Cladistics in Exercise Science: Classifying Movement, Anatomy, and Performance

What do cladistics use?

While "cladistics" is a biological methodology primarily used to classify organisms based on shared evolutionary traits and common ancestry, in the fields of exercise science and kinesiology, we employ analogous systematic frameworks and analytical tools to categorize, understand, and apply principles related to human movement, anatomical structures, and physiological adaptations. These methods allow us to build comprehensive models for effective training, rehabilitation, and performance enhancement.

The Conceptual Parallel: Classification in Exercise Science

Just as cladistics relies on specific data to build phylogenetic trees, exercise science utilizes distinct sets of information and analytical methods to classify and understand the complexities of human movement and physical adaptation. The core "use" is the systematic organization of knowledge to derive actionable insights.

Key "Tools" and Data in Kinesiological Classification

In exercise science, our "cladistic tools" are the fundamental principles and data points we employ to categorize, analyze, and prescribe interventions. These include:

• Anatomical and Structural Data:

  • Musculoskeletal Anatomy: Understanding the origin, insertion, action, and innervation of individual muscles (e.g., classifying muscles by primary joint action: knee extensors, hip flexors).
  • Joint Classification: Categorizing joints by structure (fibrous, cartilaginous, synovial) and function (synarthroses, amphiarthroses, diarthroses) informs movement potential and stability.
  • Bone Structure: Analyzing bone types, densities, and lever arms for biomechanical advantage.

• Physiological Data:

  • Energy Systems: Classifying exercises and activities based on the dominant energy pathway utilized (e.g., ATP-PC for power, glycolysis for strength-endurance, oxidative for endurance).
  • Muscle Fiber Types: Understanding the properties of Type I (slow-twitch) and Type II (fast-twitch) fibers to tailor training for specific adaptations.
  • Cardiorespiratory Responses: Analyzing heart rate, oxygen consumption (VO2), and ventilatory thresholds to classify exercise intensity and adaptations.

• Biomechanical Analysis:

  • Movement Patterns: Categorizing fundamental human movements (e.g., squat, hinge, push, pull, lunge, carry, rotation) based on shared biomechanical principles and joint actions. This is analogous to identifying "shared derived characteristics" in movement.
  • Force-Velocity Relationship: Understanding how force production changes with contraction velocity to classify types of resistance training.
  • Lever Systems: Analyzing the body's lever systems (first, second, third class) to understand mechanical advantage in exercises.
  • Kinetic Chain Classification: Distinguishing between open kinetic chain (OKC) and closed kinetic chain (CKC) exercises based on distal segment freedom.

• Motor Control and Learning Principles:

  • Skill Classification: Categorizing motor skills based on factors like precision, organization, and environmental predictability (e.g., discrete vs. continuous, open vs. closed skills).
  • Feedback Types: Classifying feedback (internal vs. external, knowledge of results vs. knowledge of performance) to optimize motor learning.

Application in Practice: Constructing "Training Trees"

Just as cladistics constructs phylogenetic trees to illustrate evolutionary relationships, exercise professionals implicitly build "training trees" or frameworks. We use these classifications to:

• Program Design: Systematically organize exercises based on their biomechanical similarities, physiological demands, and target adaptations. For example, a "pushing" movement pattern tree might include variations like bench press, overhead press, and push-ups, all sharing the core "pushing" characteristic but differing in specific joint angles or stability demands.
• Assessment and Diagnosis: Identify deviations from optimal movement patterns or classify dysfunctional movements based on their shared characteristics (e.g., common compensations during a squat).
• Progression and Regression: Understand the hierarchical nature of skill acquisition and strength development, allowing for logical progressions (e.g., bodyweight squat to goblet squat to barbell back squat).
• Research and Education: Provide a standardized language and framework for studying human movement, facilitating communication and advancing knowledge within the field.

In essence, while the term "cladistics" directly refers to biological classification, the underlying principle of systematically organizing and understanding complex relationships through shared characteristics is a fundamental methodology that exercise science and kinesiology profoundly "use" in their pursuit of optimizing human health and performance.