Regeneration in gap models: Priority issues for studying forest responses to climate change

Recruitment algorithms in forest gap models are examined with particular re gard to their suitability for simulating forest ecosystem responses to a ch anging climate. The traditional formulation of recruitment is found limitin g in three areas. First, the aggregation of different regeneration stages ( seed production, dispersal, storage, germination and seedling establishment ) is likely to result in less accurate predictions of responses as compared to treating each stage separately. Second, the related assumptions that se eds of all species are uniformly available and that environmental condition s are homogeneous, are likely to cause overestimates of future species dive rsity and forest migration rates. Third, interactions between herbivores (u ngulates and insect pests) and forest vegetation are a big unknown with pot entially serious impacts in many regions. Possible strategies for developin g better gap model representations for the climate-sensitive aspects of eac h of these key areas are discussed. A working example of a relatively new m odel that addresses some of these limitations is also presented for each ca se. We conclude that better models of regeneration processes are desirable for predicting effects of climate change, but that it is presently impossib le to determine what improvements can be expected without carrying out rigo rous tests for each new formulation.