Global change and their environmental stressors have a significant impact on soil biodiversity -- a meta-analysis
Bibliographic record
Abstract
Anthropogenic global changes are impacting biodiversity, however, many previous meta-analyses investigating the impact of different global changes on biodiversity have omitted soil fauna, or are limited in the scope of the global changes studied. Threats to soil biodiversity by global changes need to be understood to mitigate effects on ecosystem services provided by soils. We conducted a meta-analysis using 3,173 effect sizes from 627 publications focused on six global changes (climate change, land-use intensification, pollution, nutrient enrichment, invasive species, and habitat fragmentation) and their associated environmental stressors on soil fauna. We classified stressors as either pulse (short-term, acute) or press (long-term, chronic) stressors, and expected pulse stressors to have less impact on soil biodiversity due to buffering effects of the soil. Unexpectedly, pollution caused the largest loss in soil fauna communities, which is worrying due to continually increasing levels of pollution, as well as the poor mechanistic understanding of pollution impacts. There was no clear pattern of pulse stressors having a smaller impact on soil biodiversity than press stressors. Overall, this work shows the importance of including soil biodiversity in large-scale global change analyses, as soil organisms often do not show the same responses as organisms above-ground.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".