There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Genetics and analysis of quantitative traits

Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Citation classic - optimal foraging - a selective review of theory and tests

A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems In many cases, however, the edges are not continuously active As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts In some cases, edges are active for non-negligible periods of time: eg, the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks

Temporal Networks

Ecological and evolutionary dynamics can occur on similar timescales. However, theoretical predictions of how rapid evolution can affect ecological dynamics are inconclusive and often depend on untested model assumptions. Here we report that rapid prey evolution in response to oscillating predator density affects predator-prey (rotifer-algal) cycles in laboratory microcosms. Our experiments tested explicit predictions from a model for our system that allows prey evolution. We verified the predicted existence of an evolutionary tradeoff between algal competitive ability and defence against consumption, and examined its effects on cycle dynamics by manipulating the evolutionary potential of the prey population. Single-clone algal cultures (lacking genetic variability) produced short cycle periods and typical quarter-period phase lags between prey and predator densities, whereas multi-clonal (genetically variable) algal cultures produced long cycles with prey and predator densities nearly out of phase, exactly as predicted. These results confirm that prey evolution can substantially alter predator-prey dynamics, and therefore that attempts to understand population oscillations in nature cannot neglect potential effects from ongoing rapid evolution.

/pdf/rapid-evolution-drives-ecological-dynamics-in-a-predator-2vaualam26.pdf

Rapid evolution drives ecological dynamics in a predator–prey system

Summary

1
We review theoretical and empirical studies to identify instances where evolutionary processes significantly affect the dynamics of populations, communities and ecosystems.

2
Early theoretical work on eco-evolutionary dynamics was concerned with the effect of (co)evolution on the stability of two-species predator–prey systems and the occurrence of character displacement in simple competitive systems. Today's theoretical ecologists are extending this work to study the eco-evolutionary dynamics of multispecies communities and the functioning and evolutionary emergence of ecosystems.

3
In terms of methodology, eco-evolutionary modelling has diversified from simple, locus-based population genetic models to encompass models of clonal selection, quantitative trait dynamics and adaptive dynamics.

4
The few empirical studies on community dynamics that explicitly considered evolutionary processes support the view that evolutionary and ecological dynamics often occur on similar time-scales, and that they co-determine the dynamical behaviour of ecological communities.

http://max2.ese.u-psud.fr/epc/conservation/PDFs/HIPE/Fussmann2007.pdf

Eco‐evolutionary dynamics of communities and ecosystems

Population biologists have long been interested in the oscillations in population size displayed by many organisms in the field and laboratory. A wide range of deterministic mathematical models predict that these fluctuations can be generated internally by nonlinear interactions among species and, if correct, would provide important insights for understanding and predicting the dynamics of interacting populations. We studied the dynamical behavior of a two-species aquatic laboratory community encompassing the interactions between a demographically structured herbivore population, a primary producer, and a mineral resource, yet still amenable to description and parameterization using a mathematical model. The qualitative dynamical behavior of our experimental system, that is, cycles, equilibria, and extinction, is highly predictable by a simple nonlinear model.

https://science.sciencemag.org/content/sci/290/5495/1358.full.pdf

Crossing the Hopf Bifurcation in a Live Predator-Prey System

Microevolution is typically ignored as a factor directly affecting ongoing population dynamics. We show here that density-dependent natural selection has a direct and measurable effect on a planktonic predator-prey interaction. We kept populations of Brachionus calyciflorus, a monogonont rotifer that exhibits cyclical parthenogenesis, in continuous flow-through cultures (chemostats) for more than 900 days. Initially, females frequently produced male offspring, especially at high population densities. We observed rapid evolution, however, towards low propensity to reproduce sexually, and by 750 days, reproduction had become entirely asexual. There was strong selection favouring asexual reproduction because, under the turbulent chemostat regime, males were unable to mate with females, produced no offspring, and so had zero fitness. In replicated chemostat experiments we found that this evolutionary process directly influenced the population dynamics. We observed very specific but reproducible plankton dynamics which are explained well by a mathematical model that explicitly includes evolution. This model accounts for both asexual and sexual reproduction and treats the propensity to reproduce sexually as a quantitative trait under selection. We suggest that a similar amalgam of ecological and evolutionary mechanisms may drive the dynamics of rapidly reproducing organisms in the wild.

/pdf/evolution-as-a-critical-component-of-plankton-dynamics-40e3db80g8.pdf

Evolution as a critical component of plankton dynamics

Biologists use mathematical functions to model, understand and predict nature. For most biological processes, however, the exact analytical form is not known. This is also true for one of the most basic life processes: the uptake of food or resources. We show that the use of several nearly indistinguishable functions, which can serve as phenomenological descriptors of resource uptake, may lead to alarmingly different dynamical behaviour in a simple community model. More specifically, we demonstrate that the degree of resource enrichment needed to destabilize the community dynamics depends critically on the mathematical nature of the uptake function.

Gregor F. Fussmann

Papers

Rapid evolution drives ecological dynamics in a predator–prey system

Eco‐evolutionary dynamics of communities and ecosystems

Crossing the Hopf Bifurcation in a Live Predator-Prey System

Evolution as a critical component of plankton dynamics

Community response to enrichment is highly sensitive to model structure.