Evolutionary relatedness is how closely two organisms share a common ancestor, inferred from phylogenetic trees and cladograms built on shared traits, DNA, and protein sequences. The more recently two lineages split, the more closely related they are.
Evolutionary relatedness is exactly what it sounds like: how closely related two organisms are based on their shared evolutionary history. The closer their most recent common ancestor, the more related they are. You can't see this directly, so you infer it from evidence and map it onto a phylogenetic tree or cladogram.
What counts as evidence? Three big things (EK 7.9.A and EK 7.9.B). First, morphological similarities, meaning shared physical traits in living or fossil species. Second, molecular data like DNA and protein sequences, where more matching sequence means more recent shared ancestry. Third, the pattern of traits gained or lost over time, which lets you place an out-group (the lineage least related to everything else) and read where branches split. Every node on the tree is a most recent common ancestor, and every one of these trees is a hypothesis that gets revised as new evidence comes in (EK 7.9.B.3).
This sits in Unit 7: Natural Selection, specifically Topic 7.9 Phylogeny, and it's the payoff of the whole evolution unit. Natural selection and speciation explain HOW lineages diverge; evolutionary relatedness is how you READ that divergence after the fact. It directly supports learning objectives AP Bio 7.9.A (describe the evidence used to infer evolutionary relationships) and AP Bio 7.9.B (explain how trees and cladograms infer relatedness). On the exam this connects to the Evolution big idea: a tree isn't a fixed truth, it's a testable hypothesis about descent with modification.
Keep studying AP® Biology Unit 7
Phylogenetic Tree vs. Cladogram (Unit 7)
Both diagram evolutionary relatedness, but only a phylogenetic tree shows the amount of change over time, calibrated by fossils or a molecular clock. A cladogram just shows branching order with no time scale, so it tells you who's related but not how long ago they split.
Molecular Clock and mtDNA (Unit 7)
A molecular clock turns sequence differences into a timeline of relatedness, assuming mutations accumulate at a steady rate. The 2018 bear FRQ used mitochondrial DNA (mtDNA) exactly this way, building a tree of bear populations from their genetic differences.
Convergent Evolution (Unit 7)
Here's the trap: two species can look similar without being closely related. Convergent evolution produces shared traits from independent adaptation, not shared ancestry, so analogous traits can fake relatedness if you only look at morphology. This is why DNA evidence often settles the argument.
Speciation (Unit 7)
Relatedness is the record of speciation events. Every node where a branch splits represents a population that diverged into separate lineages, so a tree is basically a logbook of every speciation that produced the species you're comparing.
Expect to read trees, not just define the term. MCQ stems give you a diagram and ask which two species are most closely related (answer: the pair sharing the most recent common ancestor at a node), or hand you percent DNA similarity and ask which pair shows greater relatedness (98% shared = more related than 45% shared). You'll also distinguish shared derived traits from convergent look-alikes, like feathers and hollow bones in birds and theropod dinosaurs pointing to shared ancestry. On FRQs, you analyze real data: the 2018 Long FRQ built a bear phylogeny from mtDNA, and the 2023 short FRQ on ruminants asked you to reason about evolutionary relationships from a given setup. The verbs to nail are describe the evidence (7.9.A) and explain how the diagram supports a relatedness claim (7.9.B).
Looking alike does not equal being related. Convergent evolution can make distantly related species share traits because they faced similar environments, not because they share a recent ancestor (think wings on birds and bats). True evolutionary relatedness is judged by shared derived traits and especially DNA and protein sequence data, which are harder to fake than body shape.
Evolutionary relatedness measures how recently two organisms share a common ancestor, read off nodes in a phylogenetic tree or cladogram.
Evidence for relatedness comes from morphological similarities, DNA and protein sequences, and the pattern of traits gained or lost over time.
More shared DNA sequence means greater relatedness, so two primates sharing 98% of their DNA are more closely related than two fish sharing 45%.
A phylogenetic tree shows time (via fossils or a molecular clock) while a cladogram only shows branching order, so don't read a time scale into a cladogram.
Trees are hypotheses, not facts, and they get revised whenever new fossil or molecular evidence appears.
Convergent evolution can make unrelated species look alike, so similar appearance alone is not proof of close relatedness.
It's how closely two organisms share a common ancestor, inferred from phylogenetic trees and cladograms built on shared traits, DNA, and protein sequences. It lives in Topic 7.9 Phylogeny under learning objectives 7.9.A and 7.9.B.
No. Convergent evolution can produce similar traits in distantly related species that adapted to similar environments. That's why DNA and protein sequence data are stronger evidence of relatedness than physical appearance alone.
Both show branching order and common ancestors, but a phylogenetic tree also shows the amount of change over time, calibrated by fossils or a molecular clock. A cladogram shows who is related without any time scale or measure of evolutionary distance.
Find the pair that shares the most recent common ancestor, meaning their branches split at the closest node. If Species A and B diverged 5 million years ago but B and C diverged 15 million years ago, A and B are the most closely related.
More matching DNA or protein sequence means a more recent common ancestor, so higher sequence similarity equals closer relatedness. The 2018 bear FRQ used mitochondrial DNA to build a phylogenetic tree, and you may be asked to compare percent similarity to rank relatedness.
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