C4.1Theme C — Interaction and interdependence
Populations and communities — IB Biology SL Revision Notes & Topical Questions
10 min read 13 parts Lesson 8 of 9 2 quizzes
Curriculum Equation Key قوانين الرقم الهيدروجيني والاتزان الأيوني - pH & Acid-Base Equilibrium FormulasFast Exam Solution
pH = -log[H⁺] | pOH = -log[OH⁻] | pH + pOH = 14 | [H⁺][OH⁻] = 10⁻¹⁴
Word Equation & Conditions: الرقم الهيدروجيني = -لوغاريتم تركيز أيون الهيدروجين | pH + pOH = 14
Location & Specifications: الاتزان الأيوني، كيمياء 3 ثانوي، التحصيلي، و AP Chemistry.
Lesson summary
C4.1 Populations and communities — IB BIOLOGY SL notes: Describe how populations are sampled and limited, how communities interact, and how association between species is tested.Population = a group of organisms of the same species living in an area at one timeMembers interact an…
- Random sampling
- Systematic sampling
- Sampling error
- Population estimate
- Standard deviation
- Lincoln index
Part 1 of 11Populations and sampling
Population
Population a group of organisms of the same species living in an area at one time
- Members interact and can breed together.
- Populations isolated from each other cannot exchange genes and may diverge.
Levels
- Levels individual, population, community, then ecosystem
Sampling
- Sampling measuring small samples that represent the whole, because counting every organism is rarely possible
Random sampling
- Random sampling sample positions are chosen at random, which avoids bias
- Lay a grid over the area and use random number coordinates.
- It is best when the area is reasonably uniform.
- Choosing interesting spots would overestimate the number of species.
Systematic sampling
- Systematic sampling sample positions at fixed intervals, so no section is missed by chance
- A transect line from a feature such as a river or from shore to dunes shows the effect of an environmental feature.
Sampling error
Sampling error the difference between an estimated and the true population size
- A random sample may miss an area with no individuals or one with many.
- Good design and a large enough sample reduce the error.
- Methods must be reported so that readers can evaluate the error.
Part 2 of 11Quadrats and data
Quadrat
- Quadrat a frame of known area used for sessile organisms
- A 1 m2 quadrat suits herbaceous plants or limpets.
- A 400 m2 area marked with string suits trees.
- Quadrats are placed randomly or systematically along a transect.
Data recorded
- Presence or absence of a species.
- Frequency, the number of individuals in the quadrat.
- Abundance on the ACFOR scaleabundant, common, frequent, occasional, rare or none.
- Percentage cover, which is easier if the quadrat is divided into smaller squares.
Population estimate
Population estimate mean count per quadrat × total area / quadrat area
Mean
- Mean the average count per quadrat
Standard deviation
- Standard deviation shows spread about the mean
- A small SD means little variation.
- A large SD means a patchy distribution.
Part 3 of 11Mark-release-recapture
- Use
- estimating populations of motile organisms
1
Catch as many individuals as possible, count them (M) and mark them harmlessly.
2
Release them and allow time for random mixing.
3
Catch a second large sample (N) and count the marked individuals recaptured (R).
4
Calculate the Lincoln index.
Lincoln index
- Lincoln index population size = M × N / R, rounded to a whole organism
Assumptions
- The marked individuals mix fully with the population.
- Marking does not affect survival, for example by making them more visible to predators.
- The marks stay visible throughout the sampling.
- The population stays the same size, with no births, deaths or migration.
Part 4 of 11Carrying capacity and feedback
Carrying capacity (K)
Carrying capacity (K) the maximum number of individuals of a species that an ecosystem can support
- The population levels off at K.
Abiotic limits
- Abiotic limits light, temperature and soil minerals
Biotic limits
- Biotic limits competition for resources, predation and disease use up energy that would go to growth and reproduction
Population density
Population density the number of individuals per unit area
- Density-dependent factors act more strongly at high density, such as disease, competition and predation.
- Density-independent factors have the same effect at any density, such as a flood.
Negative feedback
- Negative feedback density-dependent factors keep a population near K
- Above K, survival and reproduction fall, so the population decreases.
- Below K, survival and reproduction rise, so the population increases.
- The population fluctuates around K.
Positive feedback
- Positive feedback more individuals give more reproduction and further growth until a density-dependent factor limits it
Part 5 of 11Predators, prey and population control
Predator-prey cycle
- Predators increase when prey is plentiful.
- Prey decreases as predators increase.
- Predators then decrease because food is short.
- Prey increases when predators fall and the cycle repeats.
- The Canada lynx and snowshoe hare is a famous example, and real systems have many other species.
Top-down control
- Top-down control predators or herbivores limit a population
- A fall in foxes can raise rabbit numbers and reduce grass growth.
- Predators also change prey behaviour, diet and where prey spend time.
Bottom-up control
- Bottom-up control the supply of resources such as light or nutrients limits a population
Dominant control
- Dominant control one type usually dominates at a time, and overfishing can switch the sea to top-down control
Allelopathy
Allelopathy secretion of harmful secondary metabolites that reduce the survival of competitors
- Garlic mustard secretes sinigrin, which reduces seed germination and root growth in other plants.
- Himalayan balsam and some others release chemicals into the soil.
- Some plants store chemicals in leaves that are released when the leaves decay.
Antibiotic secretion
- Antibiotic secretion an allelopathic strategy in Penicillium and some bacteria that reduces competition
Part 6 of 11Population growth curves
Sigmoid growth curve
- Sigmoid growth curve three phases
- Exponential phaseno limiting factors, so both numbers and growth rate increase.
- Transition phaselimiting factors act and the growth rate slows.
- Plateau phasedeath rate equals birth rate at carrying capacity, with small fluctuations.
Example
- Antarctic fur seals recovered after hunting, though the curve is idealised and later declined with climate change
Model
- Model the sigmoid curve is an idealised model and few real populations follow it exactly
Exponential growth
- Exponential growth growth rate is proportional to the number of individuals
- On a log scale on the y-axis an exponentially growing population plots as a straight line.
- A log10 scale shows 1, 2, 3 as 10, 100, 1000.
Yeast model
- Yeast model the turbidity of a broth culture, measured with a colorimeter or turbidity meter, estimates cell numbers over time
Duckweed model
1
Place a few duckweed fronds in a dish with distilled water and liquid fertiliser.
2
Keep it in bright light but out of direct sunlight.
3
Count the fronds after one week.
4
Repeat weekly for six weeks, topping up with distilled water.
5
Plot the counts to show the growth curve.
Part 7 of 11Intraspecific and interspecific relationships
Intraspecific and interspecific relationships
Community
Community populations of different species living and interacting in the same area
- A community interacting with its abiotic environment forms an ecosystem.
Intraspecific cooperation
- Intraspecific cooperation individuals of one species benefit each other
- Orcas hunt together, meerkats share watching and care roles, and ants build nests together.
Intraspecific competition
- Intraspecific competition individuals of the same species need the same resources
- Plants compete for light, minerals, water and space.
- Animals compete for food, mates and territory, as red deer males and robins do.
- Competition need not involve visible conflict.
| Relationship | Species A | Species B | Example |
|---|---|---|---|
| Herbivory | Gains | Plant damaged | Cattle grazing grass |
| Predation | Predator gains | Prey killed | Lions hunting zebra |
| Interspecific competition | Harmed | Harmed | Red and grey squirrels |
| Mutualism | Gains | Gains | Coral polyp and zooxanthellae |
| Parasitism | Parasite gains | Host harmed | Fleas on mammals, mistletoe on trees |
| Pathogenicity | Pathogen gains | Host diseased | Mycobacterium tuberculosis |
Part 8 of 11Mutualism examples
Legume root nodules
- Rhizobium bacteria fix nitrogen gas into ammonia and then nitrates
- The plant uses nitrates for proteins and nucleic acids.
- The bacteria gain carbohydrates from photosynthesis.
Mycorrhizae
- Mycorrhizae fungal hyphae greatly increase the root surface area for water and minerals
- Orchid seeds gain nutrients for germination from mycorrhizae.
- Some orchids cannot photosynthesise and rely on fungi to break down dead matter, benefiting only when the orchid dies.
Corals
- Corals polyps give shelter and the zooxanthellae algae give carbohydrates
- Polyps secrete calcium carbonate that forms the reef.
Part 9 of 11Invasive species and testing competition
Invasive species
Invasive species a non-native species that harms the environment it is introduced to
- Humans bring them by trade, escapes, accidental transport such as rats on ships, or biological control.
- They have no natural predators or competitors, so numbers rise rapidly.
- They can displace natives, prey heavily on them or bring new diseases.
- Grey squirrels have largely outcompeted red squirrels in the UK.
Endemic species
Endemic species a species found in only one place, so local extinction means total extinction
- More than 10% of Australia's endemic mammals have gone extinct since European settlement, many due to foxes and cats.
Testing interspecific competition
- If removing one species changes the distribution of the other, competition is likely to have occurred, but this does not prove it.
- Cultures of bacteria grown alone and together can be compared in the lab.
- In the field, take random quadrats then remove one species from a small area and watch the other.
Hypotheses can be tested in the laboratory with good control or in the field with more realism but less control
Part 10 of 11Chi-squared test for association
Association
- Association species in a symbiosis tend to occur together, a positive association, and competitors tend to be apart, a negative association
- Independent species show no association other than by chance.
Null hypothesis
- Null hypothesis there is no association between the distributions of the two species
1
Sample many random quadrats and record presence or absence of each species.
2
Build a 2 × 2 contingency table of observed values (both, one, the other, neither).
3
Calculate the row, column and grand totals.
4
Calculate each expected value as row total × column total / grand total.
5
Calculate Σ(O - E)2 / E.
6
Find the degrees of freedom as (columns - 1) × (rows - 1), which is 1 for a 2 × 2 table.
7
Use p = 0.05 and a critical value table, which gives 3.84 for 1 degree of freedom.
8
If the chi-squared value is larger than the critical value, reject the null hypothesis because there is a significant association.
- Interpretation
- a significant result shows a likely important factor but does not prove species depend on each other
Part 11 of 11More from the specification
More from the specification
Sigmoid population growth curves
- Exponential (logarithmic) growth decelerates as carrying capacity (K) is approached due to density-dependent environmental resistance.
Statistical significance testing
- Using chi-squared or t-tests to evaluate ecological association null hypotheses, accepting statistical significance when p < 0.05.
Ecological niche and habitat
- The precise abiotic habitat conditions and biotic interactions that determine a species' distribution and survival.
Intertidal distribution patterns
- Zonation of rocky shore organisms reflects differential tolerance to desiccation and wave action.
- (such as dog whelks and limpets)
Habitat
- The place where an organism lives.
Statistically significant
- A difference with a probability of less than 5% of being due to chance.
Logarithmic scale
- Scale in which each interval is a multiple of the last
Key terms
| Term | Meaning |
|---|---|
| Carrying capacity | The maximum population size of a species that an ecosystem can support. |
| Density-dependent factor | A factor whose effect on a population depends on the population density. |
| Lincoln index | An estimate of population size, M × N / R, from mark-release-recapture. |
| Sigmoid growth curve | An S-shaped curve with exponential, transition and plateau phases. |
| Mutualism | A relationship between two species in which both benefit. |
| Invasive species | A non-native species that harms the ecosystem it is introduced into. |
| Allelopathy | The release of chemicals that harm competing organisms. |
| Chi-squared test | A statistical test of whether observed results differ significantly from expected results. |
Avoid these mistakes
1
Saying a larger sample removes all sampling error — it reduces it but a sample never matches the whole population exactly
2
Saying the Lincoln index works whatever happens in the population — it assumes no births, deaths or migration
3
Saying the population stops growing because it is full — limiting factors slow growth until birth and death rates balance at K
4
Saying a significant chi-squared result proves that the species depend on each other — it shows an association only
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