Titlebook: Data-driven Modelling of Structured Populations; A Practical Guide to Stephen P. Ellner,Dylan Z. Childs,Mark Rees Book 2016 Springer Intern

兵團(tuán)

Evaluation in Education and Human Servicesethods for finding ESS are presented. We then extend these ideas to cover stochastic environments and function-valued traits. For function-valued traits we model the entire function rather than the underlying parameters, and so we are not tied to a specific fitted function.

prodrome

C. G. Morgan,Y. P. Yianni,S. S. Sandhuduals who can be re-found at each census. Better methods for fitting IPMs using mark-recapture data where recapture is not certain, or data on unmarked individuals, will greatly expand the scope for IPM applications, especially applications to animal populations.

不近人情

Simple Deterministic IPM, illustrate the process of fitting an IPM to population data, we generate artificial data using individual-based models of the monocarpic perennial ., and of the Soay sheep (.) population on St. Kilda (Clutton-Brock and Pemberton 2004).

使害羞

Density Dependence,f density dependence. We first present some examples of formulating, parameterizing, and implementing a density-dependent IPM. We outline the general theory of density-dependent IPMs, and then look at what the theory tells us about the Soay sheep IPM when we add intraspecific competition, and how the dynamics depend on demographic parameters.

裂隙

遍及

Flinch

https://doi.org/10.1007/978-1-4613-1919-1bation. We begin by showing how to calculate the . and . of . to perturbations of the kernel, vital rate functions, and their parameters. We finish by briefly describing how to derive analogous expressions for life cycle statistics.

惡心

Deciding to Enter the Research Fieldre presented. Methods for construction and implementation of density-independent IPMs are then presented. The key properties of the stochastic growth rate (.) are summarized, along with methods for its estimation and appropriate perturbation theory. Methods for implementing Life Table Response Experiments (LTREs) analyses are discussed.

Ingredient

Data-driven Modelling of Structured Populations978-3-319-28893-2Series ISSN 2193-4789 Series E-ISSN 2193-4797

Torrid

Thomas A. Ban M.D.,Leonard Levy M.D.ection Model (IPM), and survey various extensions to the basic IPM. Advice on using the book and the things you need to know (maths, stats, and programming-wise) are then covered. A final section covers notation and highlights areas where confusion might occur as a result of symbols having different meanings depending on the context.