Abstract
Population and land management relies on understanding population regulation and growth, which may be impacted by variation in population growth parameters within and among populations. We explored the interactions between variation in carrying capacity (K), intrinsic population growth rate (r), and strength of density dependence (β) within and among elk (Cervus elaphus) herds in a small part of the geographic range of the species. We also estimated stochastic fluctuations in abundance around K for each herd. We fit linear Ricker growth models using Bayesian statistics to seven time series of elk population survey data. Our results indicate that K and β varied among herds, and that r and β varied temporally within herds. We also found that herds with smaller K had less stochastic fluctuation in abundances around K, but higher temporal variation in β within herds. Population regulation and the rate of return to the equilibrium abundance is often understood in terms of β, but ecological populations are dynamic systems, and temporal variation in population growth parameters may also influence regulation. Population models which accommodate variation both within and among herds in population growth parameters are necessary, even in mild climates, to fully understand population dynamics and manage populations.
Highlights
Population and land management relies on understanding population regulation and growth, which may be impacted by variation in population growth parameters within and among populations
Estimating K, r, temporal variation in K and r, and fluctuations in abundances around K is critical for understanding population dynamics and regulation[6,8]
The growth model with temporal variation in both r and β was selected for the five herds in Redwood National and State Parks (RNSP) (Table 1, Fig. 1)
Summary
Population and land management relies on understanding population regulation and growth, which may be impacted by variation in population growth parameters within and among populations. Population regulation and the rate of return to the equilibrium abundance is often understood in terms of β, but ecological populations are dynamic systems, and temporal variation in population growth parameters may influence regulation. Regulation of populations is driven by density-dependent factors, the strength of which should impact the time to return to an equilibrium abundance around which the population fluctuates[1] This results in a carrying capacity (K) which can be defined as a long-term stationary probability distribution of population abundance[2,3,4,5]. The Ricker model is commonly used to approximate population dynamics and estimate population growth parameters for species with slow life h istories[9,10,11]. The simplicity and parsimony of the Ricker model make it an insightful approximating m odel[14,15,16,17]
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