Impact of Non-Native Terrestrial Mammals on the Structure of the Terrestrial Mammal Food Web of Newfoundland, Canada
Bibliographic record
Abstract
The island of Newfoundland is unique because it has as many non-native terrestrial mammals as native ones. The impacts of non-native species on native flora and fauna can be profound and invasive species have been identified as one of the primary drivers of species extinction. Few studies, however, have investigated the effects of a non-native species assemblage on community and ecosystem properties. We reviewed the literature to build the first terrestrial mammal food web for the island of Newfoundland and then used network analyses to investigate how the timing of introductions and trophic position of non-native species has affected the structure of the terrestrial mammal food web in Newfoundland. The first non-native mammals (house mouse and brown rat) became established in Newfoundland with human settlement in the late 15th and early 16th centuries. Coyotes and southern red-backed voles are the most recent mammals to establish themselves on the island in 1985 and 1998, respectively. The fraction of intermediate species increased with the addition of non-native mammals over time whereas the fraction of basal and top species declined over time. This increase in intermediate species mediated by non-native species arrivals led to an overall increase in the terrestrial mammal food web connectance and generality (i.e. mean number of prey per predator). This diverse prey base and sources of carrion may have facilitated the natural establishment of coyotes on the island. Also, there is some evidence that the introduction of non-native prey species such as the southern red-backed vole has contributed to the recovery of the threatened American marten. Long-term monitoring of the food web is required to understand and predict the impacts of the diverse novel interactions that are developing in the terrestrial mammal food web of Newfoundland.
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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) | 0.001 | 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 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".