explain that biodiversity can be assessed at different levels, including: the number and range of different ecosystems and habitats, the number of species and their relative abundance, the genetic variation within each species

Biodiversity – Assessment at Different Levels

Definition (Cambridge AS & A Level 9700, Topic 18) – Biodiversity is the variety of life at all levels of biological organisation: ecosystems (and habitats), species, and genetic variation within species. It underpins ecosystem services and is a key indicator of ecological health.

Why assess biodiversity at several levels?

• Each level provides complementary information. A region may have many habitats but few species, or many species but low genetic variation.
• Integrated assessments help set conservation priorities, monitor the effectiveness of management actions and satisfy the syllabus’s AO3 (evaluation of investigations).

1. Ecosystem & Habitat Diversity (Ecological level)

• What is measured: number, type and spatial extent of ecosystems and habitats within a defined area.
• Typical indicators:

  • Habitat (ecosystem) richness – count of distinct habitat types.
  • Patch‑size distribution and total area of each habitat.
  • Fragmentation indices – e.g. edge‑to‑core ratio, nearest‑neighbour distance.

• Common methods:

  • Remote sensing – satellite imagery, aerial photographs.
  • Geographic Information Systems (GIS) – mapping, area calculation, landscape metrics.
  • Field surveys – habitat classification using standard keys (e.g. UK NVC, Braun‑Blanquet).

Link‑in Box (AO1 – Cell Structure & Membranes)

Habitat quality often depends on soil‑water interactions, which are governed by cell‑membrane transport processes (Topic 3). Understanding how nutrients move through plant root cells helps explain why some habitats are more productive than others.

2. Species Diversity (Species level)

• Components:

  • Species richness (S) – total number of species recorded.
  • Species evenness – how equally individuals are distributed among the species.

• Quantitative indices:

  • Relative abundance of species \(pi = \frac{ni}{N}\) where \(n_i\) = individuals of species i, \(N\) = total individuals.
  • Shannon–Wiener index

    \[ H' = -\sum{i=1}^{S} pi \ln p_i \]

  • Simpson’s index

    \[ D = \sum{i=1}^{S} pi^{2} \] (diversity often expressed as \(1-D\)).

  • Margalef’s richness index \[ R = \frac{S-1}{\ln N} \] – useful for comparing sites with different sample sizes.

• Sampling techniques (AO2):

  • Quadrat sampling (plants, sessile invertebrates).
  • Transect walks and line‑intercept methods (grassland, marine benthos).
  • Pitfall traps, sweep nets, and light traps (mobile invertebrates).
  • Capture‑mark‑recapture (vertebrates).
  • Point counts (birds, bats).

• Design considerations (AO3):

  • Random vs. systematic placement of quadrats/transects.
  • Number of replicates – power analysis can be used to estimate the sample size needed to detect a given difference in \(H'\) with 95 % confidence.
  • Seasonality – repeat surveys in different seasons to capture phenological changes.
  • Detection probability – use double‑observer or distance‑sampling methods where appropriate.

Worked Example – Shannon–Wiener index

1. Total individuals \(N = 100\).
2. Relative abundances: \(p1=0.40,\; p2=0.30,\; p3=0.20,\; p4=0.10\).
3. Apply the formula

   \[

   H' = -(0.40\ln0.40 + 0.30\ln0.30 + 0.20\ln0.20 + 0.10\ln0.10)

   = 1.279\; \text{(bits)}

   \]

4. Interpretation – moderate diversity; dominance by the two grasses reduces evenness, but the presence of two wildflowers adds some balance.

Statistical Treatment (AO2)

• Calculate 95 % confidence intervals for \(H'\) using bootstrap resampling (e.g., 1 000 replicates).
• Use a two‑sample t‑test or Mann‑Whitney U test to compare \(H'\) between a disturbed and an undisturbed site.
• Report effect size (Cohen’s d) to indicate ecological relevance.

Link‑in Box (AO1 – Enzyme Kinetics)

Species‑level diversity can affect ecosystem processes such as decomposition. Enzyme activity (Topic 5) in soils is often measured to link species composition with rates of organic‑matter breakdown.

3. Genetic Diversity (Genetic level)

• What is measured: variation in DNA sequences among individuals of a single species.
• Key parameters:

  • Allelic richness – number of different alleles at a locus.
  • Observed heterozygosity (\(H_O\)) – proportion of heterozygotes.
  • Expected heterozygosity (\(H_E\)) – probability that two randomly drawn alleles differ (gene diversity).
  • Nucleotide diversity (\(\pi\)) – average proportion of nucleotide differences between all possible pairs of sequences.

• Laboratory methods (AO2):

  • Microsatellite (SSR) analysis.
  • Single‑nucleotide polymorphism (SNP) genotyping.
  • AFLP, RAPD, and DNA sequencing (e.g., mitochondrial COI barcoding).
  • Population‑genetics software – GenAlEx, Arlequin, STRUCTURE.

• Population‑genetics principle (AO2): Hardy–Weinberg equilibrium

  \[ p^{2}+2pq+q^{2}=1 \]

  Deviation from HWE can indicate inbreeding, genetic drift or selection – all relevant to conservation.

Link‑in Box (AO1 – DNA Replication & Mutation)

Genetic diversity arises from DNA replication fidelity (Topic 6) and mutation processes. Understanding the molecular basis of mutation helps explain why some populations retain higher variability.

4. Integrating the Three Levels – A Hierarchical View

5. Threats to Biodiversity & Conservation Strategies (AO3)

Major Threats (Cambridge syllabus)

• Habitat loss & fragmentation (deforestation, urban expansion).
• Invasive alien species out‑competing natives.
• Over‑exploitation (over‑fishing, hunting).
• Pollution (eutrophication, plastics, acid rain).
• Climate change (temperature shifts, sea‑level rise).

Conservation Tools

Case‑Study Box – Coral‑Reef Bleaching (2020‑2022)

• Rising sea‑surface temperatures caused extensive bleaching of the Great Barrier Reef.
• Consequences: sharp decline in coral species richness, loss of associated fish and invertebrate diversity, reduced genetic diversity in surviving colonies.
• Conservation response: selective breeding of heat‑tolerant corals, stricter fishing limits, reduction of local stressors (e.g., agricultural runoff).

6. Practical Investigation – Assessing Species Diversity (AO2 & AO3)

1. Design a quadrat survey – Choose a homogeneous habitat, lay out a 1 m × 1 m quadrat, record the number of individuals of each species. Repeat in at least 8 randomly placed quadrats to ensure adequate replication.
2. Data handling – Compile counts into a spreadsheet, calculate total individuals (N) and relative abundances (\(p_i\)).
3. Calculate diversity indices – Compute \(H'\), \(1-D\) and Margalef’s R for each quadrat. Use bootstrap resampling (1 000 replicates) to obtain 95 % confidence intervals.
4. Statistical comparison – Apply an independent‑samples t‑test (or Mann‑Whitney if data are non‑normal) to test for differences between a disturbed site and a control site.
5. Evaluation of errors –

   • Mis‑identification of species (mitigated by using a reliable field guide and, where possible, DNA barcoding).
   • Unequal detection probability (addressed by standardising search time and using double‑observer methods).
   • Edge effects in small quadrats (reduced by increasing quadrat size or applying a buffer zone).
   • Seasonal variation (minimised by sampling in the same phenological stage for all sites).

6. Conclusion & recommendations – Summarise the ecological significance of any observed differences and suggest management actions (e.g., habitat enhancement, creation of corridors).

7. Comparative Summary of Biodiversity Assessment

8. Road‑Map to the Full Cambridge Biology Syllabus (AS & A Level)

These “link‑in” boxes and the roadmap ensure that students see how biodiversity connects with the wider biological curriculum, satisfying AO1 (knowledge), AO2 (application) and AO3 (evaluation) across the whole Cambridge 9700 syllabus.