Land-use and land-cover changes have contributed substantially to climate change and are expected to continue to do so in the future (Le Quéré et al., 2009; Pitman et al., 2009; Houghton et al., 2012) due to the release of large quantities of carbon when natural ecosystems (mostly forests) are converted into croplands or pastures, or due to changes in management or land-use intensity (Erb et al., 2013). Intensification of crop management leads to release of additional greenhouse gases, like N2O from fertiliser application (Zaehle et al., 2011), or CH4 from cattle and rice production (Verburg and Denier van der Gon, 2001; Steinfeld et al., 2006). Changes that follow land use change in the surface reflectivity and the way absorbed energy is distributed towards evapotranspiration or heating at the near-surface affect regional climate substantially (Pitman et al., 2009; Pongratz et al., 2009). Changes in land systems can also result in increased carbon sequestration, due to e.g. the land-sparing effects of intensification, if not overcompensated by rebound effects (Lambin and Meyfroidt, 2011) or due to management changes in forests that do not result in changes in land cover, such as forest grazing or litter raking. These examples illustrate that studying the complex and highly dynamic interactions and feedbacks among climate and natural ecosystems is not sufficient to adequately describe the functioning of the Earth System and its components. Land use and its change over time is an important component of the Earth system. Nevertheless, the recent 5th Assessment Report by the IPCC WG1 is the first where land use change has been explicitly, although rudimentarily, accounted for in projections of climate change. Recent, model-based studies, have shown that land use change has an important impact on the radiative forcing calculation (Jones et al., 2012). From a human system’s perspective, climate and climate change also contribute to land use change (Mertz et al., 2010). Climate determines the types of crops that can be grown (Easterling et al., 2007; Gornall et al., 2010). Harvest failures following floods, heat-waves or droughts can lead to food-shortages, and increases in local and global grain prices (Beddington, 2010). Indirect climate-effects like fires or insect-outbreaks can also affect the yield of forests and crops. At the same time, in other regions climate change also favours higher agriculture yields in areas limited by temperature and rainfall. As an example, the agriculture production of Argentina (one of the major global food producers) has been clearly favoured by climate change (represented here as rainfall increase) in recent decades.
An emerging challenge is, therefore, to quantify impacts and feedbacks between land systems, the societies managing these systems, and the climate system, and to take into consideration regional to global scales and short- and longer-term time perspectives. A global scale perspective is needed because climate systems operate on global scales, and increasing land systems also operate at such scales, as illustrated in section 2.4. The debate on indirect land use change arising from land-based bioenergy production is a prominent example of global-scale dynamics (Fargione et al., 2008), but equally important is the possibility to supply food to regions that suffer from, for example, a climate-induced crisis. Issues of time arise from legacy effects of land use change in the climate system (Houghton et al., 2012) or from time-lags between introduction of a climate policy and its actual take-up by local farmers (Alexander et al., 2013). The climate, environmental and socio-economic research communities are confronted with providing the required understanding of the fundamental processes that operate at the interface of the climate and land systems, and their manifold interactions across local, regional, and global scales. A key challenge is to find ways to bridge, philosophically and methodologically, the diverse scientific communities. Finding ways to synthesise available data and knowledge in these communities will allow further development of the mechanisms represented in models, advance our capacity to evaluate model performance, and yield information to support policy development and societies towards successful adaptation and mitigation strategies (Hibbard et al., 2010; Rounsevell et al., 2013).