Benefits and trade-offs of optimizing global land use for food, water, and carbon.

Current large-scale patterns of land use reflect history, local traditions, and production costs, much more so than they reflect biophysical potential or global supply and demand for food and freshwater, or-more recently-climate change mitigation. We quantified alternative land-use allocations that consider trade-offs for these demands by combining a dynamic vegetation model and an optimization algorithm to determine Pareto-optimal land-use allocations under changing climate conditions in 2090-2099 and alternatively in 2033-2042. These form the outer bounds of the option space for global land-use transformation. Results show a potential to increase all three indicators (+83% in crop production, +8% in available runoff, and +3% in carbon storage globally) compared to the current land-use configuration, with clear land-use priority areas: Tropical and boreal forests were preserved, crops were produced in temperate regions, and pastures were preferentially allocated in semiarid grasslands and savannas. Transformations toward optimal land-use patterns would imply extensive reconfigurations and changes in land management, but the required annual land-use changes were nevertheless of similar magnitude as those suggested by established land-use change scenarios. The optimization results clearly show that large benefits could be achieved when land use is reconsidered under a "global supply" perspective with a regional focus that differs across the world's regions in order to achieve the supply of key ecosystem services under the emerging global pressures.

Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.

Monitoring of circulating angiogenic factors in dendritic cell-based cancer immunotherapy.

BACKGROUND: A promising treatment approach for patients with malignant disease that recently has found its way into clinical trials is based on vaccination with autologous dendritic cells loaded with tumor antigens. However, adequate assays for monitoring clinical and immunologic responses still are under debate. In recent years, the determination of angiogenic markers has shown considerable potential in the diagnosis and prognosis of patients with malignant disease, because tumor growth and spread are promoted by angiogenesis, the formation of new blood vessels. METHODS: The authors established a method for measuring the plasma levels of three modulators of angiogenesis: vascular endothelial growth factor, platelet-derived endothelial cell growth factor, and thrombospondin-1. The angiogenic blood profile of a healthy control group was characterized and compared with a group of patients with malignant disease. Ultimately, levels of circulating angiogenic factors were monitored in the course of dendritic cell-based cancer immunotherapy. RESULTS: Baseline levels of angiogenic mediators varied substantially among healthy individuals but showed consistent values for each individual. Blood levels of circulating angiogenic factors were elevated significantly in patients with advanced disease and were highly sensitive to dendritic cell-based immunotherapy. CONCLUSIONS: To our knowledge, the current report was the first to analyze circulating levels of angiogenic factors during dendritic cell-based immunotherapy. The authors observed a noteworthy change in the angiogenic blood profile with treatment, and this change was correlated with the induction of an immunologic response.