19,318 research outputs found
Biological invasions in agricultural settings: insights from evolutionary biology and population genetics
Invasion biology and agriculture are intimately related for several reasons and in particular because many agricultural pest species are recent invaders. In this article we suggest that the reconstruction of invasion routes with population genetics-based methods can address fundamental questions in ecology and practical aspects of the management of biological invasions in agricultural settings. We provide a brief description of the methods used to reconstruct invasion routes and describe their main characteristics. In particular, we focus on a scenario - the bridgehead invasion scenario -, which had been overlooked until recently. We show that this scenario, in which an invasive population is the source of other invasive populations, is evolutionarily parsimonious and may have played a crucial role in shaping the distribution of many recent agricultural pests
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Evolutionary biology for the 21st century
New theoretical and conceptual frameworks are required for evolutionary biology to capitalize on the wealth of data now becoming available from the study of genomes, phenotypes, and organisms - including humans - in their natural environments.Molecular and Cellular BiologyOrganismic and Evolutionary Biolog
How Turing parasites expand the computational landscape of digital life
Why are living systems complex? Why does the biosphere contain living beings
with complexity features beyond those of the simplest replicators? What kind of
evolutionary pressures result in more complex life forms? These are key
questions that pervade the problem of how complexity arises in evolution. One
particular way of tackling this is grounded in an algorithmic description of
life: living organisms can be seen as systems that extract and process
information from their surroundings in order to reduce uncertainty. Here we
take this computational approach using a simple bit string model of coevolving
agents and their parasites. While agents try to predict their worlds, parasites
do the same with their hosts. The result of this process is that, in order to
escape their parasites, the host agents expand their computational complexity
despite the cost of maintaining it. This, in turn, is followed by increasingly
complex parasitic counterparts. Such arms races display several qualitative
phases, from monotonous to punctuated evolution or even ecological collapse.
Our minimal model illustrates the relevance of parasites in providing an active
mechanism for expanding living complexity beyond simple replicators, suggesting
that parasitic agents are likely to be a major evolutionary driver for
biological complexity.Comment: 13 pages, 8 main figures, 1 appendix with 5 extra figure
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
A Review on the Application of Natural Computing in Environmental Informatics
Natural computing offers new opportunities to understand, model and analyze
the complexity of the physical and human-created environment. This paper
examines the application of natural computing in environmental informatics, by
investigating related work in this research field. Various nature-inspired
techniques are presented, which have been employed to solve different relevant
problems. Advantages and disadvantages of these techniques are discussed,
together with analysis of how natural computing is generally used in
environmental research.Comment: Proc. of EnviroInfo 201
Is there an optimization in bounded rationality? The ratio of aspiration levels
Simon’s (1955) famous paper was one of the first to cast doubt on the validity of rational choice theory; it has been supplemented by many more papers in the last three and a half decades. Nevertheless, rational choice theory plays a crucial role in classical and neoclassical economic theory, which presumes a completely rational agent. The central points characterizing such an agent are: (1) The agent uses all the information that is given to him. (2) The agent has clear preferences with respect to the results of different actions. (3) The agent has adequate competences to optimize his decisions. As an alternative to this conception, Simon (1955) himself suggests the concept of “bounded rationality”. In this context, Simon (1956) discusses a principle, which he names the “satisficing principle” (for explanations with respect to this notion cf. Gigerenzer & Todd 1999, p. 13). It assumes that, instead of searching for an optimal action, the search for an action terminates if an alternative has been found that satisfies a given “aspiration level”. It will be demonstrated that although the satisficing principle is nothing but a heuristic, there is a mathematical optimization at work when aspiration levels are used in this kind of problems. The question about the optimal aspiration level can be posed. Optimization within the framework of bounded rationality is possible. However, the way in which such an optimization can be achieved is very simple: Optimal thresholds in binary sequential decisions rest with the median.
Adaptive dynamics in logistic branching populations
We consider a trait-structured population subject to mutation, birth and
competition of logistic type, where the number of coexisting types may
fluctuate. Applying a limit of rare mutations to this population while keeping
the population size finite leads to a jump process, the so-called `trait
substitution sequence', where evolution proceeds by successive invasions and
fixations of mutant types. The probability of fixation of a mutant is
interpreted as a fitness landscape that depends on the current state of the
population. It was in adaptive dynamics that this kind of model was first
invented and studied, under the additional assumption of large population.
Assuming also small mutation steps, adaptive dynamics' theory provides a
deterministic ODE approximating the evolutionary dynamics of the dominant trait
of the population, called `canonical equation of adaptive dynamics'. In this
work, we want to include genetic drift in this models by keeping the population
finite. Rescaling mutation steps (weak selection) yields in this case a
diffusion on the trait space that we call `canonical diffusion of adaptive
dynamics', in which genetic drift (diffusive term) is combined with directional
selection (deterministic term) driven by the fitness gradient. Finally, in
order to compute the coefficients of this diffusion, we seek explicit
first-order formulae for the probability of fixation of a nearly neutral mutant
appearing in a resident population. These formulae are expressed in terms of
`invasibility coefficients' associated with fertility, defense, aggressiveness
and isolation, which measure the robustness (stability w.r.t. selective
strengths) of the resident type. Some numerical results on the canonical
diffusion are also given
The use of multilayer network analysis in animal behaviour
Network analysis has driven key developments in research on animal behaviour
by providing quantitative methods to study the social structures of animal
groups and populations. A recent formalism, known as \emph{multilayer network
analysis}, has advanced the study of multifaceted networked systems in many
disciplines. It offers novel ways to study and quantify animal behaviour as
connected 'layers' of interactions. In this article, we review common questions
in animal behaviour that can be studied using a multilayer approach, and we
link these questions to specific analyses. We outline the types of behavioural
data and questions that may be suitable to study using multilayer network
analysis. We detail several multilayer methods, which can provide new insights
into questions about animal sociality at individual, group, population, and
evolutionary levels of organisation. We give examples for how to implement
multilayer methods to demonstrate how taking a multilayer approach can alter
inferences about social structure and the positions of individuals within such
a structure. Finally, we discuss caveats to undertaking multilayer network
analysis in the study of animal social networks, and we call attention to
methodological challenges for the application of these approaches. Our aim is
to instigate the study of new questions about animal sociality using the new
toolbox of multilayer network analysis.Comment: Thoroughly revised; title changed slightl
Ab Initio Modeling of Ecosystems with Artificial Life
Artificial Life provides the opportunity to study the emergence and evolution
of simple ecosystems in real time. We give an overview of the advantages and
limitations of such an approach, as well as its relation to individual-based
modeling techniques. The Digital Life system Avida is introduced and prospects
for experiments with ab initio evolution (evolution "from scratch"),
maintenance, as well as stability of ecosystems are discussed.Comment: 13 pages, 2 figure
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