MASTER GRADUATE-LEVEL ECOLOGY QUIZLET

# SECTION 1: SPECIES INTERACTIONS

Mutualism

Interaction between species that benefits both (e.g., bees and flowers).

Commensalism

Interaction where one species benefits, other unaffected (e.g., barnacles on whales).

Parasitism

Interaction where one species benefits, other harmed (e.g., tapeworms in intestines).

Predation

One species consumes another (e.g., lion preying on zebra).

Competition

Species compete for limited resources; can be interspecific or intraspecific.

Competition coefficient (α)

In Lotka–Volterra competition, α = effect of species 2 on species 1 relative to species 1 on itself.

Lotka–Volterra competition model

dN₁/dt = r₁N₁ (1 - (N₁ + α₁₂N₂)/K₁), dN₂/dt = r₂N₂ (1 - (N₂ + α₂₁N₁)/K₂)

Example: competition

If K₁ = 100, N₂ = 20, α₁₂ = 0.5 → effective competition = 20 × 0.5 = 10; N₁ limited by 10 individuals.

Facilitation

Positive effect of one species on another without direct resource exchange.

Example: facilitation

Nurse plants help seedlings establish in deserts.

Allelopathy

Chemical inhibition of one species by another (plants releasing toxins into soil).

Apparent competition

Two species negatively affect each other indirectly via shared predator.

Example: apparent competition

Species A increases predator → predator increases → Species B declines.

# SECTION 2: POPULATION DYNAMICS

Exponential growth

dN/dt = rN; continuous growth under unlimited resources.

Logistic growth

dN/dt = rN(1 - N/K); growth limited by carrying capacity K.

Carrying capacity (K)

Maximum sustainable population size in a habitat.

Intrinsic growth rate (r)

Maximum per capita growth rate of a population.

Discrete-time growth

Nₜ₊₁ = Nₜ + rNₜ or Nₜ₊₁ = Nₜ e^(rΔt)

Density dependence

Population growth affected by population density (e.g., competition, predation).

Allee effect

Reduced growth at low population densities.

Lotka–Volterra predator-prey model

dN/dt = rN - aNP, dP/dt = baNP - mP; N = prey, P = predator.

Functional response

Type I: linear; Type II: saturating; Type III: sigmoidal.

Quantitative example: logistic

If r = 0.5, K = 100, N = 50 → dN/dt = 0.5 × 50 × (1 - 50/100) = 12.5

Quantitative example: predator-prey

If a = 0.01, N = 200, P = 10 → predation rate = 0.01 × 200 × 10 = 20 prey per unit time.

# SECTION 3: COMMUNITY STRUCTURE

Species richness

Number of species in a community.

Species evenness

Relative abundance distribution of species.

Diversity index

Shannon: H' = -Σ(pᵢ ln pᵢ); Simpson: D = Σ pᵢ²

Quantitative example: Shannon

If species proportions = [0.5, 0.3, 0.2] → H' = -[0.5ln0.5 + 0.3ln0.3 + 0.2ln0.2] ≈ 1.03

Rank-abundance curve

Plots species abundance vs. rank; visualizes evenness.

Beta diversity

Change in species composition between habitats.

Community assembly rules

Processes that determine species composition (e.g., competition, environmental filtering).

Niche differentiation

Species coexist by using resources differently.

Example: niche differentiation

Warblers feeding at different canopy levels.

Neutral theory

Species equivalence and stochastic processes drive community structure.

Island biogeography

S = cA^z; S = species richness, A = area, z ≈ 0.2–0.35

Species-area relationship

Number of species increases with habitat area.

Extinction debt

Species expected to go extinct due to past habitat loss, even if still present.

# SECTION 4: COMMUNITY NETWORKS & FOOD WEBS

Community network

Representation of species and their interactions.

Food web

Network of feeding relationships; shows energy flow.

Trophic level

Position in food chain (producer, consumer, etc.).

Primary producer

Autotrophs converting energy into biomass.

Primary consumer

Herbivores feeding on producers.

Secondary consumer

Carnivores feeding on herbivores.

Tertiary consumer

Carnivores feeding on secondary consumers.

Omnivore

Species feeding across multiple trophic levels.

Link (L)

Feeding interaction between two species.

Connectance (C)

C = L / N²; proportion of realized links.

Example: connectance

If N = 10, L = 30 → C = 30 / 100 = 0.3

Linkage density

Average links per species; LD = L / N

Example: linkage density

LD = 30 / 10 = 3

Interaction strength

Effect of one species on another’s growth/abundance.

Keystone species

Disproportionate effect relative to abundance (e.g., Pisaster sea star).

Ecosystem engineer

Species modifying habitat (e.g., beavers creating wetlands).

Trophic cascade

Predator indirectly affects producers through herbivores (wolves → elk → vegetation).

Top-down control

Predators regulate community structure.

Bottom-up control

Nutrients or producers regulate structure.

Interaction matrix

aᵢⱼ = effect of j on i; used to assess stability.

Stability criterion

All eigenvalues of interaction matrix have negative real parts → stable.

May’s complexity–stability paradox

Increased species richness/connectance reduces stability in random networks unless interactions weak.

Modularity

Network clusters with stronger within-module interactions → stability.

Nestedness

Generalists interact with subsets of specialists → robustness.

Portfolio effect

Weak links buffer community fluctuations.

Allometric scaling

Interaction strength/metabolic rate scale with body size.

Energy transfer efficiency

~10% per trophic level.

Detrital food web

Includes decomposers; essential for nutrient cycling.

Simulation models

Explore stability under varying S, C, σ.

Network robustness

Proportion of species remaining after sequential removals.

Functional redundancy

Multiple species performing similar roles buffer against extinctions.

Alternative stable states

Multiple community configurations possible (e.g., coral reef shifts).