Variable effort harvesting models in random environments: generalization to density-dependent noise intensities

Area of Science:

• Ecology
• Mathematical Biology
• Stochastic Processes

Background:

• Previous models analyzed population growth under harvesting in random environments.
• Existing models had limitations regarding the representation of environmental fluctuations' impact on population growth rates.

Purpose of the Study:

• To generalize previous findings on population dynamics under harvesting in random environments.
• To incorporate density-dependent positive noise intensities of very general form.

Main Methods:

• Utilized stochastic differential equation models.
• Extended analysis to include general density-dependent positive noise intensities.
• Derived conditions for population non-extinction and stationary distributions.

Main Results:

• Established conditions for population non-extinction and the existence of stationary distributions.
• Results are independent of specific environmental fluctuation impacts.
• Provided a more generalized framework for population dynamics modeling.

Conclusions:

• The generalized models offer broader applicability for understanding population persistence and stability.
• This work provides minimal requirements for effective density-dependent harvesting policies.
• The findings are robust across diverse population growth functions and harvesting strategies.