CIE AS/A Level Biology -18.2 Biodiversity- Study Notes- New Syllabus
CIE AS/A Level Biology -18.2 Biodiversity- Study Notes- New Syllabus
Ace A level Biology Exam with CIE AS/A Level Biology -18.2 Biodiversity- Study Notes- New Syllabus
Key Concepts:
- define the terms ecosystem and niche
- 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
- explain the importance of random sampling in determining the biodiversity of an area
- describe and use suitable methods to assess the distribution and abundance of organisms in an area, limited to frame quadrats, line transects, belt transects and mark-release-recapture using the Lincoln index (the formula for the Lincoln index will be provided, as shown in the Mathematical requirements)
- use Spearman’s rank correlation and Pearson’s linear correlation to analyse the relationships between two variables, including how biotic and abiotic factors affect the distribution and abundance of species (the formulae for these correlations will be provided, as shown in the Mathematical requirements)
- use Simpson’s index of diversity (D) to calculate the biodiversity of an area, and state the significance of different values of D (the formula for Simpson’s index of diversity will be provided, as shown in the Mathematical requirements)
Ecosystem and Niche
🌱 1. Ecosystem
- Definition: An ecosystem is a community of living organisms (biotic factors) interacting with each other and their physical environment (abiotic factors) in a specific area.
- Key Idea: Includes energy flow and nutrient cycling.
- Example: A pond, rainforest, desert.
🌿 2. Niche
- Definition: A niche is the role or function of a species within its ecosystem, including how it obtains food, interacts with other species, and survives.
- Key Idea: Two species cannot occupy the exact same niche in the same habitat (competitive exclusion principle).
- Example: Bees pollinating flowers, wolves hunting herbivores.
📌 Key Points
| Term | Definition | Example |
|---|---|---|
| Ecosystem | Community of organisms + environment | Pond ecosystem |
| Niche | Role/function of a species in ecosystem | Bee pollination role |
Biodiversity Assessment
🌱 Key Concept
- Biodiversity is the variety of life at all levels of biological organization.
It can be assessed at different levels: ecosystem, species, and genetic.
1. Ecosystem and Habitat Diversity
- Definition: Variety of ecosystems or habitats in a given area.
- Assessment: Count the number of distinct ecosystems and range of habitats.
- Example: Forests, wetlands, coral reefs, grasslands.
2. Species Diversity
- Definition: Variety of species in an ecosystem.
- Assessment:
- Species richness: Number of species present.
- Relative abundance: How common or rare each species is.
- Example: A rainforest with 200 bird species vs. a desert with 20 bird species.
3. Genetic Diversity
- Definition: Variation of alleles within a species.
- Importance:
- Ensures adaptation to changing environments.
- Reduces risk of disease or extinction.
- Example: Different breeds of dogs or varieties of wheat.
📌 Key Points
| Level | What is Assessed | Example |
|---|---|---|
| Ecosystem/Habitat | Number and range of ecosystems | Forest, desert, wetland |
| Species | Number of species + relative abundance | 200 vs 20 bird species |
| Genetic | Variation within species | Dog breeds, wheat varieties |
Importance of Random Sampling in Biodiversity Studies
🌱 Key Concept
- Random sampling is a method used to collect data without bias, giving a true representation of biodiversity in an area.
- Ensures that all species and individuals have an equal chance of being included.
🔹 Reasons for Using Random Sampling
- Reduces bias
- Avoids selecting only easily seen or accessible species.
- Example: Not only counting plants near paths but also deeper in a forest.
- Provides representative data
- Random sampling reflects the true diversity and abundance of species in the area.
- Allows statistical analysis
- Data collected randomly can be used to calculate indices, like species richness and diversity indices.
- Saves time and resources
- Instead of counting all individuals, sampling a subset provides reliable estimates.
🔹 Example
- Using quadrats placed randomly in a meadow to count plant species ensures all microhabitats are represented.
📌 Key Points
- Random sampling avoids bias, ensures accuracy, and allows reliable comparison between areas or over time.
- Essential for monitoring biodiversity and making conservation decisions.
Assessing Distribution and Abundance of Organisms
🌱 Key Concept
- Distribution: Where organisms are found in an area.
- Abundance: Number of individuals of a species in a given area.
- Methods: Use sampling techniques to estimate these reliably.
1. Frame Quadrats
- Use: To study plants or slow-moving organisms in a small area.
- Method:
- Place a square or rectangular frame randomly.
- Count the number of individuals or estimate percentage cover.
- Repeat in multiple random locations.
- Output: Species abundance, frequency, and distribution patterns.
2. Line Transects
- Use: To study how organisms are distributed along a line (e.g., gradient, shorelines).
- Method:
- Stretch a rope or tape along the area.
- Record every organism touching the line at regular intervals.
- Output: Shows distribution along a gradient.
3. Belt Transects
- Use: To study distribution and abundance along a strip.
- Method:
- Combine line transect and quadrats.
- Place quadrats adjacent to each other along the line.
- Count all organisms in each quadrat.
- Output: More detailed than line transect; shows density and distribution.
4. Mark-Release-Recapture (Lincoln Index)
- Use: To estimate the population size of mobile animals.
- Method:
- Capture a sample of animals, mark them harmlessly, and release.
- After some time, recapture a sample.
- Count how many are marked and unmarked.
- Population Estimate Formula (Lincoln Index):
- N = (n₁ × n₂) / n₃
- N = total population size
- n₁ = number of individuals marked in first sample
- n₂ = total number captured in second sample
- n₃ = number of marked individuals recaptured
📌 Key Points
| Method | Best For | What it Measures |
|---|---|---|
| Frame Quadrats | Plants, slow organisms | Abundance, distribution, % cover |
| Line Transect | Gradient studies | Distribution along a line |
| Belt Transect | Gradient studies | Detailed density & distribution |
| Mark–Release–Recapture | Mobile animals | Population size estimation |
Analysing Relationships Between Variables
🌱 Key Concept
- Correlation measures how two variables are related.
- In ecology, it helps determine how biotic or abiotic factors affect species distribution and abundance.
1. Spearman’s Rank Correlation
- Use: For ordinal or non-normally distributed data.
- Purpose: Measures the strength and direction of a monotonic relationship.
- Interpretation:
- rs = +1 → perfect positive correlation
- rs = −1 → perfect negative correlation
- rs = 0 → no correlation
- Example: Relationship between soil pH ranking and plant species richness.
2. Pearson’s Linear Correlation
- Use: For interval or ratio data that are normally distributed.
- Purpose: Measures strength and direction of a linear relationship.
- Interpretation:
- r = +1 → perfect positive linear correlation
- r = −1 → perfect negative linear correlation
- r = 0 → no linear correlation
- Example: Relationship between light intensity (lux) and rate of photosynthesis.
🌿 Applications in Ecology
- Abiotic factors: Temperature, light, soil pH, salinity.
- Biotic factors: Competition, predation, mutualism.
- Use correlation to:
- Predict how environmental changes affect species.
- Identify limiting factors in ecosystems.
📌 Key Points
| Method | Data Type | Use | Example |
|---|---|---|---|
| Spearman’s Rank | Ordinal/non-normal | Monotonic relationships | Soil pH rank vs plant diversity |
| Pearson’s Linear | Interval/ratio | Linear relationships | Light intensity vs photosynthesis rate |
Correlation does not imply causation – it only shows association between variables.
Simpson’s Index of Diversity
🌱 Key Concept
- Simpson’s Index of Diversity (D) measures species diversity in an area, taking into account both species richness and relative abundance.
- Values of D range from 0 to 1.
Formula
- \( D = 1 – \frac{\sum n(n-1)}{N(N-1)} \)
- Where:
- \( n \) = number of individuals of each species
- \( N \) = total number of individuals of all species
Interpretation of D Values
| D Value | Significance |
|---|---|
| Close to 0 | Low diversity – area dominated by few species |
| Close to 1 | High diversity – many species with similar abundance |
🔹 Importance of Simpson’s Index
- Assesses ecosystem health: Higher diversity → more stable and resilient ecosystem.
- Monitors environmental changes: A drop in D may indicate habitat degradation.
- Comparison between areas: Helps identify biodiversity hotspots.
Example
- Meadow with 4 species: 10, 20, 30, 40 individuals.
- Calculate \( D \) using the formula to determine diversity level.