Biological Evolution and Phylogenetics
Lab and Lecture Context
Labs are emphasized for dissections and related activities; there is built-in downtime in the module flow (e.g., a lighter second week after a dissection week) to upload materials to Top Hat and complete other activities. This structure ensures students have ample time to process information from intensive lab sessions, such as uploading detailed dissection observations and completing online quizzes or preparation for the next module. The emphasis on lab attendance highlights their critical role in practical skill development and understanding anatomical details.
Lectures are more flexible but still have structure; visuals like a pie chart illustrate the abundance of fish in the world and explain why much of the first half of the semester focuses on fish.
Naming Conventions and Linnaean System
Linnaeus aimed to streamline how we name organisms with the Linnaean system, connecting naming to evolutionary relationships. Linnaeus's hierarchical classification (Kingdom, Phylum, Class, Order, Family, Genus, Species) sought to group organisms based on shared characteristics, which, while initially morphological, later became understood through the lens of common descent. This system provides a standardized, binomial nomenclature (Genus species) for universal communication among scientists.
The Linnaean approach is conceptually connected to evolutionary processes, though it is distinct from artificial selection.
Artificial selection is a real-world process where traits are chosen by humans; the underlying genetics is the same as natural selection, but the selection pressures differ. Unlike natural selection, where environmental pressures dictate which traits are advantageous for survival and reproduction, artificial selection involves humans deliberately breeding individuals with desired traits. This accelerates the rate at which specific alleles (gene variants) become more frequent within a population, leading to significant phenotypic changes over relatively short evolutionary timescales.
Trait selection in artificial selection leads to a higher prevalence of chosen genes in a population over generations; this happens at the population level, not in individuals evolving in real time.
A common example cited is dog domestication: wolves were selected by humans for particular traits, leading to the diversity of dogs over generations; this reflects selection pressures acting on populations over time.
Evolution, Selection, and Population Change
Evolution is a population-level process; individuals don’t evolve during a single lifetime. Evolution, defined as a change in allele frequencies in a population over successive generations, operates through various mechanisms including natural selection, genetic drift, gene flow, and mutation. While natural selection drives adaptation by favoring advantageous traits, it's crucial to understand that individuals possess fixed genetic information and cannot 'evolve' within their own lifespan. Instead, the genetic makeup of the population shifts as certain individuals with advantageous traits are more successful at passing on their genes.
Traits that are selected for become more prevalent in a population across generations, illustrating evolutionary change.
First Activity: Phylogenetic Trees
The initial lab activity centers on a phylogenetic tree.
Almost every chapter starts with a phylogenetic tree; you will work with a data set to construct a tree and identify patterns. A phylogenetic tree, or phylogeny, is a hypothesis about the evolutionary relationships among a set of organisms or groups of organisms called taxa. In the lab, you will use a character matrix data set, which typically lists observable traits (morphological, genetic, behavioral) for different taxa. By analyzing shared derived characteristics (synapomorphies), which are homologous traits unique to a group of descendants from a common ancestor, you will infer branching points (nodes) and common ancestors to construct the tree. The 'patterns' you identify include clades (groups of organisms that include an ancestor and all of its descendants) and sister taxa (two descendants that split from the same node).
Key concept: homologous features are shared traits due to common ancestry. The prefix "homo-" means the same; "hetero-" means different.
You will assess traits to determine homology and build a tree accordingly.
Example discussion point: a shortened tail is shared across different lineages (eutherians vs. marsupials), illustrating how similar traits can appear in related groups. This example highlights that while a shortened tail might be present in both eutherian mammals (e.g., some primates or rodents) and marsupials (e.g., kangaroos), a careful examination of additional homologous features beyond the tail (e.g., reproductive strategies, bone structures, genetic markers) is necessary to determine if the shortened tail is a truly homologous trait inherited from a very distant common ancestor of both groups, or if it represents an analogous trait that evolved independently due to similar selective pressures (convergent evolution). In many cases, similar physical appearances can be the result of convergent evolution, not shared ancestry.
Homology, Traits, and Evolutionary Signals
Homologous traits: features shared due to common ancestry.
In constructing trees, you seek combinations of traits that best explain the evolutionary relationships.
The development of traits and the layering of multiple features can seem intuitive at first, but adding more features increases analytical complexity. When constructing phylogenetic trees, incorporating a greater number of characters, especially those that are less prone to homoplasy (traits shared by species that are not due to common ancestry, often through convergent evolution or reversals), improves the robustness of the phylogeny. The analytical complexity arises from the need to distinguish between true homologous characters (phylogenetic signals) and homoplastic characters (evolutionary noise), often requiring sophisticated algorithms and statistical methods to find the most parsimonious (simplest) tree.
Fossorial adaptations (living underground) often lead to convergent trends like reduced or absent eyes and limb modifications due to the dark environment.
Example: For instance, consider fossorial mammals like moles (eutherian) and marsupial moles. Both exhibit highly convergent features such as spade-like forelimbs for digging, compact bodies, and greatly reduced or vestigial eyes, all adaptations to subterranean life. However, despite these striking similarities, genetic and reproductive analyses reveal they are distantly related, demonstrating how similar environmental pressures can drive the evolution of similar, yet independently derived, features.
Lab and Lecture Context
Labs are emphasized for dissections and related activities; there is built-in downtime in the module flow (e.g., a lighter second week after a dissection week) to upload materials to Top Hat and complete other activities. This structure ensures students have ample time to process information from intensive lab sessions, such as uploading detailed dissection observations and completing online quizzes or preparation for the next module. The emphasis on lab attendance highlights their critical role in practical skill development and understanding anatomical details.
Lectures are more flexible but still have structure; visuals like a pie chart illustrate the abundance of fish in the world and explain why much of the first half of the semester focuses on fish.
Naming Conventions and Linnaean System
Linnaeus aimed to streamline how we name organisms with the Linnaean system, connecting naming to evolutionary relationships. Linnaeus's hierarchical classification (Kingdom, Phylum, Class, Order, Family, Genus, Species) sought to group organisms based on shared characteristics, which, while initially morphological, later became understood through the lens of common descent. This system provides a standardized, binomial nomenclature (Genus species) for universal communication among scientists.
The Linnaean approach is conceptually connected to evolutionary processes, though it is distinct from artificial selection.
Artificial selection is a real-world process where traits are chosen by humans; the underlying genetics is the same as natural selection, but the selection pressures differ. Unlike natural selection, where environmental pressures dictate which traits are advantageous for survival and reproduction, artificial selection involves humans deliberately breeding individuals with desired traits. This accelerates the rate at which specific alleles (gene variants) become more frequent within a population, leading to significant phenotypic changes over relatively short evolutionary timescales.
Trait selection in artificial selection leads to a higher prevalence of chosen genes in a population over generations; this happens at the population level, not in individuals evolving in real time.
A common example cited is dog domestication: wolves were selected by humans for particular traits, leading to the diversity of dogs over generations; this reflects selection pressures acting on populations over time.
Evolution, Selection, and Population Change
Evolution is a population-level process; individuals don’t evolve during a single lifetime. Evolution, defined as a change in allele frequencies in a population over successive generations, operates through various mechanisms including natural selection, genetic drift, gene flow, and mutation. While natural selection drives adaptation by favoring advantageous traits, it's crucial to understand that individuals possess fixed genetic information and cannot 'evolve' within their own lifespan. Instead, the genetic makeup of the population shifts as certain individuals with advantageous traits are more successful at passing on their genes.
Traits that are selected for become more prevalent in a population across generations, illustrating evolutionary change.
First Activity: Phylogenetic Trees
The initial lab activity centers on a phylogenetic tree.
Almost every chapter starts with a phylogenetic tree; you will work with a data set to construct a tree and identify patterns. A phylogenetic tree, or phylogeny, is a hypothesis about the evolutionary relationships among a set of organisms or groups of organisms called taxa. In the lab, you will use a character matrix data set, which typically lists observable traits (morphological, genetic, behavioral) for different taxa. By analyzing shared derived characteristics (synapomorphies), which are homologous traits unique to a group of descendants from a common ancestor, you will infer branching points (nodes) and common ancestors to construct the tree. The 'patterns' you identify include clades (groups of organisms that include an ancestor and all of its descendants) and sister taxa (two descendants that split from the same node).
Key concept: homologous features are shared traits due to common ancestry. The prefix "homo-" means the same; "hetero-" means different.
You will assess traits to determine homology and build a tree accordingly.
Example discussion point: a shortened tail is shared across different lineages (eutherians vs. marsupials), illustrating how similar traits can appear in related groups. This example highlights that while a shortened tail might be present in both eutherian mammals (e.g., some primates or rodents) and marsupials (e.g., kangaroos), a careful examination of additional homologous features beyond the tail (e.g., reproductive strategies, bone structures, genetic markers) is necessary to determine if the shortened tail is a truly homologous trait inherited from a very distant common ancestor of both groups, or if it represents an analogous trait that evolved independently due to similar selective pressures (convergent evolution). In many cases, similar physical appearances can be the result of convergent evolution, not shared ancestry.
Homology, Traits, and Evolutionary Signals
Homologous traits: features shared due to common ancestry.
In constructing trees, you seek combinations of traits that best explain the evolutionary relationships.
The development of traits and the layering of multiple features can seem intuitive at first, but adding more features increases analytical complexity. When constructing phylogenetic trees, incorporating a greater number of characters, especially those that are less prone to homoplasy (traits shared by species that are not due to common ancestry, often through convergent evolution or reversals), improves the robustness of the phylogeny. The analytical complexity arises from the need to distinguish between true homologous characters (phylogenetic signals) and homoplastic characters (evolutionary noise), often requiring sophisticated algorithms and statistical methods to find the most parsimonious (simplest) tree.
Fossorial adaptations (living underground) often lead to convergent trends like reduced or absent eyes and limb modifications due to the dark environment.
Example: For instance, consider fossorial mammals like moles (eutherian) and marsupial moles. Both exhibit highly convergent features such as spade-like forelimbs for digging, compact bodies, and greatly reduced or vestigial eyes, all adaptations to subterranean life. However, despite these striking similarities, genetic and reproductive analyses reveal they are distantly related, demonstrating how similar environmental pressures can drive the evolution of similar, yet independently derived, features.