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Lineamientos para la conservación de la conectividad a través de redes y corredores ecológicos

2021· book· es· W3146437312 on OpenAlexfundno aff
Jodi Hilty, Graeme L. Worboys, Annika T. H. Keeley, Stephen Woodley, Barbara J. Lausche, Harvey J. Locke, Mark H. Carr, Ian Pulsford, Jamie Pittock, Wilson J. White, David M. Theobald, Jessica Levine, Melly Reuling, James Watson, Rob Ament, Craig Groves, Gary Tabor

Bibliographic record

Venuenot available
Typebook
Languagees
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
FundersWorld Bank GroupSvenska Forskningsrådet FormasInternational Fund for Animal WelfareYellowstone to Yukon Conservation InitiativeGordon and Betty Moore Foundation
KeywordsHumanitiesGeographyPolitical scienceArt

Abstract

fetched live from OpenAlex

En ecosistemas terrestres, dulceacuícolas y marinos, los corredores ecológicos son una designación de conservación necesaria para asegurar la salud de los ecosistemas. Los corredores son elementos fundamentales de las redes ecológicas para la conservación y complementan los objetivos de las áreas protegidas y OMEC al conectar estos hábitats con otras áreas naturales intactas. Estos lineamientos responden a la creciente demanda por la conectividad que han manifestado académicos, tomadores de decisiones y profesionales de la conservación. Los ecosistemas bien conectados apoyan una serie de funciones ecológicas, incluyendo la migración, ciclos de agua y de nutrientes, polinización, dispersión de semillas, seguridad alimentaria, resiliencia frente al clima y resistencia a enfermedades. Estos lineamientos ofrecen orientación sobre cómo conservar los valores de la conectividad en diferentes contextos de la conservación de forma consistente y medible. Los 25 estudios de caso de estos lineamientos ofrecen ejemplos y buenas prácticas que muestran algunos enfoques que pueden asegurar la conectividad ecológica entre diferentes ecosistemas y especies a diferentes escalas espaciales y temporales. Para asegurar la integración y aceleración de la adopción de las medidas de conservación de la conectividad con el fin de amortiguar y promover la adaptación al cambio climático, es necesario enfatizar las capacidades humanas y técnicas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.278
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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