TY - JOUR
T1 - Linking contemporary vegetation models with spatially explicit animal population models
AU - Holt, R. D.
AU - Pacala, Stephen Wilson
AU - Smith, T. W.
AU - Jianguo Liu, Liu
PY - 1995/1/1
Y1 - 1995/1/1
N2 - Spatially explicit models for animal populations (SEPMs) necessarily embody assumptions about plant community structure and dynamics. In research focused on questions with short time horizons, however, the spatial patterning of vegetation can be reasonably approximated as a fixed landscape templet for animal population dynamics. But if one needs to consider longer time scales (eg decades to centuries), landscapes will be dynamic. Models of vegetation dynamics provide useful tools for predicting landscape dynamics. The authors outline the sorts of output from vegetation models that might be useful in animal SEPMs and discuss recent forest simulators, which predict with reasonable accuracy some variables (eg tree species composition), but which, to date, are quite poor for others (eg seed production). -from Authors
AB - Spatially explicit models for animal populations (SEPMs) necessarily embody assumptions about plant community structure and dynamics. In research focused on questions with short time horizons, however, the spatial patterning of vegetation can be reasonably approximated as a fixed landscape templet for animal population dynamics. But if one needs to consider longer time scales (eg decades to centuries), landscapes will be dynamic. Models of vegetation dynamics provide useful tools for predicting landscape dynamics. The authors outline the sorts of output from vegetation models that might be useful in animal SEPMs and discuss recent forest simulators, which predict with reasonable accuracy some variables (eg tree species composition), but which, to date, are quite poor for others (eg seed production). -from Authors
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U2 - 10.2307/1942048
DO - 10.2307/1942048
M3 - Article
AN - SCOPUS:0028844859
SN - 1051-0761
VL - 5
SP - 20
EP - 27
JO - Ecological Applications
JF - Ecological Applications
IS - 1
ER -