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Record W4307511780 · doi:10.1186/s13750-022-00288-6

What evidence exists for the use of urban forest management in nature-based carbon solutions and bird conservation. A systematic map protocol

2022· article· en· W4307511780 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Evidence · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsEnvironment and Climate Change CanadaConcordia UniversityUniversité de Sherbrooke
FundersConcordia UniversityGovernment of Canada
KeywordsForest managementNature ConservationEnvironmental resource managementProtocol (science)GeographySilvicultureAgroforestryEnvironmental planningForestryEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: There is global interest in finding innovative solutions that address current climate and societal challenges in an urban context. Cities are often on the front lines of environmental change, meaning urban greening strategies have high potential to provide benefits across human communities, while protecting global biodiversity. There is growing consensus that nature-based solutions can provide multiple benefits to people and nature while also mitigating the effects of climate change. Urban forest management is well-suited to a nature-based solutions framework due to the wide variety of services trees provide our communities. Effective approaches to urban forest management also have the potential to promote other forms of urban biodiversity, particularly birds and species at risk. However, studies that integrate strategies for both climate and biodiversity conservation are rare. The goal of this systematic map is to gather and describe information on two desired outcomes of urban forest management: (1) conserving avian diversity and species at risk (2) carbon storage and sequestration (i.e., nature-based climate solutions). METHODS: We will identify relevant articles from two separate searches for inclusion in our systematic map that address (1) urban forestry and avian and species at risk conservation and, (2) urban forestry and carbon storage and sequestration. We will search two bibliographic databases, consult 20 relevant organizational websites, and solicit grey literature through an open call for evidence. Eligibility screening will be conducted at two stages: (1) title and abstract and (2) full text. Relevant information from included papers will be extracted and entered in a searchable, coded database. Synthesis of evidence will describe the key characteristics of each study (e.g., geographic locations, interventions, outcomes, species studied) and identify knowledge gaps and clusters of evidence. Our systematic map will guide further research on opportunities for multiple benefits using nature-based solutions, particularly as they relate to urban forest management. Furthermore, our evidence base will support both management and funding decisions to ensure the effective use of resources for maximum benefits across people and ecosystems.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.295
Teacher spread0.213 · 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