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Record W2033519181 · doi:10.3389/fevo.2015.00037

A mechanistic analysis of density dependence in algal population dynamics

2015· article· en· W2033519181 on OpenAlexaff
Adrian Borlestean, Paul C. Frost, Dennis L. Murray

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsTrent University
Fundersnot available
KeywordsDensity dependencePopulation densityIntraspecific competitionPopulationBiologyCompetition (biology)EcologyNutrientPer capita

Abstract

fetched live from OpenAlex

Population density regulation is a fundamental principle in ecology, but the specific process underlying functional expression of density dependence remains to be fully elucidated. One view contends that patterns of density dependence are largely fixed across a species irrespective of environmental conditions, whereas another is that the strength and expression of density dependence are fundamentally variable depending on the nature of exogenous or endogenous constraints acting on the population. We conducted a study investigating the expression of density dependence in Chlamydomonas spp. grown under a gradient from low to high nutrient density. We predicted that the relationship between per capita growth rate (pgr) and population density would vary from concave up to concave down as nutrient density became less limiting and populations experienced weaker density regulation. Contrary to prediction, we found that the relationship between pgr and density became increasingly concave-up as nutrient levels increased. We also found that variation in pgr increased, and pgr levels reached higher maxima in nutrient-limited environments. Most likely, these results are attributable to population growth suppression in environments with high intraspecific competition due to limited nutrient resources. Our results suggest that density regulation is strongly variable depending on exogenous and endogenous processes acting on the population, implying that expression of density dependence depends extensively on local conditions. Additional experimental work should reveal the mechanisms influencing how the expression of density dependence varies across populations through space and time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.874

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)0.0000.000

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 head0.006
GPT teacher head0.202
Teacher spread0.197 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2015
Admission routes1
Has abstractyes

Explore more

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