85,774 research outputs found
Geometric factors influencing the diet of vertebrate predators in marine and terrestrial environments
Predator–prey relationships are vital to ecosystem function and there is a need for greater predictive
understanding of these interactions. We develop a geometric foraging model predicting minimum
prey size scaling in marine and terrestrial vertebrate predators taking into account habitat
dimensionality and biological traits. Our model predicts positive predator–prey size relationships
on land but negative relationships in the sea. To test the model, we compiled data on diets of 794
predators (mammals, snakes, sharks and rays). Consistent with predictions, both terrestrial endotherm
and ectotherm predators have significantly positive predator–prey size relationships. Marine
predators, however, exhibit greater variation. Some of the largest predators specialise on small
invertebrates while others are large vertebrate specialists. Prey–predator mass ratios were generally
higher for ectothermic than endothermic predators, although dietary patterns were similar.
Model-based simulations of predator–prey relationships were consistent with observed relationships,
suggestin
Fluctuations and Correlations in Lattice Models for Predator-Prey Interaction
Including spatial structure and stochastic noise invalidates the classical
Lotka-Volterra picture of stable regular population cycles emerging in models
for predator-prey interactions. Growth-limiting terms for the prey induce a
continuous extinction threshold for the predator population whose critical
properties are in the directed percolation universality class. Here, we discuss
the robustness of this scenario by considering an ecologically inspired
stochastic lattice predator-prey model variant where the predation process
includes next-nearest-neighbor interactions. We find that the corresponding
stochastic model reproduces the above scenario in dimensions 1< d \leq 4, in
contrast with mean-field theory which predicts a first-order phase transition.
However, the mean-field features are recovered upon allowing for
nearest-neighbor particle exchange processes, provided these are sufficiently
fast.Comment: 5 pages, 4 figures, 2-column revtex4 format. Emphasis on the lattice
predator-prey model with next-nearest-neighbor interaction (Rapid
Communication in PRE
Model Predator Dan Prey Dengan Model Susceptible - Infected – Susceptible
A predator-prey model with infected prey is an interaction between a predator and a prey population with infected prey. This model is a result of the predator-prey model with logistic growth in the prey population which is combined with Susceptible-Infected-Susceptible (SIS) model in the prey. The equations in this model are non linear differential equation with three dependent variables. In this system, is size of prey population at time , is the fraction of the prey that are infectious at time and is size of predator population at time . It is assumed that infected prey are vulnerable than by a factor . Stability analysis system is done to all five equilibriain this linearized. Each of stability in those equilibria points is based on theeigen values
Effects of rapid prey evolution on predator-prey cycles
We study the qualitative properties of population cycles in a predator-prey
system where genetic variability allows contemporary rapid evolution of the
prey. Previous numerical studies have found that prey evolution in response to
changing predation risk can have major quantitative and qualitative effects on
predator-prey cycles, including: (i) large increases in cycle period, (ii)
changes in phase relations (so that predator and prey are cycling exactly out
of phase, rather than the classical quarter-period phase lag), and (iii)
"cryptic" cycles in which total prey density remains nearly constant while
predator density and prey traits cycle. Here we focus on a chemostat model
motivated by our experimental system [Fussmann et al. 2000,Yoshida et al. 2003]
with algae (prey) and rotifers (predators), in which the prey exhibit rapid
evolution in their level of defense against predation. We show that the effects
of rapid prey evolution are robust and general, and furthermore that they occur
in a specific but biologically relevant region of parameter space: when traits
that greatly reduce predation risk are relatively cheap (in terms of reductions
in other fitness components), when there is coexistence between the two prey
types and the predator, and when the interaction between predators and
undefended prey alone would produce cycles. Because defense has been shown to
be inexpensive, even cost-free, in a number of systems [Andersson and Levin
1999, Gagneux et al. 2006,Yoshida et al. 2004], our discoveries may well be
reproduced in other model systems, and in nature. Finally, some of our key
results are extended to a general model in which functional forms for the
predation rate and prey birth rate are not specified.Comment: 35 pages, 8 figure
Predator-prey cycles from resonant amplification of demographic stochasticity
In this paper we present the simplest individual level model of predator-prey
dynamics and show, via direct calculation, that it exhibits cycling behavior.
The deterministic analogue of our model, recovered when the number of
individuals is infinitely large, is the Volterra system (with density-dependent
prey reproduction) which is well-known to fail to predict cycles. This
difference in behavior can be traced to a resonant amplification of demographic
fluctuations which disappears only when the number of individuals is strictly
infinite. Our results indicate that additional biological mechanisms, such as
predator satiation, may not be necessary to explain observed predator-prey
cycles in real (finite) populations.Comment: 4 pages, 2 figure
A synthetic Escherichia coli predator–prey ecosystem
We have constructed a synthetic ecosystem consisting of two Escherichia coli populations, which communicate bi-directionally through quorum sensing and regulate each other's gene expression and survival via engineered gene circuits. Our synthetic ecosystem resembles canonical predator–prey systems in terms of logic and dynamics. The predator cells kill the prey by inducing expression of a killer protein in the prey, while the prey rescue the predators by eliciting expression of an antidote protein in the predator. Extinction, coexistence and oscillatory dynamics of the predator and prey populations are possible depending on the operating conditions as experimentally validated by long-term culturing of the system in microchemostats. A simple mathematical model is developed to capture these system dynamics. Coherent interplay between experiments and mathematical analysis enables exploration of the dynamics of interacting populations in a predictable manner
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