Elk Population Dynamics When Carrying Capacities Vary Within and Among Herds




Koetke, Lisa J.

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Population and land management relies on understanding population regulation and growth, which may be impacted by variation in carrying capacity (K) within and among populations. I fit linear Ricker growth models using Bayesian statistics to seven time series of population survey data of elk (Cervus elaphus). I explored the effects of variation in K among herds (i.e., populations) on temporal variation in the maximum intrinsic population growth rate (r max) and strength of density dependence (β) within herds in a small part of the geographic range of the species. I also estimated stochastic fluctuations in abundance around K for each herd. My results indicate that r max was similar among herds due to similar life history traits, while K and β varied among herds. Also, r max and β varied temporally within herds. Variation in r max is traditionally viewed as being generated from density-independent factors such as climatic variables, but the variation might also be generated from individual movement. I also found that herds with smaller K will have stronger density dependence (i.e., smaller β), higher temporal variation in β within herds, and less fluctuation in abundances around K. 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 such as K and r max may also influence regulation. Population growth 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.



Bayesian statistics, Cervus elaphus, Fluctuation in abundances, Maximum intrinsic growth rate, Regulation, Ricker model, Strength of density dependence


Koetke, L. J. (2019). <i>Elk population dynamics when carrying capacities vary within and among herds</i> (Unpublished thesis). Texas State University, San Marcos, Texas.


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