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Record W3161612924 · doi:10.1111/csp2.450

Treatment of climate change in extinction risk assessments and recovery plans for threatened species

2021· article· en· W3161612924 on OpenAlexaffabout
Ilona Naujokaitis‐Lewis, Sarah Endicott, Jessica Guezen

Bibliographic record

VenueConservation Science and Practice · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of GuelphEnvironment and Climate Change Canada
Fundersnot available
KeywordsThreatened speciesClimate changeExtinction (optical mineralogy)BiodiversityVulnerability (computing)Environmental resource managementHabitatPopulationEcologyGeographyEnvironmental scienceBiologyEnvironmental healthComputer science

Abstract

fetched live from OpenAlex

Abstract The ongoing threat of climate change poses an increasing risk to biodiversity, especially for currently threatened species. Climate change can both directly impact species and interact with other pre‐existing threats, such as habitat loss, to further amplify species' risk of extinction. Recognizing the threat of climate change in extinction risk assessments and recovery planning for imperilled species is essential for tailoring and prioritizing recovery actions for climate‐threatened species. Using species legally listed in Canada we show that 44.1% of species' risk assessments identify the threat of climate change, nonetheless, 43.5% of assessments completely omit climate change. Species assessed more recently were more likely to be identified as climate‐threatened, however, the strength of this relationship varied across taxonomic groups. The likelihood that climate change was identified as a threat was also strongly affected by the use of a standardized threat assessment process. Of the climate‐threatened species, less than half (46.0%) of species' recovery plans specified actions aimed explicitly at minimizing climate impacts and only 3.8% of recovery plans recommended habitat or population management actions. Climate‐targeted recovery actions were more likely to be included in more recent plans, and were marginally more likely for species where climate change was considered a major threat. Our findings highlight the urgent need for consistent and standardized assessments of the threat of climate change, including the consideration of potential synergies between climate change and other existing threats. Performing species‐specific climate change vulnerability assessments may serve to complement existing assessment and recovery planning processes. We provide additional recommendations aimed at threatened species recovery planners for improving the integration of the threat of climate change into species extinction risk assessments and recovery planning processes for listed species.

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)0.020
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.132
GPT teacher head0.369
Teacher spread0.237 · 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 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

Citations18
Published2021
Admission routes2
Has abstractyes

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