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Genes, Morphology, Performance, and Fitness: Quantifying Organismal Performance to Understand Adaptive Evolution

David G. Matthews, Terry R. Dial, George Lauder

2023Integrative and Comparative Biology17 citationsDOIOpen Access PDF

Abstract

To understand the complexities of morphological evolution, we must understand the relationships between genes, morphology, performance, and fitness in complex traits. Genomicists have made tremendous progress in finding the genetic basis of many phenotypes, including a myriad of morphological characters. Similarly, field biologists have greatly advanced our understanding of the relationship between performance and fitness in natural populations. However, the connection from morphology to performance has primarily been studied at the interspecific level, meaning that in most cases we lack a mechanistic understanding of how evolutionarily relevant variation among individuals affects organismal performance. Therefore, functional morphologists need methods that will allow for the analysis of fine-grained intraspecific variation in order to close the path from genes to fitness. We suggest three methodological areas that we believe are well suited for this research program and provide examples of how each can be applied within fish model systems to build our understanding of microevolutionary processes. Specifically, we believe that structural equation modeling, biological robotics, and simultaneous multi-modal functional data acquisition will open up fruitful collaborations among biomechanists, evolutionary biologists, and field biologists. It is only through the combined efforts of all three fields that we will understand the connection between evolution (acting at the level of genes) and natural selection (acting on fitness).

Topics & Concepts

Natural selectionIntraspecific competitionBiologyEvolutionary biologyAdaptation (eye)Selection (genetic algorithm)Variation (astronomy)Genetic FitnessEvolutionary developmental biologyMorphology (biology)Fitness landscapeField (mathematics)EcologyComputer scienceArtificial intelligencePopulationZoologyNeuroscienceSociologyMathematicsPure mathematicsAstrophysicsDemographyPhysicsPhysiological and biochemical adaptationsEvolution and Genetic DynamicsFish Ecology and Management Studies