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

被引:29
|
作者
Metcalf, C. Jessica E. [1 ]
Ellner, Stephen P. [2 ]
Childs, Dylan Z. [3 ]
Salguero-Gomez, Roberto [4 ,5 ]
Merow, Cory [6 ,7 ]
McMahon, Sean M. [7 ]
Jongejans, Eelke [8 ]
Rees, Mark [3 ]
机构
[1] Princeton Univ, Dept Ecol & Evolut Biol, Princeton, NJ 08544 USA
[2] Cornell Univ, Dept Ecol & Evolutionary Biol, Ithaca, NY USA
[3] Univ Sheffield, Dept Anim & Plant Sci, Sheffield S10 2TN, S Yorkshire, England
[4] Max Planck Inst Demog Res, Evolutionary Demog Lab, D-18057 Rostock, Germany
[5] Univ Queensland, Sch Biol Sci, Ctr Biodivers & Conservat Sci, St Lucia, Qld 4072, Australia
[6] US Fish & Wildlife Serv, Div Migratory Bird Management, Laurel, MD USA
[7] Smithsonian Environm Res Ctr, Edgewater, MD 21037 USA
[8] Radboud Univ Nijmegen, Dept Anim Ecol & Ecophysiol, NL-6525 ED Nijmegen, Netherlands
来源
METHODS IN ECOLOGY AND EVOLUTION | 2015年 / 6卷 / 09期
基金
美国国家科学基金会;
关键词
covariation; integral projection model; population growth rate; population projection; population viability; random vs. fixed effects; sampling effects; stochastic simulations; MATRIX MODELS; SIZE; AGE; DECISIONS; EVOLUTION; FITNESS; DENSITY;
D O I
10.1111/2041-210X.12405
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
1. Temporal fluctuations in vital rates such as survival, growth or reproduction alter long-term population dynamics and can change the dynamics from invasion and population persistence to extinction. Projections of population dynamics made in the absence of such fluctuations may consequently be misleading. However, data for estimation of yearly fluctuations in demographic parameters are often limited. Accordingly, the current diverse range of statistical and demographic modelling strategies used for stochastic population modelling may influence predictions. 2. We used simulations to explore the effects of different methods of parameter estimation on projections of population dynamics obtained using stochastic integral projection models (IPMs). The simulations were built from data on a monocarpic thistle, Carlina vulgaris, and an ungulate, Soay sheep, Ovis aries; these populations are subject to yearly fluctuation in vital rates facilitating the exploration of the effects of different methods of model construction on the properties of stochastic IPMs. Specifically, we looked at effects on the stochastic growth rate, log lambda(s), and themean and variance in the one-step population growth rate (Nt+1/N-t). 3. Our analyses showed that none of the tested approaches resulted in large biases in the estimation of log lambda(s). However, when realistic study durations (e.g. 12 years) were used for statistical modelling, the confidence intervals around the lambda(s) estimates remained large. Estimation of the variance in one-step population growth rates, on the other hand, was strongly sensitive to the method employed, and the overestimation and underestimation of the variance were also influenced by the life history of the organism. 4. Our findings highlight the need to consider the influences of statistical and demographic modelling approaches when population dynamics have significant temporal stochasticity, as in population viability analyses and evolutionary predictions of bet hedging.
引用
收藏
页码:1007 / 1017
页数:11
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