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Related Experiment Video

Updated: Sep 15, 2025

Author Spotlight: Development and Challenges of Feeding Assays for Insect Pest Management

Author Spotlight: Development and Challenges of Feeding Assays for Insect Pest Management

Published on: May 26, 2023

Predicting the Phenology of Herbivorous Insects.

Zimo Yang¹, Elise Woodruff¹, David Held¹

¹Department of Entomology and Plant Pathology Auburn University Auburn Alabama USA.

Ecology and Evolution

|July 15, 2025

Summary

Understanding insect phenology variation is key for sustainable agriculture and climate change adaptation. Our study reveals factors like phylogeny, body size, and environment influence insect development timing, improving predictive models.

Keywords:

degree days integrative pest management lower developmental threshold multilevel Bayesian models phylogenetic models phytophagy thermal requirements

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Last Updated: Sep 15, 2025

Author Spotlight: Development and Challenges of Feeding Assays for Insect Pest Management

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Published on: May 26, 2023

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

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Published on: January 9, 2019

Author Spotlight: Analysis of Ovarian Anatomy in Migratory Insects to Overcome Experimental Challenges

Author Spotlight: Analysis of Ovarian Anatomy in Migratory Insects to Overcome Experimental Challenges

Published on: July 14, 2023

Area of Science:

Ecology
Evolutionary Biology
Entomology

Background:

Herbivorous insect phenology is crucial for agriculture and climate change impact assessments.
Current models lack understanding of phenological variation across insect populations and its drivers.

Purpose of the Study:

To analyze factors influencing herbivorous insect phenology variation.
To improve the generalizability and accuracy of insect phenology models.

Main Methods:

Comparative analysis of 601 published herbivorous insect phenology models.
Application of multilevel Bayesian models to assess variation drivers.

Main Results:

Phylogenetic relatedness, adult body size, feeding site, host plant, geography, and model parameterization explain phenological variation.
Minimum developmental temperatures vary adaptively across insect life stages.

Conclusions:

Incorporating population and environmental variation enhances herbivorous insect phenology predictions.
Improved models support sustainable agriculture and climate change management.