Weed seedbank community structure’s response to land-use intensity and its relationships to soil properties in Atlantic Canada
Bibliographic record
Abstract
Abstract A diversity of management and environmental factors influence weed seedbank community composition, yet the conditions under which each of these factors is an important driver of the weed seedbank are poorly understood. To investigate this relationship, we used a series of univariate and multivariate analyses to test associations between soil health, nematode community composition parameters, and the composition of the weed seedbank at 59 agricultural sites in the Prince Edward Island Soil Quality Monitoring (PEI SQM) Network spanning a range of land-use intensities and using potato ( Solanum tuberosum L.) production systems as a case study. Land-use intensity is a nonstandard term that refers to increasing agricultural activity, including tillage and use of synthetic inputs to sustain high crop yield. Sites were classified into low, medium, and high land-use intensity categories based on frequency of potato cultivation in the past 10 yr. A total of 36 different weed species were found across all sites, and while neither seedbank density nor species richness was influenced by land-use intensity, community assemblage was. Seedbank communities at low land-use intensity sites were largely associated with grass weeds and other weakly competitive species, positively correlated with soil CO 2 respiration and nematode community richness and diversity, and negatively correlated with the carbon to nitrogen ratio. In contrast, seedbank communities at medium and high land-use intensity sites were similar and composed of many highly competitive weedy species and correlated with the frequency of potato in the rotation and soil N and K, two commonly used soil fertility inputs. The absence of common agricultural weed species at low land-use intensity sites filtered by soil edaphic factors and abundance of neutral species despite past history of annual cropping suggest that these sites are not refuges for these species and may present a template for the design of weed seed–suppressive soils.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".