Quantitative Ecology and Evolutionary Biology: Integrating by Otso Ovaskainen, Henrik Johan de Knegt, Maria del Mar

By Otso Ovaskainen, Henrik Johan de Knegt, Maria del Mar Delgado

This novel, interdisciplinary textual content achieves an integration of empirical info and thought because of mathematical types and statistical equipment. The emphasis all through is on spatial ecology and evolution, specially at the interaction among environmental heterogeneity and organic tactics. The e-book presents a coherent topic through interlinking the modelling methods used for various subfields of spatial ecology: circulate ecology, inhabitants ecology, group ecology, and genetics and evolutionary ecology (each being represented through a separate chapter). each one bankruptcy starts off through describing the idea that of every modelling procedure in its organic context, is going directly to current the correct mathematical versions and statistical equipment, and ends with a dialogue of the advantages and barriers of every technique. The recommendations and methods mentioned through the e-book are illustrated all through with the aid of empirical examples.

This is a complicated textual content compatible for any biologist attracted to the combination of empirical facts and idea in spatial ecology/evolution by using quantitative/statistical tools and mathematical types. The booklet can be of relevance and use as a textbook for graduate-level classes in spatial ecology, ecological modelling, theoretical ecology, and statistical ecology.

Show description

Read Online or Download Quantitative Ecology and Evolutionary Biology: Integrating models with data PDF

Best evolution books

Denying Evolution: Creationism, Scientism, and the Nature of Science

Denying Evolution goals at taking a clean examine the evolution–creation controversy. It offers a really "balanced" remedy, no longer within the experience of treating creationism as a sound clinical thought (it demonstrably is not), yet within the experience of dividing the blame for the talk both among creationists and scientists—the former for subscribing to varied sorts of anti-intellectualism, the latter for discounting technology schooling and proposing technology as scientism to the general public and the media.

L'outre-mer francais : Evolution institutionnelle et affirmations identitaires

Les derniers "confettis" de l'empire colonial français demeurent castle mal connus. Jusqu'à 2003, notre droit distinguait implicitement ceux des territoires dont les populations étaient assimilables à l. a. state française (départements) et ceux dont elles ne l'étaient pas (territoires). Depuis, cette contrast a laissé position à une palette de statuts issus de négociations entre chacun de ces territoires et los angeles République.

Linguistic evolution through language acquisition: Formal and computational models

This groundbreaking research of the way young ones collect language and the results on language switch over the generations attracts on quite a lot of examples. The booklet covers particular syntactic universals and the character of syntactic switch. It studies the language-learning mechanisms required to obtain an latest linguistic method (accurately and to impose additional constitution on an rising process) and the evolution of language(s) on the subject of this studying mechanism.

The Evolution of Dynamics: Vibration Theory from 1687 to 1742

During this learn we're enthusiastic about Vibration conception and the matter of Dynamics through the part century that the e-book of Newton's Principia. the connection that existed among those topic! ! is obscured in retrospection for it's now nearly very unlikely to not view (linear) Vibration conception as linearized Dynamics.

Extra info for Quantitative Ecology and Evolutionary Biology: Integrating models with data

Sample text

E. that the individuals do not die or reproduce when crossing the edges. 7L), k(L) = D(M) /D(L) , k(H) = D(M) /D(H) . In this model the probability density becomes discontinuous across the edge even if the edge is invisible for the individual, because the individual spends more time on that side of the edge where it moves slower. 6. 7L): k(L) = exp zb a(L) /D /exp zb a(M) /D , k(H) = exp zb a(H) /D /exp zb a(M) /D . In this model, the probability density is discontinuous across the edges because the individual shows edge-mediated behaviour.

Assuming that the number of steps that the random walker takes is sufficiently large, the behaviour of random walk (a Lagrangian model) is approximated by diffusion (an Eulerian model). In the diffusion model, the state variable is the probability that the individual is at location (x, y) at time t, denoted by v(x, y, t). As we construct our model in continuous space, v is actually not a probability but technically a probability density, an issue to which we will return later. 2) where the parameter D is called the diffusion coefficient, and for the random walk model described earlier it obtains the value D = L2 /(4τ ) = 1/4.

This is intuitive, as the random component of movement will smooth out the pattern generated by the deterministic tendency to climb uphill. Our assumption of the diffusion rate being inversely proportional to altitude was rather arbitrary. We could have more generally assumed that the diffusion rate is any decreasing function of altitude. Similarly, we could have assumed that the bias term is not directly proportional to the negative of the slope but any decreasing function of the slope of the altitude.

Download PDF sample

Rated 4.38 of 5 – based on 36 votes