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Record W3088343377 · doi:10.1111/csp2.288

Conservation value of national forest roadless areas

2020· article· en· W3088343377 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConservation Science and Practice · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsCanadian Parks and Wilderness Society
Fundersnot available
KeywordsNature ConservationGeographyNational parkProtected areaEnvironmental protectionEnvironmental resource managementAgroforestryArchaeologyEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Conservation scientists call for establishing additional protected areas amidst ongoing threats of expanding human development. Nevertheless, some existing protected areas are being downsized and demoted of their existing conservation protections. In 2001, the Roadless Area Conservation Rule prohibited road construction and timber harvest in 240,000 km 2 of inventoried roadless areas (IRAs) located on United States Department of Agriculture Forest Service lands. IRAs represent a non‐legislative protected status that is in jeopardy of conservation demotion or “degazettement,” and few national protected area assessments recognize the IRA designation. Since the rule's conception two decades ago, little research has been conducted to assess the conservation values of IRAs and the values they could add to the existing system of highly protected areas in the continental United States. To increase understanding of these conservation values, we assessed three aspects of roadless areas: (a) how wild and intact are IRA lands compared to state, national, and protected lands, (b) how do IRAs complement the size, connectedness, and representation of protected lands, and (c) how do IRAs contribute to protection of important ecosystem services (drinking water and annual carbon capture)? Through this analysis we found that many IRAs are among the most wild, undeveloped areas both in the nation and within their respective states. IRAs increase the size of—and reduce isolation between—protected areas, likely buffering them from external stressors. In some places, IRAs protect watersheds that deliver drinking water to hundreds of thousands of people. IRAs also add significantly to the total carbon captured by existing protected areas. The results of our evaluation demonstrate the potential of IRAs to contribute to the conservation value of the U.S. protected area system and to deliver important ecosystem services.

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.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.160
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.004
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 head0.050
GPT teacher head0.307
Teacher spread0.257 · 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