Towards understanding predictability in ecology: A forest gap model case study
A. M. Raiho, M. Dietze, A. Dawson, C. Rollinson, J. Tipton, J. McLachlan
This paper evaluates uncertainty components in forest gap model predictions using a data assimilation algorithm, finding that process uncertainty dominates over demographic and initial condition uncertainties.
bioRxiv · May 5, 2020 · PreprintEcology