Populations & Communities — Practice · Grade 10 Science

Chapter: Ecosystems & Conservation Decisions

What this practice covers

By the end of Populations & Communities you should be able to:

11 questions, multiple choice, numeric and written answer, each with a worked explanation.

Vocabulary used: population, exponential growth, logistic growth, carrying capacity, limiting factor, symbiosis.

Problem 1

All the members of a single species living and interbreeding in the same area make up a
  1. community
  2. biome
  3. trophic level
  4. population
Answer and explanation

population

A population is one species in one area; a community is all the different populations together.

Problem 2

A bacterial colony starts with 200 cells and doubles every hour. Growing exponentially, how many cells are there after 4 hours?
Answer and explanation

3200 cells

N = 200 × 2⁴ = 200 × 16 = 3,200 cells.

Problem 3

On a logistic (S-shaped) growth curve, the population finally levels off at
  1. the carrying capacity
  2. twice the carrying capacity
  3. an ever-increasing value
  4. zero
Answer and explanation

the carrying capacity

Logistic growth flattens out at the carrying capacity (K), where birth and death rates roughly balance.

Problem 4

A tapeworm lives inside a dog's intestine, absorbing nutrients from the dog's food and gradually weakening the dog. This symbiotic relationship is an example of
  1. commensalism
  2. parasitism
  3. competition
  4. mutualism
Answer and explanation

parasitism

In parasitism one species benefits (the tapeworm) at the direct expense of the other (the dog).

Problem 5

Explain the difference between a density-dependent and a density-independent limiting factor, and give one example of each.
Answer and explanation

A density-dependent limiting factor grows stronger as a population becomes more crowded — for example, competition for food, disease, or predation. A density-independent limiting factor affects a population regardless of its density — for example, a hard freeze, a flood, or a wildfire. Density-dependent factors tend to pull a population back toward its carrying capacity, while density-independent factors can strike no matter how sparse or crowded the population is.

Problem 6

A population starts at 200, gains 30 births and 10 immigrants, and loses 20 deaths and 5 emigrants. Find the new size. Explain the reasoning in your own words.
Answer and explanation

215 individuals under the stated accounting.

Net change=30+10−20−5=15.

New size=200+15=215.

Response criteria

  • Use the stated conditions.
  • Show the evidence or calculation.
  • Explain the conclusion and any stated limitation.

Problem 7

A population gains 40 births and loses 55 deaths with no migration. What is net change? Show the reasoning, not just the conclusion.
Hints

Include both migration flows, not just births and deaths.

Answer and explanation

−15 individuals.

Problem 8

Why can density-dependent disease regulate growth differently from a sudden storm?
Hints

State what the supplied observations or conditions establish, and separate that from any assumption.

Answer and explanation

Transmission may increase with crowding, while a storm can affect populations regardless of density, depending on the event.

Problem 9

A loss can reduce abundance without regulating it in the same wayA loss can reduce abundance without regulating it in the same wayPer-individual loss rate (model units)02460204060Population density (model units)Density-dependent exampleDensity-independent example
Original selected loss-rate/density models, not universal storm or infection behavior.
Interpret the supplied visual. Why is a larger total number lost not alone evidence of density dependence?
Answer and explanation

More individuals can experience the same per-individual risk; density dependence concerns how that risk or effect changes with density.

A density-dependent effect changes per-individual impact with density, as selected competition or infection processes can. A density-independent event can affect abundance without that same dependence, though its final consequences still interact with conditions. A storm killing organisms does not automatically create feedback that restores a fixed population. Define the per-individual effect and compare densities under matched conditions. Changes in total losses can occur simply because more individuals are exposed even when the per-individual rate is unchanged.

More individuals can experience the same per-individual risk; density dependence concerns how that risk or effect changes with density.

Response criteria

  • Read the structures, axes, directions and units correctly.
  • Connect the evidence with the biological mechanism.
  • Respect stated model assumptions and distinguish an observation from a further inference.

Problem 10

A population starts at 80, with 20 births, 12 deaths, 9 immigrants and 5 emigrants. Find final count, change and percentage change.
Answer and explanation

Final count is 80+20−12+9−5 = 92. Change is +12, or 12/80×100 = 15%, under the stated boundary and interval.

Final count is 80+20−12+9−5 = 92. Change is +12, or 12/80×100 = 15%, under the stated boundary and interval.

Response criteria

  • Use the stated measurements or conditions, with correct units.
  • Connect the result to the biological mechanism or evidence relationship.
  • Identify the assumption, model limit or further evidence requested.

Problem 11

OpenSciEd graph titled observed Masai giraffe numbers, 1977–2015 in Kenya, with a high early peak, lower later counts and sharp fluctuations; its displayed data credit names IUCN and Muller et al. (2018).
Historical observed Masai giraffe numbers in Kenya, OpenSciEd 7.5; retain the graph’s displayed IUCN/Muller et al. (2018) annotation. Historical Masai giraffe observations in Kenya · OpenSciEd · 7.5 Ecosystem Dynamics, Lesson 10 graph; data source retained in image, source, CC BY 4.0. Figure excerpt rendered from the PDF and resized for the web.
Compare the high early peak with the generally lower later counts, and identify one subinterval with an increase. Does every pair of endpoints show a decline? Explain why neither an increase nor a decline alone identifies a unique cause. State two details about survey methods/context that would help interpret the counts.
Answer and explanation

The high early peak exceeds 1,000 observed giraffes, while most later plotted counts are much lower. The record is not monotonic: a valid rise occurs just after the very low count near 2000. Trend descriptions depend on the chosen endpoints, so the early peak-to-later decline is not a claim that every possible interval declines. Neither a rise nor a decline isolates causality. Comparable survey area/effort, detection methods, dates/season and habitat or population movement information help interpret the counts.

Read the named organism, region, years and count axis.

Compare both a long interval and a specific rising segment rather than choose one convenient section.

Request sampling/detection and biological context before assigning a cause.

Response criteria

  • Compare the high early peak with later values, identify a rising segment and explain why endpoint choice matters.
  • Retain the organism/region/interval and observed-count meaning.
  • State two relevant monitoring details and a causal limitation.

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