R. M. Gifford

Bio: R. M. Gifford is an academic researcher from Cooperative Research Centre. The author has contributed to research in topics: Land use, land-use change and forestry & Secondary forest. The author has an hindex of 1, co-authored 1 publications receiving 2676 citations.

Soil carbon stocks and land use change: a meta analysis

Abstract: The effects of land use change on soil carbon stocks are of concern in the context of international policy agendas on greenhouse gas emissions mitigation. This paper reviews the literature for the influence of land use changes on soil C stocks and reports the results of a meta analysis of these data from 74 publications. The meta analysis indicates that soil C stocks decline after land use changes from pasture to plantation (−10%), native forest to plantation (−13%), native forest to crop (−42%), and pasture to crop (−59%). Soil C stocks increase after land use changes from native forest to pasture (+ 8%), crop to pasture (+ 19%), crop to plantation (+ 18%), and crop to secondary forest (+ 53%). Wherever one of the land use changes decreased soil C, the reverse process usually increased soil carbon and vice versa. As the quantity of available data is not large and the methodologies used are diverse, the conclusions drawn must be regarded as working hypotheses from which to design future targeted investigations that broaden the database. Within some land use changes there were, however, sufficient examples to explore the role of other factors contributing to the above conclusions. One outcome of the meta analysis, especially worthy of further investigation in the context of carbon sink strategies for greenhouse gas mitigation, is that broadleaf tree plantations placed onto prior native forest or pastures did not affect soil C stocks whereas pine plantations reduced soil C stocks by 12–15%.

Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change

Abstract: Most prior studies have found that substituting biofuels for gasoline will reduce greenhouse gases because biofuels sequester carbon through the growth of the feedstock. These analyses have failed to count the carbon emissions that occur as farmers worldwide respond to higher prices and convert forest and grassland to new cropland to replace the grain (or cropland) diverted to biofuels. By using a worldwide agricultural model to estimate emissions from land-use change, we found that corn-based ethanol, instead of producing a 20% savings, nearly doubles greenhouse emissions over 30 years and increases greenhouse gases for 167 years. Biofuels from switchgrass, if grown on U.S. corn lands, increase emissions by 50%. This result raises concerns about large biofuel mandates and highlights the value of using waste products.

Greenhouse gas mitigation in agriculture

Abstract: Agricultural lands occupy 37% of the earth's land surface. Agriculture accounts for 52 and 84% of global anthropogenic methane and nitrous oxide emissions. Agricultural soils may also act as a sink or source for CO2, but the net flux is small. Many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management and restoration of degraded lands and cultivated organic soils. Lower, but still significant mitigation potential is provided by water and rice management, set-aside, land use change and agroforestry, livestock management and manure management. The global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030, considering all gases, is estimated to be approximately 5500–6000 Mt CO2-eq. yr−1, with economic potentials of approximately 1500–1600, 2500–2700 and 4000–4300 Mt CO2-eq. yr−1 at carbon prices of up to 20, up to 50 and up to 100 US$ t CO2-eq.−1, respectively. In addition, GHG emissions could be reduced by substitution of fossil fuels for energy production by agricultural feedstocks (e.g. crop residues, dung and dedicated energy crops). The economic mitigation potential of biomass energy from agriculture is estimated to be 640, 2240 and 16 000 Mt CO2-eq. yr−1 at 0–20, 0–50 and 0–100 US$ t CO2-eq.−1, respectively.

Deep soil organic matter—a key but poorly understood component of terrestrial C cycle

Abstract: Despite their low carbon (C) content, most subsoil horizons contribute to more than half of the total soil C stocks, and therefore need to be considered in the global C cycle. Until recently, the properties and dynamics of C in deep soils was largely ignored. The aim of this review is to synthesize literature concerning the sources, composition, mechanisms of stabilisation and destabilization of soil organic matter (SOM) stored in subsoil horizons. Organic C input into subsoils occurs in dissolved form (DOC) following preferential flow pathways, as aboveground or root litter and exudates along root channels and/or through bioturbation. The relative importance of these inputs for subsoil C distribution and dynamics still needs to be evaluated. Generally, C in deep soil horizons is characterized by high mean residence times of up to several thousand years. With few exceptions, the carbon-to-nitrogen (C/N) ratio is decreasing with soil depth, while the stable C and N isotope ratios of SOM are increasing, indicating that organic matter (OM) in deep soil horizons is highly processed. Several studies suggest that SOM in subsoils is enriched in microbial-derived C compounds and depleted in energy-rich plant material compared to topsoil SOM. However, the chemical composition of SOM in subsoils is soil-type specific and greatly influenced by pedological processes. Interaction with the mineral phase, in particular amorphous iron (Fe) and aluminum (Al) oxides was reported to be the main stabilization mechanism in acid and near neutral soils. In addition, occlusion within soil aggregates has been identified to account for a great proportion of SOM preserved in subsoils. Laboratory studies have shown that the decomposition of subsoil C with high residence times could be stimulated by addition of labile C. Other mechanisms leading to destabilisation of SOM in subsoils include disruption of the physical structure and nutrient supply to soil microorganisms. One of the most important factors leading to protection of SOM in subsoils may be the spatial separation of SOM, microorganisms and extracellular enzyme activity possibly related to the heterogeneity of C input. As a result of the different processes, stabilized SOM in subsoils is horizontally stratified. In order to better understand deep SOM dynamics and to include them into soil C models, quantitative information about C fluxes resulting from C input, stabilization and destabilization processes at the field scale are necessary.

Climate-smart soils

Abstract: Soils are integral to the function of all terrestrial ecosystems and to food and fibre production. An overlooked aspect of soils is their potential to mitigate greenhouse gas emissions. Although proven practices exist, the implementation of soil-based greenhouse gas mitigation activities are at an early stage and accurately quantifying emissions and reductions remains a substantial challenge. Emerging research and information technology developments provide the potential for a broader inclusion of soils in greenhouse gas policies. Here we highlight 'state of the art' soil greenhouse gas research, summarize mitigation practices and potentials, identify gaps in data and understanding and suggest ways to close such gaps through new research, technology and collaboration.

Modelling the role of agriculture for the 20th century global terrestrial carbon balance

Abstract: In order to better assess the role of agriculture within the global climate-vegetation system, we present a model of the managed planetary land surface, Lund-Potsdam-Jena managed Land (LPJmL), which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs). Based on the LPJ-Dynamic Global Vegetation Model, LPJmL simulates the transient changes in carbon and water cycles due to land use, the specific phenology and seasonal CO2 fluxes of agricultural-dominated areas, and the production of crops and grazing land. It uses 13 CFTs (11 arable crops and two managed grass types), with specific parameterizations of phenology connected to leaf area development. Carbon is allocated daily towards four carbon pools, one being the yield-bearing storage organs. Management (irrigation, treatment of residues, intercropping) can be considered in order to capture their effect on productivity, on soil organic carbon and on carbon extracted from the ecosystem. For transient simulations for the 20th century, a global historical land use data set was developed, providing the annual cover fraction of the 13 CFTs, rain-fed and/or irrigated, within 0.5 degrees grid cells for the period 1901-2000, using published data on land use, crop distributions and irrigated areas. Several key results are compared with observations. The simulated spatial distribution of sowing dates for temperate cereals is comparable with the reported crop calendars. The simulated seasonal canopy development agrees better with satellite observations when actual cropland distribution is taken into account. Simulated yields for temperate cereals and maize compare well with FAO statistics. Monthly carbon fluxes measured at three agricultural sites also compare well with simulations. Global simulations indicate a similar to 24% (respectively similar to 10%) reduction in global vegetation (respectively soil) carbon due to agriculture, and 6-9 Pg C of yearly harvested biomass in the 1990s. In contrast to simulations of the potential natural vegetation showing the land biosphere to be an increasing carbon sink during the 20th century, LPJmL simulates a net carbon source until the 1970s (due to land use), and a small sink (mostly due to changing climate and CO2) after 1970. This is comparable with earlier LPJ simulations using a more simple land use scheme, and within the uncertainty range of estimates in the 1980s and 1990s. The fluxes attributed to land use change compare well with Houghton's estimates on the land use related fluxes until the 1970s, but then they begin to diverge, probably due to the different rates of deforestation considered. The simulated impacts of agriculture on the global water cycle for the 1990s are similar to 5% (respectively similar to 20%) reduction in transpiration (respectively interception), and similar to 44% increase in evaporation. Global runoff, which includes a simple irrigation scheme, is practically not affected. (Less)