David A. Eitelberg
VU University Amsterdam
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by David A. Eitelberg.
Global Change Biology | 2016
Reinhard Prestele; Peter Alexander; Mark Rounsevell; Almut Arneth; Katherine Calvin; Jonathan C. Doelman; David A. Eitelberg; Kerstin Engström; Shinichiro Fujimori; Tomoko Hasegawa; Petr Havlik; Atul K. Jain; Tamás Krisztin; Page Kyle; Prasanth Meiyappan; Alexander Popp; Ronald D. Sands; Rüdiger Schaldach; Jan Schüngel; Elke Stehfest; A.A. Tabeau; Hans van Meijl; Jasper van Vliet; Peter H. Verburg
Abstract Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.
Global Change Biology | 2017
Peter Alexander; Reinhard Prestele; Peter H. Verburg; Almut Arneth; Claudia Baranzelli; Filipe Batista e Silva; Calum Brown; Adam Butler; Katherine Calvin; Nicolas Dendoncker; Jonathan C. Doelman; Robert Dunford; Kerstin Engström; David A. Eitelberg; Shinichiro Fujimori; Paula A. Harrison; Tomoko Hasegawa; Petr Havlik; Sascha Holzhauer; Chris Jacobs-Crisioni; Atul K. Jain; Tamás Krisztin; Page Kyle; Carlo Lavalle; Timothy M. Lenton; Jiayi Liu; Prasanth Meiyappan; Alexander Popp; Tom Powell; Ronald D. Sands
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.
Journal of Land Use Science | 2017
David A. Eitelberg; Jasper van Vliet; Peter H. Verburg
ABSTRACT Land systems are described based on various characteristics, including land cover composition and agricultural production. However, it is uncertain to what extent livestock, particularly monogastric livestock, determines land systems. We included monogastrics in a land system classification, and statistically analyzed the land cover composition and agricultural production of otherwise similar land systems with and without monogastric livestock. The results indicate that land systems with monogastrics are statistically different from their counterparts in the classification without monogastrics in terms of grassland area and crop yields, but are less different in terms of tree area, crop area, and ruminant livestock production. We then used a land systems map that includes monogastrics in the classification and a similar map that does not include monogastrics to project future changes in a novel manner that integrates livestock as a determinant of land systems. The results show that including monogastrics in otherwise similar projections yields less cropland intensification and more cropland expansion in several world regions, including Northern Africa and the Middle East. Other regions, such as Europe and Australia, were characterized by less decrease or more increase in tree area in the application with monogastrics, mainly due to the occurrence of open forests with monogastrics. This study prompts a call for improved characterization of land systems for land use and cover change (LUCC) assessments in order to better represent LUCC driven by monogastric livestock.
Environmental Management | 2016
Huirong Yu; Peter H. Verburg; Liming Liu; David A. Eitelberg
Cultural heritage landscapes are consistently perceived as landscapes of high value. However, these landscapes are very vulnerable to change. In China, rapid land use change, especially urbanization, has become one of the main challenges for the conservation of cultural heritage landscapes in rural areas. This paper focuses on the designated cultural villages in rural China by systematically analyzing the spatial distribution of the designated cultural landscape across the country and assessing the threats these traditional landscapes are facing under current and future urbanization and other land use pressures. Current designated cultural heritage landscapes in China are predominantly located in the rural and peri-urban regions of Central and South China and less frequently found in other regions. Especially in these regions risks to land use change are large. These risks are assessed based on observed recent land use change and land use model simulations for scenarios up to 2050. The risk assessment reveals that especially in Southeast China along the sea coast and near the cities along the Yangtze River, high pressures are expected on cultural heritage landscapes due to urbanization. At the same time, in Southwest China, especially in Yunnan and Guizhou provinces, high pressures due to other land use changes are expected, including land abandonment. This assessment gives direction and guidance toward the selection of the most threatened cultural villages for detailed investigation and additional protection measures.
Global Change Biology | 2015
David A. Eitelberg; Jasper van Vliet; Peter H. Verburg
Global Environmental Change-human and Policy Dimensions | 2017
Jasper van Vliet; David A. Eitelberg; Peter H. Verburg
Global Environmental Change-human and Policy Dimensions | 2016
David A. Eitelberg; Jasper van Vliet; Jonathan C. Doelman; Elke Stehfest; Peter H. Verburg
Science of The Total Environment | 2016
Samantha Jane Hughes; João Alexandre Cabral; Rita Bastos; Rui Cortes; Joana R. Vicente; David A. Eitelberg; Huirong Yu; João Honrado; Mário Santos
Ecological Indicators | 2016
Rita Bastos; Manuela D’Amen; Joana R. Vicente; Mário Santos; Huirong Yu; David A. Eitelberg; João Gonçalves; Emilio Civantos; João Honrado; João Alexandre Cabral
Archive | 2013
Peter H. Verburg; Hermann Lotze-Campen; Alexander Popp; Marcus Lindner; Hans Verkerk; Emmi Kakkonen; Elizabeth Schrammeijer; John Helming; A.A. Tabeau; Nynke Schulp; Emma H. van der Zanden; Carlo Lavalle; Filipe Batista e Silva; David A. Eitelberg