Suchergebnisse

Intro -- Preface -- Contents -- 1 Introduction -- 1.1 Linking individuals, traits, and population dynamics -- 1.2 Survey of research applications -- 1.3 About this book -- 1.3.1 Mathematical prerequisites -- 1.3.2 Statistical prerequisites and data requirements -- 1.3.3 Programming prerequisites -- 1.4 Notation and nomenclature -- 2 Simple Deterministic IPM -- 2.1 The individual-level state variable -- 2.2 Key assumptions and model structure -- 2.3 From life cycle to model: specifying a simple IPM -- 2.3.1 Changes -- 2.4 Numerical implementation -- 2.5 Case study 1A: A monocarpic perennial -- 2.5.1 Summary of the demography -- 2.5.2 Individual-based model (IBM) -- 2.5.3 Demographic analysis using lm and glm -- 2.5.4 Implementing the IPM -- 2.5.5 Basic analysis: projection and asymptotic behavior -- 2.5.6 Always quantify your uncertainty! -- 2.6 Case study 2A: Ungulate -- 2.6.1 Summary of the demography -- 2.6.2 Individual-based model -- 2.6.3 Demographic analysis -- 2.6.4 Implementing the IPM -- 2.6.5 Basic analysis -- 2.7 Model diagnostics -- 2.7.1 Model structure -- 2.7.2 Demographic rate models -- 2.7.3 Implementation: choosing the size range -- 2.7.4 Implementation: the number of mesh points -- 2.8 Looking ahead -- 2.9 Appendix: Probability Densities and the Change of Variables Formula -- 2.10 Appendix: Constructing IPMs when more than one census per time year is available -- 3 Basic Analyses 1: Demographic Measures and Eventsin the Life Cycle -- 3.1 Demographic quantities -- 3.1.1 Population growth -- 3.1.2 Age-specific vital rates -- 3.1.3 Generation time -- 3.2 Life cycle properties and events -- 3.2.1 Mortality: age and size at death -- 3.2.2 Reproduction: who, when, and how much? -- 3.2.3 And next… -- 3.3 Case study 1B: Monocarp life cycle properties and events -- 3.3.1 Population growth.

When plants establish outside their native range, their ability to adapt to the new environment is influenced by both demography and dispersal. However, the relative importance of these two factors is poorly understood. To quantify the influence of demography and dispersal on patterns of genetic diversity underlying adaptation, we used data from a globally distributed demographic research network comprising 35 native and 18 nonnative populations of Plantago lanceolata. Species-specific simulation experiments showed that dispersal would dilute demographic influences on genetic diversity at local scales. Populations in the native European range had strong spatial genetic structure associated with geographic distance and precipitation seasonality. In contrast, nonnative populations had weaker spatial genetic structure that was not associated with environmental gradients but with higher within-population genetic diversity. Our findings show that dispersal caused by repeated, long-distance, human-mediated introductions has allowed invasive plant populations to overcome environmental constraints on genetic diversity, even without strong demographic changes. The impact of invasive plants may, therefore, increase with repeated introductions, highlighting the need to constrain future introductions of species even if they already exist in an area. ; This research was supported by a Science Foundation Ireland grant to Y.M.B. (European Research Council Development Programme15/ERCD/2803). A.L.S. was supported by a Marie Skłodowska-Curie Individual Fellowship (746191) under the European Union Horizon 2020 Programme for Research and Innovation. Additional support came from: Catalan Institution for Research and Advanced Studies (ICREA) (Academia Award to S.M.-B.), Spanish Government (Ministerio de Economía y Competitividad BFU2015-64001-P/MINECO/FEDER to S.M.-B.), Estonian Ministry of Education and Research (Institutional Research Funding IUT20–29 to M.P.), European Regional Development Fund (Centre of Excellence Ecol Change to M.P.), New Zealand Ministry for Business Innovation (Employment's Strategic Science Investment Fund to R.G.) and Academy of Finland (285746 to S.R.)