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Use DLNMs to identify important lag time windows (i.e. what we did in Global Change Bio) but rather than using DLNMs in the IPM, make vital rates models that include averages of SPEI in those periods as simple parametric predictors. E.g. something like surv ~ s(log_size_prev) + spei_wet_t2 where spei_wet_t2 is the average SPEI in the wet season two years prior to the census.
The text was updated successfully, but these errors were encountered:
Use DLNMs to identify important lag time windows (i.e. what we did in Global Change Bio) but rather than using DLNMs in the IPM, make vital rates models that include averages of SPEI in those periods as simple parametric predictors. E.g. something like
surv ~ s(log_size_prev) + spei_wet_t2
wherespei_wet_t2
is the average SPEI in the wet season two years prior to the census.The text was updated successfully, but these errors were encountered: