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Record W2891380430 · doi:10.1101/422501

Towards an applied metaecology

2018· preprint· en· W2891380430 on OpenAlexaff
Luís Schiesari, Miguel G. Matias, Paulo Inácio Prado, Mathew A. Leibold, Cécile H. Albert, Jennifer G. Howeth, Shawn Leroux, Renata Pardini, Tadeu Siqueira, Pedro H. S. Brancalion, Mar Cabeza, Renato Mendes Coutinho, José Alexandre Felizola Diniz‐Filho, Bertrand Fournier, Daniel J. G. Lahr, Thomas M. Lewinsohn, Ayana de Brito Martins, Carla Morsello, Pedro R. Peres‐Neto, Valério D. Pillar, Diego P. Vázquez

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldEnvironmental Science
TopicEcosystem dynamics and resilience
Canadian institutionsUniversité du Québec à MontréalMemorial University of NewfoundlandMcGill University
FundersUniversidade de São PauloConselho Nacional de Desenvolvimento Científico e TecnológicoAcademy of FinlandFundação de Amparo à Pesquisa do Estado de São PauloLabex OT-MedAgence Nationale de la RechercheNational Science Foundation
KeywordsInterdependenceSocial connectednessContext (archaeology)Environmental changeComputer scienceAction (physics)Risk analysis (engineering)Work (physics)Environmental resource managementConceptual frameworkEcological systems theoryManagement scienceClimate changeEcologyBusinessGeographyEnvironmental scienceEngineeringSociologyPsychology

Abstract

fetched live from OpenAlex

Abstract The complexity of ecological systems is a major challenge for practitioners and decision-makers who work to avoid, mitigate and manage environmental change. Here, we illustrate how metaecology - the study of spatial interdependencies among ecological systems through fluxes of organisms, energy, and matter - can enhance understanding and improve managing environmental change at multiple spatial scales. We present several case studies illustrating how the framework has leveraged decision-making in conservation, restoration and risk management. Nevertheless, an explicit incorporation of metaecology is still uncommon in the applied ecology literature, and in action guidelines addressing environmental change. This is unfortunate because the many facets of environmental change can be framed as modifying spatial context, connectedness and dominant regulating processes - the defining features of metaecological systems. Narrowing the gap between theory and practice will require incorporating system-specific realism in otherwise predominantly conceptual studies, as well as deliberately studying scenarios of environmental change.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations3
Published2018
Admission routes1
Has abstractyes

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