How robust are future projections of forest landscape dynamics? Insights from a systematic comparison of four forest landscape models
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Date
2020-12
Publication Type
Journal Article
ETH Bibliography
yes
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Abstract
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.
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Publication status
published
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Book title
Journal / series
Volume
134
Pages / Article No.
104844
Publisher
Elsevier
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Forest landscape models; Model comparison; Variance partitioning; Disturbances; Dispersal; Future projections
Organisational unit
03535 - Bugmann, Harald / Bugmann, Harald
Notes
Funding
163250 - Advanced Tree MOrtality MOdeling (ATMO^2) (SNF)