Please enable JavaScript.
Coggle requires JavaScript to display documents.
DavidRasccon53-54.pdf - Coggle Diagram
DavidRasccon53-54.pdf
chaapter 53
Exponential Model of Population Growth
Ideal Conditions
abundant resources
max reproduction
no limiting factors
Population Change
births increase population (B)
deaths decrease population (D)
ΔN = B − D
Per Capita Growth (r)
change per individual
r = per capita rate
formula: ΔN = rN
Instantaneous Growth Form
dN/dt = rN
J-shaped Curve
constant growth rate
faster additions as population increases
curve steepens over time
Higher r = Faster Growth
r high = fast slope
r low = slow slope
When Exponential Growth Happens
new habitat
rebound after crash
human protection → population boom
Logistic Growth & Carrying Capacity
Carrying Capacity (K)
Definition
Maximum population size
Environment can sustain
Long-term, without degradation
Depends On Limiting Resources
Energy
Shelter
Refuge from predators
Nutrients
Water
Nesting / roosting sites
Bats
High K: many insects + roost sites
Low K: food OK but few shelters
Effects of Crowding
Resource Limitation
Less food per individual
Less space / shelter
More competition
Birth Rate Changes
Per capita birth rate ↓
Fewer resources for reproduction
Death Rate Changes
Per capita death rate ↑
Starvation
Disease (density-dependent)
Result
Per capita population growth rate ↓
Contrast with constant r in exponential model
Logistic Growth Model – Equation
Start from Exponential
dN/dt = rN
Modify for Carrying Capacity
Key Pieces
r = intrinsic rate of increase
N = current population size
K = carrying capacity
Logistic Curve Shape
S-Shaped (Sigmoid) Curve
Initial phase: slow increase
Middle: steep, rapid growth
Late: slows as N → K
Inflection Point
Around N = K/2
Maximum growth rate
Comparison to Exponential
Same r initially
Exponential: keeps rising, J-shaped
Logistic: levels off at K
Real Populations vs Model
Lab Populations – Good Fit
Constant environment
Limited resources
Few species (no predators/competitors)
Example: Paramecium
ab Populations – Overshoot
Daphnia (water fleas)
Population exceeds K
Then drops, stabilizes near K
Reasons For Overshoot
Time lags
Natural Populations
Often fluctuate
K may be hard to define
Environment not constant
Life History Traits & Natural Selection
Life History Definition
Components Influenced by Natural Selection
Survival traits
Reproductive traits
Life History =
Timing of reproduction
Frequency of reproduction
Number of offspring
Parental investment
Evolutionary Outcome Reflected In
Development
Physiology
Behavior
Diversity of Life Histories
Key Variables
Age at first reproduction
Frequency of reproduction
Number of offspring per episode
Variation Examples
Reproductive Age
Loggerhead turtle: ~30 years
Coho salmon: 3–4 years
Reproductive Strategies
Semelparity (one-shot reproduction)
Salmon → thousands of eggs once → die
Agave → grows long, flowers once, dies
Adapted to harsh, unpredictable conditions
Iteroparity (repeated reproduction)
Loggerhead turtles → multiple clutches over decades
Oaks, maples, horses, sea urchins
Trade-offs in Life Histories
Resource Limitation
Organisms cannot maximize all traits
Investment in one function reduces another
Parent Survival Trade-off
Kestrel Study
Larger brood → lower parent survival
Parental care cost increases mortality
Red Deer Example
Reproducing females more likely to die next winter
Offspring Trade-offs
Number vs size
Feeding vs quantity
Care vs reproduction frequency
Offspring Number & Survival Patterns
Many Small Offspring
Low survival chance
Disturbed habitats
Example: dandelions, quail, sardines, mice
Fewer Large Offspring
High provisioning
Higher survival probability
r-selection vs K-selection
K-selection
Selection near carrying capacity (K)
Competitive environments
Few offspring, large investment
r-selection
Maximizes intrinsic growth rate (r)
Uncrowded environments
Rapid reproduction, many offspring
Spectrum Concept
Most organisms fall between extremes
Framework tied to logistic model
Density-Dependent Regulation & Population Dynamics
Density & Population Change
Births vs Deaths
If B > D → population grows
If D > B → population declines
Density-Independent Factors
Not affected by population density
Example: dune fescue grass mortality
Density-Dependent Factors
Birth ↓ with higher density
Death ↑ with higher density
Example: dune fescue reproduction tied to resource scarcity
Regulation
Populations stop growing when
Birth = death
Negative feedback stabilizes size
Density-Dependent Mechanisms (Negative Feedback)
Competition
Resource limitation
Less nutrients → lower reproduction
Farmers model: fertilizer reduces competition
Disease
Transmits more readily at high density
Examples: influenza, tuberculosis in cities
Predation
Predator captures more prey at high density
Example: snowy owl preying on lemmings
Territoriality
Space as limiting resource
Example: cheetahs → scent marking boundaries
Surplus non-breeders = density constraint
Intrinsic Factors
Physiological stress
Aggression, hormones → delayed sexual maturity
Example: white-footed mice decline reproduction even with food
Stability vs Fluctuation
Population Dynamics
Yearly or spatial changes in abundance
Influence predator / prey cycles
Moose & Wolf Example
Factors Causing Fluctuations
Harsh winter → weakened moose → decline
Mild weather → growth
High moose density → predation, parasites ↑
First crash: wolf peak (1975–80)
Second crash: harsh winter (~1995)
Population Cycles (Boom & Bust)
Regular Cycles
Hares & lynx (~10-year cycles)
Birds (ruffed grouse, ptarmigans ~3–10 yrs)
Small herbivores (vole, lemming cycles)
Hypotheses for Hare-Lynx Cycles
Food Limitation
Tested → extra food ↑ hare density
BUT cycle continued → hypothesis rejected
Predation
Radio-tracking: >90% of hares killed by predators
Predator exclusion reduces collapse phase
Conclusion: predator overexploitation drives cycles
Immigration, Emigration & Metapopulations
Movement Effects
Crowding ↑ → emigration ↑
Populations linked by dispersal
Metapopulation Concept
Many local populations
Habitat patches vary in quality/size/isolation
Local extinctions & recolonization balance
Glanville Fritillary Butterfly
Habitat
~500 meadows occupied
~4000 suitable patches
Dynamics
Local populations constantly shift
Species persists via recolonization
Genetic Influence
Pgi gene → affects flight ability
Heterozygotes fly farther & cooler temps
Higher colonization success → fitness advantage
Global Human Population Growth
Historical Pattern
1650 → ~500 million
1930 → ~2 billion
1975 → ~4 billion
8 billion today
➤ Faster Than Exponential (Past)
Doubling time shrank
Industrial Revolution → population boom
Now: Still Rapid, But Slowing
Growth rate peaked ~1962 (~2.1%)
~1% in 2022
Projected ~0.5% in 2050
Causes of Slowing
Disease (e.g., AIDS)
Voluntary population control
Social and economic changes
Regional Patterns & Demographic Transition
Stable Population Conditions
Birth rate ≈ death rate
High–high OR low–low
Demographic Transition
Shift: high birth & death → low birth & death
Accompanies industrialization
Drivers
Improved health care
Better sanitation
Education access (especially for women)
Industrialized Nations
Near replacement (≈2.1 children/woman) or below
Many below replacement → eventual decline without immigration
Developing Nations
~80% of world population
Higher birth rates
Main source of global population growth
Age Structure & Social Effects
Age-Structure Definition
Relative number in each age group
Graphed as pyramids
Examples
Zambia: broad base → many young → rapid future growth
United States: fairly even → slow growth (immigration important)
Italy: narrow base → aging → future population decline
Implications
Young-heavy:
Pressure on schools, jobs
Need for education & employment planning
Aging-heavy
Fewer workers
More retirees
Strain on Social Security, pensions, Medicare
Infant Mortality & Life Expectancy
Definitions
Infant mortality = deaths per 1,000 live births
Life expectancy at birth = average predicted lifespan
Global Variation
High mortality, low life expectancy in some countries
Low mortality, high life expectancy in others
Effects
High infant mortality → parents may have more children
Health, stability, and disease all impact these metrics
chapter 54
Overview of Interaction Types
Interspecific Interactions
Between different species
Shape communities
Effect Notation
= increases survival / reproduction
– = decreases survival / reproduction
0 = no effect
Major Categories
Competition (– / –)
Exploitation (+ / –)
Predation
Herbivory
Parasitism
Positive interactionsMutualism
Mutualism (+ / +)
Commensalism (+ / 0)
Competition (– / –)
Competitive Exclusion
Gause Experiment
Paramecium aurelia vs P. caudatum
Alone → each reaches own carrying capacity
Together → P. caudatum goes extinct
Principle
Two species competing for same limiting resource
Cannot coexist permanently
One uses resource more efficiently → excludes other
Niches & Resource Partitioning
Ecological Niche
Species’ role in ecosystem
Set of biotic + abiotic resources used
Temperature range
Perch size
Activity time
Food types
Competitive Exclusion Restated
Two species cannot coexist with identical niches
Fundamental vs Realized Niche
Fundamental Niche
Niche potentially occupied
Tested without competitors
Realized Niche
Niche actually occupied
Limited by competition
Barnacles
Chthamalus high on rocks
Balanus lower on rocks
Removing Balanus → Chthamalus expands down
Conclusion: competition shrinks realized niche
Character Displacement
Definition
Traits diverge more in sympatric than allopatric populations
Reduces competition
Galápagos Finches Example
Geospiza fuliginosa and G. fortis
Allopatric → similar beak depth
Sympatric → different beak sizes
Exploitation (+ / –)
Predation (+ / –)
Predator Adaptations
Acute senses
Claws, fangs, venom
Speed, stealth, camouflage
Prey Adaptations
Behavior: hiding, fleeing, herds/schools
Active defense: mobbing, defending young
Morphological / Chemical Defenses
Mechanical: quills (porcupine)
Chemical: skunk spray
Aposematic coloration: bright warning colors
Cryptic coloration: camouflage
Mimicry
Batesian mimicry
Harmless species mimics harmful one
Example: hawkmoth larva mimics snake
Müllerian mimicry
2+ harmful species share same warning look
Example: cuckoo bee + yellow jacket
Predator Mimicry
Mimic octopus
Mimics sea snake, flounder, stingray
Used for both attack and defense
Herbivory (+ / –)
Definition
Herbivore eats parts of plants or algae
Usually harms, but doesn’t kill entire plant
Herbivore Adaptations
Chemical sensors (insects’ feet)
Smell-based selection (goats, etc.)
Specialized teeth & digestive systems
Plant Defenses
Structural: spines, thorns
Chemical: toxins
Distasteful compounds: cinnamon, cloves, mint
Growth-altering chemicals for insect herbivores
Parasitism (+ / –)
Definition
Parasite gets nourishment from hostHost is harmed
Types
Endoparasites: inside host (tapeworms)
Ectoparasites: on outer surface (ticks, lice)
Parasitoids: larvae develop in host, kill host
Complex Life Cycles
Behavior Modification
Parasite changes host behavior
Infected crustaceans leave cover → eaten by bird host
Population Effects
Can lower host survival & density
Positive Interactions
Definition
At least one species benefits
Neither is harmed
Includes mutualism & commensalism
Mutualism (+ / +)
Both partners benefit
Examples
Termites / ruminants + gut microbes
Pollination & seed dispersal by animals
Mycorrhizae: plant roots + fungi
Corals + photosynthetic algae
Acacia trees + ants (Fig 54.9)
Costs & Benefits
Each pays a cost (resources given up)
Overall benefit > cost
Mutualism may break down if cost > benefit
Commensalism (+ / 0)
Definition
One species benefits
Other is not affected
Examples
Shade-dependent wildflowers under trees
Wildflowers benefit from shade
Trees unaffected
Cattle egrets & large herbivores
Birds eat flushed insects
Interaction Can Shift
Sometimes herbivores also benefit
Birds eat ticks
Birds give predator warnings
Can change from +/0 → +/+
Community Diversity & Trophic Structure
Species Diversity
Definition
Variety of species in a community
Components
Species richness
Number of species
Relative abundance
Proportion of each species
Example Communities (A vs B)
Same richness (4 species each)
Different relative abundance
A: more even → more diverse
B: one species dominates
Shannon Diversity Index (H)
Interpretation
Higher H → more diverse community
Uses
Compare communities
Combine richness + evenness
Measuring Diversity – Challenges
Rare Species
Hard to sample enough
Difficult to identify
DNA Barcoding
Use DNA sequences
Short “barcode” region
Compare to reference database
Reveals: samples that look different may be same species
Microorganisms & Molecular Tools
Extract DNA from sample
PCR amplify rRNA genes
Restriction enzymes + gel → DNA profile
Use profile to compute Shannon
Diversity & Community Stability
Resistance to Invasion
Introduced Species
Humans move species outside native range
Sessile Marine Invertebrate Experiment
Communities with different richness
Introduced tunicate added
Trophic Structure
Food Webs
Definition
Linked food chains
Shows who eats whom
Antarctic Marine Web
Producers: phytoplankton
Grazers: krill, copepods
Carnivores: fishes, squid, penguins, seals, whales
Nonexclusive Consumers
Species feed at multiple trophic levels
Limits on Food Chain Length
Observation
Most chains ≤ 5 links
Energetic Hypothesis
Only ~10% energy passed to next level
Limits biomass available at higher levels
High productivity → can support more levels
Tree-Hole Experiment
Artificial tree holes with high, medium, low leaf litter
More litter = more energy at base
Result: longest food chains in high-productivity treatments
Size Constraint
Higher trophic carnivores usually larger
Large carnivores need large prey
Exception: baleen whales (huge, eat tiny krill via filter feeding)
Species With Large Impact
Foundation Species
Big effect via habitat creation or dominance
Examples
Trees, kelp, desert shrubs
Keystone Species
Pisaster Sea Star Experiment
Pisaster eats dominant mussel (Mytilus)
Remove Pisaster
Mussels take over
Species richness drops ~17 → ~2
Ecosystem Engineers
Definition
Species that physically modify environment
Example: Beavers
Fell trees, build dams
Create ponds/wetlands
Change habitat for many species
Top-Down Control
Higher trophic levels control lower ones
Biogeographic Factors & Community Diversity
Big-Scale Biogeography
Main Factors
Latitude (tropics vs temperate vs polar)
Area (small vs large regions / islands)
Adds to local factors
Species interactions
Foundation / keystone species
Disturbance
Latitudinal Gradients
Basic Pattern
More species in tropics
Fewer toward poles
Evolutionary History
Tropical vs Temperate
Tropics generally older communities
Temperate / polar → reset by glaciations
Time for Speciation
More uninterrupted time → more speciation events
Higher species richness in tropics
Climate
Key Climatic Factors
Sunlight high in tropics
Precipitation high in tropics
Evapotranspiration
Evaporation + plant transpiration
Depends on
Solar radiation
Temperature
Water availability
Area Effects
Species–Area Curve
Pattern
Explanation
More habitats & microhabitats
More resources
Larger population sizes
Island Equilibrium Model
Islands
Oceanic islands
Habitat patches
Lakes
Mountain tops
Forest fragments
Immigration vs Extinction
Immigration Curve
High when few species present
Extinction Curve
Low when few species present
Increases as more species compete
Equilibrium
Where immigration rate = extinction rate
Gives equilibrium number of species
Species composition still turns over
Effects of Island Size
Small Islands
Lower immigration (harder to hit)
Higher extinction (fewer resources, smaller pops)
Fewer habitats
Large
Higher immigration
Lower extinction
Higher equilibrium species richness
Effects of Distance
Near vs Far
Near islands
Higher immigration
Lower extinction
Far islands
Lower immigration
Higher extinction
Prediction
Near + large → most species
Far + small → fewest species
Pathogens Alter Community Structure
Pathogens as Community Drivers
Definition
Disease-causing agents
Microorganisms
Viruses
Viroids
Prions
Effects on Community Structure
Coral Reef
Impact
Staghorn & elkhorn corals decimated
Coral loss →
Overgrowth by algae
Herbivorous fish dominate
Reef collapses structurally
Biodiversity plummets
Sudden Oak Death
Pathogen
Phytophthora ramorum
Response
Genome sequencing to find control strategies
Zoonotic Diseases
Pathogens transferred from animals to humans
Vectors
Often parasites
Ticks
Lice
Mosquitoes
Examples
Rabies
Plague
Chagas’ disease
Salmonella
Sleeping sickness
Lyme disease
Zika
Ebola
Monkeypox
COVID-19
Human Influence on Disease Spread
Climate change
Expands host ranges
Habitat destruction
Increases human-wildlife contact
Global transport
Moves pathogens rapidly