OCR A-Level Biology: Biodiversity, Classification and Evolution — Complete Revision Guide

Biodiversity, Classification and Evolution forms the second half of Module 4 of the OCR A-Level Biology A (H420) specification, sitting alongside communicable diseases and immunity. It is one of the most data-rich and quantitatively examined courses on the H420 path, bringing together the three intellectual pillars that organise all of modern biology: how we measure life's variety (biodiversity and sampling), how we group it (classification and phylogeny), and how we explain it (variation, natural selection and speciation). Both Paper 1 (Biological Processes) and Paper 3 (Unified Biology) of H420 reliably set extended-response items on natural selection, speciation and the comparison of the five-kingdom and three-domain classification systems, alongside calculation-driven items on Simpson's index, the Hardy-Weinberg equation and chi-squared testing.

Course 7 of 12 on the LearningBro OCR A-Level Biology learning path consolidates the evolutionary and ecological framework on which the rest of the path's biology depends. It draws on biological molecules for the molecular phylogenetic markers used in modern taxonomy, on nucleic acids, enzymes and biological reactions for the rRNA-based work that produced the three-domain system, and it sits adjacent to genetics and inheritance (which develops allele-frequency change in detail) and to cloning, biotechnology and ecosystems (which extends the in-situ and ex-situ conservation framework introduced here).

Guide Overview

The Biodiversity, Classification and Evolution course is structured as twelve lessons that move from biodiversity measurement and conservation through classification and phylogeny to the mechanism of evolution and the statistical tests used to test evolutionary hypotheses.

OCR H420 Specification Coverage

This course covers OCR H420 Modules 4.2 (Biodiversity) and 4.3 (Classification and Evolution) in full. The specification organises this material around three principal areas — quantitative biodiversity, hierarchical classification with phylogenetic reasoning, and evolutionary mechanism — each mapped here to one or more lessons (refer to the official OCR specification document for exact wording).

Sub-module	Topic area	Primary lesson(s)
4.2.1	Levels of biodiversity (habitat, species, genetic)	Biodiversity Levels
4.2.1	Sampling techniques (quadrat, transect, Lincoln index)	Sampling Techniques
4.2.1	Simpson's Index of Diversity	Simpson's Index of Diversity
4.2.1	Genetic diversity within and between populations; allele frequency	Genetic Diversity and Allele Frequencies
4.2.1	Factors affecting biodiversity (deforestation, agriculture, climate change)	Factors Affecting Biodiversity
4.2.1	In-situ and ex-situ conservation; CITES and Rio convention	Conservation: In Situ and Ex Situ
4.3.1	Taxonomic hierarchy; binomial nomenclature	Classification: Taxonomic Hierarchy
4.3.1	Five-kingdom vs three-domain systems; molecular evidence	Five Kingdom and Three Domain Systems
4.3.1	Phylogeny; cladograms; molecular clocks	Phylogeny and Cladistics
4.3.2	Evidence for evolution (fossil, comparative anatomy, molecular)	Evidence for Evolution
4.3.2	Variation (continuous, discontinuous); natural selection (directional, stabilising, disruptive)	Variation, Natural Selection and Adaptation
4.3.2	Speciation (allopatric, sympatric); Hardy-Weinberg; chi-squared	Speciation and Statistical Testing

Module 4.2 and 4.3 content is examined across all three H420 papers, with Paper 1 and Paper 2 reliably setting an extended-response item on natural selection, speciation or the comparison of classification systems, and Paper 3 favouring quantitative items on Simpson's index, Hardy-Weinberg p-squared plus 2pq plus q-squared equal to one, and chi-squared goodness-of-fit testing of Mendelian inheritance ratios.

Biodiversity Levels and Sampling

The biodiversity levels lesson develops the three nested scales the specification requires candidates to distinguish. Habitat (or ecosystem) diversity counts the variety of habitats in a region; species diversity combines species richness (the number of species present) with species evenness (the relative abundance of each); genetic diversity is the variety of alleles within and between populations of one species. The three scales are causally linked — habitat diversity is the substrate for speciation, species diversity supports the food-web complexity that ecosystem function requires, and genetic diversity is the raw material on which natural selection acts.

The sampling techniques lesson develops the standard field methods: random quadrat sampling (using coordinates from a grid) for sessile organisms, systematic line and belt transects for environmental gradients (across a sand-dune succession or up a rocky-shore zonation), and the mark-release-recapture Lincoln index for mobile populations, where the estimated population size equals the product of the first and second sample sizes divided by the number of recaptured marked individuals. Candidates must identify the appropriate technique for a given study system and recognise the assumptions underlying the Lincoln index — no births, deaths or migration during the sampling interval, no mark loss, no behavioural change from being marked, and random mixing of marked individuals back into the population. Random sampling is preferred over opportunistic sampling because it minimises observer bias.

The choice of technique follows the biology of the organism. Sessile or slow-moving organisms (plants, limpets, barnacles) are sampled with quadrats — placed at random coordinates to estimate abundance, density, percentage cover or frequency across a uniform habitat. Where there is an environmental gradient — a change in an abiotic factor across space, such as light down a woodland edge, salinity up an estuary, or exposure up a rocky shore — a transect captures how community composition changes along that gradient: a line transect records what touches the line at set intervals, while a belt transect uses quadrats at intervals to give abundance data. Mobile animals cannot be counted with a quadrat because they move in and out of it, so the mark-release-recapture method is used instead.

Worked example — the Lincoln index

The Lincoln (Petersen) index estimates the size $N$ of a mobile population from two captures:

$N = \frac{n_1 \times n_2}{m_2}$

where $n_1$ is the number marked and released in the first capture, $n_2$ is the total caught in the second capture, and $m_2$ is the number of marked (recaptured) individuals in the second sample. Suppose a student pitfall-trapping ground beetles catches, marks and releases 45 beetles ( $n_1 = 45$ ). A week later they re-trap and catch 50 beetles ( $n_2 = 50$ ), of which 15 carry the mark ( $m_2 = 15$ ). Then:

$N = \frac{45 \times 50}{15} = \frac{2250}{15} = 150 \text{ beetles}$

The logic is a proportion: the fraction of the second sample that is marked ( $m_2/n_2 = 15/50 = 0.30$ ) is assumed equal to the fraction of the whole population that was marked ( $n_1/N = 45/N$ ), so $45/N = 0.30$ and $N = 150$ . If any assumption is violated the estimate is biased in a predictable direction, and examiners love to test that reasoning: if marked beetles are more likely to be eaten (mark increases predation) or the mark rubs off, $m_2$ falls, so the calculated $N$ is an overestimate; if there is significant immigration or births between the two samples, the true population has grown and the method again mis-estimates it. Being able to name the assumption and state the direction of the resulting error is the AO3 discriminator on Lincoln-index questions.

Simpson's Index of Diversity

The Simpson's Index lesson is the quantitative core of the biodiversity sub-module and a routine source of AO2 calculation marks. The OCR formulation is

$D = 1 - \sum \left(\frac{n}{N}\right)^2$

where $n$ is the number of individuals of a given species and $N$ is the total number of individuals across all species. Values approach zero in communities dominated by one species and approach one in evenly-distributed multi-species communities. The Index combines richness and evenness in a single quantity, and is to be preferred over a raw species count when communities of different evenness are being compared. Candidates must calculate $D$ from a frequency table, comment on the value relative to a comparison habitat, and justify why a higher value indicates greater ecological stability.

A fully worked Simpson's Index calculation

Simpson's Index is worth practising until the arithmetic is mechanical, because in the exam you will be handed a raw species table and expected to reach a value to the correct number of decimal places under time pressure. Suppose a student sampling an area of species-rich chalk grassland with a $0.25\ \text{m}^2$ quadrat records the following counts across five plant species:

Species	Count ( $n$ )	$n/N$	$(n/N)^2$
Salad burnet	20	0.286	0.0816
Common rock-rose	15	0.214	0.0459
Wild thyme	12	0.171	0.0294
Bird's-foot trefoil	15	0.214	0.0459
Fairy flax	8	0.114	0.0131
Total	$N = 70$		$\sum = 0.2159$

Applying the formula:

$D = 1 - \sum \left(\frac{n}{N}\right)^2 = 1 - 0.2159 = 0.784$

A value of $D = 0.78$ is high, indicating a diverse and even community. Now contrast this with an improved (fertilised, reseeded) grassland dominated by a single vigorous grass, where the counts are 60, 4, 3, 2, 1 for five species with the same $N = 70$ . Here $\sum (n/N)^2 = (60/70)^2 + (4/70)^2 + (3/70)^2 + (2/70)^2 + (1/70)^2 = 0.7347 + 0.0033 + 0.0018 + 0.0008 + 0.0002 = 0.7408$ , so $D = 1 - 0.741 = 0.26$ . Same species richness (five species in each), same total abundance, yet the diversity index collapses from 0.78 to 0.26 — and that single number is what lets you make the argument that intensive management has degraded the community even though a naive species count says the two habitats are identical. That comparison, and the reasoning it licenses, is exactly the AO3 move examiners reward.

Exam technique — Simpson's Index: Always show the summation column of $(n/N)^2$ values as your working; if your final answer is wrong, the method marks in the table are still awarded. Keep unrounded intermediate values in your calculator (use the memory or answer key) and round only at the end — premature rounding of each $(n/N)^2$ term is a routine source of the "answer outside the accepted range" penalty. Note that OCR's convention gives higher $D$ for higher diversity; some textbooks quote a reciprocal form ( $1/\sum(n/N)^2$ ) or the un-subtracted $\sum(n/N)^2$ (Simpson's dominance), which run the opposite way. Use the formula printed on the paper, not the one you half-remember.

A recurring conceptual error is to treat a high $D$ as intrinsically "good" without qualification. What a high $D$ actually indicates is a community that is more resistant to environmental change and to the loss of any single species, because no one species is load-bearing for the whole food web — greater diversity buffers ecosystem function. That is a statement about ecological stability, and phrasing the interpretation in those terms (rather than a vague "more diversity is better") is what separates a full-mark AO2 response from a partial one.

Genetic Diversity and Factors Affecting Biodiversity

The genetic diversity lesson develops the third biodiversity scale at the population-genetics level. Allele frequency — the proportion of all gene copies at a locus accounted for by a particular allele — is the operative variable in evolutionary change; any rise or fall in allele frequency between generations is, by definition, evolution. Genetic diversity is reduced by genetic bottlenecks (population crashes that retain only a fraction of the original allele pool), founder effects (small samples colonising a new area), inbreeding in small populations and intensive artificial selection in domesticated species. The full mechanistic treatment of allele-frequency change sits ahead in genetics and inheritance.

The factors affecting biodiversity lesson develops the principal anthropogenic drivers — habitat destruction (deforestation, drainage of wetlands, urbanisation), monoculture and intensive agriculture, pollution, overexploitation of harvested species, introduction of invasive species, and climate change. Examiners reward candidates who can identify a named driver, trace its mechanism (loss of habitat heterogeneity, eutrophication, selective predation pressure) and propose a specific intervention. The H420 specification requires candidates to discuss these drivers in academic register, paraphrasing textbook consensus on extinction rates and biodiversity counts rather than citing specific contested figures.

Conservation: In Situ and Ex Situ

The conservation lesson develops the two complementary conservation frameworks. In-situ conservation protects species in their natural habitats through legally designated reserves (national parks, sites of special scientific interest, marine protected areas), habitat restoration and active species management. Ex-situ conservation removes individuals to controlled environments — captive breeding programmes in zoos, plant species in botanic gardens, seed banks for crop and wild plant genetic resources — to maintain populations that cannot be sustained in the wild and ultimately to reintroduce them. The lesson contrasts the relative strengths of each approach: in-situ preserves co-evolved community context but is vulnerable to ongoing habitat pressures, while ex-situ buys time but risks domestication and loss of fitness for the original environment.

International conservation frameworks — CITES regulating trade in endangered species, the Rio Convention on Biological Diversity, the Countryside Stewardship Scheme as a UK example — are examined as the institutional architecture that delivers conservation in practice. Cross-links into cloning, biotechnology and ecosystems develop the in-situ and ex-situ framework further into the ecosystem-management and biotechnology-assisted conservation context.

Classification: Taxonomic Hierarchy and the Three Domains

The taxonomic hierarchy lesson develops the nested ranks — domain, kingdom, phylum, class, order, family, genus, species — that organise biological diversity into a single hierarchical scheme. The binomial nomenclature paraphrased from Linnaeus's eighteenth-century system gives each species a two-part Latin name (genus and specific epithet, italicised with the genus capitalised). The biological species concept paraphrased from Mayr's mid-twentieth-century formulation defines a species as a group of organisms capable of interbreeding to produce fertile offspring; the morphological and phylogenetic species concepts handle the cases (asexual organisms, extinct taxa) where the biological concept does not apply.

The five-kingdom and three-domain lesson contrasts the older Whittaker five-kingdom system (Animalia, Plantae, Fungi, Protoctista, Prokaryotae) with the three-domain system (Archaea, Bacteria, Eukarya) paraphrased from Woese's work on ribosomal RNA sequence comparison in the late 1970s and 1980s. The molecular evidence showed that the prokaryotic kingdom contained two deeply divergent lineages — bacteria and archaea — that differ in membrane lipid chemistry, RNA polymerase structure, ribosomal RNA sequence and cell-wall composition, and that archaea are in some respects more closely related to eukaryotes than to bacteria. Candidates are reliably asked to explain why the three-domain system replaced the five-kingdom system at the highest taxonomic level, citing the molecular evidence over morphological grouping.

Phylogeny, Cladistics and Evidence for Evolution

The phylogeny and cladistics lesson develops the reconstruction of evolutionary relationships from shared derived characters (synapomorphies). Cladograms are branching diagrams in which each node represents a common ancestor and each branch represents a lineage; sister taxa share a more recent common ancestor than either does with any outgroup. Molecular clocks use the rate of neutral mutation in non-coding or synonymous sites to estimate divergence times. Cross-links into nucleic acids, enzymes and biological reactions develop the rRNA-based taxonomy that underwrites the three-domain system.

The evidence for evolution lesson develops the three principal lines: the fossil record (transitional forms, sequence of appearance consistent with phylogenetic prediction, biostratigraphic dating), comparative anatomy (homologous structures inherited from a common ancestor and modified by divergent selection — the pentadactyl limb being the textbook example — versus analogous structures arising from convergent selection on unrelated lineages), and molecular evidence (sequence comparison of conserved proteins such as cytochrome c, and of ribosomal RNA). The convergent triangulation of these three independent lines is what gives the modern evolutionary synthesis its empirical weight.

Variation, Natural Selection and Speciation

The variation, natural selection and adaptation lesson develops the central mechanism. Continuous variation is polygenic, environmentally modulated and normally distributed (height, mass); discontinuous variation is typically governed by one or a few loci and falls into discrete categories (blood group, eye colour in simple cases). Natural selection, paraphrased from the framework set out by Darwin in 1859 and independently by Wallace in the same period, operates whenever there is heritable variation in a trait that affects reproductive success: individuals with favourable phenotypes leave more offspring, the favourable alleles rise in frequency, and the population adapts. The three modes — directional selection (one extreme favoured, mean shifts; antibiotic resistance, peppered moth industrial melanism), stabilising selection (the mean favoured, variance reduced; human birth weight) and disruptive selection (both extremes favoured at the expense of the mean; can precipitate speciation) — must be distinguished, sketched and exemplified.

The speciation and statistical testing lesson develops two modes of speciation. Allopatric speciation occurs when a geographical barrier physically isolates two subpopulations, divergent selection (and genetic drift in small isolated populations) drives genetic differentiation, and reproductive isolation evolves as a by-product until interbreeding is no longer possible even if the populations rejoin. Sympatric speciation occurs without geographical isolation, typically through behavioural, temporal or polyploid reproductive isolation acting within a single geographical range — the polyploid origin of many flowering-plant species being a clear example.

The same lesson develops the two principal statistical tests the OCR specification requires. The Hardy-Weinberg principle — paraphrased from independent contributions by Hardy and Weinberg in 1908 — gives genotype frequencies under the null model of no evolution as

$p^2 + 2pq + q^2 = 1$

where $p$ and $q$ are the allele frequencies at a diallelic locus. It is paired with the allele-frequency identity $p + q = 1$ . The principle assumes large population, random mating, no mutation, no migration and no selection; any deviation from these assumptions produces evolutionary change. Candidates use the equation to calculate allele and genotype frequencies from observed data, including the frequency of heterozygous carriers of a recessive condition from the observed frequency of affected homozygotes.

Worked example — Hardy-Weinberg

The single most examined Hardy-Weinberg question type gives you the frequency of the recessive phenotype and asks for the carrier frequency. This works because the recessive phenotype is the only genotype whose frequency you can read directly: recessive individuals are homozygous ( $\text{aa}$ ), so their frequency is $q^2$ . Everything else follows.

Suppose cystic fibrosis (recessive) affects 1 in 2500 people in a population. The steps are always the same:

The recessive phenotype frequency is $q^2$ . So $q^2 = 1/2500 = 0.0004$ .
Take the square root to find $q$ , the recessive allele frequency: $q = \sqrt{0.0004} = 0.02$ .
Use $p + q = 1$ to find $p$ , the dominant allele frequency: $p = 1 - 0.02 = 0.98$ .
Carriers are heterozygous ( $\text{Aa}$ ), frequency $2pq$ : $2pq = 2 \times 0.98 \times 0.02 = 0.0392$ .

So roughly $0.039$ , or about 1 in 26 people, are carriers — a strikingly high figure that surprises students and is precisely why the calculation is worth teaching. As a self-check, the three genotype frequencies must sum to 1: $p^2 + 2pq + q^2 = 0.9604 + 0.0392 + 0.0004 = 1.000$ . If your three genotype frequencies do not sum to 1 you have made an arithmetic slip, so always run that check before writing your final line.

Exam technique — Hardy-Weinberg: The commonest error, and the classic Grade B ceiling on these questions, is confusing an allele frequency with a genotype frequency — quoting $q$ when the question asks for the frequency of affected individuals ( $q^2$ ), or quoting $q^2$ when it asks for carriers ( $2pq$ ). Read the question twice and label every quantity. The second commonest error is forgetting the factor of 2 in $2pq$ : there are two ways to be heterozygous ( $\text{Aa}$ and $\text{aA}$ ), which is where the 2 comes from. Only take a square root when you are moving from a genotype frequency to an allele frequency; never square-root an allele frequency. Finally, state the assumption the question implicitly relies on — that the population is in Hardy-Weinberg equilibrium (large, randomly mating, no selection/mutation/migration) — because a "state one assumption" follow-up is almost guaranteed.

The chi-squared ( $\chi^2$ ) goodness-of-fit test

The chi-squared test compares observed and expected frequencies under a null hypothesis (typically a Mendelian $3:1$ , $9:3:3:1$ or $1:1$ ratio). The formula on the OCR data sheet is

$\chi^2 = \sum \frac{(O - E)^2}{E}$

where $O$ is the observed count in each category and $E$ is the expected count under the null hypothesis. Work in counts, never percentages, and calculate the expected counts by applying the predicted ratio to the actual total sample size. The routine is best shown as a table. Suppose a monohybrid cross is predicted to give a $3:1$ ratio of purple to white flowers, and 160 offspring are scored: 108 purple and 52 white. Under a $3:1$ ratio the expected counts are $\tfrac{3}{4} \times 160 = 120$ purple and $\tfrac{1}{4} \times 160 = 40$ white.

Category	$O$	$E$	$O - E$	$(O-E)^2$	$(O-E)^2/E$
Purple	108	120	−12	144	1.20
White	52	40	+12	144	3.60
Total	160	160			$\chi^2 = 4.80$

So $\chi^2 = 1.20 + 3.60 = 4.80$ . The degrees of freedom equal the number of categories minus one: here $2 - 1 = 1$ . Reading the chi-squared distribution table at 1 degree of freedom and the $p = 0.05$ significance level gives a critical value of $3.84$ . The decision rule is: if the calculated $\chi^2$ exceeds the critical value, reject the null hypothesis; if it is less than or equal to the critical value, there is no significant difference between observed and expected, so you do not reject the null. Here $4.80 > 3.84$ , so we reject the null hypothesis: the observed ratio differs significantly from $3:1$ , and something other than simple Mendelian segregation (linkage, epistasis, or reduced viability of one genotype) may be operating.

Exam technique — chi-squared: Four marks are routinely lost on this test in avoidable ways. First, candidates run the test on percentages or ratios instead of raw counts — the test is defined for counts only. Second, they miscount degrees of freedom (it is categories minus one, so $2-1=1$ for a $3:1$ cross and $4-1=3$ for a $9:3:3:1$ dihybrid cross — not the number of offspring). Third, they invert the decision rule; the mnemonic is "calculated greater than critical → reject" (a big difference between observed and expected produces a big $\chi^2$ , which signals the null is wrong). Fourth, they stop at "reject/accept" without the biological sentence. Always finish with an interpretation: "the difference between observed and expected is greater than would be expected by chance alone at the 5% level, so we reject the null hypothesis," or conversely "any difference is attributable to chance, so we accept the null hypothesis and conclude the data are consistent with a $3:1$ ratio." That final sentence is where the AO3 mark lives.

Linking to the Other Courses

Biodiversity, Classification and Evolution is the most synoptic course on the H420 path. The molecular phylogeny in the phylogeny and cladistics lesson rests on the protein and nucleic acid biochemistry developed in biological molecules and nucleic acids, enzymes and biological reactions. The natural-selection mechanism feeds directly into the antibiotic-resistance content of communicable diseases and immunity, where mutation-and-selection at the bacterial population level is the textbook example. The allele-frequency mathematics of the Hardy-Weinberg principle is developed in greater inheritance-pattern detail in genetics and inheritance. The conservation-management content of the in-situ and ex-situ lesson is extended into ecosystem and biotechnology frameworks in cloning, biotechnology and ecosystems. The chi-squared statistical testing introduced here is the canonical test for the Mendelian inheritance ratios that genetics develops, and the broader statistical toolkit is consolidated in the final exam-preparation course on the path. Even the cardiac-cycle and dissociation-curve content of exchange and transport is given evolutionary context here, because the four-chamber double circulation is itself an evolutionary adaptation to high metabolic rate.

Required Practicals / PAGs

This course anchors two of the OCR H420 Practical Endorsement PAGs:

PAG 3 (Sampling techniques in the field) — random quadrat sampling, line and belt transects, mark-release-recapture for mobile populations, anchored in the sampling techniques lesson and in the Simpson's Index calculation lesson. PAG 3 quantitative output (raw counts, calculated index values, Lincoln index population estimates) is reliably examined on Paper 3.
PAG 11 (Research skills — planning and presenting biological investigations) — provides the methodological framework for designing and presenting biodiversity, evolution and population-genetics investigations, anchored across the factors affecting biodiversity lesson, the conservation lesson, and the speciation and statistical testing lesson.

Examiners use PAG 3 in particular as the practical context for Simpson's Index and Lincoln index calculations on Paper 3; PAG 11 underwrites the experimental-design extended-response items on the same paper.

Common Mark-Loss Patterns

A consolidated list of the errors examiners reliably penalise across Module 4.2 and 4.3 items — the subtle ones that separate a Grade A from a Grade A* answer are worth internalising early:

Confusing species richness with species diversity. Richness is a raw count of species; diversity (Simpson's $D$ ) combines richness and evenness. Two habitats with identical richness can have very different diversity, and quoting a species count when the question asks about diversity forfeits the mark.
Treating a high Simpson's $D$ as an unqualified "good." State the consequence: greater resistance to environmental change and to the loss of any single species, i.e. greater ecological stability.
Confusing an allele frequency with a genotype frequency in Hardy-Weinberg. The affected recessive phenotype is $q^2$ ; carriers are $2pq$ ; the recessive allele is $q$ . Square-root only when moving from genotype to allele frequency.
Describing natural selection as organisms "trying to" or "wanting to" adapt. Selection is not purposive. Variation arises first (by mutation), and the environment then filters it; individuals do not adapt within their lifetime in response to need. Lamarckian, goal-directed language is heavily penalised.
Confusing the three modes of selection. Directional shifts the mean toward one extreme (antibiotic resistance); stabilising favours the mean and reduces variance (human birth mass); disruptive favours both extremes at the expense of the mean and can drive speciation.
Blurring allopatric and sympatric speciation. Allopatric requires a geographical barrier; sympatric occurs within one geographical range (behavioural, temporal or polyploid isolation). The word "geographical" is the discriminator.
Saying the three-domain system "is more accurate" without the evidence. Cite the molecular basis: ribosomal RNA sequence differences, plus membrane lipid chemistry, RNA polymerase and cell-wall composition, revealed Archaea and Bacteria as deeply divergent lineages that morphology alone had lumped together.
Muddling homologous and analogous structures. Homologous structures (pentadactyl limb) share a common ancestor and diverged — evidence for common descent; analogous structures (wings of birds and insects) arise by convergent evolution and are not evidence of recent shared ancestry.
Running chi-squared on percentages, or miscounting degrees of freedom (categories minus one, not sample size).

Mini-FAQ

Is the peppered moth an example of directional or disruptive selection? Directional. Industrial melanism shifted the population mean toward the dark (melanic) form when soot-darkened bark made pale moths conspicuous to predators; one extreme was favoured and the mean moved toward it. It is not disruptive selection, which would require both extremes to be favoured simultaneously.

When do I use Simpson's Index rather than just counting species? Whenever you need to compare communities that may differ in evenness, or to make an argument about ecological stability. A raw species count ignores relative abundance, so it cannot distinguish an even community from one dominated by a single species — Simpson's $D$ can, as the worked chalk-grassland example shows.

Do I have to memorise the Simpson's, Hardy-Weinberg and chi-squared formulae? Hardy-Weinberg ( $p^2 + 2pq + q^2 = 1$ and $p + q = 1$ ) is worth knowing cold — it is quick to state and you must recognise which term maps to which genotype. Simpson's Index and chi-squared are typically printed on the data sheet, but the marks are in correct substitution and interpretation, not in recalling the symbols.

What is the difference between a species and a taxon? A taxon is any named group at any rank (a genus, a family and a kingdom are all taxa); a species is the base rank, defined via Mayr's biological species concept as a group that can interbreed to produce fertile offspring. Asexual and extinct organisms use the morphological and phylogenetic species concepts instead.

Closing

Biodiversity, Classification and Evolution is the conceptual capstone of Module 4 and one of the most quantitatively examined courses on the OCR H420 specification. The biodiversity-measurement toolkit (Simpson's Index, Lincoln index), the three-domain classification framework, the three lines of evidence for evolution, the three modes of natural selection and the two modes of speciation, together with the Hardy-Weinberg and chi-squared statistical tests, return across essentially every series of OCR Biology papers. Start with the Biodiversity, Classification and Evolution course and work through the twelve lessons in sequence; build a flashcard deck for the named statistical formulae and the canonical worked examples (peppered moth for directional selection, polyploid plants for sympatric speciation, the Galapagos finches for allopatric divergence) and drill Simpson's Index and Hardy-Weinberg calculations until they are automatic. The Module 5 physiology and Module 6 genetics content that follows then become a series of consequences of the evolutionary and ecological framework established here.

OCR A-Level Biology: Biodiversity, Classification and Evolution — Complete Revision Guide

Guide Overview

OCR H420 Specification Coverage

Sub-module	Topic area	Primary lesson(s)
4.2.1	Levels of biodiversity (habitat, species, genetic)	Biodiversity Levels
4.2.1	Sampling techniques (quadrat, transect, Lincoln index)	Sampling Techniques
4.2.1	Simpson's Index of Diversity	Simpson's Index of Diversity
4.2.1	Genetic diversity within and between populations; allele frequency	Genetic Diversity and Allele Frequencies
4.2.1	Factors affecting biodiversity (deforestation, agriculture, climate change)	Factors Affecting Biodiversity
4.2.1	In-situ and ex-situ conservation; CITES and Rio convention	Conservation: In Situ and Ex Situ
4.3.1	Taxonomic hierarchy; binomial nomenclature	Classification: Taxonomic Hierarchy
4.3.1	Five-kingdom vs three-domain systems; molecular evidence	Five Kingdom and Three Domain Systems
4.3.1	Phylogeny; cladograms; molecular clocks	Phylogeny and Cladistics
4.3.2	Evidence for evolution (fossil, comparative anatomy, molecular)	Evidence for Evolution
4.3.2	Variation (continuous, discontinuous); natural selection (directional, stabilising, disruptive)	Variation, Natural Selection and Adaptation
4.3.2	Speciation (allopatric, sympatric); Hardy-Weinberg; chi-squared	Speciation and Statistical Testing

Biodiversity Levels and Sampling

Worked example — the Lincoln index

The Lincoln (Petersen) index estimates the size $N$ of a mobile population from two captures:

$N = \frac{n_1 \times n_2}{m_2}$

$N = \frac{45 \times 50}{15} = \frac{2250}{15} = 150 \text{ beetles}$

Simpson's Index of Diversity

The Simpson's Index lesson is the quantitative core of the biodiversity sub-module and a routine source of AO2 calculation marks. The OCR formulation is

$D = 1 - \sum \left(\frac{n}{N}\right)^2$

A fully worked Simpson's Index calculation

Species	Count ( $n$ )	$n/N$	$(n/N)^2$
Salad burnet	20	0.286	0.0816
Common rock-rose	15	0.214	0.0459
Wild thyme	12	0.171	0.0294
Bird's-foot trefoil	15	0.214	0.0459
Fairy flax	8	0.114	0.0131
Total	$N = 70$		$\sum = 0.2159$

Applying the formula:

$D = 1 - \sum \left(\frac{n}{N}\right)^2 = 1 - 0.2159 = 0.784$

Exam technique — Simpson's Index: Always show the summation column of $(n/N)^2$ values as your working; if your final answer is wrong, the method marks in the table are still awarded. Keep unrounded intermediate values in your calculator (use the memory or answer key) and round only at the end — premature rounding of each $(n/N)^2$ term is a routine source of the "answer outside the accepted range" penalty. Note that OCR's convention gives higher $D$ for higher diversity; some textbooks quote a reciprocal form ( $1/\sum(n/N)^2$ ) or the un-subtracted $\sum(n/N)^2$ (Simpson's dominance), which run the opposite way. Use the formula printed on the paper, not the one you half-remember.

Genetic Diversity and Factors Affecting Biodiversity

Conservation: In Situ and Ex Situ

Classification: Taxonomic Hierarchy and the Three Domains

Phylogeny, Cladistics and Evidence for Evolution

Variation, Natural Selection and Speciation

$p^2 + 2pq + q^2 = 1$

Worked example — Hardy-Weinberg

Suppose cystic fibrosis (recessive) affects 1 in 2500 people in a population. The steps are always the same:

The recessive phenotype frequency is $q^2$ . So $q^2 = 1/2500 = 0.0004$ .
Take the square root to find $q$ , the recessive allele frequency: $q = \sqrt{0.0004} = 0.02$ .
Use $p + q = 1$ to find $p$ , the dominant allele frequency: $p = 1 - 0.02 = 0.98$ .
Carriers are heterozygous ( $\text{Aa}$ ), frequency $2pq$ : $2pq = 2 \times 0.98 \times 0.02 = 0.0392$ .

Exam technique — Hardy-Weinberg: The commonest error, and the classic Grade B ceiling on these questions, is confusing an allele frequency with a genotype frequency — quoting $q$ when the question asks for the frequency of affected individuals ( $q^2$ ), or quoting $q^2$ when it asks for carriers ( $2pq$ ). Read the question twice and label every quantity. The second commonest error is forgetting the factor of 2 in $2pq$ : there are two ways to be heterozygous ( $\text{Aa}$ and $\text{aA}$ ), which is where the 2 comes from. Only take a square root when you are moving from a genotype frequency to an allele frequency; never square-root an allele frequency. Finally, state the assumption the question implicitly relies on — that the population is in Hardy-Weinberg equilibrium (large, randomly mating, no selection/mutation/migration) — because a "state one assumption" follow-up is almost guaranteed.

The chi-squared ( $\chi^2$ ) goodness-of-fit test

The chi-squared test compares observed and expected frequencies under a null hypothesis (typically a Mendelian $3:1$ , $9:3:3:1$ or $1:1$ ratio). The formula on the OCR data sheet is

$\chi^2 = \sum \frac{(O - E)^2}{E}$

Category	$O$	$E$	$O - E$	$(O-E)^2$	$(O-E)^2/E$
Purple	108	120	−12	144	1.20
White	52	40	+12	144	3.60
Total	160	160			$\chi^2 = 4.80$

Exam technique — chi-squared: Four marks are routinely lost on this test in avoidable ways. First, candidates run the test on percentages or ratios instead of raw counts — the test is defined for counts only. Second, they miscount degrees of freedom (it is categories minus one, so $2-1=1$ for a $3:1$ cross and $4-1=3$ for a $9:3:3:1$ dihybrid cross — not the number of offspring). Third, they invert the decision rule; the mnemonic is "calculated greater than critical → reject" (a big difference between observed and expected produces a big $\chi^2$ , which signals the null is wrong). Fourth, they stop at "reject/accept" without the biological sentence. Always finish with an interpretation: "the difference between observed and expected is greater than would be expected by chance alone at the 5% level, so we reject the null hypothesis," or conversely "any difference is attributable to chance, so we accept the null hypothesis and conclude the data are consistent with a $3:1$ ratio." That final sentence is where the AO3 mark lives.

Linking to the Other Courses

Required Practicals / PAGs

This course anchors two of the OCR H420 Practical Endorsement PAGs:

PAG 3 (Sampling techniques in the field) — random quadrat sampling, line and belt transects, mark-release-recapture for mobile populations, anchored in the sampling techniques lesson and in the Simpson's Index calculation lesson. PAG 3 quantitative output (raw counts, calculated index values, Lincoln index population estimates) is reliably examined on Paper 3.
PAG 11 (Research skills — planning and presenting biological investigations) — provides the methodological framework for designing and presenting biodiversity, evolution and population-genetics investigations, anchored across the factors affecting biodiversity lesson, the conservation lesson, and the speciation and statistical testing lesson.

Common Mark-Loss Patterns

A consolidated list of the errors examiners reliably penalise across Module 4.2 and 4.3 items — the subtle ones that separate a Grade A from a Grade A* answer are worth internalising early:

Confusing species richness with species diversity. Richness is a raw count of species; diversity (Simpson's $D$ ) combines richness and evenness. Two habitats with identical richness can have very different diversity, and quoting a species count when the question asks about diversity forfeits the mark.
Treating a high Simpson's $D$ as an unqualified "good." State the consequence: greater resistance to environmental change and to the loss of any single species, i.e. greater ecological stability.
Confusing an allele frequency with a genotype frequency in Hardy-Weinberg. The affected recessive phenotype is $q^2$ ; carriers are $2pq$ ; the recessive allele is $q$ . Square-root only when moving from genotype to allele frequency.
Describing natural selection as organisms "trying to" or "wanting to" adapt. Selection is not purposive. Variation arises first (by mutation), and the environment then filters it; individuals do not adapt within their lifetime in response to need. Lamarckian, goal-directed language is heavily penalised.
Confusing the three modes of selection. Directional shifts the mean toward one extreme (antibiotic resistance); stabilising favours the mean and reduces variance (human birth mass); disruptive favours both extremes at the expense of the mean and can drive speciation.
Blurring allopatric and sympatric speciation. Allopatric requires a geographical barrier; sympatric occurs within one geographical range (behavioural, temporal or polyploid isolation). The word "geographical" is the discriminator.
Saying the three-domain system "is more accurate" without the evidence. Cite the molecular basis: ribosomal RNA sequence differences, plus membrane lipid chemistry, RNA polymerase and cell-wall composition, revealed Archaea and Bacteria as deeply divergent lineages that morphology alone had lumped together.
Muddling homologous and analogous structures. Homologous structures (pentadactyl limb) share a common ancestor and diverged — evidence for common descent; analogous structures (wings of birds and insects) arise by convergent evolution and are not evidence of recent shared ancestry.
Running chi-squared on percentages, or miscounting degrees of freedom (categories minus one, not sample size).

OCR A-Level Biology: Biodiversity, Classification and Evolution — Complete Revision Guide

Guide Overview

OCR H420 Specification Coverage

Biodiversity Levels and Sampling

Worked example — the Lincoln index

Simpson's Index of Diversity

A fully worked Simpson's Index calculation

Genetic Diversity and Factors Affecting Biodiversity

Conservation: In Situ and Ex Situ

Classification: Taxonomic Hierarchy and the Three Domains

Phylogeny, Cladistics and Evidence for Evolution

Variation, Natural Selection and Speciation

Worked example — Hardy-Weinberg

The chi-squared (χ2\chi^2χ2) goodness-of-fit test

Linking to the Other Courses

Required Practicals / PAGs

Common Mark-Loss Patterns

Mini-FAQ

Closing

Related Reading

Stay in the loop

OCR A-Level Biology: Biodiversity, Classification and Evolution — Complete Revision Guide

Guide Overview

OCR H420 Specification Coverage

Biodiversity Levels and Sampling

Worked example — the Lincoln index

Simpson's Index of Diversity

A fully worked Simpson's Index calculation

Genetic Diversity and Factors Affecting Biodiversity

Conservation: In Situ and Ex Situ

Classification: Taxonomic Hierarchy and the Three Domains

Phylogeny, Cladistics and Evidence for Evolution

Variation, Natural Selection and Speciation

Worked example — Hardy-Weinberg

The chi-squared (χ2\chi^2χ2) goodness-of-fit test

Linking to the Other Courses

Required Practicals / PAGs

Common Mark-Loss Patterns

Mini-FAQ

Closing

Related Reading

Stay in the loop

The chi-squared ( $\chi^2$ ) goodness-of-fit test

The chi-squared ( $\chi^2$ ) goodness-of-fit test