expansion range and over time since removal. We inoculated seedlings with field-collected soils from under sagebrush canopies and in herbaceous interspace, as well as in areas where sagebrush had been removed for 1 or 5 years. We then used ITS2 sequencing and extracellular enzyme assays to characterize the structure and function of soil microbial communities and to determine what microbial mechanisms drove seedling responses. Conspecific sagebrush seedlings responded negatively to soil legacy effects of shrub removal, with a more negative PSF ratio, reduced height, and higher root:shoot ratios in shrub removal inoculum than in shrub and herbaceous soil inoculum. Seedlings in shrub removal inoculum also had enriched foliar isotope ratios, reflecting higher resource use efficiency. Soil communities of seedlings with shrub removal inoculum had increased fungal diversity, pathogen, and saprotroph richness, and altered fungal community composition. Legacy effects on soil fungal diversity and functional group richness were present in seedlings with 1-year shrub removal inoculum, while effects on fungal community composition were found in 1 and 5-year shrub removal inoculated seedlings. Despite changes in functional group richness, fungal diversity and community composition proved the strongest drivers of seedling performance overall. This work provides novel insight into how soil legacy effects post removal of a native range expanding species may limit rather than promote the performance of conspecifics over short and long time periods, with important implications for management as global change continues to shift the geographic ranges of woody plants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".