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Record W1778915173 · doi:10.1111/oik.02883

The biodiversity–ecosystem service relationship in urban areas: a quantitative review

2015· review· en· W1778915173 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOikos · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsEcosystem servicesBiodiversityUrbanizationUrban ecosystemGeographyEnvironmental resource managementHabitatEcologyService (business)PopulationEcosystemUrban ecologyEnvironmental planningBusinessBiologyEnvironmental healthEnvironmental science

Abstract

fetched live from OpenAlex

By 2050, up to 75% of people globally will live in cities. Despite the potential ramifications of this urbanization for ecosystem services (ES), and the importance of locally produced ES for the health and wellbeing of urban residents, syntheses addressing the underlying ecology of ES provision rarely include urban areas. Here, I conduct a quantitative review of urban ES studies in the ecological literature, synthesizing trends across the discipline. I also quantify the extent to which this work considers the organisms and ecosystem components responsible for ES provision using two approaches: assessment of biodiversity–ES relationships, and an adaptation of the service provider concept. The majority of urban ES studies were conducted in western, developed countries, and typically assessed a single service in a single city – largely ignoring ES synergies and tradeoffs, and cross‐city comparisons. While several different ES are studied in urban ecosystems, the field is dominated by weather and climate‐related regulating services, with assessments of cultural services particularly lacking. Most studies described a habitat type as the service provider; however, studies that considered the biodiversity–ES relationship were more likely to identify a specific functional group, community, or population as the key provider of an ES. The biodiversity–ES relationship itself was most frequently characterized as dependent on the composition of species, functional traits, or structures, rather than correlated with the magnitude of any specific biodiversity metric. While the study of ES in urban ecosystems is increasing, there exists considerable room for further research. Future studies would benefit by expanding the number and categories of ES assessed within and across cities, as well as broadening the geographical scope of urban ES research. Biodiversity–ES assessments in urban ecosystems would also benefit from an expansion of the biodiversity types considered, particularly regarding non‐species based approaches, and consideration of non‐native and invasive species. Synthesis Urban ecosystem services (ES) affect the health and wellbeing of over 3.5 billion people who live in cities. However, syntheses addressing ES provision rarely include urban areas. I conducted the first quantitative review focused explicitly on the ecology of urban ES, including the role of biodiversity in service provision. I found that studies typically measure only a single service in one city, precluding assessment of ES synergies, tradeoffs, and cross‐city comparisons. I also found that while most studies attribute ES provision to a habitat or land‐use type, studies that consider biodiversity‐ES relationships are more likely to recognize a specific functional group, community, or population as the key provider of an ES.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.318
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.014

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 head0.123
GPT teacher head0.339
Teacher spread0.216 · 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