scholarly journals Incorporating variability in simulations of seasonally forced phenology using integral projection models

2017 ◽  
Vol 8 (1) ◽  
pp. 162-175 ◽  
Author(s):  
Devin W. Goodsman ◽  
Brian H. Aukema ◽  
Nate G. McDowell ◽  
Richard S. Middleton ◽  
Chonggang Xu
Keyword(s):  
Integral Projection Models ◽  
Integral Projection

scholarly journals Advancing population ecology with integral projection models: a practical guide

2014 ◽  
Vol 5 (2) ◽  
pp. 99-110 ◽  
Author(s):  
Cory Merow ◽  
Johan P. Dahlgren ◽  
C. Jessica E. Metcalf ◽  
Dylan Z. Childs ◽  
Margaret E.K. Evans ◽  
...  
Keyword(s):  
Population Ecology ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Practical Guide

Integral projection models

2021 ◽  
pp. 181-196
Author(s):  
Edgar J. González ◽  
Dylan Z. Childs ◽  
Pedro F. Quintana-Ascencio ◽  
Roberto Salguero-Gómez
Keyword(s):  
Population Dynamics ◽  
Environmental Variables ◽  
Linear Models ◽  
Vital Rates ◽  
Matrix Population Models ◽  
Generalised Linear Models ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Over Time

Integral projection models (IPMs) allow projecting the behaviour of a population over time using information on the vital processes of individuals, their state, and that of the environment they inhabit. As with matrix population models (MPMs), time is treated as a discrete variable, but in IPMs, state and environmental variables are continuous and are related to the vital rates via generalised linear models. Vital rates in turn integrate into the population dynamics in a mechanistic way. This chapter provides a brief description of the logic behind IPMs and their construction, and, because they share many of the analyses developed for MPMs, it only emphasises how perturbation analyses can be performed with respect to different model elements. The chapter exemplifies the construction of a simple and a more complex IPM structure with an animal and a plant case study, respectively. Finally, inverse modelling in IPMs is presented, a method that allows population projection when some vital rates are not observed.

Integral projection models for finite populations in a stochastic environment

Ecology ◽  
2011 ◽  
Vol 92 (5) ◽  
pp. 1146-1156 ◽  
Author(s):  
Yngvild Vindenes ◽  
Steinar Engen ◽  
Bernt-Erik Sæther
Keyword(s):  
Stochastic Environment ◽  
Finite Populations ◽  
Integral Projection Models ◽  
Integral Projection

scholarly journals Investigating the interaction between ungulate grazing and resource effects on Vaccinium myrtillus populations with integral projection models

Oecologia ◽  
2010 ◽  
Vol 163 (3) ◽  
pp. 695-706 ◽  
Author(s):  
Stein Joar Hegland ◽  
Eelke Jongejans ◽  
Knut Rydgren
Keyword(s):  
Vaccinium Myrtillus ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Ungulate Grazing ◽  
Resource Effects

scholarly journals Avoiding unintentional eviction from integral projection models

Ecology ◽  
2012 ◽  
Vol 93 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Jennifer L. Williams ◽  
Tom E. X. Miller ◽  
Stephen P. Ellner
Keyword(s):  
Integral Projection Models ◽  
Integral Projection

Statistical modelling of annual variation for inference on stochastic population dynamics using Integral Projection Models

2015 ◽  
Vol 6 (9) ◽  
pp. 1007-1017 ◽  
Author(s):  
C. Jessica E. Metcalf ◽  
Stephen P. Ellner ◽  
Dylan Z. Childs ◽  
Roberto Salguero‐Gómez ◽  
Cory Merow ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Annual Variation ◽  
Statistical Modelling ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Stochastic Population Dynamics

scholarly journals Integral Projection Models for trees: a new parameterization method and a validation of model output

2010 ◽  
Vol 98 (2) ◽  
pp. 345-355 ◽  
Author(s):  
Pieter A. Zuidema ◽  
Eelke Jongejans ◽  
Pham D. Chien ◽  
Heinjo J. During ◽  
Feike Schieving
Keyword(s):  
Model Output ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Parameterization Method
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