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Record W2767208550 · doi:10.1111/1365-2664.13045

A review of riverine ecosystem service quantification: Research gaps and recommendations

2017· review· en· W2767208550 on OpenAlexafffund
Dalal E.L. Hanna, Stephanie A. Tomscha, Camille Ouellet Dallaire, Elena M. Bennett

Bibliographic record

VenueJournal of Applied Ecology · 2017
Typereview
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEcosystem servicesEnvironmental resource managementService (business)EcosystemEcosystem managementValuation (finance)Ecosystem healthBusinessEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Abstract Increasing demand for benefits provided by riverine ecosystems threatens their sustainable provision. The ecosystem service concept is a promising avenue to inform riverine ecosystem management, but several challenges have prevented the application of this concept. We quantitatively assess the field of riverine ecosystem services’ progress in meeting these challenges. We highlight conceptual and methodological gaps, which have impeded integration of the ecosystem service concept into management. Across 89 relevant studies, 33 unique riverine ecosystem services were evaluated, for a total of 404 ecosystem service quantifications. Studies quantified between 1 and 23 ecosystem services, although the majority (55%) evaluated three or less. Among studies that quantified more than one service, 58% assessed interactions between services. Most studies (71%) did not include stakeholders in their quantification protocols, and 34% developed future scenarios of ecosystem service provision. Almost half (45%) conducted monetary valuation, using 16 methods. Only 9% did not quantify or discuss uncertainties associated with service quantification. The indicators and methods used to quantify the same type of ecosystem service varied. Only 3% of services used indicators of capacity, flow and demand in concert. Our results suggest indicators, data sources and methods for quantifying riverine ecosystem services should be more clearly defined and accurately represent the service they intend to quantify. Furthermore, more assessments of multiple services across diverse spatial extents and of riverine service interactions are needed, with better inclusion of stakeholders. Addressing these challenges will help riverine ecosystem service science inform river management. Synthesis and applications . The ecosystem service concept has great potential to inform riverine ecosystem management and decision‐making processes. However, this review of riverine ecosystem service quantification uncovers several remaining research gaps, impeding effective use of this tool to manage riverine ecosystems. We highlight these gaps and point to studies showcasing methods that can be used to address them.

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 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)0.004
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.149
GPT teacher head0.410
Teacher spread0.261 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations162
Published2017
Admission routes2
Has abstractyes

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