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)

Read more

Summary

Introduction

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]

Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.