Selective plant foraging and the top‐down suppression of native diversity in a restored prairie
Bibliographic record
Abstract
Summary Clarifying what species are being consumed at what times can improve our understanding of how anthropogenic change affects food web dynamics, with implications for community assembly including restoration. This includes human‐based changes to plant communities via species introductions, which can interact with consumer feeding preferences to indirectly alter assembly outcomes including reduced restoration success if planted species are preferentially targeted. We used DNA barcoding of plant material in rodent scat, combined with field‐based feeding trials, rodent trapping, and rodent exclosures to test for dietary preferences and assembly impacts of native rodents on a restored and regionally rare tallgrass prairie of central North America. We examined whether native rodents preferred non‐targeted and mostly non‐native oldfield plants that are more locally abundant, thus protecting the rarer native planted species from consumption, or if rodents preferred native plants regardless of abundance. Our results supported the latter outcome. Barcoding revealed that native rodents consumed mostly non‐planted oldfield species for 10 months of the year (92% of the diet). The exceptions were August–September, when planted prairie species accounted for 87% of plants consumed and coincided with their peak seed production. Cafeteria trials suggested diet seasonality to be explained by food limitation – native prairie seeds were consumed year‐round when made available. Non‐targeted oldfield species thus appeared to be of sufficient quality to support rodent populations (peaking at 23 individuals ha−1in summer), but without rescuing rarer prairie species from targeted granivory and resulting in reduced prairie diversity outside of experimental exclosures. Synthesis and applications. Our work illustrates how anthropogenic‐based changes to producer communities may affect feeding pathways in grassland food webs, potentially facilitating establishment by non‐target species via indirect consumer effects that can be difficult to detect. These findings suggest that rodents may reduce the restoration success of tallgrass prairie in our region, with some planted species likely to suffer future recruitment difficulties due to granivory. Managers may need to consider multiple trophic levels with restoration, not just the commonly planted producer communities but also the consumers and predators associated with them.
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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 | 0.001 |
| 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".