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Competition and Facilitation between a Disease and a Predator in a Stunted Prey Population.

Boerlijst MC, de Roos AM - PLoS ONE (2015)

Bottom Line: In contrast to predators, parasites do not necessarily kill their host but instead they may change host life history.Here, the disease facilitates the predator, and predator density will be substantially increased.We discuss the implications of our results for the dynamics and structure of the natural Ligula-Roach system.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, P.O. Box 94248, 1090 GE, Amsterdam, The Netherlands.

ABSTRACT
The role of diseases and parasites has received relatively little attention in modelling ecological dynamics despite mounting evidence of their importance in structuring communities. In contrast to predators, parasites do not necessarily kill their host but instead they may change host life history. Here, we study the impact of a parasite that selectively infects juvenile prey individuals and prevents them from maturing into adults. The model is inspired by the Ligula intestinalis tape worm and its cyprinid fish host Rutilis rutilis. We demonstrate that the parasite can promote as well as demote the so-called stunting in its host population, that is, the accumulation of juvenile prey, which leads to strong exploitation competition and consequently to a bottleneck in maturation. If competition between infected and uninfected individuals is strong, stunting will be enhanced and bistability between a stunted and non-stunted prey population occurs. In this case, the disease competes with the predator of its host species, possibly leading to predator extinction. In contrast, if the competition between infected and uninfected individuals is weak, the stunting is relieved, and epi-zoonotic cycles will occur, with recurrent epidemic outbreaks. Here, the disease facilitates the predator, and predator density will be substantially increased. We discuss the implications of our results for the dynamics and structure of the natural Ligula-Roach system.

No MeSH data available.


Related in: MedlinePlus

Dynamics for varying disease invasion threshold.Plotting dynamics as a function of predator death rate μP, and disease invasion threshold (μJ+α)/β. (a) Dynamics for the case of δ = 1. In the white area the disease cannot invade, and in the pink area there is a single endemic equilibrium. The blue area indicates bistability between a stunted endemic state and a non-stunted disease free state. The red line denotes predator extinction. The green and blue line are thresholds below which the disease can invade respectively, the stunted and non-stunted host population. The dashed black lines indicate the disease free region of bistability (b) Dynamics for the case of δ = 0. In the green area only the disease free non-stunted state is stable. The yellow area indicates stable recurrent epidemics, and in the purple area there is bistability of recurrent epidemics and an endemic state. The orange line is a Hopf bifurcation, either supercritical (solid line) or subcritical (dashed line). Other lines and areas are as described in Fig 4a (c) Bifurcation diagram for the subcritical Hopf bifurcation for β = 0.06. The bifurcation resembles that of Fig 3c, but now there is a region of bistability between an endemic state and a stable limit cycle for 0.588 < μP < 0.595. The red area denotes the amplitude of the stable limit cycle, and the dashed red line shows the minimum and maximum of the unstable limit cycle. For parameters see Fig 3.
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pone.0132251.g004: Dynamics for varying disease invasion threshold.Plotting dynamics as a function of predator death rate μP, and disease invasion threshold (μJ+α)/β. (a) Dynamics for the case of δ = 1. In the white area the disease cannot invade, and in the pink area there is a single endemic equilibrium. The blue area indicates bistability between a stunted endemic state and a non-stunted disease free state. The red line denotes predator extinction. The green and blue line are thresholds below which the disease can invade respectively, the stunted and non-stunted host population. The dashed black lines indicate the disease free region of bistability (b) Dynamics for the case of δ = 0. In the green area only the disease free non-stunted state is stable. The yellow area indicates stable recurrent epidemics, and in the purple area there is bistability of recurrent epidemics and an endemic state. The orange line is a Hopf bifurcation, either supercritical (solid line) or subcritical (dashed line). Other lines and areas are as described in Fig 4a (c) Bifurcation diagram for the subcritical Hopf bifurcation for β = 0.06. The bifurcation resembles that of Fig 3c, but now there is a region of bistability between an endemic state and a stable limit cycle for 0.588 < μP < 0.595. The red area denotes the amplitude of the stable limit cycle, and the dashed red line shows the minimum and maximum of the unstable limit cycle. For parameters see Fig 3.

Mentions: Until now, we have fixed the invasion threshold for the disease at JS = 1.67. Here, we explore what happens if we vary the disease invasion threshold. We demonstrate this by varying the disease infectivity β, but varying disease virulence α, will yield similar results. In Fig 4a we plot a two-parameter diagram for the case of δ = 1 (i.c. full competitive ability of infected juveniles), were we map the dynamics as a function of the predator death rate μP and the disease invasion threshold (μJ+α)/β. There exist three distinct areas that differ in dynamics. In the white area, the disease cannot invade, and the dynamics are identical to Fig 1. In the blue shaded area there is bistability between a stunted endemic state and a non-stunted disease free state. In the pink area, there is a single endemic equilibrium. The red line indicates the threshold below which the predator goes extinct in the endemic state. The green line indicates the threshold below which a stunted endemic state exists, and the blue line is the threshold below which a non-stunted endemic state exists. With increasing severity of the disease (i.c. increasing infectivity β and/or decreasing virulence α) the area of bistability increases, and the predator is reduced to lower densities or even extinction.


Competition and Facilitation between a Disease and a Predator in a Stunted Prey Population.

Boerlijst MC, de Roos AM - PLoS ONE (2015)

Dynamics for varying disease invasion threshold.Plotting dynamics as a function of predator death rate μP, and disease invasion threshold (μJ+α)/β. (a) Dynamics for the case of δ = 1. In the white area the disease cannot invade, and in the pink area there is a single endemic equilibrium. The blue area indicates bistability between a stunted endemic state and a non-stunted disease free state. The red line denotes predator extinction. The green and blue line are thresholds below which the disease can invade respectively, the stunted and non-stunted host population. The dashed black lines indicate the disease free region of bistability (b) Dynamics for the case of δ = 0. In the green area only the disease free non-stunted state is stable. The yellow area indicates stable recurrent epidemics, and in the purple area there is bistability of recurrent epidemics and an endemic state. The orange line is a Hopf bifurcation, either supercritical (solid line) or subcritical (dashed line). Other lines and areas are as described in Fig 4a (c) Bifurcation diagram for the subcritical Hopf bifurcation for β = 0.06. The bifurcation resembles that of Fig 3c, but now there is a region of bistability between an endemic state and a stable limit cycle for 0.588 < μP < 0.595. The red area denotes the amplitude of the stable limit cycle, and the dashed red line shows the minimum and maximum of the unstable limit cycle. For parameters see Fig 3.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4492505&req=5

pone.0132251.g004: Dynamics for varying disease invasion threshold.Plotting dynamics as a function of predator death rate μP, and disease invasion threshold (μJ+α)/β. (a) Dynamics for the case of δ = 1. In the white area the disease cannot invade, and in the pink area there is a single endemic equilibrium. The blue area indicates bistability between a stunted endemic state and a non-stunted disease free state. The red line denotes predator extinction. The green and blue line are thresholds below which the disease can invade respectively, the stunted and non-stunted host population. The dashed black lines indicate the disease free region of bistability (b) Dynamics for the case of δ = 0. In the green area only the disease free non-stunted state is stable. The yellow area indicates stable recurrent epidemics, and in the purple area there is bistability of recurrent epidemics and an endemic state. The orange line is a Hopf bifurcation, either supercritical (solid line) or subcritical (dashed line). Other lines and areas are as described in Fig 4a (c) Bifurcation diagram for the subcritical Hopf bifurcation for β = 0.06. The bifurcation resembles that of Fig 3c, but now there is a region of bistability between an endemic state and a stable limit cycle for 0.588 < μP < 0.595. The red area denotes the amplitude of the stable limit cycle, and the dashed red line shows the minimum and maximum of the unstable limit cycle. For parameters see Fig 3.
Mentions: Until now, we have fixed the invasion threshold for the disease at JS = 1.67. Here, we explore what happens if we vary the disease invasion threshold. We demonstrate this by varying the disease infectivity β, but varying disease virulence α, will yield similar results. In Fig 4a we plot a two-parameter diagram for the case of δ = 1 (i.c. full competitive ability of infected juveniles), were we map the dynamics as a function of the predator death rate μP and the disease invasion threshold (μJ+α)/β. There exist three distinct areas that differ in dynamics. In the white area, the disease cannot invade, and the dynamics are identical to Fig 1. In the blue shaded area there is bistability between a stunted endemic state and a non-stunted disease free state. In the pink area, there is a single endemic equilibrium. The red line indicates the threshold below which the predator goes extinct in the endemic state. The green line indicates the threshold below which a stunted endemic state exists, and the blue line is the threshold below which a non-stunted endemic state exists. With increasing severity of the disease (i.c. increasing infectivity β and/or decreasing virulence α) the area of bistability increases, and the predator is reduced to lower densities or even extinction.

Bottom Line: In contrast to predators, parasites do not necessarily kill their host but instead they may change host life history.Here, the disease facilitates the predator, and predator density will be substantially increased.We discuss the implications of our results for the dynamics and structure of the natural Ligula-Roach system.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, P.O. Box 94248, 1090 GE, Amsterdam, The Netherlands.

ABSTRACT
The role of diseases and parasites has received relatively little attention in modelling ecological dynamics despite mounting evidence of their importance in structuring communities. In contrast to predators, parasites do not necessarily kill their host but instead they may change host life history. Here, we study the impact of a parasite that selectively infects juvenile prey individuals and prevents them from maturing into adults. The model is inspired by the Ligula intestinalis tape worm and its cyprinid fish host Rutilis rutilis. We demonstrate that the parasite can promote as well as demote the so-called stunting in its host population, that is, the accumulation of juvenile prey, which leads to strong exploitation competition and consequently to a bottleneck in maturation. If competition between infected and uninfected individuals is strong, stunting will be enhanced and bistability between a stunted and non-stunted prey population occurs. In this case, the disease competes with the predator of its host species, possibly leading to predator extinction. In contrast, if the competition between infected and uninfected individuals is weak, the stunting is relieved, and epi-zoonotic cycles will occur, with recurrent epidemic outbreaks. Here, the disease facilitates the predator, and predator density will be substantially increased. We discuss the implications of our results for the dynamics and structure of the natural Ligula-Roach system.

No MeSH data available.


Related in: MedlinePlus