Matrix projection models meet variation in the real world

Salguero-Gomez, Roberto and de Kroon, Hans (2010) Matrix projection models meet variation in the real world. Journal of Ecology, 98 2: 250-254. doi:10.1111/j.1365-2745.2009.01635.x

Author Salguero-Gomez, Roberto
de Kroon, Hans
Title Matrix projection models meet variation in the real world
Journal name Journal of Ecology   Check publisher's open access policy
ISSN 0022-0477
Publication date 2010-03
Year available 2010
Sub-type Editorial
DOI 10.1111/j.1365-2745.2009.01635.x
Open Access Status
Volume 98
Issue 2
Start page 250
End page 254
Total pages 5
Place of publication Oxford, United Kingdom
Publisher Wiley-Blackwell Publishing Ltd.
Collection year 2010
Language eng
Formatted abstract
1. Projection matrices have become the dominant modelling approach in plant demography because they (i) are relatively easy to formulate, (ii) compile complex data in a structured and analytically tractable manner, (iii) provide numerous parameters with direct biological meaning, (iv) allow the investigator to address broad or specific, experimental and/or theoretical, ecological and evolutionary questions, and (v) produce uniform outputs, enabling direct comparisons between the results of different studies.

2. The last decade has witnessed major advancements in this field that have brought demographic models much closer to the real world, in particular in the analysis of effects of spatial and temporal environmental variation on populations. The present Special Feature contributes to that progress with novel methodologies and applications on Integral Projection Models, stochastic Life Table Response Experiment analyses, stochastic elasticities, transient dynamics and phylogenetic analyses.

3.Synthesis. Environmental stochasticity is an integral part of ecosystems, and plant populations exhibit a tremendous array of demographic strategies to deal with its effects. The analytical challenge of understanding how populations avoid, tolerate or depend on stochasticity is finally overcome with the new matrix approaches. The tools are now available to interpret the effects of changes in temporal and spatial variation on plant populations. 
Keyword Demographic buffering
Integral projection model
Plant demography
Population dynamics
Projection matrix
Stochastic elasticity
Q-Index Code CX
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Editorial
Collection: School of Biological Sciences Publications
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