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Record W1517073017 · doi:10.22230/jem.2012v13n2a148

Designing a Long-term Ecological Change Monitoring Program for BC Parks

2012· article· en· W1517073017 on OpenAlexaff
Pamela Wright, Tory Stevens

Bibliographic record

VenueJournal of Ecosystems and Management · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsClimate changeEnvironmental resource managementStressorWork (physics)Citizen scienceEnvironmental planningScale (ratio)Adaptation (eye)EcologyGeographyEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Global climate changes are impacting the entire landscape and although intended as ecological reservoirs and refugia, parks and protected areas are not immune to these changes. Provincially, BC Parks’ staff identify stressors and threats in conservation risk assessments and have identified myriad challenges amplified by climate change. The role of monitoring in protected areas management in general, and with respect to climate change in particular, is identified as central to most assessment and adaptation strategies. This paper describes our work in the development and implementation of a province-wide long-term ecological change monitoring (LTEM) program that can be conducted using a hybrid scientific/citizen-science model. The intent is to help understand a) the state of ecological integrity of BC Parks on a provincial scale and b) long-term ecological change of which climate change is one of the leading causes. Although still in the preliminary stages of implementation, we reflect on some of the lessons we are learning along the way from discussions with field staff, scientists and managers in the protected areas field.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.075
GPT teacher head0.304
Teacher spread0.229 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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