Speciation and Statistical Testing

Spec Mapping — OCR H420 Module 4.2.2 — Classification and evolution, content statements covering allopatric and sympatric speciation, reproductive isolation, statistical tests used in biological investigations (Student's t-test, Spearman's rank correlation, standard deviation), and the named examples of evolution in action (MRSA / antibiotic resistance, peppered moth, Darwin's finches) (refer to the official OCR H420 specification document for exact wording). This lesson closes Module 4.2.2 and integrates the mechanisms, evidence, and quantitative tools of the whole module.

Natural selection explains how populations adapt to their environments; speciation explains how new species arise. In parallel, biologists need statistical tools to decide whether observed differences between populations are real or due to chance. OCR A-Level Biology A Module 4.2.2 requires you to understand allopatric and sympatric speciation, to use statistical tests (Student's t-test, Spearman's rank correlation, standard deviation), and to recognise named examples of evolution in action.

The conceptual framework for speciation is principally the work of Ernst Mayr (1942 Systematics and the Origin of Species), who articulated the biological species concept and the central role of geographic isolation in allopatric speciation. Charles Darwin had already noted the importance of geographic isolation through his Beagle observations of the Galápagos finches (paraphrased here from his published notes). The statistical machinery comes from a separate twentieth-century lineage: William Sealy Gosset ("Student"), working at the Guinness brewery in Dublin, developed the t-test in 1908 to compare small samples of beer; Charles Spearman developed the rank-correlation coefficient in 1904; the framework of null-hypothesis significance testing was formalised by Ronald Fisher in the 1920s and 1930s.

Key Definitions:

• Speciation — the evolution of new species.
• Reproductive isolation — the inability of two populations to interbreed and produce fertile offspring.
• Allopatric speciation — speciation that occurs when populations are geographically separated.
• Sympatric speciation — speciation that occurs without geographical separation.
• Null hypothesis (H₀) — a statistical hypothesis that there is no significant difference/relationship.

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What Is Speciation?

A new species forms when a population splits and the two resulting populations become reproductively isolated: they can no longer interbreed to produce fertile offspring. Speciation is the process by which biodiversity increases.

Reproductive isolation can be:

• Prezygotic — preventing mating or fertilisation.
  • Temporal isolation (different breeding seasons).
  • Ecological isolation (different habitats).
  • Behavioural isolation (different courtship rituals).
  • Mechanical isolation (incompatible anatomy).
  • Gametic isolation (incompatible gametes).
• Postzygotic — zygote forms but is non-viable or infertile.
  • Hybrid inviability (zygote dies).
  • Hybrid sterility (offspring is sterile — e.g. the mule).
  • Hybrid breakdown (F₁ viable but F₂ inviable).

Once isolation is complete, the two populations evolve independently — mutations occur in one that do not reach the other, selection pressures differ, and eventually genetic differences accumulate to the point that even if the populations rejoin, they cannot interbreed.

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Allopatric Speciation

flowchart LR
    A[Original Population] --> B[Geographical barrier forms]
    B --> C[Population 1]
    B --> D[Population 2]
    C --> E[Different selection pressures]
    D --> F[Different selection pressures]
    E --> G[Genetic divergence]
    F --> G
    G --> H[Reproductive isolation]
    H --> I[Two species]

Allopatric means "in different homelands". A population is physically divided by a geographical barrier — a mountain range, a river, an island forming, a continent splitting, or simply a great distance. Once separated, the two subpopulations:

1. Experience different selection pressures (different climates, predators, food).
2. Undergo different mutations by chance.
3. Genetic drift acts independently in each.
4. Over many generations, they accumulate differences until they can no longer interbreed.

Examples

• Galápagos finches — Darwin's finches diverged into 18 species on separate islands of the Galápagos archipelago. Each island offers different food (cactus, seeds of different sizes, insects, even blood), and beak shapes have evolved accordingly.
• Antelope squirrels (Ammospermophilus) — two species on opposite sides of the Grand Canyon diverged after the canyon formed.
• Pine beetles — populations on isolated mountain ranges have diverged.
• Ring species — Ensatina salamanders in California, Larus gulls around the Arctic — each neighbour interbreeds, but the ends do not.

Allopatric speciation is the most common mode and is uncontroversial. Any geographical barrier that prevents gene flow can set the process in motion.

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Sympatric Speciation

Sympatric means "in the same homeland". Speciation occurs without geographical separation. Mechanisms include:

Ecological Isolation

Populations exploit different niches within the same area. For example:

• Apple maggot flies (Rhagoletis pomonella) — originally laid eggs only on hawthorn; after apples were introduced to North America in the 17th century, some flies switched to apples. Apple-flies and hawthorn-flies now mate at different times (because the fruits ripen at different times) and are on their way to becoming separate species.
• Cichlid fish in African lakes — hundreds of species have formed in single lakes (Victoria, Malawi, Tanganyika) through adaptive radiation into different diets, depths and colours, with no physical barriers.

Temporal Isolation

Populations breed at different times. For example, two plant populations might flower a few weeks apart, preventing cross-pollination despite sharing the same meadow.

Behavioural Isolation

Mate choice based on different preferences — colour, song, courtship dance — isolates populations. Cichlid fish females prefer males of particular colours; if some females switch their preference, speciation can follow.

Polyploidy

Polyploidy — possessing more than two sets of chromosomes — is a very fast form of sympatric speciation in plants. A polyploid individual cannot interbreed with its diploid parents because offspring would be triploid and sterile, so it is instantly reproductively isolated.

• Autopolyploidy — duplication of one species' genome.
• Allopolyploidy — combining genomes from two species (e.g. modern bread wheat, Triticum aestivum, is a hexaploid combining three different wheat genomes).

Polyploidy is estimated to account for the origin of 15% of flowering plant species. It is rarer in animals but does occur (some frogs, fish and insects).

Comparison of Speciation Modes

Feature	Allopatric	Sympatric
Geographic separation?	Yes	No
Rate	Usually slow	Sometimes fast (polyploidy)
Commonness	Most common	Less common
Example	Darwin's finches	Apple maggot flies, bread wheat

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Statistical Testing in Biology

When comparing two samples (two habitats, two treatments, two species), we need to know whether differences are real or just due to chance. Statistical tests assign a probability (p value) to the null hypothesis that there is no real difference.

The conventional threshold is p < 0.05, meaning: "if the null hypothesis were true, the observed difference would happen by chance less than 5% of the time." If p < 0.05, we reject the null hypothesis and conclude that the difference is statistically significant.

Which Test to Use?

Question	Test
Is there a difference between the means of two normally distributed samples?	Student's t-test
Is there a correlation between two ranked variables?	Spearman's rank
Are observed frequencies different from expected?	Chi-squared test (covered elsewhere in the spec)
What is the spread of the data?	Standard deviation

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Standard Deviation

Standard deviation (SD or σ) measures the spread of data around the mean. A small SD means data points are clustered close to the mean; a large SD means they are widely spread.

$s = \sqrt{\frac{\sum(x - \bar{x})^2}{n - 1}}$s=n−1∑(x−xˉ)2​​

Where:

• x is each data value
• x̄ is the mean
• n is the number of data points

For normally distributed data:

• Around 68% of values lie within 1 SD of the mean.
• Around 95% lie within 2 SD.
• Around 99.7% lie within 3 SD.

Worked example

Heights of five plants (cm): 12, 14, 15, 15, 19. Mean = 15.

Deviations from mean: −3, −1, 0, 0, +4.

Squared deviations: 9, 1, 0, 0, 16. Sum = 26.

Variance = 26 / (5 − 1) = 6.5. SD = √6.5 ≈ 2.55 cm.

Standard deviation is the basis for many other statistics, including error bars on graphs and the t-test itself.

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Student's t-test

The t-test compares the means of two samples to decide whether the difference is statistically significant. For two independent samples:

$t = \frac{|\bar{x}_1 - \bar{x}_2|}{\sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}}$t=n1​s12​​+n2​s22​​​∣xˉ1​−xˉ2​∣​

Where:

• x̄₁, x̄₂ are the sample means
• s₁², s₂² are the sample variances
• n₁, n₂ are the sample sizes

Procedure

1. State the null hypothesis (H₀): there is no significant difference between the means.
2. State the alternative hypothesis (H₁): there is a significant difference between the means.
3. Calculate t using the formula.
4. Calculate the degrees of freedom: df = n₁ + n₂ − 2.
5. Compare t with the critical value from a statistical table at p = 0.05 and the appropriate df.
6. Conclude:
   • If calculated t > critical t: reject H₀ — the difference is significant.
   • If calculated t ≤ critical t: accept H₀ — no significant difference.

Example

A biologist measures the height of poppies on two sides of a hill: sunny side (n=10, mean=32.0 cm, SD=4.0) and shaded side (n=10, mean=27.5 cm, SD=3.5).

Degrees of freedom = 10 + 10 − 2 = 18. Critical t at p = 0.05 is 2.10.

$t = \frac{|32.0 - 27.5|}{\sqrt{\frac{16}{10} + \frac{12.25}{10}}} = \frac{4.5}{\sqrt{2.825}} = \frac{4.5}{1.68} \approx 2.68$t=1016​+1012.25​​∣32.0−27.5∣​=2.825​4.5​=1.684.5​≈2.68

Because 2.68 > 2.10, we reject H₀. The poppies are significantly taller on the sunny side.

Exam Tip: OCR rarely expects you to calculate t by hand in an exam — but you must be able to interpret the output and state clearly: "calculated t > critical t, so we reject the null hypothesis at p = 0.05."

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Spearman's Rank Correlation

Spearman's rank tests whether two variables are correlated — whether one tends to increase or decrease as the other changes. It uses the rank order of values rather than raw values, making it robust to outliers and non-normal distributions.

$r_s = 1 - \frac{6 \sum d^2}{n(n^2 - 1)}$rs​=1−n(n2−1)6∑d2​

Where:

• d is the difference between the two ranks for each data pair
• n is the number of data pairs

Values of r_s:

• +1 — perfect positive correlation.
• 0 — no correlation.
• −1 — perfect negative correlation.

Procedure

1. State H₀: no correlation between the two variables.
2. Rank each variable separately (lowest = 1, highest = n).
3. Find d (the difference in ranks) for each data pair and square it.
4. Sum d² and substitute into the formula.
5. Compare r_s with the critical value at p = 0.05 and the relevant n.
6. Conclude: if |r_s| > critical value, reject H₀.

Example

A student investigates the relationship between light intensity and moss cover in eight quadrats. She ranks light intensity (1 = dimmest) and moss cover (1 = least), computes d for each pair, and finds Σd² = 20 with n = 8.

$r_s = 1 - \frac{6 \times 20}{8 \times (64 - 1)} = 1 - \frac{120}{504} = 1 - 0.238 = 0.762$rs​=1−8×(64−1)6×20​=1−504120​=1−0.238=0.762

Critical value at n = 8, p = 0.05 ≈ 0.738. Because 0.762 > 0.738, we reject H₀ and conclude there is a significant positive correlation.

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Evolution in Action: Named Examples

OCR explicitly wants you to know examples of evolution happening in modern times.

MRSA (Methicillin-Resistant Staphylococcus aureus)

• Background: S. aureus is a common skin bacterium. Penicillin cured most infections in the 1940s, but resistance emerged rapidly. Methicillin (introduced 1959) was a penicillinase-resistant alternative; by 1961 MRSA was identified.
• Mechanism: The mecA gene codes for an altered penicillin-binding protein, PBP2a, that is not inhibited by beta-lactam antibiotics. MecA spread via the SCCmec mobile genetic element and by plasmid transfer between bacteria.
• Evolution: Classic directional selection. Antibiotic use selects for any cell carrying resistance; resistant cells multiply rapidly.
• Consequences: MRSA now causes tens of thousands of deaths each year globally. Newer strains (VISA, VRSA) are even more resistant.

Peppered Moth (Biston betularia)