Invasion theory as a management tool for increasing native biodiversity in urban ecosystems
Bibliographic record
Abstract
Abstract Human activity has altered ecosystems in some places to a point where traditional restoration, ecosystem management and conservation interventions might not be feasible. This is especially true in densely populated urban areas if ongoing stressors are not ameliorated. As a result, different management options are needed for increasing native biodiversity and ecosystem function in novel urban ecosystems. One strategy for increasing biodiversity in urban ecosystems is to employ invasion biology theory to augment the establishment and proliferation of desirable native species. Invasion hypotheses, including fluctuating resources, enemy release, novel weapons, invasional meltdown (facilitation) and propagule pressure, all provide insights into the mechanisms that increase the establishment and spread of populations. These hypotheses point to specific interventions that can be used in urban restoration and management. Synthesis and applications . Viewing invasion mechanisms as a way to increase native biodiversity in novel urban ecosystems provides a useful reframing for assessing possible applications and management interventions for the most difficult‐to‐restore landscapes. We argue that conservation managers can use and test invasion hypotheses to inform biodiversity management practices in novel landscapes.
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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 | 0.000 |
| 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".