Mark Easter

Agricultural management explains historic changes in regional soil carbon stocks.

Agriculture is considered to be among the economic sectors having the greatest greenhouse gas mitigation potential, largely via soil organic carbon (SOC) sequestration. However, it remains a challenge to accurately quantify SOC stock changes at regional to national scales. SOC stock changes resulting from SOC inventory systems are only available for a few countries and the trends vary widely between studies. Process-based models can provide insight in the drivers of SOC changes, but accurate input data are currently not available at these spatial scales. Here we use measurements from a soil inventory dating from the 1960s and resampled in 2006 covering the major soil types and agricultural regions in Belgium together with region-specific land use and management data and a process-based model. The largest decreases in SOC stocks occurred in poorly drained grassland soils (clays and floodplain soils), consistent with drainage improvements since 1960. Large increases in SOC in well drained grassland soils appear to be a legacy effect of widespread conversion of cropland to grassland before 1960. SOC in cropland increased only in sandy lowland soils, driven by increasing manure additions. Modeled land use and management impacts accounted for more than 70% of the variation in observed SOC changes, and no bias could be demonstrated. There was no significant effect of climate trends since 1960 on observed SOC changes. SOC monitoring networks are being established in many countries. Our results demonstrate that detailed and long-term land management data are crucial to explain the observed SOC changes for such networks.

ECOLOGICAL IMPACT OF HISTORICAL LAND-USE PATTERNS IN THE GREAT PLAINS: A METHODOLOGICAL ASSESSMENT

This paper demonstrates a method for using historical county-level agricultural land-use data to drive an ecosystem model. Four case study counties from the U.S. Great Plains during the 19th and 20th centuries are used to represent different agroecosystems. The paper also examines the sensitivity of the estimates of county-level ecosystem properties when using different levels of detail in the land-use histories. Using weighted averages of multiple-model runs for grassland, dryland cropping, and irrigated cropping improved prediction over a simple, single-run approach that models the prevailing land use. Model runs with the same land use and environment generally reach similar levels of soil carbon and nitrogen mineralization after ∼50 years, no matter when they began, with faster convergence for irrigated cropland. Model results show that cultivation of grasslands results in large losses of soil carbon and an increase in soil nitrogen mineralization for the first 20–30 years of cultivation, which is followed by low soil carbon loss and nitrogen mineralization 50 years after cultivation started. The recently observed increase in irrigated agriculture in the central and northern Great Plains (2.7 million ha) has resulted in a net carbon storage of 21.3 Tg carbon, while irrigated cotton production has resulted in a net loss of 12.1 Tg carbon.

Counting carbon on the farm: Reaping the benefits of carbon offset programs

Reducing anthropogenic greenhouse gas (GHG) emissions is the greatest environmental challenge facing society over the coming decades (NAS 2005). Although the largest global source of emission stems from the use of fossil fuels, land use, including agriculture, is the second greatest contributor to increasing GHG concentrations in the atmosphere, accounting for about 30% of total net emissions (IPCC 2007). The majority of these land use emissions are associated with deforestation and land conversion, mainly in the tropics; however, in the United States, agriculture contributes around 7% of total emissions (EPA 2007). The three main GHGs of concern—carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)—are all emitted through various agricultural activities, with the CH4 and N2O dominating agricultural emissions in the United States. However, agriculture has the capacity to not only significantly reduce its own emissions, but also to offset CO2 emissions from other sectors of the economy via carbon sequestration (CAST 2004; Paustian et al. 2006). By employing practices that increase organic matter content (about half of which is carbon) of soils, it is estimated that as much as 50 to 200 million t C per year of carbon offsets could be produced by US agriculture (Lal et al.…

Methods for the quantification of GHG emissions at the landscape level for developing countries in smallholder contexts

Landscape scale quantification enables farmers to pool resources and expertise. However, the problem remains of how to quantify these gains. This article considers current greenhouse gas (GHG) quantification methods that can be used in a landscape scale analysis in terms of relevance to areas dominated by smallholders in developing countries. In landscape scale carbon accounting frameworks, measurements are an essential element. Sampling strategies need careful design to account for all pools/fluxes and to ensure judicious use of resources. Models can be used to scale-up measurements and fill data gaps. In recent years a number of accessible models and calculators have been developed which can be used at the landscape scale in developing country areas. Some are based on the Intergovernmental Panel on Climate Change (IPCC) method and others on dynamic ecosystem models. They have been developed for a range of different purposes and therefore vary in terms of accuracy and usability. Landscape scale assessments of GHGs require a combination of ground sampling, use of data from census, remote sensing (RS) or other sources and modelling. Fitting of all of these aspects together needs to be performed carefully to minimize uncertainties and maximize the use of scarce resources. This is especially true in heterogeneous landscapes dominated by smallholders in developing countries.

Simulation of management and soil interactions impacting SOC dynamics in sugarcane using the CENTURY Model

Newer methods of management and harvesting of sugarcane are being considered to improve soil and water conservation in Brazil. Our aim in this study was to evaluate soil C dynamics under sugarcane cultivation as influenced by the use of conservation management, using measurements from four different management systems and land use histories, i.e. conventional management with preharvest burning, no burning with residue retention and two systems without burning plus additional organic amendments. Field sites also differed in terms of soil texture. We compared field measurements of soil C stocks, 13C and microbial biomass with simulated results from the Century ecosystem model for each of the sites and management histories. We also did long‐term simulations of the management treatments and sites to approximate steady‐state SOC levels, to explore potential management‐induced differences in SOC stocks and interactions with soil texture. The model accurately represented treatment and site differences for total SOC stocks, in which SOC stocks were strongly affected by both rates of organic matter input to soil and soil clay content. However, the model tended to underestimate the relative contribution of sugarcane‐derived C to total SOC for sites with high residue and external organic matter amendments. Measured microbial biomass C across the sites was closely aligned with relative amounts of organic matter input but did not appear to be strongly affected by soil texture, whereas the model predicted that both texture and organic matter input rate would impact microbial biomass C. Long‐term simulations of the conservation management alternatives suggested that SOC stocks could be maintained at or above levels in the original native Cerradão vegetation, whereas conventional practices using residue burning would result in a reduction of SOC to ca. 60% of native levels. Our results support the use of the CENTURY model as an aid to assess the impacts of different soil management practices on SOC stocks under sugarcane in Brazil.

Ecosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design

Renewable fuel standards in the US and elsewhere mandate the production of large quantities of cellulosic biofuels with low greenhouse gas (GHG) footprints, a requirement which will likely entail extensive cultivation of dedicated bioenergy feedstock crops on marginal agricultural lands. Performance data for such systems is sparse, and non‐linear interactions between the feedstock species, agronomic management intensity, and underlying soil and land characteristics complicate the development of sustainable landscape design strategies for low‐impact commercial‐scale feedstock production. Process‐based ecosystem models are valuable for extrapolating field trial results and making predictions of productivity and associated environmental impacts that integrate the effects of spatially variable environmental factors across diverse production landscapes. However, there are few examples of ecosystem model parameterization against field trials on both prime and marginal lands or of conducting landscape‐scale analyses at sufficient resolution to capture interactions between soil type, land use, and management intensity. In this work we used a data‐diverse, multi‐criteria approach to parameterize and validate the DayCent biogeochemistry model for upland and lowland switchgrass using data on yields, soil carbon changes, and soil nitrous oxide emissions from US field trials spanning a range of climates, soil types, and management conditions. We then conducted a high‐resolution case study analysis of a real‐world cellulosic biofuel landscape in Kansas in order to estimate feedstock production potential and associated direct biogenic GHG emissions footprint. Our results suggest that switchgrass yields and emissions balance can vary greatly across a landscape large enough to supply a biorefinery in response to variations in soil type and land‐use history, but that within a given land base both of these performance factors can be widely modulated by changing management intensity. This in turn implies a large sustainable cellulosic biofuel landscape design space within which a system can be optimized to meet economic or environmental objectives.

Carbon benefits of wolfberry plantation on secondary saline land in Jingtai oasis, Gansu:A case study on application of the CBP model

The largest global source of anthropogenic CO2 emissions comes from the burning of fossil fuel and approximately 30% of total net emissions come from land use and land use change. Forestation and reforestation are regarded worldwide as effective options of sequestering carbon to mitigate climate change with relatively low costs compared with industrial greenhouse gas (GHG) emission reduction efforts. Cash trees with a steady augmentation in size are recognized as a multiple-beneficial solution to climate change in China. The reporting of C changes and GHG emissions for sustainable land management (SLM) practices such as afforestation is required for a variety of reasons, such as devising land management options and making policy. The Carbon Benefit Project (CBP) Simple Assessment Tool was employed to estimate changes in soil organic carbon (SOC) stocks and GHG emissions for wolfberry (Lycium barbarum L.) planting on secondary salinized land over a 10 year period (2004-2014) in the Jingtai oasis in Gansu with salinized barren land as baseline scenario. Results show that wolfberry plantation, an intensively managed ecosystem, served as a carbon sink with a large potential for climate change mitigation, a restorative practice for saline land and income stream generator for farmers in soil salinized regions in Gansu province. However, an increase in wolfberry production, driven by economic demands, would bring environmental pressures associated with the use of N fertilizer and irrigation. With an understanding of all of the components of an ecosystem and their interconnections using the Drivers-Pressures-State-Impact-Response (DPSIR) framework there comes a need for strategies to respond to them such as capacity building, judicious irrigation and institutional strengthening. Cost benefit analysis (CBA) suggests that wolfberry cultivation was economically profitable and socially beneficial and thus well-accepted locally in the context of carbon sequestration. This study has important implications for Gansu as it helps to understand the role cash trees can play in carbon emission reductions. Such information is necessary in devising management options for sustainable land management (SLM).

Sustainable Land Management Through Soil Organic Carbon Management and Sequestration — The GEFSOC Modelling System

Soil organic carbon (SOC) is vital for ecosystem and agro-ecosystem function. Any sustainable land management strategy should, therefore, include a consideration of long-term effects on SOC. In the future, we have the opportunity to adopt land management strategies that lead to greater C storage in the soil. However, to do so, we need consistent estimates of SOC stocks and changes under varying land use and climate change scenarios. A Global Environment Facility (GEF) project developed a generically applicable system (the GEFSOC Modelling System) for making such estimates. The system links two dynamic SOC models, designed for site scale applications (Century and RothC) and an empirical method, to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. The system was developed using data from four contrasting eco-regions (The Brazilian Amazon, Jordan, Kenya and the Indian part of the Indo-Gangetic Plains). These areas were chosen, as they are located in regions previously underrepresented by soil C models. The system was then used to estimates SOC stocks and changes between 1990 and 2030 under likely land use change scenarios in each of the four regions. Losses in SOC of between 5 and 16 % were projected for each of the four areas over a 30-year period (2000–2030), driven by a range of factors including deforestation, overgrazing and conversion of grazing land to agriculture. Implications for sustainable land management and future land use policy are discussed for The Brazilian Amazon, Jordan, Kenya and the Indian Indo-Gangetic Plains.

Chapter 15 – COMET2.0—Decision Support System for Agricultural Greenhouse Gas Accounting

Improved agricultural practices have a significant potential to mitigate greenhouse gas (GHG) emissions. A key issue for implementing mitigation options is quantifying emissions practically and cost effectively. Web-based systems using process-based models provide a promising approach.

A model for estimating windbreak carbon within COMET-Farm™

Agroforestry as a land management practice presents a method for partially offsetting greenhouse gas emissions from agricultural land. Of all agroforestry practices in the United States, windbreaks in particular are used throughout the United States providing a useful starting point for deriving a modelling system which could quantify the amount of carbon sequestered on U.S. agricultural land and provide for broad usability. We present our first approximation to this end by presenting a model that estimates current and future stocks within multiple carbon pools of windbreak systems such as live trees, the O horizon, downed woody debris and standing dead trees. In this article, we describe each modelled process driving carbon fluxes within carbon pools including novel windbreak tree growth and mortality models. Our model is generalized by region and species group allowing us to run scenarios for any common tree species in any location within the contiguous United States. Integrated into the agricultural greenhouse gas accounting tool, COMET-Farm™, the windbreak component gives landowners and land managers power to view agroforestry systems in the same context as agricultural operations and provides an alternative to intensive biomass inventories.