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18.2 Biodiversity

Syllabus
9700–2028–2029
Topic
18.2
Level
A2

Learning objectives

18.2.1Ecology terms• Terms: ecosystem, niche18.2.2Levels of biodiversity assessment• Biodiversity assessment levels:- Number and range of ecosystems and habitats- Number of species and relative abundance- Genetic variation within species18.2.3Importance of random sampling• Importance of random sampling18.2.4Methods to assess distribution and abundance• Methods to assess distribution and abundance: frame quadrats, line transects, belt transects, mark-release-recapture (Lincoln index)18.2.5Spearman's and Pearson's correlation• Spearman's rank correlation and Pearson's linear correlation: analyse relationships between variables, biotic/abiotic factors18.2.6Simpson's index of diversity (D)• Simpson's index of diversity (D): calculate biodiversity, significance of values

Ecosystem and niche describe different scales

An ecosystem is the interacting system of a community of organisms and the environment they live in. It includes biotic components, abiotic conditions, energy flow and nutrient cycling. A habitat is where a species lives; its niche is the role it plays there.

Ecosystem — a system scale: populations interact with one another and with physical and chemical conditions.
Habitat — a place boundary: where the organism is found.
Niche — a role-and-resource boundary: how the organism obtains energy, uses conditions and interacts with other species and the physical environment.

Niche overlap means two species use some of the same resources or conditions. The more their roles and resource use overlap, the greater the potential for competition; distinct resource use can allow different species to fit into the same ecosystem. This is a relationship-level interpretation, not a biodiversity count or an automatic proof of competition.

Use the terms in this order:

  1. Name the ecosystem as the interacting living-and-non-living system.
  2. Identify the habitat as the place occupied by a species.
  3. Describe the niche through energy use, physical conditions and interactions.
  4. Compare niches when explaining overlap, possible competition or how multiple species can occupy an ecosystem; keep measurement of biodiversity for a separate assessment.

A habitat is not a niche: location alone does not describe a species’ role. Ecosystem, habitat and niche are concepts rather than sampling methods; this card does not introduce quadrats, correlation statistics or Simpson’s index.

Biodiversity has three assessment levels

Biodiversity describes the range and variety of genes, species and habitats within a region. It can be assessed at three linked levels.

  • Ecosystem/habitat diversity — the number and range of different ecosystems or habitats in the area.
  • Species diversity — the number of different species and how evenly individuals are distributed among them.
  • Genetic diversity — the variety of genes and alleles within each species, including differences between populations of the same species.

Species richness is only the number of species. Species diversity also considers evenness: an area can contain many species but still have lower species diversity if most individuals belong to one or two species. Keep these terms separate when interpreting evidence.

Biodiversity can support ecosystem resilience because variation provides more ways for populations and ecosystems to respond to environmental change. This is a general ecological relationship, not a guarantee that every diverse ecosystem resists every disturbance.

Biodiversity is broader than a species count: ecosystem/habitat, species and genetic levels answer different questions. This card defines the assessment levels; random sampling, field methods, correlation tests and Simpson’s index are separate cards.

Random sampling reduces investigator bias

Random sampling gives every possible sampling position an equal chance of selection. This prevents the investigator choosing unusually species-rich, accessible or visually interesting places and therefore reduces selection bias.

  1. Mark out the study area as a grid and assign coordinates.
  2. Use a random-number generator or random-number table to select coordinate pairs.
  3. Place the same sampling unit at each selected position and use the same identification and counting rules.
  4. Take many independent samples across the area and calculate the required abundance or diversity measure.

A less biased sample is more likely to represent the whole area, so an estimate can be generalised with greater confidence. Repetition also reduces the influence of an unusual sampling point and allows variation between samples to be assessed.

Random selection reduces bias; it does not guarantee that one or a few samples are representative. The study still needs an adequate sample size, a clearly defined area and standardised methods.

Match biodiversity methods to organisms and patterns

Choose a method from the organism's mobility and the evidence needed: quadrats estimate abundance in fixed areas, transects show distribution across a gradient, and mark-release-recapture estimates a mobile population.

Method Best use Record
Frame quadrat plants or slow/sessile organisms across an area species identity plus count, frequency or percentage cover in a known area; use random positions and repeats
Line transect presence and distribution along an environmental gradient species touching the line, continuously or at fixed points
Belt transect quantitative change in abundance across a gradient quadrats continuously or at regular intervals along a line
Mark-release-recapture mobile animals in a defined population first catch marked and released; after mixing, count total and marked individuals in a second catch

N = \frac{n_1 n_2}{m_2}

Here NN is estimated population size, n1n_1 is the first sample, n2n_2 is the whole second sample and m2m_2 is marked animals recaptured. If 27 frogs are marked, 33 are caught later and 13 are marked, N=(27×33)/13=68.5N=(27\times33)/13=68.5, reported as 69 animals.

The Lincoln estimate assumes marks are harmless, retained and recognised; marked animals mix fully and are as likely to be recaptured as others; and the population is effectively closed to births, deaths, immigration and emigration between samples. Repeat sampling and standardise effort.

Choose Spearman or Pearson for paired ecological data

Spearman's rank correlation and Pearson's linear correlation test whether paired values of two variables are associated. Either can relate a biotic measurement, such as species abundance, to an abiotic factor, such as altitude or temperature.

Test Use when What the coefficient measures
Spearman's rsr_s data can be ranked; the relationship is monotonic; normality or a linear pattern is not required strength and direction of rank association
Pearson's rr both variables are quantitative, the relationship is approximately linear and assumptions including normality are met strength and direction of linear association
  1. Pair measurements from the same sampling units and plot a scatter graph.
  2. State the null hypothesis: there is no correlation between the variables.
  3. Choose the test, then use the supplied formula to calculate rsr_s or rr.
  4. Compare the magnitude of the calculated coefficient with the critical value for sample size and probability level.
  5. If it meets or exceeds the critical value, reject the null hypothesis and report the direction in biological context; otherwise do not reject it.

Coefficients range from −1-1 to +1+1: the sign gives direction and values nearer either extreme indicate stronger association. Statistical significance is not causation; another variable or the sampling design may explain the pattern.

Simpson's index combines richness and evenness

Simpson's index of diversity, DD, combines species richness with relative abundance. Diversity is higher when more species are present and individuals are distributed more evenly among them.

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

nn = number of individuals of one species.
NN = total number of individuals of all species in the sample.
Calculate (n/N)2(n/N)^2 for every species, add these values, then subtract the sum from 1.

A sample contains 6 individuals of species A, 3 of B and 1 of C, so N=10N=10. D=1−[(6/10)2+(3/10)2+(1/10)2]=1−(0.36+0.09+0.01)=0.54D=1-[(6/10)^2+(3/10)^2+(1/10)^2]=1-(0.36+0.09+0.01)=0.54. A community dominated by one species would have a lower value.

DD ranges from 0 towards 1. A value closer to 1 indicates greater diversity; a value near 0 indicates low diversity or strong dominance. Compare samples collected with compatible methods and effort: a higher DD does not identify which species caused the difference.