IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group III: Mitigation of Climate Change Land-use change and land-use management

Understanding land-use and land-cover changes is crucial to understanding climate change. Even if land activities are not considered as subject to mitigation policy, the impact of land-use change on emissions, sequestration, and albedo plays an important role in radiative forcing and the carbon cycle.

Over the past several centuries, human intervention has markedly changed land surface characteristics, in particular through large-scale land conversion for cultivation (Vitousek et al., 1997). Land-cover changes have an impact on atmospheric composition and climate via two mechanisms: biogeophysical and biogeochemical. Biogeophysical mechanisms include the effects of changes in surface roughness, transpiration, and albedo that, over the past millennium, are thought to have had a global cooling effect (Brovkin et al., 1999). Biogeochemical effects result from direct emissions of CO2 into the atmosphere from deforestation. Cumulative emissions from historical land-cover conversion for the period 1920–1992 have been estimated to be between 206 and 333 Pg CO2 (McGuire et al., 2001), and as much as 572 Pg CO2 for the entire industrial period 1850–2000, roughly one-third of total anthropogenic carbon emissions over this period (Houghton, 2003). In addition, land management activities (e.g. cropland fertilization and water management, manure management and forest rotation lengths) also affect land-based emissions of CO2 and non-CO2 GHGs, where agricultural land management activities are estimated to be responsible for the majority of global anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. For example, USEPA (2006a) estimated that agricultural activities were responsible for approximately 52% and 84% of global anthropogenic CH4 or N2O emissions respectively in the year 2000, with a net contribution from non-CO2 GHGs of 14% of all anthropogenic greenhouse gas emissions in that year.

Projected changes in land use were not explicitly represented in carbon cycle studies until recently. Previous studies into the effects of future land-use changes on the global carbon cycle employed trend extrapolations (Cramer et al., 2004), extreme assumptions about future land-use changes (House et al., 2002), or derived trends of land-use change from the SRES storylines (Levy et al., 2004). However, recent studies (e.g. Brovkin et al., 2006; Matthews et al., 2003; Gitz and Ciais, 2004) have shown that land use, as well as feedbacks in the society-biosphere-atmosphere system (e.g. Strengers et al., 2004), must be considered in order to achieve realistic estimates of the future development of the carbon cycle; thereby providing further motivation for ongoing development to explicitly model land and land-use drivers in global integrated assessment and climate economic frameworks. For example, in a model comparison study of six climate models of intermediate complexity, Brovkin et al. (2006) concluded that land-use changes contributed to a decrease in global mean annual temperature in the range of 0.13–0.25°C, mainly during the 19th century and the first half of the 20th century, which is in line with conclusions from other studies, such as Matthews et al. (2003).

In general, land-use drivers influence either the demand for land-based products and services (e.g. food, timber, bio-energy crops, and ecosystem services) or land-use production possibilities and opportunity costs (e.g. yield-improving technologies, temperature and precipitation changes, and CO2 fertilization). Non-market values – both use and non-use such as environmental services and species existence values respectively – will also shape land-use outcomes.

Food demand is a dominant land-use driver, and population and economic growth are the most significant food demand drivers through per person consumption. Total world food consumption is expected to increase by over 50% by 2030 (Bruinsma, 2003). Moreover, economic growth is expected to generate significant structural change in consumption patterns, with diets shifting to include more livestock products and fewer staples such as roots and tubers. As a result, per person meat consumption is expected to show a strong global increase, in the order of 25% by 2030, with faster growth in developing and transitional countries of more than 40% and 30%, respectively (Bruinsma, 2003; Cassman et al., 2003). The Millennium Ecosystem Assessment (MEA) scenarios projected that global average meat consumption would increase from 36 kg/person in 1997 to 41–70 kg/person by 2050, with corresponding increases in overall food and livestock feed demands (Carpenter et al., 2005). Additional cropland is expected to be required to support these projected increases in demand. Beyond 2050, food demand is expected to level off with slow-down of population growth.

Technological change is also a critical driver of land use, and a critical assumption in land-use projections. For example, Sands and Leimbach (2003) suggest that, globally, 800 million hectares of cropland expansion could be avoided with a 1% annual growth in crop yields. Similarly, Kurosawa (2006) estimates decreased cropland requirements of 18% by 2050, relative to 2000, with 2% annual growth in global average crop yields. Alternatively, the MEA scenarios implement a more complex representation of yield growth projections that, in addition to autonomous technological change, reflect the changes in production practices, investments, technology transfer, environmental degradation, and climate change. The net effect is positive, but shows declining productivity growth over time for some commodities, due in large part to diminishing marginal technical productivity gains and environmental degradation. In all these studies, increasing (decreasing) net productivity per hectare results in reduced (increased) cropland demand.

Also important to land-use projections are potential changes in climate. For instance, rising temperatures and CO2 fertilization may improve regional crop yields in the short term, thereby reducing pressure for additional cropland and resulting in increased afforestation. However, modelling the beneficial impacts of CO2 fertilization is not as straightforward as once thought. Recent results suggest: lower crop productivity improvements in the field than shown previously with laboratory results (e.g. Ainsworth and Long, 2005); likely increases in tropospheric ozone and smog associated with higher temperatures that will depress plant growth and partially offset CO2 fertilization; expected increases in the variability of annual yields; CO2 effects favouring C3 plants (e.g. wheat, barley, potatoes, rice) over C4 plants (e.g. maize, sugar cane, sorghum, millet) while temperature increases favour C4 over C3 plants; potential decreased nutritional content in plants subjected to CO2 fertilization and increased frequency of temperature extremes; and increases in forest disturbance frequency and intensity. See IPCC (2007b, Chapter 5) for an overall discussion of these issues and this literature. Long-term projections need to consider these issues, as well as examining the potential limitations or saturation points of plant responses. However, to date, long-term scenarios from integrated assessment models are only just beginning to represent climate feedbacks on terrestrial ecosystems, much less fully account for the many effects. Current integrated assessment representations only consider CO2 fertilization and changes in yearly average temperature, if they consider climate change effects at all (e.g. USCCSP, 2006; Van Vuuren et al., 2007).

Only a few global studies have focused on long-term (century) land-use projections. The most comprehensive studies, in terms of sector and land-type coverage, are the SRES (Nakicenovic et al., 2000), the SRES implementation with the IMAGE model (Strengers et al., 2004), the scenarios from the Global Scenarios Group (Raskin et al., 2002), UNEP’s Global Environment Outlook (UNEP, 2002), the Millennium Ecosystem Assessment (Carpenter et al., 2005), and some of the EMF-21 Study models (Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006; Riahi et al., 2006; Van Vuuren et al., 2007). Recent sector-specific economic studies have also contributed global land-use projections for climate analysis, especially for forestry (Sands and Leimbach, 2003; Sohngen and Mendelsohn, 2003, 2007; Sathaye et al., 2006; Sohngen and Sedjo, 2006). In general, the post-SRES scenarios, though scarce in number for agricultural land use, have projected increasing global cropland areas, smaller forest-land areas, and mixed results for changes in global grassland (Figure 3.7). Unlike the SRES land-use scenarios that span a broader range while representing diverse storylines, the post-SRES scenarios, for forestry in particular, illustrate greater convergence across models on projected land-use change.

Most post-SRES global scenarios project significant changes in agricultural land caused primarily by regional changes in food demand and production technology. Scenarios with larger amounts of land used for agriculture result from assumptions about higher population growth rates, higher food demands, and lower rates of technological improvement that generate negligible increases in crop yields. Combined, these effects are projected to lead to a sizeable expansion (up to 40%) of agricultural land between 1995 and 2100 (Figure 3.7). Conversely, lower population growth and food demand, and more rapid technological change, are projected to result in lower demand for agricultural land (as much as 20% less global agricultural acreage by the end of the century). In the short-term, almost all scenarios suggest an increase in cropland acreage and decline in forest land to meet projected increases in food, feed, and livestock grazing demands over the next few decades. Cropland changes range from -18% to +69% by 2050 relative to 2000 (from -123 to +1158 million hectares) and forest-land changes range from -18% to +3% (from -680 to +94 million hectares) by 2050. The changes in global forest generally mirror the agricultural scenarios; thereby, illustrating both the positive and negative aspects of some existing global land modelling. Most of the long-term scenarios assume that forest trends are driven almost exclusively by cropland expansion or contraction, and only deal superficially with driving forces, such as global trade in agricultural and forest products and conservation demands.

Figure 3.7

Figure 3.7: Global cropland (a), forest land (b) and grassland (c) projections.

Notes: shaded areas indicate SRES scenario ranges, post-SRES scenarios denoted with solid lines. IMAGE-EMF21 = Van Vuuren et al. (2006a) scenario from EMF-21 Study; IMAGE-MA-xx = Millennium Ecosystem Assessment (Carpenter et al., 2005) scenarios from the IMAGE model for four storylines (GO = Global Orchestration, OS = Order from Strength, AM = Adapting Mosaic, TG = TechnoGarden); AgLU-x.x% = Sands and Leimbach (2003) scenarios with x.x% annual growth in crop yield; GTM-2003 = Sohngen and Mendelsohn (2003) global forest scenario; GTM-EMF21 = Sohngen and Sedjo (2006) global forest scenario from EMF-21 Study; GCOMAP-EMF21 = Sathaye et al. (2006) global forest scenario from EMF-21 Study; GRAPE-EMF21 = Kurosawa (2006) scenario from EMF-21 Study.

Without incentives or technological innovation, biomass crops are currently not projected to assume a large share of global business as usual land cover – no more than about 4% by 2100. Until long-run energy price expectations rise (due to a carbon price, economic scarcity, or other force), biomass and other less economical energy supply technologies (some with higher greenhouse gas emission characteristics than biomass), are not expected to assume more significant baseline roles.