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Record W4322005185 · doi:10.5194/egusphere-egu23-7943

Framing origins and dynamics of biodiversity in the paradigm of space and time scaling

2023· preprint· en· W4322005185 on OpenAlexaff
Andrej Spiridonov, S. Lovejoy, Lauras Balakauskas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiodiversityBiotaEvolutionary dynamicsBiologyEvolutionary biologyEcologySociology

Abstract

fetched live from OpenAlex

The biodiversity is the fundamental aspect and transitive measure of biota and the evolutionary process itself. The biodiversity is usually understood as the diversity of morphological or structural types, and also as the number of taxa (species, genera, families etc.) or branches of different ranks in evolutionary trees or networks. The biodiversity is hierarchical and universal feature of biological systems. Despite its conceptual simplicity, the origins and patterns of variability of diversity, except the fact that they are based on the evolutionary process, are rather hardly comprehensively understood. Therefore, the determination of origins, and the dynamics of biodiversity through the space and time, is one of the most fundamental open questions of biology. The theory of evolution reveals a number of possibilities on how biodiversity can change, and also predicts patterns which underlie the mechanism: if the biodiversity is autonomous and self-regulating process, or if opposite is true – the biodiversity is a driven variable dependant on many varying Earth system, and possibly astrophysical components. One of the most promising approaches in characterizing the dynamics of biodiversity, and discriminating between the underlying causes of the dynamics, is the analysis of scaling. The spatial scaling of biodiversity is a well developed field of science. The dependence of species richness on the geographical area is described by power laws. The values of parameters could be interpreted with respect to possible controlling genealogical and ecological mechanisms of evolution. The scaling of biodiversity in space, also suggests the scaling of biodiversity as a function of time scale. The scaling is time scale symmetry which connects the large and small scales, and it reveals the uniformity of a mechanism in a scaling range. Presented approach allows the summarization of macroevolution in very simple terms. Here we present a case of global marine animal biodiversity, and based on the revealed crossover-like time scaling pattern, we suggest that two competing time symmetric scaling mechanisms, with opposite effects on biodiversity (stabilizing versus destabilizing), are responsible for the evolution of the biota at the eon scale. The presented results can serve as a null model in understanding global evolution, and also can serve in sharpening and strengthening of our intuitions in exploring and explaining macroevolutionary patterns. The research was supported by the project S-MIP-21-9 “The role of spatial structuring in major transitions in macroevolution”.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.019
Scholarly communication0.0070.013
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.282
Teacher spread0.256 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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