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Agroecologies defined by species distribution models improve model fit of genotype by environment interactions to identify the best performing chicken breeds for smallholder systems

Kebede, Fasil Getachew; Komen, Hans; Dessie, Tadelle; Hanotte, Olivier; Kemp, Steve; Alemu, Setegn Worku; Bastiaansen, John W. M.

Agroecologies defined by species distribution models improve model fit of genotype by environment interactions to identify the best performing chicken breeds for smallholder systems Thumbnail


Authors

Fasil Getachew Kebede

Hans Komen

Tadelle Dessie

Professor OLIVIER HANOTTE OLIVIER.HANOTTE@NOTTINGHAM.AC.UK
DIRECTOR OF FROZEN ARK PROJECT & PROFESSOR OF GENETICS & CONSERVATION

Steve Kemp

Setegn Worku Alemu

John W. M. Bastiaansen



Abstract

Animal performance is an outcome of genetic effects, environmental influences, and their interaction. Understanding the influences of the environment on performance is important to identify the right breeds for a given environment. Agroecological zonation is commonly used to classify environments and compare the performance of breeds before their wider introduction into a new environment. Environmental classes, also referred to as agroecologies, are traditionally defined based on agronomically important environmental predictors. We hypothesized that our own classification of agroecologies for livestock at a species level and incorporating the most important environmental predictors may improve genotype by environment interactions (GxE) estimations over conventional methodology. We collected growth performance data on improved chicken breeds distributed to multiple environments in Ethiopia. We applied species distribution models (SDMs) to identify the most relevant environmental predictors and to group chicken performance testing sites into agroecologies. We fitted linear mixed-effects models (LMM) to make model comparisons between conventional and SDM-defined agroecologies. Then we used Generalized Additive Models (GAMs) to visualize the influences of SDM-identified environmental predictors on the live body weight of chickens at species level. The model fit in LMM for GxE prediction improved when agroecologies were defined based on SDM-identified environmental predictors. Partial dependence plots (PDPs) produced by GAMs showed complex relationships between environmental predictors and body weight. Our findings suggest that multi-environment performance evaluations of candidate breeds should be based on SDM-defined environmental classes or agroecologies. Moreover, our study shows that GAMs are well-suited to visualizing the influences of bioclimatic factors on livestock performance.

Citation

Kebede, F. G., Komen, H., Dessie, T., Hanotte, O., Kemp, S., Alemu, S. W., & Bastiaansen, J. W. M. (2023). Agroecologies defined by species distribution models improve model fit of genotype by environment interactions to identify the best performing chicken breeds for smallholder systems. Frontiers in Sustainable Food Systems, 7, Article 1305799. https://doi.org/10.3389/fsufs.2023.1305799

Journal Article Type Article
Acceptance Date Nov 22, 2023
Online Publication Date Dec 7, 2023
Publication Date 2023
Deposit Date Apr 23, 2024
Publicly Available Date Apr 24, 2024
Journal Frontiers in Sustainable Food Systems
Electronic ISSN 2571-581X
Peer Reviewed Peer Reviewed
Volume 7
Article Number 1305799
DOI https://doi.org/10.3389/fsufs.2023.1305799
Keywords generalized additive model, chicken breed, genotype by environment interactions, smallholder systems, species distribution models
Public URL https://nottingham-repository.worktribe.com/output/28995100
Publisher URL https://www.frontiersin.org/articles/10.3389/fsufs.2023.1305799/full

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