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Introduction to Predator-Prey Dynamics
Long-standing question: Do predators preferentially target the old, young, sick, and weak?
Origin: Concept developed in the early 1950s based on wolf behavior (PR campaign to improve public perception).
Preferential Targeting by Predators
Predation Modes
Coursing Predators: Often target vulnerable individuals (e.g., wolves).
Stalking or Sit-and-Wait Predators: Less likely to preferentially target weaker individuals.
Ambush Predators: Do not show preference; prey vulnerability relies on random chance.
Random Chance and Prey Behavior
Example of chronic wasting disease in deer:
Predators (e.g., mountain lions) showed a preference for diseased deer based on behavioral changes, not physical weakness.
Disease alters behavior (e.g., droopy head syndrome), making deer easier to hunt.
Historical Context of Predator Control
Viewpoint shifted over centuries; believed that eliminating predators results in increased game species.
The 1905 Kaibab Plateau incident: Removal of predators led to a deer population surge then crash due to starvation.
Removal of 781 mountain lions, 30 wolves, 5,000 coyotes, etc.
Result: Deer increased to 100,000 but decreased to 10,000 due to overgrazing.
Re-evaluation of Evidence
1970s Reevaluation:
Research by Graham Cawley suggested habitat quality improvements (e.g., logging increased food for deer) contributed to deer population spikes.
Domesticated livestock removal also played a crucial role in enhancing deer numbers.
Isle Royale Moose and Wolves Study
Wolves colonized the island in 1949, leading to the longest-running predator-prey study.
Findings showed:
Wolves dampened population swings of moose.
Moose numbers were primarily tied to browse availability, not just predation.
Average moose numbers remained stable before and after wolf introduction.
Bottom-Up vs Top-Down Regulation
Bottom-Up Perspective
Adequate habitat drives prey abundance.
Prey availability then influences predator abundance.
Top-Down Perspective
Predators limit prey abundance, impacting habitat through reduced herbivore populations.
Ongoing debate: Which dynamic is dominant?
Logical Considerations in Predator-Prey Interactions
Prey Abundance
Trophic pyramid explains prey’s higher numbers than predators.
Energy transfer is inefficient (90% loss between trophic levels).
Predator Response Dynamics
Time lag in predator population increase in response to growing prey populations.
Territoriality can restrict predator numbers even when prey is abundant.
Additive vs Compensatory Mortality
Additive Mortality: Predation adds to other mortality causes.
Compensatory Mortality: Predation replaces existing mortality sources.
Full compensatory mortality means no net effect on prey population size.
Situations of Predator Limitation
Predators are more likely to limit prey numbers when:
Prey populations are not abundant.
Prey are highly preferred by predators.
Predation mortality is partially additive.
Examples of Research Findings
Bottom-Up Evidence
Studies showed short-term increases in prey numbers without long-term changes when predators are removed.
Ex: Texas deer study.
Birds and hares similarly showed that predation effects were largely compensatory.
Top-Down Evidence
Case studies of wolves limiting caribou populations, and mountain lions impacting bighorn sheep abundances despite alternative prey availability.
Example: Sea otters regulating sea urchin populations, affecting kelp forests.
Predator Pit Dynamics
Temporary shift in predator-prey dynamics where a decline in prey might allow predators to effectively limit numbers due to scarcity.
Counterintuitive, suggesting conditions where normally bottom-up dynamics flip.
Conclusion
Future discussions on predator-prey dynamics will further explore the implications of bottom-up and top-down effects.
Introduction of the predator pit concept to be revisited for deeper understanding.