Gap models are perhaps the most widely used class of individual-based tree
models used in ecology and climate change research. However, most gap model
emphasize, in terms of process detail, computer code, and validation effor
t, tree growth with little attention to the simulation of plant death or mo
rtality. Mortality algorithms have been mostly limited to general relations
hips because of sparse data on the causal mechanisms of mortality. If gap m
odels are to be used to explore community dynamics under changing climates,
the limitations and shortcomings of these mortality algorithms must be ide
ntified and the simulation of mortality must be improved. In this paper, we
review the treatment of mortality in gap models, evaluate the relationship
s used to represent mortality in the current generation of gap models, and
then assess the prospects for making improvements, especially for applicati
ons involving global climate change. Three needs are identified to improve
mortality simulations in gap models: (1) process-based empirical analyses a
re needed to create more climate-sensitive stochastic mortality functions,
(2) fundamental research is required to quantify the biophysical relationsh
ips between mortality and plant dynamics, and (3) extensive field data are
needed to quantify, parameterize, and validate existing and future gap mode
l mortality functions.