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Record W2561500759 · doi:10.5751/es-09048-210447

Ecological restoration, ecosystem services, and land use: a European perspective

2016· article· en· W2561500759 on OpenAlexvenueno aff
Anne Tolvanen, James Aronson

Bibliographic record

VenueEcology and Society · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
FundersMaj ja Tor Nesslingin Säätiö
KeywordsEcosystem servicesEnvironmental resource managementRestoration ecologyEcologyPerspective (graphical)EcosystemGeographyLand useEcosystem managementEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

This special feature provides an overview on how the ecosystem service concept has been and can be incorporated into the science, practice, and policies of ecological restoration (ER) and evidence-based land-use. It includes an edited selection of eleven invited and peer-reviewed papers based on presentations given during the 9th European Conference on Ecological Restoration in 2014. The focus is on Europe, but many contributors also make appraisals and recommendations at the global scale. Based on the contributors' papers, and our own overview of the promise of ecological restoration in the existing international treaties, coalitions, and conventions, we propose that the following actions could contribute to the positive impacts of ER on biodiversity maintenance, ecosystem functioning, progressive mainstreaming the concepts of both ER and ecosystem services, significant mitigation and offsetting of anthropogenic climate change, and lasting enhancement of both ecosystem and human health: ! ER should be incorporated into land use planning, wherever needed, and the synergies and trade-offs of different land use scenarios should be assessed in terms of their impacts on ecosystem services. ! The discourse of ER should be enlarged, wherever it is needed, to include multifunctional land use that simultaneously supports sustainable production systems, built environments, and the quality and quantity of diverse ecosystem services. This approach will generate ecological, social, and economic benefits in the long run. ! Monitoring and evaluation of ER projects should be a continuous process involving careful selection of indicators chosen with the full range of stakeholders in mind, and a sufficiently long-term perspective to catch the progress of long-term or highly dynamic ecosystem processes. ! Scientists should actively participate in policy and land management discussions in order to give their views on the potential outcomes of decisions. ! Greater cooperation and exchanges are needed within the EU and globally in order to accelerate the upscaling, improvement, and mainstreaming of both large-scale ER and the science and application of the ecosystem services concept.

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)0.000
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 score0.008
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations49
Published2016
Admission routes1
Has abstractyes

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