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Record W4391636510 · doi:10.32942/x2zg7s

Global exposure risk of frogs to increasing environmental dryness

2024· preprint· en· W4391636510 on OpenAlexaff
Nicholas C. Wu, Rafael Parelli Bovo, Urtzi Enriquez‐Urzelai, Susana Clusella‐Trullas, Michael Kearney, Carlos Navas, Jacinta D. Kong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicCOVID-19 impact on air quality
Canadian institutionsCarleton University
FundersFundação de Amparo à Pesquisa do Estado de São PauloAkademie Věd České RepublikyNational Research Foundation
KeywordsDrynessEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Species exposed to prolonged drying are at risk of population declines or extinctions. A key missing element for assessments of climate change risk is the sensitivity of species to water loss and their microhabitat preference, or ecotype, as both dictate the risk of environmental drying. Here, we identified globally where water-sensitive ectotherms, i.e. anurans, are at risk to increasing aridity and drought, examined which ecotypes are more sensitive to water loss from 238 species, and estimated how behavioural activity is impacted by future drought and warming scenarios through biophysical models. Under an intermediate and high emission scenario, 6.6 and 33.5% of areas occupied by anurans will increase to arid-like conditions, and 15.4 and 36.1% are at risk of exposure to a combination of increasing drought intensity, frequency, and duration by 2080¬–2100, respectively. Critically, increasing arid-like conditions will increase water loss rates and anurans in dry regions will almost double the water loss rates under a high emission scenario. Biophysical models showed that during the warmest quarter of the year, the combination of drought and warming reduced an anuran’s potential activity by 17.9% relative to the current conditions compared to warming alone which reduced potential activity by 8%. Our results exemplify the widespread exposure risk of environmental drying for anurans, posing a serious challenge for the lives of water-sensitive species beyond the effects of temperature alone.

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), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.008
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.014
GPT teacher head0.292
Teacher spread0.278 · 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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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