Existing evidence on the effect of urban forest management in carbon solutions and avian conservation: a systematic literature map
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Urgent solutions are needed in cities to mitigate twin crises of global climate change and biodiversity loss. Urban nature-based solutions (actions that protect, sustainably manage, and restore ecosystems while simultaneously providing human wellbeing and biodiversity benefits) are being advocated for as multi-functional tools capable of tackling these societal challenges. Urban forest management is a proposed nature-based solution with potential to address both climate change mitigation and biodiversity loss along with multiple other benefits. However, bodies of evidence measuring multiple outcomes (e.g., biodiversity conservation and nature-based climate solutions) remain siloed which limits conservation and management opportunities. In this article, we present a systematic map of the literature on urban forest management strategies that measure both biodiversity goals (through avian conservation) and climate change mitigation goals (through carbon storage and sequestration). METHODS: Following a published protocol, we searched for evidence related to urban forest management strategies for (1) avian conservation and (2) carbon solutions within the global temperate region in academic and grey literature. In addition to Scopus, ProQuest and Web of Science Core Collection, we searched 21 specialist websites. We screened English language documents using predefined inclusion criteria on titles and abstracts, and then full texts. All qualifying literature items were coded, and metadata were extracted. No study validity appraisal was conducted. We identified knowledge clusters and gaps related to forest management strategies for both topics. REVIEW FINDINGS: Our searches identified 19,073 articles published, of which 5445 were duplicates. The title and abstract screening removed a further 11,019 articles. After full-text screening (1762 and 1406), a total of 277 avian and 169 forest carbon literature items met the eligibility criteria and were included in the final database. We found a large knowledge base for broad-scale avian metrics: abundance, species richness. We similarly found that both avian and carbon solutions most often used broad-scale forest management components: land use type, composition, and forested area and least often considered fragmentation, connectivity, and diversity metrics (abundance, richness). The most understudied avian metrics were foraging, resources, and survival while the most understudied carbon solutions metrics were soil carbon, dead wood and organic matter and infrastructure. Avian literature most often used an experimental design (56% with comparator, 44% no comparator) while forest carbon solutions literature was dominated by observational studies (86%). In both topics, studies most often occurred over short timelines between 0 and 1 and 2-5 years. The body of evidence for both avian and carbon outcomes present a scale-mismatch between the scale of forest management strategy (e.g., land use type) and scale of application (e.g., patch). For example, the majority of studies considered forest strategies at broad scales, like land use type or composition, yet were conducted at a patch or multi-patch scale. Our systematic map also highlights that multi-city and regional urban scales are underrepresented in both carbon solutions and avian conservation and will require additional research efforts. Finally, we highlight gaps in the inclusion of recommendations in both bodies of literature. Roughly 30% of articles in each topic's database did not include recommendations for practitioners or researchers. CONCLUSIONS: Our systematic map provides a database and identifies knowledge gaps and clusters of urban forest management strategies for (1) avian conservation and (2) carbon solutions. Overall, our map will allow researchers to fill existing gaps in literature through new research investigations, meta-analyses or systematic reviews while also pointing policymakers toward strong knowledge bases in addition to understudied or mismatched areas that require more funding.
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 | 0.001 | 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 it