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So, we can study simultaneously several population models: competing species, predator-prey, mutualism, and so forth.
Thus we can study several population models simultaneously: competitive, predator-prey, mutual, and so forth.
Several population models have been developed to characterize the pharmacokinetics of tacrolimus following kidney transplantation and to identify covariates for individual dose selection.
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Under several population genetic models, TEs are expected to be rapidly removed from gene-rich regions [ 47].
And many authors have studied stability in distribution of several stochastic population models in recent years (see [29, 30] etc).. Thus, we could try to consider these aspects and get much more interesting results in the future investigation.
Several closed population models were used to generate abundance estimates [19].
There are several types of population models such as interspecific competition models, predator-prey models, and facultative mutualism models [4].
Our work illustrates several advantages of simpler population models [39].
We generated several population time series under each model, and used a Bayesian approach to fit the three models to the simulated data.
We simulate several population time series under each model with different magnitudes of noise ranging from low to high, and use a Bayesian approach [ 14] to fit the three models to the simulated data using Markov chain Monte Carlo (MCMC) methods [ 15].
We generated several population time series under each model, with values of r set to 0.5, 1.9 and 3, and without loss of generality, the expected value of the mean carrying capacity, K, was set to Euler's number e (i.e., k = log(K) = 1).
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