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

Citations

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Data

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.

Publication status

published

Editor

Book title

Volume

134

Pages / Article No.

104844

Publisher

Elsevier

Event

Edition / version

Methods

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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 check_circle

Notes

Funding

163250 - Advanced Tree MOrtality MOdeling (ATMO^2) (SNF)

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