Increasing poultry product consumption trends have attracted researchers and development practitioners to look for interventions that transform the low-input low-output-based village chicken production to a high yielding production system. However, due to the intricate nature of the production system, there is a dearth of evidence that helps design comprehensive interventions at the smallholder level. Using national-level representative data collected from 3555 village chicken producers in Ethiopia, Nigeria, and Tanzania, this study examines the technical efficiency of village chicken production and investigates the main factors that explain the level of inefficiency. We applied a stochastic frontier analysis to simultaneously quantify the level of technical efficiency and identify factors associated with heterogeneity in inefficiency. We found that the level of technical efficiency is extremely low in the three countries, suggesting enormous opportunities to enhance productivity using available resources. The heterogeneity in technical efficiency is strongly associated with producers’ experience in breed improvements and flock management, limited technical knowledge and skills, limited access to institutions and markets, smaller flock size, gender disparities, and household livelihood orientation. We argue the need to adopt an integrated approach to enhance village producers’ productivity and transform the traditional subsistence-based production system into a commercially oriented semi-intensive production system.

Smallholder poultry production dominated by indigenous chickens is an important source of livelihoods for most rural households in Ethiopia. The long history of domestication and the presence of diverse agroecologies in Ethiopia create unique opportunities to study the effect of environmental selective pressures. Species distribution models (SDMs) and Phenotypic distribution models (PDMs) can be applied to investigate the relationship between environmental variation and phenotypic differentiation in wild animals and domestic populations. In the present study we used SDMs and PDMs to detect environmental variables related with habitat suitability and phenotypic differentiation among nondescript Ethiopian indigenous chicken populations. 34 environmental variables (climatic, soil, and vegetation) and 19 quantitative traits were analyzed for 513 adult chickens from 26 populations. To have high variation in the dataset for phenotypic and ecological parameters, animals were sampled from four spatial gradients (each represented by six to seven populations), located in different climatic zones and geographies. Three different ecotypes are proposed based on correlation test between habitat suitability maps and phenotypic clustering of sample populations. These specific ecotypes show phenotypic differentiation, likely in response to environmental selective pressures. Nine environmental variables with the highest contribution to habitat suitability are identified. The relationship between quantitative traits and a few of the environmental variables associated with habitat suitability is non-linear. Our results highlight the benefits of integrating species and phenotypic distribution modeling approaches in characterization of livestock populations, delineation of suitable habitats for specific breeds, and understanding of the relationship between ecological variables and quantitative traits, and underlying evolutionary processes.

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Ethiopia's 60 million chickens are reared primarily in free range, smallholder systems. Therefore, upgrading smallholder poultry to small-scale commercial systems is central to rural development. With the aim of providing access to improved chicken by rural farmers in Ethiopia, the live body weight at week 17 and number of eggs per bird per week for one locally improved and three tropically adapted dual-purpose chicken strains was tested through a project called the African Chicken Genetic Gains. Both traits were analyzed by fitting a linear mixed model with week and pen as random effects, and station and breed as fixed effects. The result showed that both breed and station effects were significant for both traits. The introduced breeds performed better than the local improved breed for both traits. Thus, the introduction of system-appropriate high-yielding tropically adapted breeds has the potential to increase the productivity of chicken.

. Adaptive phenotypic and genetic variation in chickens: a landscape genomics approach Smallholder chicken production is an integral part of tropical farming systems and contributes significantly to sustainable livelihoods. Performance of chickens in these systems is too low to meet the growing demands for meat and eggs. Unavailability of productive and adaptive breeds is a major constraint. Knowledge on phenotypic and genetic variation among populations contributes to the design of sustainable chicken genetic improvement and development programmes. I follow a landscape genomics approach and integrate genetic, phenotypic, and environmental information in my study design. In the first part of this thesis, I aim to identify the environmental drivers of local adaptation and detect genomic footprints of natural selection in indigenous chickens. I use species distribution models (SDMs) to identify environmental predictors associated with habitat suitability. Based on higher level of matching between the presence of distinct phenotypes and availability of unique environmental niches, I classify the Ethiopian chicken populations into three ecotypes. I perform selection signatures analyses ( 𝐹 and XP-EHH) and redundancy analyses (RDA) at different analytical layers (considering gradient and agroecology) to identify candidate loci and genomic regions linked mainly with local adaptation. I show that Ethiopian chicken populations differentiated the most between gradients but selection pressures leading to adaptive variation are stronger between agroecologies. I indicate that the results from RDA match the outputs from signatures of selection analyses ( 𝐹 and XP-EHH). I show that RDA can be used as an alternative approach to GWAS in random mating, indigenous chicken populations which have sufficiently interacted with the environment. I demonstrate that signatures of selection analysis with the two methods ( 𝐹 and XP-EHH) can be used complementarily with RDA to shed light on the relationship between genomic, phenotypic, and environmental variation in local adaptation studies in indigenous chickens. I show that phenotypic distribution models (PDMs) such as boosted generalized additive models (GAMs) are valuable tools in animal breeding to integrate environmental and phenotypic information and to predict phenotypic values. In the second part of the thesis, I evaluate the performance of improved chicken breeds introduced into smallholder systems. I show that that agroecologies defined by SDMs improve model fit in GxE predictions. I utilize the concept of phenotypic plasticity to compare yield stability of improved chicken breeds. I show that two approaches of multi-environment breed performance analysis (MEPA), namely, additive main effects and multiplicative interaction models (AMMI) and linear mixed-effects models (LMM) are applicable in chicken to identify and recommend more productive and stable breeds. Together, I demonstrate how adaptive phenotypic and genetic variation can be exploited to enhance the performance of chick...

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