Population Characteristics:

1. POPULATION SIZE (N) Definition: • Total number of individuals in a population • Absolute count

   Examples: • 500 deer in a forest • 2,000 bacteria in a culture • 7.8 billion humans on Earth

   Factors influencing size: • Birth rate (natality) • Death rate (mortality) • Immigration (individuals moving in) • Emigration (individuals moving out)

   Equation: ΔN = (B - D) + (I - E) where B=births, D=deaths, I=immigration, E=emigration

2. POPULATION DENSITY Definition: • Number of individuals per unit area or volume • N / area

   Examples: • 50 trees per hectare • 100 fish per cubic meter • 10,000 people per square mile

   Factors influencing density: • Resource availability (more resources → higher density) • Competition (limits density) • Predation (reduces density) • Disease (spreads faster at high density) • Habitat quality • Social behavior (territorial species have lower density)

   Measurement methods: • Direct count (small populations) • Sampling + extrapolation • Mark-recapture method • Indirect indicators (tracks, nests, etc.)

3. DISPERSION PATTERNS How individuals are spatially distributed

   a) CLUMPED (Most Common) Pattern: Individuals grouped together in patches

   Appearance: • • • • • • • • • •

   Causes: • Resources clumped (water holes, food patches) • Social behavior (herding, schooling, flocking) • Offspring stay near parents • Limited dispersal ability

   Examples: • Schools of fish • Herds of elephants • Plants near water source • Humans in cities

   Advantages: • Protection from predators (safety in numbers) • Cooperative hunting/foraging • Mate finding easier • Thermoregulation (huddling)

   Disadvantages: • Increased competition • Disease spreads faster • Easier for predators to find

   b) UNIFORM (Rare) Pattern: Individuals evenly spaced

   Appearance: • • • • • • • • • • • •

   Causes: • Territorial behavior • Competition for space • Allelopathy (plants release chemicals inhibiting neighbors) • Direct antagonistic interactions

   Examples: • Territorial birds (nesting sites) • Creosote bush in desert (allelopathy) • Penguin nests (pecking distance apart) • Trees in planted orchards

   Advantages: • Reduced competition • Guaranteed space/resources • Reduced disease transmission

   Disadvantages: • Energy spent defending territory • May be too spread out for mating

   c) RANDOM (Least Common) Pattern: No predictable pattern

   Appearance: • • • • • • • •

   Causes: • Resources distributed randomly • No strong social interactions • No strong competition for space • Random dispersal

   Examples: • Dandelions in a field (wind dispersal) • Forest trees (some species) • Rare in nature - requires very specific conditions

   Requirements: • Uniform environment • No social behavior • Random seed dispersal • No territoriality

Analyzing Dispersion: • Statistical tests compare observed to expected random distribution • Variance-to-mean ratio:

• Ratio = 1: random
• Ratio > 1: clumped
• Ratio < 1: uniform

Ecological Significance: • Affects population dynamics • Influences sampling methods • Indicates social structure • Reflects resource distribution • Important for conservation planning

Key Insight: Dispersion patterns are not random - they reflect underlying ecological processes (resource availability, social behavior, competition)!

Mark-Recapture Method (Lincoln-Petersen Index):

Purpose: • Estimate population size when direct counting impossible • Used for mobile animals • Non-destructive sampling

Procedure:

1. CAPTURE • Capture a sample of individuals • Mark them (tags, bands, paint, etc.) • Record number marked (M)

2. RELEASE • Release marked individuals back into population • Allow time to mix randomly with population • Marked individuals redistribute

3. RECAPTURE • After sufficient time, capture another sample • Record total captured (C) • Record number of marked individuals recaptured (R)

4. CALCULATE • Use proportion to estimate total population

Formula: N = (M × C) / R

Where: • N = total population size (estimate) • M = number marked in first capture • C = total number in second capture • R = number of marked individuals recaptured

Logic: The proportion of marked individuals in the second sample should equal the proportion of marked individuals in the entire population.

R/C = M/N

Solving for N: N = (M × C) / R

SOLVING THE PROBLEM:

Given: • M = 50 fish marked initially • C = 100 fish captured in second sample • R = 10 marked fish recaptured

Calculation: N = (M × C) / R N = (50 × 100) / 10 N = 5,000 / 10 N = 500 fish

Estimated population size: 500 fish

Interpretation: • 10 out of 100 recaptured were marked • That's 10% marked in second sample • If 10% of total population is marked • And we marked 50 fish • Then total population = 50 / 0.10 = 500 fish

Assumptions (Important!):

1. CLOSED POPULATION • No births, deaths, immigration, emigration • Population size constant between captures • If violated: underestimate (deaths) or overestimate (births/immigration)

2. MARKS DON'T AFFECT SURVIVAL • Marked individuals survive at same rate as unmarked • Marks don't make individuals more/less vulnerable to predators • If marks increase mortality: overestimate population

3. MARKS DON'T AFFECT CATCHABILITY • Marked individuals equally likely to be recaptured • No "trap-happy" or "trap-shy" behavior • If trap-shy: overestimate • If trap-happy: underestimate

4. RANDOM MIXING • Marked individuals disperse randomly through population • No segregation of marked/unmarked • Sufficient time between captures for mixing • If inadequate mixing: biased estimate

5. MARKS RETAINED • Marks don't fall off or fade • All marks recognizable in recapture • If marks lost: overestimate population

6. SAMPLING IS RANDOM • All individuals have equal capture probability • No bias toward certain sizes, sexes, ages

Violations and Corrections:

• Multiple recaptures: More accurate Use Schnabel method (multiple mark-recapture events)

• Mark loss: Use double-marking Two types of marks; estimate loss rate

• Population change: Use Jolly-Seber method Allows for open populations (births, deaths, migration)

Applications:

1. Fish populations • Tag fish with numbered tags • Recapture via fishing

2. Small mammals • Ear tags, toe clipping • Trap grids

3. Birds • Leg bands with unique numbers • Recapture at banding stations

4. Large mammals • Photo identification (unique markings) • Example: Whale flukes, leopard spots

5. Insects • Fluorescent powder • Light traps for recapture

Advantages: • Non-destructive • Relatively simple • Cost-effective • Works for mobile populations

Disadvantages: • Requires assumptions • Labor-intensive • May stress animals • Subject to bias if assumptions violated

Key Insight: Mark-recapture uses sampling and probability to estimate population size when complete census is impossible. Accuracy depends on meeting key assumptions!

Survivorship Curves: Graphical representation of survival rates across different ages in a population.

Graph axes: • X-axis: Age (% of maximum lifespan) • Y-axis: Number of survivors (log scale) or % surviving

THREE TYPES:

TYPE I - HIGH EARLY SURVIVAL

Curve shape: │ │──────── │
│
│ ╲ │ ╲╲ └──────────────╲╲ Young → Old

Characteristics: • High survival through early and middle life • Most mortality in old age • Low juvenile mortality • Deaths mainly from aging/senescence • Long lifespan for most individuals

Examples: • Humans (developed countries) • Large mammals (elephants, whales) • Gorillas, chimpanzees • Some large herbivores (bison, rhinos)

Reproductive Strategy (K-selected): • FEW offspring • HIGH parental care • Large offspring size • Slow development • Late maturation • Repeated reproduction over lifetime • Invest heavily in each offspring • Stable environments • Population near carrying capacity

Example: Humans • Usually 1 offspring at a time • Gestation: 9 months • Years of parental care • Sexual maturity: ~15 years • Long lifespan (~70-80 years) • Multiple births over lifetime

TYPE II - CONSTANT MORTALITY

Curve shape: │ │╲ │ ╲ │ ╲ │ ╲ │ ╲ └─────╲ Young → Old

Characteristics: • Constant mortality rate across all ages • Equal probability of death at any age • Linear decrease (on log scale) • Death from random events, predation • Not age-dependent

Examples: • Many birds (songbirds, robins) • Small mammals (squirrels, mice) • Some reptiles (lizards) • Some perennial plants

Reproductive Strategy (Intermediate): • MODERATE number of offspring • MODERATE parental care • Medium offspring size • Some parental investment • Death from predation, accidents (not age)

Example: Birds • 3-6 eggs per clutch • Incubation and feeding of young • Fledglings leave nest in weeks • Some remain vulnerable to predation • Multiple breeding seasons

TYPE III - HIGH EARLY MORTALITY

Curve shape: │╲ │ ╲╲ │ ╲╲ │ ╲ │ ───── │ ──── └───────────── Young → Old

Characteristics: • Very high juvenile mortality • Low survival of young • Those that survive to adulthood live long time • Death mainly in early life • Steep initial drop, then levels off

Examples: • Fish (salmon, cod) • Marine invertebrates (oysters, sea urchins) • Plants (oak trees, dandelions) • Insects (butterflies, beetles) • Amphibians (frogs, toads) • Sea turtles

Reproductive Strategy (r-selected): • MANY offspring • LITTLE/NO parental care • Small offspring size • Rapid development • Early maturation • Often single reproduction event • "Spray and pray" strategy • Unstable/unpredictable environments • Below carrying capacity, rapid growth

Example: Sea turtles • 100+ eggs per nest • Buried in sand, no care • Hatchlings vulnerable to predators • Only ~1% survive to adulthood • Those that survive can live 50+ years • Trade quantity for quality

Example: Oak trees • Thousands of acorns produced • No parental care • Most eaten by animals, don't germinate • Few survive to mature trees • Mature trees live 100+ years

COMPARISON TABLE:

Feature | Type I | Type II | Type III ---------------|-------------|--------------|------------- Juvenile death | Low | Moderate | Very high Old age death | High | Moderate | Low (if survive) Offspring # | Few | Moderate | Many Parental care | High | Moderate | None/minimal Offspring size | Large | Medium | Small Strategy | K-selected | Intermediate | r-selected Environment | Stable | Variable | Unpredictable Lifespan | Long | Medium | Long (if survive)

r-selected vs. K-selected:

r-selected (Type III): • Rapid growth rate (r) • Many small offspring • Early maturity • Short lifespan • Little parental care • Opportunistic • Pioneer species • Example: Weeds, insects, fish

K-selected (Type I): • Near carrying capacity (K) • Few large offspring • Late maturity • Long lifespan • High parental care • Competitive • Climax species • Example: Elephants, primates

Real Populations: • Most species fall on continuum • Not strictly Type I, II, or III • May show intermediate patterns • Can vary by population/environment

Human Survivorship Changes: • Historical: More Type II or III (high infant mortality) • Modern developed countries: Strong Type I (medicine, sanitation) • Developing countries: Transitioning from II/III to I

Ecological Significance: • Reflects life history strategy • Indicates selective pressures • Affects population growth • Important for conservation (identify vulnerable life stages) • Predicts population responses to disturbance

Key Insight: Survivorship curves reflect fundamental trade-offs in life history: invest heavily in a few offspring (Type I) vs. produce many and hope some survive (Type III)!

Population Regulation Factors:

DENSITY-DEPENDENT Factors: Effect varies with population density - stronger impact at high density

Characteristics: • Intensity increases as population grows • Provide negative feedback • Regulate population around carrying capacity • Biotic (living) factors • Act like "brakes" on population growth • Tend to stabilize populations

Types and Examples:

1. COMPETITION (Intraspecific) Mechanism: • Same species compete for limited resources • More individuals → less per capita resources • Reduces survival and reproduction

   Examples: • Plants competing for light, water, nutrients • Lions fighting over territory • Birds competing for nesting sites

   Effect at high density: • Smaller body size • Lower reproductive rate • Higher mortality • Slower growth rate

2. PREDATION Mechanism: • High prey density attracts more predators • Easier for predators to find prey • Predator populations increase • Increased predation rate

   Examples: • Lynx eating snowshoe hares (cyclic) • Wolves hunting elk • Ladybugs eating aphids

   Effect at high density: • More prey killed per predator • Functional response (predators eat more) • Numerical response (predator population grows)

3. DISEASE and PARASITISM Mechanism: • High density → easier disease transmission • More contact between individuals • Pathogens spread faster • Epidemics more likely

   Examples: • Plague in prairie dog colonies • Dutch elm disease in dense forests • COVID-19 in crowded cities • Parasitic mites in high-density bee colonies

   Effect at high density: • Disease spreads exponentially • Higher mortality • Can cause population crashes

4. TOXIC WASTE ACCUMULATION Mechanism: • Organisms produce waste products • High density → waste accumulates • Becomes toxic • Inhibits growth/survival

   Examples: • Yeast producing alcohol (kills itself) • Bacteria in culture (waste buildup) • Algae producing toxins

   Effect at high density: • Self-poisoning • Growth inhibition • Mass mortality

5. STRESS and AGGRESSIVE BEHAVIOR Mechanism: • Crowding causes physiological stress • Increased aggression • Hormonal changes • Reduced reproduction

   Examples: • Rodents at high density (reduced fertility) • Territorial fights increase • Infanticide in crowded populations • Social stress in primates

   Effect at high density: • Lower birth rates • Higher infant mortality • Behavioral changes • Suppressed immune systems

Density-dependent graph: Mortality Rate ↑ │ ╱ │ ╱ │ ╱ │ ╱ │╱ └──────────→ Population Density

DENSITY-INDEPENDENT Factors: Effect does NOT vary with population density - same impact regardless

Characteristics: • Intensity unrelated to population size • No feedback • Don't regulate at carrying capacity • Abiotic (non-living) factors mostly • Catastrophic events • Cause unpredictable fluctuations

Types and Examples:

1. WEATHER/CLIMATE Mechanism: • Extreme conditions kill fixed percentage • Doesn't matter how dense population is

   Examples: • Frost killing insects (kills 90% regardless of density) • Drought reducing all plant populations • Heat wave killing animals • Hurricane destroying habitat

   Effect: • Same % mortality at any density • Population crashes • Unpredictable timing

2. NATURAL DISASTERS Mechanism: • Physical destruction of habitat/organisms • Indiscriminate killing

   Examples: • Volcanic eruptions • Floods • Fires (some) • Tsunamis • Landslides

   Effect: • Mass mortality events • Destroys portions of habitat • Resets succession

3. SEASONAL CHANGES Mechanism: • Predictable environmental changes • Affects all individuals similarly

   Examples: • First frost killing annual plants • Dry season reducing all populations • Winter killing some insects

   Effect: • Seasonal population declines • Predictable cycles

4. HUMAN ACTIVITIES Mechanism: • Habitat destruction • Pollution • Harvesting

   Examples: • Pesticide application (kills % regardless of density) • Clear-cutting forest • Oil spill • Development destroying habitat

   Effect: • Population reduction • Often catastrophic • Not related to pre-disturbance density

Density-independent graph: Mortality Rate ↑ │──────────── │ │ │ │ └──────────→ Population Density (Flat line - constant regardless of density)

KEY DIFFERENCES:

Feature | Density-Dependent | Density-Independent ---------------------|----------------------|-------------------- Effect varies? | YES (with density) | NO (constant) Type | Biotic (usually) | Abiotic (usually) Feedback? | Negative feedback | No feedback Regulates at K? | YES | NO Predictability | Predictable | Unpredictable Stabilizing? | YES | NO (destabilizing) Examples | Competition, disease | Weather, disasters

COMBINED EFFECTS in Nature:

Most populations affected by BOTH:

1. Example: Aphid population • Density-dependent: Ladybug predation increases when aphids abundant • Density-independent: Cold snap kills 80% regardless of density

2. Example: Salmon population • Density-dependent: Competition for spawning sites • Density-independent: Flood destroys eggs in stream

3. Example: Forest trees • Density-dependent: Competition for light and nutrients • Density-independent: Hurricane blows down portion of forest

Interactions: • Density-independent event reduces population • Then density-dependent factors less intense (more resources per individual) • Population may rebound quickly • Or vice versa: High density population more vulnerable to disease outbreak

r-selected vs. K-selected: • r-selected species: More affected by density-independent factors

• Live in unpredictable environments
• Boom-and-bust cycles

• K-selected species: More affected by density-dependent factors

• Live in stable environments near K
• Regulated by competition, predation

Conservation Implications: • Small populations: Density-independent factors more dangerous (less buffering) • Large populations: Density-dependent factors keep in check • Need to identify which factors limiting for management

Key Principle: Density-dependent factors provide feedback that regulates populations around carrying capacity, while density-independent factors cause unpredictable fluctuations. Most natural populations experience both!

Life History Strategies: Two extremes of a continuum in how organisms allocate energy to growth, reproduction, and survival.

r-SELECTED STRATEGY: "r" = intrinsic rate of increase (maximum growth rate)

Characteristics:

1. REPRODUCTION • Many offspring • Small offspring size • Little/no parental care • Early sexual maturity • Short generation time • Often single reproductive event (semelparous) • High reproductive rate

2. SURVIVAL • Type III survivorship curve • High juvenile mortality • Short lifespan (if don't reach adulthood) • Low competitive ability

3. POPULATION DYNAMICS • Rapid population growth • Boom-and-bust cycles • Population well below K • Little intraspecific competition • Density-independent mortality

4. ECOLOGY • Opportunistic • "Colonizers" or "pioneers" • Exploit temporary resources • Wide dispersal • High mobility

Environments Favoring r-selection: • UNPREDICTABLE, UNSTABLE • Frequent disturbance • Early successional stages • Temporary habitats • Resource availability fluctuates • High mortality from abiotic factors

Examples:

1. INSECTS • Mosquitoes: 100s of eggs, no care, days to mature • Fruit flies: Rapid generation time • Locusts: Massive reproduction, boom-bust cycles • Aphids: Parthenogenesis, rapid reproduction

2. PLANTS • Dandelions: 1000s of seeds, wind dispersal • Annual weeds: Quick maturation, many seeds • Pioneer plants: Colonize disturbed areas

3. FISH • Salmon: 1000s-millions of eggs, spawn once and die • Cod: Millions of eggs, no parental care • Most marine fish: Broadcast spawning

4. SMALL MAMMALS • Mice: Large litters (6-8), multiple per year • Rats: Reach maturity in weeks

5. MICROORGANISMS • Bacteria: Binary fission, exponential growth • Rapid doubling time (20 minutes for E. coli)

Strategy Summary: "Quantity over quality" - Produce many offspring, hope some survive

K-SELECTED STRATEGY: "K" = carrying capacity (stable population size environment can support)

Characteristics:

1. REPRODUCTION • Few offspring • Large offspring size • Extensive parental care • Late sexual maturity • Long generation time • Multiple reproductive events (iteroparous) • Low reproductive rate

2. SURVIVAL • Type I survivorship curve • Low juvenile mortality • Long lifespan • High competitive ability • Efficient resource use

3. POPULATION DYNAMICS • Slow population growth • Stable population size • Population near carrying capacity • Strong intraspecific competition • Density-dependent regulation

4. ECOLOGY • Specialist • "Equilibrium" species • Stable resource use • Territorial • Limited dispersal

Environments Favoring K-selection: • PREDICTABLE, STABLE • Rare disturbance • Late successional/climax stages • Permanent habitats • Constant resource availability • Crowded, competitive • Mortality from biotic factors (competition, predation)

Examples:

1. LARGE MAMMALS • Elephants: 1 calf per 4-5 years, 22-month gestation, years of care • Whales: 1 calf, long gestation, nurse for years • Primates: 1-2 offspring, extensive care, learn from parents • Humans: Ultimate K-selected (1 baby, ~20 years to independence)

2. LARGE BIRDS • Eagles: 1-2 eggs, both parents feed for months • Albatross: 1 egg per 2 years, long-lived (50+ years) • Condors: 1 egg, 6 months of care

3. TREES (mature forest) • Oak, maple: Large seeds (acorns), nutrient-rich • Coconut palm: Large seed with food supply • Sequoia: Long-lived (1000s of years)

4. SOME REPTILES • Crocodiles: Guard nest and young • Some snakes: Parental care

Strategy Summary: "Quality over quantity" - Invest heavily in each offspring to ensure survival

COMPARISON TABLE:

Trait | r-selected | K-selected -------------------|-------------------|------------------ Offspring number | Many | Few Offspring size | Small | Large Parental care | None/minimal | Extensive Maturation | Early/rapid | Late/slow Lifespan | Short | Long Reproduction | Often once | Repeated Mortality | Type III | Type I Competition | Low | High Environment | Unstable | Stable Population growth | Rapid (r) | Slow, near K Example | Mosquito | Elephant

TRADE-OFFS:

Energy Allocation: • r-selected: Energy to reproduction • K-selected: Energy to growth, maintenance, parental care

Cannot maximize both: • More offspring → less per offspring investment • More parental care → fewer offspring possible

Evolutionary Logic:

In UNSTABLE environments: • High unpredictable mortality anyway • Parental care won't prevent it • Better to make many offspring • Rapid reproduction → exploit resources before they disappear

In STABLE environments: • Resources limited, competition intense • Better competitors survive • Parental investment increases offspring competitive ability • Quality matters more than quantity

CONTINUUM in Reality: • Most species fall between extremes • Not strictly r or K • May shift strategies in different conditions • Even within species: phenotypic plasticity

Examples of Intermediate: • Songbirds: 3-6 eggs, some parental care, multiple broods • Rabbits: Multiple litters, moderate offspring, some care • Many fish: Intermediate numbers, some care (e.g., sunfish guarding nest)

ENVIRONMENTAL CHANGE:

Succession: • Early succession: r-selected species dominate

• Weeds, fast-growing plants
• Colonize bare soil

• Late succession: K-selected species dominate

• Mature forest trees
• Competitive dominants

Disturbance: • After fire, flood, clear-cutting: r-selected invade • Stable mature ecosystem: K-selected persist

HUMAN IMPACTS:

r-selected problems: • Pests (insects, weeds) • Rapid evolution (pesticide resistance) • Invasive species (reproduce rapidly) • Hard to control (boom populations)

K-selected problems: • Extinction risk (slow reproduction) • Cannot recover quickly from disturbance • Small population sizes • Examples: Elephants, rhinos, great apes threatened

Conservation: • K-selected species need special protection • Long generation time → slow recovery • Small populations vulnerable • Critical to protect breeding adults

Key Insight: r and K selection represent alternative solutions to the challenge of survival and reproduction. r-selection bets on quantity and speed, K-selection bets on quality and competitive ability. Environment determines which strategy succeeds!