Spatial data replacing temporal data in population viability analyses: An empirical investigation for plants

Ramula, S, Dinnetz, P and Lehtila, K (2009) Spatial data replacing temporal data in population viability analyses: An empirical investigation for plants. BASIC AND APPLIED ECOLOGY, 10 5: 401-410. doi:10.1016/j.baae.2008.10.007


Author Ramula, S
Dinnetz, P
Lehtila, K
Title Spatial data replacing temporal data in population viability analyses: An empirical investigation for plants
Formatted title
Spatial data replacing temporal data in population viability analyses: An empirical investigation for plants
Journal name BASIC AND APPLIED ECOLOGY   Check publisher's open access policy
ISSN 1439-1791
Publication date 2009-08-01
Year available 2009
Sub-type Article (original research)
DOI 10.1016/j.baae.2008.10.007
Open Access Status
Volume 10
Issue 5
Start page 401
End page 410
Total pages 10
Place of publication Germany
Publisher Urban und Fischer Verlag
Language eng
Subject C1
Formatted abstract
In conservation management, there is an urgent need for estimates of population viability and for knowledge of the contributions of different life-history stages to population growth rates. Collection of long-term demographic data from a study population is time-consuming and may considerably delay the start of proper management actions. We examined the possibility of replacing a long-term temporal data set (demographic data from several years within a population) with a short-term spatial data set (demographic data from different populations for the same subset of two continuous years) for stochastic estimates of population viability. Using matrix population models for ten perennial plant species, we found that the matrix elements of spatial data sets often deviated from those of temporal data sets and that matrix elements generally varied more spatially than temporally. The appropriateness of replacing temporal data with spatial data depended on the subset of years and populations used to estimate stochastic population growth rates (log λs). Still, the precision of log λs estimates measured as variation in the yearly change of logarithmic population size rarely differed significantly between the spatial and temporal data sets. Since a spatiotemporal comparison of matrix elements and their variation cannot be used to assess whether spatial and temporal data sets are interchangeable, we recommend further research on the topic.
Keyword Demography
RELATIVE PREDICTIONS
Q-Index Code C1
Q-Index Status Provisional Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: Spatial Ecology Lab Publications
School of Biological Sciences Publications
 
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Created: Thu, 03 Sep 2009, 17:44:35 EST by Mr Andrew Martlew on behalf of School of Biological Sciences