Integrated population models: a novel analysis framework for deeper insights into population dynamics

Abstract

Integrated population models (IPMs) represent the single, unified analysis of population count data and demographic data. This modelling framework is quite novel and can be implemented within the classical or the Bayesian mode of statistical inference. Here, we briefly show the basic steps that need to be taken when an integrated population model is adopted, and review existing integrated population models for birds and mammals. There are important advantages of integrated compared to conventional analyses that analyse each dataset separately and then try to make an inference about population dynamics. First, integrated population models allow the estimating of more demographic quantities, because there is information about all demographic processes operating in a population, and this information is exploited. Second, parameter estimates become more precise, and this enhances statistical power. Finally, all sources of uncertainty due to process variability and the sampling process(es) are adequately included. Core of the integrated models is the link of changes in the population size and the demographic rates via a demographic model (usually a Leslie matrix model) and the likelihoods of all existing datasets. We discuss some critical assumptions that are typically made in integrated population models and highlight fruitful areas of future research. Currently, we have found 25 studies that used integrated population models. Central to most studies was statistical development rather than their application to address an ecological question, which is not surprising given that integrated population models are still a new development. We predict that integrated population models will become a common and important tool in studies of population dynamics, both in ecology and its applications, such as conservation biology or wildlife management. Keywords

Extinction Risk and Conservation Options for Maui Parrotbill, an Endangered Hawaiian Honeycreeper

“…observation error models to both data sets, and integrates the analysis to estimate key demographic parameters using all available data (e.g., Schaub and Abadi 2011;Rushing et al 2017).…”

When Do Mountain Whitefish (Prosopium williamsoni) Spawn? A Comparison of Estimates Based on Gonadosomatic Indices and Spawner and Egg Counts

“…Integrated models provide estimates based on the information in different datasets [38]. They are of interest in the current context because they would allow all the available information to be incorporated into a single model.…”

Literature review of giant gartersnake (<em>Thamnophis gigas</em>) biology and conservation

“…CMR studies are used to estimate abundance (Dorazio and Royle, 2003;Chao and Huggins, 2005a;Wylie and others, 2010;Halstead and others, 2011c;Couturier and others, 2013); density (Efford, 2004;Royle and Young, 2008;Royle and others, 2009;Kéry and others, 2011); survival (Williams and others, 2002;Stanford and King, 2004;Lind and others, 2005;Royle and Dorazio, 2008;Halstead and others, 2011c;Kéry and Schaub, 2011); recruitment (Gimenez and others, 2007;Dupuis and Schwarz, 2007;Halstead and others, 2011c); population growth rate (Kéry and Royle, 2009;Schaub and Abadi, 2011;Halstead and others, 2011c;Couturier and others, 2013); and individual growth rate, age, and asymptotic size (Eaton and Link, 2011;Fellers and others, 2013). The purpose of CMR methods is to obtain unbiased estimates of demographic parameters that account for the imperfect detection of individuals in the population (Williams and others, 2002;Amstrup and others, 2005;Royle and Dorazio, 2008;King and others, 2009;Kéry and Schaub, 2011) and the variables that affect the probability that an individual is detected or captured (for example, weather, effort, date, etc.).…”