Premium
Assessing uncertainties in land cover projections
Author(s) -
Alexander Peter,
Prestele Reinhard,
Verburg Peter H.,
Arneth Almut,
Baranzelli Claudia,
Batista e Silva Filipe,
Brown Calum,
Butler Adam,
Calvin Katherine,
Dendoncker Nicolas,
Doelman Jonathan C.,
Dunford Robert,
Engström Kerstin,
Eitelberg David,
Fujimori Shinichiro,
Harrison Paula A.,
Hasegawa Tomoko,
Havlik Petr,
Holzhauer Sascha,
Humpenöder Florian,
JacobsCrisioni Chris,
Jain Atul K.,
Krisztin Tamás,
Kyle Page,
Lavalle Carlo,
Lenton Tim,
Liu Jiayi,
Meiyappan Prasanth,
Popp Alexander,
Powell Tom,
Sands Ronald D.,
Schaldach Rüdiger,
Stehfest Elke,
Steinbuks Jevgenijs,
Tabeau Andrzej,
Meijl Hans,
Wise Marshall A.,
Rounsevell Mark D. A.
Publication year - 2017
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.13447
Subject(s) - land cover , climate change , environmental science , land use , range (aeronautics) , climate model , cover (algebra) , environmental resource management , climatology , ecology , mechanical engineering , materials science , engineering , composite material , biology , geology
Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.