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Life History Traits

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Imitative and Direct Learning as Interacting Factors in Life History Evolution.

Artificial life
The idea that lifetime learning can have a significant effect on life history evolution has recently been explored using a series of artificial life simulations. These involved populations of competing individuals evolving by natural selection to lea...

Augmenting biologging with supervised machine learning to study behavior of the medusa .

The Journal of experimental biology
Zooplankton play critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood because of the difficulty in studying individuals Here, we combine biologging with supervised machine learning (ML) to propose a pipeline f...

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Nature plants
Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely inaccessible, imposing direct barriers to understanding crop yield and fitness traits. Here, we asse...

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

Plant physiology
Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance ...