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Towards a quantification of the water planetary boundary

2020· article· en· W3113085559 on OpenAlexaff
Lan Wang‐Erlandsson, Tom Gleeson, Fernando Jaramillo, Samuel C. Zipper, Dieter Gerten, Arne Tobian, Miina Porkka, Agnes Pranindita, Ruud van der Ent, Patrick Keys, Ingo Fetzer, Matti Kummu, Anna Chrysafi, Will Steffen, H. H. G. Savenije, Makoto Taniguchi, Line Gordon, Sarah Cornell, Arie Staal, Yoshihide Wada

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPlanetary boundariesWater cycleEarth system scienceBoundary (topology)Environmental scienceBiosphereGroundwaterEarth scienceAstrobiologyEcologyGeologyMathematicsBiologySustainability

Abstract

fetched live from OpenAlex

<p>The planetary boundaries framework defines nine Earth system processes that together demarcate a safe operating space for humanity at the planetary scale. Freshwater - the bloodstream of the biosphere - is an obvious member of the planetary boundary framework.  Water fluxes and stores play a key role for the stability of the Earth’s climate and the world’s aquatic and terrestrial ecosystems. Recent work has proposed to represent the water planetary boundary through six sub-boundaries based on the five primary water stores, i.e., atmospheric water, soil moisture, surface water, groundwater, and frozen water. In order to make it usable on all spatial scales we examine bottom-up and top-down approaches for quantification of the water planetary boundary. For the bottom-up approaches, we explore possible spatially distributed variables defining each of the proposed sub-boundaries, as well as possible weighting factors and keystone regions that can be used for aggregation of the distributed water sub-boundaries to the global scale. For the top-down approaches, we re-examine the stability of key biomes and tipping elements in the Earth System that may be crucially influenced by water cycle modifications. To identify the most appropriate variables for representing the water planetary boundary, we evaluate the range of explored variables with regard to scientific evidence and scientific representation using a hierarchy-based evaluation framework. Finally, we compare the highest ranked top-down and bottom-up approaches in terms of the scientific outcome and implications for governance. In sum, this comprehensive and systematic identification and evaluation of variables, weighting factors, and baseline conditions provides a detailed basis for the future operational quantification of the water planetary boundary. </p>

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)0.000
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 score0.048
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.026
GPT teacher head0.194
Teacher spread0.169 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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