Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables

Methods in Ecology and Evolution - Tập 13 Số 1 - Trang 91-104 - 2022
Rémi Fay1, Matthieu Authier2, Sandra Hamel3, Stéphanie Jenouvrier4,5, Martijn van de Pol6,7, Emmanuelle Cam8, Jean‐Michel Gaillard9, Nigel G. Yoccoz10, Paul Acker1, Andrew M. Allen7, Lise M. Aubry11, Christophe Bonenfant9, Hal Caswell12, Christophe F. D. Coste1, Benjamin Larue13, Christie Le Cœur14, Marlène Gamelon1,9, Kaitlin R. Macdonald15, María Moirón16, Alex Nicol‐Harper4,17, Fanie Pelletier13, Jay J. Rotella15, Céline Teplitsky16, Laura Touzot9, Caitlin P. Wells11, Bernt‐Erik Sæther1
1Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway
2Observatoire PELAGIS UMS‐CNRS 3462 Université de la Rochelle La Rochelle France
3Département de biologie Université Laval Québec City QC Canada
4Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
5Centre d'Etudes Biologiques de Chizé UMR 7372 Centre National de la Recherche Scientifique Villiers en Bois France
6College of Science and Engineering, James Cook University, Townsville, QLD, Australia
7Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
8LEMAR CNRS IRD Ifremer Université Brest Plouzané France
9Laboratoire de Biométrie et Biologie Évolutive CNRS Unité Mixte de Recherche (UMR) 5558 Université Lyon 1 Université de Lyon Villeurbanne France
10Department of Arctic and Marine Biology, UiT–The Arctic University of Norway, Tromsø, Norway
11Fish, Wildlife and Conservation Biology Department, Colorado State University, Fort Collins, CO, USA
12Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands
13Département de biologie, Université de Sherbrooke, Sherbrooke, QC, Canada
14Department of Biosciences, Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo, Oslo, Norway
15Department of Ecology, Montana State University, Bozeman, MT, USA
16CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
17School of Ocean and Earth Science, National Oceanography Centre, University of Southampton Waterfront Campus, Southampton, UK

Tóm tắt

Abstract An increasing number of empirical studies aim to quantify individual variation in demographic parameters because these patterns are key for evolutionary and ecological processes. Advanced approaches to estimate individual heterogeneity are now using a multivariate normal distribution with correlated individual random effects to account for the latent correlations among different demographic parameters occurring within individuals. Despite the frequent use of multivariate mixed models, we lack an assessment of their reliability when applied to Bernoulli variables. Using simulations, we estimated the reliability of multivariate mixed effect models for estimating correlated fixed individual heterogeneity in demographic parameters modelled with a Bernoulli distribution. We evaluated both bias and precision of the estimates across a range of scenarios that investigate the effects of life‐history strategy, levels of individual heterogeneity and presence of temporal variation and state dependence. We also compared estimates across different sampling designs to assess the importance of study duration, number of individuals monitored and detection probability. In many simulated scenarios, the estimates for the correlated random effects were biased and imprecise, which highlight the challenge in estimating correlated random effects for Bernoulli variables. The amount of fixed among‐individual heterogeneity was frequently overestimated, and the absolute value of the correlation between random effects was almost always underestimated. Simulations also showed contrasting performances of mixed models depending on the scenario considered. Generally, estimation bias decreases and precision increases with slower pace of life, large fixed individual heterogeneity and large sample size. We provide guidelines for the empirical investigation of individual heterogeneity using correlated random effects according to the life‐history strategy of the species, as well as, the volume and structure of the data available to the researcher. Caution is warranted when interpreting results regarding correlated individual random effects in demographic parameters modelled with a Bernoulli distribution. Because bias varies with sampling design and life history, comparisons of individual heterogeneity among species is challenging. The issue addressed here is not specific to demography, making this warning relevant for all research areas, including behavioural and evolutionary studies.

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Methods in Ecology and Evolution

Tập 13 Số 1

91-104

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