Abstract: Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 degrees C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 +/- 5.6 EJ yr(-1) of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 degrees C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth’s carbon and energy budget.

Abstract: Organic agriculture aims to produce food while establishing an ecological balance to augment ecosystem services (ES) and has been rapidly expanding in the world since the 1980s. Recently, however, in several European countries, including Denmark, organic farmers have converted back to conventional farming. Hence, understanding how agricultural ES are affected by the number of years since conversion to organic farming is imperative for policy makers to guide future agricultural policy. In order to investigate the long-term effects of conversion to organic farming on ES we performed i) a model simulation case study by applying the Daisy model to simulate 14 different conversion scenarios for a Danish farm during a 65 year period with increasing number of years under organic farming, and ii) an on-farm case study in Denmark with one conventional farm, one organic farm under conversion, and three organic farms converted 10, 15 and 58 years ago, respectively. Both the model simulation case study and the on-farm case study showed that non-marketable ES values increased with increasing number of years under organic farming. Trade-offs between marketable and non-marketable ES were not evident, since also marketable ES values generally showed an increasing trend, except when the price difference between organic and conventional products in the model simulation study was the smallest, and when an alfalfa pre-crop in the on-farm case study resulted in a significantly higher level of plant available nitrogen, which boosted the yield and the associated marketable ES of the subsequent winter rye crop. These results indicate a possible benefit of preserving long-term organic farms and could be used to argue for agricultural policy interventions to offset further reduction in the number of organic farms or the land area under organic farming.

Abstract: The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950–2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980–2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980.