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How robust are future projections of forest landscape dynamics? Insights from a systematic comparison of four forest landscape models

Title: How robust are future projections of forest landscape dynamics? Insights from a systematic comparison of four forest landscape models
Authors: Petter G.; Mairota P.; Albrich K.; Bebi P.; Bruna J.; Bugmann H.; Haffenden A.; Scheller R. M.; Schmatz D. R.; Seidl R.; Speich M.; Vacchiano G.; Lischke H.
Contributors: G. Petter; P. Mairota; K. Albrich; P. Bebi; J. Bruna; H. Bugmann; A. Haffenden; R.M. Scheller; D.R. Schmatz; R. Seidl; M. Speich; G. Vacchiano; H. Lischke
Publisher Information: Elsevier Ltd
Publication Year: 2020
Collection: The University of Milan: Archivio Istituzionale della Ricerca (AIR)
Subject Terms: Forest landscape model; Model comparison; Variance partitioning; Disturbance; Dispersal; Future projections; Settore AGR/05 - Assestamento Forestale e Selvicoltura
Description: 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.
Document Type: article in journal/newspaper
Language: English
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:000591374100003; volume:134; firstpage:1; lastpage:13; numberofpages:13; journal:ENVIRONMENTAL MODELLING & SOFTWARE; https://hdl.handle.net/2434/768110
DOI: 10.1016/j.envsoft.2020.104844
Availability: https://hdl.handle.net/2434/768110; https://doi.org/10.1016/j.envsoft.2020.104844
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.5A9A13FD
Database: BASE