Integral projection models for species with complex demography

被引:423
作者
Ellner, SP [1 ]
Rees, M
机构
[1] Cornell Univ, Dept Ecol & Evolutionary Biol, Ithaca, NY 14853 USA
[2] Univ Sheffield, Dept Plant & Anim Sci, Sheffield S10 2TN, S Yorkshire, England
关键词
structured populations; integral model; matrix model; sensitivity analysis; latent variability; thistle;
D O I
10.1086/499438
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Matrix projection models occupy a central role in population and conservation biology. Matrix models divide a population into discrete classes, even if the structuring trait exhibits continuous variation ( e. g., body size). The integral projection model ( IPM) avoids discrete classes and potential artifacts from arbitrary class divisions, facilitates parsimonious modeling based on smooth relationships between individual state and demographic performance, and can be implemented with standard matrix software. Here, we extend the IPM to species with complex demographic attributes, including dormant and active life stages, cross- classification by several attributes ( e. g., size, age, and condition), and changes between discrete and continuous structure over the life cycle. We present a general model encompassing these cases, numerical methods, and theoretical results, including stable population growth and sensitivity/ elasticity analysis for density- independent models, local stability analysis in density- dependent models, and optimal/ evolutionarily stable strategy life- history analysis. Our presentation centers on an IPM for the thistle Onopordum illyricum based on a 6- year field study. Flowering and death probabilities are size and age dependent, and individuals also vary in a latent attribute affecting survival, but a predictively accurate IPM is completely parameterized by fitting a few regression equations. The online edition of the American Naturalist includes a zip archive of R scripts illustrating our suggested methods.
引用
收藏
页码:410 / 428
页数:19
相关论文
共 60 条
  • [1] Allan C. J., 1996, Plant Protection Quarterly, V11, P242
  • [2] [Anonymous], 1990, LECT NOTES BIOMATHEM
  • [3] Population responses to perturbations: predictions and responses from laboratory mite populations
    Benton, TG
    Cameron, TC
    Grant, A
    [J]. JOURNAL OF ANIMAL ECOLOGY, 2004, 73 (05) : 983 - 995
  • [4] Individual covariation in life-history traits: Seeing the trees despite the forest
    Cam, E
    Link, WA
    Cooch, EG
    Monnat, JY
    Danchin, E
    [J]. AMERICAN NATURALIST, 2002, 159 (01) : 96 - 105
  • [5] Caswell H., 1988, P85
  • [6] Caswell Hal, 2001, pi
  • [7] Evolution of size-dependent flowering in a variable environment: construction and analysis of a stochastic integral projection model
    Childs, DZ
    Rees, M
    Rose, KE
    Grubb, PJ
    Ellner, SP
    [J]. PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2004, 271 (1537) : 425 - 434
  • [8] Evolution of complex flowering strategies: an age- and size-structured integral projection model
    Childs, DZ
    Rees, M
    Rose, KE
    Grubb, PJ
    Ellner, SP
    [J]. PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2003, 270 (1526) : 1829 - 1838
  • [9] Clark JS, 2003, ECOLOGY, V84, P1370, DOI 10.1890/0012-9658(2003)084[1370:UAVIDA]2.0.CO
  • [10] 2