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Record W4281874923 · doi:10.1002/wcc.792

Mangrove forests under climate change in a 2°C world

2022· article· en· W4281874923 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWiley Interdisciplinary Reviews Climate Change · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersAdvance QueenslandUniversity of WaterlooMacquarie University
KeywordsMangroveClimate changeEcologySubtropicsEcosystemGeographyGlobal warmingIntertidal zoneEnvironmental scienceGlobal changeEcological forecastingEnvironmental resource managementClimatologyBiology

Abstract

fetched live from OpenAlex

Abstract The world's nations are committed to keeping global temperature rises to less than 2°C to avoid the worst impacts of climate change. Such a target is crucial for mangrove forests, because they are located primarily in tropical and subtropical regions that are expected to see large changes in climatic conditions; their intertidal location and sensitivity to changes in environmental conditions means that mangroves are expected to be on the front line of climate change impacts. We conceptualize what a 2°C world might look like for mangroves, and in particular the potential negative and positive responses of the mangrove ecosystem to anticipated changes in future atmospheric CO 2 concentrations, temperature, sea level, cyclone activity, storminess and changes in the frequency, and magnitude of climatic oscillations. We also assess the spatial distribution of such stressors, their relative contributions to mangrove ecosystem dynamics, and discuss the challenges in attributing mangrove ecosystem dynamics to climate change versus other global change stressors. Such knowledge can help future‐proof conservation and restoration activities, improve the Intergovernmental Panel on Climate Change's confidence level ascribed to climate change impacts on mangrove forests, and highlight the key temperature thresholds beyond which the future of the world's mangroves is less certain. This article is categorized under: Climate, Ecology, and Conservation > Modeling Species and Community Interactions Climate, Ecology, and Conservation > Observed Ecological Changes

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)0.001
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 score0.179
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.010
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.055
GPT teacher head0.314
Teacher spread0.259 · 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