Predator types, urbanization, and tree cover drive top-down control of herbivorous and carnivorous preys in an urban agroecosystem
Bibliographic record
Abstract
Prey-predator interactions hold significant importance, widely acknowledged as crucial processes within ecosystems. Yet, there is a scarcity of empirical data that effectively illustrates the influence of urbanization on such interactions. We performed a common garden experiment utilizing 1250 clay models to assess the predation risks faced by herbivorous and carnivorous prey in an urban agroecosystem in the southern Philippines. Our findings revealed significant differences in attack risks between the trophic levels, with herbivorous caterpillars (n = 246; 53.25%) experiencing higher predation rates compared to carnivorous lizards (n = 216; 46.75%). Interestingly, while the trophic level of the prey did not directly predict predation risk, the presence of predators showed significant effects. Arthropods emerged as the dominant predators of herbivorous prey compared to other predators, whereas mammalian predators predominantly attacked carnivorous prey. The landscape variable also had a strong influence on the risk of predation. We found that increasing tree cover was significantly related to increased predation risk, while built-up showed the opposite. Our research findings support the ‘increasing disturbance hypothesis’, suggesting that rising urbanization rates reduce predator diversity, resulting in a decrease and loss of predation pressure.
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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 | 0.000 | 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) | 0.000 | 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".