Direct and indirect effects of native range expansion on soil microbial community structure and function
Bibliographic record
Abstract
Summary Analogous to the spread of non‐native species, shifts in native species’ ranges resulting from climate and land use change are also creating new combinations of species in many ecosystems. These native range shifts may be facilitated by similar mechanisms that provide advantages for non‐native species and may also have comparable impacts on the ecosystems they invade. Soil biota, in particular bacteria and fungi, are important regulators of plant community composition and below‐ground ecosystem function. Compared to non‐native plant invasions, there have been relatively few studies examining how soil biota influence – or are influenced by – native species range shifts. Here, we examined how a native range‐expanding sagebrush species (Artemisia rothrockii) affects below‐ground abiotic conditions and microbial community structure and function using next‐generation sequencing coupled with other biotic and abiotic soil analyses. We utilized a range‐expansion gradient, together with a shrub removal experiment and structural equation models, to determine the direct and indirect drivers of these interconnected processes. Sagebrush colonization increased bacterial and archaeal richness and diversity and altered community composition across the expansion gradient. Soil organic C and N and soil moisture increased with sagebrush presence; however, results varied across the expansion gradient. We found no relationship between sagebrush and soil pH; however, pH strongly influenced microbial richness and diversity. Microbial (substrate‐induced) respiration was influenced by soil organic N, as well as microbial diversity and functional group relative abundances, highlighting direct and indirect effects of sagebrush on microbial community structure and function. Microbial community composition of soils after 4 years of sagebrush removal was more similar to communities in shrub interspaces than underneath shrubs, suggesting microbial community resilience. Synthesis. Our results suggest that native range expansions can have important impacts on soil biological communities, soil chemistry and hydrology which can further impact below‐ground ecosystem processes such as nutrient cycling and litter decomposition. The combination of high‐throughput sequencing and structural equation modelling used here offers an exciting yet underutilized approach to understanding how both native and non‐native species’ range expansions may affect the structure and function of soil ecosystems.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".