Dynamic behavior of positive solutions for a leslie predator-prey system with mutual interference and feedback controls.
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ABSTRACT:
SUBMITTER: Zhang C
PROVIDER: S-EPMC3918402 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Specialist predators with oscillating dynamics are often strongly affected by the population dynamics of their prey, yet they are not always the cause of prey cycling. Only those that exert strong (delayed) regulation of their prey can be. Inferring predator-prey coupling from time series therefore requires contrasting models with top-down versus bottom-up predator-prey dynamics. We study here the joint dynamics of population densities of the Icelandic gyrfalcon Falco rusticolus, and its prey, the rock ptarmigan Lagopus muta. The dynamics of both species are likely not only linked to each other but also to stochastic weather variables acting as confounding factors. We infer the degree of coupling between populations, as well as forcing by abiotic variables, using multivariate autoregressive models MAR(p), with p = 1 and 2 time lags. MAR(2) models, allowing for species to cycle independently from each other, further suggest alternative scenarios where a cyclic prey influences its predator but not the other way around (i.e., bottom-up scenarios). The classical MAR(1) model predicts that the time series exhibit predator-prey feedback (i.e., reciprocal dynamic influence between prey and predator), and that weather effects are weak and only affecting the gyrfalcon population. Bottom-up MAR(2) models produced a better fit but less realistic cross-correlation patterns. Simulations of MAR(1) and MAR(2) models further demonstrate that the top-down MAR(1) models are more likely to be misidentified as bottom-up dynamics than vice versa. We therefore conclude that predator-prey feedback in the gyrfalcon-ptarmigan system is likely the main cause of observed oscillations, though bottom-up dynamics cannot yet be excluded with certainty. Overall, we showed how to make more out of ecological time series by using simulations to gauge the quality of model identification, and paved the way for more mechanistic modeling of this system by narrowing the set of important biotic and abiotic drivers.
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Project description:Interference competition occurs when access to an available resource is negatively affected by interactions with other individuals, where mutual interference involves individuals of the same species. The interactive phenomena among individuals may be size-dependent, since body size is a major factor that may alter prey consumption rates and ultimately the dynamics and structure of food webs.A study was initiated in order to evaluate the effect of mutual interference in the prey-specific attack rates and handling times of same size class predators, incorporating variation in consumer size. For this purpose, laboratory functional response experiments were conducted using same age predators, that is, newly hatched (first instar) or mature (fifth instar) nymphs of the polyphagous mirid predator Macrolophus pygmaeus preying on Ephestia kuehniella (Lepidoptera: Pyralidae) eggs.The experiments involved four predator density treatments, that is, one, two, three, or four predators of same age, that is, either first- or fifth-instar nymphs, which were exposed to several prey densities. The Crowley-Martin model, which allows for interference competition between foraging predators, was used to fit the data.The results showed that mutual interference between predator's nymphs may occur that affect their foraging efficiency. The values of the attack rate coefficient were dependent on the predator density and for the first-instar nymphs were significantly lower at the highest predator density than the lower predator densities, whereas for the fifth-instar nymphs in all density treatments were significantly lower to that of the individual foragers' ones.These results indicate that mutual interference is more intense for larger predators and is more obvious at low prey densities where the competition level is higher. The wider use of predator-dependent functional response models will help toward a mechanistic understanding of intraspecific interactions and its consequences on the stability and structure of food webs.
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