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Record W2168550963 · doi:10.1111/1365-2435.12391

Is successional research nearing its climax? New approaches for understanding dynamic communities

2014· article· en· W2168550963 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Ecology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsEcological successionEcologyConceptual frameworkBiologyTraitCommunityEnvironmental resource managementComputer scienceEcosystemSociology

Abstract

fetched live from OpenAlex

Summary Succession has been a focus of extensive ecological study for well over a century. Despite this sustained interest, succession remains a central theme in ecological research and is positioned to continue that prominence in this era of expanding human impacts. Community ecology is currently experiencing a profound conceptual expansion, providing many new insights into succession. Here we present an existing conceptual framework of successional drivers that includes variation in site conditions, species availability and species performance, and expand it to include both evolutionary and geographic sources of variation. This framework is useful because it specifies relationships among individual drivers and is causally complete. While we generally think about succession as a within‐site process, the inclusion of phylogenetic and geographic processes allows integration across broader scales. We use the conceptual framework to highlight several opportunities for successional research that have developed within community ecology, but have not been fully integrated into succession work. These ideas represent not only individual drivers of succession, but also potential synergistic processes operating through interaction with other drivers. The complexity of drivers in succession strongly argues for the need to move away from single factor studies towards combinatorial studies that incorporate multiple drivers. Utilizing a trait‐based approach should allow researchers to address successional drivers at multiple ecological scales and lead to new insights that integrate ecological systems. Our ability to do this will depend on the availability of equivalent data across multiple systems, suggesting the need for more standardization in successional studies. Addressing the research opportunities highlighted here will not only produce insights into successional systems, but also expand our understanding of fundamental questions in community ecology as a whole. Of particular importance is the ability to address broader scale questions that go beyond the idiosyncrasies of individual sites and systems. Understanding the dynamics of successional systems will remain critical to understanding, managing and predicting anthropogenic impacts on natural systems.

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 categoriesScience and technology studies, Insufficient 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 score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.286
GPT teacher head0.343
Teacher spread0.056 · 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