1,524 research outputs found
Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory
Hubbell's 2001 neutral theory unifies biodiversity and biogeography by modelling steady-state distributions of species richness and abundances across spatio-temporal scales. Accurate predictions have issued from its core premise that all species have identical vital rates. Yet no ecologist believes that species are identical in reality. Here I explain this paradox in terms of the ecological equivalence that species must achieve at their coexistence equilibrium, defined by zero net fitness for all regardless of intrinsic differences between them. I show that the distinction of realised from intrinsic vital rates is crucial to evaluating community resilience. An analysis of competitive interactions reveals how zero-sum patterns of abundance emerge for species with contrasting life-history traits as for identical species. I develop a stochastic model to simulate community assembly from a random drift of invasions sustaining the dynamics of recruitment following deaths and extinctions. Species are allocated identical intrinsic vital rates for neutral dynamics, or random intrinsic vital rates and competitive abilities for niche dynamics either on a continuous scale or between dominant-fugitive extremes. Resulting communities have steady-state distributions of the same type for more or less extremely differentiated species as for identical species. All produce negatively skewed log-normal distributions of species abundance, zero-sum relationships of total abundance to area, and Arrhenius relationships of species to area. Intrinsically identical species nevertheless support fewer total individuals, because their densities impact as strongly on each other as on themselves. Truly neutral communities have measurably lower abundance/area and higher species/abundance ratios. Neutral scenarios can be parameterized as null hypotheses for testing competitive release, which is a sure signal of niche dynamics. Ignoring the true strength of interactions between and within species risks a substantial misrepresentation of community resilience to habitat los
Modelling Food Webs
We review theoretical approaches to the understanding of food webs. After an
overview of the available food web data, we discuss three different classes of
models. The first class comprise static models, which assign links between
species according to some simple rule. The second class are dynamical models,
which include the population dynamics of several interacting species. We focus
on the question of the stability of such webs. The third class are species
assembly models and evolutionary models, which build webs starting from a few
species by adding new species through a process of "invasion" (assembly models)
or "speciation" (evolutionary models). Evolutionary models are found to be
capable of building large stable webs.Comment: 34 pages, 2 figures. To be published in "Handbook of graphs and
networks" S. Bornholdt and H. G. Schuster (eds) (Wiley-VCH, Berlin
Population Dynamics on Complex Food Webs
In this work we analyse the topological and dynamical properties of a simple
model of complex food webs, namely the niche model. In order to underline
competition among species, we introduce "prey" and "predators" weighted overlap
graphs derived from the niche model and compare synthetic food webs with real
data. Doing so, we find new tests for the goodness of synthetic food web models
and indicate a possible direction of improvement for existing ones. We then
exploit the weighted overlap graphs to define a competition kernel for
Lotka-Volterra population dynamics and find that for such a model the stability
of food webs decreases with its ecological complexity.Comment: 11 Pages, 5 Figures, styles enclosed in the submissio
Species assembly in model ecosystems, II: Results of the assembly process
In the companion paper of this set (Capitan and Cuesta, 2010) we have
developed a full analytical treatment of the model of species assembly
introduced in Capitan et al. (2009). This model is based on the construction of
an assembly graph containing all viable configurations of the community, and
the definition of a Markov chain whose transitions are the transformations of
communities by new species invasions. In the present paper we provide an
exhaustive numerical analysis of the model, describing the average time to the
recurrent state, the statistics of avalanches, and the dependence of the
results on the amount of available resource. Our results are based on the fact
that the Markov chain provides an asymptotic probability distribution for the
recurrent states, which can be used to obtain averages of observables as well
as the time variation of these magnitudes during succession, in an exact
manner. Since the absorption times into the recurrent set are found to be
comparable to the size of the system, the end state is quickly reached (in
units of the invasion time). Thus, the final ecosystem can be regarded as a
fluctuating complex system where species are continually replaced by newcomers
without ever leaving the set of recurrent patterns. The assembly graph is
dominated by pathways in which most invasions are accepted, triggering small
extinction avalanches. Through the assembly process, communities become less
resilient (e.g., have a higher return time to equilibrium) but become more
robust in terms of resistance against new invasions.Comment: 14 pages, 13 figures. Revised versio
Phase Transitions and Spatio-Temporal Fluctuations in Stochastic Lattice Lotka-Volterra Models
We study the general properties of stochastic two-species models for
predator-prey competition and coexistence with Lotka-Volterra type interactions
defined on a -dimensional lattice. Introducing spatial degrees of freedom
and allowing for stochastic fluctuations generically invalidates the classical,
deterministic mean-field picture. Already within mean-field theory, however,
spatial constraints, modeling locally limited resources, lead to the emergence
of a continuous active-to-absorbing state phase transition. Field-theoretic
arguments, supported by Monte Carlo simulation results, indicate that this
transition, which represents an extinction threshold for the predator
population, is governed by the directed percolation universality class. In the
active state, where predators and prey coexist, the classical center
singularities with associated population cycles are replaced by either nodes or
foci. In the vicinity of the stable nodes, the system is characterized by
essentially stationary localized clusters of predators in a sea of prey. Near
the stable foci, however, the stochastic lattice Lotka-Volterra system displays
complex, correlated spatio-temporal patterns of competing activity fronts.
Correspondingly, the population densities in our numerical simulations turn out
to oscillate irregularly in time, with amplitudes that tend to zero in the
thermodynamic limit. Yet in finite systems these oscillatory fluctuations are
quite persistent, and their features are determined by the intrinsic
interaction rates rather than the initial conditions. We emphasize the
robustness of this scenario with respect to various model perturbations.Comment: 19 pages, 11 figures, 2-column revtex4 format. Minor modifications.
Accepted in the Journal of Statistical Physics. Movies corresponding to
Figures 2 and 3 are available at
http://www.phys.vt.edu/~tauber/PredatorPrey/movies
- …