Investigating tritrophic interactions using bioenergetic demographic models.

Area of Science:

• Ecology
• Ecosystem Dynamics
• Population Modeling

Background:

• Understanding apex predator effects on prey dynamics is a central ecological debate.
• Terrestrial studies often use correlational approaches, limiting mechanistic insights into population dynamics.
• Mechanistic models can explore the complexity of species interactions.

Purpose of the Study:

• To develop and apply a bioenergetic mechanistic model for a tritrophic system (grass-elk-wolf).
• To investigate the impact of wolf reintroduction on the Yellowstone ecosystem.
• To understand the interplay of bioenergetics, demography, and body mass in predator-prey interactions.

Main Methods:

• Developed a bioenergetic mechanistic model integrating a seasonal vegetation growth function with two integral projection models (IPMs) for herbivore (elk) and carnivore (wolf) populations.
• IPMs incorporated bioenergetic principles for resource acquisition, energy transformation, and reproduction based on body mass.
• Parameterized the model using data from northern Yellowstone National Park to simulate grass, elk, and wolf population dynamics.

Main Results:

• The model accurately predicted elk and wolf population sizes before and after wolf reintroduction.
• Wolf reintroduction led to a 61% reduction in elk numbers and a stable wolf population of 99 individuals.
• Vegetation biomass increased significantly, and the elk population shifted from food-limited to predator-limited, exhibiting stabilized numbers and a slight increase in average body mass.

Conclusions:

• Explicitly linking bioenergetics, population demography, and body mass provides novel mechanistic insights into predator-prey interactions.
• Apex predators play a crucial role in regulating prey populations and influencing ecosystem structure and stability.
• The model demonstrates the profound cascading effects of top-down control in ecological systems.