Dracula's Menagerie Reloaded: Assessing the Relative Roles of Habitat and Interspecific Interactions in an Intact Mammalian Assemblage Using Structural Equation Modeling
Bibliographic record
Abstract
Interspecific interactions play a central role in structuring animal communities and food webs. In particular, carnivores are important topdown regulators in ecological communities and the loss of carnivore species can have devastating ecosystem effects. Similarly, carnivore reintroductions are successful if the prey base is sufficient to support population growth, making the case for the importance of bottom-up regulation processes. As such, rewilding efforts targeted at restoring food webs and natural community regulation processes (trophic rewilding) have become increasingly popular. However, investigations of regulation processes in terrestrial vertebrate communities often take place in heavily altered systems, potentially biasing inference on the presence or importance of top-down versus bottom-up regulation processes. Here, we use a stable mammalian assemblage in the Romanian Carpathians to evaluate the relative importance of top-down and bottom-up processes and provide a benchmark for understanding the effects and the success of rewilding initiatives. To do so, we used camera trap data from two consecutive years in the Southern Romanian Carpathians and developed hypothesisbased interaction pathways for top-down and bottom-up regulation in a piecewise structural equation modeling (SEM) framework. Results from SEMs indicate that while both top-down (wolf and Eurasian lynx-driven) and bottom-up processes (driven by roe deer, red deer, wild boar and hare abundance) play important roles in shaping community structure, landscape characteristics (i.e., terrain ruggedness, road density, elevation, and forest cover) have a greater effect on both predators and prey. The results of this research have implications for rewilding efforts in Europe and globally. This study highlights the importance of preserving natural habitats, underscoring that effective species conservation and coexistence must go hand in hand with conserving natural spaces.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".