Urban forest invertebrates: how they shape and respond to the urban environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Invertebrates comprise the most diversified animal group on Earth. Due to their long evolutionary history and small size, invertebrates occupy a remarkable range of ecological niches, and play an important role as “ecosystem engineers” by structuring networks of mutualistic and antagonistic ecological interactions in almost all terrestrial ecosystems. Urban forests provide critical ecosystem services to humans, and, as in other systems, invertebrates are central to structuring and maintaining the functioning of urban forests. Identifying the role of invertebrates in urban forests can help elucidate their importance to practitioners and the public, not only to preserve biodiversity in urban environments, but also to make the public aware of their functional importance in maintaining healthy greenspaces. In this review, we examine the multiple functional roles that invertebrates play in urban forests that contribute to ecosystem service provisioning, including pollination, predation, herbivory, seed and microorganism dispersal and organic matter decomposition, but also those that lead to disservices, primarily from a public health perspective, e.g., transmission of invertebrate-borne diseases. We then identify a number of ecological filters that structure urban forest invertebrate communities, such as changes in habitat structure, increased landscape imperviousness, microclimatic changes and pollution. We also discuss the complexity of ways that forest invertebrates respond to urbanisation, including acclimation, local extinction and evolution. Finally, we present management recommendations to support and conserve viable and diverse urban forest invertebrate populations into the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it