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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]

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities. [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]