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Time, transients and elasticity.

C V Haridas¹, Shripad Tuljapurkar

¹Biological Sciences, Stanford University, Stanford, CA 94305, USA. charidas@stanford.edu

Ecology Letters

|September 22, 2007

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Life history traits influence population growth rate elasticities by affecting population structure. Short-term elasticity depends on stable stage distribution and population momentum in non-stable populations.

Area of Science:

Population Ecology
Demography
Mathematical Biology

Background:

Understanding how life history traits impact population dynamics is crucial for ecological and conservation studies.
Short-term elasticities quantify the immediate impact of demographic rate changes on population growth.
Previous research has primarily focused on stable populations, leaving dynamics in non-stable populations less understood.

Purpose of the Study:

To investigate the influence of life history on short-term population growth rate elasticities.
To develop analytical methods for decomposing and calculating these elasticities.
To explore the role of population structure, particularly stable stage distribution and population momentum, in elasticity calculations.

Main Methods:

Decomposition of short-term elasticity into components related to population structure and vital rates.

Related Experiment Videos

Derivation of exact analytical formulas for elasticity components.

Analysis of elasticity in both stable and non-stable population structures.

Main Results:

Short-term elasticity in stable populations is primarily determined by stable stage distribution (SSD) and reproductive value.
In non-stable populations, elasticity is influenced by the projection of initial structure onto the SSD, equivalent to population momentum.
The demographic damping rate dictates the convergence rate of short-term elasticity towards its limiting values.

Conclusions:

Life history significantly shapes short-term population growth elasticities through its effects on population structure.
Population momentum is a key factor in elasticity for non-stable populations, especially when certain life stages are underrepresented.
The derived analytical framework provides a robust method for assessing demographic responses across diverse population states.