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Record W4403064580 · doi:10.1186/s13750-024-00344-3

Existing evidence on the effect of urban forest management in carbon solutions and avian conservation: a systematic literature map

2024· article· en· W4403064580 on OpenAlexafffund
Kayleigh Hutt‐Taylor, Corinne G. Bassett, Riikka Kinnunen, Barbara Frei, Carly D. Ziter

Bibliographic record

VenueEnvironmental Evidence · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsEnvironment and Climate Change CanadaUniversity of British ColumbiaConcordia University
FundersDivision of Materials ResearchConcordia UniversityNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsForest managementNature ConservationGeographySilvicultureEnvironmental resource managementForestryAgroforestryEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.042
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0420.036
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.030
GPT teacher head0.260
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2024
Admission routes2
Has abstractyes

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