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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.

In the latest projections of future greenhouse gas emissions for the Intergovernmental Panel on Climate Change (IPCC), few Earth System Models included the effect of nitrogen limitation, a key process limiting forest regrowth. Few included forest management (wood harvest). We estimate the impacts of nitrogen limitation on the CO2 emissions from land use and land use change (LULUC), including wood harvest, for the period 1900-2100. We use a land surface model that includes a fully coupled carbon and nitrogen cycle and accounts for forest regrowth processes following agricultural abandonment and wood harvest. Future projections are based on the four Representation Concentration Pathways used in the IPCC Fifth Assessment Report, and we account for uncertainty in future climate for each scenario based on ensembles of climate model outputs. Results show that excluding nitrogen limitation will underestimate global LULUC emissions by 34-52 PgC (20-30%) during the 20th century (range across three different historical LULUC reconstructions) and by 128-187 PgC (90-150%) during the 21st century (range across the four IPCC scenarios). The full range for estimated LULUC emissions during the 21st century including climate model uncertainty is 91 to 227 PgC (with nitrogen limitation included). The underestimation increases with time because (1) projected annual wood harvest rates from forests summed over the 21st century are 380-1080% higher compared to those of the 20th century, resulting in more regrowing secondary forests; (2) nitrogen limitation reduces the CO2 fertilization effect on net primary production of regrowing secondary forests following wood harvest and agricultural abandonment; and (3) nitrogen limitation effect is aggravated by the gradual loss of soil nitrogen from LULUC disturbance. Our study implies that (1) nitrogen limitation of CO2 uptake is substantial and sensitive to nitrogen inputs; (2) if LULUC emissions are larger than previously estimated in studies without nitrogen limitation, then meeting the same climate mitigation target would require an equivalent additional reduction of fossil fuel emissions; (3) the effectiveness of land-based mitigation strategies will critically depend on the interactions between nutrient limitations and secondary forests resulting from LULUC; and (4) it is important for terrestrial biosphere models to consider nitrogen constraint in estimates of the strength of future land carbon uptake. [ABSTRACT FROM AUTHOR]

The high uncertainty in land-based CO2 fluxes estimates is thought to be mainly due to uncertainty in not only quantifying historical changes among forests, croplands, and grassland, but also due to different processes included in calculation methods. Inclusion of a nitrogen (N) cycle in models is fairly recent and strongly affects carbon (C) fluxes. In this study, for the first time, we use a model with C and N dynamics with three distinct historical reconstructions of land-use and land-use change ( LULUC) to quantify LULUC emissions and uncertainty that includes the integrated effects of not only climate and CO2 but also N. The modeled global average emissions including N dynamics for the 1980s, 1990s, and 2000-2005 were 1.8 ± 0.2, 1.7 ± 0.2, and 1.4 ± 0.2 GtC yr−1, respectively, (mean and range across LULUC data sets). The emissions from tropics were 0.8 ± 0.2, 0.8 ± 0.2, and 0.7 ± 0.3 GtC yr−1, and the non tropics were 1.1 ± 0.5, 0.9 ± 0.2, and 0.7 ± 0.1 GtC yr−1. Compared to previous studies that did not include N dynamics, modeled net LULUC emissions were higher, particularly in the non tropics. In the model, N limitation reduces regrowth rates of vegetation in temperate areas resulting in higher net emissions. Our results indicate that exclusion of N dynamics leads to an underestimation of LULUC emissions by around 70% in the non tropics, 10% in the tropics, and 40% globally in the 1990s. The differences due to inclusion/exclusion of the N cycle of 0.1 GtC yr−1 in the tropics, 0.6 GtC yr−1 in the non tropics, and 0.7 GtC yr−1 globally (mean across land-cover data sets) in the 1990s were greater than differences due to the land-cover data in the non tropics and globally (0.2 GtC yr−1). While land-cover information is improving with satellite and inventory data, this study indicates the importance of accounting for different processes, in particular the N cycle. [ABSTRACT FROM AUTHOR]

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., (© 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

The high uncertainty in land-based CO2 fluxes estimates is thought to be mainly due to uncertainty in not only quantifying historical changes among forests, croplands, and grassland, but also due to different processes included in calculation methods. Inclusion of a nitrogen (N) cycle in models is fairly recent and strongly affects carbon (C) fluxes. In this study, for the first time, we use a model with C and N dynamics with three distinct historical reconstructions of land-use and land-use change (LULUC) to quantify LULUC emissions and uncertainty that includes the integrated effects of not only climate and CO2 but also N. The modeled global average emissions including N dynamics for the 1980s, 1990s, and 2000-2005 were 1.8 ± 0.2, 1.7 ± 0.2, and 1.4 ± 0.2 GtC yr(-1) , respectively, (mean and range across LULUC data sets). The emissions from tropics were 0.8 ± 0.2, 0.8 ± 0.2, and 0.7 ± 0.3 GtC yr(-1) , and the non tropics were 1.1 ± 0.5, 0.9 ± 0.2, and 0.7 ± 0.1 GtC yr(-1) . Compared to previous studies that did not include N dynamics, modeled net LULUC emissions were higher, particularly in the non tropics. In the model, N limitation reduces regrowth rates of vegetation in temperate areas resulting in higher net emissions. Our results indicate that exclusion of N dynamics leads to an underestimation of LULUC emissions by around 70% in the non tropics, 10% in the tropics, and 40% globally in the 1990s. The differences due to inclusion/exclusion of the N cycle of 0.1 GtC yr(-1) in the tropics, 0.6 GtC yr(-1) in the non tropics, and 0.7 GtC yr(-1) globally (mean across land-cover data sets) in the 1990s were greater than differences due to the land-cover data in the non tropics and globally (0.2 GtC yr(-1) ). While land-cover information is improving with satellite and inventory data, this study indicates the importance of accounting for different processes, in particular the N cycle., (© 2013 John Wiley & Sons Ltd.)