TY - JOUR
T1 - How robust are future projections of forest landscape dynamics? Insights from a systematic comparison of four forest landscape models
AU - Petter, Gunnar
AU - Mairota, Paola
AU - Albrich, Katharina
AU - Bebi, Peter
AU - Brůna, Josef
AU - Bugmann, Harald
AU - Haffenden, Austin
AU - Scheller, Robert M.
AU - Schmatz, Dirk R.
AU - Seidl, Rupert
AU - Speich, Matthias
AU - Vacchiano, Giorgio
AU - Lischke, Heike
N1 - Publisher Copyright:
© 2020 The Author(s)
PY - 2020/12
Y1 - 2020/12
N2 - Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha−1. Disturbances strongly influenced landscape dynamics and contributed substantially to uncertainty in model projections (~25–40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics.
AB - Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha−1. Disturbances strongly influenced landscape dynamics and contributed substantially to uncertainty in model projections (~25–40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics.
KW - Dispersal
KW - Disturbances
KW - Forest landscape models
KW - Future projections
KW - Model comparison
KW - Variance partitioning
UR - http://www.scopus.com/inward/record.url?scp=85090288221&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2020.104844
DO - 10.1016/j.envsoft.2020.104844
M3 - Article
AN - SCOPUS:85090288221
SN - 1364-8152
VL - 134
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 104844
ER -