integrated lec 20 Flashcards
Cycles in Predator and Prey Population
Predator-prey interactions often exhibit population cycles, where predator and prey populations rise and fall in a coupled, lagged manner.
-Lotka Volterra model shows coupled oscillations where prey population peaks first, followed by predators.
examples of cycles in predator and prey pop
Hudson’s Bay Company Data:
Lynx and hare pelts (1845–1935) showed population cycles.
Factors influencing these cycles:
Over-browsing by hares depleting food plants.
Social stress in overcrowded hare populations.
Indicates cycles are not purely Lotka-Volterra based but are influenced by additional ecological factors.
Huffaker’s Mites Experiment (1958):
Used prey and predator mites on trays of oranges.
Demonstrated how habitat complexity (e.g., barriers) helped sustain cycles.
Without sufficient complexity, predator-prey interaction led to unstable dynamics, often driving one species extinct.
How do ecological factors such as habitat complexity influence predator-prey cycles in nature?
Habitat complexity influences predator-prey cycles by modifying predation rates, encounter frequencies, and population stability. Greater complexity tends to stabilize cycles by providing refuges, spatial variation, and dispersal opportunities for prey, while simpler habitats often lead to more volatile cycles with higher risks of local extinctions.
Ecological factors like habitat complexity play a significant role in influencing predator-prey cycles in nature by affecting interactions between predators and their prey. Here’s how habitat complexity specifically impacts these dynamics:
- Refuges for Prey
How it works: Habitat complexity often provides prey with refuges, such as dense vegetation, burrows, or physical structures where they can hide from predators.
Impact on predator-prey cycles:
By reducing the predation rate, refuges can stabilize predator-prey cycles and prevent extreme fluctuations.
Prey populations are less likely to crash entirely, providing a more stable food source for predators.
This can delay or dampen the amplitude of cycles. - Heterogeneous Resource Availability
How it works: Complex habitats often have varying microenvironments that support diverse resources for prey and predators.
Impact on predator-prey cycles:
Prey populations can grow in resource-rich areas, creating “hotspots” of predator-prey interactions.
Predators may exploit these areas while leaving other areas untouched, leading to spatially asynchronous cycles.
This spatial variation can smooth out population fluctuations at the larger scale. - Movement and Encounter Rates
How it works: Complex habitats reduce the efficiency of predator movements, lowering the encounter rates with prey.
Impact on predator-prey cycles:
Reduced encounter rates decrease the predation pressure, allowing prey populations to recover more quickly.
This can lead to longer, less dramatic predator-prey cycles as opposed to rapid booms and crashes. - Diverse Predation Strategies
How it works: In complex habitats, predators may rely on different hunting strategies, such as ambush or active pursuit, depending on the environment.
Impact on predator-prey cycles:
The diversity of predation strategies can lead to more complex, multi-species predator-prey dynamics.
Some prey species may thrive in one part of the habitat while others are suppressed, introducing more nuanced cycles. - Prey Dispersal and Meta-Populations
How it works: In a complex habitat, prey populations can disperse to new areas when predation pressure is high.
Impact on predator-prey cycles:
This dispersal reduces local prey extinctions and prevents predators from driving prey populations to critically low levels.
It allows for a more dynamic predator-prey interaction, where local extinctions are compensated by recolonization, creating a spatially patchy but overall stable cycle. - Predator Competition and Specialization
How it works: Complex habitats often support multiple predator species, which can compete or specialize in different prey types.
Impact on predator-prey cycles:
Competition among predators can reduce the pressure on a single prey species, stabilizing that prey population.
Predator specialization may lead to more independent cycles for different predator-prey pairs, reducing the risk of cascading extinctions. - Temporal Variation in Habitat Complexity
How it works: Seasonal changes, such as leaf fall, snow cover, or water levels, alter habitat complexity over time.
Impact on predator-prey cycles:
This temporal variation adds another layer of dynamics, where predator-prey interactions fluctuate seasonally.
For example, prey may have better refuge during certain times of the year, allowing populations to recover before the next predation peak.
Real-World Examples:
Lynx-Hare Cycles:
In the boreal forests of Canada, snowshoe hares rely on dense vegetation for cover. When habitat complexity is reduced (e.g., after overbrowsing), hares become more vulnerable to lynx predation, exacerbating the population crash phase of the cycle.
Coral Reef Ecosystems:
In coral reefs, the complexity of coral structures provides hiding spaces for smaller fish, which are prey for larger predators. The loss of coral complexity due to bleaching or destruction can lead to dramatic prey population declines and destabilized predator-prey interactions.
Antagonistic Coevolution
Definition: Reciprocal evolutionary adaptations between predators and prey (or hosts and parasites), often described as an “arms race.”
Key Features:
Prey evolve defenses to avoid predation, while predators develop counter-adaptations to overcome these defenses.
Central to the Red Queen Hypothesis:
In evolutionary terms, “it takes all the running you can do to stay in the same place” (constant adaptation to maintain fitness relative to evolving adversaries).
Examples of Antagonistic Coevolution:
- Garter Snakes vs. Rough-Skinned Newts:
Newts (genus Taricha) produce tetrodotoxin (TTX), a potent neurotoxin.
Garter snakes (Thamnophis) have evolved resistance to TTX.
In areas where newts are more toxic, snakes exhibit higher TTX resistance, demonstrating local adaptation.
- Life-Dinner Principle:
Unequal Selection Pressure: Predators and prey face different evolutionary stakes:
Prey face life-or-death consequences.
Predators face reproductive consequences (missing a meal but surviving).
Result: Prey often evolve more elaborate and faster defenses than predators’ counter-adaptations.
Prey Defenses and Predator Counter-Adaptations:
Defenses:
Morphological (e.g., spines, shells).
Chemical (e.g., plant secondary chemicals, animal toxins like TTX).
Behavioral (e.g., avoiding detection, fleeing, group behavior).
Inducible Defenses: Activated in response to predator presence (e.g., Daphnia develop protective helmets).
Counter-Adaptations:
Enhanced sensory abilities (e.g., echolocation).
Physiological tolerance to toxins.
Behavioral strategies for overcoming defenses.
What is the Red Queen Hypothesis, and how does it relate to predator-prey interactions?
The Red Queen Hypothesis is an evolutionary theory that describes how organisms must continuously adapt and evolve not just for reproductive success, but also to survive against ever-evolving opponents, such as predators, prey, or parasites
Why is prey adaptation often faster than predator counter-adaptation (refer to the life-dinner principle)?
The Life-Dinner Principle
The principle states:
For prey: Failure in the interaction (being caught by the predator) results in death, which is the ultimate evolutionary cost. This creates strong selective pressure for prey to evolve effective defenses quickly.
For predators: Failure in the interaction (failing to catch the prey) results in the loss of a meal, which is a less severe evolutionary cost than death. While catching prey is important for survival and reproduction, the stakes are lower compared to the prey.
Why Prey Adaptation is Faster
The life-dinner principle explains why prey are under stronger and more immediate selective pressure than predators:
Higher Consequences for Prey:
If prey fail to escape, they are removed from the gene pool entirely. This creates intense selection for traits like speed, camouflage, or other defenses.
For predators, a missed meal is significant but not always life-threatening. They can still survive to hunt another day.
Asymmetry in Selection Pressure:
The selective pressure to avoid death is much stronger than the selective pressure to increase hunting success.
As a result, prey evolve adaptations like cryptic coloration, toxic defenses, or rapid escape behaviors more quickly than predators evolve countermeasures.
Population Dynamics:
Prey often reproduce more rapidly than predators (e.g., mice versus owls). This allows prey populations to adapt faster because genetic variations spread more quickly in faster-reproducing species.
Predators, which are typically larger and reproduce more slowly, take longer to evolve counter-adaptations.
Arms Race Costs:
Developing counter-adaptations (e.g., faster speed or toxin resistance) is often energetically costly for predators. If the costs of adapting outweigh the benefits, predators may not evolve countermeasures as quickly as prey evolve defenses
How does local adaptation affect the coevolution of Thamnophis and Taricha?
Key Idea: Local adaptation drives a geographic mosaic of coevolution between Thamnophis garter snakes and Taricha newts, shaping their predator-prey dynamics.
-Newts (Taricha):
Produce tetrodotoxin (TTX) as a defense.
Higher TTX levels in regions with resistant predators (hotspots).
Lower TTX in regions without resistant predators (coldspots) to conserve energy.
-Snakes (Thamnophis):
Evolve TTX resistance in hotspots to prey on toxic newts.
Resistance has trade-offs (e.g., reduced speed and performance), so it’s absent in coldspots.
Arms Race:
Hotspots: High toxin levels in newts and strong resistance in snakes.
Coldspots: Minimal coevolutionary adaptation.
Outcome:
Reciprocal adaptation creates a geographic mosaic of coevolution.
Hotspots and coldspots drive biodiversity and ecological dynamics.
Flowchart of antagonistic coevolution:
Prey evolves defense → Predator evolves counter-adaptation → New prey adaptation.
What is the latitudinal gradient in species richness?
A: Biodiversity is highest at the equator and decreases toward the poles due to stable climates and resource abundance
Provide examples of invasive species and their impacts.
A:
Asian carp: Disrupt freshwater ecosystems.
Purple loosestrife: Displace native wetland plants.
Emerald ash borer: Destroys ash trees
What is the Enemy Release Hypothesis?
A: Invasive species succeed because they lack natural predators or pathogens in new environments
Define ecosystem function and give examples.
A: Processes that regulate energy and nutrient flow, such as primary production, nutrient cycling, and decomposition.
How do predators affect community structure?
A: Predators prevent competitive exclusion, promoting coexistence. For example, Pisaster sea stars maintain biodiversity in intertidal zones by preying on mussels
What are amplification and dilution effects in disease ecology?
Amplification: More host species increase pathogen abundance (e.g., mosquito diversity increases malaria prevalence).
Dilution: Diverse hosts reduce disease spread
Summarize Robert Paine’s experiment with sea stars.
A: Removing sea stars led to mussel dominance and reduced biodiversity, demonstrating the role of predators in maintaining species diversity
What factors influence lynx and hare population cycles?
A: Factors include food availability (e.g., browsing impacts) and predator-prey dynamics, with cycles lagging between predator and prey
Provide an example of antagonistic coevolution.
A: Garter snakes evolved resistance to tetrodotoxin (TTX) from toxic newts (Taricha), showcasing reciprocal adaptations
How does biodiversity enhance ecosystem function?
A: Through:
Complementarity: Species use resources differently.
Facilitation: Some species improve others’ success.
Redundancy: Overlapping roles provide stability.
How does host diversity affect disease risk?
A:
Dilution: Reduced disease risk with diverse hosts.
Amplification: Higher risk with more host species, as seen with mosquito diversity increasing malaria cases in Kenya